Phase I/II clinical trial of a helper peptide vaccine plus PD-1 blockade in PD-1 antibody-naïve and PD-1 antibody-experienced patients with melanoma (MEL64)

Recent advances in immunotherapy and its combination therapies for advanced melanoma: a review

The incidence of melanoma is increasing year by year and is highly malignant, with a poor prognosis. Its treatment has always attracted much attention. Among the more clinically applied immunotherapies are immune checkpoint inhibitors, bispecific antibodies, cancer vaccines, adoptive cell transfer therapy, and oncolytic virotherapy. With the continuous development of technology and trials, in addition to immune monotherapy, combinations of immunotherapy and radiotherapy have shown surprising efficacy. In this article, we review the research progress of immune monotherapy and combination therapy for advanced melanoma, with the aim of providing new ideas for the treatment strategy for advanced melanoma.

Second-generation checkpoint inhibitors and Treg depletion synergize with a mouse cancer vaccine in accordance with tumor microenvironment characterization

BACKGROUND

Despite advances in checkpoint inhibitor (CPI) therapy for cancer treatment, many cancers remain resistant. Tumors deemed "cold" based on lack of T cell infiltration show reduced potential for CPI therapy. Cancer vaccines may overcome the inadequacy of existing T cells by inducing the needed antitumor T cell response to synergize with CPIs and overcome resistance.

METHODS

CT26 and TC1 tumor cells were injected subcutaneously into mice. Mice were treated with combinations of CPIs alone or a cancer vaccine specific to the tumor antigen E7 present in TC1 cells. CPIs for the TC1 model were selected because of immunophenotyping TC1 tumors. Antitumor and protumor immunity, tumor size and survival, sequence and timing of vaccine and CPI administration, and efficacy of treatment in young and aged mice were probed.

RESULTS

While "hot" CT26 tumors are treatable with combinations of second-generation CPIs alone or with anti-TGFβ, "cold" TC1 tumor reduction requires the synergy of a tumor-antigen-specific vaccine in combination with two CPIs, anti-TIGIT and anti-PD-L1, predicted by tumor microenvironment (TME) characterization. The synergistic triple combination delays tumor growth better than any pairwise combination and improves survival in a CD8+T cell-dependent manner. Depletion of CD4+T cells improved the treatment response, and depleting regulatory T cells (Treg) revealed Tregs to be inhibiting the response as also predicted from TME analysis. We found the sequence of CPI and vaccine administration dictates the success of the treatment, and the triple combination administered concurrently induces the highest E7-specific T cell response. Contrary to young mice, in aged mice, the cancer vaccine alone is ineffective, requiring the CPIs to delay tumor growth.

CONCLUSIONS

These findings show how pre-existing or vaccine-mediated de novo T cell responses can both be amplified by and facilitate synergistic CPIs and Treg depletion that together lead to greater survival, and how analysis of the TME can help rationally design combination therapies and precision medicine to enhance clinical response to CPI and cancer vaccine therapy.

Multipeptide vaccines for melanoma in the adjuvant setting: long-term survival outcomes and post-hoc analysis of a randomized phase II trial

The critical roles of CD4+ T cells have been understudied for cancer vaccines. Here we report long-term clinical outcomes of a randomized multicenter phase II clinical trial (NCT00118274), where patients with high-risk melanoma received a multipeptide vaccine targeting CD8+ T cells (12MP) and were randomized to receive either of two vaccines for CD4+ (helper) T cells: 6MHP (6 melanoma-specific helper peptides), or tet (a nonspecific helper peptide from tetanus toxoid). Cyclophosphamide (Cy) pre-treatment was also assessed. Primary outcomes for T cell responses to 12MP, 6MHP, and tet were previously reported, suggesting immunogenicity of both vaccines but that CD8 T cell responses to 12MP were lower when tet was replaced with 6MHP. Here, in post-hoc analyses, we report durable prolongation of overall survival by adding 6MHP instead of tet. That benefit was experienced only by male patients. A favorable interaction of 6MHP and Cy is also suggested. Multivariable Cox regression analysis of the intent-to-treat population identify vaccine arm (12MP + 6MHP+Cy) and patient sex (male) as the two significant predictors of enhanced survival. These findings support the value of adding cognate T cell help to cancer vaccines and also suggest a need to assess the impact of patient sex on immune therapy outcomes.

Neoadjuvant personalized cancer vaccines: the final frontier?

INTRODUCTION

Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review.

AREAS COVERED

The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing.

