A pan-cancer analysis of the oncogenic role of procollagen C-endopeptidase enhancer (PCOLCE) in human

Gao, Hui; Li, Qiuyun

doi:10.1097/md.0000000000032444

Cited by 6 publications

(4 citation statements)

References 42 publications

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“…Previous studies have suggested that PCOLCE-AS1 is downregulated in gastric cancer and acts as a tumor suppressor by regulating the expression of PCOLCE, which encodes an enzyme that enhances the activity of procollagen C-endopeptidase of procollagen types I-III [ 45 ]. Additionally, PCOLCE-AS1 may also modulate the immune infiltration and response of various immune cells, such as B cells, T cells, macrophages, neutrophils, and dendritic cells, in gastric cancer [ 46 ]. In this study, we found that the expression of PCOLCE-AS1 was positively correlated with periodontitis and significantly positively associated with plasma cell infiltration and the activation of most immune pathways, particularly the interferon receptor pathway.…”

Section: Discussionmentioning

confidence: 99%

RETRACTED ARTICLE: Identification and assessment of differentially expressed necroptosis long non-coding RNAs associated with periodontitis in human

He,

Zheng,

et al. 2023

BMC Oral Health

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Background Periodontitis is the most common oral disease and is closely related to immune infiltration in the periodontal microenvironment and its poor prognosis is related to the complex immune response. The progression of periodontitis is closely related to necroptosis, but there is still no systematic study of long non-coding RNA (lncRNA) associated with necroptosis for diagnosis and treatment of periodontitis. Material and methods Transcriptome data and clinical data of periodontitis and healthy populations were obtained from the Gene Expression Omnibus (GEO) database, and necroptosis-related genes were obtained from previously published literature. FactoMineR package in R was used to perform principal component analysis (PCA) for obtaining the necroptosis-related lncRNAs. The core necroptosis-related lncRNAs were screened by the Linear Models for Microarray Data (limma) package in R, PCA principal component analysis and lasso algorithm. These lncRNAs were then used to construct a classifier for periodontitis with logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the sensitivity and specificity of the model. The CIBERSORT method and ssGSEA algorithm were used to estimate the immune infiltration and immune pathway activation of periodontitis. Spearman’s correlation analysis was used to further verify the correlation between core genes and periodontitis immune microenvironment. The expression level of core genes in human periodontal ligament cells (hPDLCs) was detected by RT-qPCR. Results A total of 10 core necroptosis-related lncRNAs (10-lncRNAs) were identified, including EPB41L4A-AS1, FAM30A, LINC01004, MALAT1, MIAT, OSER1-DT, PCOLCE-AS1, RNF144A-AS1, CARMN, and LINC00582. The classifier for periodontitis was successfully constructed. The Area Under the Curve (AUC) was 0.952, which suggested that the model had good predictive performance. The correlation analysis of 10-lncRNAs and periodontitis immune microenvironment showed that 10-lncRNAs had an impact on the immune infiltration of periodontitis. Notably, the RT-qPCR results showed that the expression level of the 10-lncRNAs obtained was consistent with the chip analysis results. Conclusions The 10-lncRNAs identified from the GEO dataset had a significant impact on the immune infiltration of periodontitis and the classifier based on 10-lncRNAs had good detection efficiency for periodontitis, which provided a new target for diagnosis and treatment of periodontitis.

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Section: Discussionmentioning

confidence: 99%

RETRACTED ARTICLE: Identification and assessment of differentially expressed necroptosis long non-coding RNAs associated with periodontitis in human

He,

Zheng,

et al. 2023

BMC Oral Health

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“…Another enzyme driving collagen rearrangements and recently associated with immune infiltrating cells is PCOLCE, which localizes in the TME of several cancer types. Bioinformatic analyses highlighted that PCOLCE is a prognostic predictor for PAAD, thymoma and CES ( 51 ). Even if the molecular mechanisms behind this observation are still unknown, PCOLCE expression correlates with the extent of CD4 + T, CD8 + T, NK cell infiltration.…”

Section: Resultsmentioning

confidence: 99%

The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature

Fejza,

Carobolante,

Poletto

et al. 2023

Front. Immunol.

