Yvonne Y. Li

Adaptive resistance to therapeutic PD-1 blockade is associated with upregulation of alternative immune checkpoints

Despite compelling antitumour activity of antibodies targeting the programmed death 1 (PD-1): programmed death ligand 1 (PD-L1) immune checkpoint in lung cancer, resistance to these therapies has increasingly been observed. In this study, to elucidate mechanisms of adaptive resistance, we analyse the tumour immune microenvironment in the context of anti-PD-1 therapy in two fully immunocompetent mouse models of lung adenocarcinoma. In tumours progressing following response to anti-PD-1 therapy, we observe upregulation of alternative immune checkpoints, notably T-cell immunoglobulin mucin-3 (TIM-3), in PD-1 antibody bound T cells and demonstrate a survival advantage with addition of a TIM-3 blocking antibody following failure of PD-1 blockade. Two patients who developed adaptive resistance to anti-PD-1 treatment also show a similar TIM-3 upregulation in blocking antibody-bound T cells at treatment failure. These data suggest that upregulation of TIM-3 and other immune checkpoints may be targetable biomarkers associated with adaptive resistance to PD-1 blockade.

Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors.

BackgroundAdenocarcinomas of the tongue are rare and represent the minority (20 to 25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment.ResultsIn the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. There were 1,078 genes that exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations, administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumors and 9 new somatic protein coding mutations. The observed mutations and amplifications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways.ConclusionsWe conclude that complete genomic characterization of a rare tumor has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.

cisRED: a database system for genome-scale computational discovery of regulatory elements.

We describe cisRED, a database for conserved regulatory elements that are identified and ranked by a genome-scale computational system (). The database and high-throughput predictive pipeline are designed to address diverse target genomes in the context of rapidly evolving data resources and tools. Motifs are predicted in promoter regions using multiple discovery methods applied to sequence sets that include corresponding sequence regions from vertebrates. We estimate motif significance by applying discovery and post-processing methods to randomized sequence sets that are adaptively derived from target sequence sets, retain motifs with p-values below a threshold and identify groups of similar motifs and co-occurring motif patterns. The database offers information on atomic motifs, motif groups and patterns. It is web-accessible, and can be queried directly, downloaded or installed locally.

Drug repositioning for personalized medicine

Human diseases can be caused by complex mechanisms involving aberrations in numerous proteins and pathways. With recent advances in genomics, elucidating the molecular basis of disease on a personalized level has become an attainable goal. In many cases, relevant molecular targets will be identified for which approved drugs already exist, and the potential repositioning of these drugs to a new indication can be investigated. Repositioning is an accelerated route for drug discovery because existing drugs have established clinical and pharmacokinetic data. Personalized medicine and repositioning both aim to improve the productivity of current drug discovery pipelines, which expend enormous time and cost to develop new drugs, only to have them fail in clinical trials because of lack of efficacy or toxicity. Here, we discuss the current state of research in these two fields, focusing on recent large-scale efforts to systematically find repositioning candidates and elucidate individual disease mechanisms in cancer. We also discuss scenarios in which personalized drug repositioning could be particularly rewarding, such as for diseases that are rare or have specific mutations, as well as current challenges in this field. With an increasing number of drugs being approved for rare cancer subtypes, personalized medicine and repositioning approaches are poised to significantly alter the way we diagnose diseases, infer treatments and develop new drugs.

STK11/LKB1 Deficiency Promotes Neutrophil Recruitment and Proinflammatory Cytokine Production to Suppress T-cell Activity in the Lung Tumor Microenvironment

STK11/LKB1 is among the most commonly inactivated tumor suppressors in non-small cell lung cancer (NSCLC), especially in tumors harboring KRAS mutations. Many oncogenes promote immune escape, undermining the effectiveness of immunotherapies, but it is unclear whether the inactivation of tumor suppressor genes, such as STK11/LKB1, exerts similar effects. In this study, we investigated the consequences of STK11/LKB1 loss on the immune microenvironment in a mouse model of KRAS-driven NSCLC. Genetic ablation of STK11/LKB1 resulted in accumulation of neutrophils with T-cell-suppressive effects, along with a corresponding increase in the expression of T-cell exhaustion markers and tumor-promoting cytokines. The number of tumor-infiltrating lymphocytes was also reduced in LKB1-deficient mouse and human tumors. Furthermore, STK11/LKB1-inactivating mutations were associated with reduced expression of PD-1 ligand PD-L1 in mouse and patient tumors as well as in tumor-derived cell lines. Consistent with these results, PD-1-targeting antibodies were ineffective against Lkb1-deficient tumors. In contrast, treating Lkb1-deficient mice with an IL6-neutralizing antibody or a neutrophil-depleting antibody yielded therapeutic benefits associated with reduced neutrophil accumulation and proinflammatory cytokine expression. Our findings illustrate how tumor suppressor mutations can modulate the immune milieu of the tumor microenvironment, and they offer specific implications for addressing STK11/LKB1-mutated tumors with PD-1-targeting antibody therapies.

