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. 2021 Oct 22;16(10):e0258797. doi: 10.1371/journal.pone.0258797

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in male patients with liver hepatocellular carcinoma

Jian Zhou 1,#, Yue Zhu 2,#, Songlin Ma 3,#, Yi Li 1, Kun Liu 4, Sihuan Xu 2, Xin Li 2, Li Li 5, Junfang Hu 6, Yan Liu 2,*
Editor: Katherine James7
PMCID: PMC8535175  PMID: 34679093

Abstract

Background

Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors. However, the etiology and exact molecular mechanism of LIHC are still not fully understood, which makes it urgent for us to further study the molecular events behind.

Methods

In this study, differences in mRNA expression between LIHC samples and normal adjacent samples were found through analyzing the TCGA database, and key targets were sought. We analyzed 371 LIHC samples and 50 normal adjacent samples according to P <0.01 and logFC>2.5, a total of 1092 genes were identified differentially expressed, including 995 up-regulated genes and 97 down-regulated genes. We predicted the interactions of these differentially expressed mRNAs, and used Cyto-Hubba to locate the hub gene-dynein cytoplasmic 1 intermediate chain 1 (DYNC1I1).

Results

Survival analysis showed that DYNC1I1 was a prognostic factor for LIHC male patients. Functional enrichment indicated that DYNC1I1 and differentially expressed interacting proteins were involved in the cell cycle.

Conclusion

In conclusion, this study discovers that DYNC1I1 can be used as a prognostic marker for LIHC male patients.

Introduction

Liver hepatocellular carcinoma (LIHC) is one of the most common malignant tumors of the digestive tract. Globally, the incidence of LIHC ranks the sixth in the incidence of malignant tumors and the fourth in mortality [1]. LIHC seriously affects the lives and health of people. At present, the overall prognosis of LIHC is unsatisfactory. The main reasons include the insidious disease, high degree of malignancy, recurrence and metastasis [2]. Therefore, the identification of LIHC-specific biomarkers can help predict and monitor disease progression, and more importantly, through the implementation of early intervention, cases that may evolve into aggressive diseases can be reduced [3].

The Cancer Genome Atlas Project (TCGA) was jointly launched in 2006 by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). The TCGA database contains genome data for 33 tumor projects and provides original sequencing data to all researchers [4]. TCGA has released many mRNA sequencing data of LIHC cancer patients. This study aimed to determine the mRNA expression differences between LIHC samples and normal adjacent samples through analyzing high-throughput mRNA data downloaded from the TCGA database. We used protein interactions [5] and Cyto-Hubba [6] to find the hub gene-DYNC1I1. Also, we assessed the prognostic value of DYNC1I1 and analyzed the possible biological functions of DYNC1I1, which were expected to provide new insights into the underlying molecular mechanisms of LIHC.

Material and methods

Data processing

Raw sequencing data and clinical information were downloaded from the TCGA database (https://cancergenome.nih.gov/). Altogether, a total number of 421 samples were enrolled in this study, including 371 LIHC samples and 50 normal adjacent samples. We used the R language package to process mRNAs sequencing data. The differentially expressed mRNAs between LIHC samples and normal adjacent samples are analyzed by the “DESeq2” package in R. When we were calculating the fold change (FC) of individual mRNA expression, we considered that the differentially expressed mRNAs with P < 0.01 and logFC > 2.5 as significant.

Differential gene analysis

The R package of "DESeq2_1.28.1" [7] was used for Principal Component Analysis (PCA) and MA-plot of significant differentially expressed mRNA, and we used the code "dds <- dds[rowSums(counts(dds))>1,]" to delete low-expressed genes. The "pheatmap_1.0.12" package [8] and "ggrepel_0.8.2" package [9] in R were used for heatmap and volcano map, respectively. The default parameters were used for all analysis.

Functional enrichment analysis

We used the R package “ClusterProfiler_3.16.1” [10] for gene Ontology (GO) enrichment and used the online database DAVID [11] for gene Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway analysis. GO terms or KEGG pathways with P < 0.05 were considered statistically significant.

Protein-Protein Interaction (PPI) network construction and analysis of modules

STRING is a search tool that can analyze the interaction relationship between genes/proteins (https://string-db.org/). Using STRING to analyze the PPI network can help us understand the relationships between different genes/proteins. Cyto-Hubba software was used to screen for hub genes. We used 11 algorithms of the Cyto-Hubba software to screen out the hub gene: MCC, DMNC, MNC, Degree, EPC, BottleNeck, EcCentricity, Closeness, Radiality, Betweenness, Stress.

Prognosis analysis

We used the LIHC patient data in TCGA and the "Survival" package and "Survminer" package of R language to draw the survival curve of LIHC patients.

Results

Identification of differentially expressed mRNAs in LIHC

We retrospectively analyzed the TCGA LIHC dataset. In the present study, a total of 421 samples were enrolled in this study, including 371 LIHC samples and 50 normal adjacent samples, to identify the differentially expressed genes. PCA showed that LIHC samples and normal adjacent samples fell in different areas, and the two groups of samples were effectively distinguished (Fig 1A, 1B) depicted the transcription abundance values of LIHC samples and normal adjacent samples as MA-plot. According to P < 0.01 and logFC > 2.5, a total number of 1092 differentially expressed mRNAs were identified between LIHC samples and normal adjacent samples, including 995 up-regulated and 97 down-regulated mRNAs. We presented the result in the form of Heat map (Fig 1C) and Volcano plot (Fig 1D).

Fig 1. Identification of expression differences between LIHC samples and normal adjacent samples.