EXPERT OPINION

Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

Complete response of recurrent perihilar cholangiocarcinoma following sintilimab combined with lenvatinib plus S-1: a case report and review of literature

Perihilar cholangiocarcinoma is a refractory malignancy with an unfavorable prognosis and a high probability of recurrence. Systemic chemotherapy is critical for palliative treatment, but effective therapeutic strategies for perihilar cholangiocarcinoma after first-line chemotherapy failure are scarce. Here, we introduced a sustained benefit following sintilimab combined with lenvatinib plus S-1 in a patient with recurrent perihilar cholangiocarcinoma. A 52-year-old female patient was admitted to our hospital due to yellow skin and sclera, and further radiological examination revealed perihilar cholangiocarcinoma. The patient underwent surgery and histopathological results confirmed moderately differentiated adenocarcinoma with metastatic lymph nodes. Postoperative adjuvant chemotherapy with gemcitabine and S-1 was given. One year after surgery, the patient experienced hepatic recurrence. Then, she received radiofrequency ablation combined with gemcitabine and cisplatin. Unfortunately, radiological assessment revealed progressive disease with multiple liver metastases after treatment. Subsequently, she received sintilimab combined with lenvatinib plus S-1 and the lesions were completely regressed following 14 cycles of combination therapy. The patient recovered well without disease recurrence at the last follow-up. Sintilimab combined with lenvatinib plus S-1 may be an alternative therapeutic option for chemotherapy-refractory perihilar cholangiocarcinoma, and further evaluation in a larger number of patients is needed.

Prediction of survival and immunotherapy response by the combined classifier of G protein-coupled receptors and tumor microenvironment in melanoma

BACKGROUND

Melanoma is the deadliest form of skin tumor, and G protein-coupled receptors (GPCRs) play crucial roles in its carcinogenesis. Furthermore, the tumor microenvironment (TME) affects the overall survival (OS) and the response to immunotherapy. The combination of GPCRs and TME from a multi-omics perspective may help to predict the survival of the melanoma patients and their response to immunotherapy.

METHODS

Bulk-seq, single-cell RNA sequencing (scRNA-seq), gene mutations, immunotherapy responses, and clinicopathologic feature data were downloaded from public databases, and prognostic GPCRs and immune cells were screened using multiple machine learning algorithms. The expression levels of GPCRs were detected using real-time quantitative polymerase chain reaction (qPCR) in A375 and HaCaT cell lines. The GPCR-TME classifier was constructed and verified using different cohorts and multi-omics. Gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), and tracking tumor immunophenotype (TIP) were used to identify the key biological pathways among the GPCR-TME subgroups. Then, tumor mutational burden (TMB), vital mutant genes, antigen presentation genes, and immune checkpoints were compared among the subgroups. Finally, the differences in immunotherapy response rates among the GPCR-TME subgroups were investigated.

RESULTS

A total of 12 GPCRs and five immune cell types were screened to establish the GPCR-TME classifier. No significant differences in the expression levels of the 12 GPCRs were found in the two cell lines. Patients with high GPCR score or low TME score had a poor OS; thus, the GPCRlow/TMEhigh subgroup had the most favorable OS. The scRNA-seq result revealed that immune cells had a higher GPCR score than tumor and stromal cells. The GPCR-TME classifier acted as an independent prognostic factor for melanoma. GSEA, WGCNA, and TIP demonstrated that the GPCRlow/TMEhigh subgroup was related to the activation and recruitment of anti-tumor immune cells and the positive regulation of the immune response. From a genomic perspective, the GPCRlow/TMEhigh subgroup had higher TMB, and different mutant genes. Ultimately, higher expression levels of antigen presentation genes and immune checkpoints were observed in the GPCRlow/TMEhigh subgroup, and the melanoma immunotherapy cohorts confirmed that the response rate was highest in the GPCRlow/TMEhigh cohort.

CONCLUSIONS

We have developed a GPCR-TME classifier that could predict the OS and immunotherapy response of patients with melanoma highly effectively based on multi-omics analysis.

Programmed cell death-1 blockade therapy in melanoma: Resistance mechanisms and combination strategies

Melanoma is a highly aggressive tumor derived from melanocytes. In recent years, the incidence and mortality of melanoma have gradually increased, seriously threatening human health. Classic treatments like surgery, chemotherapy, and radiotherapy show very limited efficacy. Due to the high immunogenicity of melanoma cells, immune checkpoint inhibitors have received considerable attention as melanoma treatments. One such therapy is blockade of programmed cell death-1 (PD-1), which is one of the most important negative immune regulators and is mainly expressed on activated T cells. Disruption of the interactions between PD-1 and its ligands, programmed death-ligand 1 (PD-L1) or programmed death-ligand 2 (PD-L2) rejuvenates exhausted T cells and enhances antitumor immunity. Although PD-1 blockade therapy is widely used in melanoma, a substantial proportion of patients still show no response or short durations of remission. Recent researches have focused on revealing the underlying mechanisms for resistance to this treatment and improving its efficacy through combination therapy. Here, we will introduce the resistance mechanisms associated with PD-1 blockade therapy in melanoma and review the combination therapies available.

Immunotherapy Assessment: A New Paradigm for Radiologists

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.