Abstract 2737: Clinical and epidemiologic predictors of clonal immune responses in colorectal cancer

The quantity and quality of immune responses in colorectal cancers (CRC) are widely variable and have important clinical, therapeutic, and prognostic implications. We studied clinical and epidemiologic factors that might influence T-cell quantity and clonality within colorectal adenocarcinomas to better understand the drivers of diverse immune responses. Incident cases of CRC from the Molecular Epidemiology of Colorectal Cancer Study (MECC) were interviewed, and 6,006 cases had complete epidemiologic data. Archived tumor blocks were retrieved from 3,865 (64.4%) cases, and all were reviewed by a single expert pathologist who quantified TILS/hpf. Sufficient tissue for macrodissection and measurement of TCR abundance and clonality using the immunoSEQ assay (Adaptive Biotechnologies) was available and completed for 2,750 cases. Logistic regression, negative binomial regression and linear regression models were used to evaluate potential associations between clinical and epidemiologic variables for: TILS/hpf, TCR abundance, and T-cell clonality. The stage distribution was representative of cancer incidence in the population, and the MSI-H phenotype was observed in 14.2% of cases. Clinical, pathologic, and epidemiologic variables including aspirin, alcohol, diet, hormone use, physical activity, smoking, and statins were assessed in relation to immune measures. Among other findings, >5 years of statins (p<0.001) and daily aspirin (p=0.037) were each strongly associated with T-cell clonality. Our study suggests that important parameters of the adaptive immune response may be mediated by modifiable factors. Mechanisms regulating immune responses in CRC may have implications for chemoprevention as well as immunotherapy.

Citation Format: Stephen B. Gruber, Joseph D. Bonner, Sidney S. Lindsey, Ya-Yu Tsai, Rebeca Sanz-Pamplona, M. Henar Alonso, Marilena Melas, Hedy S. Rennert, Kevin J. McDonnell, Gregory E. Idos, Christopher P. Walker, W. Martin Kast, Diane Da Silva, Harlan S. Robins, Joel K. Greenson, Victor Moreno, Stephanie L. Schmit, Gad Rennert. Clinical and epidemiologic predictors of clonal immune responses in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2737.

Abstract 824: Germline genetic regulation of the adaptive immune response in colorectal cancer

Adaptive immune responses in the tumor microenvironment of colorectal cancer (CRC) play an important role in prognosis. However, the contributions of germline genetic variations to the strength and diversity of T cell responses in CRC are unclear. We conducted a genome-wide association study to examine the relationships between germline genetic variants and measures of the T cell repertoire in colorectal tumors. Germline DNA samples from 5,581 CRC cases recruited into the Molecular Epidemiology of Colorectal Cancer Study (MECC) were genotyped in batches using four different platforms. Genotype data were imputed to the Haplotype Reference Consortium panel separately by genotyping platform. Tumor DNA samples were extracted from paraffin blocks, and tumor infiltrating lymphocytes per high powered field (TILs/hpf) were quantified by a single gastrointestinal pathologist. TCR abundance and clonality within individual CRCs were measured using the immunoSEQ assay (Adaptive Biotechnologies). Appropriate quality control steps and data transformations were applied to fit downstream statistical modeling assumptions. After standard quality control on both imputed genotypes and transformed immune metrics, 2,876 (TILs/hpf) and 2,395 (TCR abundance and clonality) cases with approximately 9 million imputed genetic variants were included in the discovery phase. Logistic or linear regression models were used to evaluate the associations between allelic dosage of each variant and each immune-related outcome, adjusting for sex, age at diagnosis, genotyping platform, and principal components for global ancestry. Three independent datasets were available to replicate our findings using similar quality control measures and regression models: Colonomics (N=96; TILs/hpf, TCR abundance, clonality), the CRC Genetics Study (N=162; TCR abundance, clonality), and the Harvard Cohorts (N=505; TILs/hpf; in progress). The discovery phase identified 5 independent genetic variants associated with TILs/hpf, 15 associated with TCR abundance, and 19 associated with clonality at p<5X10E-06. Replication analyses as well as expression quantitative trait analyses and in silico functional annotation are underway for the loci of interest. Our study suggests that germline genetic variation is associated with the quantity and quality of adaptive immune responses in CRC.

