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Big data in basic and translational cancer research

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Summary: Histomorphology and DNA methylation profiling are both important diagnostic methods in cancer pathology. While histomorphology is already well-established, DNA methylation profiling serves as an adjunct tool to improve the accuracy of pathological diagnosis. Besides identifying new entities and consolidating morphologically disparate cancers, DNA methylation profiling holds great promise for non-invasive cancer detection and classification.

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Summary: Using a network-based approach, 407 master regulator proteins were identified to canalize individual cancer samples into 112 transcriptionally distinct tumor subtypes. These proteins were organized into 24 pan-cancer master regulator block modules regulating key cancer hallmarks and predictive of patient outcome. Genomic alterations were predicted to induce aberrant MR activity, providing insight into mechanisms linking tumor genetics and transcriptional identity.
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Synthetic lethality across normal tissues is strongly associated with cancer risk, onset, and tumor suppressor specificity

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21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer

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Summary: Synthetic lethality is becoming an important cancer therapeutic paradigm, but comprehensive selective treatment opportunities for various tumors have not been fully explored. The Synthetic Lethality Knowledge Graph (SLKG) integrates data on different tumors, drugs, and drug targets to provide therapy options for synthetic lethality and synthetic dosage lethality, prioritizing the identification of repurposable drug candidates and combinations with supporting evidence for novel tumor therapy discovery.

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Summary: Tyrosine kinase inhibitors have clinical effectiveness in treating certain subsets of cancers with receptor tyrosine kinase somatic mutations, but limited duration of response and development of drug resistance are common issues. Single-cell RNA sequencing revealed multiple cancer cell subpopulations with epigenetic changes and variable therapeutic sensitivity. Overrepresented gene ontologies associated with drug tolerance include epithelial-to-mesenchymal transition, drug metabolism, and vesicle transport. Combination therapy targeting specific drug tolerant cell subpopulations shows promise in inhibiting drug resistance.

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Synthetic lethality-mediated precision oncology via the tumor transcriptome

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Summary: Precision oncology has advanced significantly by targeting actionable mutations in cancer driver genes and exploring the utility of tumor transcriptome to guide patient treatment. SELECT, a precision oncology framework harnessing genetic interactions, has shown predictive accuracy in 80% of tested clinical trials and is publicly available for academic use, providing a foundation for future prospective clinical studies.
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Michael Klein et al.

Summary: The CRSO method can infer combinations of alterations that cooperate to drive tumor formation in individual patients, identifying driver gene combinations and new synergies that provide novel insights into cancer etiology and personalized treatments.

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Darlan C. Minussi et al.

Summary: Breast tumors and cell lines consist of numerous subclones organized into a few major superclones. Following clonal TP53 mutations, loss-of-heterozygosity events, and genome doubling, primary tumors undergo a period of transient genomic instability, with ongoing copy number evolution during expansion. Subcloned daughter cells demonstrate genomic rediversification, showing that triple-negative breast cancers continually evolve chromosome aberrations and maintain subclonal diversity during primary tumor growth.

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Ruishan Liu et al.

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Deep learning in histopathology: the path to the clinic

Jeroen van der Laak et al.

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Andrey Fedorov et al.

Summary: The NCI's CRDC aims to establish a national cloud-based data science infrastructure, with IDC as a new component dedicated to supporting cancer imaging research. IDC enables a broad spectrum of cancer researchers to easily access and explore the value of deidentified imaging data and support integrated analyses with nonimaging data.

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A Transcriptionally Distinct Subpopulation of Healthy Acinar Cells Exhibit Features of Pancreatic Progenitors and PDAC

Vishaka Gopalan et al.

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