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Checkpoint inhibitors have proven effectiveness in clinical trials for non-small cell lung cancer (NSCLC) patients, but if this is congruent with routine patient care is discussed. We present real-world experience with the PD1-inhibitor nivolumab in NSCLC.Patients with NSCLC were considered eligible for nivolumab treatment after one or more lines of chemotherapy, and when in reasonable performance status (PS) [Eastern Cooperative Oncology Group (ECOG) 3]. Treatment was given according to guidelines in the two phase III studies, CA209017 and CA209057. Response evaluation was done according to Recist 1.1, and treatment given until unequivocal progression or intolerable toxicity.Fifty-eight patients (30 females) commenced therapy in the period June-August 2015. Median age was 64.6 years (range 32.3-88.2). Twenty-four patients had squamous cell carcinoma and 32 adenocarcinoma, 38 had received two or more prior lines of therapy. Fourteen cases (24%) were in ECOG PS 2. After a medium observation time of 14.3 months, 13 (22%) are still in treatment. Median time to treatment failure (TTF) was 4.0 months, 34% were off treatment during the first two months. Median overall survival (OS) is 11.7 months. There was no difference in TTF or OS among patients with squamous versus non-squamous histology or between 1 versus1 prior line of therapy. Four patients (7%) were off treatment due to toxicity, none were grade 4 or 5.Nivolumab treatment outside clinical trials seems to perform as expected.

Lung neuroendocrine tumors (LNETs) comprise small-cell lung cancer (SCLC), large-cell neuroendocrine tumors (LCNEC), and pulmonary carcinoids (PCA), and account for 25% of all lung cancer cases. The low 5-year survival rate of the highly aggressive LNETs (SCLC and LCNEC) combined with the lack of an effective treatment, suggest that understanding how these tumors arise and identifying therapeutic targets are unmet needs. We performed genome/exome, and transcriptome sequencing of 29 SCLC (Ref.1), 60 LCNEC, and 45 PCA to better understand their molecular origin and identify altered genes that may offer therapeutic opportunities. In contrast to SCLC and LCNEC, we found that RB1 and TP53 mutations were rare events in PCA suggesting that PCA are not early progenitor lesions of SCLC or LCNEC, but arise through independent mechanisms. Moreover, GSEA analysis showed that genes of the RB1 pathway were downregulated in SCLC but not in PCA. Our data also show that inactivation of chromatin-remodeling genes, specifically genes involved in histone methylation and subunits of the SWI/SNF complex, is sufficient to drive transformation in PCA. In a preliminary analysis of 15 LCNEC (Ref.2) we observed a predominance of mutations typical of SCLC, such as RB1, TP53, and CREBBP/EP300. In this larger series, we additionally found samples with mutations frequent in adenocarcinoma (AD) or squamous (SQ) lung cancer. We could then distinguish two well-defined groups of LCNEC: a SCLC-like group, carrying MYCL1 amplifications and mutations in both RB1 and TP53 genes; and an AD/SQ-like group, harbouring CDKN2A deletions, TTF1 amplifications, and frequent mutations in KEAP1 and STK11. Interestingly, RB1, STK11, and KEAP1 mutations happened in an almost mutually exclusive way. These data suggest that LCNEC might represent an evolutionary trunk that can branch to SCLC or AD/SQ, and also that LNETs and non-LNETs are not completely different entities. This is already suggested by the fact that one of the resistance mechanisms of EGFR-mutant adenocarcinomas to tyrosine-kinase inhibitors