Decoding Spatial Tissue Architecture: A Scalable Bayesian Topic Model for Multiplexed Imaging Analysis.

Recent progress in multiplexed tissue imaging is advancing the study of tumor microenvironments to enhance our understanding of treatment response and disease progression. Cellular neighborhood analysis is a popular computational approach for these complex image data. Despite its popularity, there are significant challenges, including high computational demands that limit feasibility for large-scale applications and the lack of a principled strategy for integrative analysis across images. This absence hampers the precise and consistent identification of spatial features and tracking of their dynamics over disease progression. To overcome these challenges, we introduce SpaTopic, a spatial topic model designed to decode high-level spatial architecture across multiplexed tissue images. This algorithm integrates both cell type and spatial information within a topic modelling framework, originally developed for natural language processing and adapted for computer vision. Spatial information is incorporated into the flexible design of documents, representing densely overlapping regions in images. The model employs an efficient collapsed Gibbs sampling algorithm for both statistical and computational inference. We benchmarked the performance against five state-of-the-art algorithms through various case studies using different single-cell spatial transcriptomic and proteomic imaging platforms across different tissue types. Our findings demonstrate that SpaTopic consistently identifies biologically and clinically significant spatial "topics" such as tertiary lymphoid structures (TLSs) and tracks dynamic changes in spatial features over disease progression. Its computational efficiency and broad applicability across various molecular imaging platforms will enhance the analysis of large-scale tissue imaging datasets.

Spatial Immunophenotyping from Whole-Slide Multiplexed Tissue Imaging Using Convolutional Neural Networks.

The multiplexed immunofluorescence (mIF) platform enables biomarker discovery through the simultaneous detection of multiple markers on a single tissue slide, offering detailed insights into intratumor heterogeneity and the tumor-immune microenvironment at spatially resolved single cell resolution. However, current mIF image analyses are labor-intensive, requiring specialized pathology expertise which limits their scalability and clinical application. To address this challenge, we developed CellGate, a deep-learning (DL) computational pipeline that provides streamlined, end-to-end whole-slide mIF image analysis including nuclei detection, cell segmentation, cell classification, and combined immuno-phenotyping across stacked images. The model was trained on over 750,000 single cell images from 34 melanomas in a retrospective cohort of patients using whole tissue sections stained for CD3, CD8, CD68, CK-SOX10, PD-1, PD-L1, and FOXP3 with manual gating and extensive pathology review. When tested on new whole mIF slides, the model demonstrated high precision-recall AUC. Further validation on whole-slide mIF images of 9 primary melanomas from an independent cohort confirmed that CellGate can reproduce expert pathology analysis with high accuracy. We show that spatial immuno-phenotyping results using CellGate provide deep insights into the immune cell topography and differences in T cell functional states and interactions with tumor cells in patients with distinct histopathology and clinical characteristics. This pipeline offers a fully automated and parallelizable computing process with substantially improved consistency for cell type classification across images, potentially enabling high throughput whole-slide mIF tissue image analysis for large-scale clinical and research applications.

Durable complete response in a patient with leptomeningeal melanoma after treatment with dabrafenib, trametinib, and nivolumab.

Leptomeningeal disease (LMD) is a devastating complication of melanoma with a dismal prognosis. We present the case of a young man with stage IV BRAF V600E mutant melanoma with lung, lymph node, and brain metastases initially treated with ipilimumab and nivolumab, who subsequently developed LMD. Upon change to BRAF/MEK targeted therapy with nivolumab, a durable complete response was achieved and remains ongoing, off treatment, 7 years from diagnosis. Management of symptomatic LMD remains a critical unmet clinical challenge, with limited clinical trial data. This exceptional case is instructive, as the first published case of the use of the triplet, and the first durable response with therapy discontinuation, in melanoma LMD. The triple-drug regimen may be considered a viable option in fit patients. This case highlights the potential for long-term disease control and the critical and urgent need to develop clinical trials inclusive of patients with LMD to define the best treatment strategies.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

Early On-Treatment Assessment of T Cells, Cytokines, and Tumor DNA with Adaptively Dosed Nivolumab + Ipilimumab: Final Results from the Phase 2 ADAPT-IT Study.

