Cancer-Germline Antigen Expression Discriminates Clinical Outcome to CTLA-4 Blockade.

CTLA-4 immune checkpoint blockade is clinically effective in a subset of patients with metastatic melanoma. We identify a subcluster of MAGE-A cancer-germline antigens, located within a narrow 75 kb region of chromosome Xq28, that predicts resistance uniquely to blockade of CTLA-4, but not PD-1. We validate this gene expression signature in an independent anti-CTLA-4-treated cohort and show its specificity to the CTLA-4 pathway with two independent anti-PD-1-treated cohorts. Autophagy, a process critical for optimal anti-cancer immunity, has previously been shown to be suppressed by the MAGE-TRIM28 ubiquitin ligase in vitro. We now show that the expression of the key autophagosome component LC3B and other activators of autophagy are negatively associated with MAGE-A protein levels in human melanomas, including samples from patients with resistance to CTLA-4 blockade. Our findings implicate autophagy suppression in resistance to CTLA-4 blockade in melanoma, suggesting exploitation of autophagy induction for potential therapeutic synergy with CTLA-4 inhibitors.

Spatial signatures identify immune escape via PD-1 as a defining feature of T-cell/histiocyte-rich large B-cell lymphoma.

T-cell/histiocyte-rich large B-cell lymphoma (TCRLBCL) is an aggressive variant of diffuse large B-cell lymphoma (DLBCL) characterized by rare malignant B cells within a robust but ineffective immune cell infiltrate. The mechanistic basis of immune escape in TCRLBCL is poorly defined and not targeted therapeutically. We performed a genetic and quantitative spatial analysis of the PD-1/PD-L1 pathway in a multi-institutional cohort of TCRLBCLs and found that malignant B cells harbored PD-L1/PD-L2 copy gain or amplification in 64% of cases, which was associated with increased PD-L1 expression (P = .0111). By directed and unsupervised spatial analyses of multiparametric cell phenotypic data within the tumor microenvironment, we found that TCRLBCL is characterized by tumor-immune "neighborhoods" in which malignant B cells are surrounded by exceptionally high numbers of PD-L1-expressing TAMs and PD-1+ T cells. Furthermore, unbiased clustering of spatially resolved immune signatures distinguished TCRLBCL from related subtypes of B-cell lymphoma, including classic Hodgkin lymphoma (cHL) and DLBCL-NOS. Finally, we observed clinical responses to PD-1 blockade in 3 of 5 patients with relapsed/refractory TCRLBCL who were enrolled in clinical trials for refractory hematologic malignancies (NCT03316573; NCT01953692), including 2 complete responses and 1 partial response. Taken together, these data implicate PD-1 signaling as an immune escape pathway in TCRLBCL and also support the potential utility of spatially resolved immune signatures to aid the diagnostic classification and immunotherapeutic prioritization of diverse tumor types.

Adjuvant dabrafenib plus trametinib versus placebo in patients with resected, BRAFV600-mutant, stage III melanoma (COMBI-AD): exploratory biomarker analyses from a randomised, phase 3 trial.