is through trans-differentiation to SCLC (Ref.3). Finally, we also identified new targetable driver genes in SCLC and LCNEC: FGFR1 amplifications were observed in 6% and 18% of the cases respectively; PTEN mutations were identified in 10% of the SCLC cases; and interestingly, one of the LCNEC samples (belonging to the SCLC-like group) harboured an activating RFWD2-NTRK1 fusion gene suggesting that fusions affecting NTRK1 may not only be a targetable opportunity for AD (Ref.4) but also for LCNEC and, based on the molecular similarities, also SCLC. (1) Peifer and Fernandez-Cuesta et al. Nat Genetics 2012 (2) The Clinical Lung Cancer Genome Project (CLCGP) and Network Genomic Medicine (NGM) Sci Transl Med 2013 (3) Sequist et al., Sci Transl Med 2011 (4) Vaishnavi et al. Nat Medicine 2013 Citation Format: Lynnette Fernandez-Cuesta, Martin Peifer, Xin Lu, Danila Seidel, Thomas Zander, Frauke Leenders, Luka Ozretić, Odd-Terje Brustugun, John K. Field, Gavin Wright, Benjamin Solomon, Reinhard Buettner, Christian Brambilla, Elisabeth Brambilla, Roman K. Thomas. Cross-entity mutation analysis of lung neuroendocrine tumors sheds light into their molecular origin and identifies new therapeutic targets. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1531. doi:10.1158/1538-7445.AM2014-1531

Aim: Novel molecularly targeted agents such as small molecule kinase inhibitors and antibodies targeted against immune check-point inhibitors have begun to erode the dominant position held by platinum-based chemotherapy in the treatment of NSCLC. While in some cases, activating kinase mutations appear to be mutually exclusive (EGFR and KRAS), there are many overlapping molecular subsets within NSCLC. As we continue to develop novel drugs, it is important that we develop a greater understanding of the prevalence, overlap, and prognostic significance of drug targets including activating mutations, signaling pathways, and tumor immune markers, as this will aid in trial design and predictive biomarker development for drug combinations or sequential treatment regimens. Methods: Seven biomarkers - TTF1, p63, EGFR mutation, KRAS mutation, MET immunohistochemistry [IHC], PDL1 IHC, NaPI2B IHC- across two sample sets (Set 1, n = 561; Set 2, n = 310) were tested. Set 1 contained surgically resected cases obtained at MD Anderson Cancer Center (MDA) during 2003-2005. Samples from Set 2 were part of a collaboration between the University of Colorado Cancer Center (UofC), USA and The Norwegian Radium Hospital, and contained surgically-resected NSCLC tissues collected from 2006–2011. Results: The prevalence, overlap, and prognostic significance of each biomarker were compared between the two cohorts. Most endpoints were consistent between the cohorts. However, significant differences in prevalence were observed within adenocarcinomas for MET (50% vs. 34%, MDA vs. UofC; p 67% of patients in both cohorts were positive for more than one biomarker and >33% were positive for at least three biomarkers. Correlations with patient characteristics and outcomes will be described in further detail. Conclusions: These data suggest that the biomarker landscape in NSCLC is complex with most patients having multiple targetable alterations. Thus, the treatment landscape for NSCLC will become increasingly complex as more experimental agents approach pivotal testing. Disclosure: D. Shames, M. Kowanetz, Y. Xiao, Y. Choi, H. Koeppen, R. Firestein, Y. Wang, S. Mocci, C. Bowden and L.C. Amler all declare that: I am an employee of Genentech Inc. I own stock in Roche Holdings. All other authors have declared no conflicts of interest.

