Value In Colon Cancer Research Articles

LGR6 is a prognostic biomarker for less differentiated tumors in lymph nodes of colon cancer patients.

The aim was to investigate whether the stem cell marker LGR6 has prognostic value in colon cancer, alone or in combination with the prognostic biomarkers CEA and CXCL16. LGR6 mRNA levels were determined in 370 half lymph nodes of 121 colon cancer patients. Ability to predict relapse after curative surgery was estimated by Kaplan-Meier survival model and Cox regression analyses. Patients with high LGR6 levels [LGR6(+)] had a decreased mean survival time of 11 months at 5-year follow-up and 47 months at 12-year follow-up, respectively, with hazard ratios of 3.2 and 2.8. LGR6 mRNA analysis added prognostic value to CEA and CXCL16 mRNA analysis. In the poor prognosis groups CEA(+) and CXCL16(+), further division was achieved by LGR6 analysis. LGR6(+) patients had a very poor prognosis. LGR6 also identified a small number of CEA(-), TNM stage I patients who relapsed suggesting stem cell origin of these tumors. LGR6 and LGR5 levels correlated strongly in lymph nodes of stage I and IV patients but not in stage II patients, suggesting that these stem cell markers are differentially regulated. This study highlights LGR6 as a useful prognostic biomarker independently and in combination with CEA, CXCL16 or LGR5 identifying different risk groups.

Venous invasion detectable only by elastic stain shows weak prognostic value in colon cancer.

Large venous invasion (VI) is prognostically significant in colon cancer. The increased use of elastic stains by pathologists results in higher VI detection rates compared to routine stains alone. This study assesses the prognostic value of VI detected by elastic versus routine stains. Colon cancers resected between 2014 and 2017 underwent pathology slide review for VI. Cases without VI on routine stain were stained by elastic trichrome and re-examined. Demographic, clinical, pathological and outcome data were gathered by retrospective review. Kaplan-Meier curves with log-rank tests were performed for survival categorised by VI status. Cox regression was performed for multivariate analysis. Of 277 cases, 97 (35%) showed VI by routine stain alone, with an additional 58 (21%) discovered by subsequent elastic stains. Thus, elastic trichrome increased VI detection by 60%. However, only VI detected by routine stain showed worse overall survival (P < 0.001). VI detected by elastic stain only was not prognostically different from cases without VI (P = 0.428). For stage 2 cancers, VI was not prognostically significant regardless of method of detection. For stage 3 cases, only VI detected by routine stain was prognostic for overall survival (P = 0.002) with a hazard ratio of 4.04 by multivariate regression (P = 0.028). VI detectable only by elastic stains do not show prognostic significance for survival in colon cancer. For pathologists with high baseline VI detections rates on routine stain, reflexive use of elastic stain may be of limited value.

Identification of molecular targets and underlying mechanisms of Fuzheng Shengbai Decoction against colon cancer based on network pharmacology.

To investigate the molecular targets and underlying mechanisms of Fuzheng Shengbai Decoction (FZSBD) against colon cancer (CC). Multiple network pharmacology approaches were used to predict the molecular targets and underlying mechanisms of FZSBD against CC. The expression of potential molecular targets was determined. The effects of FZSBD on cell viability, proliferation, migration, invasion, and the cell cycle of CC cells were investigated. The therapeutic efficacy, hematological, immunological, and inflammatory data in patients with CC were evaluated after treatment with the XELOX regimen with and without FZSBD. A total of 912 potential targets in FZSBD and 2765 DEGs in CC specimens were screened. Five hub genes (TP53, MYC, VEGFA, CCND1, and IL1B) closely associated with immune-related signaling pathways and the cell cycle process were identified. The five hub genes were of prognostic value in CC. The gene and protein expression of the five hub genes was significantly higher in CC tumor tissue samples than that of normal tissue samples. Furthermore, with increasing doses, FZSBD increasingly inhibited growth, migration, and invasion, and suppressed the cell cycle process of CC cells. Supplementing of FZSBD to the XELOX regimen enhanced immune modulation and alleviated inflammatory responses. This study identified the molecular targets and underlying mechanisms of FZSBD treatment against CC and may provide clues for future research on the treatment of CC with FZSBD.

