Analysis of real-world data to investigate evolving treatment sequencing patterns in advanced non-small cell lung cancers and their impact on survival.

Background: Although optimal sequencing of systemic therapy in cancer care is critical to achieving maximal clinical benefit, there is a lack of analysis of treatment sequencing in advanced non-small cell lung cancer (aNSCLC) in real-world settings. Methods: A retrospective cohort study of 13,340 lung cancer patients within the Mount Sinai Health System (MSHS) was performed. Systemic therapy data of aNSCLC in 2,106 patients was the starting point in our analysis to investigate how treatment sequencing has evolved, the impact of sequencing patterns on clinical outcomes, and the effectiveness of 2nd line chemotherapy after patients progressed on immune checkpoint inhibitor (ICI)-based therapy as the 1st line of therapy (LOT). Results: There is a significant shift to more ICI-based therapy and multiple lines of targeted therapy after 2015. We compared clinical outcomes of two patient populations with different treatment sequencing patterns, with the 1st group receiving chemotherapy as the 1st LOT followed by ICI-based treatment, and the 2nd group treated in the opposite order receiving a 1st line ICI-containing regimen followed by a 2nd line chemotherapy. No statistically significant difference in overall survival (OS) was observed between the two groups [group 2 vs. group 1, adjusted hazard ratio (aHR) =1.36, P=0.39]. We assessed the efficacy of the 2nd line chemotherapy in three patient populations given either 1st line ICI single agent, 1st line ICI-chemotherapy combination, or 1st line chemotherapy alone, there was no statistically significant difference in time-to-next treatment (TTNT) and in OS among the three patient groups. Conclusions: Analysis of real-world data has shown two treatment sequencing patterns in aNSCLC, ICI followed by chemotherapy or chemotherapy followed by ICI, achieved similar clinical benefit. The chemotherapies routinely used following platinum doublet 1st LOT, is effective as the 2nd line option after ICI-chemotherapy combination in the 1st line setting.

Analysis of Real-World Data to Investigate the Impact of Race and Ethnicity on Response to Programmed Cell Death-1 and Programmed Cell Death-Ligand 1 Inhibitors in Advanced Non-Small Cell Lung Cancers.

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.

A composite biomarker of neutrophil-lymphocyte ratio and hemoglobin level correlates with clinical response to PD-1 and PD-L1 inhibitors in advanced non-small cell lung cancers.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been incorporated into various clinical oncology guidelines for systemic treatment of advanced non-small cell lung cancers (aNSCLC). However, less than 50% (and 20%) of the patients responded to the therapy as a first (or second) line of therapy. PD-L1 immunohistochemistry (IHC) is an extensively studied biomarker of response to ICI, but results from this test have equivocal predictive power. In order to identify other biomarkers that support clinical decision-making around whether to treat with ICIs or not, we performed a retrospective study of patients with aNSCLC who underwent ICI-based therapy in the Mount Sinai Health System between 2014 and 2019. METHODS: We analyzed data from standard laboratory tests performed in patients as a part of the routine clinical workup during treatment, including complete blood counts (CBC) and a comprehensive metabolic panel (CMP), to correlate test results with clinical response and survival. RESULTS: Of 11,138 NSCLC patients identified, 249 had been treated with ICIs. We found associations between high neutrophil-to-lymphocyte ratio (NLR ≥ 5) and poor survival in ICI-treated NSCLC. We further observed that sustained high NLR after initiation of treatment had a more profound impact on survival than baseline NLR, regardless of PD-L1 status. Hazard ratios when comparing patients with NLR ≥ 5 vs. NLR < 5 are 1.7 (p = 0.02), 3.4 (p = 4.2 × 10- 8), and 3.9 (p = 1.4 × 10- 6) at baseline, 2-8 weeks, and 8-14 weeks after treatment start, respectively. Mild anemia, defined as hemoglobin (HGB) less than 12 g/dL was correlated with survival independently of NLR. Finally, we developed a composite NLR and HGB biomarker. Patients with pretreatment NLR ≥ 5 and HGB < 12 g/dL had a median overall survival (OS) of 8.0 months (95% CI 4.5-11.5) compared to the rest of the cohort with a median OS not reached (95% CI 15.9-NE, p = 1.8 × 10- 5), and a hazard ratio of 2.6 (95% CI 1.7-4.1, p = 3.5 × 10- 5). CONCLUSIONS: We developed a novel composite biomarker for ICI-based therapy in NSCLC based on routine CBC tests, which may provide meaningful clinical utility to guide treatment decision. The results suggest that treatment of anemia to elevate HGB before initiation of ICI therapy may improve patient outcomes or the use of alternative non-chemotherapy containing regimens.

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

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Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits.

