Search Results (439)

Immunotherapy (IT) and especially immune checkpoint blockade (ICB) changed the therapeutic approach in non-small cell lung cancer (NSCLC). Nevertheless, primary or secondary resistance and a percentage of long responders and survivors have been observed. The aim of this study is to gain a deeper understanding of the complex mechanisms of primary and secondary resistance to IT, involving tumor cells, the tumor microenvironment (TME), and the host, in order to find strategies to overcome it. With this aim in mind, a search for key words has been performed to identify relevant evidence in the literature. The most widely used approach is the combination of IT with chemotherapy (CT) and/or radiotherapy (RT), relying on the synergistic effect on the enhancement of immunogenic cell death. Since a dual role has been observed, a lot of questions are yet to be answered regarding the complex effect of these therapies, especially on the TME. Preclinical and clinical studies investigate the best sequencing and timing of chemoradiation with IT, and the optimal RT volumes, sites, and dose/fractionation regimens to favor immune stimulation over suppression on the TME. Moving forward, multiple agents addressing coinhibitory or costimulatory receptors on immune or tumor cells are under evaluation. The huge potential of combination therapies becoming apparent. Questions regarding targets, selection of patients, and time and sequence of administration are yet to be answered, considering the complex mechanisms of resistance. Dynamic biomarkers to guide personalized treatment decisions are needed. Full article

The sodium iodide symporter (NIS) is a key protein in thyroid function responsible for iodine uptake, and it may be involved in the pathogenesis of autoimmune thyroiditis. However, it is also expressed in the salivary glands, the primary target of autoreactive cells in Sjögren’s syndrome (SS). Given the common link between the two diseases, we computationally investigated whether the epitopes of NIS can trigger an immune response leading to SS in Hashimoto’s thyroiditis (HT) patients genetically predisposed to both diseases. The TepiTool 2016, ABCpred 2006, and DiscoTope 2.0 servers were used to predict T-cell and B-cell epitopes by inputting the FASTA sequences and 3D structures of NIS, thyroid peroxidase (TPO) and Ro60 Y RNA-binding protein (Ro60), which served as reference antigens for HT and SS, respectively. T-cell epitopes were selected based on their binding to a panel of human leukocyte antigen (HLA) alleles associated with both SS and HT. We identified a total of 376 linear T-cell epitopes, 64 linear B-cell epitopes and 68 conformational B-cell epitopes of NIS. Compared to TPO, NIS T-cell epitopes showed significantly lower affinity for HLA alleles (p < 0.0001), while no significant difference was found compared to Ro60. While linear B-cell epitopes of NIS, TPO, and Ro60 showed similar binding affinity, conformational epitopes of NIS were predicted to have higher immunogenicity than Ro60 (p = 0.04), while no significant difference was found compared to TPO. These pivotal findings, discovered by the methods of computer modeling, suggest that NIS can potentially activate T cells and B cells in patients with genetic predisposition to SS and HT and need to be confirmed by further laboratory studies. Full article

