CD4 T cell-activating neoantigens enhance personalized cancer vaccine efficacy.

Personalized cancer vaccines aim to activate and expand cytotoxic antitumor CD8+ T cells to recognize and kill tumor cells. However, the role of CD4+ T cell activation in the clinical benefit of these vaccines is not well defined. We previously established a personalized neoantigen vaccine (PancVAX) for the pancreatic cancer cell line Panc02, which activates tumor-specific CD8+ T cells but required combinatorial checkpoint modulators to achieve therapeutic efficacy. To determine the effects of neoantigen-specific CD4+ T cell activation, we generated a vaccine (PancVAX2) targeting both major histocompatibility complex class I- (MHCI-) and MHCII-specific neoantigens. Tumor-bearing mice vaccinated with PancVAX2 had significantly improved control of tumor growth and long-term survival benefit without concurrent administration of checkpoint inhibitors. PancVAX2 significantly enhanced priming and recruitment of neoantigen-specific CD8+ T cells into the tumor with lower PD-1 expression after reactivation compared with the CD8+ vaccine alone. Vaccine-induced neoantigen-specific Th1 CD4+ T cells in the tumor were associated with decreased Tregs. Consistent with this, PancVAX2 was associated with more proimmune myeloid-derived suppressor cells and M1-like macrophages in the tumor, demonstrating a less immunosuppressive tumor microenvironment. This study demonstrates the biological importance of prioritizing and including CD4+ T cell-specific neoantigens for personalized cancer vaccine modalities.

Immune landscape of tertiary lymphoid structures in hepatocellular carcinoma (HCC) treated with neoadjuvant immune checkpoint blockade.

Neoadjuvant immunotherapy is thought to produce long-term remissions through induction of antitumor immune responses before removal of the primary tumor. Tertiary lymphoid structures (TLS), germinal center-like structures that can arise within tumors, may contribute to the establishment of immunological memory in this setting, but understanding of their role remains limited. Here, we investigated the contribution of TLS to antitumor immunity in hepatocellular carcinoma (HCC) treated with neoadjuvant immunotherapy. We found that neoadjuvant immunotherapy induced the formation of TLS, which were associated with superior pathologic response, improved relapse free survival, and expansion of the intratumoral T and B cell repertoire. While TLS in viable tumor displayed a highly active mature morphology, in areas of tumor regression we identified an involuted TLS morphology, which was characterized by dispersion of the B cell follicle and persistence of a T cell zone enriched for ongoing antigen presentation and T cell-mature dendritic cell interactions. Involuted TLS showed increased expression of T cell memory markers and expansion of CD8+ cytotoxic and tissue resident memory clonotypes. Collectively, these data reveal the circumstances of TLS dissolution and suggest a functional role for late-stage TLS as sites of T cell memory formation after elimination of viable tumor.

Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.

Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.

Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses.

Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.

Converging on a Cure: The Roads to Predictive Immunotherapy.

SUMMARY: Convergence science teams integrating clinical, biological, engineering, and computational expertise are inventing new forecast systems to monitor and predict evolutionary changes in tumor and immune interactions during early cancer progression and therapeutic response. The resulting methods should inform a new predictive medicine paradigm to select adaptive immunotherapeutic regimens personalized to patients' tumors at a given time during their cancer progression for durable patient response.

Worth a Pound of Cure? Emerging Strategies and Challenges in Cancer Immunoprevention.

Cancer immunoprevention applies immunologic approaches such as vaccines to prevent, rather than to treat or cure, cancer. Despite limited success in the treatment of advanced disease, the development of cancer vaccines to intercept premalignant states is a promising area of current research. These efforts are supported by the rationale that vaccination in the premalignant setting is less susceptible to mechanisms of immune evasion compared with established cancer. Prophylactic vaccines have already been developed for a minority of cancers mediated by oncogenic viruses (e.g., hepatitis B and human papillomavirus). Extending the use of preventive vaccines to non-virally driven malignancies remains an unmet need to address the rising global burden of cancer. This review provides a broad overview of clinical trials in cancer immunoprevention with an emphasis on emerging vaccine targets and delivery platforms, translational challenges, and future directions.

A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy.

