scholarly journals Upregulation of HSPA1A/HSPA1B/HSPA7 and Downregulation of HSPA9 Were Related to Poor Survival in Colon Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yufeng Guan ◽  
Xianjun Zhu ◽  
Junjie Liang ◽  
Min Wei ◽  
Shan Huang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Methylation Level ◽  
Cox Regression ◽  
Clinicopathological Characteristics ◽  
Signal Pathways ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Favorable Prognosis ◽  
Hsp70 Family ◽  
Cancer Tissues

The human HSP70 family is a type of heat shock protein (HSP), consisting of 13 members encoded by the HSPA genes. HSPs play important roles in regulating cellular responses and functions during carcinogenesis, but their relationship with colon cancer is unclear. In our study, we found that the expressions of HSPA1B, HSPA4, HSPA5, HSPA6, HSPA8, HSPA9, HSPA13, and HSPA14 were significantly increased, while those of HSPA1A, HSPA2, HSPA7, and HSPA12B were significantly decreased in colon cancer tissues. The expression of HSPA gene family members was associated with some clinicopathological characteristics, including age, gender, TNM stage, pathological stage, and CEA level. Furthermore, the Kaplan–Meier method and Cox regression analysis showed that high HSPA1A, HSPA1B, and HSPA7 expressions were related to unfavorable survival, and high HSPA9 was associated with favorable survival. The relationships between HSPA1A and HSPA9 expression and survival were validated in the GEO dataset, and the HSPA1A and HSPA9 protein expression differences between colon cancer tissues and normal tissues were validated in the UALCAN database. Methylation of HSPA1A and HSPA9 was also analyzed, and it was found that the methylation of the HSPA1A promoter was significantly increased, and the methylation of the HSPA9 promoter was significantly decreased in colon cancer tissues. Increasing the methylation level of the HSPA1A gene and decreasing the methylation level of HSPA9 were related to favorable prognosis. The expression difference of HSPA1A/HSPA1B/HSPA7/HSPA9 was verified in colon cancer cell lines and colonic epithelial cells. Gene ontology analysis was used to screen signal pathways related to HSPA1A-, HSPA1B-, HSPA7-, and HSPA9- high phenotype. In summary, the increased expressions of HSPA1A1, HSPA1B, and HSPA7 were associated with poor prognosis, while that of HSPA9 was related to favorable prognosis for colon cancer patients.

scholarly journals Increased Expression of TRPS1 Affects Tumor Progression and Correlates with Patients' Prognosis of Colon Cancer

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Jun Hong ◽  
Jie Sun ◽  
Tao Huang
Keyword(s):  
Colon Cancer ◽  
Cox Regression ◽  
Mrna Level ◽  
Human Colon ◽  
Positive Lymph Node ◽  
Human Colon Cancer ◽  
Poor Prognostic Factor ◽  
Cox Regression Analysis ◽  
Potential Marker ◽  
Cancer Tissues

Aim. To detect the expression pattern of tricho-rhino-phalangeal syndrome-1 (TRPS1) in human colon cancer and to analyze its correlation with prognosis of patients with this disease.Methods. The expressions of TRPS1 in human colon cancer and its corresponding noncancerous colon tissues were detected at both mRNA and protein levels.Results. The mRNA and protein expression levels of TRPS1 were both significantly higher in colon cancer than in corresponding noncancerous colon tissues (bothP<0.001). The protein level of TRPS1 in colon cancer tissues was significantly correlated with the mRNA level (r=0.9,P<0.001). Additionally, immunohistochemistry analysis also found increased TRPS1 expression in 63.0% (63/100) of colon cancer tissues. High TRPS1 expression was significantly associated with positive lymph node metastasis (P=0.006) and higher pathological stage (P=0.008) of patients with colon cancer. Multivariate Cox regression analysis further suggested that the increased expression of TRPS1 was an independent poor prognostic factor for this disease.Conclusion. Our data offer the convincing evidence for the first time that the increased expression of TRPS1 may be involved in the pathogenesis and progression of colon cancer. TRPS1 might be a potential marker to predict the prognosis in colon cancer.

