Identification of 6 Hub Proteins and Protein Risk Signature of Colorectal Cancer

Background. Colorectal cancer (CRC) is the second most common cause of cancer death in the United States and the third most common cancer globally. The incidence of CRC tends to be younger, and we urgently need a reliable prognostic assessment strategy. Methods. Protein expression profile and clinical information of 390 CRC patients/samples were downloaded from the TCPA and TCGA database, respectively. The Kaplan-Meier, Cox regression, and Pearson correlation analysis were applied in this study. Results. Based on the TCPA and TCGA database, we screened 6 hub proteins and first constructed protein risk signature, all of which were significantly associated with CRC patients’ overall survival (OS). The risk score was an independent prognostic factor and significantly related with the size of the tumor in situ ( T ). 6 hub proteins were differentially expressed in cancer and normal tissues and in different CRC stages, which were validated at the ONCOMINE database. Next, 40 coexpressed proteins of 6 hub proteins were extracted from the TCPA database. In the protein-protein interaction (PPI) network, HER1, HER2, and CTNNB1 were at the center. Function enrichment analysis illustrated that 46 proteins were mainly involved in the EGFR (HER1) tyrosine kinase inhibitor resistance pathway. Conclusion. Studies indicated that 6 hub proteins might be considered as new targets for CRC therapies, and the protein risk signature can be used to predict the OS of CRC patients.

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Clinical impact of medical policy supporting universal germline testing for patients with colorectal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.10514 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 10514-10514

Author(s):

Sarah M. Nielsen ◽

Joline Dalton ◽

Kathryn E. Hatchell ◽

Stacey DaCosta Byfield ◽

Chad Moretz ◽

...

Keyword(s):

Colorectal Cancer ◽

Genetic Testing ◽

Clinical Information ◽

The United States ◽

Clinical Treatment ◽

Administrative Claims ◽

Treatment Trials ◽

Precision Therapy ◽

Medical Policy ◽

Germline Testing

10514 Background: Colorectal cancer (CRC) affects approximately 104,000 patients (pts) annually in the United States, up to 45% of which are estimated to be genetic and/or familial. Aligned with clinical guidelines, in 2020, a large U.S. insurer established Medical Policy allowing for and reimbursing germline genetic testing (GGT) for all CRC pts. This study reports overall uptake of GGT in CRC pts under this inclusive policy, actionable findings and treatment implications for pts tested, stratified by self-reported ancestry/ethnicity. Methods: Two independent de-identified datasets were reviewed, including administrative claims data of commercially insured and Medicare Advantage enrollees, aged 18+ with CRC (≥1 claim with ICD10 C18, C19 or C20 in the first position) who were continuously enrolled (CE) in the health plan from 1/2019-10/2020. Evidence of genetic testing based on CPT codes, was examined during 2020. A second de-identified dataset of CRC pts whose GGT was billed to the insurer under the Medical Policy, was also reviewed. Patient demographics, clinical information and GGT results were descriptively analyzed. Results: Of the >18,000,000 CE enrollees, 55,595 were identified as CRC pts, of whom 1,675 (3%) received GGT. From the GGT dataset, 788 pts had test results available for review. 143 (18%) pts had pathogenic/likely pathogenic (P/LP) variants in genes including MSH2, MLH1, PMS2, MSH6, CHEK2, APC, BRCA2, ATM, MUTYH (biallelic). Of pts with P/LP variants, 96 (67%) were potentially eligible for precision therapy and/or clinical treatment trials. Overall, 133 (93%) had P/LP variants in genes with precision therapy, clinical trial and/or published management implications. In a subset of pts (n=674) with ethnicity data; Asian, Black/African-American and Hispanic pts showed lower relative uptake of germline testing than Caucasians (Table). Conclusions: Despite Medical Policy allowing for GGT for all pts with CRC, only 3% of eligible pts received testing. If all CRC pts had been tested, these data suggest up to 6,705 pts with P/LP variants conferring potential eligibility for precision therapy (PD-1/PD-L1 inhibitors) or clinical treatment trials (PARP inhibitors), and an additional 2,602 pts with mutations in genes with published management recommendations, could have been identified, but were missed. Additional research is needed to identify obstacles to systematic implementation of this Medical Policy, the best timing of GGT to prevent CRC and improve access to underrepresented populations. CRC patients with germline genetic testing.[Table: see text]

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A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML)

Frontiers in Genetics ◽

10.3389/fgene.2021.681867 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chunxia Zhao ◽

Yulu Wang ◽

Famei Tu ◽

Shuai Zhao ◽

Xiaoying Ye ◽

...

