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Tuberculosis is a public health problem in Mexico. From 1999 to 2002, we assessed retrospectively the epidemiological, clinical, and treatment characteristics of pulmonary tuberculosis in the hospitals of the Mexican Institute of Public Health in the state of Colima (Mexico). We included 184 cases diagnosed with pulmonary tuberculosis. A database containing demographic, epidemiological, and clinical information was constructed and analyzed. We estimate a median patient delay of 83 d and a mean treatment delay of 2.3 d. Of 14 cases suspected for multiresistance and microbiologically assayed, 5 were found to carry a multi-drug-resistant strain. We also found a significant association between a short patient delay and the presence of hemoptysis ( p = 0.002) or dyspnea ( p<0.001). 86 patients (46.8%) were sputum smear microscopy negative at the end of treatment and 40 (21.7%) completed treatment giving an overall success rate of 68.5%, which compares unfavorably with the World Health Organization target success rate of 85%. Five (2.7%) patients failed treatment, 10 (5.4%) died, 39 (21.2%) interrupted treatment, and 4 (2.2%) transferred to another reporting unit. A 2002 strategic change in drug distribution seemed to prove successful. [ABSTRACT FROM AUTHOR]

As SARS-CoV-2 variants continue to emerge capable of evading neutralizing antibodies, it has become increasingly important to fully understand the breadth and functional profile of T cell responses to determine their impact on the immune surveillance of variant strains. Here, sampling healthy individuals, we profiled the kinetics and polyfunctionality of T cell immunity elicited by mRNA vaccination. Modeling of anti-spike T cell responses against ancestral and variant strains of SARS-CoV-2 suggested that epitope immunodominance and cross-reactivity are major predictive determinants of T cell immunity. To identify immunodominant epitopes across the viral proteome, we generated a comprehensive map of CD4+ and CD8+ T cell epitopes within non-spike proteins that induced polyfunctional T cell responses in convalescent patients. We found that immunodominant epitopes mainly resided within regions that were minimally disrupted by mutations in emerging variants. Conservation analysis across historical human coronaviruses combined with in silico alanine scanning mutagenesis of non-spike proteins underscored the functional importance of mutationally-constrained immunodominant regions. Collectively, these findings identify immunodominant T cell epitopes across the mutationally-constrained SARS-CoV-2 proteome, potentially providing immune surveillance against emerging variants, and inform the design of next-generation vaccines targeting antigens throughout SARS-CoV-2 proteome for broader and more durable protection.

Neoantigen immunoediting drives immune checkpoint blockade efficacy, yet the molecular features of neoantigens and how neoantigen immunogenicity shapes treatment response remain poorly understood. To address these questions, 80 patients with non-small cell lung cancer were enrolled in the biomarker cohort of CheckMate 153 (CA209-153), which collected radiographic guided biopsy samples before treatment and during treatment with nivolumab. Early loss of mutations and neoantigens during therapy are both associated with clinical benefit. We examined 1,453 candidate neoantigens, including many of which that had reduced cancer cell fraction after treatment with nivolumab, and identified 196 neopeptides that were recognized by T cells. Mapping these neoantigens to clonal dynamics, evolutionary trajectories and clinical response revealed a strong selection against immunogenic neoantigen-harboring clones. We identified position-specific amino acid and physiochemical features related to immunogenicity and developed an immunogenicity score. Nivolumab-induced microenvironmental evolution in non-small cell lung cancer shared some similarities with melanoma, yet critical differences were apparent. This study provides unprecedented molecular portraits of neoantigen landscapes underlying nivolumab's mechanism of action., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification. As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/ ., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Experts discuss the challenges and opportunities of using artificial intelligence (AI) to study the evolution of cancer cells and their microenvironment, improve diagnosis, predict treatment response, and ensure responsible implementation in the clinic., Competing Interests: Declaration of interests M.G. received research funding from the NSF, Google, Quanta Computing, Janssen, Moore Foundation, Volkswagen Foundation, and Takeda. These funds have been paid to MIT, and not to M.G. personally. The affiliations of M.G. are: MIT in EECS & IMES; LIDS; CSAIL & JClinic Faculty Member; and CIFAR Azrieli Global Scholar at Vector Institute. D.C. is a co-inventor on a patent (US11230599/EP4226944A3) filed by MSKCC on using tumor mutational burden to predict immunotherapy response, which has been licensed to Personal Genome Diagnostics (PGDx). J.T. is a shareholder and co-founder of Ellogon.AI. J.T. is a collaborator of Kaiko.ai, obtaining research funding. F.M. is the co-founder of ModellaAI. Patents around generative AI for medicine and corresponding work conducted in the lab of F.M. have been licensed to ModellaAI. J.N.K. declares consulting services for Owkin, France; DoMore Diagnostics, Norway; Panakeia, UK; Scailyte, Switzerland; Mindpeak, Germany; and MultiplexDx, Slovakia. Furthermore, J.N.K. holds shares in StratifAI GmbH, Germany, has received a research grant by GSK, and has received honoraria by AstraZeneca, Bayer, Eisai, Janssen, MSD, BMS, Roche, Pfizer, and Fresenius. The other authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Predictive modeling of macromolecular recognition and protein-protein complementarity represents one of the cornerstones of biophysical sciences. However, such models are often hindered by the combinatorial complexity of interactions at the molecular interfaces. Exemplary of this problem is peptide presentation by the highly polymorphic major histocompatibility complex class I (MHC-I) molecule, a principal component of immune recognition. We developed human leukocyte antigen (HLA)-Inception, a deep biophysical convolutional neural network, which integrates molecular electrostatics to capture non-bonded interactions for predicting peptide binding motifs across 5,821 MHC-I alleles. These predictions of generated motifs correlate strongly with experimental peptide binding and presentation data. Beyond molecular interactions, the study demonstrates the application of predicted motifs in analyzing MHC-I allele associations with HIV disease progression and patient response to immune checkpoint inhibitors. A record of this paper's transparent peer review process is included in the supplemental information., Competing Interests: Declaration of interests E.W., A.S., J.K.C., and K.S.A. have submitted a patent application concerning the prediction methods outlined in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA) -II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA -II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA -II+ epithelial cells. In lung cancer, widespread loss of HLA -II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