Genomic Analysis of Metastatic Cutaneous Squamous Cell Carcinoma

Purpose: A rare 5% of cutaneous squamous cell carcinomas (cSCC) metastasize, lack FDA-approved therapies, and carry a poor prognosis. Our aim was to identify recurrent genomic alterations in this little-studied population of metastatic cSCCs. Experimental Design: We performed targeted sequencing of 504 cancer-associated genes on lymph node metastases in 29 patients with cSCC and identified mutations and somatic copy-number alterations associated with metastatic cSCC. We determined significantly mutated, deleted, and amplified genes and associated genomic alterations with clinical variables. Results: The cSCC genome is heterogeneous with widely varying numbers of genomic alterations and does not appear to be associated with human papillomavirus. We found previously identified recurrently altered genes (TP53, CDKN2A, NOTCH1/2) but also a wide spectrum of oncogenic mutations affecting RAS/RTK/PI3K, squamous differentiation, cell cycle, and chromatin remodeling pathway genes. Specific mutations in known oncogenic drivers and pathways were correlated with inferior patient outcomes. Our results suggest potential therapeutic targets in metastatic cSCC, including PIK3CA, FGFR3, BRAF, and EGFR, similar to those reported in SCCs of the lung and head and neck, suggesting that clinical trials could be developed to accrue patients with SCCs from multiple sites of origin. Conclusions: We have genomically characterized a rare cohort of 29 metastatic cSCCs and identified a diverse array of oncogenic alterations that can guide future studies of this disease. Clin Cancer Res; 21(6); 1447–56. ©2015 AACR.

A Computational Approach to Finding Novel Targets for Existing Drugs

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-targets associated disease, added insight into the drugs mechanism of action, and added insight into the drugs side effects.

LKB1 loss links serine metabolism to DNA methylation and tumorigenesis

Intermediary metabolism generates substrates for chromatin modification, enabling the potential coupling of metabolic and epigenetic states. Here we identify a network linking metabolic and epigenetic alterations that is central to oncogenic transformation downstream of the liver kinase B1 (LKB1, also known as STK11) tumour suppressor, an integrator of nutrient availability, metabolism and growth. By developing genetically engineered mouse models and primary pancreatic epithelial cells, and employing transcriptional, proteomics, and metabolic analyses, we find that oncogenic cooperation between LKB1 loss and KRAS activation is fuelled by pronounced mTOR-dependent induction of the serine–glycine–one-carbon pathway coupled to S-adenosylmethionine generation. At the same time, DNA methyltransferases are upregulated, leading to elevation in DNA methylation with particular enrichment at retrotransposon elements associated with their transcriptional silencing. Correspondingly, LKB1 deficiency sensitizes cells and tumours to inhibition of serine biosynthesis and DNA methylation. Thus, we define a hypermetabolic state that incites changes in the epigenetic landscape to support tumorigenic growth of LKB1-mutant cells, while resulting in potential therapeutic vulnerabilities.

Genomic Landscape of Human Papillomavirus–Associated Cancers

Recent next-generation sequencing studies have generated a comprehensive overview of the genomic landscape of human papillomavirus (HPV)–associated cancers. This review summarizes these findings to provide insight into the tumor biology of these cancers and potential therapeutic opportunities for HPV-driven malignancies. In addition to the tumorigenic properties of the HPV oncoproteins, integration of HPV DNA into the host genome is suggested to be a driver of the neoplastic process. Integration may confer a growth and survival advantage via enhanced expression of viral oncoproteins, alteration of critical cellular genes, and changes in global promoter methylation and transcription. Alteration of cellular genes may lead to loss of function of tumor suppressor genes, enhanced oncogene expression, loss of function of DNA repair genes, or other vital cellular functions. Recurrent integrations in RAD51B, NR4A2, and TP63, leading to aberrant forms of these proteins, are observed in both HPV-positive head and neck squamous cell carcinoma (HNSCC) and cervical carcinoma. Additional genomic alterations, independent of integration events, include recurrent PIK3CA mutations (and aberrations in other members of the PI3K pathway), alterations in receptor tyrosine kinases (primarily FGFR2 and FGFR3 in HPV-positive HNSCC, and ERBB2 in cervical squamous cell carcinoma), and genes in pathways related to squamous cell differentiation and immune responses. A number of the alterations identified are potentially targetable, which may lead to advances in the treatment of HPV-associated cancers. Clin Cancer Res; 21(9); 2009–19. ©2015 AACR.

Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers

Given the success of targeted agents in specific populations it is expected that some degree of molecular biomarker testing will become standard of care for many, if not all, cancers. To facilitate this, cancer centers worldwide are experimenting with targeted “panel” sequencing of selected mutations. Recent advances in genomic technology enable the generation of genome-scale data sets for individual patients. Recognizing the risk, inherent in panel sequencing, of failing to detect meaningful somatic alterations, we sought to establish processes to integrate data from whole-genome analysis (WGA) into routine cancer care. Between June 2012 and August 2014, 100 adult patients with incurable cancers consented to participate in the Personalized OncoGenomics (POG) study. Fresh tumor and blood samples were obtained and used for whole-genome and RNA sequencing. Computational approaches were used to identify candidate driver mutations, genes, and pathways. Diagnostic and drug information were then sought based on these candidate “drivers.” Reports were generated and discussed weekly in a multidisciplinary team setting. Other multidisciplinary working groups were assembled to establish guidelines on the interpretation, communication, and integration of individual genomic findings into patient care. Of 78 patients for whom WGA was possible, results were considered actionable in 55 cases. In 23 of these 55 cases, the patients received treatments motivated by WGA. Our experience indicates that a multidisciplinary team of clinicians and scientists can implement a paradigm in which WGA is integrated into the care of late stage cancer patients to inform systemic therapy decisions.