Survival Of Colon Adenocarcinoma Research Articles

Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer.

CD276 is a promising prognostic indicator and an attractive therapeutic target in various malignancies. However, current methods for CD276 detection are time-consuming and expensive, limiting extensive studies and applications of CD276. We aimed to develop a pathomic model for CD276 prediction from H&E-stained pathological images, and explore the underlying mechanism of the pathomic features by associating the pathomic model with transcription profiles. A dataset of colon adenocarcinoma (COAD) patients was retrieved from the Cancer Genome Atlas (TCGA) database. The dataset was divided into the training and validation sets according to the ratio of 8:2 by a stratified sampling method. Using the gradient boosting machine (GBM) algorithm, we established a pathomic model to predict CD276 expression in COAD. Univariate and multivariate Cox regression analyses were conducted to assess the predictive performance of the pathomic model for overall survival in COAD. Gene Set Enrichment Analysis (GESA) was performed to explore the underlying biological mechanisms of the pathomic model. The pathomic model formed by three pathomic features for CD276 prediction showed an area under the curve (AUC) of 0.833 (95%CI: 0.784-0.882) in the training set and 0.758 (95%CI: 0.637-0.878) in the validation set, respectively. The calibration curves and Hosmer-Lemeshow goodness of fit test showed that the prediction probability of high/low expression of CD276 was in favorable agreement with the real situation in both the training and validation sets (P=0.176 and 0.255, respectively). The DCA curves suggested that the pathomic model acquired high clinical benefit. All the subjects were categorized into high pathomic score (PS) (PS-H) and low PS (PS-L) groups according to the cutoff value of PS. Univariate and multivariate Cox regression analysis indicated that PS was a risk factor for overall survival in COAD. Furthermore, through GESA analysis, we found several immune and inflammatory-related pathways and genes were associated with the pathomic model. We constructed a pathomics-based machine learning model for CD276 prediction directly from H&E-stained images in COAD. Through integrated analysis of the pathomic model and transcriptomics, the interpretability of the pathomic model provide a theoretical basis for further hypothesis and experimental research.

Prognostic and immunological role of adaptor related protein complex 3 subunit mu2 in colon cancer

The expression levels and prognostic role of AP3M2 in colorectal adenocarcinoma (CRAC) have yet to be fully unveiled. Our study comprehensively investigated the clinical significance of AP3M2 in colorectal cancer through an extensive bioinformatics data mining process (TCGA, GEO, GEPIA, Timer, Ualcan, ROCPLOT, and David), followed by experimental validation. We found AP3M2 is a cancer gene, which can be used to distinguish between colorectal cancer and colorectal adenomas, liver metastasis, lung metastasis, colorectal polyp. Higher AP3M2 expression levels were associated with longer overall survival in colon adenocarcinoma. AP3M2 might be the primary biomarker for oxaliplatin in colon cancer and an acquired resistance biomarker for oxaliplatin and 5-fu. AP3M2 was positively associated with CD274, CTLA4. AP3M2 might be associated with T-cell, NF-kappaB transcription factor activity, and response to hypoxia. AP3M2 could predict chemotherapy effectiveness and prognosis for colon cancer patients. AP3M2 might inhibit tumor growth via influencing tumor-infiltrating immune cells in the context of Tumor microenvironment. AP3M2 plays as an oncogene in CRAC and is suggested as a new potential biotarget for therapy.

Prognostic and immunotherapeutic significance of immunogenic cell death-related genes in colon adenocarcinoma patients

