scholarly journals Development of a new, simple and cost-effective diagnostic tool for genetic screening of hereditary colorectal cancer--the DNA microarray assay.

2013 ◽  
Vol 60 (2) ◽  
Author(s):  
Zoran Stojcev ◽  
Tomasz Banasiewicz ◽  
Michał Kaszuba ◽  
Adam Sikorski ◽  
Marek Szczepkowski ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
High Risk ◽  
Genetic Screening ◽  
Dna Microarrays ◽  
Risk Group ◽  
Cost Effective ◽  
High Risk Group ◽  
Hereditary Colorectal Cancer ◽  
Detection Of Mutations

Detection of mutations in families with a hereditary predisposition to colon cancer gives an opportunity to precisely define the high-risk group. 36 patients operated on for colon cancer, with familiar prevalence of this malignancy, were investigated using the DNA microarrays method with the potential detection of 170 mutations in MLH1, MSH2, MSH6, CHEK2, and NOD2 genes. In microarrays analysis of DNA in 9 patients (25% of the investigated group), 6 different mutations were found. The effectiveness of genetic screening using the microarray method is comparable to the effectiveness of other, much more expensive and time-consuming methods.

Identifying an immune-related gene-pair for prognosis prediction of metastatic colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15565-e15565
Author(s):  
Qiqi Zhu ◽  
Du Cai ◽  
Wei Wang ◽  
Min-Er Zhong ◽  
Dejun Fan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Related Gene ◽  
Training Cohort ◽  
Gene Pairs ◽  
Immune Related Gene

e15565 Background: Few robust predictive biomarkers have been applied in clinical practice due to the heterogeneity of metastatic colorectal cancer (mCRC) . Using the gene pair method, the absolute expression value of genes can be converted into the relative order of genes, which can minimize the influence of the sequencing platform difference and batch effects, and improve the robustness of the model. The main objective of this study was to establish an immune-related gene pairs signature (IRGPs) and evaluate the impact of the IRGPs in predicting the prognosis in mCRC. Methods: A total of 205 mCRC patients containing overall survival (OS) information from the training cohort ( n = 119) and validation cohort ( n = 86) were enrolled in this study. LASSO algorithm was used to select prognosis related gene pairs. Univariate and multivariate analyses were used to validate the prognostic value of the IRGPs. Gene sets enrichment analysis (GSEA) and immune infiltration analysis were used to explore the underlying biological mechanism. Results: An IRGPs signature containing 22 gene pairs was constructed, which could significantly separate patients of the training cohort ( n = 119) and validation cohort ( n = 86) into the low-risk and high-risk group with different outcomes. Multivariate analysis with clinical factors confirmed the independent prognostic value of IRGPs that higher IRGPs was associated with worse prognosis (training cohort: hazard ratio (HR) = 10.54[4.99-22.32], P < 0.001; validation cohort: HR = 3.53[1.24-10.08], P = 0.012). GSEA showed that several metastasis and immune-related pathway including angiogenesis, TGF-β-signaling, epithelial-mesenchymal transition and inflammatory response were enriched in the high-risk group. Through further analysis of the immune factors, we found that the proportions of CD4+ memory T cell, regulatory T cell, and Myeloid dendritic cell were significantly higher in the low-risk group, while the infiltrations of the Macrophage (M0) and Neutrophil were significantly higher in the high-risk group. Conclusions: The IRGPs signature could predict the prognosis of mCRC patients. Further prospective validations are needed to confirm the clinical utility of IRGPs in the treatment decision.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse( P <0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals A Novel Seventeen-Gene Metabolic Signature for Predicting Prognosis in Colon Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Dakui Luo ◽  
Zezhi Shan ◽  
Qi Liu ◽  
Sanjun Cai ◽  
Qingguo Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Differentially Expressed ◽  
Metabolic Signature ◽  
Metabolic Genes ◽  
Prognostic Prediction

