Immune-Related Colitis Is Associated with Fecal Microbial Dysbiosis and Can Be Mitigated by Fecal Microbiota Transplantation.

Colitis induced by treatment with immune-checkpoint inhibitors (ICI), termed irColitis, is a substantial cause of morbidity complicating cancer treatment. We hypothesized that abnormal fecal microbiome features would be present at the time of irColitis onset and that restoring the microbiome with fecal transplant from a healthy donor would mitigate disease severity. Herein, we present fecal microbiota profiles from 18 patients with irColitis from a single center, 5 of whom were treated with healthy-donor fecal microbial transplantation (FMT). Although fecal samples collected at onset of irColitis had comparable α-diversity to that of comparator groups with gastrointestinal symptoms, irColitis was characterized by fecal microbial dysbiosis. Abundances of Proteobacteria were associated with irColitis in multivariable analyses. Five patients with irColitis refractory to steroids and biologic anti-inflammatory agents received healthy-donor FMT, with initial clinical improvement in irColitis symptoms observed in four of five patients. Two subsequently exhibited recurrence of irColitis symptoms following courses of antibiotics. Both received a second "salvage" FMT that was, again, followed by clinical improvement of irColitis. In summary, we observed distinct microbial community changes that were present at the time of irColitis onset. FMT was followed by clinical improvements in several cases of steroid- and biologic-agent-refractory irColitis. Strategies to restore or prevent microbiome dysbiosis in the context of immunotherapy toxicities should be further explored in prospective clinical trials.

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.

GABA Regulates Electrical Activity and Tumor Initiation in Melanoma.

Oncogenes can initiate tumors only in certain cellular contexts, which is referred to as oncogenic competence. In melanoma, whether cells in the microenvironment can endow such competence remains unclear. Using a combination of zebrafish transgenesis coupled with human tissues, we demonstrate that GABAergic signaling between keratinocytes and melanocytes promotes melanoma initiation by BRAFV600E. GABA is synthesized in melanoma cells, which then acts on GABA-A receptors in keratinocytes. Electron microscopy demonstrates specialized cell-cell junctions between keratinocytes and melanoma cells, and multielectrode array analysis shows that GABA acts to inhibit electrical activity in melanoma/keratinocyte cocultures. Genetic and pharmacologic perturbation of GABA synthesis abrogates melanoma initiation in vivo. These data suggest that GABAergic signaling across the skin microenvironment regulates the ability of oncogenes to initiate melanoma. SIGNIFICANCE: This study shows evidence of GABA-mediated regulation of electrical activity between melanoma cells and keratinocytes, providing a new mechanism by which the microenvironment promotes tumor initiation. This provides insights into the role of the skin microenvironment in early melanomas while identifying GABA as a potential therapeutic target in melanoma. See related commentary by Ceol, p. 2128. This article is featured in Selected Articles from This Issue, p. 2109.

Tissue-specific features of the T cell repertoire after allogeneic hematopoietic cell transplantation in human and mouse.

T cells are the central drivers of many inflammatory diseases, but the repertoire of tissue-resident T cells at sites of pathology in human organs remains poorly understood. We examined the site-specificity of T cell receptor (TCR) repertoires across tissues (5 to 18 tissues per patient) in prospectively collected autopsies of patients with and without graft-versus-host disease (GVHD), a potentially lethal tissue-targeting complication of allogeneic hematopoietic cell transplantation, and in mouse models of GVHD. Anatomic similarity between tissues was a key determinant of TCR repertoire composition within patients, independent of disease or transplant status. The T cells recovered from peripheral blood and spleens in patients and mice captured a limited portion of the TCR repertoire detected in tissues. Whereas few T cell clones were shared across patients, motif-based clustering revealed shared repertoire signatures across patients in a tissue-specific fashion. T cells at disease sites had a tissue-resident phenotype and were of donor origin based on single-cell chimerism analysis. These data demonstrate the complex composition of T cell populations that persist in human tissues at the end stage of an inflammatory disorder after lymphocyte-directed therapy. These findings also underscore the importance of studying T cell in tissues rather than blood for tissue-based pathologies and suggest the tissue-specific nature of both the endogenous and posttransplant T cell landscape.