In recent years, genes associated with immunogenic cell death (ICD)-related genes have garnered significant interest as potential targets for immunotherapy. As a frontier in cancer treatment, immunotherapy has notably enhanced the therapeutic outcomes for cancer patients. However, since only a subset of patients benefits from this treatment approach, there is an imperative need for biomarker research to enhance patient sensitivity to immunotherapy. Expression of ICD-related genes and clinical patient data were sourced from The Cancer Genome Atlas (TCGA) database. Utilizing univariate Cox regression analysis, we constructed a signature for predicting the overall survival of colon adenocarcinoma (COAD) patients. A genomic feature analysis was performed, incorporating tumor mutation burden (TMB) and copy number variation (CNV). The immunological characteristics were analyzed via the ssGSEA and GSEA algorithms, with the resulting data visualized using R software (version 4.2.1). According to the univariate regression analysis for COAD, AIM2 emerged as the gene most significantly associated with overall survival among the 32 ICD-related genes in the TCGA dataset. Patients were divided into two groups based on high or low AIM2 expression, and genomic differences between the groups were explored. Patients expressing high levels of AIM2 had a higher TMB and a lower CNV. In addition, these patients had elevated immune checkpoint, immune cell, and immune function scores, thus indicating increased sensitivity to immunotherapy. TIDE analysis further confirmed that these patients were likely to respond more effectively to immunotherapy. Subclass mapping analysis corroborated our findings, demonstrating that patients with high AIM2 expression responded more positively to immunotherapy. Additionally, our study found that the suppression of AIM2 could significantly enhance the proliferation, invasion, and migration capabilities of colon cancer cells. In this research, we identified a novel prognostic signature suggesting that patients with higher AIM2 expression levels are more likely to respond favorably to immunotherapy.

Downregulated expression of plakophilin-2 gene in patients with colon adenocarcinoma predicts an unfavorable prognosis and immune infiltrate.

Plakophilin 2 gene (PKP2) has been revealed to be differentially expressed in various cancer types and is correlated with prognosis. However, the role of PKP2 in colon adenocarcinoma remains indistinct. Differences in transcriptional expression of PKP2 between colon adenocarcinoma tissues and normal adjacent tissues were acquired from the publicly available dataset-the Cancer Genome Atlas. A receiver operating curve (ROC) was constructed to differentiate colon adenocarcinoma tissues from adjacent normal tissues. The Kaplan-Meier plot method was performed to evaluate the effect of PKP2 on survival. The correlation between mRNA expression of PKP2 and immune infiltrating was determined by the Tumor Immune Estimation Resource and Tumor-Immune System Interaction databases. The expression of PKP2 in colon adenocarcinoma tissues was significantly downregulated compared with corresponding adjacent normal tissues. Decreased PKP2 mRNA expression was associated with lymph node metastases and advanced pathological stage. The ROC curve analysis indicated that with a cutoff value of 6.034, the sensitivity and specificity for PKP2 differentiating the colon adenocarcinoma tissues from the adjacent normal tissues were 90.2 and 66.5% respectively. Kaplan-Meier plot survival analysis revealed that colon adenocarcinoma patients with low-PKP2 had a worse prognosis than those with high-PKP2 (68.2 vs. 101.4 months, p = 0.028). Correlation analysis showed that mRNA expression of PKP2 was correlative with immune infiltrates. Downregulated PKP2 is significantly correlated with unfavorable immune infiltrating and survival in colon adenocarcinoma. This research indicates that PKP2 can be selected as a novel biomarker of potential immunotherapy targets and unfavorable prognosis in colon adenocarcinoma.

A novel signature model based on mitochondrial-related genes for predicting survival of colon adenocarcinoma

BackgroundColon cancer is the foremost reason of cancer-related mortality worldwide. Colon adenocarcinoma constitutes 90% of colon cancer, and most patients with colon adenocarcinoma (COAD) are identified until advanced stage. With the emergence of an increasing number of novel pathogenic mechanisms and treatments, the role of mitochondria in the development of cancer, has been studied and reported with increasing frequency.MethodsWe systematically analyzed the effect of mitochondria-related genes in COAD utilizing RNA sequencing dataset from The Cancer Genome Atlas database and 1613 mitochondrial function-related genes from MitoMiner database. Our approach consisted of differentially expressed gene, gene set enrichment analysis, gene ontology terminology, Kyoto Encyclopedia of Genes and Genomes, independent prognostic analysis, univariate and multivariate analysis, Kaplan–Meier survival analysis, immune microenvironment correlation analysis, and Cox regression analysis.ResultsConsequently, 8 genes were identified to construct 8 mitochondrial-related gene model by applying Cox regression analysis, CDC25C, KCNJ11, NOL3, P4HA1, QSOX2, Trap1, DNAJC28, and ATCAY. Meanwhile, we assessed the connection between this model and clinical parameters or immune microenvironment. Risk score was an independent predictor for COAD patients’ survival with an AUC of 0.687, 0.752 and 0.762 at 1-, 3- and 5-year in nomogram, respectively. The group with the highest risk score had the lowest survival rate and the worst clinical stages. Additionally, its predictive capacity was validated in GSE39582 cohort.ConclusionIn summary, we established a prognostic pattern of mitochondrial-related genes, which can predict overall survival in COAD, which may enable a more optimized approach for the clinical treatment and scientific study of COAD. This gene signature model has the potential to improve prognosis and treatment for COAD patients in the future, and to be widely implemented in clinical settings. The utilization of this mitochondrial-related gene signature model may be benefit in the treatments and medical decision-making of COAD.

