scholarly journals Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients

2021 ◽  
Vol 9 ◽  
Author(s):  
Jiasheng Xu ◽  
Tianyi Ling ◽  
Siqi Dai ◽  
Shuwen Han ◽  
Kefeng Ding
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Cells ◽  
Regulatory Network ◽  
Clinical Information ◽  
Risk Groups ◽  
Lasso Regression ◽  
Cerna Network ◽  
Significant Difference ◽  
Prognosis Model

Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses.Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis.Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients.

scholarly journals A Prognostic Model for Colon Cancer Patients Based on Eight Signature Autophagy Genes

2020 ◽  
Vol 8 ◽  
Author(s):  
Jiasheng Xu ◽  
Siqi Dai ◽  
Ying Yuan ◽  
Qian Xiao ◽  
Kefeng Ding
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Risk Groups ◽  
Low Risk ◽  
Differentially Expressed ◽  
Training Set ◽  
Autophagy Gene

ObjectiveTo screen key autophagy genes in colon cancer and construct an autophagy gene model to predict the prognosis of patients with colon cancer.MethodsThe colon cancer data from the TCGA were downloaded as the training set, data chip of GSE17536 as the validation set. The differential genes of the training set were obtained and were analyzed for enrichment and protein network. Acquire autophagy genes from Human Autophagy Database www.autophagy.lu/project.html. Autophagy genes in differentially expressed genes were extracted using R-packages limma. Using LASSO/Cox regression analysis combined with clinical information to construct the autophagy gene risk scoring model and divide the samples into high and low risk groups according to the risk value. The Nomogram assessment model was used to predict patient outcomes. CIBERSORT was used to calculate the infiltration of immune cells in the samples and study the relationship between high and low risk groups and immune checkpoints.ResultsNine hundred seventy-six differentially expressed genes were screened from training set, including five hundred sixty-eight up-regulated genes and four hundred eight down regulated genes. These differentially expressed genes were mainly involved: the regulation of membrane potential, neuroactive ligand-receptor interaction. We identified eight autophagy genes CTSD, ULK3, CDKN2A, NRG1, ATG4B, ULK1, DAPK1, and SERPINA1 as key prognostic genes and constructed the model after extracting the differential autophagy genes in the training set. Survival analysis showed significant differences in sample survival time after grouping according to the model. Nomogram assessment showed that the model had high reliability for predicting the survival of patients with colon cancer in the 1, 3, 5 years. In the high-risk group, the infiltration degrees of nine types of immune cells are different and the samples can be well distinguished according to these nine types of immune cells. Immunological checkpoint correlation results showed that the expression levels of CTLA4, IDO1, LAG3, PDL1, and TIGIT increased in high-risk groups.ConclusionThe prognosis prediction model based on autophagy gene has a good evaluation effect on the prognosis of colon cancer patients. Eight key autophagy genes can be used as prognostic markers for colon cancer.

scholarly journals Prognostic and Predictive Value of BGN in Colon Cancer Outcomes and Response to Immunotherapy

2022 ◽  
Vol 11 ◽  
Author(s):  
Zi-Xuan He ◽  
Sheng-Bing Zhao ◽  
Xue Fang ◽  
Ji-Fu E ◽  
Hong-Yu Fu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Immune Response ◽  
Cancer Patients ◽  
Immune Cells ◽  
Matrix Protein ◽  
Cox Regression ◽  
Extracellular Matrix Protein ◽  
Great Promise ◽  
Clinical Prognosis ◽  
Expression Levels