Fig 1

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A. PCA of 371 LIHC samples and 50 normal adjacent samples expression analysis. Red represented normal adjacent samples, and blue represented LIHC samples; B.MA-plot of the differential mRNA expression analysis; C. Heat map of the differential mRNA expression analysis. Blue represented normal adjacent samples, and red represented LIHC samples; D. Volcano plot of the differential mRNA expression analysis. Red represented differential mRNAs that were highly expressed in LIHC samples.

Functional annotation of differentially expressed mRNAs in LIHC

In order to understand the biological roles of the 1092 differentially expressed mRNAs in LIHC, we performed GO and KEGG pathway enrichment analysis using the R package “Clusterprofiler”, which showed 20 most significant cellular components, biological process and molecular function terms, and 9 significant KEGG pathways. GO analysis revealed that major terms enriched in the cellular component terms were ion channel complex and transmembrane transporter complex (Fig 2A). The most significantly enriched biological process category were organelle fission and nuclear division (Fig 2B). For the molecular function category, the primary enriched terms were passive transmembrane transporter activity, ion channel activity, and DNA−binding transcription activator activity (Fig 2C). KEGG pathway analysis indicates that the differentially expressed mRNAs played relevant roles in cell cycle, cytokine−cytokine receptor interaction (Fig 2D). The specific details of GO and KEGG pathway enrichment analysis are in the S1–S4 Tables.

Fig 2. Functional enrichment analysis of differentially expressed mRNAs.

Fig 2

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The most important GO terms for cell component (A), biological process (B) and molecular function (C) of 1092 differential genes were shown in the figures; D. Gene networks identified through KEGG pathway analysis of the differentially expressed mRNAs.

Using string and Cyto-Hubba to identify the hub gene in LIHC

We used STRING online database to analyze 1092 differentially expressed mRNAs and construct PPI network (Fig 3A), for details about PPI calculation in STRING, see S5 Table. Then, we downloaded the results and use Cyto-Hubba software for analysis. We analyzed the results of PPI using 11 algorithms of Cyto-Hubba software. We extracted the top 100 hub genes from 11 algorithms, and get the only key gene DYNC1I1 after taking the intersection (Fig 3B). The detailed scoring of genes in PPI by 11 algorithms was in S6 Table.

Fig 3. Identify the hub gene.

Fig 3

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A. Use STRING online database to build a PPI network that interacts with DYNC1I1; B. Use Cyto-Hubba software to identify the hub gene. DYNC1I1 was the only hub gene that intersects among the top 100 genes obtained by each of the 11 algorithms.

Characterization of DYNC1I1

DYNC1I1 (Dynein Cytoplasmic 1 Intermediate Chain 1) is an important cargo-binding subunit of cytoplasmic dynein. It serves as one of several non-catalytic accessory components of the cytoplasmic dynein 1 complex that are thought to be involved in linking dynein to cargos and to adapter proteins that regulate dynein function. DYNC1I1 is located at chr7: 95772554–96110322 (Fig 4A). We use online database SWISS–MODEL [12] to examine the protein structure of DYNC1I1, Fig 4B showed the protein structure of DYNC1I1, the structure consists of multiple beta folds to form a compact space structure. There was an alpha helix at the N-terminal and the C-terminal, and the alpha helix at the N-terminal is free to the outside. We detected the expression of DYNC1I1 in LIHC data of the TCGA database, and the results showed that the expression of DYNC1I1 in LIHC samples was higher than in normal adjacent samples, and the P value = 3.690758e-05, which was statistically significant (Fig 4C). We extracted 50 pairs of LIHC samples in the TCGA data, and the results showed that the expression of DYNC1I1 in the paired LIHC samples was also higher than in the paired normal adjacent samples, and the P value = 0.0056 (Fig 4D). The expression of DYNC1I1 in LIHC male patients and female patients was also different (P = 0.0026), and the results showed that its expression in male patients was higher than in female patients (Fig 4E). We further explored whether the elevated expression of DYNC1I1 level in LIHC affected the survival of patients. LIHC data with gene expression and clinical information from TCGA were used to investigate DYNC1I1 prognostic significances. The survival rate of DYNC1I1 high expression group was significantly lower (P = 0.001, hazard ratio: 0.98, 95% CI: 0.84–1.1, Fig 4F). Our previous results showed that the expression of DYNC1I1 in LIHC male patients was higher than in female patients. Therefore, we separately investigated the impact of DYNC1I1 on the survival of LIHC male and female patients. The results found that DYNC1I1 had a significant impact on the survival of male patients (Fig 4G), while it had not statistically significant impact on the survival of female patients (Fig 4H). These results indicated that high expression of DYNC1I1 was an adverse factor for the survival of LIHC male patients.

Fig 4. Characterization of DYNC1I1.

Fig 4

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Genomic localization (A) and protein structure (B) of DYNC1I1; C. Differential expression of DYNC1I1 in LIHC samples and normal adjacent samples (P = 3.690758e-05); D. Differential expression of DYNC1I1 in 50 pairs of LIHC samples and normal adjacent samples (P = 0.0056); E. Differential expression of DYNC1I1 in LIHC male patients and female patients (P = 0.0026); F. Association between DYNC1I1 expression and disease-free survival time in the TCGA-LIHC dataset (P = 0.001). G-H. DYNC1I1 had a significant impact on the survival of LIHC male patients (P = 0.002), but has no significant impact on the survival of LIHC female patients (P = 0.07).

