Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

Julia González-Rincón; José A Garcia-Vela; Sagrario Gómez; Belén Fernández-Cuevas; Sara Nova-Gurumeta; Nuria Pérez-Sanz; Miguel Alcoceba; Marcos González; Eduardo Anguita; Javier López-Jiménez; Eva González-Barca; Lucrecia Yáñez; Ernesto Pérez-Persona; Javier de la Serna; Miguel Fernández-Zarzoso; Guillermo Deben; Francisco J Peñalver; María C Fernández; Jaime Pérez de Oteyza; M Ángeles Andreu; M Ángeles Ruíz-Guinaldo; Raquel Paz-Arias; M Dolores García-Malo; Valle Recasens; Rosa Collado; Raúl Córdoba; Belén Navarro-Matilla; Margarita Sánchez-Beato; José A García-Marco

doi:10.1371/journal.pone.0257353

. 2021 Sep 10;16(9):e0257353. doi: 10.1371/journal.pone.0257353

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

Julia González-Rincón ^1,², José A Garcia-Vela ³, Sagrario Gómez ¹, Belén Fernández-Cuevas ⁴, Sara Nova-Gurumeta ⁴, Nuria Pérez-Sanz ⁴, Miguel Alcoceba ^2,⁵, Marcos González ^2,⁵, Eduardo Anguita ⁶, Javier López-Jiménez ⁷, Eva González-Barca ⁸, Lucrecia Yáñez ⁹, Ernesto Pérez-Persona ¹⁰, Javier de la Serna ¹¹, Miguel Fernández-Zarzoso ¹², Guillermo Deben ¹³, Francisco J Peñalver ¹⁴, María C Fernández ¹⁵, Jaime Pérez de Oteyza ¹⁶, M Ángeles Andreu ¹⁷, M Ángeles Ruíz-Guinaldo ¹⁸, Raquel Paz-Arias ¹⁹, M Dolores García-Malo ²⁰, Valle Recasens ²¹, Rosa Collado ²², Raúl Córdoba ²³, Belén Navarro-Matilla ⁴, Margarita Sánchez-Beato ^1,^2,^‡,^*, José A García-Marco ^4,^‡,^*

Editor: Francesco Bertolini²⁴

PMCID: PMC8432772 PMID: 34506616

Abstract

Chronic Lymphocytic Leukemia (CLL) is the most prevalent leukemia in Western countries and is notable for its variable clinical course. This variability is partly reflected by the mutational status of IGHV genes. Many CLL samples have been studied in recent years by next-generation sequencing. These studies have identified recurrent somatic mutations in NOTCH1, SF3B1, ATM, TP53, BIRC3 and others genes that play roles in cell cycle, DNA repair, RNA metabolism and splicing. In this study, we have taken a deep-targeted massive sequencing approach to analyze the impact of mutations in the most frequently mutated genes in patients with CLL enrolled in the REM (rituximab en mantenimiento) clinical trial. The mutational status of our patients with CLL, except for the TP53 gene, does not seem to affect the good results obtained with maintenance therapy with rituximab after front-line FCR treatment.

Introduction

Chronic Lymphocytic Leukemia (CLL) is the most prevalent leukemia in Western countries and is notable for its variable clinical course. This variability is partly reflected by the mutational status of IGHV genes that defines two subgroups characterized by different clinical outcomes. IGHV-mutated status is associated with long-lasting stable disease and better prognosis, while the IGHV-unmutated genotype (U-IGHV) is associated with a more active and proliferative disease [1–3]. Many CLL samples have been studied in recent years by next-generation sequencing (NGS). These studies have identified recurrent somatic mutations in genes, such as NOTCH1, SF3B1, ATM, TP53, BIRC3, and others, which play roles in cell cycle, DNA repair, RNA metabolism and splicing, inflammation and NOTCH and WNT signaling pathways[4–6]. Some of them have been found to have prognostic and/or predictive significance. Mutations in TP53, ATM, SF3B1 and NOTCH1 are associated with a significantly shorter time to first treatment and/or overall survival (OS) [4, 7]. In general, patients with a more aggressive disease have higher mutation rates, and patients with shorter progression-free survival (PFS) harbor more mutations per megabase [7]. The standard treatment of choice as first-line therapy for young physically fit patients with CLL is the combination of chemoimmunotherapy (CIT) with fludarabine, cyclophosphamide and rituximab (FCR). Long-term results from three studies [8–10] have demonstrated a long-duration PFS and OS of nearly 12 years in the subset of patients with mutated IGHV and an absence of adverse genetic features (11q deletion [del(11)] or 17p deletion [del(17)]/TP53 mutation) after treatment with front-line FCR. However, the recent introduction of targeted oral agents, including BTK and BCL2 inhibitors (ibrutinib, acalabrutinib and venetoclax), alone or in combination with monoclonal antibodies (rituximab or obinutuzumab) have demonstrated considerable efficacy in the front-line treatment of patients with CLL with U-IGHV and high-risk cytogenetic biomarkers (del(11q) and del(17p)/TP53 mutation) [11–13]. However, we do not know the prognostic impact of new recurrent mutations in patients with CLL suitable for front-line immuno-chemotherapy. Indeed, undetectable measurable residual disease (MRD) at the end of treatment is currently the most powerful predictor of clinical outcome related to favorable PFS and prolonged OS in CLL [8, 14].