BACKGROUND: Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. RESULTS: We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. CONCLUSION: In sum, by integrating genetic and electronic medical record data, and leveraging one of the world's largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

Melanocortin 4 Receptor Pathway Dysfunction in Obesity: Patient Stratification Aimed at MC4R Agonist Treatment.

Context: The hypothalamic melanocortin 4 receptor (MC4R) pathway serves a critical role in regulating body weight. Loss of function (LoF) mutations in the MC4R pathway, including mutations in the pro-opiomelanocortin (POMC), prohormone convertase 1 (PCSK1), leptin receptor (LEPR), or MC4R genes, have been shown to cause early-onset severe obesity. Methods: Through a comprehensive epidemiological analysis of known and predicted LoF variants in the POMC, PCSK1, and LEPR genes, we sought to estimate the number of US individuals with biallelic MC4R pathway LoF variants. Results: We predict ~650 α-melanocyte-stimulating hormone (MSH)/POMC, 8500 PCSK1, and 3600 LEPR homozygous and compound heterozygous individuals in the United States, cumulatively enumerating >12,800 MC4R pathway-deficient obese patients. Few of these variants have been genetically diagnosed to date. These estimates increase when we include a small subset of less rare variants: ß-MSH/POMC,PCSK1 N221D, and a PCSK1 LoF variant (T640A). To further define the MC4R pathway and its potential impact on obesity, we tested associations between body mass index (BMI) and LoF mutation burden in the POMC, PCSK1, and LEPR genes in various populations. We show that the cumulative allele burden in individuals with two or more LoF alleles in one or more genes in the MC4R pathway are predisposed to a higher BMI than noncarriers or heterozygous LoF carriers with a defect in only one gene. Conclusions: Our analysis represents a genetically rationalized study of the hypothalamic MC4R pathway aimed at genetic patient stratification to determine which obese subpopulations should be studied to elucidate MC4R agonist (e.g., setmelanotide) treatment responsiveness.

APPLICATIONS OF GENETICS, GENOMICS AND BIOINFORMATICS IN DRUG DISCOVERY.

As the impact of genetics, genomics, and bioinformatics on drug discovery has been increasingly recognized, this session of the 2018 Pacific Symposium on Biocomputing (PSB) aims to facilitate scientific discussions between academia and pharmaceutical industry on how to best apply genetics, genomics and bioinformatics to enable drug discovery. The selected papers focus on developing and applying computational approaches to understand drug mechanisms of action and develop drug combination strategies, to enable in silico drug screening, and to further delineate disease pathways for target identification and validation.

Extraordinary clinical benefit to sequential treatment with targeted therapy and immunotherapy of a BRAF V600E and PD-L1 positive metastatic lung adenocarcinoma.

BACKGROUND: The treatment algorithm for metastatic non-small cell lung cancers (NSCLCs) has been evolving rapidly due to the development of new therapeutic agents. Although guidelines are provided by National Comprehensive Cancer Network (NCCN) for treatment options according to biomarker testing results, sequentially applying the three main modalities (chemotherapy, targeted therapy and immunotherapy) remains an ad hoc practice in clinic. In light of recent FDA approval of dabrafenib and trametinib combination for metastatic NSCLCs with BRAF V600E mutation, one question arises due to insufficient clinical data is if the targeted therapy should be used before immunotherapy in patients with both BRAF V600E and PD-L1 expression. CASE PRESENTATION: We present a case of 74-year-old female, former smoker with metastatic lung adenocarcinoma. The BRAF V600E mutation among other abnormalities was identified by comprehensive genomic profiling. The patient had an excellent 2-year response to the combination of pemetrexed and sorafenib. The patient was then treated with dabrafenib due to the presence of the BRAF V600E mutation and intolerance to cytotoxic chemotherapy. Not only the patient had an 18-month durable response to dabrafenib, she experienced outstanding quality of life with no serious adverse effects. At the time of symptomatic progression, the patient was then treated with two cycles of pembrolizumab based on her positive PD-L1 staining (90%). She had early response and came off pembrolizumab due to side effects. Seven months after initiation of pembrolizumab, the patient is off all the therapy and is currently asymptomatic. The patient is surviving with metastatic disease for over 7 years as of to date. CONCLUSIONS: By appropriately sequencing the three main modalities of systemic therapies, we are able to achieve long-term disease control with minimal side effects even in a geriatric patient with multiple comorbidities. We argue that it is reasonable to first use a BRAF inhibitor before considering immunotherapy for NSCLCs positive for both BRAF V600E and PD-L1.

Cancer gene profiling in non-small cell lung cancers reveals activating mutations in JAK2 and JAK3 with therapeutic implications.

