Anti-integrin αvß6 antibody in Takayasu arteritis patients with or without ulcerative colitis.

Background: It has been well documented that Takayasu arteritis (TAK) and ulcerative colitis (UC) coexist in the same patients. HLA-B*52 characterizes the co-occurrence, which is one of the common genetic features between these two diseases, indicating shared underlying pathologic mechanisms. Anti-integrin αvß6 antibody (Ab) is present in sera of UC patients in a highly specific manner. We investigated if there were any associations between anti-integrin αvß6 Ab and TAK, considering the risk HLA alleles. Methods: A total of 227 Japanese TAK patients were recruited in the current study and their serum samples were subjected to measurement of anti-integrin αvß6 Ab by ELISA. The clinical information, including the co-occurrence of UC, was collected. The HLA allele carrier status was determined by Luminex or genotype imputation. Results: The information about the presence of UC was available for 165 patients, among which eight (4.84%) patients had UC. Anti-integrin αvß6 antibody was identified in 7 out of 8 TAK subjects with UC (87.5%) while only 5 out of 157 (3.18%) TAK subjects without UC had the antibody (OR 121, p=7.46×10-8). A total of 99 out of 218 (45.4%) patients were HLA-B*52 carriers. There was no significant association between the presence of anti-integrin αvß6 Ab and HLA-B*52 carrier status in those without UC (OR 2.01, 95% CI 0.33-12.4, p = 0.189). Conclusions: The prevalence of anti-integrin αvß6 Ab was high in TAK patients with UC, but not in the absence of concomitant UC. The effect of HLA-B*52 on anti-integrin αvß6 Ab production would be minimal.

Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design.

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient's specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Immune profiling of dedifferentiated liposarcoma and identification of novel antigens for targeted immunotherapy.

Dedifferentiated liposarcoma (DDLS) is an aggressive, recurring sarcoma with limited treatments. T-cell immunotherapies selectively target malignant cells, holding promise against DDLS. The development of successful immunotherapy for DDLS requires a thorough evaluation of the tumor immune microenvironment and the identification and characterization of targetable immunogenic tumor antigens. To assess the complexity of the human DDLS tumor immune microenvironment and to identify target antigens, we used the nCounter NanoString platform, analyzing gene expression profiles across 29 DDLS and 10 healthy adipose tissue samples. Hierarchical clustering of tumors based on expression of tumor inflammation signature genes revealed two distinct groups, consisting of 15 inflamed tumors and 14 non-inflamed tumors, demonstrating tumor heterogeneity within this sarcoma subtype. Among the identified antigens, PBK and TTK exhibited substantial upregulation in mRNA expression compared to healthy adipose tissue controls, further corroborated by positive protein expression by IHC. This data shows considerable inter-tumoral heterogeneity of inflammation, which should be taken into consideration when designing an immunotherapy for DDLS, and provides a novel targetable antigen in DDLS. The results of this study lay the groundwork for the development of a novel immunotherapy for this highly aggressive sarcoma.

OTUB2 silencing promotes ovarian cancer via mitochondrial metabolic reprogramming and can be synthetically targeted by CA9 inhibition.

Ovarian cancer is an aggressive gynecological tumor characterized by a high relapse rate and chemoresistance. Ovarian cancer exhibits the cancer hallmark of elevated glycolysis, yet effective strategies targeting cancer cell metabolic reprogramming to overcome therapeutic resistance in ovarian cancer remain elusive. Here, we revealed that epigenetic silencing of Otubain 2 (OTUB2) is a driving force for mitochondrial metabolic reprogramming in ovarian cancer, which promotes tumorigenesis and chemoresistance. Mechanistically, OTUB2 silencing destabilizes sorting nexin 29 pseudogene 2 (SNX29P2), which subsequently prevents hypoxia-inducible factor-1 alpha (HIF-1α) from von Hippel-Lindau tumor suppressor-mediated degradation. Elevated HIF-1α activates the transcription of carbonic anhydrase 9 (CA9) and drives ovarian cancer progression and chemoresistance by promoting glycolysis. Importantly, pharmacological inhibition of CA9 substantially suppressed tumor growth and synergized with carboplatin in the treatment of OTUB2-silenced ovarian cancer. Thus, our study highlights the pivotal role of OTUB2/SNX29P2 in suppressing ovarian cancer development and proposes that targeting CA9-mediated glycolysis is an encouraging strategy for the treatment of ovarian cancer.

Tumor Antigens beyond the Human Exome.