Keyword(s):

Cox Regression ◽

Survival Curve ◽

Pearson Correlation ◽

Enrichment Analysis ◽

Risk Groups ◽

Gene Set Enrichment Analysis ◽

Kaplan Meier ◽

Non Coding Rna ◽

Novel Biomarkers ◽

Meier Survival Curve

BackgroundSome studies have proven that autophagy and lncRNA play important roles in AML. Several autophagy related lncRNA signatures have been shown to affect the survival of patients in some other cancers. However, the role of autophagy related lncRNA in AML has not been explored yet. Hence, this study aims to find an autophagy related lncRNA signature that can affect survival for AML patients.MethodA Pearson correlation analysis, a Kaplan–Meier survival curve, a univariate cox regression, and a multivariate cox regression were performed to establish an autophagy related lncRNA signature. A univariate cox regression, a multivariate cox regression, a Kaplan–Meier survival curve, and a ROC curve were applied to confirm if the signature is an independent prognosis for AML patients. The relationship between the signature and the clinical features was explored by using a T test. Gene Set Enrichment Analysis (GSEA) was used to investigate the potential tumor related pathways.ResultsA four-autophagy related lncRNA (MIR133A1HG, AL359715.1, MIRLET7BHG, and AL356752.1) signature was established. The high risk score based on signature was related to the short survival time of AML patients. The signature was an independent factor for the prognosis for AML patients (HR = 1.684, 95% CI = 1.324–2.142, P < 0.001). The signature was correlated with age, leukocyte numbers, and FAB (M3 or non-M3). The P53, IL6/JAK/STAT3, TNF-α, INF-γ, and IL2/STAT5 pathways might contribute to the differences between the risk groups based on signature in AML.ConclusionThe four autophagy related lncRNAs and their signature might be novel biomarkers for predicting the survival of AML patients. Some biological pathways might be the potential mechanisms of the signature for the survival of AML patients.

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Identification of a Hypoxia - Related lncRNA Signature For The Prognosis of Colorectal Cancer

10.21203/rs.3.rs-757504/v1 ◽

2021 ◽

Author(s):

HUA HUANG ◽

Shanshan Xu ◽

Youran Li ◽

Yunfei Gu ◽

Lijiang Ji

Keyword(s):

Colorectal Cancer ◽

Roc Analysis ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Receptor Interaction ◽

Prognostic Signature ◽

Gene Set Enrichment ◽

Gene Set

Abstract Background: Colorectal cancer (CRC), the commonly seen malignancy, ranks the 3rd place among the causes of cancer-associated mortality. As suggested by more and more studies, long coding RNAs (lncRNAs) have been considered as prognostic biomarkers for CRC. But the significance of hypoxic lncRNAs in predicting CRC prognosis remains unclear.Methods: The gene expressed profiles for CRC cases were obtained based on the Cancer Genome Atlas (TCGA) and applied to estimate the hypoxia score using a single-sample gene set enrichment analysis (ssGSEA) algorithm. Overall survival (OS) of high- and low-hypoxia score group was analyzed by the Kaplan–Meier (KM) plot. To identify differentially expressed lncRNAs (DELs) between two hypoxia score groups, this study carried out differential expression analysis, and then further integrated with the DELs between controls and CRC patients to generate the hypoxia-related lncRNAs for CRC. Besides, prognostic lncRNAs were screened by the univariate Cox regression, which were later utilized for constructing the prognosis nomogram for CRC by adopting the least absolute shrinkage and selection operator (LASSO) algorithm. In addition, both accuracy and specificity of the constructed prognostic signature were detected through the receiver operating characteristic (ROC) analysis. Moreover, our constructed prognosis signature also was validated in the internal testing test. This study operated gene set enrichment analysis (GSEA) for exploring potential biological functions associated with the prognostic signature. Finally, the ceRNA network of the prognostic lncRNAs was constructed.Results: Among 2299 hypoxia-related lncRNAs of CRC in total, LINC00327, LINC00163, LINC00174, SYNPR-AS1, and MIR31HG were identified as prognostic lncRNAs by the univariate Cox regression, and adopted for constructing the prognosis signature for CRC. ROC analysis showed the predictive power and accuracy of the prognostic signature. Additionally, the GSEA revealed that ECM-receptor interaction, PI3K-Akt pathway, phagosome, and Hippo pathway were mostly associated with the high-risk group. 352 miRNAs-mRNAs pairs and 177 lncRNAs-miRNAs were predicted.Conclusion: To conclude , we identified 5 hypoxia-related lncRNAs to establish an accurate prognostic signature for CRC, providing important prognostic markers and therapeutic target.