Function analysis of DYNC1I1

We extracted the proteins that interact with DYNC1I1 in the PPI results (Fig 5A), The specific details of the PPI results were in the Table 1. To reveal the potential biological functions of these interacting proteins, we conducted GO and KEGG analysis. GO function annotation of the interacting proteins was performed using the R package “Clusterprofiler”. The most significant GO terms for cellular component, biological process and molecular function were shown in Fig 5B–5D. The KEGG pathway analysis was performed using the DAVID database, and the results of the analysis were shown in Fig 5E. The interacting proteins were mainly enriched in cell cycle, Progesterone−mediated oocyte maturation and Oocyte meiosis. This analysis indicated that DYNC1I1 was mainly involved in cell cycle. The specific details of GO and KEGG pathway enrichment analysis were in the S7–10 Tables.

Fig 5. Function analysis of DYNC1I1.

Fig 5

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The figure showed the cellular component (A), biological process (B) and molecular function (C) of DYNC1I1 and the proteins that interacted with it (D); E. Possible pathways mediated by DYNC1I1 and its interacting proteins. The color of the dot represents the P value, and the size of the dot represented the number of counts.

Table 1. Proteins that interact with DYNC1I1.

Gene PPI
DYNC1I1 KIF20A KIF11 MAD2L1 ZWINT SPTA1 FOLR1 PLK1 SGOL1 NDC80 NUF2 SKA1 SPC24 KIF4A KIF18A RACGAP1 SGOL2 KIF23 SPC25 KIF15 KIF5A ERCC6L KIF2C
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Discussion

LIHC is a highly malignant tumor with a high mortality rate. The treatment of LIHC is mainly surgical resection, but due to its high recurrence and metastasis rate, the prognosis of LIHC patients is often far from satisfactory [13, 14]. Due to the insidious onset, rapid progress, high recurrence and metastasis rate of LIHC, the prognosis of patients is poor, the overall 5-year survival remains at 25%-39%, and the recurrence rate of advanced LIHC patients is about 80% [15]. Therefore, a better understanding of the progression of LIHC and new mechanisms of occurrence and progression will help us find new therapeutic targets, formulate more effective treatment strategies, and extend the survival time of LIHC patients.

At present, the first-line targeted drugs for LIHC treatment include levatinib and sorafenib, and the second-line targeted drugs include cabotinib, regorafenib, ramucirumab and nivolumab [16]. In order to improve the prognosis of patients with LIHC and advance development of this field, more researches are needed on molecular targeted therapies that use genome maps and biomarker matching [17, 18]. With the advancement of RNA sequencing and other technologies, the mechanism of the occurrence and progress of LIHC is constantly being explored, and more targets are identified and utilized [19, 20].

In the present study, we find that DYNC1I1 is differentially expressed in LIHC patients, and it is significantly related to patient survival. Previous studies have shown that DYNC1I1 can promote the progression and metastasis of gastric cancer [21, 22], colon cancer [23] and glioblastoma [24], but no study has found that DYNC1I1 has a biological function in LIHC and is a prognostic factor of LIHC. The content of our research makes researchers better understand the biological functions of DYNC1I1.

In order to gain new insight into the molecular functions of DYNC1I1, we screened the differentially expressed genes that interact with it, analyzed related pathways, and performed GO annotations. Abnormal signal pathways play a vital role in the occurrence and development of LIHC in male patients. We discover that DYNC1I1 can regulate the cell cycle and is related to some transmembrane transportation, which indicates that DYNC1I1 may not only affect the progress of LIHC in male patients, but also affect drug transportation.

In summary, we have identified DYNC1I1 as a potential prognostic predictor of LIHC for male patients. In future research, we will classify patients’ samples by sex and use a larger sample size to verify our research results, and the molecular mechanism of DYNC1I1 in progression of LIHC also needs more in-depth functional researches.

Supporting information

S1 Table

(XLSX)

Click here for additional data file. (52.9KB, xlsx)
S2 Table

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S3 Table

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S4 Table

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S5 Table

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S6 Table

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S7 Table

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S8 Table

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S9 Table

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S10 Table

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Click here for additional data file. (10.3KB, xlsx)

Data Availability

In this study the original sequence data and clinical information can be downloaded from TCGA database (https://cancergenome.nih.gov/), and all the data generated by the analysis are included in this article.

Funding Statement

This study was funded by the Hubei Province health and family planning scientific research project (WJ2019M257) and Wuhan Municipal Health scientific research project (WX20C13). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