In this study, we have taken a deep-targeted massive sequencing approach to analyze the impact of mutations in the most frequently mutated genes in a prospectively selected group of patients with CLL with active progressive disease who require treatment. All patients were enrolled in the REM (Rituximab En Mantenimiento [Rituximab in Maintenance]) clinical trial, which consisted of rituximab maintenance for 36 months after achieving at least a partial clinical response to front-line FCR treatment [15].

Materials and methods

Patients and samples

Seventy-one peripheral blood samples from treatment-naïve patients with CLL with progressive active disease were included in the present study. The patients were enrolled in the REM clinical trial. REM is a multicenter, non-randomized, prospective phase II clinical trial evaluating the overall response and PFS in patients with CLL with active progressive disease after first-line treatment with FCR, followed by rituximab maintenance every two months for three years in responding patients [15]. Samples were collected at the time of enrollment before treatment. Patient characteristics are summarized in Table 1.

Table 1. Patients’ features.

	Category	REM trial
Gender	Male/Female	47/24
Age (years)	Median (range)	59.6 (37–71)
Binet stage	A	12
	B	43
	C	16
	0	5
Rai stage	I-II	47
	III-IV	19
Copy number	trisomy 12	10/71 (14.1%)
alterations	del(13q)/normal	37/71 (52.1%)
	del(17p)	3/71 (4.2%)
	del(11q)	20/71 (28.2%)
IGHV	Unmutated	44/67 (65.4%)
CD38	> 30% positive	36/69 (52,2%)
ZAP70	> 20% positive	39/66 (59%)
CD49d	> 20% positive	27/68 (39.7%)

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The research project was approved by the Ethics Committee of Hospital Universitario Puerta de Hierro-Majadahonda and conducted following the Declaration of Helsinki. All patients gave their written informed consent for blood collection and the processing of biological analyses included in the present study. The REM study was registered as a clinical trial with NCT#: 00545714 and EudraCT#: 2007-002733-36.

Samples were collected from peripheral blood mononuclear cells (PBMCs) using Ficoll (Rafer, Zaragoza, Spain). Tumor-cell purity was calculated based on the CD19/CD5 ratio, measured by FACS. It ranged from 75% to 98%. DNA was extracted with DNAzol Genomic DNA Isolation Reagent (Molecular Research Center, Cincinnati, OH, USA) following the manufacturer’s instructions. The quality and quantity of purified DNA were assessed by fluorimetry (Qubit, Invitrogen, Waltham, MA, USA) and gel electrophoresis.

Genetic characterization

Cytogenetic aberrations were analyzed by fluorescence in situ hybridization (FISH) with the Vysis CLL FISH Probe Kit, following the manufacturer’s recommendations for detecting deletions of TP53 (17p13.1), ATM (11q22.3), D13S319 (13q14.3), MYC rearrangements/amplification (8q24.12-q24.13) and gain of the D12Z3 sequence (trisomy 12) in peripheral blood specimens from patients with CLL. Cut-off values for a positive FISH result were 3% and 10% for gains and deletions, respectively.

Amplifications of the IGHV-diversity (D)-joining (J) segment were performed on genomic DNA using standard procedures and analyzed by Sanger sequencing according to ERIC recommendations [16]. IGHV sequences were considered mutated or unmutated using the conventional cut-off of 98% identity with the closest germline IGHV gene.

Flow cytometry and MRD analysis

Samples were stained and lysed using a direct immunofluorescence technique as previously described [15]. In summary, sequential bone marrow (BM) and peripheral blood (PB) samples were collected in tubes containing K3 EDTA as anticoagulant. BM samples were immediately diluted 1/1 (vol/vol) in phosphate-buffered saline (PBS). Whole BM and PB samples (approximately 2x10⁶ cells in 100 μL per test) were stained and lysed using a direct immunofluorescence technique, as previously described [15]. The antibody combinations tested were CD22/CD23/CD19/CD5, CD81/CD22/CD19/CD5, CD20/CD38/CD19/CD5, CD20/CD79b/CD19/CD5 and sIgKappa/sIgLambda/CD19/CD5. Cells were acquired in two consecutive steps in order to increase the sensitivity of the analysis. First, 20,000 events corresponding to all nucleated cells were acquired. In the second step, the acquisition was done through a "live gate" drawn on the SSC/CD19+ region in which B-lymphocytes are located. When no CLL cells were detected, to have a limit of detection of 0.01%, a minimum of 20 events was needed and 200,000 events were acquired. To ensure a lower limit of quantification of 0.01%, a minimum of 50 events were required. For ZAP70, CD38 and CD49d measurements see García-Marco et al. 2019 [15].

Targeted massive sequencing

To select genes to be analyzed, we browsed the COSMIC and ICGC databases and reviewed previously published data on CLL (library designed in 2013) [17–26]. Based on their recurrence and prognostic/predictive capacity described in the literature and in our results, the following recurrently mutated genes were selected: ATM, BIRC3, BRAF, CHD2, CSMD3, DDX3X, FBXW7, KLHL6, KRAS, LRP1B, MAPK1, MYD88, NFKBIE, NOTCH1, PLEKHG5, POT1, SAMHD1, SF3B1, SI, SMARCA2, TGM7, TP53, XPO1, MUC2, and ZMYM3. EGR2 (not included in the HaloPlex design) was analyzed independently (see below).

