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Immunotherapy has revolutionized the treatment of advanced melanoma. Because the pathways mediating resistance to immunotherapy are largely unknown, we conducted transcriptome profiling of preimmunotherapy tumor biopsies from patients with melanoma that received PD-1 blockade or adoptive cell therapy with tumor-infiltrating lymphocytes. We identified two melanoma-intrinsic, mutually exclusive gene programs, which were controlled by IFNγ and MYC, and the association with immunotherapy outcome. MYC-overexpressing melanoma cells exhibited lower IFNγ responsiveness, which was linked with JAK2 downregulation. Luciferase activity assays, under the control of JAK2 promoter, demonstrated reduced activity in MYC-overexpressing cells, which was partly reversible upon mutagenesis of a MYC E-box binding site in the JAK2 promoter. Moreover, silencing of MYC or its cofactor MAX with siRNA increased JAK2 expression and IFNγ responsiveness of melanomas, while concomitantly enhancing the effector functions of T cells coincubated with MYC-overexpressing cells. Thus, we propose that MYC plays a pivotal role in immunotherapy resistance through downregulation of JAK2.

Comparison between proteome and transcriptome profiling. Related to Figure 1.

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Immunotherapy has revolutionized the treatment of advanced melanoma. Because the pathways mediating resistance to immunotherapy are largely unknown, we conducted transcriptome profiling of preimmunotherapy tumor biopsies from patients with melanoma that received PD-1 blockade or adoptive cell therapy with tumor-infiltrating lymphocytes. We identified two melanoma-intrinsic, mutually exclusive gene programs, which were controlled by IFNγ and MYC, and the association with immunotherapy outcome. MYC-overexpressing melanoma cells exhibited lower IFNγ responsiveness, which was linked with JAK2 downregulation. Luciferase activity assays, under the control of JAK2 promoter, demonstrated reduced activity in MYC-overexpressing cells, which was partly reversible upon mutagenesis of a MYC E-box binding site in the JAK2 promoter. Moreover, silencing of MYC or its cofactor MAX with siRNA increased JAK2 expression and IFNγ responsiveness of melanomas, while concomitantly enhancing the effector functions of T cells coincubated with MYC-overexpressing cells. Thus, we propose that MYC plays a pivotal role in immunotherapy resistance through downregulation of JAK2.

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Supplementary Table from Adenosine-Deaminase-Acting-on-RNA-1 Facilitates T-cell Migration toward Human Melanoma Cells

The effect of tumor/T-cell interactions on subsequent immune infiltration is undefined. Here, we report that preexposure of melanoma cells to cognate T cells enhanced the chemotaxis of new T cells in vitro. The effect was HLA class I–restricted and IFNγ-dependent, as it was abolished by β2M-knockdown, MHC-blocking antibodies, JAK1 inhibitors, JAK1-silencing and IFNgR1-blocking antibodies. RNA sequencing (RNA-seq) of 73 melanoma metastases showed a significant correlation between the interferon-inducible p150 isoform of adenosine-deaminase-acting-on-RNA-1 (ADAR1) enzyme and immune infiltration. Consistent with this, cocultures of cognate melanoma/T-cell pairs led to IFNγ-dependent induction of ADAR1-p150 in the melanoma cells, as visualized in situ using dynamic cell blocks, in ovo using fertilized chick eggs, and in vitro with Western blots. ADAR1 staining and RNA-seq in patient-derived biopsies following immunotherapy showed a rise in ADAR1-p150 expression concurrently with CD8+ cell infiltration and clinical response. Silencing ADAR1-p150 abolished the IFNγ-driven enhanced T-cell migration, confirming its mechanistic role. Silencing and overexpression of the constitutive isoform of ADAR1, ADAR1-p110, decreased and increased T-cell migration, respectively. Chemokine arrays showed that ADAR1 controls the secretion of multiple chemokines from melanoma cells, probably through microRNA-mediated regulation. Chemokine receptor blockade eliminated the IFNγ-driven T-cell chemotaxis. We propose that the constitutive ADAR1 downregulation observed in melanoma contributes to immune exclusion, whereas antigen-specific T cells induce ADAR1-p150 by releasing IFNγ, which can drive T-cell infiltration.

