scholarly journals Diagnostic and prognostic values of upregulated SPC25 in patients with hepatocellular carcinoma

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9535
Author(s):  
Xiaolin Yang ◽  
Hongzhi Sun ◽  
Ying Song ◽  
Li Yang ◽  
Haibo Liu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Roc Curve ◽  
Cox Regression ◽  
Expression Patterns ◽  
Staging System ◽  
Cancer Genome ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Neoplastic Tissues

Background Spindle pole body component 25 (SPC25) plays a vital role in many cellular processes, such as tumorigenesis. However, the clinical significance of SPC25 in hepatocellular carcinoma (HCC) has not been investigated. This study aimed to explore the expression patterns of SPC25 in HCC and non-neoplastic tissues and to investigate the diagnostic and prognostic values of SPC25. Method The expression of SPC25 was examined in 374 HCC issues and 50 non-neoplastic tissues from The Cancer Genome Atlas (TCGA) cohort. The diagnostic and prognostic values of SPC25 were analyzed via receiver operating characteristic (ROC) curve and survival analyses, respectively. Univariate and multivariate Cox regression analyses were used to identify the prognostic factors and to establish a nomogram. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC) database. Results The expression of SPC25 in HCC tissues was significantly higher than that in normal tissues in both cohorts (all P < 0.001). The ROC curve analysis indicated that SPC25 expression has high diagnostic value in HCC with area under the curve (AUC) value of 0.969 (95% confidence interval [CI] [0.948–0.984]) and 0.945 (95% CI [0.920–0.965]) for TCGA and ICGC cohorts, respectively. Patients with HCC exhibiting high SPC25 expression were associated with worse prognosis than those exhibiting low SPC25 expression in both cohorts (all P < 0.001). SPC25 was independently associated with overall survival in both cohorts (all P < 0.001). The concordance indices of the nomogram for predicting overall survival in TCGA and ICGC cohorts were 0.647 and 0.805, respectively, which were higher than those of the American Joint Committee on Cancer (AJCC) staging system. Conclusion SPC25 was upregulated in HCC and independently predicted poor overall survival of patients with HCC. Therefore, SPC25 is an effective diagnostic and prognostic biomarker for HCC. An SPC25-based nomogram was more accurate and useful than the AJCC staging system to predict prognosis of HCC.

scholarly journals The prognostic significance of different proportion of signet-ring cells of colorectal carcinoma

2021 ◽  
Author(s):  
Wei Chen ◽  
Huajun Cai ◽  
Kui Chen ◽  
Xing Liu ◽  
Weizhong Jiang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Staging System ◽  
Signet Ring Cell ◽  
Significant Difference ◽  
Signet Ring ◽  
Ajcc Staging System ◽  
Ajcc Staging

While the prognosis of patients with partial SRCC (PSRCC) has been rarely reported, colorectal signet-ring cell carcinoma (SRCC) has been associated with poor prognosis. The aim of this study was to analyze the prognosis of patients with different SRC composition and establish a prediction model. A total of 91 patients with SRC component were included in the study. These patients were divided into two groups: SRCC group (SRC composition > 50%; n=41) and partial SRCC (PSRCC) group (SRC composition ≤ 50%; n=50). COX regression model was used to identify independent prognostic factors for overall survival (OS). A predictive nomogram was established and compared with the 7th AJCC staging system. After a median follow-up of 16 months, no significant difference in OS was observed in either group. Preoperative carcinoembryonic antigen (CEA) level, pN stage, M stage, preoperative ileus, and adjuvant chemotherapy were independent prognostic risk factors for OS (p<0.05). A nomogram for predicting the overall survival of colorectal SRCC was established with a C-index of 0.800, and it showed better performance than that of the 7th AJCC staging system (p<0.001). In summary, the ratio of SRC component was not an independent prognostic factor of the OS. Those patients with less than 50% of SRC component should be given the same clinical attention. A predictive nomogram for survival based on five independent prognostic factors was developed and showed better performance than the 7th AJCC staging system. This resulted to be helpful for individualized prognosis prediction and risk assessment.

scholarly journals A Nomogram Based on a Three-Gene Signature Derived from AATF Coexpressed Genes Predicts Overall Survival of Hepatocellular Carcinoma Patients

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jun Liu ◽  
Jianjun Lu ◽  
Zhanzhong Ma ◽  
Wenli Li
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Clinical Practice ◽  
Correlation Coefficient ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Gene Signature ◽  
Cancer Genome ◽  
Survival Prediction