We used two methods for target enrichment and library preparation:

A HaloPlex Target Enrichment custom panel was designed using the web-based tool SureDesign (Agilent Technologies, Santa Clara, CA, USA) (earray.chem.agilent.com/suredesign/). The design covered all coding exons, and UTR regions of the 25 selected genes, including ten flanking bases at the 3`and 5`ends (Human assembly GRCh37/hg19). The final design included 5734 amplicons covering 344,420 bases, with 99.15% of target bases covered by at least one probe. The target regions were captured using a HaloPlex Target Enrichment kit, following the manufacturer’s instructions (HaloPlex Target Enrichment System Protocol for Illumina, San Diego, CA, USA). Briefly, 200 ng of genomic DNA was digested with the specific cocktail of restriction enzymes provided in the kit. Digested DNA was then hybridized to a probe for target enrichment, indexed and captured. Each DNA was then amplified by PCR at Tm = 60°C, for 21 cycles, using a Herculase II Fusion Enzyme kit (Agilent Technologies, Santa Clara, CA, USA). Next, amplified target libraries were purified using an Agencourt AMPure XP Kit (Beckman Coulter Genomics, Brea, CA, USA), following the manufacturer’s guidelines, and quantified combining Bioanalyzer and Qubit data. Pools were made by combining 5–7 indexed libraries up to a final concentration of 10 nM. Paired-end sequencing was performed in a MiSeq instrument (Illumina) at IMEGEN (Parc Científic de la Universitat de València, Paterna, Valencia, Spain). The mean read depth within the regions of interest was approximately 1181 reads/base (QC data in S1 Table in S1 File)).
For hotspots in EGR2 (a gene not included in the HaloPlex panel), ultra-deep sequencing of specific PCR-based amplification protocol was adopted and sequenced in MiSeq sequencer (Illumina, San Diego, CA, USA). Amplicons of approximately 100 bp were designed with a primer3-based tool (http://bioinfo.ut.ee/primer3-0.4.0/) for the target hotspots in the EGR2 (S2 Table in S1 File). Independent PCR amplifications were conducted with TaqGold Polymerase (Life Technologies, Carlsbad, CA, USA). Libraries were constructed with the NEBNext^® DNA Library Prep Reagent Set for Illumina (New England Biolabs, Ipswich, MA, USA) following the manufacturer’s instructions [27]. A library pool was constructed combining all the indexed libraries. Paired-end sequencing was performed in a MiSeq instrument. 100% and 66.67% of the analyzable target regions were covered by at least 5,000 and 10,000 reads, respectively (QC data in S1 Table in S1 File).

Data analysis and variant calling

Data were analyzed using two pipelines: i) MiSeq Reporter alignment, which was performed using the Burrows-Wheeler Aligner (BWA). Variants were identified and annotated with the Genome Analysis Toolkit (GATK); and ii) analysis with SureCall 2.1.13 (Agilent Technologies, Santa Clara, CA, USA) software. The variant lists obtained were analyzed by filtering in Excel and visualizing with the Integrative Genome Viewer (IGV) tool [28].

We applied the filters to identify putative somatic mutations, filtering out those not reaching 100x and those of bad quality (based on the QC Score obtained from MiSeq Reporter). The percentage of reads supporting the mutation from the total number of reads at a given position was taken as 5% in the tumor DNA with a minimum depth of around 200. Only those variants with an allele frequency greater than 20% were considered for validation. Biological impact predictions for detected variants were obtained from the Ensembl Variant Effect Predictor (VEP: http://www.ensembl.org/tools.html), SIFT and PolyPhen predictions for the effect of the mutations on protein function. Variants present in germline DNA or identified as SNPs were excluded from the candidate list.

Matched non-tumoral samples were not available for most patients. The GATK annotates the SNPs available at dbSNP 132 (hg19) and 1000 Genomes Project. Variants present in germline DNA or identified as SNPs were excluded from the candidate list. SNVs with variant allele frequency ≥ 5% and not listed as a single nucleotide polymorphism, or listed but with a MAF < 0.01% (The Exome Aggregation Consortium, 1000 Genomes Project of the International Genome Sample Resource (IGSR), Single Nucleotide Polymorphism Database (dbSNP) v132 of the National Center for Biotechnology Information (NCBI)) were considered. Missense, frameshift, and nonsense mutations were selected.

Data have been deposited in the Sequence Read Archive (SRA) database (http://www.ncbi.nlm.nih.gov/sra) (Accession number: PRJNA322600).

Validation of mutations by Sanger sequencing

A group of selected variants was chosen for validation by Sanger sequencing. According to the following criteria, mutations to be validated were chosen: VAF greater than 20%, not previously described as recurrent, and with sufficient available DNA. Some known variants were also validated. The validation primers (available upon request) were designed with the Primer3 web tool and sequenced with the Big Dye terminator v3.1 Cycle Sequencing kit and an ABI3730 DNA Analyzer (Life Technologies, Carlsbad, CA, USA).

Statistical analysis

The significance of bivariate relationships between factors was assessed using Pearson’s chi-squared or Fisher’s exact test; values of P < 0.05 were considered significant. Endpoints were PFS, OS and MRD status. OS was calculated from the date of sampling to the date of death or last follow-up, whichever came first. Time to progression was calculated from the date of first treatment to the date of clinical progression or death due to progression. Logistic regression was used to evaluate the association of genetic alterations with MRD. Univariate and multivariate Cox proportional hazard (PH) regression models were used to test the associations of mutations with outcomes. A manual backward selection strategy was used to obtain the final model, with the criterion for eliminating variables being a significance level of P > 0.05. The PH assumption was tested using Schoenfeld residuals [29]. Hazard ratios, with 95% confidence intervals, were estimated for each parameter. All calculations were performed using IBM SPSS Statistics 19 and STATA v14.1.