Supplementary Figure from Adenosine-Deaminase-Acting-on-RNA-1 Facilitates T-cell Migration toward Human Melanoma Cells

The effect of tumor/T-cell interactions on subsequent immune infiltration is undefined. Here, we report that preexposure of melanoma cells to cognate T cells enhanced the chemotaxis of new T cells in vitro. The effect was HLA class I–restricted and IFNγ-dependent, as it was abolished by β2M-knockdown, MHC-blocking antibodies, JAK1 inhibitors, JAK1-silencing and IFNgR1-blocking antibodies. RNA sequencing (RNA-seq) of 73 melanoma metastases showed a significant correlation between the interferon-inducible p150 isoform of adenosine-deaminase-acting-on-RNA-1 (ADAR1) enzyme and immune infiltration. Consistent with this, cocultures of cognate melanoma/T-cell pairs led to IFNγ-dependent induction of ADAR1-p150 in the melanoma cells, as visualized in situ using dynamic cell blocks, in ovo using fertilized chick eggs, and in vitro with Western blots. ADAR1 staining and RNA-seq in patient-derived biopsies following immunotherapy showed a rise in ADAR1-p150 expression concurrently with CD8+ cell infiltration and clinical response. Silencing ADAR1-p150 abolished the IFNγ-driven enhanced T-cell migration, confirming its mechanistic role. Silencing and overexpression of the constitutive isoform of ADAR1, ADAR1-p110, decreased and increased T-cell migration, respectively. Chemokine arrays showed that ADAR1 controls the secretion of multiple chemokines from melanoma cells, probably through microRNA-mediated regulation. Chemokine receptor blockade eliminated the IFNγ-driven T-cell chemotaxis. We propose that the constitutive ADAR1 downregulation observed in melanoma contributes to immune exclusion, whereas antigen-specific T cells induce ADAR1-p150 by releasing IFNγ, which can drive T-cell infiltration.

PURPOSE Tumor-intrinsic features may render large B-cell lymphoma (LBCL) insensitive to CD19-directed chimeric antigen receptor T cells (CAR-T). We hypothesized that TP53 genomic alterations are detrimental to response outcomes in LBCL treated with CD19-CAR-T. MATERIALS AND METHODS Patients with LBCL treated with CD19-CAR-T were included. Targeted next-generation sequencing was performed on pre–CAR-T tumor samples in a subset of patients. Response and survival rates by histologic, cytogenetic, and molecular features were assessed. Within a cohort of newly diagnosed LBCL with genomic and transcriptomic profiling, we studied interactions between cellular pathways and TP53 status. RESULTS We included 153 adults with relapsed or refractory LBCL treated with CD19-CAR-T (axicabtagene ciloleucel [50%], tisagenlecleucel [32%], and lisocabtagene maraleucel [18%]). Outcomes echoed pivotal trials: complete response (CR) rate 54%, median overall survival (OS) 21.1 months (95% CI, 14.8 to not reached), and progression-free survival 6 months (3.4 to 9.7). Histologic and cytogenetic LBCL features were not predictive of CR. In a subset of 82 patients with next-generation sequencing profiling, CR and OS rates were comparable with the unsequenced cohort. TP53 alterations (mutations and/or copy number alterations) were common (37%) and associated with inferior CR and OS rates in univariable and multivariable regression models; the 1-year OS in TP53-altered LBCL was 44% (95% CI, 29 to 67) versus 76% (65 to 89) in wild-type ( P = .012). Transcriptomic profiling from a separate cohort of patients with newly diagnosed lymphoma (n = 562) demonstrated that TP53 alterations are associated with dysregulation of pathways related to CAR-T-cell cytotoxicity, including interferon and death receptor signaling pathway and reduced CD8 T-cell tumor infiltration. CONCLUSION TP53 is a potent tumor-intrinsic biomarker that can inform risk stratification and clinical trial design in patients with LBCL treated with CD19-CAR-T. The role of TP53 should be further validated in independent cohorts.