S213 Intratumoral Human Cytomegalovirus Abundance in Colon Adenocarcinoma Is Associated With Poor Survival Outcomes and Increased Intratumoral Regulatory T-cell Infiltrate in Elderly Patients

Introduction: Although higher rates of human cytomegalovirus (CMV) are known to be associated with colorectal cancer, the impact of CMV on patient survival and its impact on the immune milieu in the tumor microenvironment have not been studied extensively. As such, we assess the associations of intratumoral CMV RNA signatures in colon adenocarcinoma with overall and age-specific survival and intratumoral immune cell abundance. Methods: Microbial RNA sequencing (RNA-seq) data was procured as described previously by Poore et al. and used to calculate average log counts per million (CPM) of CMV. Abundance of intratumoral immune cell types was estimated via the quanTIseq method described previously by Finotello et al. The Cancer Genome Atlas Colon Adenocarcinoma clinical dataset was downloaded from cBioPortal.org. Only patients with primary tumor sites in the colon were included for further analysis. Survival data was processed using GraphPad Prism software to generate Kaplan-Meier curves. Relative hazard ratios (HRs) for overall and age-specific survival were estimated with cox proportional hazards models using the lifelines python package. Spearman correlation analysis was calculated with Bonferroni correction for multiple comparisons. Results: Our study included 432 patients with primary colon adenocarcinoma and CMV RNA-seq data. Comparison of the rate of overall survival for patients in the top and bottom quintiles of CMV log CPM showed higher CMV abundance was associated with significantly decreased survival (p=0.04) (Figure). When stratified by age, individuals aged ≥65 with higher CMV abundance had increased overall mortality risk (HR 1.21; p< 0.001) while no significant association was observed between CMV abundance and survival in those aged ≤55 (Table). Spearman correlation analysis showed intratumoral CMV signatures were significantly positively correlated with CD8+ T cell (correlation coefficient=0.20; p=0.001) and regulatory T cell (correlation coefficient=0.17; p=0.005) abundance in individuals aged ≥65 but not in those aged ≤55. Conclusion: To our knowledge, this is the largest study investigating associations of intratumoral CMV signatures with patient survival in colon adenocarcinoma and the first to characterize an age-specific correlation between intratumoral CMV and immune cell abundance. Further research elucidating the molecular mechanisms by which CMV modulates the tumor microenvironment is warranted.Figure 1.: Kaplan-Meier Overall Survival Curve comparing top quintile (n = 86, black) vs bottom quintile (n=86, gray) of CMV recoveries in Colon Adenocarcinoma Table 1. - Associations of intratumoral cytomegalovirus abundance, sex, and tumor stage with mortality risk in patients with colon adenocarcinoma stratified by age using Cox proportional hazards model Age ≥65 Parameter Hazard Ratio (HR) P-value CMV abundance Per unit increase in CMV log CPM 1.21 < 0.001 Sex Female 1 Male 1.04 0.94 Tumor stage I-II 1 III-IV 3.87 0.009 Age ≤55 CMV abundance Per unit increase in CMV log CPM 0.94 0.77 Sex Female 1 Male 0.94 0.91 Tumor stage I-II 1 III-IV 3.44 0.23

High Expression of ATP6V1C2 Predicts Unfavorable Overall Survival in Patients With Colon Adenocarcinoma.

