Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide and is derived from an accumulation of genetic and epigenetic changes. This study explored potential prognostic markers in CRC via the construction and in-depth analysis of a competing endogenous RNA (ceRNA) network, which was generated through a three-step process. First, we screened candidate hub genes in CRC as the primary gene markers to survey their related regulatory non-coding RNAs, miRNAs. Second, the interacting miRNAs were used to search for associated lncRNAs. Thus, candidate RNAs were first constructed into ceRNA networks based on close associations with miRNAs. Further analysis at the isomiR level was also performed for each miRNA locus to understand the detailed expression patterns of the multiple variants. Finally, RNAs were performed an in-depth analysis of expression correlations, which contributed to further screening and validation of potential RNAs with close correlations to each other. Using this approach, nine hub genes, 13 related miRNAs, and 29 candidate lncRNAs were collected and used to construct the ceRNA network. Further in-depth analysis identified the MFAP5-miR-200b-3p-AC005154.6 axis as a potential prognostic marker in CRC. MFAP5 and miR-200b-3p have previously been reported to play important roles in tumorigenesis. These RNAs showed potential prognostic values, and the combination of them may have more sensitivity than using them alone. In conclusion, MFAP5, miR-200b-3p, and AC005154.6 may have potential prognostic value in CRC and may provide a prognostic reference for this patient population.

This study aimed to discuss the potential roles of isomiRs of miR-27 family in metabolisms associated with disease via analyses of their evolution, expression, and function. miR-27b-3p was relatively highly expressed in liver cancer samples compared to miR-27a-3p and miR-27-5p loci. The diversity of isomiRs in miR-27-3p locus is similar to that of miRNAs among homologous genes. IsomiRs exhibited variable expression across different cancer tissue types, and some of them were abnormally expressed in ob/ob mice. Further experimental validation indicated that the protein expression of metabolism-related proteins, including PEPCK, G6Pase, FAS, and CPT1A, were significantly suppressed when canonical miR-27b was transfected into AML-12 cells. In contrast, the expression of these proteins was only slightly inhibited by isomiR-27b-1 or isomiR-27b-2 after transfection into AML-12 cells. These observations support that isomiRs exhibiting sequence divergence are functional regulatory molecules, and that they may contribute to biological processes via coordinated interactions in regulatory networks.

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/

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Cholangiocarcinoma (CCA), an aggressive tumor with poor prognosis, is a malignant cancer with increasing incidence and mortality rates. It is important to survey crucial genes in CCA to find and design potential drug targets, especially for those genes associated with cell proliferation that is a key biological process in tumorgenesis. Herein, we surveyed genes associated with cell proliferation via a comprehensive pan-cancer analysis. Candidate genes were further analyzed using multiple approaches, including cross-analysis from diverse molecular levels, examination of potential function and interactions, and additional experimental validation. We primarily screened 15 potential genes based on 11 validated genes, and these 26 genes were further examined to delineate their biological functions and potential roles in cancer treatment. Several of them were involved synthetically lethal genetic interactions, especially for RECQL4, TOP2A, MKI67 and ASPM, indicating their potential roles in drug design and cancer treatment. Further experimental validation indicated that some genes were significantly upregulated in several cancer cell lines, implying their important roles in tumorigenesis. Our study identifies some genes associated with cell proliferation, which may be potential future targets in molecular targeted therapy.