Purpose:Treatment of metastatic melanoma has dramatically improved in recent years, thanks to the development of immunotherapy and BRAF-MEK–targeted therapies. However, these developments revealed marked heterogeneity in patient response, which is yet to be fully understood. In this work, we aimed to associate the proteomic profiles of metastatic melanoma with the patient clinical information, to identify protein correlates with metastatic location and prior treatments.Experimental Design:We performed mass spectrometry–based proteomic analysis of 185 metastatic melanoma samples and followed with bioinformatics analysis to examine the association of metastatic location, BRAF status, survival, and immunotherapy response with the tumor molecular profiles.Results:Bioinformatics analysis showed a high degree of functional heterogeneity associated with the site of metastasis. Lung metastases presented higher immune-related proteins, and higher mitochondrial-related processes, which were shown previously to be associated with better immunotherapy response. In agreement, epidemiological analysis of data from the National Cancer Database showed improved response to anti-programmed death 1, mainly in patients with lung metastasis. Focus on lung metastases revealed prognostic and molecular heterogeneity and highlighted potential tissue-specific biomarkers. Analysis of the BRAF mutation status and prior treatments with MAPK inhibitors proposed the molecular basis of the effect on immunotherapy response and suggested coordinated combination of immunotherapy and targeted therapy may increase treatment efficacy.Conclusions:Altogether, the proteomic data provided novel molecular determinants of critical clinical features, including the effects of sequential treatments and metastatic locations. These results can be the basis for development of site-specific treatments toward treatment personalization.

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Tumor-intrinsic features may render large B-cell lymphoma (LBCL) insensitive to CD19-directed chimeric antigen receptor T cells (CAR-T). We hypothesized that TP53 genomic alterations are detrimental to response outcomes in LBCL treated with CD19-CAR-T. MATERIALS AND METHODS: Patients with LBCL treated with CD19-CAR-T were included. Targeted next-generation sequencing was performed on pre–CAR-T tumor samples in a subset of patients. Response and survival rates by histologic, cytogenetic, and molecular features were assessed. Within a cohort of newly diagnosed LBCL with genomic and transcriptomic profiling, we studied interactions between cellular pathways and TP53 status. RESULTS: We included 153 adults with relapsed or refractory LBCL treated with CD19-CAR-T (axicabtagene ciloleucel [50%], tisagenlecleucel [32%], and lisocabtagene maraleucel [18%]). Outcomes echoed pivotal trials: complete response (CR) rate 54%, median overall survival (OS) 21.1 months (95% CI, 14.8 to not reached), and progression-free survival 6 months (3.4 to 9.7). Histologic and cytogenetic LBCL features were not predictive of CR. In a subset of 82 patients with next-generation sequencing profiling, CR and OS rates were comparable with the unsequenced cohort. TP53 alterations (mutations and/or copy number alterations) were common (37%) and associated with inferior CR and OS rates in univariable and multivariable regression models; the 1-year OS in TP53-altered LBCL was 44% (95% CI, 29 to 67) versus 76% (65 to 89) in wild-type (P = .012). Transcriptomic profiling from a separate cohort of patients with newly diagnosed lymphoma (n = 562) demonstrated that TP53 alterations are associated with dysregulation of pathways related to CAR-T-cell cytotoxicity, including interferon and death receptor signaling pathway and reduced CD8 T-cell tumor infiltration. CONCLUSION: TP53 is a potent tumor-intrinsic biomarker that can inform risk stratification and clinical trial design in patients with LBCL treated with CD19-CAR-T. The role of TP53 should be further validated in independent cohorts.