BACKGROUND: Adjuvant dabrafenib plus trametinib reduced the risk of relapse versus placebo in patients with resected, BRAFV600-mutant, stage III melanoma in the phase 3 COMBI-AD trial. This prespecified exploratory biomarker analysis aimed to evaluate potential prognostic or predictive factors and mechanisms of resistance to adjuvant targeted therapy. METHODS: COMBI-AD is a randomised, double-blind, placebo-controlled, phase 3 trial comparing dabrafenib 150 mg orally twice daily plus trametinib 2 mg orally once daily versus two matched placebos. Study participants were at least 18 years of age and underwent complete resection of stage IIIA (lymph node metastases >1 mm), IIIB, or IIIC cutaneous melanoma, per American Joint Committee on Cancer 7th edition criteria, with a BRAFV600E or BRAFV600K mutation. Patients were randomly assigned (1:1) to the two treatment groups by an interactive voice response system, stratified by mutation type and disease stage. Patients, physicians, and the investigators who analysed data were masked to treatment allocation. The primary outcome was relapse-free survival, defined as the time from randomisation to disease recurrence or death from any cause. Biomarker assessment was a prespecified exploratory outcome of the trial. We assessed intrinsic tumour genomic features by use of next-generation DNA sequencing and characteristics of the tumour microenvironment by use of a NanoString RNA assay, which might provide prognostic and predictive information. This trial is registered with ClinicalTrials.gov, number NCT01682083, and is ongoing but no longer recruiting participants. FINDINGS: Between Jan 31, 2013, and Dec 11, 2014, 870 patients were enrolled in the trial. Median follow-up at data cutoff (April 30, 2018) was 44 months (IQR 38-49) in the dabrafenib plus trametinib group and 42 months (21-49) in the placebo group. Intrinsic tumour genomic features were assessed in 368 patients (DNA sequencing set) and tumour microenvironment characteristics were assessed in 507 patients (NanoString biomarker set). MAPK pathway genomic alterations at baseline did not affect treatment benefit or clinical outcome. An IFNγ gene expression signature higher than the median was prognostic for prolonged relapse-free survival in both treatment groups. Tumour mutational burden was independently prognostic for relapse-free survival in the placebo group (high TMB, top third; hazard ratio [HR] 0·56, 95% CI 0·37-0·85, p=0·0056), but not in the dabrafenib plus trametinib group (0·83, 95% CI 0·53-1·32, p=0·44). Patients with tumour mutational burden in the lower two terciles seem to derive a substantial long-term relapse-free survival benefit from targeted therapy (HR [versus placebo] 0·49, 95% CI 0·35-0·68, p<0·0001). However, patients with high tumour mutational burden seem to have a less pronounced benefit with targeted therapy (HR [versus placebo] 0·75, 95% CI 0·44-1·26, p=0·27), especially if they had an IFNγ signature lower than the median (HR 0·88 [95% CI 0·40-1·93], p=0·74). INTERPRETATION: Tumour mutational burden alone or in combination with IFNγ gene expression signature or other markers for an adaptive immune response might be of relevance for identifying patients with stage III melanoma who might derive clinical benefit from targeted therapy. Further validation in prospective clinical trials is warranted. FUNDING: Novartis Pharmaceuticals.

Topological analysis reveals a PD-L1-associated microenvironmental niche for Reed-Sternberg cells in Hodgkin lymphoma.

Signaling between programmed cell death protein 1 (PD-1) and the PD-1 ligands (PD-L1, PD-L2) is essential for malignant Hodgkin Reed-Sternberg (HRS) cells to evade antitumor immunity in classical Hodgkin lymphoma (cHL). Copy number alterations of 9p24.1/CD274(PD-L1)/PDCD1LG2(PD-L2) contribute to robust PD-L1 and PD-L2 expression by HRS cells. PD-L1 is also expressed by nonmalignant tumor-associated macrophages (TAMs), but the relationships among PD-L1+ HRS cells, PD-L1+ TAMs, and PD-1+ T cells remain undefined. We used multiplex immunofluorescence and digital image analysis to examine the topography of PD-L1+ and PD-1+ cells in the tumor microenvironment (TME) of cHL. We find that the majority of PD-L1 in the TME is expressed by the abundant PD-L1+ TAMs, which physically colocalize with PD-L1+ HRS cells in a microenvironmental niche. PD-L1+ TAMs are enriched for contacts with T cells, and PD-L1+ HRS cells are enriched for contacts with CD4+ T cells, a subset of which are PD-1+ Our data define a unique topology of cHL in which PD-L1+ TAMs surround HRS cells and implicate CD4+ T cells as a target of PD-1 blockade.

Targetable genetic features of primary testicular and primary central nervous system lymphomas.

