ArticleDiscover oncology2022
Identification of stromal microenvironment characteristics and key molecular mining in pancreatic cancer.
Article in Discover oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Establishment of M2 macrophage-related prognostic signature in pancreatic ductal adenocarcinoma.Discover oncology · 2025Article
- The construction and validation of ECM-related prognosis model in laryngeal squamous cell carcinoma.Heliyon · 2023Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
purposePancreatic cancer is one of the deadliest cancers worldwide. The extracellular matrix (ECM) microenvironment affects the drug sensitivity and prognosis of pancreatic cancer patients. This study constructed an 8-genes pancreatic ECM scoring (PECMS) model, to classify the ECM features of pancreatic cancer, analyze the impact of ECM features on survival and drug sensitivity, and mine key molecules that influence ECM features in pancreatic cancer.
methodsGSVA score calculation and clustering were performed in TCGA-PAAD patients. Lasso regression was used to construct the PECMS model. The association between PECMS and patient survival was analyzed and validated in the CPTAC-3 dataset of TCGA and our single-center retrospective cohort. The relationships between PECMS and features of the matrix microenvironment were analyzed. Finally, PECMS feature genes were screened and verified in pancreatic cancer specimens to select key genes associated with the ECM microenvironment.
resultThe survival of the PECMS-high group was significantly worse. The PECMS-high group showed higher oxidative stress levels, lower levels of antigen presentation- and MHC-I molecule-related pathways, and less immune effector cell infiltration. Data from IMvigor-210 cohort suggested that PECMS-low group patients were more sensitive to immune checkpoint blockers. The PECMS score was negatively correlated with chemotherapy drug sensitivity. The negative association of PECMS with survival and drug sensitivity was validated in our retrospective cohort. KLHL32 expression predicted lower oxidative stress level and more immune cells infiltrate in pancreatic cancer.
conclusionPECMS is an effective predictor of prognosis and drug sensitivity in pancreatic cancer patients. KLHL32 may play an important role in the construction of ECM, and the mechanism is worth further study.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.