The Relationship Between microRNA-195 and the Prognosis of Cervical Cancer

2020 ◽  
Author(s):  
Shuangqing Cao ◽  
Lei Zheng
Keyword(s):  
Cervical Cancer ◽  
Overall Survival ◽  
Prognostic Value ◽  
Cox Regression ◽  
Rank Test ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Cancer Tissues ◽  
The Relationship

Abstract Background: MicroRNA-195 (miR-195), a tumor suppressor, had reported to be involved in carcinogenesis and the progression of some cancers. However, the prognostic value of miR-195 in cervical cancer remained unclear. The purpose of this study was to detect the expression of miR-195 in cervical cancer tissues and to investigate its correlation with tumor progression and prognosis.Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the relative mRNA expression of miR-195 in cervical cancer tissues and corresponding adjacent normal tissues. The relationship between miR-195 expression and clinical characteristics of patients was analyzed by chi-square test. Kaplan-Meier method was applied to compare the overall survival, and the prognostic value of miR-195 was estimated via cox regression analysis.Results: Compared with normal tissues, miR-195 expression was significantly down-regulated in cervical cancer tissues (P < 0.001). Importantly, decreased expression of miR-195 was closely associated with FIGO stage, lymph node metastasis and vascular invasion (P < 0.05). Additionally, Kaplan-Meier analysis indicated that patients with high miR-195 expression had obviously longer overall survival than those with low miR-195 expression (log rank test, P = 0.001). And miR-195 was an independent prognostic factor of cervical cancer patients via univariate and multivariate cox regression analyses.Conclusions: Decreased expression of miR-195 is associated with the progression of cervical cancer. And miR-195 may have potency to predict the prognosis of cervical cancer.

scholarly journals Myocardial Metabolic Response Predicts Chemotherapy Curative Potential on Hodgkin Lymphoma: A Proof-of-Concept Study

Biomedicines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 971
Author(s):  
Cecilia Marini ◽  
Matteo Bauckneht ◽  
Anna Borra ◽  
Rita Lai ◽  
Maria Isabella Donegani ◽  
...  
Keyword(s):  
Hodgkin Lymphoma ◽  
Cox Regression ◽  
Metabolic Response ◽  
Progression Free Survival ◽  
Disease Relapse ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Pet Ct ◽  
Genome Sharing

Genome sharing between cancer and normal tissues might imply a similar susceptibility to chemotherapy toxicity. The present study aimed to investigate whether curative potential of doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) is predicted by the metabolic response of normal tissues in patients with Hodgkin lymphoma (HL). METHODS: According to current guidelines, 86 patients with advanced-stage (IIB-IVB) HL, prospectively enrolled in the HD0607 trial (NCT00795613), underwent 18 F-fluorodeoyglucose PET/CT imaging at diagnosis and, at interim, after two ABVD courses, to decide regimen maintenance or its escalation. In both scans, myocardial FDG uptake was binarized according to its median value. Death and disease relapse were recorded to estimate progression-free survival (PFS) during a follow-up with median duration of 43.8 months (range 6.97–60). RESULTS: Four patients (4.6%) died, while six experienced disease relapse (7%). Complete switch-off of cancer lesions and cardiac lighting predicted a favorable outcome at Kaplan–Mayer analyses. The independent nature and additive predictive value of their risk prediction were confirmed by the multivariate Cox regression analysis. CONCLUSION: Susceptibility of HL lesions to chemotherapy is at least partially determined by factors featuring the host who developed it.

