scholarly journals Identification of HCG18 and MCM3AP-AS1 That Associate With Bone Metastasis, Poor Prognosis and Increased Abundance of M2 Macrophage Infiltration in Prostate Cancer

2021 ◽  
Vol 20 ◽  
pp. 153303382199006
Author(s):  
Yanfang Chen ◽  
Zheng Chen ◽  
Jian Mo ◽  
Mao Pang ◽  
Zihao Chen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Cox Regression ◽  
Trichostatin A ◽  
Gene Expression Omnibus ◽  
Macrophage Infiltration ◽  
M2 Macrophage ◽  
Cox Regression Analysis ◽  
Therapeutic Drugs ◽  
Competing Endogenous Rnas

Background: Bone metastasis is a leading cause of the high mortality rate of prostate cancer (PCa), but curative strategies remain lacking. Recent studies suggest long non-coding RNAs (lncRNAs) may be potential targets to develop drugs. However, PCa bone metastasis-specifically-related lncRNAs were rarely reported. This study aimed to identify crucial lncRNAs and reveal their function mechanisms. Methods: GSE32269 and GSE26964 microarray datasets, downloaded from the Gene Expression Omnibus database, were used to analyze differentially expressed genes (DEGs)/lncRNAs (DELs) and miRNAs (DEMs), respectively. Weighted gene co-expression network analysis was performed to screen PCa bone metastasis-associated modules. The co-expression and competing endogenous RNAs (ceRNAs) networks were constructed to identify hub lncRNAs. Univariate Cox regression analysis was conducted to determine their prognostic values. The correlation of lncRNAs with immune infiltrating cells was analyzed by using Tumor IMmune Estimation Resource. Therapeutic drugs were predicted by querying the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD). Results: A total of 18 DELs, 2,614 DEGs and 86 DEMs were screened between bone metastatic and primary PCa samples. Four modules enriched by DEGs were shown to be bone metastasis-associated. LncRNA HCG18 and MCM3AP-AS1 were identified to be important because they existed in both of the co-expression and ceRNA networks (forming the relationship pairs: HCG18/MCM3AP-AS1-KNTC1, MCM3AP-AS1-hsa-miR-508-3p-DTL and HCG18/MCM3AP-AS1-hsa-miR-127-3p-CDKN3). All the genes in these interaction pairs were significantly associated with overall survival of PCa patients. Also, HCG18, MCM3AP-AS1 and their target mRNAs were positively correlated with various tumor-infiltrated immune cells, especially increased M2 macrophages. Valproic acid and trichostatin A may be effective to treat PCa bone metastasis by targeting HCG18 and MCM3AP-AS1. Conclusion: HCG18 and MCM3AP-AS1 that regulate M2 macrophage infiltration may be important targets to treat PCa bone metastasis and improve prognosis.

scholarly journals Prognostic Association between Common Laboratory Tests and Overall Survival in Elderly Men with De Novo Metastatic Castration Sensitive Prostate Cancer: A Population-Based Study in Canada

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2844
Author(s):  
Christopher J. D. Wallis ◽  
Bobby Shayegan ◽  
Scott C. Morgan ◽  
Robert J. Hamilton ◽  
Ilias Cagiannos ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Overall Survival ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
De Novo ◽  
Population Based ◽  
Population Based Study ◽  
Cox Regression Analysis ◽  
Lymphocyte Ratio ◽  
Laboratory Markers

De novo cases of metastatic prostate cancer (mCSPC) are associated with poorer prognosis. To assist in clinical decision-making, we aimed to determine the prognostic utility of commonly available laboratory-based markers with overall survival (OS). In a retrospective population-based study, a cohort of 3556 men aged ≥66 years diagnosed with de novo mCSPC between 2014 and 2019 was identified in Ontario (Canada) administrative database. OS was assessed by using the Kaplan–Meier method. Multivariate Cox regression analysis was performed to evaluate the association between laboratory markers and OS adjusting for patient and disease characteristics. Laboratory markers that were assessed include neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), albumin, hemoglobin, serum testosterone and PSA kinetics. Among the 3556 older men with de novo mCSPC, their median age was 77 years (IQR: 71–83). The median survival was 18 months (IQR: 10–31). In multivariate analysis, a statistically significant association with OS was observed with all the markers (NLR, PLR, albumin, hemoglobin, PSA decrease, reaching PSA nadir and a 50% PSA decline), except for testosterone levels. Our findings support the use of markers of systemic inflammation (NLR, PLR and albumin), hemoglobin and PSA metrics as prognostic indicators for OS in de novo mCSPC.