Results and discussion

Gene mutations and correlation with patients’ cytogenetic and phenotypic features

Seventy-one peripheral blood samples from treatment-naïve patients with CLL enrolled in the REM clinical trial [15] with symptomatic, progressive disease were included in our analysis (Table 1). Samples were collected at the time of enrollment in the REM clinical trial (up to 28 days before the first cycle of FCR).

We analyzed the impact of mutations in 26 genes by targeted deep-sequencing as described in the "Methods" section. After sequencing, the median read depth within the regions of interest was 1485 reads/base. A total of 100 mutations were identified in 49/71 (69.0%) patients. Eighteen (25.3%) patients harbored one mutation, whereas 31 (43.6%) had multiple mutations. We did not detect any mutations in 22 patients (31%) (Fig 1 and S3 Table in S1 File).

Fig 1 — Rows correspond to sequenced genes and genetic features; columns represent individual patients with CLL. (Figure done with oncoprint tool in cBioPortal). Colour code: IGHV: red, unmutated IGHV, blue: mutated IGHV, orange: no data. Genetic alterations: green, missense mutation; black, truncating mutation; light blue, deletion; red, gain.

The most recurrently mutated genes were SF3B1 (14 mutations in 14 cases; 19.7%) with the recurrent mutation Lys700Glu found in four patients; NOTCH1 (13 mutations in 12 cases; 16.9% of patients), 8 of them were the previously published indel Pro2515Argfs*4 located in the C-terminal PEST domain of NOTCH1 (Fig 1 and S2 Table in S1 File); and ATM (14 mutations in 9 cases; 12.6%). Other frequently mutated genes were XPO1 (eight cases; 11.2%), TP53 (six cases; 8.4%), CSMD3 (five cases; 7.0%), EGR2 and POT1 (in four cases each one; 5.6%) and LRP1B, NFKBIE, FBXW7, PLEKHG5, SAMHD1, and SI (three cases; 4.2%); two out of 3 NFKBIE mutations correspond to the previously published indel Tyr245Ile255*16.

Statistical analysis of the presence of gene mutations with CLL phenotypic or cytogenetic characteristics revealed some significant associations (S4 Table in S1 File). The presence of ≥ 2 gene mutations was associated with aggressive CLL features such as U-IGHV (P = 0.017), ZAP70 (P = 0.001) and CD49d expression (P = 0.005). As expected, patients with mutations in TP53 had a concurrent del(17p) (P < 0.001). Five of the six TP53-mutated samples were found in elderly patients (> 65 years; P = 0.001). Eighty-three percent of NOTCH1-mutated samples (10/12) showed concurrent mutations in other genes, and NOTCH1 mutations were associated with the expression of ZAP70 (P = 0.021) CD49d (P = 0.001) and were more frequently found in IGHV-U cases (P = 0.006). It was hypothesized that mutations in NOTCH1 regulate CD49d expression through the NFkB pathway involvement, favoring drug resistance [30]. All XPO1-mutated samples were found in the U-IGHV group (P = 0.044). Finally, mutations in EGR2 were associated with del(11q) (P = 0.065), and all of them expressed CD38 in more than 30% of CLL cells (although not statistically significant, P = 0.115). By contrast, mutant LRP1B was only detected in samples with a normal/del(13q) karyotype (P = 0.048). Therefore, mutations in NOTCH1 and XPO1 were enriched among cases with high-risk disease.

Association with clinical follow-up and response to therapy

Regarding the prognostic significance of gene mutations in patients with CLL with an active progressive disease requiring treatment, we analyzed the clinical significance of these genetic alterations in terms of clinical response, PFS, OS and analyzing their association with measurable MRD (data available for 61 patients) at the end of treatment. Statistical analyses took all the mutations with VAF > 5% into account since we did not find any significant differences between clonal and subclonal mutations. We analyzed del(11q) together with ATM mutations (ATM/del(11q)) and del(17p) with TP53 mutations (TP53/del(17p)).

Achieving undetectable MRD remission is the most important predictor of PFS in patients treated with CIT, independent of clinical remission status and patients’ pretreatment characteristics [8, 14], and it is currently accepted by the European Medicines Agency (EMA) as a surrogate marker for PFS. In our series, undetectable MRD was significantly associated with prolonged PFS (HR: 6.049, P < 0.001) and so for OS (HR: 3.907, P = 0.044) (S1 Fig in S2 File), as it is also shown for the whole REM series in the previous publication by García-Marco et al. [15], and in accordance with the criteria established in previous studies [14]. Therefore, we analyzed the correlation between gene mutations and MRD (in 61 patients with MRD data) by logistic regression analysis including cytogenetic abnormalities, IGHV status, number of mutations (0–1 mut vs. ≥ 2 mut) and genes mutated in at least 3 samples (5% of cases): SF3B1, NOTCH1, XPO1, CSMD3, EGR2, POT1, FBXW7, NFKBIE, and PLEKHG5. We analyzed del(11q) together with ATM mutations (ATM/del(11q)) and del(17p) with TP53 mutations (TP53/del(17p)). Our results showed that additionally to IGHV mutational status (OR: 10,35, P = 0.004), NOTCH1 mutations (OR: 4,35, P = 0.046), were associated with detectable MDR and, therefore, could be used as predictor of MRD detection together with U-IGHV status.

