Skip to main content
NCBI home page
PLOS One logoLink to PLOS One
. 2024 Dec 30;19(12):e0316394. doi: 10.1371/journal.pone.0316394

An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers

Trang Thi Quynh Tran 1,2, Tung The Pham 1, Than Thi Nguyen 1,3, Trang Hien Do 1, Phuong Thi Thu Luu 1, Uyen Quynh Nguyen 2, Linh Dieu Vuong 4, Quang Ngoc Nguyen 4, Son Van Ho 3, Hang Viet Dao 5, Tong Van Hoang 6, Lan Thi Thuong Vo 1,2,*
Editor: Osman El-Maarri7
PMCID: PMC11684646  PMID: 39775734

Abstract

The autonomous and active Long-Interspersed Element-1 (LINE-1, L1) and the non-autonomous Alu retrotransposon elements, contributing to 30% of the human genome, are the most abundant repeated sequences. With more than 90% of their sequences being methylated in normal cells, these elements undeniably contribute to the global DNA methylation level and constitute a major part of circulating-cell-free DNA (cfDNA). So far, the hypomethylation status of LINE-1 and Alu in cellular and extracellular DNA has long been considered a prevailing hallmark of ageing-related diseases and cancer. This study demonstrated that errors in LINE-1 and Alu methylation level measurements were caused by an excessive input quantity of genomic DNA used for bisulfite conversion. Using the minuscule DNA amount of 0.5 ng, much less than what has been used and recommended so far (500 ng-2 μg) or 1 μL of cfDNA extracted from 1 mL of blood, we revealed hypermethylation of LINE-1 and Alu in 407 tumour samples of primary breast, colon and lung cancers when compared with the corresponding pair-matched adjacent normal tissue samples (P < 0.05–0.001), and in cfDNA from 296 samples of lung cancers as compared with 477 samples from healthy controls (P < 0.0001). More importantly, LINE-1 hypermethylation in cfDNA is associated with healthy ageing. Our results have not only contributed to the standardized bisulfite-based protocols for DNA methylation assays, particularly in applications on repeated sequences but also provided another perspective for other repetitive sequences whose epigenetic properties may have crucial impacts on genome architecture and human health.

Introduction

Nearly half of the human genome is comprised of retrotransposon elements, the repetitive sequences that can propagate via a “copy and paste” mechanism based on transcription and reverse transcription [1,2]. The autonomous and active Long-Interspersed Element-1 (LINE-1, L1) and the non-autonomous Alu elements are the most abundant repeated sequences in the human genome with an estimated more than 105 and 106 copies per genome, respectively [1,2]. Despite having a strong cis preference for its own RNA, LINE-1 is also responsible for the trans mobilisation of Alu and other SVAs non-autonomous elements [3,4].

Recent emerging works have highlighted the fundamental role of LINE-1 and Alu in heterochromatin compartmentalization, 3D genome folding, and overall genome spatial organization [5–7]. LINE-1 can integrate into germ, embryonic and differentiated cells, providing a rich source of regulatory elements and functional modules, and resulting in a more diverse landscape of somatic genome variation and phenotypic diversity [8,9]. Particularly, Alu sequences contain multiple potential splice donor/acceptor sites and binding sites for transcription factors such as enhancers and insulators [10], thus maintaining lineage-specific enhancer-promoter loops [11] and regulating transcriptional and post-transcriptional hubs [10–12].

LINE-1 and Alu elements are heavily methylated and silenced in healthy controls but hypomethylated and derepressed in cancer and ageing-related diseases [13,14]. In age-related diseases and cancers, LINE-1 transposition promotes chromosomal rearrangements, transcriptional deregulation, oncogenic activation, and aberrations of non-coding RNAs [9,15]. In particular, LINE-1 transcripts can cause heterochromatin erosion [16], induce the DNA damage response and cell cycle exit [17] and inflammation in ageing (inflammageing) [18]. Similarly, in diseases and cancer, Alu hypomethylation, corresponding to open chromatin, induces insertions and non-allelic homologous recombination, thus leading to instability and somatic complexity of the genome [19]. Hypomethylated Alu, behaving as cell-type-specific enhancers for nearby genes [20], is strictly associated with an increase in Alu RNA transcribed by either RNA polymerase III (Pol III) or RNA polymerase II (Pol II), thus altering transcriptional and post-transcriptional hubs [10,21,22].

Contributing to 30% of the human genome, with 99% of their sequences being methylated [1], LINE-1 and Alu elements constitute a major part of circulating-cell-free DNA (cfDNA) and undeniably contribute to the global DNA methylation level [14,23]. Moreover, the cfDNA integrity (cfDI) index, calculated as the ratio of long to short Alu fragments amplified at the same locus, is considered as a biomarker for cancer diagnosis [24]. cfDNA derived from cancer cells promotes tumour cell survival [25], facilitates colorectal tumour malignancy and stimulates the proliferation of hormone-receptor-positive breast cancer cells [26,27]. On the contrary, cfDNA modulates anti-tumour immunity in response to chemotherapy [28]. The methylated cfDNA fragments inhibit the proliferation of tumour cells [29]. Hence, fragmented cfDNA methylation signatures, associated with the dual effect of both pro- and anti-tumour, and global cellular DNA methylation can serve as a tool for real-time and accurate monitoring of cancer screening, accurate disease-progression surveillance and improvement of treatment [13,24].

DNA methylation at CpG sites at the 5’UTR of the human LINE-1, serving as an internal promoter, is one of the key mechanisms for silencing LINE-1 [13]. Similarly, up to 33% of all CpG sites in the human genome are located in the Alu sequences, and the methylation of these sites is a primary mechanism in silencing almost all Alu elements in normal cells [14]. As a matter of fact, a hypomethylated status of the LINE-1 and Alu in cellular DNA as well as in cfDNA has been considered hallmarks of ageing, age-related pathologies and cancer [19,30]. However, some recent studies have raised a challenging debate about whether LINE-1 and Alu in cellular DNA and cfDNA is supposed to be hypomethylated or hypermethylated [31–33]. It has been revealed that LINE-1 hypermethylation and its silencing promoted the growth of tumour subclones [34] and metastasis [35], protected cancer cell subpopulations from lethal drug exposure [36], and allowed cancer cells to bypass antitumour immune responses [37]. Likewise, an increased level of Alu transcripts in diseases and cancers is associated with innate immune responses and apoptosis, protection of endogenous DNA damage and resistance to DNA damaging agents [38,39]. This proclivity towards the hypermethylated status of LINE-1 and Alu in cancer cells, with their repression favouring fitness advantages for tumour survival and progression, suggests a re-evaluation of the prevailing hallmark of LINE- 1 and Alu hypomethylation in cancer.

Bisulfite conversion-based methods, the gold standard for quantifying and mapping methylation, with the ability to convert unmethylated cytosines to uracil residues while leaving methylated cytosines intact have been massively utilised to profile the methylation status of whole genomes and transposable elements through PCR-based amplification, post-PCR sequencing, and methylation arrays [40,41]. Using a wide range of DNA input (45 ng-1.6 μg) for bisulfite treatment, a significant conflict surrounding global methylation level, including that of LINE-1 and Alu, in 32 reference samples, profiled either by whole genome bisulfite sequencing (WGBS) or pyrosequencing and methylation-specific PCR has been reported in a multicentre benchmarking study performed by 18 laboratories in 7 different countries [42]. Our previous studies have demonstrated that an excessive input of genomic DNA, corresponding to an excessive copy number of the LINE-1 repeats used for bisulfite conversion caused errors in methylation measurements of LINE-1 elements [43]. The effect of copy number variant on DNA methylation has been also mentioned using bisulfite-free methods such as methylated DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain-based capture (MBDCap) [44].

In this study, we first focused on the quantitative assessment of the optimal DNA input amount for bisulfite conversions to eliminate the risk of incomplete conversions, and subsequently analysed the methylation profile of LINE-1 and Alu in pair-matched tumour tissues and adjacent normal tissues of primary breast, lung and colon cancer samples. Since cfDNA retains the genetic and epigenetic characteristics of the tissue from which it was released [30], we also analysed the methylation profile of these elements in plasma from healthy individuals and lung cancer patients. As such, we demonstrated again the impact of DNA input in the methylation assessment of repetitive sequences. We established that these repeats were significantly hypermethylated in tumour tissue samples and cfDNA samples from lung cancer patients as compared with adjacent normal samples and cfDNA from healthy controls. More importantly, LINE-1 hypermethylation in cfDNA is positively correlated with healthy ageing. Our findings provide information for a re-evaluation of the methylation profile of LINE-1 and Alu and suggest another perspective for other repetitive sequences whose epigenetic properties may have crucial impacts on genome architecture and human health [45].

Materials and methods

Sample collection, DNA isolation and bisulfite conversion

Primary tumour tissue samples and their corresponding adjacent normal tissue samples were collected from fresh-frozen biopsies from 201 breast cancer patients, 133 colon cancer patients and 73 lung cancer patients. Sample classifications were done by pathologists at the Vietnam National Cancer Hospital and the 175 Hospital (Ho Chi Minh City). Blood samples were collected from 477 healthy participants and 296 patients with primary lung cancers. The recruitment period spanned from April 1st, 2023 to December 31st, 2023. Informed consent was obtained from healthy participants and patients in written form, and all collection methods were performed in accordance with the relevant guidelines and regulations by the Ethics Committee of the Vietnam Academy of Science and Technology (01-2023/NCHG-HDDD). DNAs were extracted from tissues using the DNeasy Blood & Tissue Kit (Qiagen). After DNA quantification using the Qubit4 Fluorometer (Thermo Fisher Scientific), a concentration of 0.5 ng of genomic DNA was subjected to bisulfite conversion. One millilitre of blood was collected in K2-EDTA collection tubes, then centrifuged at 2000 g for 10 minutes at 4°C. Approximately 0.4 mL of plasma was transferred to a new tube and then centrifuged at 6000 g for 30 minutes at 4°C to remove residual blood and cell debris. cfDNA was extracted from the plasma using the MagMAX Cell-Free DNA Isolation kit (Thermo Fisher Scientific) and subjected to bisulfite conversion. All bisulfite reaction of DNA extracted from tissues and cfDNA was performed using the EZ DNA Methylation-Gold® kit (Zymo Research).

