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Multidimensional analyses identify genes of high priority for pancreatic cancer research
Zeribe C. Nwosu, Heather M. Giza, Maya Nassif, Verodia Charlestin, Rosa E. Menjivar, Daeho Kim, Samantha B. Kemp, Peter Sajjakulnukit, Anthony Andren, Li Zhang, William K.M. Lai, Ian Loveless, Nina Steele, Jiantao Hu, Biao Hu, Shaomeng Wang, Marina Pasca di Magliano, Costas A. Lyssiotis
Zeribe C. Nwosu, Heather M. Giza, Maya Nassif, Verodia Charlestin, Rosa E. Menjivar, Daeho Kim, Samantha B. Kemp, Peter Sajjakulnukit, Anthony Andren, Li Zhang, William K.M. Lai, Ian Loveless, Nina Steele, Jiantao Hu, Biao Hu, Shaomeng Wang, Marina Pasca di Magliano, Costas A. Lyssiotis
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Research Article Gastroenterology Oncology

Multidimensional analyses identify genes of high priority for pancreatic cancer research

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Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a drug-resistant and lethal cancer. Identification of the genes that consistently show altered expression across patient cohorts can expose effective therapeutic targets and strategies. To identify such genes, we separately analyzed 5 human PDAC microarray datasets. We defined genes as “consistent” if upregulated or downregulated in 4 or more datasets (adjusted P < 0.05). The genes were subsequently queried in additional datasets, including single-cell RNA-sequencing data, and we analyzed their pathway enrichment, tissue specificity, essentiality for cell viability, and association with cancer features, e.g., tumor subtype, proliferation, metastasis, and poor survival outcome. We identified 2,010 consistently upregulated and 1,928 downregulated genes, of which more than 50% to our knowledge were uncharacterized in PDAC. These genes spanned multiple processes, including cell cycle, immunity, transport, metabolism, signaling, and transcriptional/epigenetic regulation — cell cycle and glycolysis being the most altered. Several upregulated genes correlated with cancer features, and their suppression impaired PDAC cell viability in prior CRISPR/Cas9 and RNA interference screens. Furthermore, the upregulated genes predicted sensitivity to bromodomain and extraterminal (epigenetic) protein inhibition, which, in combination with gemcitabine, disrupted amino acid metabolism and in vivo tumor growth. Our results highlight genes for further studies in the quest for PDAC mechanisms, therapeutic targets, and biomarkers.

Authors

Zeribe C. Nwosu, Heather M. Giza, Maya Nassif, Verodia Charlestin, Rosa E. Menjivar, Daeho Kim, Samantha B. Kemp, Peter Sajjakulnukit, Anthony Andren, Li Zhang, William K.M. Lai, Ian Loveless, Nina Steele, Jiantao Hu, Biao Hu, Shaomeng Wang, Marina Pasca di Magliano, Costas A. Lyssiotis

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Figure 4

scRNA-seq data showing the expression of the consistent genes in tumor and surrounding cell population.

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scRNA-seq data showing the expression of the consistent genes in tumor a...
(A) Uniform manifold approximation and projections (UMAPs) of single-cell RNA-sequencing (scRNA-seq) data of human PDAC, depicting various cell populations and cell type marker plots. KRT19, keratin 19; KRT8, keratin 8 (pancreatic ductal epithelial markers); AMY2A, amylase α2A; CTRB2, chymotrypsinogen B2 (pancreatic acinar cell markers); FOXP3, forkhead box P3 (regulatory T cell [Treg] marker); GZMB, granzyme B (cytotoxic T/natural killer [NK] cell marker); ACTA2, actin α2 smooth muscle; COL1A1, collagen type I α1 chain (fibroblast markers); CD14, cluster of differentiation 14; APOE, apolipoprotein E; C1QA; complement C1q A chain (macrophage/myeloid cell markers); HBA2, hemoglobin subunit α2; HBB, hemoglobin subunit β (red blood cell markers). Sample size: n = 61 primary tumors. (B) UMAPs showing cell populations expressing CUGs that showed tumor-specific upregulation in microarrays and laser capture microdissection dataset (in Figure 3) and (C) CDGs that showed tumor-specific downregulation. (D) UMAPs showing consistently upregulated glycolysis genes that emerged as more tumor-specific (upper row, except PFKM) or ubiquitously expressed in most other cell types (lower row). On the right is a schematic summary showing the glycolysis steps associated with the displayed genes. *Consistent in 3 of 5 datasets shown in Figure 1.

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