References

  • 1.Duran SR, Jaquiss RDB. Hepatocellular Carcinoma[J]. N Engl J Med, 2019, 381(1):e2. [DOI] [PubMed] [Google Scholar]
  • 2.Villanueva A, Hernandez-Gea V, Llovet JM. Medical therapies for hepatocellular carcinoma: a critical view of the evidence[J]. Nat Rev Gastroenterol Hepatol, 2013, 10(1):34–42 doi: 10.1038/nrgastro.2012.199 [DOI] [PubMed] [Google Scholar]
  • 3.Yang JD, Heimbach JK. New advances in the diagnosis and management of hepatocellular carcinoma[J]. Bmj, 2020, 371:m3544 doi: 10.1136/bmj.m3544 [DOI] [PubMed] [Google Scholar]
  • 4.Chandran UR, Medvedeva OP, Barmada MM, et al. TCGA Expedition: A Data Acquisition and Management System for TCGA Data[J]. PLoS One, 2016, 11(10):e0165395 doi: 10.1371/journal.pone.0165395 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets[J]. Nucleic Acids Res, 2019, 47(D1):D607–d613 doi: 10.1093/nar/gky1131 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Otasek D, Morris JH, Bouças J, et al. Cytoscape Automation: empowering workflow-based network analysis[J]. Genome Biol, 2019, 20(1):185 doi: 10.1186/s13059-019-1758-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[J]. Genome Biol, 2014, 15(12):550 doi: 10.1186/s13059-014-0550-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.R K. Pheatmap: Pretty Heatmaps[J]. 2015,
  • 9.H W. ggplot2: Elegant Graphics for Data Analysis.[J]. Springer, 2009, [Google Scholar]
  • 10.Yu G, Wang LG, Han Y, et al. clusterProfiler: an R package for comparing biological themes among gene clusters[J]. Omics, 201216(5):284–287 doi: 10.1089/omi.2011.0118 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Dennis G Jr., Sherman BT, Hosack DA, et al. DAVID: Database for Annotation, Visualization, and Integrated Discovery[J]. Genome Biol, 2003, 4(5):P3 [PubMed] [Google Scholar]
  • 12.Waterhouse A, Bertoni M, Bienert S, et al. SWISS-MODEL: homology modelling of protein structures and complexes[J]. Nucleic Acids Res, 2018, 46(W1):W296–w303 doi: 10.1093/nar/gky427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Yang JD, Hainaut P, Gores GJ, et al. A global view of hepatocellular carcinoma: trends, risk, prevention and management[J]. Nat Rev Gastroenterol Hepatol, 2019, 16(10):589–604 doi: 10.1038/s41575-019-0186-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Huang Z, Zhou JK, Peng Y, et al. The role of long noncoding RNAs in hepatocellular carcinoma[J]. Mol Cancer, 2020, 19(1):77 doi: 10.1186/s12943-020-01188-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Zuo Q, He J, Zhang S, et al. PGC1α suppresses metastasis of HCC by inhibiting Warburg effect via PPARγ-dependent WNT/β-catenin/PDK1 axis[J]. Hepatology, 2020, [Google Scholar]
  • 16.Llovet JM, Zucman-Rossi J, Pikarsky E, et al. Hepatocellular carcinoma[J]. Nat Rev Dis Primers, 2016, 2:16018 doi: 10.1038/nrdp.2016.18 [DOI] [PubMed] [Google Scholar]
  • 17.Lim H, Ramjeesingh R, Liu D, et al. Optimizing Survival by Changing the Landscape of Targeted Therapy for Intermediate and Advanced Hepatocellular Carcinoma: A Systematic Review[J]. J Natl Cancer Inst, 2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Finn RS, Zhu AX. Evolution of Systemic Therapy for Hepatocellular Carcinoma[J]. Hepatology, 2020, [DOI] [PubMed] [Google Scholar]
  • 19.Kudo M, Ueshima K, Yokosuka O, et al. Sorafenib plus low-dose cisplatin and fluorouracil hepatic arterial infusion chemotherapy versus sorafenib alone in patients with advanced hepatocellular carcinoma (SILIUS): a randomised, open label, phase 3 trial[J]. Lancet Gastroenterol Hepatol, 2018, 3(6):424–432 doi: 10.1016/S2468-1253(18)30078-5 [DOI] [PubMed] [Google Scholar]
  • 20.Pillai A, Ahn J, Kulik L. Integrating Genomics Into Clinical Practice in Hepatocellular Carcinoma: The Challenges Ahead[J]. Am J Gastroenterol, 2020, [DOI] [PubMed] [Google Scholar]
  • 21.Gong LB, Wen T, Li Z, et al. DYNC1I1 Promotes the Proliferation and Migration of Gastric Cancer by Up-Regulating IL-6 Expression[J]. Front Oncol, 2019, 9:491 doi: 10.3389/fonc.2019.00491 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Gong L, Wen T, Li Z, et al. TNPO2 operates downstream of DYNC1I1 and promotes gastric cancer cell proliferation and inhibits apoptosis[J]. Cancer Med, 2019, 8(17):7299–7312 doi: 10.1002/cam4.2582 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Yin Z, Yan X, Wang Q, et al. Detecting Prognosis Risk Biomarkers for Colon Cancer Through Multi-Omics-Based Prognostic Analysis and Target Regulation Simulation Modeling[J]. Front Genet, 2020, 11:524 doi: 10.3389/fgene.2020.00524 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Sakthikumar S, Roy A, Haseeb L, et al. Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes[J]. Genome Biol, 2020, 21(1):127. doi: 10.1186/s13059-020-02035-x [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Eduardo Andrés-León

4 Jun 2021

PONE-D-21-13904

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in patients with Liver hepatocellular carcinoma

PLOS ONE

Dear Dr. Liu,

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.

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Additional Editor Comments:

In the analysis it is stated that 371 samples of LIHC and adjacent normal tissue are used. However, the total number of "normal" samples is 50, so I would like to know if in a paired analysis (among the 50 paired samples) DYNC1I1 still appears as a prominent gene.

On the other hand, the text included in the differential expression analysis is not very detailed. Has any kind of filter been done to eliminate low expressed genes ? with what cpm value ? The P value is adjusted ? with which method ?

Please note that any kind of analysis must include the necessary details for the work to be reproducible by others.

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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: Partly

Reviewer #2: Partly

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

Reviewer #1: I Don't Know

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: The present work describes the discovery of a novel prognostic biomarker for liver hepatocellular carcinoma patients. Using TCGA available RNA-seq and clinical patients’ data and applying bioinformatics approaches, authors unveil DYNC1|1 as the most significantly deregulated gene in a series of LIHC patients. I would like to address the following aspects related to this manuscript:

Major comments:

1. The main figures of the paper should represent the results described in the text. The figures selected do not have enough quality to be evaluated and the description in the legend is not well described. Please, add high quality figure that could be evaluated, a main title and a complete description of the plots and graphics represented, included the meaning of colour keys (colours should be correlating between figures) and symbols.