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An inflammatory cytokine signature helps predict COVID-19 severity and death

10.1101/2020.05.28.20115758 ◽

2020 ◽

Cited By ~ 20

Author(s):

Diane Marie Del Valle ◽

Seunghee Kim-schulze ◽

Huang Hsin-hui ◽

Noam D Beckmann ◽

Sharon Nirenberg ◽

...

Keyword(s):

New York ◽

Disease Severity ◽

Cox Regression ◽

Predictive Biomarkers ◽

Clinical Information ◽

Serum Levels ◽

The United States ◽

High Serum ◽

Laboratory Test Results ◽

Tnf Α

The COVID-19 pandemic caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to more than 100,000 deaths in the United States. Several studies have revealed that the hyper-inflammatory response induced by SARS-CoV-2 is a major cause of disease severity and death in infected patients. However, predictive biomarkers of pathogenic inflammation to help guide targetable immune pathways are critically lacking. We implemented a rapid multiplex cytokine assay to measure serum IL-6, IL-8, TNF-α, and IL-1β in hospitalized COVID-19 patients upon admission to the Mount Sinai Health System in New York. Patients (n=1484) were followed up to 41 days (median 8 days) and clinical information, laboratory test results and patient outcomes were collected. In 244 patients, cytokine measurements were repeated over time, and effect of drugs could be assessed. Kaplan-Meier methods were used to compare survival by cytokine strata, followed by Cox regression models to evaluate the independent predictive value of baseline cytokines. We found that high serum IL-6, IL-8, and TNF-α levels at the time of hospitalization were strong and independent predictors of patient survival. Importantly, when adjusting for disease severity score, common laboratory inflammation markers, hypoxia and other vitals, demographics, and a range of comorbidities, IL-6 and TNF-α serum levels remained independent and significant predictors of disease severity and death. We propose that serum IL-6 and TNF-α levels should be considered in the management and treatment of COVID-19 patients to stratify prospective clinical trials, guide resource allocation and inform therapeutic options. We also propose that patients with high IL-6 and TNF-α levels should be assessed for combinatorial blockade of pathogenic inflammation in this disease.

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The Impact of Colorectal Cancer Screening in a Veteran Hospital Population

The American Surgeon ◽

10.1177/000313481307900330 ◽

2013 ◽

Vol 79 (3) ◽

pp. 296-300 ◽

Cited By ~ 1

Author(s):

John Trombold ◽

Russellw Farmer ◽

Michael McCafferty

Keyword(s):