Background/Objectives: Notwithstanding the declaration by the World Health Organization in May 2023 regarding the conclusion of the COVID-19 pandemic, new cases of this potentially lethal infection continue to be documented globally, exerting a sustained influence on the worldwide economy and social structures. Contemporary SARS-CoV-2 variants, while associated with a reduced propensity for severe acute pathology, retain the capacity to induce long-term post-COVID syndrome, including in ambulatory patient populations. This clinical phenomenon may be attributable to potential autoimmune reactions hypothetically triggered by antiviral antibodies, thereby underscoring the need for developing novel, universal vaccines against COVID-19. The nucleocapsid protein (N), being one of its most conserved and highly immunogenic components of SARS-CoV-2, presents a promising target for such investigative efforts. However, the protective role of anti-N antibodies, generated during natural infection or through immunization with N-based vaccines, alongside the potential adverse effects associated with their production, remains to be fully elucidated. In the present study, we aim to identify potential sites of homology in structures or sequences between the SARS-CoV-2 N protein and human antigens detected using hyperimmune sera against N protein obtained from mice, rabbits, and hamsters. Methods: We employed Western blot analysis of lysates from human cell lines (MCF7, HEK293T, THP-1, CaCo2, Hep2, T98G, A549) coupled with mass spectrometric identification to assess the cross-reactivity of polyclonal and monoclonal antibodies generated against recombinant SARS-CoV-2 N protein with human self-antigens. Results: We showed that anti-N antibodies developed in mice and rabbits exhibit pronounced immunoreactivity towards specific components of the human proteome. In contrast, anti-N immunoglobulins from hamsters showed no non-specific cross-reactivity with either hamster or human proteomic extracts because of the lack of autoreactivity or immunogenicity differences. Subsequent mass spectrometric analysis of the immunoreactive bands identified principal autoantigenic targets, which were predominantly heat shock proteins (including HSP90-beta, HSP70, mitochondrial HSP60, and HSPA8), histones (H2B, H3.1–3), and key metabolic enzymes (G6PD, GP3, PKM, members of the 1st family of aldo-keto reductases). Conclusions: The results obtained herein highlight the differences in the development of anti-N humoral responses in humans and in the Syrian hamster model. These data provide a foundational basis for formulating clinical recommendations to predict possible autoimmune consequences in COVID-19 convalescents and are of critical importance for the rational design of future N protein-based, cross-protective vaccine candidates against novel coronavirus infections. Full article

Epizootic hemorrhagic disease (EHD) is an important livestock disease caused by Epizootic hemorrhagic disease virus (EHDV). The recent incursion and wide distribution of EHDV in Europe have increased the need for effective vaccine candidates. Background/Objectives: The VP2 protein of EHDV forms the outer capsid layer of the virion and is essential for viral assembly and host cell entry. Owing to its antigenic properties, VP2 represents a major target for vaccine development. However, the recombinant production of VP2 is limited by low stability and poor yields, representing a significant barrier for the generation of safe and effective subunit vaccines. Methods: To overcome these limitations, the VP2 protein from EHDV serotype 8 (EHDV-8) was rationally engineered with targeted modifications at both the amino and carboxyl termini of its coding sequence. Recombinant expression was performed using a baculovirus vector-mediated system in Trichoplusia ni pupae (CrisBio^® technology), employed as living biofactories. Results: The engineering of VP2 resulted in up to a tenfold increase in protein yields compared with the wild-type sequence, while maintaining the trimeric structural integrity of the recombinant protein. Both wild-type and engineered VP2 protein variants were formulated and used to immunize IFNAR(−/−) mice, a model susceptible to EHDV infection. Both engineered and wild-type VP2 formulations elicited comparable neutralizing antibody responses in vaccinated animals. Furthermore, immunization with either formulation conferred full protection against lethal EHDV-8 challenge. Conclusions: In this work, we demonstrated that the rational engineering of the VP2 protein significantly improved recombinant expression yields in a baculovirus-based system without compromising structural integrity or immunogenicity. These findings additionally demonstrate the feasibility of producing high-quality VP2 antigens in T. ni pupae using CrisBio^® technology and support their potential application in the development of subunit vaccines against EHDV. Full article

Background/Objectives: The rise of immune escape variants of the SARS-CoV-2 virus has prompted the development of vaccines based on the variant’s spike antigen sequence. Since variant-specific SARS-CoV-2 vaccines are mostly administered as boosters to individuals previously vaccinated with reference (Ref.) strain-based vaccines, a better understanding of their immunogenicity in this context is essential. Protein subunit vaccines have a well-established track record of safety. Herein, we assessed the ability of variant-specific protein subunit vaccine formulations to boost pre-existing Ref. strain-specific immune responses compared to boosting with a Ref. strain-specific formulation in young and aged female Balb/c mice. Methods: Following a priming vaccination series with Ref. spike protein adjuvanted with sulfated lactosyl archaeol (SLA) archaeosomes on days 0 and 21, immune responses were evaluated in young and aged female Balb/c mice. On day 91, mice received a third immunization with Ref., Beta, or Delta spike protein formulations, with or without SLA archaeosomes. Antibody titers, neutralization activity, and cellular immune responses were measured to assess the impact of the booster formulation. Results: Aged mice exhibited lower antibody titers throughout the study and a decline over time compared to young mice. After a third immunization, responses were boosted by all vaccine formulations (Ref., Beta, or Delta), with or without adjuvant. However, variant-specific antigen formulations did not overcome immune imprinting from the priming series or increase neutralization activity against the corresponding SARS-CoV-2 variants in either age group. Conclusions: Variant-specific protein subunit vaccines enhanced immune responses but did not overcome immune imprinting induced by the Ref. strain’s priming. The inclusion of SLA archaeosomes improved cellular immunity, supporting their potential role in optimizing booster vaccine performance, particularly in aged populations. Full article