Primary central nervous system lymphomas (PCNSLs) and primary testicular lymphomas (PTLs) are extranodal large B-cell lymphomas (LBCLs) with inferior responses to current empiric treatment regimens. To identify targetable genetic features of PCNSL and PTL, we characterized their recurrent somatic mutations, chromosomal rearrangements, copy number alterations (CNAs), and associated driver genes, and compared these comprehensive genetic signatures to those of diffuse LBCL and primary mediastinal large B-cell lymphoma (PMBL). These studies identify unique combinations of genetic alterations in discrete LBCL subtypes and subtype-selective bases for targeted therapy. PCNSLs and PTLs frequently exhibit genomic instability, and near-uniform, often biallelic, CDKN2A loss with rare TP53 mutations. PCNSLs and PTLs also use multiple genetic mechanisms to target key genes and pathways and exhibit near-uniform oncogenic Toll-like receptor signaling as a result of MYD88 mutation and/or NFKBIZ amplification, frequent concurrent B-cell receptor pathway activation, and deregulation of BCL6. Of great interest, PCNSLs and PTLs also have frequent 9p24.1/PD-L1/PD-L2 CNAs and additional translocations of these loci, structural bases of immune evasion that are shared with PMBL.

Diffuse large B-cell lymphoma patient-derived xenograft models capture the molecular and biological heterogeneity of the disease.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined by transcriptional classifications, specific signaling and survival pathways, and multiple low-frequency genetic alterations. Preclinical model systems that capture the genetic and functional heterogeneity of DLBCL are urgently needed. Here, we generated and characterized a panel of large B-cell lymphoma (LBCL) patient-derived xenograft (PDX) models, including 8 that reflect the immunophenotypic, transcriptional, genetic, and functional heterogeneity of primary DLBCL and 1 that is a plasmablastic lymphoma. All LBCL PDX models were subjected to whole-transcriptome sequencing to classify cell of origin and consensus clustering classification (CCC) subtypes. Mutations and chromosomal rearrangements were evaluated by whole-exome sequencing with an extended bait set. Six of the 8 DLBCL models were activated B-cell (ABC)-type tumors that exhibited ABC-associated mutations such as MYD88, CD79B, CARD11, and PIM1. The remaining 2 DLBCL models were germinal B-cell type, with characteristic alterations of GNA13, CREBBP, and EZH2, and chromosomal translocations involving IgH and either BCL2 or MYC Only 25% of the DLBCL PDX models harbored inactivating TP53 mutations, whereas 75% exhibited copy number alterations of TP53 or its upstream modifier, CDKN2A, consistent with the reported incidence and type of p53 pathway alterations in primary DLBCL. By CCC criteria, 6 of 8 DLBCL PDX models were B-cell receptor (BCR)-type tumors that exhibited selective surface immunoglobulin expression and sensitivity to entospletinib, a recently developed spleen tyrosine kinase inhibitor. In summary, we have established and characterized faithful PDX models of DLBCL and demonstrated their usefulness in functional analyses of proximal BCR pathway inhibition.

An Aryl Hydrocarbon Receptor-Mediated Amplification Loop That Enforces Cell Migration in ER-/PR-/Her2- Human Breast Cancer Cells.

The endogenous ligand-activated aryl hydrocarbon receptor (AHR) plays an important role in numerous biologic processes. As the known number of AHR-mediated processes grows, so too does the importance of determining what endogenous AHR ligands are produced, how their production is regulated, and what biologic consequences ensue. Consequently, our studies were designed primarily to determine whether ER-/PR-/Her2- breast cancer cells have the potential to produce endogenous AHR ligands and, if so, how production of these ligands is controlled. We postulated that: 1) malignant cells produce tryptophan-derived AHR ligand(s) through the kynurenine pathway; 2) these metabolites have the potential to drive AHR-dependent breast cancer migration; 3) the AHR controls expression of a rate-limiting kynurenine pathway enzyme(s) in a closed amplification loop; and 4) environmental AHR ligands mimic the effects of endogenous ligands. Data presented in this work indicate that primary human breast cancers, and their metastases, express high levels of AHR and tryptophan-2,3-dioxygenase (TDO); representative ER-/PR-/Her2- cell lines express TDO and produce sufficient intracellular kynurenine and xanthurenic acid concentrations to chronically activate the AHR. TDO overexpression, or excess kynurenine or xanthurenic acid, accelerates migration in an AHR-dependent fashion. Environmental AHR ligands 2,3,7,8-tetrachlorodibenzo[p]dioxin and benzo[a]pyrene mimic this effect. AHR knockdown or inhibition significantly reduces TDO2 expression. These studies identify, for the first time, a positive amplification loop in which AHR-dependent TDO2 expression contributes to endogenous AHR ligand production. The net biologic effect of AHR activation by endogenous ligands, which can be mimicked by environmental ligands, is an increase in tumor cell migration, a measure of tumor aggressiveness.

ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways.

MOTIVATION: Although gene-expression signature-based biomarkers are often developed for clinical diagnosis, many promising signatures fail to replicate during validation. One major challenge is that biological samples used to generate and validate the signature are often from heterogeneous biological contexts-controlled or in vitro samples may be used to generate the signature, but patient samples may be used for validation. In addition, systematic technical biases from multiple genome-profiling platforms often mask true biological variation. Addressing such challenges will enable us to better elucidate disease mechanisms and provide improved guidance for personalized therapeutics. RESULTS: Here, we present a pathway profiling toolkit, Adaptive Signature Selection and InteGratioN (ASSIGN), which enables robust and context-specific pathway analyses by efficiently capturing pathway activity in heterogeneous sets of samples and across profiling technologies. The ASSIGN framework is based on a flexible Bayesian factor analysis approach that allows for simultaneous profiling of multiple correlated pathways and for the adaptation of pathway signatures into specific disease. We demonstrate the robustness and versatility of ASSIGN in estimating pathway activity in simulated data, cell lines perturbed pathways and in primary tissues samples including The Cancer Genome Atlas breast carcinoma samples and liver samples exposed to genotoxic carcinogens. AVAILABILITY AND IMPLEMENTATION: Software for our approach is available for download at: http://www.bioconductor.org/packages/release/bioc/html/ASSIGN.html and https://github.com/wevanjohnson/ASSIGN.

RamiGO: an R/Bioconductor package providing an AmiGO visualize interface.

SUMMARY: The R/Bioconductor package RamiGO is an R interface to AmiGO that enables visualization of Gene Ontology (GO) trees. Given a list of GO terms, RamiGO uses the AmiGO visualize API to import Graphviz-DOT format files into R, and export these either as images (SVG, PNG) or into Cytoscape for extended network analyses. RamiGO provides easy customization of annotation, highlighting of specific GO terms, colouring of terms by P-value or export of a simplified summary GO tree. We illustrate RamiGO functionalities in a genome-wide gene set analysis of prognostic genes in breast cancer. AVAILABILITY AND IMPLEMENTATION: RamiGO is provided in R/Bioconductor, is open source under the Artistic-2.0 License and is available with a user manual containing installation, operating instructions and tutorials. It requires R version 2.15.0 or higher. URL: http://bioconductor.org/packages/release/bioc/html/RamiGO.html

GeneSigDB: a manually curated database and resource for analysis of gene expression signatures.

GeneSigDB (http://www.genesigdb.org or http://compbio.dfci.harvard.edu/genesigdb/) is a database of gene signatures that have been extracted and manually curated from the published literature. It provides a standardized resource of published prognostic, diagnostic and other gene signatures of cancer and related disease to the community so they can compare the predictive power of gene signatures or use these in gene set enrichment analysis. Since GeneSigDB release 1.0, we have expanded from 575 to 3515 gene signatures, which were collected and transcribed from 1604 published articles largely focused on gene expression in cancer, stem cells, immune cells, development and lung disease. We have made substantial upgrades to the GeneSigDB website to improve accessibility and usability, including adding a tag cloud browse function, facetted navigation and a 'basket' feature to store genes or gene signatures of interest. Users can analyze GeneSigDB gene signatures, or upload their own gene list, to identify gene signatures with significant gene overlap and results can be viewed on a dynamic editable heatmap that can be downloaded as a publication quality image. All data in GeneSigDB can be downloaded in numerous formats including .gmt file format for gene set enrichment analysis or as a R/Bioconductor data file. GeneSigDB is available from http://www.genesigdb.org.

A phase 2, multicenter, open-label study of anti-LAG-3 ieramilimab in combination with anti-PD-1 spartalizumab in patients with advanced solid malignancies.

