scholarly journals A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients

2018 ◽  
Vol 50 (5) ◽  
pp. 1882-1890 ◽  
Author(s):  
Jian Zhao ◽  
Jian Xu ◽  
An-quan Shang ◽  
Rui Zhang
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Receiver Operating Characteristics ◽  
Operating Characteristics ◽  
Cox Regression Analysis ◽  
Lncrna Expression ◽  
Expression Signature ◽  
Receiver Operating ◽  
Testing Set

Background/Aims: Colorectal cancer (CRC) is one of the most common malignant tumor with high migration and invasion capacity. Long non-coding RNAs (lncRNAs) have been identified to influence multiple cancers progression through competitively binding microRNAs (miRNAs). In this study, we proposed to develop a lncRNA-based signature for CRC survival outcomes. Methods: LncRNA expression profiles of CRC patients were extracted from the Gene Expression Omnibus (GEO) data sets GSE38832 (training set) and GSE29621 (testing set) . Associations between lncRNA expression and CRC disease free survival (DFS) were evaluated through univariate Cox regression analysis, and prognosis signature constructed by combination of weighted lncRNA expression values were obtained through multivariate Cox regression analysis. Robustness of the prognosis signature was evaluated through receiver operating characteristics analysis in the testing set. Results: A weighted prognosis signature of six lncRNAs, including LINC01583, LINC00276, LUNAR1, DKFZp434J0226, SFTA1P and OGFOD3, was yielded from multivariate Cox regression analysis. Samples with significantly different DFS dislayed distinct signatures, indicating considerable predictory accuracy of this expression signature. Conclusion: Robustness of the prognosis signature was evaluated in the testing set through Kaplan-Meier and receiver operating characteristics (ROC) analysis. Furthermore, functional enrichment analysis of lncRNAs suggested significant enrichment of cancer related pathways. Our results revealed the promise of lncRNAs as prognostic biomarkers.

scholarly journals Prediction of Prognostic Biomarkers and Construction of an Autophagy Prognostic Model for Colorectal Cancer Using Bioinformatics

2020 ◽  
Vol 19 ◽  
pp. 153303382098417
Author(s):  
Ting-ting Liu ◽  
Shu-min Liu
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Small Gtpase ◽  
Functional Enrichment ◽  
Clinical Correlation ◽  
Cox Regression Analysis ◽  
Prognostic Analysis ◽  
Key Genes

Objective: The incidence of colorectal cancer is increasing every year, and autophagy may be related closely to the pathogenesis of colorectal cancer. Autophagy is a natural catabolic mechanism that allows the degradation of cellular components in eukaryotic cells. However, autophagy plays a dual role in tumorigenesis. It not only promotes normal cell survival and tumor growth but also induces cell death and suppresses tumors survival. In addition, the pathogenesis of various conditions, including inflammation, neurodegenerative diseases, or tumors, is associated with abnormal autophagy. The present work aimed to examine the significance of autophagy-related genes (ARGs) in prognosis prediction, to construct an autophagy prognostic model, and to identify independent prognostic factors for colorectal cancer (CRC). Methods: This study discovered a total of 36 ARGs in CRC cases using The Cancer Genome Atlas (TCGA) and Human Autophagy-dedicated (HADd) databases along with functional enrichment analysis. Then, an autophagy prognostic model was constructed using univariate Cox regression analysis, and the key prognostic genes were screened. Finally, independent prognostic markers were determined through independent prognostic analysis and clinical correlation analysis of key genes. Results: Of the 36 differentially expressed ARGs, 13 were related to prognosis, as determined by univariate Cox regression analysis. A total of 6 key genes were obtained by a multivariate Cox regression analysis. Independent prognostic values were shown by 3 genes, namely, microtubule-associated protein 1 light chain 3 (MAP1LC3C), small GTPase superfamily and Rab family (RAB7A), and WD-repeat domain phosphoinositide-interacting protein 2 (WIPI2) by independent prognostic analysis and clinical correlation. Conclusions: In this study, molecular bioinformatics technology was employed to determine and construct a prognostic model of autophagy for colon cancer patients, which revealed 3 autophagy-related features, namely, MAP1LC3C, WIPI2, and RAB7A.

