Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma.

Treatment of cancer has been revolutionized by immune checkpoint blockade therapies. Despite the high rate of response in advanced melanoma, the majority of patients succumb to disease. To identify factors associated with success or failure of checkpoint therapy, we profiled transcriptomes of 16,291 individual immune cells from 48 tumor samples of melanoma patients treated with checkpoint inhibitors. Two distinct states of CD8+ T cells were defined by clustering and associated with patient tumor regression or progression. A single transcription factor, TCF7, was visualized within CD8+ T cells in fixed tumor samples and predicted positive clinical outcome in an independent cohort of checkpoint-treated patients. We delineated the epigenetic landscape and clonality of these T cell states and demonstrated enhanced antitumor immunity by targeting novel combinations of factors in exhausted cells. Our study of immune cell transcriptomes from tumors demonstrates a strategy for identifying predictors, mechanisms, and targets for enhancing checkpoint immunotherapy.

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery.

To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRß chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A∗02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

Identification of bacteria-derived HLA-bound peptides in melanoma.

A variety of species of bacteria are known to colonize human tumours1-11, proliferate within them and modulate immune function, which ultimately affects the survival of patients with cancer and their responses to treatment12-14. However, it is not known whether antigens derived from intracellular bacteria are presented by the human leukocyte antigen class I and II (HLA-I and HLA-II, respectively) molecules of tumour cells, or whether such antigens elicit a tumour-infiltrating T cell immune response. Here we used 16S rRNA gene sequencing and HLA peptidomics to identify a peptide repertoire derived from intracellular bacteria that was presented on HLA-I and HLA-II molecules in melanoma tumours. Our analysis of 17 melanoma metastases (derived from 9 patients) revealed 248 and 35 unique HLA-I and HLA-II peptides, respectively, that were derived from 41 species of bacteria. We identified recurrent bacterial peptides in tumours from different patients, as well as in different tumours from the same patient. Our study reveals that peptides derived from intracellular bacteria can be presented by tumour cells and elicit immune reactivity, and thus provides insight into a mechanism by which bacteria influence activation of the immune system and responses to therapy.

B cells and tertiary lymphoid structures promote immunotherapy response.

Treatment with immune checkpoint blockade (ICB) has revolutionized cancer therapy. Until now, predictive biomarkers1-10 and strategies to augment clinical response have largely focused on the T cell compartment. However, other immune subsets may also contribute to anti-tumour immunity11-15, although these have been less well-studied in ICB treatment16. A previously conducted neoadjuvant ICB trial in patients with melanoma showed via targeted expression profiling17 that B cell signatures were enriched in the tumours of patients who respond to treatment versus non-responding patients. To build on this, here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders. Our findings were corroborated using a computational method (MCP-counter18) to estimate the immune and stromal composition in this and two other ICB-treated cohorts (patients with melanoma and renal cell carcinoma). Histological evaluation highlighted the localization of B cells within tertiary lymphoid structures. We assessed the potential functional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal expansion and unique functional states of B cells in responders. Mass cytometry showed that switched memory B cells were enriched in the tumours of responders. Together, these data provide insights into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.

Genomic Landscape of Lynch Syndrome Colorectal Neoplasia Identifies Shared Mutated Neoantigens for Immunoprevention.

BACKGROUND & AIMS: Lynch syndrome (LS) carriers develop mismatch repair-deficient neoplasia with high neoantigen (neoAg) rates. No detailed information on targetable neoAgs from LS precancers exists, which is crucial for vaccine development and immune-interception strategies. We report a focused somatic mutation and frameshift-neoAg landscape of microsatellite loci from colorectal polyps without malignant potential (PWOMP), precancers, and early-stage cancers in LS carriers. METHODS: We generated paired whole-exome and transcriptomic sequencing data from 8 colorectal PWOMP, 41 precancers, 8 advanced precancers, and 12 early-stage cancers of 43 LS carriers. A computational pipeline was developed to predict, rank, and prioritize the top 100 detected mutated neoAgs that were validated in vitro using ELISpot and tetramer assays. RESULTS: Mutation calling revealed >10 mut/Mb in 83% of cancers, 63% of advanced precancers, and 20% of precancers. Cancers displayed an average of 616 MHC-I neoAgs/sample, 294 in advanced precancers, and 107 in precancers. No neoAgs were detected in PWOMP. A total of 65% of our top 100 predicted neoAgs were immunogenic in vitro, and were present in 92% of cancers, 50% of advanced precancers, and 29% of precancers. We observed increased levels of naïve CD8+ and memory CD4+ T cells in mismatch repair-deficient cancers and precancers via transcriptomics analysis. CONCLUSIONS: Shared frameshift-neoAgs are generated within unstable microsatellite loci at initial stages of LS carcinogenesis and can induce T-cell responses, generating opportunities for vaccine development, targeting LS precancers and early-stage cancers.