Background: Pembrolizumab has reshaped the neoadjuvant treatment landscape for triple-negative breast cancer (TNBC). However, the influence of BRCA1/2 mutational status on the efficacy of chemo-immunotherapy remains unclear, particularly in real-world settings. Since BRCA-mutated tumors exhibit homologous recombination deficiency (HRD) and high genomic instability, they may be more immunogenic and responsive to immune checkpoint inhibitors. This multicenter study investigated the association between BRCA1/2 mutations and pathologic complete response (pCR) in TNBC patients treated with pembrolizumab-based neoadjuvant chemotherapy (NACT). Methods: We retrospectively analyzed 184 patients with stage II–III TNBC treated between 2021 and 2024 across eleven Italian oncology centers. All received pembrolizumab combined with platinum- and taxane-based NACT followed by anthracyclines, according to the KEYNOTE-522 regimen. Germline BRCA1/2 status was determined by next-generation sequencing. The primary endpoint was pCR, defined as ypT0/is ypN0. Fisher’s exact test and logistic regression models were used to assess associations between clinical–pathological variables and pCR. Results: Among 184 patients, 25 (13.6%) harbored BRCA1 mutations, 12 (6.5%) BRCA2 mutations, and 147 (79.9%) were wild-type. pCR was achieved in 80.0% of BRCA1-mutated, 75.0% of BRCA2-mutated, and 61.1% of wild-type tumors. When pooled, BRCA1/2-mutated cases showed a higher likelihood of achieving pCR (78.4% vs. 61.1%; odds ratio [OR] = 2.17; 95% CI 1.01–4.97; p = 0.056). High tumor-infiltrating lymphocytes (≥30%) were also associated with increased pCR rates. The frequency of BRCA mutations (20.1%) was consistent with that reported in major TNBC series. No comparative analysis of toxicity or survival outcomes was performed due to the retrospective design and limited follow-up. Conclusions: In this multicenter real-world cohort, TNBC patients carrying BRCA1/2 mutations exhibited a trend toward higher pCR rates with pembrolizumab-based NACT compared with wild-type tumors. These findings suggest enhanced chemosensitivity and immune responsiveness in BRCA-deficient disease, warranting further validation in larger prospective studies with survival endpoints. Full article

Background: Short peptide epitopes are valuable for mechanistic studies, yet their intrinsic low immunogenicity and lack of commercial antibodies hinder rapid antibody generation. Methods: We developed a reproducible, sequence-level workflow combining cross-species/structural triage, independent MHC-I/II prioritization, and conservative heteroclitic-style substitutions to enhance predicted MHC affinity while preserving native epitope features. Using visfatin as a model, two optimized fragments were conjugated to KLH and tested in mice for antibody titers, isotype profiles, and binding kinetics. Results: Mutant peptides improved MHC-binding prediction, elicited stronger antibody titers, and promoted isotype maturation (increased IgG1). Importantly, antibodies maintained measurable binding to wild-type sequences, indicating preserved cross-recognition. Similar effects were reproduced with additional antigens. Conclusions: This proof-of-concept study, based on small exploratory mouse cohorts (n = 3 per group), demonstrates that strategic, minimal sequence edits can significantly enhance peptide immunogenicity while preserving native epitope recognition. This streamlined workflow provides a low-barrier route to generate epitope-directed antibodies when commercial reagents are unavailable. Full article