TMUB1 expression is associated with the prognosis of colon cancer and immune cell infiltration.

TMUB1 is a transmembrane protein involved in biological signaling and plays an important role in the stability and transcription of P53. However, its role in tumor remains unknown. Using R language, the expression level of 33 cancer spectrum TMUB1 was analyzed by the public database TCGA, GEO and HPA, the differential expressed gene (DEG) screening and protein interaction (PPI) network was constructed, and the differential genes of TMUB1 in colon cancer were identified. The relevant signaling pathways were identified by gene functional annotation and enrichment analysis. The ssGSEA algorithm in GSVA were used for immune infiltration analysis. The Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, nomogram and calibration map analysis were constructed to evaluate the correlation between TMUB1 expression and clinical prognosis. The expression levels of TMUB1 in intestinal cancer cell lines as well as in 10 intestinal cancer tissues were verified by qPCR experiments. Through the bioinformatics analysis of multiple databases and preliminary experimental studies, we found that the expression of TMUB1 was significantly increased in colon cancer tumors, and was correlated with the clinical N stage, pathological grade, lymphatic metastasis and BMI of colon cancer. TMUB1 may be involved in the regulation of the malignant progression of colon cancer. Meanwhile, patients with high expression of TMUB1 mRNA had worse OS and DSS, and TMUB1 expression was an independent prognostic factor for OS and DSS. It was further found that highly expressed TMUB1 tissues showed low levels of immune infiltration and stromal infiltration. We reported the expression level of TMUB1 in colon cancer and analyzed its potential prognostic value in colon cancer through the bioinformatics analysis and preliminary experimental studies. The high expression of TMUB1 is a negative prognostic factor for colon cancer patients. TMUB1 may be a potential target for colon cancer.

Association between Ki67 expression and therapeutic outcome in colon cancer.

Ki67 is a commonly used proliferation marker in pathological diagnosis of tumors; however, its prognostic value in colon cancer is controversial. A total of 312 consecutive patients with stage I-III colon cancer who underwent radical surgery with or without adjuvant chemotherapy were included in the present study. Ki67 expression was assessed using immunohistochemistry and was classified according to 25% intervals. The association between Ki67 expression and clinicopathological features was analyzed. Long-term postoperative survival, including disease-free survival (DFS) and overall survival, was calculated, and its association with Ki67 was analyzed. High Ki67 expression (>50%) was associated with improved DFS in patients treated with adjuvant chemotherapy postoperatively, but not in patients who received surgery alone (P=0.138). Ki67 expression was significantly associated with histological differentiation of the tumor (P=0.01), while it was not associated with other clinicopathological factors. Multivariate analysis demonstrated that pathological T and N stage were independent prognostic factors. In conclusion, high Ki67 expression was associated with a good therapeutic outcome in patients receiving adjuvant chemotherapy in colon cancer.

β-Sitosterol blocks the LEF-1-mediated Wnt/β-catenin pathway to inhibit proliferation of human colon cancer cells

ObjectivesThis study aimed to investigate the LEF-1-mediated Wnt/β-catenin pathway for its biological functions and prognostic value in colon cancer (CC). Furthermore, the potential molecular mechanism of β-sitosterol in CC was investigated in vitro. MethodsClinical information and gene expression profiles from CC patients were obtained based on Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. In addition, we applied R software “Limma” package for the differential analysis of LEF-1 between cancer and para-carcinoma tissue samples. Kaplan–Meier (KM) survival analysis was adopted for analyzing whether LEF-1 was of prognostic significance. Moreover, gene set enrichment analysis (GSEA) was adopted for pathway enrichment analysis and visualization. In addition, CCK8, plate cloning, scratch and high-content screening (HCS) imaging assays were performed to examine the therapeutic efficacy of β-sitosterol in human CC HCT116 cells. siRNA technology was employed to knock down LEF1 expression in HCT116 cells. qRT-PCR and Western-blot (WB) analysis were carried out to analyze the HCT-116 mRNA and protein expression levels, respectively. ResultsLEF-1 was up-regulated within CC and acted as an oncogenic gene. LEF-1 up-regulation predicted the dismal prognostic outcome and activated the Wnt/β-catenin pathway. β-sitosterol effectively suppressed HCT116 cells proliferation and invasion. For the mechanism underlying β-sitosterol, β-sitosterol was found to significantly down-regulate LEF-1 gene and protein expression and disrupt Wnt/β-catenin pathway transmission in HCT116 cells. After suppressing LEF-1 expression, its downstream targets including C-myc, Survivin and CCND1 were also down-regulated. ConclusionAccording to our results, LEF-1 down-regulation can effectively block Wnt/β-catenin pathway, inhibit CC cell growth and migration. Collectively, β-sitosterol can be used to treat CC, which can provide anti-tumor activity by targeting LEF-1.