BackgroundMultiplex immunofluorescence (mIF) can provide invaluable insights into spatial biology and the complexities of the immune tumor microenvironment (iTME). However, existing analysis approaches are both laborious and highly user-dependent. In order to overcome these limitations we developed a novel, end-to-end deep learning (DL) pipeline for rapid and accurate analysis of both tumor-microarray (TMA) and whole slide mIF images.MethodsOur pipeline consists of two DL models: a multi-classifier for classifying multi-channel cell images into 12 different cell types, and a binary classifier for determining the positivity of a given marker in single-channel images. The DL multi-classifier was trained on 7,000 tiles labeled with cell annotations from a publicly available CODEX dataset, consisting of 140 tissue cores from 35 colorectal cancer (CRC) patients. For the binary classifier training, the multi-channel tiles were further split into ∼100,000 single-channel tiles, for which the ground truth was inferred from the known expression of these markers in each cell-type. This DL binary classifier was then utilized to quantify the positivity of various cell state (phenotypic) markers. In addition, the binary classifier was exploited as a cell-typing tool, by predicting the positivity of individual lineage cell markers. The performance of our DL models was evaluated on 1,800 annotations from 14 test tissue cores. The models were further evaluated on a new 6-plex melanoma cohort, stained with PhenoImager®, and were compared to the performance of clustering, manual thresholding or machine learning-based cell-typing methods applied on the same test sets.ResultsOur DL multi-classifier achieved highly accurate results, outperforming all of the tested cell-typing methods, including clustering, manual-thresholding and ML-based approaches, in both CODEX CRC and PhenoImager melanoma cohorts (accuracy of 91% and 87%, respectively), with F1-scores above 80% in the vast majority of cell types. Our DL binary classifier, which was trained solely on the lineage markers of the CRC dataset, also outperformed existing methods, demonstrating excellent F1-scores (>80%) for determining the positivity of unseen phenotypic and lineage markers across the two tumor types and imaging modalities. Notably, as little as 20 annotations were required in order to boost the performance on an unseen dataset to above 85% accuracy and 80% F1-scores. As a result, the DL binary classifier could successfully be used as a cell-typing model, in a manner that is transferable between experimental approaches.ConclusionsWe present a novel state-of-the-art DL-based framework for multiplex imaging analysis, that enables accurate cell typing and phenotypic marker quantification, which is robust across markers, tumor indications, and imaging modalities.

Background: Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that develop in non-lymphoid tissues and are associated with better prognosis and immunotherapy response across cancer types. Multiple IHC stainings are required for an accurate detection of TLS, making it challenging to implement as a clinical biomarker. Here, we developed a deep learning (DL) model that extracts nuclear morphology features to detect TLS from H&E slides and demonstrated its prognostic role in colorectal cancer (CRC) patients. Methods: A publicly available dataset consisting of 140 tissue cores from 35 CRC pts stained with H&E and 56 protein markers using the CODEX multiplex immunofluorescence (mIF) system was analyzed. Immune cell aggregates on the H&E were annotated by expert pathologists as either TLS or lymphocyte aggregates (LA), based on marker expression from the mIF stain on the same core. TLS were defined as dense aggregates of CD3+/CD20+/CD21+ cells, while all other immune cell aggregates were defined as LA. Next, HoVerNet was used to perform nuclear segmentation on cells within the TLS and LA on the H&E. Nuclear features including eccentricity, solidity, convexity, and nuclear intensity per cell were extracted and the mean and variance of each feature was summarized per tissue core. Based on these features, a univariate analysis comparing TLS and LA was performed, and a TLS classifier was trained using multivariate logistic regression. The classifier performance was assessed using 5 repeats of 5-fold cross validation and average accuracy and area under the ROC curve (AUC) were calculated. Overall survival (OS) was compared between patients with predicted TLS and LA using a Cox proportional hazard regression analysis. Results: From the 140 tissue cores, we identified cores with either TLS (n=18), LA (n=34) or none (n=92). No core presented both TLS and LA. In a Mann Whitney univariate analysis, cells in TLS areas demonstrated a higher mean nuclear eccentricity (p Conclusions: Nuclear based morphological features can be used to accurately detect the presence of TLS and LA from H&E slides, without the need for mIF or IHC stainings. Given the predictive value of TLS presence, this work demonstrates the potential for H&E slides to be used for patient selection for immunotherapy treatments. Citation Format: Becky Arbiv, Tal Dankovich, Sun Dagan, Yuval Shachaf, Tomer Dicker, Ron Elran, Avi Laniado, Amit Bart, Ori Zelichov, Ettai Markovits. Identification of tertiary lymphoid structures from H&E slides using deep learning analysis of nuclear morphology is associated with favorable survival in colorectal cancer patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4316.

