Identification of 13 Novel Loci in a Genome-Wide Association Study on Taiwanese with Hepatocellular Carcinoma.

Liver cancer is caused by complex interactions among genetic factors, viral infection, alcohol abuse, and metabolic diseases. We conducted a genome-wide association study and polygenic risk score (PRS) model in Taiwan, employing a nonspecific etiology approach, to identify genetic risk factors for hepatocellular carcinoma (HCC). Our analysis of 2836 HCC cases and 134,549 controls revealed 13 novel associated loci such as the FAM66C gene, noncoding genes, liver-fibrosis-related genes, metabolism-related genes, and HCC-related pathway genes. We incorporated the results from the UK Biobank and Japanese database into our study for meta-analysis to validate our findings. We also identified specific subtypes of the major histocompatibility complex that influence both viral infection and HCC progression. Using this data, we developed a PRS to predict HCC risk in the general population, patients with HCC, and HCC-affected families. The PRS demonstrated higher risk scores in families with multiple HCCs and other cancer cases. This study presents a novel approach to HCC risk analysis, identifies seven new genes associated with HCC development, and introduces a reproducible PRS model for risk assessment.

Comprehensive Analysis and Drug Modulation of Human Endogenous Retrovirus in Hepatocellular Carcinomas.

BACKGROUND: Human endogenous retroviruses (HERVs) play an important role in the development of cancer and many diseases. Here, we comprehensively explored the impact of HERVs on hepatocellular carcinomas (HCCs). METHODS: We employed Telescope to identify HERVs and quantify their expression in the total RNA sequencing data obtained from 254 HCC samples, comprising 254 tumor tissues and 34 matched normal tissues. RESULTS: In total, 3357 locus-specific activations of HERVs were differentially expressed, and 180 were correlated with patient survival. Using these 180 HERVs for classification, we found four subgroups with survival correlation. Higher expression levels of the 180 HERVs were correlated with poorer survival, while age, AFP, some mutations, and copy and structural variants differed among subgroups. The differential expression of host genes in high expression of these 180 HERVs primarily involved the activation of pathways related to immunity and infection, lipid and atherosclerosis, MAPK and NF-kB signaling, and cytokine-cytokine receptor interactions. Conversely, there was a suppression of pathways associated with RNA processing, including nucleocytoplasmic transport, surveillance and ribosome biogenesis, and transcriptional misregulation in cancer pathways. Almost all genes involved in HERV activation restriction, KRAB zinc finger proteins, RNA nucleocytoplasmic transport, stemness, HLA and antigen processing and presentation, and immune checkpoints were overexpressed in cancerous tissues, and many over-expressed HERV-related nearby genes were correlated with high HERV activation and poor survival. Twenty-three immune and stromal cells showed higher expression in non-cancerous than cancerous tissues, and seven were correlated with HERV activation. Small-molecule modulation of alternative splicing (AS) altered the expression of survival-related HERVs and their activation-related genes, as well as nearby genes. CONCLUSION: Comprehensive and integrated approaches for evaluating HERV expression and their correlation with specific pathways have the potential to provide new companion diagnostics and therapeutic strategies for HCC.

Whole genome and RNA sequencing analyses for 254 Taiwanese hepatocellular carcinomas.

