Background & Aims: The identification of colorectal cancer (CRC) molecular subtypes has prognostic and potentially diagnostic value for patients, yet reliable subtyping remains unavailable in the clinic. The current consensus molecular subtype (CMS) classification in CRCs is based on complex RNA expression patterns quantified at the gene level. The clinical application of these methods, however, is challenging due to high uncertainty of single-sample classification and associated costs.
View Article and Find Full Text PDFInference of gene regulatory networks from gene perturbation experiments is the most reliable approach for investigating interdependence between genes. Here, we describe the initial gene perturbations, expression measurements, and preparation steps, followed by network modeling using TopNet. Summarization and visualization of the estimated networks and optional genetic testing of dependencies revealed by the network model are demonstrated.
View Article and Find Full Text PDFMalignant cell transformation and the underlying reprogramming of gene expression require the cooperation of multiple oncogenic mutations. This cooperation is reflected in the synergistic regulation of non-mutant downstream genes, so-called cooperation response genes (CRGs). CRGs affect diverse hallmark features of cancer cells and are not known to be functionally connected.
View Article and Find Full Text PDFMetabolic reprogramming is critical to oncogenesis, but the emergence and function of this profound reorganization remain poorly understood. Here we find that cooperating oncogenic mutations drive large-scale metabolic reprogramming, which is both intrinsic to cancer cells and obligatory for the transition to malignancy. This involves synergistic regulation of several genes encoding metabolic enzymes, including the lactate dehydrogenases LDHA and LDHB and mitochondrial glutamic pyruvate transaminase 2 (GPT2).
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