Moving Spatially Resolved Multiplexed Protein Profiling toward Clinical Oncology.

The shift in cancer therapy from broadly cytotoxic agents toward "personalized" treatments that target specific alterations in each patient's tumor requires diagnostic pathology approaches that are quantitative and biospecimen-friendly. Novel multiplexed antibody-based imaging technologies can measure single-cell expression of over 60 proteins in intact tumor sections and hold promise for clinical oncology.

Cross-platform dataset of multiplex fluorescent cellular object image annotations.

Defining cellular and subcellular structures in images, referred to as cell segmentation, is an outstanding obstacle to scalable single-cell analysis of multiplex imaging data. While advances in machine learning-based segmentation have led to potentially robust solutions, such algorithms typically rely on large amounts of example annotations, known as training data. Datasets consisting of annotations which are thoroughly assessed for quality are rarely released to the public. As a result, there is a lack of widely available, annotated data suitable for benchmarking and algorithm development. To address this unmet need, we release 105,774 primarily oncological cellular annotations concentrating on tumor and immune cells using over 40 antibody markers spanning three fluorescent imaging platforms, over a dozen tissue types and across various cellular morphologies. We use readily available annotation techniques to provide a modifiable community data set with the goal of advancing cellular segmentation for the greater imaging community.

T cell immunotherapies engage neutrophils to eliminate tumor antigen escape variants.

Cancer immunotherapies, including adoptive T cell transfer, can be ineffective because tumors evolve to display antigen-loss-variant clones. Therapies that activate multiple branches of the immune system may eliminate escape variants. Here, we show that melanoma-specific CD4+ T cell therapy in combination with OX40 co-stimulation or CTLA-4 blockade can eradicate melanomas containing antigen escape variants. As expected, early on-target recognition of melanoma antigens by tumor-specific CD4+ T cells was required. Surprisingly, complete tumor eradication was dependent on neutrophils and partly dependent on inducible nitric oxide synthase. In support of these findings, extensive neutrophil activation was observed in mouse tumors and in biopsies of melanoma patients treated with immune checkpoint blockade. Transcriptomic and flow cytometry analyses revealed a distinct anti-tumorigenic neutrophil subset present in treated mice. Our findings uncover an interplay between T cells mediating the initial anti-tumor immune response and neutrophils mediating the destruction of tumor antigen loss variants.

Deep Learning-Inferred Multiplex ImmunoFluorescence for Immunohistochemical Image Quantification.

Reporting biomarkers assessed by routine immunohistochemical (IHC) staining of tissue is broadly used in diagnostic pathology laboratories for patient care. To date, clinical reporting is predominantly qualitative or semi-quantitative. By creating a multitask deep learning framework referred to as DeepLIIF, we present a single-step solution to stain deconvolution/separation, cell segmentation, and quantitative single-cell IHC scoring. Leveraging a unique de novo dataset of co-registered IHC and multiplex immunofluorescence (mpIF) staining of the same slides, we segment and translate low-cost and prevalent IHC slides to more expensive-yet-informative mpIF images, while simultaneously providing the essential ground truth for the superimposed brightfield IHC channels. Moreover, a new nuclear-envelop stain, LAP2beta, with high (>95%) cell coverage is introduced to improve cell delineation/segmentation and protein expression quantification on IHC slides. By simultaneously translating input IHC images to clean/separated mpIF channels and performing cell segmentation/classification, we show that our model trained on clean IHC Ki67 data can generalize to more noisy and artifact-ridden images as well as other nuclear and non-nuclear markers such as CD3, CD8, BCL2, BCL6, MYC, MUM1, CD10, and TP53. We thoroughly evaluate our method on publicly available benchmark datasets as well as against pathologists' semi-quantitative scoring. The code, the pre-trained models, along with easy-to-run containerized docker files as well as Google CoLab project are available at https://github.com/nadeemlab/deepliif.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer.

