A prognostic index based on an eleven gene signature to predict systemic recurrences in colorectal cancer

Abstract Approximately half of colorectal cancer (CRC) patients experience disease recurrence and metastasis, and these individuals frequently fail to respond to treatment due to their clinical and biological diversity. Here, we aimed to identify a prognostic signature consisting of a small gene group for precisely predicting CRC heterogeneity. We performed transcriptomic profiling using RNA-seq data generated from the primary tissue samples of 130 CRC patients. A prognostic index (PI) based on recurrence-associated genes was developed and validated in two larger independent CRC patient cohorts (n = 795). The association between the PI and prognosis of CRC patients was evaluated using Kaplan–Meier plots, log-rank tests, a Cox regression analysis and a RT-PCR analysis. Transcriptomic profiling in 130 CRC patients identified two distinct subtypes associated with systemic recurrence. Pathway enrichment and RT-PCR analyses revealed an eleven gene signature incorporated into the PI system, which was a significant prognostic indicator of CRC. Multivariate and subset analyses showed that PI was an independent risk factor (HR = 1.812, 95% CI = 1.342–2.448, P < 0.001) with predictive value to identify low-risk stage II patients who responded the worst to adjuvant chemotherapy. Finally, a comparative analysis with previously reported Consensus Molecular Subgroup (CMS), high-risk patients classified by the PI revealed a distinct molecular property similar to CMS4, associated with a poor prognosis. This novel PI predictor based on an eleven gene signature likely represents a surrogate diagnostic tool for identifying high-risk CRC patients and for predicting the worst responding patients for adjuvant chemotherapy.

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Identification and validation of a hub gene prognostic index for hepatocellular carcinoma

Future Oncology ◽

10.2217/fon-2020-1112 ◽

2021 ◽

Author(s):

Q Shi ◽

Z Meng ◽

XX Tian ◽

YF Wang ◽

WH Wang

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Prognostic Index ◽

Interaction Network ◽

Gene Signature ◽

Gene Expression Omnibus ◽

Cox Regression Analysis ◽

Protein Protein Interaction ◽

Normal Tissues ◽

Significant Independent Prognostic Factor

Aims: We aim to provide new insights into the mechanisms of hepatocellular carcinoma (HCC) and identify key genes as biomarkers for the prognosis of HCC. Materials & methods: Differentially expressed genes between HCC tissues and normal tissues were identified via the Gene Expression Omnibus tool. The top ten hub genes screened by the degree of the protein nodes in the protein–protein interaction network also showed significant associations with overall survival in HCC patients. Results: A prognostic model containing a five-gene signature was constructed to predict the prognosis of HCC via multivariate Cox regression analysis. Conclusion: This study identified a novel five-gene signature ( CDK1, CCNB1, CCNB2, BUB1 and KIF11) as a significant independent prognostic factor.

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Development and validation of a robust prognostic and predictive signature for colorectal cancer (CRC) patients

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.4036 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. 4036-4036

Author(s):

A. M. Glas ◽

P. Roepman ◽

R. Salazar ◽

G. Capella ◽

V. Moreno ◽

...

Keyword(s):