Ieramilimab, a humanized anti-LAG-3 monoclonal antibody, was well tolerated in combination with the anti-PD-1 antibody spartalizumab in a phase 1 study. This phase 2 study aimed to further investigate the efficacy and safety of combination treatment in patients with selected advanced (locally advanced or metastatic) solid malignancies. Eligible patients with non-small cell lung cancer (NSCLC), melanoma, renal cell carcinoma (RCC), mesothelioma, and triple-negative breast cancer (TNBC) were grouped depending on prior anti-PD-1/L1 therapy (anti-PD-1/L1 naive or anti-PD-1/L1 pretreated). Patients received ieramilimab (400 mg) followed by spartalizumab (300 mg) every 3 weeks. The primary endpoint was objective response rate (ORR), along with safety, pharmacokinetics, and biomarker assessments. Of 235 patients, 142 were naive to anti-PD-1/L1 and 93 were pretreated with anti-PD-1/L1 antibodies. Durable responses (>24 months) were seen across all indications for patients naive to anti-PD-1/L1 and in melanoma and RCC patients pretreated with anti-PD1/L1. The most frequent study drug-related AEs were pruritus (15.5%), fatigue (10.6%), and rash (10.6%) in patients naive to anti-PD-1/L1 and fatigue (18.3%), rash (14.0%), and nausea (10.8%) in anti-PD-1/L1 pretreated patients. Biomarker assessment indicated higher expression of T-cell-inflamed gene signature at baseline among responding patients. Response to treatment was durable (>24 months) in some patients across all enrolled indications, and safety findings were in accordance with previous and current studies exploring LAG-3/PD-1 blockade.

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle-Based Blood Test: Performance in a Training and Verification Cohort.

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles from blood. The novel Mercy Halo Ovarian Cancer Test (OC Test) uses immunoaffinity capture of tumor-associated extracellular vesicles, followed by proximity-ligation real-time quantitative PCR to detect combinations of up to three biomarkers to maximize specificity and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cutoff between cancer and noncancer. Performance was verified and compared with cancer antigen 125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, and 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI, 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI, 87.8%-99.2%), and an area under the curve of 0.97 (95% CI, 0.93-0.99) and detected 73.5% (61/83; 95% CI, 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, nonovarian cancers, and inflammatory conditions when compared with cancer antigen 125. The combined sensitivity and specificity of this new test suggests it may have potential in OC screening.

iBBiG: iterative binary bi-clustering of gene sets.

MOTIVATION: Meta-analysis of genomics data seeks to identify genes associated with a biological phenotype across multiple datasets; however, merging data from different platforms by their features (genes) is challenging. Meta-analysis using functionally or biologically characterized gene sets simplifies data integration is biologically intuitive and is seen as having great potential, but is an emerging field with few established statistical methods. RESULTS: We transform gene expression profiles into binary gene set profiles by discretizing results of gene set enrichment analyses and apply a new iterative bi-clustering algorithm (iBBiG) to identify groups of gene sets that are coordinately associated with groups of phenotypes across multiple studies. iBBiG is optimized for meta-analysis of large numbers of diverse genomics data that may have unmatched samples. It does not require prior knowledge of the number or size of clusters. When applied to simulated data, it outperforms commonly used clustering methods, discovers overlapping clusters of diverse sizes and is robust in the presence of noise. We apply it to meta-analysis of breast cancer studies, where iBBiG extracted novel gene set-phenotype association that predicted tumor metastases within tumor subtypes. AVAILABILITY: Implemented in the Bioconductor package iBBiG CONTACT: aedin@jimmy.harvard.edu.

Interleukin 17 signaling supports clinical benefit of dual CTLA-4 and PD-1 checkpoint inhibition in melanoma.

Recent studies suggest that BRAFV600-mutated melanomas in particular respond to dual anti-programmed cell death protein 1 (PD-1) and anti-cytotoxic T lymphocyte-associated protein 4 (CTLA-4) immune checkpoint inhibition (ICI). Here we identified an over-representation of interleukin (IL)-17-type 17 helper T (TH17) gene expression signatures (GES) in BRAFV600-mutated tumors. Moreover, high baseline IL-17 GES consistently predicted clinical responses in dual-ICI-treated patient cohorts but not in mono anti-CTLA-4 or anti-PD-1 ICI cohorts. High IL-17 GES corresponded to tumor infiltration with T cells and neutrophils. Accordingly, high neutrophil infiltration correlated with clinical response specifically to dual ICI, and tumor-associated neutrophils also showed strong IL-17-TH17 pathway activity and T cell activation capacity. Both the blockade of IL-17A and the depletion of neutrophils impaired dual-ICI response and decreased T cell activation. Finally, high IL-17A levels in the blood of patients with melanoma indicated a higher global TH17 cytokine profile preceding clinical response to dual ICI but not to anti-PD-1 monotherapy, suggesting a future role as a biomarker for patient stratification.