BACKGROUND: Comprehensive and integrative analysis of hepatocellular carcinoma (HCC) is important. In this study, we explored Taiwanese HCCs using multi-omics analyses. METHODS: We analyzed 254 HCCs by whole genome sequencing and total RNA sequencing, and then used bioinformatic tools to analyze genomic and transcriptomic alterations in coding and non-coding sequences to explore the clinical importance of each sequence. RESULTS: The frequencies of the five most commonly mutated cancer-related genes were TERT, TP53, CTNNB1, RB1, and ARID1A. Genetic alteration frequencies influenced the etiology of HCC; some alterations were also correlated with clinicopathological conditions. Many cancer-related genes had copy number alterations (CNAs) and structure variants (SVs) that changed according to etiology and exhibited potential associations with survival. We also identified several alterations in histone-related genes, HCC-related long non-coding RNAs, and non-coding driver genes that may contribute to the onset and progression of HCC. Transcriptomic analysis revealed that 229 differentially expressed and 148 novel alternative splicing (AS) genes, as well as the presence of fusion genes, were associated with patient survival. Moreover, somatic mutations, CNAs, and SVs were associated with immune checkpoint gene expression and tumor microenvironment. Finally, we identified relationships among AS, immune checkpoint gene expression and tumor microenvironment. CONCLUSIONS: This study shows that genomic alterations are associated with survival, including DNA-based and RNA-based data. Moreover, genomic alterations and their associations with immune checkpoint genes and the tumor microenvironment may provide novel insights for the diagnosis and treatment of HCC.

Dysregulation of Immune Cell Subpopulations in Atypical Hemolytic Uremic Syndrome.

Atypical hemolytic uremic syndrome (aHUS) is a rare, life-threatening thrombotic microangiopathy. Definitive biomarkers for disease diagnosis and activity remain elusive, making the exploration of molecular markers paramount. We conducted single-cell sequencing on peripheral blood mononuclear cells from 13 aHUS patients, 3 unaffected family members of aHUS patients, and 4 healthy controls. We identified 32 distinct subpopulations encompassing 5 B-cell types, 16 T- and natural killer (NK) cell types, 7 monocyte types, and 4 other cell types. Notably, we observed a significant increase in intermediate monocytes in unstable aHUS patients. Subclustering analysis revealed seven elevated expression genes, including NEAT1, MT-ATP6, MT-CYB, VIM, ACTG1, RPL13, and KLRB1, in unstable aHUS patients, and four heightened expression genes, including RPS27, RPS4X, RPL23, and GZMH genes, in stable aHUS patients. Additionally, an increase in the expression of mitochondria-related genes suggested a potential influence of cell metabolism on the clinical progression of the disease. Pseudotime trajectory analysis revealed a unique immune cell differentiation pattern, while cell-cell interaction profiling highlighted distinctive signaling pathways among patients, family members, and controls. This single-cell sequencing study is the first to confirm immune cell dysregulation in aHUS pathogenesis, offering valuable insights into molecular mechanisms and potential new diagnostic and disease activity markers.

Genetic contributions to female gout and hyperuricaemia using genome-wide association study and polygenic risk score analyses.

OBJECTIVES: To identify genetic variants and polygenic risk score (PRS) relating to female gout and asymptomatic hyperuricaemia (AH) in a genome-wide association study (GWAS). METHODS: Gout, AH and normouricemia controls were included from Taiwan biobank and China Medical University Hospital. All participants were divided into discovery and replication cohorts for GWAS. PRS was estimated according to whether the variant exhibited a protective effect on the phenotypes or not. Each cohort was separated into two groups by the age of 50 years old. RESULTS: A total of 59 472 females were enrolled, and gout and AH occupied 1.60% and 19.59%, respectively. Six variants located in genes SLC2A9, C5orf22, CNTNAP2 and GLRX5 were significantly predictors of female gout in those aged ≥50. For those aged <50 years old, only the variant rs147750368 (SPANXN1) on chromosome X was found. Most variants located in genes SLC2A9, ZNF518B, PKD2 and ABCG2 were found to be significantly related to AH in both age groups. The PRS could explain ∼0.59% to 0.89% of variance of gout in variants with protective effects, which showed 6.2 times of mean PRS in the risk variants, but only 1.2 times in the AH phenotype. Moreover, the PRS also revealed a dose-response trend between AH rates and quartile scores. CONCLUSION: The variants in gene SLC2A9 are the major genetic factors for females associated with gout in those aged ≥50. PRS can provide a more robust prediction of the gout/AH under a homogeneous selection of variants that show effects on the traits.