scholarly journals Influence of Old Age on Risk of Lymph Node Metastasis and Survival in Patients With T1 Colorectal Cancer: A Population-Based Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hua Ye ◽  
Bin Zheng ◽  
Qi Zheng ◽  
Ping Chen
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Lymph Node ◽  
Elderly Patients ◽  
Old Age ◽  
Tumor Size ◽  
Cox Regression ◽  
Cox Regression Analysis ◽  
T1 Colorectal Cancer ◽  
Well Differentiated

BackgroundWe aimed at determining the influence of old age on lymph node metastasis (LNM) and prognosis in T1 colorectal cancer (CRC).MethodsWe collected data from eligible patients in Surveillance, Epidemiology, and End Results database between 2004 and 2015. Independent predictors of LNM were identified by logistic regression analysis. Cox regression analysis, propensity score-matched analysis, and competing risks analysis were used to analyze the associations between old age and lymph node (LN) status and to validate the prognostic value of old age on cancer-specific survival (CSS).ResultsIn total, 10,092 patients were identified. Among them, 6,423 patients (63.6%) had greater than or equal to 12 examined lymph nodes (LNE ≥12), and 5,777 patients (57.7%) were 65 years or older. The observed rate of LNM was 4.6% (15 out of 325) in T1 CRC elderly patients, with tumor size <3 cm, well differentiated, with negative carcinoembryonic antigen (CEA) level, and adenocarcinoma. Logistic regression models demonstrated that tumor size ≥3 cm (odds ratio, OR = 1.316, P = 0.038), poorly differentiated (OR = 3.716, P < 0.001), older age (OR = 0.633 for ages 65–79 years, OR = 0.477 for age over 80 years, both P <0.001), and negative CEA level (OR = 0.71, P = 0.007) were independent prognostic factors. Cox regression analysis demonstrated that CSS was not significantly different between elderly patients undergoing radical resection with LNE ≥12 and those with LNE <12 (hazard ratio = 0.865, P = 0.153), which was firmly validated after a propensity score-matched analysis by a competing risks model.ConclusionsThe predictive value of tumor size, grading, primary site, histology, CEA level, and age for LNM should be considered in medical decision making about local resection. We found that tumor size was <3 cm, well differentiated, negative CEA level, and adenocarcinoma in elderly patients with T1 colorectal cancer which was suitable for local excision.

scholarly journals Exploration and Verification of a Six-RNA Binding Proteins-based Prognosis Evaluating Model for Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Miao Chen ◽  
Shujie Li ◽  
Jiakang Zhang ◽  
Jianbo Han ◽  
Lili Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Survival Analysis ◽  
Binding Proteins ◽  
Cancer Genome ◽  
Functional Enrichment ◽  
Operating Characteristics ◽  
Training Cohort ◽  
Cox Regression Analysis ◽  
Receiver Operating

