Patterns of Recurrence after Curative Intent Hepatic Resection for Colorectal Liver Metastasis.

BACKGROUND: Improved surgical techniques and more intensive systemic therapy have increased the number of oligometastatic colorectal cancer patients eligible for resection, but a significant percentage of these patients will ultimately recur. Furthermore, distinct recurrence patterns have been associated with different outcomes. METHODS: Data for 195 patients who underwent curative-intent colorectal liver metastasis (CRLM) resection from 2016-2022 at Johns Hopkins Hospital were retrospectively collected. Cox regression univariate and multivariate analysis identified features associated with survival outcomes. Association between risk factors and site of recurrences was conducted via logistic regression with initial recurrences grouped into intrahepatic-only, extrahepatic-only, and concurrent intra- and extrahepatic recurrence. RESULTS: The 1- and 2-year recurrence free survival (RFS) rates were 46% and 22% respectively. The 1- and 2-year overall survival (OS) rates were 95% and 88% respectively. Median OS was 71.7 months. Multivariate analysis identified age <60 years old, N2 nodal status, R1 liver margin, and higher preoperative carcinoembryonic antigen as top prognostic factors for worse RFS. Additionally, patients with left-sided primary tumors had higher risk of intrahepatic-only recurrence while mutant KRAS was associated with higher risk of extrahepatic recurrence with or without liver recurrence. DISCUSSION OR CONCLUSION: These results from a recent cohort of patients treated with current standard of care therapies identifies features associated with elevated recurrence risk and specific recurrence patterns. These insights into CRLM recurrence patterns support a larger prospective study to identify subgroups of patients who may require additional therapies to prevent recurrence.

Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic responders.

Pancreatic adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. We generated a spatial multi-omics atlas encompassing 26 PDAC tumors from patients treated with combination immunotherapies. Using machine learning-enabled H&E image classification models and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within TLS niches spanning across distinct morphologies and immunotherapies. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation in pathological responders, confirmed with spatial proteomics and BCR profiling. Our study also identifies spatial features of pathologic immune responses, revealing TLS maturation colocalizing with IgG/IgA distribution and extracellular matrix remodeling. HIGHLIGHTS: Integrated multi-modal spatial profiling of human PDAC tumors from neoadjuvant immunotherapy clinical trials reveal diverse spatial niches enriched in TLS.TLS maturity is influenced by tumor location and the cellular neighborhoods in which TLS immune cells are recruited.Unsupervised machine learning of genome-wide signatures on spatial transcriptomics data characterizes the TLS-enriched TME and associates TLS transcriptomes with survival outcomes in PDAC.Interactions of spatially variable gene expression patterns showed TLS maturation is coupled with immunoglobulin distribution and ECM remodeling in pathologic responders.Intratumoral plasma cell and immunoglobin gene expression spatial dynamics demonstrate trafficking of TLS-driven humoral immunity in the PDAC TME. Significance: We report a spatial multi-omics atlas of PDAC tumors from a series of immunotherapy neoadjuvant clinical trials. Intratumorally, pathologic responders exhibit mature TLS that propagate plasma cells into malignant niches. Our findings offer insights on the role of TLS-associated humoral immunity and stromal remodeling during immunotherapy treatment.

Sex-dependent effects in the aged melanoma tumor microenvironment influence invasion and resistance to targeted therapy.

There is documented sex disparity in cutaneous melanoma incidence and mortality, increasing disproportionately with age and in the male sex. However, the underlying mechanisms remain unclear. While biological sex differences and inherent immune response variability have been assessed in tumor cells, the role of the tumor-surrounding microenvironment, contextually in aging, has been overlooked. Here, we show that skin fibroblasts undergo age-mediated, sex-dependent changes in their proliferation, senescence, ROS levels, and stress response. We find that aged male fibroblasts selectively drive an invasive, therapy-resistant phenotype in melanoma cells and promote metastasis in aged male mice by increasing AXL expression. Intrinsic aging in male fibroblasts mediated by EZH2 decline increases BMP2 secretion, which in turn drives the slower-cycling, highly invasive, and therapy-resistant melanoma cell phenotype, characteristic of the aged male TME. Inhibition of BMP2 activity blocks the emergence of invasive phenotypes and sensitizes melanoma cells to BRAF/MEK inhibition.

Patient-derived Organoid Pharmacotyping As A Predictive Tool for Therapeutic Selection in Pancreatic Ductal Adenocarcinoma.

