Identification of ZDHHC1 as a Pyroptosis Inducer and Potential Target in the Establishment of Pyroptosis-Related Signature in Localized Prostate Cancer.
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ABSTRACT:
SUBMITTER: Luo CG
PROVIDER: S-EPMC9800907 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
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Identification of ZDHHC1 as a Pyroptosis Inducer and Potential Target in the Establishment of Pyroptosis-Related Signature in Localized Prostate Cancer.
Luo Cheng-Gong CG Gui Cheng-Peng CP Huang Gao-Wei GW Chen Jin-Long JL Li Jia-Ying JY Li Peng-Ju PJ Xu Quan-Hui QH Wang Ying-Han YH Zhu Jiang-Quan JQ Liang Hui H Wang Zhu Z Deng Qiong Q Cao Jia-Zheng JZ Luo Jun-Hang JH Lu Jun J Chen Wei W
Oxidative medicine and cellular longevity 20221222
Pyroptosis or cellular inflammatory necrosis is a programmed cell death kind. Accumulating evidence shows that pyroptosis plays a crucial role in the invasion, metastasis, and proliferation of tumor cells, thus affecting the prognosis of tumors and therapeutic effects. Prostate cancer (PCa), a common malignancy among men, is associated with inflammation. Pathophysiological effects of pyroptosis on tumor development and progression, as well as the mediation of PCa, are known, but its effects on t ...[more]
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Project description:BackgroundPyroptosis and prostate cancer (PCa) are closely related. The role of pyroptosis-related long non-coding RNAs (lncRNAs) (PRLs) in PCa remains elusive. This study aimed to explore the relationship between PRL and PCa prognosis.MethodsGene expression and clinical signatures were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. A PRL risk prediction model was established by survival random forest analysis and least absolute shrinkage and selection operator regression. Functional enrichment, immune status, immune checkpoints, genetic mutations, and drug susceptibility analyses related to risk scores were performed by the single-sample gene set enrichment analysis, gene set variation analysis, and copy number variation analysis. PRL expression was verified in PCa cells. Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine, wound healing, transwell, and Western blotting assay were used to detect the proliferation, migration, invasion, and pyroptosis of PCa cells, respectively.ResultsPrognostic features based on six PRL (AC129507.1, AC005253.1, AC127502.2, AC068580.3, LIMD1-AS1, and LINC01852) were constructed, and patients in the high-score group had a worse prognosis than those in the low-score group. This feature was determined to be independent by Cox regression analysis, and the area under the curve of the 1-, 3-, and 5-year receiver operating characteristic curves in the testing cohort was 1, 0.93, and 0.92, respectively. Moreover, the external cohort validation confirmed the robustness of the PRL risk prediction model. There was a clear distinction between the immune status of the two groups. The expression of multiple immune checkpoints was also reduced in the high-score group. Gene mutation proportion in the high-score group increased, and the sensitivity to drugs increased significantly. Six PRLs were upregulated in PCa cells. Silencing of AC005253.1 inhibited cell proliferation, migration, and invasion in DU145 and PC-3 cells. Moreover, silencing of AC005253.1 promoted pyroptosis and inflammasome AIM2 expression.ConclusionsOverall, we constructed a prognostic model of PCa with six PRLs and identified their expression in PCa cells. The experimental verification showed that AC005253.1 could affect the proliferation, migration, and invasion abilities of PCa cells. Meanwhile, AC005253.1 may play an important role in PCa by affecting pyroptosis through the AIM2 inflammasome. This result requires further research for verification.
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Project description:PurposeTo provide a comprehensive review of the means by which to optimize target volume definition for the purposes of treatment planning for patients with intact prostate cancer with a specific emphasis on focal boost volume definition.MethodsHere we conduct a narrative review of the available literature summarizing the current state of knowledge on optimizing target volume definition for the treatment of localized prostate cancer.ResultsHistorically, the treatment of prostate cancer included a uniform prescription dose administered to the entire prostate with or without coverage of all or part of the seminal vesicles. The development of prostate magnetic resonance imaging (MRI) and positron emission tomography (PET) using prostate-specific radiotracers has ushered in an era in which radiation oncologists are able to localize and focally dose-escalate high-risk volumes in the prostate gland. Recent phase 3 data has demonstrated that incorporating focal dose escalation to high-risk subvolumes of the prostate improves biochemical control without significantly increasing toxicity. Still, several fundamental questions remain regarding the optimal target volume definition and prescription strategy to implement this technique. Given the remaining uncertainty, a knowledge of the pathological correlates of radiographic findings and the anatomic patterns of tumor spread may help inform clinical judgement for the definition of clinical target volumes.ConclusionAdvanced imaging has the ability to improve outcomes for patients with prostate cancer in multiple ways, including by enabling focal dose escalation to high-risk subvolumes. However, many questions remain regarding the optimal target volume definition and prescription strategy to implement this practice, and key knowledge gaps remain. A detailed understanding of the pathological correlates of radiographic findings and the patterns of local tumor spread may help inform clinical judgement for target volume definition given the current state of uncertainty.