Head and neck squamous-cell carcinoma (HNSCC) is a disease with a generally poor prognosis; half of treated patients eventually develop recurrent and/or metastatic (R/M) disease. Patients with R/M HNSCC generally have incurable disease with a median survival of 10 to 15 months. Although immune-checkpoint blockade (ICB) has improved outcomes in patients with R/M HNSCC, identifying patients who are likely to benefit from ICB remains a challenge. Biomarkers in current clinical use include tumor mutational burden and immunohistochemistry for programmed death-ligand 1, both of which have only modest predictive power. Machine learning (ML) has the potential to aid in clinical decision-making as an approach to estimate a tumor's likelihood of response or a patient's likelihood of experiencing clinical benefit from therapies such as ICB. Previously, we described a random forest ML model that had value in predicting ICB response using 11 or 16 clinical, laboratory, and genomic features in a pan-cancer development cohort. However, its applicability to certain cancer types, such as HNSCC, has been unknown, due to a lack of cancer-type-specific validation. Here, we present the first validation of a random forest ML tool to predict the likelihood of ICB response in patients with R/M HNSCC. The tool had adequate predictive power for tumor response (area under the receiver operating characteristic curve = 0.65) and was able to stratify patients by overall (HR = 0.53 [95% CI 0.29-0.99], p = 0.045) and progression-free (HR = 0.49 [95% CI 0.27-0.87], p = 0.016) survival. The overall accuracy was 0.72. Our study validates an ML predictor in HNSCC, demonstrating promising performance in a novel cohort of patients. Further studies are needed to validate the generalizability of this algorithm in larger patient samples from additional multi-institutional contexts.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design., (© The Author(s) 2024. Published by Oxford University Press.)

BACKGROUNDRecurrent and/or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) is generally an incurable disease, with patients experiencing median survival of under 10 months and significant morbidity. While immune checkpoint blockade (ICB) drugs are effective in approximately 20% of patients, the remaining experience limited clinical benefit and are exposed to potential adverse effects and financial costs. Clinically approved biomarkers, such as tumor mutational burden (TMB), have a modest predictive value in HNSCC.METHODSWe analyzed clinical and genomic features, generated using whole-exome sequencing, in 133 ICB-treated patients with R/M HNSCC, of whom 69 had virus-associated and 64 had non-virus-associated tumors.RESULTSHierarchical clustering of genomic data revealed 6 molecular subtypes characterized by a wide range of objective response rates and survival after ICB therapy. The prognostic importance of these 6 subtypes was validated in an external cohort. A random forest-based predictive model, using several clinical and genomic features, predicted progression-free survival (PFS), overall survival (OS), and response with greater accuracy than did a model based on TMB alone. Recursive partitioning analysis identified 3 features (systemic inflammatory response index, TMB, and smoking signature) that classified patients into risk groups with accurate discrimination of PFS and OS.CONCLUSIONThese findings shed light on the immunogenomic characteristics of HNSCC tumors that drive differential responses to ICB and identify a clinical-genomic classifier that outperformed the current clinically approved biomarker of TMB. This validated predictive tool may help with clinical risk stratification in patients with R/M HNSCC for whom ICB is being considered.FUNDINGFundación Alfonso Martín Escudero, NIH R01 DE027738, US Department of Defense CA210784, The Geoffrey Beene Cancer Research Center, The MSKCC Population Science Research Program, the Jayme Flowers Fund, the Sebastian Nativo Fund, and the NIH/NCI Cancer Center Support Grant P30 CA008748.

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment., (© 2023. The Author(s).)

It is poorly understood how the tumor immune microenvironment influences disease recurrence in localized clear-cell renal cell carcinoma (ccRCC). Here we performed whole-transcriptomic profiling of 236 tumors from patients assigned to the placebo-only arm of a randomized, adjuvant clinical trial for high-risk localized ccRCC. Unbiased pathway analysis identified myeloid-derived IL6 as a key mediator. Furthermore, a novel myeloid gene signature strongly correlated with disease recurrence and overall survival on uni- and multivariate analyses and is linked to TP53 inactivation across multiple data sets. Strikingly, effector T-cell gene signatures, infiltration patterns, and exhaustion markers were not associated with disease recurrence. Targeting immunosuppressive myeloid inflammation with an adenosine A2A receptor antagonist in a novel, immunocompetent, Tp53-inactivated mouse model significantly reduced metastatic development. Our findings suggest that myeloid inflammation promotes disease recurrence in ccRCC and is targetable as well as provide a potential biomarker-based framework for the design of future immuno-oncology trials in ccRCC., Significance: Improved understanding of factors that influence metastatic development in localized ccRCC is greatly needed to aid accurate prediction of disease recurrence, clinical decision-making, and future adjuvant clinical trial design. Our analysis implicates intratumoral myeloid inflammation as a key driver of metastasis in patients and a novel immunocompetent mouse model. This article is highlighted in the In This Issue feature, p. 2221., (©2022 American Association for Cancer Research.)

Programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1)-blockade immunotherapies have limited efficacy in the treatment of bladder cancer. Here, we show that NKG2A associates with improved survival and responsiveness to PD-L1 blockade immunotherapy in bladder tumors that have high abundance of CD8 + T cells. In bladder tumors, NKG2A is acquired on CD8 + T cells later than PD-1 as well as other well-established immune checkpoints. NKG2A + PD-1 + CD8 + T cells diverge from classically defined exhausted T cells through their ability to react to human leukocyte antigen (HLA) class I-deficient tumors using T cell receptor (TCR)-independent innate-like mechanisms. HLA-ABC expression by bladder tumors is progressively diminished as disease progresses, framing the importance of targeting TCR-independent anti-tumor functions. Notably, NKG2A + CD8 + T cells are inhibited when HLA-E is expressed by tumors and partly restored upon NKG2A blockade in an HLA-E-dependent manner. Overall, our study provides a framework for subsequent clinical trials combining NKG2A blockade with other T cell-targeted immunotherapies, where tumors express higher levels of HLA-E., Competing Interests: Declaration of interests L.W., R.P.S., and J.Z. are employees of Sema4. A.H. receives research funds from Zumutor Biologics and is on the advisory boards of HTG Molecular Diagnostics, Immunorizon, UroGen, and Takeda. N.B. is an extramural member of the Parker Institute for Cancer Immunotherapy; receives research funds from Regeneron, Harbor Biomedical, DC Prime, and Dragonfly Therapeutics; and is on the advisory boards of Neon Therapeutics, Novartis, Avidea, Boehringer Ingelheim, Rome Therapeutics, Rubius Therapeutics, Roswell Park Comprehensive Cancer Center, BreakBio, Carisma Therapeutics, CureVac, Genotwin, BioNTech, Gilead Therapeutics, Tempest Therapeutics, and the Cancer Research Institute. A patent related to this work was filed to the United States Patent and Trademark Office (63/313,823)., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Defects in pathways governing genomic fidelity have been linked to improved response to immune checkpoint blockade therapy (ICB). Pathogenic POLE/POLD1 mutations can cause hypermutation, yet how diverse mutations in POLE/POLD1 influence antitumor immunity following ICB is unclear. Here, we comprehensively determined the effect of POLE/POLD1 mutations in ICB and elucidated the mechanistic impact of these mutations on tumor immunity. Murine syngeneic tumors harboring Pole/Pold1 functional mutations displayed enhanced antitumor immunity and were sensitive to ICB. Patients with POLE/POLD1 mutated tumors harboring telltale mutational signatures respond better to ICB than patients harboring wild-type or signature-negative tumors. A mutant POLE/D1 function-associated signature-based model outperformed several traditional approaches for identifying POLE/POLD1 mutated patients that benefit from ICB. Strikingly, the spectrum of mutational signatures correlates with the biochemical features of neoantigens. Alterations that cause POLE/POLD1 function-associated signatures generate T cell receptor (TCR)-contact residues with increased hydrophobicity, potentially facilitating T cell recognition. Altogether, the functional landscapes of POLE/POLD1 mutations shape immunotherapy efficacy., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The effects of cytokine and protein stabilizing carriers, such as serum albumin, on tumor response to immune checkpoint blockade (ICB) is not well understood. By examining 1714 patients across 16 cancer types, we found that high pretreatment serum albumin level predicts favorable tumor radiographic response following ICB treatment in a dose-dependent fashion. Serum albumin is a candidate biomarker that can be combined with tumor mutational burden (TMB) for additional predictive capacity, and the tumor response rate to ICB was ~49% in the albumin-high/TMB-high group., (© 2022. The Author(s).)

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose 1 . Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Immune checkpoint blockade (ICB) therapy has substantially improved the outcomes of patients with many types of cancers, including renal cell carcinoma (RCC). Initially studied as monotherapy, immunotherapy-based combination regimens have improved the clinical benefit achieved by ICB monotherapy and have revolutionized RCC treatment. While biomarkers like PD-L1 and tumor mutational burden (TMB) are FDA approved as biomarkers for ICB monotherapy, there are no known biomarkers for combination immunotherapies. Here, we describe the clinical outcomes and genomic determinants of response from a phase Ib/II clinical trial on patients with advanced RCC evaluating the efficacy of lenvatinib, a multi-kinase inhibitor mainly targeting VEGFR and FGFR plus pembrolizumab, an anti-PD1 immunotherapy. Concurrent treatment with lenvatinib and pembrolizumab resulted in an objective response rate of 79% (19/24) and tumor shrinkage in 96% (23/24) of patients. While tumor mutational burden (TMB) did not predict for clinical benefit, germline HLA-I diversity strongly impacted treatment efficacy. Specifically, HLA-I evolutionary divergence (HED), which measures the breadth of a patient's immunopeptidome, was associated with both improved clinical benefit and durability of response. Our results identify lenvatinib plus pembrolizumab as a highly active treatment strategy in RCC and reveal HLA-I diversity as a critical determinant of efficacy for this combination. HED also predicted better survival in a separate cohort of patients with RCC following therapy with anti-PD-1-based combination therapy. IMPLICATIONS: These findings have substantial implications for RCC therapy and for understanding immunogenetic mechanisms of efficacy and warrants further investigation., (©2021 American Association for Cancer Research.)

