Dendritic cells matured with recombinant human sperm associated antigen 9 (rhSPAG9) induce CD4+, CD8+ T cells and activate NK cells: a potential candidate molecule for immunotherapy in cervical cancer

Optimization and Validation of a Harmonized Protocol for Generating Therapeutic-Grade Dendritic Cells in a Randomized Phase II Clinical Trial, Using Two Varied Antigenic Sources

Autologous dendritic cell (DC)-based immunotherapy is a cell-based advanced therapy medicinal product (ATMP) that was first introduced more than three decades ago. In the current study, our objective was to establish a harmonized protocol using two varied antigenic sources and a good manufacturing practice (GMP)-compliant, manual method for generating clinical-grade DCs at a limited-resource academic setting. After obtaining ethical committee-approved informed consent, the recruited patients underwent leukapheresis, and single-batch DC production was carried out. Using responder-independent flow cytometric assays as quality control (QC) criteria, we propose a differentiation and maturation index (DI and MI, respectively), calculated with the QC cut-off and actual scores of each batch for comparison. Changes during cryopreservation and personnel variation were assessed periodically for up to two to three years. Using our harmonized batch production protocol, the average DI was 1.39 and MI was 1.25. Allogenic responder proliferation was observed in all patients, while IFN-gamma secretion, evaluated using flow cytometry, was detected in 10/36 patients and significantly correlated with CD8+ T cell proliferation (p value-0.0002). Tracking the viability and phenotype of cryopreserved MDCs showed a >90% viability for up to three years, while a mature DC phenotype was retained for up to one year. Our results confirm that the manual/semi-automated protocol was simple, consistent, and cost-effective, without the requirement for expensive equipment and without compromising on the quality of the final product.

Advancing Immunotherapies for HPV-Related Cancers: Exploring Novel Vaccine Strategies and the Influence of Tumor Microenvironment

The understanding of the relationship between immunological responses and cancers, especially those related to HPV, has allowed for the study and development of therapeutic vaccines against these neoplasias. There is a growing number of studies about the composition and influence of the tumor microenvironment (TME) in the progression or establishment of the most varied types of cancer. Hence, it has been possible to structure immunotherapy approaches based on therapeutic vaccines that are even more specific and directed to components of TME and the immune response associated with tumors. Among these components are dendritic cells (DCs), which are the main professional antigen-presenting cells (APCs) already studied in therapy strategies for HPV-related cancers. On the other hand, tumor-associated macrophages are also potential targets since the profile present in tumor infiltrates, M1 or M2, influences the prognosis of some types of cancer. These two cell types can be targets for therapy or immunomodulation. In this context, our review aims to provide an overview of immunotherapy strategies for HPV-positive tumors, such as cervical and head and neck cancers, pointing to TME immune cells as promising targets for these approaches. This review also explores the potential of immunotherapy in cancer treatment, including checkpoint inhibitors, cytokine immunotherapies, immunotherapy vaccines, and cell therapies. Furthermore, it highlights the importance of understanding the TME and its effect on the design and achievement of immunotherapeutic methods.

A panel of seven immune-related genes can serve as a good predictive biomarker for cervical squamous cell carcinoma

Objective: Cervical cancer is one of the most common gynecological malignancies. The interaction between tumor microenvironment and immune infiltration is closely related to the progression of cervical squamous cell carcinoma (CSCC) and patients' prognosis. Herein, a panel of immune-related genes was established for more accurate prognostic prediction. Methods: The transcriptome information of tumor and normal samples were obtained from TCGA-CSCC and GTEx. Differentially expressed genes (DEGs) were defined from it. Immune-related genes (IRGs) were retrieved from the ImmPort database. After removing the transcriptome data which not mentioned in GSE44001, IR-DEGs were preliminarily identified. Then, TCGA-CSCC samples were divided into training and testing set (3:1) randomly. Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were used in turn to construct the signature to predict the overall survival (OS) and disease-free survival (DFS). External validation was performed in GSE44001, and initial clinical validation was performed by qRT-PCR. Function enrichment analysis, immune infiltration analysis and establishment of nomogram were conducted as well. Results: A prognostic prediction signature consisting of seven IR-DEGs was established. High expression of NRP1, IGF2R, SERPINA3, TNF and low expression of ICOS, DES, HCK suggested that CSCC patients had shorter OS (POS<0.001) and DFS (PDFS<0.001). AUC values of 1-, 3-, five- year OS were 0.800, 0.831 and 0.809. Analyses in other validation sets showed good consistency with the results in training set. The signature can serve as an independent prognostic factor for OS (HR = 1.166, p < 0.001). AUC values of 1-, 3-, five- year OS based on the nomogram were 0.769, 0.820 and 0.807. Functional enrichment analysis suggested that these IR-DEGs were associated with receptor interaction and immune cell activity. Immune infiltration analysis indicated that patients in high-risk group had lower immune infiltration, weaker immune function, and were more likely to benefit from immune checkpoint inhibitor therapy. Through qRT-PCR on clinical samples, expression of NRP1, IGF2R, SERPINA3 and TNF were significantly upregulated in tumor tissue, while ICOS and DES were significantly downregulated. Conclusion: To conclude, the immune-related signature can provide strong support for exploration of immune infiltration, prediction of prognosis and response to immunotherapy through stratify CSCC patients into subgroups.