Netie: inferring the evolution of neoantigen-T cell interactions in tumors.

Neoantigens are the key targets of antitumor immune responses from cytotoxic T cells and play a critical role in affecting tumor progressions and immunotherapy treatment responses. However, little is known about how the interaction between neoantigens and T cells ultimately affects the evolution of cancerous masses. Here, we develop a hierarchical Bayesian model, named neoantigen-T cell interaction estimation (netie) to infer the history of neoantigen-CD8+ T cell interactions in tumors. Netie was systematically validated and applied to examine the molecular patterns of 3,219 tumors, compiled from a panel of 18 cancer types. We showed that tumors with an increase in immune selection pressure over time are associated with T cells that have an activation-related expression signature. We also identified a subset of exhausted cytotoxic T cells postimmunotherapy associated with tumor clones that newly arise after treatment. These analyses demonstrate how netie enables the interrogation of the relationship between individual neoantigen repertoires and the tumor molecular profiles. We found that a T cell inflammation gene expression profile (TIGEP) is more predictive of patient outcomes in the tumors with an increase in immune pressure over time, which reveals a curious synergy between T cells and neoantigen distributions. Overall, we provide a new tool that is capable of revealing the imprints left by neoantigens during each tumor's developmental process and of predicting how tumors will progress under further pressure of the host's immune system.

A novel statistical method for decontaminating T-cell receptor sequencing data.

The T-cell receptor (TCR) repertoire is highly diverse among the population and plays an essential role in initiating multiple immune processes. TCR sequencing (TCR-seq) has been developed to profile the T cell repertoire. Similar to other high-throughput experiments, contamination can happen during several steps of TCR-seq, including sample collection, preparation and sequencing. Such contamination creates artifacts in the data, leading to inaccurate or even biased results. Most existing methods assume 'clean' TCR-seq data as the starting point with no ability to handle data contamination. Here, we develop a novel statistical model to systematically detect and remove contamination in TCR-seq data. We summarize the observed contamination into two sources, pairwise and cross-cohort. For both sources, we provide visualizations and summary statistics to help users assess the severity of the contamination. Incorporating prior information from 14 existing TCR-seq datasets with minimum contamination, we develop a straightforward Bayesian model to statistically identify contaminated samples. We further provide strategies for removing the impacted sequences to allow for downstream analysis, thus avoiding any need to repeat experiments. Our proposed model shows robustness in contamination detection compared with a few off-the-shelf detection methods in simulation studies. We illustrate the use of our proposed method on two TCR-seq datasets generated locally.

Analysis of Immune Intratumor Heterogeneity Highlights Immunoregulatory and Coinhibitory Lymphocytes as Hallmarks of Recurrence in Stage I Non-Small Cell Lung Cancer.

Our understanding of the molecular mechanisms underlying postsurgical recurrence of non-small cell lung cancer (NSCLC) is rudimentary. Molecular and T cell repertoire intratumor heterogeneity (ITH) have been reported to be associated with postsurgical relapse; however, how ITH at the cellular level impacts survival is largely unknown. Here we report the analysis of 2880 multispectral images representing 14.2% to 27% of tumor areas from 33 patients with stage I NSCLC, including 17 cases (relapsed within 3 years after surgery) and 16 controls (without recurrence ≥5 years after surgery) using multiplex immunofluorescence. Spatial analysis was conducted to quantify the minimum distance between different cell types and immune cell infiltration around malignant cells. Immune ITH was defined as the variance of immune cells from 3 intratumor regions. We found that tumors from patients having relapsed display different immune biology compared with nonrecurrent tumors, with a higher percentage of tumor cells and macrophages expressing PD-L1 (P =.031 and P =.024, respectively), along with an increase in regulatory T cells (Treg) (P =.018), antigen-experienced T cells (P =.025), and effector-memory T cells (P =.041). Spatial analysis revealed that a higher level of infiltration of PD-L1+ macrophages (CD68+PD-L1+) or antigen-experienced cytotoxic T cells (CD3+CD8+PD-1+) in the tumor was associated with poor overall survival (P =.021 and P =.006, respectively). A higher degree of Treg ITH was associated with inferior recurrence-free survival regardless of tumor mutational burden (P =.022), neoantigen burden (P =.021), genomic ITH (P =.012) and T cell repertoire ITH (P =.001). Using multiregion multiplex immunofluorescence, we characterized ITH at the immune cell level along with whole exome and T cell repertoire sequencing from the same tumor regions. This approach highlights the role of immunoregulatory and coinhibitory signals as well as their spatial distribution and ITH that define the hallmarks of tumor relapse of stage I NSCLC.

Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer.

The successful development and implementation of precision immuno-oncology therapies requires a deeper understanding of the immune architecture at a patient level. T-cell receptor (TCR) repertoire sequencing is a relatively new technology that enables monitoring of T-cells, a subset of immune cells that play a central role in modulating immune response. These immunologic relationships are complex and are governed by various distributional aspects of an individual patient's tumor profile. We propose Bayesian QUANTIle regression for hierarchical COvariates (QUANTICO) that allows simultaneous modeling of hierarchical relationships between multilevel covariates, conducts explicit variable selection, estimates quantile and patient-specific coefficient effects, to induce individualized inference. We show QUANTICO outperforms existing approaches in multiple simulation scenarios. We demonstrate the utility of QUANTICO to investigate the effect of TCR variables on immune response in a cohort of lung cancer patients. At population level, our analyses reveal the mechanistic role of T-cell proportion on the immune cell abundance, with tumor mutation burden as an important factor modulating this relationship. At a patient level, we find several outlier patients based on their quantile-specific coefficient functions, who have higher mutational rates and different smoking history.

Multiomics Analysis Reveals Distinct Immunogenomic Features of Lung Cancer with Ground-Glass Opacity.

Rationale: Ground-glass opacity (GGO)-associated lung cancers are common and radiologically distinct clinical entities known to have an indolent clinical course and superior survival, implying a unique underlying biology. However, the molecular and immune characteristics of GGO-associated lung nodules have not been systemically studied. Objectives: To provide mechanistic insights for the treatment of these radiologically distinct clinical entities. Methods: We initiated a prospective cohort study to collect and characterize pulmonary nodules with GGO components (nonsolid and part-solid nodules) or without GGO components, as precisely quantified by using three-dimensional image reconstruction to delineate the molecular and immune features associated with GGO. Multiomics assessment conducted by using targeted gene panel sequencing, RNA sequencing, TCR (T-cell receptor) sequencing, and circulating tumor DNA detection was performed. Measurements and Main Results: GGO-associated lung cancers exhibited a lower tumor mutation burden than solid nodules. Transcriptomic analysis revealed a less active immune environment in GGO components and immune pathways, decreased expression of immune activation markers, and less infiltration of most immune-cell subsets, which was confirmed by using multiplex immunofluorescence. Furthermore, T-cell repertoire sequencing revealed lower T-cell expansion in GGO-associated lung cancers. HLA loss of heterozygosity was significantly less common in lung adenocarcinomas with GGO components than in those without. Circulating tumor DNA analysis suggested that the release of tumor DNA to the peripheral blood was correlated with the tumor size of non-GGO components. Conclusions: Compared with lung cancers presenting with solid lung nodules, GGO-associated lung cancers are characterized by a less active metabolism and a less active immune microenvironment, which may be the mechanisms underlying their indolent clinical course. Clinical trial registered with www.clinicaltrials.gov (NCT03320044).

Augmented Lipocalin-2 Is Associated with Chronic Obstructive Pulmonary Disease and Counteracts Lung Adenocarcinoma Development.

