Literature DB >> 36158075

Analysis of the role of m6A and lncRNAs in prognosis and immunotherapy of hepatocellular carcinoma.

Yan Xu1, Rong Liu1.   

Abstract

Objective: To study the role of m6A and lncRNAs in the prognosis and immunotherapy of hepatocellular carcinoma, construct the risk score of overall survival of hepatocellular carcinoma, and search for new therapeutic targets and drugs.
Methods: The data used in this study are obtained from The Cancer Genome Atlas (TCGA) database. A total of 424 HCC samples were included. The co-expression of lncRNAs and M6A-related genes in HCC was analyzed, COX regression analysis was conducted to construct the risk score for HCC prognosis, and the model's validity was further verified in different clinical trials subtypes and principal component analysis. GO enrichment analysis and immune function analysis were performed for the differential genes in the high-risk group and the low-risk group divided by risk score and analyzed the prognostic effect of TMB on the two groups. Based on the results, potential therapeutic agents for HCC were screened.
Results: The risk score can better predict the prognosis of HCC, the area under the ROC curve is 0.727. Differential genes were mainly located in the extracellular matrix and chromosomal regions and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation of cells. Type Ⅱ IFN response, type Ⅰ IFN response and MHC class Ⅰ were the three most different functions in terms of immune function between the high-risk group and the low-risk group. Type II IFN response, type I IFN response was significantly down-regulated in the high-risk group, while MHC class I was up-regulated. 14 potential therapeutic drugs were screened out. Conclusions: The risk score constructed with NRAV and AL031985.3 had a good predictive effect on the prognosis of HCC. Differences in genes and immune function between high-risk and low-risk groups promoted the occurrence and progression of HCC.
© 2022 The Author(s).

Entities:  

Keywords:  AL031985.3; Hepatocellular carcinoma; Immune function; NRAV; Risk score; m6A

Year:  2022        PMID: 36158075      PMCID: PMC9489786          DOI: 10.1016/j.heliyon.2022.e10612

Source DB:  PubMed          Journal:  Heliyon        ISSN: 2405-8440


Introduction

Hepatocellular carcinoma (HCC) is one of the most common cancers in the world and the second leading cause of cancer-related deaths [1]. There are approximately 841,000 new cases and 782,000 deaths of HCC each year [2]. There are many methods to treat HCC, including surgery, radiofrequency ablation, transarterial chemoembolization (TACE), hepatic arterial infusion chemotherapy (HAIC), and drug therapy [3, 4, 5]. But the current treatment results of these methods are not satisfactory. The 3-year survival rate of HCC was only 12.7% and the median survival was 9 months [6]. Sorafenib is the first targeted drug used in the treatment of advanced HCC. It is a blocker of vascular endothelial growth factor receptors (VEGFRs). Although Sorafenib was established as a first-line drug for advanced HCC in 2017, it only prolonged the median overall survival of patients by 2.8 months [7]. After sorafenib, there are many clinical trials aimed at the treatment of advanced liver cancer, including Sunitinib [8], Brivanib [9], Linifanib [10], Lenvatinib [11]. It is worth noting that even lenvatinib (which has been approved for advanced HCC) did not show an advantage in the efficacy comparison with sorafenib [12]. Therefore, we need to develop better therapeutic targets and drugs for HCC. N6-methyladenosine (m6A) is the most extensive and abundant transcription modification among eukaryotic messenger RNAs (mRNAs) [13], microRNAs (miRNAs) [14], and long non-coding RNAs (lncRNAs) [15]. M6A is mainly divided into three parts: “writers”, “erasers”, and “readers”. The main role of “writers” is to catalyze the production of m6A, including Methyltransferase-like 3 (METTL3) [16], KIAA1429 [17], METTL14 [18], RBM15/15B [19] and Wilms tumor 1-associated protein (WTAP) [20]. The core function of “erasers” is to remove the methyl code from mRNA, including alkB homologue 5 (ALKBH5) [21] and fat mass and obesity-associated protein (FTO) [22]. “Reader” is responsible for decoding m6A methylation, including nuclear ribonucleoprotein (HNRNP) protein [23], IGF2 mRNA binding proteins (IGF2BP) [24], eukaryotic initiation factor (eIF) 3[25] and YT521-B homology (YTH) domain-containing protein [26]. Studies have found that m6A modification plays an important role in tumor proliferation, differentiation, invasion, and metastasis, and can also be used as a tumor oncogene or anti-oncogene [27, 28, 29]. M6A regulates many aspects of the development of HCC. METTL3 is related to the poor prognosis of HCC patients and promotes the proliferation, migration, and colony formation of HCC cells [30]. In addition, METTL14 is an anti-metastatic factor, and its down-regulation will also promote the progression and metastasis of HCC [31]. Therefore, it is of great significance to study the regulation of m6A in liver cancer, to identify new therapeutic targets and potential therapeutic drugs, and to improve the prognosis of patients with liver cancer. LncRNAs contain more than 200 nucleotides, interacts with DNA, RNA, or protein, regulate gene expression at the transcription or post-transcription level, and are closely related to the progression of gastric cancer, HCC, and colon cancer [32, 33, 34, 35]. Studies have shown that many lncRNAs, including MIAT [36], CDKN2BAS [37], and PCNAP1 [38], promote the proliferation and invasion of HCC cells, and lncRNA-D16366 can be used as a biological marker for the diagnosis and prognosis of HCC [39]. Therefore, studying the interaction between lncRNA and m6A in the occurrence and development of HCC can further discover its influence on the development of HCC, find potential therapeutic targets and drugs, and improve the prognosis of HCC patients.

Methods

Data of the research

The data used in this study are obtained from The Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/tcga/). A total of 424 HCC samples were included, including 50 normal samples and 374 tumor samples. Clinical data mainly included age, survival status, TMN stage, tumor stage, grade, and gender.

Co-expression analysis of m6A and lncRNA

mRNAs and lncRNAs were screened from TCGA transcriptome data. Subsequently, m6A gene expression was extracted from transcriptome data. A total of 23 m6A genes were used in this paper. (Writers: METTL3, METTL14, METTL16, WTAP, VIRMA, ZC3H13, RBM15, RBM15B. Readers: YTHDC1, YTHDC2, YTHDF1, YTHDF2, YTHDF3, HNRNPC, FMR1, LRPPRC, HNRNPA2B1, IGFBP1, IGFBP2, IGFBP3, RBMX. Erasers: FTO, ALKBH5.) In the analysis of co-expression of the m6A genes and lncRNAs, the correlation test was adopted. The filter criterion for the correlation coefficient was set as corFilter = 0.4, and the filter criterion for the p-value of the correlation test was set as pvalueFilter = 0.001. Drawing the Sankey diagram based on the co-expression relationship of m6A and lncRNAs.

Construct a prognostic model

Clinical data of the samples were combined with m6A-related lncRNA data, then divided into a training group and test group by 1:1. The training group is used to build the model, and the text group is used to validate the model. Construct predictive models using the “survival”, “caret”, “glmnet”, “survminer”, and “timeROC” packages. When constructing the prediction model, univariate COX regression was adopted, coxPfilter was set to 0.05, and then the forest map was drawn. Univariate COX regression was performed for the training group, followed by Lasso regression and cross-validation. Then the COX model is constructed. The text group works the same way as the training group. The samples of the two groups were divided into the high-risk group and the low-risk group with the median risk score as the boundary, and the ROC curves of the high-risk group and the low-risk group were plotted. Used the “pheatmap” package to draw the risk curve, sorted the samples according to the patient risk score, and then drew the risk curve, survival status map, and risk heat map of the overall sample, the training group, and the text group, respectively. Univariate COX analysis and multivariate COX analysis were performed for the risk score, followed by independent prognostic analysis to obtain the forest map of the risk score. The predictive function of the model was calculated by the area under the ROC curve. The validity of the model was evaluated by the c-index curve. Used the “survival”, “regplot”, and “rms” packages to draw a nomogram of the risk score.

Model validation for clinical grouping

Used the “survival” and “survminer” packages to plot the survival curves of the high-risk group and the low-risk group in subgroups of age, sex, and tumor stage, respectively, to verify the validity of the risk score.

Principal component analysis

Principal component analysis was performed using the “limma” and “scatterplot3d” packages, and PCA plots of all gene expression levels, m6A-related gene expression levels, m6A-related lncRNA expression levels, and model-related lncRNA expression levels were plotted.

Risk differential analysis and GO enrichment analysis

The wilcoxon test was used to analyze the genes that differ between the high-risk and low-risk groups, and the filter conditions were set as logFCfilter = 1 and fdrFilter = 0.05. GO enrichment analysis of differential genes in high-risk group and low-risk group was performed using “clusterProfiler”, “org.Hs.eg.db”, “enrichplot”, “ggplot2”, “ggpubr”, and “dplyr” packages. (pvalueFilter = 0.05, qvalueFilter = 0.05).

Immune function analysis

Used “limma”, “GSVA”, “GSEABase”, “pheatmap”, and “reshape2” to perform differential analysis of immune function between the high-risk group and low-risk group, and drew a heat map. The mutation dataset of HCC was divided into the high-risk group and low-risk group by risk score, and then drew the waterfall chart of gene mutations in the high-risk group and low-risk group, respectively.

Tumor mutational burden (TMB)

Get TMB data from the TCGA database and selected the results of varscan for analysis. TMB data for each sample was extracted using Strawberry Perl software. Using the “limma” and “ggpubr” packages in R software to merge TMB data with high-risk group data and low-risk group data, and draw a violin plot. Then use the “survival” and “survminer” packages to draw the survival curves of TMB and TMB combined with the risk score.

Screening for potential drugs

The “pRRophetic” package was used to predict potential therapeutic drugs for HCC. Combined the data of drug sensitivity with the data of the high-risk group and low-risk group, calculated the IC50 value of the drug in the high-risk group and low-risk group, and then drew the box plot.

Statistics

Analysis was performed using R 4.1.2 and Strawberry Perl.

Results

A total of 424 HCC samples were included, including 50 normal samples and 374 tumor samples. The co-expression of the m6A genes and lncRNAs can be seen in Table 1. LncRNAs were positively regulated by the m6A genes in HCC samples. YTHDC1 is involved in the most extensive regulation of lncRNAs in HCC. The correlation between the m6A genes and lncRNAs can be seen in Figure 1.
Table 1

Co-expression of m6A and lncRNA.