2. Line 102-103. Please, include a table (in supplementary data) with the 20 most significant GO terms described in the text and 9 KEGG significant pathways with their score. Provide plots with more quality.

3. Line 119. Please provide a table (supplementary data) with the top ten genes obtained with the 11 different algorithms and their scores. Is only DYNC1|1 in the intersection of these algorithms? If not, include a ranking of the top ten (maximum) and their scores.

4. It would be interesting if authors could provide a table with the interacting genes belonging to the same hub than DYNC1|1. It could complete the information and add some valuable insight about the possible functionality of this alteration in liver cancer (main text).

5. Line 124. In the characterization of DYNC1|1 there is a lack of description. Authors showed in a figure the gene location and protein structure, but they did not add much detail in the text. Please, complete the description (family of the gene, which kind of protein codifies…), features of the structure and potential functionality of the gene (if it was previously described).

6. Line 126. Authors described the significant difference of DYNC1|1 expression between LIHC and normal adjacent tissue, but they did not include the statistical value for this comparison in the text. The same was done when they compared male vs female in LIHC. Please, include all these statistics, and add in the “Methods” sections how these statistics were performed.

7. In line with the previous comments and comparisons performed, the individual comparisons “LIHC vs control” in male and women independently were missed, and due to the observation of the authors that the expression in male is significantly higher than in women, I was wondering whether DYNC1|1 would be still useful as a prognostic marker for women with LIHC, or if the overexpression of this gene will remain significant in this comparison. Please, include these comparisons in this section and their statistics.

8. Line 133. Please, divide de survival rate also by gender in high and low DYNC1|1. Add the results in the text and the related graphics in supplementary information.

9. Line 153 to line 180. This text seems like an introduction and summary of the authors’ work. Just a reminder that this is the “Discussion” section. I suggest beginning with the discussion in line 181, maybe including a different first sentence that complete the paragraph. The previous discarded text could be included in the short introduction of de manuscript.

10. I should recommend authors to be more specific in some comments throughout the text because some of them like “its efficacy is still not optimistic” or “easy recurrence” do not sound very scientific. For avoiding being vague in the expression of this information, please provide previous statistics in related works supporting these comments.

11. In the discussion there is some information missing. Please provide more detail about the results in other cancers with DYNC1|1 (the sense of the deregulation, possible role on these cancers, etc) and add a proper comparison with the results obtained in this work.

12. Line 193. I am not totally sure what authors mean with the term “multi-cell cycle” and its regulation by DYNC1|1. Please, explain this concept.

Minor comments:

- Please, describe the abbreviations before including them in the text, i.e. like PPI (line 76).

- Line 80: Please change the sentence: “We use MCC, DMNC…” and substitute for “We used 11 algorithms of the Cyto-Hubba software to screen out the hub gene: MCC, DMNC, MNC…” instead, for expressing the methods a clearer way.

Reviewer #2: In this manuscript, the authors retrospectively analyzed the available TCGA data for LIHC to identify genes and pathways that are dysregulated in cancer compared to normal adjacent tissue. In their analyses, they identify DYNC1I1 as a hub gene in LIHC and a potential prognostic factor.

The analyses are well performed, however there are a few issues that should be solved before publications.

In general, I would highly recommend that they increase the font size of all the writing in the figures, most of which is currently not readable in the printed size.

Some more details would be appreciated in the figure legends. For example: specify what are the blue dots in figure 1B and the red dots in figure 1D. The legend of figure 3 has not details at all, it only indicates the tools that were used. In Figure 4A is the red line indicating the position of the gene? Please specify these details.

Cyto-Hubba identified DYNC1I1 as a hub gene. Was this the only gene at the intersection of the 11 lists? Please specify if this is the case.

Since they show that DYNC1I1 expression is higher in male patients (Figure 4D), it would be interesting to stratify the survival by sex and determine whether the prognostic significance is different in male vs female patients.

The first part of the discussion is more or less a repetition of the introduction and could be eliminated or incorporated in the introduction.

In the discussion they mention that DYNC1I1 is an independent prognostic factor, however, this is not fully demonstrated, because no multivariate analysis of the survival data is performed. Without this analysis, they should remove “independent”.

Finally, I would suggest that the authors adhere the general practice of writing in the past tense, if possible.

**********

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: No

Reviewer #2: 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. 2021 Oct 22;16(10):e0258797. doi: 10.1371/journal.pone.0258797.r002

Author response to Decision Letter 0

15 Jul 2021

Response Letter

Dear Editor-in-Chief,

Thank you very much for your letter and advice. We have revised the manuscript, and would like to re-submit it for your consideration. We have addressed the comments raised by the reviewers and editor, and the amendments are highlighted in red in the revised manuscript. The responses to the editor' and reviewers' comments are listed below this letter.

We hope that the revised version of the manuscript is now acceptable for publication in your journal.

Looking forward to hearing from you soon.

With kind regards,

Yours sincerely,

Yan Liu Dr.

Puren Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China.

Tel/Fax: 027-86367776

Email: liuyan@wust.edu.cn

We would like to express our sincere thanks to the editor and reviewers for the constructive and positive comments.

Replies to Editor

In the analysis it is stated that 371 samples of LIHC and adjacent normal tissue are used. However, the total number of "normal" samples is 50, so I would like to know if in a paired analysis (among the 50 paired samples) DYNC1I1 still appears as a prominent gene.

