HRD effects on first-line adjuvant chemotherapy and PARPi maintenance therapy in Chinese ovarian cancer patients.

Homologous recombination deficiency (HRD) testing has been approved by FDA for selecting epithelial ovarian cancer (EOC) patients who may benefit from the first-line poly (ADP-ribose) polymerase inhibitor (PARPi) maintenance therapy. However, the effects of HRD on the clinical outcomes of first-line chemotherapy and first-line PARPi maintenance therapy have not been rigorously evaluated in Chinese EOC patients. Here, we developed an HRD assay and applied it to two large retrospectively collected Chinese EOC patient cohorts. In the first-line adjuvant chemotherapy cohort (FACT, N = 380), HRD status significantly improved PFS (median, 15.6 months vs. 9.4 months; HR, 0.688; 95% CI, 0.526-0.899; P = 0.003) and OS (median, 89.5 months vs. 60.9 months; HR, 0.636; 95% CI, 0.423-0.955; P = 0.008). In the first-line PARPi maintenance therapy cohort (FPMT, N = 83), HRD status significantly improved PFS (median, NA vs. 12 months; HR, 0.438; 95% CI, 0.201-0.957; P = 0.033) and OS (median, NA vs. NA months; HR, 0.12; 95% CI, 0.029-0.505; P = 0.001). Our results demonstrate that HRD status is a significant predictor for PFS and OS in both first-line chemotherapy and first-line PARPi maintenance therapy, providing strong real-world evidence for conducting genetic testing and improving clinical recommendations for Chinese EOC patients.

RNA editing increases the nucleotide diversity of SARS-CoV-2 in human host cells.

SARS-CoV-2 is a positive-sense, single-stranded RNA virus responsible for the COVID-19 pandemic. It remains unclear whether and to what extent the virus in human host cells undergoes RNA editing, a major RNA modification mechanism. Here we perform a robust bioinformatic analysis of metatranscriptomic data from multiple bronchoalveolar lavage fluid samples of COVID-19 patients, revealing an appreciable number of A-to-I RNA editing candidate sites in SARS-CoV-2. We confirm the enrichment of A-to-I RNA editing signals at these candidate sites through evaluating four characteristics specific to RNA editing: the inferred RNA editing sites exhibit (i) stronger ADAR1 binding affinity predicted by a deep-learning model built from ADAR1 CLIP-seq data, (ii) decreased editing levels in ADAR1-inhibited human lung cells, (iii) local clustering patterns, and (iv) higher RNA secondary structure propensity. Our results have critical implications in understanding the evolution of SARS-CoV-2 as well as in COVID-19 research, such as phylogenetic analysis and vaccine development.

Genomic characterization of co-existing neoplasia and carcinoma lesions reveals distinct evolutionary paths of gallbladder cancer.

Gallbladder carcinoma is the most common cancer of the biliary tract with dismal survival largely due to delayed diagnosis. Biliary tract intraepithelial neoplasia (BilIN) is the common benign tumor that is suspected to be precancerous lesions. However, the genetic and evolutionary relationships between BilIN and carcinoma remain unclear. Here we perform whole-exome sequencing of coexisting low-grade BilIN (adenoma), high-grade BilIN, and carcinoma lesions, and normal tissues from the same patients. We identify aging as a major factor contributing to accumulated mutations and a critical role of CTNNB1 mutations in these tumors. We reveal two distinct carcinoma evolutionary paths: carcinoma can either diverge earlier and evolve more independently or form through the classic adenoma/dysplasia-carcinoma sequence model. Our analysis suggests that extensive loss-of-heterozygosity and mutation events in the initial stage tend to result in a cancerous niche, leading to the subsequent BilIN-independent path. These results reframes our understanding of tumor transformation and the evolutionary trajectory of carcinogenesis in the gallbladder, laying a foundation for the early diagnosis and effective treatment of gallbladder cancer.

Multi-omics characterization of molecular features of gastric cancer correlated with response to neoadjuvant chemotherapy.

Neoadjuvant chemotherapy is a common treatment for patients with gastric cancer. Although its benefits have been demonstrated, neoadjuvant chemotherapy is underutilized in gastric cancer management, because of the lack of biomarkers for patient selection and a limited understanding of resistance mechanisms. Here, we performed whole-genome, whole-exome, and RNA sequencing on 84 clinical samples (including matched pre- and posttreatment tumors) from 35 patients whose responses to neoadjuvant chemotherapy were rigorously defined. We observed increased microsatellite instability and mutation burden in nonresponse tumors. Through comparisons of response versus nonresponse tumors and pre- versus posttreatment samples, we found that C10orf71 mutations were associated with treatment resistance, which was supported by drug response data and potentially through inhibition of cell cycle, and that MYC amplification correlated with treatment sensitivity, whereas MDM2 amplification showed the opposite pattern. Neoadjuvant chemotherapy also reshapes tumor-immune signaling and microenvironment. Our study provides a critical basis for developing precision neoadjuvant regimens.

CEAS: cis-regulatory element annotation system.

The recent availability of high-density human genome tiling arrays enables biologists to conduct ChIP-chip experiments to locate the in vivo-binding sites of transcription factors in the human genome and explore the regulatory mechanisms. Once genomic regions enriched by transcription factor ChIP-chip are located, genome-scale downstream analyses are crucial but difficult for biologists without strong bioinformatics support. We designed and implemented the first web server to streamline the ChIP-chip downstream analyses. Given genome-scale ChIP regions, the cis-regulatory element annotation system (CEAS) retrieves repeat-masked genomic sequences, calculates GC content, plots evolutionary conservation, maps nearby genes and identifies enriched transcription factor-binding motifs. Biologists can utilize CEAS to retrieve useful information for ChIP-chip validation, assemble important knowledge to include in their publication and generate novel hypotheses (e.g. transcription factor cooperative partner) for further study. CEAS helps the adoption of ChIP-chip in mammalian systems and provides insights towards a more comprehensive understanding of transcriptional regulatory mechanisms. The URL of the server is http://ceas.cbi.pku.edu.cn.