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Cancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2- breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.

Although recent advanced sequencing technologies have improved the resolution of genomic and proteomic data to better characterize molecular phenotypes, efficient computational tools to analyze and interpret the large-scale omic data are still needed. To address this, we have developed a network-based bioinformatic tool called Ollivier-Ricci curvature-omics (ORCO). ORCO incorporates gene interaction information with omic data into a biological network, and computes Ollivier-Ricci curvature (ORC) values for individual interactions. ORC, an edge-based measure, indicates network robustness and captures global gene signaling changes in functional cooperation using a consistent information passing measure, thereby helping identify therapeutic targets and regulatory modules in biological systems. This tool can be applicable to any data that can be represented as a network. ORCO is an open-source Python package and publicly available on GitHub at https://github.com/aksimhal/ORC-Omics.

Cancer transcriptional patterns exhibit both shared and unique features across diverse cancer types, but whether these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that cancer transcriptional diversity mirrors patterns in normal tissues optimized for distinct functional tasks. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2- breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients., Competing Interests: AUTHORS’ DISCLOSURES The authors declare no competing interests.

Objective: To investigate the effect of circRNA&#95;005647 on fibrotic phenotype of mouse cardiac fibroblasts (CFs) and explore its mechanism., Methods: We used an angiotensin Ⅱ (Ang-Ⅱ) capsule pump (daily dose of 1.46 mg/kg for 2 weeks) to establish a mouse model of myocardial fibrosis in C57BL/6 mice. Masson staining was used to detect myocardial fibrosis in the myocardium. The expression of circRNA&#95;005647 in the myocardium of Ang-Ⅱ-infused mice and in Ang-Ⅱ-treated CFs were detected with real-time PCR. Actinomycin D and RNase R exonuclease digestion were used to test the stability of circRNA&#95;005647 in mouse CFs. Over- expression of circRNA&#95;005647 was achieved in the CFs by infecting the cells with a recombinant circRNA&#95;005647 adenovirus (rAd-circRNA&#95;005647), and the expressions of Col1a1, Col3a1 and Acta2 were detected in the cells with real-time PCR and Western blotting. Dual luciferase reporter assay, RNA antisense purification and RNA Pull down assay were performed to identify the interaction between circRNA&#95;005647 and miR-27b-3p., Results: CircRNA&#95;005647 was up- regulated in the myocardium of Ang-Ⅱ- infused mice and in Ang-Ⅱ-treated mouse CFs ( P < 0.01). CircRNA&#95;005647 was more stable than its host gene Myosin IXA ( Myo9a ) in response to actinomycin D ( P < 0.01) and RNase R exonuclease treatment. The expressions of fibrosis-associated genes was down-regulated in the CFs over-expressing circRNA&#95; 005647 ( P < 0.05). Dual luciferase reporter assay, RNA antisense purification and RNA Pull down assay revealed the interaction between miR-27b-3p and circRNA&#95;005647. MiR-27b-3p obviously enhanced the fibrotic phenotype but reversed the inhibitory effect of circRNA&#95;005647 on the expression of fibrosis associated genes in the CFs ( P < 0.05)., Conclusions: CircRNA&#95;005647 is upregulated in cardiac fibrosis and inhibits the expression of fibrosis-related genes through sponging miR-27b-3p in mouse CFs.

Objective: To investigate the role of miR-199a-3p in cardiac fibrosis and the potential target of miR-199a-3p., Methods: Cardiac fibroblasts were isolated from C57BL/6 mice and cultured. The miR-199a-3p mimic and Smad1 siRNA were transiently transfected into the cardiac fibroblasts via liposome. Dual luciferase reporter assay was performed to confirm the interaction between miR-199a-3p and the 3'-UTR of Smad1. The expressions of Smad1 and fibrosis-related genes at the mRNA and protein levels in the cells after miR-199a-3p mimic transfection were determined using RT-qPCR and Western blotting, respectively. The expressions of Smad1, Smad3 and fibrosis-related genes at the protein level in cells transfected with miR-199a-3p mimic and Smad1 siRNA were detected using Western blotting., Results: Over-expression of miR-199a-3p significantly increased the expression of cardiac fibrosis-related genes in cultured mouse cardiac fibroblasts. Dual luciferase reporter assay revealed the interaction of miR-199a-3p with the 3'-UTR of Smad1. The results of RT-qPCR and Western blotting confirmed that miR-199a-3p inhibited Smad1 expression at the post- transcriptional level. Transfection with miR-199a-3p mimic and siRNA-mediated Smad1 silencing consistently activated the Smad3 signaling pathway and enhanced the expressions of cardiac fibrosis-related genes in the cardiac fibroblasts., Conclusions: As the target gene of miR-199a-3p, Smad1 mediates the pro-fibrotic effect of miR-199a-3p by activating the Smad3 signaling in cultured mouse cardiac fibroblasts.

Objective: To investigate the association of desmoplakin with the distribution and function of Nav1.5 by RNA silencing technology in HL-1 cells., Methods: HL-1 cells with desmoplakin expression suppression by RNA silencing were examined for desmoplakin and Nav1.5 protein expressions by Western blotting, and the distribution and co-location of desmoplakin and Nav1.5 protein were detected by immunofluorescence staining. Patch-clamp recording was applied to analyze the changes in whole-cell sodium current after desmoplakin silencing., Results: Compared with the untreated group and negative control group, the cells with desmoplakin silencing showed obviously reduced expressions of desmoplakin and Nav1.5 proteins. Co-localization of desmoplakin and Nav1.5 was detected at cell-cell contact in untreated and control conditions, and desmoplakin expression silencing induced a drastic redistribution of Nav1.5 with decreased peak current density (156.3∓6.2 vs 41.8∓3.1, n=6, P<0.05), a shift in voltage dependence of steady-state inactivation (-42 mV vs -61 mV, n=5, P<0.05), and prolonged time of recovery from inactivation., Conclusion: Desmoplakin silencing caused redistribution of Nav1.5 protein and also changes in its electrophysiological properties in HL-1 cells.