Personalized cancer vaccines are a key strategy for training the immune system to recognize and respond to tumor-specific antigens. Our earlier software release, AutoEpiCollect 1.0, was designed to accelerate the vaccine design process, but the identification of tumor-specific genetic variants remains a manual process and is highly burdensome. In this study, we introduce AutoEpiCollect 2.0, an improved version with integrated genetic analysis capabilities that automate the identification and prioritization of tumorigenic variants from individual tumor samples. AutoEpiCollect 2.0 connects with RNA sequencing and cross-references the resulting RNAseq data for efficient determination of cancer-specific and prognostic gene variants. Using AutoEpiCollect 2.0, we conducted two case studies to design personalized peptide vaccines for two distinct cancer types: cervical squamous cell carcinoma and breast carcinoma. Case 1 analyzed five cervical tumor samples from different stages, ranging from CIN1 to cervical cancer stage IIB. CIN3 was selected for detailed analysis due to its pre-invasive status and clinical relevance, as it is the earliest stage where patients typically present symptoms. Case 2 examined five breast tumor samples, including HER2-negative, ER-positive, PR-positive, and triple-negative subtypes. In three of these breast samples, the same epitope was identified and was synthesized by identical gene variants. This finding suggests the presence of shared antigenic targets across subtypes. We identified the top MHC class I and class II epitopes for both cancer types. In cervical carcinoma, the most immunogenic epitopes were found in proteins expressed by HSPG2 and MUC5AC. In breast carcinoma, epitopes with the highest potential were derived from proteins expressed by BRCA2 and AHNAK2. These epitopes were further validated through pMHC-TCR modeling analysis. Despite differences in cancer type and tumor subtype, both case studies successfully identified high-potential epitopes suitable for personalized vaccine design. The integration of AutoEpiCollect 2.0 streamlined the variant analysis workflow and reduced the time required to identify key tumor antigens. This study demonstrates the value of automated data integration in genomic analysis for cancer vaccine development. Furthermore, by applying RNAseq in a standardized workflow, the approach enables both patient-specific and population-level vaccine design, based on statistically frequent gene variants observed across tumor datasets. AutoEpiCollect 2.0 is freely available as a website based tool for user to design vaccine. Full article

The landscape of cancer immunotherapy has been redefined by mRNA vaccines as rapid clinically viable strategies that help induce potent, tumor-specific immune responses. This review highlights the current advances in mRNA engineering and antigen design to establish an integrated immunological framework for cancer vaccine development. Achieving durable clinical benefit requires more than antigen expression. Effective vaccines need precise epitope selection, optimized delivery systems, and rigorous immune monitoring. The field is shifting from merely inducing immune responses to focusing more on the biochemistry and molecular design principles that combine magnitude, polyfunctionality, and longevity to overcome tumor-induced immune suppression. We examine an integrated immunological framework for mRNA cancer vaccine development, examining how rational molecular engineering of vaccine components, from nucleoside modifications and codon optimization to untranslated regions and linker sequences, shapes immunogenicity and therapeutic efficacy. Future directions will depend on balancing combinatorial strategies combining vaccination with immune checkpoint inhibitors and adoptive cell therapies. Full article

Breast cancer (BC) is a heterogeneous disease, and triple-negative breast cancer (TNBC) is the most aggressive and immunogenic subtype. A significant proportion of TNBC cases are linked to hereditary cancer syndromes involving pathogenic germline variants, most commonly in BRCA1/2. However, few studies have compared hereditary and sporadic TNBC in admixed populations. In this study, molecular and immunological features were analyzed through the analysis of 62 Colombian TNBC samples (20 hereditary and 42 sporadic cases) by RNA sequencing to identify molecular and immune differences. We used an external validation cohort of 16 TCGA TNBC cases (8 BRCA-mutated and 8 non-mutated) to replicate our findings. Results: We found a set of 921 differentially expressed genes (DEGs) between hereditary and sporadic TNBC. Hereditary tumors were enriched for pathways related to extracellular matrix (ECM) remodeling, structural components, and DNA damage response and exhibited a more immunologically active tumor microenvironment compared to sporadic tumors. LASSO logistic regression identified 23 genes with discriminatory potential, showing that hereditary tumors are characterized by complex immune regulation, inflammatory processes, and activation of key oncogenic pathways. Conclusions: Hereditary TNBC is characterized by molecular and biological functions linked to ECM remodeling and its constituents and an active immune microenvironment. This integrated molecular–immune profile provides insight into the distinct biology of hereditary tumors in admixed populations. Full article