Background. Hepatocellular carcinoma (HCC) is a common cancer with an extremely high mortality rate. Therefore, there is an urgent need in screening key biomarkers of HCC to predict the prognosis and develop more individual treatments. Recently, AATF is reported to be an important factor contributing to HCC. Methods. We aimed to establish a gene signature to predict overall survival of HCC patients. Firstly, we examined the expression level of AATF in the Gene Expression Omnibus (GEO), the Cancer Genome Atlas (TCGA), and the International Union of Cancer Genome (ICGC) databases. Genes coexpressed with AATF were identified in the TCGA dataset by the Poisson correlation coefficient and used to establish a gene signature for survival prediction. The prognostic significance of this gene signature was then validated in the ICGC dataset and used to build a combined prognostic model for clinical practice. Results. Gene expression data and clinical information of 2521 HCC patients were downloaded from three public databases. AATF expression in HCC tissue was higher than that in matched normal liver tissues. 644 genes coexpressed with AATF were identified by the Poisson correlation coefficient and used to establish a three-gene signature (KIF20A, UCK2, and SLC41A3) by the univariate and multivariate least absolute shrinkage and selection operator Cox regression analyses. This three-gene signature was then used to build a combined nomogram for clinical practice. Conclusion. This integrated nomogram based on the three-gene signature can predict overall survival for HCC patients well. The three-gene signature may be a potential therapeutic target in HCC.

Estimating survival probability in stage III melanoma: A multivariable individualized patient risk assessment nomogram

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 8020-8020
Author(s):  
D. G. Coit ◽  
C. Qin Zhou ◽  
A. Patel ◽  
K. Panageas
Keyword(s):  
Risk Assessment ◽  
Overall Survival ◽  
Patient Care ◽  
Staging System ◽  
Stage Iii ◽  
Patient Risk ◽  
Ajcc Staging System ◽  
Predicting Outcome ◽  
Stage Iii Melanoma ◽  
Ajcc Staging

8020 Background: Recent revisions in the AJCC staging system have increased its complexity without comparable improvement in prognostic accuracy for patients with Stage III melanoma. Furthermore, there remains significant prognostic heterogeneity, even within Stages IIIA, IIIB, and IIIC. The current study was undertaken to develop a model for individual patient risk assessment, both to facilitate patient care, and to help define prognostically homogeneous patient populations for entry into clinical trials. Methods: Patients with AJCC Stage III melanoma were identified from a prospective single institution database. Overall survival was calculated from the date of Stage III to last followup. A multivariate Cox model of independent prognostic factors was developed, and a multivariable individualized patient risk assessment nomogram was built from that model. Results: Among 1,064 patients with Stage III melanoma, 535 have died, at a median followup of 44 months. Independent predictors of overall survival are shown in the table. Individual patient three and five year survival was predicted by incorporating all eight variables into a prognostic nomogram. The nomogram was superior to the AJCC Staging system in predicting outcome in Stage III melanoma patients. Conclusions: Individual patient risk assessment is more accurate than traditional AJCC staging in predicting outcome in Stage III melanoma. This approach, which can be easily incorporated into a handheld computing environment, offers potential advantages for both patient care and clinical research, and should be explored in the next iteration of the AJCC staging system. [Table: see text] No significant financial relationships to disclose.

scholarly journals Evaluation of the new AJCC staging system for resectable hepatocellular carcinoma

2011 ◽  
Vol 9 (1) ◽  
pp. 114 ◽  
Author(s):  
Chih H Cheng ◽  
Chen F Lee ◽  
Tsung H Wu ◽  
Kun M Chan ◽  
Hong S Chou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Staging System ◽  
Ajcc Staging System ◽  
Ajcc Staging