Finally, we performed univariate Cox PH regressions with each of the following clinical variables: IGHV status, gender, age (> vs. ≤ 65 years), Binet stage (low vs. high risk), cytogenetic alterations and with genes mutated in at least 5% of the patients: ATM/del(11q) (24 cases out of 71, 34%), SF3B1 (14 cases, 20%), NOTCH1 (12 cases, 17%), XPO1 (8 cases, 11%), TP53/del(17p) (6 cases, 8.5%), CSMD3 (5 cases, 7%), EGR2 (4 cases, 5.5%), and POT1 (4 cases, 5.5%). In the multivariate analyses of the variables that were significant in the univariate analyses (Table 2A and S2A Fig in S2 File), we found that TP53/del(17p) (HR: 12.843, P < 0.001) and EGR2 mutations (HR: 8.256; P = 0.002) increased the risk of progression after treatment. These findings suggest that EGR2 mutations could be an adverse prognostic biomarker in patients with CLL prospectively treated with FCR followed by R maintenance and could be used as a biomarker to identify patients with poorer outcomes after standard CIT. These results are similar to those reported from the UK LRFCLL4 trial and CLL Research Consortium (CRC) [31], in which alterations in both genes were significantly associated with PFS. The CLL8 study [32] showed that TP53 and SF3B1 were the strongest adverse prognostic markers in patients with CLL receiving current-standard first-line therapy; however, EGR2 was neither associated with PFS nor OS [33].

Table 2. Univariate and multivariate analysis.

A. Progression-free survival B. Overall Survival.

A
	Univariate				Multivariate
	HR	P	95.0% CI		HR	P	95.0% CI
	HR	P	lower	upper	HR	P	lower	upper
TP53del17p	10,234	<0.001	3,936	26,609	12,843	<0.001	4,724	34,920
EGR2	5,052	0,014	1,394	18,310	8,256	0,002	2,114	32,238
IGHV	3,572	0,019	1,237	10,310
Age < 65y >	3,040	0,005	1,404	6,584
Binet_2	2,719	0,012	1,245	5,937
B
	Univariate				Multivariate
	HR	P	95.0% CI		HR	P	95.0% CI
	HR	P	lower	upper	HR	P	lower	upper
TP53del17p	10,465	<0.001	3,182	34,420	10,739	<0.001	3,192	36,136
Binet_2	4,094	0,009	1,426	11,749	4,164	0,009	1,437	12,242
Age < 65y >	4,054	0,010	1,396	11,726

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For OS, additionally to Binet stage only TP53mut/del(17p) was found to be an adverse prognostic marker (Table 2B and S2B Fig in S2 File), and also reported by others studies [4, 31, 32].

In conclusion, we have found that the mutation frequencies of several genes by next-generation sequencing, mainly SF3B1, NOTCH1, and ATM1, are similar to those reported in series of patients with CLL requiring therapy.

Also, our results show that the mutational status of patients with CLL in cases that reach an undetectable measurable residual disease at 10⁻⁴ level does not seem to affect the PFS status compared to cases with absence or few gene mutations after front-line FCR treatment followed by limited Rituximab maintenance [15]. Mutations of most recurrent driver genes in CLL, except for the TP53 gene, do not seem to affect the sustained clinical response obtained with front-line FCR treatment followed by Rituximab maintenance for three years in our cohort of patients.

Supporting information

S1 File. Supporting tables.

This file contains S1 Table: Coverage and sequencing quality data for HaloPlex and hotspots. S2 Table: Hotspot custom primers for EGR2. S3 Table: Somatic variants from targeted resequencing. S4 Table: Clinical characteristics, cytogenetic abnormalities and molecular markers REM series of 71 patients).

(XLSX)

Click here for additional data file.^{(48.3KB, xlsx)}

S2 File. Supporting figures.

This PDF file contains S1 Fig: MRD association with progression-free survival (A) and overall survival (B). S2 Fig: Progression-free survival (PFS) and overall survival (OS).

(PDF)

Click here for additional data file.^{(402.6KB, pdf)}

Acknowledgments

We are indebted to the patients who contributed to this study. We thank E. Ramil, A. Royuela and I. Fernández Miranda, from the Instituto de Investigación Sanitaria Puerta de Hierro-Segovia de Arana, and J.L. Bueno from Hospital Universitario Puerta de Hierro-Majadahonda, for their invaluable help with the sequencing (ER) and statistical analysis (AR, IFM and JLB).

Data Availability

Data have been deposited in the Sequence Read Archive (SRA) database (http://www.ncbi.nlm.nih.gov/sra) (Accession number: PRJNA322600).

Funding Statement

This work was supported by the Instituto de Salud Carlos III (ISCII) of the Spanish Ministry of Economy and Competence (MINECO) ISCIII-MINECO AES-FEDER (Plan Estatal de I+D+I 2008-2011 and 2013-2016 https://www.isciii.es/QueHacemos/Financiacion/Paginas/Accion-Estrategica-en-Salud.aspx) (MSB: RD12/0036/0060, PI14/00221, PIE14/0064, PI17/00272; MSB and JGR: CIBERONC CB16/12/00291, MA and MG: CB16/12/00233), Comunidad Autónoma de Madrid (https://www.comunidad.madrid/servicios/educacion/convocatorias-ayudas-investigacion) (MSB: B2017/BMD3778), MSB: Fundación de la Asociación Española Contra el Cáncer (https://www.aecc.es/es/investigacion/fundacion-cientifica-aecc) and JAGM: Roche Farma, S.A., Madrid, Spain. JGR was a recipient of an iPFIS predoctoral fellowship (IFI14/00003) and MSB held a Miguel Servet II contract (CPII16/00024), supported by ISCIII-MINECO AES-FEDER (Plan Estatal I+D+I 2013-2016) and the Fundación de Investigación Biomédica Puerta de Hierro. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0257353.r001

Decision Letter 0

Francesco Bertolini

8 Jun 2021

PONE-D-21-13505

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

PLOS ONE

Dear Dr. Sanchez-Beato,

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Reviewer #1: The authors sequenced the coding exons and UTR regions of over 20 candidate genes of chronic lymphocytic leukemia (CLL) in 71 CLL patients. They evaluated association between the mutations identified and cytogenetic, phenotypic features and survival rates of the patients.