m6AlncRNACorpvalueRegulation
YTHDF2AL031985.30.511482.54E-26positive
YTHDF1NORAD0.5506224.93E-31positive
YTHDF1AC091057.10.5473031.31E-30positive
YTHDF1PTOV1-AS10.5316771.12E-28positive
YTHDF1AC125257.10.5260775.24E-28positive
YTHDF1AL035461.20.5256155.94E-28positive
YTHDF1RNF216P10.5232271.13E-27positive
YTHDF1AC099850.30.5221581.51E-27positive
YTHDF1LINC002050.5210272.05E-27positive
YTHDF1HCG180.5191643.37E-27positive
YTHDF1AC093227.10.5174725.28E-27positive
YTHDF1AL078644.10.51647.02E-27positive
YTHDF1BACE1-AS0.5148151.06E-26positive
YTHDF1SREBF2-AS10.5145121.15E-26positive
YTHDF1WAC-AS10.5085865.37E-26positive
YTHDF1AC005288.10.5050181.34E-25positive
YTHDF1AC145207.50.5043181.60E-25positive
YTHDF1MCM3AP-AS10.504121.68E-25positive
YTHDF1NRAV0.5008043.87E-25positive
YTHDF1SNHG10.5006494.03E-25positive
YTHDF1AC102953.20.5005254.15E-25positive
YTHDC2AC005288.10.5949523.52E-37positive
YTHDC2PAXIP1-AS20.5902091.78E-36positive
YTHDC2Z68871.10.5901411.82E-36positive
YTHDC2EBLN3P0.5899311.96E-36positive
YTHDC2AC008906.10.5602932.69E-32positive
YTHDC2AC005034.50.5581545.16E-32positive
YTHDC2FGD5-AS10.5390011.43E-29positive
YTHDC2AC108010.10.5379571.93E-29positive
YTHDC2AC024075.10.5359533.40E-29positive
YTHDC2AC104532.20.5273983.65E-28positive
YTHDC2AC025917.10.5257895.67E-28positive
YTHDC2AC073046.10.5236951.00E-27positive
YTHDC2OIP5-AS10.5231331.16E-27positive
YTHDC2AC010834.30.5149321.03E-26positive
YTHDC2AL109614.10.514571.14E-26positive
YTHDC2LINC006300.5100463.69E-26positive
YTHDC2AC021078.10.5098393.89E-26positive
YTHDC2Z83843.10.5089174.93E-26positive
YTHDC2AL031846.20.5014083.33E-25positive
YTHDC1AC005288.10.7421671.25E-66positive
YTHDC1AC007406.40.7228771.09E-61positive
YTHDC1AC010834.30.69211.28E-54positive
YTHDC1LINC006300.6836897.69E-53positive
YTHDC1ZNF32-AS20.6647014.91E-49positive
YTHDC1EBLN3P0.6561722.05E-47positive
YTHDC1FAM111A-DT0.6430894.96E-45positive
YTHDC1ANKRD10-IT10.6420097.71E-45positive
YTHDC1LINC020350.6364297.33E-44positive
YTHDC1CR936218.10.6310096.26E-43positive
YTHDC1THAP9-AS10.6256035.09E-42positive
YTHDC1MCM3AP-AS10.6254195.46E-42positive
YTHDC1LINC015600.6210052.93E-41positive
YTHDC1AL031714.10.620243.91E-41positive
YTHDC1FGD5-AS10.6182928.13E-41positive
YTHDC1AL157392.30.6171461.25E-40positive
YTHDC1EIF3J-DT0.6157152.12E-40positive
YTHDC1ABALON0.6152072.56E-40positive
YTHDC1AC004771.20.6117639.08E-40positive
YTHDC1AC073046.10.6051949.73E-39positive
YTHDC1HCG180.6018793.15E-38positive
YTHDC1AC093227.10.6005145.10E-38positive
YTHDC1AC091057.10.5992737.87E-38positive
YTHDC1AC037459.20.5983361.09E-37positive
YTHDC1WARS2-AS10.5957212.70E-37positive
YTHDC1AC009120.30.5952523.18E-37positive
YTHDC1LINC009090.5946743.88E-37positive
YTHDC1NORAD0.5942254.52E-37positive
YTHDC1AC129510.10.5926777.69E-37positive
YTHDC1AC109460.20.5916561.09E-36positive
YTHDC1AC091185.10.5888172.85E-36positive
YTHDC1AC008124.10.5884123.26E-36positive
YTHDC1LINC002650.5861327.01E-36positive
YTHDC1Z68871.10.5809213.93E-35positive
YTHDC1AL132989.10.5782579.37E-35positive
YTHDC1PSMA3-AS10.5758822.02E-34positive
YTHDC1AL133355.10.5709039.92E-34positive
YTHDC1AC092614.10.5690921.76E-33positive
YTHDC1AC092910.30.5689751.82E-33positive
YTHDC1AP005899.10.5669823.41E-33positive
YTHDC1C2orf49-DT0.5666973.72E-33positive
YTHDC1TAPT1-AS10.5605892.46E-32positive
YTHDC1LENG8-AS10.5603182.67E-32positive
YTHDC1AC138028.40.5598643.07E-32positive
YTHDC1MIR4453HG0.5572896.71E-32positive
YTHDC1AC112220.20.5572866.72E-32positive
YTHDC1ZEB1-AS10.5567247.96E-32positive
YTHDC1CTBP1-DT0.55352.10E-31positive
YTHDC1NFYC-AS10.5521783.11E-31positive
YTHDC1AC004067.10.5515883.70E-31positive
YTHDC1UBA6-AS10.5505784.99E-31positive
YTHDC1INE10.5488718.26E-31positive
YTHDC1NRAV0.548111.03E-30positive
YTHDC1UBE2Q1-AS10.5478811.10E-30positive
YTHDC1AC106037.20.547511.23E-30positive
YTHDC1AF131215.50.5465671.62E-30positive
YTHDC1LINC006410.5459551.94E-30positive
YTHDC1MAP3K14-AS10.5438443.58E-30positive
YTHDC1AC008969.10.5433994.07E-30positive
YTHDC1AC107027.30.5426115.10E-30positive
YTHDC1AC008760.10.5399621.09E-29positive
YTHDC1AC005104.10.5396321.20E-29positive
YTHDC1AC096586.20.538621.60E-29positive
YTHDC1HMGN3-AS10.5373452.29E-29positive
YTHDC1ASH1L-AS10.5372362.37E-29positive
YTHDC1SEC24B-AS10.5368852.61E-29positive
YTHDC1AC004076.20.5356023.75E-29positive
YTHDC1AL031670.10.5344715.15E-29positive
YTHDC1OIP5-AS10.5335896.59E-29positive
YTHDC1AL078644.10.5333816.99E-29positive
YTHDC1AC005253.10.5306891.48E-28positive
YTHDC1AC022150.20.5304331.58E-28positive
YTHDC1AP003392.10.5294252.09E-28positive
YTHDC1AC087289.50.5289152.41E-28positive
YTHDC1FBXL19-AS10.5288012.49E-28positive
YTHDC1TRAPPC12-AS10.5276753.39E-28positive
YTHDC1XPC-AS10.5252046.64E-28positive
YTHDC1AC026412.30.523829.67E-28positive
YTHDC1PKD1P6-NPIPP10.522771.28E-27positive
YTHDC1AL049840.40.52191.62E-27positive
YTHDC1LINC015210.5206772.25E-27positive
YTHDC1AL049840.30.5205072.36E-27positive
YTHDC1LINC003420.5204182.41E-27positive
YTHDC1AP001469.20.5189133.60E-27positive
YTHDC1AC232271.10.518813.70E-27positive
YTHDC1WAC-AS10.5187463.77E-27positive
YTHDC1AC004596.10.5180994.48E-27positive
YTHDC1N4BP2L2-IT20.5165556.73E-27positive
YTHDC1AC108010.10.516387.05E-27positive
YTHDC1ADNP-AS10.5162817.24E-27positive
YTHDC1PTOV1-AS10.514931.03E-26positive
YTHDC1AL031282.20.5146421.11E-26positive
YTHDC1AL355102.40.5142741.23E-26positive
YTHDC1AC004908.10.5140271.31E-26positive
YTHDC1AC015849.30.5100563.68E-26positive
YTHDC1KANSL1L-AS10.5098293.90E-26positive
YTHDC1AC245060.20.5079456.33E-26positive
YTHDC1NIFK-AS10.5073357.40E-26positive
YTHDC1CTBP1-AS0.5063789.46E-26positive
YTHDC1THBS3-AS10.5042391.63E-25positive
YTHDC1LAMC1-AS10.5037131.86E-25positive
YTHDC1AC067852.30.5035481.94E-25positive
YTHDC1AC099850.30.5026132.46E-25positive
YTHDC1AC127024.40.5024972.53E-25positive
YTHDC1AC114956.20.5018772.96E-25positive
YTHDC1AC025287.30.5014363.30E-25positive
WTAPAC026356.10.5820712.69E-35positive
WTAPTRAF3IP2-AS10.5691471.73E-33positive
WTAPAC099850.30.5547611.44E-31positive
WTAPAC091057.10.5272773.78E-28positive
WTAPAL031714.10.5218111.66E-27positive
VIRMAOTUD6B-AS10.6455821.78E-45positive
VIRMAUBR5-AS10.5869825.27E-36positive
VIRMAAF117829.10.539391.28E-29positive
VIRMAAC064807.10.5115522.50E-26positive
RBMXHCG180.6986624.73E-56positive
RBMXAC091057.10.6689867.20E-50positive
RBMXAC099850.30.668598.61E-50positive
RBMXPTOV1-AS10.6114121.03E-39positive
RBMXAC007406.40.6027372.33E-38positive
RBMXLINC006300.5950273.43E-37positive
RBMXMCM3AP-AS10.5936565.50E-37positive
RBMXSNHG10.5897732.06E-36positive
RBMXWAC-AS10.5863766.46E-36positive
RBMXAC005288.10.5844441.23E-35positive
RBMXLINC009090.5825782.28E-35positive
RBMXTRAF3IP2-AS10.5799855.34E-35positive
RBMXNIFK-AS10.576861.47E-34positive
RBMXASH1L-AS10.5729635.15E-34positive
RBMXZNF32-AS20.5727035.60E-34positive
RBMXAC093227.10.5706161.09E-33positive
RBMXWARS2-AS10.5683932.19E-33positive
RBMXEIF3J-DT0.5668463.55E-33positive
RBMXAL078644.10.5622151.49E-32positive
RBMXNRAV0.5600552.90E-32positive
RBMXDNAJC9-AS10.5597913.14E-32positive
RBMXLINC002050.5589764.02E-32positive
RBMXMIR600HG0.546881.48E-30positive
RBMXNUTM2A-AS10.5465981.61E-30positive
RBMXLINC020350.5451362.46E-30positive
RBMXLENG8-AS10.5450932.49E-30positive
RBMXLINC006410.5390121.43E-29positive
RBMXAC025176.10.5361523.21E-29positive
RBMXSBF2-AS10.5344985.11E-29positive
RBMXLINC006650.5329057.98E-29positive
RBMXAC107027.30.5319931.03E-28positive
RBMXFAM111A-DT0.5301291.72E-28positive
RBMXAL050341.20.5290132.34E-28positive
RBMXAL157392.30.5264274.76E-28positive
RBMXAC004076.20.5250236.98E-28positive
RBMXAL008729.10.5244598.13E-28positive
RBMXSNHG320.5234481.07E-27positive
RBMXAL592148.30.5182664.28E-27positive
RBMXDDX11-AS10.518234.32E-27positive
RBMXTMEM147-AS10.5174235.35E-27positive
RBMXAC008969.10.5158798.05E-27positive
RBMXAC007066.20.5145521.14E-26positive
RBMXAC232271.10.5144471.17E-26positive
RBMXAC099850.10.5128191.79E-26positive
RBMXPSMA3-AS10.5093364.43E-26positive
RBMXAL356481.10.5091164.69E-26positive
RBMXAC127024.50.5088435.03E-26positive
RBMXSNHG40.5087195.19E-26positive
RBMXTMCO1-AS10.5079276.36E-26positive
RBMXLINC015600.5077936.58E-26positive
RBMXZNF529-AS10.5071177.83E-26positive
RBMXSEC24B-AS10.5054581.20E-25positive
RBMXAC125257.10.5050721.32E-25positive
RBMXCAPN10-DT0.503881.78E-25positive
RBMXAL121772.30.503851.80E-25positive
RBMXAP000873.10.5033692.03E-25positive
RBMXSNHG200.5029452.26E-25positive
RBMXLINC006530.5021352.77E-25positive
RBMXAC018690.10.5003094.38E-25positive
RBM15BAC091057.10.5603552.64E-32positive
RBM15BFGD5-AS10.5533762.17E-31positive
RBM15BHCG180.5527252.64E-31positive
RBM15BBACE1-AS0.5467711.53E-30positive
RBM15BLINC002050.5409338.26E-30positive
RBM15BAC099850.30.5307141.47E-28positive
RBM15BCTBP1-DT0.5303061.64E-28positive
RBM15BAC125257.10.528322.84E-28positive
RBM15BAC005288.10.5276953.37E-28positive
RBM15BSREBF2-AS10.5220541.56E-27positive
RBM15BMCM3AP-AS10.5201872.57E-27positive
RBM15BPTOV1-AS10.5196612.95E-27positive
RBM15BAL078644.10.5105073.27E-26positive
RBM15BNRAV0.500484.20E-25positive
RBM15AC125257.10.5053431.23E-25positive
METTL3AC007406.40.5744833.17E-34positive
METTL3TMEM147-AS10.5733694.53E-34positive
METTL3LINC006410.5593583.58E-32positive
METTL3AC007066.20.5561819.38E-32positive
METTL3PTOV1-AS20.5556051.12E-31positive
METTL3MCM3AP-AS10.5527662.61E-31positive
METTL3AC093227.10.5421135.89E-30positive
METTL3PKD1P6-NPIPP10.5412767.49E-30positive
METTL3AL512770.10.534594.98E-29positive
METTL3AC091057.10.5317411.10E-28positive
METTL3TRAF3IP2-AS10.5312431.27E-28positive
METTL3AC107068.10.5304051.60E-28positive
METTL3AC127024.40.5264244.77E-28positive
METTL3AC027601.10.524857.31E-28positive
METTL3DNAJC9-AS10.5221.58E-27positive
METTL3AC084018.10.5211961.96E-27positive
METTL3AL355075.20.5211691.97E-27positive
METTL3AL049840.40.5212.07E-27positive
METTL3LENG8-AS10.5208572.15E-27positive
METTL3AC008735.20.517035.94E-27positive
METTL3AC124045.10.5118152.33E-26positive
METTL3AC018690.10.5115862.47E-26positive
METTL3HCG180.5091984.59E-26positive
METTL3SEMA3F-AS10.5089584.88E-26positive
METTL3AL161452.10.5076316.86E-26positive
METTL3AL008729.10.5064379.31E-26positive
METTL3KDM4A-AS10.5045391.51E-25positive
METTL3AL157392.30.5039741.74E-25positive
METTL3AL031670.10.50361.92E-25positive
METTL3AC074117.10.5013113.41E-25positive
METTL3AC037459.20.5010773.62E-25positive
METTL3AC073575.20.5009373.75E-25positive
METTL3C2orf49-DT0.5006324.04E-25positive
METTL3MED8-AS10.5002744.42E-25positive
METTL16STARD7-AS10.5650256.27E-33positive
METTL16AC020915.10.5008633.82E-25positive
METTL14FGD5-AS10.5341675.61E-29positive
METTL14EBLN3P0.5216621.73E-27positive
LRPPRCAC005288.10.5664614.01E-33positive
LRPPRCAC092614.10.5447492.75E-30positive
LRPPRCMCM3AP-AS10.5379381.94E-29positive
LRPPRCHCG180.5323179.40E-29positive
LRPPRCAL133243.20.515379.20E-27positive
LRPPRCAC016747.10.508765.14E-26positive
LRPPRCFGD5-AS10.50649.40E-26positive
LRPPRCSNHG160.5036411.90E-25positive
LRPPRCAC099850.30.500474.21E-25positive
HNRNPCHCG180.6278552.14E-42positive
HNRNPCAC091057.10.5851519.72E-36positive
HNRNPCSNHG10.5644017.61E-33positive
HNRNPCAC099850.30.5595513.38E-32positive
HNRNPCLINC009090.5542891.66E-31positive
HNRNPCAC007406.40.5399361.10E-29positive
HNRNPCAC005288.10.5295792.01E-28positive
HNRNPCLINC002050.5269934.08E-28positive
HNRNPCMCM3AP-AS10.5265084.66E-28positive
HNRNPCNRAV0.5258975.50E-28positive
HNRNPCTRAF3IP2-AS10.5120552.19E-26positive
HNRNPCLINC006410.5070417.98E-26positive
HNRNPCAL078644.10.5026162.46E-25positive
HNRNPCPTOV1-AS10.5024592.55E-25positive
HNRNPCAC093227.10.5008133.86E-25positive
HNRNPCWARS2-AS10.5006544.02E-25positive
HNRNPA2B1AC091057.10.6971741.01E-55positive
HNRNPA2B1AC099850.30.6416938.77E-45positive
HNRNPA2B1MCM3AP-AS10.6107441.32E-39positive
HNRNPA2B1TRAF3IP2-AS10.58182.94E-35positive
HNRNPA2B1LINC002050.5760771.90E-34positive
HNRNPA2B1AL355488.10.5715138.18E-34positive
HNRNPA2B1PTOV1-AS10.5678642.59E-33positive
HNRNPA2B1LINC009090.5655235.37E-33positive
HNRNPA2B1ZNF32-AS20.5617681.71E-32positive
HNRNPA2B1C2orf49-DT0.5592123.74E-32positive
HNRNPA2B1AC005288.10.5586614.43E-32positive
HNRNPA2B1AC007406.40.558554.58E-32positive
HNRNPA2B1HCG180.5584524.72E-32positive
HNRNPA2B1NCK1-DT0.5540351.79E-31positive
HNRNPA2B1AC018690.10.5478971.10E-30positive
HNRNPA2B1WARS2-AS10.5390571.41E-29positive
HNRNPA2B1LENG8-AS10.5354553.91E-29positive
HNRNPA2B1AC025176.10.532329.39E-29positive
HNRNPA2B1LINC006300.5309911.36E-28positive
HNRNPA2B1TMCO1-AS10.5292892.17E-28positive
HNRNPA2B1SNHG210.5273443.71E-28positive
HNRNPA2B1WAC-AS10.5268614.23E-28positive
HNRNPA2B1AL050341.20.5267714.33E-28positive
HNRNPA2B1SNHG10.5267284.39E-28positive
HNRNPA2B1FAM111A-DT0.525725.77E-28positive
HNRNPA2B1RNF216P10.5213571.88E-27positive
HNRNPA2B1AC125257.10.5206962.24E-27positive
HNRNPA2B1AC102953.20.5202712.51E-27positive
HNRNPA2B1SNHG40.5171785.71E-27positive
HNRNPA2B1CAPN10-DT0.5166756.52E-27positive
HNRNPA2B1AL031714.10.5162857.23E-27positive
HNRNPA2B1DDX11-AS10.515628.62E-27positive
HNRNPA2B1AC093227.10.5146621.11E-26positive
HNRNPA2B1AC012467.20.5139891.32E-26positive
HNRNPA2B1THAP9-AS10.5125631.92E-26positive
HNRNPA2B1ADNP-AS10.511722.39E-26positive
HNRNPA2B1LINC002940.51122.73E-26positive
HNRNPA2B1PTOV1-AS20.5101873.55E-26positive
HNRNPA2B1UBE2Q1-AS10.5084055.63E-26positive
HNRNPA2B1DLEU20.507227.63E-26positive
HNRNPA2B1AC073842.20.5067198.67E-26positive
HNRNPA2B1AP005136.30.5060531.03E-25positive
HNRNPA2B1AL031985.30.5048221.41E-25positive
HNRNPA2B1AC092910.30.5009863.70E-25positive
FTOAC005288.10.5360763.28E-29positive
FMR1FMR1-IT10.5532392.27E-31positive
Figure 1