Immunohistochemical evaluation of ALDH1 and ALDH2 as cancer stem cell markers in Iraqi patients with colon carcinoma

Colon cancer is the second most popular cause of death. is a important public health issue in developed countries for many years because of its frequency even with the screening and preventative strategies. It stills the second most common cancer in women and third prevalent cancer in men. Like other tumors. The most drug resistance subsets of cancer cells with high proliferation capacity are colon cancer stem cells (CCSCs) with self renewal and multi differentiation capacities. recently indicate that aldehyde dehydrogenase have role in drug resistance ALDH1 and ALDH2 have prognostic and clinicopathological value in colon cancer. The research involved 60 patients (both men and women) ranging in age from 35 to 65 years old. The samples taken from the Ministry of Health and Environment the medical city hospital’s histology laboratory, the Department of Education Laboratories. Colon cancer samples were divided into three groups: group I contained 20 samples from patients recently diagnosed with colon cancer, group II included samples from relapse patients who received chemotherapy but the tumor relapsed, and group III are resistance patient. This study was planned to evaluate the ALDH1 and ALDH2 as a marker for colon cancer stem cell.The percentage of the positivity forALDH1 and ALDH 2 shows in Figs. 3-7. The result are different between groups. Group one (new diagnosis patients) recorded low expression forALDH1 and ALDH2 about 33% forALDH1 and 48% forALDH2 in comparison with group II (relapsed patient) that represented moderate expression to the marker ( 63% and 72% forALDH1 and ALDH2, respectively). While, the higher expression was for group III (resistance patient) with percent of expression 80% and 90%

Integrated computer analysis and a self-built Chinese cohort study identified GSTM2 as one survival-relevant gene in human colon cancer potentially regulating immune microenvironment.

According to a recent report by GLOBOCAN, colorectal cancer is the third most common and second most deadly cancer in 2020. In our previous proteomic study, we found that the expression of GSTM2 in colon tissues was significantly lower than that in para-cancer tissues, and its lower expression was associated with reduced overall survival rate of patients, suggesting that this gene might play a role in the occurrence of colon cancer. As a member of the detoxifying enzyme family, GSTM2 is likely to play an important role in the initiation of tumors. Whereas, the functions of GSTM2 in colon cancer are barely known. In this study, using the RNA-Seq datasets of colon cancer patients from public database (ntumor = 457, nnormal = 41), we confirmed the reduced expression of GSTM2 and its prognostic value in colon cancer. Furthermore, we used our own Chinese cohort (ntumor = 100, nnormal = 72) verified the lower GSTM2 expression in colon cancer, and also its effects on patient prognosis. Subsequently, we uncovered two potential reasons for the lower expression of GSTM2 in colon cancer tissues, including the deep deletion of GSTM2 on genome, and the up-regulation of RAD21 or SP1. Moreover, we disclosed that GSTM2 might be involved in several immune-related pathways in colon cancer, such as chemokine signaling and leukocyte transendothelial migration. Finally, we revealed that the GSTM2 expression was closely related to the immune-related scores of colon cancer and the infiltration ratios of various immune cells, suggesting that GSTM2 might regulate the development of colon cancer by modulating immune microenvironment. In conclusion, we uncovered the prognostic value of GSTM2 based on the public data and our own data, revealed its potential regulatory role in tumor immune microenvironment, and disclosed the probable reasons for its lower expression in colon cancer. The findings of our study provide a potential prognostic biomarker and drug target for clinical diagnosis and treatment of colon cancer.