Spartalizumab or placebo in combination with dabrafenib and trametinib in patients with BRAF V600-mutant melanoma: exploratory biomarker analyses from a randomized phase 3 trial (COMBI-i).

BACKGROUND: The randomized phase 3 COMBI-i trial did not meet its primary endpoint of improved progression-free survival (PFS) with spartalizumab plus dabrafenib and trametinib (sparta-DabTram) vs placebo plus dabrafenib and trametinib (placebo-DabTram) in the overall population of patients with unresectable/metastatic BRAF V600-mutant melanoma. This prespecified exploratory biomarker analysis was performed to identify subgroups that may derive greater treatment benefit from sparta-DabTram. METHODS: In COMBI-i (ClinicalTrials.gov, NCT02967692), 532 patients received spartalizumab 400 mg intravenously every 4 weeks plus dabrafenib 150 mg orally two times daily and trametinib 2 mg orally one time daily or placebo-DabTram. Baseline/on-treatment pharmacodynamic markers were assessed via flow cytometry-based immunophenotyping and plasma cytokine profiling. Baseline programmed death ligand 1 (PD-L1) status and T-cell phenotype were assessed via immunohistochemistry; BRAF V600 mutation type, tumor mutational burden (TMB), and circulating tumor DNA (ctDNA) via DNA sequencing; gene expression signatures via RNA sequencing; and CD4+/CD8+ T-cell ratio via immunophenotyping. RESULTS: Extensive biomarker analyses were possible in approximately 64% to 90% of the intention-to-treat population, depending on sample availability and assay. Subgroups based on PD-L1 status/TMB or T-cell inflammation did not show significant differences in PFS benefit with sparta-DabTram vs placebo-DabTram, although T-cell inflammation was prognostic across treatment arms. Subgroups defined by BRAF V600K mutation (HR 0.45 (95% CI 0.21 to 0.99)), detectable ctDNA shedding (HR 0.75 (95% CI 0.58 to 0.96)), or CD4+/CD8+ ratio above median (HR 0.58 (95% CI 0.40 to 0.84)) derived greater PFS benefit with sparta-DabTram vs placebo-DabTram. In a multivariate analysis, ctDNA emerged as strongly prognostic (p=0.007), while its predictive trend did not reach significance; in contrast, CD4+/CD8+ ratio was strongly predictive (interaction p=0.0131). CONCLUSIONS: These results support the feasibility of large-scale comprehensive biomarker analyses in the context of a global phase 3 study. T-cell inflammation was prognostic but not predictive of sparta-DabTram benefit, as patients with high T-cell inflammation already benefit from targeted therapy alone. Baseline ctDNA shedding also emerged as a strong independent prognostic variable, with predictive trends consistent with established measures of disease burden such as lactate dehydrogenase levels. CD4+/CD8+ T-cell ratio was significantly predictive of PFS benefit with sparta-DabTram but requires further validation as a biomarker in melanoma. Taken together with previous observations, further study of checkpoint inhibitor plus targeted therapy combination in patients with higher disease burden may be warranted. TRIAL REGISTRATION NUMBER: NCT02967692.

Phase I/II study of the LAG-3 inhibitor ieramilimab (LAG525) ± anti-PD-1 spartalizumab (PDR001) in patients with advanced malignancies.