Answer:

Thank you very much for your question. We extracted 50 pairs of matched patients and analyzed the data. The results show that DYNC1I1 is still a significant prominent gene.

On the other hand, the text included in the differential expression analysis is not very detailed. Has any kind of filter been done to eliminate low expressed genes ? with what cpm value ? The P value is adjusted ? with which method ?

Answer:

Thank you for your question. We use the R package "Deseq2" to process the counts data of the transcriptome, and use the code "dds <- dds[rowSums(counts(dds))>1,]" to delete low-expressed genes. The CPM value should be applied to the "edgeR" package, but this R package was not used in our analysis. We use the R package "Deseq2" to adjust the P value. The code is

"dds <-DESeqDataSetFromMatrix(countData=exprSet, colData=metadata, design=~sample,tidy=TRUE)

dds <- dds[rowSums(counts(dds))>1,]

dds <- DESeq(dds,parallel = T)".

And our subsequent analysis is based on the Padj value.

Replies to Reviewer 1

Reviewer #1: The present work describes the discovery of a novel prognostic biomarker for liver hepatocellular carcinoma patients. Using TCGA available RNA-seq and clinical patients’ data and applying bioinformatics approaches, authors unveil DYNC1|1 as the most significantly deregulated gene in a series of LIHC patients. I would like to address the following aspects related to this manuscript:

Major comments:

1.The main figures of the paper should represent the results described in the text. The figures selected do not have enough quality to be evaluated and the description in the legend is not well described. Please, add high quality figure that could be evaluated, a main title and a complete description of the plots and graphics represented, included the meaning of colour keys (colours should be correlating between figures) and symbols.

Answer:

Thank you for your suggestion, we have updated the clarity of the figures and changed the description of the figures.

2.Line 102-103. Please, include a table (in supplementary data) with the 20 most significant GO terms described in the text and 9 KEGG significant pathways with their score. Provide plots with more quality.

Answer:

Thank you for your suggestion, we have added the GO and KEGG data tables in the supplementary materials.

3.Line 119. Please provide a table (supplementary data) with the top ten genes obtained with the 11 different algorithms and their scores. Is only DYNC1|1 in the intersection of these algorithms? If not, include a ranking of the top ten (maximum) and their scores.

Answer:

Thank you for your suggestion. There is only DYNC1I1 in the intersection of TOP100, so we provide the scores of the top ten genes and the scores of all genes in the supplementary materials. The file name is " Cyto-Hubba _score".

4.It would be interesting if authors could provide a table with the interacting genes belonging to the same hub than DYNC1|1. It could complete the information and add some valuable insight about the possible functionality of this alteration in liver cancer (main text).

Answer:

Thank you for your suggestion. We have added a list of proteins that interact with DYNC1I1 in the main text.

5.Line 124. In the characterization of DYNC1|1 there is a lack of description. Authors showed in a figure the gene location and protein structure, but they did not add much detail in the text. Please, complete the description (family of the gene, which kind of protein codifies…), features of the structure and potential functionality of the gene (if it was previously described).

Answer:

Thanks for your suggestion, we have added a related description in the article.

6.Line 126. Authors described the significant difference of DYNC1|1 expression between LIHC and normal adjacent tissue, but they did not include the statistical value for this comparison in the text. The same was done when they compared male vs female in LIHC. Please, include all these statistics, and add in the “Methods” sections how these statistics were performed.

Answer:

Thank you for your suggestion. We have added the P value data to the main text, and described the use of the R package "DESeq2" to analyze the data in the method.

7.In line with the previous comments and comparisons performed, the individual comparisons “LIHC vs control” in male and women independently were missed, and due to the observation of the authors that the expression in male is significantly higher than in women, I was wondering whether DYNC1|1 would be still useful as a prognostic marker for women with LIHC, or if the overexpression of this gene will remain significant in this comparison. Please, include these comparisons in this section and their statistics.

Answer:

Thank you for your valuable comments. Our research found that the expression of DYNC1I1 in men is higher than that in women, and it can predict the prognosis very well in men, but not in women. We have added this part to the main text.

8.Line 133. Please, divide de survival rate also by gender in high and low DYNC1|1. Add the results in the text and the related graphics in supplementary information.

Answer:

Thank you for your comments. We have added this part to the main text.

9.Line 153 to line 180. This text seems like an introduction and summary of the authors’ work. Just a reminder that this is the “Discussion” section. I suggest beginning with the discussion in line 181, maybe including a different first sentence that complete the paragraph. The previous discarded text could be included in the short introduction of de manuscript.

Answer:

Thank you for your comments, we have made changes to this part of the content.

10.I should recommend authors to be more specific in some comments throughout the text because some of them like “its efficacy is still not optimistic” or “easy recurrence” do not sound very scientific. For avoiding being vague in the expression of this information, please provide previous statistics in related works supporting these comments.

Answer:

Thanks for your suggestions, we have modified these descriptions accordingly.

11.In the discussion there is some information missing. Please provide more detail about the results in other cancers with DYNC1|1 (the sense of the deregulation, possible role on these cancers, etc) and add a proper comparison with the results obtained in this work.

Answer:

Thank you for your suggestions. We have added and modified relevant content according to your suggestions.

12.Line 193. I am not totally sure what authors mean with the term “multi-cell cycle” and its regulation by DYNC1|1. Please, explain this concept.

Answer:

Thank you for your correction. Due to our negligence, we can see that DYNC1I1 regulates the cell cycle in KEGG, which we have corrected in the article.

Minor comments:

- Please, describe the abbreviations before including them in the text, i.e. like PPI (line 76).