Cancer carrier screening in the general population using whole-genome sequencing.

BACKGROUND: Cancer is a major cause of death, and its early identification and intervention have potential for clinical actionability and benefits for human health. The studies using whole-genome sequencing (WGS) and large samples analysis of cancer-related genes have been rarely done. METHODS: We performed WGS to explore germline mutations in coding and non-coding areas of cancer-related genes and non-coding driver genes and regulatory areas. Structural variants (SVs) was also analyzed. We used several tools and a subgrouping method to analyze the variants in 1491 healthy participants. Moreover, 275 cancer-related genes sequencing was carried out in 125 cancer patients. RESULTS: The incidence of familial cancer in the Taiwanese general population is 8.79% (131/1491). Cancer carrier rate of cancer-related genes is about 7.04% (105/1491) for pathogenic/likely pathogenic variants (P/LP) on ClinVar database only, and 28.24% (421/1491) for P/LP and loss of function variants. The carrier frequencies of cancer-related genes P/LP on ClinVar database were as follows: 8.40% (11/131), 7.11% (28/394), and 6.83% (66/966) in FC, 1MC, and nMC, respectively. The SVs and non-coding driver gene variants are uncommon. There are 1.54% (23/1491) of actionable cancer genes in American College of Medical Genetics and Genomics (ACMG), and the germline mutation rate of 275 cancer-related genes is 7.2% (9/125) in cancer patients including 4.0% (5/125) of actionable cancer genes in ACMG. After analyzing the frequencies of P/LP variants on GJB2 and SLC25A13 genes, we suggest that these two genes may not be cancer-related genes and need be re-evaluated. CONCLUSIONS: WGS analysis can completely detect germline mutations in cancer carriers. This study use subgrouping approach for samples provides a strategy to study whether a gene or variant is a cancer-related gene or variant in the future studies.

Integrated genomic analyses of hepatocellular carcinoma.

BACKGROUND: Genomic alterations play important roles in the development of cancer. We explored the impact of protein-coding genes and transcriptomic changes on clinical and molecular alterations in Taiwanese hepatocellular carcinoma (HCC) patients. METHODS: We analyzed 147 whole-exome sequencing and 100 RNA sequencing datasets of HCC and compared them with The Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma cohort and develop a panel of 81 apoptosis-related genes for molecular classification. RESULTS: TERT (50%), TP53 (25%), CTNNB1 (14%), ARID1A (12%), and KMT2C (11%) were the most common genetic alterations of cancer-related genes. ALDH2 and KMT2C mutated at much higher frequencies in our cohort than in TCGA, whereas CTNNB1 was found only in 14% of our Taiwanese patients. A high germline mutation rate of ALDH2 in the APOBEC mutational signature and herb drug-related aristolochic acid-associated signature was also observed. Groups A and B of HCC were identified when we used apoptosis-related genes for molecular classification. The latter group, which had poorer survival outcomes, had significantly more aDC, CD4+ Tem, macrophages M2, NKT, plasma cells, and Th1 cells, and less CD4+ memory T cells, CD8+ Tcm, cDC, iDC, and Th2 cells, as well as more inter-chromosome fusion genes. Metatranscriptomic analysis revealed 54 cases of HBV infection. Moreover, we found that the main target gene of HBV integration is ALB. CONCLUSIONS: Unique genomic alterations were observed in our Taiwanese HCC patients. Molecular classification using apoptosis-related genes could lead to new therapeutic approaches for HCC.

Single-cell RNA sequencing of immune cells in patients with acute gout.