Tumor mutational burden (TMB), a surrogate for tumor neoepitope burden, is used as a pan-tumor biomarker to identify patients who may benefit from anti-program cell death 1 (PD1) immunotherapy, but it is an imperfect biomarker. Multiple additional genomic characteristics are associated with anti-PD1 responses, but the combined predictive value of these features and the added informativeness of each respective feature remains unknown. We evaluated whether machine learning (ML) approaches using proposed determinants of anti-PD1 response derived from whole exome sequencing (WES) could improve prediction of anti-PD1 responders over TMB alone. Random forest classifiers were trained on publicly available anti-PD1 data (n = 104), and subsequently tested on an independent anti-PD1 cohort (n = 69). Both the training and test datasets included a range of cancer types such as non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), melanoma, and smaller numbers of patients from other tumor types. Features used include summaries such as TMB and number of frameshift mutations, as well as more gene-level features such as counts of mutations associated with immune checkpoint response and resistance. Both ML algorithms demonstrated area under the receiver-operator curves (AUC) that exceeded TMB alone (AUC 0.63 "human-guided," 0.64 "cluster," and 0.58 TMB alone). Mutations within oncogenes disproportionately modulate anti-PD1 responses relative to their overall contribution to tumor neoepitope burden. The use of a ML algorithm evaluating multiple proposed genomic determinants of anti-PD1 responses modestly improves performance over TMB alone, highlighting the need to integrate other biomarkers to further improve model performance.

FSH-blocking therapeutic for osteoporosis.

Pharmacological and genetic studies over the past decade have established the follicle-stimulating hormone (FSH) as an actionable target for diseases affecting millions, namely osteoporosis, obesity, and Alzheimer's disease. Blocking FSH action prevents bone loss, fat gain, and neurodegeneration in mice. We recently developed a first-in-class, humanized, epitope-specific FSH-blocking antibody, MS-Hu6, with a KD of 7.52 nM. Using a Good Laboratory Practice (GLP)-compliant platform, we now report the efficacy of MS-Hu6 in preventing and treating osteoporosis in mice and parameters of acute safety in monkeys. Biodistribution studies using 89Zr-labeled, biotinylated or unconjugated MS-Hu6 in mice and monkeys showed localization to bone and bone marrow. The MS-Hu6 displayed a ß phase t½ of 7.5 days (180 hr) in humanized Tg32 mice. We tested 217 variations of excipients using the protein thermal shift assay to generate a final formulation that rendered MS-Hu6 stable in solution upon freeze-thaw and at different temperatures, with minimal aggregation, and without self-, cross-, or hydrophobic interactions or appreciable binding to relevant human antigens. The MS-Hu6 showed the same level of "humanness" as human IgG1 in silico and was non-immunogenic in ELISpot assays for IL-2 and IFN-γ in human peripheral blood mononuclear cell cultures. We conclude that MS-Hu6 is efficacious, durable, and manufacturable, and is therefore poised for future human testing.

Cancer vaccines.

Given the renewed interest in vaccine development sparked by the COVID-19 pandemic, we are revisiting the current state of vaccine development for cancer prevention and treatment. Experts discuss different vaccine types, their antigens and modes of action, and where we stand on their clinical development, plus the challenges we need to overcome for their broad implementation.

Messenger RNA vaccines for cancer immunotherapy: progress promotes promise.

The COVID-19 pandemic has elevated mRNA vaccines to global recognition due to their unprecedented success rate in protecting against a deadly virus. This international success is underscored by the remarkable versatility, favorable immunogenicity, and overall safety of the mRNA platform in diverse populations. Although mRNA vaccines have been studied in preclinical models and patients with cancer for almost three decades, development has been slow. The recent technological advances responsible for the COVID-19 vaccines have potential implications for successfully adapting this vaccine platform for cancer therapeutics. Here we discuss the lessons learned along with the chemical, biologic, and immunologic adaptations needed to optimize mRNA technology to successfully treat cancers.

Implantation of a neoantigen-targeted hydrogel vaccine prevents recurrence of pancreatic adenocarcinoma after incomplete resection.

Tumor involvement of major vascular structures limits surgical options in pancreatic adenocarcinoma (PDAC), which in turn limits opportunities for cure. Despite advances in locoregional approaches, there is currently no role for incomplete resection. This study evaluated a gelatinized neoantigen-targeted vaccine applied to a grossly positive resection margin in preventing local recurrence. Incomplete surgical resection was performed in mice bearing syngeneic flank Panc02 tumors, leaving a 1 mm rim adherent to the muscle bed. A previously validated vaccine consisting of neoantigen peptides, a stimulator of interferon genes (STING) agonist and AddaVaxTM (termed PancVax) was embedded in a hyaluronic acid hydrogel and applied to the tumor bed. Tumor remnants, regional lymph nodes, and spleens were analyzed using histology, flow cytometry, gene expression profiling, and ELISPOT assays. The immune microenvironment at the tumor margin after surgery alone was characterized by a transient influx of myeloid-derived suppressor cells (MDSCs), prolonged neutrophil influx, and near complete loss of cytotoxic T cells. Application of PancVax gel was associated with enhanced T cell activation in the draining lymph node and expansion of neoantigen-specific T cells in the spleen. Mice implanted with PancVax gel demonstrated no evidence of residual tumor at two weeks postoperatively and healed incisions at two months postoperatively without local recurrence. In summary, application of PancVax gel at a grossly positive tumor margin led to systemic expansion of neoantigen-specific T cells and effectively prevented local recurrence. These findings support further work into locoregional adjuncts to immune modulation in PDAC.

