Background: Consensus molecular subtype 4 (CMS4) is a recently identified aggressive colon cancer subtype for which platelet-derived growth factor receptors (PDGFRs) and KIT are potential therapeutic targets. We aimed to develop a clinically applicable CMS4 reverse transcription polymerase chain reaction (RT-qPCR) test to select patients for PDGFR/KIT-targeted therapy. Methods: We used logistic regression to develop a CMS4 prediction rule based on microarray expression values of PDGFRA , PDGFRB , PDGFC , and KIT (566 training and 1259 test samples, using the 273-gene random forest classifier as CMS4 reference standard). We next translated the prediction rule into a single-sample RT-qPCR test, which we independently validated in 29 fresh tumor samples. To study intratumor CMS4 heterogeneity, we used the RT-qPCR test to analyze five random regions of 20 colon tumors. Results: The microarray-based prediction rule diagnosed CMS4-type tumors extremely well in both training and independent test samples (training: area under the curve [AUC] = 0.95, 95% confidence interval [CI] = 0.94 to 0.97; test: AUC = 0.95, 95% CI = 0.94 to 0.96), with excellent calibration and approximately 80% overall net benefit over a large threshold range. Translation into an RT-qPCR test did not affect discrimination (AUC = 0.97, 95% CI = 0.93 to 1.00, independent validation). RT-qPCR analysis of five random tumor regions revealed extensive intratumor CMS4 heterogeneity in nine out of 20 tumors. At least two regions likely have to be analyzed to identify patients that are predominantly CMS4 positive (>50% average CMS4 chance). Conclusion: The CMS4 RT-qPCR test is a promising clinical tool for selecting individual patients for CMS4-subtype-targeted therapy.
Background: Consensus molecular subtype 4 (CMS4) is a recently identified aggressive colon cancer subtype for which platelet-derived growth factor receptors (PDGFRs) and KIT are potential therapeutic targets. We aimed to develop a clinically applicable CMS4 reverse transcription polymerase chain reaction (RT-qPCR) test to select patients for PDGFR/KIT-targeted therapy. Methods: We used logistic regression to develop a CMS4 prediction rule based on microarray expression values of PDGFRA , PDGFRB , PDGFC , and KIT (566 training and 1259 test samples, using the 273-gene random forest classifier as CMS4 reference standard). We next translated the prediction rule into a single-sample RT-qPCR test, which we independently validated in 29 fresh tumor samples. To study intratumor CMS4 heterogeneity, we used the RT-qPCR test to analyze five random regions of 20 colon tumors. Results: The microarray-based prediction rule diagnosed CMS4-type tumors extremely well in both training and independent test samples (training: area under the curve [AUC] = 0.95, 95% confidence interval [CI] = 0.94 to 0.97; test: AUC = 0.95, 95% CI = 0.94 to 0.96), with excellent calibration and approximately 80% overall net benefit over a large threshold range. Translation into an RT-qPCR test did not affect discrimination (AUC = 0.97, 95% CI = 0.93 to 1.00, independent validation). RT-qPCR analysis of five random tumor regions revealed extensive intratumor CMS4 heterogeneity in nine out of 20 tumors. At least two regions likely have to be analyzed to identify patients that are predominantly CMS4 positive (>50% average CMS4 chance). Conclusion: The CMS4 RT-qPCR test is a promising clinical tool for selecting individual patients for CMS4-subtype-targeted therapy.
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