Sankey diagram of m6A and lncRNA. All m6A genes are shown above, and all m6a-related lncRNAs in HCC are shown below. The line indicates that there is the correlation between the two.

Co-expression of m6A and lncRNA. Sankey diagram of m6A and lncRNA. All m6A genes are shown above, and all m6a-related lncRNAs in HCC are shown below. The line indicates that there is the correlation between the two. Cox regression analysis was performed on the m6A-related lncRNA on HCC, and the results were shown in Figure 2. Univariate Cox regression analysis of m6A-related lncRNAs showed that the HR of AL031985.3 was 3.383 [1.931, 5.930], and the HR of NRAV was 2.468, [1.672, 3.697]. After univariate Cox regression-related lncRNAs were incorporated into the prognostic model and optimized, the included lncRNAs were NRAV and AL031985.3. The correlation between m6A-related genes and two lncRNAs was shown in Figure 3. ZC3H13 had no correlation with the two lncRNAs, FMR1 had no correlation with AL031985.3, and was negatively correlated with NRAV. IGFBP1 and IGFBP2 were negatively correlated with the two lncRNAs, while the remaining genes showed positive correlations. The risk score of HCC prognosis constructed by m6A-related lncRNA was: Risk score = 0.706559118591986∗ NRAV+ 0.766983203593444∗ AL031985.3.
Figure 2

a: COX regression analysis was performed on the influence of m6A-related lncRNAs on HCC. b: Lasso regression of m6A-related lncRNAs. c: Cross-validation results of prediction models.

Figure 3

Heatmap of correlations between lncRNAs (NRAV, AL031985.3) and m6A-related genes in HCC. Among the m6A-related genes, blue represents “writers”, green represents “Reader”, and red represents “erasers”. In the correlation heatmap, red represents a positive correlation between lncRNAs and m6A-related genes, and blue represents a negative correlation. The darker the color, the stronger the correlation. “∗” means Pvalue<0.05, “∗∗” means Pvalue<0.01, “∗∗∗” means Pvalue<0.001.

a: COX regression analysis was performed on the influence of m6A-related lncRNAs on HCC. b: Lasso regression of m6A-related lncRNAs. c: Cross-validation results of prediction models. Heatmap of correlations between lncRNAs (NRAV, AL031985.3) and m6A-related genes in HCC. Among the m6A-related genes, blue represents “writers”, green represents “Reader”, and red represents “erasers”. In the correlation heatmap, red represents a positive correlation between lncRNAs and m6A-related genes, and blue represents a negative correlation. The darker the color, the stronger the correlation. “∗” means Pvalue<0.05, “∗∗” means Pvalue<0.01, “∗∗∗” means Pvalue<0.001. In the survival curves of all sample group, training group and text group, the overall survival time of the low-risk group was longer than that of the high-risk group, as shown in Figure 4. The risk curve of the prediction model can be seen in Figure 5. No matter in the whole sample group, training group, or text group, with the increase in risk score, the death of patients increased, and the expression of NRAV and AL031985.3 increased.
Figure 4

a: the survival curve of the whole sample group, b: the survival curve of the training group, c: the survival curve of the text group. The high-risk group and the low-risk group are divided by the median value of the risk score, with red representing the survival curve of the high-risk group and blue representing the survival curve of the low-risk group. Among the three groups, the high-risk group had a worse prognosis than the low-risk group.

Figure 5

The risk curve of the three groups. In Figures 5a, (1) and (2) are the same in abscissa. They are the samples arranged according to the risk score from small to large, and the ordinate is the risk score of the samples. The patient risk score increases from left to right, with the median risk score dividing patients into high-risk (red) and low-risk (blue) groups. (2) The far point in red represents the death of the patient, the blue represents the survival of the patient, and the ordinate represents the survival time of the patient. As the patient's risk score increases, the number of patients who died increases. (3) Red represents the high expression of lncRNA, and blue represents low expression. In the high-risk group, both NRAV and AL031985.3 were highly expressed. The same trend as Figure 5a can be seen in Figure 5b and Figure 5c. As the risk score increased, the number of deaths increased, and NRAV and AL031985.3 were highly expressed in the high-risk group.

a: the survival curve of the whole sample group, b: the survival curve of the training group, c: the survival curve of the text group. The high-risk group and the low-risk group are divided by the median value of the risk score, with red representing the survival curve of the high-risk group and blue representing the survival curve of the low-risk group. Among the three groups, the high-risk group had a worse prognosis than the low-risk group. The risk curve of the three groups. In Figures 5a, (1) and (2) are the same in abscissa. They are the samples arranged according to the risk score from small to large, and the ordinate is the risk score of the samples. The patient risk score increases from left to right, with the median risk score dividing patients into high-risk (red) and low-risk (blue) groups. (2) The far point in red represents the death of the patient, the blue represents the survival of the patient, and the ordinate represents the survival time of the patient. As the patient's risk score increases, the number of patients who died increases. (3) Red represents the high expression of lncRNA, and blue represents low expression. In the high-risk group, both NRAV and AL031985.3 were highly expressed. The same trend as Figure 5a can be seen in Figure 5b and Figure 5c. As the risk score increased, the number of deaths increased, and NRAV and AL031985.3 were highly expressed in the high-risk group. In subgroups of age, gender, and tumor stage, overall survival was longer in the low-risk group than in the high-risk group, as shown in Figure 6. The chi-square test of clinical data between groups can be seen in Table 2, Pvalue >0.05 in each group, so there is no difference in age, gender, grade, and stage among all groups.
Figure 6

a: Survival curves of the high-risk and low-risk groups in the age group <60 years, b: Survival curves of the high-risk and low-risk groups in the age group>60 years, c: Survival curves of the high-risk and low-risk groups in the male group, d: Survival curves of the high-risk and low-risk groups in the female group, e: Survival curves of the high-risk and low-risk groups in the stage Ⅰ-Ⅱ group, f: Survival curves of the high-risk and low-risk groups in the stage Ⅲ-Ⅳ group. It can be seen from the above survival curve results of different groups that the risk score has a good predictive effect on the survival of HCC patients of different genders, ages, tumor stages, and grades.

Table 2

The comparison of clinical data between train group and text group.

CovariatesTypeTotalTestTrainPvalue
Age≤65232(62.7%)116(63.04%)116(62.37%)0.9782
Age>65138(37.3%)68(36.96%)70(37.63%)
GenderFEMALE121(32.7%)69(37.5%)52(27.96%)0.065
GenderMALE249(67.3%)115(62.5%)134(72.04%)
GradeG155(14.86%)21(11.41%)34(18.28%)0.3224
GradeG2177(47.84%)91(49.46%)86(46.24%)
GradeG3121(32.7%)61(33.15%)60(32.26%)
GradeG412(3.24%)7(3.8%)5(2.69%)
Gradeunknown5(1.35%)4(2.17%)1(0.54%)
StageStage I171(46.22%)86(46.74%)85(45.7%)0.9747
StageStage II85(22.97%)42(22.83%)43(23.12%)
StageStage III85(22.97%)43(23.37%)42(22.58%)
StageStage IV5(1.35%)3(1.63%)2(1.08%)
Stageunknown24(6.49%)10(5.43%)14(7.53%)
TT1181(48.92%)91(49.46%)90(48.39%)0.7669
TT293(25.14%)44(23.91%)49(26.34%)
TT380(21.62%)42(22.83%)38(20.43%)
TT413(3.51%)5(2.72%)8(4.3%)
Tunknown3(0.81%)2(1.09%)1(0.54%)
MM0266(71.89%)136(73.91%)130(69.89%)1
MM14(1.08%)2(1.09%)2(1.08%)
Munknown100(27.03%)46(25%)54(29.03%)
NN0252(68.11%)124(67.39%)128(68.82%)0.6033
NN14(1.08%)3(1.63%)1(0.54%)
Nunknown114(30.81%)57(30.98%)57(30.65%)
a: Survival curves of the high-risk and low-risk groups in the age group <60 years, b: Survival curves of the high-risk and low-risk groups in the age group>60 years, c: Survival curves of the high-risk and low-risk groups in the male group, d: Survival curves of the high-risk and low-risk groups in the female group, e: Survival curves of the high-risk and low-risk groups in the stage Ⅰ-Ⅱ group, f: Survival curves of the high-risk and low-risk groups in the stage Ⅲ-Ⅳ group. It can be seen from the above survival curve results of different groups that the risk score has a good predictive effect on the survival of HCC patients of different genders, ages, tumor stages, and grades. The comparison of clinical data between train group and text group. In univariate analysis, Hazard ratio (HR) of the risk score was 1.573, 95%IC [1.375,1.8], P < 0.001, and in multivariate analysis, HR of the risk score was 1.466, 95%IC: [1.272,1.169], P < 0.001. Univariate and multivariate analyses of the risk score showed that the risk score was an independent predictor of HCC prognosis (Figure 7).
Figure 7

Independent prognostic analysis of risk scores. a: In univariate analysis, Hazard ratio (HR) of the prediction model was 1.573, 95%IC [1.375,1.8], P < 0.001. b: In multivariate analysis, HR of the prediction model was 1.466, 95%IC: [1.272,1.169], P < 0.001. Therefore, the risk score is an independent predictor of prognosis in HCC patients.

