Deep single-cell transcriptome analysis reveals transitional cancer cell state in the pancreatic cancer tumor microenvironment associated with poor prognosis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE194247 | GEO | 2022/05/01
REPOSITORIES: GEO
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Project description:Deep single-cell transcriptome analysis reveals transitional cancer cell state in the pancreatic cancer tumor microenvironment associated with poor prognosis
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Project description:Background & Aims: Loss of ataxia-telangiectasia mutated, occurring in patients with multiple primary malignancies, including pancreatic cancer, is associated with poor prognosis. This study investigated the detailed molecular mechanism through which ataxia-telangiectasia mutated expression affects the prognosis of pancreatic-cancer patients Methods: Ataxia-telangiectasia mutated and phosphorylated ataxia-telangiectasia mutated levels in pancreatic-cancer patients who underwent surgical resection were analyzed using immunohistochemistry staining. RNA sequencing was performed on ataxia-telangiectasia mutated-knockdown pancreatic-cancer cells to elucidate the mechanism underlying the involvement of ataxia-telangiectasia mutated in pancreatic cancer. Results: Immunohistochemical analysis showed that 15.3% and 27.8% of clinical samples had low levels of ataxia-telangiectasia mutated and phosphorylated ataxia-telangiectasia mutated, respectively. Low phosphorylated ataxia-telangiectasia mutated expression substantially reduced overall and disease-free survival in pancreatic-cancer patients. Loss of ataxia-telangiectasia mutated promoted MET and NTN1 over-expression via hypoxia-inducible factor-1α, thereby enhancing pancreatic-cancer cell proliferation and migration. Conclusions: These results demonstrate that the loss of ataxia-telangiectasia mutated activates downstream proto-oncogenes, inhibits apoptosis, and promotes tumor growth; moreover, loss of phosphorylated ataxia-telangiectasia mutated leads to poor prognosis in pancreatic-cancer patients. Thus, ataxia-telangiectasia mutated may serve as a potential molecular marker to monitor patient prognosis and as a potential target for pancreatic cancer therapy
2023-02-13 | GSE224882 | GEO
Project description:We identified five distinct functional subclusters of pancreatic cancer cells and six distinct cancer-associated fibroblast subclusters. We deeply profiled their characteristics, and we found that these subclusters successfully deconvoluted most of the features suggested in bulk transcriptome analysis of pancreatic cancer. Among those subclusters, we identified a novel cancer cell subcluster, Ep_VGLL1, showing intermediate characteristics between the extremities of basal-like and classical dichotomy, despite its prognostic value. Molecular features of Ep_VGLL1 suggest its transitional properties between basal-like and classical subtypes, which is strongly supported by spatial transcriptome data.
2023-11-17 | GSE235449 | GEO
Project description:We identified five distinct functional subclusters of pancreatic cancer cells and six distinct cancer-associated fibroblast subclusters. We deeply profiled their characteristics, and we found that these subclusters successfully deconvoluted most of the features suggested in bulk transcriptome analysis of pancreatic cancer. Among those subclusters, we identified a novel cancer cell subcluster, Ep_VGLL1, showing intermediate characteristics between the extremities of basal-like and classical dichotomy, despite its prognostic value. Molecular features of Ep_VGLL1 suggest its transitional properties between basal-like and classical subtypes, which is strongly supported by spatial transcriptome data.
2023-11-17 | GSE235315 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE14987: Expression data from ERBB2 over-expression and EGF stimulation in MCF10A cells GSE14988: Expression data from DHT stimulation vs. control in LNCaP cells Refer to individual Series
2010-02-21 | E-GEOD-14990 | biostudies-arrayexpress
Project description:Pancreatic ductal adenocarcinoma (PDAC) is characterized by the presence of relatively few tumor cells surrounded a heterocellular non-cancerous cell population embedded in extracellular matrix, collectively named stroma. Despite the recognition that the stroma is an important contributor to the typically poor outcome of PDAC, its analysis has been hampered by the analysis of bulk tissue. Similar issues have precluded meaningful analysis of the epithelial compartment. Here, we present the proteome analysis of a set of sixteen lasercapture microdissected PDAC samples, investigating tumor and stroma, together with bulk tumor samples, yielding the deepest PDAC proteomic to date.
