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On page 1 showing 1 ~ 4 papers out of 4 papers

The Origins and Vulnerabilities of Two Transmissible Cancers in Tasmanian Devils.

  • Maximilian R Stammnitz‎ et al.
  • Cancer cell‎
  • 2018‎

Transmissible cancers are clonal lineages that spread through populations via contagious cancer cells. Although rare in nature, two facial tumor clones affect Tasmanian devils. Here we perform comparative genetic and functional characterization of these lineages. The two cancers have similar patterns of mutation and show no evidence of exposure to exogenous mutagens or viruses. Genes encoding PDGF receptors have copy number gains and are present on extrachromosomal double minutes. Drug screening indicates causative roles for receptor tyrosine kinases and sensitivity to inhibitors of DNA repair. Y chromosome loss from a male clone infecting a female host suggests immunoediting. These results imply that Tasmanian devils may have inherent susceptibility to transmissible cancers and present a suite of therapeutic compounds for use in conservation.


Base editing screens map mutations affecting interferon-γ signaling in cancer.

  • Matthew A Coelho‎ et al.
  • Cancer cell‎
  • 2023‎

Interferon-γ (IFN-γ) signaling mediates host responses to infection, inflammation and anti-tumor immunity. Mutations in the IFN-γ signaling pathway cause immunological disorders, hematological malignancies, and resistance to immune checkpoint blockade (ICB) in cancer; however, the function of most clinically observed variants remains unknown. Here, we systematically investigate the genetic determinants of IFN-γ response in colorectal cancer cells using CRISPR-Cas9 screens and base editing mutagenesis. Deep mutagenesis of JAK1 with cytidine and adenine base editors, combined with pathway-wide screens, reveal loss-of-function and gain-of-function mutations, including causal variants in hematological malignancies and mutations detected in patients refractory to ICB. We functionally validate variants of uncertain significance in primary tumor organoids, where engineering missense mutations in JAK1 enhanced or reduced sensitivity to autologous tumor-reactive T cells. We identify more than 300 predicted missense mutations altering IFN-γ pathway activity, generating a valuable resource for interpreting gene variant function.


Acute Immune Signatures and Their Legacies in Severe Acute Respiratory Syndrome Coronavirus-2 Infected Cancer Patients.

  • Sultan Abdul-Jawad‎ et al.
  • Cancer cell‎
  • 2021‎

Given the immune system's importance for cancer surveillance and treatment, we have investigated how it may be affected by SARS-CoV-2 infection of cancer patients. Across some heterogeneity in tumor type, stage, and treatment, virus-exposed solid cancer patients display a dominant impact of SARS-CoV-2, apparent from the resemblance of their immune signatures to those for COVID-19+ non-cancer patients. This is not the case for hematological malignancies, with virus-exposed patients collectively displaying heterogeneous humoral responses, an exhausted T cell phenotype and a high prevalence of prolonged virus shedding. Furthermore, while recovered solid cancer patients' immunophenotypes resemble those of non-virus-exposed cancer patients, recovered hematological cancer patients display distinct, lingering immunological legacies. Thus, while solid cancer patients, including those with advanced disease, seem no more at risk of SARS-CoV-2-associated immune dysregulation than the general population, hematological cancer patients show complex immunological consequences of SARS-CoV-2 exposure that might usefully inform their care.


Pan-cancer proteomic map of 949 human cell lines.

  • Emanuel Gonçalves‎ et al.
  • Cancer cell‎
  • 2022‎

The proteome provides unique insights into disease biology beyond the genome and transcriptome. A lack of large proteomic datasets has restricted the identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types are analyzed by mass spectrometry. Deploying a workflow to quantify 8,498 proteins, these data capture evidence of cell-type and post-transcriptional modifications. Integrating multi-omics, drug response, and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline reveals thousands of protein biomarkers of cancer vulnerabilities that are not significant at the transcript level. The power of the proteome to predict drug response is very similar to that of the transcriptome. Further, random downsampling to only 1,500 proteins has limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger) is a comprehensive resource available at https://cellmodelpassports.sanger.ac.uk.


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