Evolutionary dependency of cancer mutations in gene pairs inferred by nonsynonymous-synonymous mutation ratios.

BACKGROUND: Determining the impact of somatic mutations requires understanding the functional relationship of genes acquiring mutations; however, it is largely unknown how mutations in functionally related genes influence each other. METHODS: We employed non-synonymous-to-synonymous or dNdS ratios to evaluate the evolutionary dependency (ED) of gene pairs, assuming a mutation in one gene of a gene pair can affect the evolutionary fitness of mutations in its partner genes as mutation context. We employed PanCancer- and tumor type-specific mutational profiles to infer the ED of gene pairs and evaluated their biological relevance with respect to gene dependency and drug sensitivity. RESULTS: We propose that dNdS ratios of gene pairs and their derived cdNS (context-dependent dNdS) scores as measure of ED distinguishing gene pairs either as synergistic (SYN) or antagonistic (ANT). Mutation contexts can induce substantial changes in the evolutionary fitness of mutations in the paired genes, e.g., IDH1 and IDH2 mutation contexts lead to substantial increase and decrease of dNdS ratios of ATRX indels and IDH1 missense mutations corresponding to SYN and ANT relationship with positive and negative cdNS scores, respectively. The impact of gene silencing or knock-outs on cell viability (genetic dependencies) often depends on ED, suggesting that ED can guide the selection of candidates for synthetic lethality such as TCF7L2-KRAS mutations. Using cell line-based drug sensitivity data, the effects of targeted agents on cell lines are often associated with mutations of genes exhibiting ED with the target genes, informing drug sensitizing or resistant mutations for targeted inhibitors, e.g., PRSS1 and CTCF mutations as resistant mutations to EGFR and BRAF inhibitors for lung adenocarcinomas and melanomas, respectively. CONCLUSIONS: We propose that the ED of gene pairs evaluated by dNdS ratios can advance our understanding of the functional relationship of genes with potential biological and clinical implications.

A Subset of Microsatellite Unstable Cancer Genomes Prone to Short Insertions over Deletions Is Associated with Elevated Anticancer Immunity.

Deficiencies in DNA mismatch repair (MMRd) leave characteristic footprints of microsatellite instability (MSI) in cancer genomes. We used data from the Cancer Genome Atlas and International Cancer Genome Consortium to conduct a comprehensive analysis of MSI-associated cancers, focusing on indel mutational signatures. We classified MSI-high genomes into two subtypes based on their indel profiles: deletion-dominant (MMRd-del) and insertion-dominant (MMRd-ins). Compared with MMRd-del genomes, MMRd-ins genomes exhibit distinct mutational and transcriptomic features, including a higher prevalence of T>C substitutions and related mutation signatures. Short insertions and deletions in MMRd-ins and MMRd-del genomes target different sets of genes, resulting in distinct indel profiles between the two subtypes. In addition, indels in the MMRd-ins genomes are enriched with subclonal alterations that provide clues about a distinct evolutionary relationship between the MMRd-ins and MMRd-del genomes. Notably, the transcriptome analysis indicated that MMRd-ins cancers upregulate immune-related genes, show a high level of immune cell infiltration, and display an elevated neoantigen burden. The genomic and transcriptomic distinctions between the two types of MMRd genomes highlight the heterogeneity of genetic mechanisms and resulting genomic footprints and transcriptomic changes in cancers, which has potential clinical implications.

Cellular abundance-based prognostic model associated with deregulated gene expression of leukemic stem cells in acute myeloid leukemia.