Colorectal Cancer ◽

Colon Cancer ◽

High Risk ◽

Adjuvant Chemotherapy ◽

Cancer Patients ◽

Gene Signature ◽

Low Risk ◽

Stage Ii ◽

Significant Difference ◽

Independent Cohort

4036 Background: Between 25 and 35% of stage II CRC patients will experience a recurrence of their disease and may benefit from adjuvant chemotherapy. Official guidelines give suggestions but no clear recommendation for best risk stratification. Here we describe the development a robust signature that predicts disease relapse and can assist in treatment decisions. Methods: Fresh frozen tumor tissues from 180 patients with stage I, II and III colorectal cancer undergoing surgery were analyzed using high density Agilent 44K oligonucleotide arrays. Median FU was 70.2 months; 85% of patients did not receive adjuvant chemotherapy. Unsupervised hierarchical clustering based on full-genome gene expression measurement indicated the existence of 3 main colon molecular subclasses. Survival analysis of the 3 classes showed that subtype C (n= 27) had a poor outcome and subtype A (n= 48) good outcome. Only the intermediate group B (n=104) was used to develop a signature by using a cross validation procedure to score all genes for their association with 5-yr distant metastasis free survival (DMFS) and subsequently applied to all samples (n=180). The obtained gene signature was further validated on an independent cohort of 178 stage II + III colon samples. Results: A set of 38 prognosis related gene probes showed robust DMFS association in over 50% of all iterations in the Training Set of 180 samples. The gene signature was validated on an independent cohort of 178 samples from stage II + III colon cancer patients. The profile classified 61% of the validation samples as low-risk and 39% as high-risk. The low- and high-risk samples showed a significant difference in DMFS with a HR of 3.19 (P= 8.5e-4). Five-year DMFS rates were 89% (95%CI 83–95) for low-risk and 62% (95%CI 50–77) for high-risk samples. Moreover, the profile showed a significant performance within stage II (P=0.0058) and III (P=0.036) only samples. The performance of the profile was significant for both untreated (P=0.0082) and treated patients (P=0.016) suggesting that its power is independent of treatment benefits. Conclusions: ColoPrint is able to predict the prognosis of stage II and III colon cancer patients and facilitates the identification of patients who would benefit from adjuvant chemotherapy. [Table: see text]

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An Immune-Related Prognostic Signature for Predicting Clinical Outcomes and Immune Landscape in IDH-Mutant Lower-Grade Gliomas

Journal of Oncology ◽

10.1155/2021/3766685 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Gang Xiao ◽

Xuan Gao ◽

Lifeng Li ◽

Chao Liu ◽

Zhiyuan Liu ◽

...

Keyword(s):

High Risk ◽

Clinical Outcomes ◽

Immune Cell ◽

Cox Regression ◽

Immune Escape ◽

Gene Signature ◽

Individual Therapy ◽

Lower Grade ◽

Prognostic Signature ◽

Cox Regression Analysis

Background. IDH mutation is the most common in diffuse LGGs, correlated with a favorable prognosis. However, the IDH-mutant LGGs patients with poor prognoses need to be identified, and the potential mechanism leading to a worse outcome and treatment options needs to be investigated. Methods. A six-gene immune-related prognostic signature in IDH-mutant LGGs was constructed based on two public datasets and univariate, multivariate, and LASSO Cox regression analysis. Patients were divided into low- and high-risk groups based on the median risk score in the training and validation sets. We analyzed enriched pathways and immune cell infiltration, applying the GSEA and the immune evaluation algorithms. Results. Stratification and multivariate Cox analysis unveiled that the six-gene signature was an independent prognostic factor. The signature (0.806/0.795/0.822) showed a remarkable prognostic performance, with 1-, 3-, and 5-year time-dependent AUC, higher than for grade (0.612/0.638/0.649) and 1p19q codeletion status (0.606/0.658/0.676). High-risk patients had higher infiltrating immune cells. However, the specific immune escape was observed in the high-risk group after immune activation, owing to increasing immunosuppressive cells, inhibitory cytokines, and immune checkpoint molecules. Moreover, a novel nomogram model was developed to evaluate the survival in IDH-mutant LGGs patients. Conclusion. The six-gene signature could be a promising prognostic biomarker, which is promising to promote individual therapy and improve the clinical outcomes of IDH-mutant gliomas. The study also refined the current classification system of IDH-mutant gliomas, classifying patients into two subtypes with distinct immunophenotypes and overall survival.

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A Novel Signature Constructed by Immune-Related LncRNA Predicts the Immune Landscape of Colorectal Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.695130 ◽

2021 ◽

Vol 12 ◽

Author(s):

Mengyu Sun ◽

Tongyue Zhang ◽

Yijun Wang ◽

Wenjie Huang ◽

Limin Xia

Keyword(s):