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Project description:Prostate cancer (PC) is the most common and the second leading cause of cancer-related death among American men. Early diagnosis is a prerequisite to improving therapeutic benefits. However, the current clinical biomarkers for PC do not reliably decipher indolent PC from other urogenital disorders. Thus, effective clinical intervention necessitates development of new biomarkers for early detection of PC. The present study aimed to identify the miRNA signature in organ-confined (Gleason Score 6) prostate tumors. MicroRNA (miRNA/miR) array analysis identified 118 upregulated and 73 downregulated miRNAs in microdissected tumors in comparison to matched neighboring normal prostate epithelium. The miRs-Plus-A1083, -92b-5p, -18a-3p, -19a-3p, -639, -3622b-3p, -3189-3p, -155-3p, -410, -1179, 548b-5p, and -4469 are predominantly expressed (7-11-fold), whereas miRs-595, 4490, -3120-5p, -1299, -21-5p, -3677-3, -let-7b-5p, -5189, 3-121-5p, -4518, -200a-5p, -3682-5p, -3689d, -3149 represent the most downregulated (12-113-fold) miRNAs in microdissected prostate tumors. The array expression profile of selected miRNA signature and their potential mRNA targets was validated by qRT-PCR analysis in PC cell lines. Integrated in silico and computational prediction analyses demonstrated that the dysregulated miRNA signature map to key regulatory factors involved in tumorigenesis, including cell cycle, apoptosis, and p53 pathways. The newly identified miRNA signature has potential clinical utility as biomarkers, prognostic indicators, and therapeutic targets for early detection of PC. Further studies are needed to assess the functional significance and clinical usefulness of the identified miRNAs. Impact Statement To our knowledge his is the first study of identifying miRNA signatures in microdissected indolent (Gleason score 6) prostate cancer in comparison to matched normal prostate epithelium. By employing in silico and computational prediction analysis, the study provides a landscape of potential miRNA targets and key cellular pathways involved in prostate tumorigenesis. Identification if miRNAs and their relevant targets and pathways pave the way for underpinning their mechanistic role of miRNAs in human prostate tumorigenesis, and possibly other human cancers. Importantly, the outcome of the study has important clinical implications for the management of prostate cancer, including the use of miRNA(s) as biomarkers for early detection of prostate cancer.
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Project description:The purpose of our current study was to establish a long non-coding RNA(lncRNA) signature and assess its prognostic and diagnostic power in papillary thyroid cancer (PTC). LncRNA expression profiles were obtained from the Cancer Genome Atlas (TCGA). The key module and hub lncRNAs related to PTC were determined by weighted gene co-expression network analysis (WGCNA) and LASSO Cox regression analyses, respectively. Functional enrichment analyses, including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis were implemented to analyze the possible biological processes and signaling pathways of hub lncRNAs. Associations between key lncRNA expressions and tumor-infiltrating immune cells were identified using the TIMER website, and proportions of immune cells in high/low risk score groups were compared. Kaplan-Meier Plotter was used to evaluate the prognostic significance of hub genes in PTC. A diagnostic model was conducted with logistic regression analysis, and its diagnostic performance was assessed by calibration/receiver operating characteristic curves and principal component analysis. A nine-lncRNAs signature (SLC12A5-AS1, LINC02028, KIZ-AS1, LINC02019, LINC01877, LINC01444, LINC01176, LINC01290, and LINC00581) was established in PTC, which has significant diagnostic and prognostic power. Functional enrichment analyses elucidated the regulatory mechanism of the nine-lncRNAs signature in the development of PTC. This signature and expressions of nine hub lncRNAs were correlated with the distributions of tumor infiltrating immune cells. A diagnostic nomogram was also established for PTC. By comparing with the published models with less than or equal to nine lncRNAs, our signature showed a preferable performace for prognosis prediction. In conclusion, our present research established an innovative nine-lncRNAs signature and a six-lncRNAs nomogram that might act as a potential indicator for PTC prognosis and diagnosis, which could be conducive to the PTC treatment.