Background: Previous studies have reported that genes highly expressed in leukemic stem cells (LSC) may dictate the survival probability of patients and expression-based cellular deconvolution may be informative in forecasting prognosis. However, whether the prognosis of acute myeloid leukemia (AML) can be predicted using gene expression and deconvoluted cellular abundances is debatable. Methods: Nine different cell-type abundances of a training set composed of the AML samples of 422 patients, were used to build a model for predicting prognosis by least absolute shrinkage and selection operator Cox regression. This model was validated in two different validation sets, TCGA-LAML and Beat AML (n = 179 and 451, respectively). Results: We introduce a new prognosis predicting model for AML called the LSC activity (LSCA) score, which incorporates the abundance of 5 cell types, granulocyte-monocyte progenitors, common myeloid progenitors, CD45RA + cells, megakaryocyte-erythrocyte progenitors, and multipotent progenitors. Overall survival probabilities between the high and low LSCA score groups were significantly different in TCGA-LAML and Beat AML cohorts (log-rank p-value = 3.3×10-4 and 4.3×10-3, respectively). Also, multivariate Cox regression analysis on these two validation sets shows that LSCA score is independent prognostic factor when considering age, sex, and cytogenetic risk (hazard ratio, HR = 2.17; 95% CI 1.40-3.34; p < 0.001 and HR = 1.20; 95% CI 1.02-1.43; p < 0.03, respectively). The performance of the LSCA score was comparable to other prognostic models, LSC17, APS, and CTC scores, as indicated by the area under the curve. Gene set variation analysis with six LSC-related functional gene sets indicated that high and low LSCA scores are associated with upregulated and downregulated genes in LSCs. Conclusion: We have developed a new prognosis prediction scoring system for AML patients, the LSCA score, which uses deconvoluted cell-type abundance only.

Development of virus-induced genome editing methods in Solanaceous crops.

Genome editing (GE) using CRISPR/Cas systems has revolutionized plant mutagenesis. However, conventional transgene-mediated GE methods have limitations due to the time-consuming generation of stable transgenic lines expressing the Cas9/single guide RNA (sgRNA) module through tissue cultures. Virus-induced genome editing (VIGE) systems have been successfully employed in model plants, such as Arabidopsis thaliana and Nicotiana spp. In this study, we developed two VIGE methods for Solanaceous plants. First, we used the tobacco rattle virus (TRV) vector to deliver sgRNAs into a transgenic tomato (Solanum lycopersicum) line of cultivar Micro-Tom expressing Cas9. Second, we devised a transgene-free GE method based on a potato virus X (PVX) vector to deliver Cas9 and sgRNAs. We designed and cloned sgRNAs targeting Phytoene desaturase in the VIGE vectors and determined optimal conditions for VIGE. We evaluated VIGE efficiency through deep sequencing of the target gene after viral vector inoculation, detecting 40.3% and 36.5% mutation rates for TRV- and PVX-mediated GE, respectively. To improve editing efficiency, we applied a 37°C heat treatment, which increased the editing efficiency by 33% to 46% and 56% to 76% for TRV- and PVX-mediated VIGE, respectively. To obtain edited plants, we subjected inoculated cotyledons to tissue culture, yielding successful editing events. We also demonstrated that PVX-mediated GE can be applied to other Solanaceous crops, such as potato (Solanum tuberosum) and eggplant (Solanum melongena). These simple and highly efficient VIGE methods have great potential for generating genome-edited plants in Solanaceous crops.

Longitudinal Transcription Profiling of Bladder Cancers Dictate the Response to BCG Treatment and Disease Progression.

Although the intravesical instillation of Bacillus Calmette-Guerin (BCG) is widely used as adjuvant treatment for nonmuscle-invasive bladder cancers, the clinical benefit is variable across patients, and the molecular mechanisms underlying the sensitivity to BCG administration and disease progression are poorly understood. To establish the molecular signatures that predict the responsiveness and disease progression of bladder cancers treated with BCG, we performed transcriptome sequencing (RNA-seq) for 13 treatment-naïve and 22 post-treatment specimens obtained from 14 bladder cancer patients. To overcome disease heterogeneity, we used non-negative matrix factorization to identify the latent molecular features associated with drug responsiveness and disease progression. At least 12 molecular features were present, among which the immune-related feature was associated with drug responsiveness, indicating that pre-treatment anti-cancer immunity might dictate BCG responsiveness. We also identified disease progression-associated molecular features indicative of elevated cellular proliferation in post-treatment specimens. The progression-associated molecular features were validated in an extended cohort of BCG-treated bladder cancers. Our study advances understanding of the molecular mechanisms of BCG activity in bladder cancers and provides clinically relevant gene markers for evaluating and monitoring patients.