Colorectal Cancer ◽

High Risk ◽

Immune Cell ◽

Cox Regression ◽

Risk Group ◽

Univariate Analysis ◽

The Cancer Genome Atlas ◽

High Morbidity ◽

Cox Regression Analysis ◽

Chemotherapy Drugs

Colorectal cancer (CRC) has the characteristics of high morbidity and mortality. LncRNA not only participates in the progression of CRC through genes and transcription levels, but also regulates the tumor microenvironment and leads to the malignant phenotype of tumors. Therefore, we identified immune-related LncRNAs for the construction of clinical prognostic model. We searched The Cancer Genome Atlas (TCGA) database for original data. Then we identified differentially expressed irlncRNA (DEirlncRNA), which was paired and verified subsequently. Next, univariate analysis, Lasso and Cox regression analysis were performed on the DEirlncRNA pair. The ROC curve of the signature was drawn, and the optimal cut-off value was found. Then the cohort was divided into a high-risk and a low-risk group. Finally, we re-evaluated the signature from different perspectives. A total of 16 pairs of DEirlncRNA were included in the construction of the model. After regrouping according to the cut-off value of 1.275, the high-risk group showed adverse survival outcomes, progressive clinicopathological features, specific immune cell infiltration status, and high sensitivity to some chemotherapy drugs. In conclusion, we constructed a signature composed of immune-related LncRNA pair with no requirement of the specific expression level of genes, which shows promising clinical predictive value in CRC patients.

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An autophagy-related long non-coding RNA signature for patients with colorectal cancer

Physiology International ◽

10.1556/2060.2021.00125 ◽

2021 ◽

Author(s):

Dongyan Zhao ◽

Xizhen Sun ◽

Sidan Long ◽

Shukun Yao

Keyword(s):

Colorectal Cancer ◽

Overall Survival ◽

High Risk ◽

Cox Regression ◽

Risk Group ◽

Expression Profiles ◽

High Risk Group ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Cox Regression Analysis

AbstractAimLong non-coding RNAs (lncRNAs) have been identified to regulate cancers by controlling the process of autophagy and by mediating the post-transcriptional and transcriptional regulation of autophagy-related genes. This study aimed to investigate the potential prognostic role of autophagy-associated lncRNAs in colorectal cancer (CRC) patients.MethodsLncRNA expression profiles and the corresponding clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) database. Based on the TCGA dataset, autophagy-related lncRNAs were identified by Pearson correlation test. Univariate Cox regression analysis and the least absolute shrinkage and selection operator analysis (LASSO) Cox regression model were performed to construct the prognostic gene signature. Gene set enrichment analysis (GSEA) was used to further clarify the underlying molecular mechanisms.ResultsWe obtained 210 autophagy-related genes from the whole dataset and found 1187 lncRNAs that were correlated with the autophagy-related genes. Using Univariate and LASSO Cox regression analyses, eight lncRNAs were screened to establish an eight-lncRNA signature, based on which patients were divided into the low-risk and high-risk group. Patients’ overall survival was found to be significantly worse in the high-risk group compared to that in the low-risk group (log-rank p = 2.731E-06). ROC analysis showed that this signature had better prognostic accuracy than TNM stage, as indicated by the area under the curve. Furthermore, GSEA demonstrated that this signature was involved in many cancer-related pathways, including TGF-β, p53, mTOR and WNT signaling pathway.ConclusionsOur study constructed a novel signature from eight autophagy-related lncRNAs to predict the overall survival of CRC, which could assistant clinicians in making individualized treatment.

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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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Immunological nomograms predicting prognosis and guiding adjuvant chemotherapy in stage II colorectal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.4_suppl.499 ◽

2019 ◽

Vol 37 (4_suppl) ◽

pp. 499-499

Author(s):

Junjie Peng ◽

Yaqi Li ◽

Yang Feng

Keyword(s):