Primer design

The LINE-1 primer sets were designed to target the 5′ UTR region of the H1LS family (S1 Fig). The Alu primer sets targeted a region located in the 5’ region of the Alu consensus sequences (S1 Fig). The methylation-dependent-specific PCR (MSP) primers used for profiling LINE-1 and Alu methylation were derived from the CpG-containing sequences. The methylation-independent-specific PCR (MIP) primers were derived from the non-CpG-containing sequence [43] and used for the normalization of the DNA input. The specificity of the MSP primers, designed to specifically recognize methylated LINE-1 and Alu sequences, was tested using (i) methylated human DNA and (ii) unmethylated human DNA (Zymo Research), both are treated by bisulfite and (iii) untreated human genomic DNA (Promega) as templates for qPCR. Amplification products were only obtained from the reactions with bisulfite-treated methylated human DNA, ensuring the accuracy of MSP primers designed for only the methylated targets. Primer sequences, amplicon lengths and qPCR conditions are presented in S1 Table.

Determination of PCR amplification efficiency

A serial dilution of human methylated DNA amount (Zymo Research) ranging from 15 pg to 500 pg was bisulfite treated and used as templates for amplification either with the MIP primer set, specific to the bisulfite-converted reference sequence, or the MSP primer sets, specific to the methylated LINE-1 and Alu sequences. The PCR amplification efficiency was assessed by (i) plotting the CT values against the DNA input and (ii) plotting the ΔCT values, calculated by subtracting the CT value of the MSP primer set from that of the MIP primer set against the DNA input.

Quantification of bisulfite conversion efficiency

An artificially synthesized IC system, consisting of two sequences, named ConIC (Converted IC) and UnIC (Unconverted IC), containing both cytosine-free (CF) sequences and CpG-containing sequences, has been used in this study [43]. The ConIC and UnIC are both 122 bp in length, subcloned into the pTZ57R/T vector, and identical in sequence, except that all 15 cytosines in the UnIC are replaced by thymines in the ConIC, allowing the ConIC to be used as the calibrator for 100% bisulfite conversion efficiency, with the UnIC as the indicator to quantitatively evaluate the bisulfite conversion efficiency of the CpG sequence. The concentration of the linearized recombinant plasmids with the inserted sequences UnIC and ConIC was quantified using the QubitTM 4 Fluorometer (Thermo Fisher Scientific) [43]. The copy number was estimated according to the molecular weight, amount, and length of the plasmid. To evaluate the impact of input amount on bisulfite conversions, a series of concentrations, equivalent to 1010–106 copies of the linearized plasmids UnIC and ConIC, was diluted in 500 ng of genomic DNA, converted by bisulfite, and subjected to qPCR with the CF and the MSP primer sets, respectively specific to the cytosine-free sequences and methylation-specific sequences of the IC [43]. In addition, a serial dilution of the human methylated DNA ranging from 500 ng to 0.5 ng was converted by bisulfite. Bisulfite-converted DNA inputs of 5 ng, 50 ng and 500 ng, diluted by 5, 50 and 500 folds and 20, 200 and 2000 folds, were respectively used for LINE-1 and Alu methylation assessment. Two μL of the diluted solutions and the bisulfite-converted DNA inputs of 0.5 ng and 1 ng were then used as templates for qPCR.

Quantification of cfDNA amount and cfDNA integrity (cfDI)

The total amount of plasma DNA was represented by either the LINE-1 copy number or the Alu copy number present in plasma. To calculate LINE-1 copy number, 1 μL of cfDNA was subjected to quantitative real-time PCR (qPCR) with the LINE-1 primers corresponding to an 88 bp amplicon. To calculate cfDNA integrity, 1 μL of cfDNA was subjected to qPCR with the two Alu primer sets corresponding to 78 bp and 205 bp amplicons, respectively. Absolute quantification of LINE-1 and Alu copy number was determined from a standard curve using 10-fold serial dilutions of human genomic DNA (Promega) ranging from 10.000 pg to 0.1 pg on the premise that a diploid genome (~6 pg) consists of 106 copies of the Alu sequence and 105 copies of the LINE-1 sequence, respectively.

Quantitative methylation-specific PCR (qMSP)

LINE-1 and Alu methylation status was quantified via real-time PCR with a volume of 20 μL per reaction, using bisulfite-converted DNA as the template and the SsoAdvancedTM Universal SYBR® Green Supermix (Biorad). Real-time PCR assays were duplexed for both of the following reactions: (i) using the MIP primers to quantify bisulfite-converted reference sequences, and (ii) using the MSP primers to quantify methylated LINE-1 and Alu sequences. Water with no DNA template was included in each PCR reaction as a control for contamination. All qPCR reactions were performed using the QuantStudioTM Real-time PCR instrument (Thermo Fisher Scientific).

Methylation level calculation

The classical ΔΔCT approach using a calibrator was chosen to calculate the methylation level [46]. Validation of the ΔΔCT method when using a serial concentration of human methylated DNA that was treated with bisulfite and used as qPCR templates with the MIP and the MSP primer sets was analysed via the simple linear regression model. Three duplicated reactions were carried out for each sample: one using the MIP primer set to quantify the total DNA input (Ref) after bisulfite conversion and the others using the MSP primer sets to quantify the methylated LINE-1 and Alu targets. A serial dilution of the human methylated DNA, treated with bisulfite, was used as the standard with a defined methylation level of 100%, and thus, as a calibrator for the measurement of LINE-1 and Alu methylation levels. The relative level of methylated targets was calculated for each sample as follows: ΔΔCTSample = ΔCTSample− ΔCTCalibrator, where ΔCTSample = CTSample/Methylated target−CTSample/Ref and ΔCTCalibrator = CTCalibrator/Methylated target−CTCalibrator/Ref. MethylationSample = 2-ΔΔCTSample x 100 (%). Samples with both replicates returning a CT value greater than 29 were excluded from the study.

Statistical analysis

In the box plot, the ΔCT values are represented as min to max with median values. In all dot plots, the ΔCT value, the methylation level of LINE-1 and Alu are represented as median values with an interquartile range. All comparisons between more than two groups based on the quantitative values were assessed via the Kruskal-Wallis test. Comparisons between two groups based on the quantitative values were assessed via the Unpaired T test when normality was met, otherwise by the Mann-Whitney U test for independent samples and the Wilcoxon matched-pairs signed rank test for pair-matched samples. The relationship between the LINE-1 and Alu methylation level and age was assessed via Spearman’s rank correlation test. The linear relationship between the CT value and the genomic DNA input, and thus, the number of LINE-1 and Alu copies input for qPCR, was evaluated through simple linear regression analysis. For all statistical analyses, a P-value of < 0.05 was considered significant. All analyses and graphing were performed using the GraphPad Prism® program version 9 (https://www.graphpad.com/scientific-software/prism/).

Results

Design of primers specific to LINE-1 and Alu consensus sequences

The subfamily LINE-1, consisting of around one half million copies in the human genome, comprises almost all of the youngest and currently active human-specific L1Hs family [1,2]. Similarly, Alu elements have accumulated around 1 million copies in the human genome. Based on diagnostic nucleotides, Alu elements are classified into three major subfamilies: AluJ (the oldest), AluS (intermediate), and AluY (youngest) [47]. The most active human Alu subfamilies are AluY, which contribute to 13% of human-specific Alu elements [47]. Since these elements are highly heterogeneous, we first generated LINE-1 and Alu consensus sequences based on a panel of young and old individual subfamily of each repeat element followed by Repeat-Masker and ClustalW algorithm [48]. The MSP primer sets were designed from these LINE-1 and Alu consensus sequences and used for further methylation analysis (S1 Fig).

Assessment of PCR amplification efficiency

A serial dilution of human methylated DNA amount ranging from 15 pg to 500 pg was bisulfite treated and used as templates in qPCR. The CT values have a strong linear relationship with the DNA input for the MIP primer set, specific to the bisulfite-converted reference sequence, and the MSP primer sets, specific to the methylated LINE-1 and Alu sequences (R2 > 0.99). There was a statistically insignificant difference (< 5%) in amplification efficiency (E value) with 94.58% for the reference (L1-Ref) amplicons, 91.92% for the methylated LINE-1 (L1-Me) amplicons and 90.32% for the methylated Alu (Alu-Me) amplicons (Fig 1A and 1C). The difference in CT values of both the reference and the methylated target was then plotted against the logarithm of the template input amount, with absolute value of slopes of the fitted line to be 0.0145 and 0.0512 (P > 0.5), thus demonstrating the Livak formula suitable for the relative quantification of methylated LINE-1 and Alu (Fig 1B and 1D). Taken together, these results indicate the designed MIP and MSP primer sets were optimised to PCR amplification, thus ensuring accurate measurement of LINE-1 and Alu methylation levels using the Livak formula [46].

Fig 1. Evaluation of PCR amplification efficiency of the MIP and MSP primer sets on the 100% human methylated DNA.

Fig 1

Open in a new tab

(A, C) A serial dilution of human methylated DNA ranging from 15 pg to 500 pg was bisulfite-treated and used as the template for qPCR with the MIP (L1-Ref) primers and the MSP (L1-Me and Alu-Me, respectively) primer sets specific to the LINE-1 (A) and Alu (C) targets. The CT values have a strong linear relationship with the DNA input (R2 > 0.99) and the amplification efficiency (E value > 90%) of the reference amplicon does not differ from that of the methylated amplicons (< 5% difference). (B, D) The ΔCT value, calculated by subtracting the CT value of the MSP primer set from that of the MIP primer set for each sample, is almost constant (P > 0.5), independent on DNA inputs, indicating the Livak ΔΔCT formula to be suitable for relative quantification of methylation level. Simple linear regression was used in statistical analysis. Number of observations for each assay was ≥ 3.

The impact of excessive DNA amounts on methylation assessments

One of the technical weaknesses of bisulfite conversions is the incomplete conversion of unmethylated cytosines, leading to an overestimation of methylation level. On the other hand, the conversion exclusively occurs on single-stranded DNA, thus, double-stranded DNA must be completely denatured during the bisulfite reaction [40,41]. Inefficient denaturation of excessive amounts of genomic DNA can result in an insufficient yield of the single-stranded DNA that is quantitatively measured through qMSP reactions, consequently leading to an underestimation of methylation level.

To understand the faulty underestimation of DNA methylation, an IC system, consisting of two artificial sequences, named ConIC and UnIC, containing both cytosine-free (CF) sequences and CpG-containing sequences, has been artificially synthesized [43]. They are identical in sequence, with the exception that in the ConIC, all cytosines have been converted into thymines. As such, the ConIC can be used as the calibrator for 100% bisulfite conversion efficiency, while the UnIC is the indicator to quantitatively evaluate the bisulfite conversion efficiency of the CpG sequence [43]. A serial dilution of the IC, corresponding to 1010, 109, 108, 107 and 106 copies, was spiked with 500 ng genomic DNA, converted by bisulfite, and used as templates for qMSP with the CF and MSP primer sets. Plotting the log of the UnIC copy number against the ΔCT value at each dilution shows significantly constant ΔCT values only within the range of 108 to 106 copies and starts to differ from the 109 copies dilution. (Fig 2A). The 1010 copies of the UnIC gave a dramatical increase in the ΔCT value (Fig 2A). These phenomena were not observed with the ConIC, indicating that PCR amplifications were not inhibited by the excessive amount of template but instead by errors in CpG conversion due to an excessive amount of UnIC input for bisulfite.

