Danielle Greenawalt

Abstract KRAS is the most common oncogenic driver in lung adenocarcinoma (LUAC). We previously reported that STK11/LKB1 (KL) or TP53 (KP) comutations define distinct subgroups of KRAS-mutant LUAC. Here, we examine the efficacy of PD-1 inhibitors in these subgroups. Objective response rates to PD-1 blockade differed significantly among KL (7.4%), KP (35.7%), and K-only (28.6%) subgroups (P < 0.001) in the Stand Up To Cancer (SU2C) cohort (174 patients) with KRAS-mutant LUAC and in patients treated with nivolumab in the CheckMate-057 phase III trial (0% vs. 57.1% vs. 18.2%; P = 0.047). In the SU2C cohort, KL LUAC exhibited shorter progression-free (P < 0.001) and overall (P = 0.0015) survival compared with KRASMUT;STK11/LKB1WT LUAC. Among 924 LUACs, STK11/LKB1 alterations were the only marker significantly associated with PD-L1 negativity in TMBIntermediate/High LUAC. The impact of STK11/LKB1 alterations on clinical outcomes with PD-1/PD-L1 inhibitors extended to PD-L1–positive non–small cell lung cancer. In Kras-mutant murine LUAC models, Stk11/Lkb1 loss promoted PD-1/PD-L1 inhibitor resistance, suggesting a causal role. Our results identify STK11/LKB1 alterations as a major driver of primary resistance to PD-1 blockade in KRAS-mutant LUAC. Significance: This work identifies STK11/LKB1 alterations as the most prevalent genomic driver of primary resistance to PD-1 axis inhibitors in KRAS-mutant lung adenocarcinoma. Genomic profiling may enhance the predictive utility of PD-L1 expression and tumor mutation burden and facilitate establishment of personalized combination immunotherapy approaches for genomically defined LUAC subsets. Cancer Discov; 8(7); 822–35. ©2018 AACR. See related commentary by Etxeberria et al., p. 794. This article is highlighted in the In This Issue feature, p. 781

Murine syngeneic tumor models are critical to novel immuno-based therapy development, but the molecular and immunologic features of these models are still not clearly defined. The translational relevance of differences between the models is not fully understood, impeding appropriate preclinical model selection for target validation, and ultimately hindering drug development. Across a panel of commonly used murine syngeneic tumor models, we showed variable responsiveness to immunotherapies. We used array comparative genomic hybridization, whole-exome sequencing, exon microarray analysis, and flow cytometry to extensively characterize these models, which revealed striking differences that may underlie these contrasting response profiles. We identified strong differential gene expression in immune-related pathways and changes in immune cell-specific genes that suggested differences in tumor immune infiltrates between models. Further investigation using flow cytometry showed differences in both the composition and magnitude of the tumor immune infiltrates, identifying models that harbor "inflamed" and "non-inflamed" tumor immune infiltrate phenotypes. We also found that immunosuppressive cell types predominated in syngeneic mouse tumor models that did not respond to immune-checkpoint blockade, whereas cytotoxic effector immune cells were enriched in responsive models. A cytotoxic cell-rich tumor immune infiltrate has been correlated with increased efficacy of immunotherapies in the clinic, and these differences could underlie the varying response profiles to immunotherapy between the syngeneic models. This characterization highlighted the importance of extensive profiling and will enable investigators to select appropriate models to interrogate the activity of immunotherapies as well as combinations with targeted therapies in vivo Cancer Immunol Res; 5(1); 29-41. ©2016 AACR.

Agents targeting the PD1-PDL1 axis have transformed cancer therapy. Factors that influence clinical response to PD1-PDL1 inhibitors include tumor mutational burden, immune infiltration of the tumor and local PDL1 expression. To identify peripheral correlates of the anti-tumor immune response in the absence of checkpoint blockade, we performed a retrospective study of circulating T cell subpopulations and matched tumor gene expression in melanoma and non-small cell lung carcinoma (NSCLC) patients. Notably, both melanoma and NSCLC patients whose tumors exhibited increased inflammatory gene transcripts presented high CD4+ and CD8+ central memory T cell (CM) to effector T cell (Eff) ratios in blood. Consequently, we evaluated CM/Eff T cell ratios in a second cohort of NSCLC. The data showed that high CM/Eff T cell ratios correlated with increased tumor PDL1 expression. Furthermore, of the 22 patients within this NSCLC cohort who received nivolumab, those with high CM/Eff T cell ratios, had longer progression-free survival (PFS) (median survival: 91 vs. 215 days). These findings show that by providing a window into the state of the immune system, peripheral T cell subpopulations inform about the state of the anti-tumor immune response and identify potential blood biomarkers of clinical response to checkpoint inhibitors in melanoma and NSCLC.

Esophageal cancer is a particularly aggressive tumor with poor prognosis, however, our current knowledge of the genes and pathways involved in tumorigenesis of the esophagus are limited. To obtain insight into the molecular processes underlying tumorigenesis of the esophagus, we have used cDNA microarrays to compare the gene expression profiles of 128 tissue samples representing the major histological subtypes of esophageal cancer (squamous cell carcinoma and adenocarcinoma (ADC)) as well as Barrett's esophagus (BE), the precursor lesion to ADC, and normal esophageal epithelium. Linear discriminant analysis and unsupervised hierarchical clustering show the separation of samples into 4 distinct groups consistent with their histological subtype. Differentially expressed genes were identified between each of the tissue types. Comparison of gene ontologies and gene expression profiles identified gene profiles specific to esophageal cancer, as well as BE. "Esophageal cancer clusters," representing proliferation, immune response, and extracellular matrix genes were identified, as well as digestion, hydrolase, and transcription factor clusters specific to the columnar phenotype observed during BE and esophageal ADC. These clusters provide valuable insight into the molecular and functional differences between normal esophageal epithelium, BE, and the 2 histologically distinct forms of esophageal cancers. Our thorough, unbiased analysis provides a rich source of data for further studies into the molecular basis of tumorigenesis of the esophagus, as well as identification of potential biomarkers for early detection of progression.