BACKGROUND: Lymphocyte-activation gene 3 (LAG-3) is an inhibitory immunoreceptor that negatively regulates T-cell activation. This paper presents preclinical characterization of the LAG-3 inhibitor, ieramilimab (LAG525), and phase I data for the treatment of patients with advanced/metastatic solid tumors with ieramilimab ±the anti-programmed cell death-1 antibody, spartalizumab. METHODS: Eligible patients had advanced/metastatic solid tumors and progressed after, or were unsuitable for, standard-of-care therapy, including checkpoint inhibitors in some cases. Patients received ieramilimab ±spartalizumab across various dose-escalation schedules. The primary objective was to assess the maximum tolerated dose (MTD) or recommended phase II dose (RP2D). RESULTS: In total, 255 patients were allocated to single-agent ieramilimab (n=134) and combination (n=121) treatment arms. The majority (98%) had received prior antineoplastic therapy (median, 3). Four patients experienced dose-limiting toxicities in each treatment arm across various dosing cohorts. No MTD was reached. The RP2D on a 3-week schedule was declared as 400 mg ieramilimab plus 300 mg spartalizumab and, on a 4-week schedule (once every 4 weeks; Q4W), as 800 mg ieramilimab plus 400 mg spartalizumab; tumor target (LAG-3) suppression with 600 mg ieramilimab Q4W was predicted to be similar to the Q4W, RP2D schedule. Treatment-related adverse events (TRAEs) occurred in 75 (56%) and 84 (69%) patients in the single-agent and combination arms, respectively. Most common TRAEs were fatigue, gastrointestinal, and skin disorders, and were of mild severity; seven patients experienced at least one treatment-related serious adverse event in the single-agent (5%) and combination group (5.8%). Antitumor activity was observed in the combination arm, with 3 (2%) complete responses and 10 (8%) partial responses in a mixed population of tumor types. In the combination arm, eight patients (6.6%) experienced stable disease for 6 months or longer versus six patients (4.5%) in the single-agent arm. Responding patients trended towards having higher levels of immune gene expression, including CD8 and LAG3, in tumor tissue at baseline. CONCLUSIONS: Ieramilimab was well tolerated as monotherapy and in combination with spartalizumab. The toxicity profile of ieramilimab in combination with spartalizumab was comparable to that of spartalizumab alone. Modest antitumor activity was seen with combination treatment. TRIAL REGISTRATION NUMBER: NCT02460224.

GCOD - GeneChip Oncology Database.

BACKGROUND: DNA microarrays have become a nearly ubiquitous tool for the study of human disease, and nowhere is this more true than in cancer. With hundreds of studies and thousands of expression profiles representing the majority of human cancers completed and in public databases, the challenge has been effectively accessing and using this wealth of data. DESCRIPTION: To address this issue we have collected published human cancer gene expression datasets generated on the Affymetrix GeneChip platform, and carefully annotated those studies with a focus on providing accurate sample annotation. To facilitate comparison between datasets, we implemented a consistent data normalization and transformation protocol and then applied stringent quality control procedures to flag low-quality assays. CONCLUSION: The resulting resource, the GeneChip Oncology Database, is available through a publicly accessible website that provides several query options and analytical tools through an intuitive interface.

Role of Tumor-Infiltrating B Cells in Clinical Outcome of Patients with Melanoma Treated With Dabrafenib Plus Trametinib.

PURPOSE: Although patients with unresectable or metastatic melanoma can experience long-term survival with BRAF- and MEK-targeted agents or immune checkpoint inhibitors over 5 years, resistance develops in most patients. There is a distinct lack of pretherapeutic biomarkers to identify which patients are likely to benefit from each therapy type. Most research has focused on the predictive role of T cells in antitumor responses as opposed to B cells. PATIENTS AND METHODS: We conducted prespecified exploratory biomarker analysis using gene expression profiling and digital pathology in 146 patients with previously untreated BRAF V600-mutant metastatic melanoma from the randomized, phase III COMBI-v trial and treated with dabrafenib plus trametinib who had available tumor specimens from screening. RESULTS: Baseline cell-cycle gene expression signature was associated with progression-free survival (P = 0.007). Patients with high T-cell/low B-cell gene signatures had improved median overall survival (not reached [95% confidence interval (CI), 33.8 months-not reached]) compared with patients with high T-cell/high B-cell signatures (19.1 months; 95% CI, 13.4-38.6 months). Patients with high B-cell signatures had high B-cell infiltration into the tumor compartment, corresponding with decreased MAPK activity and increased expression of immunosuppressive markers. CONCLUSIONS: B cells may serve as a potential biomarker to predict clinical outcome in patients with advanced melanoma treated with dabrafenib plus trametinib. As separate studies have shown an opposite effect for B-cell levels and response to immunotherapy, B cells may serve as a potential biomarker to facilitate treatment selection. Further validation in a larger patient cohort is needed.

