• 2018-07
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2020-03
  • 2020-07
  • 2020-08
  • 2021-03
  • br a much higher predictive ability than that of the


    a much higher predictive ability than that AUY922 (NVP-AUY922) of the TNM stage, considered as a continuous variable, in the training and validation cohorts. Since stage is a categorical variable, we converted TMRS-RFS from continuous to three-classified variables to enhance comparability, and the superior predictive accuracy of TMRS-RFS was sustained even as a categorical variable (Sup-plemental Fig. S3a–c and Table 1). Using multivariate analysis, the TMRS-RFS model was also found to be a strong independent risk factor when treated as a continuous variable in all patient cohorts (Table 2). Similar results were also found for the TMRS-OS model in 678 patients with doc-umented OS information (Fig. 2c, Supplemental Fig. S3d–e, Tables 1–2).
    Table 1
    Harrell's concordance indexes of the TMRS model and stage in different cohorts.
    Abbreviation: TMRS, tumour microenvironment risk score; RFS, relapse-free survival; OS, overall survival. a Continuous variables.
    b Category variables.
    Table 2
    Univariate and multivariate survival analyses of TMRS-RFS, TMRS-OS and clinical variables.
    Entire p-Value
    Entire p-Value
    Training p-Value Validation p-Value
    Entire p-Value
    TMRS-OSa /
    Abbreviation: TMRS, tumour microenvironment risk score, UVA, univariate analysis, MVA, multivariate analysis; RFS, relapse-free survival; OS, overall survival; CMS, consensus molecular subtypes; NE, not enter. a Continuous variable.
    The predictive power of the TMRS-RFS and TMRS-OS models was next tested in various subgroups stratified by patient dataset, age, gen-der, stage, tumour site, and CMS subtype in the entire cohort, respec-tively, where TMRS-RFS and TMRS-OS were both analysed as continuous variables. Forest plots indicated that, for both models, a higher value could significantly identify the patients with worse prog-noses in all subgroups (Fig. 2d–e).
    3.4. TMRS panel predicts therapeutic benefit of chemotherapy in colon cancer
    Adjuvant chemotherapy (ADJC) is the main treatment strategy for non-metastatic colon cancer patients [35]. Since only the GSE39582 dataset recorded chemotherapy information of patients, we analysed the relationship between the TMRS panel and ADJC benefits in this dataset, where OS was used as the treatment outcome. Survival benefits of low-TMRS-RFS and low-TMRS-OS were maintained regardless of ADJC conduction (Fig. 3a–b). Interestingly, it was observed that ADJC significantly reduced the mortality risk of patients only in low-TMRS-RFS and low-TMRS-OS groups but did not confer survival benefits to pa-tients in high-TMRS-RFS or high-TMRS-OS groups (Fig. 3c). Further-more, the results of stratified analysis of each stage (Supplemental Fig. S4), showed that treatment benefits of ADJC were higher for pa-tients in groups with low scores, in either Stage II or III. To develop a clinically relevant quantitative method for predicting the probability of patient mortality, we constructed two nomograms (Fig. 3d–e) inte-grating both TMRS panel derived scores and independent clinical prog-nostic factors in the GSE39582 dataset (Supplemental Table S7). The calibration plots showed that the derived nomograms performed well compared to the performance of an ideal model (Fig. 3f–g). Decision curve analysis revealed that clinical usefulness of the nomograms signif-icantly overwhelmed the TNM stage (Fig. 3h–i).
    3.5. Identification of TMRS-RFS and TMRS-OS related biological pathways and processes
    The correlations between TMRS panel derived scores with clinical characteristics and molecular subtypes were further investigated in the GSE39582 series (Fig. 4a–b). In terms of clinical characteristics, both TMRS-RFS and TMRS-OS were increased in patients with more ad-vanced stages and patients who had relapsed and died due to the dis-ease. Furthermore, while gender influenced the value of TMRS-RFS, that of TMRS-OS varied between age and tumour site. In terms of molec-ular characteristics, we observed that KRAS mutation simultaneously up-regulated the values of TMRS-OS and TMRS-RFS, and patients in mo-lecular subtypes C4, C6, and CMS4 exhibited significantly higher values of TMRS models than others. However, mismatch repair status was sig-nificantly correlated only with the TMRS-RFS level. Next, we used GSVA