Answer:

Thanks for your suggestion, we have revised the acronyms.

- Line 80: Please change the sentence: “We use MCC, DMNC…” and substitute for “We used 11 algorithms of the Cyto-Hubba software to screen out the hub gene: MCC, DMNC, MNC…” instead, for expressing the methods a clearer way.

Answer:

Thanks for your suggestion, we have made changes.

Reviewer #2: In this manuscript, the authors retrospectively analyzed the available TCGA data for LIHC to identify genes and pathways that are dysregulated in cancer compared to normal adjacent tissue. In their analyses, they identify DYNC1I1 as a hub gene in LIHC and a potential prognostic factor.

The analyses are well performed, however there are a few issues that should be solved before publications.

In general, I would highly recommend that they increase the font size of all the writing in the figures, most of which is currently not readable in the printed size.

Answer:

Thanks for your suggestion, we have updated the figures.

Some more details would be appreciated in the figure legends. For example: specify what are the blue dots in figure 1B and the red dots in figure 1D. The legend of figure 3 has not details at all, it only indicates the tools that were used. In Figure 4A is the red line indicating the position of the gene? Please specify these details.

Answer:

Thank you for your suggestions. We have added and modified relevant content according to your suggestions.

Cyto-Hubba identified DYNC1I1 as a hub gene. Was this the only gene at the intersection of the 11 lists? Please specify if this is the case.

Answer:

Yes, this is the only gene in the TOP100 among the 11 algorithms.

Since they show that DYNC1I1 expression is higher in male patients (Figure 4D), it would be interesting to stratify the survival by sex and determine whether the prognostic significance is different in male vs female patients.

Answer:

Thank you for your suggestion. DYNC1I1 has different effects on the survival of men and women, and we have added this content in the main text.

The first part of the discussion is more or less a repetition of the introduction and could be eliminated or incorporated in the introduction.

Answer:

Thanks for your suggestion, we revised the first part of the discussion.

In the discussion they mention that DYNC1I1 is an independent prognostic factor, however, this is not fully demonstrated, because no multivariate analysis of the survival data is performed. Without this analysis, they should remove “independent”.

Answer:

Thank you for your suggestion. We changed the "independent prognosis" to "prognosis".

Finally, I would suggest that the authors adhere the general practice of writing in the past tense, if possible.

Answer:

Thanks for your suggestion, we will ask native English speakers to help us modify the grammar of the article.

Attachment

Submitted filename: Response to Reviewers.doc

Click here for additional data file. (46KB, doc)

Decision Letter 1

Katherine James

9 Aug 2021

PONE-D-21-13904R1

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in male patients with Liver hepatocellular carcinoma

PLOS ONE

Dear Dr. Liu,

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.

You will see that while the reviewers are persuaded of the importance of your study and agree with your revisions, reviewer 1 has suggested several minor changes to the text. In addition I have several comments below that require clarification.

Please submit your revised manuscript by Sep 23 2021 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:

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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: http://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,

Katherine James, 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.

Additional Editor Comments:

PlosOne requires methods to be described in sufficient detail for another researcher to reproduce the experiments described and currently your analyses would not be reproducible from the provided methodology. I have several minor comments that require clarification:

Please clarify package names and versions for all R packages used.

Please also clarify parameters used in all software. If defaults were used please state “using default parameters” or similar in the text.

You have clarified processing of the RNAseq data in the response to review: “use the code "dds <- dds[rowSums(counts(dds))>1,]" to delete low-expressed genes”. This information should be in the methods.

Please ensure all methodology is covered, for instance the DAVID database is mentioned in the results section but not in the methods.

Additionally, what is the source of the structural data in figure 4?

Please add appropriate references for all software and databases used.

The STRING database contains multiple types of interaction from several sources, many of which are functional interactions rather than physical PPI eg co-expression data. Please detail the sources chosen and score threshold applied. If functional data are included in the network, please change the text accordingly as this is not a PPI network.

At line 213 please change “gender” to “sex” to clarify this is a biological classification.

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

2. 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

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

Reviewer #1: Yes

Reviewer #2: Yes

4. 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

5. 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

6. 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: The authors have completed the requests and added some valuable information and discussion about the different aspects pointed out during the first revision, improving considerably the quality of the manuscript. I am happy with the result of these changes. However, there is still some minor remaining aspects that I would like to point out before the manuscript will be ready for publication:

Minor comments:

1. Line 69. There are still some misspelling words. Please, substitute “considerd” for “considered” and “logFC <2.5 are significant” for “logFC >2.5 as significant”.

2. Lines 108-109. Please, include the information “using the R package “clusterprofiler” in Methods’ section, “Functional enrichment analysis” (line 73) where it corresponds. This information should be there and not in the Results’ section. Same happened with the sentence: “GO function annotation of the interacting proteins was performed using the R package” (line 170-171), move that information to the same section.

3. Lines 142, 145, 148, 154. Please, substitute “than that” only for “than”.

4. Line 147. Write “and the results showed that…” instead of “and the resulted show that…”.

5. Lines 157-158. Please, insert here that “These results indicated that high expression of DYNC1|1…”.

6. Lines 186, 188, 189. Please, eliminate in the indicated lines the word “rate” after “recurrence”, “recurrence” and “survival” consecutively.

7. Lines 209, 211. Add “LIHC in male patients” instead “LIHC male patients”.

8. Line 212. Same here, add “LIHC for male patients”.

9. Line 213. “we will classify patients’ samples by gender…”.

Reviewer #2: (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.

