CXCR7 expression is associated with disease-free and disease-specific survival in cervical cancer patients.
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ABSTRACT:
SUBMITTER: Schrevel M
PROVIDER: S-EPMC3341866 | biostudies-other | 2012 Apr
REPOSITORIES: biostudies-other
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Project description:Pancreatic adenocarcinoma up-regulated factor (PAUF) is a novel soluble protein involved in tumor development and metastases. This study was to investigate the PAUF expression and its prognostic value in cervical cancer patients. The expression of PAUF was immunohistochemically determined in 345 formalin-fixed, paraffin-embedded cervical cancer tissues and 107 normal cervical epitheliums. Subsequently, its associations with clinicopathological characteristics and patient survival were assessed. PAUF protein was expressed both in cytoplasm and nucleus, and cytoplasmic expression was more frequent in cancers than normal tissues (32% versus 17%, P = .002), and the difference was prominent in glandular cells. Notably, the expression was more frequent in adenocarcinoma than in squamous cell carcinoma (57% versus 25%, respectively; P < .001), and the differential expression was also seen at the messenger RNA level (P = .014). Cox regression analysis showed that the cytoplasmic expression of PAUF protein was independently associated with poor disease-free (hazard ratio = 2.3; 95% confidence interval, 1.2-4.3; P = .008) and overall survival (hazard ratio = 2.9; 95% confidence interval, 1.2-7.5; P = .020). Detection of PAUF expression may aid current evaluation of prognosis in cervical adenocarcinoma.
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Project description:BACKGROUND The present study explored the expression of coiled-coil domain-containing 34 (CCDC34) in cervical cancer (CC) and its prognostic value. MATERIAL AND METHODS GEPIA and Oncomine cancer databases were mined to predict the CCDC34 differential expression level between a CC group and a normal group. Immunohistochemistry was performed to examine the CCDC34 expression in 67 CC and corresponding adjacent tissues. CD31 and vascular endothelial growth factor (VEGF) were stained to reflect tumor angiogenesis in 67 CC tissues. Kaplan-Meier univariate and Cox multivariate survival analysis were done to evaluate the correlation between CCDC34 expression and prognosis of CC patients. RESULTS Both GEPIA and Oncomine cancer databases mining results revealed that CCDC34 was more highly expressed in the CC group than in the normal group (all P<0.05). Our immunochemical staining data showed that CCDC34 expression was dramatically higher in CC than in adjacent normal tissues (71.6 vs. 20.9%; P<0.001). High expression of CCDC34 was strongly associated with histological grade (P=0.022), lymph node metastasis (P=0.044), and FIGO stage (P=0.002). Furthermore, patients with CCDC34-positive expression had much more MVD than those with CCDC34-negative expression (P<0.001). Kaplan-Meier survival analysis showed that CCDC34-positive expression was associated with worse overall survival (OS) (P=0.004) and disease-free survival (DFS) (P=0.005). Additionally, Cox multivariate analysis revealed that CCDC34 was an independent unfavorable prognostic parameter of DFS and OS (P=0.040 and 0.039, respectively). CONCLUSIONS High expression of CCDC34 is an independent unfavorable prognostic parameter for OS and DFS of CC patients, which was strongly associated with tumor angiogenesis.
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Project description:Pre-treatment survival prediction plays a key role in many diseases. We aimed to determine the prognostic value of pre-treatment Magnetic Resonance Imaging (MRI) based radiomic score for disease-free survival (DFS) in patients with early-stage (IB-IIA) cervical cancer. Methods: A total of 248 patients with early-stage cervical cancer underwent radical hysterectomy were included from two institutions between January 1, 2011 and December 31, 2017, whose MR imaging data, clinicopathological data and DFS data were collected. Patients data were randomly divided into the training cohort (n = 166) and the validation cohort (n=82). Radiomic features were extracted from the pre-treatment T2-weighted (T2w) and contrast-enhanced T1-weighted (CET1w) MR imagings for each patient. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazard model were applied to construct radiomic score (Rad-score). According to the cutoff of Rad-score, patients were divided into low- and high- risk groups. Pearson's correlation and Kaplan-Meier analysis were used to evaluate the association of Rad-score with DFS. A combined model incorporating Rad-score, lymph node metastasis (LNM) and lymphovascular space invasion (LVI) by multivariate Cox proportional hazard model was constructed to estimate DFS individually. Results: Higher Rad-scores were significantly associated with worse DFS in the training and validation cohorts (P<0.001 and P=0.011, respectively). The Rad-score demonstrated better prognostic performance in estimating DFS (C-index, 0.753; 95% CI: 0.696-0.805) than the clinicopathological features (C-index, 0.632; 95% CI: 0.567-0.700). However, the combined model showed no significant improvement (C-index, 0.714; 95%CI: 0.642-0.784). Conclusion: The results demonstrated that MRI-derived Rad-score can be used as a prognostic biomarker for patients with early-stage (IB-IIA) cervical cancer, which can facilitate clinical decision-making.
