Prognostic and Predictive Models for Left- and Right- Colorectal Cancer Patients: A Bioinformatics Analysis Based on Ferroptosis-Related Genes

Chen, Yingying; Li, Hua

doi:10.3389/fonc.2022.833834

Cited by 15 publications

(11 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To explore whether different sides of mCRC impact this DDRscore model’ accuracy, we divided the training group into left- and right-side metastatic colorectal cancer (LmCRC, RmCRC) cohorts. Researches show that left- and right-side colorectal cancer are significantly different in clinical features and prognosis ( 26 , 27 ). The Kaplan–Meier curves show that the survival of LmCRC/RmCRC cohort cases in the high-DDRscore group was significantly lower than those in the low-DDRscore group ( Figures 5A, C ).…”

Section: Resultsmentioning

confidence: 99%

“…Some researchers have demonstrated that mCRCs are clinically heterogeneous. Left- and right-sided mCRC patients have significantly different genomics, prognosis, and clinical characteristics ( 26 , 30 ). Although left-sided mCRCs show a better prognosis compared to right-sided ones in previous research, our DDRscore model indicates that all enrolled mCRCs (AUC=0.763) are better than those divided into LmCRC9 (AUC=0.722) and RmCRC cohorts (AUC=0.707).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma

Wei

Su²,

Zhang³

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

BackgroundColorectal cancer (CRC) is the third most prevalent malignancy and the one of most lethal cancer. Metastatic CRC (mCRC) is the third most common cause of cancer deaths worldwide. DNA damage response (DDR) genes are closely associated with the tumorigenesis and development of CRC. In this study, we aimed to construct a DDR-related gene signature for predicting the prognosis of mCRC patients.MethodsThe gene expression and corresponding clinical information data of CRC/mCRC patients were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A prognostic model was obtained and termed DDRScore by the multivariate Cox proportional hazards regression in the patients with mCRC. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were employed to validate the predictive ability of the prognostic model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed for patients between the high-DDRscore and low-DDRscore groups.ResultsWe constructed a prognostic model consisting of four DDR-related genes (EME2, MSH4, MLH3, and SPO11). Survival analysis showed that patients in the high-DDRscore group had a significantly worse OS than those in the low-DDRscore group. The area under the curve (AUC) value of the ROC curve of the predictive model is 0.763 in the training cohort GSE72970, 0.659 in the stage III/IV colorectal cancer (CRC) patients from The Cancer Genome Atlas (TCGA) data portal, and 0.639 in another validation cohort GSE39582, respectively. GSEA functional analysis revealed that the most significantly enriched pathways focused on nucleotide excision repair, base excision repair, homologous recombination, cytokine receptor interaction, chemokine signal pathway, cell adhesion molecules cams, ECM-receptor interaction, and focal adhesion.ConclusionThe DDRscore was identified as an independent prognostic and therapy response predictor, and the DDR-related genes may be potential diagnosis or prognosis biomarkers for mCRC patients.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma

Wei

Su²,

Zhang³

et al. 2023

Front. Oncol.

View full text Add to dashboard Cite

show abstract

“…Prediction models for CRC patients have been widely reported [33][34][35]. But previous literature tended to be based on a single aspect of CRC development, such as N 6 methylation alone, and some were relatively limited with either no internal tests or no external validation.…”

Section: Discussionmentioning

confidence: 99%

The Role of RNA Methylation Modification Related Genes in Prognosis and Immunotherapy of Colorectal Cancer

Lin

Chen

et al. 2022

Preprint

View full text Add to dashboard Cite

This study aimed to analyze the effects of RNA methylation regulatory genes in prognosis and treatment of CRC. Prognostic signature associated with CRCs were constructed by differential expression analysis, Cox and LASSO analyses. ROC and Kaplan-Meier survival analyses were used to validate the reliability of the developed model. Finally, normal and cancerous tissue were collected to validate gene by qRT-PCR. A prognostic risk model based on LRPPRC and UHRF2 was constructed and relevant to the OS of CRC. Ultimately, PCR validation showed that a significant upregulation in the expression of LRPPRC and UHRF2 in cancerous tissue. A prognostic risk model based on LRPPRC and UHRF2 was successfully built, and the model could predict the immunotherapy efficacy of CRC.

show abstract

“…The KM technique was applied to generate survival curves illustrating the disparities in expected survival time and probability across the high-and low-risk patients in both CGGA and TCGA datasets. With the aid of the "timeROC" package in R (Chen and Li, 2022), the ROC curves were plotted, and the area under the curves (AUC) for 1-, 3-, 5-, and 7-year OS were computed for both the CGGA and TCGA cohorts. To additionally test the viability of the risk score-based predictive model in patients with LGG in both the CGGA and TCGA datasets, the principal component analysis (PCA) and the t-distributed stochastic neighbour embedding (t-SNE) analyses were done.…”

Section: Discrepancies In the Clinical Characteristics Tumour Immune ...mentioning

confidence: 99%

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma

Miao

Liu

et al. 2022

Front. Genet.

View full text Add to dashboard Cite

Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.

show abstract

Prognostic and Predictive Models for Left- and Right- Colorectal Cancer Patients: A Bioinformatics Analysis Based on Ferroptosis-Related Genes

Cited by 15 publications

References 50 publications

Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma

Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma

The Role of RNA Methylation Modification Related Genes in Prognosis and Immunotherapy of Colorectal Cancer

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma

Contact Info

Product

Resources

About