Aims: Colon adenocarcinoma (COAD) is responsible for 90% of all colorectal cancer cases and is one of the most common causes of cancer-related deaths worldwide. ATP6V1s (cytosolic V1 domain of vacuolar adenosine triphosphatase) participate in the biological process of transporting hydrogen ions and are implicated in tumor growth and metastasis. ATP6V1C2 as a family member has been documented to associate with esophageal carcinoma and renal clear cell carcinoma, while its roles in COAD remain elusive. Methods: The expression status, potential molecular mechanism, and prognostic value of ATP6V1C2 in COAD were investigated using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. In addition, its biological roles in COAD were explored through in vitro studies. Results: ATP6V1C2 showed a significantly higher expression level in COAD compared with matched non-cancerous tissues. High expression of ATP6V1C2 predicted a shorter overall survival both in TCGA and GEO COAD datasets, and ATP6V1C2 was identified as an independent factor associated with overall survival in COAD. Bioinformatic analyses showed that high expression of ATP6V1C2 was associated with high epithelial–mesenchymal transition (EMT) score and Wnt signaling pathway was significantly enriched from differentially expressed genes between ATP6V1C2-high and -low group. We also found that high expression of ATP6V1C2 could decrease pathway activity of CD8 T effector implicated in tumor microenvironment (TME). In vitro study revealed that ATP6V1C2 knockdown resulted in aberrant expression of Wnt- and EMT-related genes and inhibited COAD cell proliferation and growth. Conclusion: This is the first study to reveal the molecular functions of ATP6V1C2 in COAD. Our study suggests that overexpressed ATP6V1C2 might promote EMT by activating Wnt signaling pathway, resulting in cancer metastasis and poor prognosis. This study paves the way for understanding potential molecular mechanisms and therapeutic perspectives in COAD.

ISYNA1: An Immunomodulatory-Related Prognostic Biomarker in Colon Adenocarcinoma and Pan-Cancer.

Background: Colon adenocarcinoma (COAD) is a common digestive system tumor in the world. However, the role and function of ISYNA1 (inositol-3-phosphate synthase 1) in COAD remain unclear. We aim to explore the role of ISYNA1 in pan-cancer, especially in COAD. Methods: The expression, clinical characteristic, and prognosis of ISYNA1 in pan-cancer were evaluated using the TCGA (the Cancer Genome Atlas), GTEx (the Genotype-Tissue Expression), and CCLE (Cancer Cell Line Encyclopedia). Pathway enrichment analysis of ISYNA1 was conducted using the R package “clusterProfiler.” We analyzed the correlation between the immune cell infiltration level and ISYNA1 expression using two sources of immune cell infiltration data, including the TIMER online database and ImmuCellAI database. Results: ISYNA1 was highly expressed in COAD and other cancer types compared with respective normal tissues. High ISYNA1 expression predicted poorer survival in COAD. We also found that ISYNA1 expression was positively correlated with the infiltration level of tumor-associated macrophages and tumor-associated fibroblasts in COAD. Conclusion: In conclusion, our findings revealed ISYNA1 to be a potential prognostic biomarker in COAD. High ISYNA1 expression indicates the immunosuppressive microenvironment.

Gene Expression Profiling of Tricarboxylic Acid Cycle and One Carbon Metabolism Related Genes for Prognostic Risk Signature of Colon Carcinoma.

Colorectal cancer (CRC) is one of the most prevalent malignant tumors worldwide. Colon adenocarcinoma (COAD) is the most common pathological type of CRC and several biomarkers related to survival have been confirmed. Yet, the predictive effect of a single gene biomarker is not enough. The tricarboxylic acid (TCA) cycle and carbon metabolism play an important role in tumors. Thus, we aimed to identify new gene signatures from the TCA cycle and carbon metabolism to better predict the survival of COAD. This study performed mRNA expression profiling in large COAD cohorts (n = 417) from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression and multivariate Cox regression analysis were performed, and receiver operating characteristic (ROC) curve was used to screen the variable combinations model which is most relevant to patient prognosis survival mostly. Univariable or multivariate analysis results showed that SUCLG2, SUCLG1, ACLY, SUCLG2P2, ATIC and ACO2 have associations with survival in COAD. Combined with clinical variables, we confirmed model 1 (AUC = 0.82505), most relevant to patient prognosis survival. Model 1 contains three genes: SUCLG2P2, SUCLG2 and ATIC, in which SUCLG2P2 and SUCLG2 were low-expressed in COAD, however, ATIC was highly expressed, and the expressions above are related to stages of CRC. Pearson analysis showed that SUCLG2P2, SUCLG2 and ATIC were correlated in normal COAD tissues, while only SUCLG2P2 and SUCLG2 were correlated in tumor tissues. Finally, we verified the expressions of these three genes in COAD samples. Our study revealed a possible connection between the TCA cycle and carbon metabolism and prognosis and showed a TCA cycle and carbon metabolism related gene signature which could better predict survival in COAD patients.

