CSSLdb: Discovery of cancer-specific synthetic lethal interactions based on machine learning and statistic inference.

Synthetic lethality (SL) occurs when the inactivation of two genes results in cell death while the inactivation of either gene alone is non-lethal. SL-based therapy has become a promising anti-cancer treatment option with the increasing researches and applications in clinical practice, while the specific therapeutic opportunities for various cancers have not yet been comprehensively investigated. Herein, we described a computational approach based on machine learning and statistical inference to discover the cancer-specific synthetic lethal interactions. First, Random Forest and One-Class SVM were used to perform cancer unbiased prediction of synthetic lethality. Then, two strategies, including mutual exclusivity and differential expression, were used to screen cancer-specific synthetic lethal interactions, resulting in 14,582 SL gene pairs in 33 cancer types. Finally, we developed a freely available database of CSSLdb (Cancer Specific Synthetic Lethality Database, http://www.tmliang.cn/CSSL/) to present cancer-specific synthetic lethal genetic interactions, which would enrich the relevant research and contribute to underlying therapy strategies based on synthetic lethality.

GBCdb: RNA expression landscapes and ncRNA-mRNA interactions in gallbladder carcinoma.

Gallbladder carcinoma (GBC), an aggressive malignant tumor of the biliary system, is characterized by high cellular heterogeneity and poor prognosis. Fewer data have been reported in GBC than other common cancer types. Multi-omics data will contribute to the understanding of the molecular mechanisms of cancer, cancer diagnosis and prognosis. Herein, to provide better understanding of the molecular events in GBC pathogenesis, we developed GBCdb ( http://tmliang.cn/gbc/ ), a user-friendly interface for the query and browsing of GBC-associated genes and RNA interaction networks using published multi-omics data, which also included experimentally supported data from different molecular levels. GBCdb will help to elucidate the potential biological roles of different RNAs and allow for the exploration of RNA interactions in GBC. These resources will provide an opportunity for unraveling the potential molecular features of Gallbladder carcinoma.

Systematic analysis of cancer-specific synthetic lethal interactions provides insight into personalized anticancer therapy.

The concept of synthetic lethality has great potential for anticancer therapy as a new strategy to specifically kill cancer cells while sparing normal cells. To further understand the potential molecular interactions and gene characteristics involved in synthetic lethality, we performed a comprehensive analysis of predicted cancer-specific genetic interactions. Many genes were identified as cancer-associated genes that contributed to multiple biological processes and pathways, and the gene features were not random, indicating their potential roles in human carcinogenesis. Some relevant genes detected in multiple cancers were prone to be enriched in specific biological progresses and pathways, especially processes associated with DNA damage, chromosome-related functions and cancer pathways. These findings strongly implicated potential roles for these genes in cancer pathophysiology and functional relationships, as well as applications for future anticancer drug discovery. Further experimental validation indicated that the synthetic lethal interaction of APC and GFER may provide a potential anticancer strategy for patients with APC-mutant colon cancer. These results will contribute to further exploration of synthetic lethal interactions and broader application of the concept of synthetic lethality in anticancer therapeutics.

A comprehensive multi-omics analysis reveals molecular features associated with cancer via RNA cross-talks in the Notch signaling pathway.

The Notch signaling has an important role in multiple cellular processes and is related to carcinogenic process. To understand the potential molecular features of the crucial Notch pathway, a comprehensive multi-omics analysis is performed to explore its contributions in cancer, mainly including analysis of somatic mutation landscape, pan-cancer expression, ncRNA regulation and potential prognostic power. The screened 22 Notch core genes are relative stable in DNA variation. Dynamic expression patterns are associated with the Notch activity, which are mainly regulated by multiple ncRNAs via interactions of ncRNA:mRNA and ceRNA networks. The Notch pathway shows a potential prognostic ability through integrating multi-omics features as well as their targets, and it is correlated with immune infiltration and maybe available drug targets, implying the potential role in individualized treatment. Collectively, all of these findings contribute to exploring crucial role of the key pathway in cancer pathophysiology and gaining mechanistic insights into cross-talks among RNAs and biological pathways, which indicates the possible application of the well-conserved Notch signaling pathway in precision medicine.

SLOAD: a comprehensive database of cancer-specific synthetic lethal interactions for precision cancer therapy via multi-omics analysis.

Synthetic lethality has been widely concerned because of its potential role in cancer treatment, which can be harnessed to selectively kill cancer cells via identifying inactive genes in a specific cancer type and further targeting the corresponding synthetic lethal partners. Herein, to obtain cancer-specific synthetic lethal interactions, we aimed to predict genetic interactions via a pan-cancer analysis from multiple molecular levels using random forest and then develop a user-friendly database. First, based on collected public gene pairs with synthetic lethal interactions, candidate gene pairs were analyzed via integrating multi-omics data, mainly including DNA mutation, copy number variation, methylation and mRNA expression data. Then, integrated features were used to predict cancer-specific synthetic lethal interactions using random forest. Finally, SLOAD (http://www.tmliang.cn/SLOAD) was constructed via integrating these findings, which was a user-friendly database for data searching, browsing, downloading and analyzing. These results can provide candidate cancer-specific synthetic lethal interactions, which will contribute to drug designing in cancer treatment that can promote therapy strategies based on the principle of synthetic lethality. Database URL http://www.tmliang.cn/SLOAD/.