Adoptive cell transfer (ACT) using autologous tumor infiltrating lymphocytes (TILs) was previously shown to yield clinical response in metastatic melanoma patients as an advanced line. Unfortunately, there is no reliable marker for predicting who will benefit from the treatment. We analyzed TIL samples from the infusion bags used for treatment of 57 metastatic melanoma patients and compared their microRNA profiles. The discovery cohort included six responding patients and seven patients with progressive disease, as defined by RECIST1.1. High throughput analysis with NanoString nCounter demonstrated significantly higher levels of miR-34a-5p and miR-22-3p among TIL from non-responders. These results were validated in TIL infusion bag samples from an independent cohort of 44 patients, using qRT-PCR of the individual microRNAs. Using classification trees, a data-driven predictive model for response was built, based on the level of expression of these microRNAs. Patients that achieved stable disease were classified with responders, setting apart the patients with progressive disease. Moreover, the expression levels of miR-34a-5p in the infused TIL created distinct survival groups, which strongly supports its role as a potential biomarker for TIL-ACT therapy. Indeed, when tested against autologous melanoma cells, miRLow TIL cultures exhibited significantly higher cytotoxic activity than miRHigh TIL cultures, and expressed features of terminally exhausted effectors. Finally, overexpression of miR-34a-5p or miR-22-3p in TIL inhibited their cytotoxic ability in vitro. Overall, we show that a two-microRNA signature correlates with failure of TIL-ACT therapy and survival in melanoma patients.

Immunotherapy with checkpoint inhibitors revolutionized melanoma treatment in both the adjuvant and metastatic setting, yet not all metastatic patients respond, and metastatic disease still often recurs among immunotherapy-treated patients with locally advanced disease. TNFSF4 is a co-stimulatory checkpoint protein expressed by several types of immune and non-immune cells, and was shown in the past to enhance the anti-neoplastic activity of T cells. Here, we assessed its expression in melanoma and its association with outcome in locally advanced and metastatic disease. We used publicly available data from The Cancer Genome Atlas (TCGA) and the Cancer Cell Line Encyclopedia (CCLE), and RNA sequencing data from anti-PD1-treated patients at Sheba medical center. TNFSF4 mRNA is expressed in melanoma cell lines and melanoma samples, including those with low lymphocytic infiltrates, and is not associated with the ulceration status of the primary tumor. Low expression of TNFSF4 mRNA is associated with worse prognosis in all melanoma patients and in the cohorts of stage III and stage IIIc-IV patients. Low expression of TNFSF4 mRNAs is also associated with worse prognosis in the subgroup of patients with low lymphocytic infiltrates, suggesting that tumoral TNFSF4 is associated with outcome. TNFSF4 expression was not correlated with the expression of other known checkpoint mRNAs. Last, metastatic patients with TNFSF4 mRNA expression within the lowest quartile have significantly worse outcome on anti-PD1 treatment, and a significantly lower response rate to these agents. Our current work points to TNFSF4 expression in melanoma as a potential determinant of prognosis, and warrants further translational and clinical research.

This decade has introduced drastic changes in melanoma therapy, predominantly due to the materialization of the long promise of immunotherapy. Cytotoxic T cells are the chief component of the immune system, which are targeted by different strategies aimed to increase their capacity against melanoma cells. To this end, reprogramming of T cells occurs by T cell centered manipulation, targeting the immunosuppressive tumor microenvironment or altering the whole patient. These are enabled by delivery of small molecules, functional monoclonal antibodies, different subunit vaccines, as well as living lymphocytes, native or genetically engineered. Current FDA-approved therapies are focused on direct T cell manipulation, such as immune checkpoint inhibitors blocking CTLA-4 and/or PD-1, which paves the way for an effective immunotherapy backbone available for combination with other modalities. Here we review the biology and clinical developments that enable melanoma immunotherapy today and in the future.

