RABC: Rheumatoid Arthritis Bioinformatics Center.

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.

Effects of genetic variation on the structure of RNA and protein.

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

A review of disease risk prediction methods and applications in the omics era.

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Epigenome-wide methylation haplotype association analysis identified HLA-DRB1, HLA-DRB5 and HLA-DQB1 as risk factors for rheumatoid arthritis.

The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA-risk methylation haplotypes (meplotype). With 354 ACPA-positive RA patients and 335 normal controls selected from a case-control study based on Swedish population, we conducted the first RA epigenome-wide meplotype association study using our software EWAS2.0, mainly including (i) converted the ß value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case-control association test and (iv) screened for RA-risk meplotypes by odd ratio (OR) and p-values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p-value < .05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA-risk meplotypes were identified on three risk genes: HLA-DRB1, HLA-DRB5 and HLA-DQB1. Our results reported the relationship between DNA methylation pattern on HLA-DQB1 and the risk of RA for the first time, demonstrating the co-demethylation of 'cg22984282' and 'cg13423887' on HLA-DQB1 gene (meplotype UU, p-value = 2.90E - 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA-related genes from a new perspective and its applicability to the study of other disease.

EWASdb: epigenome-wide association study database.

DNA methylation, the most intensively studied epigenetic modification, plays an important role in understanding the molecular basis of diseases. Furthermore, epigenome-wide association study (EWAS) provides a systematic approach to identify epigenetic variants underlying common diseases/phenotypes. However, there is no comprehensive database to archive the results of EWASs. To fill this gap, we developed the EWASdb, which is a part of 'The EWAS Project', to store the epigenetic association results of DNA methylation from EWASs. In its current version (v 1.0, up to July 2018), the EWASdb has curated 1319 EWASs associated with 302 diseases/phenotypes. There are three types of EWAS results curated in this database: (i) EWAS for single marker; (ii) EWAS for KEGG pathway and (iii) EWAS for GO (Gene Ontology) category. As the first comprehensive EWAS database, EWASdb has been searched or downloaded by researchers from 43 countries to date. We believe that EWASdb will become a valuable resource and significantly contribute to the epigenetic research of diseases/phenotypes and have potential clinical applications. EWASdb is freely available at http://www.ewas.org.cn/ewasdb or http://www.bioapp.org/ewasdb.

EWAS: epigenome-wide association study software 2.0.

Motivation: With the development of biotechnology, DNA methylation data showed exponential growth. Epigenome-wide association study (EWAS) provide a systematic approach to uncovering epigenetic variants underlying common diseases/phenotypes. But the EWAS software has lagged behind compared with genome-wide association study (GWAS). To meet the requirements of users, we developed a convenient and useful software, EWAS2.0. Results: EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our 'population epigenetic framework' and can perform: (i) epigenome-wide single marker association study; (ii) epigenome-wide methylation haplotype (meplotype) association study and (iii) epigenome-wide association meta-analysis. Users can use EWAS2.0 to execute chi-square test, t-test, linear regression analysis, logistic regression analysis, identify the association between epi-alleles, identify the methylation disequilibrium (MD) blocks, calculate the MD coefficient, the frequency of meplotype and Pearson's correlation coefficients and carry out meta-analysis and so on. Finally, we expect EWAS2.0 to become a popular software and be widely used in epigenome-wide associated studies in the future. Availability and implementation: The EWAS software is freely available at http://www.ewas.org.cn or http://www.bioapp.org/ewas.

Genome-wide haplotype association study identifies risk genes for non-small cell lung cancer.

Lung cancer is the leading cause of cancer-related death worldwide. Most lung cancer is non-small cell lung cancer (NSCLC), in which malignant cells form in the lung epithelium. Mutations in multiple genes and environmental factors both contribute to NSCLC, and although some NSCLC susceptibility genes have been characterized, the pathogenesis of this disease remains unclear. To identify genes conferring NSCLC risk and determine their associated pathological mechanism, we combined genome-wide haplotype associated analysis with gene prioritization using 224,677 SNPs in 37 NSCLC cell lines and 116 unrelated European individuals. Five candidate genes were identified: ESR1, TGFBR1, INSR, CDH3, and MAP3K5. All of these have previously been implicated in NSCLC, with the exception of CDH3, which can therefore be considered a novel indicator of NSCLC risk. Functional annotation confirmed the relationship between these five genes and NSCLC. Our findings are indicative of the underlying pathological mechanisms of NSCLC and provide information to support future directions in diagnosing and treating NSCLC.