Colorectal Cancer ◽

High Risk ◽

Adjuvant Chemotherapy ◽

Cox Regression ◽

Univariate Analysis ◽

Tumor Infiltrating Lymphocytes ◽

Risk Groups ◽

High Risk Group ◽

Stage Ii ◽

Stage Ii Colorectal Cancer

499 Background: The type, abundance, and location of tumor-infiltrating lymphocytes (TILs) have been associated with prognosis in colorectal cancer. The objective of this study was to assess the prognostic role of TILs and develop a nomogram for accurate prognostication of stage II colorectal cancer. Methods: Immunohistochemistry was conducted to assess the densities of intraepithelial and stromal CD3+, CD8+, CD45RO+ and FOXP3+ TILs, and to estimate PD-L1 expression in tumor cells for 168 patients with stage II colorectal cancer. The prognostic roles of these features were evaluated using COX regression model, and nomograms were established to stratify patients into low and high-risk groups and compare the benefit from adjuvant chemotherapy. Results: In univariate analysis, patients with high intraepithelial or stromal CD3+, CD8+, CD45RO+ and FOXP3+ TILs were associated significantly with better relapse-free survival (RFS) and overall survival (OS), except for stromal CD45RO+ TILs, whereas PD-L1 expression wasn't associated with RFS or OS. In multivariate analysis, patients with high intraepithelial CD3+ and stromal FOXP3+ TILs were associated with better RFS (p < 0.001 and p = 0.032, respectively), while only stromal FOXP3+ TILs was an independent prognostic factor for OS (p = 0.031). The nomograms were well calibrated and showed a c-index of 0.751 and 0.757 for RFS and OS, respectively. After stratifying into low and high-risk groups, the high-risk group exhibited a better OS from adjuvant chemotherapy (3-year OS of 81.9% v 34.3%, p = 0.006). Conclusions: These results may help improve the prognostication of stage II colorectal cancer and identify a high-risk subset of patients who appeared to benefit from adjuvant chemotherapy.

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Can red cell distribution width and hemoglobin level variations be utilized to predict the prognosis of Stage III operative colorectal cancer patients with adjuvant chemotherapy treatment?

10.21203/rs.2.22551/v1 ◽

2020 ◽

Author(s):

Jie Li ◽

Yuan-Yi Rui ◽

Bo Song ◽

Ke Zhang ◽

Bo Yi ◽

...

Keyword(s):

Colorectal Cancer ◽

Adjuvant Chemotherapy ◽

Cancer Patients ◽

Cox Regression ◽

Stage Iii ◽

Red Cell ◽

Cell Distribution ◽

Distribution Width ◽

Cox Regression Analysis ◽

Colorectal Cancer Patients

Abstract Background: The aim of this study was to find that if the red cell distribution width (RDW) or hemoglobin (Hb) level variations had prognostic value in stage III colorectal cancer patients treated with operation and adjuvant chemotherapy. Methods: One hundred and twenty-two patients were included in this retrospective study. All were diagnosed and re-staged as stage III colorectal cancer in Sichuan Cancer Hospital according to the AJCC Cancer Staging Manual, 8 th edition, 2018. The patients received R0 resection before adjuvant chemotherapy. The baseline information, routine blood examination data, pathological outcome and prognostic stature was retracted from the database. Receiver operating characteristic (ROC) curve analysis was utilized to determine the cut-off value, while the survival analyses were performed with Kaplan-Meier curve, the log-rank test and the Cox regression analysis. Results: The chemotherapy-associated hemoglobin change (change between the pre- and post-chemotherapy hemoglobin levels) was identified to be associated with the metastasis (P=0.030). The optimal cut-off point was calculated to be -9.5 by the ROC curve of the hemoglobin change, while the area under the curve was 0.648 (95% CI: 0.524-0.772). The results showed that patients with larger hemoglobin decrease had significantly worse disease free survival (DFS) than those with smaller decrease (P=0.020). Factors associated with DFS in uni-variate COX regression analysis were the number of harvested lymph nodes (P=0.040) and the perineural invasion (P=0.020). The peri-chemotherapy change of hemoglobin level was estimated to have significant effect on patient survival (P=0.010). Conclusions: We concluded that chemotherapy-associated Hb change (change between the pre- and post-chemotherapy) was a DFS prognostic factor for the stage III colorectal cancer patients who underwent operation and adjuvant chemotherapy.

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An Oxidative Stress Index-Based Score for Prognostic Prediction in Colorectal Cancer Patients Undergoing Surgery

Oxidative Medicine and Cellular Longevity ◽

10.1155/2021/6693707 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Yinghao Cao ◽

Shenghe Deng ◽

Lizhao Yan ◽

Junnan Gu ◽

Fuwei Mao ◽

...