Cell subpopulations in the blood and joint fluid of patients with gout are poorly understood. Single-cell RNA sequencing and bioinformatic tools were used to identify cell subsets and their gene signatures in blood and synovial fluid (SF) cells, determine their relationships, characterize the diversity, and evaluate interactions among specific cell types. We identified 34 subpopulations (5 types of B cells, 16 types of T and natural killer cells, 9 types of monocytes, and 4 other cell types) in the blood of five healthy subjects and seven patients with acute gouty, and the SF of three patients with acute gout. We found that naïve CD4 T cells and classical monocytes cell populations were enriched in patients with gout, whereas plasmacytoid dendritic cells and intermediate monocytes were more abundant in healthy subjects. SF was enriched in Th1/Th17 cells, effector memory CD8 T cells, mucosal-associated invariant T cells, and macrophages. Subclusters of these cell subpopulations showed different compositions between healthy subjects and those with acute gout, according to blood and SF samples. At the cellular level, the inflammation score of a subpopulation or subcluster was highest in SF, following by the blood of acute gout patients and healthy person, whereas energy score showed the opposite trend. We also detected specific cell-cell interactions for interleukin-1, tumor necrosis factor-α, and transforming growth factor-ß1 expression in the cells of patients with acute gout. Our study reveals cellular and molecular insights on inflammatory responses to hyperuricemia or uric crystal and may provide therapeutic guidance to improve treatments for gout.

Molecular Classification of Hepatocellular Carcinoma Using Wnt-Hippo Signaling Pathway-Related Genes.

In Taiwan, a combination of hepatitis B and C infection, economic boom-related food and alcohol overconsumption, and Chinese medicine prescriptions has led to a high rate of hepatocellular carcinoma (HCC). However, the causative factors and underlying tumor biology for this unique HCC environment have not been identified. Wnt and Hippo signaling pathways play an important regulatory role in HCC development, and their functions are generally considered as positive and negative regulators of cell proliferation, respectively. In this study, we characterized the molecular features of HCC using a newly developed classification system based on the expression of the Wnt-Hippo signaling pathway-related genes. RNA sequencing (RNA-Seq) was performed on liver tumor tissues from 100 patients with liver cancer. RNA-Seq data for 272 previously characterized Wnt-Hippo signaling pathway-related genes were used for hierarchical clustering. We analyzed the data in terms of prognostic value, transcriptome features, immune infiltration, and clinical characteristics, and compared the resulting subclasses with previously published classifications. Four subclasses of HCC (HCCW1-4) were identified. Subclass HCCW1 displayed the highest PCDHB4 expression. Subclass HCCW2 displayed lower Edmondson-Steiner grades (I and II) and CTNNB1 mutation frequencies. Subclass HCCW3 was associated with a good prognosis, the highest PCDHGB7 expression, high CD8+ naïve T cells abundance, and relatively low TP53 mutation rates. Subclass HCCW4 was associated with a poor prognosis, the highest PCDHB2 and PCDHB6 expression, a relatively high abundance of Th1 cells, NKT and class-switched memory B cells, relatively low enrichment of cDC, iDC, and CD4+ memory T cells, and high Edmondson-Steiner grades (III and IV). We also identified Wnt-Hippo signaling pathway-related genes that may influence immune cell infiltration. We developed a panel of 272 Wnt-Hippo signaling pathway-related genes to classify HCC into four groups based on Taiwanese HCC and The Cancer Genome Atlas Liver Hepatocellular Carcinoma datasets. This novel molecular classification system may aid the treatment of HCC.

Polygenic risk score trend and new variants on chromosome 1 are associated with male gout in genome-wide association study.

