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Background Checkpoint blockade immunotherapy, represented by PD-1 or PD-L1 antibody treatment, has been of tremendous success in clinical practice. However, the low clinical response rate and lack of biomarkers for prediction of the immune response limit the clinical application of anti-PD-1 immunotherapy. Our recent work showed that a combination of low-dose decitabine and PD-1-ab significantly improved the complete response (CR) rate of cHL patients from 32 to 71%, which indicates that there is a significant correlation between epigenetic regulation and the clinical response to immunotherapy. Methods We recruited two groups of Hodgkin lymphoma patients who were treated with anti-PD-1 and DAC+anti-PD-1. CD8+ T cells were isolated from the patients' peripheral blood, DNA methylation was analyzed by EPIC, the expression profile was analyzed by RNA-seq, and multigroup analysis was performed with IPA and GSEA functional annotations. We explored the effect of DAC on the function of CD8+ T cells in the blood, spleen, tumor and lymph nodes using a mouse model. Furthermore, we explored the function of Tils in the tumor microenvironment. Then, we constructed Runx3-knockout mice to confirm the T-cell-specific function of Runx3 in CD8+ T cells and analyzed various subtypes of T cells and cytokines using mass cytometry (CyTOF). Results Multiomics analysis identified that DNA methylation reprogramming of Runx3 was a crucial mediator of CD8+ T-cell function. Multiomics data showed that reversal of methylation of the Runx3 promoter promoted the infiltration of CD8+ TILs and mitigated the exhaustion of CD8+ T cells. Furthermore, experiments on tissue-specific Runx3-knockout mice showed that Runx3 deficiency reduced CD8+ T infiltration and the differentiation of effector T and memory T cells. Furthermore, Runx3 deficiency significantly decreased CCR3 and CCR5 levels. Immunotherapy experiments in Runx3 conditional knockout mice showed that DAC could not reverse the resistance of anti-PD-1 in the absence of Runx3. Moreover, both our clinical data and data from TISIDB showed that Runx3 could be a potential biomarker for immunotherapy to predict the clinical response rate. Conclusion We demonstrate that the DNA methylation of Runx3 plays a critical role in CD8+ T-cell infiltration and differentiation during decitabine-primed PD-1-ab immunotherapy, which provides a supporting mechanism for the essential role of epiregulation in immunotherapy.

The current second-line treatment of advanced gastric or gastroesophageal junction adenocarcinoma remains unsatisfactory. Anti-PD-1 monoclonal antibody combined with anti-angiogenic therapy shows anti-tumor activity and synergistic effect. We aimed to assess the efficacy and safety of the combination therapy of camrelizumab, apatinib, and S-1 in patients with gastric or gastroesophageal junction adenocarcinoma.In this open-label, single-arm, phase 2 trial, in each 21-day cycle, eligible patients received 200 mg intravenous camrelizumab in the first day, 500 mg oral apatinib once daily continuously, and specific dose oral S-1 in the first 14 days until the trial was discontinued disease progression, development of intolerable toxicity, or withdrawal of consent. The primary endpoint was objective response rate. The secondary endpoints were disease control rate, progression-free survival and overall survival, and safety. This study was registered at ClinicalTrials.gov, NCT04345783.Between May 2019 and August 2020, we enrolled a total of 24 patients in this trial. At the data cutoff (December 1, 2020), the median follow-up duration was 8.13 months. Seven of 24 (29.2%, 95%CI 14.9-49.2%) patients reached objective response. The median-progression-free survival was 6.5 months (95%CI 6.01-6.99) and the median overall survival was not reached. Grade 3 or 4 adverse events occurred in 6 (25.0%) patients, including elevated transaminase, thrombocytopenia, fatigue, proteinuria, and intestinal obstruction. No serious treatment-related adverse events or treatment-related deaths occurred.In this trial, the combination of camrelizumab, apatinib, and S-1 showed promising anti-tumor activity and manageable toxicity as a second-line therapy in patients with advanced gastric or gastroesophageal junction adenocarcinoma, regardless of PD-L1 expression.NCT04345783.

Background Racial disparities among clinical trial participants present a challenge to assess whether trial results can be generalized into patients representing diverse races and ethnicities. The objective of this study was to evaluate the impact of race and ethnicity on treatment response in patients with advanced non‐small cell lung cancer (aNSCLC) treated with programmed cell death‐1 (PD‐1) or programmed cell death‐ligand 1 (PD‐L1) inhibitors through analysis of real‐world data (RWD). Materials and Methods A retrospective cohort study of 11,138 patients with lung cancer treated at hospitals within the Mount Sinai Health System was performed. Patients with confirmed aNSCLC who received anti‐PD‐1/PD‐L1 treatment were analyzed for clinical outcomes. Our cohort included 249 patients with aNSCLC who began nivolumab, pembrolizumab, or atezolizumab treatment between November 2014 and December 2018. Time‐to‐treatment discontinuation (TTD) and overall survival (OS) were the analyzed clinical endpoints. Results After a median follow‐up of 14.8 months, median TTD was 7.8 months (95% confidence interval, 5.4–not estimable [NE]) in 75 African American patients versus 4.6 (2.4–7.2) in 110 White patients (hazard ratio [HR], 0.63). Median OS was not reached (18.4–NE) in African American patients versus 11.6 months (9.7–NE) in White patients (HR, 0.58). Multivariable Cox regression conducted with potential confounders confirmed longer TTD (adjusted HR, 0.65) and OS (adjusted HR, 0.60) in African American versus White patients. Similar real‐world response rate (42.6% vs. 43.5%) and disease control rate (59.6% vs. 56.5%) were observed in the African American and White patient populations. Further investigation revealed the African American patient group had lower incidence (14.7%) of putative hyperprogressive diseases (HPD) upon anti‐PD‐1/PD‐L1 treatment than the White patient group (24.5%). Conclusion Analysis of RWD showed longer TTD and OS in African American patients with aNSCLC treated with anti‐PD‐1/PD‐L1 inhibitors. Lower incidence of putative HPD is a possible reason for the favorable outcomes in this patient population. Implications for Practice There is a significant underrepresentation of minority patients in randomized clinical trials, and this study demonstrates that real‐world data can be used to investigate the impact of race and ethnicity on treatment response. In retrospective analysis of patients with advanced non‐small cell lung cancer treated with programmed cell death‐1 or programmed cell death‐ligand 1 inhibitors, African American patients had significantly longer time‐to‐treatment discontinuation and longer overall survival. Analysis of real‐world data can yield clinical insights and establish a more complete picture of medical interventions in routine clinical practice., Racial disparities in clinical trials affect whether trial results can be generalized for diverse patient populations. This article evaluates real‐world data to assess the impact of race and ethnicity on treatment response in patients with advanced non‐small cell lung cancer treated with PD‐1 or PD‐L1 inhibitors.

Background: The technique for anterior chest wall reconstruction after resection of primary sternal tumors (PST) still continue to evolve. Methods: A total of 12 PST patients from three hospitals who underwent en-bloc resection were included in our study. After finishing sternum resection, autologous iliac bone combined with Y-shaped titanium plate were applied to rebuild the anterior chest wall. Postoperative outcomes were analyzed. Results: There were 10 different types of tumors located in manubrium (6 cases), sternum body (4 cases) and Louis’s angle (2 cases) in our research. For these patients, the median resected tumor size and the area of defect after sternal resection were 279.0 cm 3 and 215.0 cm 2 , respectively. The mean operative time was 299.2±65.2 min and intra-operative blood loss was 431.2±213.0 mL. mean duration of drainage was 9.9±2.6 days. In their perioperative period, significant circulatory and respiratory complications occurred in 8 patients. Postoperative chest X-ray and tridimensional CT images showed autogenous reconstruction of the sternum and titanium in good position. No side effects were observed 6–12 months post reconstructive surgery, but one patient suffered from anchor loss and prosthesis migration. Y-shaped titanium plates from two patients were separately removed at 24 and 26 months when the reconstructive sternum integrated with skeleton anterior chest wall well. Conclusions: Our study demonstrates the safety and feasibility of this new technique for anterior chest wall reconstruction after sternectomies.