Comparing the evolutionary conservation between human essential genes, human orthologs of mouse essential genes and human housekeeping genes.

Human housekeeping genes are often confused with essential human genes, and several studies regard both types of genes as having the same level of evolutionary conservation. However, this is not necessarily the case. To clarify this, we compared the differences between human housekeeping genes and essential human genes with respect to four aspects: the evolutionary rate (dN/dS), protein sequence identity, single-nucleotide polymorphism (SNP) density and level of linkage disequilibrium (LD). The results showed that housekeeping genes had lower evolutionary rates, higher sequence identities, lower SNP densities and higher levels of LD compared with essential genes. Together, these findings indicate that housekeeping and essential genes are two distinct types of genes, and that housekeeping genes have a higher level of evolutionary conservation. Therefore, we suggest that researchers should pay careful attention to the distinctions between housekeeping genes and essential genes. Moreover, it is still controversial whether we should substitute human orthologs of mouse essential genes for human essential genes. Therefore, we compared the evolutionary features between human orthologs of mouse essential genes and human housekeeping genes and we got inconsistent results in long-term and short-term evolutionary characteristics implying the irrationality of simply replacing human essential genes with human orthologs of mouse essential genes.

Characterization of a Gallid herpesvirus 2 strain with novel reticuloendotheliosis virus long terminal repeat inserts.

A bacterial artificial chromosome clone, designated LCY, was constructed from a Gallid herpesvirus 2 (GaHV-2) isolate from a GaHV-2 and reticuloendotheliosis virus co-infected clinical sample. The LCY GaHV-2 insert was sequenced and found to consist of 175,319 nucleotides. LCY GaHV-2 open reading frames (ORFs) had a high sequence identity to those of reference strains. The major difference was that two REV long terminal repeats (LTRs), in the same direction, were inserted at the internal repeat short (IRs)/unique short (Us) and Us/terminal repeat short (TRs) junctions. In addition, the a-like sequence and UL36 were different from other strains. Phylogenetic analysis revealed that LCY was closely related to pandemic strains in China. A pathogenicity study and a vaccination-challenge test were performed on LCY and the reference strain, GA. The results showed that LCY induced gross Marek's disease (MD) lesions and mortality in 71.4 and 7.1% of chickens, respectively, which are lower rates than those observed for the reference strain GA (85.7 and 35.7%). The commercially available CVI988 vaccine provided complete protection against LCY and GA (100%). These results showed that the isolate exhibited lower pathogenicity in SPF chickens. This study revealed that a novel pattern of LTR inserts was found in the strain LCY and that the strain was of low virulence. The present work expands the available genetic information for GaHV-2 and will be useful for the control of MD in China.

Genome-wide haplotype association analysis identifies SERPINB9, SERPINE2, GAK, and HSP90B1 as novel risk genes for oral squamous cell carcinoma.

The oral squamous cell carcinoma (OSCC) is one of the most common malignant epithelial neoplasms and considered to be caused by the genetic damage. In addition, smoking habit and excessive alcohol consumption have been estimated to be the main risk factors. Although the association between OSCC and genetic susceptibility loci has been observed in many different populations, most of these studies simply focused on the single nucleotide polymorphism. Therefore, we made a contrast analysis between the 112 OSCC patients from the GEO database and 245 normal samples from the HapMap project. First, we performed a genome-wide haplotype association study by comparing the frequency of the haplotypes in the case-control experiment. Then, we mapped the haplotypes to the corresponding genes, screened the risk genes according to significant haplotypes (P < 1E-04), and prioritized the OSCC genes based on their similarity to the known OSCC susceptibility genes. We filtered four OSCC genes including SERPINB9, SERPINE2, GAK, and HSP90B1 through the gene global prioritization score (P < 0.005). SERPINB9 ranked first in the candidate gene list and contained a significant haplotype TAGGA (P value = 3.12E-11). The second risk gene was SERPINE2 with the haplotype GGGCCCTTT, which was closely similar to the SERPINB9.

Molecular and pathogenicity characterization of Gallid herpesvirus 2 newly isolated in China from 2009 to 2013.