BACKGROUND: Gout is a highly hereditary disease, but not all those carrying well-known risk variants have developing gout attack even in hyperuricemia status. We performed a genome-wide association study (GWAS) and polygenic risk score (PRS) analysis to illustrate the new genetic architectures of gout and asymptomatic hyperuricemia (AH). METHODS: GWAS was performed to identify variants associated with gout/AH compared with normouricemia. The participants were males, enrolled from the Taiwan Biobank and China Medical University, and divided into discovery (n=39,594) and replication (n=891) cohorts for GWAS. For PRS analysis, the discovery cohort was grouped as base (n=21,814) and target (n=17,780) cohorts, and the score was estimated by grouping the polymorphisms into protective or not for the phenotypes in the base cohort. RESULTS: The genes ABCG2 and SLC2A9 were found as the major genetic factors governing gouty and AH, and even in those carrying the rs2231142 (ABCG2) wild-genotype. Surprisingly, variants on chromosome 1, such as rs7546668 (DNAJC16), rs10927807 (AGMAT), rs9286836 (NUDT17), rs4971100 (TRIM46), rs4072037 (MUC1), and rs2974935 (MTX1), showed significant associations with gout in both discovery and replication cohorts (all p-values < 1e-8). Concerning the PRS, the rates of gout and AH increased with increased quartile PRS in those SNPs having risk effects on the phenotypes; on the contrary, gout/AH rates decreased with increased quartile PRS in those protective SNPs. CONCLUSIONS: We found new variants on chromosome 1 significantly relating to gout, and PRS predicts the risk of developing gout/AH more robustly based on the SNPs' effect types on the trait.

Mutation Analysis of Second Primary Tumors in Oral Cancer in Taiwanese Patients through Next-Generation Sequencing.

Head and neck cancer has poor overall survival. Patients with head and neck cancer more frequently develop second primary tumors than do patients with other cancers, leading to a poor prognosis. In this study, we used next-generation sequencing to analyze and compare mutations between first tumors and second tumors in oral cancer. We retrieved tumor tissues collected from 13 patients who were diagnosed twice as having cancer. We used driver gene and trunk mutations to distinguish between recurrent cancer and primary cancer in oral cancer. We observed unique driver gene mutations in three patients with an initial clinical diagnosis of recurrent cancer; hence, we believe that the corresponding patients had primary cancer. Four patients with an initial clinical diagnosis of primary cancer were found to actually have recurrent cancer according to our results. Genetic testing can be used to enhance the accuracy of clinical diagnosis.

A nine-gene signature identification and prognostic risk prediction for patients with lung adenocarcinoma using novel machine learning approach.

BACKGROUND: Lung adenocarcinoma (LUAD) is one the most prevalent cancer with high mortality and its risk stratification is limited due lack of reliable molecular biomarkers. Although several studies have been conducted to identify gene signature involved in LUAD progression, most currently used methods to select gene features did not fully consider the problem of the existence of strong pairwise gene correlations as it resulted inconsistency in gene election. Therefore, it is crucial to develop new strategy to identify reliable gene signatures that improve risk prediction. METHODS AND RESULTS: In this study, novel feature selection strategy (1) univariate Cox regression model to select survival associated genes (2) integrating rigid Cox regression with Adaptive Lasso model to identify informative survival associated genes (3) stepwise Cox regression model to identify optimal gene signature and (4) prognostic risk predictive model for LUAD (PRPML) was constructed. The PRPML was developed-based on four machine learning (ML) methods including logistic regression (LR), K-nearest neighbors (KNN), support vector machine with the radial kernel (SVMR), and average neural network (Avnet). The PRPML model successfully stratified high-risk and low-risk groups of patients with LUAD in three datasets. The PRPML achieved an area under the curve (AUC) of 0.812 and 0.863 in the validation datasets. Finally, a nine-potential gene signature was found and showed great potential for risk prediction. CONCLUSIONS: Our study demonstrates that the developed strategy identified a nine potential gene signature for accurate risk prediction performance and this signature could provide valuable clue into the understanding of the molecular mechanism of LUAD disease.

Clinical application of liquid biopsy in cancer patients.