OBJECTIVE: We integrate a new approach to chemosensitivity data for clinically-relevant regimen matching, and demonstrate the relationship with clinical outcomes in a large PDO biobank. SUMMARY BACKGROUND DATA: Pancreatic ductal adenocarcinoma (PDAC) usually recurs following potentially curative resection. Prior studies related patient-derived organoid (PDO) chemosensitivity with clinical responses. METHODS: PDOs were established from pre-treatment biopsies in a multi-institution clinical trial (n=21) and clinical specimens at a high-volume pancreatectomy center (n=74, of which 48 were pre-treated). PDO in vitro chemosensitivities to standard-of-care chemotherapeutics (pharmacotypes) were matched to potential clinically-relevant regimens by a weighted nearest-neighbors analysis. Clinical outcomes were then compared for patients who had well-matched versus poorly-matched treatment according to this metric. RESULTS: Our function matched 91% of PDOs to a standard-of-care regimen (9% pan-resistant). PDOs poorly-matched to the neoadjuvant regimen received would have matched to an alternative in 34% of cases. Patients receiving neoadjuvant chemotherapy well-matched to their pharmacotype experienced improved CA 19-9 response (60% decreased to normal when well-matched, 29% when poorly-matched, P<0.05) and lymph node down-staging (33% N0 after poorly-matched, 69% after well-matched, P<0.05). Patients receiving both well-matched neoadjuvant and adjuvant chemotherapy experienced improved recurrence-free- and overall survival (median RFS 8.5 mo poorly-matched, 15.9 mo well-matched, P<0.05; median OS 19.5 vs. 30.3 mo, P<0.05). CONCLUSION: In vitro PDO pharmacotyping can inform PDAC therapy selection. We demonstrate improved outcomes including survival for patients treated with regimens well-matched to their PDO chemosensitivities. A subsequent prospective study using PDO pharmacotype matching could improve oncologic outcomes and improve quality of life by avoiding therapies not expected to be effective.

PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.

This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology.

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

Phosphodiesterase-5 inhibition collaborates with vaccine-based immunotherapy to reprogram myeloid cells in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is highly lethal and resistant to immunotherapy. Although immune recognition can be enhanced with immunomodulatory agents including checkpoint inhibitors and vaccines, few patients experience clinical efficacy because the tumor immune microenvironment (TiME) is dominated by immunosuppressive myeloid cells that impose T cell inhibition. Inhibition of phosphodiesterase-5 (PDE5) was reported to downregulate metabolic regulators arginase and inducible NOS in immunosuppressive myeloid cells and enhance immunity against immune-sensitive tumors, including head and neck cancers. We show for the first time to our knowledge that combining a PDE5 inhibitor, tadalafil, with a mesothelin-specific vaccine, anti-programmed cell death protein 1, and anti-cytotoxic T lymphocyte-associated protein 4 yields antitumor efficacy even against immune-resistant PDAC. To determine immunologic advantages conferred by tadalafil, we profiled the TiME using mass cytometry and single-cell RNA-sequencing analysis with Domino to infer intercellular signaling. Our analyses demonstrated that tadalafil reprograms myeloid cells to be less immunosuppressive. Moreover, tadalafil synergized with the vaccine, enhancing T cell activation including mesothelin-specific T cells. Tadalafil treatment was also associated with myeloid/T cell signaling axes important for antitumor responses (e.g., Cxcr3, Il12). Our study shows that PDE5 inhibition combined with vaccine-based immunotherapy promotes pro-inflammatory states of myeloid cells, activation of T cells, and enhanced myeloid/T cell crosstalk to yield antitumor efficacy against immune-resistant PDAC.

Integration of Clinical Trial Spatial Multiomics Analysis and Virtual Clinical Trials Enables Immunotherapy Response Prediction and Biomarker Discovery.

Due to the lack of treatment options, there remains a need to advance new therapeutics in hepatocellular carcinoma (HCC). The traditional approach moves from initial molecular discovery through animal models to human trials to advance novel systemic therapies that improve treatment outcomes for patients with cancer. Computational methods that simulate tumors mathematically to describe cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico, potentially greatly accelerating delivery of new therapeutics to patients. To facilitate the design of dosing regimens and identification of potential biomarkers for immunotherapy, we developed a new computational model to track tumor progression at the organ scale while capturing the spatial heterogeneity of the tumor in HCC. This computational model of spatial quantitative systems pharmacology was designed to simulate the effects of combination immunotherapy. The model was initiated using literature-derived parameter values and fitted to the specifics of HCC. Model validation was done through comparison with spatial multiomics data from a neoadjuvant HCC clinical trial combining anti-PD1 immunotherapy and a multitargeted tyrosine kinase inhibitor cabozantinib. Validation using spatial proteomics data from imaging mass cytometry demonstrated that closer proximity between CD8 T cells and macrophages correlated with nonresponse. We also compared the model output with Visium spatial transcriptomics profiling of samples from posttreatment tumor resections in the clinical trial and from another independent study of anti-PD1 monotherapy. Spatial transcriptomics data confirmed simulation results, suggesting the importance of spatial patterns of tumor vasculature and TGFß in tumor and immune cell interactions. Our findings demonstrate that incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides a novel approach for patient outcome prediction and biomarker discovery. Significance: Incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides an effective approach for patient outcome prediction and biomarker discovery.

Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade.

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable, but is hindered by the limited performance of existing biomarkers. Here, we leveraged in-silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We tested 90 biomarker candidates, including various cellular and molecular species, by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pre-treatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.

A new Neu-a syngeneic model of spontaneously metastatic HER2-positive breast cancer.

Metastatic disease results from the dissemination of tumor cells beyond their organ of origin to grow in distant organs and is the primary cause of death in patients with advanced breast cancer. Preclinical murine models in which primary tumors spontaneously metastasize are valuable tools for studying metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. The NT2.5-lung metastasis (-LM) cell line was derived from serial passaging of tumor cells that were macro-dissected from spontaneous lung metastases after orthotopic mammary implantation of parental NT2.5 cells. Within one week of NT2.5-LM implantation, metastases are observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. We demonstrate that NT2.5-LM metastases are positive for NeuN-the murine equivalent of human epidermal growth factor 2 (HER2). We further demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT), suggestive of their enhanced metastatic potential. Genomic analyses support these findings and reveal enrichment in EMT-regulating pathways. In addition, the metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. The new NT2.5-LM model provides certain advantages over the parental NT2/NT2.5 model, given its more rapid and spontaneous development of metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses.

Personalized neoantigen vaccine and pembrolizumab in advanced hepatocellular carcinoma: a phase 1/2 trial.

Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor ß-chain (TCRß) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .

Transfer Learning Reveals Cancer-Associated Fibroblasts Are Associated with Epithelial-Mesenchymal Transition and Inflammation in Cancer Cells in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial-mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell-cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation. SIGNIFICANCE: Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.

An orientation to the US National Cancer plan for the research community.

The US National Cancer Act of 1971 designated the director of the National Cancer Institute as responsible for coordinating federal agencies and nonfederal organizations to make progress against cancer. As part of her role, the immediate past director of the National Cancer Institute (MMB) led the development of a National Cancer Plan that was formally released on April 3, 2023. The plan includes 8 aspirational goals "to achieve a society where every person with cancer lives a full and active life and to prevent most cancers so that few people need to face this diagnosis." Research findings provide a foundation for each goal, and research gaps are included in the strategies for meeting each goal. The President's Cancer Panel, also created by the National Cancer Act, conducted an initial assessment of progress toward the plan goals by hearing from 12 organizations at a virtual public meeting on September 7, 2023. The purpose of this commentary is to orient the scientific community to the plan and call attention to related knowledge gaps that could benefit from research.

Mesothelin CAR T Cells Secreting Anti-FAP/Anti-CD3 Molecules Efficiently Target Pancreatic Adenocarcinoma and its Stroma.

PURPOSE: Targeting solid tumors with chimeric antigen receptor (CAR) T cells remains challenging due to heterogenous target antigen expression, antigen escape, and the immunosuppressive tumor microenvironment (TME). Pancreatic cancer is characterized by a thick stroma generated by cancer-associated fibroblasts (CAF), which may contribute to the limited efficacy of mesothelin-directed CAR T cells in early-phase clinical trials. To provide a more favorable TME for CAR T cells to target pancreatic ductal adenocarcinoma (PDAC), we generated T cells with an antimesothelin CAR and a secreted T-cell-engaging molecule (TEAM) that targets CAF through fibroblast activation protein (FAP) and engages T cells through CD3 (termed mesoFAP CAR-TEAM cells). EXPERIMENTAL DESIGN: Using a suite of in vitro, in vivo, and ex vivo patient-derived models containing cancer cells and CAF, we examined the ability of mesoFAP CAR-TEAM cells to target PDAC cells and CAF within the TME. We developed and used patient-derived ex vivo models, including patient-derived organoids with patient-matched CAF and patient-derived organotypic tumor spheroids. RESULTS: We demonstrated specific and significant binding of the TEAM to its respective antigens (CD3 and FAP) when released from mesothelin-targeting CAR T cells, leading to T-cell activation and cytotoxicity of the target cell. MesoFAP CAR-TEAM cells were superior in eliminating PDAC and CAF compared with T cells engineered to target either antigen alone in our ex vivo patient-derived models and in mouse models of PDAC with primary or metastatic liver tumors. CONCLUSIONS: CAR-TEAM cells enable modification of tumor stroma, leading to increased elimination of PDAC tumors. This approach represents a promising treatment option for pancreatic cancer.

