Molecular signatures associated with tumor-specific immune response in melanoma patients treated with dendritic cell-based immunotherapy

Long-Term Survival and Immune Response Dynamics in Melanoma Patients Undergoing TAPCells-Based Vaccination Therapy

Cancer vaccines present a promising avenue for treating immune checkpoint blockers (ICBs)-refractory patients, fostering immune responses to modulate the tumor microenvironment. We revisit a phase I/II trial using Tumor Antigen-Presenting Cells (TAPCells) (NCT06152367), an autologous antigen-presenting cell vaccine loaded with heat-shocked allogeneic melanoma cell lysates. Initial findings showcased TAPCells inducing lysate-specific delayed-type hypersensitivity (DTH) reactions, correlating with prolonged survival. Here, we extend our analysis over 15 years, categorizing patients into short-term (<36 months) and long-term (≥36 months) survivors, exploring novel associations between clinical outcomes and demographic, genetic, and immunologic parameters. Notably, DTHpos patients exhibit a 53.1% three-year survival compared to 16.1% in DTHneg patients. Extended remissions are observed in long-term survivors, particularly DTHpos/M1cneg patients. Younger age, stage III disease, and moderate immune events also benefit short-term survivors. Immunomarkers like increased C-type lectin domain family 2 member D on CD4+ T cells and elevated interleukin-17A were detected in long-term survivors. In contrast, toll-like receptor-4 D229G polymorphism and reduced CD32 on B cells are associated with reduced survival. TAPCells achieved stable long remissions in 35.2% of patients, especially M1cneg/DTHpos cases. Conclusions: Our study underscores the potential of vaccine-induced immune responses in melanoma, emphasizing the identification of emerging biological markers and clinical parameters for predicting long-term remission.

Prognostic and immunological role of cancer-associated fibroblasts-derived exosomal protein in esophageal squamous cell carcinoma

BACKGROUND

Cancer-associated fibroblasts (CAFs) are a crucial component of the tumor microenvironment (TME) and play significant roles in tumor initiation, progression, and immune evasion. Despite this, the specific exosomal proteins derived from CAFs and their functions in esophageal squamous cell carcinoma (ESCC) remain unknown. Therefore, this study aims to investigate the impact and prognostic significance of CAFs-derived exosomal proteins in ESCC.

MATERIALS AND METHODS

Exosomes obtained from CAFs and normal fibroblasts (NFs) were isolated using ultracentrifugation, and the protein expression profiles of the exosomes were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Tumor proliferation was assessed using CCK-8 and colony formation assays, while cell invasion and migration were evaluated using transwell assays. Lasso regression analysis was employed to establish a signature based on CAFs-derived exosomal proteins using the TCGA database. The immunological and prognostic roles of this signature were comprehensively investigated through survival analysis, gene set enrichment analysis (GSEA), immune analysis, immunotherapy response analysis, and drug sensitivity analysis. The GSE160269 dataset was utilized for single-cell transcriptome analysis to further elucidate the role of the signature in the TME. Additionally, cDNA microarray analysis was utilized to validate the prognostic value of the signature.

RESULTS

Our findings demonstrate that exosomes derived from CAFs significantly enhance the proliferation, invasion, and migration of esophageal cancer cells. We identified 842 differentially expressed exosomal proteins through LC-MS/MS analysis, and two key proteins were utilized to establish a risk signature. Survival analysis revealed a significantly worse prognosis in the high-risk group, with multivariate analysis indicating that the risk score serves as an independent prognostic factor. Moreover, we observed a significant correlation between the risk score and immune cell infiltration, immunotherapy response, and sensitivity to chemotherapeutic treatments in the study population. Lastly, single-cell transcriptome analysis further revealed the expression patterns of TNFRSF10B and ILF3 in different cell subpopulations.

CONCLUSION

In conclusion, our study has successfully established a robust prognostic signature based on CAFs-derived exosomal proteins, which can serve as a reliable biomarker for predicting prognosis and evaluating the immune microenvironment in ESCC.