The integrated stress response (ISR) is a conserved pathway that is activated by cells that are exposed to stress. In lung adenocarcinoma, activation of the ATF4 branch of the ISR by certain oncogenic mutations has been linked to the regulation of amino acid metabolism. In the present study, we provide evidence for ATF4 activation across multiple stages and molecular subtypes of human lung adenocarcinoma. In response to extracellular amino acid limitation, lung adenocarcinoma cells with diverse genotypes commonly induce ATF4 in an eIF2α-dependent manner, which can be blocked pharmacologically using an ISR inhibitor. Although suppressing eIF2α or ATF4 can trigger different biological consequences, adaptive cell-cycle progression and cell migration are particularly sensitive to inhibition of the ISR. These phenotypes require the ATF4 target gene asparagine synthetase (ASNS), which maintains protein translation independently of the mTOR/PI3K pathway. Moreover, NRF2 protein levels and oxidative stress can be modulated by the ISR downstream of ASNS. Finally, we demonstrate that ASNS controls the biosynthesis of select proteins, including the cell-cycle regulator cyclin B1, which are associated with poor lung adenocarcinoma patient outcome. Our findings uncover new regulatory layers of the ISR pathway and its control of proteostasis in lung cancer cells. Implications: We reveal novel regulatory mechanisms by which the ISR controls selective protein translation and is required for cell-cycle progression and migration of lung cancer cells.

// Sierra A. Colavito 1 , James T. Platt 2 , Matthew A. Held 3 , Zongzhi Liu 2 , Ryan Sokup 1 and David F. Stern 4 , 5 1 Department of Biology, University of Wisconsin-La Crosse, La Crosse, WI, USA 2 Department of Internal Medicine and Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA 3 Department of Molecular, Cellular and Biomedical Sciences, University of New Hampshire, Durham, NH, USA 4 Department of Pathology, Yale School of Medicine, New Haven, CT, USA 5 Yale Cancer Center, New Haven, CT, USA Correspondence to: Sierra A. Colavito, email: scolavito@uwlax.edu Keywords: epithelial-mesenchymal transition; triple-negative breast cancer; targeted drug combination screen; claudin-low breast cancer; CHK1 Received: June 25, 2019 Accepted: July 05, 2019 Published: August 06, 2019 ABSTRACT Mesenchymal stem-like (MSL) breast cancers are enriched for cells with tumor reconstituting and mesenchymal characteristics. These cancers are often triple-negative and have a poor prognosis. Few effective targeted treatment options exist for patients with these cancers, and even when targeted therapies exist, resistance often arises and tumors recur, due in part to drug-tolerant persisting tumor cells with self-renewal capability. Effective treatment strategies will combine agents that target the bulk-tumor and reconstituting cells. In order to identify such a combination therapy, we conducted an inhibitor screen using 40 targeted agents at three different doses in all pairwise combinations. Checkpoint Kinase 1 (CHK1) inhibitors were identified as potent inhibitors of MSL breast cancers. When combined with a pro-apoptotic agent/B Cell Lymphoma 2 (BCL2) inhibitor, the effectiveness of the combination regimen was super-additive compared to either treatment alone and was selective for MSL cancers. Treatment of MSL breast cancer cells results in DNA damage, cell-cycle defects characterized by a prolonged S-phase, increased apoptosis and decreased colony forming abilities compared to untreated cells. These data suggest that a combination of a CHK1 and BCL2 inhibitor could be an effective treatment for patients with MSL breast cancer. Several other effective drug combinations were also identified.

Background Although EGFR mutant tumors exhibit low response rates to immune checkpoint blockade overall, some EGFR mutant tumors do respond to these therapies; however, there is a lack of understanding of the characteristics of EGFR mutant lung tumors responsive to immune checkpoint blockade. Patients and methods We retrospectively analyzed de-identified clinical and molecular data on 171 cases of EGFR mutant lung tumors treated with immune checkpoint inhibitors from the Yale Cancer Center, Memorial Sloan Kettering Cancer Center, University of California Los Angeles, and Dana Farber Cancer Institute. A separate cohort of 383 EGFR mutant lung cancer cases with sequencing data available from the Yale Cancer Center, Memorial Sloan Kettering Cancer Center, and The Cancer Genome Atlas was compiled to assess the relationship between tumor mutation burden and specific EGFR alterations. Results Compared with 212 EGFR wild-type lung cancers, outcomes with programmed cell death 1 or programmed death-ligand 1 (PD-(L)1) blockade were worse in patients with lung tumors harboring alterations in exon 19 of EGFR (EGFRΔ19) but similar for EGFRL858R lung tumors. EGFRT790M status and PD-L1 expression did not impact response or survival outcomes to immune checkpoint blockade. PD-L1 expression was similar across EGFR alleles. Lung tumors with EGFRΔ19 alterations harbored a lower tumor mutation burden compared with EGFRL858R lung tumors despite similar smoking history. Conclusions EGFR mutant tumors have generally low response to immune checkpoint inhibitors, but outcomes vary by allele. Understanding the heterogeneity of EGFR mutant tumors may be informative for establishing the benefits and uses of PD-(L)1 therapies for patients with this disease.

e13563 Background: Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous disease with multiple phenotypes and endotypes and associated with lung cancer development. In this study, we analyzed the clinical features of COPD including various phenotypic and endotypic features from the electronic health records (EHR) as the potential risk factors for lung cancer development in a large cohort of COPD patients. Methods: We identified a COPD cohort based on electronic Medical Records and Genomics (eMERGE) network COPD cohort identification algorithms with minor modifications from the Mount Sinai Data Warehouse (2000-2020) and followed the patients on the first diagnosis of lung cancer. The development of lung cancer in COPD patients was confirmed by manual chart review. We retrieved the clinical features from EHRs and conducted Kaplan Meier (KM) analysis and multivariable Cox-regression modeling for hazard ratio (HR) analysis. Results: We found that 3.8 % of COPD patients (824 out of 21,658) developed lung cancer. While COPD patients with emphysema and smoking history (former or current) showed an increased risk of lung cancer onset, patients with concurrent asthma and corticosteroid (ICS) inhalation history showed a reduced risk of lung cancer onset (adjusted HR in Table). Interestingly, COPD patients with higher eosinophil counts showed late onset of lung cancer (>300 cells/ul, cancer rate at 5y=2.4%, p=< 0.002; 150-300 cells/ul, cancer rate at 5y=2.9%, p=0.003) when compared to patients with low eosinophils count (300 cells/ul; HR:0.72, 95% CI: 0.57-0.89, p=0.003) when compared to those with low eosinophils count (

