Yekaterina B. Khotskaya

EGFR modulates microRNA maturation in response to hypoxia through phosphorylation of AGO2

MicroRNAs (miRNAs) are generated by two-step processing to yield small RNAs that negatively regulate target gene expression at the post-transcriptional level. Deregulation of miRNAs has been linked to diverse pathological processes, including cancer. Recent studies have also implicated miRNAs in the regulation of cellular response to a spectrum of stresses, such as hypoxia, which is frequently encountered in the poorly angiogenic core of a solid tumour. However, the upstream regulators of miRNA biogenesis machineries remain obscure, raising the question of how tumour cells efficiently coordinate and impose specificity on miRNA expression and function in response to stresses. Here we show that epidermal growth factor receptor (EGFR), which is the product of a well-characterized oncogene in human cancers, suppresses the maturation of specific tumour-suppressor-like miRNAs in response to hypoxic stress through phosphorylation of argonaute 2 (AGO2) at Tyr 393. The association between EGFR and AGO2 is enhanced by hypoxia, leading to elevated AGO2-Y393 phosphorylation, which in turn reduces the binding of Dicer to AGO2 and inhibits miRNA processing from precursor miRNAs to mature miRNAs. We also identify a long-loop structure in precursor miRNAs as a critical regulatory element in phospho-Y393-AGO2-mediated miRNA maturation. Furthermore, AGO2-Y393 phosphorylation mediates EGFR-enhanced cell survival and invasiveness under hypoxia, and correlates with poorer overall survival in breast cancer patients. Our study reveals a previously unrecognized function of EGFR in miRNA maturation and demonstrates how EGFR is likely to function as a regulator of AGO2 through novel post-translational modification. These findings suggest that modulation of miRNA biogenesis is important for stress response in tumour cells and has potential clinical implications.

Targeting TRK family proteins in cancer

&NA; The tropomyosin receptor kinase (TRK) family includes TRKA, TRKB, and TRKC proteins, which are encoded by NTRK1, NTRK2 and NTRK3 genes, respectively. Binding of neurotrophins to TRK proteins induces receptor dimerization, phosphorylation, and activation of the downstream signaling cascades via PI3K, RAS/MAPK/ERK, and PLC‐gamma. TRK pathway aberrations, including gene fusions, protein overexpression, and single nucleotide alterations, have been implicated in the pathogenesis of many cancer types, with NTRK gene fusions being the most well validated oncogenic events to date. Although the NTRK gene fusions are infrequent in most cancer types, certain rare tumor types are predominately driven by these events. Conversely, in more common histologies, such as lung and colorectal cancers, prevalence of the NTRK fusions is well below 5%. Selective inhibition of TRK signaling may therefore be beneficial among patients whose tumors vary in histologies, but share underlying oncogenic NTRK gene alterations. Currently, several TRK‐targeting compounds are in clinical development. The ongoing Phase 2 trials with entrectinib and LOXO‐101, two of the leading TRK inhibitors, are designed as ‘basket trials’, inclusive of patients whose tumors harbor NTRK gene fusions, independent of histology. Additional Phase 1 studies of other TRK inhibitors, including MGCD516, PLX7486, DS‐6051b, and TSR‐011, are underway. Interim data examining NTRK‐rearranged tumors treated with entrectinib or LOXO‐101 demonstrate encouraging activity, with patients achieving rapid and durable responses. Consequently, both drugs have achieved orphan designation from regulatory agencies, and efforts are underway to further expedite their development.

Inhibition of type I insulin-like growth factor receptor signaling attenuates the development of breast cancer brain metastasis.

Brain metastasis is a common cause of mortality in cancer patients, yet potential therapeutic targets remain largely unknown. The type I insulin-like growth factor receptor (IGF-IR) is known to play a role in the progression of breast cancer and is currently being investigated in the clinical setting for various types of cancer. The present study demonstrates that IGF-IR is constitutively autophosphorylated in brain-seeking breast cancer sublines. Knockdown of IGF-IR results in a decrease of phospho-AKT and phospho-p70s6k, as well as decreased migration and invasion of MDA-MB-231Br brain-seeking cells. In addition, transient ablation of IGFBP3, which is overexpressed in brain-seeking cells, blocks IGF-IR activation. Using an in vivo experimental brain metastasis model, we show that IGF-IR knockdown brain-seeking cells have reduced potential to establish brain metastases. Finally, we demonstrate that the malignancy of brain-seeking cells is attenuated by pharmacological inhibition with picropodophyllin, an IGF-IR-specific tyrosine kinase inhibitor. Together, our data suggest that the IGF-IR is an important mediator of brain metastasis and its ablation delays the onset of brain metastases in our model system.

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.

Aurora A kinase activates YAP signaling in triple-negative breast cancer

The Yes-associated protein (YAP) is an effector that transduces the output of the Hippo pathway to transcriptional modulation. Considering the role of YAP in cancers, this protein has emerged as a key node in malignancy development. In this study, we determined that Aurora A kinase acts as a positive regulator for YAP-mediated transcriptional machinery. Specifically, YAP associates with Aurora A predominantly in the nucleus. Activation of Aurora A can impinge on YAP activity through direct phosphorylation. Moreover, aberrant expression of YAP and Aurora A signaling is highly correlated with triple-negative breast cancer (TNBC). We herein provide evidence to establish the functional relevance of this newly discovered regulatory axis in TNBC.

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.