RB-pathway disruption is associated with improved response to neoadjuvant chemotherapy in breast cancer

Abstract

Purpose: We sought to determine whether dysregulation of the retinoblastoma (RB) tumor suppressor pathway was associated with improved response to neoadjuvant chemotherapy in breast cancer.

Experimental design: An RB-loss signature was used to analyze the association between pathway status and pathologic complete response in gene expression datasets encompassing three different neoadjuvant regimens. Parallel immunohistochemical analysis of the RB pathway was conducted on pretreatment biopsies to determine the association with pathologic response to neoadjuvant chemotherapy.

Results: An RB-loss gene expression signature was associated with increased pathologic complete response in datasets from breast cancer patients treated with 5-fluorouracil/adriamycin/cytoxan (FAC; P < 0.001), T/FAC (P < 0.001), and Taxane/Adriaymcin (P < 0.001) neoadjuvant therapy encompassing approximately 1,000 patients. The association with improved response to neoadjuvant chemotherapy was true in both estrogen receptor (ER)-positive and ER-negative breast cancer. Elevated expression of p16ink4a is associated with the RB-loss signature (R = 0.493-0.5982), and correspondingly p16ink4a mRNA levels were strongly associated with pathologic complete response in the same datasets analyzed. In an independent cohort, immunohistochemical analyses of RB and p16ink4a revealed an association of RB loss (P = 0.0018) or elevated p16ink4a (P = 0.0253) with pathologic complete response. In addition, by Miller-Payne and clinicopathologic scoring analyses, RB-deficient tumors experienced an overall improved response to neoadjuvant chemotherapy.

Conclusion: Disruption of the RB pathway as measured by several independent methods was associated with improved response to neoadjuvant chemotherapy. The RB-pathway status was relevant for pathologic response in both ER-positive and ER-negative breast cancer with similar results observed with multiple chemotherapy regimens. Combined, these data indicate that RB status is associated with the response to neoadjuvant chemotherapy in breast cancer and could be used to inform treatment.

©2012 AACR.

Figures

Figure 1. RB loss signature is associated with response to FAC neoadjuvant therapy

(A) Tumors were clustered based on the relative level of the RB loss signature. The heat map depicts all of the genes within the signature. Below the bars denote the average RB loss signature value, the RB1 transcript, clinically defined ER status, and the expression of the ESR1 transcript. The bottom color bar provides the relationship to pathological complete response (pCR) vs residual or progressed disease (no pCR). The relationship of chemotherapy response to RB loss signature was determined using KS statistical modeling. (B) ROC analyses of the RB loss signature in this cohort was determined for predicting response (left panel) and the RB loss signature expression value as a function of no pCR vs. pCR was determined (right panel). (C) Bar graphs demonstrating the frequency of response based on median signature value (left panel) or a previously determined cutpoint (right panel).

Figure 2. Signature of RB loss is associated with response to FAC neoadjuvant therapy in both ER-positive and ER-negative breast cancer

(A) Tumors that were either clinically defined as ER-positive or ER-negative were clustered based on the relative level of the RB loss signature. The heat maps depicts all of the genes within the signature. The bars denote the average RB loss signature value, the RB1 transcript, clinically defined ER status, and the expression of the ESR1 transcript. The color bar provides the relationship to pathological complete response (pCR) vs residual or proressed disease (no pCR). The relationship of chemotherapy response to RB loss signature was determined using KS statistical modeling. (B) ROC analyses of the RB loss signature in either ER-positive or ER-negative cases was determined for predicting response (left panel) and the RB loss signature expression value as a function of no pCR vs. pCR was determined (right panel). (C) Bar graphs demonstrating the frequency of response of ER-positive and ER-negative cases based on median signature value (top panels) or a previously determined cutpoint (lower panels).

Figure 3. The RB loss signature is associated with response to TA neoadjuvant therapy

(A) Total tumors and ER-positive/ER-negative groupings were clustered based on the relative level of the RB loss signature. The heat map depicts all of the genes within the signature. Below the bars denote the average RB loss signature value, the RB1 transcript, clinically defined ER status, and the expression of the ESR1 transcript. Color bar provides the relationship to pathological complete response (pCR) vs residual or progressed disease (no pCR). The relationship of chemotherapy response to RB loss signature was determined using KS statistical modeling. (B) ROC analyses of the RB loss signature in this cohort was determined for all cases as well as by ER-status (left panel). The differentiation RB loss signature expression value was a function of no pCR vs. pCR was determined in total and ER-specific groups (right panel). (C) Bar graphs demonstrating the frequency of response based on median signature value (left panel) or a previously determined cutpoint (right panel).

Figure 4. The RB loss signature is associated with response to TFAC neoadjuvant therapy

(A) Total tumors and ER-positive/ER-negative groupings were clustered based on the relative level of the RB loss signature. The heat map depicts all of the genes within the signature. Below the bars denote the average RB loss signature value, the RB1 transcript, clinically defined ER status, and the expression of the ESR1 transcript. Color bar provides the relationship to pathological complete response (pCR) vs residual or progressed disease (no pCR). The relationship of chemotherapy response to RB loss signature was determined using KS statistical modeling. (B) ROC analyses of the RB loss signature in this cohort was determined for all cases as well as by ER-stautus (left panel). The differentiation RB loss signature expression value was a function of no pCR vs. pCR was determined in total and ER-specific groups (right panel). (C) Bar graphs demonstrating the frequency of response based on median signature value (left panel) or a previously determined cutpoint (right panel).

Figure 5. The expression of CDKN2A is associated with RB deficiency and response to neoadjuvant therapy

Cases treated with FAC, TA, and TFAC were clustered based on the relative expression of CDKN2A. The correlation between CDKN2A expression and the RB loss signature was determined (R-value shown). The RB1 expression, ER-status, ESR1 expression, and pathological response were shown. The statistical relationship with response was defined using the KS statistic. (B) ROC analyses of CDKN2A expression in these cohorts and the relationship relative expression levels in pCR vs. non pCR cases was determined. Data shown are for FAC and TA cases. (C) Bargraphs demonstrate the frequency of response based on the median CDKN2A expression value.

Figure 6. Histological analyses of RB and p16ink4a in neoadjuvant treated cases

(A) Representative case that failed to respond to neoadjuvant chemotherapy. a. Pretreatment specimen stained with Hematoxylin/Eosin. b. Pretreatment specimen stained for p16ink4a expression with low staining in tumor. c. Pretreatment specimen stained for RB showing robust nuclear staining in tumor. d. Post treatment specimen showing residual disease. (B) Representative case that responded to neoadjuvant chemotherapy. a. Pretreatment specimen stained with Hematoxylin/Eosin. b. Pretreatment specimen stained for p16ink4a expression showing robust tumor specific staining. c. Pretreatment specimen stained for RB showing lack of staining in the tumor tissue (stroma/leukocytes stain positive for RB). d. Post treatment specimen showing complete pathological response. (C) Bar graphs depicting the response frequency stratified by RB status (left panel) or p16ink4a levels (right panel). (D) Scatter plots showing the Miller-Payne Score of individual cases in the cohort. Cases were stratified by RB status (left panel) or p16ink4a levels (right panel). (E) Scatter plots showing the CPS of individual cases in the cohort. Cases were stratified by RB status (left panel) or p16ink4a levels (right panel).