Identification of Autophagy-Related LncRNA to Predict the Prognosis of Colorectal Cancer.

Objective: To establish a prediction model based on autophagy-related lncRNAs and investigate the functional enrichment of autophagy-related lncRNAs in colorectal cancer. Methods: TCGA database was used to extract the transcriptome data and clinical features of colorectal cancer patients. HADb was used to obtain autophagy-related genes. Pearson correlation analysis was performed to identify autophagy-related lncRNAs. The autophagy-related lncRNAs with prognostic values were selected. Based on the selected lncRNAs, the risk score model and nomogram were constructed, respectively. Calibration curve, concordance index, and ROC curve were performed to evaluate the predictive efficacy of the prediction model. GSEA was performed to figure out the functional enrichment of autophagy-related lncRNAs. Results: A total of 13413 lncRNAs and 938 autophagy-related genes were obtained. A total of 709 autophagy-related genes were identified in colon cancer tissues, and 11 autophagy-related lncRNAs (AL138756.1, LINC01063, CD27-AS1, LINC00957, EIF3J-DT, LINC02474, SNHG16, AC105219.1, AC068580.3, LINC02381, and LINC01011) were finally selected and set as prognosis-related lncRNAs. According to the risk score, patients were divided into the high-risk and low-risk groups, respectively. The survival K–M (Kaplan–Meier) curve showed the low-risk group exhibits better overall survival than the high-risk group. The AUCs under the ROC curves were 0.72, 0.814, and 0.83 at 1, 3, and 5 years, respectively. The C-index (concordance index) of the model was 0.814. The calibration curves at 1, 3, and 5 years showed the predicting values were consistent with the actual values. Functional enrichment analysis showed that autophagy-related lncRNAs were enriched in several pathways. Conclusions: A total of 11 specific autophagy-related lncRNAs were identified to own prognostic value in colon cancer. The predicting model based on the lncRNAs and clinical features can effectively predict the OS. Furthermore, functional enrichment analysis showed that autophagy-related genes were enriched in various biological pathways.

Identification of Hub Genes for Early Diagnosis and Predicting Prognosis in Colon Adenocarcinoma.

Colon adenocarcinoma (COAD) is among the most common digestive system malignancies worldwide, and its pathogenesis and gene signatures remain unclear. This study explored the genetic characteristics and molecular mechanisms underlying colon cancer development. Three gene expression data sets were obtained from the Gene Expression Omnibus (GEO) database. GEO2R was used to determine differentially expressed genes (DEGs) between COAD and normal tissues. Then, the intersection of the data sets was obtained. Metascape was used to perform the functional enrichment analyses. Next, STRING was used to build protein-protein interaction (PPI) networks. Hub genes were identified and analysed using Cytoscape. Next, survival analysis and expression analysis of the hub genes were performed. ROC curve analysis was performed for further test of the diagnostic efficacy. Finally, alterations in the hub genes were predicted and analysed by cBioPortal. Altogether, 436 DEGs were detected. The DEGs were mainly enriched in cell cycle phase transition, nuclear division, meiotic nuclear division, and cytokinesis. Based on PPI networks, 20 hub genes were selected. Among them, 6 hub genes (CCNB1, CCNA2, AURKA, NCAPG, DLGAP5, and CENPE) showed significant prognostic value in colon cancer (P < 0.05), while 5 hub genes (CDK1, CCNB1, CCNA2, MAD2L1, and DLGAP5) were associated with early colon cancer diagnosis and ROC curve analysis showed good diagnostic accuracy. In conclusion, integrated bioinformatics analysis was used to identify hub genes that reveal the potential mechanism of carcinogenesis and progression of colon cancer. The hub genes might be novel biomarkers for early diagnosis, treatment, and prognosis of colon cancer.

Comprehensive Analysis of Microsatellite-Related Transcriptomic Signature and Identify Its Clinical Value in Colon Cancer.

