Identifying Mitochondrial-Related Genes NDUFA10 and NDUFV2 as Prognostic Markers for Prostate Cancer through Biclustering.
Ontology highlight
ABSTRACT:
SUBMITTER: Zhang H
PROVIDER: S-EPMC8168472 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundProstate cancer (PCa) is an immune-responsive disease. The current study sought to explore a robust immune-related prognostic gene signature for PCa.MethodsData were retrieved from the tumor Genome Atlas (TCGA) database and GSE46602 database for performing the least absolute shrinkage and selection operator (LASSO) cox regression model analysis. Immune related genes (IRGs) data were retrieved from ImmPort database.ResultsThe weighted gene co-expression network analysis (WGCNA) showed that nine functional modules are correlated with the biochemical recurrence of PCa, including 259 IRGs. Univariate regression analysis and survival analysis identified 35 IRGs correlated with the prognosis of PCa. LASSO Cox regression model analysis was used to construct a risk prognosis model comprising 18 IRGs. Multivariate regression analysis showed that risk score was an independent predictor of the prognosis of PCa. A nomogram comprising a combination of this model and other clinical features showed good prediction accuracy in predicting the prognosis of PCa. Further analysis showed that different risk groups harbored different gene mutations, differential transcriptome expression and different immune infiltration levels. Patients in the high-risk group exhibited more gene mutations compared with those in the low-risk group. Patients in the high-risk groups showed high-frequency mutations in TP53. Immune infiltration analysis showed that M2 macrophages were significantly enriched in the high-risk group implying that it affected prognosis of PCa patients. In addition, immunostimulatory genes were differentially expressed in the high-risk group compared with the low-risk group. BIRC5, as an immune-related gene in the prediction model, was up-regulated in 87.5% of prostate cancer tissues. Knockdown of BIRC5 can inhibit cell proliferation and migration.ConclusionIn summary, a risk prognosis model based on IGRs was developed. A nomogram comprising a combination of this model and other clinical features showed good accuracy in predicting the prognosis of PCa. This model provides a basis for personalized treatment of PCa and can help clinicians in making effective treatment decisions.
| S-EPMC8417385 | biostudies-literature
Project description:MOTIVATION: Recent genomic studies have confirmed that cancer is of utmost phenotypical complexity, varying greatly in terms of subtypes and evolutionary stages. When classifying cancer tissue samples, subnetwork marker approaches have proven to be superior over single gene marker approaches, most importantly in cross-platform evaluation schemes. However, prior subnetwork-based approaches do not explicitly address the great phenotypical complexity of cancer. RESULTS: We explicitly address this and employ density-constrained biclustering to compute subnetwork markers, which reflect pathways being dysregulated in many, but not necessarily all samples under consideration. In breast cancer we achieve substantial improvements over all cross-platform applicable approaches when predicting TP53 mutation status in a well-established non-cross-platform setting. In colon cancer, we raise prediction accuracy in the most difficult instances from 87% to 93% for cancer versus non-cancer and from 83% to (astonishing) 92%, for with versus without liver metastasis, in well-established cross-platform evaluation schemes. AVAILABILITY: Software is available on request.
| S-EPMC2935415 | biostudies-literature
Project description:BACKGROUND: Currently, the TNM classification of malignant tumours based on clinicopathological staging remains the standard for colorectal cancer (CRC) prognostication. Recently, we identified the mitochondrial oxidative phosphorylation chain as a consistently overrepresented category in the published gene expression profiling (GEP) studies on CRC prognosis. METHODS: We evaluated associations of putative regulatory single nucleotide polymorphisms (SNPs) in genes from the oxidative phosphorylation chain with survival and disease prognosis in 613 CRC patients from Northern Germany (PopGen cohort). RESULTS: Two SNPs in the 3' untranslated region of UQCRB (complex III), rs7836698 and rs10504961, were associated with overall survival (HR = 0.52, 95% CI 0.32-0.85 and HR = 0.64, 95% CI 0.42-0.99, for TT carriers). These associations were restricted to the group of patients with cancer located in the colon (HR = 0.42, 95% CI 0.22-0.82 and HR = 0.46, 95% CI 0.25-0.83). Multivariate analysis indicated that both markers might act as independent prognostic markers. Additionally, the TT carriers were ~2 times more likely to develop tumours in the colon than in the rectum. Two SNPs in COX6B1 (complex IV) were associated with lymph node metastasis in a dominant model (rs6510502, OR = 1.75, 95% CI 1.20-2.57; rs10420252, OR = 1.68, 95% CI 1.11-2.53); rs6510502 was associated also with distant metastasis (OR = 1.67, 95% CI 1.09-2.56 in a dominant model). CONCLUSIONS: This is the first report suggesting that markers in genes from the mitochondrial oxidative chain might be prognostic factors for CRC. Additional studies replicating the presented findings are needed.