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: No

Reviewer #2: 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. 2021 Oct 22;16(10):e0258797. doi: 10.1371/journal.pone.0258797.r004

Author response to Decision Letter 1

13 Aug 2021

Response Letter

Dear Editor-in-Chief,

Thank you very much for your letter and advice. We have revised the manuscript, and would like to re-submit it for your consideration. We have addressed the comments raised by the reviewers and editor, and the amendments are highlighted in red in the revised manuscript. The responses to the editor' and reviewers' comments are listed below this letter.

We hope that the revised version of the manuscript is now acceptable for publication in your journal.

Looking forward to hearing from you soon.

With kind regards,

Yours sincerely,

Yan Liu Dr.

Puren Hospital Affiliated to Wuhan University of Science and Technology, Wuhan, Hubei, 430081, China.

Tel/Fax: 027-86367776

Email: liuyan@wust.edu.cn

We would like to express our sincere thanks to the editor and reviewers for the constructive and positive comments.

Replies to 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.

Answer: Thank you for your suggestions. We have revised and updated the references.

Replies to Editor

Please clarify package names and versions for all R packages used.

Answer: Thank you for your valuable comments. We updated the package name and version of all the R package.

Please also clarify parameters used in all software. If defaults were used please state “using default parameters” or similar in the text.

Answer: Thank you for your comment, we revised the relevant content.

You have clarified processing of the RNAseq data in the response to review: “use the code "dds <- dds[rowSums(counts(dds))>1,]" to delete low-expressed genes”. This information should be in the methods.

Answer: Thank you for your suggestions, we revised the relevant content.

Please ensure all methodology is covered, for instance the DAVID database is mentioned in the results section but not in the methods.

Answer: Thank you for your comment. We revised the relevant content.

Additionally, what is the source of the structural data in figure 4?

Answer: Thanks for your comment. Data was obtained from the online database Swiss-Model (https://swissmodel.expasy.org/repository/uniprot/O14576?csm=55A6FF971E632DA0), and we revised the relevant content in text.

Please add appropriate references for all software and databases used.

Answer: Thank you for your suggestions. We have added relevant references.

The STRING database contains multiple types of interaction from several sources, many of which are functional interactions rather than physical PPI eg co-expression data. Please detail the sources chosen and score threshold applied. If functional data are included in the network, please change the text accordingly as this is not a PPI network.

Answer: Thanks for your suggestion. Homo sapiens was selected for STRING analysis, and the detailed scoring value was added to the supplementary materials.

At line 213 please change “gender” to “sex” to clarify this is a biological classification.

Answer: Thank you for your comment, we have made changes to this part of the content.

Replies to Reviewer 1

Reviewer #1: The authors have completed the requests and added some valuable information and discussion about the different aspects pointed out during the first revision, improving considerably the quality of the manuscript. I am happy with the result of these changes. However, there is still some minor remaining aspects that I would like to point out before the manuscript will be ready for publication:

Minor comments:

1.Line 69. There are still some misspelling words. Please, substitute “considerd” for “considered” and “logFC <2.5 are significant” for “logFC >2.5 as significant”.

Answer: Thanks for your suggestions, we have made changes.

2.Lines 108-109. Please, include the information “using the R package “clusterprofiler” in Methods’ section, “Functional enrichment analysis” (line 73) where it corresponds. This information should be there and not in the Results’ section. Same happened with the sentence: “GO function annotation of the interacting proteins was performed using the R package” (line 170-171), move that information to the same section.

Answer: Thank you for your valuable comments. We have made corresponding modifications in the article.

3.Lines 142, 145, 148, 154. Please, substitute “than that” only for “than”.

Answer: Thank you for your suggestions. We changed the "than that" to "than".

4.Line 147. Write “and the results showed that…” instead of “and the resulted show that…”.

Answer: Thanks for your suggestion, we have made changes.

5.Lines 157-158. Please, insert here that “These results indicated that high expression of DYNC1|1…”.

Answer: Thanks for your suggestion, we have modified these descriptions accordingly.

6.Lines 186, 188, 189. Please, eliminate in the indicated lines the word “rate” after “recurrence”, “recurrence” and “survival” consecutively.

Answer: Thanks for your suggestions, we have made changes.

7.Lines 209, 211. Add “LIHC in male patients” instead “LIHC male patients”.

Answer: Thanks for your suggestions, we changed the "LIHC male patients" to "LIHC in male patients".

8.Line 212. Same here, add “LIHC for male patients”.

Answer: Thank you for your suggestion, we have made changes to this part of the content.

9. Line 213. “we will classify patients’ samples by gender…”.

Answer: Thanks for your suggestion, we have made changes.

Attachment

Submitted filename: Response to Reviewers.doc

Click here for additional data file. (35.6KB, doc)

Decision Letter 2

Katherine James

6 Oct 2021

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in male patients with Liver hepatocellular carcinoma

PONE-D-21-13904R2

Dear Dr. Liu,

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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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,

Katherine James, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Katherine James

14 Oct 2021

PONE-D-21-13904R2

Bioinformatics analysis identifies DYNC1I1 as prognosis marker in male patients with Liver hepatocellular carcinoma

Dear Dr. Liu:

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. Katherine James

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

    (XLSX)

    Click here for additional data file. (52.9KB, xlsx)
    S2 Table

    (XLSX)

    Click here for additional data file. (353.7KB, xlsx)
    S3 Table

    (XLSX)

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    Data Availability Statement

    In this study the original sequence data and clinical information can be downloaded from TCGA database (https://cancergenome.nih.gov/), and all the data generated by the analysis are included in this article.

    Articles from PLoS ONE are provided here courtesy of PLOS

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