Citation Format: Stephanie L. Schmit, Ya-Yu Tsai, Joseph Bonner, Rebeca Sanz-Pamplona, Amit D. Joshi, Sidney S. Lindsey, Marilena Melas, Kevin J. McDonnell, Gregory E. Idos, Christopher P. Walker, W. Martin Kast, Diane Da Silva, Tomotaka Ugai, Hedy S. Rennert, Harlan S. Robins, Joel K. Greenson, Shuji Ogino, Victor Moreno, Gad Rennert, Stephen B. Gruber. Germline genetic regulation of the adaptive immune response in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 824.

Abstract 835: T-cell abundance, clonality and disease specific survival in colorectal cancer

Immune responses to colorectal cancer (CRC) are important prognostic factors as measured by either tumor infiltrating lymphocytes per high powered field or the presence of Crohn's like lymphoid reaction. New technologies to quantify specific features of immune responses include immunoSeq (Adaptive Biotechnologies), which accurately quantifies T-cell receptor (TCR) abundance and T-cell receptor clonality. Here we measured the independent contributions of TCR abundance and TCR clonality to 5-year CRC-specific survival in the Molecular Epidemiology of Colorectal Cancer (MECC) study. The MECC study consented, interviewed, and followed 6,006 incident cases of CRC diagnosed between March 31, 1998 and July 1, 2017 (median follow-up time = 6.9 years). Archived paraffin blocks were retrieved, and 2,750 cases had sufficient tissue and adequate DNA extraction to perform the immunoSeq assay. Analyses were restricted to 1,625 samples with more than 100 T-cells to permit accurate quantification of TCR abundance and TCR clonality as measured by Simpson Clonality Index. TCR abundance was log2 transformed for analyses, and Simpson Clonality Index was log2-transformed and z-scale normalized separately by assay version. In unadjusted models, dichotomized log2 transformed TCR abundance (Hazard Ratio (HR) = 0.57, 95% confidence interval (CI) 0.47-0.71, p=9.77E-08) and dichotomized TCR clonality (HR = 0.77, 95% CI 0.63-0.94, p=0.01) were each statistically significantly associated with 5-year CRC-specific survival. In a model with adjustment for age, sex, microsatellite instability, stage and assay version, both dichotomized log2 transformed TCR abundance (HR = 0.61, 95% CI, 0.49-0.75, p=3.03E-06), and dichotomized TCR clonality (HR = 0.81, 95% CI, 0.66-0.99, p=0.048) were associated with improved 5-year disease-specific survival.

Conclusion: TCR abundance and TCR clonality are independent prognostic indicators in CRC.

Citation Format: Joseph Bonner, Sephanie L. Schmit, Sidney S. Lindsey, Ya-Yu Tsai, Rebeca Sanz-Pamplona, M. Henar Alonso, Marilena Melas, Hedy S. Rennert, Kevin J. McDonnell, Gregory Idos, Christopher P. Walker, W. Martin Kast, Diane Da Silva, Harlan S. Robins, Joel K. Greenson, Victor Moreno, Gad Rennert, Stephen B. Gruber. T-cell abundance, clonality and disease specific survival in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 835.

How omnivory affects the survival and choices of earwig Doru luteipes (Scudder) (Dermaptera: Forficulidae)?