I have some questions about the data analysis:

Age is a strong player of survival and a dichotomized age variable as a covariate may not be enough to account for age effects. What if age is used as the time scale in Cox regression?

Many of these patients have cytogenetic abnormalities. It is important to evaluate effects of mutations while accounting for the cytogenetic abnormalities, i.e., cytogenetic abnormalities should be included as covariate in the regression analysis.

Lines 302-304: “MRD negativity was significantly associated with prolonged PFS (P Person < 0.001) and nearly so for OS (P Fisher =0.065)” Are the data shown in the result? Why using a Chi-square test in the analysis instead of a survival model?

Logistic regression should be used to evaluate the association with MRD status so that contributions from multiple mutations can be evaluated jointly and covariates such as cytogenetic abnormalities can be adjusted for.

For the Cox regression is the number of mutations per individuals associated with survival? What about the type of genetic alterations (missense, truncating, deletion) of the mutations?

Table 3, was age not significant in the multivariate analysis? As mentioned previously cytogenetic abnormalities needs to be adjusted for.

Line 250, 49/71 seems to be a typo. Shouldn’t the number of patients with at least one mutation be 54 (23+31)?

Reviewer #2: The manuscript by González-Rincón and colleagues reports the results of a deep targeted sequencing approach of the most frequently mutated genes carried out in patients with CLL enrolled in the REM clinical trial where they have been treated with FCR followed by 36 months of rituximab maintenance (bimonthly). They conclude that only TP53 mutations affect the outcome in the study.

I have few suggestions:

- On lines 247-252, where describing the occurrence of mutations it is reported that 69% of patients harbored at least one mutation, while only 23.9% did not. The numbers do not add up to 100. Indeed, it is also reported that 32.4% had one mutations and 43.7% had more than one, for a total of 76.1% which seems more correct. Please double check the numbers or the wording.

- It is interesting to note that SF3B1 is the most frequently mutated gene and much higher than expected in contrast to many other series. How reliable was the VAF in the call for mutations? Any explanation?

- It is not clear which conclusions the authors want to draw. As they state in the abstract "The mutational status of our CLL patients, except for the TP53 gene, does not seem to affect the good results obtained with maintenance therapy with rituximab after front line FCR treatment" though in the last sentence of the paper, they mention a possible use of these analyses to decide between "a continuous versus a time-limited therapy". this does not seem to be a conclusion from this study as they do confirm that the analysis for TP53 status is enough to predict poor response to FCR (despite maintenance). Please revise the wording and reconcile the conclusions.

Minor comments

- Please replace CLL patients with "patients with CLL" throughout the whole text

- Please do not capitalize "del(17p) or del(11q)" not even at the beginning of the sentence or in a table (see e.g. table 1)

- Please on line 135, replace the sentence "....cut-off of a 2% mismatch from germline IGHV sequences." with " cut-off of 98% identity with the closest germline IGHV gene"

- Typically for unmutated IGHV, UM (or U) IGHV is used and not IGHV-U. Consider to align with previous works.

- On line 292, as the authors are planning to explore the predictive value of these gene mutations, the authors might simplify the wording by replacing the sentence "we analyzed the clinical significance of these genetic alterations by studying their effect on the therapeutic response" with "we analyzed the predictive value of these genetic alterations in terms of clinical response, PFS, etc".

- from line 299 onward, please replace "MRD negative/negativity" with "undetectable MRD" or "detectable MRD" instead of "positivity".

Reviewer #3: The manuscript reports on an ancillary biological study of a phase 2 trial where patients with treatment naive CLL received FCR, followed by rituximab maintenance every two months for three years. The study includes 71 patients, whose pre-treatment leukemia samples were profiled for CLL biomarkers including IGHV and targeted gene mutations, and cytogenetics. The study cohort is also provided by longitudinal MRD data. The results further validate previous findings that TP53 abnormalities are the sole lesions associated with outcome. Accordingly, in its current form, the manuscript does not add any further novel finding compared to what already known in the field of prognostic biomarkers of CLL treated with chemoimmunotherapy. In addition, from a conceptual standpoint, FCR has been largely abandoned thanks to the transition to pathway inhibitor therapies in CLL. Thus the results are of eventual historical interest, but do not have actual implications. Finally maintenance with rituximab is not a standard approach in CLL and the study does not help in signaling those patients whose molecular profile may benefit or not from maintenance. Novelty of the manuscript can be substantially improved in the authors can validate or further develop upon AI methods, that leveraging on big data, frameworks for the integration of patient biomarker data over time to improve prognostic accuracy and personalized therapy selection (PMID: 31280963).

**********

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PLoS One. 2021 Sep 10;16(9):e0257353. doi: 10.1371/journal.pone.0257353.r002

Author response to Decision Letter 0

7 Jul 2021

Reviewer #1:

The authors sequenced the coding exons and UTR regions of over 20 candidate genes of chronic lymphocytic leukemia (CLL) in 71 CLL patients. They evaluated association between the mutations identified and cytogenetic, phenotypic features and survival rates of the patients.