Rationale: Early pathogenesis of lung adenocarcinoma (LUAD) remains largely unknown. We found that, relative to wild-type littermates, the innate immunomodulator Lcn2 (lipocalin-2) was increased in normal airways from mice with knockout of the airway lineage gene Gprc5a (Gprc5a-/-) and that are prone to developing inflammation and LUAD. Yet, the role of LCN2 in lung inflammation and LUAD is poorly understood.Objectives: Delineate the role of Lcn2 induction in LUAD pathogenesis.Methods: Normal airway brushings, uninvolved lung tissues, and tumors from Gprc5a-/- mice before and after tobacco carcinogen exposure were analyzed by RNA sequencing. LCN2 mRNA was analyzed in public and in-house data sets of LUAD, lung squamous cancer (LUSC), chronic obstructive pulmonary disease (COPD), and LUAD/LUSC with COPD. LCN2 protein was immunohistochemically analyzed in a tissue microarray of 510 tumors. Temporal lung tumor development, gene expression programs, and host immune responses were compared between Gprc5a-/- and Gprc5a-/-/Lcn2-/- littermates.Measurements and Main Results:Lcn2 was progressively elevated during LUAD development and positively correlated with proinflammatory cytokines and inflammation gene sets. LCN2 was distinctively elevated in human LUADs, but not in LUSCs, relative to normal lungs and was associated with COPD among smokers and patients with LUAD. Relative to Gprc5a-/- mice, Gprc5a-/-/Lcn2-/- littermates exhibited significantly increased lung tumor development concomitant with reduced T-cell abundance (CD4+) and richness, attenuated antitumor immune gene programs, and increased immune cell expression of protumor inflammatory cytokines.Conclusions: Augmented LCN2 expression is a molecular feature of COPD-associated LUAD and counteracts LUAD development in vivo by maintaining antitumor immunity.

Combination anti-CTLA-4 plus anti-PD-1 checkpoint blockade utilizes cellular mechanisms partially distinct from monotherapies.

Immune checkpoint blockade therapy targets T cell-negative costimulatory molecules such as cytotoxic T lymphocyte antigen-4 (CTLA-4) and programmed cell death-1 (PD-1). Combination anti-CTLA-4 and anti-PD-1 blockade therapy has enhanced efficacy, but it remains unclear through what mechanisms such effects are mediated. A critical question is whether combination therapy targets and modulates the same T cell populations as monotherapies. Using a mass cytometry-based systems approach, we comprehensively profiled the response of T cell populations to monotherapy and combination anti-CTLA-4 plus anti-PD-1 therapy in syngeneic murine tumors and clinical samples. Most effects of monotherapies were additive in the context of combination therapy; however, multiple combination therapy-specific effects were observed. Highly phenotypically exhausted cluster of differentiation 8 (CD8) T cells expand in frequency following anti-PD-1 monotherapy but not combination therapy, while activated terminally differentiated effector CD8 T cells expand only following combination therapy. Combination therapy also led to further increased frequency of T helper type 1 (Th1)-like CD4 effector T cells even though anti-PD-1 monotherapy is not sufficient to do so. Mass cytometry analyses of peripheral blood from melanoma patients treated with immune checkpoint blockade therapies similarly revealed mostly additive effects on the frequencies of T cell subsets along with unique modulation of terminally differentiated effector CD8 T cells by combination ipilimumab plus nivolumab therapy. Together, these findings indicate that dual blockade of CTLA-4 and PD-1 therapy is sufficient to induce unique cellular responses compared with either monotherapy.

18F-fluorodeoxyglucose positron emission tomography correlates with tumor immunometabolic phenotypes in resected lung cancer.

Enhanced tumor glycolytic activity is a mechanism by which tumors induce an immunosuppressive environment to resist adoptive T cell therapy; therefore, methods of assessing intratumoral glycolytic activity are of considerable clinical interest. In this study, we characterized the relationships among tumor 18F-fluorodeoxyglucose (FDG) retention, tumor metabolic and immune phenotypes, and survival in patients with resected non-small cell lung cancer (NSCLC). We retrospectively analyzed tumor preoperative positron emission tomography (PET) 18F-FDG uptake in 59 resected NSCLCs and investigated correlations between PET parameters (SUVMax, SUVTotal, SUVMean, TLG), tumor expression of glycolysis- and immune-related genes, and tumor-associated immune cell densities that were quantified by immunohistochemistry. Tumor glycolysis-associated immune gene signatures were analyzed for associations with survival outcomes. We found that each 18F-FDG PET parameter was positively correlated with tumor expression of glycolysis-related genes. Elevated 18F-FDG SUVMax was more discriminatory of glycolysis-associated changes in tumor immune phenotypes than other 18F-FDG PET parameters. Increased SUVMax was associated with multiple immune factors characteristic of an immunosuppressive and poorly immune infiltrated tumor microenvironment, including elevated PD-L1 expression, reduced CD57+ cell density, and increased T cell exhaustion gene signature. Elevated SUVMax identified immune-related transcriptomic signatures that were associated with enhanced tumor glycolytic gene expression and poor clinical outcomes. Our results suggest that 18F-FDG SUVMax has potential value as a noninvasive, clinical indicator of tumor immunometabolic phenotypes in patients with resectable NSCLC and warrants investigation as a potential predictor of therapeutic response to immune-based treatment strategies.