Development and Validation of Prognostic Nomograms Predicting Recurrence and Survival in Patients with Solitary Hepatocellular Carcinoma Following Curative Liver Resection

2021 ◽  
Author(s):  
Xinxin Chen ◽  
Wenxia Qiu ◽  
Xuekun Xie ◽  
Zefeng Chen ◽  
Zhiwei Han ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Resection ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Clinicopathological Characteristics ◽  
Tumor Diameter ◽  
Cox Regression Analysis ◽  
Tumor Capsule ◽  
Calibration Curves ◽  
Solitary Hepatocellular Carcinoma

Abstract Background: This work was designed to establish and verify our nomograms integrating clinicopathological characteristics with hematological biomarkers to predict both disease-free survival (DFS) and overall survival (OS) in solitary hepatocellular carcinoma (HCC) patients following hepatectomy.Methods: We scrutinized the data retrospectively from 414 patients with a clinicopathological diagnosis of solitary HCC from Guangxi Medical University Cancer Hospital (Nanning, China) between January 2004 and December 2012. Following the random separation of the samples in a 7:3 ratio into the training set and validation set, the former set was assessed by Cox regression analysis to develop two nomograms to predict the 1-year and 3-year DFS and OS (3-years and 5-years). This was followed by discrimination and calibration estimation employing Harrell’s C-index (C-index) and calibration curves, while the internal validation was also assessed.Results: In the training cohort, the tumor diameter, tumor capsule, macrovascular invasion, and alpha-fetoprotein (AFP) were included in the DFS nomogram. Age, tumor diameter, tumor capsule, macrovascular invasion, microvascular invasion, and aspartate aminotransferase (AST) were included in the OS nomogram. The C-index was 0.691 (95% CI: 0.644-0.738) for the DFS-nomogram and 0.713 (95% CI: 0.670-0.756) for the OS-nomogram. The survival probability calibration curves displayed a fine agreement between the predicted and observed ranges in both data sets. Conclusion: Our nomograms combined clinicopathological features with hematological biomarkers to emerge effective in predicting the DFS and OS in solitary HCC patients following curative liver resection. Therefore, the potential utility of our nomograms for guiding individualized treatment clinically and monitor the recurrence monitoring in these patients.

scholarly journals Development of prognosis model for colon cancer based on autophagy-related genes

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Xu Wang ◽  
Yuanmin Xu ◽  
Ting Li ◽  
Bo Chen ◽  
Wenqi Yang
Keyword(s):  
Colon Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Cox Regression ◽  
Patient Survival ◽  
Expression Profiles ◽  
Cox Regression Analysis ◽  
Risk Patients

Abstract Background Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. Methods Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. Results Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. Conclusion The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment.

scholarly journals Dipeptidyl peptidase like 6 promoter methylation is a potential prognostic biomarker for pancreatic ductal adenocarcinoma

2020 ◽  
Vol 40 (7) ◽  
Author(s):  
Xin Zhao ◽  
Di Cao ◽  
Zhangyong Ren ◽  
Zhe Liu ◽  
Shaocheng Lv ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Promoter Methylation ◽  
Methylation Level ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Dipeptidyl Peptidase ◽  
Ductal Adenocarcinoma ◽  
Gene Promoters ◽  
Cox Regression Analysis

Abstract Background: Hypermethylation of gene promoters plays an important role in tumorigenesis. The present study aimed to identify and validate promoter methylation-driven genes (PMDGs) for pancreatic ductal adenocarcinoma (PDAC). Methods: Based on GSE49149 and the PDAC cohort of The Cancer Genome Atlas (TCGA), differential analyses of promoter methylation, correlation analysis, and Cox regression analysis were performed to identify PMDGs. The promoter methylation level was assessed by bisulfite sequencing polymerase chain reaction (BSP) in paired tumor and normal tissues of 72 PDAC patients. Kaplan−Meier survival analyses were performed to evaluate the clinical value of PMDGs. Results: In GSE49149, the β-value of the dipeptidyl peptidase like 6 (DPP6) promoter was significantly higher in tumor compared with normal samples (0.50 vs. 0.24, P&lt;0.001). In the PDAC cohort of TCGA, the methylation level of the DPP6 promoter was negatively correlated with mRNA expression (r = −0.54, P&lt;0.001). In a multivariate Cox regression analysis, hypermethylation of the DPP6 promoter was an independent risk factor for PDAC (hazard ratio (HR) = 543.91, P=0.002). The results of BSP revealed that the number of methylated CG sites in the DPP6 promoter was greater in tumor samples than in normal samples (7.43 vs. 2.78, P&lt;0.001). The methylation level of the DPP6 promoter was moderately effective at distinguishing tumor from normal samples (area under ROC curve (AUC) = 0.74, P&lt;0.001). Hypermethylation of the DPP6 promoter was associated with poor overall (HR = 3.61, P&lt;0.001) and disease-free (HR = 2.01, P=0.016) survivals for PDAC patients. Conclusion: These results indicate that DPP6 promoter methylation is a potential prognostic biomarker for PDAC.