Independent prognostic analysis of risk scores. a: In univariate analysis, Hazard ratio (HR) of the prediction model was 1.573, 95%IC [1.375,1.8], P < 0.001. b: In multivariate analysis, HR of the prediction model was 1.466, 95%IC: [1.272,1.169], P < 0.001. Therefore, the risk score is an independent predictor of prognosis in HCC patients. The areas under the ROC curve for predicting 1-year, 3-year, and 5-year survival of patients with HCC by risk score were 0.727, 0.686, and 0.678, respectively. This shows that the risk score we constructed has a better prediction effect on the survival of HCC patients. To further verify the prediction effect of the risk score, we compared the prediction effect of the risk score with age, gender, tumor stage, and grade. The results showed that the area under the ROC curve of the risk score was 0.727, which was significantly better than age, sex, tumor stage, and grade. Besides that, the C-index of risk score was also significantly better than age, sex, tumor stage, and grade (Figure 8). The above results indicate that risk score can be used as an effective method for prognosis prediction of HCC patients.
Figure 8

a: The area under the ROC curve of 1 year, 3 years, and 5 years. The area under the ROC curve of the risk score for predicting 1-year survival of HCC patients was 0.727, that for predicting 3-year survival was 0.686, and that for predicting 5-year survival was 0.678. b: The area under the ROC curve of the risk score, age, gender, grade, and stage, c: The C-index curve of risk score, age, gender, grade, and stage. As can be seen from Figure 8b and Figure 8c, the risk score can better predict the prognosis of HCC patients.

a: The area under the ROC curve of 1 year, 3 years, and 5 years. The area under the ROC curve of the risk score for predicting 1-year survival of HCC patients was 0.727, that for predicting 3-year survival was 0.686, and that for predicting 5-year survival was 0.678. b: The area under the ROC curve of the risk score, age, gender, grade, and stage, c: The C-index curve of risk score, age, gender, grade, and stage. As can be seen from Figure 8b and Figure 8c, the risk score can better predict the prognosis of HCC patients. Based on the risk score constructed by lncRNAs, we drew the nomogram (Figure 9a). We took the 15th sample as an example. The patient had a total score of 396 for all items, and the probability of survival over 1 year was 82%, the probability of survival over 3 years was 66.2%, and the probability of survival over 5 years was 55.9%. The results of the correction curve of the nomogram also showed that the nomogram had a better prediction effect on the 1-, 3-, and 5-year survival rates of HCC patients (Figure 9b).
Figure 9

a: The nomogram of the risk score. We take the 15th sample as an example, with a total score of 396 points for each item. Therefore, the probability of his survival over 1 year is 82%, the probability of his survival over 3 years is 66.2%, and the probability of his survival over 5 years is 55.9%. b: Calibration curves for risk scores predicting patients at 1, 3, and 5 years.

a: The nomogram of the risk score. We take the 15th sample as an example, with a total score of 396 points for each item. Therefore, the probability of his survival over 1 year is 82%, the probability of his survival over 3 years is 66.2%, and the probability of his survival over 5 years is 55.9%. b: Calibration curves for risk scores predicting patients at 1, 3, and 5 years. Principal component analysis (PCA) was performed on the whole gene, m6A genes, m6A-related lncRNAs, and lncRNAs used for risk scores construction, respectively, as shown in Figure 10. The results showed that compared with m6A genes, m6A-related lncRNAs, and other genes, the lncRNAs used for risk score construction had the best discrimination between high-risk group and low-risk group samples. This means that the lncRNAs used to construct the risk score can well distinguish samples from the high-risk group and the low-risk group.
Figure 10

a: PCA of the whole gene, b: PCA of m6A genes, c: PCA of m6A-related lncRNAs, d: PCA of lncRNAs used for risk scores construction. The results showed that compared with m6A genes, m6A-related lncRNAs, and other genes, the lncRNAs used for risk score construction had the best discrimination between high-risk group and low-risk group samples. This means that the lncRNAs used to construct the risk score can well distinguish samples from the high-risk group and the low-risk group.

a: PCA of the whole gene, b: PCA of m6A genes, c: PCA of m6A-related lncRNAs, d: PCA of lncRNAs used for risk scores construction. The results showed that compared with m6A genes, m6A-related lncRNAs, and other genes, the lncRNAs used for risk score construction had the best discrimination between high-risk group and low-risk group samples. This means that the lncRNAs used to construct the risk score can well distinguish samples from the high-risk group and the low-risk group. Genes that differ between high-risk and low-risk groups were shown in Table 3. Differential genes were highly expressed in the high-risk group (Figure 11a). The GO enrichment analysis of the differential genes showed that the differential genes were mainly located in the extracellular matrix and chromosomal regions, and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation of cells (Figure 11b).
Table 3

Genes that differ between high-risk and low-risk groups.

