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Multidimensional analyses identify genes of high priority for pancreatic cancer research
Zeribe C. Nwosu, … , Marina Pasca di Magliano, Costas A. Lyssiotis
Zeribe C. Nwosu, … , Marina Pasca di Magliano, Costas A. Lyssiotis
Published January 7, 2025
Citation Information: JCI Insight. 2025;10(4):e174264. https://doi.org/10.1172/jci.insight.174264.
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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 5

Consistent genes correlate with poor cancer prognostic features.

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Consistent genes correlate with poor cancer prognostic features.
(A) Ven...
(A) Venn diagram showing overlap between CUGs or CDGs and genes expressed by PDAC basal-like or classical subtypes. The basal-like versus classical subtype genes included are statistically upregulated or downregulated (P < 0.05) in 2 or more datasets, namely, TCGA (n = 31 basal-like vs. 31 classical), GSE71729 (Moffitt dataset, n = 27 basal-like vs. 27 classical), and Puleo (n = 64 basal-like vs. 64 classical tumor samples). Genes in red/green are selected examples. (B) Heatmap depicting topmost upregulated or downregulated genes in proliferation-high PDAC. *Indicates proliferation markers used for the tumor stratification and included as positive controls. Genes included are statistically up-/downregulated in proliferation-high relative to proliferation-low tumors in 2 or more of TCGA (n = 64 proliferation-high vs. 86 proliferation-low), GSE71729 (n = 77 proliferation-high vs. 68 proliferation-low), and Puleo (n = 99 proliferation-high vs. 210 proliferation-low) tumors (P < 0.05). Pro, proliferation. (C) Pathway annotation of 783 CUGs and 588 CDGs that overlapped with genes differentially expressed in proliferation-high vs. -low tumors in at least 2 datasets. cAMP, cyclic adenosine monophosphate; cGMP, cyclic guanosine monophosphate; PKG, protein kinase G. (D) Venn diagrams showing CUGs and, below, CDGs overlapping with genes in liver metastasis compared with normal liver tissues from GSE71729 and GSE19279 datasets (P < 0.05). See Supplemental Methods for sample sizes/types. (E) Pathway annotation of the CUGs and CDGs that overlapped between liver metastasis compared with normal liver tissues. PI3K, phosphoinositide 3-kinase; ECM, extracellular matrix. (F) Kaplan-Meier (KM) overall survival (OS) plots (log-rank test, P < 0.05) of genes that predicted survival in the clinical cohorts analyzed. Tumor sample size: TCGA (n = 146), GSE71729 (n = 125), Puleo (n = 288); and ICGC (n = 267). (G) Topmost genes that predicted OS in at least 3 of the 4 pancreatic adenocarcinoma datasets, i.e., TCGA, Puleo et al., GSE71729/Moffitt, and International Cancer Genome Consortium (IGCG) datasets. High expression of the genes in green predicts “better” outcome, whereas those in red predict “worse” outcome.

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