Doru luteipes (Scudder, 1876) is an omnivorous predator that finds different food resources in the corn plant: eggs of Spodoptera frugiperda (J.E. Smith, 1797), uredospores of Puccinia polysora (Underw, 1897), and pollen. Knowing the survival and food preferences of this predator is essential to define its relevance as a biological control agent. We hypothesize that the foraging behavior and predatory capacity of D. luteipes may be affected when several food resources, especially eggs of S. frugiperda, uredospores of P. polysora, and pollen are concurrently in the same plant. The survival of D. luteipes in the nymph stage and their preference among food resources, often available in corn plants, were determined. To verify the survival of D. luteipes, newly hatched nymphs were fed exclusively with 1- uredospores of P. polysora, 2- eggs of S. frugiperda, 3- corn pollen, 4- a combination of uredospores + eggs, and 5- artificial diet (control). In another experiment, nymphs and adults of D. luteipes with 24 and 48 hours of fasting were individually released in the center of a container with four diets: 1- uredospores of P. polysora, 2- eggs of S. frugiperda, 3- corn pollen, 4- artificial diet, and maintained for 10 minutes, to evaluate the food choice and feeding time. The exclusive feeding with S. frugiperda eggs caused low nymph survival (8%), but the combination of P. polysora uredospores + S. frugiperda eggs allowed 58.3% survival. D. luteipes preferred feeding during the nighttime and the most significant proportions of choices by nymphs and adults were for pollen and diet, with adults spending more time eating pollen. These findings indicate that the trophic choices of D. luteipes are relevant to understand its contribution as an agent to control pest insects and fungal diseases in corn.

Evaluation of a flash glucose monitoring system in dogs with diabetic ketoacidosis

The flash glucose monitoring system (FGMS) Freestyle Libre provides estimates of blood glucose by constantly measuring the glucose concentration of the interstitial fluid through a sensor inserted in the subcutaneous space. The aim of this study was to evaluate the applicability and accuracy of the FGMS in dogs with diabetic ketoacidosis (DKA). Seven dogs with DKA examined at the Veterinary Hospital of the State University of Londrina were included in this study. The sensor was placed on the dorsal cervical region, shortly after the diagnosis of DKA was confirmed and maintained for 5 d. The measurement of blood glucose was performed simultaneously with the veterinary portable blood glucose meter (PBGM) AlphaTRAK 2 every 2 to 4 h and with the hexokinase method every 12 h. The PBGM's precision was evaluated following the ISO15197:2013 criteria. Blood glucose estimates were strongly associated (r = 0.89; P < 0.0001), and the mean absolute relative difference in relation to the PBGM was 25.2% (-70.4% to 101.9%). The evaluation of these data using the consensus error grid analysis showed that 95.4% and 94.8% of the samples were in Zones A and B (clinically acceptable) using the PBGM and the hexokinase method as a reference, respectively. The ISO15197:2013 criteria were not met. There was no difference in the accuracy of the device among days (P = 0.74); however, there was a difference between the hydration status (P = 0.019) and blood glucose ranges (hypoglycemic, euglycemic, and hyperglycemic; P < 0.0001), in which it was less precise in measuring the blood glucose range in hypoglycemic dogs. Therefore, it can be concluded that in spite of the fact that the device did not meet the ISO 15197:2013 criteria, the FGMS evaluated presents good clinical precision and can be a valuable tool in treating dogs with diabetic DKA.