Purpose: Tumor heterogeneity may represent a barrier to preoperative genomic characterization by needle biopsy in clear cell renal cell carcinoma (ccRCC). The extent of heterogeneity in small renal tumors remains unknown. Therefore, we set out to evaluate heterogeneity in resected large and small renal tumors. Experimental Design: We conducted a study from 2013 to 2016 that evaluated 47 consecutive ccRCC tumors resected during radical or partial nephrectomy. Cases were designated as small (7 cm) tumors. Each tumor had three regions sampled. Copy-number variation (CNV) was assessed and gene expression analysis was performed to characterize the clear-cell A and B (ccA/ccB) profile and the cell-cycle progression (CCP) score. Genomic heterogeneity between three regions was evaluated using CNV subclonal events, regional expression profiles, and correlation between gene expression. Results: Twenty-three small and 24 large tumors were analyzed. Total CNVs and subclonal CNVs events were less frequent in small tumors (P < 0.001). Significant gene expression heterogeneity was observed for both CCP scores and ccA/ccB classifications. Larger tumors had more variance in CCP scores (P = 0.026). The distribution of ccA/ccB differed between small and large tumors with mixed ccA/ccB tumors occurring more frequently in the larger tumors (P = 0.024). Analysis of five mixed tumors (with both ccA/ccB regions) demonstrated the more aggressive ccB phenotype had greater CNV events (P = 0.014). Conclusions: Small renal tumors have much less genomic complexity and fewer subclonal events. Pretreatment genomic characterization with single-needle biopsy in small tumors may be useful to assess biologic potential and may influence therapy. Clin Cancer Res; 24(17); 4137–44. ©2018 AACR.

Mechanisms underlying the propensity of latent lung adenocarcinoma (LUAD) to relapse are poorly understood. In this study, we show how differential expression of a network of extracellular matrix (ECM) molecules and their interacting proteins contributes to risk of relapse in distinct LUAD subtypes. Overexpression of the hyaluronan receptor HMMR in primary LUAD was associated with an inflammatory molecular signature and poor prognosis. Attenuating HMMR in LUAD cells diminished their ability to initiate lung tumors and distant metastases. HMMR upregulation was not required for dissemination in vivo, but enhanced ECM-mediated signaling, LUAD cell survival, and micrometastasis expansion in hyaluronan-rich microenvironments in the lung and brain metastatic niches. Our findings reveal an important mechanism by which disseminated cancer cells can coopt the inflammatory ECM to persist, leading to brain metastatic outgrowths. Cancer Res; 77(8); 1905–17. ©2017 AACR.

e19512 Background: Targeted therapy is an important treatment for chronic lymphocytic leukemia (CLL). However, optimal strategies for deploying small molecule inhibitors or antibody therapies in the real world are not well understood, largely due to a lack of outcomes data. We implemented a novel temporal phenotyping algorithm pipeline to derive lines of therapy (LOT) and disease progression in CLL patients. Here, the CLL treatment pattern and time to the next treatment (TTNT) were analyzed in real-world data (RWD) using patient electronic health records. Methods: We identified a CLL cohort with LOT from the Mount Sinai Data Warehouse (2003-2020). Each LOT consisted of either a single agent or combinations defined by NCCN CLL guidelines. We developed a natural language processing (NLP)-based temporal phenotyping approach to automatically identify the number of lines and therapeutic regimens. The sequence of treatment and time interval for each patient were derived from the systematic treatment data. Time to event analysis and multivariate (i.e., age, gender, race, other treatment patterns) Cox proportional hazard (CoxPH) models were used to analyze the patterns and predictors of TTNT. Results: Four hundred eleven CLL patients received 1 to 7 LOTs. Ibrutinib was the predominant 1st LOT (40.8% of patients) followed by anti-CD20-based antibody therapies and chemotherapy in 30.6 and 19.2% of patients, respectively, followed by Acalabrutinib, Venetoclax, and Idelalisib in 3.4, 2.7, and 0.7% of patients, respectively (Table 1). The 2nd to 5th LOT showed the same or similar trends. We next analyzed the TTNT in the 1st line of each therapeutic class. Acalabrutinib resulted in a longer median TTNT than Ibrutinib. Both Acalabrutinib and Ibrutinib showed longer TTNT compared to Venetoclax (median TTNTs were 742 and 598 vs. 373 days: HR = 0.23, p=0.015 and HR = 0.48, p=0.03, respectively). In addition, patients with age equal to or older than 65 showed longer TNNT (HR=0.16, p=0.016). Conclusions: Our result shows the potential of RWD usage in clinical decision making as real-world evidence reported here is consistent with results derived from clinical trial data. Linking this study to genetic data and other covariates affecting treatment outcomes may provide additional insights into the optimal sequences of the targeted therapies in CLL. Table 1: Therapeutic class and patient numbers (%) in each line.[Table: see text]

6592 Background: Clinical trial phenotyping is the process of extracting clinical features and patient characteristics from eligibility criteria. Phenotyping is a crucial step that precedes automated cohort identification from patient electronic health records (EHRs) against trial criteria. We establish a clinical trial phenotyping pipeline to transform clinical trial eligibility criteria into computable criteria and enable high throughput cohort selection in EHRs. Methods: Formalized clinical trial criteria attributes were acquired from a natural-language processing (NLP)-assisted approach. We implemented a clinical trial phenotyping pipeline that included three components: First, a rule-based knowledge engineering component was introduced to annotate the trial attributes into a computable and customizable granularity from EHRs. The second component involved normalizing annotated attributes using standard terminologies and pre-defined reference tables. Third, a knowledge base of computable criteria attributes was built to match patients to clinical trials. We evaluated the pipeline performance by independent manual review. The inter-rater agreement of the annotation was measured on a random sample of the knowledge base. The accuracy of the pipeline was evaluated on a subset of randomly selected matched patients for a subset of randomly selected attributes. Results: Our pipeline phenotyped 2954 clinical trials from five cancer types including Non-Small Cell Lung Cancer, Small Cell Lung Cancer, Prostate Cancer, Breast Cancer, and Multiple Myeloma. We built a knowledge base of 256 computable attributes that included comorbidities, comorbidity-related treatment, previous lines of therapy, laboratory tests, and performance such as ECOG and Karnofsky score. Among 256 attributes, 132 attributes were encoded using standard terminologies and 124 attributes were normalized to customized concepts. The inter-rater agreement of the annotation measured by Cohen’s Kappa coefficient was 0.83. We applied the knowledge base to our EHRs and efficiently identified 33258 potential subjects for cancer clinical trials. Our evaluation on the patient matching indicated the F1 score was 0.94. Conclusions: We established a clinical trial phenotyping pipeline and built a knowledge base of computable criteria attributes that enabled efficient screening of EHRs for patients meeting clinical trial eligibility criteria, providing an automated way to efficiently and accurately identify clinical trial cohorts. The application of this knowledge base to patient matching from EHR data across different institutes demonstrates its generalization capability. Taken together, this knowledge base will be particularly valuable in computer-assisted clinical trial subject selection and clinical trial protocol design in cancer studies based on real-world evidence.

