Dataset Information

Gene expression profiles of inflammatory breast cancer: correlation with response to neoadjuvant chemotherapy and metastasis-free survival.

ABSTRACT:

Background

Inflammatory breast cancer (IBC) is an aggressive disease. To date, no molecular feature reliably predicts either the response to chemotherapy (CT) or the survival. Using DNA microarrays, we searched for multigene predictors.

Patients and methods

The World IBC Consortium generated whole-genome expression profiles of 137 IBC and 252 non-IBC (nIBC) samples. We searched for transcriptional profiles associated with pathological complete response (pCR) to neoadjuvant anthracycline-based CT and distant metastasis-free survival (DMFS) in respective subsets of 87 and 106 informative IBC samples. Correlations were investigated with predictive and prognostic gene expression signatures published in nIBC (nIBC-GES). Supervised analyses tested genes and activation signatures of 19 biological pathways and 234 transcription factors.

Results

Three of five tested prognostic nIBC-GES and the two tested predictive nIBC-GES discriminated between IBC with and without pCR, as well as two interferon activation signatures. We identified a 107-gene signature enriched for immunity-related genes that distinguished between responders and nonresponders in IBC. Its robustness was demonstrated by external validation in three independent sets including two IBC sets and one nIBC set, with independent significant predictive value in IBC and nIBC validation sets in multivariate analysis. We found no robust signature associated with DMFS in patients with IBC, and neither of the tested prognostic GES, nor the molecular subtypes were informative, whereas they were in our nIBC series (220 stage I-III informative samples).

Conclusion

Despite the relatively small sample size, we show that response to neoadjuvant CT in IBC is, as in nIBC, associated with immunity-related processes, suggesting that similar mechanisms responsible for pCR exist. Analysis of a larger IBC series is warranted regarding the correlation of gene expression profiles and DMFS.

SUBMITTER: Bertucci F

PROVIDER: S-EPMC3905779 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Publications

Gene expression profiles of inflammatory breast cancer: correlation with response to neoadjuvant chemotherapy and metastasis-free survival.

Bertucci F F Ueno N T NT Finetti P P Vermeulen P P Lucci A A Robertson F M FM Marsan M M Iwamoto T T Krishnamurthy S S Masuda H H Van Dam P P Woodward W A WA Cristofanilli M M Reuben J M JM Dirix L L Viens P P Symmans W F WF Birnbaum D D Van Laere S J SJ

Annals of oncology : official journal of the European Society for Medical Oncology 20131202 2

<h4>Background</h4>Inflammatory breast cancer (IBC) is an aggressive disease. To date, no molecular feature reliably predicts either the response to chemotherapy (CT) or the survival. Using DNA microarrays, we searched for multigene predictors.<h4>Patients and methods</h4>The World IBC Consortium generated whole-genome expression profiles of 137 IBC and 252 non-IBC (nIBC) samples. We searched for transcriptional profiles associated with pathological complete response (pCR) to neoadjuvant anthrac ...[more]

PMID: 24299959

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Project description:BackgroundNeoadjuvant chemotherapy (NACT) is considered a standard treatment strategy for locally advanced triple negative breast cancer (TNBC). TNBC patients who achieve a pathologic complete response (pCR) are predicted to have a better prognosis while unfavorable chemo-sensitivity is still associated with a higher risk of disease relapse. The objective of this study was to construct a nomogram to predict disease-free survival (DFS) for TNBC patients following NACT.MethodsA total of 165 TNBC patients who underwent standard NACT and surgery were retrospectively reviewed, and data on their clinicopathological factors before and after NACT were collected. Independent prognostic factors for DFS were identified by Cox regression based on lower Akaike information criteria (AIC) and Bayesian information criterion (BIC). A nomogram to predict the 2-year and 5-year DFS following NACT for TNBC was constructed based on training cohort (n = 132) and validated by a validation cohort (n = 33).ResultsEither limited or full pCR (breast-only pCR, node-only pCR, or both-pCR) indicated significantly improved DFS and overall survival (OS) (p < 0.001). Lager residual tumor size (hazard ratio [HR] 1.175, p = 0.011) and the presence of lymphatic vessel invasion (LVI) (HR 3.168, p = 0.001) were identified as independent predictors of disease relapse in the training cohort. Five variables, including age, primary tumor size, histological grade, residual tumor size, and LVI were used to establish the nomogram. The C-index of the nomogram was 0.815, and calibration curves showed an acceptable consistency between the actual and nomogram-predicted 2-year and 5-year DFS. The proposed nomogram demonstrated superior predictive performance compared with Residual Cancer Burden (RCB) classification and the 8th American Joint Committee on Cancer Post Neoadjuvant Therapy Classification (AJCC ypTNM) staging system (area under the curve [AUC] for 2-year DFS: 0.870 vs. 0.758 vs. 0.711, respectively; AUC for 5-year DFS: 0.794 vs. 0.731 vs. 0.702, respectively) in the validation cohort.ConclusionsThe nomogram proposed in our study enabled to quantify the risk of disease relapse and demonstrated superior predictive performance than a survival predict instrument. It was an easy-to-use tool for clinicians to guide individualized surveillance of TNBC patients following standard NACT.

Dataset Information

Gene expression profiles of inflammatory breast cancer: correlation with response to neoadjuvant chemotherapy and metastasis-free survival.

Background

Patients and methods

Results

Conclusion

Publications

Gene expression profiles of inflammatory breast cancer: correlation with response to neoadjuvant chemotherapy and metastasis-free survival.

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