During the course of our continuous surveillance of Gallid herpesvirus 2 (GaHV-2), 44 isolates were obtained from GaHV-2-positive chickens of different flocks in China from 2009 to 2013. The meq gene, considered as a major GaHV-2 oncogene, was sequenced and was found to contain an open reading frame of 1020 nucleotides encoding a 339 amino acid (aa) polypeptide in all isolates. Compared with the GaHV-2 GA strain, the meq genes in 15.9 % (7/44) of the isolates analyzed in this study contained an aa substitution mutation at position 88 (A to T) of which is the first report. The main characteristics of Chinese GaHV-2 isolates meq genes included the substitutions K77E, D80Y, V115A, T139A, P176R, and P217A, and the aa substitution frequency at positions 139 and 176 showed an increase. To test the pathogenicity of the isolates, a pathogenicity study and a vaccination-challenge test were performed on three selected isolates (ZY/1203, WC/1203, and WC/1110) and reference strain GA. The results showed that the three isolates induced gross Marek's disease (MD) lesions in 95.0-100 % cases, which was a higher rate than that obtained for strain GA (82.4 %). Three isolates induced mortality in 10-21.1 % of specific-pathogen-free chickens, which was similar to results with strain GA (23.5 %). The commercially available CVI988 vaccine induced lower protective indices (PIs) against ZY/1203 (82.4) and WC/1110 (83.3) as compared to those against WC/1203 (100) and GA (100). These results showed an evolving trend in the meq genes of the isolates; three isolates exhibited higher morbidity as compared to the reference strain and the vaccine induced lower PIs against two isolates as compared to that against the reference strain.

Genome-wide haplotype association study identifies BLM as a risk gene for prostate cancer in Chinese population.

Prostate cancer (PC) is a common malignant tumor that occurs in the prostate epithelial cells. It is generally considered to be caused by both genetic and environmental factors. To identify the genetic risk factors of PC in Chinese population, we carried out a genome-wide haplotype-based association study. The 33 Chinese PC cases were from the public GEO database (GSE18333), and the 139 Chinese controls (CHB) were from the HapMap project. Our analysis included three stages: (1) identifying the linkage disequilibrium (LD) blocks and performing genome-wide haplotype association scan, (2) mapping PC-risk haplotypes to PC candidate genes, and (3) prioritizing PC candidate genes based on their similarity to known PC susceptibility genes. The results showed that (1) 749 haplotypes were significantly associated with PC (P < 1E-5). (2) Then, we mapped these significant haplotypes to genes and got 454 PC candidate genes. (3) After prioritizing the candidate genes based on their similarity to known PC susceptibility genes, we found that seven novel PC susceptibility genes including BLM, RPS6KA2, FRK, ERBB4, RBL1, PAK7, and ERBB2IP. Among the seven genes, BLM gene ranked first (P = 1.89E-04). A haplotype GGTTACCCCTC (rs2270131, rs2073919, rs11073953, rs12592875, rs16944863, rs2238337, rs414634, rs401549, rs17183344, rs16944884, and rs16944888) on chromosome 15q26.1 had significant association with PC (P = 2.37E-11). To our knowledge, this is the first genetic association study to show the significant association between BLM gene and PC susceptibility in Chinese population.

Isolation and full-genome sequence of two reticuloendotheliosis virus strains from mixed infections with Marek's disease virus in China.

Reticuloendotheliosis virus (REV), classified as a gammaretrovirus, has a variety of hosts, including chickens, ducks, geese, turkeys, and wild birds. REV causes a series of pathological syndromes, especially the immunosuppression of the host, which may lead to an increased susceptibility to other pathogens, thus greatly damaging the poultry industry. Mixed infections of REV and Marek's disease virus (MDV) have been reported in many countries, including China. Previous reports revealed that MDV vaccines were not efficacious, and even less-virulent MDV strains would cause some losses due to mixed infections with REV. Additionally, contaminants in the MDV vaccine might be the main source of REV. In this study, two clinical samples were collected from two flocks of chickens that were diagnosed with MDV. Subsequently, two REV isolates were obtained from the clinical samples. The isolates, named CY1111 and SY1209, were further confirmed through an indirect immunofluorescence assay and electron microscopy. Complete genome sequences of the two REV strains were determined to test the relationship between them and other REV strains. Phylogenetic trees showed that the two REV strains were closely related to most REV strains that were isolated from a variety of hosts. Therefore, REVs might spread freely among these hosts under natural conditions. Additionally, most REV strains in China were in the same clade. The present work offers some information regarding REV in China.

Association between polymorphisms in the promoter region of interleukin-10 and susceptibility to inflammatory bowel disease.