Combined PD-1, BRAF and MEK inhibition in advanced BRAF-mutant melanoma: safety run-in and biomarker cohorts of COMBI-i.

Immune and targeted therapies achieve long-term survival in metastatic melanoma; however, new treatment strategies are needed to improve patients' outcomes1,2. We report on the efficacy, safety and biomarker analysis from the single-arm safety run-in (part 1; n = 9) and biomarker (part 2; n = 27) cohorts of the randomized, placebo-controlled, phase 3 COMBI-i trial (NCT02967692) of the anti-PD-1 antibody spartalizumab, in combination with the BRAF inhibitor dabrafenib and MEK inhibitor trametinib. Patients (n = 36) had previously untreated BRAF V600-mutant unresectable or metastatic melanoma. In part 1, the recommended phase 3 regimen was identified based on the incidence of dose-limiting toxicities (DLTs; primary endpoint): 400 mg of spartalizumab every 4 weeks plus 150 mg of dabrafenib twice daily plus 2 mg of trametinib once daily. Part 2 characterized changes in PD-L1 levels and CD8+ cells following treatment (primary endpoint), and analyzed additional biomarkers. Assessments of efficacy and safety were key secondary endpoints (median follow-up, 24.3 months). Spartalizumab plus dabrafenib and trametinib led to an objective response rate (ORR) of 78%, including 44% complete responses (CRs). Grade ≥3 treatment-related adverse events (TRAEs) were experienced by 72% of patients. All patients had temporary dose modifications, and 17% permanently discontinued all three study drugs due to TRAEs. Early progression-free survival (PFS) events were associated with low tumor mutational burden/T cell-inflamed gene expression signature (GES) or high immunosuppressive tumor microenvironment (TME) GES levels at baseline; an immunosuppressive TME may also preclude CR. Overall, the efficacy, safety and on-treatment biomarker modulations associated with spartalizumab plus dabrafenib and trametinib are promising, and biomarkers that may predict long-term benefit were identified.

Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients.

BACKGROUND: While immune checkpoint blockade has greatly improved clinical outcomes in diseases such as melanoma, there remains a need for predictive biomarkers to determine who will likely benefit most from which therapy. To date, most biomarkers of response have been identified in the tumors themselves. Biomarkers that could be assessed from peripheral blood would be even more desirable, because of ease of access and reproducibility of sampling. METHODS: We used mass cytometry (CyTOF) to comprehensively profile peripheral blood of melanoma patients, in order to find predictive biomarkers of response to anti-CTLA-4 or anti-PD-1 therapy. Using a panel of ~ 40 surface and intracellular markers, we performed in-depth phenotypic and functional immune profiling to identify potential predictive biomarker candidates. RESULTS: Immune profiling of baseline peripheral blood samples using CyTOF revealed that anti-CTLA-4 and anti-PD-1 therapies have distinct sets of candidate biomarkers. The distribution of CD4+ and CD8+ memory/non-memory cells and other memory subsets was different between responders and non-responders to anti-CTLA-4 therapy. In anti-PD-1 (but not anti-CTLA-4) treated patients, we discovered differences in CD69 and MIP-1ß expressing NK cells between responders and non-responders. Finally, multivariate analysis was used to develop a model for the prediction of response. CONCLUSIONS: Our results indicate that anti-CTLA-4 and anti-PD-1 have distinct predictive biomarker candidates. CD4+ and CD8+ memory T cell subsets play an important role in response to anti-CTLA-4, and are potential biomarker candidates. For anti-PD-1 therapy, NK cell subsets (but not memory T cell subsets) correlated with clinical response to therapy. These functionally active NK cell subsets likely play a critical role in the anti-tumor response triggered by anti-PD-1.