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Project description:Hepatocellular carcinoma (HCC) is a heterogeneous disease with a poor prognosis and limited markers for predicting patient survival. Because chemokines and chemokine receptors play numerous and integral roles in HCC disease progression, the CXCR4-CXCL12-CXCR7 axis was studied in HCC patients. CXCR4 and CXCR7 expression was analyzed by immunohistochemistry in 86 HCC patients (training cohort) and validated in 42 unrelated HCC patients (validation cohort). CXCR4 levels were low in 22.1% of patients, intermediate in 30.2%, and high in 47.7%, whereas CXCR7 levels were low in 9.3% of patients, intermediate in 44.2% and high in 46.5% of the patients in the training cohort. When correlated to patient outcome, only CXCR4 affected overall survival (P=0.03). CXCR4-CXCL12-CXCR7 mRNA levels were examined in 33/86 patients. Interestingly, the common CXCR4-CXCR7 ligand CXCL12 was expressed at significantly lower levels in tumor tissues compared to adjacent normal liver (P=0.032). The expression and function of CXCR4 and CXCR7 was also analyzed in several human HCC cell lines. CXCR4 was expressed in Huh7, Hep3B, SNU398, SNU449 and SNU475 cells, whereas CXCR7 was expressed in HepG2, Huh7, SNU449 and SNU475 cells. Huh7, SNU449 and SNU475 cells migrated toward CXCL12, and this migration was inhibited by AMD3100/anti-CXCR4 and by CCX771/anti-CXCR7. Moreover, SNU449 and Huh7 cells exhibited matrix invasion in the presence of CXCL12 and CXCL11, a ligand exclusive to CXCR7. In conclusion, CXCR4 affects the prognosis of HCC patients but CXCR7 does not. Therefore, the CXCR4-CXCL12-CXCR7 axis plays a role in the interaction of HCC with the surrounding normal tissue and represents a suitable therapeutic target.
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Project description:BackgroundCervical cancer continues to be one of the leading causes of cancer deaths among females in low and middle-income countries. In this study, we aimed to assess the independent prognostic value of clinical and potential prognostic factors in progression-free survival (PFS) in cervical cancer.MethodsWe conducted a retrospective study on 92 cervical cancer patients treated from 2017 to 2019 at the Zhuhai Hospital of Traditional Chinese and Western Medicine. Tumor characteristics, treatment options, progression-free survival and follow-up information were collected. Kaplan-Meier method was used to assess the PFS.ResultsResults showed that the number of retrieved lymph nodes had a statistically significant effect on PFS of cervical cancer patients (P = 0.002). Kaplan-Meier survival curve analysis showed that cervical cancer patients with initial symptoms age 25-39 had worse survival prognoses (P = 0.020). And the using of uterine manipulator in laparoscopic treatment showed a better prognosis (P < 0.001). A novel discovery of our study was to verify the prognostic values of retrieved lymph nodes count combining with FIGO staging system, which had never been investigated in cervical cancer before. According to the Kaplan-Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis, significant improvements were found after the combination of retrieved lymph nodes count and FIGO stage in predicting PFS for cervical cancer patients (P < 0.001, AUC = 0.826, 95% CI: 0.689-0.962).ConclusionNumber of retrieved lymph nodes, initial symptoms age, uterine manipulator, and retrieved lymph nodes count combining with FIGO staging system could be potential prognostic factors for cervical cancer patients.