scholarly journals Elevated Expression of Glycerol-3-Phosphate Phosphatase as a Biomarker of Poor Prognosis and Aggressive Prostate Cancer

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1273
Author(s):  
Mohamed Amine Lounis ◽  
Veronique Ouellet ◽  
Benjamin Péant ◽  
Christine Caron ◽  
Zhenhong Li ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Biochemical Recurrence ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Specific Antigen ◽  
Metabolic Stress ◽  
Cancer Specific Survival ◽  
High Risk Prostate Cancer ◽  
Increased Risk

The limitations of the biomarker prostate-specific antigen (PSA) necessitate the pursuit of biomarkers capable of better identifying high-risk prostate cancer (PC) patients in order to improve their therapeutic management and outcomes. Aggressive prostate tumors characteristically exhibit high rates of glycolysis and lipogenesis. Glycerol 3-phosphate phosphatase (G3PP), also known as phosphoglycolate phosphatase (PGP), is a recently identified mammalian enzyme, shown to play a role in the regulation of glucose metabolism, lipogenesis, lipolysis, and cellular nutrient-excess detoxification. We hypothesized that G3PP may relieve metabolic stress in cancer cells and assessed the association of its expression with PC patient prognosis. Using immunohistochemical staining, we assessed the epithelial expression of G3PP in two different radical prostatectomy (RP) cohorts with a total of 1797 patients, for whom information on biochemical recurrence (BCR), metastasis, and mortality was available. The association between biomarker expression, biochemical recurrence (BCR), bone metastasis, and prostate cancer-specific survival was established using log-rank and multivariable Cox regression analyses. High expression of G3PP in PC epithelial cells is associated with an increased risk of BCR, bone metastasis, and PC-specific mortality. Multivariate analysis revealed high G3PP expression in tumors as an independent predictor of BCR and bone metastasis development. High G3PP expression in tumors from patients eligible for prostatectomies is a new and independent prognostic biomarker of poor prognosis and aggressive PC for recurrence, bone metastasis, and mortality.

Perioperative Activation of Disseminated Tumor Cells in Bone Marrow of Patients With Prostate Cancer

2009 ◽  
Vol 27 (10) ◽  
pp. 1549-1556 ◽  
Author(s):  
Dorothea Weckermann ◽  
Bernhard Polzer ◽  
Thomas Ragg ◽  
Andreas Blana ◽  
Günter Schlimok ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Marrow ◽  
Tumor Cells ◽  
Cox Regression ◽  
Systemic Disease ◽  
Disseminated Tumor Cells ◽  
Comparative Genomic ◽  
Prognostic Impact ◽  
Primary Tumors ◽  
Cox Regression Analysis

Purpose The outcome of prostate cancer is highly unpredictable. To assess the dynamics of systemic disease and to identify patients at high risk for early relapse we followed the fate of disseminated tumor cells in bone marrow for up to 10 years and genetically analyzed such cells isolated at various stages of disease. Patients and Methods Nine hundred bone marrow aspirates from 384 patients were stained using the monoclonal antibody A45-B/B3 directed against cytokeratins 8, 18, and 19. Log-rank statistics and Cox regression analysis were applied to determine the prognostic impact of positive cells detected before surgery (244 patients) and postoperatively (214 patients). Samples from primary tumors (n = 55) and single disseminated tumor cells (n = 100) were analyzed by comparative genomic hybridization. Results Detection of cytokeratin-positive cells before surgery was the strongest independent risk factor for metastasis within 48 months (P < .001; relative risk [RR], 5.5; 95% CI, 2.4 to 12.9). In contrast, cytokeratin-positive cells detected 6 months to 10 years after radical prostatectomy were consistently present in bone marrow with a prevalence of approximately 20% but had no influence on disease outcome. Characteristic genotypes of cytokeratin-positive cells were selected at manifestation of metastasis. Conclusion Cytokeratin-positive cells in the bone marrow of prostate cancer patients are only prognostically relevant when detected before surgery. Because we could not identify significant genetic differences between pre- and postoperatively isolated tumor cells before manifestation of metastasis, we postulate the existence of perioperative stimuli that activate disseminated tumor cells. Patients with cytokeratin-positive cells in bone marrow before surgery may therefore benefit from adjuvant therapies.