Colorectal Cancer ◽

Cancer Screening ◽

Colorectal Cancer Screening ◽

Operative Mortality ◽

Cox Regression ◽

Medical Center ◽

The United States ◽

Curative Intent ◽

Colon And Rectal Cancer ◽

The Impact

Colon and rectal cancer is the second most common cause of cancer death in the United States. Screening effectively decreases colorectal cancer mortality. This study aims to evaluate the impact of colorectal cancer screening within a Veterans Affairs Medical Center and treatment outcomes. Institutional Review Board approval was obtained for a retrospective analysis of all colorectal cancer cases that were identified through the Tumor Registry of the Robley Rex VA Medical Center from 2000 to 2009. Data collected included age at diagnosis, race, risk factors, diagnosis by screening versus symptomatic evaluation, screening test, tumor location and stage, operation performed, operative mortality, and survival. A value of P < 0.05 on Fisher's exact, χ2, analysis of variance, or Cox regression analyses was considered significant. Three hundred fifty-four patients with colorectal cancer (255 colon, 99 rectal) were identified. One hundred twenty-one patients (34%) were diagnosed by screening. In comparison with those diagnosed by symptom evaluation (n = 233), these patients had earlier stage cancers, were more likely to have a curative intent procedure, and had improved 5-year survival rates. Older patients (older than 75 years old) were more likely to present with symptoms. High-risk patients were more likely to have colonoscopic screening than fecal occult blood testing. More blacks had Stage IV disease than nonblacks. Curative intent 30-day operative mortality was 2.1 per cent for colectomy and 0 per cent for rectal resection. Screening for colorectal cancer in the veteran population allows for better survival, detection at an earlier stage, and higher likelihood of resection.

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Genomics and prognosis analysis of epithelial-mesenchymal transition in colorectal cancer patients

BMC Cancer ◽

10.1186/s12885-020-07615-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Zizhen Zhang ◽

Sheng Zheng ◽

Yifeng Lin ◽

Jiawei Sun ◽

Ning Ding ◽

...

Keyword(s):

Colorectal Cancer ◽

Cox Regression ◽

Epithelial Mesenchymal Transition ◽

Enrichment Analysis ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Related Gene ◽

Mesenchymal Transition ◽

Cox Regression Analysis

Abstract Background The epithelial-mesenchymal transition (EMT) plays a pivotal role in various physiological processes, such as embryonic development, tissue morphogenesis, and wound healing. EMT also plays an important role in cancer invasion, metastasis, and chemoresistance. Additionally, EMT is partially responsible for chemoresistance in colorectal cancer (CRC). The aim of this research is to develop an EMT-based prognostic signature in CRC. Methods RNA-seq and microarray data, together with clinical information, were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. A total of 244 differentially expressed EMT-related genes (ERGs) were obtained by comparing the expression between normal and tumor tissues. An EMT-related signature of 11 genes was identified as crucially related to the overall survival (OS) of patients through univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO), and Cox regression analysis. Finally, we established a clinical nomogram to predict the survival possibility of CRC patients by integrating clinical characteristics and the EMT-related gene signature. Results Two hundred and forty-four differentially expressed ERGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that EMT-related signaling pathway genes were highly related to CRC. Kaplan-Meier analysis revealed that the 11-EMT signature could significantly distinguish high- and low-risk patients in both TCGA and GEO CRC cohorts. In addition, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusion We developed a novel EMT-related gene signature for the prognosis prediction of CRC patients, which could improve the individualized outcome prediction in CRC.

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Comprehensive analysis of ceRNA networks reveals prognostic lncRNAs related to immune infiltration in colorectal cancer

BMC Cancer ◽

10.1186/s12885-021-07995-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jingyi Chen ◽

