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. 2012 May 1;72(9):2350-61.
doi: 10.1158/0008-5472.CAN-11-4201. Epub 2012 Mar 6.

Impact of intertumoral heterogeneity on predicting chemotherapy response of BRCA1-deficient mammary tumors

Sven Rottenberg  1 , Marieke A Vollebergh, Bas de Hoon, Jorma de Ronde, Philip C Schouten, Ariena Kersbergen, Serge A L Zander, Marina Pajic, Janneke E Jaspers, Martijn Jonkers, Martin Lodén, Wendy Sol, Eline van der Burg, Jelle Wesseling, Jean-Pierre Gillet, Michael M Gottesman, Joost Gribnau, Lodewyk Wessels, Sabine C Linn, Jos Jonkers, Piet Borst
Affiliations

Impact of intertumoral heterogeneity on predicting chemotherapy response of BRCA1-deficient mammary tumors

Sven Rottenberg et al. Cancer Res. .

Abstract

The lack of markers to predict chemotherapy responses in patients poses a major handicap in cancer treatment. We searched for gene expression patterns that correlate with docetaxel or cisplatin response in a mouse model for breast cancer associated with BRCA1 deficiency. Array-based expression profiling did not identify a single marker gene predicting docetaxel response, despite an increase in Abcb1 (P-glycoprotein) expression that was sufficient to explain resistance in several poor responders. Intertumoral heterogeneity explained the inability to identify a predictive gene expression signature for docetaxel. To address this problem, we used a novel algorithm designed to detect differential gene expression in a subgroup of the poor responders that could identify tumors with increased Abcb1 transcript levels. In contrast, standard analytical tools, such as significance analysis of microarrays, detected a marker only if it correlated with response in a substantial fraction of tumors. For example, low expression of the Xist gene correlated with cisplatin hypersensitivity in most tumors, and it also predicted long recurrence-free survival of HER2-negative, stage III breast cancer patients treated with intensive platinum-based chemotherapy. Our findings may prove useful for selecting patients with high-risk breast cancer who could benefit from platinum-based therapy.

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Figures

Figure 1
Figure 1
Reproducibility of docetaxel or cisplatin sensitivity of individual KB1P tumors using orthotopic transplantation. Tumor fragments of spontaneous mammary tumors were transplanted orthotopically into syngeneic wild-type female mice as shown in (A) for docetaxel and (B) for cisplatin. When tumors reached a volume of 150–250mm3, animals were treated with docetaxel (A, filled squares) or cisplatin (B, filled squares). Treatment of tumors was resumed once the tumor relapsed to its original size (100%).
Figure 2
Figure 2
Analysis of intrinsic (A, B, C) or acquired (D, E) docetaxel resistance of KB1P tumors using gene expression profiling. A, Relative tumor size of 43 individual tumors after completion of initial treatment using 25mg docetaxel per kg i.v. on days 0, 7 and 14. Tumors with a relative volume below 100% (bar) were classified as good responders, the remaining as poor responders. B, SAM of untreated tumors of good vs. poor docetaxel responders (Δ=0.7) using the MEEBO or Illumina platforms. C, Average of median-normalized cycle threshold (CT) values determined by quantitative TLDA of 46 genes encoding ABC proteins. D, SAM of tumors that acquired docetaxel resistance (Δ=1.1, FDR=0). E, Ratios of Abcb1a or Abcb1b gene expression (RT-MLPA) of docetaxel-resistant tumors and samples from the matched drug-sensitive control tumors. Error bars indicate standard deviation of three independent reactions.
Figure 3
Figure 3
Identification of outliers present in subgroups of poor docetaxel responders using an algorithm developed by de Ronde et al. (34). Clustering analysis of top 50 ranked genes is shown. Each blue block represents a tumor with higher expression than the maximum of the expression of that particular gene in the responder group.
Figure 4
Figure 4
Quantification of the expression of the mouse Abcb1 genes in untreated mouse mammary tumors. A, RT-MLPA analyses of Abcb1a or Abcb1b transcript levels of 43 individual KB1P tumors. Error bars indicate standard deviation of three independent reactions. B, time until relapse of KB1P tumors treated with the MTD of cisplatin, docetaxel or doxorubicin. The 5 tumors that showed increased Abcb1 gene expression are highlighted in red. In panel C the remaining 15 poor docetaxel responders that were also treated with cisplatin and doxorubicin are indicated in red.
Figure 5
Figure 5
Docetaxel responses of P-gp;BRCA1;p53-deficient (KB1PM) mammary tumors. A, Abcb1a/1b-/- alleles were crossed to homozygosity into the KCre;Brca1F/F;p53F/F model. KB1PM tumors were then orthotopically transplanted into female FVB/N animals and treated with docetaxel as indicated for KB1P tumors in Figure 1. B, 11 orthotopically transplanted KB1PM tumors were left untreated or received docetaxel (rhombi). Comparison of the time until tumors relapsed back to the original size of treatment start (C) or survival (D) of KB1PM-1 to -11 with the orthotopically transplanted P-gp-proficient KB1P tumors T7-T43 (logrank test).
Figure 6
Figure 6
Correlation of gene expression with the response to platinum drugs. A, Time required for 35 individual KB1P tumors to grow back to 100% after cisplatin treatment. The bar indicates the mean. B, SAM of highly vs. moderately cisplatin-sensitive KB1P tumors using the MEEBO (Δ=1.5; FDR=0) or Illumina (Δ=0.7; FDR=0) platforms. C, KM survival curves according to XIST gene expression levels of patients who had been randomized between conventional (CONV, red) and intensive platinum-based chemotherapy (IPB, black). P values were calculated using the logrank test.
Figure 7
Figure 7
X chromosome aberrations investigated by FISH. A, examples of normal XaXi or abnormal cells with Xa or XaXa configuration (green: XIST RNA probe; red: RNF12 DNA). B, overview of 24 patients for which FISH results were obtained and their correlation to XIST RNA expression (0: XIST low, 1: XIST high) or aCGH (0: normal copy number, 1: XIST lost). Normal XiXa, XaXa and loss of Xi are also indicated categorically (0= no, 1= yes). XIST RNA cloud describes whether a normal XIST cloud is absent in >60% of cells (0) or not (1). (C) Associations between low XIST gene expression and aberrations identified by FISH (n=24, Fisher’s exact test). OR: Odds ratio, CI: Confidence interval
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