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Sotigalimab and/or nivolumab with chemotherapy in first-line metastatic pancreatic cancer: clinical and immunologic analyses from the randomized phase 2 PRINCE trial.

Chemotherapy combined with immunotherapy has improved the treatment of certain solid tumors, but effective regimens remain elusive for pancreatic ductal adenocarcinoma (PDAC). We conducted a randomized phase 2 trial evaluating the efficacy of nivolumab (nivo; anti-PD-1) and/or sotigalimab (sotiga; CD40 agonistic antibody) with gemcitabine/nab-paclitaxel (chemotherapy) in patients with first-line metastatic PDAC ( NCT03214250 ). In 105 patients analyzed for efficacy, the primary endpoint of 1-year overall survival (OS) was met for nivo/chemo (57.7%, P = 0.006 compared to historical 1-year OS of 35%, n = 34) but was not met for sotiga/chemo (48.1%, P = 0.062, n = 36) or sotiga/nivo/chemo (41.3%, P = 0.223, n = 35). Secondary endpoints were progression-free survival, objective response rate, disease control rate, duration of response and safety. Treatment-related adverse event rates were similar across arms. Multi-omic circulating and tumor biomarker analyses identified distinct immune signatures associated with survival for nivo/chemo and sotiga/chemo. Survival after nivo/chemo correlated with a less suppressive tumor microenvironment and higher numbers of activated, antigen-experienced circulating T cells at baseline. Survival after sotiga/chemo correlated with greater intratumoral CD4 T cell infiltration and circulating differentiated CD4 T cells and antigen-presenting cells. A patient subset benefitting from sotiga/nivo/chemo was not identified. Collectively, these analyses suggest potential treatment-specific correlates of efficacy and may enable biomarker-selected patient populations in subsequent PDAC chemoimmunotherapy trials.

Treatment of ovarian clear cell carcinoma with immune checkpoint blockade: a case series.

BACKGROUND: Although immune checkpoint blockade has demonstrated limited effectiveness against ovarian cancer, subset analyses from completed trials suggest possible superior efficacy in the clear cell carcinoma subtype. OBJECTIVE: To describe the outcomes of patients with ovarian clear cell carcinoma treated with immune checkpoint blockade. METHODS: This was a single-institution, retrospective case series of patients with ovarian clear cell carcinoma treated with a programmed cell death protein 1 (PD-1) or programmed death-ligand 1 (PD-L1) inhibitor with or without concomitant cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibition between January 2016 and June 2021. Demographic variables, tumor microenvironment, molecular data, and clinical outcomes were examined. Time to treatment failure was defined as the number of days between start of treatment and next line of treatment or death. RESULTS: A total of 16 eligible patients were analyzed. The median treatment duration was 56 days (range 14-574); median time to treatment failure was 99 days (range 27-1568). The reason for discontinuation was disease progression in 88% of cases. Four patients (25%) experienced durable clinical benefit (time to treatment failure ≥180 days). One patient was treated twice with combined immune checkpoint blockade and experienced a complete response each time. All 12 patients who underwent clinical tumor-normal molecular profiling had microsatellite-stable disease, and all but one had low tumor mutation burden. Multiplex immunofluorescence analysis available from pre-treatment biopsies of two patients with clinical benefit demonstrated abundant tumor-infiltrating lymphocytes expressing PD-1. CONCLUSION: Our study suggests a potential role for immune checkpoint blockade in patients with clear cell carcinoma of the ovary. Identification of genetic and microenvironmental biomarkers predictive of response will be key to guide therapy.

Tumor Immune Microenvironment and Response to Neoadjuvant Chemotherapy in Hormone Receptor/HER2+ Early Stage Breast Cancer.