2021-09-08 | PXD011289 | Pride
Project description:BackgroundPrevious studies have shown that RNA Polymerase III Subunit G (POLR3G) has oncogenic effects in cultured cells and mice. However, the role of POLR3G in transitional cell carcinoma (TCC) has not been reported. This study explores the potential of POLR3G as a novel molecular marker for TCC.MethodsThe RNA sequencing data and clinical information of patients with TCC were downloaded from The Cancer Genome Atlas official website. Transcriptome analysis was performed as implemented in the edgeR package to explore whether POLR3G was up-regulated in TCC tissues compared to normal bladder tissues. The expression of POLR3G in bladder cancer cell line T24 and human uroepithelial cell line SV-HUC-1 were detected via quantitative real time polymerase chain reaction (qRT-PCR). Correlations between POLR3G expression and clinicopathological characteristics were analyzed using Mann-Whitney U test or Kruskal-Wallis H test. Clinicopathological characteristics associated with overall survival were explored using the Kaplan-Meier method and Cox regression analyses. Gene set enrichment analysis (GSEA) was performed to explore the associated gene sets enriched in different POLR3G expression phenotypes and the online tool Tumor IMmune Estimation Resource (TIMER) was used to explore the correlation between POLR3G expression and tumor immune infiltration in TCC.ResultsTranscriptome analysis showed that POLR3G was significantly up-regulated in TCC tissues compared to normal bladder tissues. Furthermore, qRT-PCR revealed high expression of POLR3G in T24 cells compared to SV-HUC-1 cells. Overall, POLR3G expression was associated with race, tumor status, tumor subtype, T classification, and pathological stage. Kaplan-Meier survival analysis revealed that higher POLR3G expression was associated with lower overall survival. The univariate Cox regression model revealed that age at diagnosis, pathological stage, and POLR3G expression were associated with prognosis of TCC patients. Further multivariate analyses identified these three clinicopathological characteristics as independent prognostic factors for overall survival. GSEA analysis showed that several gene sets associated with tumor development and metastasis, including TGF-β signaling, PI3K-AKT-mTOR signaling, and IL6-JAK-STAT3 signaling, were significantly enriched in POLR3G high expression phenotype. Immune infiltration analysis revealed that the expression of POLR3G was significantly correlated with infiltrating levels of immune cells, including CD8+ T cells, neutrophils, and dendritic cells; and the expression of POLR3G was also significantly correlated with the expression of immune checkpoint molecules, such as PD1, PD-L1, PD-L2, CTLA4, LAG3, HAVCR2, and TIGIT.ConclusionsPOLR3G was up-regulated in TCC and high POLR3G expression correlated with poor prognosis. POLR3G can potentially be used as a prognostic marker for TCC and might be of great value in predicting the response to immunotherapy.
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Project description:Gene expression signatures are used in the clinic as prognostic tools to determine the risk of individual patients with localized breast tumors developing distant metastasis. We lack a clear understanding, however, of whether these correlative biomarkers link to a common biological network that regulates metastasis. We find that the c-MYC oncoprotein coordinately regulates the expression of 13 different "poor-outcome" cancer signatures. In addition, functional inactivation of MYC in human breast cancer cells specifically inhibits distant metastasis in vivo and invasive behavior in vitro of these cells. These results suggest that MYC oncogene activity (as marked by "poor-prognosis" signature expression) may be necessary for the translocation of poor-outcome human breast tumors to distant sites.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2010-02-01 | GSE14990 | GEO
Project description:Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.
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