Downregulated ARID1A by miR-185 Is Associated With Poor Prognosis and Adverse Outcomes in Colon Adenocarcinoma.

AT-rich interaction domain 1A (ARID1A) is a tumor suppressor gene that mutates in several cancer types, including breast cancer, ovarian cancer, and colorectal cancer (CRC). In colon adenocarcinoma (COAD), the low expression of ARID1A was reported but the molecular reason is unclear. We noticed that ARID1A low expression was associated with increased levels of miR-185 in the COAD. Therefore, this study aims to explore ncRNA-dependent mechanism that regulates ARID1A expression in COAD regarding miR-185. The expression of ARID1A was tested in COAD cell line under the effect of miR-185 mimics compared with inhibitor. The molecular features associated with loss of ARID1A and its association with tumor prognosis were analyzed using multi-platform data from The Cancer Genome Atlas (TCGA), and gene set enrichment analysis (GSEA) to identify potential signaling pathways associated with ARID1A alterations in colon cancer. Kaplan-Meier survival curve showed that a low level of ARID1A was closely related to low survival rate in patients with COAD. Results showed that inhibiting miR-185 expression in the COAD cell line significantly restored the expression of ARID1A. Further, the increased expression of ARID1A significantly improved the prolonged overall survival of COAD. We noticed that there is a possible relationship between ARID1A high expression and tumor microenvironment infiltrating immune cells. Furthermore, the increase of ARID1A in tumor cells enhanced the response of inflammatory chemokines. In conclusion, this study demonstrates that ARID1A is a direct target of miR-185 in COAD that regulates the immune modulations in the microenvironment of COAD.

Decreased Tumoral Expression of Colon-Specific Water Channel Aquaporin 8 Is Associated With Reduced Overall Survival in Colon Adenocarcinoma.

