Fraser Symmans

Phase II study of tariquidar, a selective P-glycoprotein inhibitor, in patients with chemotherapy-resistant, advanced breast carcinoma

The primary objective of this study was to determine whether addition of the selective P‐glycoprotein (P‐gp) inhibitor tariquidar (XR9576) to chemotherapy could induce an objective tumor response in patients who previously were resistant to the same agents. The secondary objectives were to evaluate P‐gp expression by immunohistochemistry (IHC), to determine functional activity of the P‐gp transporter before and after administration of tariquidar with serial technetium‐99m (99mTc)‐sestamibi scans, and to correlate those parameters with clinical response.

Evaluation of a 30-Gene Paclitaxel, Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy Response Predictor in a Multicenter Randomized Trial in Breast Cancer

Purpose: We examined in a prospective, randomized, international clinical trial the performance of a previously defined 30-gene predictor (DLDA-30) of pathologic complete response (pCR) to preoperative weekly paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide (T/FAC) chemotherapy, and assessed if DLDA-30 also predicts increased sensitivity to FAC-only chemotherapy. We compared the pCR rates after T/FAC versus FACx6 preoperative chemotherapy. We also did an exploratory analysis to identify novel candidate genes that differentially predict response in the two treatment arms. Experimental Design: Two hundred and seventy-three patients were randomly assigned to receive either weekly paclitaxel × 12 followed by FAC × 4 (T/FAC, n = 138), or FAC × 6 (n = 135) neoadjuvant chemotherapy. All patients underwent a pretreatment fine-needle aspiration biopsy of the tumor for gene expression profiling and treatment response prediction. Results: The pCR rates were 19% and 9% in the T/FAC and FAC arms, respectively (P < 0.05). In the T/FAC arm, the positive predictive value (PPV) of the genomic predictor was 38% [95% confidence interval (95% CI), 21-56%], the negative predictive value was 88% (95% CI, 77-95%), and the area under the receiver operating characteristic curve (AUC) was 0.711. In the FAC arm, the PPV was 9% (95% CI, 1-29%) and the AUC was 0.584. This suggests that the genomic predictor may have regimen specificity. Its performance was similar to a clinical variable–based predictor nomogram. Conclusions: Gene expression profiling for prospective response prediction was feasible in this international trial. The 30-gene predictor can identify patients with greater than average sensitivity to T/FAC chemotherapy. However, it captured molecular equivalents of clinical phenotype. Next-generation predictive markers will need to be developed separately for different molecular subsets of breast cancers. Clin Cancer Res; 16(21); 5351–61. ©2010 AACR.

Multifactorial Approach to Predicting Resistance to Anthracyclines

PURPOSE Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER) -negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-α (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. PATIENTS AND METHODS The TOP trial included 149 patients, 139 of whom were evaluable for response prediction analyses. The primary end point was pathologic complete response (pCR). TOP2A and gene expression profiles were evaluated using pre-epirubicin biopsies. Gene expression data from ER-negative samples of the EORTC (European Organisation for Research and Treatment of Cancer) 10994/BIG (Breast International Group) 00-01 and MDACC (MD Anderson Cancer Center) 2003-0321 neoadjuvant trials were used for validation purposes. RESULTS A pCR was obtained in 14% of the evaluable patients in the TOP trial. TOP2A amplification, but not protein overexpression, was significantly associated with pCR (P ≤ .001 v P ≤ .33). We developed an anthracycline-based score (A-Score) combining three signatures: a TOP2A gene signature and two previously published signatures related to tumor invasion and immune response. The A-Score was characterized by a high negative predictive value ([NPV]; NPV, 0.98; 95% CI, 0.90 to 1.00) overall and in the human epidermal growth factor receptor 2 (HER2) -negative and HER2-positive subpopulations. Its performance was independently confirmed in the anthracycline-based arms of the two validation trials (BIG 00-01: NPV, 0.83; 95% CI, 0.64 to 0.94 and MDACC 2003-0321: NPV, 1.00; 95% CI, 0.80 to 1.00). CONCLUSION Given its high NPV, the A-Score could become, if further validated, a useful clinical tool to identify those patients who do not benefit from anthracyclines and could therefore be spared the non-negligible adverse effects.