I have some questions about the data analysis:

Age is a strong player of survival and a dichotomized age variable as a covariate may not be enough to account for age effects. What if age is used as the time scale in Cox regression?

R: We considered including the variable “Age” as a continuous variable in the Cox regression analysis since we agree with the reviewer that it is more accurate. However, we eventually decided to dichotomize this variable to use it in the multivariate analysis with other dichotomic variables and ease the comparison with other studies, where “Age” is used as a categoric variable. The threshold at 65 years is the usual standard in most multivariate analysis published in recent years. However, we did the analysis using age as a continuous variable but did not reach significance (P = 0.072).

R: Cytogenetic abnormalities were included in the analyses, but none were significant in the regression analysis except when TP53 mutations and del17q were joined as a single variable.

R: Thank you for the suggestion. We have done the survival models (Cox and Kaplan-Meier) and included them in the manuscript (Page 14, line 306, and Figure S1).

R: Thank you for the suggestion. We have used logistic regression and included the results in page 14, line 310.

For the Cox regression is the number of mutations per individuals associated with survival? What about the type of genetic alterations (missense, truncating, deletion) of the mutations?

R: Yes, we considered the number of mutations in the survival analysis, but there was no association with OS or PFS. Due to the low number of samples, we considered that we would not obtain relevant results by splitting the type of mutations. The appropriate analysis would be done for each gene independently, and our series does not allow us to do this study properly.

Table 3, was age not significant in the multivariate analysis? As mentioned previously cytogenetic abnormalities needs to be adjusted for.

R: Age was significant in the univariate analysis, as indicated in now table 2, but loses significance in the multivariate analyses. None of the cytogenetic alterations was significant, except for TP53/del17q, as shown in the table.

Line 250, 49/71 seems to be a typo. Shouldn’t the number of patients with at least one mutation be 54 (23+31)?

R: Thank you for the observation. We have corrected this and other errors.

Reviewer #2:

The manuscript by González-Rincón and colleagues reports the results of a deep targeted sequencing approach of the most frequently mutated genes carried out in patients with CLL enrolled in the REM clinical trial where they have been treated with FCR followed by 36 months of rituximab maintenance (bimonthly). They conclude that only TP53 mutations affect the outcome in the study.

I have few suggestions:

R: We apologize for these mistakes; the numbers have been revised and corrected.

R: According to our experience, data in previous publications, and sequencing depth, we think that VAF is reliable, as we described in the Methods section (page 9, line 200).

One possible explanation might be the characteristics of the series, composed by progressive cases in need of treatment compared to others that considered any kind of patient (see page 16, line 347).

- It is not clear which conclusions the authors want to draw. As they state in the abstract “The mutational status of our CLL patients, except for the TP53 gene, does not seem to affect the good results obtained with maintenance therapy with rituximab after front line FCR treatment” though in the last sentence of the paper, they mention a possible use of these analyses to decide between “a continuous versus a time-limited therapy”. This does not seem to be a conclusion from this study as they do confirm that the analysis for TP53 status is enough to predict poor response to FCR (despite maintenance). Please revise the wording and reconcile the conclusions.

R: Thank you for the suggestion. We have changed the last sentence of the discussion. We hope it would help to clarify our conclusion.

“Mutations of most recurrent driver genes in CLL, except for the TP53 gene, do not seem to affect the sustained clinical response obtained with front-line FCR treatment followed by Rituximab maintenance for three years in our cohort of patients”.

Minor comments

- Please replace CLL patients with “patients with CLL” throughout the whole text

- Please do not capitalize “del(17p) or del(11q)” not even at the beginning of the sentence or in a table (see e.g. table 1)

- Please on line 135, replace the sentence “....cut-off of a 2% mismatch from germline IGHV sequences.” with “cut-off of 98% identity with the closest germline IGHV gene”

- Typically for unmutated IGHV, UM (or U) IGHV is used and not IGHV-U. Consider to align with previous works.

- On line 292, as the authors are planning to explore the predictive value of these gene mutations, the authors might simplify the wording by replacing the sentence “we analyzed the clinical significance of these genetic alterations by studying their effect on the therapeutic response” with “we analyzed the predictive value of these genetic alterations in terms of clinical response, PFS, etc”.

- from line 299 onward, please replace “MRD negative/negativity” with “undetectable MRD” or “detectable MRD” instead of “positivity”.

R: Thank you for the suggestions. We have modified them in this new version and corrected this and other mistakes.

Reviewer #3:

The manuscript reports on an ancillary biological study of a phase 2 trial where patients with treatment naive CLL received FCR, followed by rituximab maintenance every two months for three years. The study includes 71 patients, whose pre-treatment leukemia samples were profiled for CLL biomarkers including IGHV and targeted gene mutations, and cytogenetics. The study cohort is also provided by longitudinal MRD data. The results further validate previous findings that TP53 abnormalities are the sole lesions associated with outcome. Accordingly, in its current form, the manuscript does not add any further novel finding compared to what already known in the field of prognostic biomarkers of CLL treated with chemoimmunotherapy. In addition, from a conceptual standpoint, FCR has been largely abandoned thanks to the transition to pathway inhibitor therapies in CLL. Thus the results are of eventual historical interest, but do not have actual implications. Finally maintenance with rituximab is not a standard approach in CLL and the study does not help in signaling those patients whose molecular profile may benefit or not from maintenance. Novelty of the manuscript can be substantially improved in the authors can validate or further develop upon AI methods, that leveraging on big data, frameworks for the integration of patient biomarker data over time to improve prognostic accuracy and personalized therapy selection (PMID: 31280963).

