BACKGROUND: Owing to the complex processes required for anthracycline-induced cytotoxicity, a prospectively defined multifactorial Consensus Signature (ConSig) might improve prediction of anthracycline response in triple-negative breast cancer (TNBC) patients, whose only standard systemic treatment option is chemotherapy. AIMS: We aimed to construct and evaluate a multifactorial signature, comprising measures of each function required for anthracycline sensitivity in TNBC. METHODS: ConSigs were constructed based on five steps required for anthracycline function: drug penetration, nuclear topoisomerase IIα (topoIIα) protein location, increased topoIIα messenger RNA (mRNA) expression, apoptosis induction, and immune activation measured by, respectively, HIF1α or SHARP1 signature, LAPTM4B mRNA, topoIIα mRNA, Minimal Gene signature or YWHAZ mRNA, and STAT1 signature. TNBC patients treated with neoadjuvant anthracycline-based chemotherapy without taxane were identified from publicly available gene expression data derived with Affymetrix HG-U133 arrays (training set). In silico analyses of correlation between gene expression data and pathological complete response (pCR) were performed using receiver-operating characteristic curves. To determine anthracycline specificity, ConSigs were assessed in patients treated with anthracycline plus taxane. Specificity, sensitivity, positive and negative predictive value, and odds ratio (OR) were calculated for ConSigs. Analyses were repeated in two validation gene expression data sets derived using different microarray platforms. RESULTS: In the training set, 29 of 147 patients had pCR after anthracycline-based chemotherapy. Various combinations of components were evaluated, with the most powerful anthracycline response predictors being ConSig1: (STAT1+topoIIα mRNA +LAPTM4B) and ConSig2: (STAT1+topoIIα mRNA+HIF1α). ConSig1 demonstrated high negative predictive value (85%) and high OR for no pCR (3.18) and outperformed ConSig2 in validation sets for anthracycline specificity. CONCLUSIONS: With further validation, ConSig1 may help refine selection of TNBC patients for anthracycline chemotherapy.
A multifactorial ‘Consensus Signature’ by in silico analysis to predict response to neoadjuvant anthracycline-based chemotherapy in triple-negative breast cancer
FORCATO, Mattia;BICCIATO, Silvio;
2015
Abstract
BACKGROUND: Owing to the complex processes required for anthracycline-induced cytotoxicity, a prospectively defined multifactorial Consensus Signature (ConSig) might improve prediction of anthracycline response in triple-negative breast cancer (TNBC) patients, whose only standard systemic treatment option is chemotherapy. AIMS: We aimed to construct and evaluate a multifactorial signature, comprising measures of each function required for anthracycline sensitivity in TNBC. METHODS: ConSigs were constructed based on five steps required for anthracycline function: drug penetration, nuclear topoisomerase IIα (topoIIα) protein location, increased topoIIα messenger RNA (mRNA) expression, apoptosis induction, and immune activation measured by, respectively, HIF1α or SHARP1 signature, LAPTM4B mRNA, topoIIα mRNA, Minimal Gene signature or YWHAZ mRNA, and STAT1 signature. TNBC patients treated with neoadjuvant anthracycline-based chemotherapy without taxane were identified from publicly available gene expression data derived with Affymetrix HG-U133 arrays (training set). In silico analyses of correlation between gene expression data and pathological complete response (pCR) were performed using receiver-operating characteristic curves. To determine anthracycline specificity, ConSigs were assessed in patients treated with anthracycline plus taxane. Specificity, sensitivity, positive and negative predictive value, and odds ratio (OR) were calculated for ConSigs. Analyses were repeated in two validation gene expression data sets derived using different microarray platforms. RESULTS: In the training set, 29 of 147 patients had pCR after anthracycline-based chemotherapy. Various combinations of components were evaluated, with the most powerful anthracycline response predictors being ConSig1: (STAT1+topoIIα mRNA +LAPTM4B) and ConSig2: (STAT1+topoIIα mRNA+HIF1α). ConSig1 demonstrated high negative predictive value (85%) and high OR for no pCR (3.18) and outperformed ConSig2 in validation sets for anthracycline specificity. CONCLUSIONS: With further validation, ConSig1 may help refine selection of TNBC patients for anthracycline chemotherapy.Pubblicazioni consigliate
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