Abstract IA41: Novel Approaches for Accessing Molecular Heterogeneity

Ovarian cancer is the fifth leading cause of cancer-related deaths in women and is the deadliest gynecological malignancy in the United States. The standard treatment of ovarian cancer is based on debulking surgery followed by platinum- and taxane-based chemotherapy, and has remained the same over the past three decades. Over those years, molecular targeted and combination therapies have been developed and clinically approved, however the overall survival rate has not improved significantly due to chemo-resistance. Further, the majority of patients experience recurrence of treatment-resistant tumors. The genomic diversity within a tumor and the varying cell types within its microenvironment has placed significant importance on heterogeneity and its clinical implications. Intra-tumor heterogeneity has often been blamed for treatment failure in ovarian carcinoma. Consequently, intra-tumor heterogeneity is a key factor driving drug resistance, therapeutic failure, and poor outcomes and poses a significant challenge to personalized cancer medicine. Intra-tumor heterogeneity is a hallmark of cancer where the molecular and cellular interactions within the tumor microenvironment can dictate a cancer’s fate. Molecular profiling of bulk tissue specimens using methods such as whole-transcriptome sequencing are limited in their ability to resolve fine grain molecular signatures and hinder our utility to dissect the underlying biology of individual tumors. Although informatics approaches are available that attempt to disentangle tissue heterogeneity from bulk tumor data, emerging spatial whole transcriptome sequencing technologies allow a more precise delineation of cellular and molecular substructure in a comprehensive unbiased approach. Spatial Transcriptomics (ST) enables high-throughput whole transcriptomic sequencing within a single intact tissue by using a glass slide arrayed with barcoded cDNA primers at a resolution of 100um (3-30 cells). This workflow requires no tissue dissociation keeping fragile cell types intact. Resulting data from this workflow is overlaid on the tissue, displayed as a “cluster reference map”, providing comprehensive unbiased transcriptional substructure and unique possibilities for subsequent in situ analysis. The overall goal of this study is to utilize ST to unveil the unexplored landscape of intra-tumor heterogeneity in ovarian cancer and determine its translational relevance. Here, we applied ST to profile gene expression in fresh frozen OCT embedded sections from nine high grade ovarian patients. Three serial 5-micron frozen sections were placed on proprietary 10x Genomics Spatial Transcriptomics (ST) slides and processed using manufacturer specifications. Libraries were sequenced on the Illumina NovaSeq 6000 system and data was processed using 10X Genomics analytical tools. Next, we aggregated the transcriptional profiles of serial sections from each case increasing our power to cluster similar regions and identify differentially expressed genes within these tissues. Using serial sections of solid tumors from each subject we were not only able to profile each section at 100um resolution but also spatially resolve gene expression signatures and cluster regions of tissue based on these signatures. This ST workflow reliably quantitated an average spatial distribution of 19,285 genes per section in our ovarian cancer cohort. Interestingly, within our cohort we have extreme outliers that include primary tumors that did not have any response to standard adjuvant chemotherapy, paclitaxel and carboplatin, and patients that sustained a durable response to standard adjuvant chemotherapy and diagnosed as disease free ≥3 years and then presented with recurrent disease. We identified tumor heterogeneity as unique spatially-resolved gene expression clusters across each tissue section defined by individual gene sets associated with tumorigenic molecular processes, immune cell quantity and localization. These approaches highlight the power of spatial whole-transcriptomic sequencing in solid tumor studies to help unravel the complexity of heterogeneous cancers and provide a comprehensive characterization of transcriptional substructure within a single tissue section.

Citation Format: Lee D. Gibbs, Lynda Roman, Michelle Webb, Rania Bassiouni, Stephen R Williams, Neil I. Weisenfeld, Nigel F. Delaney, Yifeng Yin, Solomon Rotimi, Jennifer Chew, Meghan Frey, Jing Qian, Heather Miller, Laila Murderspach, Diane Da Silva, Troy McEachron, David W. Craig, John D. Carpten. Novel Approaches for Accessing Molecular Heterogeneity [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr IA41.

Abstract NG03: Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in high-grade ovarian cancers

Ovarian cancer is the fifth leading cause of cancer-related deaths in women and is the deadliest gynecological malignancy in the United States. The standard treatment of ovarian cancer is based on debulking surgery followed by platinum- and taxane-based chemotherapy, and has remained the same over the past three decades. Over those years, molecular targeted and combination therapies have been developed and clinically approved, however the overall survival rate has not improved significantly due to chemo-resistance. Further, the majority of patients experience recurrence of treatment-resistant tumors. The genomic diversity within a tumor and the varying cell types within its microenvironment has placed significant importance on heterogeneity and its clinical implications. Intra-tumor heterogeneity has often been blamed for treatment failure in ovarian carcinoma. Consequently, intra-tumor heterogeneity is a key factor driving drug resistance, therapeutic failure, and poor outcomes and poses a significant challenge to personalized cancer medicine.