Abstract BackgroundRNA binding protein (RBP) plays a crucial role in tumorigenesis at post-transcriptional level in various cancer types. Nevertheless, the role of RBPs in liver hepatocellular carcinoma (LIHC) remains obscure. We attempted to uncover the association between RBPs and the prognosis of LIHC patients. MethodsWe analyzed the transcriptome and corresponding clinical data of LIHC patients from the cancer genome atlas (TCGA) (training cohort) and international cancer genome consortium (ICGC) (validating cohort) database with a series of bioinformatics methods. Differently expressed RNA-binding proteins (DERBPs) were screened and subjected to functional enrichment analysis and co-expression network establishment. Overall survival (OS) related DERBPs and our prognosis risk model were confirmed by univariate, LASSO and multivariate regression analysis in training cohort. Survival analysis, Receiver operating characteristic curve (ROC) and nomogram were conducted in both training and validating groups to confirm the performance of our model. Human protein atlas (HPA) database and Kaplan-Meier plotter were used to verify the expression and prognostic significance of the hub RBPs respectively.Results There were 330 RBPs were found significantly different in TCGA. Functional analysis indicated most of the DERBPs were majored in RNA processing, alternative splicing and metabolism, etc. 6 RBPs (UPF3B, MRPL54, ZC3H13, DHX58, PPARGC1A, EIF2AK4) were recognized as OS related and enrolled into our prognostic model. Survival analysis showed the risk signature was negatively correlated with the OS of LIHC patients in both training (p = 5.808e-06) and validating (p = 3.38e-03) groups. The area under curves (AUC) of the receiver operating characteristics (ROC) curve in training and validating cohorts was 0.756, 0.781 respectively which indicating the good performance of our model. The risk signature was an independent hazardous factor in multivariate COX regression analysis either in TCGA (HR = 1.626;95% CI 1.394 -1.897, p < 0.001) or ICGC (HR = 1.939;95% CI 1.324 -2.838, p < 0.001). Nomogram and calibration curve indicated our model had best performance in predicting 3-year survival rate.ConclusionsWe constructed a six-RBPs based risk signature model which had moderate efficiency in LIHC patients’ prognosis forecasting which may assist practitioners to make better decision in the management of LIHC.

scholarly journals The expression of long-chain non-coding RNA DMTF1v4 in colorectal cancer tissue and its relationship with clinicopathological features

2019 ◽  
Vol 17 ◽  
pp. 205873921984554
Author(s):  
Yanjuan Cai ◽  
Shutong Zhuang ◽  
Hongpeng Liu ◽  
Jianfu Qiu ◽  
Li Zeng
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Cancer Tissue ◽  
Depth Of Invasion ◽  
Cox Regression Analysis ◽  
Node Metastasis ◽  
Non Coding Rna ◽  
Long Chain

Emerging studies have showed that long-chain non-coding RNA DMTF1v4 might participate in the process of multidrug resistance phenotype of gastric cancer. However, its expression and function in colorectal cancer (CRC) is still unknown. In this study, we discovered that DMTF1v4 was generally 5.15 ± 1.67 times upregulated in CRC tissues compared to the adjacent normal tissues. Moreover, the expression level of DMTF1v4 was closely related to the distant metastasis of tumor, but it was not related to age, sex, tumor location, tumor staging, depth of invasion, lymph node metastasis, and differentiation level. Survival analysis showed that the overall survival rate of patients with high expression of DMTF1v4 was 45.0% in cancer tissues, which was significantly lower than 82.5% of DMTF1v4 low expression patients (χ2 = 11.562, P < 0.01). The results of univariate COX regression analysis showed that DMTF1v4, TNM (tumor, node, metastasis) staging, distant metastasis, and tumor differentiation were closely related to the prognosis of patients ( P < 0.05). Multivariate COX regression analysis showed that DMTF1v4 and distant metastasis could be independent prognostic factors for CRC patients. In conclusion, this study revealed that DMTF1v4 might promote the development of CRC, which can be used as an independent factor to judge the prognosis of CRC.

Nomogram to predict survival of pulmonary large-cell neuroendocrine carcinoma after surgery

2020 ◽  
Author(s):  
Qian Huang ◽  
Jie Liu ◽  
Huifang Cai ◽  
Qi Zhang ◽  
Lina Wang
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Predictive Performance ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Operating Characteristics ◽  
Cox Regression Analysis

Abstract Background Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis, and surgery is the main treatment. However, there are no effective predictive tools to assess the prognosis of postoperative patients. Our aim is to identify prognostic factors and construct nomogram to accurately assess prognosis. Methods Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of Cox regression analysis, construct nomogram for predicting 1-, 3-, and 5-year survival. The predictive performance of nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Results We finally screened 903 patients with pulmonary LCNEC who underwent surgery. The Cox regression analysis showed that age, SEER stage, T stage, N stage, M stage, tumor size, and chemotherapy were independent prognostic factors for overall survival (P<0.05). The C-index of the nomogram is 0.681 on the training cohort and 0.675 on the validation cohort. The AUC and calibration plots show that the nomogram has good performance. Conclusion We constructed and validated nomogram for predicting 1-, 3-, and 5-year survival of patients with pulmonary LCNEC after surgery. Our nomogram provides reference information for assessing the overall survival of these patients.