BackgroundMicrosatellite has been proved to be an important prognostic factor and a treatment reference in colon cancer. The transcriptome profile and tumor microenvironment of different microsatellite statuses are different. Metastatic colon cancer patients with microsatellite instability-high (MSI-H) are sensitive to immune checkpoint inhibitors (ICIs), but not fluorouracil. Efforts have been devoted to identify the predictive factors of immunotherapy.MethodsWe analyzed the transcriptome profile of different microsatellite statuses in colon cancer by using single-cell and bulk transcriptome data from publicly available databases. The immune cells in the tumor microenvironment were analyzed by the ESTIMATION algorithm. The microsatellite-related gene signature (MSRS) was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression based on the differentially expressed genes (DEGs) and its prognostic value and predictive value of response to immunotherapy were assessed. The prognostic value of the MSRS was also validated in another cohort.ResultsThe MSI-H cancers cells were clustered differentially in the dimension reduction plot. Most of the immune cells have a higher proportion in the tumor immune microenvironment, except for CD56 bright natural killer cells. A total of 238 DEGs were identified. Based on the 238 DEGs, a neural network was constructed with a Kappa coefficient of 0.706 in the testing cohort. The MSRS is a favorable prognostic factor of overall survival, which was also validated in another cohort (GSE39582). Besides, MSRS is correlated with tumor mutation burden in MSI-H colon cancer. However, the MSRS is a barely satisfactory factor in predicting immunotherapy with the area under the curve (AUC) of 0.624.ConclusionWe developed the MSRS, which is a robust prognostic factor of overall survival in spite of a barely satisfactory immunotherapy predictor. Further studies may need to improve the predictive ability.

Niclosamide induces miR-148a to inhibit PXR and sensitize colon cancer stem cells to chemotherapy.

SummaryTumor recurrence is often attributed to cancer stem cells (CSCs). We previously demonstrated that down-regulation of Pregnane X Receptor (PXR) decreases the chemoresistance of CSCs and prevents colorectal cancer recurrence. Currently, no PXR inhibitor is usable in clinic. Here, we identify miR-148a as a targetable element upstream of PXR signaling in CSCs, which when over-expressed decreases PXR expression and impairs tumor relapse after chemotherapy in mouse tumor xenografts. We then develop a fluorescent reporter screen for miR-148a activators and identify the anti-helminthic drug niclosamide as an inducer of miR-148a expression. Consequently, niclosamide decreased PXR expression and CSC numbers in colorectal cancer patient-derived cell lines and synergized with chemotherapeutic agents to prevent CSC chemoresistance and tumor recurrence in vivo. Our study suggests that endogenous miRNA inducers is a viable strategy to down-regulate PXR and illuminates niclosamide as a neoadjuvant repurposing strategy to prevent tumor relapse in colon cancer.

PBK/TOPK Is a Favorable Prognostic Biomarker Correlated with Antitumor Immunity in Colon Cancers.

Immune checkpoint inhibitor therapy has proven efficacy in a subset of colon cancer patients featuring a deficient DNA mismatch repair system or a high microsatellite instability profile. However, there is high demand for more effective biomarkers to expand the colon cancer population responding to ICI therapy. PBK/TOPK, a serine/threonine kinase, plays a role in cell cycle regulation and mitotic progression. Here, we investigated the correlation between PBK/TOPK expression and tumor immunity and its prognostic value in colon cancer. Based on large-scale bioinformatics analysis, we discovered that elevated PBK/TOPK expression predicted a favorable outcome in patients with colon cancer and was positively associated with immune infiltration levels of CD8+ T cells, CD4+ T cells, natural killer cells, and M1 macrophages. In contrast, a negative correlation was found between PBK/TOPK expression and immune suppressor cells, including regulatory T cells and M2 macrophages. Furthermore, the expression of PBK/TOPK was correlated with the expression of T-cell cytotoxicity genes in colon cancer. Additionally, high PBK/TOPK expression was associated with mutations in DNA damage repair genes, and thus with increased tumor mutation and neoantigen burden. These findings suggest that PBK/TOPK may serve as a prognostic and predictive biomarker for immunotherapy in colon cancer.