| S-EPMC3420261 | biostudies-literature
Project description:BackgroundAn increasing number of studies has indicated that the tumor microenvironment (TME), an important component of tumor tissue, has clinicopathological significance in predicting disease outcome and therapeutic efficacy. However, little evidence in prostate cancer (PCa) is available.MethodsThe cohort of TCGA-PRAD (n=477) was used in this study. Based on the proportion of 22 types of immune cells calculated by CIBERSORT, the TME was classified by K-means clustering and differentially expressed genes (DEGs) were determined. The TMEscore was calculated based on cluster signature genes, which were obtained from DEGs by the random forest method, and the samples were classified into two subtypes. Analyses of somatic mutation and copy number variation (CNVs) were further conducted to identify the genetic characteristics of the two subtypes. Correlation analysis was performed to explore the correlation between TMEscore and the tumor response to immune checkpoint inhibitors (ICIs) as well as the prognosis of PCa.ResultsBased on the distribution of infiltrating immune cells in the TME, we constructed the TMEscore model and classified PCa samples into high and low TMEscore groups. Survival analysis indicated that the high TMEscore group had significantly better survival outcome than the low TMEscore group. Correlation analysis showed a significantly positive correlation between TMEscore and the known prognostic factors of PCa.ConclusionsOur study indicates that the TMEscore could be a potential prognostic biomarker in PCa. A comprehensive description of the characteristics of TME may help predict the response to therapies and provide new treatment strategies for PCa patients.
| S-EPMC8661256 | biostudies-literature
Project description:This paper demonstrates how economic modelling can be used to derive estimates of the cost-effectiveness of prognostic markers in the management of clinically localised and moderately graded prostate cancer. The model uses a Markov process and is populated using published evidence and local data. The robustness of the results has been tested using sensitivity analysis. Three treatment policies of 'monitoring' (observation), radical prostatectomy, or a selection-based management policy using DNA-ploidy as an experimental marker, have been evaluated. Modelling indicates that a policy of managing these tumours utilising experimental markers has an estimated cost per quality-adjusted life year (QALY) of pound 12 068. Sensitivity analysis shows the results to be relatively sensitive to quality-of-life variables. If novel and experimental markers can achieve specificity in excess of 80%, then a policy of radical surgery for those identified as being at high risk and conservative treatment for the remainder would be both better for patients and cost-effective. The analysis suggests that a radical prostatectomy treatment policy for the moderately graded tumours (Gleason grades -7) modelled in this paper may be inferior to a conservative approach in the absence of reliable prognostic markers, being both more costly and yielding fewer QALYs.
| S-EPMC2376796 | biostudies-other
Project description:Prostate cancer is the second leading cause of cancer death in the United States and Europe. Diagnosis and risk estimation of cancer recurrence is often critical with the common clinicopathologic parameters of prostate-specific antigen, tumor stage and grade. Therefore it is mandatory to develop new diagnostic and prognostic markers for prostate cancer. miRNAs have been shown to be novel markers in a series of other cancer types. We show for the first time, that good overall classification of normal and malignant prostate tissue was possible with combination of just two miRNAs (hsa-miR-205, hsa-miR-183). Further, hsa-miR-96 is shown to be associated with the recurrence-free interval after radical prostatectomy.
2009-09-15 | GSE14857 | GEO
Project description:Prostate cancer (PCa) is one of the most common malignancies for males, but very little is known about its pathogenesis. This study aimed to identify novel biomarkers associated with PCa prognosis and elucidate the underlying molecular mechanism. First, The Cancer Genome Atlas (TCGA) RNA-sequencing data were utilized to identify differentially expressed genes (DEGs) between tumor and normal samples. The DEGs were then applied to construct a co-expression and mined using structure network analysis. The magenta module that was highly related to the Gleason score (r = 0.46, p = 3e-26) and tumor stage (r = 0.38, p = 2e-17) was screened. Subsequently, all genes of the magenta module underwent function annotation. From the key module, CCNA2, CKAP2L, NCAPG, and NUSAP1 were chosen as the four candidate genes. Finally, internal (TCGA) and external data sets (GSE32571, GSE70770, and GSE141551) were combined to validate and predict the value of real hub genes. The results show that the above genes are up-regulated in PCa samples, and higher expression levels show significant association with higher Gleason scores and tumor T stage. Moreover, receiver operating characteristic curve and survival analysis validate the excellent value of hub genes in PCa progression and prognosis. In addition, the protein levels of these four genes also remain higher in tumor tissues when compared with normal tissues. Gene set enrichment analysis and gene set variation analysis for a single gene reveal the close relation with cell proliferation. Meanwhile, 11 small molecular drugs that have the potential to treat PCa were also screened. In conclusion, our research identified four potential prognostic genes and several candidate molecular drugs for treating PCa.