Although mutations in DNA are the best-studied source of neoantigens that determine response to immune checkpoint blockade, alterations in RNA splicing within cancer cells could similarly result in neoepitope production. However, the endogenous antigenicity and clinical potential of such splicing-derived epitopes have not been tested. Here, we demonstrate that pharmacologic modulation of splicing via specific drug classes generates bona fide neoantigens and elicits anti-tumor immunity, augmenting checkpoint immunotherapy. Splicing modulation inhibited tumor growth and enhanced checkpoint blockade in a manner dependent on host T cells and peptides presented on tumor MHC class I. Splicing modulation induced stereotyped splicing changes across tumor types, altering the MHC I-bound immunopeptidome to yield splicing-derived neoepitopes that trigger an anti-tumor T cell response in vivo. These data definitively identify splicing modulation as an untapped source of immunogenic peptides and provide a means to enhance response to checkpoint blockade that is readily translatable to the clinic., Competing Interests: Declaration of interests O.A.-W. has served as a consultant for H3B Biomedicine, Foundation Medicine, Merck, Prelude Therapeutics, and Janssen, and is on the scientific advisory board of Envisagenics, Pfizer Boulder, and AIChemy. O.A.-W. has received prior research funding from Loxo Oncology and H3 Biomedicine unrelated to this work. S.X.L. has served as a consultant (uncompensated) for PTC Therapeutics. B.R. has served as a consultant for Bayer and Roche. D.Z. reports clinical research support to his institution from Astra Zeneca, Plexxikon, and Genentech and personal/consultancy fees from Merck, Synlogic Therapeutics, Tesaro, Bristol Myers Squibb (BMS), Genentech, Xencor, Memgen, Calidi Biotherapeutics, and Agenus. L.A.D. is a member of the board of directors of Personal Genome Diagnostics (PGDx) and Jounce Therapeutics. L.A.D. is a compensated consultant to PGDx, 4Paws (PetDx), Innovatus CP, Se’er, Delfi, Kinnate, and Neophore. L.A.D. is an uncompensated consultant for, but has received clinical trial support from, Merck. L.A.D. holds equity in PGDx, Jounce, Se’er, Delfi, Kinnate, and Neophore and divested equity in Thrive Earlier Detection in 2021. His spouse holds equity in Amgen. J.D.W. is a consultant for Amgen, Apricity, Arsenal IO, Ascentage Pharma, AstraZeneca, Astellas, Boehringer Ingelheim, BMS, Chugai, Dragonfly, F Star, Eli Lilly, Georgiamune, IMVAQ, Merck, Polynoma, Psioxus, Recepta, Trieza, Truvax, Sellas, and Werewolf Therapeutics. J.D.W. has grant/research support from BMS and Sephora. J.D.W. reports equity in Tizona Pharmaceuticals, Imvaq, Beigene, Linneaus, Apricity, Arsenal IO, and Georgiamune. T.M. is an inventor on patents involving the use of anti-PD-1 antibodies. T.M. is a consultant for Immunos Therapeutics and Pfizer. T.M. is a cofounder of and equity holder in IMVAQ. T.M. receives research funding from BMS, Surface Oncology, Kyn Therapeutics, Infinity Pharmaceuticals, Peregrine Pharmaceuticals, Adaptive Biotechnologies, Leap Therapeutics, and Aprea Therapeutics. S.X.L., O.A.-W., and R.K.B. are inventors on a patent application submitted by FHCRC related to this work., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated, but the effect of immune heterogeneity on clinical outcome in ccRCC has not been fully characterized. Here we perform paired single-cell RNA (scRNA) and T cell receptor (TCR) sequencing of 167,283 cells from multiple tumor regions, lymph node, normal kidney, and peripheral blood of two immune checkpoint blockade (ICB)-naïve and four ICB-treated patients to map the ccRCC immune landscape. We detect extensive heterogeneity within and between patients, with enrichment of CD8A + tissue-resident T cells in a patient responsive to ICB and tumor-associated macrophages (TAMs) in a resistant patient. A TCR trajectory framework suggests distinct T cell differentiation pathways between patients responding and resistant to ICB. Finally, scRNA-derived signatures of tissue-resident T cells and TAMs are associated with response to ICB and targeted therapies across multiple independent cohorts. Our study establishes a multimodal interrogation of the cellular programs underlying therapeutic efficacy in ccRCC., Competing Interests: Declaration of interests T.A.C. is a co-founder of Gritstone Oncology and holds equity. T.A.C. holds equity in An2H. T.A.C. acknowledges grant funding from Bristol-Myers Squibb, AstraZeneca, Illumina, Pfizer, An2H, and Eisai. T.A.C. has served as an advisor for Bristol-Myers Squibb, Illumina, Eisai, and An2H. M.S.K. has licensed the use of TMB for the identification of patients who benefit from immune checkpoint therapy to PGDx. S.W. holds equity in Illumina., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: TCEB1-mutant renal cell carcinoma (RCC) is a rare variant of RCC with clear-cell features. Owing to its unique morphological and molecular features it has recently been proposed as a separate entity. Initial series suggested an indolent, early-stage phenotype. Here we expand our clinical cohort and describe a more detailed genomic analysis looking for potential drivers of aggressiveness., Design, Setting, and Participants: We identified five new cases in our institutional sequencing cohort, four of whom were found to have high-stage disease (American Joint Committee on Cancer stage III/IV). Twelve previously reported cases were pooled for comparison purposes (Sato, The Cancer Genome Atlas, TRACERx Renal)., Outcome Measures and Statistical Analysis: We used our previously validated pipeline to analyze somatic mutations and copy number alterations (CNAs) in seven tumor samples with available data and estimated the number of cancer cells bearing each somatic mutation. The oncogenic potential of mutations was assessed using OncoKB and two other algorithms. Mann-Whitney U tests were used to evaluate differences in genomic markers between stage groups., Results and Limitations: All tumors showed biallelic inactivation of the TCEB1 gene according to a combination of somatic mutation and CNA analyses. Mutations were always found in residues involved in hydrophobic interactions with VHL. We found that high-stage tumors had additional oncogenic mutations (median 1, interquartile range [IQR] 1-1 vs 2, IQR 2-2; median difference 1, 95% confidence interval [CI] 1-1; p= 0.002) and showed whole-genome doubling events. They also seemed to have a higher burden of somatic CNAs (median fraction CNA genome 0.10, IQR 0.10-0.15 vs 0.63, IQR 0.58-0.68), however, this finding did not reach statistical significance (median difference 0.49, 95% CI 0.33-0.63; p=0.052)., Conclusions: TCEB1-mutant RCC can show variable behavior ranging from very indolent to aggressive. Specific molecular events leading to high genomic instability seem to be associated with aggressiveness. This study expands the clinical spectrum of TCEB1-mutant RCC., Patient Summary: We present four cases of aggressive TCEB1-mutant renal cell carcinoma, a rare type of kidney cancer. In-depth analysis of the genomes of these tumors revealed certain abnormalities that might explain this aggressive behavior., (Copyright © 2019 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