scholarly journals A Novel 8-Gene Prognostic Signature for Survival Prediction of Uveal Melanoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Zhongjun Tang ◽  
Kebo Cai
Keyword(s):  
Gene Expression ◽  
Regression Analysis ◽  
Uveal Melanoma ◽  
Cox Regression ◽  
Gene Expression Signature ◽  
Survival Prediction ◽  
Hub Genes ◽  
Data Set ◽  
Cox Regression Analysis ◽  
Expression Signature

Background. Uveal melanoma (UM) has favorable local tumor control, but once metastasis develops, the prognosis is rather poor. Thus, it is urgent to develop metastasis predicting markers. Objective. Our study investigated a novel gene expression-based signature in predicting metastasis for patients with UM. Methods. In the discovery phase, 63 patients with UM from GEO data set GSE22138 were analyzed using the Weighted Correlation Network Analysis (WGCNA) to identify metastasis-related hub genes. The Least Absolute Shrinkage and Selection Operator (Lasso) Cox regression was used to select candidate genes and build a gene expression signature. In the validation phase, the signature was validated in The Cancer Genome Atlas database. Results. Forty-one genes were identified as hub genes of metastasis by WGCNA. After the Lasso Cox regression analysis, eight genes including RPL10A, EIF1B, TIPARP, RPL15, SLC25A38, PHLDA1, TFDP2, and MEGF10 were highlighted as candidate predictors. The gene expression signature for UM (UMPS) could independently predict MFS by univariate and multivariate Cox regression analysis. Incorporating UMPS increased the AUC of the traditional clinical model. In the validation cohort, UMPS performed well in predicting the MFS of UM patients. Conclusions. UMPS, an eight-gene-based signature, is useful in predicting prognosis for patients with UM.

scholarly journals Επίπεδα VEGF σε πλευριτική συλλογή και περιφερικό δείγμα αίματος σε ασθενείς με καρκίνο πνεύμονα

2015 ◽  
Author(s):  
Ιωάννης Γκιόζος
Keyword(s):  
Regression Analysis ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Performance Status ◽  
Roc Curves ◽  
Characteristic Curves ◽  
Cox Regression Analysis ◽  
Receiver Operating Characteristic Curves ◽  
Receiver Operating