genelowMeanhighMeanlogFCpValuefdr
SOGA10.7624413851.8247783881.2590229294.72E-231.93E-21
CYS10.2780460912.0539216392.884985180.0338875370.0408347
CTNND20.5771508073.064004252.4083980551.86E-074.03E-07
C4orf482.3101281955.1559300011.1582597640.000103960.0001662
SOX124.0845225328.3484461341.0313402571.47E-151.01E-14
AL662795.20.7483580711.5654147011.0647442646.32E-175.75E-16
FTCD115.97625554.82683524-1.080875351.10E-191.81E-18
RHOV0.1464167312.7469316044.2296686671.41E-115.17E-11
CDCA81.9596288196.025579721.6205196363.72E-253.14E-23
CYP4F239.1031269718.70670726-1.063728341.73E-151.18E-14
NPTX22.1920383038.3321438971.9264147476.22E-050.0001019
OLFML32.4449229066.7302619521.4608736831.82E-063.55E-06
AC137723.11.6252618970.633187447-1.359967661.47E-104.68E-10
RNF1571.5971507983.2411971331.0210262351.96E-074.24E-07
RMI21.8635546983.7616352961.0133028161.82E-161.49E-15
RHNO13.2210343486.5077919671.0146440892.18E-274.63E-25
IFT571.4348895363.0457375011.0858519316.87E-133.02E-12
DYRK21.2425839612.5799938871.054024313.39E-231.45E-21
IL2RG4.70685718410.813683131.2000220022.51E-064.82E-06
AP000769.10.9091002272.1724400521.2568051036.69E-101.95E-09
SCRN10.9103065293.7048604972.0249948881.23E-103.95E-10
CD2425.2422919471.667169961.5054694769.37E-144.73E-13
CSGALNACT10.8419903822.0075206581.2535391750.0027541240.0037626
FZD70.4750869591.8687921661.9758426212.95E-141.62E-13
CSPP11.3109489332.818570421.1043521251.15E-146.76E-14
PPP1R14D0.7133026081.7997138891.3351814184.72E-079.79E-07
FAM133A0.6089623321.7428055461.5169867121.77E-063.45E-06
SOX95.21290591115.203058521.5442018661.09E-124.68E-12
MRC21.5450810714.0856466271.402881898.57E-050.0001382
CD443.5647275898.4932843041.2525307111.77E-053.07E-05
TUBA1A5.8265602111.922011921.0329113961.03E-051.84E-05
SPATS21.6587614673.8116848591.2003224063.07E-349.14E-31
CXCL50.3675174066.7728400974.203876451.71E-094.74E-09
P3H42.4661471735.804618291.2349423011.13E-157.96E-15
BACE21.6505509367.9865194492.2746192483.95E-089.24E-08
ANKRD10-IT11.490815843.096105231.0543524543.62E-111.26E-10
ABCC11.0611736673.8439102471.856913875.95E-186.73E-17
CYP4A1199.7399304543.74599058-1.18902047.55E-188.26E-17
IDO10.8078928251.626693821.0097069060.0124290870.0158238
RHPN11.135369932.7780939431.2909329491.94E-117.01E-11
PDCD10.6549825521.9665244441.5861197381.11E-051.97E-05
CFTR0.2317591523.999784524.1092240616.93E-050.000113
NDC801.4212018343.5217095581.3091644771.97E-171.98E-16
CRYAB4.81703841111.362797221.2380996990.0170374260.0213031
IER5L2.2340437395.442356591.2845740551.57E-126.59E-12
CYP2C8141.83332357.30456804-1.307474477.27E-122.77E-11
SPRED10.9316324712.3616910861.341987441.33E-181.74E-17
CBX20.5097336281.6636128381.7065042871.58E-161.31E-15
EPO0.9882297824.9754800872.3319172998.62E-112.83E-10
PITX10.6544837752.9060789472.1506445636.62E-122.53E-11
ALOX51.0945135113.419699851.643579941.02E-092.91E-09
MCUB0.7322853091.8416488231.3305202271.52E-104.82E-10
ANG369.2250878177.8023201-1.054226434.14E-173.87E-16
MUC1327.4007478256.087004441.0334512640.0016107150.0022677
FXYD21.9128915717.2831015641.9287978659.30E-061.67E-05
AC009005.10.927488761.9063861831.0394386972.24E-118.00E-11
COL1A214.9065590538.588120171.3722094928.31E-061.50E-05
AC016885.30.7417048921.6677763841.1690086750.0042627250.0057043
PLXNA30.8764525652.0274891361.2099462681.43E-148.30E-14
MMP72.72788594113.346293892.2905839492.27E-064.37E-06
CXCL84.10953197611.953280471.5403606044.06E-089.48E-08
TTC220.9082016361.8630234121.0365612642.19E-106.81E-10
TINAG1.6193766243.3795654511.0613991970.0012559140.0017894
NAA401.50471363.3234700031.1432014151.23E-301.04E-27
ZDHHC10.9452125212.147307521.1838181710.0009070240.0013155
ANTXR11.5044069273.1637002351.0724180540.0011122160.0015963
NBL11.2143680753.3527367911.4651334590.0002758580.0004226
NCEH11.0485806744.7616770622.1830319182.95E-162.30E-15
CRYBB10.2924420194.4678513663.9333586697.81E-050.0001265
BCL9L1.492577113.1240014581.0655896613.02E-121.22E-11
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DES0.4655745832.3257496732.320611620.0295461290.0358467
GP21.2949400264.2819251621.7253742980.0260333560.0318055
IGSF2317.626093136.446796873-1.45105832.01E-151.35E-14
FMNL11.1016977542.2514100131.0311003341.43E-094.01E-09
TYMS5.9165298612.021181581.0227555431.13E-146.68E-14
MAGEA121.5234005034.7009228991.6256487420.000703020.0010318
ATP1B37.88134723417.073288731.1152268142.02E-182.51E-17
FBXL191.4130481452.9520276171.0628955975.61E-292.47E-26
NCDN2.0960888984.6148179381.1385738288.51E-305.17E-27
CYP4A2228.2082388610.86706028-1.376154884.81E-185.54E-17
NXPH41.5096348835.1752574321.7774309642.23E-141.25E-13
SLC25A240.4923584431.6945074111.7830850441.19E-125.11E-12
RRM24.0360276818.8076634351.1258232717.88E-188.56E-17
CTSV0.3127962282.6034132333.0571093032.24E-161.80E-15
FIBIN0.782504992.1111555551.4318610276.01E-059.85E-05
MDFI0.7912182712.4689649931.6417587340.0004087930.0006149
PAEP2.0002258621.182950823.4046687531.78E-084.35E-08
SULF11.0525638523.3733772971.6802859311.82E-084.45E-08
CPNE70.6114336421.7704284511.5338307010.0003598480.0005447
HJURP1.2634832563.6166221011.5172363142.85E-228.77E-21
SLC41A11.5210601083.4305535611.1733642262.30E-161.83E-15
SFRP50.92672700614.674911473.9850635760.0016472890.0023151
TMC61.5566044924.1457183211.4132196715.56E-101.64E-09
AC136601.22.0444841060.956327002-1.096160933.21E-087.60E-08
PCK1132.985851559.95370077-1.149352054.78E-163.59E-15
NDN2.6049704367.0918167951.4448882680.004535860.0060466
AC006329.13.8243796031.701556959-1.168370283.47E-141.88E-13
CLDN44.69804723414.425513281.618489538.52E-092.17E-08
KRT800.2586427982.6773505733.3717731341.65E-084.04E-08
CDCA7L0.8906312312.7076239111.6041272541.02E-181.36E-17
LINC0155428.873536259.929266032-1.539988833.54E-088.32E-08
PDE4A0.8401838291.8267351361.1204905453.24E-087.66E-08
PCLAF1.5235159643.9835112581.3866360351.37E-213.60E-20
CYP2A133.9434990940.583964867-2.755522831.68E-138.14E-13
ARHGEF250.7070962351.4656384821.0515508050.0201449530.0249499
MT1E166.833302249.87607975-1.741987320.0029818260.0040573
RCAN30.70052721.498968031.097456647.11E-187.85E-17
KIF20A1.5308179944.5337254991.566394285.15E-221.49E-20
FOXJ10.3569837042.5713920362.8486194585.00E-132.25E-12
LINC009420.4969915532.7322259452.4587835589.20E-102.63E-09
MMP10.4124513253.71611843.1715006924.00E-101.20E-09
LINC0101815.346341617.613101589-1.011338541.00E-082.52E-08
DCLRE1B0.95353691.9246509211.013236131.52E-262.41E-24
RACGAP12.2092639365.3525819791.2766692023.04E-231.33E-21
GPD1L1.1718345792.7001982231.2042963932.66E-151.75E-14
MAGEA33.5554339088.365298441.2343913733.78E-056.35E-05
SLCO3A10.9740199482.014183211.0481716922.16E-053.72E-05
PLPP21.6775115916.265930441.9012060192.15E-085.22E-08
LAMC20.2361781353.0935143263.7112993996.11E-050.0001001
PLCD30.5463866521.9756465561.8543307261.31E-136.48E-13
TES3.7504835697.9410263071.0822488531.26E-171.32E-16
SH3RF11.5531393943.3764837811.120334312.50E-118.89E-11
EPS8L33.3926166518.233319381.2790757693.32E-101.01E-09
AC011591.11.8900948030.874295948-1.112264981.35E-062.66E-06
TMPRSS30.9801308582.9119921231.570960171.00E-072.25E-07
GRAMD1B0.6101732151.5509326381.345845271.04E-082.62E-08
PTPRS1.0482863822.3893813311.1886042160.0108834690.0139351
UBE2C6.92710867220.734630991.581717166.99E-187.74E-17
CCL280.9359820832.2070168351.2375448162.60E-086.24E-08
MOB3B0.9470412322.0844906591.1381957624.74E-057.88E-05
CXCL61.6747576287.5788777832.1780319192.70E-054.61E-05
AC021146.914.290350415.917827812-1.271901674.68E-142.48E-13
NKD20.6501932051.4456053591.1527333760.0127744430.0162202
BUB10.7643439442.328842431.6073191482.10E-252.03E-23
NUP2105.04961517710.267084421.02378121.65E-225.56E-21
DPYSL31.5595206683.4906088871.1623760440.0003571860.0005411
KIRREL20.0251285062.932198436.8665140042.00E-074.32E-07
CLSTN16.22002474116.465365091.4044422782.25E-193.44E-18
MISP2.120816924.5852670561.1123856761.16E-062.31E-06
HHIPL20.9883398262.2947160561.2152365670.0014298140.0020255
MMP25.27465420113.644902451.371213660.0054375510.0071842
RAD51AP11.0039335962.5832120131.3635022095.10E-221.48E-20
F30.6937870341.7558776661.339627553.62E-099.68E-09
SPDL10.9945129572.096534611.0759445742.14E-239.96E-22
TMEM2011.0885055322.2504481961.0478636154.02E-221.19E-20
RAVER10.9438526482.1695286481.2007480851.21E-158.51E-15
ITGB41.3848609795.9873288372.1121713511.13E-093.21E-09
GPC40.856595422.9625960781.7901760735.41E-071.11E-06
AC079360.12.0225140210.765451872-1.401766136.27E-091.62E-08
CABYR1.4118577912.9312543741.053923398.69E-071.75E-06
RBP20.6460349072.2687967061.8122433180.0002038770.0003164
STK261.4761393893.0510545871.0474790331.25E-125.35E-12
TPM28.23269034516.613354241.0129075150.0005442560.000808
HSD17B1371.2307627933.13393212-1.104191021.03E-051.84E-05
ARMCX10.9846017742.472522481.3283713947.08E-071.44E-06
APOA5153.216751965.87362752-1.217801141.19E-191.94E-18
ROBO14.405809329.3602469351.0871395331.77E-094.89E-09
FOXM12.0838117886.0288958471.5326688282.75E-228.49E-21
VANGL10.8370542771.718645521.0378789323.77E-231.59E-21
LINC002210.6638333771.6007208461.2698286610.0007606510.0011127
KIF4A1.3807608994.3456250121.6541001731.74E-238.35E-22
FCGR2A1.561017623.3356769261.0954927437.98E-112.64E-10
CA91.28215016923.453365914.1931578361.81E-238.65E-22
CENPM2.4791749136.1387588271.3080869316.40E-201.11E-18
TNFAIP28.00325584816.927470111.0807074361.63E-084.01E-08
NMB3.1545121796.9615751321.1419968479.81E-113.20E-10
RTL8B1.0204303382.4332941221.2537330190.0001278460.0002026
WNK20.4007544932.4420227622.6072860489.21E-102.63E-09
C2CD4A0.761558482.8332718581.8954423071.66E-073.63E-07
RAB251.959693676.8097451341.7969726470.0401435660.0479457
FLNA11.7248001633.157603931.4997764245.30E-091.38E-08
KRT238.64509313619.66949811.1860067340.01027280.013193
FNDC514.712270594.727985832-1.63772235.88E-091.53E-08
FAM117B0.6434343031.8089570381.4912933873.11E-229.39E-21
LAMC112.6003657825.468003271.015220244.66E-152.92E-14
CLIP21.7286410854.444935391.3625240931.30E-147.62E-14
ANLN1.0476924433.690848611.8167372961.14E-251.24E-23
IMPDH12.1112849296.5872991581.6415657796.03E-164.42E-15
MAGEC23.1563605837.2078338341.1913037240.0188795870.0234805
SEL1L32.3167294629.6400883512.0569567875.28E-122.05E-11
MXRA50.5027597641.576509621.6487928730.0081769290.010609
TNFRSF11B1.7103861954.8274790911.4969478979.02E-071.81E-06
CXCL12.94965076815.059145312.3520238332.90E-086.89E-08
TMC50.5978039313.2385036142.4375830661.62E-094.51E-09
PKM7.98478981344.226280612.4695775816.18E-254.83E-23
AC010547.20.2367805752.1220334023.1638247294.82E-058.00E-05
ANXA2P21.5284439453.3097473721.114657461.85E-141.05E-13
PAPLN0.9315739183.5656894691.9364389135.63E-101.66E-09
CYP8B197.7536297937.21709778-1.393184724.63E-142.46E-13
HPR251.3515068109.4280816-1.199723331.02E-168.77E-16
CYBA13.5971398327.965025921.0403204572.44E-075.23E-07
OSBPL30.7159503171.7266750221.2700651982.33E-172.29E-16
CHGA0.2877079164.1547553523.8520867050.0184916210.0230269
PRSS20.53887675515.947769854.8872555250.0003632680.0005496
BCL92.3194508684.8071106841.0513867362.76E-194.15E-18
LINGO11.1786759232.4220296411.0390494171.30E-052.29E-05
GSTP112.888445435.156017861.4476934080.0048641410.0064603
LHFPL21.0506983042.5398858071.273415162.92E-151.91E-14
RASEF0.9001764542.2960957581.3509030761.99E-053.45E-05
PLTP8.82920105923.223715121.3952439784.57E-068.50E-06
WDR541.0079017892.3421298971.2164660231.13E-157.96E-15
EPCAM13.3368158631.06872551.2200487940.0004431770.0006641
BAMBI11.0292323.365796711.0830661573.82E-121.52E-11
B4GALT56.85994831313.84831721.0134410647.79E-201.33E-18
GLYATL119.542999347.936262886-1.300120182.94E-194.36E-18
H2AC70.6675139861.3735324881.0410210641.05E-062.09E-06
CTH39.3507040719.42141986-1.018740779.40E-082.11E-07
IL2RB1.0923828082.2457217721.0397006860.0004327490.0006495
IGHV4-398.35114260738.187028142.1930371420.0043212980.0057774
FMOD3.081785886.4098169961.056516540.001219760.0017408
ARHGEF22.1540374064.8633026121.1748930617.94E-188.62E-17
MICAL11.5367310733.2586350831.0844030851.57E-115.73E-11
MAGEA62.7996554046.8478951391.2904113463.12E-065.91E-06
SAA11663.310761770.2018143-1.110749310.0011991470.0017136
POSTN2.1782086686.684800261.6177422851.58E-073.45E-07
AC007423.14.2453024451.704951015-1.316137050.0099429720.0127943
LAD115.710489133.345008341.0857427146.97E-050.0001135
COLCA20.8143941392.4194320751.5708693532.28E-131.08E-12
RDH1659.9416692225.58666655-1.228167061.38E-115.09E-11
SH3YL10.8107117011.7301029871.0935970480.0205131480.0253742
TC2N1.1239586543.0059535061.4192337291.64E-063.20E-06
FBLN13.6341280512.142675681.7404051990.0001309130.0002071
C4orf460.6670254781.4977363141.1669698762.66E-301.86E-27
FCGR3A7.27374911115.064103161.0503437154.83E-068.96E-06
H2AW1.7956353764.3874021851.2888725378.14E-092.08E-08
ATP1A146.6862051103.10684411.1430718722.02E-172.02E-16
ELOVL70.9736825314.0642931952.0614811171.54E-104.90E-10
ABCC41.1874052932.4998394981.0740230211.35E-093.79E-09
YBX32.6044032575.4296758631.0599132282.30E-053.95E-05
CCDC9B0.8182739852.1349119241.3835206611.51E-062.98E-06
PLEKHB23.753368488.0936957361.1086126842.12E-226.82E-21
GINS11.268355613.7634570571.5690992187.62E-244.17E-22
CTHRC12.4140516977.6893716551.671409141.18E-103.81E-10
KEL0.2517614522.0676503333.0378629180.0013053370.0018569
AC022784.10.6224741811.4501360151.2201023210.0015655470.0022082
PLCB10.7170443231.4849631031.0502928814.95E-132.23E-12
PTPRC1.3617914842.9612875951.1207187938.85E-050.0001425
SMIM100.629780461.5810258731.3279400768.96E-050.0001442
LAIR10.9840545852.0531343741.0610178042.98E-087.07E-08
GPRIN10.5869280241.5699336521.4194480913.59E-231.52E-21
CDC70.741943612.0327285131.4540360991.08E-235.52E-22
CTAG22.7998595419.5024218681.7629408040.0002252770.0003479
KIF111.0451919442.9347677751.4894784391.19E-248.53E-23
E2F31.7434411333.9874264331.1935202493.40E-276.75E-25
CPVL5.12704270310.768076621.0705617616.80E-061.24E-05
WIPF11.497658213.0413803191.0220178192.64E-075.62E-07
TACSTD20.9537109124.9256052812.3686770910.0399600320.0477315
ZSWIM40.8813264342.0378828381.2093227283.91E-162.98E-15
NAALADL11.1183253442.5833653811.2079117480.0005268340.0007837
HES42.2193229475.0552872971.1876734664.31E-081.00E-07
NCK24.36611316911.940828571.4514815189.68E-113.16E-10
RAB311.7407455913.6811189361.0804389947.21E-091.85E-08
MUC201.4137449593.6342061231.3621183680.0122258050.0155783
MUC61.9071072716.7040862441.8136547140.0071447510.0093289
PNMA50.4825971892.1236329122.1376429890.0125506770.0159683
MAMLD10.9174663121.8984120171.0490660480.0001722130.000269
CCNB15.43433310713.713174931.3353877235.11E-211.16E-19
MPZL16.78925327613.89405441.033142846.42E-271.16E-24
MAB21L20.4262172291.8375527572.1081248550.0005524250.0008195
SINHCAF1.2362505553.4716537391.4896518927.95E-177.07E-16
FANCD20.5675751611.4959825761.3982100141.14E-224.01E-21
LINC025061.4966561973.1058030531.0532234950.0056507160.0074518
B3GNT90.6364200461.7844709771.4874452539.91E-155.93E-14
SLC12A21.3944711383.1887031581.1932517262.20E-085.33E-08
LINC023623.3580754621.561193037-1.104985723.27E-098.80E-09
ADCY11.7482041120.795043258-1.136768372.92E-054.96E-05
HENMT10.7521115431.5875074191.077744795.58E-059.19E-05
LCAT22.5070893310.8917337-1.047145881.67E-116.06E-11
YEATS21.0964019262.3694976151.111804442.45E-323.65E-29
STX32.379241095.6262758611.2416788221.42E-192.26E-18
PSRC11.1949100532.856822361.2575093082.15E-193.32E-18
TMED31.2925602312.7593782821.094111745.01E-101.49E-09
NEK21.6745951724.3189243131.3668596633.59E-206.55E-19
LRRC11.5231379683.3557266481.1395785727.45E-176.68E-16
MLLT111.1048797832.3522145171.0901302320.0001702160.000266
NCF22.5956531995.6593457681.1245376442.06E-106.42E-10
ADAP10.6167164721.4442276261.227618866.65E-061.21E-05
GPRC5B1.8332023883.947504361.1065747890.0003889440.0005868
GRB72.8400679866.428647611.1785898054.34E-081.01E-07
NDST1-AS11.7253190530.669094058-1.366582246.41E-061.17E-05
SLC7A53.2791344557.0010727041.0942609311.31E-083.25E-08
NDUFA4L25.70225811616.265850421.5122410028.28E-081.87E-07
MLANA0.0995998432.10718944.4030327150.0011275750.0016172
COMP0.5333163931.8773552461.8156380930.0009927770.0014337
EGLN30.6274885592.6248029252.0645480472.74E-121.11E-11
AGRN10.673650824.006242891.1693559143.55E-162.72E-15
PRR15L3.3947859748.3420616061.2970833451.77E-053.09E-05
PKMYT10.811716931.9165723621.239479861.07E-202.26E-19
MFSD61.3463861512.941008961.1272189371.27E-093.59E-09
G6PC206.861504791.6913541-1.173807596.21E-187.00E-17
C15orf482.9919418138.313047921.474295414.79E-101.43E-09
CDR2L0.9459596032.9325990221.6323293448.16E-050.0001319
RAD510.7129024041.7308228121.2796815481.55E-203.13E-19
MARVELD11.793159353.6939600551.0426645664.47E-068.31E-06
TUSC31.2261484743.8274375051.6422451366.60E-071.35E-06
UAP1L10.6736832193.3131722032.2980709212.21E-151.47E-14
CTSE0.6346663953.18065482.3252534437.12E-050.000116
FGFR10.6237705252.1479814621.7838942552.69E-054.59E-05
SPC251.1461179572.7489888491.2621455222.16E-204.15E-19
CAD2.8692952975.7684524891.0074878852.93E-231.29E-21
CYP1B13.8159622198.3649535031.1323106331.40E-052.47E-05