Colon cancer survival is dependent on metastatic potential and treatment. Large RNA-sequencing data sets may assist in identifying colon cancer-specific biomarkers to improve patient outcomes. This study aimed to identify a highly specific biomarker for overall survival in colon adenocarcinoma by using an RNA-sequencing data set. Raw RNA-sequencing and clinical data for patients with colon adenocarcinoma (n = 271) were downloaded from The Cancer Genome Atlas. A binomial regression model was used to calculate differential RNA expression between paired colon cancer and normal epithelium samples (n = 40). Highly differentially expressed RNAs were examined. This study was conducted at the University of Louisville using data acquired by The Cancer Genome Atlas. Patients from US accredited cancer centers between 1998 and 2013 were analyzed. The primary outcome measures were recurrence-free and overall survival. The median age was 66 years (147/271 men, 180/271 White patients). Thirty RNAs were differentially expressed in colon adenocarcinoma compared with paired normal epithelium, using a log-fold change cutoff of ±6. Using median expression as a cutoff, 4 RNAs were associated with worse overall survival: decreased ZG16 (log-rank = 0.023), aquaporin 8 (log-rank = 0.023), and SLC26A3 (log-rank = 0.098), and increased COL1A1 (log-rank = 0.105). On multivariable analysis, low aquaporin 8 expression (HR, 1.748; 95% CI, 1.016-3.008; p = 0.044) was a risk factor for worse overall survival. Our final aquaporin 8 model had an area under the curve of 0.85 for overall survival. On subgroup analysis, low aquaporin 8 was associated with worse overall survival in patients with high microsatellite instability and in patients with stage II disease. Low aquaporin 8 expression was associated with KRAS and BRAF mutations. Aquaporin 8 immunohistochemistry was optimized for clinical application. This was a retrospective study. Aquaporin 8 is a water channel selectively expressed in normal colon tissue. Low aquaporin 8 expression is a risk factor for worse overall survival in patients who have colon cancer. Aquaporin 8 measurement may have a role as a colon-specific prognostic biomarker and help in patient risk stratification for increased surveillance. See Video Abstract at http://links.lww.com/DCR/B603. ANTECEDENTES:La supervivencia del cáncer de colon depende del potencial metastásico y del tratamiento. Grandes conjuntos de datos de secuenciación de ARN pueden ayudar a identificar biomarcadores específicos del cáncer de colon para mejorar los resultados de los pacientes.OBJETIVO:Identificar un biomarcador altamente específico para la supervivencia general en el adenocarcinoma de colon utilizando un conjunto de datos de secuenciación de ARN.DISEÑO:La secuenciación de ARN sin procesar y los datos clínicos para pacientes con adenocarcinoma de colon (n = 271) se descargaron de The Cancer Genome Atlas. Se utilizó un modelo de regresión binomial para calcular la expresión diferencial de ARN entre muestras de cáncer de colon emparejadas y muestras de epitelio normal (n = 40). Se examinaron los ARN expresados de forma altamente diferencial.ENTORNO CLINICO:Este estudio se realizó en la Universidad de Louisville utilizando datos adquiridos por The Cancer Genome Atlas.PACIENTES:Se analizaron pacientes de centros oncológicos acreditados en Estados Unidos entre 1998-2013.PRINCIPALES MEDIDAS DE VALORACION:Las principales medidas de valoración fueron la supervivencia general y libre de recurrencia.RESULTADOS:La mediana de edad fue de 66 años (147/271 hombres, 180/271 caucásicos). Treinta ARN se expresaron diferencialmente en el adenocarcinoma de colon en comparación con el epitelio normal emparejado, utilizando un límite de cambio logarítmico de ± 6. Utilizando la expresión mediana como punto de corte, cuatro ARN se asociaron con una peor supervivencia general: disminución de ZG16 (rango logarítmico = 0,023), acuaporina8 (rango logarítmico = 0,023) y SLC26A3 (rango logarítmico = 0,098) y aumento de COL1A1 (log -rango = 0,105). En el análisis multivariable, la baja expresión de acuaporina8 (HR = 1,748, IC del 95%: 1,016-3,008, p = 0,044) fue un factor de riesgo para una peor supervivencia global. Nuestro modelo de aquaporin8 final tuvo un AUC de 0,85 para la supervivencia global. En el análisis de subgrupos, la acuaporina8 baja se asoció con una peor supervivencia general en pacientes con MSI-H y en pacientes en estadio II. La baja expresión de acuaporina8 se asoció con mutaciones de KRAS y BRAF. La inmunohistoquímica de aquaporina8 se optimizó para su aplicación clínica.LIMITACIONES:Este fue un estudio retrospectivo.CONCLUSIÓN:La acuaporina8 es un canal de agua expresado selectivamente en el tejido normal del colon. La baja expresión de AQP8 es un factor de riesgo de peor supervivencia global en pacientes con cáncer de colon. La medición de aquaporina8 puede tener un papel como un biomarcador de pronóstico específico del colon y ayudar en la estratificación del riesgo del paciente para una mayor vigilancia. Consulte Video Resumen en http://links.lww.com/DCR/B603.

Clinical implications and nomogram prediction of long noncoding RNA FRGCA as diagnostic and prognostic indicators in colon adenocarcinoma.