Yuxuan Song ◽

Mei Li ◽

Yu Zhang ◽

Tingru Lin ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Target Genes ◽

Immune Cell ◽

Pearson Correlation ◽

Enrichment Analysis ◽

Cell Types ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cerna Network

Abstract Background Competing endogenous RNA (ceRNA) represents a class of RNAs (e.g., long noncoding RNAs [lncRNAs]) with microRNA (miRNA) binding sites, which can competitively bind miRNA and inhibit its regulation of target genes. Increasing evidence has underscored the involvement of dysregulated ceRNA networks in the occurrence and progression of colorectal cancer (CRC). The purpose of this study was to construct a ceRNA network related to the prognosis of CRC and further explore the potential mechanisms that affect this prognosis. Methods RNA-Seq and miRNA-Seq data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs), and a prognosis-related ceRNA network was constructed based on DElncRNA survival analysis. Subsequently, pathway enrichment, Pearson correlation, and Gene Set Enrichment Analysis (GSEA) were performed to determine the function of the genes in the ceRNA network. Gene Expression Profiling Interactive Analysis (GEPIA) and immunohistochemistry (IHC) were also used to validate differential gene expression. Finally, the correlation between lncRNA and immune cell infiltration in the tumor microenvironment was evaluated based on the CIBERSORT algorithm. Results A prognostic ceRNA network was constructed with eleven key survival-related DElncRNAs (MIR4435-2HG, NKILA, AFAP1-AS1, ELFN1-AS1, AC005520.2, AC245884.8, AL354836.1, AL355987.4, AL591845.1, LINC02038, and AC104823.1), 54 DEmiRNAs, and 308 DEmRNAs. The MIR4435-2HG- and ELFN1-AS1-associated ceRNA subnetworks affected and regulated the expression of the COL5A2, LOX, OSBPL3, PLAU, VCAN, SRM, and E2F1 target genes and were found to be related to prognosis and tumor-infiltrating immune cell types. Conclusions MIR4435-2HG and ELFN1-AS1 are associated with prognosis and tumor-infiltrating immune cell types and could represent potential prognostic biomarkers or therapeutic targets in colorectal carcinoma.

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Identification of a Glycolysis-Related LncRNA Signature to Predict Survival in Diffuse Glioma Patients

Frontiers in Oncology ◽

10.3389/fonc.2020.597877 ◽

2021 ◽

Vol 10 ◽

Author(s):

Yangyang Wang ◽

Wenjianlong Zhou ◽

Shunchang Ma ◽

Xiudong Guan ◽

Dainan Zhang ◽

...

Keyword(s):

Cell Cycle ◽

Overall Survival ◽

Risk Score ◽

Cox Regression ◽

Pearson Correlation ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Diffuse Glioma ◽

Roc Curve Analysis

Glycolysis refers to one of the critical phenotypes of tumor cells, regulating tumor cell phenotypes and generating sufficient energy for glioma cells. A range of noticeable genes [such as isocitrate dehydrogenase (IDH), phosphatase, and tensin homolog (PTEN), or Ras] overall impact cell proliferation, invasion, cell cycle, and metastasis through glycolysis. Moreover, long non-coding RNAs (LncRNAs) are increasingly critical to disease progression. Accordingly, this study aimed to identify whether glycolysis-related LncRNAs have potential prognostic value for glioma patients. First, co-expression network between glycolysis-related protein-coding RNAs and LncRNAs was established according to Pearson correlation (Filter: |r| > 0.5 & P < 0.001). Furthermore, based on univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) analysis and multivariate Cox regression, a predictive model were built; vital glycolysis-related LncRNAs were identified; the risk score of every single patient was calculated. Moreover, receiver operating characteristic (ROC) curve analysis, gene set enrichment analysis (GSEA), GO and KEGG enrichment analysis were performed to assess the effect of risk score among glioma patients. 685 cases (including RNA sequences and clinical information) from two different cohorts of the Chinese Glioma Genome Atlas (CGGA) database were acquired. Based on the mentioned methods, the risk score calculation formula was yielded as follows: Risk score = (0.19 × EXPFOXD2-AS1) + (−0.27 × EXPAC062021.1) + (−0.16 × EXPAF131216.5) + (−0.05 × EXPLINC00844) + (0.11 × EXPCRNDE) + (0.35 × EXPLINC00665). The risk score was independently related to prognosis, and every single mentioned LncRNAs was significantly related to the overall survival of patients. Moreover, functional enrichment analysis indicated that the biologic process of the high-risk score was mainly involved in the cell cycle and DNA replication signaling pathway. This study confirmed that glycolysis-related LncRNAs significantly impact poor prognosis and short overall survival and may act as therapeutic targets in the future.