e18747 Background: Accurate longitudinal cancer treatments are vital for establishing primary endpoints such as outcome as well as for the investigation of adverse events. However, many longitudinal therapeutic regimens are not well captured in structured electronic health records (EHRs). Thus, their recognition in unstructured data such as clinical notes is critical to gain an accurate description of the real-world patient treatment journey. Here, we demonstrate a scalable approach to extract high-quality longitudinal cancer treatments from lung cancer patients' clinical notes using a Bidirectional Long Short Term Memory (BiLSTM) and Conditional Random Fields (CRF) based natural language processing (NLP) pipeline. Methods: The lung cancer (LC) cohort of 4,698 patients was curated from the Mount Sinai Healthcare system (2003-2020). Two domain experts developed a structured framework of entities and semantics that captured treatment and its temporality. The framework included therapy type (chemotherapy, targeted therapy, immunotherapy, etc.), status (on, off, hold, planned, etc.) and temporal reasoning entities and relations (admin_date, duration, etc.) We pre-annotated 149 FDA-approved cancer drugs and longitudinal timelines of treatment on the training corpus. A NLP pipeline was implemented with BiLSTM-CRF-based deep learning models to train and then apply the resulting models to the clinical notes of LC cohort. A postprocessor was developed to subsequently post-coordinate and refine the output. We performed both cross-evaluation and independent evaluation to assess the pipeline performance. Results: We applied the NLP pipeline to the 853,755 clinical notes, and identified 1,155 distinct entities for 194 cancer generic drugs, including 74 chemotherapy drugs, 21 immunotherapy drugs, and 99 targeted therapy drugs. We identified chemotherapy, immunotherapy, or targeted therapy data for 3,509 patients in the LC cohort from the clinical notes. Compared to only 2,395 patients with cancer treatments in structured EHR, this pipeline identified cancer treatments from notes for additional 2,303 patients who did not have any available cancer treatment data in the structured EHR. Our evaluation schema indicates that the longitudinal cancer drug recognition pipeline delivers strong performance (named entity recognization for drugs and temporal: F1 = 95%; drug-temporal relation recognition: F1 = 90%). Conclusions: We developed a high-performance BiLSTM-CRF based NLP pipeline to recognize longitudinal cancer treatments. The pipeline recovers and encodes as twice as many patients with cancer treatments compared with structured EHR. Our study indicates deep NLP with temporal reasoning could substantially accelerate the extraction of treatment profiles at scale. The pipeline is adjustable and can be applied across different cancers.

The majority of EGFR mutant lung adenocarcinomas respond well to EGFR tyrosine kinase inhibitors (TKIs). However, the majority of these responses are partial, with drug-tolerant residual disease remaining even at the time of maximal response. This residual disease serves as a reservoir for the emergence of acquired resistance and tumor relapse, which inevitably occurs in patients treated with TKIs. It is thus critical to understand the biology of residual tumor cells and find out the mechanisms that underlie drug tolerance. Knowledge of such mechanisms could lead to the identification of potential strategies to forestall the emergence of drug resistance. Studies of residual disease have been hampered by the difficulty of studying these persister cells in patient specimens, and most studies to date have relied on analysis of established cell lines in culture. To investigate the cellular and molecular properties of residual tumor cells in vivo, we leveraged patient-derived models of EGFR mutant lung cancer. Three EGFR mutant PDXs were treated with the 3rd-generation TKI osimertinib. Tumors regressed in all cases, but measurable residual tumor remained in 2 out of the 3 PDXs even after 6 weeks of osimertinib treatment. Whole-exome sequencing (WES) of the untreated PDXs compared to the residual tumors revealed an unchanged mutational landscape between the samples, indicating that genetic mechanisms did not account for drug tolerance. Bulk RNA-sequencing, however, revealed extensive transcriptional changes between the untreated PDX and residual disease. In one of the PDXs, we identified upregulation of neuroendocrine lineage transcription factor ASCL1 in residual disease compared to untreated tumors. Using single-cell RNA-sequencing, we found a pre-existing ASCL1hi tumor cell population in untreated tumors, suggesting that these cells, which possessed drug-tolerant properties, were selected for during drug treatment. Depending on the cell line examined, expression of ASCL1 in human mutant EGFR lung cancer cell lines increased the number of persister clones following osimertinib treatment, indicating that the cellular context contributed to ASCL1’s role in conferring drug tolerance. Our studies provide insights into the role of neuroendocrine factor ASCL1 as a potential driver of drug tolerance in mutant EGFR lung cancer, and ongoing work is focused on identifying the mechanistic underpinnings of these findings. Citation Format: Bomiao Hu, Fernando J. de Miguel, Zongzhi Liu, Lok-Hei Chan, Mary Ann Melnick, Qin Yan, Don Nguyen, Rong Fan, Katerina Politi. ASCL1 confers tolerance to tyrosine kinase inhibitors in EGFR mutant lung cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr A13.

Background Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) like erlotinib are effective for treating patients with EGFR mutant lung cancer; however, drug resistance inevitably emerges. Approaches to combine immunotherapies and targeted therapies to overcome or delay drug resistance have been hindered by limited knowledge of the effect of erlotinib on tumor-infiltrating immune cells. Methods Using mouse models, we studied the immunological profile of mutant EGFR-driven lung tumors before and after erlotinib treatment. Results We found that erlotinib triggered the recruitment of inflammatory T cells into the lungs and increased maturation of alveolar macrophages. Interestingly, this phenotype could be recapitulated by tumor regression mediated by deprivation of the EGFR oncogene indicating that tumor regression alone was sufficient for these immunostimulatory effects. We also found that further efforts to boost the function and abundance of inflammatory cells, by combining erlotinib treatment with anti-PD-1 and/or a CD40 agonist, did not improve survival in an EGFR-driven mouse model. Conclusions Our findings lay the foundation for understanding the effects of TKIs on the tumor microenvironment and highlight the importance of investigating targeted and immuno-therapy combination strategies to treat EGFR mutant lung cancer. Electronic supplementary material The online version of this article (10.1186/s40425-019-0643-8) contains supplementary material, which is available to authorized users.

e14062 Background: Real world evidence generated from electronic health records (EHRs) is playing an increasing role in health care decisions. It has been recognized as an essential element to assess cancer outcomes in real-world settings. Automatically abstracting outcomes from notes is becoming a fundamental challenge in medical informatics. In this study, we aim to develop a system to automatically abstract outcomes (Progression, Response, Stable Disease) from notes in lung cancer. Methods: A lung cancer cohort (n = 5,003) was obtained from the Mount Sinai Data Warehouse. The progress, pathology and radiology notes of patients were used. We integrated various techniques of Natural Language Processing (NLP) and Artificial Intelligence (AI) and developed a system to automatically abstract outcomes. The corresponding images, biopsies and lines of treatments (LOTs) were abstracted as attributes of outcomes. This system includes four information models: 1. Customized NLP annotator model: preprocessor, section detector, sentence splitter, named entity recognition, relation detector; CRF and LSTM methods were applied to recognize entities and relations. 2. Clinical Outcome container model: biopsy evidence extractor, lines of treatment detector, image evidence extractor, clinical outcome event recognizer, date detector, and temporal reasoning; Domain-specific rules were crafted to automatically infer outcomes. 3. Document Summarizer; 4. Longitudinal Outcome Summarizer. Results: To evaluate the outcomes abstracted, we curated a subset (n = 792) from patient cohort for which LOTs were available. About 61% of the outcomes identified were supported by radiologic images (time window = ±14 days) or biopsy pathology results (time window = ±100 days). In 91% (720/792) of patients, Progression was abstracted within a time window of 90 days prior to first-line treatment. Also, 72% of the Progression events identified were accompanied by a downstream event (e.g., treatment change or death). We randomly selected 250 outcomes for manual curation, and 197 outcomes were assessed to be correct (precision = 79%). Moreover, our automated abstraction system improved human abstractor efficiency to curate outcomes, reducing curation time per patient by 90%. Conclusions: We have demonstrated the feasibility and effectiveness of NLP and AI approaches to abstract outcomes from lung cancer EHR data. It promises to automatically abstract outcomes and other clinical entities from notes across all cancers.

