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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.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.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.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.

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.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.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.Unique genomic alterations were observed in our Taiwanese HCC patients. Molecular classification using apoptosis-related genes could lead to new therapeutic approaches for HCC.

Analysis of circulating tumor DNA (ctDNA) offers an unbiased and noninvasive way to assess the genetic profiles of tumors. This study aimed to analyze mutations in ctDNA and their correlation with tissue mutations in patients with a variety of cancers. We included 21 cancer patients treated with surgical resection for whom we collected paired tissue and plasma samples. Next-generation sequencing (NGS) of all exons was performed in a targeted human comprehensive cancer panel consisting of 275 genes. Six patients had at least one mutation that was concordant between tissue and ctDNA sequencing. Among all mutations (n = 35) detected by tissue and blood sequencing, 20% (n = 7) were concordant at the gene level. Tissue and ctDNA sequencing identified driver mutations in 66.67% and 47.62% of the tested samples, respectively. Tissue and ctDNA NGS detected actionable alterations in 57.14% and 33.33% of patients, respectively. When somatic alterations identified by each test were combined, the total proportion of patients with actionable mutations increased to 71.43%. Moreover, variants of unknown significance that were judged likely pathogenic had a higher percentage in ctDNA exclusively. Across six representative genes (PIK3CA, CTNNB1, AKT1, KRAS, TP53, and MET), the sensitivity and specificity of detection using mutations in tissue sample as a reference were 25 and 96.74%, respectively. This study indicates that tissue NGS and ctDNA NGS are complementary rather than exclusive approaches; these data support the idea that ctDNA is a promising tool to interrogate cancer genetics.