PURPOSE: The Adaptively Dosed ImmunoTherapy Trial (ADAPT-IT;NCT03122522) investigated adaptive ipilimumab discontinuation in melanoma based on early radiographic assessment. Initial findings indicated similar effectiveness compared with conventional nivolumab-ipilimumab (nivo-ipi). Exploratory biomarker analyses and final clinical results are now reported. PATIENTS AND METHODS: Patients with unresectable melanoma received two doses of nivo-ipi. Radiographic assessment at Week 6 informed continuation of ipilimumab before nivolumab maintenance. The primary endpoint was overall response rate at Week 12. Plasma was assayed for circulating tumor DNA and 10 cytokines using a multiplex immunoassay. Flow cytometry of peripheral blood mononuclear cells was performed with an 11-color panel. RESULTS: Among the treated patients, expansion of proliferating T-cell populations was observed in responders and nonresponders. Baseline IL6 levels were low in patients achieving an objective radiographic response (median 1.30 vs. 2.86 pg/mL; P = 0.025). High baseline IL6 levels were associated with short progression-free survival [PFS; HR = 1.24, 95% confidence interval (CI), 1.01-1.52; P = 0.041]. At Week 6, patients with response had lower average tumor variant allele fractions than nonresponders (median 0.000 vs. 0.019; P = 0.014). Greater increases in average variant allele fractions from baseline to Week 6 correlated with short PFS (HR = 1.11, 95% CI, 1.01-1.21; P = 0.023). Week 12 overall response rate was 47% (95% CI, 35%-59%) with a median follow-up of 34 months among survivors. Median PFS was 21 months (95% CI, 10-not reached); 76% of responses (95% CI, 64%-91%) persisted at 36 months. CONCLUSIONS: Adaptively dosed nivo-ipi responses are durable and resemble historical data for conventional nivo-ipi. Baseline IL6 and circulating tumor DNA changes during treatment warrant further study as biomarkers of nivo-ipi response.

Phase Ib Trial of Phenformin in Patients with V600-mutated Melanoma Receiving Dabrafenib and Trametinib.

PURPOSE: Preclinical studies show that activation of AMP kinase by phenformin can augment the cytotoxic effect and RAF inhibitors in BRAF V600-mutated melanoma. We conducted a phase Ib dose-escalation trial of phenformin with standard dose dabrafenib/trametinib in patients with metastatic BRAF V600-mutated melanoma. EXPERIMENTAL DESIGN: We used a 3+3 dose-escalation design which explored phenformin doses between 50 and 200 mg twice daily. Patients also received standard dose dabrafenib/trametinib. We measured phenformin pharmacokinetics and assessed the effect of treatment on circulating myeloid-derived suppressor cells (MDSC). RESULTS: A total of 18 patients were treated at dose levels ranging from 50 to 200 mg twice daily. The planned dose-escalation phase had to be cancelled because of the COVID 19 pandemic. The most common toxicities were nausea/vomiting; there were two cases of reversible lactic acidosis. Responses were seen in 10 of 18 patients overall (56%) and in 2 of 8 patients who had received prior therapy with RAF inhibitor. Pharmacokinetic data confirmed drug bioavailability. MDSCs were measured in 7 patients treated at the highest dose levels and showed MDSC levels declined on study drug in 6 of 7 patients. CONCLUSIONS: We identified the recommended phase II dose of phenformin as 50 mg twice daily when administered with dabrafenib/trametinib, although some patients will require short drug holidays. We observed a decrease in MDSCs, as predicted by preclinical studies, and may enhance immune recognition of melanoma cells. SIGNIFICANCE: This is the first trial using phenformin in combination with RAF/MEK inhibition in patients with BRAF V600-mutated melanoma. This is a novel strategy, based on preclinical data, to increase pAMPK while blocking the MAPK pathway in melanoma. Our data provide justification and a recommended dose for a phase II trial.

A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy.