Purpose: Treatment of metastatic melanoma has dramatically improved in recent years, thanks to the development of immunotherapy and BRAF-MEK–targeted therapies. However, these developments revealed marked heterogeneity in patient response, which is yet to be fully understood. In this work, we aimed to associate the proteomic profiles of metastatic melanoma with the patient clinical information, to identify protein correlates with metastatic location and prior treatments. Experimental Design: We performed mass spectrometry–based proteomic analysis of 185 metastatic melanoma samples and followed with bioinformatics analysis to examine the association of metastatic location, BRAF status, survival, and immunotherapy response with the tumor molecular profiles. Results: Bioinformatics analysis showed a high degree of functional heterogeneity associated with the site of metastasis. Lung metastases presented higher immune-related proteins, and higher mitochondrial-related processes, which were shown previously to be associated with better immunotherapy response. In agreement, epidemiological analysis of data from the National Cancer Database showed improved response to anti-programmed death 1, mainly in patients with lung metastasis. Focus on lung metastases revealed prognostic and molecular heterogeneity and highlighted potential tissue-specific biomarkers. Analysis of the BRAF mutation status and prior treatments with MAPK inhibitors proposed the molecular basis of the effect on immunotherapy response and suggested coordinated combination of immunotherapy and targeted therapy may increase treatment efficacy. Conclusions: Altogether, the proteomic data provided novel molecular determinants of critical clinical features, including the effects of sequential treatments and metastatic locations. These results can be the basis for development of site-specific treatments toward treatment personalization.

Adoptive cell transfer (ACT) using autologous tumor infiltrating lymphocytes (TILs) was previously shown to yield clinical response in metastatic melanoma patients as an advanced line. Unfortunately, there is no reliable marker for predicting who will benefit from the treatment. We analyzed TIL samples from the infusion bags used for treatment of 57 metastatic melanoma patients and compared their microRNA profiles. The discovery cohort included six responding patients and seven patients with progressive disease, as defined by RECIST1.1. High throughput analysis with NanoString nCounter demonstrated significantly higher levels of miR-34a-5p and miR-22-3p among TIL from non-responders. These results were validated in TIL infusion bag samples from an independent cohort of 44 patients, using qRT-PCR of the individual microRNAs. Using classification trees, a data-driven predictive model for response was built, based on the level of expression of these microRNAs. Patients that achieved stable disease were classified with responders, setting apart the patients with progressive disease. Moreover, the expression levels of miR-34a-5p in the infused TIL created distinct survival groups, which strongly supports its role as a potential biomarker for TIL-ACT therapy. Indeed, when tested against autologous melanoma cells, miR