Advances in dendritic cell vaccination therapy of cancer

Traditionally, vaccines have helped eradication of several infectious diseases and also saved millions of lives in the human history. Those prophylactic vaccines have acted through inducing immune responses against a live attenuated, killed organism or antigenic subunits to protect the recipient against a real infection caused by the pathogenic microorganism. Nevertheless, development of anticancer vaccines as valuable targets in human health has faced challenges and requires further optimizations. Dendritic cells (DCs) are the most potent antigen presenting cells (APCs) that play essential roles in tumor immunotherapies through induction of CD8+ T cell immunity. Accordingly, various strategies have been tested to employ DCs as therapeutic vaccines for exploiting their activity against tumor cells. Application of whole tumor cells or purified/recombinant antigen peptides are the most common approaches for pulsing DCs, which then are injected back into the patients. Although some hopeful results are reported for a number of DC vaccines tested in animal and clinical trials of cancer patients, such approaches are still inefficient and require optimization. Failure of DC vaccination is postulated due to immunosuppressive tumor microenvironment (TME), overexpression of checkpoint proteins, suboptimal avidity of tumor-associated antigen (TAA)-specific T lymphocytes, and lack of appropriate adjuvants. In this review, we have an overview of the current experiments and trials evaluated the anticancer efficacy of DC vaccination as well as focusing on strategies to improve their potential including combination therapy with immune checkpoint inhibitors (ICIs).

Immunotherapy discovery on tumor organoid-on-a-chip platforms that recapitulate the tumor microenvironment

Cancer immunotherapy has achieved remarkable success over the past decade by modulating patients' own immune systems and unleashing pre-existing immunity. However, only a minority of cancer patients across different cancer types are able to benefit from immunotherapy treatment; moreover, among those small portions of patients with response, intrinsic and acquired resistance remains a persistent challenge. Because the tumor microenvironment (TME) is well recognized to play a critical role in tumor initiation, progression, metastasis, and the suppression of the immune system and responses to immunotherapy, understanding the interactions between the TME and the immune system is a pivotal step in developing novel and efficient cancer immunotherapies. With unique features such as low reagent consumption, dynamic and precise fluid control, versatile structures and function designs, and 3D cell co-culture, microfluidic tumor organoid-on-a-chip platforms that recapitulate key factors of the TME and the immune contexture have emerged as innovative reliable tools to investigate how tumors regulate their TME to counteract antitumor immunity and the mechanism of tumor resistance to immunotherapy. In this comprehensive review, we focus on recent advances in tumor organoid-on-a-chip platforms for studying the interaction between the TME and the immune system. We first review different factors of the TME that recent microfluidic in vitro systems reproduce to generate advanced tools to imitate the crosstalk between the TME and the immune system. Then, we discuss their applications in the assessment of different immunotherapies' efficacy using tumor organoid-on-a-chip platforms. Finally, we present an overview and the outlook of engineered microfluidic platforms in investigating the interactions between cancer and immune systems, and the adoption of patient-on-a-chip models in clinical applications toward personalized immunotherapy.

Machine Learning Analysis of Immune Cells for Diagnosis and Prognosis of Cutaneous Melanoma

Tumor infiltration, known to associate with various cancer initiations and progressions, is a promising therapeutic target for aggressive cutaneous melanoma. Then, the relative infiltration of 24 kinds of immune cells in melanoma was assessed by a single sample gene set enrichment analysis (ssGSEA) program from a public database. The multiple machine learning algorithms were applied to evaluate the efficiency of immune cells in diagnosing and predicting the prognosis of melanoma. In comparison with the expression of immune cell in tumor and normal control, we built the immune diagnostic models in training dataset, which can accurately classify melanoma patients from normal (LR AUC = 0.965, RF AUC = 0.99, SVM AUC = 0.963, LASSO AUC = 0.964, and NNET AUC = 0.989). These diagnostic models were also validated in three outside datasets and suggested over 90% AUC to distinguish melanomas from normal patients. Moreover, we also developed a robust immune cell biomarker that could estimate the prognosis of melanoma. This biomarker was also further validated in internal and external datasets. Following that, we created a nomogram with a composition of risk score and clinical parameters, which had high accuracies in predicting survival over three and five years. The nomogram's decision curve revealed a bigger net benefit than the tumor stage. Furthermore, a risk score system was used to categorize melanoma patients into high- and low-risk subgroups. The high-risk group has a significantly lower life expectancy than the low-risk subgroup. Finally, we observed that complement, epithelial-mesenchymal transition, and inflammatory response were significantly activated in the high-risk group. Therefore, the findings provide new insights for understanding the tumor infiltration relevant to clinical applications as a diagnostic or prognostic biomarker for melanoma.

Genetic association of primary nonresponse to anti-TNFα therapy in patients with inflammatory bowel disease

OBJECTIVES

Primary nonresponse (PNR) to antitumor necrosis factor-α (TNFα) biologics is a serious concern in patients with inflammatory bowel disease (IBD). We aimed to identify the genetic variants associated with PNR.

PATIENTS AND METHODS

Patients were recruited from outpatient GI clinics and PNR was determined using both clinical and endoscopic findings. A case-control genome-wide association study was performed in 589 IBD patients and associations were replicated in an independent cohort of 293 patients. Effect of the associated variant on gene expression and TNFα secretion was assessed by cell-based assays. Pleiotropic effects were investigated by Phenome-wide association study (PheWAS).