e21514 Background: Although some advanced non-small cell lung cancer (aNSCLC) patients respond favorably to immune checkpoint inhibitors, a larger portion either do not respond or experience negative side effects. At present, there is no consensus on how to best predict response to immunotherapy (IO) agents. Complete blood count (CBC) data have shown correlation with both progression and survival for patients treated with IO. However, previous studies have been relatively small, or did not focus on aNSCLC. Given CBCs are measured routinely for every patient throughout their course of therapy, we used real-world data (RWD) to assess the biomarker potential of CBCs in predicting response at the start and through the course of therapy. Methods: We performed a retrospective cohort study of 11,138 lung cancer patients treated at hospitals in the Mount Sinai Health System of whom 249 aNSCLC and were treated with anti-PD1/PD-L1 therapy. We extracted and harmonized medical record data using an automated abstraction engine and evaluated the impact of changes in CBCs, including eosinophils, lymphocytes, monocytes, neutrophils, red blood cells and platelets after treatment initiation. Time to treatment discontinuation (TTD) and overall survival (OS) were our clinical endpoints. Results: Abnormal baseline levels of monocytes, neutrophils, and red bloods cells were associated with OS; counts taken between 2-8 weeks were modestly to significantly associated with poorer OS, with hazard ratios ranging from 1.7-4.7. Most strikingly, neutrophil levels above 7 (HR = 4.3, p = 3.2*10−10, 95% CI = 2.7-6.7) and a neutrophil-to-lymphocyte ratio > 5 (HR = 3.4, p = 8.0*10−8, 95% CI = 2.2-5.4) were associated with poorer OS. For those with normal neutrophil levels at baseline, progressing to high levels at 2-8 weeks resulted in a hazard for OS of 5.0 (p = 4.4*10−8, 95% CI = 2.8-9.0). Those with progression are more likely to have high neutrophil levels at baseline, or an increase in neutrophil levels from normal to high levels between baseline and 2-8 weeks or 8-14 weeks. Our results remained consistent even after controlling for factors that may affect neutrophil levels including concurrent chemotherapy, administration of neutropenia medications, or concurrent infections. Repeating the analysis with TTD as the primary endpoint showed similar but less significant trends. Conclusions: RWD showed changes in blood cell counts after anti-PD1/PD-L1 therapy were associated with OS in aNSCLC and show promise as a predictive biomarker.

e14054 Background: Matching clinical attributes (i.e. indications, lab tests, treatment regimens) of clinical trial eligibility criteria with real world patient data is extremely challenging. Attribute phenotyping is one of the key components of Trial2Patient, a customized system developed by Sema4 to find patients for clinical trials. Transforming treatment regimens to a standard ontology and encoding drugs with standard nomenclatures will facilitate the semantic retrieval of treatments mentioned in clinical trial criteria. This will also enable the interoperation between different data sources that is often required for fast-learning and scalable healthcare information system. Methods: Free text containing treatment regimen/medication terms were extracted and preprocessed from three sources: 1) clinical trials listed in a commercial database citeline.com, 2) clinical trials listed in clinicaltrials.gov, and 3) National Comprehensive Cancer Network (NCCN) Guidelines. The regimen terms such as neoadjuvant therapy for non-small cell lung cancer, checkpoint inhibitor, EGFR inhibitor, androgen deprivation therapy (ADT), among many others, were profiled by AI methods (i.e. pattern reorganization and rule-based) and knowledge engineering via Sema4’s in-house knowledge base (CAV), Pharmaprojects in citline.com and NCCN Guidelines. The drugs related to each regimen were identified and mapped to RxCUI via RxNorm ontology. Results: We identified 76 regimen terms for non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and prostate cancer (e.g. PD-L1 ≥1% nonsquamous NSCLC, bone antiresorptive therapy for M1 castration resistant prostate cancer), and 14,476 drug-category pair (e.g. pembrolizumab is a PD-1 inhibitor, pembrolizumab is used as the third line and beyond systemic therapy for M1 CRPC). All drugs identified were mapped to RxCUI for real world patient matching. Conclusions: This approach systematically extracted and normalized regimens and medications mentioned in clinical trials in NSCLC, SCLC and prostate cancer to standard codes. These standardized data can be used in mapping treatment histories of a patient to the eligibility criteria for clinical studies or for identifying studies relevant to a patient. The outcome of profiling cancer treatment regimens through standard ontology RxNorm may be particularly valuable in cancer studies based on real-world evidence.

Accumulating evidence indicates that dysregulation of miRNAs could contribute to tumor growth and metastasis of chondrosarcoma by infuencing cell proliferation and invasion. In the current study, we are interested to examine the role of miRNAs in the carcinogenesis and progression of chondrosarcoma. Here, using comparative miRNA profiling of tissues and cells of chondrosarcoma and cartilage, we identified miR-494 as a commonly downregulated miRNA in the tissues of patients with chondrosarcoma and chondrosarcoma cancer cell line, and upregulation of miR-494 could inhibit proliferation and invasion of chondrosarcoma cancer cells in vivo and in vitro. Moreover, our data demonstrated that SOX9, the essential regulator of the process of cartilage differentiation, was the direct target and functional mediator of miR-494 in chondrosarcoma cells. And downregulation of SOX9 could also inhibit migration and invasion of chondrosarcoma cells. In the last, we identified low expression of miR-494 was significantly correlated with poor overall survival and prognosis of chondrosarcoma patients. Thus, miR-494 may be a new common therapeutic target and prognosis biomarker for chondrosarcoma.

BRAF inhibitors have revolutionized treatment of mutant BRAF metastatic melanomas. However, resistance develops rapidly following BRAF inhibitor treatment. We have found that BRAF-mutant melanoma cell lines are more sensitive than wild-type BRAF cells to the small molecule tyrosine kinase inhibitor dovitinib. Sensitivity is associated with inhibition of a series of known dovitinib targets. Dovitinib in combination with several agents inhibits growth more effectively than either agent alone. These combinations inhibit BRAF-mutant melanoma and colorectal carcinoma cell lines, including cell lines with intrinsic or selected BRAF inhibitor resistance. Hence, combinations of dovitinib with second agents are potentially effective therapies for BRAF-mutant melanomas, regardless of their sensitivity to BRAF inhibitors.

Cyclic GMP-AMP (cGAMP) synthase (cGAS) stimulator of interferon genes (STING) senses pathogen-derived or abnormal self-DNA in the cytosol and triggers an innate immune defense against microbial infection and cancer. STING agonists induce both innate and adaptive immune responses and are a new class of cancer immunotherapy agents tested in multiple clinical trials. However, STING is commonly silenced in cancer cells via unclear mechanisms, limiting the application of these agonists. Here, we report that the expression of STING is epigenetically suppressed by the histone H3K4 lysine demethylases KDM5B and KDM5C and is activated by the opposing H3K4 methyltransferases. The induction of STING expression by KDM5 blockade triggered a robust interferon response in a cytosolic DNA-dependent manner in breast cancer cells. This response resulted in resistance to infection by DNA and RNA viruses. In human tumors, KDM5B expression is inversely associated with STING expression in multiple cancer types, with the level of intratumoral CD8+ T cells, and with patient survival in cancers with a high level of cytosolic DNA, such as human papilloma virus (HPV)-positive head and neck cancer. These results demonstrate a novel epigenetic regulatory pathway of immune response and suggest that KDM5 demethylases are potential targets for antipathogen treatment and anticancer immunotherapy., Author summary Pathogens often find ways to turn down cell-intrinsic antipathogen immune responses by the host. Similarly, cancer cells use various mechanisms to evade attack by immune cells. One of the common mechanisms is suppression of the stimulator of interferon genes (STING)-dependent innate immune response. Using potent and specific small-molecule inhibitors and genetic-depletion approaches, we found that the silenced STING pathway can be reactivated in breast cancer cells by suppressing KDM5 demethylases. Activation of the STING pathway led to a robust interferon response, which blocked viral infection, and was associated with increased tumor-infiltrated lymphocytes and better patient survival in multiple cancer types. This discovery has major clinical implications for treating both pathogen infection and cancer because KDM5 inhibition provides a fast, robust, and reversible control of innate immune response. Since the discovery of histone demethylase activity of KDM5 proteins a decade ago, significant efforts have been dedicated to developing KDM5 inhibitors for clinical applications. In fact, a KDM5 inhibitor recently entered phase I clinical trial for treatment of hepatitis B infection. Here, we provide mechanistic insights on how KDM5 inhibitors block viral infection. Moreover, our results suggest that KDM5 inhibitors can also be combined with other cancer immunotherapies.

