Personalized neoantigen pulsed dendritic cell vaccine for advanced lung cancer

Lung cancer is a leading cause of cancer-related deaths globally. While advancements in targeted therapies and immune checkpoint inhibitors (ICIs) have improved outcomes for some patients with advanced disease, there remains a significant unmet need for effective treatment options, particularly for those who have relapsed after frontline therapies. The immune system's ability to specifically target and eliminate tumors has led to the exploration of several immunotherapeutic strategies including ICIs, adoptive cell therapy (ACT), and cancer vaccines. Neoantigens, tumor-specific antigens derived from somatic mutations, are increasingly recognized as critical targets for these immunotherapies. Studies have demonstrated the effectiveness of neoantigen-targeted TILs in achieving tumor regression. Neoantigen-based RNA or peptide vaccines have shown promise in melanoma and glioblastoma. Dendritic cells (DCs), which act as antigen-presenting cells, are a key focus in cancer vaccine development, as they induce stronger immune responses compared to antigen-adjuvant vaccines. Given the high tumor mutation burden and neoantigen levels in lung cancer, neoantigen-based DC vaccines present a promising therapeutic strategy. This study aimed to evaluate the safety and efficacy of a personalized neoantigen peptide-pulsed autologous DC vaccine (Neo-DCVac) in patients with advanced lung cancer, addressing the lack of prospective clinical trials focusing on this approach for lung cancer.

The introduction thoroughly reviews the existing literature on lung cancer treatment, highlighting the limitations of current therapies and the growing interest in immunotherapeutic approaches. It specifically cites several studies demonstrating the potential of neoantigens as immunotherapy targets and the effectiveness of DC-based vaccines in other cancer types. The review emphasizes the lack of clinical trials using neoantigen-based DC vaccines for lung cancer, establishing the rationale for the current study.

This study employed a single-arm, multicenter, pilot study design. Eighteen patients with relapsed advanced lung cancer were initially recruited; however, five were excluded due to insufficient actionable neoepitopes, HLA heterogeneity loss, or rapid tumor progression. The remaining 12 patients underwent whole-exome sequencing (WES) and RNA sequencing of tumor and blood samples to identify neoantigens. A median of 312 somatic nonsynonymous mutations were identified per patient. HLA haplotypes were determined to predict neoantigens. Following stringent filtering criteria (strong MHC binding affinity, high tumor variant allele fraction, expression in RNA-seq), 13-30 peptide-based neoantigens were selected for each patient. Autologous DCs were generated from peripheral blood mononuclear cells (PBMCs), pulsed with the neoantigens, and matured in vitro. The resulting Neo-DCVac was administered subcutaneously, with pretreatment using cyclophosphamide and subsequent GM-CSF administration. Safety was monitored by assessing adverse events using the NCI Common Terminology Criteria for Adverse Events v4.0. Efficacy was evaluated using RECIST v1.1 criteria after each vaccination cycle. T-cell responses to neoantigens were analyzed using ELISpot assays, flow cytometry for activation markers (CD134, CD137), intracellular cytokine staining (IFN-γ, IL-2, TNF-α, CD107a), and CBA analysis of cytokines. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan-Meier method.

Neo-DCVac manufacturing was feasible for all patients, yielding a median of 1.80 × 10⁸ DCs per patient. All treatment-related adverse events were grade 1-2, with no dose delays or discontinuations. The objective response rate was 25% (3/12 patients achieved partial responses), while the disease control rate was 75% (9/12 patients). Median PFS was 5.5 months, and median OS was 7.9 months. Analysis of T-cell responses showed that post-vaccination PBMCs exhibited stronger responses to mutant peptides compared to wild-type peptides in all evaluable patients. In patients with more than 8 T-cell response neoantigens, there was one objective response and five patients achieved disease control. In those with fewer than 8 responses, 50% experienced disease progression. Combination therapy with ICIs showed promising results, with all four patients achieving disease control and tumor size reduction. Case studies of individual patients provided detailed clinical and immune response data, demonstrating the successful activation of T cells and antitumor activity. The number of neoantigens recognized by post-immunization PBMCs seemed to be related to clinical efficacy.

The findings demonstrate the feasibility, safety, and potential efficacy of Neo-DCVac in treating heavily pretreated advanced lung cancer patients. The observed response rates, although from a small pilot study, are encouraging, particularly considering the poor prognosis of the patient population. The successful elicitation of specific T-cell responses against neoantigens supports the rationale for this approach. The apparent correlation between the number of neoantigens recognized and clinical outcome warrants further investigation with a larger cohort. The synergistic effect observed with ICIs suggests a potential benefit of combination therapy. Limitations of bioinformatics neoantigen prediction and the need for improved screening methods are acknowledged. Further research with larger sample sizes is needed to validate these findings and optimize the vaccine strategy.

This pilot study provides initial evidence for the safety and efficacy of a personalized neoantigen-pulsed dendritic cell vaccine in advanced lung cancer. The observed response rates, and particularly the evidence of synergy with immune checkpoint inhibitors, justify further investigation in larger, controlled clinical trials. Improving neoantigen prediction and optimizing vaccine design are crucial for enhancing the therapeutic potential of this approach.

The primary limitation is the small sample size of this pilot study, which restricts the statistical power and generalizability of the findings. The study's single-arm design prevents direct comparison with other treatment strategies. The reliance on in silico neoantigen prediction introduces uncertainty, and the potential impact of this on the results is acknowledged. The analysis of T-cell responses was also limited to a subset of patients. Further studies are needed to validate these findings and address these limitations.