Background: Tumor-intrinsic molecular features informing risk and resistance mechanisms in large-B-cell lymphoma (LBCL) treated with CD19-directed chimeric antigen receptor T-cells (CAR-T) are lacking. TP53 has been implicated in aberrant apoptosis signaling and immune evasion. We hypothesized that TP53-alterations are detrimental in LBCL treated with CD19-CAR-T. Methods: Patients with relapsed/refractory LBCL treated with CD19-CAR-T were included. Targeted next-generation sequencing (NGS) encompassing protein-coding exons of over 400 genes (MSK-IMPACT) was performed on pre-CAR-T tumor samples in a subset of patients. Response and survival rates by tumor-intrinsic histological, cytogenetic, and molecular markers were assessed. Interactions between genomic aberrations and cellular pathways that could contribute to CAR-T resistance were studied using publicly available datasets with genomic and transcriptomic profiling. Results: We included 136 adults with LBCL treated with CD19-CAR-T. (axicabtagene-ciloleucel [70, 51%], tisagenlecleucel [38, 28%], lisocabtagene-maraleucel [28. 21%]). Patients were heavily pre-treated (≥4 treatment lines [58%]) and primarily categorized as diffuse large B-cell lymphoma (DLBCL)-NOS (79%) followed by double/triple hit high-grade lymphoma (12%). DLBCL transformed from follicular lymphoma, high KI67-index, germinal center B-cell cell of origin, and double expressor phenotype were highly represented (43%, 47%, 50%, and 40%, respectively). Outcomes in the complete cohort echoed pivotal trials: best overall response rate 78% (Fig. A), median overall survival (OS) 22.7 months (95%CI 14.8-NR), median progression-free survival 6.2 months (3.3-12.3). A subset of 76 patients had tumor NGS profiling. Clinical features and CR and OS rates were similar across patients with and without NGS. TP53 genomic alterations were common (28, 37%). A total of 26 TP53 mutations (22 missense; 2 in-frame deletions; 2 splice sites) were identified in 23 patients. An additional five patients had TP53 homozygous deletions (i.e., copy number alterations). Two patients had concurrent TP53 mutations and homozygous deletions. Among tumor-intrinsic factors, only TP53-alterations were predictive of complete response (CR) in univariable and multivariable logistic regression; no association was observed with histological and cytogenetic features (Fig. B). TP53-alterations were also predictive of OS in univariable and multivariable Cox regression (Fig. C-D; 1-year OS in TP53-altered (48% [95% CI 32 - 71]) vs. wild-type (75% [64 - 89]), p = 0.039). Notably, in TP53-altered LBCL, axicabtagene-ciloleucel therapy was associated with superior OS compared to aggregated 41BB products (HR 3.40 [1.19-9.66]) in multivariable Cox regression adjusted for age, performance status, and primary refractory disease (Fig. E). Transcriptomic analysis of publicly available samples from newly diagnosed LBCL patients (n=562) demonstrated that TP53-alterations are associated with dysregulation of pathways related to CAR-T cell cytotoxicity, including downregulation of interferon and death receptor pathway genes, and reduced CD8 T-cell tumor infiltration (Fig. F-H). Conclusions: We show, for the first time, that TP53 alterations are a valuable prognostic and potentially predictive marker in LGBL CD19-CAR-T recipients. Gene expression profiling suggests that TP53 alterations result in an immunosuppressive tumor-microenvironment and impaired apoptosis signaling, which could lead to decreased CAR-T efficacy. Figure 1 Figure 1. Disclosures Shouval: Medexus: Consultancy. Batlevi: Life Sciences: Consultancy; Kite Pharma: Consultancy; Juno/Celgene: Consultancy; GLG Pharma: Consultancy; Pfizer: Current holder of individual stocks in a privately-held company; Medscape: Honoraria; BMS: Current holder of individual stocks in a privately-held company; Seattle Genetics: Consultancy; Memorial Sloan Kettering Cancer Center: Current Employment; Moderna: Current holder of individual stocks in a privately-held company; Regeneron: Current holder of individual stocks in a privately-held company; Viatris: Current holder of individual stocks in a privately-held company; Karyopharm: Consultancy; TG Therapeutics: Consultancy; ADC Therapeutics: Consultancy; Dava Oncology: Honoraria; Bayer: Research Funding; TouchIME: Honoraria; Xynomic: Research Funding; Roche/Genentech: Research Funding; Novartis: Research Funding; Epizyme: Research Funding; Janssen: Research Funding; Autolus: Research Funding. Dahi: Kite / Gilead: Membership on an entity's Board of Directors or advisory committees. Giralt: AMGEN: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; SANOFI: Membership on an