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Identification of prognostic immune-related lncRNA signature predicting the overall survival for colorectal cancer

10.21203/rs.3.rs-620796/v1 ◽

2021 ◽

Author(s):

Jianxin Li ◽

Ting Han ◽

Xin Wang ◽

Yinchun Wang ◽

Qingqiang Yang

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

High Risk ◽

Cox Regression ◽

Risk Group ◽

Enrichment Analysis ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Regression Analyses

Abstract Background Long non-coding RNA (lncRNA) is an important regulator of gene expression and serves fundamental role in immune regulation. The present study aimed to develop a novel immune-related lncRNA signature to accurately assess the prognosis of patients with colorectal cancer (CRC). Methods Transcriptome data and clinical information of patients with CRC were downloaded from The Cancer Genome Atlas (TCGA), and the immune-related mRNAs were extracted from immunomodulatory gene datasets IMMUNE RESPONSE and IMMUNE SYSTEM PROCESS based on the Molecular Signatures Database (MSigDB). Then, the immune-related lncRNAs were identified by a correlation analysis between immune-related mRNAs and lncRNAs. Subsequently, univariate, lasso and multivariate Cox regression were used to identify an immune-related lncRNA signature in training cohort, and the predict ability of the signature was further confirmed in the testing cohort and the entire TCGA cohort. Finally, the lncRNA-mRNA co-expression network was established to explore the biological role of the immune-related lncRNA signature. Results In total, 272 Immune-related lncRNAs were identified, five of which were applied to construct an immune-related lncRNA signature based on univariate, lasso and multivariate Cox regression analyses. The signature divided patients with CRC into low- and high-risk groups, and patients with CRC in high-risk group had poorer overall survival than those in low-risk group. Univariate and multivariate Cox regression analyses confirmed that the signature could be an independent prognostic factor in human CRC. Furthermore, functional enrichment analysis revealed that the immune-related lncRNA signature was significantly enriched in immune process and tumor classical pathways. Conclusions The present study revealed that the novel immune-related lncRNA signature could be exploited as underlying molecular biomarkers and therapeutic targets for the patients with CRC.

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Competing Endogenous RNA in Colorectal Cancer: An Analysis for Colon, Rectum, and Rectosigmoid Junction

Frontiers in Oncology ◽

10.3389/fonc.2021.681579 ◽

2021 ◽

Vol 11 ◽

Author(s):

Lucas Maciel Vieira ◽

Natasha Andressa Nogueira Jorge ◽

João Batista de Sousa ◽

João Carlos Setubal ◽

Peter F. Stadler ◽

...

Keyword(s):

Colorectal Cancer ◽

Expression Profiles ◽

Enrichment Analysis ◽

Clinical Information ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Anatomical Site ◽

Rna Expression ◽

Rectosigmoid Junction

BackgroundColorectal cancer (CRC) is a heterogeneous cancer. Its treatment depends on its anatomical site and distinguishes between colon, rectum, and rectosigmoid junction cancer. This study aimed to identify diagnostic and prognostic biomarkers using networks of CRC-associated transcripts that can be built based on competing endogenous RNAs (ceRNA).MethodsRNA expression and clinical information data of patients with colon, rectum, and rectosigmoid junction cancer were obtained from The Cancer Genome Atlas (TCGA). The RNA expression profiles were assessed through bioinformatics analysis, and a ceRNA was constructed for each CRC site. A functional enrichment analysis was performed to assess the functional roles of the ceRNA networks in the prognosis of colon, rectum, and rectosigmoid junction cancer. Finally, to verify the ceRNA impact on prognosis, an overall survival analysis was performed.ResultsThe study identified various CRC site-specific prognosis biomarkers: hsa-miR-1271-5p, NRG1, hsa-miR-130a-3p, SNHG16, and hsa-miR-495-3p in the colon; E2F8 in the rectum and DMD and hsa-miR-130b-3p in the rectosigmoid junction. We also identified different biological pathways that highlight differences in CRC behavior at different anatomical sites, thus reinforcing the importance of correctly identifying the tumor site.ConclusionsSeveral potential prognostic markers for colon, rectum, and rectosigmoid junction cancer were found. CeRNA networks could provide better understanding of the differences between, and common factors in, prognosis of colon, rectum, and rectosigmoid junction cancer.

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