Abstract SY36-01: Optimizing neoadjuvant therapy prior to surgery: Biomarker and target discovery

Surgery is the oldest type of cancer therapy and remains at the forefront of modern oncology because of its effectiveness in the treatment of many types of cancer. In most patients presenting with localized cancer, surgical advances over the past 30 years offer effective local control of the lesion, and in many this translates to cancer cure. However, in a number of patients tumor recurrence, commonly at distant sites rather than at the local site, occurs and is commonly associated with a fatal outcome. Future surgery includes using progressively less invasive approaches to accomplish local tumor control and combining this efficacious intervention with other approaches in order to reduce metastatic recurrence and thus improve overall cure rates. With surgery as the “curative" or "primary” modality, therapies that enhance the outcome of surgery are termed neoadjuvant or adjuvant when delivered before or after surgery, respectively. Here we discuss neoadjuvant chemotherapy (NAC) prior to bladder cancer surgery as a model applicable to other cancer types of how this is being used to develop biomarkers of therapy prediction while identifying novel therapeutic targets. Bladder cancer is the second most common cancer of the genitourinary tract, and primary treatment consists of transurethral resection of the tumor. At diagnosis, 30% of patients present with muscle-invasive disease (MIBC), in which case standard of care consists of removal of the bladder (radical cystectomy; RC) and pelvic lymph node dissection. Despite this extensive surgery, 5-year survival rates do not exceed 60%, due to the presence of occult nodal or visceral micrometastases at the time of surgery. The use of platinum-based NAC has improved outcome in MIBC patients, with the most commonly used regimen being gemcitabine/cisplatinum. The benefit of NAC is a reduction of 14% in the risk of death. Importantly, pathologic complete response (i.e., stage pT0) at RC is associated with an excellent 5-year survival rate of 85%, but only 25% of patients experience this. The remaining 75% of patients are exposed to complications such as neutropenia (70-80%), neutropenic sepsis (2-14%), mucositis (1-22%), and death (1-3%), without an improved outcome. These patients are also subjected to a delay in RC, which might negatively affect their prognosis. Given this situation, the search for tools that can predict which patients benefit from NAC has been a focus of investigation. The NAC approach has two major advantages for biomarker discovery: 1) robust surrogate outcomes of survival (i.e., stage pT0 at RC) and 2) ability to examine pre- and post samples collected during standard of care, which greatly facilitates biomarker discovery both practically and scientifically. Gene expression analysis has been used in an attempt to predict response to NAC. An early study has shown that gene expression can be used to build predictive models of the response to a single drug as well as to combination regimens. In this study, baseline gene expression profiles from a panel of 40 bladder cancer cell lines were used to develop chemotherapy response prediction models, which showed highly significant concordance with empirical patient responses. In another study by Takata and colleagues, gene expression was measured in tumor samples from 27 patients with MIBC prior to neoadjuvant treatment with methotrexate vinblastine, Adriamycin, and cisplatin (MVAC) chemotherapy. The authors identified a set of 50 genes that significantly differed between 14 responders and 13 nonresponders. The same investigators have subsequently validated their predictive signature on 22 additional patients, showing that their gene expression signature could predict MVAC response in 19 out of 22 cases. Als and colleagues analyzed gene expression in 30 patients with locally advanced or metastatic bladder cancer, identifying 55 genes that proved to be expressed at lower levels in patients with longer survival. Two genes that discriminated patients by their survival—EMMPRIN and survivin—were further investigated by immunostaining, which showed they were significantly associated with overall survival, with double-positive tumors exhibiting a response rate of 27% and double-negative tumors exhibiting a response rate of 82%. The use of molecular profiles to predict treatment outcomes requires a training dataset to identify the profile and a second independent clinical trial to validate it. This strategy is useful when patient material is available but usually cannot be used to develop response biomarkers to regimens before clinical studies are carried out. A new strategy was proposed by our group that extrapolates in vitro drug response data to make in vivo predictions based on the gene expression profiles that are common to both. This approach, called COXEN (COeXpression ExtrapolatioN), uses expression microarray data as a “Rosetta stone” for translating between drug activities in a cancer cell line panel and drug activities in a set of clinical tumors. Using a variety of cancer cell lines and their gene expression profiles and drug sensitivity, Lee et al. used COXEN to predict sensitivity to cisplatin and paclitaxel chemotherapies in bladder cancer cell lines and sensitivity to docetaxel and tamoxifen in breast cancer patients, and also demonstrate the utility of COXEN in drug screening. This approach was used to identify a promising new agent in bladder cancer, called C1311, while predicting the response of bladder cancer patients to chemotherapy both in the neoadjuvant and treatment settings. In 2011, next-generation sequencing (NGS) began identifying mutations in urothelial bladder cancer. This first breakthrough study was followed by several others, including work by The Cancer Genome Atlas (TCGA), which have enabled comprehensive cataloguing of genomic alterations. Given that such alterations number in the hundreds, evaluating their functional impact individually is challenging. Still, evaluating their function is absolutely necessary if we are to translate sequencing data into novel avenues for therapeutic intervention. Given this need, we developed and implemented a high throughput strategy that tests the hypothesis that some of these alterations are indeed loss of function in tumor growth suppressors. We tabulated gene alterations discovered by next-generation sequencing in bladder cancer and employed RNA interference (RNAi)–based gene depletion to study the impact of gene expression on tumor phenotypes in vitro and in vivo. This led to the functional identification of a number of novel tumor suppressors and promoters. Similar experiments with overexpression gene libraries were carried out to define genes whose overexpression drives tumor progression and could then be considered for development as drug targets. This approach provides a novel framework for the efficient functional evaluation of hundreds of genomic alterations found in cancer and allows us to define those that are drivers rather than passengers in tumor growth. In addition, it can also be applied to define which RNA and DNA gene alterations found to be associated with drug resistance in patients are functional drivers of this phenotype. These could then constitute targets of second-line drug therapy. Two recent studies have used NGS to explore the genomic landscape of chemotherapy-resistant urothelial carcinoma. The first study performed whole-exome sequencing on pretreatment tumor and germline DNA from patients with muscle-invasive urothelial carcinoma who received neoadjuvant cisplatin-based chemotherapy followed by RC to identify somatic mutations that occurred preferentially in chemotherapy responders. The authors found ERCC2, a nucleotide excision repair gene, to be the only significantly mutated gene enriched in the cisplatin responders compared with nonresponders. The second study performed whole-exome sequencing and clonality analysis of bladder cancers collected before and after chemotherapy. Analysis of these data indicated that chemotherapy-treated bladder cancer is characterized by intrapatient mutational heterogeneity and that such chemotherapy-treated urothelial carcinoma is enriched with clonal mutations involving L1 cell adhesion molecule and integrin signaling pathways. Both studies provide new perspectives on the mechanisms and genes driving chemotherapy resistance and possible avenues of overcoming this. In conclusion, surgery, the oldest type of cancer therapy, when used in combination with systemic therapy guided by discoveries made with molecular tools, promises to not only advance our understanding of cancer but also lead to a quantum improvement in patient outcome. There is every expectation that, given their effects on metastatic disease, the use of neoadjuvant and adjuvant immunotherapy with surgery will also have a significant impact and can be studied using the same tools described here. Citation Format: Dan Theodorescu. Optimizing neoadjuvant therapy prior to surgery: Biomarker and target discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr SY36-01. doi:10.1158/1538-7445.AM2017-SY36-01