Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications. DIFFREG focuses on the differential regulation between transcription factors (TFs) and their target genes rather than differential gene expression and integrates transcriptome profiling with the human transcriptional regulatory network to analyze differential gene regulation between healthy and RCC cases. In this study, RNA-seq tissue samples ( = 1020) from the Cancer Genome Atlas (TCGA), including healthy and tumor subjects, were integrated with a comprehensive human TF-gene interactome dataset (1122603 interactions between 1289 TFs and 25177 genes). Comparative analysis of DIFFREG profiles, consisting of perturbed TF-gene interactions, from three common subtypes (clear cell RCC, papillary RCC and chromophobe RCC) revealed subtype-specific alterations, supporting the hypothesis that these signatures in the transcriptional regulome profiles may be considered potential biomarkers that may play an important role in elucidating the molecular mechanisms of RCC development and translating knowledge about the genetic basis of RCC into the clinic. In addition, these indicators may help oncologists make the best decisions for diagnosis and prognosis management.
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http://dx.doi.org/10.1089/omi.2023.0167 | DOI Listing |
Front Immunol
December 2024
The Federal Medical Biological Agency (FMBA of Russia), Moscow, Russia.
COVID-19 is characterized by systemic pro-inflammatory shifts with the development of serious alterations in the functioning of the immune system. Investigations of the gene expression changes accompanying the infection state provide insight into the molecular and cellular processes depending on the sickness severity and virus variants. Severe Delta COVID-19 has been characterized by the appearance of a monocyte subset enriched for proinflammatory gene expression signatures and a shift in ligand-receptor interactions.
View Article and Find Full Text PDFGenome Biol
December 2024
Department of Statistics, Stanford University, CA, Stanford, 94305, USA.
The inherent similarities between natural language and biological sequences have inspired the use of large language models in genomics, but current models struggle to incorporate chromatin interactions or predict in unseen cellular contexts. To address this, we propose EpiGePT, a transformer-based model designed for predicting context-specific human epigenomic signals. By incorporating transcription factor activities and 3D genome interactions, EpiGePT outperforms existing methods in epigenomic signal prediction tasks, especially in cell-type-specific long-range interaction predictions and genetic variant impacts, advancing our understanding of gene regulation.
View Article and Find Full Text PDFNature
November 2024
Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
Extrachromosomal DNA (ecDNA) presents a major challenge for cancer patients. ecDNA renders tumours treatment resistant by facilitating massive oncogene transcription and rapid genome evolution, contributing to poor patient survival. At present, there are no ecDNA-specific treatments.
View Article and Find Full Text PDFNature
November 2024
Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
The chromosomal theory of inheritance dictates that genes on the same chromosome segregate together while genes on different chromosomes assort independently. Extrachromosomal DNAs (ecDNAs) are common in cancer and drive oncogene amplification, dysregulated gene expression and intratumoural heterogeneity through random segregation during cell division. Distinct ecDNA sequences, termed ecDNA species, can co-exist to facilitate intermolecular cooperation in cancer cells.
View Article and Find Full Text PDFNature
November 2024
Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
Extrachromosomal DNA (ecDNA) is a major contributor to treatment resistance and poor outcome for patients with cancer. Here we examine the diversity of ecDNA elements across cancer, revealing the associated tissue, genetic and mutational contexts. By analysing data from 14,778 patients with 39 tumour types from the 100,000 Genomes Project, we demonstrate that 17.
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