Construction of a long noncoding RNA-based competing endogenous RNA network and prognostic signatures of left- and right-side colon cancer

BackgroundCancers located on the right and left sides of the colon have distinct clinical and molecular characteristics. This study aimed to explore the regulatory mechanisms of location-specific long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) in colon cancer and identify potential prognostic biomarkers.MethodDifferentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between right- and left-side colon cancers were identified by comparing RNA sequencing profiles. Functional enrichment analysis was performed for the DEGs, and a ceRNA network was constructed. Associations between DELs and patient survival were examined, and a DEL-based signature was constructed to examine the prognostic value of these differences. Clinical colon cancer tissues and Gene Expression Omnibus (GEO) datasets were used to validate the results.ResultsWe identified 376 DELs, 35 DEMs, and 805 DEGs between right- and left-side colon cancers. The functional enrichment analysis revealed the functions and pathway involvement of DEGs. A ceRNA network was constructed based on 95 DEL–DEM–DEG interactions. Three DELs (LINC01555, AC015712, and FZD10-AS1) were associated with the overall survival of patients with colon cancer, and a prognostic signature was established based on these three DELs. High risk scores for this signature indicated poor survival, suggesting that the signature has prognostic value for colon cancer. Examination of clinical colon cancer tissues and GEO dataset analysis confirmed the results.ConclusionThe ceRNA regulatory network suggests roles for location-specific lncRNAs in colon cancer and allowed the development of an lncRNA-based prognostic signature, which could be used to assess prognosis and determine treatment strategies in patients with colon cancer.

Correlations Between Tumor Mutation Burden and Immunocyte Infiltration and Their Prognostic Value in Colon Cancer.

BackgroundColon cancer has a huge incidence and mortality worldwide every year. Immunotherapy could be a new therapeutic option for patients with advanced colon cancer. Tumor mutation burden (TMB) and immune infiltration are considered critical in immunotherapy but their characteristics in colon cancer are still controversial.MethodsThe somatic mutation, transcriptome, and clinical data of patients with colon cancer were obtained from the TCGA database. Patients were divided into low or high TMB groups using the median TMB value. Somatic mutation landscape, differentially expressed genes, and immune-related hub genes, Gene Ontology and KEGG, gene set enrichment, and immune infiltration analyses were investigated between the two TMB groups. Univariate and multivariate Cox analyses were utilized to construct a prognostic gene signature. The differences in immune infiltration, and the expression of HLA-related genes and checkpoint genes were investigated between the two immunity groups based on single sample gene set enrichment analysis. Finally, a nomogram of the prognostic prediction model integrating TMB, immune infiltration, and clinical parameters was established. Calibration plots and receiver operating characteristic curves (ROC) were drawn, and the C-index was calculated to assess the predictive ability.ResultsMissense mutations and single nucleotide polymorphisms were the major variant characteristics in colon cancer. The TMB level showed significant differences in N stage, M stage, pathological stage, and immune infiltration. CD8+ T cells, activated memory CD4+ T cells, activated NK cells, and M1 macrophages infiltrated more in the high-TMB group. The antigen processing and presentation signaling pathway was enriched in the high-TMB group. Two immune related genes (CHGB and SCT) were identified to be correlated with colon cancer survival (HR = 1.39, P = 0.01; HR = 1.26, P = 0.02, respectively). Notably, the expression of SCT was identified as a risk factor in the immune risk model, in which high risk patients showed poorer survival (P = 0.04). High immunity status exhibited significant correlations with immune response pathways, HLA-related genes, and immune checkpoint genes. Finally, including nine factors, our nomogram prediction model showed better calibration (C-index = 0.764) and had an AUC of 0.737.ConclusionIn this study, we investigated the patterns and prognostic roles of TMB and immune infiltration in colon cancer, which provided new insights into the tumor microenvironment and immunotherapies and the development of a novel nomogram prognostic prediction model for patients with colon cancer.

Low levels of BRCA1 protein expression predict a worse prognosis in stage I-II colon cancer.