e20642 Background: While optimal sequencing of systemic therapy in aNSCLC is critical to achieve maximal clinical benefit, it is practically challenging to study tx sequencing through clinical trials. RWD allow retrospective, observational studies to examine tx patterns and associated clinical outcomes. Methods: 1,609 aNSCLC patients who received systemic therapies at Mount Sinai hospitals were analyzed for the number of line of therapy (LOT), therapeutic modalities (chemotherapy, targeted therapy and immunotherapy), and the sequence in which treatments were given when LOT > 1. Time to tx discontinuation (TTD) was used as a surrogate clinical endpoint for outcomes. Results: 578 of the 1,609 (36%) patients received more than one LOT. 356 (22%) received tyrosine kinase inhibitors (TKIs), and 297 (16%) received immune checkpoint inhibitors (CPIs). Kaplan-Meier analysis revealed that among 297 patients who received CPIs, median TTD was longer in the 1st line setting (295 days, 95% CI 169 to 523; n=132) than when LOT > 1 (169 days, 95% CI 113 to 269; n=165), although the difference was not statistically significant (P=0.092, log-rank test). No difference of TTD on TKIs was observed between LOT = 1 and LOT > 1 (P=0.51). With respect to tx sequencing, when patients (n=94) received TKIs as the 1st LOT, 60%, 35%, and 5% of them received another TKI, chemotherapy, or a CPI-containing regimen, respectively, as the 2nd LOT. Among patients (n=370) who progressed on 1st line platinum-based chemotherapy, 52%, 32%, and 16% received another chemo regimen, a CPI-containing regimen, or a targeted therapy, respectively, as the 2nd LOT; these percentages shifted significantly toward more CPIs (24%, 66%, 10% for chemo, CPI, targeted, respectively) when only 2016-2018 data were examined. In the 2nd line setting after platinum therapy, TTD was significantly longer in the CPI group (332 days, 95% CI 169-484) compared to the chemo group (88 days, 95% CI 65-100; P

e18141 Background: Clinical trials remain the most reliable means to evaluate drug efficacy and safety for evidence-based cancer care. However, there is a significant racial disparity among participants in clinical trials. For example, only 1-3% of the participants in registration trials of immune checkpoint inhibitors (CPIs) in advanced non-small cell lung cancers (aNSCLCs) were Black. RWD data enable assessment of whether clinical trial results can be generalized to broader populations. Methods: We analyzed clinical records of > 145,000 cancer patients treated at Mount Sinai hospitals. Therapeutic agents approved by FDA in recent years were assessed for responses across various race groups. Time to treatment discontinuation (TTD) was used as a surrogate clinical endpoint for outcomes. Results: Overall we did not observe significant differences in TTD among different race groups for the following drugs and indications we examined: palbociclib in metastatic breast cancer (mBC), EGFR tyrosine kinase inhibitors in aNSCLC, EGFR antibody cetuximab and panitumumab in metastatic colorectal cancer with wild type KRAS, abiraterone in metastatic castration-resistant prostate cancer (mCRPC), enzalutamide in mCRPC, sorafenib in unresectable hepatocellular carcinoma (HCC), CPIs in metastatic melanoma. For example, the median TTD of palbociclib in combination with fulvestrant or letrozole in post-menopausal women with HR+HER2- mBC was 181, 261, and 160 days in White (n = 114), Black (n = 55), other (n = 48) race groups, respectively (P = 0.61, log-rank test). Among patients with unresectable HCC treated with sorafenib, the median TTD was 64, 49, and 67 days in the White (n = 201), Black (n = 127) and other (n = 243) race groups, respectively (P = 0.70). However, when CPIs in aNSCLC were examined, we observed a significantly longer TTD in the Black group (median TTD not reached; n = 77) compare to the non-Black group (169 days, 95% CI 133-331; n = 211), P = 0.0049, median follow up 194 days. Conclusions: RWD showed there are no apparent differences of treatment response in various race groups for most new therapeutic agents. Preliminary results of CPIs in aNSCLC suggested a favorable response in the Black than the non-Black population.

SummaryMolecular programs that mediate normal cell differentiation are required for oncogenesis and tumor cell survival in certain cancers. How cell-lineage-restricted genes specifically influence metastasis is poorly defined. In lung cancers, we uncovered a transcriptional program that is preferentially associated with distal airway epithelial differentiation and lung adenocarcinoma (ADC) progression. This program is regulated in part by the lineage transcription factors GATA6 and HOPX. These factors can cooperatively limit the metastatic competence of ADC cells, by modulating overlapping alveolar differentiation and invasogenic target genes. Thus, GATA6 and HOPX are critical nodes in a lineage-selective pathway that directly links effectors of airway epithelial specification to the inhibition of metastasis in the lung ADC subtype.

Resistance and partial responses to targeted monotherapy are major obstacles in cancer treatment. Systematic approaches to identify efficacious drug combinations for cancer are not well established, especially in the context of genotype. To address this, we have tested pairwise combinations of an array of small-molecule inhibitors on early-passage melanoma cultures using combinatorial drug screening. Results reveal several inhibitor combinations effective for melanomas with activating RAS or BRAF mutations, including mutant BRAF melanomas with intrinsic or acquired resistance to vemurafenib. Inhibition of both EGF receptor and AKT sensitized treatment-resistant BRAF mutant melanoma cultures to vemurafenib. Melanomas with RAS mutations were more resistant to combination therapies relative to BRAF mutants, but were sensitive to combinations of statins and cyclin-dependent kinase inhibitors in vitro and in vivo. These results show the use of combinatorial drug screening for discovering unique treatment regimens that overcome resistance phenotypes of mutant BRAF- and RAS-driven melanomas. Significance: We have used drug combinatorial screening to identify effective combinations for mutant BRAF melanomas, including those resistant to vemurafenib, and mutant RAS melanomas that are resistant to many therapies. Mechanisms governing the interactions of the drug combinations are proposed, and in vivo xenografts show the enhanced benefit and tolerability of a mutant RAS-selective combination, which is currently lacking in the clinic. Cancer Discov; 3(1); 52–67. ©2012 AACR. See related commentary by Al-Lazikani and Workman, p. 14 This article is highlighted in the In This Issue feature, p. 1

