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Lung Adenocarcinoma Transcriptomic Analysis Predicts Adenylate Kinase Signatures Contributing to Tumor Progression and Negative Patient Prognosis.

ABSTRACT: The ability to detect and respond to hypoxia within a developing tumor appears to be a common feature amongst most cancers. This hypoxic response has many molecular drivers, but none as widely studied as Hypoxia-Inducible Factor 1 (HIF-1). Recent evidence suggests that HIF-1 biology within lung adenocarcinoma (LUAD) may be associated with expression levels of adenylate kinases (AKs). Using LUAD patient transcriptome data, we sought to characterize AK gene signatures related to lung cancer hallmarks, such as hypoxia and metabolic reprogramming, to identify conserved biological themes across LUAD tumor progression. Transcriptomic analysis revealed perturbation of HIF-1 targets to correlate with altered expression of most AKs, with AK4 having the strongest correlation. Enrichment analysis of LUAD tumor AK4 gene signatures predicts signatures involved in pyrimidine, and by extension, nucleotide metabolism across all LUAD tumor stages. To further discriminate potential drivers of LUAD tumor progression within AK4 gene signatures, partial least squares discriminant analysis was used at LUAD stage-stage interfaces, identifying candidate genes that may promote LUAD tumor growth or regression. Collectively, these results characterize regulatory gene networks associated with the expression of all nine human AKs that may contribute to underlying metabolic perturbations within LUAD and reveal potential mechanistic insight into the complementary role of AK4 in LUAD tumor development.

SUBMITTER: Chacon-Barahona JA

PROVIDER: S-EPMC8705281 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundExosomes play a role in intercellular communication and participate in the interaction between pancreatic ductal adenocarcinoma (PDAC) cells and immune cells. Macrophages can receive tumor cell-derived exosomes to polarize into M2-type macrophages, which can enhance the invasion and metastasis of pancreatic cancer, leading to poor prognosis. However, the mechanism by which pancreatic cancer cell-derived exosomes promote M2-type macrophages is still unclear.MethodsM2 macrophage-associated exosome-derived key module genes were identified by differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) analysis using exoRbase 2.0, The Cancer Genome Atlas (TCGA), and The International Cancer Genome Consortium (ICGC) databases. Multivariate Cox regression analysis was used to identify key prognostic genes and obtain regression coefficients to establish prognostic signature. Immune infiltration, tumor mutations, and GSEA among different risk groups were compared. exoRbase 2.0, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), HPA, and TISCH2 databases were used to further analyze the expression pattern of S100A9 in pancreatic cancer. In vitro experiments, cell-derived exosome isolation, quantitative polymerase chain reaction (qPCR), western blot, flow cytometry analysis, cell transfection, transwell assay, and CCK-8 assay were applied to investigate the roles of S100A9 in macrophage M2 polarization and tumor progression.ResultsThe key genes of PDAC-derived exosomes promoting M2-type macrophage polarization were identified, and a risk score model was established. The risk score is related to the expression of common immune checkpoints, immune score, and stromal score, and the tumor mutational burden and biological function of high- and low-risk groups were also different. S100A9 was positively correlated with M2-type macrophage marker. In addition, scRNA-seq data from the TISCH2 database revealed that S100A9 is predominantly expressed in pancreatic cancer cells and mono/macrophage cells, suggesting that S100A9 in pancreatic cancer cells could be received by macrophages, thereby inducing macrophage polarization. In vitro, we used exosomes from BxPC-3 cell lines to coculture macrophages and found that macrophages were mainly polarized toward M2 type, which further promoted the proliferation and metastasis of PDAC.ConclusionsOur study established a reliable risk score model for PDAC-derived exosomes and M2 macrophages, identified the important role of S100A9 in macrophage M2 polarization, which provides a new strategy for the diagnosis and treatment of PDAC, and strengthened the understanding of the mechanism of tumor development and metastasis.

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Lung Adenocarcinoma Transcriptomic Analysis Predicts Adenylate Kinase Signatures Contributing to Tumor Progression and Negative Patient Prognosis.

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