NOV/CCN3 Promotes Cell Migration and Invasion in Intrahepatic Cholangiocarcinoma via miR-92a-3p.

Intrahepatic cholangiocarcinoma (ICC) is a common type of human cancer with a poor prognosis, and investigating the potential molecular mechanisms that can contribute to gene diagnosis and therapy. Herein, based on the recently concerned vertebrate-specific Cyr61/CTGF/NOV (CCN) gene family because of its important roles in diverse diseases, we obtained NOV/CCN3 to query for its potential roles in tumorigenesis via bioinformatics analysis. Experimental validations confirmed that both NOV mRNA and protein are up-regulated in two ICC cell lines, suggesting that it may promote cell migration and invasion by promoting EMT. To elucidate the detailed regulatory mechanism, miR-92a-3p is screened and identified as a negative regulatory small RNA targeting NOV, and further experimental validation demonstrates that miR-92a-3p contributes to NOV-mediated migration and invasion of ICC via the Notch signaling pathway. Our study reveals that NOV may be a potential target for diagnosing and treating ICC, which will provide experimental data and molecular theoretical foundation for cancer treatment, particularly for future precision medicine.

Protein profiling reveals potential isomiR-associated cross-talks among RNAs in cholangiocarcinoma.

Cholangiocarcinomas (CCAs) are tumors that arise from the cholangiocytes. Although some genes have been shown with important roles in pathological process, interactions or cross-talks among different RNAs are important to understand the detailed molecular mechanisms in cancer development, especially discussing cross-talks among isomiRs and other RNAs. Herein, to characterize crucial genes in CCA, the protein expression profile was performed to survey potential crucial mRNAs and related non-coding RNAs (ncRNAs) in mRNA-ncRNA network, mainly including miRNAs/isomiRs and lncRNAs. Deregulated mRNAs were firstly obtained if consistent expression patterns were found at protein and mRNA levels, and related miRNAs/isomiRs were screened according to regulatory relationships. Diverse isomiRs from a given miRNA locus also contributed to interactions between the small RNAs and target mRNAs, and miRNAs were further used to survey related lncRNAs to expand the interactions. Thus, several groups of RNAs were constructed as candidate competitive endogenous RNA (ceRNA) networks. Finally, we found that RAB11FIP1:miR-101-3p:MIR3142HG may be a potential ceRNA network, and the interactions among them may be more complex due to variety of isomiRs. Simultaneously, RAB11FIP1 and miR-194-5p were also detected other related lncRNAs (FBXL19-AS1, SNHG1 and PVT1) that may be crucial in coding-non-coding RNA regulatory network. Our results show that diverse isomiRs with sequence and expression heterogeneities contribute to ceRNA regulatory network that may have crucial roles in CCA, which will expand our understanding of interactions among diverse RNAs and their contributions in cancer development.

Screening and identification of haptoglobin showing its important role in pathophysiological process of gallbladder carcinoma.

Gallbladder cancer (GBC) with poor prognosis has been a major cause of cancer-related deaths worldwide. In this study, we aimed to screen and identify crucial genes in GBC through integrative analysis of multiple datasets and further experimental validation. A candidate crucial gene, up-regulated haptoglobin (HP), was firstly screened, and then further analysis and validation mainly focused on whether higher enrichment level of HP was responsible for pathophysiological process of GBC. HP was found with diverse expression patterns in various cancer types, and the dynamic expression patterns indicated its spatiotemporal characteristics in different tissues and disease stages, implicating its role in multiple biological processes. Further experimental validation showed that HP could promote the GBC-SD cell proliferation, migration and invasion, implying its role in pathophysiological process of GBC. HP may have a crucial role in occurrence and development of GBC, and it provides possibility as a potential biomarker or target in cancer prognosis and treatment.

Integrative omics analysis reveals relationships of genes with synthetic lethal interactions through a pan-cancer analysis.

Synthetic lethality is thought to play an important role in anticancer therapies. Herein, to understand the potential distributions and relationships between synthetic lethal interactions between genes, especially for pairs deriving from different sources, we performed an integrative analysis of genes at multiple molecular levels. Based on inter-species phylogenetic conservation of synthetic lethal interactions, gene pairs from yeast and humans were analyzed; a total of 37,588 candidate gene pairs containing 7,816 genes were collected. Of these, 49.74% of genes had 2-10 interactions, 22.93% were involved in hallmarks of cancer, and 21.61% were identified as core essential genes. Many genes were shown to have important biological roles via functional enrichment analysis, and 65 were identified as potentially crucial in the pathophysiology of cancer. Gene pairs with dysregulated expression patterns had higher prognostic values. Further screening based on mutation and expression levels showed that remaining gene pairs were mainly derived from human predicted or validated pairs, while most predicted pairs from yeast were filtered from analysis. Genes with synthetic lethality were further analyzed with their interactive microRNAs (miRNAs) at the isomiR level which have been widely studied as negatively regulatory molecules. The miRNA-mRNA interaction network revealed that many synthetic lethal genes contributed to the cell cycle (seven of 12 genes), cancer pathways (five of 12 genes), oocyte meiosis, the p53 signaling pathway, and hallmarks of cancer. Our study contributes to the understanding of synthetic lethal interactions and promotes the application of genetic interactions in further cancer precision medicine.