Breast cancer remains the most prevalent malignancy among women worldwide, with hormone receptor-positive (HR+) tumors comprising approximately 70% of cases. Traditionally, HR+ breast cancer has been classified as immunologically “cold” due to its low PD-L1 expression, reduced tumor-infiltrating lymphocytes, and low tumor mutational burden, collectively limiting immunotherapy responsiveness. However, emerging evidence indicates significant molecular heterogeneity within HR+ tumors, characterized by specific genetic signatures and features of the tumor microenvironment (TME) that can be therapeutically reprogramed through chemotherapy-induced immunogenic cell death combined with immune checkpoint inhibition. Recent clinical trials demonstrate that biomarker-selected immune-enriched HR+ subsets, identified by MammaPrint Ultra-High 2 classification, homologous recombination deficiency, or elevated tumor-infiltrating lymphocytes, achieve notable pathological complete response rates with immune checkpoint inhibitor combinations. This review summarizes the dynamic interactions between genetic determinants and TME plasticity in HR+ breast cancer and critically assesses combination strategies across 31 neoadjuvant trials. We demonstrate that optimal efficacy requires biomarker-guided patient selection integrating genetic and TME features, precise sequencing, and a mechanistic understanding of drug-specific immunomodulatory effects. The integration of platform trial designs (I-SPY2, CheckMate-7FL) with composite biomarker algorithms represents a paradigm shift toward precision neoadjuvant immunotherapy, offering a conceptual framework for transforming outcomes in molecularly defined HR+ breast cancer subsets. Full article

Background: Tumor immunogenicity is a concept for modeling the susceptibility of tumors to immune checkpoint inhibitors (ICIs) and other immunotherapies. Single biomarkers, such as tumor mutation burden (TMB) or PDL1 expression, have been shown to correlate with ICI outcomes but are poor predictors of overall and progression-free survival (OS, PFS). Complex machine learning models that integrate multiple biomarkers have shown improved predictions but often lack clear a priori interpretability. In this study, we developed a coherent Multi-Omics Tumor Immunogenicity score (MOTIscore) that combines immunogenicity biomarkers derived from genomic and transcriptomic data and demonstrated its generalizability across multiple cancer types. Methods: Several immunogenicity biomarkers, including TMB, neoantigen burden, T-cell receptor repertoire, PDL1 expression, B2M expression, and variants in pathways of ICI response and resistance, were integrated using a weighted sum scoring scheme. The weights were determined using statistical tests in a large melanoma ICI cohort. We compared the MOTIscore with a machine learning (ML) model trained using the same biomarkers and evaluated the model using melanoma, gastric cancer, and pan-cancer datasets. Results: MOTIscore achieved results similar to those of the ML model in predicting ICI in melanoma and gastric cancer, with both outperforming TMB. Gastric cancer and melanoma patients with high MOTIscores had a significantly extended overall and progression-free survival. Gene set enrichment analysis revealed the enrichment of immune-related pathways in patients with high MOTIscores. Differential expression analysis between patients with high and low immunogenicity identified highly expressed C-X-C motif chemokine ligands as important characteristics associated with successful ICI therapy and significantly improved PFS. MOTIscores varied widely across cancers treated in the molecular tumor board at our hospital and showed distinct distributions between non-immunogenic and immunogenic cancer types. Conclusions: MOTIscore demonstrated improved ICI outcome predictions compared to single-omics biomarkers. Patients with higher tumor immunogenicity also show significantly improved OS and PFS in melanoma and gastric cancer. The results demonstrate the potential use of the MOTIscore to prioritize ICI in personalized cancer treatment. However, ICI outcomes and survival should be investigated in prospective studies, and additional cancer types and larger patient cohorts are needed. Full article

