Gene expression signatures encompassing dozens to hundreds of genes have been associated with many important parameters of cancer, but mechanisms of their control are largely unknown. Here we present a method based on genetic linkage that can prospectively identify functional regulators driving large-scale transcriptional signatures in cancer. Using this method we show that the wound response signature, a poor-prognosis expression pattern of 512 genes in breast cancer, is induced by coordinate amplifications of MYC and CSN5 (also known as JAB1 or COPS5). This information enabled experimental recapitulation, functional assessment and mechanistic elucidation of the wound signature in breast epithelial cells.
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http://dx.doi.org/10.1038/ng1752 | DOI Listing |
Nat Commun
December 2024
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, 100871, Beijing, China.
Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines.
View Article and Find Full Text PDFNAR Genom Bioinform
December 2024
State Key Laboratory of Aridland Crop Science, Gansu Agricultural University, No. 1 Yingmen Village, Anning District, Lanzhou 730070, Gansu Province, China.
Research on the dynamic expression of genes in plants is important for understanding different biological processes. We used the large amounts of transcriptomic data from various plant sample sources that are publicly available to investigate whether the expression levels of a subset of highly variable genes (HVGs) can be used to accurately identify the phenotypes of plants. Using maize ( L.
View Article and Find Full Text PDFSci Rep
December 2024
BioSpyder Technologies, Inc., Carlsbad, CA, USA.
We report the development and performance of a novel genomics platform, TempO-LINC, for conducting high-throughput transcriptomic analysis on single cells and nuclei. TempO-LINC works by adding cell-identifying molecular barcodes onto highly selective and high-sensitivity gene expression probes within fixed cells, without having to first generate cDNA. Using an instrument-free combinatorial indexing approach, all probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 + cells per sample.
View Article and Find Full Text PDFBioorg Med Chem
December 2024
State Key Laboratory of Macromolecular Drugs and Large-scale Manufacturing, School of Pharmaceutical Sciences, Wenzhou Medical University, 1210 University Town, Wenzhou, Zhejiang 325035, China. Electronic address:
X-ray repair cross-complementing 2 (XRCC2), a critical protein in homologous recombination (HR), plays a significant role in the occurrence, progression, and drug resistance of colorectal cancer (CRC). In this study, a series of xanthohumol C derivatives were synthesized, and their anticancer activity was evaluated. The results revealed that A33 demonstrated the potent anticancer activity and effectively inhibited the proliferation of CRC cells in vitro.
View Article and Find Full Text PDFMalar J
December 2024
Institute of Tropical Medicine, Eberhard Karls University of Tübingen, Tübingen, Germany.
Background: Molecular methods play an important role in clinical trials assessing anti-malarial drugs and vaccines, as well as in epidemiological studies aimed at detecting Plasmodium species, especially when dealing with large sample sizes. Molecular techniques are more sensitive and generally have a higher throughput compared to the gold standard microscopy. Further optimization can be achieved with automation of nucleic acid isolation, allowing for rapid and precise extraction.
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