BACKGROUND: This study was to determine the prevalence and clinical significance of clonal hematopoiesis (CH)-related variants, and somatic and germline mutations in cancer patients and healthy individuals. METHODS: We performed next-generation sequencing of 275 cancer-related genes be-tween plasma and white blood cells in 92 cancer patients and 47 controls without cancer. Blood samples were recruited from May 2017 to July 2021, and blood cancer patients were excluded. For all statistical analysis in this study, p < 0.05 was considered statistically significant. RESULTS: Overall, 38.04% of patients and 46.81% of controls harbored at least one CH-related mutation in plasma cell-free DNA. Based on our results, older cancer patients exhibited a CH phenomenon more frequently than younger patients (p = 0.0024). A total of 39 somatic pathogenic (P)/likely pathogenic (LP) mutations were identified in 17 genes in 21 of 92 patients. We found that the presence of P/LP variants in cancer-related gene predicted shorter overall survival (OS) (p = 0.001). Multivariate analysis adjusted for CH-related mutations, germline mutations, and tumor stage, also indicated that somatic mutations correlated significantly with OS (p = 0.022). Moreover, the frequency of a germline P/LP variant was that of seven of 92 individuals in the cancer group and one of 42 individuals in the control group. CONCLUSIONS: We characterized the CH-related variants, and somatic and germline mutations in cancer patients and healthy individuals, and the results have important clinical significance.

APOE and KLF14 genetic variants are sex-specific for low high-density lipoprotein cholesterol identified by a genome-wide association study.

To demonstrate the loci that relate to high-density lipoprotein cholesterol (HDL-C) levels and genetic sex heterogeneity, we enrolled 41,526 participants aged between 30 and 70 years old from the Taiwan Biobank in a genome-wide association study. We applied the Manhattan plot to display the p-values estimated for the relationships between loci and low HDL-C. A total of 160 variants were significantly associated with low HDL-C. The genotype TT of rs1364422 located in the KLF14 gene has 1.30 (95% CI=1.20 - 1.42) times the risk for low-HDL compared to genotype CC in females (log(-p) =8.98). Moreover, the genes APOC1, APOE, PVRL2, and TOMM40 were associated significantly with low-HDL-C in males only. Excluding the variants with high linkage disequilibrium, we revealed the rs429358 located in APOE as the major genetic variant for lowering HDL-C, in which genotype CT has 1.24 (95% CI= 1.16 - 1.32) times the risk. In addition, we also examine 12 genes related to HDL-C in both sexes, including LPL, ABCA1, APOA5, BUD13, ZPR1, ALDH1A2, LIPC, CETP, HERPUD1, LIPG, ANGPTL8, and DOCK6. In conclusion, low-HDL-C is a genetic and sex-specific phenotype, and we discovered that the APOE and KLF14 are specific to low-HDL-C for men and women, respectively.

Long Noncoding RNA NTT Context-Dependently Regulates MYB by Interacting With Activated Complex in Hepatocellular Carcinoma Cells.

BACKGROUND: Long noncoding RNA (lncRNA) mediates the pathogenesis of various diseases, including cancer and cardiovascular, infectious, and metabolic diseases. This study examined the role of lncRNA NTT in the development and progression of cancer. METHODS: The expression of NTT was determined using tissues containing complementary DNA (cDNA) from patients with liver, lung, kidney, oral, and colon cancers. The expression of cis-acting genes adjacent to the NTT locus (CTGF, STX7, MYB, BCLAF1, IFNGR1, TNFAIP3, and HIVEP2) was also assessed. We used knockdown and chromatin immunoprecipitation (ChIP) assays to identify the cis-acting genes that interact with NTT. RESULTS: NTT was most significantly downregulated in hepatocellular carcinoma (HCC), while a higher NTT level correlated with a shorter survival time of patients with HCC. Multivariate analysis indicated NTT was not an independent predictor for overall survival. MYB was significantly upregulated, and its increased expression was associated with dismal survival in HCC patients, similar to the results for NTT. NTT knockdown significantly decreased cellular migration. ChIP of HCC cell lines revealed that NTT is regulated by the transcription factor ATF3 and binds to the MYB promoter via the activated complex. Additionally, when NTT was knocked down, the expression of MYB target genes such as Bcl-xL, cyclinD1, and VEGF was also downregulated. NTT could play a positive or negative regulator for MYB with a context-dependent manner in both HCC tissues and animal model. CONCLUSION: Our study suggests that NTT plays a key role in HCC progression via MYB-regulated target genes and may serve as a novel therapeutic target.

