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A detailed comprehension of MHC-epitope recognition is essential for the design and development of new antigens that could be effectively used in immunotherapy. Yet, the high variability of the peptide together with the large abundance of MHC variants binding makes the process highly specific and large-scale characterizations extremely challenging by standard experimental techniques. Taking advantage of the striking predictive accuracy of AlphaFold, we report a structural and dynamic-based strategy to gain insights into the molecular basis that drives the recognition and interaction of MHC class I in the immune response triggered by pathogens and/or tumor-derived peptides. Here, we investigated at the atomic level the recognition of E7 and TRP-2 epitopes to their known receptors, thus offering a structural explanation for the different binding preferences of the studied receptors for specific residues in certain positions of the antigen sequences. Moreover, our analysis provides clues on the determinants that dictate the affinity of the same epitope with different receptors. Collectively, the data here presented indicate the reliability of the approach that can be straightforwardly extended to a large number of related systems. [ABSTRACT FROM AUTHOR]

We investigated the possibility of using Raman spectroscopy assisted by artificial intelligence methods to identify liver cancer cells and distinguish them from their Non-Tumor counterpart. To this aim, primary liver cells (40 Tumor and 40 Non-Tumor cells) obtained from resected hepatocellular carcinoma (HCC) tumor tissue and the adjacent non-tumor area (negative control) were analyzed by Raman micro-spectroscopy. Preliminarily, the cells were analyzed morphologically and spectrally. Then, three machine learning approaches, including multivariate models and neural networks, were simultaneously investigated and successfully used to analyze the cells' Raman data. The results clearly demonstrate the effectiveness of artificial intelligence (AI)-assisted Raman spectroscopy for Tumor cell classification and prediction with an accuracy of nearly 90% of correct predictions on a single spectrum. [ABSTRACT FROM AUTHOR]

Virus-like particles (VLPs) are self-assembled viral protein complexes that mimic the native virus structure without being infectious. VLPs, similarly to wild type viruses, are able to efficiently target and activate dendritic cells (DCs) triggering the B and T cell immunities. Therefore, VLPs hold great promise for the development of effective and affordable vaccines in infectious diseases and cancers. Vaccine formulations based on VLPs, compared to other nanoparticles, have the advantage of incorporating multiple antigens derived from different proteins. Moreover, such antigens can be functionalized by chemical modifications without affecting the structural conformation or the antigenicity. This review summarizes the current status of preventive and therapeutic VLP-based vaccines developed against human oncoviruses as well as cancers. [ABSTRACT FROM AUTHOR]

Simple Summary: HCC is a disease with highly unmet medical needs. Specific target antigens for the development of active (vaccine) and/or passive (adoptive T-cell therapy) cancer immunotherapy strategies are needed. The aim of our study was to exploit the high number of data derived from a public dataset to identify HCC-specific overexpressed proteins, leading to potential epitopes recognized by CD8+ cytotoxic T cells, which may share homology to viral epitopes. Circulating CD8+ T cells were revealed to be targeting both HCC and viral-related epitopes, suggesting the possible use in HCC-specific immunotherapies. Hepatocellular carcinoma (HCC) is the third leading cause of death from cancer globally. Indeed, only a few treatments are available, most of which are effective only for the early stages of the disease. Therefore, there is an urgent needing for potential markers for a specifically targeted therapy. Candidate proteins were selected from datasets of The Human Protein Atlas, in order to identify specific tumor-associated proteins overexpressed in HCC samples associated with poor prognosis. Potential epitopes were predicted from such proteins, and homology with peptides derived from viral proteins was assessed. A multiparametric validation was performed, including recognition by PBMCs from HCC-patients and healthy donors, showing a T-cell cross-reactivity with paired epitopes. These results provide novel HCC-specific tumor-associated antigens (TAAs) for immunotherapeutic anti-HCC strategies potentially able to expand pre-existing virus-specific CD8+ T cells with superior anticancer efficacy. [ABSTRACT FROM AUTHOR]