Identification of Prognosis-Relevant Subgroups in Patients with Chemoresistant Triple Negative Breast Cancer

Purpose: Patients with triple-negative breast cancer (TNBC) and residual disease after neoadjuvant chemotherapy generally have worse outcome; however, some patients with residual tumor after neoadjuvant chemotherapy do not relapse. We hypothesize that there are subgroups of patients with chemoresistant TNBC with different prognosis. Experimental Design: Forty-nine chemoresistant cases from 111 patients with TNBC treated with neoadjuvant chemotherapy (M.D. Anderson Cancer Center, Houston, TX) constituted the discovery cohort, and 25 chemoresistant samples from 47 neoadjuvant chemotherapy-treated TNBC (The Methodist Hospital, Houston, TX) were chosen for validation. Extended validation was carried out in 269 operable TNBC predicted to be chemoresistant by expression pattern from published datasets. Results: We established a seven-gene prognostic signature using dChip and gene set enrichment analyses. In the independent validation cohort, the classifier predicted correctly with positive predictive value of 75.0% and negative predictive value (i.e., relapse-free survival; RFS) of 76.9% at 3 years. Those predicted to relapse had a HR of 4.67 [95% confidence interval (CI): 1.27–17.15] for relapse in 3 years. In extended validation, patients predicted not to relapse exhibited 3-year RFS of 78.9%, whereas the 3-year RFS was 48.5% for patients predicted to relapse, with HR of 2.61 (95% CI: 1.52–4.49). The TNBC subgroup that predicted to have relatively favorable prognosis was characterized by high expression of “luminal-like” genes [androgen-receptor (AR) and GATA3], whereas the subgroup with worse prognosis was characterized by expression of cancer stem-cell markers. Conclusion: We developed a clinically relevant signature for patients with chemoresistant TNBC. For these women, new therapeutic strategies like targeting AR activation or cancer stem cells may need to be developed. Clin Cancer Res; 19(10); 2723–33. ©2013 AACR.

Mitotic Deregulation by Survivin in ErbB2-Overexpressing Breast Cancer Cells Contributes to Taxol Resistance

Purpose: Taxol resistance remains a major obstacle to improve the benefit of breast cancer patients. Here, we studied whether overexpression of ErbB2 may lead to mitotic deregulation in breast cancer cells via up-regulation of survivin that confers Taxol resistance. Experimental Design: ErbB2-overexpressing and ErbB2-low-expressing breast cancer cell lines were used to compare their mitotic exit rate, survivin expression level, and apoptosis level in response to Taxol. Survivin was then down-regulated by antisense oligonucleotides to evaluate its contribution to mitotic exit and Taxol resistance in ErbB2-overexpressing breast cancer cells. At last, specific PI3K/Akt and Src inhibitors were used to investigate the involvement of these two pathways in ErbB2-mediated survivin up-regulation and Taxol resistance. Results: We found that ErbB2-overexpressing cells expressed higher levels of survivin in multiple breast cancer cell lines and patient samples. ErbB2-overexpressing cells exited M phase faster than ErbB2-low-expressing cells, which correlated with the increased resistance to Taxol-induced apoptosis. Down-regulation of survivin by antisense oligonucleotide delayed mitotic exit of ErbB2-overexpressing cells and also sensitized ErbB2-overexpressing cells to Taxol-induced apoptosis. Moreover, ErbB2 up-regulated survivin at translational level and PI3K/Akt and Src activation are involved. In addition, combination treatment of Taxol with PI3K/Akt and Src inhibitor led to increased apoptosis in ErbB2-overexpressing breast cancer cells than single treatment. Conclusions: Survivin up-regulation by ErbB2 is a critical event in ErbB2-mediated faster mitotic exit and contributes to Taxol resistance.

International Expert Consensus on Primary Systemic Therapy in the Management of Early Breast Cancer: Highlights of the Fifth Symposium on Primary Systemic Therapy in the Management of Operable Breast Cancer, Cremona, Italy (2013).

Expert consensus-based recommendations regarding key issues in the use of primary (or neoadjuvant) systemic treatment (PST) in patients with early breast cancer are a valuable resource for practising oncologists. PST remains a valuable therapeutic approach for the assessment of biological antitumor activity and clinical efficacy of new treatments in clinical trials. Neoadjuvant trials provide endpoints, such as pathological complete response (pCR) to treatment, that potentially translate into meaningful improvements in overall survival and disease-free survival. Neoadjuvant trials need fewer patients and are less expensive than adjuvant trial, and the endpoint of pCR is achieved in months, rather than years. For these reasons, the neoadjuvant setting is ideal for testing emerging targeted therapies in early breast cancer. Although pCR is an early clinical endpoint, its role as a surrogate for long-term outcomes is the key issue. New and better predictors of treatment efficacy are needed to improve treatment and outcomes. After PST, accurate management of post-treatment residual disease is mandatory. The surgery of the sentinel lymph-node could be an acceptable option to spare the axillary dissection in case of clinical negativity (N0) of the axilla at the diagnosis and/or after PST. No data exists yet to support the modulation of the extent of locoregional radiation therapy on the basis of the response attained after PST although trials are underway.