BACKGROUND An increase in thyroid cancers, predominantly papillary thyroid carcinoma (PTC), has been recently reported in children. METHODS The histopathology of 28 consecutive PTCs from the northeast United States was reviewed. None of the patients (ages 6-18 years; 20 females, 8 males) had significant exposure to radiation. Nucleic acid from tumors was tested for genetic abnormalities (n = 27). Negative results were reevaluated by targeted next-generation sequencing. RESULTS Seven of 27 PTCs (26%) had neurotrophic tyrosine kinase receptor (NTRK) fusion oncogenes (NTRK type 3/ets variant 6 [NTRK3/ETV6], n =5; NTRK3/unknown, n = 1; and NTRK type 1/translocated promoter region, nuclear basket protein [NTRK1/TPR], n = 1), including 5 tumors that measured >2 cm and 3 that diffusely involved the entire thyroid or lobe. All 7 tumors had lymphatic invasion, and 5 had vascular invasion. Six of 27 PTCs (22%) had ret proto-oncogene (RET) fusions (RET/PTC1, n = 5; RET/PTC3, n = 1); 2 tumors measured >2 cm and diffusely involved the thyroid, and 5 had lymphatic invasion, with vascular invasion in 2. Thirteen PTCs had the B-Raf proto-oncogene, serine/threonine kinase (BRAF) valine-to-glutamic acid mutation at position 600 (BRAFV600E) (13 of 27 tumors; 48%), 11 measured

Background: Clear cell renal cell carcinoma (ccRCC) is the most lethal form of kidney cancer. Small molecule VEGFR inhibitors are widely used but are not curative and various resistance mechanisms such as activation of the MET pathway have been described. Dual MET/VEGFR2 inhibitors have recently shown clinical benefit but limited preclinical data evaluates their effects in ccRCC. Methods: An interrogation of the Cancer Genome Atlas (TCGA) dataset was performed to evaluate oncogenic alterations in the MET/VEGFR2 pathway. We evaluated the in vitro effects of Cabozantinib, a dual MET/VEGFR2 inhibitor, using a panel of ccRCC cell lines. Drug effects of cell viability and proliferation, migration, cell scatter, anchorage independent growth, and downstream MET/VEGFR2 signaling pathways were assessed. Results: Twelve percent of TCGA cases had possible MET/HGF oncogenic alterations with co-occurrence noted (p

Associations of ErbB4 (ERBB4/HER4), the fourth member of the EGFR family, with cancer are variable, possibly as a result of structural diversity of this receptor. There are multiple structural isoforms of ERBB4 arising by alternative mRNA splicing, and a subset undergo proteolysis that releases membrane-anchored and soluble isoforms that associate with transcription factors and coregulators to modulate transcription. To compare the differential and common signaling activities of full-length (FL) and soluble intracellular isoforms of ERBB4, four JM-a isoforms (FL and soluble intracellular domain (ICD) CYT-1 and CYT-2) were expressed in isogenic MCF10A cells and their biologic activities were analyzed. Both FL and ICD CYT-2 promoted cell proliferation and invasion, and CYT-1 suppressed cell growth. Transcriptional profiling revealed several new and underexplored ERBB4-regulated transcripts, including: proteases/protease inhibitors (MMP3 and SERPINE2), the YAP/Hippo pathway (CTGF, CYR61, and SPARC), the mevalonate/cholesterol pathway (HMGCR, HMGCS1, LDLR, and DHCR7), and cytokines (IL8, CCL20, and CXCL1). Many of these transcripts were subsequently validated in a luminal breast cancer cell line that normally expresses ERBB4. Furthermore, ChIP-seq experiments identified ADAP1, APOE, SPARC, STMN1, and MXD1 as novel molecular targets of ERBB4. These findings clarify the diverse biologic activities of ERBB4 isoforms, and reveal new and divergent functions. Implications: ErbB4 as a regulator of Hippo and mevalonate pathways provides new insight into milk production and anabolic processes in normal mammary epithelia and cancer. Mol Cancer Res; 12(8); 1140–55. ©2014 AACR.

Background Genotyping platforms such as single nucleotide polymorphism (SNP) arrays are powerful tools to study genomic aberrations in cancer samples. Allele specific information from SNP arrays provides valuable information for interpreting copy number variation (CNV) and allelic imbalance including loss-of-heterozygosity (LOH) beyond that obtained from the total DNA signal available from array comparative genomic hybridization (aCGH) platforms. Several algorithms based on hidden Markov models (HMMs) have been designed to detect copy number changes and copy-neutral LOH making use of the allele information on SNP arrays. However heterogeneity in clinical samples, due to stromal contamination and somatic alterations, complicates analysis and interpretation of these data. Methods We have developed MixHMM, a novel hidden Markov model using hidden states based on chromosomal structural aberrations. MixHMM allows CNV detection for copy numbers up to 7 and allows more complete and accurate description of other forms of allelic imbalance, such as increased copy number LOH or imbalanced amplifications. MixHMM also incorporates a novel sample mixing model that allows detection of tumor CNV events in heterogeneous tumor samples, where cancer cells are mixed with a proportion of stromal cells. Conclusions We validate MixHMM and demonstrate its advantages with simulated samples, clinical tumor samples and a dilution series of mixed samples. We have shown that the CNVs of cancer cells in a tumor sample contaminated with up to 80% of stromal cells can be detected accurately using Illumina BeadChip and MixHMM. Availability The MixHMM is available as a Python package provided with some other useful tools at http://genecube.med.yale.edu:8080/MixHMM.

Lung adenocarcinoma (LUAD) is a heterogeneous and deadly subtype of non-small cell lung cancer that metastasizes rapidly to distant organs. Recent transcriptional profiling of primary LUADs by TCGA identified three molecular subgroups with unique clinical and biological features. Amongst the most aggressive LUADs are tumors classified in the proximal inflammatory (PI) subtype. However, the molecular mechanisms that dictate metastatic competence of this tumor type remain undefined. Using a bioinformatic approach, we found that PI tumors are significantly enriched for the expression of extracellular matrix genes and their corresponding cell surface receptors compared to tumors of other subtypes. Among these receptors, hyaluronan mediated motility receptor (HMMR) was found to be significantly upregulated. Knockdown of HMMR in LUAD cells decreased their potential to invade, migrate, and form colonies in vitro. In an experimental mouse model of metastasis, suppression of HMMR decreased metastatic incidence and burden. Interestingly, using an orthotopic model of LUAD, suppression of HMMR attenuated tumor initiating capacity of LUAD cells within an inflammatory microenvironment without affecting tumor progression. In distant organs, HMMR is similarly essential for tumor re-initiation and expansion of micrometastases to macrometastases. Our findings suggest that the aggressive behavior of PI LUADs requires the interaction between HMMR and the tumor microenvironment. Citation Format: Laura E. Stevens, Minghui Zhao, Zongzhi Liu, Don Nguyen. A novel molecular subset of metastatic lung adenocarcinoma is defined by the function of the proteoglycan receptor HMMR. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2269. doi:10.1158/1538-7445.AM2015-2269