BackgroundColon cancer is one of the most frequent malignancies and causes high mortality worldwide. Exploring the tumor-immune interactions in the tumor microenvironment and identifying new prognostic and therapeutic biomarkers will assist in decoding the novel mechanism of tumor immunotherapy. BGN is a typical extracellular matrix protein that was previously validated as a signaling molecule regulating multiple processes of tumorigenesis. However, its role in tumor immunity requires further investigation.MethodsThe differentially expressed genes in three GEO datasets were analyzed, and BGN was identified as the target gene by intersection analysis of PPIs. The relevance between clinical outcomes and BGN expression levels was evaluated using data from the GEO database, TCGA and tissue microarray of colon cancer samples. Univariable and multivariable Cox regression models were conducted for identifying the risk factors correlated with clinical prognosis of colon cancer patients. Next, the association between BGN expression levels and the infiltration of immune cells as well as the process of the immune response was analyzed. Finally, we predicted the immunotherapeutic response rates in the subgroups of low and high BGN expression by TIS score, ImmuCellAI and TIDE algorithms.ResultsBGN expression demonstrated a statistically significant upregulation in colon cancer tissues than in normal tissues. Elevated BGN was associated with shorter overall survival as well as unfavorable clinicopathological features, including tumor size, serosa invasion and length of hospitalization. Mechanistically, pathway enrichment and functional analysis demonstrated that BGN was positively correlated with immune and stromal scores in the TME and primarily involved in the regulation of immune response. Further investigation revealed that BGN was strongly expressed in the immunosuppressive phenotype and tightly associated with the infiltration of multiple immune cells in colon cancer, especially M2 macrophages and induced Tregs. Finally, we demonstrated that high BGN expression presented a better immunotherapeutic response in colon cancer patients.ConclusionBGN is an encouraging predictor of diagnosis, prognosis and immunotherapeutic response in patients with colon cancer. Assessment of BGN expression represents a novel approach with great promise for identifying patients who may potentially benefit from immunotherapy.

Characteristics and Oncological Outcome of Clinical T3a Prostate Cancer Patients Undergoing Radical Prostatectomy in the Multi-Parametric MRI Era

2020 ◽  
Author(s):  
Kasumi Yoshitomi ◽  
Shinya Yamamoto ◽  
Tatsuya Yamamoto ◽  
Eri Fukagawa ◽  
Kosuke Hamada ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Rate ◽  
Radical Prostatectomy ◽  
Cancer Patients ◽  
Digital Rectal Examination ◽  
Oncological Outcome ◽  
Risk Groups ◽  
Free Survival ◽  
Significant Difference ◽  
Preoperative Factors

Abstract We aimed to reveal the association between the method of diagnosis (multi-parametric magnetic resonance imaging [mpMRI] and digital rectal examination [DRE]) and oncological outcomes of patients with clinical T3a (cT3a) prostate cancer after radical prostatectomy (RP) and stratify them according to oncological risk. We included 132 cT3a prostate cancer patients who underwent RP between 2008 and 2018. The biochemical recurrence (BCR)-free survival rate was evaluated according to the method of diagnosis (mpMRI alone; mpMRI group vs. DRE [with or without mpMRI]; DRE group). Several preoperative factors were evaluated in the multivariate analysis. Patients were divided into risk groups by our prediction model. The mpMRI group had significantly longer BCR-free survival than the DRE group (p<0.0001). The method of diagnosis (hazard ratio [HR]=2.69; 95% confidence interval [CI] 1.45-5.06; p=0.0017) and % positive cores (HR=4.36; 95% CI 1.14-16.5; p=0.031) were independent prognostic factors. Patients were divided into three risk groups based on these factors. There was a significant difference in BCR-free survival rate among the groups (p=0.0002).The method of diagnosis of cT3a prostate cancer was associated with BCR-free survival, and we categorized patients into risk groups. These assessments were attributable to the appropriate therapeutic strategy for patients with cT3a prostate cancer.

scholarly journals Evaluating macrophage migration inhibitory factor 1 expression as a prognostic biomarker in colon cancer

Tumor Biology ◽  
2020 ◽  
Vol 42 (6) ◽  
pp. 101042832092452
Author(s):  
Lina Olsson ◽  
Gudrun Lindmark ◽  
Marie-Louise Hammarström ◽  
Sten Hammarström ◽  
Basel Sitohy
Keyword(s):  
Colon Cancer ◽  
Lymph Nodes ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Migration Inhibitory Factor ◽  
Inhibitory Factor ◽  
Expression Levels ◽  
Significant Difference ◽  
Mrna Expression Levels ◽  
Inhibitory Factor 1