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Project description:Non-alcoholic fatty liver disease (NAFLD) has emerged as one of the major causes of liver-related morbidity and mortality globally. It ranges from simple steatosis to non-alcoholic steatohepatitis (NASH) characterized by ballooning and hepatic inflammation. In the past few years, pyroptosis has been shown as a type of programmed cell death that triggers inflammation and plays a role in the development of NASH. However, the roles of pyroptosis-related genes (PRGs) in NASH remained unclear. In this study, we studied the expression level of pyroptosis-related genes (PRGs) in NASH and healthy controls, developed a diagnostic model of NASH based on PRGs and explored the pathological mechanisms associated with pyroptosis. We further compared immune status between NASH and healthy controls, analyzed immune status in different subtypes of NASH. We identified altogether twenty PRGs that were differentially expressed between NASH and normal liver tissues. Then, a novel diagnostic model consisting of seven PRGs including CASP3, ELANE, GZMA, CASP4, CASP9, IL6 and TP63 for NASH was constructed with an area under the ROC curve (AUC) of 0.978 (CI 0.965-0.99). Obvious variations in immune status between healthy controls and NASH cases were detected. Subsequently, the consensus clustering method based on differentially expressed PRGs was constructed to divide all NASH cases into two distinct pyroptosis subtypes with different immune and biological characteristics. Pyroptosis-related genes may play an important role in NASH and can provide new insights into the diagnosis and underlying mechanisms of NASH.
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Project description:Neuroendocrine prostate cancer (NEPC) is an aggressive subtype of prostate cancer which does not respond to hormone therapy. Research of NEPC has been hampered by a lack of clinically relevant in vivo models. Recently, we developed a first-in-field patient tissue-derived xenograft model of complete neuroendocrine transdifferentiation of prostate adenocarcinoma. By comparing gene expression profiles of a transplantable adenocarcinoma line (LTL331) and its NEPC subline (LTL331R), we identified DEK as a potential biomarker and therapeutic target for NEPC. In the present study, elevated DEK protein expression was observed in all NEPC xenograft models and clinical NEPC cases, as opposed to their benign counterparts (0%), hormonal naïve prostate cancer (2.45%) and castration-resistant prostate cancer (29.55%). Elevated DEK expression was found to be an independent clinical risk factor, associated with shorter disease-free survival of hormonal naïve prostate cancer patients. DEK silencing in PC-3 cells led to a marked reduction in cell proliferation, cell migration and invasion. The results suggest that DEK plays an important role in the progression of prostate cancer, especially to NEPC, and provides a potential biomarker to aid risk stratification of prostate cancer and a novel target for therapy of NEPC.
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Project description:Background: Ischemic stroke (IS) is a common and serious neurological disease, and multiple pathways of cell apoptosis are implicated in its pathogenesis. Recently, extensive studies have indicated that pyroptosis is involved in various diseases, especially cerebrovascular diseases. However, the exact mechanism of interaction between pyroptosis and IS is scarcely understood. Thus, we aimed to investigate the impact of pyroptosis on IS-mediated systemic inflammation. Methods: First, the RNA regulation patterns mediated by 33 pyroptosis-related genes identified in 20 IS samples and 20 matched-control samples were systematically evaluated. Second, a series of bioinformatics algorithms were used to investigate the contribution of PRGs to IS pathogenesis. We determined three composition classifiers of PRGs which potentially distinguished healthy samples from IS samples according to the risk score using single-variable logistic regression, LASSO-Cox regression, and multivariable logistic regression analyses. Third, 20 IS patients were classified by unsupervised consistent cluster analysis in relation to pyroptosis. The association between pyroptosis and systemic inflammation characteristics was explored, which was inclusive of immune reaction gene sets, infiltrating immunocytes and human leukocyte antigen genes. Results: We identified that AIM2, SCAF11, and TNF can regulate immuno-inflammatory responses after strokes via the production of inflammatory factors and activation of the immune cells. Meanwhile, we identified distinct expression patterns mediated by pyroptosis and revealed their immune characteristics, differentially expressed genes, signaling pathways, and target drugs. Conclusion: Our findings lay a foundation for further research on pyroptosis and IS systemic inflammation, to improve IS prognosis and its responses to immunotherapy.
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