ASRGL10.990023632.4917457671.3316220121.16E-146.86E-14
TEAD24.18045450311.26959791.4307043342.53E-193.81E-18
TMEM74B1.2564657663.0727648651.2901660091.26E-072.79E-07
ASAP12.0773553914.6887272341.1744483015.83E-198.17E-18
LOX0.9217274272.8395648361.6232577677.79E-143.97E-13
RHBDF22.3816438714.8206027061.0172558322.86E-151.87E-14
PAQR41.5626905573.9217939951.327481631.53E-203.09E-19
COL1A129.1564271274.178118961.3471797444.86E-069.00E-06
TRIM476.97443007314.461145951.0520346461.50E-137.33E-13
FERMT10.628575881.4481591021.2040612945.98E-101.75E-09
LGALS93.7004003327.5882805831.0360916661.38E-073.05E-07
RGS24.73210556216.640245421.8141225496.17E-122.37E-11
ANO114.275140566.395939747-1.15827675.48E-071.13E-06
LRIG31.7038883693.6758076371.1092304491.53E-126.42E-12
NCAPG1.1900003763.3725706291.5028866271.45E-213.80E-20
GPNMB5.65956651117.627431061.6390587771.96E-074.24E-07
KIFC12.7200503137.7840914671.5168953258.35E-233.06E-21
RENBP3.65449964610.445661021.5151579935.37E-071.11E-06
KIF230.5418610421.9037201981.8128266221.91E-262.88E-24
SERPINI11.6269821435.0598617981.6368995647.84E-122.98E-11
IFFO21.36130323.0196176931.1493774747.38E-201.26E-18
CMTM41.1531095852.3464188621.0249309482.68E-108.24E-10
AGAP2-AS10.8363225481.9324017961.2082637330.0058067630.0076491
SAA2204.58712388.23878713-1.213230480.0076741730.0099851
HSD17B6222.6620503109.7435786-1.020719161.99E-171.99E-16
TRIP130.8329275062.8765118851.788057595.87E-254.63E-23
B3GNT33.72761457812.102459631.6989756781.14E-062.28E-06
MELK1.3469112663.8548651491.5170255821.49E-237.32E-22
C19orf331.9851118675.3228869161.4229886070.0010783610.0015496
NCAPG21.2363340732.7076116751.1309522123.49E-218.34E-20
SAA2-SAA454.947345922.76048135-1.271518730.0026501260.0036282
VSIG10.4667956941.7971763151.9448687970.0002332070.0003596
EVC0.9013272072.1100085621.2271260094.17E-067.80E-06
SMOX2.4735208816.1974215451.3251020244.21E-163.19E-15
IL4I10.7869994333.0974428261.9766431519.42E-166.71E-15
HS1BP3-IT17.2479611253.619053986-1.001962591.30E-093.66E-09
ADAM171.0313877232.3368826931.1799985371.30E-192.09E-18
KIF125.83051800314.416293511.3060043213.54E-088.32E-08
ZNF3200.5407656571.5992660271.5643345053.21E-131.49E-12
ISYNA15.44870910713.602309771.3198652760.0044808610.0059773
SRPX21.0431195184.0684018251.9635577091.08E-051.92E-05
BSPRY1.1463943032.4489726241.0950733014.45E-057.42E-05
KIRREL10.9417525192.0506547851.1226647510.0001056360.0001688
SCPEP18.14609458918.241187711.1630191972.30E-131.09E-12
NEURL31.1457329174.6343196472.016086785.40E-111.83E-10
POLA11.032629192.0910704451.0179193795.84E-232.28E-21
FANCI1.0547179032.6621575841.3357387898.83E-244.71E-22
TRIM162.1115242994.6412393871.1362252611.69E-105.33E-10
AL162582.12.7594661130.863154397-1.676698622.01E-106.27E-10
UROC116.992714546.651649996-1.353132181.66E-105.24E-10
TGFB17.9678916717.652629291.1476131458.56E-071.73E-06
CORO2A1.3367773092.7976451221.0654538211.29E-093.64E-09
CRYGS0.7197047982.512404031.8035913087.08E-071.44E-06
STMN18.49610509918.889277361.1526939922.88E-194.30E-18
FBLIM13.8010910898.6808702791.1914260852.08E-117.46E-11
HLA-DOA1.892948884.261851171.1708447620.0044808610.0059773
ASPDH33.685044713.46154716-1.323263988.35E-191.14E-17
CDC205.02630341516.601926421.7237809887.66E-222.16E-20
PLA2G72.565511125.626238811.1329245128.68E-050.0001398
OXCT10.9339967812.1223748931.1841900321.19E-062.37E-06
PPP1R186.01157235812.567423431.063874618.22E-177.28E-16
IGHV1-30.2851920231.8094600482.6655537210.0126117280.0160392
PLEKHG21.1597880492.3532083721.0207678966.10E-186.89E-17
GBA312.168147655.822792763-1.063326391.46E-094.08E-09
PAQR51.1352327143.4196582671.5908640922.44E-129.97E-12
IGSF31.141253133.7242904861.7063467875.70E-142.97E-13
CDC451.3659984893.4305903331.3285009671.26E-202.60E-19
AP001065.33.7581973351.524818848-1.301402962.13E-204.12E-19
AC026401.32.1401188714.501246171.0726335353.60E-184.27E-17
CRHBP1.7825354740.758628294-1.23246571.63E-063.19E-06
ADRA2A0.4898875651.5669052831.6773953960.0161563680.0202829
ACSS11.4774641193.1539104391.0940185982.11E-085.11E-08
FAAP240.7550437181.5762181171.0618351031.44E-273.29E-25
IGF2BP11.1624575312.6438763641.1854767043.57E-056.01E-05
RTL60.8705005412.1245993951.2872737394.21E-101.26E-09
TRNP17.15093327516.216088641.1812224331.64E-105.18E-10
ALPI2.9297435386.5412192631.1587851940.0146569660.0184978
PDGFRA0.8911981141.8744555611.0726535380.028287460.0343933
DUSP96.3390034116.24213341.3574131941.84E-053.19E-05
NRM4.26098168110.521484781.3040805577.06E-211.56E-19
PTGDS25.39593323160.27303132.6578622930.0212671790.0262441
FGD60.7714878322.0267934711.393483781.18E-171.24E-16
CHST40.3589240842.8821277433.0053836448.84E-061.59E-05
CARMIL10.7789021172.0461607861.393405571.46E-181.87E-17
FYB10.9095122572.0305532651.1587078861.06E-051.90E-05
TUBA1B17.685602138.752609071.1317181098.94E-233.23E-21
AC004832.51.5196420130.745203306-1.028025521.40E-115.15E-11
OLFM40.0868870585.4886981575.9811788893.00E-065.70E-06
SLC7A10.7342105942.2086290551.5888852972.09E-141.17E-13
SNAP250.5709930763.2216964162.4962753964.63E-121.82E-11
LMNB23.0514580728.2583033651.4363466491.19E-272.82E-25
IFT1400.6801262511.401485771.0430826151.94E-141.09E-13
CHEK10.8209070741.8679536651.1861678453.66E-218.67E-20
PTHLH0.3058607862.2391108492.8719788943.30E-101.00E-09
CLGN2.7304040336.6901871631.2929321211.64E-105.18E-10
ZG164.6964202522.005288251-1.227751886.94E-102.02E-09
ARMCX20.5898729161.591240581.4316758980.0001121520.0001787
SLC34A20.18103052911.211092495.9525500494.66E-068.65E-06
PRSS220.0938959892.0338972694.4370394663.49E-055.89E-05
EMP35.24253460511.557964441.1405509523.63E-077.61E-07
MMP1410.9672752536.335638191.7281801031.95E-151.31E-14
SLC16A31.4243568984.8740284421.7748039857.89E-177.02E-16
PAQR80.9014934982.0947544111.2163921212.85E-108.72E-10
NUSAP15.32355147612.359509141.2151605177.32E-201.25E-18
MYBL24.23983111314.787590231.8023082687.96E-222.23E-20
ATP13A22.475248255.1640719881.0609358884.81E-231.95E-21
ACSM2A30.1109787314.20418415-1.083973631.51E-192.38E-18
TMEM1560.9707161323.5261158831.8609585151.42E-062.79E-06
ADRA2C1.8754305024.1940742561.1611306030.0013144040.0018682
PFN22.2668659077.3630589741.6996062042.24E-085.41E-08
SLC36A10.9255498161.8522850861.0009236143.10E-217.48E-20
KIF2A1.1357614412.4133736771.0873914751.23E-262.03E-24
SLC38A12.1134478556.8549652341.6975508321.14E-169.71E-16
GLS2.6543805435.8421002581.1381119011.48E-151.02E-14
TGFB31.5676220143.3702680081.1042855832.35E-054.04E-05
MAPK131.7233503614.1834234621.2794680067.24E-112.41E-10
CASP21.4136178963.1716342161.1658341869.04E-321.19E-28
ELF40.7041165062.4970686441.8263494134.27E-131.94E-12
TCF193.5584325337.9715458231.1636176322.88E-194.30E-18
SAMSN10.7020235031.4836884041.07959693.17E-076.70E-07
MIR23AHG1.2818772552.8929525371.174284531.28E-062.53E-06
NEMP11.6181122073.4245299421.0815943212.62E-228.18E-21
LINC024285.3236764222.646121573-1.008543540.000464130.0006941
COL4A50.6008160941.5581441361.3748333328.08E-081.83E-07
PCSK1N1.2724549987.6641208712.590505686.40E-050.0001047
ASPM1.230644232.8934693311.2333866031.84E-151.25E-14
MCM313.6135320229.099295941.0959428268.41E-244.54E-22
MAPRE112.2849210525.123390981.0321426161.08E-251.21E-23
AL137798.12.650896511.123724114-1.238192470.0001020660.0001633
TEDC21.2111707782.5906963211.0969376113.81E-173.59E-16
FOLH1B1.512104680.519534122-1.541267619.26E-061.66E-05
DCXR420.4422837176.9769336-1.248346435.52E-164.08E-15
CENPH1.3831193422.8930866431.0646838863.95E-221.17E-20
NTS12.25950821151.60447493.6283393271.02E-051.82E-05
TTC39A0.6155803212.4241573961.9774643567.45E-176.68E-16
MELTF0.7949331052.3229447441.5470494722.99E-098.08E-09
SNHG32.0702337424.6651907131.1721423939.51E-144.79E-13
RAB3IL11.8084743655.0084488241.4695907052.43E-141.35E-13
AACS0.6411249711.4714960191.1986061338.17E-269.72E-24
GSDME0.7413677471.5634709061.0764911161.89E-105.94E-10
DLGAP50.9494604852.9049009671.6133091173.17E-229.52E-21
SLAMF70.9902257482.326816961.2325283570.003058240.004157
TYRO30.4963020741.6964885051.7732612661.19E-161.01E-15
OPN1SW0.9454981941.9566309421.0492250549.37E-178.18E-16
TNFSF13B0.9314552321.9119907281.037517191.22E-052.16E-05
NBEAL21.3898608662.977616031.099217265.07E-197.19E-18
DNER0.252320662.1651432133.1011322121.97E-053.42E-05
IQGAP12.238299445.3976264941.2699220951.78E-141.02E-13
AL035461.21.3777078572.7947915021.0204706629.37E-113.07E-10
AC090204.10.8498134451.9524789211.2000888998.62E-050.000139
DLG30.5269909691.6393868581.6373061934.39E-101.31E-09
PLGLA2.68465611.128560126-1.250254011.18E-093.33E-09
CENPU2.3682734614.9435459081.0617105543.12E-194.63E-18
MAFG-DT0.9777597581.9933444611.0276391044.88E-132.20E-12
AZGP1358.0799149178.0887726-1.007685033.88E-184.56E-17
SERPINA11123.713029960.9909264-1.020330925.55E-091.44E-08
HLA-U1.1289258142.2809992761.0147153040.0007962510.0011617
STMN20.7571255441.997029231.3992510010.0081139150.010533
KCNJ110.7108054431.4735552821.0517745514.88E-101.45E-09
CHML1.3734401583.0131111291.133459831.28E-161.08E-15
PDE7A0.8766126022.0826440531.2484049643.56E-231.51E-21
ALDOA43.11331274104.07247841.2713832781.87E-203.69E-19
CA122.0250273055.6627268081.4835555692.59E-064.95E-06
TRIM710.6548167421.4670378051.1637429351.97E-063.82E-06
TMEM1580.3125849471.7626515842.4954271223.37E-055.69E-05
IGLV3-259.30793333821.406721921.2015311050.0168116310.0210517
NRSN22.7420727347.8746320261.521945673.05E-111.07E-10
TLDC20.6646862151.8250842311.4572177091.69E-105.33E-10
CDCA41.770696134.0406843431.1902830013.57E-253.06E-23
RARRES13.1888565817.5130071221.2363512561.19E-052.11E-05
DUOX20.4887493038.9003164194.1866900762.22E-053.82E-05
RGS12.7428065297.8319515371.5137189762.13E-128.82E-12
DCDC23.19044221713.251761942.0543558821.98E-053.42E-05
PTGFR0.9961171872.6211494511.3958122330.0086808760.0112384
MMP120.523842343.2079572622.6144503461.10E-114.09E-11
PGAP40.9325364462.6139445541.4869965241.33E-104.25E-10
ARMCX60.8559171161.9992292721.2239009272.84E-108.67E-10
IL181.2946354873.3327521221.3641680643.88E-056.51E-05
ESPL10.8688459481.8979522311.1272713762.72E-151.79E-14
EPHB60.6993087392.4436046521.8050094526.28E-071.28E-06
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CYRIB2.7252289255.4890732591.010185172.72E-228.45E-21
NQO138.2812991779.359858161.0517696550.0025670070.0035223
LINC019801.1451853642.4491940291.0967259330.0011802950.0016875
GLS22.4779559150.991931943-1.320837489.87E-050.0001582
ITGA20.6779165552.0314579561.5833358994.95E-132.23E-12
ORC10.7203486432.1681080491.5896694222.16E-239.96E-22
C12orf751.77133555510.568795352.5769015041.18E-202.47E-19
GCGR14.580609755.691348639-1.357208592.24E-085.41E-08
KIAA15229.07028596618.324592291.0145611589.03E-191.22E-17
TMEM1590.6543990432.0506645811.6478489927.87E-071.59E-06
SMIM220.1687253582.5600890083.9234452521.02E-072.28E-07
HPD718.9159057332.6224488-1.111937481.40E-125.93E-12
NDE10.7414918391.5320543011.0469647121.14E-248.29E-23
APLP10.4546256762.4679082692.4405376993.16E-098.50E-09
TUBB2B0.8497404751.9434846811.1935515476.77E-061.23E-05
CDC25A0.6534445461.6287652611.3176419835.83E-198.17E-18
CYP3A4505.9259451175.1266907-1.530527251.78E-094.92E-09
ZNF2130.7825002251.665905781.0901437352.22E-204.23E-19
HNF1B2.2275770626.2835527991.4961051661.28E-072.82E-07
TOR4A1.1024188973.0541734941.4701094943.06E-109.32E-10
HRG550.9675112241.5937742-1.189383971.28E-158.93E-15
IER314.6909171338.843218291.4027382747.75E-154.71E-14
GLYAT31.2902712310.68630063-1.549951653.12E-162.42E-15
TMEM440.8836134731.8634580681.0764950341.54E-161.29E-15
ZNF2920.7995301371.6860440161.076417885.11E-197.24E-18
LDHB7.71113783518.415313681.2558903110.0028072750.0038321
NSD21.2367398932.5848433761.0635347561.22E-236.16E-22
ABCA30.9011051652.0576052821.1911988570.0252193050.0308363
TGFA0.5550295522.2869922752.0428149996.84E-091.76E-08
MMP112.4134206835.8419095631.2753606111.86E-105.84E-10
PKIB1.4715930123.6417747631.3072629674.71E-081.09E-07
CYP2A6417.5544684127.6948302-1.709264297.48E-188.21E-17
CENPF1.2300173973.5765502971.539890013.76E-218.90E-20
PDP10.8462660661.9505732981.2047149891.24E-083.10E-08
NIBAN28.03569464619.655024821.2904035372.06E-141.16E-13
GYS217.266144477.441144493-1.214349533.99E-131.82E-12
ASAH110.9276100322.312924891.0299017378.24E-112.72E-10
DMKN0.8369525722.5780914631.6230856710.0002778820.0004256
LINC023811.2095753613.4765785741.5231675393.45E-077.25E-07
KRT201.0442894237.8272029822.9059752510.0015254810.0021538
AP001783.113.515488223.625467447-1.89837475.07E-111.73E-10
AC099850.30.9360436013.2802741041.8091687366.45E-232.51E-21
SAMD50.7296231371.5457423431.0830764750.0002429620.0003741
PLAGL21.3053764052.7278393751.0632928287.07E-199.79E-18
IKBKE1.2229210982.8438400741.2175090119.57E-181.02E-16
HMGB211.8511298623.842533691.0085129474.30E-185.02E-17
HOMER32.1769316856.0676124031.4788327951.28E-147.52E-14
CDC25C1.0964838152.2637809311.0458498363.50E-131.61E-12
SH3PXD2B1.2345309792.6223883181.0869182933.07E-162.39E-15
CEP1700.6872029411.4395949671.0668548482.57E-216.34E-20
MYLIP1.6863983163.6516576351.1146061792.12E-141.19E-13
ADAM93.0941735788.1564780741.3983922074.62E-152.90E-14
SLC6A132.3349610341.118318622-1.062067195.20E-122.02E-11
AFAP1-AS10.6299044572.1002927071.7373854797.99E-050.0001293
DNMT12.7717263656.0959450871.137065072.84E-231.26E-21
SRC3.4850912937.4428194841.0946527972.50E-141.39E-13
UCHL12.1579142513.238806872.6170636655.32E-071.10E-06
PPM1H0.9356396432.6468724671.5002637882.84E-121.15E-11
RNU6-850P0.7107621041.5799204751.1524132751.78E-127.45E-12
MYOF1.0916643023.0958207681.5037926691.28E-072.82E-07
AC112206.21.6942440470.665020782-1.349170373.65E-088.58E-08
TRIM16L3.9836021258.6139134011.1125952590.0001422030.0002241
TIMP211.9605760628.983866771.2769632030.0003720590.0005623
ANXA413.0020707828.860444191.1503520925.00E-071.03E-06
MUC5B0.98666226.8528340032.7960725971.87E-053.25E-05
RNF240.6948100261.6518142771.2493610071.49E-237.32E-22
SPINT14.40629376618.55975922.0745404054.76E-081.10E-07
G6PD5.12707337622.646863072.1431037794.57E-281.43E-25
HGFAC36.6866001815.47748709-1.245081961.54E-073.37E-07
ECT21.3470968384.2393248461.6539809553.55E-276.92E-25
FGFR311.5387045123.875374331.0490420952.52E-075.40E-07
SEMA6A0.6916476272.9643733142.0996180222.72E-086.50E-08
LINC015492.7198262031.304912128-1.059561810.0029355990.0039972
AL035446.10.9591548452.3329777651.2823369110.0005490730.0008147
ZNF831.2074188882.632478651.1244955554.44E-091.17E-08
TM4SF121.8470451249.809573761.1889849015.70E-081.31E-07
GTSF11.4431522593.9666163971.4586853661.30E-052.29E-05
TFF20.8137480118.787958313.4328740097.50E-061.36E-05
TRIM450.5340587771.66956021.644397685.78E-232.27E-21
TESC8.37372425324.139721861.5274677377.36E-081.67E-07
HTRA31.4658234074.11263261.4883508881.53E-063.00E-06
CKS220.6058652341.478856291.0093210727.48E-165.40E-15
WDR912.3587781634.8896409811.0516887972.56E-172.49E-16
NUAK22.4117272125.4219076641.1687338091.80E-105.67E-10
LIMK11.4767970334.3855658551.5702914428.16E-282.16E-25
AC083809.11.3226704194.1063825191.6344144063.24E-076.84E-07
SPHK12.4954959838.2845106971.7310899094.52E-152.84E-14
MROH2A1.9132110680.511769408-1.902430230.0066300580.0086855
RAP1GAP5.47040345114.523068231.4086271343.02E-151.97E-14
RHEX0.7000202921.9978383341.5129711950.0008816520.0012798
TRAV300.7699173231.5961045271.0517796980.0008131670.001185
SPP291.9348893636.12592556-1.347577927.93E-154.81E-14
MT1CP6.8173957040.231762958-4.878498826.06E-059.94E-05
SLC44A34.0740641068.7914607031.1096342087.80E-102.25E-09
COL9A20.3773706742.2384015952.5684146777.57E-176.77E-16
PMEPA11.6527359717.9396520032.2642195070.0001018990.0001631
ANXA539.5657274681.976130261.0509526052.08E-193.22E-18
SYT80.5619149462.6046390722.2126597912.23E-085.40E-08
TMX2P10.7930981941.7026207771.1021857372.31E-161.84E-15
PELI12.8359535195.8258791561.0386418892.12E-151.42E-14
CDCA70.4534136172.2432044412.3066614872.73E-119.66E-11
VTCN10.1642123285.4687355335.0575729471.56E-063.06E-06
SMIM61.8427301893.9716689221.1079005170.001141110.0016352
SLC7A80.6744037881.8309446781.4409036579.42E-082.11E-07
FSCN15.85935598915.625498821.4150882374.58E-081.06E-07
EHF1.140268793.0751692821.4312918862.86E-076.06E-07
AURKB2.4590401956.0743746621.3046405782.02E-172.02E-16
TEAD41.6391979633.6245414971.144808411.94E-063.76E-06
ADGRG11.9126578045.1702960021.4346680956.06E-059.93E-05
ESRP10.9718537332.7421292691.496485480.0137655550.0174338
RBBP81.9998884484.0435421691.0157001276.42E-198.95E-18
GRAMD1A5.5734280711.44160611.0376527131.22E-158.56E-15
ENO20.4390705562.898793612.7229279251.01E-181.35E-17
SLC2A11.0127644154.2093204612.0552887281.60E-105.06E-10
UGT2B10125.352252658.06017755-1.110367032.48E-131.17E-12
CLIP30.9076788492.0545772021.1785876984.90E-058.14E-05
NPNT1.4951502245.5242548681.8854894360.0058937640.0077577
HMGA123.9269242155.316088651.2090641971.23E-192.00E-18
MTMR21.186729922.6923583111.1818787844.08E-242.54E-22
MYRF3.7923178538.958360841.240154895.46E-122.12E-11
MYO100.6353245231.9263392811.6002962130.0315949390.0382154
DKK14.59491593414.092001111.6167661224.40E-079.14E-07
Figure 11