Gene expression profiling of lichenoid dermatitis immune-related adverse event from immune checkpoint inhibitors reveals increased CD14+ and CD16+ monocytes driving an innate immune response.

BACKGROUND: Cancer patients receiving antibodies abrogating immune checkpoint pathways may develop a diverse array of immune-related adverse events (irAEs), of which lichenoid dermatitis (LD) is the most common. The mechanism driving the emergence of these irAEs remain understudied, underscoring a critical need to determine the unique gene expression profiles and immune composition in LD-irAE. METHODS: LD-irAE (n = 3) and benign lichenoid keratosis (BLK) control (n = 3) were profiled with NanoString nCounter PanCancer Immune Profiling Panel interrogating the mRNA levels of 770 genes. Immunohistochemical (IHC) studies (n = 14 samples) for CD14, CD16, T-Bet, Gata-3, and FoxP3 were further evaluated using Aperio digital image analysis. RESULTS: The LD-irAE showed downregulation of 93 mRNA transcripts (P < 0.05) and upregulation of 74 mRNA transcripts (P < 0.04) including toll-like receptor (TLR) 2 and TLR4 (P < 0.05). CD14+ and CD16+ monocytes quantified by IHC (H-score) were higher in LD-irAE than in the BLK control (P < 0.05). The immune composition of LD-irAE exhibited higher numbers of T-Bet+ (Th1) cells compared with Gata-3+ (Th2) cells (P = 0.016) and lower numbers of FoxP3 (T regulatory) cells (P = 0.008). CONCLUSIONS: LD-irAE exhibited activation of CD14/TLR innate immune response with increased CD14+ and CD16+ monocytes compared with BLK control. CD14/TLR signaling may drive the development of LD-irAE.

Neoadjuvant plus adjuvant dabrafenib and trametinib versus standard of care in patients with high-risk, surgically resectable melanoma: a single-centre, open-label, randomised, phase 2 trial.

BACKGROUND: Dual BRAF and MEK inhibition produces a response in a large number of patients with stage IV BRAF-mutant melanoma. The existing standard of care for patients with clinical stage III melanoma is upfront surgery and consideration for adjuvant therapy, which is insufficient to cure most patients. Neoadjuvant targeted therapy with BRAF and MEK inhibitors (such as dabrafenib and trametinib) might provide clinical benefit in this high-risk p opulation. METHODS: We undertook this single-centre, open-label, randomised phase 2 trial at the University of Texas MD Anderson Cancer Center (Houston, TX, USA). Eligible participants were adult patients (aged ≥18 years) with histologically or cytologically confirmed surgically resectable clinical stage III or oligometastatic stage IV BRAFV600E or BRAFV600K (ie, Val600Glu or Val600Lys)-mutated melanoma. Eligible patients had to have an Eastern Cooperative Oncology Group performance status of 0 or 1, a life expectancy of more than 3 years, and no previous exposure to BRAF or MEK inhibitors. Exclusion criteria included metastases to bone, brain, or other sites where complete surgical excision was in doubt. We randomly assigned patients (1:2) to either upfront surgery and consideration for adjuvant therapy (standard of care group) or neoadjuvant plus adjuvant dabrafenib and trametinib (8 weeks of neoadjuvant oral dabrafenib 150 mg twice per day and oral trametinib 2 mg per day followed by surgery, then up to 44 weeks of adjuvant dabrafenib plus trametinib starting 1 week after surgery for a total of 52 weeks of treatment). Randomisation was not masked and was implemented by the clinical trial conduct website maintained by the trial centre. Patients were stratified by disease stage. The primary endpoint was investigator-assessed event-free survival (ie, patients who were alive without disease progression) at 12 months in the intent-to-treat population. This trial is registered at ClinicalTrials.gov, number NCT02231775. FINDINGS: Between Oct 23, 2014, and April 13, 2016, we randomly assigned seven patients to standard of care, and 14 to neoadjuvant plus adjuvant dabrafenib and trametinib. The trial was stopped early after a prespecified interim safety analysis that occurred after a quarter of the participants had been accrued revealed significantly longer event-free survival with neoadjuvant plus adjuvant dabrafenib and trametinib than with standard of care. After a median follow-up of 18·6 months (IQR 14·6-23·1), significantly more patients receiving neoadjuvant plus adjuvant dabrafenib and trametinib were alive without disease progression than those receiving standard of care (ten [71%] of 14 patients vs none of seven in the standard of care group; median event-free survival was 19·7 months [16·2-not estimable] vs 2·9 months [95% CI 1·7-not estimable]; hazard ratio 0·016, 95% CI 0·00012-0·14, p<0·0001). Neoadjuvant plus adjuvant dabrafenib and trametinib were well tolerated with no occurrence of grade 4 adverse events or treatment-related deaths. The most common adverse events in the neoadjuvant plus adjuvant dabrafenib and trametinib group were expected grade 1-2 toxicities including chills (12 patients [92%]), headache (12 [92%]), and pyrexia (ten [77%]). The most common grade 3 adverse event was diarrhoea (two patients [15%]). INTERPRETATION: Neoadjuvant plus adjuvant dabrafenib and trametinib significantly improved event-free survival versus standard of care in patients with high-risk, surgically resectable, clinical stage III-IV melanoma. Although the trial finished early, limiting generalisability of the results, the findings provide proof-of-concept and support the rationale for further investigation of neoadjuvant approaches in this disease. This trial is currently continuing accrual as a single-arm study of neoadjuvant plus adjuvant dabrafenib and trametinib. FUNDING: Novartis Pharmaceuticals Corporation.

