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Intratumoral morphological heterogeneity of breast cancer: neoadjuvant chemotherapy efficiency and multidrug resistance gene expression.

ABSTRACT: In this study, the influence of intratumoral morphological heterogeneity of breast cancer on neoadjuvant chemotherapy (NAC) efficiency was investigated. In particular, we analysed the association of NAC response and pre- and post-NAC expression of the main multidrug resistance (MDR) genes--ABCB1, ABCC1, ABCC5, ABCG1, and ABCG2, with the presence of different morphological structures in breast tumors. In addition, the expression of MDR genes was investigated in different morphological structures and in their microenvironment by comparing probes obtained using laser microdissection. The results of this study showed that tumors with alveolar structures were more frequently NAC-nonresponsive than cases without this structural type (p = 0.0028, Bonferroni-corrected p = 0.014). The presence of trabecular structures in breast tumors was also associated with chemoresistance (p = 0.0272, Bonferroni-corrected p = 0.136). High expression of MDR genes was not found in alveolar structures (including their microenvironment) and in tumors containing this structural type. In contrast, more active MDR genes and expression of the ABCB1 gene were found only in trabecular structures. Taken together, our data indicate that breast tumors with alveolar structures possess resistance to NAC, which is not related to high expression of MDR genes, whereas chemoresistance of tumors with trabecular structures can depend on the expression level of ABCB1.

SUBMITTER: Denisov EV

PROVIDER: S-EPMC3988480 | biostudies-other | 2014 Apr

REPOSITORIES: biostudies-other

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Project description:Purpose To characterize intratumoral spatial heterogeneity at perfusion magnetic resonance (MR) imaging and investigate intratumoral heterogeneity as a predictor of recurrence-free survival (RFS) in breast cancer. Materials and Methods In this retrospective study, a discovery cohort (n = 60) and a multicenter validation cohort (n = 186) were analyzed. Each tumor was divided into multiple spatially segregated, phenotypically consistent subregions on the basis of perfusion MR imaging parameters. The authors first defined a multiregional spatial interaction (MSI) matrix and then, based on this matrix, calculated 22 image features. A network strategy was used to integrate all image features and classify patients into different risk groups. The prognostic value of imaging-based stratification was evaluated in relation to clinical-pathologic factors with multivariable Cox regression. Results Three intratumoral subregions with high, intermediate, and low MR perfusion were identified and showed high consistency between the two cohorts. Patients in both cohorts were stratified according to network analysis of multiregional image features regarding RFS (log-rank test, P = .002 for both). Aggressive tumors were associated with a larger volume of the poorly perfused subregion as well as interaction between poorly and moderately perfused subregions and surrounding parenchyma. At multivariable analysis, the proposed MSI-based marker was independently associated with RFS (hazard ratio: 3.42; 95% confidence interval: 1.55, 7.57; P = .002) adjusting for age, estrogen receptor (ER) status, progesterone receptor status, human epidermal growth factor receptor type 2 (HER2) status, tumor volume, and pathologic complete response (pCR). Furthermore, imaging helped stratify patients for RFS within the ER-positive and HER2-positive subgroups (log-rank test, P = .007 and .004) and among patients without pCR after neoadjuvant chemotherapy (log-rank test, P = .003). Conclusion Breast cancer consists of multiple spatially distinct subregions. Imaging heterogeneity is an independent prognostic factor beyond traditional risk predictors.

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Intratumoral morphological heterogeneity of breast cancer: neoadjuvant chemotherapy efficiency and multidrug resistance gene expression.

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