We present TopicFlow, a computational framework for flow cytometry data analysis of patient blood samples for the identification of functional and dynamic topics in circulating T cell population. This framework applies a Latent Dirichlet Allocation (LDA) model, adapting the concept of topic modeling in text mining to flow cytometry. To demonstrate the utility of our method, we conducted an analysis of ∼17 million T cells collected from 138 peripheral blood samples in 51 patients with melanoma undergoing treatment with immune checkpoint inhibitors (ICIs). Our study highlights three latent dynamic topics identified by LDA: a T cell exhaustion topic that independently recapitulates the previously identified LAG-3+ immunotype associated with ICI resistance, a naive topic and its association with immune-related toxicity, and a T cell activation topic that emerges upon ICI treatment. Our approach can be broadly applied to mine high-parameter flow cytometry data for insights into mechanisms of treatment response and toxicity.

Integration of peripheral blood- and tissue-based biomarkers of response to immune checkpoint blockade in urothelial carcinoma.

As predictive biomarkers of response to immune checkpoint inhibitors (ICIs) remain a major unmet clinical need in patients with urothelial carcinoma (UC), we sought to identify tissue-based immune biomarkers of clinical benefit to ICIs using multiplex immunofluorescence and to integrate these findings with previously identified peripheral blood biomarkers of response. Fifty-five pretreatment and 12 paired on-treatment UC specimens were identified from patients treated with nivolumab with or without ipilimumab. Whole tissue sections were stained with a 12-plex mIF panel, including CD8, PD-1/CD279, PD-L1/CD274, CD68, CD3, CD4, FoxP3, TCF1/7, Ki67, LAG-3, MHC-II/HLA-DR, and pancytokeratin+SOX10 to identify over three million cells. Immune tissue densities were compared to progression-free survival (PFS) and best overall response (BOR) by RECIST version 1.1. Correlation coefficients were calculated between tissue-based and circulating immune populations. The frequency of intratumoral CD3+ LAG-3+ cells was higher in responders compared to nonresponders (p = 0.0001). LAG-3+ cellular aggregates were associated with response, including CD3+ LAG-3+ in proximity to CD3+ (p = 0.01). Exploratory multivariate modeling showed an association between intratumoral CD3+ LAG-3+ cells and improved PFS independent of prognostic clinical factors (log HR -7.0; 95% confidence interval [CI] -12.7 to -1.4), as well as established biomarkers predictive of ICI response (log HR -5.0; 95% CI -9.8 to -0.2). Intratumoral LAG-3+ immune cell populations warrant further study as a predictive biomarker of clinical benefit to ICIs. Differences in LAG-3+ lymphocyte populations across the intratumoral and peripheral compartments may provide complementary information that could inform the future development of multimodal composite biomarkers of ICI response. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Uncovering the hidden structure of dynamic T cell composition in peripheral blood during cancer immunotherapy: a topic modeling approach.

Immune checkpoint inhibitors (ICIs), now mainstays in the treatment of cancer treatment, show great potential but only benefit a subset of patients. A more complete understanding of the immunological mechanisms and pharmacodynamics of ICI in cancer patients will help identify the patients most likely to benefit and will generate knowledge for the development of next-generation ICI regimens. We set out to interrogate the early temporal evolution of T cell populations from longitudinal single-cell flow cytometry data. We developed an innovative statistical and computational approach using a Latent Dirichlet Allocation (LDA) model that extends the concept of topic modeling used in text mining. This powerful unsupervised learning tool allows us to discover compositional topics within immune cell populations that have distinct functional and differentiation states and are biologically and clinically relevant. To illustrate the model's utility, we analyzed ∼17 million T cells obtained from 138 pre- and on-treatment peripheral blood samples from a cohort of melanoma patients treated with ICIs. We identified three latent dynamic topics: a T-cell exhaustion topic that recapitulates a LAG3+ predominant patient subgroup with poor clinical outcome; a naive topic that shows association with immune-related toxicity; and an immune activation topic that emerges upon ICI treatment. We identified that a patient subgroup with a high baseline of the naïve topic has a higher toxicity grade. While the current application is demonstrated using flow cytometry data, our approach has broader utility and creates a new direction for translating single-cell data into biological and clinical insights.