scholarly journals Tertiary Gleason Pattern 5 is An Independent Risk Factor for Prostate Cancer with GS 7: A Retrospective Study from China.

2021 ◽  
Author(s):  
Desheng Cai ◽  
Zixin Wang ◽  
Yu Fan ◽  
Lin Cai ◽  
Kan Gong
Keyword(s):  
Prostate Cancer ◽  
Risk Factor ◽  
Independent Risk Factor ◽  
Cox Regression ◽  
Prostate Volume ◽  
Surgical Margin ◽  
Rank Test ◽  
Positive Surgical Margin ◽  
Cox Regression Analysis ◽  
Gleason Pattern

Abstract Background: Tertiary Gleason pattern 5 (TGP5) was found to be prognostic in prostate cancer (PCa) after radical prostatectomy (RP), but related data from China was rare. Our study was aimed at finding out the effect of TGP5 on PCa with Gleason score (GS) 7 and supplementing data from China in this field.Methods: A total of 229 cases met with inclusion criteria during Jan. 2014 to Dec. 2018 were reviewed. Cases were divided into GS 7 without TGP5 and GS 7 with TGP5. We compared age at diagnosis, preoperative PSA level, prostate volume, PSA density (PSAD), GS variation, clinical T staging, pathological T staging, T staging variation, extra-prostatic extension (EPE), positive surgical margin (PSM) and seminal vesicle invasion (SVI) between the groups. Effects of TGP5 on prognosis of PCa with GS 7 were evaluated using biochemical recurrence (BCR) as the primary end point.Results: TGP5 was related to higher PSM rate (P=0.001) and BCR rate (P=0.009) but not related to higher preoperative PSA level, larger prostate volume, higher PSAD, GS upgrade, poorer clinical/pathological T staging, T upstaging, EPE and SVI (all P>0.05). The median follow-up time was 24 months (interquartile range 17.5-45.5). TGP5 was an independent risk factor to PCa with GS 7 after RP using Kaplan-Meier log-rank test (P=0.018). Both univariable and multivariable cox-regression analysis pointed out that TGP5 increased the incidence of BCR in PCa with GS 7 (P<0.05). Stratified analyses were also done.Conclusion: TGP5 is an independent risk factor predicting of BCR after RP in PCa with GS 7 from China. TGP5 is related to higher PSM rate and BCR incidence. It is time to renew the contemporary Grading Group system with the consideration of TGP.

scholarly journals Identification and validation of immunotypes for clear cell RCC prognosis

2021 ◽  
Author(s):  
Zhaolin Yang ◽  
Jiale Zhou ◽  
Yizheng Xue ◽  
Yu Zhang ◽  
Kaijun Zhou ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cox Regression ◽  
Clear Cell ◽  
Survival Rates ◽  
Prognostic Index ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Immune Genes ◽  
Metastasis Model