T cell discrimination of self and non-self is the foundation of the adaptive immune response, and is orchestrated by the interaction between T cell receptors (TCRs) and their cognate ligands presented by major histocompatibility (MHC) molecules. However, the impact of host immunogenetic variation on the diversity of the TCR repertoire remains unclear. Here, we analyzed a cohort of 666 individuals with TCR repertoire sequencing. We show that TCR repertoire diversity is positively associated with polymorphism at the human leukocyte antigen class I (HLA-I) loci, and diminishes with age and cytomegalovirus (CMV) infection. Moreover, our analysis revealed that HLA-I polymorphism and age independently shape the repertoire in healthy individuals. Our data elucidate key determinants of human TCR repertoire diversity, and suggest a mechanism underlying the evolutionary fitness advantage of HLA-I heterozygosity., Competing Interests: Competing interestsNot applicable., (© The Author(s) 2020.)

Purpose: Salivary gland carcinomas (SGC) are rare, aggressive cancers with high rates of recurrence and distant metastasis. These factors, and a lack of active systemic therapies, contribute to poor clinical outcome. Response rates with immune checkpoint blockade have been low, although clinical data remain sparse. To improve the efficacy of therapies, a more comprehensive understanding of relevant molecular alterations and immunologic processes is needed., Experimental Design: To characterize the immune microenvironment and neoantigen landscape of SGCs, we performed RNA sequencing (RNA-seq) in 76 tumors representing the three most lethal histologies: adenoid cystic carcinoma (ACC), myoepithelial carcinoma (MECA), and salivary duct carcinoma (SDC). We analyzed transcriptomic profiles, tumor-infiltrating immune cell populations, and measures of T-cell activation/dysfunction. In 37 cases also undergoing exome sequencing, we analyzed somatic mutations and neoantigens., Results: SDCs exhibited high levels of immune infiltration, with corresponding higher levels of T-cell dysfunction, and higher mutational load. In contrast, ACCs were characterized by an immune-excluded microenvironment, the presence of M2-polarized macrophages and myeloid-derived suppressor cells, and very low mutational load. MECAs were more heterogeneous, with both immune-low and immune-high phenotypes represented. Across all SGCs, levels of immune infiltration were associated with mutation- and fusion-derived neoantigens, and with aggressive clinical behavior., Conclusions: These findings provide new insights into the immune microenvironment and neoantigen landscape of SGCs, showing that mechanisms of immune escape appear to differ by histology. These data nominate potential immunologic vulnerabilities and may help guide the next steps of investigation in precision immunotherapy for these difficult-to-treat cancers., (©2020 American Association for Cancer Research.)

Functional diversity of the highly polymorphic human leukocyte antigen class I (HLA-I) genes underlies successful immunologic control of both infectious disease and cancer. The divergent allele advantage hypothesis dictates that an HLA-I genotype with two alleles with sequences that are more divergent enables presentation of more diverse immunopeptidomes 1-3 . However, the effect of sequence divergence between HLA-I alleles-a quantifiable measure of HLA-I evolution-on the efficacy of immune checkpoint inhibitor (ICI) treatment for cancer remains unknown. In the present study the germline HLA-I evolutionary divergence (HED) of patients with cancer treated with ICIs was determined by quantifying the physiochemical sequence divergence between HLA-I alleles of each patient's genotype. HED was a strong determinant of survival after treatment with ICIs. Even among patients fully heterozygous at HLA-I, patients with an HED in the upper quartile respond better to ICIs than patients with a low HED. Furthermore, HED strongly impacts the diversity of tumor, viral and self-immunopeptidomes and intratumoral T cell receptor clonality. Similar to tumor mutation burden, HED is a fundamental metric of diversity at the major histocompatibility complex-peptide complex, which dictates ICI efficacy. The data link divergent HLA allele advantage to immunotherapy efficacy and unveil how ICI response relies on the evolved efficiency of HLA-mediated immunity.

Tumor immunology has changed the landscape of cancer treatment. Yet, not all patients benefit as cancer immune responsiveness (CIR) remains a limitation in a considerable proportion of cases. The multifactorial determinants of CIR include the genetic makeup of the patient, the genomic instability central to cancer development, the evolutionary emergence of cancer phenotypes under the influence of immune editing, and external modifiers such as demographics, environment, treatment potency, co-morbidities and cancer-independent alterations including immune homeostasis and polymorphisms in the major and minor histocompatibility molecules, cytokines, and chemokines. Based on the premise that cancer is fundamentally a disorder of the genes arising within a cell biologic process, whose deviations from normality determine the rules of engagement with the host's response, the Society for Immunotherapy of Cancer (SITC) convened a task force of experts from various disciplines including, immunology, oncology, biophysics, structural biology, molecular and cellular biology, genetics, and bioinformatics to address the complexity of CIR from a holistic view. The task force was launched by a workshop held in San Francisco on May 14-15, 2018 aimed at two preeminent goals: 1) to identify the fundamental questions related to CIR and 2) to create an interactive community of experts that could guide scientific and research priorities by forming a logical progression supported by multiple perspectives to uncover mechanisms of CIR. This workshop was a first step toward a second meeting where the focus would be to address the actionability of some of the questions identified by working groups. In this event, five working groups aimed at defining a path to test hypotheses according to their relevance to human cancer and identifying experimental models closest to human biology, which include: 1) Germline-Genetic, 2) Somatic-Genetic and 3) Genomic-Transcriptional contributions to CIR, 4) Determinant(s) of Immunogenic Cell Death that modulate CIR, and 5) Experimental Models that best represent CIR and its conversion to an immune responsive state. This manuscript summarizes the contributions from each group and should be considered as a first milestone in the path toward a more contemporary understanding of CIR. We appreciate that this effort is far from comprehensive and that other relevant aspects related to CIR such as the microbiome, the individual's recombined T cell and B cell receptors, and the metabolic status of cancer and immune cells were not fully included. These and other important factors will be included in future activities of the taskforce. The taskforce will focus on prioritization and specific actionable approach to answer the identified questions and implementing the collaborations in the follow-up workshop, which will be held in Houston on September 4-5, 2019.