Intra-tumor heterogeneity is a hallmark of cancer where the molecular and cellular interactions within the tumor microenvironment can dictate a cancer's fate. Molecular profiling of bulk tissue specimens using methods such as whole-transcriptome sequencing are limited in their ability to resolve fine grain molecular signatures and hinder our utility to dissect the underlying biology of individual tumors. Although informatics approaches are available that attempt to disentangle tissue heterogeneity from bulk tumor data, emerging spatial whole transcriptome sequencing technologies allow a more precise delineation of cellular and molecular substructure in a comprehensive unbiased approach. Spatial Transcriptomics (ST) enables high-throughput whole transcriptomic sequencing within a single intact tissue by using a glass slide arrayed with barcoded cDNA primers at a resolution of 100um (3-30 cells). This workflow requires no tissue dissociation keeping fragile cell types intact. Resulting data from this workflow is overlaid on the tissue, displayed as a “cluster reference map”, providing comprehensive unbiased transcriptional substructure and unique possibilities for subsequent in situ analysis.

The overall goal of this study is to utilize ST to unveil the unexplored landscape of intra-tumor heterogeneity in ovarian cancer and determine its translational relevance. Here, we applied ST to profile gene expression in fresh frozen OCT embedded sections from nine high grade ovarian patients. Three serial 5-micron frozen sections were placed on proprietary 10x Genomics Spatial Transcriptomics (ST) slides and processed using manufacturer specifications. Libraries were sequenced on the Illumina NovaSeq 6000 system and data was processed using 10X Genomics analytical tools. Next, we aggregated the transcriptional profiles of serial sections from each case increasing our power to cluster similar regions and identify differentially expressed genes within these tissues. Using serial sections of solid tumors from each subject we were not only able to profile each section at 100um resolution but also spatially resolve gene expression signatures and cluster regions of tissue based on these signatures. This ST workflow reliably quantitated an average spatial distribution of 19,285 genes per section in our ovarian cancer cohort. Interestingly, within our cohort we have extreme outliers that include primary tumors that did not have any response to standard adjuvant chemotherapy, paclitaxel and carboplatin, and patients that sustained a durable response to standard adjuvant chemotherapy and diagnosed as disease free ≥3 years and then presented with recurrent disease.

ST revealed cellular heterogeneity across the entirety of the tumor microenvironment in an anatomically resolved manner. Bioinformatic tools and molecular pathway enrichment were used to annotate tumor, stromal, and immune tissue regions. Our analyses blindly recapitulate specific histopathological annotations spatially through unsupervised gene expression clustering. These data also revealed clear transcriptional substructure, where we identified transcriptionally diverse tumor clones that have unique gene sets associated with distinct molecular processes that relate to oncogenesis (BRCA1, P53, and PTEN Pathway). and potential targetable pathways (EGFR, HER2, PI3K/AKT/MAPK signaling pathways). Additionally, we were able to create spatial heat maps of the inflammatory microenvironment at the single gene level and for gene profiles that define specific inflammatory signals and immune cell profiles. Using this approach, we went on to conduct a refined analysis of key inflammatory genes that have been previously known to play an important role in the immune response of ovarian cancer and developed a spatially resolved inflammation score for each section from each subject. Not only did we observe statistically significant regionalized inflammation scores within each subject, we also found inter-subject differences which may give clinical insight into response to treatment. Surprisingly, this technology also enabled the ability to analyze conventional and emerging immune checkpoint gene expression while accessing the cells and regions of the tissue where they are expressed. Further, our analysis of spatial maps and immune cell quantitation within a primary and recurrent tumor from the same individual revealed dynamic longitudinal changes in inflammation scores and immune infiltration between tumors and spatially within each tumor.

These approaches highlight the power of spatial whole-transcriptomic sequencing in solid tumor studies to help unravel the complexity of heterogeneous cancers and provide a comprehensive characterization of transcriptional substructure within a single tissue section.