Diffusion models have emerged as a leading framework in generative modeling, poised to transform the traditionally slow and costly process of drug discovery. This review provides a systematic comparison of their application in designing two principal therapeutic modalities: small molecules and therapeutic peptides. We dissect how the unified framework of iterative denoising is adapted to the distinct molecular representations, chemical spaces, and design objectives of each modality. For small molecules, these models excel at structure-based design, generating novel, pocket-fitting ligands with desired physicochemical properties, yet face the critical hurdle of ensuring chemical synthesizability. Conversely, for therapeutic peptides, the focus shifts to generating functional sequences and designing de novo structures, where the primary challenges are achieving biological stability against proteolysis, ensuring proper folding, and minimizing immunogenicity. Despite these distinct challenges, both domains face shared hurdles: the scarcity of high-quality experimental data, the reliance on inaccurate scoring functions for validation, and the crucial need for experimental validation. We conclude that the full potential of diffusion models will be unlocked by bridging these modality-specific gaps and integrating them into automated, closed-loop Design-Build-Test-Learn (DBTL) platforms, thereby shifting the paradigm from mere chemical exploration to the on-demand engineering of novel therapeutics. Full article

RNA interference (RNAi) offers programmable, sequence-specific silencing via small interfering RNA (siRNA) and microRNA (miRNA), but clinical translation hinges on overcoming instability, immunogenicity, and inefficient endosomal escape. This review synthesizes advances in non-viral nanocarriers—liposomes, polymeric nanoparticles, and extracellular vesicles (EVs)—that stabilize nucleic acids, tune biodistribution, and enable organ- and cell-selective delivery. We highlight design levers that now define the field: ligand-guided targeting, stimuli-responsive release, biomimicry and endogenous carriers, and rational co-delivery with small molecules. Across major disease areas—cancer and cardiovascular, respiratory, and urological disorders—these platforms achieve tissue-selective uptake (e.g., macrophages, endothelium, and myocardium), traverse physiological barriers (including the blood–brain barrier and fibrotic stroma), and remodel hostile microenvironments or immune programs to enhance efficacy while maintaining favorable safety profiles. Early clinical studies reflect this diversity, spanning targeted nanoparticles, local drug depots, exosome and cellular carriers, and inhaled formulations, e.g., and converge on core phase-I endpoints (safety, maximum tolerated dose, pharmacokinetics/pharmacodynamics, and early activity). Looking ahead, priorities include good manufacturing practice scale, consistent manufacture—especially for EVs; more efficient loading and cargo control; improved endosomal escape and biodistribution; and rigorous, long-term safety evaluation with standardized, head-to-head benchmarking. Emerging directions such as in vivo EVs biogenesis, theragnostic integration, and data-driven formulation discovery are poised to accelerate translation. Collectively, nanoparticle-enabled RNAi has matured into a versatile, clinically relevant toolkit for precise gene silencing, positioning the field to deliver next-generation therapies across diverse indications. Full article

Melanoma is the most aggressive and deadliest form of skin cancer, and the current treatments of melanoma have many limitations, which necessitate discovering new compounds and targets for melanoma. Two probes, 2155-14 and 2155-18, were identified to induce apoptotic cell death, autophagy, and immune signaling modulation through hnRNPH1/H2-dependent mechanisms. RNA sequencing following the siRNA-mediated knockdown of hnRNPH2 in melanoma cells revealed an enrichment of immune-related signaling pathways. The present study investigated the effect of genetic and pharmacologic downregulation of hnRNPH1/H2 on melanoma immunogenicity in vitro. Our results indicated that treating melanoma cell lines with 2155-14 and 2155-18 led to hnRNPH1/H2 downregulation, whereas hnRNPH2 siRNA treatment led to only hnRNPH2 downregulation. Both types of treatment resulted in a significant upregulation of pro-inflammatory pathways and simultaneous downregulation of anti-inflammatory pathways. These findings provide the first insight into the role of hnRNPH1/H2 as critical drivers of melanoma immunogenicity and suggest their potential as novel therapeutic targets for enhancing melanoma treatment outcomes. This study underscores the impact of post-transcriptional regulation on the immune environment in melanoma and in cancer in general. Full article