scholarly journals Identification of the HMMR Gene as a Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma Based on Integrated Bioinformatics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Honglan Guo ◽  
Qinqiao Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Roc Curve ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Background. We aimed to investigate the expression of the hyaluronan-mediated motility receptor (HMMR) gene in hepatocellular carcinoma (HCC) and nonneoplastic tissues and to investigate the diagnostic and prognostic value of HMMR. Method. With the reuse of the publicly available The Cancer Genome Atlas (TCGA) data, 374 HCC patients and 50 nonneoplastic tissues were used to investigate the diagnostic and prognostic values of HMMR genes by receiver operating characteristic (ROC) curve analysis and survival analysis. All patients were divided into low- and high-expression groups based on the median value of HMMR expression level. Univariate and multivariate Cox regression analysis were used to identify prognostic factors. Gene set enrichment analysis (GSEA) was performed to explore the potential mechanism of the HMMR genes involved in HCC. The diagnostic and prognostic values were further validated in an external cohort from the International Cancer Genome Consortium (ICGC). Results. HMMR mRNA expression was significantly elevated in HCC tissues compared with that in normal tissues from both TCGA and the ICGC cohorts (all P values <0.001). Increased HMMR expression was significantly associated with histologic grade, pathological stage, and survival status (all P values <0.05). The area under the ROC curve for HMMR expression in HCC and normal tissues was 0.969 (95% CI: 0.948–0.983) in the TCGA cohort and 0.956 (95% CI: 0.932–0.973) in the ICGC cohort. Patients with high HMMR expression had a poor prognosis than patients with low expression group in both cohorts (all P < 0.001 ). Univariate and multivariate analysis also showed that HMMR is an independent predictor factor associated with overall survival in both cohorts (all P values <0.001). GSEA showed that genes upregulated in the high-HMMR HCC subgroup were mainly significantly enriched in the cell cycle pathway, pathways in cancer, and P53 signaling pathway. Conclusion. HMMR is expressed at high levels in HCC. HMMR overexpression may be an unfavorable prognostic factor for HCC.

Performance of a novel TNM staging system for pancreatic neuroendocrine tumors versus the current AJCC staging system.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 156-156
Author(s):  
Motaz Qadan ◽  
Yifei Ma ◽  
Brendan C. Visser ◽  
Jeffrey A. Norton ◽  
George A. Poultsides
Keyword(s):  
Overall Survival ◽  
Neuroendocrine Tumors ◽  
Staging System ◽  
Pancreatic Neuroendocrine Tumors ◽  
Population Database ◽  
Curative Intent ◽  
Discriminatory Ability ◽  
Tnm System ◽  
Ajcc Staging System ◽  
Ajcc Staging

156 Background: Adopting a unified staging system for pancreatic neuroendocrine tumors (PNET) has been challenging. Currently, the American Joint Committee on Cancer (AJCC) recommends the use of the pancreatic adenocarcinoma staging system for PNET. We sought to validate this recommendation on a large administrative population database. Methods: Surveillance, Epidemiology, and End Results (SEER) data were used to identify patients with PNET (excluding patients with large cell, small cell, or mixed endocrine-exocrine carcinoma) who underwent curative-intent surgical resection from 1983 to 2008. The discriminatory ability of the AJCC system (recorded by SEER since 2004) was examined and a new TNM system was devised utilizing extent of disease variables. Results: Of 1,202 patients identified, 51% were female. Median age was 55 years (range, 9-93). Lymph node metastasis (present in 43% of patients) was associated with worse overall survival (OS) after resection (10-year OS, 50% vs 63%, p<.0001), as was the presence of distant metastasis (present in 24% of patients, 10-year OS, 35% vs 63%, p<.0001).The current AJCC system (available in 412 patients) distinguished overall survival adequately only between stages I and II, but not between II and III, or III and IV (Table). By modifying the T stage to be based only on size (0-1 cm, 1-2 cm, 2-4 cm, and > 4 cm) and by revising the grouping allocation, we propose a novel TNM system with improved discriminatory ability (Table). Conclusions: In this study validating the current AJCC staging system for PNET, we found stages II, III, and IV to perform similarly. We propose a simplified TNM system that better discriminates between outcomes. [Table: see text]

scholarly journals Combining Gene Expression Signature With Clinical Features for Survival Stratification of Gastric Cancer

2020 ◽  
Author(s):  
Qiang Sun ◽  
Dongyang Guo ◽  
Shuang Li ◽  
Yanjun Xu ◽  
Mingchun Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Clinical Practice ◽  
Risk Score ◽  
Genetic Risk ◽  
Cox Regression ◽  
Genetic Risk Score ◽  
Staging System ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background: The AJCC staging system is considered as the golden standard in clinical practice. However, it remains some pitfalls in assessing the prognosis of gastric cancer (GC) patients with similar clinicopathological characteristics. We aim to develop a new clinic and genetic risk score (CGRS) to improve the prognosis prediction of GC patients.Methods: The gene expression profiles of the training set from the Asian Cancer Research Group (ACRG) cohort were used for developing genetic risk score (GRS) by LASSO-Cox regression algorithms. CGRS was established by integrating GRS with clinical risk score (CRS) derived from Surveillance, Epidemiology, and End Results (SEER) database. GRS and CGRS were validated in ACRG validation set and other four independent GC cohorts with different data types, such as microarray, RNA sequencing, and qRT-PCR. Multivariable Cox regression was adopted to evaluate the independence of GRS and CGRS in prognosis evaluation.Results: We established GRS based on a nine-gene signature including APOD, CCDC92, CYS1, GSDME, ST8SIA5, STARD3NL, TIMEM245, TSPYL5, and VAT1. GRS and CGRS dichotomized GC patients into high and low risk groups with significantly different prognosis in four independent cohorts, including our Zhejiang cohort (all HR > 1, all P < 0.001). Both GRS and CGRS were prognostic signatures independent of the AJCC staging system. Receiver operating characteristic (ROC) analysis showed that area under ROC curve of CGRS was larger than that of the AJCC staging system in most cohorts we studied. Nomogram and web tool (http://39.100.117.92/CGRS/) based on CGRS were developed for clinicians to conveniently assess GC prognosis in clinical practice.Conclusions: CGRS integrating genetic signature with clinical features shows strong robustness in predicting GC prognosis, and can be easily applied in clinical practice through the web application.