Transfer learning between preclinical models and human tumors identifies a conserved NK cell activation signature in anti-CTLA-4 responsive tumors.

BACKGROUND: Tumor response to therapy is affected by both the cell types and the cell states present in the tumor microenvironment. This is true for many cancer treatments, including immune checkpoint inhibitors (ICIs). While it is well-established that ICIs promote T cell activation, their broader impact on other intratumoral immune cells is unclear; this information is needed to identify new mechanisms of action and improve ICI efficacy. Many preclinical studies have begun using single-cell analysis to delineate therapeutic responses in individual immune cell types within tumors. One major limitation to this approach is that therapeutic mechanisms identified in preclinical models have failed to fully translate to human disease, restraining efforts to improve ICI efficacy in translational research. METHOD: We previously developed a computational transfer learning approach called projectR to identify shared biology between independent high-throughput single-cell RNA-sequencing (scRNA-seq) datasets. In the present study, we test this algorithm's ability to identify conserved and clinically relevant transcriptional changes in complex tumor scRNA-seq data and expand its application to the comparison of scRNA-seq datasets with additional data types such as bulk RNA-seq and mass cytometry. RESULTS: We found a conserved signature of NK cell activation in anti-CTLA-4 responsive mouse and human tumors. In human metastatic melanoma, we found that the NK cell activation signature associates with longer overall survival and is predictive of anti-CTLA-4 (ipilimumab) response. Additional molecular approaches to confirm the computational findings demonstrated that human NK cells express CTLA-4 and bind anti-CTLA-4 antibodies independent of the antibody binding receptor (FcR) and that similar to T cells, CTLA-4 expression by NK cells is modified by cytokine-mediated and target cell-mediated NK cell activation. CONCLUSIONS: These data demonstrate a novel application of our transfer learning approach, which was able to identify cell state transitions conserved in preclinical models and human tumors. This approach can be adapted to explore many questions in cancer therapeutics, enhance translational research, and enable better understanding and treatment of disease.

Evaluating the impact of age on immune checkpoint therapy biomarkers.

Both tumors and aging alter the immune landscape of tissues. These interactions may play an important role in tumor progression among elderly patients and may suggest considerations for patient care. We leverage large-scale genomic and clinical databases to perform comprehensive comparative analysis of molecular and cellular markers of immune checkpoint blockade (ICB) response with patient age. These analyses demonstrate that aging is associated with increased tumor mutational burden, increased expression and decreased promoter methylation of immune checkpoint genes, and increased interferon gamma signaling in older patients in many cancer types studied, all of which are expected to promote ICB efficacy. Concurrently, we observe age-related alterations that might be expected to reduce ICB efficacy, such as decreases in T cell receptor diversity. Altogether, these changes suggest the capacity for robust ICB response in many older patients, which may warrant large-scale prospective study on ICB therapies among patients of advanced age.

Systemic inhibition of PTPN22 augments anticancer immunity.

Both epidemiologic and cellular studies in the context of autoimmune diseases have established that protein tyrosine phosphatase non-receptor type 22 (PTPN22) is a key regulator of T cell receptor (TCR) signaling. However, its mechanism of action in tumors and its translatability as a target for cancer immunotherapy have not been established. Here we show that a germline variant of PTPN22, rs2476601, portended a lower likelihood of cancer in patients. PTPN22 expression was also associated with markers of immune regulation in multiple cancer types. In mice, lack of PTPN22 augmented antitumor activity with greater infiltration and activation of macrophages, natural killer (NK) cells, and T cells. Notably, we generated a novel small molecule inhibitor of PTPN22, named L-1, that phenocopied the antitumor effects seen in genotypic PTPN22 knockout. PTPN22 inhibition promoted activation of CD8+ T cells and macrophage subpopulations toward MHC-II expressing M1-like phenotypes, both of which were necessary for successful antitumor efficacy. Increased PD1-PDL1 axis in the setting of PTPN22 inhibition could be further leveraged with PD1 inhibition to augment antitumor effects. Similarly, cancer patients with the rs2476601 variant responded significantly better to checkpoint inhibitor immunotherapy. Our findings suggest that PTPN22 is a druggable systemic target for cancer immunotherapy.