The aim of this study was to assess the association of polymorphisms in the promoter region of the IL-10 gene with the risk of inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC). Fifteen studies (3,693 cases and 4,574 controls) were included in a meta-analysis of association between IL-10 -1082G/A, -819C/T and -592C/A polymorphisms, and IBD, CD and UC using allele contrast and the recessive, dominant, and additive models. Hardy-Weinberg equilibrium was confirmed for each study. Heterogeneity and study quality were investigated using stratification analyses and sensitivity analyses. Polymorphism -1082G/A showed significant association with CD, with odds ratios (ORs) for the GG + GA genotype and GG versus AA genotype of 1.278 (1.004-1.627) and 1.238 (1.027-1.492) in all subjects. Significant associations were found in the Caucasian subgroup using the allele contrast, dominant, and additive models. C-allele carriers of the -819C/T polymorphism were at increased risk of IBD (OR 1.093, 95% CI 1.004-1.190). Association with the -819C/T polymorphism was also found in Caucasians with CD (C vs. T: OR 1.104, 95% CI 1.010-1.206; CC + CT vs. TT: OR 1.328, 95% CI 1.006-1.754; CC vs. TT: OR 1.339, 95% CI 1.008-1.778), and with UC (CC vs. CT + TT: OR 1.188, 95% CI 1.019-1.385). No significant association was found between the -592C/A polymorphism and IBD, CD or UC. In conclusion, the meta-analysis demonstrated clear association between the IL-10 polymorphisms -1082G/A and -819C/T and the risk of IBD.

The molecular subtypes of autoimmune diseases.

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Comparative analysis of single-cell transcriptome reveals heterogeneity and commonality in the immune microenvironment of colorectal cancer and inflammatory bowel disease.

Background: During aging, chronic inflammation can promote tumor development and metastasis. Patients with chronic inflammatory bowel diseases (IBD) are at an increased risk of developing colorectal cancer (CRC). However, the molecular mechanism underlying is still unclear. Methods: We conducted a large-scale single-cell sequencing analysis comprising 432,314 single cells from 92 CRC and 24 IBD patients. The analysis focused on the heterogeneity and commonality of CRC and IBD with respect to immune cell landscape, cellular communication, aging and inflammatory response, and Meta programs. Results: The CRC and IBD had significantly different propensities in terms of cell proportions, differential genes and their functions, and cellular communication. The progression of CRC was mainly associated with epithelial cells, fibroblasts, and monocyte-macrophages, which displayed pronounced metabolic functions. In particular, monocyte-macrophages were enriched for the aging and inflammation-associated NF-κB pathway. And IBD was enriched in immune-related functions with B cells and T cells. Cellular communication analysis in CRC samples displayed an increase in MIF signaling from epithelial cells to T cells, and an increase in the efferent signal of senescence-associated SPP1 signaling from monocyte-macrophages. Notably, we also found some commonalities between CRC and IBD. The efferent and afferent signals showed that the pro-inflammatory cytokine played an important role. And the activity of aging and inflammatory response with AUCell analysis also showed a high degree of commonality. Furthermore, using the Meta programs (MPs) with the NMF algorithm, we found that the CRC non-malignant cells shared a substantial proportion of the MP genes with CRC malignant cells (68% overlap) and IBD epithelial cells (52% overlap), respectively. And it was extensively involved in functions of cell cycle and immune response, revealing its dual properties of inflammation and cancer. In addition, CRC malignant and non-malignant cells were enriched for the senescence-related cell cycle G2M phase transition and the p53 signaling pathway. Conclusion: Our study highlights the characteristics of aging, inflammation and tumor in CRC and IBD at the single-cell level, and the dual property of inflammation-cancer in CRC non-malignant cells may provide a more up-to-date understanding of disease transformation.

Genome-wide identification of m6A-associated single nucleotide polymorphisms in complex diseases of nervous system.