A metabolic disorder is considered one of the hallmarks of cancer. Multiple differentially expressed metabolic genes have been identified in colon cancer (CC), and their biological functions and prognostic values have been well explored. The purpose of the present study was to establish a metabolic signature to optimize the prognostic prediction in CC. The related data were downloaded from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) database, and Gene Expression Omnibus (GEO) combined with GSE39582 set, GSE17538 set, GSE33113 set, and GSE37892 set. The differentially expressed metabolic genes were selected for univariate Cox regression and lasso Cox regression analysis using TCGA and GTEx datasets. Finally, a seventeen-gene metabolic signature was developed to divide patients into a high-risk group and a low-risk group. Patients in the high-risk group presented poorer prognosis compared to the low-risk group in both TCGA and GEO datasets. Moreover, gene set enrichment analyses demonstrated multiple significantly enriched metabolism-related pathways. To sum up, our study described a novel seventeen-gene metabolic signature for prognostic prediction of colon cancer.

scholarly journals Establishment of an immune-related gene pairs model to predict colon adenocarcinoma prognosis

2020 ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
Risk Groups ◽  
High Risk Group ◽  
Related Gene ◽  
Immune Genes ◽  
Gene Pairs ◽  
Immune Related Gene

Abstract Background. Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma(COAD) is the main pathological type of colon cancer. There is a lot of evidence describing the correlation between the prognosis of COAD and the immune system. The objective of the current study was the development of a robust prognostic immune-related gene pairs (IRGPs) model for estimating overall survival of COAD. Methods. The gene expression profiles and clinical information of patients with colon adenocarcinoma come from TCGA and GEO databases and are divided into training and validation cohorts. Immune genes were selected which show significantly association with prognosis. Results. Among 1647 immune genes, a 17 IRGPs model was built which was significantly associated with OS in the training cohort. In the training and validation data set, the IRGPs model divided patients into high-risk groups and low-risk groups, and the prognosis of the high-risk group was significantly worse(P＜0.001). Univariate and multivariate Cox proportional hazard analysis confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways in high-risk groups were up-regulated. T cells regulatory and Macrophage M0 were significantly highly expressed in the high-risk group. Conclusion. We successfully constructed an IRGPs model that can predict the prognosis of COAD, which provides new insights into the treatment strategy of COAD.

scholarly journals An autophagy-related long non-coding RNA signature for patients with colorectal cancer

2021 ◽  
Author(s):  
Dongyan Zhao ◽  
Xizhen Sun ◽  
Sidan Long ◽  
Shukun Yao
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
High Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis

AbstractAimLong non-coding RNAs (lncRNAs) have been identified to regulate cancers by controlling the process of autophagy and by mediating the post-transcriptional and transcriptional regulation of autophagy-related genes. This study aimed to investigate the potential prognostic role of autophagy-associated lncRNAs in colorectal cancer (CRC) patients.MethodsLncRNA expression profiles and the corresponding clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, autophagy-related lncRNAs were identified by Pearson correlation test. Univariate Cox regression analysis and the least absolute shrinkage and selection operator analysis (LASSO) Cox regression model were performed to construct the prognostic gene signature. Gene set enrichment analysis (GSEA) was used to further clarify the underlying molecular mechanisms.ResultsWe obtained 210 autophagy-related genes from the whole dataset and found 1187 lncRNAs that were correlated with the autophagy-related genes. Using Univariate and LASSO Cox regression analyses, eight lncRNAs were screened to establish an eight-lncRNA signature, based on which patients were divided into the low-risk and high-risk group. Patients’ overall survival was found to be significantly worse in the high-risk group compared to that in the low-risk group (log-rank p = 2.731E-06). ROC analysis showed that this signature had better prognostic accuracy than TNM stage, as indicated by the area under the curve. Furthermore, GSEA demonstrated that this signature was involved in many cancer-related pathways, including TGF-β, p53, mTOR and WNT signaling pathway.ConclusionsOur study constructed a novel signature from eight autophagy-related lncRNAs to predict the overall survival of CRC, which could assistant clinicians in making individualized treatment.

Specific activity of cyclin dependent kinase 1 as a novel predictor of recurrence risk in stage II colon cancer.