Fig 2. The impact of excessive DNA amounts used for bisulfite conversion on the amplification efficiency and the methylation level of LINE-1 and Alu.

Fig 2

Open in a new tab

(A) Correlation between the IC copy number (log10) and the ΔCT value. Serial dilutions of the UnIC and ConIC, corresponding to 1010, 109, 108, 107 and 106 copies, were spiked with 500 ng genomic DNA, bisulfite converted and amplified by two primer sets named CF and MSP [43]. The ΔCT (CTMSP-CTCF), calculated for each dilution, remained significantly constant only within the range of 108 to 106 copies but started to differ from the 109 copies dilution. (B, C) The amplification efficiency of the reference template and the LINE-1 and Alu methylated templates, on the 100% human methylated DNA. A serial dilution of human methylated DNA amounts, corresponding to 500 ng, 50 ng, 5 ng, 1 ng and 0.5 ng was treated by bisulfite. The ΔCT values significantly differ at input amounts from 500 ng to 0.5 ng. (D, E) An increase in methylation level of LINE-1 (D) and Alu (E) was associated with a decrease in DNA input for bisulfite conversion. (F, G) Methylation level of LINE-1 (F) and Alu (G) calculated from bisulfite-treated samples using 0.5 ng, 5 ng or 50 ng of genomic DNA extracted from breast tumours and their corresponding adjacent tissues. Hypermethylation of LINE-1 and Alu elements in breast tumour samples was detected using 0.5 ng of DNA input solely. The Mann-Whitney U test and the Kruskal-Wallis test (A), the unpaired T-test (B-E) and the Wilcoxon matched-pairs signed rank test (F, G) were used for statistical analysis. (ns) nonsignificant; (*) P < 0.05; (**); P < 0.01; (***) P < 0.001; (****) P < 0.0001.

The impact of the input DNA amount on methylation assessments was further investigated on LINE-1 and Alu repeats in human methylated DNA (Zymo Research). Five different DNA quantities: 0.5 ng, 1 ng, 5 ng, 50 ng, and 500 ng of human methylated DNA were converted by bisulfite and subsequently used as templates for qMSP with the MIP and MSP primer sets specific to LINE-1 and Alu sequences. All DNA sequences were methylated (100%) in this DNA, thus, theoretically, the ΔCT value should be constant regardless of the DNA amount for bisulfite conversions. Unexpectedly, the ΔCT values are constant only within the range of DNA input amounts from 0.5 ng to 5 ng with the LINE-1 target and from 0.5 ng to 1 ng with the Alu target, and start to dramatically increase at DNA input amounts from 5 ng to 500 ng (Fig 2B and 2C). A higher input amount of the human methylated DNA correlated with a higher ΔCT value that corresponded to a lower methylation level (Fig 2D and 2E), indicating a faulty underestimation of LINE-1 and Alu methylation, in other words, a faulty hypomethylation status of these repeat sequences.

Finally, the impact of different DNA amounts on LINE-1 and Alu methylation assessments was investigated on DNA isolated from cancer samples. Bisulfite conversion was done with 3 different DNA quantities: 0.5 ng, 5 ng, and 50 ng on 30 matched pairs of DNA samples of breast tumour tissues and their corresponding adjacent tissues. As observed in Fig 2F and 2G, LINE-1 and Alu methylation levels between breast tumours and their corresponding adjacent tissues significantly varied depending on the quantity of DNA input. Using 0.5 ng of genomic DNA, LINE-1 and Alu are hypermethylated in breast tumour samples at 62.04% and 49.40% as compared to 40.81% and 35.32%, respectively (P < 0.0001 and 0.002) in adjacent tissue samples. Difference in methylation level at the 5 ng was only observed with Alu but not with LINE-1. However, when tested with 50 ng of DNA input, an insignificant difference in LINE-1 and Alu methylation levels was seen between the tumour samples and the adjacent tissue samples (Fig 2F and 2G).

In addition, incomplete bisulfite conversion of the excessive DNA input was confirmed by using different DNA quantities ranging from 0.5 ng to 500 ng, on DNA samples of breast, colon and lung tumour tissues, which were converted by bisulfite and subsequently used as template for separate amplifications either with the primer sets specific to native consensus sequences or with the MSP primers specific to the methylated sequences. The native LINE-1 product was successfully amplified from DNA input more than 0.5 ng; however, no PCR product was detected with DNA input of 0.5 ng (S2A Fig). Sequencing of the native LINE-1 product with the native primers revealed the rare conversion of non-CpG cytosines, demonstrating renaturation to be a likely cause of incomplete conversion (S2B Fig). On the other hand, PCR products were successfully obtained with DNA inputs of 0.5 ng and 50 ng using the MSP primers specific to the methylated Alu, indicating the presence of methylated Alu in bisulfite-converted DNA (S3A Fig). No PCR product was detected with the 0.5 ng-input DNA using the primer set specific to native Alu sequences, however, native Alu was successfully amplified from the 50 ng-input DNA (S3B Fig). This PCR product was then digested by the HpaII restriction enzyme that recognized one CCGG site in the Alu sequences, indicating that some Alu sequences remained native even after bisulfite conversion (S3C Fig).

Quantification of LINE-1 and Alu copy number, and cfDNA integrity

The number of LINE-1 copies in cfDNA from 180 healthy individuals (cfNC) and 213 lung cancer patients (cfLC) was measured in qPCR reactions to quantify the cfDNA concentration and manage the amount of cfDNA for the bisulfite reactions to eliminate the risk of incomplete conversions. On the other hand, the cfDNA, released from tumor cells, varies in size [24]. The ratio between long- (mostly > 200 bp), and short- (≤ 167 bp) Alu fragments, respectively, is referred to as DNA integrity (cfDI) index [24]. Hence, the number of Alu short (78 bp) and Alu long (205 bp) fragments in cfDNA was quantitatively calculated for 163 healthy individuals and 200 lung cancer patients. Absolute quantification of LINE-1 and Alu number copies was done based on the premise that a diploid genome (~ 6 pg), respectively, consists of 105 and 106 copies of LINE-1 and Alu sequences.

cfDNA was extracted from 0.4 mL plasma collected from one millilitre of blood. The number of LINE-1 copies in one μL of the cfDNA from healthy participants was around 106, and not significantly different from that of lung cancer patients (Fig 3A). cfDNA concentration in cancer is usually higher than that in healthy populations [24], however, in our study, this phenomenon was not yet observed, likely due to the primer set, designed to be specific to the 5-UTR regions of LINE-1 which is truncated during transposition [15], hence, could not be an appropriate marker for evaluating an increase in cfDNA concentration. On the contrary, the number of short Alu copies in one μL of the cfDNA from healthy participants was less than that from lung cancer patients (P = 0.049); however, the number of long Alu copies from healthy participants was more than that from lung cancer patients (P = 0.022) (Fig 3B and 3C). Thus, the DNA integrity index (cfDI), calculated as the ratio of long to short Alu fragments, was higher in cfNC than that in cfLC (Fig 3D), indicating fragmented cfDNA increased in lung cancer patients, in line with cfDNA fragment sizes in cancer was shorter than that in healthy [24]. In addition, the number of LINE-1 and Alu copies was also quantified in two DNA quantities of 0.5 ng and 5 ng from 60 tumour tissue and adjacent tissue samples of breast, colon and lung cancer. The number of LINE-1 and Alu copies was proportional to the amount of DNA extracted from tissues; ranging from 106 to 109 copies, corresponding to 0.5 ng to 5 ng of genomic DNA, respectively (Fig 3E and 3F). Our previous study has indicated that a copy number of repeated sequences higher than 108 can lead to incomplete bisulfite conversion [43, Fig 2A]. Hence, we chose 0.5 ng of genomic DNA isolated from tissue samples and 1 μL of cfDNA for further methylation analysis of these repeats on cancer tissues and cfDNA from lung cancer patients and healthy individuals. This DNA amount is the minimum recommended for bisulfite reaction by most manufacturers.

Fig 3. Quantification of LINE-1 and Alu copy number in cfDNA and cellular DNA.

Fig 3

Open in a new tab

The number of LINE-1 copies (A), short Alu copies (B) and long Alu copies (C) in 1 μL cfDNA extracted from plasma collected from healthy controls (cfNC) and lung cancer patients (cfLC). The DNA integrity index (cfDI) was higher in cfNC than that in cfLC, indicating fragmented cfDNA increased in lung cancer patients (D). The number of LINE-1 and Alu corresponding to different quantities of 0.5 ng (E) and 5 ng (F) of DNA extracted from adjacent tissue (AD) and tumour tissues samples from breast (BC), colon (CRC) and lung (LC) cancer. The number of LINE-1 and Alu in 0.5 ng genomic DNA and in 1 μL of cfDNA is around 107 copies, appropriating for bisulfite complete conversion. The Mann-Whitney U test (A-D), the Wilcoxon matched-pairs signed rank test (E, F) were used in statistical analysis. (ns) nonsignificant. (*) P < 0.05; (****) P < 0.0001.

Analysis of LINE-1 and Alu methylation levels in tumour and adjacent tissues

Using 0.5 ng of genomic DNA for bisulfite conversion, the methylation level of LINE-1 and Alu was quantitatively measured on 201, 133 and 73 pair samples of tumour tissue and their paired tumour-adjacent tissue corresponding to breast, colon and lung cancer. Significant hypermethylation was observed for LINE-1 in tumour samples when compared with adjacent samples (Fig 4). As observed in Fig 4A, the methylated LINE-1 level in tumour tissues of breast samples (52.11%), colon samples (38.67%) and lung samples (43.76%) were significantly higher than that in the adjacent normal tissue (46.27%, 34.89% and 42.78%, respectively) (P < 0.001–0.05). Similarly, significant Alu hypermethylation was revealed in breast (47.96%), colon (49.18%) and lung (66.12%) tumour samples as compared to the corresponding adjacent tissue samples (42.93%, 45.50% and 61.45%, respectively) (P <0.01–0.05) (Fig 4B). The large-scale number of breast and colorectal cancer samples reveals statistically significant association between LINE-1 methylation and pathological stage (P = 0.0038), tumour size (P = 0.0131), as well as tumour grade (P < 0.0001) of breast cancer. However, there was insignificant association between the LINE-1 methylation level and the clinicopathological characteristics of the colon cancer tissues, except for tumour stage (P = 0.0075). Likewise, there was insignificant association between the Alu methylation level and the clinicopathological characteristics of the breast and colon cancer tissues, except for pathological stage of the breast cancer (P = 0.0426) (S2 Table).