Keyword(s):

Oxidative Stress ◽

Colorectal Cancer ◽

Prediction Models ◽

Cox Regression ◽

Prognostic Index ◽

Disease Free Survival ◽

Tnm Stage ◽

Cox Regression Analysis ◽

T Stage ◽

Prognostic Prediction

Oxidative stress plays an important role in the development of colorectal cancer (CRC). This study is aimed at developing and validating a novel scoring system, based on oxidative stress indexes, for prognostic prediction in CRC patients. A retrospective analysis of 1422 CRC patients who underwent surgical resection between January 2013 and December 2017 was performed. These patients were randomly assigned to the training set ( n = 1022 ) or the validation set ( n = 400 ). Cox regression model was used to analyze the laboratory parameters. The CRC-Integrated Oxidative Stress Score (CIOSS) was developed from albumin (ALB), direct bilirubin (DBIL), and blood urea nitrogen (BUN), which were significantly associated with survival in CRC patients. Furthermore, a survival nomogram was generated by combining the CIOSS with other beneficial clinical characteristics. The CIOSS generated was as follows: 0.074 × albumin (g/L), − 0.094 × bilirubin (μmol/L), and - 0.099 × blood urea nitrogen (mmol/L), based on the multivariable Cox regression analysis. Using 50% (0.1025) and 85% (0.481) of CIOSS as cutoff values, three prognostically distinct groups were formed. Patients with high CIOSS experienced worse overall survival (OS) ( hazard ratio HR = 4.33 ; 95% confidence interval [CI], 2.80-6.68; P < 0.001 ) and worse disease-free survival (DFS) ( HR = 3.02 ; 95% CI, 1.96-4.64; P < 0.001 ) compared to those with low CIOSS. This predictive nomogram had good calibration and discrimination. ROC analyses showed that the CIOSS possessed excellent performance ( AUC = 0.818 ) in predicting DFS. The AUC of the OS nomogram based on CIOSS, TNM stage, T stage, and chemotherapy was 0.812, while that of the DFS nomogram based on CIOSS, T stage, and TNM stage was 0.855. Decision curve analysis showed that these two prediction models were clinically useful. CIOSS is a CRC-specific prognostic index based on the combination of available oxidative stress indexes. High CIOSS is a powerful indicator of poor prognosis. The CIOSS also showed better predictive performance compared to TNM stage in CRC patients.

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Comprehensive Analysis of the Prognostic Significance of Hsa-miR-100-5p and Its Related Gene Signature in Stomach Adenocarcinoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.736274 ◽

2021 ◽

Vol 9 ◽

Author(s):

Gaoming Wang ◽

Ludi Yang ◽

Miao Hu ◽

Renhao Hu ◽

Yongkun Wang ◽

...

Keyword(s):

High Risk ◽

Cox Regression ◽

Prognostic Significance ◽

Tumor Development ◽

Risk Groups ◽

Gene Signature ◽

Risk Scores ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Stomach Adenocarcinoma

Stomach adenocarcinoma (STAD) is one of the most common cancers in the world. However, the prognosis of STAD remains poor, and the therapeutic effect of chemotherapy and immunotherapy varies from person to person. MicroRNAs (miRNAs) play vital roles in tumor development and metastasis and can be used for cancer diagnosis and prognosis. In this study, hsa-miR-100-5p was identified as the only dysregulated miRNA in STAD samples through an analysis of three miRNA expression matrices. A weighted gene co-expression network analysis (WGCNA) was performed to select hsa-miR-100-5p-related genes. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to establish a miR-100-5p-related prognostic signature. Kaplan–Meier analyses, nomograms, and univariate and multivariate Cox regression analyses were used to evaluate the prognostic signature, which was subsequently identified as an independent risk factor for STAD patients. We investigated the tumor immune environment between low- and high-risk groups and found that, among component types, M2 macrophages contributed the most to the difference between these groups. A drug sensitivity analysis suggested that patients with high-risk scores may be more sensitive to docetaxel and cisplatin chemotherapy and that patients in the low-risk group may be more likely to benefit from immunotherapy. Finally, external cohorts were evaluated to validate the robustness of the prognostic signature. In summary, this study may provide new ideas for developing more individualized therapeutic strategies for STAD patients.

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