Beyond the 5-year milestone: Long-term survivorship of melanoma patients treated off-trial with anti-PD-1.

Little is known about the long-term outcomes of anti-PD-1 treated patients with melanoma beyond 5 years, especially for patients treated off clinical trials. This retrospective cohort study includes patients with unresectable stage III/IV nonuveal melanoma treated with anti-PD-1 off-trial at Memorial Sloan Kettering Cancer Center between 2014 and 2017 who survived at least 5 years following their first anti-PD-1 dose (N = 139). We characterized overall survival (OS), melanoma-specific survival (MSS) estimates, treatment-free survival rates, and subsequent treatment courses. Median follow-up among 5-plus year survivors (N = 125) was 78.4 months (range 60.0-96.3). OS at year 7 (2 years post 5-year landmark) was 90.1% (95% CI: 83.0%-94.3%). Fourteen deaths occurred, seven due to melanoma. MSS at year 7 (2 years post 5-year landmark) was 95.0% (95% CI: 33.5%-95.2%). In patients who completed anti-PD-1 based therapy and did not require subsequent treatment by 5 years (N = 80), the probability of not requiring additional treatment for an additional 2 years was 95.7% (95% CI: 91.0%-100%). Patients treated with anti-PD-1 regimens off clinical trials who survive at least 5 years from initial anti-PD-1 treatment can be reassured of their excellent long-term prognosis, particularly if they did not require additional melanoma treatment during the first 5 years.

Decision-Making and Health-Related Quality of Life in Patients with Melanoma Considering Adjuvant Immunotherapy.

BACKGROUND: Adjuvant anti-PD1 treatment improves relapse-free survival (RFS) but has not been shown to improve overall survival (OS) in melanoma and is associated with risks of immune-related adverse events (irAEs), some permanent. We identified factors patients consider in deciding whether to undergo adjuvant anti-PD1 treatment and assessed prospective health-related quality of life (HRQoL), treatment satisfaction, and decisional regret. PATIENTS AND METHODS: Patients with stage IIIB-IV cutaneous melanoma and free of disease, were candidates for adjuvant anti-PD1 immunotherapy, and had not yet discussed adjuvant treatment options with their oncologist were eligible. Participants viewed a 4-minute informational video tailored to their disease stage which communicated comprehensive, quantitative information about the risk of relapse both with and without adjuvant treatment, and risks of each irAE before deciding whether or not to opt for adjuvant therapy. We collected data on demographics, HRQoL, and attitudes toward adjuvant treatment over 1 year. RESULTS: 14/34 patients (41%) opted for adjuvant anti-PD1 immunotherapy, 20/34 (59%) opted for observation. Patients choosing adjuvant immunotherapy scored higher on HRQoL social well-being at pre-treatment, were more likely to endorse positive statements about adjuvant immunotherapy, and to perceive that their physician preferred adjuvant therapy. They had lower decisional regret and higher satisfaction, even if they experienced toxicity or recurrence. CONCLUSIONS: When provided with comprehensive quantitative information about risks and benefits of adjuvant anti-PD1 immunotherapy, 20/34 (59%) of patients opted for observation. Patients choosing adjuvant immunotherapy had lower decisional regret and higher satisfaction over time even if they had poorer outcomes in treatment.

Nivolumab and Relatlimab in Patients With Advanced Melanoma That Had Progressed on Anti-Programmed Death-1/Programmed Death Ligand 1 Therapy: Results From the Phase I/IIa RELATIVITY-020 Trial.