| S-EPMC8078837 | biostudies-literature
Project description:Ferroptosis, an iron-dependent form of selective cell death, is involved in the development of many cancers. However, ferroptosis related genes (FRGs) in prostate cancer (PCa) are not been well studied. In this study, we collected the mRNA expression profiles and clinical information of PCa patients from TCGA and MSKCC databases. The univariate, LASSO, and multivariate Cox regression analyses were performed to construct a prognostic signature. Seven FRGs, AKR1C3, ALOXE3, ATP5MC3, CARS1, MT1G, PTGS2, and TFRC, were included to establish a risk model, which was validated in the MSKCC dataset. The results showed that the high-risk group was apparently correlated with copy number alteration load, tumor burden mutation, immune cell infiltration, mRNAsi, immunotherapy, and bicalutamide response. Moreover, we found that TFRC overexpression induced the proliferation and invasion of PCa cell lines in vitro. These results demonstrate that this risk model can accurately predict prognosis, suggesting that FRGs are promising prognostic biomarkers and potential drug targets in PCa patients.
| S-EPMC8320699 | biostudies-literature
Project description:Molecular prognostic markers are urgently needed in order to improve therapy decisions in prostate cancer. To better understand the requirements for biomarker studies, we re-analyzed prostate cancer tissue microarray immunohistochemistry (IHC) data from 39 prognosis markers in subsets of 50 - >10,000 tumors. We found a strong association between the "prognostic power" of individual markers and the number of tissues that should be minimally included in such studies. The prognostic relevance of more than 90% of the 39 IHC markers could be detected if ≥6400 tissue samples were analyzed. Studying markers of tissue quality, including immunohistochemistry of ets-related gene (ERG) and vimentin, and fluorescence in-situ hybridization analysis of human epidermal growth factor receptor 2 (HER2), we found that 18% of tissues in our tissue microarray (TMA) showed signs of reduced tissue preservation and limited immunoreactivity. Comparing the results of Kaplan-Meier survival analyses or associations to ERG immunohistochemistry in subsets of tumors with and without exclusion of these defective tissues did not reveal statistically relevant differences. In summary, our study demonstrates that TMA-based marker validation studies using biochemical recurrence as an endpoint require at least 6400 individual tissue samples for establishing statistically relevant associations between the expression of molecular markers and patient outcome if weak to moderate prognosticators should also be reliably identified.
| S-EPMC5003445 | biostudies-literature
Project description:The mitochondrion, conventionally thought to be an organelle specific to energy metabolism, is in fact multifunctional and implicated in many diseases, including cancer. To evaluate whether mitochondria-related genes are associated with increased risk for prostate cancer, we genotyped 24 single-nucleotide polymorphisms (SNP) within the mitochondrial genome and 376 tagSNPs localized to 78 nuclear-encoded mitochondrial genes. The tagSNPs were selected to achieve > or = 80% coverage based on linkage disequilibrium. We compared allele and haplotype frequencies in approximately 1,000 prostate cancer cases with approximately 500 population controls. An association with prostate cancer was not detected for any of the SNPs within the mitochondrial genome individually or for 10 mitochondrial common haplotypes when evaluated using a global score statistic. For the nuclear-encoded genes, none of the tagSNPs were significantly associated with prostate cancer after adjusting for multiple testing. Nonetheless, we evaluated unadjusted P values by comparing our results with those from the Cancer Genetic Markers of Susceptibility (CGEMS) phase I data set. Seven tagSNPs had unadjusted P < or = 0.05 in both our data and in CGEMS (two SNPs were identical and five were in strong linkage disequilibrium with CGEMS SNPs). These seven SNPs (rs17184211, rs4147684, rs4233367, rs2070902, rs3829037, rs7830235, and rs1203213) are located in genes MTRR, NDUFA9, NDUFS2, NDUFB9, and COX7A2, respectively. Five of the seven SNPs were further included in the CGEMS phase II study; however, none of the findings for these were replicated. Overall, these results suggest that polymorphisms in the mitochondrial genome and those in the nuclear-encoded mitochondrial genes evaluated are not substantial risk factors for prostate cancer.
| S-EPMC2750891 | biostudies-literature