Citation Format: Lee D. Gibbs, Stephen R. Williams, Neil I. Weisenfeld, David W. Craig, Rania Bassiouni, Nigel F. Delaney, Diane Da Silva, Yifeng Yin, Solomon Rotimi, Jennifer Chew, Meghan Frey, Michelle Webb, Jing Qian, Heather Miller, Laila Murderspach, Troy McEachron, Lynda Roman, John D. Carpten. Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in high-grade ovarian cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr NG03.

Abstract A087: Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in a diverse cohort of high-grade ovarian cancers

Introduction: Differences in tumor heterogeneity, particularly the tumor microenvironment have not yet been explored as potential molecular features underlying cancer disparities. Molecular profiling of bulk tissue specimens using methods such as whole-transcriptome sequencing are limited in their ability to resolve fine grain molecular signatures and hinder our utility to dissect underlying biology of individual tumors. Although informatics approaches are available that attempt to disentangle tissue heterogeneity from bulk tumor data, emerging spatial whole transcriptome sequencing technologies allows a more precise delineation of cellular and molecular substructure in a comprehensive unbiased way. Here we present an investigation whole-transcriptome spatial sequencing in a diverse cohort of ovarian cancer cases. Methods: Three serial 5-micron frozen sections were placed on proprietary 10x Genomics Spatial Transcriptomics (ST) slides and processed using manufacturer specifications. Libraries were sequenced on the Illumina NovaSeq 6000 system and data was processed using the 10X Genomics analytical tools. ST data from each section was analyzed to create spatially defined cellular clusters at 100-micron resolution. Results: ST revealed cellular heterogeneity across the entirety of the tumor microenvironment in an anatomically resolved manner. Bioinformatic tools and molecular pathways to infer tumor purity were used to annotate tumor, immune, and stromal substructures. These data also revealed clear transcriptional substructure in some tumors, where different tumor regions were defined by unique gene sets associated with different molecular processes known to be related to tumorigenesis. Further, we observed clear transcriptional substructure in some tumors, where different tumor regions were enriched with molecular pathways that are associated with tumorigenesis (i.e., DNA Damage Response, and Protein Translation pathways), regions defined by immune infiltration (i.e. CD8+ T cells, T regulatory cells, Macrophages, and B cells), and molecular pathways that are associated with inflammatory signalling (i.e. complement, IL2, IL-10, and IL6 signaling pathways). Conclusion: These approaches highlight the power of spatial whole-transcriptomic approaches in solid tumor studies to help unravel the complexity of heterogeneous cancers and provide a comprehensive characterization of transcriptional substructure within a single tissue section.

Citation Format: Lee D. Gibbs, Stephen R. Williams, Neil I. Weisenfeld, Rania Bassiouni, Nigel F. Delaney, Diane Da Silva, Yifeng Yin, Solomon Rotimi, Jennifer Chew, Meghan Frey, Jing Qian, Heather Miller, Laila Murderspach, Troy McEachron, David Craig, Lynda WOptional Roman, John D. Carpten. Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in a diverse cohort of high-grade ovarian cancers [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A087.

Abstract B26: Prorapeutic vaccination against shared antigens induced in future tumors

Vaccination of patients against mostly patient-specific neoantigens expressed in concurrent and recurring tumors, or tumors developing in individuals at high risk of cancer, is posing major challenges in terms of which antigens to target and is limited to a subset of patients expressing neoantigens in their tumors. Here we describe a broadly applicable vaccination strategy against shared antigens that are experimentally induced in tumor cells by downregulation of the peptide transporter TAP. Presentation of the new epitopes in tumor cells is achieved using a siRNA to downregulate TAP mRNA, which is targeted to tumor cells in situ by conjugation to a broad-range nucleolin binding oligonucleotide aptamer ligand. An immune response against the TAP downregulation-induced antigens presented by the tumor cells is elicited by downregulation of TAP in resident dendritic cells via conjugation to a CpG oligonucleotide. Vaccination against experimentally induced antigens is particularly suitable for vaccination against tumors that recur after a long period of remission, or tumors that will develop in individuals at high risk of cancer, because it eliminates the uncertainties of which neoantigens are expressed in the future tumors. Vaccination against the TAP downregulation-induced antigens was more effective than vaccination against tumor-resident, mutation-generated, shared neoantigens, was devoid of measurable toxicity, and inhibited the growth of future tumors in models of recurrence and premalignant disease. Human CD8+ T cells stimulated with TAPlow dendritic cells elicited a polyclonal CD8+ T-cell response that recognized tumor cells with experimentally reduced TAP expression, as well as CMV and EBV infected cells that naturally downregulate TAP expression. Vaccination against TAP downregulation-induced antigens overcomes the main limitations of vaccinating against mostly unique tumor-resident neoantigens and could represent a common vaccination strategy for patients with concurrent, recurrent, and future tumors.

