Outcomes for cancer patients vary greatly even within the same tumor type, and characterization of molecular subtypes of cancer holds important promise for improving prognosis and personalized treatment. This promise has motivated recent efforts to produce large amounts of multidimensional genomic (multi-omic) data, but current algorithms still face challenges in the integrated analysis of such data. Here we present Cancer Integration via Multikernel Learning (CIMLR), a new cancer subtyping method that integrates multi-omic data to reveal molecular subtypes of cancer. We apply CIMLR to multi-omic data from 36 cancer types and show significant improvements in both computational efficiency and ability to extract biologically meaningful cancer subtypes. The discovered subtypes exhibit significant differences in patient survival for 27 of 36 cancer types. Our analysis reveals integrated patterns of gene expression, methylation, point mutations, and copy number changes in multiple cancers and highlights patterns specifically associated with poor patient outcomes.

/pdf/multi-omic-tumor-data-reveal-diversity-of-molecular-10vzn7pruv.pdf

Multi-omic tumor data reveal diversity of molecular mechanisms that correlate with survival

Breast cancer is the second-most common cancer and second-leading cause of cancer mortality in American women. The dysregulation of microRNAs (miRNAs) plays a key role in almost all cancers, including breast cancer. We comprehensively analyzed miRNA expression, global gene expression, and patient survival from the Cancer Genomes Atlas (TCGA) to identify clinically relevant miRNAs and their potential gene targets in breast tumors. In our analysis, we found that increased expression of 12 mature miRNAs-hsa-miR-320a, hsa-miR-361-5p, hsa-miR-103a-3p, hsa-miR-21-5p, hsa-miR-374b-5p, hsa-miR-140-3p, hsa-miR-25-3p, hsa-miR-651-5p, hsa-miR-200c-3p, hsa-miR-30a-5p, hsa-miR-30c-5p, and hsa-let-7i-5p -each predicted improved breast cancer survival. Of the 12 miRNAs, miR-320a, miR-361-5p, miR-21-5p, miR-103a-3p were selected for further analysis. By correlating global gene expression with miRNA expression and then employing miRNA target prediction analysis, we suggest that the four miRNAs may exert protective phenotypes by targeting breast oncogenes that contribute to patient survival. We propose that miR-320a targets the survival-associated genes RAD51, RRP1B, and TDG; miR-361-5p targets ARCN1; and miR-21-5p targets MSH2, RMND5A, STAG2, and UBE2D3. The results of our stringent bioinformatics approach for identifying clinically relevant miRNAs and their targets indicate that miR-320a, miR-361-5p, and miR-21-5p may contribute to breast cancer survival.

/pdf/identification-of-micrornas-as-breast-cancer-prognosis-1v2rihjg8d.pdf

Identification of MicroRNAs as Breast Cancer Prognosis Markers through the Cancer Genome Atlas

Outcomes for cancer patients vary greatly even within the same tumor type, and characterization of molecular subtypes of cancer holds important promise for improving prognosis and personalized treatment. This promise has motivated recent efforts to produce large amounts of multidimensional genomic (9multi-omic9) data, but current algorithms still face challenges in the integrated analysis of such data. Here we present Cancer Integration via Multikernel Learning (CIMLR), a new cancer subtyping method that integrates multi-omic data to reveal molecular subtypes of cancer. We apply CIMLR to multi-omic data from 36 cancer types and show significant improvements in both computational efficiency and ability to extract biologically meaningful cancer subtypes. The discovered subtypes exhibit significant differences in patient survival for 27 of 36 cancer types. Our analysis reveals integrated patterns of gene expression, methylation, point mutations and copy number changes in multiple cancers and highlights patterns specifically associated with poor patient outcomes.

/pdf/multi-omic-tumor-data-reveal-diversity-of-molecular-76yh1dc2fm.pdf

UBE2T promotes radiation resistance in non-small cell lung cancer via inducing epithelial-mesenchymal transition and the ubiquitination-mediated FOXO1 degradation.

Ubiquitin-conjugating enzymes (E2s) are one of the three enzymes required by the ubiquitin-proteasome pathway to connect activated ubiquitin to target proteins via ubiquitin ligases. E2s determine the connection type of the ubiquitin chains, and different types of ubiquitin chains regulate the stability and activity of substrate proteins. Thus, E2s participate in the regulation of a variety of biological processes. In recent years, the importance of E2s in human health and diseases has been particularly emphasized. Studies have shown that E2s are dysregulated in variety of cancers, thus it might be a potential therapeutic target. However, the molecular basis of E2s as a therapeutic target has not been described systematically. We reviewed this issue from the perspective of the special position and role of E2s in the ubiquitin-proteasome pathway, the structure of E2s and biological processes they are involved in. In addition, the inhibitors and microRNAs targeting E2s are also summarized. This article not only provides a direction for the development of effective drugs but also lays a foundation for further study on this enzyme in the future.

https://www.mdpi.com/1422-0067/22/7/3440/pdf

The Molecular Basis of Ubiquitin-Conjugating Enzymes (E2s) as a Potential Target for Cancer Therapy

Ubiquitin-conjugating enzyme UBE2D3 is an important member of the ubiquitin-proteasome pathways. Our previous study showed that the expression of UBE2D3 was negatively related to human telomerase reverse transcriptase (hTERT) and radioresistance in human breast cancer cells. However, in esophageal carcinoma, the exact effects and mechanisms of UBE2D3 in radioresistance remain unclear. This study shows that UBE2D3 knockdown was associated with significant increases in radioresistance to X-rays, telomerase activity, telomere length, and telomere shelterins. UBE2D3 knockdown-mediated radioresistance was related to a decrease in the spontaneous and ionizing radiation-induced apoptosis, resulting from a decrease in the Bax/Bcl-2 ratio. Furthermore, UBE2D3 downregulation was associated with increased G1-S phase transition and prolonged IR-induced G2/M arrest through over expression of cyclin D1, decrease of CDC25A expression and promotion of the ATM/ATR-Chk1-CDC25C pathway. Moreover, UBE2D3 downregulation reduced spontaneous DNA double-strand breaks and accelerated the repair of DNA damage induced by IR. The current data thus demonstrate that UBE2D3 downregulation enhances radioresistance by increased telomere homeostasis and prolonged IR-induced G2/M arrest, but decreases the IR-induced apoptosis and the number of DNA damage foci. These results suggest that UBE2D3 might be a potential molecular target to improve radiotherapy effects in esophageal carcinoma.

/pdf/downregulation-of-ubiquitin-conjugating-enzyme-ube2d3-uro4tptr3p.pdf

Downregulation of Ubiquitin-conjugating Enzyme UBE2D3 Promotes Telomere Maintenance and Radioresistance of Eca-109 Human Esophageal Carcinoma Cells.

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Downregulation of Ubiquitin-conjugating Enzyme UBE2D3 Promotes Telomere Maintenance and Radioresistance of Eca-109 Human Esophageal Carcinoma Cells.