BACKGROUND: Next-generation sequencing (NGS) of cancer gene panels are widely applied to enable personalized cancer therapy and to identify novel oncogenic mutations. METHODS: We performed targeted NGS on 932 clinical cases of non-small-cell lung cancers (NSCLCs) using the Ion AmpliSeq™ Cancer Hotspot panel v2 assay. RESULTS: Actionable mutations were identified in 65% of the cases with available targeted therapeutic options, including 26% of the patients with mutations in National Comprehensive Cancer Network (NCCN) guideline genes. Most notably, we discovered JAK2 p.V617F somatic mutation, a hallmark of myeloproliferative neoplasms, in 1% (9/932) of the NSCLCs. Analysis of cancer cell line pharmacogenomic data showed that a high level of JAK2 expression in a panel of NSCLC cell lines is correlated with increased sensitivity to a selective JAK2 inhibitor. Further analysis of TCGA genomic data revealed JAK2 gain or loss due to genetic alterations in NSCLC clinical samples are associated with significantly elevated or reduced PD-L1 expression, suggesting that the activating JAK2 p.V617F mutation could confer sensitivity to both JAK inhibitors and anti-PD1 immunotherapy. We also detected JAK3 germline activating mutations in 6.7% (62/932) of the patients who may benefit from anti-PD1 treatment, in light of recent findings that JAK3 mutations upregulate PD-L1 expression. CONCLUSION: Taken together, this study demonstrated the clinical utility of targeted NGS with a focused hotspot cancer gene panel in NSCLCs and identified activating mutations in JAK2 and JAK3 with clinical implications inferred through integrative analysis of cancer genetic, genomic, and pharmacogenomic data. The potential of JAK2 and JAK3 mutations as response markers for the targeted therapy against JAK kinases or anti-PD1 immunotherapy warrants further investigation.

Genomic profiling reveals mutational landscape in parathyroid carcinomas.

Parathyroid carcinoma (PC) is an extremely rare malignancy lacking effective therapeutic intervention. We generated and analyzed whole-exome sequencing data from 17 patients to identify somatic and germline genetic alterations. A panel of selected genes was sequenced in a 7-tumor expansion cohort. We show that 47% (8 of 17) of the tumors harbor somatic mutations in the CDC73 tumor suppressor, with germline inactivating variants in 4 of the 8 patients. The PI3K/AKT/mTOR pathway was altered in 21% of the 24 cases, revealing a major oncogenic pathway in PC. We observed CCND1 amplification in 29% of the 17 patients, and a previously unreported recurrent mutation in putative kinase ADCK1. We identified the first sporadic PCs with somatic mutations in the Wnt canonical pathway, complementing previously described epigenetic mechanisms mediating Wnt activation. This is the largest genomic sequencing study of PC, and represents major progress toward a full molecular characterization of this rare malignancy to inform improved and individualized treatments.

Pulmonary Sarcomatoid Carcinomas Commonly Harbor Either Potentially Targetable Genomic Alterations or High Tumor Mutational Burden as Observed by Comprehensive Genomic Profiling.

INTRODUCTION: Pulmonary sarcomatoid carcinoma (PSC) is a high-grade NSCLC characterized by poor prognosis and resistance to chemotherapy. Development of targeted therapeutic strategies for PSC has been hampered because of limited and inconsistent molecular characterization. METHODS: Hybrid capture-based comprehensive genomic profiling was performed on DNA from formalin-fixed paraffin-embedded sections of 15,867 NSCLCs, including 125 PSCs (0.8%). Tumor mutational burden (TMB) was calculated from 1.11 megabases (Mb) of sequenced DNA. RESULTS: The median age of the patients with PSC was 67 years (range 32-87), 58% were male, and 78% had stage IV disease. Tumor protein p53 gene (TP53) genomic alterations (GAs) were identified in 74% of cases, which had genomics distinct from TP53 wild-type cases, and 62% featured a GA in KRAS (34%) or one of seven genes currently recommended for testing in the National Comprehensive Cancer Network NSCLC guidelines, including the following: hepatocyte growth factor receptor gene (MET) (13.6%), EGFR (8.8%), BRAF (7.2%), erb-b2 receptor tyrosine kinase 2 gene (HER2) (1.6%), and ret proto-oncogene (RET) (0.8%). MET exon 14 alterations were enriched in PSC (12%) compared with non-PSC NSCLCs (∼3%) (p < 0.0001) and were more prevalent in PSC cases with an adenocarcinoma component. The fraction of PSC with a high TMB (>20 mutations per Mb) was notably higher than in non-PSC NSCLC (20% versus 14%, p = 0.056). Of nine patients with PSC treated with targeted or immunotherapies, three had partial responses and three had stable disease. CONCLUSION: Potentially targetable GAs in National Comprehensive Cancer Network NSCLC genes (30%) or intermediate or high TMB (43%, >10 mutations per Mb) were identified in most of the PSC cases. Thus, the use of comprehensive genomic profiling in clinical care may provide important treatment options for a historically poorly characterized and difficult to treat disease.