Objective: Several studies indicate that macrophage migration inhibitory factor 1 plays a role for tumor progression in colon cancer. We investigated whether determination of migration inhibitory factor 1 mRNA expression levels in lymph nodes of colon cancer patients could be used as a prognostic marker. Methods: Expression levels of migration inhibitory factor 1 and carcinoembryonic antigen mRNAs were assessed in primary tumors and regional lymph nodes of 123 colon cancer patients (stages I–IV), and in colon cancer- and immune cell lines using quantitative reverse transcriptase–polymerase chain reaction. Expression of migration inhibitory factor 1 protein was investigated by two-color immunohistochemistry and immunomorphometry. Results: Migration inhibitory factor 1 mRNA was expressed at 60 times higher levels in primary colon cancer tumors compared to normal colonic tissue (medians 8.2 and 0.2 mRNA copies/18S rRNA unit; p < .0001). A highly significant difference in mRNA expression levels was found between hematoxylin-eosin positive lymph nodes and hematoxylin-eosin negative lymph nodes (p < .0001). Migration inhibitory factor 1 and carcinoembryonic antigen proteins were simultaneously expressed in many colon cancer-tumor cells. Kaplan–Meier survival model and hazard ratio analysis, using a cutoff level at 2.19 mRNA copies/18S rRNA unit, revealed that patients with lymph nodes expressing high levels of migration inhibitory factor 1 mRNA had a 3.5-fold (p = .04) higher risk for recurrence, associated with a small, but significant, difference in mean survival time (7 months, p = .03) at 12 years of follow-up. Conclusion: Although migration inhibitory factor 1 mRNA expression levels were related to severity of disease and lymph node analysis revealed that colon cancer patients with high levels had a shorter survival time after surgery than those with low levels, the difference was small and probably not useful in clinical practice.

Development and validation of a robust prognostic and predictive signature for colorectal cancer (CRC) patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 4036-4036
Author(s):  
A. M. Glas ◽  
P. Roepman ◽  
R. Salazar ◽  
G. Capella ◽  
V. Moreno ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
High Risk ◽  
Adjuvant Chemotherapy ◽  
Cancer Patients ◽  
Gene Signature ◽  
Low Risk ◽  
Stage Ii ◽  
Significant Difference ◽  
Independent Cohort

4036 Background: Between 25 and 35% of stage II CRC patients will experience a recurrence of their disease and may benefit from adjuvant chemotherapy. Official guidelines give suggestions but no clear recommendation for best risk stratification. Here we describe the development a robust signature that predicts disease relapse and can assist in treatment decisions. Methods: Fresh frozen tumor tissues from 180 patients with stage I, II and III colorectal cancer undergoing surgery were analyzed using high density Agilent 44K oligonucleotide arrays. Median FU was 70.2 months; 85% of patients did not receive adjuvant chemotherapy. Unsupervised hierarchical clustering based on full-genome gene expression measurement indicated the existence of 3 main colon molecular subclasses. Survival analysis of the 3 classes showed that subtype C (n= 27) had a poor outcome and subtype A (n= 48) good outcome. Only the intermediate group B (n=104) was used to develop a signature by using a cross validation procedure to score all genes for their association with 5-yr distant metastasis free survival (DMFS) and subsequently applied to all samples (n=180). The obtained gene signature was further validated on an independent cohort of 178 stage II + III colon samples. Results: A set of 38 prognosis related gene probes showed robust DMFS association in over 50% of all iterations in the Training Set of 180 samples. The gene signature was validated on an independent cohort of 178 samples from stage II + III colon cancer patients. The profile classified 61% of the validation samples as low-risk and 39% as high-risk. The low- and high-risk samples showed a significant difference in DMFS with a HR of 3.19 (P= 8.5e-4). Five-year DMFS rates were 89% (95%CI 83–95) for low-risk and 62% (95%CI 50–77) for high-risk samples. Moreover, the profile showed a significant performance within stage II (P=0.0058) and III (P=0.036) only samples. The performance of the profile was significant for both untreated (P=0.0082) and treated patients (P=0.016) suggesting that its power is independent of treatment benefits. Conclusions: ColoPrint is able to predict the prognosis of stage II and III colon cancer patients and facilitates the identification of patients who would benefit from adjuvant chemotherapy. [Table: see text]

