Fibrolamellar carcinoma (FLC) is a unique liver cancer primarily affecting young adults and characterized by a fusion event between DNAJB1 and PRKACA. By analyzing RNA-sequencing data from The Cancer Genome Atlas (TCGA) for >9,100 tumors across ~30 cancer types, we show that the DNAJB1-PRKACA fusion is specific to FLCs. We demonstrate that FLC tumors (n = 6) exhibit distinct messenger RNA (mRNA) and long intergenic non-coding RNA (lincRNA) profiles compared to hepatocellular carcinoma (n = 263) and cholangiocarcinoma (n = 36), the two most common liver cancers. We also identify a set of mRNAs (n = 16) and lincRNAs (n = 4), including LINC00473, that distinguish FLC from ~25 other liver and non-liver cancer types. We confirm this unique FLC signature by analysis of two independent FLC cohorts (n = 20 and 34). Lastly, we validate the overexpression of one specific gene in the FLC signature, carbonic anhydrase XII (CA12), at the protein level by western blot and immunohistochemistry. Both the mRNA and lincRNA signatures support a major role for protein kinase A (PKA) signaling in shaping the FLC gene expression landscape, and present novel candidate FLC oncogenes that merit further investigation.
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http://dx.doi.org/10.1038/srep44653 | DOI Listing |
Hum Genomics
January 2025
Population Health Program, QIMR Berghofer Medical Research Institute, Herston, QLD, 4006, Australia.
Background: TP53 variant classification benefits from the availability of large-scale functional data for missense variants generated using cDNA-based assays. However, absence of comprehensive splicing assay data for TP53 confounds the classification of the subset of predicted missense and synonymous variants that are also predicted to alter splicing. Our study aimed to generate and apply splicing assay data for a prioritised group of 59 TP53 predicted missense or synonymous variants that are also predicted to affect splicing by either SpliceAI or MaxEntScan.
View Article and Find Full Text PDFCancer Cell Int
January 2025
Institute for Genome Engineered Animal Models of Human Diseases, National Center of Genetically Engineered Animal Models for International Research, Dalian Medical University, 9 West Section Lvshun South Road, Dalian, 116044, China.
Clear cell renal cell carcinoma (ccRCC) is a globally severe cancer with an unfavorable prognosis. PANoptosis, a form of cell death regulated by PANoptosomes, plays a role in numerous cancer types. However, the specific roles of genes associated with PANoptosis in the development and advancement of ccRCC remain unclear.
View Article and Find Full Text PDFBMC Genomics
January 2025
Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.
The E. coli strains harboring the polyketide synthase (pks) island encode the genotoxin colibactin, a secondary metabolite reported to have severe implications for human health and for the progression of colorectal cancer. The present study involves whole-genome-wide comparison and phylogenetic analysis of pks harboring E.
View Article and Find Full Text PDFCommun Med (Lond)
January 2025
Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Background: Gene signatures derived from transcriptomic-causal networks offer potential for tailoring clinical care in cancer treatment by identifying predictive and prognostic biomarkers. This study aimed to uncover such signatures in metastatic colorectal cancer (CRC) patients to aid treatment decisions.
Methods: We constructed transcriptomic-causal networks and integrated gene interconnectivity into overall survival (OS) analysis to control for confounding genes.
Nat Genet
January 2025
Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Single-cell genomics technologies have accelerated our understanding of cell-state heterogeneity in diverse contexts. Although single-cell RNA sequencing identifies rare populations that express specific marker transcript combinations, traditional flow sorting requires cell surface markers with high-fidelity antibodies, limiting our ability to interrogate these populations. In addition, many single-cell studies require the isolation of nuclei from tissue, eliminating the ability to enrich learned rare cell states based on extranuclear protein markers.
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