Fig 4. LINE-1 and Alu methylation in tissues and cfDNA from cancer and healthy individuals.

Fig 4

Open in a new tab

Hypermethylation of LINE-1 (A) and Alu (B) in breast tumour (BC) samples, lung tumour (LC) samples and colon tumour (CRC) samples as compared with their corresponding adjacent tissue samples (AD). Methylation assessment was performed on DNA of 0.5 ng converted by bisulfite. Hypermethylation of LINE-1 (C) and Alu (D) in cfDNA of lung cancer samples (cfLC) as compared to that in healthy samples (cfNC), respectively. Methylation level of LINE-1 (E) but not of Alu (F) correlates with ageing in the healthy population. The Wilcoxon matched-pairs signed rank test (A, B), the Man-Whitney U test (C, D), and Spearman’s rank correlation test (E, F) were used in statistical analysis. (*) P < 0.05; (**) P < 0.01; (***) P < 0.001; (****) P < 0.0001.

Analysis of LINE-1 and Alu methylation levels in the cfDNA of the healthy and lung cancers

Using one μL of cfDNA for bisulfite conversion, we analysed LINE-1 and Alu methylation level in cfDNA samples extracted from 477 healthy donors and 296 primary lung cancer patients. Expectedly, significant hypermethylation was observed for LINE-1 and Alu in cfDNA from cancer samples compared to that in healthy samples (Fig 4). The methylated LINE-1 levels in lung cancer (49.43%) were significantly higher than that in the healthy samples (35.61%) (P < 0.0001) (Fig 4C). Likewise, significant hypermethylation was observed for Alu in cfDNA from lung cancer patients (56.31%) as compared to that from healthy donors (29.22%) (P < 0.0001) (Fig 4D). Unexpectedly, methylation level of LINE-1, but not of Alu, correlates with ageing as LINE-1 is more methylated in older healthy individuals (P = 0.0002) (Fig 4E and 4F). This correlation was not observed in cancer populations (S4 Fig). In addition, there was a significant association between the pathological stage and metastasis of lung cancer patients and the LINE-1 methylation in cfDNA solely (P = 0.0185) (S3 Table).

Correlation between LINE-1 and Alu fragmentation sizes and their methylation level in cfDNA

As cfDNA fragmentation is impacted by DNA methylation [49], we assessed the correlation between the copy number of LINE-1, short and long Alu sequences with their methylation level in cfDNA (S5 Fig). The number of LINE-1 and short Alu copies, represented by amplicons of 88 bp and 78 bp in size and classified into short-size cfDNA proportion [27,49], correlated insignificantly with their methylation in healthy individuals and lung cancer patients. LINE-1 and Alu elements are enriched by methylated CpG sites, which affect the preference of nucleases [27,50]. Thus, it is reasonable to speculate that this proportion of short-size methylated cfDNA fragments, having undergone fragmentation, became unrelated to their methylation status in both cfNC and cfLC. On the contrary, a decrease in long Alu copy number correlated with an increased Alu methylation level only in healthy individuals, which aligns with the negative relationship between cfDNA methylation and cfDNA fragment size [49]. It is worth noting that global nucleosome positioning is intrinsically affected by Alu elements [51] whose methylated status impacts nucleosome accessibility [49], explaining the no correlation between the copy number of long-size Alu and the increased Alu methylation in lung cancer. Moreover, the negative correlation between the Alu Index, typically used to measure cfDNA fragmentation, and Alu methylation level in both cfNC and cfLC (S5 Fig) also indicates a regulator role of DNA methylation in cfDNA fragmentation in both healthy individuals and cancer patients [49,50].

Discussion

Alterations of CpG methylation status at either genome-wide or gene-specific levels have been confirmed as powerful biomarkers for diagnosis, prognosis, and prediction of diseases [13,24]. Bisulfite conversion-based methods are regarded as the gold standard for quantifying and mapping methylation from selected regions (MethyLight, Methylation-Sensitive High-Resolution Sanger sequencing, pyrosequencing) to whole genome (WGBS, EPIC Capture) [40,41]. A technical weakness of bisulfite-based methods is the incomplete conversion of unmethylated cytosines, thus producing errors in methylation measurement [52]. Actually, to verify bisulfite conversion efficiency in WGBS, methylated pUC19 and unmethylated lambda phage DNA are added to genomic DNA. However, these control DNA are used in smaller amounts (0.0005% and 0.01%, respectively, both equivalent to less than 108 copies) that can be completely converted by bisulfite and thus, not be appropriate controls for the conversion of repeated targets [53]. High-throughput techniques such as Single-molecule real-time (SMRT) or Nanopore sequencing (ONT-seq), all of which are bisulfite-free methods but challenging due to the discordant data produced on the methylation profile of repeated sequences, too rich- or too poor- CpG sequences, and even different performances of DNA methylation calling tools is still controversial [41]. Until now, bisulfite-based methods have been widely used in many studies and commercial kits for DNA methylation analysis [40,54].

Bisulfite conversion exclusively occurs on single-stranded DNA, and is strictly dependent on DNA concentration, sequence complexity, GC content, and secondary structure elements [40,52]. Different commercial bisulfite conversion kits have been comprehensively evaluated for their bisulfite conversion efficiency [54]. These evaluations, however, investigated either endogenously single-locus targets or a small amount of artificially targeted templates but did not consider endogenous repeats or excessive amounts of artificial targets. Spiking an artificial unmethylated DNA molecule with genomic DNA revealed that complete bisulfite conversion is directly impacted by the copy number of the target, regardless of the genomic DNA amount (Fig 2A). Similarly, using an excessive amount of genomic DNA, corresponding to an excessive number of LINE-1 and Alu copies, for bisulfite conversion resulted in a contradicting increase of the ΔCT value in qPCR assays that eminently indicated false hypomethylation of these repeats (Fig 2B–2E). Incomplete conversion was revealed by successful amplification with the primers specific to the native consensus sequences from bisulfite-treated DNA input amounts more than 5 ng (S2 and S3 Figs). It is worth noting that 1 μg of genomic DNA input for methylation analysis, as usually recommended by most manufacturers, is equivalent to 106 copies of single-locus targets, with only 2 copies per diploid genome; however, it would be equivalent to 1011–1012 copies of LINE-1 and Alu repeats, with up to 105–106 copies per genome. It should be reminded that complete bisulfite conversions require the DNA input to consist of strictly single-stranded DNA, thus, an increase in the copy number of the double-stranded target could favourably promote renaturation, resulting in a decrease in the single-strand DNA yielded for bisulfite conversion. This phenomenon is similar to that in PCR reactions in which product yield would dramatically decline when the DNA template is over the threshold. Thus, it is reasonable that detrimental errors in LINE-1 and Alu methylation assessment are caused by an excessive amount of DNA input for bisulfite conversion, the phenomenon has been previously described in our profiling of LINE-1 methylation [43]. Based on obtained results, we speculate that the increase in copy number of LINE-1 and Alu in cancer by their transposition [15], combined with a disproportionate amount of genomic DNA used for bisulfite conversion could cause an inefficient conversion by bisulfite and is likely to result in the faulty hypomethylation of these elements, which is detected in almost all reports on ageing and cancer described so far.

In this study, our findings indicated that a cellular DNA amount of less than 0.5 ng, or 1 μL of cfDNA extracted from 1 mL of blood was appropriate for methylation quantification of repeat sequences by bisulfite-based methods. We presented direct evidence of hypermethylation of LINE-1 and Alu repeats, which is shown to predominantly occur in tissues as well as cfDNA from cancers (Fig 4). LINE-1 and Alu are hypermethylated in breast, colon, and lung tumour tissues as compared to their adjacent normal tissues (Fig 4A and 4B). Similarly, they are also hypermethylated in cfDNA from lung cancer as compared to healthy controls (Fig 4C and 4D). These results are in direct contrast to the longstanding assumption of these repeats being hypomethylated in solid and liquid biopsy samples from diseases and cancers including breast, colon and lung cancer [13,14,30].

Hypomethylation of LINE-1 and Alu repeats and their de-repression have been considered important features of ageing and cancer [9,13,19]. Recent emerging evidence, however, has revealed that this outdated assumption requires reconsidering [55]. In different types of cancer, LINE-1 hypermethylation and its silencing promote the growth of tumour subclones and metastasis [34,35], allowing cancer cells to bypass antitumour immune responses and protecting cancer cell subpopulations from lethal drug exposure [36,37]. DNA-hypomethylation-induced overexpression of LINE-1 repeats, responsible for the trans mobilisation of Alu, can result in detrimental impacts on the progression and survival of tumour cells [5]. On the other hand, an increased level of Alu transcripts in diseases and cancers has been explained by DNA hypomethylation and vice versa. This increase was, however, associated with the production of dsRNA, which can promote innate immune responses and apoptosis, prevent DNA damage and promote wound healing [20,38]. Alu siRNA processed from dsRNA can subsequently induce Alu methylation itself, elevating resistance to DNA-damaging agents [38,39]. Moreover, Alu RNA transcribed by Pol III can act as a modular trans-acting repressor of mRNA transcription through their binding on Pol II, and on protein translation; thus, inhibiting ribosome assembly [21,22]. Repression of Alu, mediated by SETDB1, an enzyme that deposits the H3K9me3 mark on Alu sequences, was observed in cancer cells [52]. These findings support our results that LINE-1 and Alu are hypermethylated in cancer, which has been hidden due to incomplete bisulfite conversions, and all together, providing a re-evaluation concerning the tumour-suppressive role of their methylation in cancer [55].

cfDNA retains the genetic and epigenetic characteristics of the tissue from which it was released [30]. As expected, hypermethylation of the LINE-1 and Alu, observed in the lung tumour tissues, was also revealed in cfDNA from lung cancer patients as compared with healthy individuals (Fig 4C and 4D). Interestingly, LINE-1 methylation in cfDNA significantly associated with pathological stage and metastasis in cancer patients (S3 Table). These elements abundant in cfDNA [23]; hence, their methylation assessment has become more favourable than other targets due to the sparse quantity of cfDNA. By demonstrating that a minuscule amount of cfDNA is preferable for their methylation assessment, our findings directly contributed to the standardized bisulfite-based protocols for DNA methylation assays, particularly in applications on repeated targets. The limitation of this study is the focus on the LINE-1 and Alu elements as an entire group, instead of studying the methylation levels of a particular family or individual LINE-1 and Alu loci, which are distinctly exhibited during normal development, ageing, diseases and cancer [2,47,56]. It is necessary for the locus- and tissue-specific patterns of their methylation to be investigated further in diseases and cancer. In addition, their hypermethylation in cfDNA, contributing to cfDNA methylation signatures can provide a promising tool for improving markers for cancer screening, accurate disease-progression surveillance and improvement of treatment [57,58].