entity's Board of Directors or advisory committees; PFIZER: Membership on an entity's Board of Directors or advisory committees; JENSENN: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; JAZZ: Membership on an entity's Board of Directors or advisory committees; CELGENE: Membership on an entity's Board of Directors or advisory committees; Actinnum: Membership on an entity's Board of Directors or advisory committees. Salles: Janssen: Consultancy; Novartis: Consultancy; Epizyme: Consultancy, Honoraria; Miltneiy: Consultancy; Regeneron: Consultancy, Honoraria; Incyte: Consultancy; Ipsen: Consultancy; Kite/Gilead: Consultancy; Morphosys: Consultancy, Honoraria; Velosbio: Consultancy; Takeda: Consultancy; Loxo: Consultancy; Genentech/Roche: Consultancy; Rapt: Consultancy; Genmab: Consultancy; Allogene: Consultancy; Debiopharm: Consultancy; BMS/Celgene: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Honoraria; Bayer: Honoraria. Sauter: Bristol-Myers Squibb: Research Funding; GSK: Consultancy; Genmab: Consultancy; Precision Biosciences: Consultancy; Kite/Gilead: Consultancy; Celgene: Consultancy, Research Funding; Gamida Cell: Consultancy; Novartis: Consultancy; Spectrum Pharmaceuticals: Consultancy; Juno Therapeutics: Consultancy, Research Funding; Sanofi-Genzyme: Consultancy, Research Funding. Scordo: i3 Health: Other: Speaker; Kite - A Gilead Company: Membership on an entity's Board of Directors or advisory committees; Angiocrine Bioscience: Consultancy, Research Funding; Omeros Corporation: Consultancy; McKinsey & Company: Consultancy. Shah: Amgen: Research Funding; Janssen Pharmaceutica: Research Funding. van den Brink: Seres: Other: Honorarium, Intellectual Property Rights, Research Fundingand Stock Options; Ceramedix: Other: has consulted, received honorarium from or participated in advisory boards ; Merck & Co, Inc: Honoraria; WindMILTherapeutics: Honoraria; MagentaTherapeutics: Honoraria; Da Volterra: Other: has consulted, received honorarium from or participated in advisory boards; Pluto Therapeutics: Current holder of stock options in a privately-held company, Other: has consulted, received honorarium from or participated in advisory boards ; GlaskoSmithKline: Other: has consulted, received honorarium from or participated in advisory boards; Forty-Seven, Inc.: Honoraria; Lygenesis: Other: has consulted, received honorarium from or participated in advisory boards ; Rheos: Honoraria; Pharmacyclics: Other; Kite Pharmaceuticals: Other; Frazier Healthcare Partners: Honoraria; Priothera: Research Funding; Wolters Kluwer: Patents & Royalties; Juno Therapeutics: Other; DKMS (nonprofit): Other; Notch Therapeutics: Honoraria; Nektar Therapeutics: Honoraria; Synthekine (Spouse): Other: has consulted, received honorarium from or participated in advisory boards; Novartis (Spouse): Other: has consulted, received honorarium from or participated in advisory boards; Jazz Pharmaceuticals: Honoraria; Therakos: Honoraria; Amgen: Honoraria. Perales: Nektar Therapeutics: Honoraria, Other; MorphoSys: Honoraria; Miltenyi Biotec: Honoraria, Other; Merck: Honoraria; Medigene: Honoraria; Kite/Gilead: Honoraria, Other; Karyopharm: Honoraria; Incyte: Honoraria, Other; Equilium: Honoraria; Cidara: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; NexImmune: Honoraria; Novartis: Honoraria, Other; Omeros: Honoraria; Sellas Life Sciences: Honoraria; Servier: Honoraria; Takeda: Honoraria. Palomba: Kite Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees.

Summary Immunotherapy has revolutionized cancer treatment, yet most patients do not respond. Here, we investigated mechanisms of response by profiling the proteome of clinical samples from advanced stage melanoma patients undergoing either tumor infiltrating lymphocyte (TIL)-based or anti- programmed death 1 (PD1) immunotherapy. Using high-resolution mass spectrometry, we quantified over 10,300 proteins in total and ∼4,500 proteins across most samples in each dataset. Statistical analyses revealed higher oxidative phosphorylation and lipid metabolism in responders than in non-responders in both treatments. To elucidate the effects of the metabolic state on the immune response, we examined melanoma cells upon metabolic perturbations or CRISPR-Cas9 knockouts. These experiments indicated lipid metabolism as a regulatory mechanism that increases melanoma immunogenicity by elevating antigen presentation, thereby increasing sensitivity to T cell mediated killing both in vitro and in vivo. Altogether, our proteomic analyses revealed association between the melanoma metabolic state and the response to immunotherapy, which can be the basis for future improvement of therapeutic response.