Colorectal cancer, especially colon adenocarcinoma (COAD), is associated with significant morbidity and mortality worldwide. Long noncoding RNA (lncRNA) has been implicated in tumorigenesis. The aim of the present study was to elucidate the potential diagnostic and prognostic values of lncRNA FRGCA in COAD.The data of 438 COAD patients were retrieved for analysis. Diagnostic significance was evaluated using tumor and nontumor tissues. Prognostic significance was evaluated using a Cox proportional regression model. Stratified analysis was performed to identify associations between clinical factors and lncRNA FRGCA expression. A nomogram was constructed using the clinical factors and lncRNA FRGCA for survival prediction. Enrichment analysis identified gene ontologies and metabolic pathways of mRNAs with high Pearson correlation coefficients with lncRNA FRGCA.lncRNA FRGCA was highly expressed in tumor tissues of COAD and demonstrated diagnostic value (area under curve = 0.763, P < .0001). Prognostic significance analysis indicated that lncRNA FRGCA had prognostic value in COAD [adjusted P < .001, hazard ratio (HR) = 0.444, 95% confidence interval (95% CI) = 0.288-0.685] and high expression of lncRNA FRGCA indicated better survival in COAD. A nomogram was evaluated for prediction of survival at 1, 3, and 5 years. Enrichment analysis revealed many mRNAs involved in the structural constituents of the mitochondrial inner membrane and translational termination, protein binding, translation, ribosome, oxidative phosphorylation, and metabolic pathways, especially the nucleoplasm.Differentially expressed in tumor vs nontumor tissues, lncRNA FRGCA had both diagnostic and prognostic implications in COAD, which may be associated with ribosome metabolism, oxidative phosphorylation, and nucleoplasm-related metabolic pathways.

Molecular profile reveals immune-associated markers of lymphatic invasion in human colon adenocarcinoma

Lymphatic invasion (LI) is an early event of metastasis and closely associated with overall survival in colon adenocarcinoma (COAD). Our aim was to gain deeper insight into the mechanism of lymphatic invasion in COAD. Subtype-specific somatic mutations and differentially expressed genes (DEGs) screening were based on The Cancer Genome Atlas (TCGA). Gene Ontology (GO) enrichment analysis was utilized to explore the biological function. The condition of tumor-infiltrating lymphocytes was performed by TIMER online database. Survival analysis was based on Kaplan-Meier curve method. Lymphatic invasion was associated with poor prognosis of patients with COAD. Nine mutations were enriched in lymphatic invasion-negative group. A total of 50 were differentially expressed between LI-positive tissues and LI-negative tissues. The DEGs were enriched in lipoprotein-related functions. MUC4 in-frame deletion at A4166-S4181 was associated with favorable prognosis of COAD patients. BMPR2 frameshift mutation g.chr2:202555407delA played cis and trans functions in downregulation of itself and CTLA4 upregulation. And it was associated with higher mutational burden. LAMP5, CUBN and TCHH were DEGs associated with prognosis and abundance of tumor-infiltrating lymphocytes. In conclusion, our study provides LI-associated genetic and transcriptional alterations, which helps to better understand the potential mechanisms and microenvironment in COAD.

Identification of prognostic miRNA biomarkers for predicting overall survival of colon adenocarcinoma and bioinformatics analysis: A study based on The Cancer Genome Atlas database.

This study was conducted to identify the prognostic microRNA (miRNA) for the prediction of survival in colon adenocarcinoma (CA). miRNA profiling of patients with CA was downloaded from The Cancer Genome Atlas (TCGA) database. After data processing, univariate Cox regression was performed to select potential prognostic miRNAs. Least absolute shrinkage and selection operator approach was conducted to identify the key prognostic miRNA biomarkers. Log-rank test was performed to compare survival outcome between patients with different regulation type of identified miRNAs. Then, bioinformatics analysis including Gene Ontology, Disease Ontology, and pathway enrichment analysis was performed on the selected prognostic miRNAs. A nomogram was generated based on the multivariate Cox proportional hazard model to illustrate the association between the identified miRNAs and the survival of patients with colorectal cancer (CRC). All analyses were conducted with packages in the R software. A total of 1881 miRNAs were obtained from TCGA database in which 15 miRNAs were finally selected in multianalysis with covariates and incorporated into functional annotation analyses. Log-rank test suggested that the identified miRNAs were associated with the survival of CA. Seven out of 15 selected miRNAs were identified for the first time in CA. Bioinformatics analysis suggested that the identified miRNAs were associated with the development and progress of CRC. The association between the identified miRNAs and the survival of patients with CRC were presented in a nomogram. The seven newly identified miRNAs might be potential prognostic biomarkers for the survival of CA. Further research about the selected miRNAs were worth to conduct.