Background: The receptor tyrosine kinase HER2 is overexpressed in 18-20% of breast cancers and is the target of the highly effective therapy, trastuzumab. Coamplicons are frequent in HER2 amplified tumors, yet their role in response to T is not defined. To identify amplicons which might predict response to T in patients we performed gene expression and copy number analysis in tumor tissue from a preoperative trial with brief exposure to T, followed by T+C. Methods: Fresh tumor core biopsies were taken before at a 2 week timepoint after a single dose of T (8mg/m2) from 80 HER2-overpressing, early breast cancer patients enrolled on a clinical trial of T>T+C. Nucleic acids were extracted using Qiagen AllPrep and were analyzed with Illumina Ref8 and Illumina QUAD 610 SNP arrays. Eight commonly amplified regions (11q13, 14q32, 17q12, 20q13, 21q22, 8p22, 8q24) were identified by FISH probe coordinates and copy number calculated using the GPHMM algorithm. Amplification was defined as 4 or more copies of the amplicon. Gene expression was analyzed in Bioconductor using LIMMA analysis. Genomic biomarkers were compared pathologic complete response (pCR) vs objective response (CR+PR) and non-response (SD+PD) by RECIST criteria at the surgical timepoint. Results: There were 50 tumor pairs with adequate RNA for gene expression and 40 baseline tumors for copy number analysis with 28 paired samples. In the 40 baseline biopsies, the 11q13 amplicon was present in 14/40 (35%) of tumors but never seen in tumors with a pCR (t-test; p=0.004975). Of note, in the tumors with amplification of 11q13 there was no evidence of change in copy number after exposure to T, however numbers were small (7 pairs). Gene expression of the 11q13 region showed no significant change in common amplicon genes after one dose of T. The 17q12 amplicon, which harbors the HER2 locus, was amplified in 35/40 (87.5%) of cases - copy number was not associated with response, however, HER2 and GRB7 gene expression levels significantly declined in pCR tumors compared with Conclusions: Integrated genomic analysis after brief exposure to T may provide useful predictors for response to T+C in early stage, HER2 positive breast cancer. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr PD07-08.

Background: Receptor tyrosine kinases (RTKs) modulate many oncogenic signaling pathways. RTKs can be activated as a result of feedback loops initiated from inhibition of downstream signaling components and contribute to resistance to small molecule targeted therapies. Target-specific inhibitors have provided many advances in cancer treatment, but it is becoming increasingly evident that single-agent treatment approaches are suboptimal. To address this, we performed single-agent compound screens against a panel of melanoma cell lines to select candidate agents for testing in combination agent screens (Cancer Discov 2013 3:52-67). One of the top single-agents effective in mutant BRAF melanomas was dovitinib (TKI258, CHIR258), a multi-RTK inhibitor shown to inhibit numerous type III, IV, and V RTKs. We present data examining the target profile of dovitinib in short-term cultured melanoma cell lines and describe effective partner agents for further testing as combination therapies. Materials and Methods: Twenty-five melanoma cell lines were screened against 150 agents. The most efficacious forty agents from the single-agent screen were collated and three consensus concentrations were determined for each compound to perform pair-wise combinations (Cancer Discov 2013 3:52-67). Growth inhibition was evaluated by ATP luminescent detection by CellTiterGlo®. Colony formation experiments were performed to confirm positive drug interactions. Phosphoproteomic approaches were used to further evaluate targets of dovitinib. Results: Dovitinib was one of the top hits from this single-agent screen that was effective in mutant BRAF melanoma cell lines. Dovitinib does not inhibit mutant BRAF directly, but inhibits RTKs. We found that multiple RTK targets of dovitinib are expressed and active in mutant BRAF melanoma cell lines. Furthermore, we found that dovitinib combines well with vemurafenib and MEK and AKT inhibitors to inhibit colony formation ability and cell proliferation. This was seen in both vemurafenib-sensitive and resistant cell lines. Conclusions: These findings further demonstrate the utility of using both single- and combination agent screening to determine genotype specific compound effects. Furthermore, these results support the rationale for using dovitinib as a partner agent with several small molecule inhibitors for melanoma combination therapy, especially in the vemurafenib-resistant setting. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B275. Citation Format: Casey G. Langdon, Matthew A. Held, Andrew B. Koo, Michael Klein, Zongzhi Liu, James T. Platt, David F. Stern. Dovitinib as a single-agent or in combination with other small molecule inhibitors for mutant BRAF melanomas. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B275.

Lung cancer is the leading cause of cancer-related deaths worldwide. This poor prognosis is due to the rapid metastatic progression of this disease, yet the mechanisms that govern lung cancer dissemination and colonization are unclear. Through an integrated approach, we identified an alveolar cell-selective gene signature that stratifies lung adenocarcinoma (ADC) into molecular subtypes of distinct prognosis and differentiation states. This transcriptional program is regulated in part by the cell fate transcription factors, GATA6 and HOPX, which are normally required for proper alveolar differentiation. In an experimental model, suppression of GATA6 and HOPX cooperatively enhances metastatic competence of lung ADC cells. Whole genome RNA sequencing reveals that this transcriptional network can modulate specific target genes and pathways involved in airway epithelial differentiation and invasion. Our findings identify a novel cell lineage molecular program whose perturbation enhances lung cancer metastasis. Citation Format: William K.C. Cheung, Minghui Zhao, Zongzhi Liu, Paul D. Cao, Laura E. Stevens, Thomas F. Westbrook, Don X. Nguyen. A lineage-selective transcriptional pathway linking lung differentiation and cancer metastasis. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3872. doi:10.1158/1538-7445.AM2013-3872

Lung cancer is the leading cause of cancer-related deaths worldwide. This poor prognosis is due to the rapid metastatic progression of this disease, yet the mechanisms that govern lung cancer dissemination and colonization are unclear. Through an integrated approach, we identified an alveolar cell-selective gene signature that stratifies lung adenocarcinoma (ADC) into molecular subtypes of distinct prognosis and differentiation states. This transcriptional program is regulated in part by the cell fate transcription factors, GATA6 and HOPX, which are normally required for proper alveolar differentiation. In an experimental model, suppression of GATA6 and HOPX cooperatively enhances metastatic competence of lung ADC cells. Whole genome RNA sequencing reveals that this transcriptional network can modulate specific target genes and pathways involved in airway epithelial differentiation and invasion. Our findings identify a novel cell lineage molecular program whose perturbation enhances lung cancer metastasis. Citation Format: William K.C. Cheung, Minghui Zhao, Zongzhi Liu, Paul D. Cao, Laura E. Stevens, Thomas F. Westbrook, Don X. Nguyen. A lineage-selective transcriptional pathway linking lung differentiation and cancer metastasis. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Invasion and Metastasis; Jan 20-23, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;73(3 Suppl):Abstract nr B56.

Metastasis and drug resistance are two major challenges in cancer therapies. The occurrence of these two events requires cancer cells to gain new mutations or change their expression profiling, or both, adapt to new environment (i.e. distal organs or drug treatments). These changes likely follow Darwin's evolutionary theory: heterogeneous of cancer cells are generated randomly and more aggressive cells are selected by the tissue environment. Stable inheritance of genome and epigenetic states could delay metastasis and drug resistance. Trimethylated lysine 4 in histone H3 (H3K4me3) is the epigenetic marker for transcriptionally active promoters and the binding site for transcriptional activators. Removing the methyl groups from trimethylated H3K4 on gene promoter regions is a common epigenetic strategy for gene silencing. The JARID1 family members are to date the only known proteins responsible for catalyzing demethylation of trimethylated H3K4. Therefore they are essential in cell differentiation and development. Even though JARID1A (RBP2) was implicated in tumorigenesis of certain cancer types, its exact roles are still poorly understood. I hypothesized that RBP2 contributes to changes of epigenetic states during the occurrence of metastasis and drug resistance. Consistent with my hypothesis, I found that RBP2 is highly expressed in metastatic breast cancer cells and Herceptin tolerant population. Loss of RBP2 decreased lung metastatic gene signature and increase drug sensitivity. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-389. doi:1538-7445.AM2012-LB-389