The Neoadjuvant Model is Still the Future for Drug Development in Breast Cancer

The many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDAs draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach. Clin Cancer Res; 21(13); 2911–5. ©2015 AACR.

Gene Expression, Molecular Class Changes, and Pathway Analysis after Neoadjuvant Systemic Therapy for Breast Cancer

Purpose: To examine gene expression differences between pre- and post-neoadjuvant systemic therapy (NST) specimens of breast cancers and identify biologic changers that may lead to new therapeutic insights. Methods: Gene expression data from prechemotherapy fine needle aspiration specimens were compared with resected residual cancers in 21 patients after 4 to 6 months of NST. We removed stroma-associated genes to minimize confounding effects. PAM50 was used to assign molecular class. Paired t test and gene set analysis were used to identify differentially expressed genes and pathways. Results: The ER and HER2 status based on mRNA expression remained stable in all but two cases, and there were no changes in proliferation metrics (Ki67 and proliferating cell nuclear antigen expression). Molecular class changed in 8 cases (33.3%), usually to normal-like class, which was associated with low residual cancer cell cellularity. The expression of 200 to 600 probe sets changed between baseline and post-NST samples. In basal-like cancers, pathways driven by increased expression of phosphoinositide 3-kinase, small G proteins, and calmodulin-dependent protein kinase II and energy metabolism were enriched, whereas immune cell–derived and the sonic hedgehog pathways were depleted in residual cancer. In non–basal-like breast cancers, notch signaling and energy metabolism (e.g., fatty acid synthesis) were enriched and sonic hedgehog signaling and immune-related pathways were depleted in residual cancer. There was no increase in epithelial–mesenchymal transition or cancer stem cell signatures. Conclusions: Our data indicate that energy metabolism related processes are upregulated and immune-related signals are depleted in residual cancers. Targeting these biologic processes may represent promising adjuvant treatment strategies for patients with residual cancer. Clin Cancer Res; 18(4); 1109–19. ©2012 AACR.

Assessing tumor-infiltrating lymphocytes in solid tumors: a practical review for pathologists and proposal for a standardized method from the International Immuno-Oncology Biomarkers Working Group: part 2: TILs in melanoma, gastrointestinal tract carcinomas, non-small cell lung carcinoma and mesothelioma, endometrial and ovarian carcinomas, squamous cell carcinoma of the head and neck, genitourinary carcinomas, and primary brain Tumors

Assessment of the immune response to tumors is growing in importance as the prognostic implications of this response are increasingly recognized, and as immunotherapies are evaluated and implemented in different tumor types. However, many different approaches can be used to assess and describe the immune response, which limits efforts at implementation as a routine clinical biomarker. In part 1 of this review, we have proposed a standardized methodology to assess tumor-infiltrating lymphocytes (TILs) in solid tumors, based on the International Immuno-Oncology Biomarkers Working Group guidelines for invasive breast carcinoma. In part 2 of this review, we discuss the available evidence for the prognostic and predictive value of TILs in common solid tumors, including carcinomas of the lung, gastrointestinal tract, genitourinary system, gynecologic system, and head and neck, as well as primary brain tumors, mesothelioma and melanoma. The particularities and different emphases in TIL assessment in different tumor types are discussed. The standardized methodology we propose can be adapted to different tumor types and may be used as a standard against which other approaches can be compared. Standardization of TIL assessment will help clinicians, researchers and pathologists to conclusively evaluate the utility of this simple biomarker in the current era of immunotherapy.

Development of Pharmacogenomic Markers to Select Preoperative Chemotherapy for Breast Cancer

Individualized selection of the most effective adjuvant (or neoadjuvant) chemotherapy for breast cancer based on the molecular characteristics of the tumor could improve the risk:benefit ratio of current therapies. It could also streamline the development of new regimens for those who are unlikely to benefit from existing drugs. It is expected that combinations of markers will be more informative to predict response than any single gene and may yield regimen-specific predictors. Novel molecular analytical tools, particularly transcriptional profiling, provide a method to test this hypothesis. Several small exploratory studies have shown encouraging results. This article reviews recent progress in this field including experience from the breast cancer pharmacogenomic marker discovery program at the Nellie B. Connally Breast Center of the University of Texas M. D. Anderson Cancer Center. This manuscript is based on a presentation that was given during the Presidential Symposium of the annual meeting of the Japanese Breast Cancer Society in 2004.