Multi-omic profiling of lung and liver tumor microenvironments of metastatic pancreatic cancer reveals site-specific immune regulatory pathways.

BACKGROUND: The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed at the metastatic stage, and standard therapies have limited activity with a dismal 5-year survival rate of only 8%. The liver and lung are the most common sites of PDAC metastasis, and each have been differentially associated with prognoses and responses to systemic therapies. A deeper understanding of the molecular and cellular landscape within the tumor microenvironment (TME) metastasis at these different sites is critical to informing future therapeutic strategies against metastatic PDAC. RESULTS: By leveraging combined mass cytometry, immunohistochemistry, and RNA sequencing, we identify key regulatory pathways that distinguish the liver and lung TMEs in a preclinical mouse model of metastatic PDAC. We demonstrate that the lung TME generally exhibits higher levels of immune infiltration, immune activation, and pro-immune signaling pathways, whereas multiple immune-suppressive pathways are emphasized in the liver TME. We then perform further validation of these preclinical findings in paired human lung and liver metastatic samples using immunohistochemistry from PDAC rapid autopsy specimens. Finally, in silico validation with transfer learning between our mouse model and TCGA datasets further demonstrates that many of the site-associated features are detectable even in the context of different primary tumors. CONCLUSIONS: Determining the distinctive immune-suppressive features in multiple liver and lung TME datasets provides further insight into the tissue specificity of molecular and cellular pathways, suggesting a potential mechanism underlying the discordant clinical responses that are often observed in metastatic diseases.

Can Personalized Neoantigens Raise the T Cell Bar?

Ott et al. report the results of a phase 1B study in which a personalized neoantigen vaccine was combined with programmed death receptor-1 blockade in patients with advanced cancers. The study provides a framework for combinatorial vaccine therapies that could mount robust T cell responses, enhance tumor killing, and provide clinical benefit.

Role of in silico structural modeling in predicting immunogenic neoepitopes for cancer vaccine development.

In prior studies, we delineated the landscape of neoantigens arising from nonsynonymous point mutations in a murine pancreatic cancer model, Panc02. We developed a peptide vaccine by targeting neoantigens predicted using a pipeline that incorporates the MHC binding algorithm NetMHC. The vaccine, when combined with immune checkpoint modulators, elicited a robust neoepitope-specific antitumor immune response and led to tumor clearance. However, only a small fraction of the predicted neoepitopes induced T cell immunity, similarly to that reported for neoantigen vaccines tested in clinical studies. While these studies have used binding affinities to MHC I as surrogates for T cell immunity, this approach does not include spatial information on the mutated residue that is crucial for TCR activation. Here, we investigate conformational alterations in and around the MHC binding groove induced by selected minimal neoepitopes, and we examine the influence of a given mutated residue as a function of its spatial position. We found that structural parameters, including the solvent-accessible surface area (SASA) of the neoepitope and the position and spatial configuration of the mutated residue within the sequence, can be used to improve the prediction of immunogenic neoepitopes for inclusion in cancer vaccines.

Metastatic Pancreatic Cancer: ASCO Guideline Update.

PURPOSE: The aim of this work was to provide an update to the ASCO guideline on metastatic pancreatic cancer pertaining to recommendations for therapy options after first-line treatment. METHODS: ASCO convened an Expert Panel and conducted a systematic review to update guideline recommendations for second-line therapy for metastatic pancreatic cancer. RESULTS: One randomized controlled trial of olaparib versus placebo, one report on phase I and II studies of larotrectinib, and one report on phase I and II studies of entrectinib met the inclusion criteria and inform the guideline update. RECOMMENDATIONS: New or updated recommendations for germline and somatic testing for microsatellite instability high/mismatch repair deficiency, BRCA mutations, and TRK alterations are provided for all treatment-eligible patients to select patients for recommended therapies, including pembrolizumab, olaparib, larotrectinib, or entrectinib, or potential clinical trials. The Expert Panel continues to endorse the remaining recommendations for second-line chemotherapy, as well as other recommendations related to treatment, follow-up, and palliative care from the 2018 version of this guideline. Additional information is available at www.asco.org/gastrointestinal-cancer-guidelines.