Anti-tumor immunity is driven by self versus non-self discrimination. Many immunotherapeutic approaches to cancer have taken advantage of tumor neoantigens derived from somatic mutations. Here, we demonstrate that gene fusions are a source of immunogenic neoantigens that can mediate responses to immunotherapy. We identified an exceptional responder with metastatic head and neck cancer who experienced a complete response to immune checkpoint inhibitor therapy, despite a low mutational load and minimal pre-treatment immune infiltration in the tumor. Using whole-genome sequencing and RNA sequencing, we identified a novel gene fusion and demonstrated that it produces a neoantigen that can specifically elicit a host cytotoxic T cell response. In a cohort of head and neck tumors with low mutation burden, minimal immune infiltration and prevalent gene fusions, we also identified gene fusion-derived neoantigens that generate cytotoxic T cell responses. Finally, analyzing additional datasets of fusion-positive cancers, including checkpoint-inhibitor-treated tumors, we found evidence of immune surveillance resulting in negative selective pressure against gene fusion-derived neoantigens. These findings highlight an important class of tumor-specific antigens and have implications for targeting gene fusion events in cancers that would otherwise be less poised for response to immunotherapy, including cancers with low mutational load and minimal immune infiltration.

Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

Background: Tobacco smoking creates DNA damage, inducing mutations and potentially altering the tumor immune microenvironment. These types of genetic and immune microenvironment alterations are critical factors known to affect tumor response to immunotherapy. Here we analyze the association between the mutational signature of tobacco smoking, tumor mutational load, and metrics of immune activity in squamous cell carcinomas arising in the head and neck and lung., Methods: Using RNA and DNA sequencing data from The Cancer Genome Atlas head and neck (HNSC; n = 287) and lung (LUSC; n = 130) squamous cell carcinoma data sets and two independent gene expression data sets (HNSC, n = 136; LUSC, n = 75), we examined associations between the mutational smoking signature, mutation count, immune cell infiltration, cytolytic activity, and interferon-γ signaling., Results: An increasing mutational smoking signature was associated with statistically significantly increased overall mutational load in both HNSC (ρ = .33, P = 1.01 × 10-7) and LUSC (ρ = .49, P = 2.80 × 10-9). In HNSC, a higher mutational smoking signature was associated with lower levels of immune infiltration (ρ = -.37, P = 1.29 × 10-10), cytolytic activity (ρ = -.28, P = 4.07 × 10-6), and interferon-γ pathway signaling (ρ = .39, P = 3.20 × 10-11). In LUSC, these associations were reversed (ρ = .19, P = .03; ρ = .20, P = .02; and ρ = .18, P = .047, respectively). Differentially expressed genes between smoking-high and smoking-low tumors revealed broad tobacco-induced immunosuppression in HNSC, in contrast to a tumor-inflamed microenvironment in smokers with LUSC., Conclusions: In squamous cell carcinomas, the genetic smoking signature is associated with higher mutational load, but variable effects on tumor immunity can occur, depending on anatomic site. In HNSC, smoking is predominantly immunosuppressive; in LUSC, more pro-inflammatory. Both tumor mutation load and immune microenvironment affect clinical response to immunotherapy. Thus, the mutational smoking signature is likely to have relevance for immunotherapeutic investigation in smoking-associated cancers.

CD8 + T cell-dependent killing of cancer cells requires efficient presentation of tumor antigens by human leukocyte antigen class I (HLA-I) molecules. However, the extent to which patient-specific HLA-I genotype influences response to anti-programmed cell death protein 1 or anti-cytotoxic T lymphocyte-associated protein 4 is currently unknown. We determined the HLA-I genotype of 1535 advanced cancer patients treated with immune checkpoint blockade (ICB). Maximal heterozygosity at HLA-I loci ("A," "B," and "C") improved overall survival after ICB compared with patients who were homozygous for at least one HLA locus. In two independent melanoma cohorts, patients with the HLA-B44 supertype had extended survival, whereas the HLA-B62 supertype (including HLA-B*15:01) or somatic loss of heterozygosity at HLA-I was associated with poor outcome. Molecular dynamics simulations of HLA-B*15:01 revealed different elements that may impair CD8 + T cell recognition of neoantigens. Our results have important implications for predicting response to ICB and for the design of neoantigen-based therapeutic vaccines., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Increasing evidence shows that tumor clonal architectures are often the consequence of a complex branching process, yet little is known about the expected dynamics and extent to which these divergent subclonal expansions occur. Here, we develop and implement more than 88,000 instances of a stochastic evolutionary model simulating genetic drift and neoplastic progression. Under different combinations of population genetic parameter values, including those estimated for colorectal cancer and glioblastoma multiforme, the distribution of sizes of subclones carrying driver mutations had a heavy right tail at the time of tumor detection, with only 1 to 4 dominant clones present at ≥10% frequency. In contrast, the vast majority of subclones were present at <10% frequency, many of which had higher fitness than currently dominant clones. The number of dominant clones (≥10% frequency) in a tumor correlated strongly with the number of subclones (<10% of the tumor). Overall, these subclones were frequently below current standard detection thresholds, frequently harbored treatment-resistant mutations, and were more common in slow-growing tumors. Significance: The model presented in this paper addresses tumor heterogeneity by framing expectations for the number of resistant subclones in a tumor, with implications for future studies of the evolution of therapeutic resistance. Cancer Res; 78(3); 830-9. ©2017 AACR ., (©2017 American Association for Cancer Research.)