a: Heatmap of differential genes between high-risk and low-risk groups. Differential genes are highly expressed in high-risk groups b: GO enrichment analysis of differential genes in high-risk and low-risk groups. The GO enrichment analysis of the differential genes showed that the differential genes were mainly located in the extracellular matrix and chromosomal regions, and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation. CC: cellular Component; BP: biological Process; MF: molecular Function.

Genes that differ between high-risk and low-risk groups. a: Heatmap of differential genes between high-risk and low-risk groups. Differential genes are highly expressed in high-risk groups b: GO enrichment analysis of differential genes in high-risk and low-risk groups. The GO enrichment analysis of the differential genes showed that the differential genes were mainly located in the extracellular matrix and chromosomal regions, and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation. CC: cellular Component; BP: biological Process; MF: molecular Function. Type Ⅱ IFN response, type Ⅰ IFN response, and MHC class Ⅰ were significantly different between the high-risk group and low-risk group. Type Ⅱ IFN response and type Ⅰ IFN Response were highly expressed in the low-risk group, while MHC class Ⅰ was highly expressed in the high-risk group. Besides that, APC co-stimulation, CCR, and Cytolytic activity were different, APC co-stimulation and CCR had high expression in the high-risk group, while Cytolytic activity had high expression in the low-risk group (Figure 12). The results suggest that changes in immune function in the high-risk group may contribute to the progression of HCC.
Figure 12

Analysis of differences in immune function between the high-risk group and low-risk group. Blue represents low-risk, red represents high-risk, “∗” represents the difference in immune function between the two groups, and “∗∗∗” represents the significant difference. The results of immune function analysis showed that, compared with the high-risk group and the low-risk group, the two immune functions of type II IFN response and type I IFN response were suppressed, and the function of major histocompatibility complex I (MHC I) was enhanced.