N6-methyladenosine (m6A) is one of the most abundant chemical modifications on RNA and can affect the occurrence and development of diseases. Some studies have shown that the expressions of some m6A-related genes are significantly regulated by single nucleotide variants (SNV). However, the function of m6A-associated single nucleotide polymorphisms (m6A-SNP) remains unclear in multiple sclerosis (MS), Alzheimer's disease (AD) and Parkinson's disease (PD). Here, we identified the disease-associated m6A-SNPs by integrating genome-wide association study (GWAS) and m6A-SNPs from the RMVar database, and confirmed the relationship between these identified m6A-SNPs and their target genes in eQTL analysis and gene differential expression analysis. Finally, 26 genes corresponding to 20 m6A-SNPs with eQTL signals were identified and differentially expressed (P < 0.05) in MS, 15 genes corresponding to 12 m6A-SNPs (P < 1e-04) were differentially expressed in AD, and 27 PD-associated m6A-SNPs that regulated the expression of 31 genes were identified. There were 5 HLA genes with eQTL signals (HLA-DQB1, HLA-DRB1, HLA-DQA1, HLA-DQA2 and HLA-DQB1-AS1) to be detected in the three diseases. In summary, our study provided new insights into understanding the potential roles of these m6A-SNPs in disease pathogenesis as well as therapeutic target.

DBGSA: a novel method of distance-based gene set analysis.

When compared with single gene functional analysis, gene set analysis (GSA) can extract more information from gene expression profiles. Currently, several gene set methods have been proposed, but most of the methods cannot detect gene sets with a large number of minor-effect genes. Here, we propose a novel distance-based gene set analysis method. The distance between two groups of genes with different phenotypes based on gene expression should be larger if a certain gene set is significantly associated with the given phenotype. We calculated the distance between two groups with different phenotypes, estimated the significant P-values using two permutation methods and performed multiple hypothesis testing adjustments. This method was performed on one simulated data set and three real data sets. After a comparison and literature verification, we determined that the gene resampling-based permutation method is more suitable for GSA, and the centroid statistical and average linkage statistical distance methods are efficient, especially in detecting gene sets containing more minor-effect genes. We believe that this distance-based method will assist us in finding functional gene sets that are significantly related to a complex trait. Additionally, we have prepared a simple and publically available Perl and R package (http://bioinfo.hrbmu.edu.cn/dbgsa or http://cran.r-project.org/web/packages/DBGSA/).

Identification of novel meQTLs strongly associated with rheumatoid arthritis by large-scale epigenome-wide analysis.

Rheumatoid arthritis (RA) is highly heritable, and previous studies have suggested that genetic variation may affect susceptibility to RA by altering epigenetic modifications (e.g. DNA methylation). Here we examined how genetic variation influences DNA methylation (DNAm) in RA by integrating individual genetic variation and DNAm data. Epigenome-wide meQTL (methylation quantitative trait loci) analysis was performed on 354 RA patients and 335 controls, scanning 30,101,744 relationships between 62 SNPs and 485,512 DNA methylation sites. Two regulatory relationship pairs (FDR < 0.05) showed very strong associations with RA risk. One was rs10796216-cg00475509, and the DNAm decreased by 0.0168 per addition of allele rs10796216-A. The other was rs6546473-cg13358873, for which a 0.0365 reduction of DNAm at cg13358873 was observed for each addition of allele rs6546473-A, and lower DNAm was found to be significantly associated with RA risk (P = 2.0407e-28). Moreover, both pairs of meQTL showed a strong regulatory relationship only in RA samples, so they can be subsequently considered as risk markers for RA. In conclusion, our integrated analysis of genetic and epigenetic variation suggests that genetic variation may affect the risk of RA by regulating DNA methylation levels. Alterations of DNAm at cg00475509 and cg13358873 loci conferred by rs10796216-A and rs6546473-A allele may suggest a potential risk for RA. Our results deepen our understanding of the genetic and epigenetic mechanisms of RA and provide novel associations that can be further investigated in future studies.

Ribosomal protein L22-like1 (RPL22L1) mediates sorafenib sensitivity via ERK in hepatocellular carcinoma.

Precision medicine in hepatocellular carcinoma (HCC) relies on validated biomarkers that help subgroup patients for targeted treatment. Here, we identified a novel candidate oncogene, ribosomal protein L22-like1 (RPL22L1), which was markedly elevated in HCC, contributed to HCC malignancy and adverse patient survival. Functional studies indicated RPL22L1 overexpression accelerated cell proliferation, migration, invasion and sorafenib resistance. Mechanism studies revealed that RPL22L1 activated ERK to induce atypical epithelial-to-mesenchymal transition (EMT) progress. Importantly, the ERK inhibitor (ERKi) could potentiate sorafenib efficiency in RPL22L1-high HCC cells. In summary, these data uncover RPL22L1 is a potential marker to guide precision therapy for utilizing ERKi to enhance the sorafenib efficacy in RPL22L1-high HCC patients.