BRCA1 and BRCA2 have been well studied for their roles in tumorigeneis, plus cancer diagnosis and treatment, but their prognostic value in colon cancer, especially for early-stage cancer, has not been fully illuminated. This study examined the expression levels of BRCA1 and BRCA2 proteins in sporadic colon cancer cases and investigated their value in prognosis. The expression levels of BRCA1 and BRCA2 in 275 colon cancer patients who underwent radical surgeries were assayed by immunohistochemical staining in dissected tumor samples. Also, its correlation with clinicopathological characteristics, disease-free survival, and overall survival was investigated. Tumors with low expression levels of BRCA1, BRCA2, and both were 19.6%, 17.8%, and 6.5%, respectively. The levels of BRCA1/2 expression were not associated with clinicopathological parameters (gender, age, histological differentiation, and tumor node metastasis stage). Patients with low-levels of BRCA1 protein in their tumors demonstrated a lower chance of 5-year disease-free survival (55.6% vs. 69.7%, P=0.046), which was more obvious in the patients with stage I-II tumors without chemotherapy (52.6% vs. 82.6%, P=0.006). Neither BRCA1 nor BRCA2 affected overall survival in this cohort. Multivariate analysis revealed that pathologic stage and the level of BRCA1 protein were independent factors of long-term disease-free survival. This study highlights BRCA1 as an independent prognosticator of early-stage colon cancer.

Identification of hub genes in colon cancer via bioinformatics analysis.

ObjectivesThis study aimed to investigate hub genes and their prognostic value in colon cancer via bioinformatics analysis.MethodsDifferentially expressed genes (DEGs) of expression profiles (GSE33113, GSE20916, and GSE37364) obtained from Gene Expression Omnibus (GEO) were identified using the GEO2R tool and Venn diagram software. Function and pathway enrichment analyses were performed, and a protein–protein interaction (PPI) network was constructed. Hub genes were verified based on The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases.ResultsWe identified 207 DEGs, 62 upregulated and 145 downregulated genes, enriched in Gene Ontology terms “organic anion transport,” “extracellular matrix,” and “receptor ligand activity”, and in the Kyoto Encyclopedia of Genes and Genomes pathway “cytokine-cytokine receptor interaction.” The PPI network was constructed and nine hub genes were selected by survival analysis and expression validation. We verified these genes in the TCGA database and selected three potential predictors (ZG16, TIMP1, and BGN) that met the independent predictive criteria. TIMP1 and BGN were upregulated in patients with a high cancer risk, whereas ZG16 was downregulated. The immunostaining results from HPA supported these findings.ConclusionThis study indicates that these hub genes may be promising prognostic indicators or therapeutic targets for colon cancer.

Identifying a new microRNA signature as a prognostic biomarker in colon cancer.

BackgroundThe aim was to identify a novel prognostic miRNA signature for colon cancer (CC) in silico.MethodsData on the expression of miRNAs and relevant clinical information for 407 patients were obtained from The Cancer Genome Atlas (TCGA), and the samples were randomly split into a validation set (n = 203) and training set (n = 204). The differential expression of miRNAs between normal tissues and patients with CC was analyzed. We detected a miRNA expression signature in the training dataset by using a Cox proportional hazard regression model. Then, we verified the signature in the validation set. Association of the miRNA signature with overall survival was assessed in the validation cohort and combined cohort by log-rank test and based on Kaplan-Meier curves. The receiver operating characteristic and disease-free survival analyses were performed to evaluate the miRNA signature of CC in the combined cohort. Multivariate and univariate Cox analyses related to survival for the miRNA signature were performed, and a nomogram was built as a prognostic model for CC. To explore the function of target genes of the miRNA signature, Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used.ResultsBetween the matched normal tissues and colon cancer tissues, 267 differentially expressed miRNAs were detected, and a single-factor CoxPH model showed that 13 miRNAs were related to overall survival in the training cohort. Then, a five-miRNA signature was identified using a CoxPH regression model with multiple factors. The five-miRNA signature had significant prognostic value in the training cohort and was validated in the validation cohort and combined cohort. A total of 193 target genes of the miRNA signature were identified. According to the results of functional analysis of the target genes, the signaling pathways MAPK, AMPK and PI3K-Akt, focal adhesion, and microRNAs in cancer were remarkably enriched.ConclusionA five-miRNA signature had increased prognostic value for CC, which may provide important biological insights for the discovery and development of molecular predictors to improve the prognosis of patients with CC.

