Purpose Treatment of advanced non-small-cell lung cancer with immune checkpoint inhibitors (ICIs) is characterized by durable responses and improved survival in a subset of patients. Clinically available tools to optimize use of ICIs and understand the molecular determinants of response are needed. Targeted next-generation sequencing (NGS) is increasingly routine, but its role in identifying predictors of response to ICIs is not known. Methods Detailed clinical annotation and response data were collected for patients with advanced non-small-cell lung cancer treated with anti-programmed death-1 or anti-programmed death-ligand 1 [anti-programmed cell death (PD)-1] therapy and profiled by targeted NGS (MSK-IMPACT; n = 240). Efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, and durable clinical benefit (DCB) was defined as partial response/stable disease that lasted > 6 months. Tumor mutation burden (TMB), fraction of copy number-altered genome, and gene alterations were compared among patients with DCB and no durable benefit (NDB). Whole-exome sequencing (WES) was performed for 49 patients to compare quantification of TMB by targeted NGS versus WES. Results Estimates of TMB by targeted NGS correlated well with WES (ρ = 0.86; P < .001). TMB was greater in patients with DCB than with NDB ( P = .006). DCB was more common, and progression-free survival was longer in patients at increasing thresholds above versus below the 50th percentile of TMB (38.6% v 25.1%; P < .001; hazard ratio, 1.38; P = .024). The fraction of copy number-altered genome was highest in those with NDB. Variants in EGFR and STK11 associated with a lack of benefit. TMB and PD-L1 expression were independent variables, and a composite of TMB plus PD-L1 further enriched for benefit to ICIs. Conclusion Targeted NGS accurately estimates TMB and elevated TMB further improved likelihood of benefit to ICIs. TMB did not correlate with PD-L1 expression; both variables had similar predictive capacity. The incorporation of both TMB and PD-L1 expression into multivariable predictive models should result in greater predictive power.

The recent successes of immunotherapy have shifted the paradigm in cancer treatment but since only a percentage of patients respond, it is imperative to identify factors impacting outcome. Obesity is reaching pandemic proportions and is a major risk factor for certain malignancies, but the impact of obesity on immune responses, in general, and in cancer immunotherapy, in particular, is poorly understood. Here we demonstrate, across multiple species and tumor models, that obesity results in increased immune aging, tumor progression and PD-1-mediated T cell dysfunction which is driven, at least in part, by leptin. Strikingly however, obesity is also associated with increased efficacy of PD-1/PD-L1 blockade in both tumor-bearing mice and clinical cancer patients. These findings advance our understanding of obesity-induced immune dysfunction and its consequences in cancer and highlight obesity as a biomarker for some cancer immunotherapies. These data indicate a paradoxical impact of obesity on cancer. There is heightened immune dysfunction and tumor progression but also greater anti-tumor efficacy and survival following checkpoint blockade which directly targets some of the pathways activated in obesity.

In the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable the selection and stratification of patients for treatment. The enormous divergence of signalling and transcriptional networks mediating the crosstalk between cancer, stromal and immune cells complicates the development of functionally relevant biomarkers based on a single gene or protein. However, the result of these complex processes can be uniquely captured in the morphometric features of stained tissue specimens. The possibility of digitizing whole-slide images of tissue has led to the advent of artificial intelligence (AI) and machine learning tools in digital pathology, which enable mining of subvisual morphometric phenotypes and might, ultimately, improve patient management. In this Perspective, we critically evaluate various Al-based computational approaches for digital pathology, focusing on deep neural networks and ‘hand-crafted’ feature-based methodologies. We aim to provide a broad framework for incorporating AI and machine learning tools into clinical oncology, with an emphasis on biomarker development. We discuss some of the challenges relating to the use of AI, including the need for well-curated validation datasets, regulatory approval and fair reimbursement strategies. Finally, we present potential future opportunities for precision oncology.

Lymphocyte-activation gene 3 (LAG-3) is an immune inhibitory receptor, with major histocompatibility complex class II (MHC-II) as a canonical ligand. However, it remains controversial whether MHC-II is solely responsible for the inhibitory function of LAG-3. Here, we demonstrate that fibrinogen-like protein 1 (FGL1), a liver-secreted protein, is a major LAG-3 functional ligand independent from MHC-II. FGL1 inhibits antigen-specific T cell activation, and ablation of FGL1 in mice promotes T cell immunity. Blockade of the FGL1-LAG-3 interaction by monoclonal antibodies stimulates tumor immunity and is therapeutic against established mouse tumors in a receptor-ligand inter-dependent manner. FGL1 is highly produced by human cancer cells, and elevated FGL1 in the plasma of cancer patients is associated with a poor prognosis and resistance to anti-PD-1/ B7-H1 therapy. Our findings reveal an immune evasion mechanism and have implications for the design of cancer immunotherapy.

Recent strategies targeting the interaction of the programmed cell death ligand-1 (PD-L1, B7-H1, CD274) with its receptor, PD-1, resulted in promising activity in early phase clinical trials. In this study, we used various antibodies and in situ mRNA hybridization to measure PD-L1 in non-small cell lung cancer (NSCLC) using a quantitative fluorescence (QIF) approach to determine the frequency of expression and prognostic value in two independent populations. A control tissue microarray (TMA) was constructed using PD-L1-transfected cells, normal human placenta and known PD-L1-positive NSCLC cases. Only one of four antibodies against PD-L1 (5H1) validated for specificity on this TMA. In situ PD-L1 mRNA using the RNAscope method was similarly validated. Two cohorts of NSCLC cases in TMAs including 340 cases from hospitals in Greece and 204 cases from Yale University were assessed. Tumors showed PD-L1 protein expression in 36% (Greek) and 25% (Yale) of the cases. PD-L1 expression was significantly associated with tumor-infiltrating lymphocytes in both cohorts. Patients with PD-L1 (both protein and mRNA) expression above the detection threshold showed statistically significant better outcome in both series (log-rank P ¼ 0.036 and P ¼ 0.027). Multivariate analysis showed that PD-L1 expression was significantly associated with better outcome independent of histology. Measurement of PD-L1 requires specific conditions and some commercial antibodies show lack of specificity. Expression of PD-L1 protein or mRNA is associated with better outcome. Further studies are required to determine the value of this marker in prognosis and prediction of response to treatments targeting this pathway. Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the United States. The overall survival (OS) for metastatic NSCLC is dismal with 5-year survival of o5% and for patients with early stage NSCLC the 5-year survival is o50%. 1 Over the past decade, identification of several oncogenic driver mutations have helped improve the outcomes in certain subtypes of patients with NSCLC. 2 However, a majority of the patients with lung cancer do not have an actionable molecular aberration. Other treatment approaches, such as immune therapies, are being investigated in clinical trials. Programmed cell death-1 (PD-1) pathway is a major immune checkpoint by which tumors suppress lymphocyte function within the tumor microenvironment, and antibody blockade of PD-1 with its ligands (B7-H1/PD-L1 and B7-DC/PD-L2) showed promising activity in several malignancies. 3 In particular, blocking antibodies against PD-1 and PD-L1 have shown clinical activity in NSCLC. 4 Preliminary data suggest that tumor PD-L1 protein expression on human cancers using chromogenic-based immunohistochemistry (IHC) in formalin-fixed paraffinembedded tissue samples (FFPE) may predict clinical response to PD-1/PD-L1 directed therapy. 4,5 There are limited data on the prevalence and the prognostic role of PD-L1 expression in NSCLC. Data from small previously ...