Objective: The aim of this meta-analysis was to discuss evidence supporting the efficacy of adjuvant human papillomavirus (HPV) vaccination in reducing the risk of recurrent cervical intraepithelial neoplasia (CIN) 2 or greater after surgical treatment. Methods: A systematic literature search was performed for studies reporting the impact of HPV vaccination on reducing the risk of recurrence of CIN 2+ after surgical excision. Results were reported as mean differences or pooled odds ratios (OR) with 95% confidence intervals (95% CI). Results: Eleven studies met the inclusion criteria and were selected for analysis. In total, 21,310 patients were included: 4039 (19%) received peri-operational adjuvant HPV vaccination while 17,271 (81%) received surgery alone. The recurrence of CIN 2+ after treatment was significantly lower in the vaccinated compared with the unvaccinated group (OR 0.35; 95% CI 0.21–0.56; p < 0.0001). The recurrence of CIN 1+ after treatment was significantly lower in the vaccinated compared with the unvaccinated group (OR 0.51; 95% CI 0.31–0.83; p = 0.006). A non-significant trend of reduction rate of HPV persistence was observed in the vaccinated compared with the unvaccinated cohorts (OR was 0.84; 95% CI 0.61–1.15; p = 0.28). Conclusions: HPV vaccination, in adjuvant setting, is associated with a reduced risk of recurrent CIN 1+ and CIN 2+ after surgical treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Endogenous viruses are "ancient" viruses that have coevolved with their host species for millions of years, developing strategies to maintain an equilibrium state with their host. In particular, human endogenous retroviruses (HERVs) are permanently integrated and make up over 8% of our genome. Recent studies have shown that the equilibrium between these endogenous retroviruses and our cells can be broken in several conditions, including cancer. HERV reactivation in cancer cells may result in (a) the activation of a viral defense response against cancer, (b) the production of viral proteins that can be recognized as targets by our immune system and (c) the expression of viral transcripts that can be used as therapeutic targets or markers for prognosis. Overall, this may positively impact on cancer immunotherapy strategies. Human endogenous retroviruses (HERVs) derive from ancestral exogenous retroviruses whose genetic material has been integrated in our germline DNA. Several lines of evidence indicate that cancer immunotherapy may benefit from HERV reactivation, which can be induced either by drugs or by cellular changes occurring in tumor cells. Indeed, several studies indicate that HERV proviral DNA can be transcribed either to double-stranded RNA (dsRNA) that is sensed as a "danger signal" by pattern recognition receptors (PRRs), leading to a viral mimicry state, or to mRNA that is translated into proteins that may contribute to the landscape of tumor-specific antigens (TSAs). Alternatively, HERV reactivation is associated with the expression of long noncoding RNAs (lncRNAs). In this review, we will highlight recent findings on HERV reactivation in cancer and its implications for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Because dendritic cells are crucial to prime and expand antigen-specific CD8+ T-cells, several strategies are designed to use them in therapeutic vaccines against infectious diseases or cancer. In this context, off-the-shelf allogeneic dendritic cell-based platforms are more attractive than individualized autologous vaccines tailored to each patient. In the present study, a unique dendritic cell line (PDC*line) platform of plasmacytoid origin, already used to prime and expand antitumor immunity in melanoma patients, was improved thanks to retroviral engineering. We demonstrated that the clinical-grade PDC*line, transduced with genes encoding viral or tumoral whole proteins, efficiently processed and stably presented the transduced antigens in different human leukocyte antigen (HLA) class I contexts. Moreover, the use of polyepitope constructs allowed the presentation of immunogenic peptides and the expansion of specific cytotoxic effectors. We also demonstrated that the addition of the Lysosome-associated membrane protein-1 (LAMP-1) sequence greatly improved the presentation of some peptides. Lastly, thanks to transduction of new HLA molecules, the PDC platform can benefit many patients through the easy addition of matched HLA-I molecules. The demonstration of the effective retroviral transduction of PDC*line cells strengthens and broadens the scope of the PDC*line platform, which can be used in adoptive or active immunotherapy for the treatment of infectious diseases or cancer. [ABSTRACT FROM AUTHOR]