Conclusion

To summarize, this study has demonstrated that detrimental errors in measurement of the LINE-1 and Alu methylation level are caused by an excessive input of genomic DNA, or an excessive copy number of these repeats, used for bisulfite conversion. A minuscule DNA amount, corresponding to a number of under 108 copies was appropriate for bisulfite-based methods to identify their hypermethylation, which is shown to predominantly occur in tissues as well as cfDNA from cancers. Particularly, LINE-1 and Alu methylation in cfDNA, associated with lung cancer, provides a potential DNA marker in real-time monitoring of diagnosis and prognosis in cancer. Our study suggests another perspective for other repetitive sequences whose epigenetic properties may have crucial impacts on genome architecture and human health.

Supporting information

S1 Table. Primer sets and quantitative real-time PCR conditions for quantification of copy number and measurement of methylation level of LINE-1 and Alu.

The methylation-dependent-specific PCR (MSP) primers (Me-) are designed from the consensus sequences of LINE-1 and Alu (S1 Fig). All non-CpG cytosines were replaced by ‘t” in the forward primers and by “a” in the reverse ones.

(PDF)

pone.0316394.s001.pdf (123.3KB, pdf)
S2 Table

Association of clinicopathological characteristics of cancer patients with LINE-1 (A) and Alu (B) methylation status in tissues of breast cancer, colon cancer and lung cancer.

(PDF)

pone.0316394.s002.pdf (198KB, pdf)
S3 Table

Association of clinicopathological characteristics of lung cancer patients with LINE-1 (A) and Alu (B) methylation status in cfDNA.

(PDF)

pone.0316394.s003.pdf (159.8KB, pdf)
S1 Fig. Identification of LINE-1 and Alu consensus sequences followed by analyses on repeat masker [48] and ClustalW.

(A-C) Alignment of the 5’ end region of L1 elements. The alignments include the old L1PA consensus sequence (A), the young L1Hs consensus representative to L1-Ta-0 (B) and L1-Ta-1 (C). The positions of the primers used in this study are shown with arrows, indicating the primers have been well designed to target all L1Hs elements including the L1 consensus sequence (accession no. X58075). (D-F) Alignment of the Alu sequences of young (AluY), intermediate (AluS) and old (Alu J) individual Alu repeats. Based on these Alu consensus sequences, the primer sets specific to methylated Alu sequences were designed. The positions of the primers used in this study are shown with arrows.

(PDF)

pone.0316394.s004.pdf (594.3KB, pdf)
S2 Fig. Detection of the native LINE-1 sequences after bisulfite conversion.

(A) The PCR product was successfully amplified with the primers specific to the native LINE-1 from bisulfite-treated DNA with 5ng, 50ng, and 500 ng, on DNA samples of breast (1), colon (2) and lung tumour (3) tissues. However, no native LINE-1 product was detected when the DNA input was 0.5 ng. (—): Negative control without DNA template. (B). Direct sequencing of PCR products amplified from bisulfite-treated DNA with an input amount of 0.5 ng using the MIP primers and an input amount of 50 ng using the primers specific to the native LINE-1 sequences. Almost non-CpG cytosines remained in DNA input of 50 ng. Rare conversions of non-CpG cytosines were underlined.

(PDF)

pone.0316394.s005.pdf (41.2KB, pdf)
S3 Fig. Detection of the native Alu sequences after bisulfite conversion.

(A). The PCR product was successfully amplified with the MSP primers specific to the methylated Alu sequences from bisulfite-treated DNA with different DNA quantities of 0.5 ng and 50 ng on DNA samples of breast (1) and colon (2) tumour tissues. (+): Recombinant plasmid containing the methylated Alu sequences used as template. (B). The PCR product was successfully amplified with the primers specific to the native Alu sequences from bisulfite-treated DNA of 50 ng input. However, no native Alu product was detected when the DNA input was 0.5 ng. PC: Positive control with DNA extracted from a blood sample as template. NTC: Negative control without DNA template. (C). Digestion of the PCR products from (B) with the HpaII restriction enzyme, recognizing one CCGG site in the Alu sequences, indicated that some native Alu sequences remained after bisulfite conversion of a DNA input of 50 ng.

(PDF)

pone.0316394.s006.pdf (41.1KB, pdf)
S4 Fig

LINE-1 (A) and Alu (B) methylation levels in cfDNA do not correlate with ageing in lung cancer patients. Methylation assessments were performed on one microlitre of bisulfite-converted cfDNA. The Spearman’s rank correlation test (A, B) was used in statistical analysis.

(PDF)

pone.0316394.s007.pdf (84.7KB, pdf)
S5 Fig. Correlation between LINE-1 and Alu fragmentation sizes with their methylation level in cfDNA from healthy individuals (cfNC) and lung cancer patients (cfLC).

No relationship was observed between the copy numbers of short LINE-1 (A) and short Alu (B) with their methylation level in both cfNC and cfLC. A negative correlation was detected between the long Alu copy number and Alu methylation in cfNC but not in cfLC (C). Alu Index negatively correlated with Alu methylation in both cfNC and cfLC (D). Correlations were assessed using Spearman’s rank correlation test.

(PDF)

pone.0316394.s008.pdf (195.5KB, pdf)

