Nora Sanchez

Oncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers in western countries, with a median survival of 6 months and an extremely low percentage of long-term surviving patients. KRAS mutations are known to be a driver event of PDAC, but targeting mutant KRAS has proved challenging. Targeting oncogene-driven signalling pathways is a clinically validated approach for several devastating diseases. Still, despite marked tumour shrinkage, the frequency of relapse indicates that a fraction of tumour cells survives shut down of oncogenic signalling. Here we explore the role of mutant KRAS in PDAC maintenance using a recently developed inducible mouse model of mutated Kras (KrasG12D, herein KRas) in a p53LoxP/WT background. We demonstrate that a subpopulation of dormant tumour cells surviving oncogene ablation (surviving cells) and responsible for tumour relapse has features of cancer stem cells and relies on oxidative phosphorylation for survival. Transcriptomic and metabolic analyses of surviving cells reveal prominent expression of genes governing mitochondrial function, autophagy and lysosome activity, as well as a strong reliance on mitochondrial respiration and a decreased dependence on glycolysis for cellular energetics. Accordingly, surviving cells show high sensitivity to oxidative phosphorylation inhibitors, which can inhibit tumour recurrence. Our integrated analyses illuminate a therapeutic strategy of combined targeting of the KRAS pathway and mitochondrial respiration to manage pancreatic cancer.

Yap1 activation enables bypass of oncogenic KRAS addiction in pancreatic cancer

Activating mutations in KRAS are among the most frequent events in diverse human carcinomas and are particularly prominent in human pancreatic ductal adenocarcinoma (PDAC). An inducible Kras(G12D)-driven mouse model of PDAC has established a critical role for sustained Kras(G12D) expression in tumor maintenance, providing a model to determine the potential for and the underlying mechanisms of Kras(G12D)-independent PDAC recurrence. Here, we show that some tumors undergo spontaneous relapse and are devoid of Kras(G12D) expression and downstream canonical MAPK signaling and instead acquire amplification and overexpression of the transcriptional coactivator Yap1. Functional studies established the role of Yap1 and the transcriptional factor Tead2 in driving Kras(G12D)-independent tumor maintenance. The Yap1/Tead2 complex acts cooperatively with E2F transcription factors to activate a cell cycle and DNA replication program. Our studies, along with corroborating evidence from human PDAC models, portend a novel mechanism of escape from oncogenic Kras addiction in PDAC.

Genetic Events That Limit the Efficacy of MEK and RTK Inhibitor Therapies in a Mouse Model of KRAS-Driven Pancreatic Cancer

Mutated KRAS (KRAS*) is a fundamental driver in the majority of pancreatic ductal adenocarcinomas (PDAC). Using an inducible mouse model of KRAS*-driven PDAC, we compared KRAS* genetic extinction with pharmacologic inhibition of MEK1 in tumor spheres and in vivo. KRAS* ablation blocked proliferation and induced apoptosis, whereas MEK1 inhibition exerted cytostatic effects. Proteomic analysis evidenced that MEK1 inhibition was accompanied by a sustained activation of the PI3K-AKT-MTOR pathway and by the activation of AXL, PDGFRa, and HER1-2 receptor tyrosine kinases (RTK) expressed in a large proportion of human PDAC samples analyzed. Although single inhibition of each RTK alone or plus MEK1 inhibitors was ineffective, a combination of inhibitors targeting all three coactivated RTKs and MEK1 was needed to inhibit proliferation and induce apoptosis in both mouse and human low-passage PDAC cultures. Importantly, constitutive AKT activation, which may mimic the fraction of AKT2-amplified PDAC, was able to bypass the induction of apoptosis caused by KRAS* ablation, highlighting a potential inherent resistance mechanism that may inform the clinical application of MEK inhibitor therapy. This study suggests that combinatorial-targeted therapies for pancreatic cancer must be informed by the activation state of each putative driver in a given treatment context. In addition, our work may offer explanative and predictive power in understanding why inhibitors of EGFR signaling fail in PDAC treatment and how drug resistance mechanisms may arise in strategies to directly target KRAS.

ALK: a tyrosine kinase target for cancer therapy.

The anaplastic lymphoma kinase (ALK) gene plays an important physiologic role in the development of the brain and can be oncogenically altered in several malignancies, including non-small-cell lung cancer (NSCLC) and anaplastic large cell lymphomas (ALCL). Most prevalent ALK alterations are chromosomal rearrangements resulting in fusion genes, as seen in ALCL and NSCLC. In other tumors, ALK copy-number gains and activating ALK mutations have been described. Dramatic and often prolonged responses are seen in patients with ALK alterations when treated with ALK inhibitors. Three of these—crizotinib, ceritinib, and alectinib—are now FDA approved for the treatment of metastatic NSCLC positive for ALK fusions. However, the emergence of resistance is universal. Newer ALK inhibitors and other targeting strategies are being developed to counteract the newly emergent mechanism(s) of ALK inhibitor resistance. This review outlines the recent developments in our understanding and treatment of tumors with ALK alterations.