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IntroductionImmune-checkpoint inhibitors (ICIs) have emerged as a core pillar of cancer therapy as single agents or in combination regimens both in adults and children. Unfortunately, ICIs provide a long-lasting therapeutic effect in only one third of the patients. Thus, the search for predictive biomarkers of responsiveness to ICIs remains an urgent clinical need. The efficacy of ICIs treatments is strongly affected not only by the specific characteristics of cancer cells and the levels of immune checkpoint ligands, but also by other components of the tumor microenvironment, among which the extracellular matrix (ECM) is emerging as key player. With the aim to comprehensively describe the relation between ECM and ICIs’ efficacy in cancer patients, the present review systematically evaluated the current literature regarding ECM remodeling in association with immunotherapeutic approaches.MethodsThis review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines and was registered at the International Prospective Register of Systematic Reviews (PROSPERO, CRD42022351180). PubMed, Web of Science, and Scopus databases were comprehensively searched from inception to January 2023. Titles, abstracts and full text screening was performed to exclude non eligible articles. The risk of bias was assessed using the QUADAS-2 tool.ResultsAfter employing relevant MeSH and key terms, we identified a total of 5070 studies. Among them, 2540 duplicates, 1521 reviews or commentaries were found and excluded. Following title and abstract screening, the full text was analyzed, and 47 studies meeting the eligibility criteria were retained. The studies included in this systematic review comprehensively recapitulate the latest observations associating changes of the ECM composition following remodeling with the traits of the tumor immune cell infiltration. The present study provides for the first time a broad view of the tight association between ECM molecules and ICIs efficacy in different tumor types, highlighting the importance of ECM-derived proteolytic products as promising liquid biopsy-based biomarkers to predict the efficacy of ICIs.ConclusionECM remodeling has an important impact on the immune traits of different tumor types. Increasing evidence pinpoint at ECM-derived molecules as putative biomarkers to identify the patients that would most likely benefit from ICIs treatments.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022351180, identifier CRD42022351180.

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“…Dysregulation of this mechanism can lead to carcinogenesis and has been documented to be related to increased PCOLCE levels in multiple cancers. According to an analysis of The Cancer Genome Atlas, increased expression of PCOLCE can confer poor prognosis in esophageal cancers, although the frequency in which PCOLCE becomes dysregulated is relatively low [ 56 ]. Additionally, The Cancer Genome Atlas groups all types of esophageal cancers together, making its exact relationship to EAC difficult to identify.…”

Section: Discussionmentioning

confidence: 99%

miRNA profiling of esophageal adenocarcinoma using transcriptome analysis

Corlett,

Button,

Scheel

et al. 2024

Cancer Biomarkers

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Esophageal adenocarcinoma (EAC) occurs following a series of histological changes through epithelial-mesenchymal transition (EMT). A variable expression of normal and aberrant genes in the tissue can contribute to the development of EAC through the activation or inhibition of critical molecular signaling pathways. Gene expression is regulated by various regulatory factors, including transcription factors and microRNAs (miRs). The exact profile of miRs associated with the pathogenesis of EAC is largely unknown, though some candidate miRNAs have been reported in the literature. To identify the unique miR profile associated with EAC, we compared normal esophageal tissue to EAC tissue using bulk RNA sequencing. RNA sequence data was verified using qPCR of 18 selected genes. Fourteen were confirmed as being upregulated, which include CDH11, PCOLCE, SULF1, GJA4, LUM, CDH6, GNA12, F2RL2, CTSZ, TYROBP, and KDELR3 as well as the downregulation of UGT1A1. We then conducted Ingenuity Pathway Analysis (IPA) to analyze for novel miR-gene relationships through Causal Network Analysis and Upstream Regulator Analysis. We identified 46 miRs that were aberrantly expressed in EAC compared to control tissues. In EAC tissues, seven miRs were associated with activated networks, while 39 miRs were associated with inhibited networks. The miR-gene relationships identified provide novel insights into potentially oncogenic molecular pathways and genes associated with carcinogenesis in esophageal tissue. Our results revealed a distinct miR profile associated with dysregulated genes. The miRs and genes identified in this study may be used in the future as biomarkers and serve as potential therapeutic targets in EAC.

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A pan-cancer analysis of the oncogenic role of procollagen C-endopeptidase enhancer (PCOLCE) in human

Cited by 6 publications

References 42 publications

RETRACTED ARTICLE: Identification and assessment of differentially expressed necroptosis long non-coding RNAs associated with periodontitis in human

RETRACTED ARTICLE: Identification and assessment of differentially expressed necroptosis long non-coding RNAs associated with periodontitis in human

The entanglement of extracellular matrix molecules and immune checkpoint inhibitors in cancer: a systematic review of the literature

miRNA profiling of esophageal adenocarcinoma using transcriptome analysis

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