Acknowledgments

The authors would like to thank Pham ATD at the Biomedical Lab, VNU University of Science for technical support.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This study was funded by the Vingroup Innovation Foundation (VINIF) under project code VINIF.2022.DA00036. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822): 860–921. doi: 10.1038/35057062 [DOI] [PubMed] [Google Scholar]
  • 2.Gasparotto E, Burattin FV, Di Gioia V, Panepuccia M, Ranzani V, Marasca F, et al. Transposable elements co-option in genome evolution and gene regulation. Int J Mol Sci. 2023;24(3): 2610. doi: 10.3390/ijms24032610 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Dewannieux M, Esnault C, Heidmann T. LINE-mediated retrotransposition of marked Alu sequences. Nat Genet. 2003;35(1): 41–48. doi: 10.1038/ng1223 [DOI] [PubMed] [Google Scholar]
  • 4.Raiz J, Damert A, Chira S, Held U, Klawitter S, Hamdorf M, et al. The non-autonomous retrotransposon SVA is trans-mobilized by the human LINE-1 protein machinery. Nucleic Acids Res. 2012;40(4): 1666–1683. doi: 10.1093/nar/gkr863 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Lu JY, Chang L, Li T, Wang T, Yin Y, Zhan G, et al. Homotypic clustering of L1 and B1/Alu repeats compartmentalizes the 3D genome. Cell Res. 2021;31(6): 613–630. doi: 10.1038/s41422-020-00466-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Romano NC, Fanti L. Transposable elements: major players in shaping genomic and evolutionary patterns. Cells. 2022;11(6): 1048. doi: 10.3390/cells11061048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Lawson HA, Liang Y, Wang T. Transposable elements in mammalian chromatin organization. Nat Rev Genet. 2023;24(10): 712–723. doi: 10.1038/s41576-023-00609-6 [DOI] [PubMed] [Google Scholar]
  • 8.Kunarso G, Chia NY, Jeyakani J, Hwang C, Lu X, Chan YS, et al. Transposable elements have rewired the core regulatory network of human embryonic stem cells. Nat Genet. 2010;42(7): 631–634. doi: 10.1038/ng.600 [DOI] [PubMed] [Google Scholar]
  • 9.Bhat A, Ghatage T, Bhan S, Lahane GP, Dhar A, Kumar R, et al. Role of transposable elements in genome stability: implications for health and disease. Int J Mol Sci. 2022;23(14): 7802. doi: 10.3390/ijms23147802 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Polak P, Domany E. Alu elements contain many binding sites for transcription factors and may play a role in regulation of developmental processes. BMC Genomics. 2006;7: 133. doi: 10.1186/1471-2164-7-133 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Ferrari R, Cucalon LI, Di Vona C, Le Dilly F, Vidal E, Lioutas A, et al. TFIIIC binding to Alu elements controls gene expression via chromatin looping and histone acetylation. Mol Cell. 2020;77(3): 475–487.e11. doi: 10.1016/j.molcel.2019.10.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Chen LL, Yang L. ALUternative regulation for gene expression. Trends Cell Biol. 2017;27(7): 480–490. doi: 10.1016/j.tcb.2017.01.002 [DOI] [PubMed] [Google Scholar]
  • 13.Ponomaryova AA, Rykova EY, Gervas PA, Cherdyntseva NV, Mamedov IZ, Azhikina TL. Aberrant methylation of LINE-1 transposable elements: a search for cancer biomarkers. Cells. 2020;9(9): 2017. doi: 10.3390/cells9092017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Rodriguez J, Vives L, Jordà M, Morales C, Muñoz M, Vendrell E, et al. Genome-wide tracking of unmethylated DNA Alu repeats in normal and cancer cells. Nucleic Acids Res. 2008;36(3): 770–784. doi: 10.1093/nar/gkm1105 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Rodriguez-Martin B, Alvarez EG, Baez-Ortega A, Zamora J, Supek F, Demeulemeester J, et al. Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition. Nat Genet. 2020;52(3): 306–319. doi: 10.1038/s41588-019-0562-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Della Valle F, Reddy P, Yamamoto M, Liu P, Saera-Vila A, Bensaddek D, et al. LINE-1 RNA causes heterochromatin erosion and is a target for amelioration of senescent phenotypes in progeroid syndromes. Sci Transl Med. 2022;14(657): eabl6057. doi: 10.1126/scitranslmed.abl6057 [DOI] [PubMed] [Google Scholar]
  • 17.Gu Z, Liu Y, Zhang Y, Cao H, Lyu J, Wang X, et al. Silencing of LINE-1 retrotransposons is a selective dependency of myeloid leukemia. Nat Genet. 2021;53(5): 672–682. doi: 10.1038/s41588-021-00829-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.De Cecco M, Ito T, Petrashen AP, Elias AE, Skvir NJ, Criscione SW, et al. L1 drives IFN in senescent cells and promotes age-associated inflammation. Nature. 2019;566(7742): 73–78. doi: 10.1038/s41586-018-0784-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Ye D, Jiang D, Zhang X, Mao Y. Alu methylation and risk of cancer: a meta-analysis. Am J Med Sci. 2020;359(5): 271–280. doi: 10.1016/j.amjms.2020.03.002 [DOI] [PubMed] [Google Scholar]
  • 20.Zhang XO, Gingeras TR, Weng Z. Genome-wide analysis of polymerase III–transcribed Alu elements suggests cell-type–specific enhancer function. Genome Res. 2019;29(9): 1402–1414. doi: 10.1101/gr.249789.119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Kassube SA, Fang J, Grob P, Yakovchuk P, Goodrich JA, Nogales E. Structural insights into transcriptional repression by noncoding RNAs that bind to human Pol II. J Mol Biol. 2013;425(19): 3639–3648. doi: 10.1016/j.jmb.2012.08.024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Ivanova E, Berger A, Scherrer A, Alkalaeva E, Strub K. Alu RNA regulates the cellular pool of active ribosomes by targeted delivery of SRP9/14 to 40S subunits. Nucleic Acids Res. 2015; 43(5): 2874–2887. doi: 10.1093/nar/gkv048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Grabuschnig S, Soh J, Heidinger P, Bachler T, Hirschböck E, Rosales Rodriguez I, et al. Circulating cell-free DNA is predominantly composed of retrotransposable elements and non-telomeric satellite DNA. J Biotechnol. 2020;313: 48–56. doi: 10.1016/j.jbiotec.2020.03.002 [DOI] [PubMed] [Google Scholar]
  • 24.Rodríguez-Ces AM, Rapado-González Ó, Salgado-Barreira Á, Santos MA, Aroso C, Vinhas AS, et al. Liquid Biopsies Based on Cell-Free DNA Integrity as a Biomarker for Cancer Diagnosis: A Meta-Analysis. Diagnostics. 2024; 14(14):1465. doi: 10.3390/diagnostics14141465 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Mittra I, Khare NK, Raghuram GV, Chaubal R, Khambatti F, Gupta D, et al. Circulating nucleic acids damage DNA of healthy cells by integrating into their genomes. J Biosci. 2015;40(1): 91–111. doi: 10.1007/s12038-015-9508-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Niu Z, Tang W, Liu T, Xu P, Zhu D, Ji M, et al. Cell-free DNA derived from cancer cells facilitates tumor malignancy through Toll-like receptor 9 signaling-triggered interleukin-8 secretion in colorectal cancer. Acta Biochim Biophys Sin. 2018;50(10): 1007–1017. doi: 10.1093/abbs/gmy104 [DOI] [PubMed] [Google Scholar]
  • 27.Wang W, Kong P, Ma G, Li L, Zhu J, Xia T, et al. Characterization of the release and biological significance of cell-free DNA from breast cancer cell lines. Oncotarget. 2017; 8(26): 43180–43191. doi: 10.18632/oncotarget.17858 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Kang TH, Mao CP, Kim YS, Kim TW, Yang A, Lam B, et al. TLR9 acts as a sensor for tumor-released DNA to modulate anti-tumor immunity after chemotherapy. J Immunother Cancer. 2019;7(1): 260. doi: 10.1186/s40425-019-0738-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Sipos F, Kiss AL, Constantinovits M, Tulassay Z, Műzes G. Modified genomic self-DNA influences in vitro survival of HT29 tumor cells via TLR9- and autophagy signaling. Pathol Oncol Res. 2019;25(4): 1505–1517. doi: 10.1007/s12253-018-0544-z [DOI] [PubMed] [Google Scholar]
  • 30.Duforestel M, Briand J, Bougras-Cartron G, Heymann D, Frenel JS, Vallette FM, et al. Cell-free circulating epimarks in cancer monitoring. Epigenomics. 2020;12(2): 145–155. doi: 10.2217/epi-2019-0170 [DOI] [PubMed] [Google Scholar]
  • 31.Barchitta M, Quattrocchi A, Maugeri A, Canto C, La Rosa N, Cantarella MA, et al. LINE-1 hypermethylation in white blood cell DNA is associated with high-grade cervical intraepithelial neoplasia. BMC Cancer. 2017;17(1): 601. doi: 10.1186/s12885-017-3582-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Dunaeva M, Derksen M, Pruijn GJM. LINE-1 hypermethylation in serum cell-free DNA of relapsing remitting multiple sclerosis patients. Mol Neurobiol. 2018;55(6): 4681–4688. doi: 10.1007/s12035-017-0679-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Hwang T, Kim S, Chowdhury T, Yu HJ, Kim KM, Kang H, et al. Genome-wide perturbations of Alu expression and Alu-associated post-transcriptional regulations distinguish oligodendroglioma from other gliomas. Commun Biol. 2022;5(1): 62. doi: 10.1038/s42003-022-03011-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Ardeljan D, Steranka JP, Liu C, Li Z, Taylor MS, Payer LM, et al. Cell fitness screens reveal a conflict between LINE-1 retrotransposition and DNA replication. Nat Struct Mol Biol. 2020;27(2): 168–178. doi: 10.1038/s41594-020-0372-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.De Araújoa ES, Kashiwabarae AY, Achatza MI, Moredo LF, De Sá BC, Duprat JP, et al. LINE-1 hypermethylation in peripheral blood of cutaneous melanoma patients is associated with metastasis. Melanoma Res. 2015;25(2): 173–177. doi: 10.1097/CMR.0000000000000141 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Guler GD, Tindell CA, Pitti R, Wilson C, Nichols K, KaiWai Cheung T, et al. Repression of stress-induced LINE-1 expression protects cancer cell subpopulations from lethal drug exposure. Cancer Cell. 2017;32(2): 221–237.e13. doi: 10.1016/j.ccell.2017.07.002 [DOI] [PubMed] [Google Scholar]
  • 37.Cuellar TL, Herzner AM, Zhang X, Goyal Y, Watanabe C, Friedman BA, et al. Silencing of retrotransposons by SETDB1 inhibits the interferon response in acute myeloid leukemia. J Cell Biol. 2017;216(11): 3535–3549. doi: 10.1083/jcb.201612160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Gussakovsky D, McKenna SA. Alu RNA and their roles in human disease states. RNA Biol. 2021;18(Suppl 2): 574–585. doi: 10.1080/15476286.2021.1989201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Yasom S, Khumsri W, Boonsongserm P, Kitkumthorn N, Ruangvejvorachai P, Sooksamran A, et al. B1 siRNA increases de novo DNA methylation of B1 elements and promotes wound healing in diabetic rats. Front Cell Dev Biol. 2022;9: 802024. doi: 10.3389/fcell.2021.802024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Kurdyukov S, Bullock M. DNA methylation analysis: choosing the right method. Biology (Basel). 2016;5(1): 3. doi: 10.3390/biology5010003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Gouil Q, Keniry A. Latest techniques to study DNA methylation. Essays Biochem. 2019;63(6): 639–648. doi: 10.1042/EBC20190027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Bock C, Halbritter F, Carmona FJ, Tierling S, Datlinger P, Assenov Y, et al. Quantitative comparison of DNA methylation assays for biomarker development and clinical applications. Nat Biotechnol. 2016;34(7): 726–737. doi: 10.1038/nbt.3605 [DOI] [PubMed] [Google Scholar]
  • 43.Pham DAT, Le SD, Doan TM, Luu PT, Nguyen UQ, Ho SV, et al. Standardization of DNA amount for bisulfite conversion for analyzing the methylation status of LINE-1 in lung cancer. PLoS One. 2021;16(8): e0256254. doi: 10.1371/journal.pone.0256254 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Robinson MD, Stirzaker C, Statham AL, Coolen MW, Song JZ, Nair SS, et al. Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias, and copy number variation. Genome Res. 20(12): 1719–1729. doi: 10.1101/gr.110601.110 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Pappalardo XG, Barra V. Losing DNA methylation at repetitive elements and breaking bad. Epigenetics Chromatin. 2021;14(1): 25. doi: 10.1186/s13072-021-00400-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2001;25(4): 402–408. doi: 10.1006/meth.2001.1262 [DOI] [PubMed] [Google Scholar]
  • 47.Price AL, Eskin E, Pevzner PA. Whole-genome analysis of Alu repeat elements reveals complex evolutionary history. Genome Res. 2004;14(11): 2245–2252. doi: 10.1101/gr.2693004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Smit AFA, Hubley R, Green P. Human ALU Subfamilies. 2012. June 26 [cited 13 December 2023]. In: Repeatmasker [Internet]. Seattle: Institute for Systems Biology. Available from: https://www.repeatmasker.org/AluSubfamilies/humanAluSubfamilies.html [Google Scholar]
  • 49.An Y, Zhao X, Zhang Z, Xia Z, Yang M, Ma L, et al. DNA methylation analysis explores the molecular basis of plasma cell-free DNA fragmentation. Nature Communications. 2023; 14:287. doi: 10.1038/s41467-023-35959-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Zhou Q, Guannan Kang G, Peiyong Jiang P, Rong Qiao R, Lam WK, Stephanie C. Y. Yu SC. Epigenetic analysis of cell-free DNA by fragmentomic profiling. PNAS. 2022; 119(44): e2209852119. doi: 10.1073/pnas.2209852119 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Tanaka Y, Yamashita R, Suzuki Y, Nakai K. Effects of Alu elements on global nucleosome positioning in the human genome. BMC Genomics. 2010; 11:309. doi: 10.1186/1471-2164-11-309 PMCID: PMC2878307 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Genereux DP, Johnson WC, Burden AF, Stöger R, Laird CD. Errors in the bisulfite conversion of DNA: modulating inappropriate- and failed-conversion frequencies. Nucleic Acids Res. 2008;36(22): e150. doi: 10.1093/nar/gkn691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Morrison J, Koeman JM, Johnson BK, Foy KK, Beddows I, Zhou W, et al. Evaluation of whole-genome DNA methylation sequencing library preparation protocols. Epigenetics Chromatin. 2021; 14:28. doi: 10.1186/s13072-021-00401-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Worm Ørntoft MB, Jensen SO, Hansen TB, Bramsen JB, Andersen CL. Comparative analysis of 12 different kits for bisulfite conversion of circulating cell-free DNA. Epigenetics. 2017;12(8): 626–636. doi: 10.1080/15592294.2017.1334024 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Kelsey MMG. Reconsidering LINE-1’s role in cancer: does LINE-1 function as a reporter detecting early cancer-associated epigenetic signatures? Evol Med Public Health. 2021;9(1): 78–82. doi: 10.1093/emph/eoab004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Costallat M, Batsché E, Rachez C, Muchardt C. The ’Alu-ome’ shapes the epigenetic environment of regulatory elements controlling cellular defense. Nucleic Acids Res. 2022;50(9): 5095–5110. doi: 10.1093/nar/gkac346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Kermi C, Lau L, Shahmirzadi A, Classon M. Disrupting mechanisms that regulate genomic repeat elements to combat cancer and drug resistance. Front Cell Dev Biol. 2022;10: 826461. doi: 10.3389/fcell.2022.826461 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Brito-Rocha T, Constâncio V, Henrique R, Jerónimo C. Shifting the cancer screening paradigm: the rising potential of blood-based multi-cancer early detection tests. Cells 2023;12(6): 935. doi: 10.3390/cells12060935 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Osman El-Maarri

8 Nov 2024

PONE-D-24-37696An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancersPLOS ONE

Dear Dr. Vo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 23 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Osman El-Maarri, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

1. When submitting your revision, we need you to address these additional requirements.

Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at 

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Thank you for stating the following financial disclosure: 

This study was funded by the Vingroup Innovation Foundation (VINIF) under project code VINIF.2022.DA00036

Please state what role the funders took in the study.  If the funders had no role, please state: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." 