Interaction of molecular alterations with immune response in melanoma.

Major advances have been made in melanoma treatment with the use of molecularly targeted therapies and immunotherapies, and numerous regimens are now approved by the US Food and Drug Administration for patients with stage IV disease. However, therapeutic resistance remains an issue to both classes of agents, and reliable biomarkers of therapeutic response and resistance are lacking. Mechanistic insights are being gained through preclinical studies and translational research, offering potential strategies to enhance responses and survival in treated patients. A comprehensive understanding of the immune effects of common mutations at play in melanoma is critical, as is an appreciation of the molecular mechanisms contributing to therapeutic resistance to immunotherapy. These mechanisms and the interplay between them are discussed herein. Cancer 2017;123:2130-42. © 2017 American Cancer Society.

Influences of BRAF Inhibitors on the Immune Microenvironment and the Rationale for Combined Molecular and Immune Targeted Therapy.

The identification of key driver mutations in melanoma has led to the development of targeted therapies aimed at BRAF and MEK, but responses are often limited in duration. There is growing evidence that MAPK pathway activation impairs antitumor immunity and that targeting this pathway may enhance responses to immunotherapies. There is also evidence that immune mechanisms of resistance to targeted therapy exist, providing the rationale for combining targeted therapy with immunotherapy. Preclinical studies have demonstrated synergy in combining these strategies, and combination clinical trials are ongoing. It is, however, becoming clear that additional translational studies are needed to better understand toxicity, proper timing, and sequence of therapy, as well as the utility of multidrug regimens and effects of other targeted agents on antitumor immunity. Insights gained through translational research in preclinical models and clinical studies will provide mechanistic insight into therapeutic response and resistance and help devise rational strategies to enhance therapeutic responses.

The WT hemochromatosis protein HFE inhibits CD8⁺ T-lymphocyte activation.

MHC class I (MHC I) antigen presentation is a ubiquitous process by which cells present endogenous proteins to CD8(+) T lymphocytes during immune surveillance and response. Hereditary hemochromatosis protein, HFE, is involved in cellular iron uptake but, while structurally homologous to MHC I, is unable to bind peptides. However, increasing evidence suggests a role for HFE in the immune system. Here, we investigated the impact of HFE on CD8(+) T-lymphocyte activation. Using transient HFE transfection assays in a model of APCs, we show that WT HFE (HFEWT ), but not C282Y-mutated HFE, inhibits secretion of MIP-1ß from antigen-specific CD8(+) T lymphocytes. HFEWT expression also resulted in major decreases in CD8(+) T-lymphocyte activation as measured by 4-1BB expression. We further demonstrate that inhibition of CD8(+) T-lymphocyte activation was independent of MHC I surface levels, ß2-m competition, HFE interaction with transferrin receptor, antigen origin, or epitope affinity. Finally, we identified the α1-2 domains of HFEWT as being responsible for inhibiting CD8(+) T-lymphocyte activation. Our data imply a new role for HFEWT in altering CD8(+) T-lymphocyte reactivity, which could modulate antigen immunogenicity.

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy.

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.