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Project description:The ability to predict the efficacy of cancer treatments is a longstanding goal of precision medicine that requires improved understanding of molecular interactions with drugs and the discovery of biomarkers of drug response. Identifying genes whose expression influences drug sensitivity can help address both of these needs, elucidating the molecular pathways involved in drug efficacy and providing potential ways to predict new patients' response to available therapies. In this study, we integrated cancer type, drug treatment, and survival data with RNA-seq gene expression data from The Cancer Genome Atlas to identify genes and gene sets whose expression levels in patient tumor biopsies are associated with drug-specific patient survival using a log-rank test comparing survival of patients with low vs. high expression for each gene. This analysis was successful in identifying thousands of such gene-drug relationships across 20 drugs in 14 cancers, several of which have been previously implicated in the respective drug's efficacy. We then clustered significant genes based on their expression patterns across patients and defined gene sets that are more robust predictors of patient outcome, many of which were significantly enriched for target genes of one or more transcription factors, indicating several upstream regulatory mechanisms that may be involved in drug efficacy. We identified a large number of genes and gene sets that were potentially useful as transcript-level biomarkers for predicting drug-specific patient survival outcome. Our gene sets were robust predictors of drug-specific survival and our results included both novel and previously reported findings, suggesting that the drug-specific survival marker genes reported herein warrant further investigation for insights into drug mechanisms and for validation as biomarkers to aid cancer therapy decisions.
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Project description:ObjectiveTo establish a comprehensive model including MRI radiomics and clinicopathological features to predict post-operative disease-free survival (DFS) in early-stage (pre-operative FIGO Stage IB-IIA) cervical cancer.MethodsA total of 183 patients with early-stage cervical cancer admitted to our Jiangsu Province Hospital underwent radical hysterectomy were enrolled in this retrospective study from January 2013 to June 2018 and their clinicopathology and MRI information were collected. They were then divided into training cohort (n = 129) and internal validation cohort (n = 54). The radiomic features were extracted from the pre-operative T1 contrast-enhanced (T1CE) and T2 weighted image of each patient. Least absolute shrinkage and selection operator regression and multivariate Cox proportional hazard model were used for feature selection, and the rad-score (RS) of each patient were evaluated individually. The clinicopathology model, T1CE_RS model, T1CE + T2_RS model, and clinicopathology combined with T1CE_RS model were established and compared. Patients were divided into high- and low-risk groups according to the optimum cut-off values of four models.ResultsT1CE_RS model showed better performance on DFS prediction of early-stage cervical cancer than clinicopathological model (C-index: 0.724 vs 0.659). T1CE+T2_RS model did not improve predictive performance (C-index: 0.671). The combination of T1CE_RS and clinicopathology features showed more accurate predictive ability (C-index=0.773).ConclusionThe combination of T1CE_RS and clinicopathology features showed more accurate predictive performance for DFS of patients with early-stage (pre-operative IB-IIA) cervical cancer which can aid in the design of individualised treatment strategies and regular follow-up.Advances in knowledgeA radiomics signature composed of T1CE radiomic features combined with clinicopathology features allowed differentiating patients at high or low risk of recurrence.
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Project description:Molecular biomarkers have the potential to predict response to the treatment of rectal cancer. In this study, we aimed to evaluate the prognostic and clinicopathological implication of RAD50 (DNA repair protein RAD50 homolog) expression in rectal cancer.A total of 266 rectal cancer patients who underwent surgery and received chemo- and radiotherapy between 2000 and 2011 were involved in the study. Postoperative RAD50 expression was determined by immunohistochemistry in surgical samples (n = 266).Using Kaplan-Meier survival analysis, we found that low RAD50 expression in postoperative samples was associated with worse disease free survival (p = 0.001) and overall survival (p < 0.001) in early stage/low-grade tumors. In a comparison of patients with low vs. high RAD50 expression, we found that low levels of postoperative RAD50 expression in rectal cancer tissues were significantly associated with perineural invasion (p = 0.002).Expression of RAD50 in rectal cancer may serve as a prognostic biomarker for long-term survival of patients with perineural invasion-positive tumors and for potential use in early stage and low-grade rectal cancer assessment.
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