Ο πρωταρχικός σκοπός της παρούσας μελέτης ήταν η προοπτική διερεύνηση της δυνητικής προγνωστικής αξίας των προθεραπευτικών επιπέδων VEGF ορού και πλευριτικού υγρού σε ασθενείς με μη μικροκυτταρικό καρκίνο πνεύμονα (ΜΜΚΠ) που παρουσιάζονται με κακοήθη πλευριτική συλλογή. Επιπρόσθετος στόχος ήταν η διαλεύκανση της διαγνωστικής χρησιμότητας των προθεραπευτικών επιπέδων VEGF ορού για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών ατόμων. Στο παρόν ερευνητικό έργο μελετήσαμε προοπτικά 40 συνεχόμενους νεοδιαγνωσθέντες ασθενείς με ΜΜΚΠ, με κακοήθη πλευριτική συλλογή χωρίς απομακρυσμένες μεταστάσεις, που παραπέμφθηκαν για ογκολογική θεραπεία και αντιμετωπίστηκαν στην Ογκολογική Μονάδα της 3ης Πανεπιστημιακής Παθολογικής Κλινικής του Γενικού Νοσοκομείου Αθηνών «Η Σωτηρία», μεταξύ Σεπτεμβρίου 2009 και Σεπτεμβρίου 2013. Τα επίπεδα VEGF ορού και πλευριτικού υγρού μετρήθηκαν με τη χρήση ανοσοενζυμικής μεθόδου (ELISA). Τα επίπεδα VEGF ορού μετρήθηκαν επίσης σε πενήντα υγιείς μάρτυρες, εξομοιωμένους ως προς το φύλο και την ηλικία με τους ασθενείς (p=0.517 και p=0.795, αντιστοίχως). Η διαγνωστική ακρίβεια των επιπέδων VEGF ορού για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών μαρτύρων υπολογίστηκε με τη χρήση καμπυλών λειτουργικού χαρακτηριστικού δέκτη (Receiver operating characteristic curves, ROC curves). Τα επίπεδα VEGF ορού και πλευριτικού υγρού συσχετίσθηκαν με δημογραφικές και κλινικοπαθολογοανατομικές παραμέτρους, συμπεριλαμβανομένου του φύλου, της ηλικίας, του ιστορικού καπνίσματος, του performance status,του ιστολογικού τύπου του όγκου και της ανταπόκρισης στη θεραπεία. Η προγνωστική αξία κάθε μεταβλητής για τη συνολική επιβίωση και το διάστημα ελεύθερο προόδου νόσου αξιολογήθηκε με μονοπαραγοντική και πολυπαραγοντική ανάλυση παλινδρόμησης του Cox (univariate and multivariate Cox regression analysis). Οι διάμεσες τιμές VEGF ορού ήταν στατιστικώς σημαντικά υψηλότερες στους ασθενείς σε σύγκριση με τους υγιείς μάρτυρες (p<0.001), ενώ το βέλτιστο διαχωριστικό όριο όσον αφορά στις τιμές VEGF ορού για τη διάκριση μεταξύ ασθενών και μαρτύρων ήταν 375 pg/ml, με τιμές ευαισθησίας και ειδικότητας 76.9% και 98.0%, αντιστοίχως. Επίπεδα VEGF ορού μεγαλύτερα απο 375 pg/ml και επίπεδα VEGF πλευριτικού υγρού μεγαλύτερα από τη διάμεση τιμή, καθώς και η παρουσία προόδου νόσου, συσχετίσθηκαν με χαμηλότερο διάστημα PFS και χαμηλότερη συνολική επιβίωση, τόσο στη μονοπαραγοντική όσο και στην πολυπαραγοντική ανάλυση επιβίωσης. Στατιστικά σημαντική συσχέτιση παρατηρήθηκε επίσης μεταξύ των επιπέδων VEGF ορού και πλευριτικού υγρού (p<0.001).Τα αποτελέσματα της μελέτης μας υποδεικνύουν ότι τα επίπεδα VEGF ορού μπορεί να χρησιμεύουν για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών, καθώς και ότι τα αυξημένα προθεραπευτικά επίπεδα VEGF τόσο στον ορό και στο πλευριτικό υγρό ασθενών με ΜΚΚΠ προχωρημένου σταδίου μπορεί να αντιπροσωπεύουν ανεξάρτητους δείκτες δυσμενούς πρόγνωσης σε αυτή την υποομάδα των ασθενών. Για την επιβεβαίωση των ευρημάτων του παρόντος ερευνητικού έργου και την περαιτέρω διερεύνηση της πιθανής αξίας των ως άνω βιοδεικτών ως δεικτών πρόβλεψης όχι μόνο της επιβίωσης των ασθενών αυτών αλλά και της ανταπόκρισής τους στις στοχευμένες αντι-αγγειογενετικές θεραπείες, απαιτείται η διενέργεια μελλοντικών προοπτικών ερευνών σε μεγαλύτερες σειρές ασθενών.

scholarly journals A New Prognostic and Therapeutic Immune-related Risk Signature of Colorectal Cancer

2021 ◽  
Author(s):  
Yuan Li ◽  
Hao Huang ◽  
Jun Feng ◽  
Yulan Zhu ◽  
Tianwei Jiang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regression Analysis ◽  
Risk Model ◽  
Cox Regression ◽  
R Package ◽  
Lasso Regression ◽  
Cox Regression Analysis ◽  
Related Risk ◽  
Set Up ◽  
Microsatellite Stability