PURPOSE: Nivolumab and relatlimab activity in advanced melanoma with prior progression on anti-programmed death-1/programmed death ligand 1 (PD-(L)1)-containing regimens is under investigation. RELATIVITY-047 demonstrated significantly improved progression-free survival (PFS) for nivolumab and relatlimab over nivolumab in previously untreated advanced melanoma. METHODS: The phase I/IIa, open-label RELATIVITY-020 trial part D assessed efficacy and safety of nivolumab and relatlimab in advanced melanoma with progression during, or within 3 months of, 1 (D1) or ≥ 1 (D2) anti-PD-(L)1-containing regimens. Safety was a primary end point. Objective response rate (coprimary end point) and PFS by blinded independent central review (BICR) were assessed. RESULTS: Five hundred eighteen patients (D1 = 354; D2 = 164) received nivolumab and relatlimab. Among evaluable patients, the objective response rate by BICR was 12.0% (95% CI, 8.8 to 15.8) in D1 (n = 351) and 9.2% (95% CI, 5.2 to 14.7) in D2 (n = 163). Responses appeared to be enriched among patients with tumors expressing programmed death ligand 1 or lymphocyte activation gene 3; however, responses were observed regardless of programmed death ligand 1 and lymphocyte activation gene 3 expression (1%). The median duration of response was not reached (95% CI, 12.9 to not reached) in D1 and 12.8 months (95% CI, 6.9 to 12.9) in D2. The median PFS by BICR was 2.1 months (95% CI, 1.9 to 3.5) in D1 and 3.2 months (95% CI, 1.9 to 3.6) in D2; the 6-month PFS rate was 29.1% (95% CI, 24.2 to 34.1) and 27.7% (95% CI, 20.5 to 35.4), respectively. The grade 3-4 treatment-related adverse event incidence was 15.0% in D1 and 12.8% in D2. One case of grade 3 myocarditis and no treatment-related deaths occurred across part D. CONCLUSION: Nivolumab and relatlimab had a manageable safety profile and demonstrated durable clinical activity in a proportion of patients with heavily pretreated advanced melanoma with prior progression on anti-PD-(L)1-containing regimens.[Media: see text].

Safety, tolerability and efficacy of agonist anti-CD27 antibody (varlilumab) administered in combination with anti-PD-1 (nivolumab) in advanced solid tumors.

BACKGROUND: Phase 1/2 dose-escalation and expansion study evaluating varlilumab, a fully human agonist anti-CD27 mAb, with nivolumab in anti-PD-1/L1 naïve, refractory solid tumors. METHODS: Phase 1 evaluated the safety of varlilumab (0.1-10 mg/kg) with nivolumab (3 mg/kg) administered once every 2 weeks. Phase 2 evaluated varlilumab regimens (3 mg/kg once every 2 weeks, 3 mg/kg once every 12 weeks, and 0.3 mg/kg once every 4 weeks) with nivolumab 240 mg once every 2 weeks in tumor-specific cohorts. Primary objective was safety; key clinical endpoints included objective response rate (ORR) and overall survival rate at 12 months (OS12) (glioblastoma (GBM) only). Exploratory objectives included determination of effects on peripheral blood and intratumoral immune signatures. RESULTS: 175 patients were enrolled (36 in phase 1 and 139 in phase 2). Phase 1 dose-escalation proceeded to the highest varlilumab dose level without determining a maximum tolerated dose. In phase 2, ORR were ovarian 12.5%, squamous cell carcinoma of the head and neck 12.5%, colorectal cancer 5%, and renal cell carcinoma 0%; GBM OS12 was 40.9%. Increased tumor PD-L1 and intratumoral T cell infiltration were observed in ovarian cancer patients, with increases of ≥5% associated with better progression-free survival. The most common treatment related adverse events were fatigue (18%), pruritus (16%), and rash (15%). CONCLUSION: Varlilumab and nivolumab were well tolerated, without significant toxicity beyond that expected for each agent alone. Clinical activity was observed in patients that are typically refractory to anti-PD-1 therapy, however, overall was not greater than expected for nivolumab monotherapy. Treatment was associated with proinflammatory changes in the tumor microenvironment, particularly in ovarian cancer where the changes were associated with better clinical outcomes. TRIAL REGISTRATION NUMBER: NCT02335918.

First-in-Human Phase I/II ICONIC Trial of the ICOS Agonist Vopratelimab Alone and with Nivolumab: ICOS-High CD4 T-Cell Populations and Predictors of Response.

