| 1. |
- Reyna, Matthew A, et al.
(author)
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Pathway and network analysis of more than 2500 whole cancer genomes
- 2020
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11
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Journal article (peer-reviewed)abstract
- The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
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| 2. |
- Schott, Benjamin H., et al.
(author)
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Modeling of variables in cellular infection reveals CXCL10 levels are regulated by human genetic variation and the Chlamydia-encoded CPAF protease
- 2020
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 10:1
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Journal article (peer-reviewed)abstract
- Susceptibility to infectious diseases is determined by a complex interaction between host and pathogen. For infections with the obligate intracellular bacterium Chlamydia trachomatis, variation in immune activation and disease presentation are regulated by both host genetic diversity and pathogen immune evasion. Previously, we discovered a single nucleotide polymorphism (rs2869462) associated with absolute abundance of CXCL10, a pro-inflammatory T-cell chemokine. Here, we report that levels of CXCL10 change during C. trachomatis infection of cultured cells in a manner dependent on both host and pathogen. Linear modeling of cellular traits associated with CXCL10 levels identified a strong, negative correlation with bacterial burden, suggesting that C. trachomatis actively suppresses CXCL10. We identified the pathogen-encoded factor responsible for this suppression as the chlamydial protease- or proteasome-like activity factor, CPAF. Further, we applied our modeling approach to other host cytokines in response to C. trachomatis and found evidence that RANTES, another T-cell chemoattractant, is actively suppressed by Chlamydia. However, this observed suppression of RANTES is not mediated by CPAF. Overall, our results demonstrate that CPAF suppresses CXCL10 to evade the host cytokine response and that modeling of cellular infection parameters can reveal previously unrecognized facets of host-pathogen interactions.
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