Abstract Purpose To develop an immunotype-based prognostic model for predicting the overall survival (OS) of patients with clear cell renal carcinoma (ccRCC). We explored novel immunotypes of patients with ccRCC, particularly those associated with overall survival. A risk-metastasis model was constructed by integrating the immunotypes with immune genes and used to test the accuracy of the immunotype model. Patients and Methods Patient cohort data were obtained from The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, Renji database, and Surveillance, Epidemiology, and End Results (SEER) database. We employed the R software to select 3 immune cells and construct an immunotype-based prediction model. Immune genes selected using random Forest Algorithm were validated by immunohistochemistry (IHC). The H&L risk-metastasis model was constructed to assess the accuracy of the immunotype model through Multivariate COX regression analysis. Result Patients with ccRCC were categorized into immunotype H subgroup and immunotype L subgroup based on the overall survival rates. The immunotypes were found to be the independent prognostic index for ccRCC prognosis. As such, we constructed a new immunotypes-based SSIGN model. Three immune genes associated with difference between immunotype H and L were identified. An H&L risk-metastasis model was constructed to evaluate the accuracy of the immunotype model. Compared to the W-Risk-metastasis model which did not incorporate immunotypes, the H&L risk-metastasis model was more precise in predicting the survival of ccRCC patients. Conclusion The established immunotype model can effectively predict the survival of ccRCC patients. Except for mast cells, T cells and macrophages are positively associated with the overall survival of patients. The three immune genes identified, herein, can predict the survival rate of ccRCC patients, and expression of these immune genes is strongly linked to poor survival. The new SSIGN model provides an accurate tool for predicting the survival of ccRCC patients. H&L risk-metastasis model can effectively predict the risk of tumor metastasis.

scholarly journals A Novel Six-mRNA Signature Predicts Survival of Patients With Glioblastoma Multiforme

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhentao Liu ◽  
Hao Zhang ◽  
Hongkang Hu ◽  
Zheng Cai ◽  
Chengyin Lu ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Cox Regression ◽  
Methylation Status ◽  
Survival Rates ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Score Model

Glioblastoma multiforme (GBM) is a devastating brain tumor and displays divergent clinical outcomes due to its high degree of heterogeneity. Reliable prognostic biomarkers are urgently needed for improving risk stratification and survival prediction. In this study, we analyzed genome-wide mRNA profiles in GBM patients derived from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify mRNA-based signatures for GBM prognosis with survival analysis. Univariate Cox regression model was used to evaluate the relationship between the expression of mRNA and the prognosis of patients with GBM. We established a risk score model that consisted of six mRNA (AACS, STEAP1, STEAP2, G6PC3, FKBP9, and LOXL1) by the LASSO regression method. The six-mRNA signature could divide patients into a high-risk and a low-risk group with significantly different survival rates in training and test sets. Multivariate Cox regression analysis confirmed that it was an independent prognostic factor in GBM patients, and it has a superior predictive power as compared with age, IDH mutation status, MGMT, and G-CIMP methylation status. By combining this signature and clinical risk factors, a nomogram can be established to predict 1-, 2-, and 3-year OS in GBM patients with relatively high accuracy.

scholarly journals Identification and Validation of a Prognostic 5-Protein Signature for Biochemical Recurrence Following Radical Prostatectomy for Prostate Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Daojun Lv ◽  
Zanfeng Cao ◽  
Wenjie Li ◽  
Haige Zheng ◽  
Xiangkun Wu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Analysis ◽  
Biochemical Recurrence ◽  
Cox Regression ◽  
Characteristic Curve ◽  
The Cancer Genome Atlas ◽  
Medical Decision ◽  
Regression Analyses ◽  
Cox Regression Analysis ◽  
Protein Signature

Background: Biochemical recurrence (BCR) is an indicator of prostate cancer (PCa)-specific recurrence and mortality. However, there is a lack of an effective prediction model that can be used to predict prognosis and to determine the optimal method of treatment for patients with BCR. Hence, the aim of this study was to construct a protein-based nomogram that could predict BCR in PCa.Methods: Protein expression data of PCa patients was obtained from The Cancer Proteome Atlas (TCPA) database. Clinical data on the patients was downloaded from The Cancer Genome Atlas (TCGA) database. Lasso and Cox regression analyses were conducted to select the most significant prognostic proteins and formulate a protein signature that could predict BCR. Subsequently, Kaplan–Meier survival analysis and Cox regression analyses were conducted to evaluate the performance of the prognostic protein-based signature. Additionally, a nomogram was constructed using multivariate Cox regression analysis.Results: We constructed a 5-protein-based prognostic prediction signature that could be used to identify high-risk and low-risk groups of PCa patients. The survival analysis demonstrated that patients with a higher BCR showed significantly worse survival than those with a lower BCR (p &lt; 0.0001). The time-dependent receiver operating characteristic curve showed that the signature had an excellent prognostic efficiency for 1, 3, and 5-year BCR (area under curve in training set: 0.691, 0.797, 0.808 and 0.74, 0.739, 0.82 in the test set). Univariate and multivariate analyses indicated that this 5-protein signature could be used as independent prognosis marker for PCa patients. Moreover, the concordance index (C-index) confirmed the predictive value of this 5-protein signature in 3, 5, and 10-year BCR overall survival (C-index: 0.764, 95% confidence interval: 0.701–0.827). Finally, we constructed a nomogram to predict BCR of PCa.Conclusions: Our study identified a 5-protein-based signature and constructed a nomogram that could reliably predict BCR. The findings might be of paramount importance for the prediction of PCa prognosis and medical decision-making.Subjects: Bioinformatics, oncology, urology.