PURPOSE: The first-in-human phase I/II ICONIC trial evaluated an investigational inducible costimulator (ICOS) agonist, vopratelimab, alone and in combination with nivolumab in patients with advanced solid tumors. PATIENTS AND METHODS: In phase I, patients were treated with escalating doses of intravenous vopratelimab alone or with nivolumab. Primary objectives were safety, tolerability, MTD, and recommended phase II dose (RP2D). Phase II enriched for ICOS-positive (ICOS+) tumors; patients were treated with vopratelimab at the monotherapy RP2D alone or with nivolumab. Pharmacokinetics, pharmacodynamics, and predictive biomarkers of response to vopratelimab were assessed. RESULTS: ICONIC enrolled 201 patients. Vopratelimab alone and with nivolumab was well tolerated; phase I established 0.3 mg/kg every 3 weeks as the vopratelimab RP2D. Vopratelimab resulted in modest objective response rates of 1.4% and with nivolumab of 2.3%. The prospective selection for ICOS+ tumors did not enrich for responses. A vopratelimab-specific peripheral blood pharmacodynamic biomarker, ICOS-high (ICOS-hi) CD4 T cells, was identified in a subset of patients who demonstrated greater clinical benefit versus those with no emergence of these cells [overall survival (OS), P = 0.0025]. A potential genomic predictive biomarker of ICOS-hi CD4 T-cell emergence was identified that demonstrated improvement in clinical outcomes, including OS (P = 0.0062). CONCLUSIONS: Vopratelimab demonstrated a favorable safety profile alone and in combination with nivolumab. Efficacy was observed only in a subset of patients with a vopratelimab-specific pharmacodynamic biomarker. A potential predictive biomarker of response was identified, which is being prospectively evaluated in a randomized phase II non-small cell lung cancer trial. See related commentary by Lee and Fong, p. 3633.

Fundamental immune-oncogenicity trade-offs define driver mutation fitness.

Missense driver mutations in cancer are concentrated in a few hotspots1. Various mechanisms have been proposed to explain this skew, including biased mutational processes2, phenotypic differences3-6 and immunoediting of neoantigens7,8; however, to our knowledge, no existing model weighs the relative contribution of these features to tumour evolution. We propose a unified theoretical 'free fitness' framework that parsimoniously integrates multimodal genomic, epigenetic, transcriptomic and proteomic data into a biophysical model of the rate-limiting processes underlying the fitness advantage conferred on cancer cells by driver gene mutations. Focusing on TP53, the most mutated gene in cancer1, we present an inference of mutant p53 concentration and demonstrate that TP53 hotspot mutations optimally solve an evolutionary trade-off between oncogenic potential and neoantigen immunogenicity. Our model anticipates patient survival in The Cancer Genome Atlas and patients with lung cancer treated with immunotherapy as well as the age of tumour onset in germline carriers of TP53 variants. The predicted differential immunogenicity between hotspot mutations was validated experimentally in patients with cancer and in a unique large dataset of healthy individuals. Our data indicate that immune selective pressure on TP53 mutations has a smaller role in non-cancerous lesions than in tumours, suggesting that targeted immunotherapy may offer an early prophylactic opportunity for the former. Determining the relative contribution of immunogenicity and oncogenic function to the selective advantage of hotspot mutations thus has important implications for both precision immunotherapies and our understanding of tumour evolution.

Tumor MHC Class I Expression Associates with Intralesional IL2 Response in Melanoma.

Cancer immunotherapy can result in lasting tumor regression, but predictive biomarkers of treatment response remain ill-defined. Here, we performed single-cell proteomics, transcriptomics, and genomics on matched untreated and IL2 injected metastases from patients with melanoma. Lesions that completely regressed following intralesional IL2 harbored increased fractions and densities of nonproliferating CD8+ T cells lacking expression of PD-1, LAG-3, and TIM-3 (PD-1-LAG-3-TIM-3-). Untreated lesions from patients who subsequently responded with complete eradication of all tumor cells in all injected lesions (individuals referred to herein as "extreme responders") were characterized by proliferating CD8+ T cells with an exhausted phenotype (PD-1+LAG-3+TIM-3+), stromal B-cell aggregates, and expression of IFNγ and IL2 response genes. Loss of membranous MHC class I expression in tumor cells of untreated lesions was associated with resistance to IL2 therapy. We validated this finding in an independent cohort of metastatic melanoma patients treated with intralesional or systemic IL2. Our study suggests that intact tumor-cell antigen presentation is required for melanoma response to IL2 and describes a multidimensional and spatial approach to develop immuno-oncology biomarker hypotheses using routinely collected clinical biospecimens.

