Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes.

Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.

Targeting PDGF signaling of cancer-associated fibroblasts blocks feedback activation of HIF-1α and tumor progression of clear cell ovarian cancer.

Ovarian clear cell carcinoma (OCCC) is a gynecological cancer with a dismal prognosis; however, the mechanism underlying OCCC chemoresistance is not well understood. To explore the intracellular networks associated with the chemoresistance, we analyze surgical specimens by performing integrative analyses that combine single-cell analyses and spatial transcriptomics. We find that a chemoresistant OCCC subpopulation with elevated HIF activity localizes mainly in areas populated by cancer-associated fibroblasts (CAFs) with a myofibroblastic phenotype, which is corroborated by quantitative immunostaining. CAF-enhanced chemoresistance and HIF-1α induction are recapitulated in co-culture assays, which show that cancer-derived platelet-derived growth factor (PDGF) contributes to the chemoresistance and HIF-1α induction via PDGF receptor signaling in CAFs. Ripretinib is identified as an effective receptor tyrosine kinase inhibitor against CAF survival. In the co-culture system and xenograft tumors, ripretinib prevents CAF survival and suppresses OCCC proliferation in the presence of carboplatin, indicating that combination of conventional chemotherapy and CAF-targeted agents is effective against OCCC.

Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data.

Many disease-associated genomic variants disrupt gene function through abnormal splicing. With the advancement of genomic medicine, identifying disease-associated splicing associated variants has become more important than ever. Most bioinformatics approaches to detect splicing associated variants require both genome and transcriptomic data. However, there are not many datasets where both of them are available. In this study, we develop a methodology to detect genomic variants that cause splicing changes (more specifically, intron retention), using transcriptome sequencing data alone. After evaluating its sensitivity and precision, we apply it to 230,988 transcriptome sequencing data from the publicly available repository and identified 27,049 intron retention associated variants (IRAVs). In addition, by exploring positional relationships with variants registered in existing disease databases, we extract 3,000 putative disease-associated IRAVs, which range from cancer drivers to variants linked with autosomal recessive disorders. The in-silico screening framework demonstrates the possibility of near-automatically acquiring medical knowledge, making the most of massively accumulated publicly available sequencing data. Collections of IRAVs identified in this study are available through IRAVDB ( https://iravdb.io/ ).

Whole genome sequencing analysis identifies recurrent structural alterations in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is the predominant type of esophageal cancer in the Asian region, including Japan. A previous study reported mutational landscape of Japanese ESCCs by using exome sequencing. However, somatic structural alterations were yet to be explored. To provide a comprehensive mutational landscape, we performed whole genome sequencing (WGS) analysis of biopsy specimens from 20 ESCC patients in a Japanese population. WGS analysis identified non-silent coding mutations of TP53, ZNF750 and FAT1 in ESCC. We detected six mutational signatures in ESCC, one of which showed significant association with smoking status. Recurrent structural variations, many of which were chromosomal deletions, affected genes such as LRP1B, TTC28, CSMD1, PDE4D, SDK1 and WWOX in 25%-30% of tumors. Somatic copy number amplifications at 11q13.3 (CCND1), 3q26.33 (TP63/SOX2), and 8p11.23 (FGFR1) and deletions at 9p21.3 (CDKN2A) were identified. Overall, these multi-dimensional view of genomic alterations improve the understanding of the ESCC development at molecular level and provides future prognosis and therapeutic implications for ESCC in Japan.

Genomic landscape of colitis-associated cancer indicates the impact of chronic inflammation and its stratification by mutations in the Wnt signaling.

Inflammatory bowel disease (IBD) increases the risk of colorectal cancer, known as colitis-associated cancer (CAC). It is still unclear what driver mutations are caused by chronic inflammation and lead to CAC development. To get insight into this issue, we investigated somatic alterations in CAC. We performed exome sequencing of 22 fresh CACs and targeted sequencing of 43 genes on 90 archive specimens from Japanese CAC patients, of which 58 were ulcerative colitis (UC) and 32 were Crohn's disease (CD). Consistently with the previous reports, TP53 was commonly mutated (66%) whereas APC, KRAS and SMAD4 were mutated less frequently (16%, 11% and 11%, respectively). Mucinous CD-CACs in the anus, an Asian-specific subtype of CD-CAC, had less somatic mutations in our target genes. We also found that RNF43, a negative regulator of the Wnt signaling, was somatically mutated in a significant fraction of CACs (10 of 90; 11%). Two lines of evidence indicated that somatic mutations of RNF43 were related to chronic inflammation. First, somatic mutations of RNF43 were significantly associated with longer duration of IBD. Second, clinico-pathological features suggested many of the APC-mutated CACs were actually sporadic colorectal cancer whereas RNF43-mutated CACs did not have this tendency. RNA-Seq analysis showed that RNF43-mutated CACs had elevated expression of c-Myc and its target genes, suggesting that RNF43 is a bona fide driver of CAC development. This study provides evidence that somatic mutation of RNF43 is the driver genetic alteration that links chronic inflammation and cancer development in about 10% of CACs.