If this statement is not correct you must amend it as needed. 

Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf.

3. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section. 

4. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I consider these data worth to be published. In spite it "contradicts" the widely accepted results regarding hypomethylation in repeated sequences, I think we, the scientific comnunity should try to replicate our epigenetic studies with a smaller amount of DNA. What I consider as very novel results are those from cfDNA, and I think authors have used good control groupd for comparison. I also think these data are worth to be publishes since they are supported by a previous study, also, other different authors had already proposed to explore new mechanistics rehardin Alu and LINE-1 in cancer development

Reviewer #2: This article is undoubtedly of interest not only to molecular biologists and also to oncologists. Article corresponds to the topics of this journal however there are several clarifying questions (comments) to the authors:

Questions:

1. Quantification of LINE-1, Alu copy number and measurement of methylation level was performed on tissue samples and cell-free DNA from lung cancer patients? Is there any results received on samples from breast cancer patients and colorectal cancer patients?

2. Why in this article did not discussed correlation (or absent of correlation) between LINE-1, Alu copy number and methylation level in tissue samples and cell-free DNA?

3. Authors quantified copy number and methylation level for the total pool of Alu elements (“short” and “long”?). This information did not indicated in results. Although in “Materials and methods” indicate that both sequences were determined.

Reviewer #3: The study aims to address the technical issue of the influence of DNA concentration on the efficiency of DNA conversion and to investigate the methylation level of repetitive sequences in the tumor.

The reviewer has several comments and observations.

Major

Page 7, line 170. Authors should provide information about the total size of the UnIC and ConIC plasmids, size of inserts and number of C in this inserts to understand the real quantitative differences between these plasmids for the bisulfite conversion. In ref. 44 there is only one indirect mention of the size of these plasmids (in S3 Table). "Linearized recombinant plasmids (4 pg equivalent to 10*6 copies)"

Page 11, line 287. What amount of DNA was used as template in the PCR reactions? Was it constant or did it vary with the amount of DNA taken for bisulfite conversion? This information should be provided.

In the discussion, the authors suggest that hypomethylation in tumor cells observed in many studies is a consequence of cytosine conversion to the methylation level of LINE-1 and discuss the mechanism of such an effect for MSP. However, hypomethylation of LINE in tumors has also been shown using direct sequencing (pyrosequencing, massive parallel sequencing), when incomplete cytosine conversion can be directly assessed in the final data. Authors should include a discussion of this issue in the Discussion section.

Minor

Page 2, line 44. Reference "221" should be replaced by "1"

Page 3, line 70. Reference is lost

Page 9, line 223-226. Two first sentences of the Result section seem to be similar to each other and should be re-written

Page 13, line 335. Change 'S2A Fig.' to 'Fig. S2A'

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Octavio Jiménez-Garza

Reviewer #2: No

Reviewer #3: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Dec 30;19(12):e0316394. doi: 10.1371/journal.pone.0316394.r002

Author response to Decision Letter 0

14 Nov 2024

Vo Thi Thuong Lan, Assoc. Prof.

Faculty of Biology, VNU University of Science,

334, Nguyen Trai, Thanh Xuan

Ha Noi, Viet Nam.

PLoS ONE Editorial Board

Ha Noi, December 14th, 2024

Dear Members of the Editorial Board,

We are deeply grateful to the Reviewers for the supportive comments and suggestions that have allowed us to considerably improve our manuscript titled “An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers” by Tran et al., submitted to the PLoS ONE under the reference ID: PONE-D-24-37696. After meticulous consideration of the comments from the Reviewers, we have now rewritten the manuscript to address their feedback and align more closely to the journal’s requirements. Modifications have been tracked in the revised manuscript and are detailed point by point in the following section.

We confirm that this study was funded by Vingroup Innovation Foundation (VINIF) under project code VINIF.2022.DA00036. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript, however, decided on the journal for publication.

In the resubmitted manuscript, we have:

� Added one sub-section in the Results “Correlation between LINE-1 and Alu fragmentation sizes and their methylation level in cfDNA” and S5 Fig.

� Added a supplementary figure S5 Fig.

� Added three citations [ref. 50 – ref. 52] to support the correlation between LINE-1 and Alu fragmentation sizes and their methylation level in cfDNA.

� Added one citation [ref. 54] as documentation of DNA controls used in whole genome bisulfite sequencing (WGBS) to verify bisulfite conversion efficiency.

To better adhere to the journal requirements, we have:

� Reformatted the manuscript to meet PloS ONE’s style requirements.

� Stated the role of the funders in the study as follows: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript, however, decided on the journal for publication.”

� Confirmed the ethics statement in Materials and Method is correct and removed this statement from the section after the main text.

� Confirmed the reference list is complete and correct.

We would like to note that author corrections were made for five papers. However, these corrections are minor, either not related to or do not alter experimental results, their interpretation or the conclusions of the articles, thus do not affect our citations.

Brief details of the corrections are as follows:

[Ref 15] corrected and added author affiliations. doi: 10.1038/s41588-023-01319-9

[Ref 18] corrected figures with data points corresponded to the means ±1 standard deviation, rather than actual data points, as well as files and data related to this error. doi: 10.1038/s41586-019-1350-9

[Ref 23] added missing Supplementary Tables. doi: 10.1093/bioinformatics/btae600

[Ref 45] corrected reversed figure legends and the text mentioning these figures. Genome Res. 2011 Jan;21(1):146

[Ref 50] corrected the molarity of the resulting solution in the methods section. doi: 10.1093/nar/gkp637

Reviewer #1:

We are grateful to the Reviewer for your comment. We are currently investigating the methylation level of repetitive sequences in cancer tissues as well as in circulating cell-free DNA (cfDNA) from gynecologic, gastrointestinal cancer patients and healthy individuals.

Reviewer #2:

1. Quantification of LINE-1, Alu copy number and measurement of methylation level was performed on tissue samples and cell-free DNA from lung cancer patients? Are there any results received on samples from breast cancer patients and colorectal cancer patients?

In our study, the copy numbers of LINE-1 and Alu and their methylation levels were quantified in tissue samples from breast, colon and lung cancer patients (Figs 3E and F, Figs 4A and B). However, their copy numbers and methylation levels were quantified in cfDNA from only lung cancer patients (cfLC) and healthy individuals (cfNC) (Figs 3A-D, Figs 4C and D).

2. Why in this article did not discussed correlation (or absent of correlation) between LINE-1, Alu copy number and methylation level in tissue samples and cell-free DNA?

We are grateful to the Reviewer for your interesting comment. In this study, we assessed the correlation between the copy numbers of LINE-1 and Alu and the DNA input amount (ng) on tissue samples (Figs 3 E and F) in order to choose the appropriate amount of DNA input (0.5 ng of cellular DNA, corresponding to less than 108 copies of LINE-1 and Alu), for bisulfite reactions. Since the number of tissue samples used for copy number quantification (N = 60) was greatly less than that for methylation level quantification (N = 201, 134 and 73 matched pairs of tumor-normal tissues from breast, colon and lung cancer, respectively), the correlation between LINE-1 and Alu copy number and their methylation level in tissue samples were not mentioned.

On the other hand, LINE-1 and Alu sequences, predominant components of cfDNA, are overrepresented by past 200% compared to their composition in the genome [ref 24], thus, the copy numbers of LINE-1 and Alu in cfDNA from lung cancer patients (cfLC) and healthy individuals (cfNC) were carefully assessed with a large number of samples (N >150) (Figs 3 A-D). Following the Reviewer’s suggestion, we included that a decrease in long Alu copy number but not in that of short Alu correlated with an increased Alu methylation level cfNC, which is in line with the fact that shorter cfDNA correlated with an increased DNA methylation [1]. Moreover, the negative correlation between Alu methylation level and Alu Index, typically used to measure cfDNA fragmentation also indicates a regulator role of DNA methylation in cfDNA fragmentation in both healthy individuals and cancer patients [1,2]. In addition, there was no correlation between LINE-1 copy number and its methylation level in cfNC and cfLC.

In the revised manuscript, we have adjusted the Results section to include this assessment under the sub-section “Correlation between LINE-1 and Alu fragmentation sizes and their methylation level in cfDNA” and added a supplementary figure S5 Fig (line 451, page 18).

3. Authors quantified copy number and methylation level for the total pool of Alu elements (“short” and “long”?). This information did not indicate in results. Although in “Materials and methods” indicate that both sequences were determined.

We thank the Reviewer for this recommendation. As explained above, we have adjusted the Results section to include an assessment of correlation between the copy number of short Alu, long Alu, and the Alu Index with the total Alu methylation level in the revised manuscript (line 451, page 18, S5 Fig).

References

1. Kim M, Park J, Oh S, Jeong BH, Byun Y, Shin SH, et al. Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis. Scientific Reports. 2024; 14(1):14797. doi: 10.1038/s41598-024-63411-2 PMID: 38926407

2. An Y, Zhao X, Zhang Z, Xia Z, Yang M, Ma L, et al. DNA methylation analysis explores the molecular basis of plasma cell-free DNA fragmentation. Nature Communications. 2023; 14:287. Doi: 10.1038/s41467-023-35959-6.

Reviewer #3: The study aims to address the technical issue of the influence of DNA concentration on the efficiency of DNA conversion and to investigate the methylation level of repetitive sequences in the tumor.

The reviewer has several comments and observations.

Major:

1. Page 7, line 170. Authors should provide information about the total size of the UnIC and ConIC plasmids, size of inserts and number of C in these inserts to understand the real quantitative differences between these plasmids for the bisulfite conversion. In ref. 44 there is only one indirect mention of the size of these plasmids (in S3 Table). "Linearized recombinant plasmids (4 pg equivalent to 10*6 copies)"

We appreciate the comment from the Reviewer. The ConIC and UnIC inserts are both 122 bp in length, subcloned into the 2886 bp pTZ57R/T vector, and were initially reported by Lan et al. (2019) [1]. It is crucial to note that these inserts are identical in sequence, except that all 15 cytosines in the UnIC are replaced by thymines in the ConIC, allowing the ConIC to be used as the calibrator for 100 % bisulfite conversion efficiency, with the UnIC as the indicator (Fig 1). We have revised the Materials and Methods section in our manuscript to include these IC definitions (line 168, page 7).

Fig 1. Nucleotide sequences (122 bp) of the UnIC and the ConIC fragments. All “C” (highlighted in red) in the UnIC sequence are replaced by ‘t” in the ConIC sequence. The CF-F/R primer set (highlighted in yellow) targeting the CF sequence in the IC is used to evaluate DNA recovery, and the MSP-F/R primer set (underlined in the UnIC) is used to assess bisulfite conversion efficiency [1].