Background: Because of the current epidemic of human papillomavirus (HPV)-related oropharyngeal cancer (OPC), a screening strategy is urgently needed. The presence of serum antibodies to HPV-16 early (E) antigens is associated with an increased risk for OPC. The purpose of this study was to evaluate the diagnostic accuracy of antibodies to a panel of HPV-16 E antigens in screening for OPC., Methods: This case-control study included 378 patients with OPC, 153 patients with nonoropharyngeal head and neck cancer (non-OPC), and 782 healthy control subjects. The tumor HPV status was determined with p16 immunohistochemistry and HPV in situ hybridization. HPV-16 E antibody levels in serum were identified with an enzyme-linked immunosorbent assay. A trained binary logistic regression model based on the combination of all E antigens was predefined and applied to the data set. The sensitivity and specificity of the assay for distinguishing HPV-related OPC from controls were calculated. Logistic regression analysis was used to calculate odds ratios with 95% confidence intervals for the association of head and neck cancer with the antibody status., Results: Of the 378 patients with OPC, 348 had p16-positive OPC. HPV-16 E antibody levels were significantly higher among patients with p16-positive OPC but not among patients with non-OPC or among controls. Serology showed high sensitivity and specificity for HPV-related OPC (binary classifier: 83% sensitivity and 99% specificity for p16-positive OPC)., Conclusions: A trained binary classification algorithm that incorporates information about multiple E antibodies has high sensitivity and specificity and may be advantageous for risk stratification in future screening trials. Cancer 2017;123:4886-94. © 2017 American Cancer Society., (© 2017 American Cancer Society.)

The mechanisms by which immune checkpoint blockade modulates tumor evolution during therapy are unclear. We assessed genomic changes in tumors from 68 patients with advanced melanoma, who progressed on ipilimumab or were ipilimumab-naive, before and after nivolumab initiation (CA209-038 study). Tumors were analyzed by whole-exome, transcriptome, and/or T cell receptor (TCR) sequencing. In responding patients, mutation and neoantigen load were reduced from baseline, and analysis of intratumoral heterogeneity during therapy demonstrated differential clonal evolution within tumors and putative selection against neoantigenic mutations on-therapy. Transcriptome analyses before and during nivolumab therapy revealed increases in distinct immune cell subsets, activation of specific transcriptional networks, and upregulation of immune checkpoint genes that were more pronounced in patients with response. Temporal changes in intratumoral TCR repertoire revealed expansion of T cell clones in the setting of neoantigen loss. Comprehensive genomic profiling data in this study provide insight into nivolumab's mechanism of action., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to determine the association of HPV16 antibodies (Abs) and oropharyngeal cancer (OPC) risk in sera obtained prior to clinical diagnosis., Methods: We identified 92 participants with incident OPC and 460 matched controls from the Janus Serum Bank Cohort in Norway. Archived tumor specimens were requested for a subset of the cases. Serum samples were collected from cases, on average, 9.3years before diagnosis (range, 0.1-14.9years). Ten cases had serum samples from multiple time points. IgG seropositivity to 8 HPV16 antigens was determined, and a logistic regression classifier of a panel of all early-antigen (EA) Abs for the predictive diagnosis of OPC was applied., Results: HPV16 EA seropositivity was present in 25.0% of patients with OPC and 7.6% of controls (odds ratio (OR), 4.1; 95% CI, 2.3-7.2, p<0.0001). Abs to E2 were strongly associated with cases 0-2years pre- diagnosis (OR, 150.1; 95% CI, 27.4-1040.0, p<0.0001), and the probability of seropositivity was inversely associated with time to diagnosis (OR, 0.7 per additional year; 95% CI, 0.6-0.9, p=0.0002). Abs to E2 were also strongly associated with tumor HPV status (OR, 35.6; 95% CI, 8.7-200.0, p<0.0001). A positive score on the binary classifier was associated with an overall OR of 15.8 (95% CI, 5.6-53.4) compared with controls (p<0.05), and was strongly associated with tumor HPV status (OR, 27.4; 95% CI, 8.6-99.6, p<0.001)., Conclusions: HPV16 Abs are detectable years prior to diagnosis of OPC, and the probability of seropositivity increases closer to diagnosis., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer., Methods: To detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n=30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n=30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n=63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed., Results: We identified 11-TAAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity., Conclusion: These are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: Mutations in TP53 induce autoantibody immune responses in a subset of cancer patients, which have been proposed as biomarkers for early detection. Here, we investigate the association of p53-specific autoantibodies with multiple tumor subtypes and determine the association with p53 mutation status and epitope specificity., Experimental Design: IgG p53 autoantibodies (p53-AAb), were quantified in 412 serum samples using a programmable ELISA assay from patients with serous ovarian, pancreatic adenocarcinoma, and breast cancer. To determine if patients generated mutation-specific autoantibodies we designed a panel of the most relevant 51 p53 point mutant proteins, to be displayed on custom programmable protein microarrays. To determine the epitope specificity we displayed 12 overlapping tiling fragments and 38 N- and C-terminal deletions spanning the length of the wild-type p53 protein., Results: We detected p53-AAb with sensitivities of 58.8% (ovarian), 22% (pancreatic), 32% (triple negative breast cancer), and 10.2% (HER2+ breast cancer) at 94% specificity. Sera with p53-AAb contained broadly reactive autoantibodies to 51 displayed p53 mutant proteins, demonstrating a polyclonal response to common epitopes. All p53-AAb displayed broad polyclonal immune response to both continuous and discontinuous epitopes at the N- and C-terminus as well as the DNA-binding domain., Conclusion and Clinical Relevance: In this comprehensive analysis, mutations in tumor p53 induce strong, polyclonal autoantibodies with broadly reactive epitope specificity., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Whole-genome analyses of human medulloblastomas show that the dominant clone at relapse is present as a rare subclone at primary diagnosis.