One of the principal goals of cancer immunotherapy is the development of efficient therapeutic cancer vaccines that are able to elicit an effector as well as memory T cell response specific to tumor antigens. In recent years, the attention has been focused on the personalization of cancer vaccines. However, the efficacy of therapeutic cancer vaccines is still disappointing despite the large number of vaccine strategies targeting different tumors that have been evaluated in recent years. While the preclinical data have frequently shown encouraging results, clinical trials have not provided satisfactory data to date. The main reason for such failures is the complexity of identifying specific target tumor antigens that should be unique or overexpressed only by the tumor cells compared to normal cells. Most of the tumor antigens included in cancer vaccines are non-mutated overexpressed self-antigens, eliciting mainly T cells with low-affinity T cell receptors (TCR) unable to mediate an effective anti-tumor response. In this review, the target tumor antigens employed in recent years in the development of therapeutic cancer vaccine strategies are described, along with potential new classes of tumor antigens such as the human endogenous retroviral elements (HERVs), unconventional antigens, and/or heteroclitic peptides. [ABSTRACT FROM AUTHOR]

Nanoparticles represent a potent antigen presentation and delivery system to elicit an optimal immune response by effector cells targeting tumor-associated antigens expressed by cancer cells. Many types of nanoparticles have been developed, such as polymeric complexes, liposomes, micelles and protein-based structures such as virus like particles. All of them show promising results for immunotherapy approaches. In particular, the immunogenicity of peptide-based cancer vaccines can be significantly potentiated by nanoparticles. Indeed, nanoparticles are able to enhance the targeting of antigen-presenting cells (APCs) and trigger cytokine production for optimal T cell response. The present review summarizes the categories of nanoparticles and peptide cancer vaccines which are currently under pre-clinical evaluation. [ABSTRACT FROM AUTHOR]

Cell surface proteins act as the go-between in carrying the information from the extracellular environment to the intracellular signaling proteins. However, these proteins are often deregulated in neoplastic diseases, including hepatocellular carcinoma. This review discusses several recent studies that have investigated the role of cell surface proteins in the occurrence and progression of HCC, highlighting the possibility to use them as biomarkers of the disease and/or targets for vaccines and therapeutics. [ABSTRACT FROM AUTHOR]

Cancer genome instability leads to accumulation of mutations which may result into tumor-specific mutated "neoantigens", not be affected by central T-cell tolerance. Such neoantigens are considered the optimal target for the patient's anti-tumor T cell immunity as well as for personalized cancer immunotherapy strategies. However, only a minor fraction of predicted neoantigens are relevant to the clinical outcome. In the present study, a prediction algorithm was applied using datasets of RNA sequencing from all 377 Hepatocellular carcinoma (HCC) patients available at The Cancer Genome Atlas (TCGA), to predict neoantigens to be presented by each patient's autologous HLA molecules. Correlation with patients' survival was performed on the 115 samples for whom the exact date of death was known. A total of 30 samples were used for the training set, and 85 samples were used for the validation sets. Neither the somatic mutations nor the number nor the quality of the predicted neoantigens correlate as single parameter with survival of HCC patients who do not undergo immunotherapy treatment. Furthermore, the preferential presentation of such neoantigens in the context of one of the major histocompatibility complex MHC class I molecules does not have an impact on the survival. On the contrary, the expression of Granzyme A (GZMA) is significantly correlated with survival and, in the context of high GZMA, a direct correlation between number and quality of neoantigens with survival is observed. This is in striking contrast to results described in cancer patients undergoing immunotherapy, in which a strong correlation between Tumor Mutational Burden (TMB), number of predicted neoantigens and survival has been reported. [ABSTRACT FROM AUTHOR]