scholarly journals Identification and Validation of a Glycolysis Related Metabolic Reprogramming Gene Signature for Predicting Survival in Colon Cancer Patients

2021 ◽  
Author(s):  
Gang Liu ◽  
Xiaowang WU ◽  
Jian Chen
Keyword(s):  
Colon Cancer ◽  
Prediction Model ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Gene Signature ◽  
Metabolic Reprogramming ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Prognosis Model ◽  
The Relationship

Abstract Background Colon cancer (CC) is one of the most common gastrointestinal malignant tumors with high mortality rate. Because of malignancy and easily metastasis feather, and limited treatments, the prognosis of CC remains poor. Glycolysis is a metabolic process of glucose in anoxic environments which is an important way to provide energy for tumor. The role of glycolysis in CC largely remains unknown and is necessary to be explored. Method In our study, we analyzed glycolysis related genes expression in CC, patients gene expression and corresponding clinical data were downloaded from GEO dataset, glycolysis related genes sets were collected from Msigdb. Through COX regression analysis, prognosis model based on glycolysis-related genes was established. The efficacy of gene model was tested by Survival analysis, ROC analysis and PCA analysis. Furthermore, the relationship between risk scores and clinical characteristic was researched. Results Our findings identified 13 glycolysis related genes (NUP107, SEC13, ALDH7A1, ALG1, CHPF, FAM162A, FBP2, GALK1, IDH1, TGFA, VLDLR, XYLT2 and OGDHL) consisted prognostic prediction model with relative high accuracy. The relationship between prediction model and clinical feathers were specifically studied, results showed age > 65years, TNM III-IV, T3-4, N1-3, M1 and high-risk score were independent prognostic risk factors with poorer prognosis. Finally, model genes were significantly expressed and EMT were activated in CC patients. Conclusion This study provided a new aspect to advance our understanding in the potential mechanism of glycolysis in CC.

scholarly journals Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

2021 ◽  
Author(s):  
Sijia Li ◽  
Hongyang Zhang ◽  
Wei Li
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

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.

miR-181 Expression is Associated With The Prognosis in Lung Cancer.

2020 ◽  
Author(s):  
Yue Zhao ◽  
Xiangjun Kong ◽  
Hongbing Wang
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Prognostic Value ◽  
Cox Regression ◽  
Suppressor Gene ◽  
Rank Test ◽  
High Morbidity ◽  
Cox Regression Analysis ◽  
Log Rank Test ◽  
Cancer Tissues

Abstract Background: Lung cancer is one of the most common cancers, with high morbidity and mortality. MiRNAs are proved to play important roles in various human cancers. In our study, we aimed to explore the prognostic value of miR-181 in lung cancerMethods: Quantitative real-time polymerase chain reaction (QRT-PCR) was used to detect the expression level of miR-181 in lung cancer tissues and the paired non-cancerous tissues. The relationship between miR-181 expression and clinicopathologic parameters were analyzed by chi-square test. Kaplan-Meier method with log rank test was applied for overall survival analysis. Furthermore, the Cox regression analyses were performed to evaluate the prognostic value of miR-181 in lung cancer.Results: Down-regulated miR-181 expression was observed in lung cancer tissues (P<0.001), moreover, its expression was significantly correlated with TNM stage (P=0.015) and metastasis (P=0.000). In addition, lung cancer patients with lower miR-181 expression level had poorer overall survival than those with higher expression (log rank test, P=0.011). Cox regression analysis suggested that miR-181 was an independent prognostic factor for lung cancer (HR=1.961, 95%CI=1.135-3.388, P=0.016).Conclusion: MiR-181 may be a tumor suppressor gene in lung cancer, which can predict outcomes for the patients.

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