BACKGROUND: Pathologic response at the time of surgery after neoadjuvant therapy for HER2 positive early breast cancer impacts both prognosis and subsequent adjuvant therapy. Comprehensive descriptions of the tumor microenvironment (TME) in patients with HER2 positive early breast cancer is not well described. We utilized standard stromal pathologist-assessed tumor infiltrating lymphocyte (TIL) quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. METHODS: We utilized standard stromal pathologist-assessed TIL quantification, quantitative multiplex immunofluorescence, and RNA-based gene pathway signatures to assess pretreatment TME characteristics associated pathologic complete response in 28 patients with hormone receptor positive, HER2 positive early breast cancer treated in the neoadjuvant setting. RESULTS: Pathologist-assessed stromal TILs were significantly associated with pathologic complete response (pCR). By quantitative multiplex immunofluorescence, univariate analysis revealed significant increases in CD3+, CD3+CD8-FOXP3-, CD8+ and FOXP3+ T-cell densities as well as increased immune cell aggregates in pCR patients. In subsets of paired pre/post-treatment samples, we observed significant changes in gene expression signatures in non-pCR patients and significant decreases in CD8+ densities after treatment in pCR patients. No RNA based pathway signature was associated with pCR. CONCLUSION: TME characterization HER2 positive breast cancer patients revealed several stromal T-cell densities and immune cell aggregates associated with pCR. These results demonstrate the feasibility of these novel methods in TME evaluation and contribute to ongoing investigations of the TME in HER2+ early breast cancer to identify robust biomarkers to best identify patients eligible for systemic de-escalation strategies.

Genomic and transcriptomic analysis of a library of small cell lung cancer patient-derived xenografts.

Access to clinically relevant small cell lung cancer (SCLC) tissue is limited because surgical resection is rare in metastatic SCLC. Patient-derived xenografts (PDX) and circulating tumor cell-derived xenografts (CDX) have emerged as valuable tools to characterize SCLC. Here, we present a resource of 46 extensively annotated PDX/CDX models derived from 33 patients with SCLC. We perform multi-omic analyses, using targeted tumor next-generation sequencing, RNA-sequencing, and immunohistochemistry to deconvolute the mutational landscapes, global expression profiles, and molecular subtypes of these SCLC models. SCLC subtypes characterized by transcriptional regulators, ASCL1, NEUROD1 and POU2F3 are confirmed in this cohort. A subset of SCLC clinical specimens, including matched PDX/CDX and clinical specimen pairs, confirm that the primary features and genomic and proteomic landscapes of the tumors of origin are preserved in the derivative PDX models. This resource provides a powerful system to study SCLC biology.

Understanding the impact of chemotherapy on the immune landscape of high-grade serous ovarian cancer.

OBJECTIVES: We quantitatively characterized the change in temporospatial expression of repressive and stimulatory checkpoints across immune cell populations in the tumor microenvironment in a cohort of high grade serous ovarian carcinomas (HGSOC) using matched samples before and after neoadjuvant platinum-based chemotherapy. METHODS: Using retrospectively collected matched tissue samples from 9 patients, cell populations were assessed using multiplex immunofluorescence using the Vectra Multispectral Imaging System (Perkin Elmer). We used multiple panels to assess: tumor (AE1/AE3), T cells (CD3, CD8, FOXP3), macrophages (CD68) as well as immune checkpoints (C3aR, PD-1, PD-L1, LAG3, IDO, ICOS, GITR). IHC staining was performed for folate receptor status. Changes in immune cell populations as well as intensities of associated repressive and stimulatory proteins were assessed pre- to post-treatment. RESULTS: We observed a consistently high pre-treatment stromal macrophage population which is reduced post-chemotherapy with post-treatment enrichment in macrophage PD-L1 expression. While inhibitory checkpoint expression on T cells was heterogeneous post-chemotherapy, we observed a change in the ThICOS+:Treg ratio which resulted in ThICOS+ cells outnumbering Treg cells post-treatment. Spatial analysis revealed the proximity of Treg cells to ThICOS+ T cells decreased post-treatment. We also observed upward shifts in Teff:Treg T cell ratios with retention of immune checkpoints PD-1, LAG3 and GITR. CONCLUSIONS: In this unique dataset of pre and post matched chemotherapy treated HGSOC patients, we observed changes in immune cell subsets expressing repressive or stimulatory proteins resulting in immune compositions more favorable to checkpoint modulations, suggesting novel therapeutic strategies in the recurrent setting.