Development and validation of a five-lncRNA signature with prognostic value in colon cancer.

Dysregulation of long noncoding RNAs (lncRNAs) has been found in a large number of human cancers, including colon cancer. Therefore, the implementation of potential lncRNAs biomarkers with prognostic prediction value are very much essential. GSE39582 data set was downloaded from database of Gene Expression Omnibus. Re-annotation analysis of lncRNA expression profiles was performed by NetAffx annotation files. Univariate and multivariate Cox proportional analyses helped select prognostic lncRNAs. Algorithm of random survival forest-variable hunting (RSF-VH) together with stepwise multivariate Cox proportional analysis were performed to establish lncRNA signature. The log-rank test was carried out to analyze and compare the Kaplan-Meier survival curves of patients' overall survival (OS). Receiver operating characteristic (ROC) analysis was used for comparing the survival prediction regarding its specificity and sensitivity based on lncRNA risk score, followed by calculating the values of area under the curve (AUC). The single-sample GSEA (ssGSEA) analysis was used to describe biological functions associated with this signature. Finally, to determine the robustness of this model, we used the validation sets including GSE17536 and The Cancer Genome Atlas data set.After re-annotation analysis of lncRNAs, a total of 14 lncRNA probes were obtained by univariate and multivariate Cox proportional analysis. Then, the RSF-VH algorithm and stepwise multivariate Cox analysis helped to build a five-lncRNA prognostic signature for colon cancer. The patients in group with high risk showed an obviously shorter survival time compared with patients in group with low risk with AUC of 0.75. In addition, the five-lncRNA signature can be used to independently predict the survival of patients with colon cancer. The ssGSEA analysis revealed that pathways such as extracellular matrix-receptor interaction was activated with an increase in risk score. These findings determined the strong power of prognostic prediction value of this five-lncRNA signature for colon cancer.

Diagnostic and prognostic values of C‑X‑C motif chemokine ligand 3 in patients with colon cancer.

The diagnostic and prognostic mechanisms of C-X-C motif chemokine ligand 3 (CXCL3) in colon cancer (CC) have not yet been reported. Therefore, the objective of the present study was to use cohorts of patients from Guangxi Medical University and the Gene Expression Omnibus (GEO) database to investigate and validate CXCL3 for the diagnosis and prognosis of CC, and to explore its prospective molecular mechanism. Reverse transcription-quantitative PCR (RT-qPCR) analysis of 38 paired tumor and non-tumor tissues, and immunohistochemistry (IHC) of 212 tumor and 46 non-tumor tissues was conducted to explore the expression of CXCL3 and its diagnostic and prognostic significance in the Guangxi Medical University CC cohort. A GEO dataset, GSE40967, was used to validate the prognostic significance of CXCL3. Gene set enrichment analysis (GSEA) was also conducted to explore the potential molecular mechanisms underlying the effects of CXCL3 in CC. The RT-qPCR results indicated that CXCL3 expression was significantly higher in cancer tissues compared with adjacent normal tissues, suggesting that it may have high diagnostic value for CC. Multivariate Cox analysis based on the IHC results suggested that there was no appreciable association between CXCL3 positivity and the overall survival (OS) time of CC. However, a stratified analysis revealed that high expression of CXCL3 was associated with considerably increased mortality in the subgroup of CC patients with tumor size <5 cm (adjusted P=0.042, adjusted HR=2.298, 95% CI=1.030–5.126) and with tumor thrombus (adjusted P=0.019, adjusted HR=5.096, 95% CI=1.306–19.886). In the GSE40967 dataset, high expression of CXCL3 was closely associated with poor OS in CC (adjusted P=0.049, adjusted HR=1.416, 95% CI=1.002–2.003). Furthermore, GSEA indicated that the high expression of CXCL3 was closely associated with DNA repair, cell cycle process, cell apoptosis process and the P53 regulation pathway. In summary, these result suggest that CXCL3 might serve as a novel biomarker in the diagnosis and prognosis of CC.