Metatranscriptomic Analysis of Human Lung Metagenomes from Patients with Lung Cancer.

This study was designed to characterize the microbiomes of the lung tissues of lung cancer patients. RNA-sequencing was performed on lung tumor samples from 49 patients with lung cancer. Metatranscriptomics data were analyzed using SAMSA2 and Kraken2 software. 16S rRNA sequencing was also performed. The heterogeneous cellular landscape and immune repertoires of the lung samples were examined using xCell and TRUST4, respectively. We found that nine bacteria were significantly enriched in the lung tissues of cancer patients, and associated with reduced overall survival (OS). We also found that subjects with mutations in the epidermal growth factor receptor gene were less likely to experience the presence of Pseudomonas. aeruginosa. We found that the presence of CD8+ T-cells, CD4+ naive T-cells, dendritic cells, and CD4+ central memory T cells were associated with a good prognosis, while the presence of pro B-cells was associated with a poor prognosis. Furthermore, high clone numbers were associated with a high ImmuneScore for all immune receptor repertoires. Clone numbers and diversity were significantly higher in unpresented subjects compared to presented subjects. Our results provide insight into the microbiota of human lung cancer, and how its composition is linked to the tumor immune microenvironment, immune receptor repertoires, and OS.

The Fusion Gene Landscape in Taiwanese Patients with Non-Small Cell Lung Cancer.

BACKGROUND: Analyzing fusion gene transcripts may yield an effective approach for selecting cancer treatments. However, few comprehensive analyses of fusions in non-small cell lung cancer (NSCLC) patients have been performed. METHODS: We enrolled 54 patients with NSCLC, and performed RNA-sequencing (RNA-Seq). STAR (Spliced Transcripts Alignment to a Reference)-Fusion was used to identify fusions. RESULTS: Of the 218 fusions discovered, 24 had been reported and the rest were novel. Three fusions had the highest occurrence rates. After integrating our gene expression and fusion data, we found that samples harboring fusions containing ASXL1, CACNA1A, EEF1A1, and RET also exhibited increased expression of these genes. We then searched for mutations and fusions in cancer driver genes in each sample and found that nine patients carried both mutations and fusions in cancer driver genes. Furthermore, we found a trend for mutual exclusivity between gene fusions and mutations in the same gene, with the exception of DMD, and we found that EGFR mutations are associated with the number of fusion genes. Finally, we identified kinase gene fusions, and potentially druggable fusions, which may play roles in lung cancer therapy. CONCLUSION: The clinical use of RNA-Seq for detecting driver fusion genes may play an important role in the treatment of lung cancer.

Construction and Validation of a Prognostic Gene-Based Model for Overall Survival Prediction in Hepatocellular Carcinoma Using an Integrated Statistical and Bioinformatic Approach.

Hepatocellular carcinoma (HCC) is one of the most common lethal cancers worldwide and is often related to late diagnosis and poor survival outcome. More evidence is demonstrating that gene-based prognostic models can be used to predict high-risk HCC patients. Therefore, our study aimed to construct a novel prognostic model for predicting the prognosis of HCC patients. We used multivariate Cox regression model with three hybrid penalties approach including least absolute shrinkage and selection operator (Lasso), adaptive lasso and elastic net algorithms for informative prognostic-related genes selection. Then, the best subset regression was used to identify the best prognostic gene signature. The prognostic gene-based risk score was constructed using the Cox coefficient of the prognostic gene signature. The model was evaluated by Kaplan-Meier (KM) and receiver operating characteristic curve (ROC) analyses. A novel four-gene signature associated with prognosis was identified and the risk score was constructed based on the four-gene signature. The risk score efficiently distinguished the patients into a high-risk group with poor prognosis. The time-dependent ROC analysis revealed that the risk model had a good performance with an area under the curve (AUC) of 0.780, 0.732, 0.733 in 1-, 2- and 3-year prognosis prediction in The Cancer Genome Atlas (TCGA) dataset. Moreover, the risk score revealed a high diagnostic performance to classify HCC from normal samples. The prognosis and diagnosis prediction performances of risk scores were verified in external validation datasets. Functional enrichment analysis of the four-gene signature and its co-expressed genes involved in the metabolic and cell cycle pathways was constructed. Overall, we developed a novel-gene-based prognostic model to predict high-risk HCC patients and we hope that our findings can provide promising insight to explore the role of the four-gene signature in HCC patients and aid risk classification.