ABCG2 and TOP-1 mRNA expression as predictive biomarkers for adjuvant FOLFIRI treatment in stage III colon cancer patients: Results from the PETAAC-3 prospective randomized clinical trial.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 11594-11594
Author(s):  
Nils Brunner ◽  
Jan Stenvang ◽  
Eva Budinska ◽  
Sune Boris Nygaard
Keyword(s):  
Colon Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Adjuvant Treatment ◽  
Stage Iii ◽  
Expression Data ◽  
P Values ◽  
Mrna Expression Data ◽  
Stage Iii Colon Cancer ◽  
Significant Difference

11594 Background: FOLFIRI as adjuvant treatment in primary colon cancer was previously tested in two pivotal prospective randomized clinical trials (PETACC-3 and CALGB 89803), both of which failed to demonstrate significant beneficial effects when adding irinotecan to 5FU. As a consequence, FOLFIRI is presently not used as adjuvant treatment for colon cancer. Methods: The study included 580 patients with mRNA expression data performed on tumor samples (FFPE) from stage III colon cancer patients enrolled in the PETACC-3 study, which randomized the patients to 5FU plus Leucovorin +/- irinotecan. Primary end-points were recurrence-free survival (RFS) and overall survival (OS). Median ABCG2 and the 75 percentile TOP-1 mRNA expression data were used to allocate the patients into one of two groups: One with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) (n = 167) and another group including all other combinations of these two genes. Kaplan Meier curves and Cox proportional hazards model were used to visualize differences between groups and calculate p-values (log-rank test). Results: The survival statistics showed a significant difference for both RFS (HR: 0.63 (0.44-0.92); p = 0.017) and OS (HR: 0.6 (0.39-0.93); p = 0.021) between the two groups when the patients received FOLFIRI. In contrast, no significant differences were observed between the groups when patients received 5FU and Leucovorin alone (p-values: RFS: 0.58; OS: 0.75). Conclusions: We here show that the combination of two independent gene expression abundance with a strong association to irinotecan treatment (high ABCG2 drug efflux pump and low TOP-1, the latter being the target for irinotecan) identified a group of stage III colon cancer patients who will not benefit from FOLFIRI adjuvant treatment while patients with other combinations of expression of these two genes appear to significantly benefit from adjuvant FOLFIRI treatment. The lack of a similar effect in patients receiving treatment with 5FU and Leucovorin only, points to a predictive value of ABCG2 and TOP-1 measurements.

scholarly journals Features of immune status in patients with metastatic and glial brain tumors at the preparatory stage of radiotherapy

2020 ◽  
Vol 28 (4) ◽  
pp. 353-363
Author(s):  
A. A. Gryazov ◽  
M. I. Lisyany ◽  
A. B. Gryazov
Keyword(s):  
Innate Immunity ◽  
Radiation Therapy ◽  
Immune System ◽  
Brain Tumors ◽  
Cancer Patients ◽  
Immune Cells ◽  
Immune Status ◽  
Myeloperoxidase Activity ◽  
Metastatic Tumors ◽  
Significant Difference