Citation Format: Greta Garrido, Brett Schrand, Agata Levay, Ailem Rabasa, Anthony Ferrantella, Diane Da Silva, Francesca D’Eramo, Koen Marijt, Lisa Daley-Bauer, Deukwoo Kwon, Martin Kast, Ed Mocarski, Vikas Dudeja, Thorbald van Hall, Eli Gilboa. Prorapeutic vaccination against shared antigens induced in future tumors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr B26.

Inhibition of Langerhans cell maturation by human papillomavirus type 16: a novel role for the annexin A2 heterotetramer in immune suppression (VIR1P.961)

Human papillomaviruses (HPV) are associated with several cancers. During its life cycle HPV16 infects the epithelial basal cells through a receptor we recently identified, the annexin A2 heterotetramer (A2t). During infection, HPV16 also interacts with Langerhans cells (LC), the antigen presenting cells of the epithelium, and induces immune suppression mediated by the HPV16 L2 minor capsid protein. Despite the importance of these virus-immune cell interactions, the specific mechanisms of HPV16 entry into LC and HPV16-induced immune suppression remain undefined. An N-terminal peptide of HPV16 L2 has been shown to specifically interact with A2t. Here, we show that incubation of human LC with this peptide blocks binding of HPV16. Inhibiting this interaction with an A2t ligand or by siRNA down-regulation of A2t, significantly decreases HPV16 internalization into LC in an L2-dependent manner. A2t is associated with inhibition of LC maturation as demonstrated through attenuated secretion of Th1-associated cytokines and decreased surface expression of MHC II on LC exposed to A2t. Conversely, small molecule inhibition of A2t prevents HPV16-induced inhibition of LC immune function as indicated by increased secretion of inflammatory cytokines and surface expression of MHC II and CD86 in HPV16 treated LC pre-exposed to A2t inhibitors. These results demonstrate that HPV16 suppresses LC maturation through an interaction with A2t, revealing a novel immune suppressive role for this protein.

HPV status in relation to clinicopathologic variables in patients with penile cancer at Los Angeles County-USC Medical Center

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Background: Penile squamous cell carcinoma (PSCC) is a disfiguring and deadly disease. US cancer registry reports a higher incidence in certain minority communities including those over-represented at LAC-USC. Human papilloma virus (HPV) infection is strongly associated with PSCC. This study examined correlations of HPV presence and subtype with PSCC patient clinicopathological variables.

Methods: After IRB approval, a retrospective review of PSCC patients at LAC-USC between 1996-2010 was completed. HPV presence and genotype was detected from primary tumors of 33 patients by DNA amplification followed by reverse line blot hybridization. Associations with patient and tumor characteristics were examined by contingency analyses.