Ipilimumab alone or in combination with nivolumab in patients with advanced melanoma who have progressed or relapsed on PD-1 blockade: clinical outcomes and translational biomarker analyses.

BACKGROUND: There are no validated biomarkers that can aid clinicians in selecting who would best benefit from anticytotoxic T lymphocyte-associated antigen 4 monotherapy versus combination checkpoint blockade in patients with advanced melanoma who have progressive disease after programmed death 1 (PD-1) blockade. METHODS: We conducted a randomized multicenter phase II trial in patients with advanced melanoma. Patients were randomly assigned to receive either 1 mg/kg of nivolumab plus 3 mg/kg of ipilimumab or 3 mg/kg of ipilimumab every 3 weeks for up to four doses. Patients were stratified by histological subtype and prior response to PD-1 therapy. The primary clinical objective was overall response rate by week 18. Translational biomarker analyses were conducted in patients with blood and tissue samples. RESULTS: Objective responses were seen in 5 of 9 patients in the ipilimumab arm and 2 of 10 patients in the ipilimumab+nivolumab arm; disease control rates (DCRs) (66.7% vs 60.0%) and rates of grade 3-4 adverse events (56% vs 50%) were comparable between arms. In a pooled analysis, patients with clinical benefit (CB), defined as Response Evaluation Criteria in Solid Tumors response or progression-free for 6 months, showed increased circulating CD4+ T cells with higher polyfunctionality and interferon gamma production following treatment. Tumor profiling revealed enrichment of NRAS mutations and activation of transcriptional programs associated with innate and adaptive immunity in patients with CB. CONCLUSIONS: In patients with advanced melanoma that previously progressed on PD-1 blockade, objective responses were seen in both arms, with comparable DCRs. Findings from biomarker analyses provided hypothesis-generating signals for validation in future studies of larger patient cohorts. TRIAL REGISTRATION NUMBER: NCT02731729.

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.

Inhibition of XPO1 Sensitizes Small Cell Lung Cancer to First- and Second-Line Chemotherapy.

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by early metastasis and extreme lethality. The backbone of SCLC treatment over the past several decades has been platinum-based doublet chemotherapy, with the recent addition of immunotherapy providing modest benefits in a subset of patients. However, nearly all patients treated with systemic therapy quickly develop resistant disease, and there is an absence of effective therapies for recurrent and progressive disease. Here we conducted CRISPR-Cas9 screens using a druggable genome library in multiple SCLC cell lines representing distinct molecular subtypes. This screen nominated exportin-1, encoded by XPO1, as a therapeutic target. XPO1 was highly and ubiquitously expressed in SCLC relative to other lung cancer histologies and other tumor types. XPO1 knockout enhanced chemosensitivity, and exportin-1 inhibition demonstrated synergy with both first- and second-line chemotherapy. The small molecule exportin-1 inhibitor selinexor in combination with cisplatin or irinotecan dramatically inhibited tumor growth in chemonaïve and chemorelapsed SCLC patient-derived xenografts, respectively. Together these data identify exportin-1 as a promising therapeutic target in SCLC, with the potential to markedly augment the efficacy of cytotoxic agents commonly used in treating this disease. SIGNIFICANCE: CRISPR-Cas9 screening nominates exportin-1 as a therapeutic target in SCLC, and exportin-1 inhibition enhances chemotherapy efficacy in patient-derived xenografts, providing a novel therapeutic opportunity in this disease.

Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer.

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively). To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 155,098 transcriptomes from 21 human biospecimens, including 54,523 SCLC transcriptomes. We observe greater tumor diversity in SCLC than lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discover a PLCG2-high SCLC phenotype with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival. SCLC exhibits greater immune sequestration and less immune infiltration than lung adenocarcinoma, and SCLC-N shows less immune infiltrate and greater T cell dysfunction than SCLC-A. We identify a profibrotic, immunosuppressive monocyte/macrophage population in SCLC tumors that is particularly associated with the recurrent, PLCG2-high subpopulation.

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.