Objectives: We hypothesized that viral and host factors impact the serologic responses to HPV early antigens in HPV-positive oropharyngeal cancer (HPVOPC)., Materials and Methods: We conducted a multicenter study to measure HPV16-specific IgG among patients with HPVOPC, their long-term sexual partners, and healthy volunteers. Risk factor surveys and rinse and gargle specimens were collected. Peripheral blood samples at diagnosis were evaluated for IgG Abs to HPV16 antigens using a programmable ELISA assay. Predictors for HPV16 serologic responses were evaluated using univariate and multivariable linear regression., Results: 116 patients with HPVOPC, 43 partners, and 81 healthy volunteers were enrolled and had baseline sera for analysis. Cases were primarily male (90%), with a median age of 56 years. Abs to E1, E2, E6 or E7 antigens were detected more often in HPVOPC compared with volunteers or partner sera (p<0.0001). HPV16 Abs to at least one early protein (E1, E2, E4, E5, E6, or E7) were detected in the sera of 90.6% of cases, 0% of partners and 7.4% of healthy volunteers. Gender, race, sexual behavior, and viral integration were not associated with antibody response. Younger age and higher oral HPV16 copy number were associated with higher HPV16 E6 and NE2 antibody levels., Conclusions: HPV16 seroreactivity is commonly detected among patients with HPVOPC at diagnosis, but not among partners or healthy volunteers. Seroreactivity among cases are correlated with viral load and stage and not with other demographic or behavioral factors. Positive HPV16 serology was strongly associated with HPV 16 oropharyngeal cancer., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: Antibodies (Abs) to the HPV16 proteome increase risk for HPV-associated OPC (HPVOPC). The goal of this study was to investigate the association of a panel of HPV16 Abs with risk for OPC as well as the association of these Abs with tumor HPV and smoking status among patients with OPC., Methods: IgG Abs to the HPV16 antigens E1, E2, E4, E5, E6, E7, L1, L2 were quantified using a programmable ELISA assay. Sera were obtained from 258 OPC patients at diagnosis and 250 healthy controls. HPV16 tumor status was measured by PCR for 137 cases. Multivariable logistic regression was used to calculate odds ratios for the association of HPV16 Abs with risk for OPC., Results: HPV16 E1, E2, E4, E5, E6, E7 and L1-specific IgG levels were elevated in OPC patients compared to healthy controls (p<0.05). After multivariable adjustment, Ab positivity for NE2, CE2, E6, and/or E7 was associated with OPC risk (OR [95% CI], 249.1 [99.3-624.9]). Among patients with OPC, Ab positivity for these antigens was associated with tumor HPV status, especially among never or light smokers (OR [95% CI], 6.5 [2.1-20.1] and OR [95% CI], 17.5 [4.0-77.2], respectively)., Conclusions: Antibodies to HPV16 proteins are associated with increased risk for HPVOPC. Among patients with OPC, HPV16 Abs are associated with tumor HPV status, in particular among HPV positive patients with no or little smoking history., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Purpose: Oropharyngeal carcinoma positive for human papillomavirus type 16 (HPV16) has a significantly better prognosis than oropharyngeal carcinoma unrelated to HPV. Within HPV16-positive oropharyngeal carcinoma, biomarkers of prognosis are urgently needed to individualize care. We hypothesized that serum antibodies specific to HPV16, the major HPV type causing oropharyngeal carcinoma, have biologic relevance and are potential biomarkers for improved prognosis among patients with HPV16-positive oropharyngeal carcinoma., Experimental Design: IgG antibodies to the HPV16 antigens E1, E4-E7, L1, L2, and the N-terminal and C-terminal fragments of E2 (NE2, CE2) were quantified using a custom programmable enzyme-linked immunosorbent assay. Sera were obtained at diagnosis from 209 oropharyngeal carcinoma patients (96 HPV16-positive). The ratios of median fluorescent intensity (MFI) for each antigen to MFI for control GST protein were determined. Kaplan-Meier survival curves and Cox proportional hazards regression were used to determine survival differences between groups. ROC curves were used to determine the best combination of E antibodies to predict disease recurrence., Results: E1, NE2, and E6 antibody positivity were all strongly associated with improved overall and progression-free survival in the entire cohort and in patients with known HPV16-positive tumors (P < 0.05). For both overall and progression-free survival among HPV-positive patients, hazard ratios were 0.2 for NE2, 0.3 for E1, and 0.3 for E6 antibody positivity., Conclusions: We identified three HPV16-specific antibodies that are associated with improved overall and progression-free survival in patients with HPV-related oropharyngeal carcinoma. These results suggest that differential serologic responses in patients may reflect differential biologic processes within the host and tumor and may have prognostic value., (©2015 American Association for Cancer Research.)

Despite the availability of major histocompatibility complex (MHC)-binding peptide prediction algorithms, the development of T-cell vaccines against pathogen and tumor antigens remains challenged by inefficient identification of immunogenic epitopes. CD8(+) T cells must distinguish immunogenic epitopes from nonimmunogenic self peptides to respond effectively against an antigen without endangering the viability of the host. Because this discrimination is fundamental to our understanding of immune recognition and critical for rational vaccine design, we interrogated the biochemical properties of 9,888 MHC class I peptides. We identified a strong bias toward hydrophobic amino acids at T-cell receptor contact residues within immunogenic epitopes of MHC allomorphs, which permitted us to develop and train a hydrophobicity-based artificial neural network (ANN-Hydro) to predict immunogenic epitopes. The immunogenicity model was validated in a blinded in vivo overlapping epitope discovery study of 364 peptides from three HIV-1 Gag protein variants. Applying the ANN-Hydro model on existing peptide-MHC algorithms consistently reduced the number of candidate peptides across multiple antigens and may provide a correlate with immunodominance. Hydrophobicity of TCR contact residues is a hallmark of immunogenic epitopes and marks a step toward eliminating the need for empirical epitope testing for vaccine development.