Analysis of differences in immune function between the high-risk group and low-risk group. Blue represents low-risk, red represents high-risk, “∗” represents the difference in immune function between the two groups, and “∗∗∗” represents the significant difference. The results of immune function analysis showed that, compared with the high-risk group and the low-risk group, the two immune functions of type II IFN response and type I IFN response were suppressed, and the function of major histocompatibility complex I (MHC I) was enhanced.

TMB analysis

Mutations in the high-risk group and low-risk group were analyzed, with the higher frequency of mutations in the high-risk group, as shown in Figure 13. But the comparison of TMB between the high-risk group and the low-risk group found no difference (P = 0.15) (Figure 14). The overall survival of the low TMB group was better than that of the high TMB group (Figure 15 a). When the TMB was the same, the high-risk group had a worse prognosis, and when the risk score was the same, the high TMB had a worse prognosis. Furthermore, the results showed that, in HCC, patients with low TMB in the low-risk group had the best prognosis (Figure 15 b). However, the Low-risk group seems to converge around year 7. This may be due to the smaller sample size of the high-TMB group in the low-risk group, especially 7 years later, no samples were included in the low-risk-high TMB group.
Figure 13

a: Frequency of mutations in the low-risk group, b: Frequency of mutations in the high-risk group. The high-risk group has a higher proportion of gene mutations, and the proportion of TP53 mutations in the high-risk group is significantly higher.

Figure 14

The comparison of TMB between the high-risk group and the low-risk group. There was no difference in TMB between the high-risk and low-risk groups.

Figure 15

a: survival curves of the high TMB group and the low TMB group. The high TMB group had a worse prognosis and shorter survival than the low TMB group; b: Comparison of survival curves of TBM combined with the risk score for HCC patients.

a: Frequency of mutations in the low-risk group, b: Frequency of mutations in the high-risk group. The high-risk group has a higher proportion of gene mutations, and the proportion of TP53 mutations in the high-risk group is significantly higher. The comparison of TMB between the high-risk group and the low-risk group. There was no difference in TMB between the high-risk and low-risk groups. a: survival curves of the high TMB group and the low TMB group. The high TMB group had a worse prognosis and shorter survival than the low TMB group; b: Comparison of survival curves of TBM combined with the risk score for HCC patients. Based on previous studies, we found a total of 14 potential drugs, including A.443654, A.770041, ABT.263 (Navitoclax), ABT.888 (Veliparib), AICAR (Acadesine), Akt. inhibitor, AMG-706 (Motesanib), AS601245, ATRA, AUY922 (Luminespib), Axitinib, AZ628, AZD.0530, Rucaparib. A.443654, ABT.888 (Veliparib), AS601245, ATRA, AUY922 (Luminespib), AZ628, and Rucaparib were more effective for the high-risk group, while A.770041, ABT.263 (Navitoclax), AICAR (Acadesine), Akt. inhibitor, AMG-706 (Motesanib), Axitinib and AZD.0530 were more effective in the low-risk group (Figure 16).
Figure 16

Drug sensitivity analysis of potential drugs for HCC. a: A.443654, b: A.770041, c: ABT.263 (Navitoclax), d: ABT.888 (Veliparib), e: AICAR (Acadesine), f: Akt. inhibitor, g: AMG-706 (Motesanib), h: AS601245, i: ATRA, j: AUY922 (Luminespib), k:Axitinib, l:AZ628, m: AZD.0530, n: Rucaparib.

Drug sensitivity analysis of potential drugs for HCC. a: A.443654, b: A.770041, c: ABT.263 (Navitoclax), d: ABT.888 (Veliparib), e: AICAR (Acadesine), f: Akt. inhibitor, g: AMG-706 (Motesanib), h: AS601245, i: ATRA, j: AUY922 (Luminespib), k:Axitinib, l:AZ628, m: AZD.0530, n: Rucaparib.

Discussion

In our research, we found that NRAV and AL031985.3 are the most closely related lncRNAs in HCC. NRAV is a negative regulator of antiviral response. There are still few studies on its function. Existing research shows that it mainly stimulates gene transcription of immune response by influencing IFITM3 and MxA [40]. Besides that, NRAV may promote the development of HCC by regulating immune cell infiltration and immune checkpoint blockade (ICB) immunotherapy-related molecules [41]. Recent studies have shown that NRAV is up-regulated in HCC samples and is associated with a poor prognosis [41, 42, 43, 44, 45]. Possible mechanisms include the involvement of NRAV in regulating acetyltransferase activity, mRNA binding, and transport of GLUT4 to plasma membrane [42]. Similar to NRAV, many studies have shown that AL031985.3 is associated with the prognosis of HCC and can be used to construct a prediction model for the prognosis of HCC [46, 47, 48]. The results of our study were also consistent with those of previous studies, indicating that NRAV and AL031985.3 were correlated with the prognosis of HCC. Studies have shown that NRAV and AL031985.3 were highly expressed in HCC tissues, modified by m6A, and were associated with prognosis [49, 50]. However, the mechanism by which m6A modifies these two lncRNAs remains unclear. METTL3, an important m6A methyltransferase, is significantly upregulated in HCC and is involved in the proliferation, migration, and colony formation of HCC cells [51]. The study by Zuo et al [52]. also demonstrated that METTL3 can up-regulate some lncRNAs, which is associated with the poor prognosis in HCC. Our results also showed that METTL3 up-regulated NRAV and AL031985.3 in tumor tissues, which was associated with poor prognosis of HCC. Yang et al [53] found that METTL14 is associated with the occurrence and metastasis of colorectal cancer. However, we found that in HCC, METTL14 was not significantly associated with NRAV and AL031985.3. High expression of IGFBP1 can inhibit the development of liver disease [54, 55], and our study also found that IGFBP1 can negatively regulate two lncRNAs. The above studies have shown that m6A is an important regulatory mode of lncRNAs, which regulates the occurrence and progression of HCC by affecting the expression of lncRNAs. Our research found that type Ⅱ IFN response, type Ⅰ IFN response, and MHC class Ⅰ were the three most different functions in terms of immune function between the high-risk group and the low-risk group. Type II IFN response, type I IFN response was significantly down-regulated in the high-risk group, while MHC class I was up-regulated. Although it was believed that the main role of type I IFN was to play an antiviral immune role, existing studies have shown that type I IFN can directly act on tumors by blocking cell cycle progression and inducing apoptosis. They also have indirect antitumor activity, promoting clearance and preventing metastasis by priming immune cells [56, 57, 58]. It is worth noting that hepatitis virus infection is an important pathogenic factor for liver cancer. Compared with other tumors, the influencing factors of type I IFN response in liver cancer are more complicated. Our results suggested that the type I IFN response is functionally enhanced in the low-risk group, which may be related to the involvement of type I IFN in the naturally occurring protective immune response of primary tumors [59]. Our results are also consistent with previous studies showing that downregulation of type I IFN enhances tumor growth in a paracrine manner, reduces T lymphocyte cytotoxicity, and the ability of dendritic cells (DC) to process and present antigens [59, 60]. Type II IFN is mainly produced by immune cells (activated T cells, natural killer cells, and macrophages) and plays an important role in anti-tumor proliferation and cellular immunity [61, 62]. The low expression of type II IFN response and type I IFN response in the high-risk group may be due to an immunodeficiency of the tumor, which is present in a variety of tumors including breast cancer, melanoma, and gastrointestinal tumors [63]. Liver cancer cells all express MHC class I (MHC-I) antigens, but not in normal liver cells [64]. MHC-I plays an important role in controlling the phagocytosis of macrophages and can protect tumor cells from phagocytosis [65]. Differences in immune function create a favorable immune environment for cell proliferation and immune escape for HCC patients. In our results, the GO enrichment analysis of the differential genes showed that the differential genes were mainly located in the extracellular matrix and chromosomal regions and may play regulatory roles in binding sites and catalytic enzymes, thereby affecting the chromosome division and cell proliferation of cells. In the high-risk group and the low-risk group, the most mutated genes were TP53, CTNNB1, TTN, and MUC16. About 11–41% of liver malignancies had CTNNB1 mutations, and 13–48% had TP53 mutations [66, 67]. CTNNB1 and TP53 mutations promoted glycolysis and cell proliferation through ALDOA phosphorylation [68]. It was worth noting that CTNNB1 and TP53 mutations were mutually exclusive, and the two mutations can cause different characteristics of HCC. HCC patients with CTNNB1 mutations had large tumors, well-differentiated, bile accumulation, and no inflammatory infiltration, while HCC patients with P53 mutations had poorly differentiated tumors, dense cells, and frequent vascular infiltration [69]. Our results also showed that in the high-risk group compared to the low-risk group, TP53 mutations increased and CTNNB1 decreased, which may mean that the patient’s tumor cells had a worse differentiated and a higher risk of vascular invasion, which meant a worse prognosis. We screened 14 potential therapeutic agents for HCC in our study. There were already some studies on these drugs. Navitoclax made liver cancer cells sensitive to sorafenib and regorafenib through a mitochondrial caspase-dependent mechanism [70]. However, the current problem was that due to the low binding affinity of Navitoclax and Mcl-1, the anti-cancer activity of Navitoclax was often weakened by the increased expression of Mcl-1 in HCC and other cancers [71]. In addition, the phase III clinical trials of veliparib combined with temozolomide in advanced HCC showed that it was well tolerated in patients with advanced HCC, but the patients did not show a significant survival benefit [72]. AICAR regulated the redox status of liver cancer cells through nuclear factor erythroid 2-related factor signaling pathway and AMP-activated protein kinase independent mechanism [73]. Akt inhibitor, as an ATP-competitive AKT kinase inhibitor, blocked the phosphorylation of downstream molecules of the AKT signaling pathway in a dose and time-dependent manner, inhibited the proliferation, and induces apoptosis of hepatoma cells [74, 75]. A-443654 was also an Akt inhibitor and has antitumor effects in various tumors [76, 77]. A-770041 was a potent Src family kinase (Lck and Src) inhibitor with antitumor activity in osteosarcoma [78]. The phase III, randomized clinical trial of motesanib in non-small cell lung cancer showed that its objective response rate was 60.1% [79]. In thyroid papilloma, the objective response rate was 14%. 67% of patients had stable disease [80]. AS601245 was a selective c-Jun-terminal kinase inhibitor, the strongly inhibits cell adhesion and migration, with antitumor potential [81, 82, 83]. All-trans retinoic acid (ATRA) was an active metabolite of vitamin A and played an important role in tumor cell proliferation, differentiation, and apoptosis [84]. AUY922, an inhibitor of heat shock protein 90, reduced the proliferation and viability of HCC cells in a dose-dependent manner [85]. Axitinib combined with radiotherapy for advanced HCC was well tolerated, with ORR of 66.7%, 1-year OS of 66.7%, and median PFS of 7.4 months [86]. AZ628 was a hydrophobic Raf-kinase inhibitor that may play a therapeutic role in breast cancer [87], adrenocortical carcinoma [88]. Saracatinib (AZD.0530) treatment abolished the activation of Fyn, down-regulated the Fyn/FAK/N-WASP signaling pathway in hepatic stellate cells, and significantly reduced the degree of CCl4-induced liver fibrosis in mice [89]. It was expected to be a therapeutic drug for liver fibrosis and HCC. Rucaparib, a poly (ADP-ribose) polymerase inhibitor, had been approved for the treatment of recurrent ovarian and prostate cancer, and clinical trial results had shown that moderate liver injury did not require dose adjustment [90]. Although many potential drugs for the treatment of HCC had been discovered through studies, we should also be aware that the mechanism of HCC development is very complex, and the effect of a single targeted drug was [91] not ideal. In the future, we should study the combination of different drugs to block the progression of HCC, to improve the overall survival of HCC patients. There were also some limits in this study. Firstly, the samples of this study are from the TCGA database, the sample size of some groups may be small. For example, in Figure 15b, the Low-risk group seems to converge around year 7. This may be due to the smaller sample size of the high-TMB group in the low-risk group, especially 7 years later, no samples were included in the low-risk-high TMB group. Secondly, the risk score constructed by the study requires further validation by external validation and prospective studies. However, our study found the role of m6A-related lncRNAs in HCC prognosis and immunotherapy, established an effective risk score, and identified 14 potential therapeutic drugs for HCC, which is significant for further improving the prognosis of HCC patients.

Conclusion

The risk score constructed with NRAV and AL031985.3 had a good predictive effect on the Prognosis of HCC. Differences in genes and immune function between high-risk groups and low-risk groups promoted the occurrence and progression of HCC.

Declarations

Author contribution statement

Yan Xu: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper. Rong LIU: Conceived and designed the experiments; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Data will be made available on request.

Declaration of interest’s statement

The authors declare no conflict of interest.

Additional information

Data associated with this study has been deposited at Figshare under the URL https://doi.org/10.6084/m9.figshare.20575707.v1.
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