2011 ◽  
Vol 29 (4_suppl) ◽  
pp. 402-402
Author(s):  
M. Maak ◽  
E. Zeestraten ◽  
M. Shibayama ◽  
T. Schuster ◽  
H. Friess ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Specific Activity ◽  
Risk Group ◽  
Tumor Resection ◽  
Recurrence Risk ◽  
High Risk Group ◽  
Stage Ii ◽  
Stage Ii Colon Cancer

402 Background: Altered cell cycle dynamics and check points are typical features of solid tumors, and cyclin dependent kinases (CDKs) play pivotal roles in these processes. Previously we have demonstrated that CDK-based analysis, composed of CDK1 and CDK2, is useful in the prediction of outcomes in early breast cancer patients (Ann Oncol. 19(1):68-72, 2008, Br J Cancer. 100(3):494-500, 2009). Clinically, there is a need for risk stratification in patients with stage II colon cancer who have a recurrence risk of 20 to 30%. Therefore we investigated the use of CDK-based analysis for recurrence prediction of stage II colon cancer patients. Methods: Fresh frozen tissue samples of 254 patients with histologically confirmed adenocarcinoma of the colon, UICC stage II, who received primary tumor resection in Munich (217 cases), and Leiden (37 cases) were used. Protein expression and activity of CDK1 and CDK2 were determined by in vitro assays as previously described. Specific activity (SA) of CDKs was calculated as kinase activity in relation to its corresponding mass concentration. Results: Development of distant metastasis was observed in 27 patients (10.6%) after a median follow up of 86 months. We found that predictive performance of CDK1SA, but not CDK2SA, for the metastasis was substantial and almost constant for long-term event prediction (average area under the curve (AUC) = 0.69). Tumor recurrence risk analysis in association with CDK1SA identified a low- (41% of population) and high- risk group (59%). Cox proportional hazard model analysis retained the CDK-based patient classification as an independent prognostic factor for distant metastases-free survival (low vs. high-risk group: Hazard ratio = 6.2, 95% CI: 1.45 to 26.9, p=0.0049). Clinical parameters such as grading, T-categories, age, and sex were excluded as confounding factors for CDK1SA-risk. Conclusions: CDK1SA allows stratification of different risk subgroups of stage II colon cancer patients. CDK1SA-based analysis is useful for predicting patients with high risk of distant recurrence, who should be treated with chemotherapy. No significant financial relationships to disclose.

Surveillance colonoscopy in Austria: Are we following the guidelines?

Endoscopy ◽  
2017 ◽  
Vol 50 (02) ◽  
pp. 119-127 ◽  
Author(s):  
Irina Gessl ◽  
Elisabeth Waldmann ◽  
Martha Britto-Arias ◽  
Daniela Penz ◽  
Eleonore Pablik ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Screening Colonoscopy ◽  
Reminder Letter ◽  
European Guidelines ◽  
Adenoma Detection ◽  
Before And After

Abstract Background and study aim The European guidelines for quality assurance in colorectal cancer screening and diagnosis contain postpolypectomy surveillance recommendations. They recommend follow-up intervals depending on the findings at index colonoscopy, and divide patients into a low-, intermediate- or high-risk group. The aim of this study was to assess the adherence of Austrian endoscopists to the European guidelines and to determine whether sending a reminder letter resulted in better adherence. Methods A single reminder letter containing the guidelines was sent to all endoscopists who participated in the Certificate of Quality for Screening Colonoscopy program in Austria. Adherence was assessed before and after the letter had been sent. Factors associated with adherence were investigated. Results We found poor baseline adherence to the guidelines. After the reminder letter, the adherence slightly improved in the low-risk group, but did not change in the intermediate-risk or high-risk groups. An adenoma detection rate of at least 20 % was associated with higher adherence rates. Generally, internists and hospitals showed better adherence compared with surgeons and private practices, respectively, both before and after the reminder letter. Conclusion A single reminder letter was not enough to improve the poor adherence to the European postpolypectomy surveillance guidelines. Thus, future studies are required to identify and eliminate all factors responsible for nonadherence to postpolypectomy guidelines in order to reach the goal of a safe, effective, and cost-effective colorectal cancer prevention tool in the near future.