Background. Studies carried out in recent decades have shown that immune cells are essential participants in the cancer process as well as cancerrelated inflammation. Focus has been increased on understanding the way how immune cells affect a tumor at different stages of the disease: early neoplastic transformation, clinically detected tumors, metastatic spread, and at surgery and radiotherapy stages. Purpose – assessing the status of the immune system in patients with brain tumors before radiation therapy and radiosurgery and comparing the features of immunity in metastatic and glial brain tumors. Materials and methods. The study presents the immunogram findings of 61 patients. Out of those: 18 patients with primary glial tumors and 23 patients with secondary metastatic tumors to the brain. The outcomes of 20 conditionally healthy non-cancer patients are presented as a control group. The age of patients is 24–75. All patients were histologically diagnosed with the tumor. Surgery was performed 1.0–3.0 years before the examination. Assessment of the immune system in patients with brain tumors was performed taking into account the cellular, humoral and phagocytic component of innate immunity. When assessing cellular immunity, the relative and absolute count of major lymphocyte subpopulations, such as CD3+ – general T-lymphocytes, CD4+ – T-lymphocytes-helpers, CD8+ – cytotoxic lymphocytes, CD16+ – natural killer lymphocytes, CD19+-B-lymphocytes, were calculated. Determining the humoral parameters included an assessment of quantitative values of IgG, IgM and IgA. Quantitative assessment of the phagocytic component of innate immunity included phagocytic activity of neutrophils (i. e. NBT test (Nitroblue Tetrazolium test), inducing (Zymosanum) and spontaneous neutrophil myeloperoxidase activity). Results. When comparing the immune parameters of the number of T- and B-subpopulations of lymphocytes in patients with primary malignant brain tumors and secondary metastatic tumors, no statistically significant difference has been detected between these params. Glioblastomas show higher levels of СD4+- and CD8+-lymphocytes in comparison with other tumour groups as well as higher levels of IgG and IgA than in other tumors, while IgM concentration is almost at the same level in three groups of patients. There is a tendency for reducing IgG and IgM level in the blood of patients with metastatic tumors. Both groups of cancer patients under study show inhibition of myeloperoxidase activity of neutrophils in the setting of maintaining the function of NBT cell activity. Conclusions. According to the findings obtained via studying immunological indicators of brain tumors, both metastatic and primary malignant glial ones, there are partial changes in various immune system components such as cellular, humoral and phagocytic activity. However, no statistically significant difference was detected between immune status indicators, that substantiates the need for further study of this issue. At the stage of preparation for radiation therapy, no significant changes in the immune system of the patients with brain tumors, that would make such treatment impossible and be consiered as one of contraindications, are observed.

scholarly journals Identification of Distinct Molecular Patterns and a Four-Gene Signature in Colon Cancer Based on Invasion-Related Genes

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunfei Dong ◽  
Tao Shang ◽  
HaiXin Ji ◽  
Xiukou Zhou ◽  
Zhi Chen
Keyword(s):  
Gene Expression ◽  
Colon Cancer ◽  
Cancer Patients ◽  
Risk Group ◽  
Univariate Analysis ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Lasso Regression ◽  
Independent Predictive Factor

BackgroundThe pathological stage of colon cancer cannot accurately predict recurrence, and to date, no gene expression characteristics have been demonstrated to be reliable for prognostic stratification in clinical practice, perhaps because colon cancer is a heterogeneous disease. The purpose was to establish a comprehensive molecular classification and prognostic marker for colon cancer based on invasion-related expression profiling.MethodsFrom the Gene Expression Omnibus (GEO) database, we collected two microarray datasets of colon cancer samples, and another dataset was obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) further underwent univariate analysis, least absolute shrinkage, selection operator (LASSO) regression analysis, and multivariate Cox survival analysis to screen prognosis-associated feature genes, which were further verified with test datasets.ResultsTwo molecular subtypes (C1 and C2) were identified based on invasion-related genes in the colon cancer samples in TCGA training dataset, and C2 had a good prognosis. Moreover, C1 was more sensitive to immunotherapy. A total of 1,514 invasion-related genes, specifically 124 downregulated genes and 1,390 upregulated genes in C1 and C2, were identified as DEGs. A four-gene prognostic signature was identified and validated, and colon cancer patients were stratified into a high-risk group and a low-risk group. Multivariate regression analyses and a nomogram indicated that the four-gene signature developed in this study was an independent predictive factor and had a relatively good predictive capability when adjusting for other clinical factors.ConclusionThis research provided novel insights into the mechanisms underlying invasion and offered a novel biomarker of a poor prognosis in colon cancer patients.

scholarly journals Effect of Aging-Related Genes on the Prognosis of Colon Cancer

2021 ◽  
Author(s):  
Yushu Liu ◽  
Jiantao Gong ◽  
Yanyi Huang ◽  
Qunguang Jiang
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Validation Cohort ◽  
External Validation ◽  
Predictive Ability ◽  
Lasso Regression ◽  
Internal Validation ◽  
Cox Regression Analysis