R: A weakness of this trial is that over the last few years, since its design, new drugs targeting aberrant signaling pathways and newer monoclonal antibodies became available, and the interest in CIT, such as FCR, has weakened. However, it is still accepted as front-line therapy by some clinical guidelines (German, Spanish-CLL, ESMO, etc.) in a subgroup of patients younger than 65 years without comorbidities and absence of cytogenetic abnormalities of worse prognosis (del11q, del17p, complex karyotypes or unmutated IGHV).

Unfortunately, REM clinical trial series has not enough data to analyze them using complex algorithms. Moreover, we only have one-point data (from treatment-naïve samples), not serial samples, precluding us from using analyses like those performed in the suggested paper that integrated risk assessments throughout patients’ disease evolution.

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PLoS One. doi: 10.1371/journal.pone.0257353.r003

Decision Letter 1

Francesco Bertolini

28 Jul 2021

PONE-D-21-13505R1

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

PLOS ONE

Dear Dr. Sanchez-Beato,

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PLOS ONE

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Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

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

Reviewer #1: Yes

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #3: Yes

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

Reviewer #1: (No Response)

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #1: I only have a minor comment, please specify what variables/covariates were included in the logistic regression.

Reviewer #3: The authors have addressed all the reviewer comments and the manuscript is improved in this current version. I have no further issues.

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Reviewer #1: No

Reviewer #3: No

PLoS One. 2021 Sep 10;16(9):e0257353. doi: 10.1371/journal.pone.0257353.r004

Author response to Decision Letter 1

5 Aug 2021

Reviewer 1: I only have a minor comment, please specify what variables/covariates were included in the logistic regression.

Thank you for drawing to our attention this ommision. We have included a sentence indicating the varibles included in the logistic regression analyis (Page 14, lines 312-316).

Attachment

Submitted filename: Rebuttal letter_PONE-D-21-13505R1.docx

Click here for additional data file.^{(413.2KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0257353.r005

Decision Letter 2

Francesco Bertolini

31 Aug 2021

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

PONE-D-21-13505R2

Dear Dr. Sanchez-Beato,

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.

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Kind regards,

Francesco Bertolini, MD, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

**********

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

Reviewer #1: (No Response)

**********

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

Reviewer #1: (No Response)

**********

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

Reviewer #1: (No Response)

**********

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

Reviewer #1: (No Response)

**********

6. Review Comments to the Author

Reviewer #1: (No Response)

**********

7. 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.

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Reviewer #1: No

PLoS One. doi: 10.1371/journal.pone.0257353.r006

Acceptance letter

Francesco Bertolini

3 Sep 2021

PONE-D-21-13505R2

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

Dear Dr. Sánchez-Beato:

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

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 plosone@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

Dr. Francesco Bertolini

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 File. Supporting tables.

(XLSX)

Click here for additional data file.^{(48.3KB, xlsx)}

S2 File. Supporting figures.

This PDF file contains S1 Fig: MRD association with progression-free survival (A) and overall survival (B). S2 Fig: Progression-free survival (PFS) and overall survival (OS).

(PDF)

Click here for additional data file.^{(402.6KB, pdf)}

Attachment

Submitted filename: Rebuttal letter PONE-D-21-13505.docx

Click here for additional data file.^{(422.3KB, docx)}

Attachment

Submitted filename: Rebuttal letter_PONE-D-21-13505R1.docx

Click here for additional data file.^{(413.2KB, docx)}

Data Availability Statement

Data have been deposited in the Sequence Read Archive (SRA) database (http://www.ncbi.nlm.nih.gov/sra) (Accession number: PRJNA322600).

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PERMALINK

Genomic mutation profile in progressive chronic lymphocytic leukemia patients prior to first-line chemoimmunotherapy with FCR and rituximab maintenance (REM)

Julia González-Rincón

José A Garcia-Vela

Sagrario Gómez

Belén Fernández-Cuevas

Sara Nova-Gurumeta

Nuria Pérez-Sanz

Miguel Alcoceba

Marcos González

Eduardo Anguita

Javier López-Jiménez

Eva González-Barca

Lucrecia Yáñez

Ernesto Pérez-Persona

Javier de la Serna

Miguel Fernández-Zarzoso

Guillermo Deben

Francisco J Peñalver

María C Fernández

Jaime Pérez de Oteyza

M Ángeles Andreu

M Ángeles Ruíz-Guinaldo

Raquel Paz-Arias

M Dolores García-Malo

Valle Recasens

Rosa Collado

Raúl Córdoba

Belén Navarro-Matilla

Margarita Sánchez-Beato

José A García-Marco

Roles

Abstract

Introduction

Materials and methods

Patients and samples

Table 1. Patients’ features.

Genetic characterization

Flow cytometry and MRD analysis

Targeted massive sequencing

Data analysis and variant calling

Validation of mutations by Sanger sequencing

Statistical analysis

Results and discussion

Gene mutations and correlation with patients’ cytogenetic and phenotypic features

Fig 1. Incidence and distribution of mutations in the 26 analyzed genes and genetic markers in the REM cohort.

Association with clinical follow-up and response to therapy

Table 2. Univariate and multivariate analysis.

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Francesco Bertolini

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Author response to Decision Letter 0

Decision Letter 1

Francesco Bertolini

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Author response to Decision Letter 1

Decision Letter 2

Francesco Bertolini

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Acceptance letter

Francesco Bertolini

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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