scholarly journals Identification and Validation of a Novel Metabolism‑Related Prognostic Signature in Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Zhihao Wang ◽  
Kidane Siele Embaye ◽  
Qing Yang ◽  
Lingzhi Qin ◽  
Chao Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Value ◽  
Cox Regression ◽  
Cancer Genome ◽  
Regression Analyses ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Tcga Dataset

Abstract Background: Given that metabolic reprogramming has been recognized as an essential hallmark of cancer cells, this study sought to investigate the potential prognostic values of metabolism-related genes(MRGs) for hepatocellular carcinoma (HCC) diagnosis and treatment. Methods: The metabolism-related genes sequencing data of HCC samples with clinical information were obtained from the International Cancer Genome Consortium(ICGC) and The Cancer Genome Atlas (TCGA). The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate Cox regression analysis were performed to identify metabolism-related DEGs that related to overall survival(OS). A novel metabolism-related prognostic signature was developed using the least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analyses . Furthermore, the signature was validated in the TCGA dataset. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in HCC. Results: A total of 178 differentially expressed MRGs were detected between the ICGA dataset and the TCGA dataset. We found that 17 MRGs were most significantly associated with OS by using the univariate Cox proportional hazards regression analysis in HCC. Then, the Lasso and multivariate Cox regression analyses were applied to construct the novel metabolism-relevant prognostic signature, which consisted of six MRGs. The prognostic value of this prognostic model was further successfully validated in the TCGA dataset. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. Six MRGs (FLVCR1, MOGAT2, SLC5A11, RRM2, COX7B2, and SCN4A) showed high prognostic performance in predicting HCC outcomes, and were further associated with tumor TNM stage, gender, age, and pathological stage. Finally, the signature was found to be associated with various clinicopathological features. Conclusions: In summary, our data provided evidence that the metabolism-based signature could serve as a reliable prognostic and predictive tool for overall survival in patients with HCC.

scholarly journals A Novel Nomogram for Predicting Cancer-Specific Survival in Women with Uterine Sarcoma: A Large Population-Based Study

2021 ◽  
Author(s):  
Yuan-jie Li ◽  
Jun Lyu ◽  
Chen Li ◽  
Hai-rong He ◽  
Jin-feng Wang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Large Population ◽  
Staging System ◽  
Uterine Sarcoma ◽  
Operating Characteristics ◽  
Cancer Specific Survival ◽  
Cox Regression Analysis ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background: To develop a comprehensive nomogram for predicting the cancer-specific survival (CSS) for uterine sarcoma (US).Methods: 3861 patients of US between 2010 to 2015 were identified for this study from the Surveillance, Epidemiology, and End Results (SEER) database. They were randomly divided into a training cohort (n = 2702) and a validation cohort (n = 1159) in a 7-to-3 ratio by R software. Multivariate Cox regression analysis was performed to select predictive variables and then to identify independent prognostic factors. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to compare the new survival nomogram with the AJCC 7th edition prognosis model.Results: We have established a nomogram for determining the 1-, 3-, and 5-year CSS probabilities of US patients. In this nomogram, pathology grade has the highest risk on CSS in US, followed by the age at diagnosis, then surgery status. The C-index for the nomogram (0.796, 0.767 for the training and validation cohort, respectively) was higher than those for the AJCC staging system (0.706 and 0.713, respectively). Furthermore, AUC value, NRI, IDI, calibration plotting, and DCA showed that this nomogram exhibited better performance than the AJCC staging system alone.Conclusion: Our study validated the first comprehensive nomogram for US which could provide more accurately and individualized survival predictions for US patients in clinical practice.

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