Aim: NaPi2b belongs to the type II family of sodium-dependent phosphate co-transporters, physiologically expressed in type II pneumocytes of lung and on the brush border membrane of small intestine. Increased expression of NaPi2b was recently described in ovary, thyroid and breast cancer. The aim of this study was to evaluate NaPi2b expression in lung cancer. Methods: Immunohistochemistry using the 10H1 primary antibody (Genentech) was performed on two cohorts of treatment naive resected NSCLC patients collected at MD Anderson, University of Texas, USA (training cohort, N = 415) and University of Oslo, Norway (testing cohort, N = 350). Moreover, 67 lung cancer cell lines were analyzed (51 non-small cell and 16 small cell lung cancer). EGFR and KRAS mutations were evaluated with the SnapShot assay. NaPi2b protein expression was scored using the H-score method (0-300). Expression was defined as high or low according to a H-score cut-off value of 200. Results: Patient characteristics did not differ significantly in the two cohorts. In the training and testing cohorts high levels of NaPi2b were detected in 48.4% and 64% of patients, respectively. Adenocarcinomas (AC) were found to express significantly higher levels of NaPi2b than squamous cell carcinoma (SqCC) (AC vs SqCC median H-score: 248 vs 11, p Conclusions: NaPi2b is a prognostic marker in NSCLC and is strongly associated with important clinicopathological and biological variables such as histology and driver mutation status. Further studies are warranted to clarify the role of NaPi2b in tumor development and progression, as well as its association with driver mutations. Disclosure: O.T. Brustugun received research funding from Roche, Astrazeneca and GlaxoSmithKline; Y. Xiao is a Genentech employee and owns stock in Roche Holdings; Y. Choi is en amployee of Genetech Inc and owns stock in Roche Holdings; Y. Wang is an employee of Genentech Inc and owns stock in Roche Holdings; R. Firestein is an employee of Genentech Inc and owns stock in Roche Holdings; A. Helland received research funding from Roche, AstraZeneca and GlaxoSmithKline; F.R. Hirsch received research funding from Celgene, Genentech, Ventana, Lilly, Imclone and Amgen, and received compensation from Genentech/Roche, Novartis, Pfizer, Brystol-Meyers Squibb, Amgen and Lilly for partecipating in their advisory boards; D. Shames is an employee of Genetech Inc and owns stock in Roche Holdings. All other authors have declared no conflicts of interest.

Introduction: Lung cancer is the most common cause of cancer deaths worldwide. The findings of new mutations and the development of targeted therapies have improved lung cancer management. Still, the prognosis remains poor and we need to know more about the genetic and epigenetic alterations in the tumors to better understand the biology of lung cancer. MicroRNAs are small non-coding RNAs that are involved in crucial biological processes in carcinogenesis by regulating gene expression at the post transcriptional level. In this project we have studied the microRNA expression patterns of lung adenocarcinomas and correspondent tumor-adjacent normal lung tissue and correlated the expression patterns with clinical data and mutational status. Methods: We have examined microRNA expression pattern in tumor tissues from 154 surgically resected lung adenocarcinomas and from 20 tumor-adjacent normal lung tissue samples. The expression of 1205 human microRNAs was conducted using the 60K microRNA microarray from Agilent technology. EGFR and KRAS mutation analyses were also performed. The analysis of differentially expressed microRNAs between groups of samples was done using significance analyses of microarrays (SAM) in the J-express software. We also performed survival analysis using univariate- and multivariate Cox regression analysis. The results are about to be validated by qRT-PCR. Results: Preliminary results show 129 differentially expressed microRNAs in tumor compared to the tumor-adjacent normal lung tissue. EGFR and KRAS mutations were found in 22/152 (14.5%) and 47/137 (34.3%) samples respectively. We have detected 17 microRNAs that are differentially expressed in EGFR mutated tumors compared to EGFR wildtype tumors. Two microRNAs were identified to have a strong association with time to progression in both univariate- and multivariate Cox regression analysis. Discussion: The microRNAs are thought to play an essential role in the development and progression of human malignancies, including lung cancer. We have identified several aberrantly expressed microRNAs that can discriminate lung adenocarcinoma tumor tissue from tumor-adjacent normal lung tissue samples. This can lead to the identification of biomarkers for early detection. 17 microRNAs were differentially expressed between EGFR mutated- and EGFR wt lung adenocarcinomas suggesting that microRNAs can be used as molecular biomarkers for lung cancer classification. We have also identified microRNAs that can be used as prognostic biomarkers. We are now confirming our results with qRT-PCR. We hypothesize that microRNA can be used as biomarkers for classification and clinical course. Citation Format: Maria Bjaanæs, Rita Halvorsen, Steinar Solberg, Lars Jørgensen, Odd-Terje Brustugun, Åslaug Helland. Differentially expressed microRNAs in adenocarcinomas of the lung and tumor-adjacent normal lung tissue. [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 1962. doi:10.1158/1538-7445.AM2013-1962