Entinostat, nivolumab and ipilimumab for women with advanced HER2-negative breast cancer: a phase Ib trial.

We report the results of 24 women, 50% (N = 12) with hormone receptor-positive breast cancer and 50% (N = 12) with advanced triple-negative breast cancer, treated with entinostat + nivolumab + ipilimumab from the dose escalation (N = 6) and expansion cohort (N = 18) of ETCTN-9844 ( NCT02453620 ). The primary endpoint was safety. Secondary endpoints were overall response rate, clinical benefit rate, progression-free survival and change in tumor CD8:FoxP3 ratio. There were no dose-limiting toxicities. Among evaluable participants (N = 20), the overall response rate was 25% (N = 5), with 40% (N = 4) in triple-negative breast cancer and 10% (N = 1) in hormone receptor-positive breast cancer. The clinical benefit rate was 40% (N = 8), and progression-free survival at 6 months was 50%. Exploratory analyses revealed that changes in myeloid cells may contribute to responses; however, no correlation was noted between changes in CD8:FoxP3 ratio, PD-L1 status and tumor mutational burden and response. These findings support further investigation of this treatment in a phase II trial.

Mimicking the breast metastatic microenvironment: characterization of a novel syngeneic model of HER2+ breast cancer.

Preclinical murine models in which primary tumors spontaneously metastasize to distant organs are valuable tools to study metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line, NT2.5-lung metastasis (-LM), that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. Within one week of orthotopic implantation of NT2.5-LM in NeuN mice, distant metastases can be observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. Metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. We demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT) and enrichment in EMT-regulating pathways, suggestive of their enhanced metastatic potential. The new NT2.5-LM model provides more rapid and spontaneous development of widespread metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses targeting distant visceral metastases.

Neoadjuvant radioimmunotherapy in pancreatic cancer enhances effector T cell infiltration and shortens their distances to tumor cells.

Radiotherapy is hypothesized to have an immune-modulating effect on the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) to sensitize it to anti-PD-1 antibody (a-PD-1) treatment. We collected paired pre- and posttreatment specimens from a clinical trial evaluating combination treatment with GVAX vaccine, a-PD-1, and stereotactic body radiation (SBRT) following chemotherapy for locally advanced PDACs (LAPC). With resected PDACs following different neoadjuvant therapies as comparisons, effector cells in PDACs were found to skew toward a more exhausted status in LAPCs following chemotherapy. The combination of GVAX/a-PD-1/SBRT drives TME to favor antitumor immune response including increased densities of GZMB+CD8+ T cells, TH1, and TH17, which are associated with longer survival, however increases immunosuppressive M2-like tumor-associated macrophages (TAMs). Adding SBRT to GVAX/a-PD-1 shortens the distances from PD-1+CD8+ T cells to tumor cells and to PD-L1+ myeloid cells, which portends prolonged survival. These findings have guided the design of next radioimmunotherapy studies by targeting M2-like TAM in PDACs.

Fibroblasts in the Aged Pancreas Drive Pancreatic Cancer Progression.

Pancreatic cancer is more prevalent in older individuals and often carries a poorer prognosis for them. The relationship between the microenvironment and pancreatic cancer is multifactorial, and age-related changes in nonmalignant cells in the tumor microenvironment may play a key role in promoting cancer aggressiveness. Because fibroblasts have profound impacts on pancreatic cancer progression, we investigated whether age-related changes in pancreatic fibroblasts influence cancer growth and metastasis. Proteomics analysis revealed that aged fibroblasts secrete different factors than young fibroblasts, including increased growth/differentiation factor 15 (GDF-15). Treating young mice with GDF-15 enhanced tumor growth, whereas aged GDF-15 knockout mice showed reduced tumor growth. GDF-15 activated AKT, rendering tumors sensitive to AKT inhibition in an aged but not young microenvironment. These data provide evidence for how aging alters pancreatic fibroblasts and promotes tumor progression, providing potential therapeutic targets and avenues for studying pancreatic cancer while accounting for the effects of aging. SIGNIFICANCE: Aged pancreatic fibroblasts secrete GDF-15 and activate AKT signaling to promote pancreatic cancer growth, highlighting the critical role of aging-mediated changes in the pancreatic cancer microenvironment in driving tumor progression. See related commentary by Isaacson et al., p. 1185.

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.

Systems immunology spanning tumors, lymph nodes, and periphery.

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.