2. Page 11, line 287. What amount of DNA was used as template in the PCR reactions? Was it constant or did it vary with the amount of DNA taken for bisulfite conversion? This information should be provided.

We thank the Reviewer for this recommendation. Five different DNA quantities of 0.5 ng, 1 ng, 5 ng, 50 ng, and 500 ng of human methylated DNA were converted by bisulfite. Bisulfite-converted DNA inputs of 5 ng, 50 ng and 500 ng, diluted by 5, 50 and 500 folds and 20, 200 and 2000 folds, were respectively used for LINE-1 and Alu methylation assessment. Two μL of the diluted solutions and the bisulfite-converted DNA inputs of 0.5 ng and 1 ng were then used as templates for qPCR. We have adjusted the Materials and Methods section of our manuscript to include this information (line 183, page 8).

3. In the discussion, the authors suggest that hypomethylation in tumor cells observed in many studies is a consequence of cytosine conversion to the methylation level of LINE-1 and discuss the mechanism of such an effect for MSP. However, hypomethylation of LINE in tumors has also been shown using direct sequencing (pyrosequencing, massive parallel sequencing), when incomplete cytosine conversion can be directly assessed in the final data. Authors should include a discussion of this issue in the Discussion section.

We fully agree with the Reviewer. The most common bisulfite-conversion-based techniques that have been performed to profile LINE-1 methylation are pyrosequencing and whole genome bisulfite sequencing (WGBS). To verify bisulfite conversion in WGBS, methylated pUC19 and unmethylated lambda phage DNA are added to genomic DNA. However, these control DNA are used in smaller amounts (0.0005% and 0.01%, respectively, both equivalent to less than 108 copies) that can be completely converted by bisulfite and thus, not be appropriate controls for the conversion of repeated targets [2,3]. In addition, the efficiency of non-CpG cytosine bisulfite conversions, used as built-in controls to verify bisulfite conversion in pyrosequencing can be hindered by sequence complexity, GC content, secondary structure elements and even a given cytosine in a particular sequence [4, ref. 5]. Based on our experiences, non-CpG cytosines located in short C stretches or right in front of CpGs are more difficult convert by bisulfite. We have adjusted our Discussion section to include this issue in the revised manuscript (line 478, page 19).

Minor:

Page 2, line 44. Reference "221" should be replaced by "1"

Page 3, line 70. Reference is lost

Page 9, line 223-226. Two first sentences of the Result section seem to be similar to each other and should be re-written

Page 13, line 335. Change 'S2A Fig.' to 'Fig. S2A'

We are grateful to the Reviewer for your comment. We have addressed the errors you noted, corrected the in-text citation, revised the first two sentences of the Results section (line 236, page 10) that were found to be similar. Additionally, we have adopted the recommended format for citing supporting information of “S Fig” instead of “Fig. S” as advised by PLoS ONE.

References

1. Lan VTT, Trang VL, Ngan NT, Son HV, Toan NL. An Internal Control for Evaluating Bisulfite Conversion in the Analysis of Short Stature Homeobox 2 Methylation in Lung Cancer. APJCP, 2019; 20(8), 2435-2443 Doi: 10.31557/APJCP.2019.20.8.2435

2. Morrison J, Koeman JM, Johnson BK, Foy KK, Beddows I, Zhou W, et al. Evaluation of whole-genome DNA methylation sequencing library preparation protocols. Epigenetics Chromatin. 2021; 14:28. doi: 10.1186/s13072-021-00401-y

3. Suzuki M, Liao W, Wos F, Johnston AD, DeGrazia J, Ishii J, et al. Whole-genome bisulfite sequencing with improved accuracy and cost. Genome Res. 2018;28(9):1364–1371. doi: 10.1101/gr.232587.117

4. Delaney C, Garg SK, Yung R. Analysis of DNA Methylation by Pyrosequencing. Methods Mol Biol. 2015;1343: 249–264. doi: 10.1007/978-1-4939-2963-4_19

Attachment

Submitted filename: Response to the Reviewer-Tran et al-Resubmitted PLoS ONE.docx

pone.0316394.s009.docx (88.4KB, docx)

Decision Letter 1

Osman El-Maarri

26 Nov 2024

PONE-D-24-37696R1An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancersPLOS ONE

Dear Dr. Vo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 10 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Osman El-Maarri, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2024 Dec 30;19(12):e0316394. doi: 10.1371/journal.pone.0316394.r004

Author response to Decision Letter 1

27 Nov 2024

Dear Members of the Editorial Board,

We sincerely appreciate the guidance from the Editors and the comments from the Reviewers throughout the review process to improve our manuscript titled “An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers” by Tran et al., submitted to PLoS ONE under the reference ID: PONE-D-24-37696R1.

As per the journal requirements kindly provided by the Editor, we have now revised the manuscript to address these points. Modifications have been tracked in the revised manuscript and are detailed point by point in the following section.

To better adhere to the journal requirements, we have:

+ Ran our figures through the PACE tool for renaming and reformatting to meet technical requirements

+ Confirmed NO retracted paper was cited in our manuscript.

+ Outlined the specifics of the corrections for the five papers that have undergone author correction cited in our manuscript and the final state of these references in the revised manuscript.

We are truly grateful for your time and efforts.

Best regards,

Attachment

Submitted filename: Response to PLoS ONE Editorial Board-Tran et al.docx

pone.0316394.s010.docx (28.9KB, docx)

Decision Letter 2

Osman El-Maarri

10 Dec 2024

An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers

PONE-D-24-37696R2

Dear Dr. Vo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Osman El-Maarri, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Osman El-Maarri

17 Dec 2024

PONE-D-24-37696R2

PLOS ONE

Dear Dr. Vo,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Priv.-Doz. Dr. Osman El-Maarri

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Primer sets and quantitative real-time PCR conditions for quantification of copy number and measurement of methylation level of LINE-1 and Alu.

    The methylation-dependent-specific PCR (MSP) primers (Me-) are designed from the consensus sequences of LINE-1 and Alu (S1 Fig). All non-CpG cytosines were replaced by ‘t” in the forward primers and by “a” in the reverse ones.

    (PDF)

    pone.0316394.s001.pdf (123.3KB, pdf)
    S2 Table

    Association of clinicopathological characteristics of cancer patients with LINE-1 (A) and Alu (B) methylation status in tissues of breast cancer, colon cancer and lung cancer.

    (PDF)

    pone.0316394.s002.pdf (198KB, pdf)
    S3 Table

    Association of clinicopathological characteristics of lung cancer patients with LINE-1 (A) and Alu (B) methylation status in cfDNA.

    (PDF)

    pone.0316394.s003.pdf (159.8KB, pdf)
    S1 Fig. Identification of LINE-1 and Alu consensus sequences followed by analyses on repeat masker [48] and ClustalW.

    (A-C) Alignment of the 5’ end region of L1 elements. The alignments include the old L1PA consensus sequence (A), the young L1Hs consensus representative to L1-Ta-0 (B) and L1-Ta-1 (C). The positions of the primers used in this study are shown with arrows, indicating the primers have been well designed to target all L1Hs elements including the L1 consensus sequence (accession no. X58075). (D-F) Alignment of the Alu sequences of young (AluY), intermediate (AluS) and old (Alu J) individual Alu repeats. Based on these Alu consensus sequences, the primer sets specific to methylated Alu sequences were designed. The positions of the primers used in this study are shown with arrows.

    (PDF)

    pone.0316394.s004.pdf (594.3KB, pdf)
    S2 Fig. Detection of the native LINE-1 sequences after bisulfite conversion.

    (A) The PCR product was successfully amplified with the primers specific to the native LINE-1 from bisulfite-treated DNA with 5ng, 50ng, and 500 ng, on DNA samples of breast (1), colon (2) and lung tumour (3) tissues. However, no native LINE-1 product was detected when the DNA input was 0.5 ng. (—): Negative control without DNA template. (B). Direct sequencing of PCR products amplified from bisulfite-treated DNA with an input amount of 0.5 ng using the MIP primers and an input amount of 50 ng using the primers specific to the native LINE-1 sequences. Almost non-CpG cytosines remained in DNA input of 50 ng. Rare conversions of non-CpG cytosines were underlined.

    (PDF)

    pone.0316394.s005.pdf (41.2KB, pdf)
    S3 Fig. Detection of the native Alu sequences after bisulfite conversion.

    (A). The PCR product was successfully amplified with the MSP primers specific to the methylated Alu sequences from bisulfite-treated DNA with different DNA quantities of 0.5 ng and 50 ng on DNA samples of breast (1) and colon (2) tumour tissues. (+): Recombinant plasmid containing the methylated Alu sequences used as template. (B). The PCR product was successfully amplified with the primers specific to the native Alu sequences from bisulfite-treated DNA of 50 ng input. However, no native Alu product was detected when the DNA input was 0.5 ng. PC: Positive control with DNA extracted from a blood sample as template. NTC: Negative control without DNA template. (C). Digestion of the PCR products from (B) with the HpaII restriction enzyme, recognizing one CCGG site in the Alu sequences, indicated that some native Alu sequences remained after bisulfite conversion of a DNA input of 50 ng.

    (PDF)

    pone.0316394.s006.pdf (41.1KB, pdf)
    S4 Fig

    LINE-1 (A) and Alu (B) methylation levels in cfDNA do not correlate with ageing in lung cancer patients. Methylation assessments were performed on one microlitre of bisulfite-converted cfDNA. The Spearman’s rank correlation test (A, B) was used in statistical analysis.

    (PDF)

    pone.0316394.s007.pdf (84.7KB, pdf)
    S5 Fig. Correlation between LINE-1 and Alu fragmentation sizes with their methylation level in cfDNA from healthy individuals (cfNC) and lung cancer patients (cfLC).

    No relationship was observed between the copy numbers of short LINE-1 (A) and short Alu (B) with their methylation level in both cfNC and cfLC. A negative correlation was detected between the long Alu copy number and Alu methylation in cfNC but not in cfLC (C). Alu Index negatively correlated with Alu methylation in both cfNC and cfLC (D). Correlations were assessed using Spearman’s rank correlation test.

    (PDF)

    pone.0316394.s008.pdf (195.5KB, pdf)
    Attachment

    Submitted filename: Response to the Reviewer-Tran et al-Resubmitted PLoS ONE.docx

    pone.0316394.s009.docx (88.4KB, docx)
    Attachment

    Submitted filename: Response to PLoS ONE Editorial Board-Tran et al.docx

    pone.0316394.s010.docx (28.9KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.

    Articles from PLOS ONE are provided here courtesy of PLOS

    RESOURCES