IDENTIFY CANCER DRIVER GENES THROUGH SHARED MENDELIAN DISEASE PATHOGENIC VARIANTS AND CANCER SOMATIC MUTATIONS.

Genomic sequencing studies in the past several years have yielded a large number of cancer somatic mutations. There remains a major challenge in delineating a small fraction of somatic mutations that are oncogenic drivers from a background of predominantly passenger mutations. Although computational tools have been developed to predict the functional impact of mutations, their utility is limited. In this study, we applied an alternative approach to identify potentially novel cancer drivers as those somatic mutations that overlap with known pathogenic mutations in Mendelian diseases. We hypothesize that those shared mutations are more likely to be cancer drivers because they have the established molecular mechanisms to impact protein functions. We first show that the overlap between somatic mutations in COSMIC and pathogenic genetic variants in HGMD is associated with high mutation frequency in cancers and is enriched for known cancer genes. We then attempted to identify putative tumor suppressors based on the number of distinct HGMD/COSMIC overlapping mutations in a given gene, and our results suggest that ion channels, collagens and Marfan syndrome associated genes may represent new classes of tumor suppressors. To elucidate potentially novel oncogenes, we identified those HGMD/COSMIC overlapping mutations that are not only highly recurrent but also mutually exclusive from previously characterized oncogenic mutations in each specific cancer type. Taken together, our study represents a novel approach to discover new cancer genes from the vast amount of cancer genome sequencing data.

Network expansion and pathway enrichment analysis towards biologically significant findings from microarrays.

In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease), and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA) for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI) database, and pathway enrichment from the human pathway database (HPD). We use a recently-published microarray dataset (GSE24215) related to insulin resistance and type 2 diabetes (T2D) as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

Glycerolipid acyltransferases in triglyceride metabolism and energy homeostasis-potential as drug targets.

Glycerolipid acyltransfereases play important roles in physiological and pathophysiological processes of triglyceride (TAG) metabolism and energy balance. Glycerol-3-phosphate acyltransferases (GPATs) are key enzymes in the triglyceride biosynthetic pathway. In addition to the mitochondrial GPAT1 that was first cloned and studied, novel microsomal enzyme isoforms have been discovered in recent years. The potential function of one of the GPATs, GPAT4, was studied in GPAT4 deficient mice that suggested its role in TAG synthesis in multiple tissues. Monoacylglycerol and diacylglycerol acyltransferases (MGAT2 and DGAT1) are important enzymes involved in intestinal triglyceride absorption, and studies in recent years from knockout mice have revealed their important role in whole body energy metabolism through changes in intestinal TAG absorption kinetics. Both MGAT2 and DGAT1 mice are resistant to dietinduced obesity and have improved insulin sensitivity and hepatic TAG accumulation. These data suggest that these enzymes are intimately involved in TAG metabolism and whole body energy homeostasis and that inhibition of these enzymes may provide therapeutic benefits for metabolic disorders such as obesity, metabolic syndrome, and type 2 diabetes.

The acyl coenzymeA:monoacylglycerol acyltransferase 3 (MGAT3) gene is a pseudogene in mice but encodes a functional enzyme in rats.

Triglyceride (TAG) absorption involves its initial hydrolysis to fatty acids and monoacylglycerol (MAG), which are resynthesized back to diacylglycerol (DAG) and TAG within enterocytes. The resynthesis of DAG is facilitated by fatty acyl-CoA dependent monoacylglycerol acyltransferases (MGATs). Three MGAT enzymes have been isolated in humans and the expression of MGAT2 and MGAT3 in the intestines suggests their functional role in the TAG absorption. In this paper, we report that the Mogat3 gene appears to be a pseudogene in mice while it is a functional gene in rats. Examination of the mouse genomic Mogat3 sequence revealed multiple changes that would result in a translational stop codon or frameshifts. The rat Mogat3 gene, however, is predicted to encode a functional enzyme of 362 amino acids. Expression of rat MGAT3 in human embryonic kidney 293 (HEK293) cells led to the formation of a 36-kDa protein that displayed significant MGAT but not DGAT activity. Tissue expression analysis of rat MGAT3 by real-time PCR analysis indicated that rat MGAT3 has a high level of expression in intestines and pancreas. Our results thus provide the molecular basis to understand the relative functional role of MGAT2 and MGAT3 and also for future exploration of MGAT3 function in animal models.