Abstract Background:Colon cancer is a common malignant cancer with high incidence and poor prognosis. Cell senescence and apoptosis are important mechanisms of tumor occurrence and development, in which aging-related genes(ARGs) play an important role. This study aimed to establish a prognostic risk model based on ARGs for diagnosis and prognosis prediction of colon cancer .Methods: We downloaded transcriptome data and clinical information of colon cancer patients from the Cancer Genome Atlas(TCGA) database and the microarray dataset(GSE39582) from the Gene Expression Omnibus(GEO) database. Univariate COX, least absolute shrinkage and selection operator(LASSO) regression algorithm and multivariate COX regression analysis were used to construct a 6-ARG prognosis model and calculated the riskScore. The prognostic signatures is validated by internal validation cohort and external validation cohort(GSE39582).In addition, functional enrichment pathways and immune microenvironment of aging-related genes(ARGs) were also analyzed. We also analyzed the correlation between rsikScore and clinical features and constructed a nomogram based on riskScore. We are the first to construct prognostic nomogram based on ARGs.Results: Through univariate COX,LASSO regression algorithm and multivariate COX regression analysis,6 prognostic ARGs (PDPK1,RAD52,GSR,IL7,BDNF and SERPINE1) were screened out and riskScore was constructed. We have verified that riskScore has good prognostic value in both internal validation cohort and external validation cohort. Pathway enrichment and immunoanalysis of ARGs provide a direction for the treatment of colon cancer patients. We also found that riskScore was closely related to the clinical characteristics of patients. Based on riskScore and related clinical features, we constructed a nomogram, which has good predictive performance.Conclusion: The 6-ARG prognostic signature we constructed has a certain clinical predictive ability. Its riskScore is also closely related to clinical characteristics, and nomogram based on this has stronger predictive ability than a single indicator. ARGs and the nomogram we constructed may provide a promising treatment for colon cancer patients.

ABCG2 and TOP1 mRNA expression as predictive biomarkers for adjuvant FOLFIRI treatment in stage III colon cancer patients: Results from the PETAAC-3 prospective randomized clinical trial.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 591-591 ◽  
Author(s):  
Nils Brunner ◽  
Sune Boris Nygaard ◽  
Eva Budinska ◽  
Jan Stenvang
Keyword(s):  
Colon Cancer ◽  
Mrna Expression ◽  
Cancer Patients ◽  
Adjuvant Treatment ◽  
Randomized Clinical Trials ◽  
Stage Iii ◽  
Expression Data ◽  
Mrna Expression Data ◽  
Stage Iii Colon Cancer ◽  
Significant Difference

591 Background: FOLFIRI as adjuvant treatment in primary colon cancer was previously tested in two pivotal prospective randomized clinical trials (PETACC-3 and CALGB 89803), both of which failed to demonstrate significant beneficial effects when adding irinotecan to 5FU. As a consequence, FOLFIRI is presently not used as adjuvant treatment for colon cancer. Methods: The study included 580 patients with mRNA expression data performed on tumor samples (FFPE) from stage III colon cancer patients enrolled in the PETACC-3 study, which randomized the patients to 5FU plus Leucovorin +/- irinotecan. Primary end-points were disease free survival (DFS) and overall survival (OS). Median ABCG2 and the 75 percentile TOP-1 mRNA expression data were used to allocate the patients into one of two groups: One with high ABCG2 expression (above median) and low TOP-1 expression (below 75 percentile) (n = 167) and another group including all other combinations of these two genes. Kaplan Meier curves and Cox proportional hazards model were used to visualize differences between groups and calculate p-values (log-rank test). Results: The survival statistics showed a significant difference for both RFS (HR: 0.63 (0.44-0.92); p = 0.017) and OS (HR: 0.6 (0.39-0.93); p = 0.021) between the two groups when the patients received FOLFIRI. In contrast, no significant differences were observed between the groups when patients received 5FU and Leucovorin alone (RFS: 0.58; OS: 0.75). Conclusions: We here show that the combination of two independent gene expression abundance with a strong association to irinotecan treatment (high ABCG2 drug efflux pump and low TOP-1, which is the target for irinotecan) identified a group of stage III colon cancer patients who will not benefit from FOLFIRI adjuvant treatment while patients with other combinations of expression of these two genes appear to significantly benefit from adjuvant FOLFIRI treatment. The lack of a similar effect in patients receiving treatment with 5FU and Leucovorin only, points to a predictive value of ABCG2 and TOP-1 measurements.

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