RESULTS

We identified rs34767465 as associated with PNR to anti-TNFα therapy (odds ratio: 2.07, 95% CI, 1.46-2.94, P = 2.43 × 10-7, [replication odds ratio: 1.8, 95% CI, 1.04-3.16, P = 0.03]). rs34767465 is a multiple-tissue expression quantitative trait loci for FAM114A2. Using RNA-sequencing and protein quantification from HapMap lymphoblastoid cell lines (LCLs), we found a significant decrease in FAM114A2 mRNA and protein expression in both heterozygous and homozygous genotypes when compared to wild type LCLs. TNFα secretion was significantly higher in THP-1 cells [differentiated into macrophages] with FAM114A2 knockdown versus controls. Immunoblotting experiments showed that depletion of FAM114A2 impaired autophagy-related pathway genes suggesting autophagy-mediated TNFα secretion as a potential mechanism. PheWAS showed rs34767465 was associated with comorbid conditions found in IBD patients (derangement of joints [P = 3.7 × 10-4], pigmentary iris degeneration [P = 5.9 × 10-4], diverticulum of esophagus [P = 7 × 10-4]).

CONCLUSIONS

We identified a variant rs34767465 associated with PNR to anti-TNFα biologics, which increases TNFα secretion through mechanism related to autophagy. rs34767465 may also explain the comorbidities associated with IBD.

A Method for Subtype Analysis with Somatic Mutations

MOTIVATION

Cancer is a highly heterogeneous disease, and virtually all types of cancer have subtypes. Understanding the association between cancers subtypes and genetic variations is fundamental to the development of targeted therapies for patients. Somatic mutation plays important roles in tumor development and has emerged as a new type of genetic variations for studying the association with cancer subtypes. However, the low prevalence of individual mutations poses a tremendous challenge to the related statistical analysis.

RESULTS

In this article, we propose an approach, SASOM, for the association analysis of cancer subtypes with somatic mutations. Our approach tests the association between a set of somatic mutations (from a genetic pathway) and subtypes, while incorporating functional information of the mutations into the analysis. We further propose a robust p-value combination procedure, DAPC, to synthesize statistical significance from different sources. Simulation studies show that the proposed approach has correct type I error and tends to be more powerful than possible alternative methods. In a real data application, we examine the somatic mutations from a cutaneous melanoma dataset, and identify a genetic pathway that is associated with immune-related subtypes.

AVAILABILITY AND IMPLEMENTATION

The SASOM R package is available at https://github.com/rksyouyou/SASOM-pkg. R scripts and data are available at https://github.com/rksyouyou/SASOM-analysis.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Personalized Dendritic Cell Vaccines-Recent Breakthroughs and Encouraging Clinical Results

With the advent of combined immunotherapies, personalized dendritic cell (DC)-based vaccination could integrate the current standard of care for the treatment of a large variety of tumors. Due to their proficiency at antigen presentation, DC are key coordinators of the innate and adaptive immune system, and have critical roles in the induction of antitumor immunity. However, despite proven immunogenicity and favorable safety profiles, DC-based immunotherapies have not succeeded at inducing significant objective clinical responses. Emerging data suggest that the combination of DC-based vaccination with other cancer therapies may fully unleash the potential of DC-based cancer vaccines and improve patient survival. In this review, we discuss the recent efforts to develop innovative personalized DC-based vaccines and their use in combined therapies, with a particular focus on ovarian cancer and the promising results of mutanome-based personalized immunotherapies.

Ex Vivo Tumor-on-a-Chip Platforms to Study Intercellular Interactions within the Tumor Microenvironment

The emergence of immunotherapies and recent FDA approval of several of them makes them a promising therapeutic strategy for cancer. While these advancements underscore the potential of engaging the immune system to target tumors, this approach has so far been efficient only for certain cancers. Extending immunotherapy as a widely acceptable treatment for various cancers requires a deeper understanding of the interactions of tumor cells within the tumor microenvironment (TME). The immune cells are a key component of the TME, which also includes other stromal cells, soluble factors, and extracellular matrix-based cues. While in vivo studies function as a gold standard, tissue-engineered microphysiological tumor models can offer patient-specific insights into cancer-immune interactions. These platforms, which recapitulate cellular and non-cellular components of the TME, enable a systematic understanding of the contribution of each component toward disease progression in isolation and in concert. Microfluidic-based microphysiological platforms recreating these environments, also known as "tumor-on-a-chip," are increasingly being utilized to study the effect of various elements of TME on tumor development. Herein are reviewed advancements in tumor-on-a-chip technology that are developed and used to understand the interaction of tumor cells with other surrounding cells, including immune cells, in the TME.