Mutation profile of non-small cell lung cancer revealed by next generation sequencing.

BACKGROUND: Precision therapy for lung cancer requires comprehensive genomic analyses. Specific effects of targeted therapies have been reported in Asia populations, including Taiwanese, but genomic studies have rarely been performed in these populations. METHOD: We enrolled 72 patients with non-small cell lung cancer, of whom 61 had adenocarcinoma, 10 had squamous cell carcinoma, and 1 had combined adenocarcinoma and squamous cell carcinoma. Whole-exome or targeted gene sequencing was performed. To identify trunk mutations, we performed whole-exome sequencing in two tumor regions in four patients. RESULTS: Nineteen known driver mutations in EGFR, PIK3CA, KRAS, CTNNB1, and MET were identified in 34 of the 72 tumors evaluated (47.22%). A comparison with the Cancer Genome Atlas dataset showed that EGFR was mutated at a much higher frequency in our cohort than in Caucasians, whereas KRAS and TP53 mutations were found in only 5.56% and 25% of our Taiwanese patients, respectively. We also identified new mutations in ARID1A, ARID2, CDK12, CHEK2, GNAS, H3F3A, KDM6A, KMT2C, NOTCH1, RB1, RBM10, RUNX1, SETD2, SF3B1, SMARCA4, THRAP3, TP53, and ZMYM2. Moreover, all ClinVar pathogenic variants were trunk mutations present in two regions of a tumor. RNA sequencing revealed that the trunk or branch genes were expressed at similar levels among different tumor regions. CONCLUSIONS: We identified novel variants potentially associated with lung cancer tumorigenesis. The specific mutation pattern in Taiwanese patients with non-small cell lung cancer may influence targeted therapies.

Comparison of multiple imputation algorithms and verification using whole-genome sequencing in the CMUH genetic biobank.

A genome-wide association study (GWAS) can be conducted to systematically analyze the contributions of genetic factors to a wide variety of complex diseases. Nevertheless, existing GWASs have provided highly ethnic specific data. Accordingly, to provide data specific to Taiwan, we established a large-scale genetic database in a single medical institution at the China Medical University Hospital. With current technological limitations, microarray analysis can detect only a limited number of single-nucleotide polymorphisms (SNPs) with a minor allele frequency of >1%. Nevertheless, imputation represents a useful alternative means of expanding data. In this study, we compared four imputation algorithms in terms of various metrics. We observed that among the compared algorithms, Beagle5.2 achieved the fastest calculation speed, smallest storage space, highest specificity, and highest number of high-quality variants. We obtained 15,277,414 high-quality variants in 175,871 people by using Beagle5.2. In our internal verification process, Beagle5.2 exhibited an accuracy rate of up to 98.75%. We also conducted external verification. Our imputed variants had a 79.91% mapping rate and 90.41% accuracy. These results will be combined with clinical data in future research. We have made the results available for researchers to use in formulating imputation algorithms, in addition to establishing a complete SNP database for GWAS and PRS researchers. We believe that these data can help improve overall medical capabilities, particularly precision medicine, in Taiwan.