Resistance to Immunotherapy in Gastric Cancer

Metastatic Gastric Cancer

This project seeks to analyze and define the mechanism (s) involved in the resistance to checkpoint therapy in metastatic GC patients. The investigators propose the use of a Next-Generation Sequencing (NGS) assay that involves 395 genes allowing us to define a specific molecular signature to characterize responder and non-responder patients to checkpoint therapy in combination with IHC analyses of specific factors. Such signature (s) could then be used to predict which individuals who might get the most benefit out of checkpoint therapy treatment. Analysis will be perfomed retrospectively using biopsies provided by mGC patients recruited at the Red de Salud UC treated with checkpoint therapy, the response of patients to treatment is evaluated by RECIST 1.1 criteria and thereby they are classified as responders or non-responders.

In Chile, gastric cancer (GC) is the leading cause of cancer death, killing 17.8 in 100,000 people/year. Most GC cases are diagnosed at advance stage, indeed 70% of diagnosed patients are stage IV classified as metastatic GC (mGC). Median survival rates with standard chemotherapy is \<6 months. In recent years the development of immune checkpoint inhibitors that activate a sustained T-cell response has revolutionized oncology treatments. Indeed, humanized monoclonal antibodies against the CTLA4 and PD1/PDL1 pathways treatments, a strategy commonly called checkpoint therapy has demonstrated effective against many malignancies. Despite this, a substantial percentage of patients (\ 60%) remain unresponsive or display non-significant clinical responses to these regimes. Previous studies suggest that cancer cells employ a variety of strategies to become resistant to these therapies, these can include: existence of genomic alterations in their mutational landscape that cause immune suppression, inhibition of the Interferon (IFN) gamma pathway (among others), upregulation of alternative immune checkpoints (other than CTLA4 or PD1/PDL1) and upregulation of the Indoleamine 2,3-DyOxygenase (IDO) enzyme. HYPOTHESIS: Metastatic GC patients, whose tumor microenvironment presents a specific mutational landscape, increased levels of alternative immune co-inhibitors and enhanced IDO expression, fail (determined by RECIST 1.1) in response to checkpoint therapy. In order to validate this hypothesis, the investigators will: 1. Retrospectively collect samples derived from mGC patients who received checkpoint therapy and clinical data including RECIST 1.1 (Response Evaluation Criteria In Solid Tumors) to classify them as responders or non-responders to checkpoint therapy. 2. Obtain RNA/DNA samples from stored patient biopsies in order to perform a comprehensive analysis of mutational landscape using Next Generation Sequencing (NGS) methods. 3. Analyze tissue samples from patients by immunohistochemistry to evaluate expression of the IDO enzyme and the levels of alternative immune co-inhibitors. Therefore, this proposal will use samples derived from mGC patients who received checkpoint therapy at the Cancer center of the Clinical Hospital at the Pontificia Universidad Catolica de Chile. Biopsies, paraffin embedded samples and full clinical history are available for analysis. The team of investigators is composed by both physicians (MD) and molecular biologists (PhD). Dr. Garrido and clinical coordinator Dr. Retamal will select patients, obtain cancer samples and perform correlations with treatment outcome and coordinate the immunohistochemistry. The laboratory of Dr. Owen (co-investigator in this proposal with Dr. Pinto) has vast experience in the field of molecular oncology and will perform the molecular analysis. The overall goal of this proposal is to elucidate the molecular mechanism(s) involved in the resistance to CTLA4/PD1/PDL1 targeted checkpoint therapy in mGC patients. The relevance lies in the high prevalence and mortality rates of this disease in Chile. Finally, its significance stems from the potential discovery and characterization diagnostic companion biomarkers that could allow stratification in order to identify mGC patients that could get the most benefit from checkpoint therapy regimes.

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