Identification and validation of a hub gene prognostic index for hepatocellular carcinoma

2021 ◽  
Author(s):  
Q Shi ◽  
Z Meng ◽  
XX Tian ◽  
YF Wang ◽  
WH Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Prognostic Index ◽  
Interaction Network ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
Cox Regression Analysis ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Significant Independent Prognostic Factor

Aims: We aim to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) and identify key genes as biomarkers for the prognosis of HCC. Materials & methods: Differentially expressed genes between HCC tissues and normal tissues were identified via the Gene Expression Omnibus tool. The top ten hub genes screened by the degree of the protein nodes in the protein–protein interaction network also showed significant associations with overall survival in HCC patients. Results: A prognostic model containing a five-gene signature was constructed to predict the prognosis of HCC via multivariate Cox regression analysis. Conclusion: This study identified a novel five-gene signature ( CDK1, CCNB1, CCNB2, BUB1 and KIF11) as a significant independent prognostic factor.

Five-Year Outcomes of Stereotactic Body Radiation Therapy (SBRT) for Prostate Cancer-The Largest Experience in China

2021 ◽  
Author(s):  
Xianzhi Zhao ◽  
Yusheng Ye ◽  
Haiyan Yu ◽  
Lingong Jiang ◽  
Chao Cheng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Progression Free Survival ◽  
Cox Regression Analysis ◽  
Gu Toxicity ◽  
Biochemical Progression ◽  
Grade 3 ◽  
Very High

Abstract Objective To evaluate the efficacy and toxicity of SBRT for localized prostate cancer (PCa). Moreover, it is the largest-to-date pilot study to report 5-year outcomes of SBRT for localized PCa from China. Methods In this retrospective study, 133 PCa patients in our center were treated by SBRT with CyberKnife (Accuray) from October 2012 to July 2019. Follow-up was performed every 3 months for evaluations of efficacy and toxicity. Biochemical progression-free survival (bPFS) and toxicities were assessed using the Phoenix definition and the Common Terminology Criteria for Adverse Events (CTCAE) v.5.0 respectively. Factors predictive of bPFS were identified with COX regression analysis. Results 133 patients (10 low-, 21 favorable intermediate-, 31 unfavorable intermediate-, 45 high-, and 26 very high risk cases on the basis of the NCCN risk classification) with a median age of 76 years (range: 54–87 years) received SBRT. The median dose was 36.25Gy (range: 34-37.5Gy) in 5 fractions. Median follow-up time was 57.7 months (3.5–97.2 months). The overall 5-year bPFS rate was 83.6% for all patients. The 5-year bPFS rate of patients with low-, favorable intermediate-, unfavorable intermediate-, high-, and very high risk PCa was 87.5%, 95.2%, 90.5%, 86.3%, and 61.6% respectively. Urinary symptoms were all alleviated after SBRT. All the patients tolerated SBRT with only 1 (0.8%) and 1 (0.8%) patient reporting grade-3 acute and late genitourinary (GU) toxicity, respectively. There were no grade 4 toxicities. Gleason score (P < 0.001, HR = 7.483, 95%CI: 2.686–20.846) was the independent predictor of bPFS rate after multivariate analysis Conclusion SBRT is an efficient and safe treatment modality for localized PCa with high 5-year bPFS rates and acceptable toxicities.

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