Abstract BackgroundAlthough some advanced colorectal cancer (CRC) patients could select immunotherapy, but still most microsatellite stability (MSS) CRC patients did not respond. Our present study aims to set up a novel system for prognostic prediction and immunotherapeutic responsiveness for MSS CRC patients.MethodsUnivariable Cox regression survival analysis and least absolute shrinkage and selector operation (LASSO) regression analysis were performed to identify prognostic genes and establish immune risk signatures. Multivariate Cox regression analysis was performed to verify whether these clinical features could predict prognosis. R package was used to analyze the relationship between the immune-related risk model and these immune cells, effector molecules, and immune checkpoints.ResultsWe constructed an immune-related signature and verified its predictive capability. Immune-related signature included 12 differentially expressed IRGs (12 DE IR MSSGs), including CXCL1, CD36, FABP4, MS4A2, NRG1, VGF, GRP, HDC, XCL1, NGF, MAGEA1, and IL13. The signature consisting of 12 DE IR MSSGs was an independent and effective prognostic factor for the overall survival of CRC patients. In addition, the signature consisting of 12 DE IR MSSGs reflected the infiltration characteristics of different immunocytes in tumor immune microenvironment. The signature consisting of 12 DE IR MSSGs also had a significant correlation with immune checkpoint molecules.

scholarly journals Construction of a Prognostic Model for Predicting Overall Survival of Patients with Colorectal Cancer

2020 ◽  
Author(s):  
Shuwen Han ◽  
Kefeng Ding
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Levulinic Acid ◽  
Prognostic Model ◽  
Cox Regression ◽  
Aminolevulinic Acid ◽  
Risk Group ◽  
Prognostic Models ◽  
Cox Regression Analysis

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies. The purpose of this study is to construct a prognostic model for predicting the overall survival (OS) in patients with CRC. Methods: The mRNA-seq and miRNA-seq data of colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ) were downloaded from The Cancer Genome Atlas (TCGA) database. The differentially expressed RNAs (DE-RNAs) between tumor and normal tissues were screened. The Kaplan-Meier and univariate Cox regression analysis were used to screen the survival-related genes. Functional enrichment analysis of survival-related genes was conducted, followed by protein-protein interaction (PPI) analysis. Subsequently, the potential drugs targeting differentially expressed mRNAs (DE-mRNAs) were investigated. Multivariate Cox regression analysis was then conducted to screen the independent prognostic factors, and these genes were used to establish a prognostic model. A receiver operator characteristic (ROC) curve was constructed, and the area under the curve (AUC) value of ROC was calculated to evaluate the specificity and sensitivity of the model. Results: A total of 855 survival-related genes were screened. These genes were mainly enriched in Gene Ontology (GO) terms, such as methylation, synapse organization, and methyltransferase activity; and pathway analysis showed that these genes were significantly involved in N-Glycan biosynthesis and the calcium signaling pathway. PPI analysis showed that aminolevulinate dehydratase (ALAD) and cholinergic receptor muscarinic 2 (CHRM2) served vital roles in the development of CRC. Aminolevulinic acid, levulinic acid, and loxapine might be potential drugs for CRC treatment. The prognostic models were built and the patients were divided into high-risk and low-risk groups based on the median of risk score (RS) as screening threshold. The OS for patients in the high-risk group was markedly shorter than that for patients in the low-risk group. Meanwhile, kazal type serine peptidase inhibitor domain 1 (KAZALD1), hippocalcin like 4 (HPCAL4), cadherin 8 (CDH8), synaptopodin 2 (SYNPO2), cyclin D3 (CCND3), and hsa_mir_26b may be independent prognostic factors that could be considered as therapeutic targets for CRC.Conclusion: We established prognostic models that could predict the OS for CRC patients and may assist clinicians in providing personalized and precision treatment in this patient population.Highlights:1. ALAD served a vital role in the development of CRC.2. CHRM2 played a role in CRC development by affecting the calcium signaling pathway.3. Aminolevulinic acid, levulinic acid, and loxapine might be potential drugs for treating CRC.4. KAZALD1 and HPCAL4 were associated with the OS of CRC.5. CDH8, SYNPO2, CCND3, and hsa-mir-26b were closely related to the prognostic of CRC staging.

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