scholarly journals Establishment of an immune-related gene pair model to predict colon adenocarcinoma prognosis

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jihang Luo ◽  
Puyu Liu ◽  
Leibo Wang ◽  
Yi Huang ◽  
Yuanyan Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Gene Pair ◽  
Risk Group ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
High Morbidity ◽  
Related Gene ◽  
Immune Genes ◽  
Immune Related Gene

Abstract Background Colon cancer is the most common type of gastrointestinal cancer and has high morbidity and mortality. Colon adenocarcinoma (COAD) is the main pathological type of colon cancer, and much evidence has supported the correlation between the prognosis of COAD and the immune system. The current study aimed to develop a robust prognostic immune-related gene pair (IRGP) model to estimate the overall survival of patients with COAD. Methods The gene expression profiles and clinical information of patients with colon adenocarcinoma were obtained from the TCGA and GEO databases and were divided into training and validation cohorts. Immune genes were selected that showed a significant association with prognosis. Results Among 1647 immune genes, a model with 17 IRGPs was built that was significantly associated with OS in the training cohort. In the training and validation datasets, the IRGP model divided patients into the high-risk group and low-risk group, and the prognosis of the high-risk group was significantly worse (P<0.001). Univariate and multivariate Cox proportional hazard analyses confirmed the feasibility of this model. Functional analysis confirmed that multiple tumor progression and stem cell growth-related pathways were upregulated in the high-risk groups. Regulatory T cells and macrophages M0 were significantly highly expressed in the high-risk group. Conclusion We successfully constructed an IRGP model that can predict the prognosis of COAD, providing new insights into the treatment strategy of COAD.

scholarly journals Prognostic utility of neutrophil-to-lymphocyte ratio in patients with metastatic colorectal cancer treated using different modalities

2020 ◽  
Vol 27 (5) ◽  
Author(s):  
G. Nogueira-Costa ◽  
I. Fernandes ◽  
R. Gameiro ◽  
J. Gramaça ◽  
A.T. Xavier ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
High Risk ◽  
Metastatic Colorectal Cancer ◽  
Real World ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
First Line ◽  
Kaplan Meier

Introduction Inflammation is a critical component in carcinogenesis. The neutrophil-to-lymphocyte ratio (nlr) has been retrospectively studied as a biomarker of prognosis in metastatic colorectal cancer (mcrc). Compared with a low nlr, a high nlr is associated with worse prognosis. In the present study, we compared real-world survival for patients with mcrc based on their nlr group, and we assessed the utility of the nlr in determining first-line chemo­therapy and metastasectomy benefit. Methods In this retrospective and descriptive analysis of patients with mcrc undergoing first-line chemotherapy in a single centre, the last systemic absolute neutrophil and lymphocyte count before treatment was used for the nlr. A receiver operating characteristic curve was used to estimate the nlr cut-off value, dividing the patients into low and high nlr groups. Median overall survival (mos) was compared using Kaplan–Meier curves and the log-rank test. A multivariate analysis was performed using a Cox regression model. Results The 102 analyzed patients had a median follow-up of 15 months. Regardless of systemic therapy, approx­imately 20% of patients underwent metastasectomy. The nlr cut-off was established at 2.35, placing 45 patients in the low-risk group (nlr < 2.35) and 57 in the high-risk group (nlr ≥ 2.35). The Kaplan–Meier analysis showed a mos of 39.1 months in the low-risk group and 14.4 months in the high-risk group (p < 0.001). Multivariate Cox regression on the nlr estimated a hazard ratio of 3.08 (p = 0.01). Survival analysis in each risk subgroup, considering the history of metastasectomy, was also performed. In the low-risk group, mos was longer for patients undergoing metastasectomy than for those not undergoing the procedure (95.2 months vs. 22.6 months, p = 0.05). In the high-risk group, mos was not statistically different for patients undergoing or not undergoing metastasectomy (24.3 months vs. 12.7 months, p = 0.08). Conclusions Our real-world data analysis of nlr in patients with mcrc confirmed that this biomarker is useful in predicting survival. It also suggests that nlr is an effective tool to choose first-line treatment and to predict the benefit of metastasectomy.

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