Adaptive Dosing of Nivolumab + Ipilimumab Immunotherapy Based Upon Early, Interim Radiographic Assessment in Advanced Melanoma (The ADAPT-IT Study).

PURPOSE: Nivolumab + ipilimumab (nivo + ipi) is highly efficacious but has high toxicity. Standard treatment in advanced melanoma is four doses of nivo + ipi followed by nivo alone. Whether four doses of nivo + ipi are needed is unclear. METHODS: The Adaptively Dosed ImmunoTherapy Trial (ADAPT-IT) study (NCT03122522) is a multicenter, single-arm phase II clinical trial. Patients received two doses of nivo (1 mg/kg) + ipi (3 mg/kg) followed by a computed tomography scan at week 6. Patients without new lesions or index lesion tumor growth of > 4% had protocol-defined early favorable antitumor effect (FATE) and ceased nivo + ipi, transitioning to nivo monotherapy. Patients without FATE at week 6 received the standard third and fourth doses of nivo + ipi followed by nivo monotherapy. The primary end point was response rate by RECIST 1.1 at week 12. Secondary end points included additional efficacy assessments and safety. RESULTS: Sixty patients were enrolled; 41 patients (68%) had FATE at week 6 and met criteria for stopping nivo + ipi. Best overall response rates by RECIST at week 12 or any time afterward were 48% (95% CI, 35 to 62) and 58% (95% CI, 45 to 71), respectively. With a median follow-up of 25 months, the estimated 18-month progression-free survival and overall survival are 52% and 80%, respectively. Fifty seven percent of patients had grade 3-5 treatment-related toxicity. CONCLUSION: The efficacy and toxicity of standard four dose nivo + ipi induction therapy in melanoma is likely driven by the first two doses. An interim computed tomography scan after two doses guided cessation of combination dosing and identified almost all responders. Longer follow-up and further study are needed to fully understand the implications of a shortened induction course of nivo + ipi.

LAG-3 expression on peripheral blood cells identifies patients with poorer outcomes after immune checkpoint blockade.

Immune checkpoint blocking antibodies are a cornerstone in cancer treatment; however, they benefit only a subset of patients and biomarkers to guide immune checkpoint blockade (ICB) treatment choices are lacking. We designed this study to identify blood-based correlates of clinical outcome in ICB-treated patients. We performed immune profiling of 188 ICB-treated patients with melanoma using multiparametric flow cytometry to characterize immune cells in pretreatment peripheral blood. A supervised statistical learning approach was applied to a discovery cohort to classify phenotypes and determine their association with survival and treatment response. We identified three distinct immune phenotypes (immunotypes), defined in part by the presence of a LAG-3+CD8+ T cell population. Patients with melanoma with a LAG+ immunotype had poorer outcomes after ICB with a median survival of 22.2 months compared to 75.8 months for those with the LAG- immunotype (P = 0.031). An independent cohort of 94 ICB-treated patients with urothelial carcinoma was used for validation where LAG+ immunotype was significantly associated with response (P = 0.007), survival (P < 0.001), and progression-free survival (P = 0.004). Multivariate Cox regression and stratified analyses further showed that the LAG+ immunotype was an independent marker of outcome when compared to known clinical prognostic markers and previously described markers for the clinical activity of ICB, PD-L1, and tumor mutation burden. The pretreatment peripheral blood LAG+ immunotype detects patients who are less likely to benefit from ICB and suggests a strategy for identifying actionable immune targets for further investigation.