Results: 20 (60.6%) patients were HPV+, and 85% of all HPV+ cases harbored at least one high-risk viral strain (80% of all positive cases had HPV 16, 5% HPV 31, 10% HPV 66). 20% of all positive cases harbored low-risk HPV 11; HPV strains 6 or 35 were not detected in any specimen. 3 patients were positive for multiple strains. Overall median age at diagnosis was 53 (range: 24-77) yrs. Median age was 56 yrs and 49 yrs for HPV+ and HPV- patients, respectively. HPV infection showed a trend towards being more prevalent in patients beyond the fifth decade of life, although this did not reach statistical significance (p=0.10). 22 (66.7%) patients were Hispanic; this ethnicity comprised 60% and 77% of HPV+ and HPV- cases, respectively (p=0.31). This cohort included Stage 0 (n= 1, n= 0), Stage 1 (n= 4, n=2), Stage 2 (n= 4, n= 4), Stage 3 (n=5, n= 1), and Stage 4 (n= 4, n= 5) HPV+ and HPV- patients, respectively. Neither HPV status nor presence of nodal metastasis was significantly associated with stage (p=0.50, p=0.52 respectively). Tumor grade was available for 30 (90.9%) cases; while HPV+ cases tended to have higher proportion of moderately-poorly differentiated tumors than HPV- cases (77.8% vs. 58.3%), this was not statistically significant (p=0.32).

Conclusions: An overwhelming majority of HPV+ cases harbored at least one high-risk viral strain. Several interesting associations of HPV status with age and grade were noted, although the study was underpowered to show significance.

Reversal of human papillomavirus-mediated suppression of Langerhans cells function with the TLR3 agonist Poly-ICR (53.7)

The human papillomavirus (HPV) family of viruses establishes persistent infections because it has evolved mechanisms that allow it to evade the human immune system. We have identified HPV-mediated suppression of antigen presentation by Langerhans cells (LC) as a key mechanism through which HPV evades immune surveillance. PolyICR is a stable TLR3 agonist that is a broad inducer of innate immunity and is being developed as a vaccine adjuvant and antitumor agent. An important feature of PolyICR is its ability to functionally activate dendritic cells to induce antigen-specific T cells. In this study, we determined whether PolyICR can overcome HPV-induced immune suppression by functionally activating human LC in the presence of HPV16 and inducing HPV16-specific T cells. PolyICR was able to activate LC that had been pre-exposed to HPV16 VLP such that expression of MHC and costimulatory molecules were highly upregulated and LC secreted high amounts of Th1 and inflammatory cytokines and chemokines. Upregulation of CCR7 resulted in a significant increase in migration capacity. LC incubated with HPV16 VLP and treated with PolyICR induced an HPV16-specific CD8+ T cell response detected by interferon gamma Elispot that was absent when LC were exposed to VLP alone. These data suggest that the TLR3 agonist PolyICR is a promising therapeutic molecule that can overcome HPV-induced immune suppression of LC and result in an LC capable of stimulating an anti-HPV T-cell mediated immune response.

LIGHT expression in prostate cancer inhibits tumor growth and induces prostate antigen-specific immunity (156.2)

An immunosuppressive tumor microenvironment has always been a hurdle for successful immunotherapy even in the presence of induced tumor-specific T cells. Regulatory T cells (Tregs) appear to be key regulators in local immune suppression. LIGHT, a ligand for lymphotoxin-β receptor (LTβR), is predominantly expressed on activated immune cells, signaling via LTβR is required for the formation of organized lymphoid tissues. Forced expression of LIGHT recruits naive T cells into tumors and is capable of establishing tumor specific immunity. However this has never been tested in prostate cancer models where tolerance to self-antigen likely exists. Here we test the hypothesis that forced expression of LIGHT in prostate tumors induces prostate cancer-specific immunity and results in tumor regression by altering the suppressive activity of Tregs and consequently enhancing a more persistent proinflammatory microenvironment. Our data show that intratumoral expression of LIGHT via adenovirus delivery in TRAMP-C2 tumor challenged mice develop de novo CD8+ IFNγ-secreting prostate antigen-specific T cells and display increased survival compared to control treated mice. LIGHT-treated mice also display an increase in ratio of tumor infiltrating lymphocytes to Tregs as well as decrease in Treg suppression activity. Our data suggest that LIGHT treatment can alter the microenvironment such that natural and vaccine-induced prostate tumor antigen specific T cells mediate tumor regression.