Automated identification of molecular effects of drugs (AIMED)

INTRODUCTION Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support. OBJECTIVES To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains. METHODS We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts. RESULTS Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts. CONCLUSIONS Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development.

Personalized cancer therapy: A publicly available precision oncology resource

High-throughput genomic and molecular profiling of tumors is emerging as an important clinical approach. Molecular profiling is increasingly being used to guide cancer patient care, especially in advanced and incurable cancers. However, navigating the scientific literature to make evidence-based clinical decisions based on molecular profiling results is overwhelming for many oncology clinicians and researchers. The Personalized Cancer Therapy website (www.personalizedcancertherapy.org) was created to provide an online resource for clinicians and researchers to facilitate navigation of available data. Specifically, this resource can be used to help identify potential therapy options for patients harboring oncogenic genomic alterations. Herein, we describe how content on www.personalizedcancertherapy.org is generated and maintained. We end with case scenarios to illustrate the clinical utility of the website. The goal of this publicly available resource is to provide easily accessible information to a broad oncology audience, as this may help ease the information retrieval burden facing participants in the precision oncology field. Cancer Res; 77(21); e123-6. ©2017 AACR.

A feasibility study of returning clinically actionable somatic genomic alterations identified in a research laboratory

Purpose Molecular profiling performed in the research setting usually does not benefit the patients that donate their tissues. Through a prospective protocol, we sought to determine the feasibility and utility of performing broad genomic testing in the research laboratory for discovery, and the utility of giving treating physicians access to research data, with the option of validating actionable alterations in the CLIA environment. Experimental design 1200 patients with advanced cancer underwent characterization of their tumors with high depth hybrid capture sequencing of 201 genes in the research setting. Tumors were also tested in the CLIA laboratory, with a standardized hotspot mutation analysis on an 11, 46 or 50 gene platform. Results 527 patients (44%) had at least one likely somatic mutation detected in an actionable gene using hotspot testing. With the 201 gene panel, 945 patients (79%) had at least one alteration in a potentially actionable gene that was undetected with the more limited CLIA panel testing. Sixty-four genomic alterations identified on the research panel were subsequently tested using an orthogonal CLIA assay. Of 16 mutations tested in the CLIA environment, 12 (75%) were confirmed. Twenty-five (52%) of 48 copy number alterations were confirmed. Nine (26.5%) of 34 patients with confirmed results received genotype-matched therapy. Seven of these patients were enrolled onto genotype-matched targeted therapy trials. Conclusion Expanded cancer gene sequencing identifies more actionable genomic alterations. The option of CLIA validating research results can provide alternative targets for personalized cancer therapy.

Clinical Use of Precision Oncology Decision Support

PURPOSE Precision oncology is hindered by the lack of decision support for determining the functional and therapeutic significance of genomic alterations in tumors and relevant clinically available options. To bridge this knowledge gap, we established a Precision Oncology Decision Support (PODS) team that provides annotations at the alteration-level and subsequently determined if clinical decision-making was influenced. METHODS Genomic alterations were annotated to determine actionability based on a variants known or potential functional and/or therapeutic significance. The medical records of a subset of patients annotated in 2015 were manually reviewed to assess trial enrollment. A web-based survey was implemented to capture the reasons why genotype-matched therapies were not pursued. RESULTS PODS processed 1,669 requests for annotation of 4,084 alterations (2,254 unique) across 49 tumor types for 1,197 patients. 2,444 annotations for 669 patients included an actionable variant call: 32.5% actionable, 9.4% potentially, 29.7% unknown, 28.4% non-actionable. 66% of patients had at least one actionable/potentially actionable alteration. 20.6% (110/535) patients annotated enrolled on a genotype-matched trial. Trial enrolment was significantly higher for patients with actionable/potentially actionable alterations (92/333, 27.6%) than those with unknown (16/136, 11.8%) and non-actionable (2/66, 3%) alterations (p=0.00004). Actionable alterations in PTEN, PIK3CA, and ERBB2 most frequently led to enrollment on genotype-matched trials. Clinicians cited a variety of reasons why patients with actionable alterations did not enroll on trials. CONCLUSION Over half of alterations annotated were of unknown significance or non-actionable. Physicians were more likely to enroll a patient on a genotype-matched trial when an annotation supported actionability. Future studies are needed to demonstrate the impact of decision support on trial enrollment and oncologic outcomes.

Precision Oncology Decision Support: Current Approaches and Strategies for the Future

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patients tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719–31. ©2018 AACR.

Physician interpretation of genomic test results and treatment selection

Genomic testing is increasingly performed in oncology, but concerns remain regarding the clinicians ability to interpret results. In the current study, the authors sought to determine the agreement between physicians and genomic annotators from the Precision Oncology Decision Support (PODS) team at The University of Texas MD Anderson Cancer Center in Houston regarding actionability and the clinical use of test results.