With the advent of immunotherapeutics, a new era in the combat against cancer has begun. Particularly promising are neo-epitope-targeted therapies as the expression of neo-antigens is tumor-specific. In turn, this allows the selective targeting and killing of cancer cells whilst healthy cells remain largely unaffected. So far, many advances have been made in the development of treatment options which are tailored to the individual neo-epitope repertoire. The next big step is the achievement of efficacious "off-the-shelf" immunotherapies. For this, shared neo-epitopes propose an optimal target. Given the tremendous potential, a thorough understanding of the underlying mechanisms which lead to the formation of neo-antigens is of fundamental importance. Here, we review the various processes which result in the formation of neo-epitopes. Broadly, the origin of neo-epitopes can be categorized into three groups: canonical, noncanonical, and viral neo-epitopes. For the canonical neo-antigens that arise in direct consequence of somatic mutations, we summarize past and recent findings. Beyond that, our main focus is put on the discussion of noncanonical and viral neo-epitopes as we believe that targeting those provides an encouraging perspective to shape the future of cancer immunotherapeutics.

Single-sEV profiling identifies the TACSTD2 + sEV subpopulation as a factor of tumor susceptibility in the elderly.

BACKGROUND: Aging is a very complex physiological phenomenon, and sEVs are involved in the regulation of this mechanism. Serum samples from healthy individuals under 30 and over 60 years of age were collected to analyze differences in sEVs proteomics. RESULTS: Based on PBA analysis, we found that sEVs from the serum of elderly individuals highly express TACSTD2 and identified a subpopulation marked by TACSTD2. Using ELISA, we verified the upregulation of TACSTD2 in serum from elderly human and aged mouse. In addition, we discovered that TACSTD2 was significantly increased in samples from tumor patients and had better diagnostic value than CEA. Specifically, 9 of the 13 tumor groups exhibited elevated TACSTD2, particularly for cervical cancer, colon cancer, esophageal carcinoma, liver cancer and thyroid carcinoma. Moreover, we found that serum sEVs from the elderly (especially those with high TACSTD2 levels) promoted tumor cell (SW480, HuCCT1 and HeLa) proliferation and migration. CONCLUSION: TACSTD2 was upregulated in the serum of elderly individuals and patients with tumors, and could serve as a dual biomarker for aging and tumors.

Comprehensive profiling of cancer neoantigens from aberrant RNA splicing.

BACKGROUND: Cancer neoantigens arise from protein-altering somatic mutations in tumor and rank among the most promising next-generation immuno-oncology agents when used in combination with immune checkpoint inhibitors. We previously developed a computational framework, REAL-neo, for identification, quality control, and prioritization of both class-I and class-II human leucocyte antigen (HLA)-presented neoantigens resulting from somatic single-nucleotide mutations, small insertions and deletions, and gene fusions. In this study, we developed a new module, SPLICE-neo, to identify neoantigens from aberrant RNA transcripts from two distinct sources: (1) DNA mutations within splice sites and (2) de novo RNA aberrant splicings. METHODS: First, SPLICE-neo was used to profile all DNA splice-site mutations in 11,892 tumors from The Cancer Genome Atlas (TCGA) and identified 11 profiles of splicing donor or acceptor site gains or losses. Transcript isoforms resulting from the top seven most frequent profiles were computed using novel logic models. Second, SPLICE-neo identified de novo RNA splicing events using RNA sequencing reads mapped to novel exon junctions from either single, double, or multiple exon-skipping events. The aberrant transcripts from both sources were then ranked based on isoform expression levels and z-scores assuming that individual aberrant splicing events are rare. Finally, top-ranked novel isoforms were translated into protein, and the resulting neoepitopes were evaluated for neoantigen potential using REAL-neo. The top splicing neoantigen candidates binding to HLA-A*02:01 were validated using in vitro T2 binding assays. RESULTS: We identified abundant splicing neoantigens in four representative TCGA cancers: BRCA, LUAD, LUSC, and LIHC. In addition to their substantial contribution to neoantigen load, several splicing neoantigens were potent tumor antigens with stronger bindings to HLA compared with the positive control of antigens from influenza virus. CONCLUSIONS: SPLICE-neo is the first tool to comprehensively identify and prioritize splicing neoantigens from both DNA splice-site mutations and de novo RNA aberrant splicings. There are two major advances of SPLICE-neo. First, we developed novel logic models that assemble and prioritize full-length aberrant transcripts from DNA splice-site mutations. Second, SPLICE-neo can identify exon-skipping events involving more than two exons, which account for a quarter to one-third of all skipping events.

The phosphatase inhibitor LB-100 creates neoantigens in colon cancer cells through perturbation of mRNA splicing.

Perturbation of protein phosphorylation represents an attractive approach to cancer treatment. Besides kinase inhibitors, protein phosphatase inhibitors have been shown to have anti-cancer activity. A prime example is the small molecule LB-100, an inhibitor of protein phosphatases 2A/5 (PP2A/PP5), enzymes that affect cellular physiology. LB-100 has proven effective in pre-clinical models in combination with immunotherapy, but the molecular underpinnings of this synergy remain understood poorly. We report here a sensitivity of the mRNA splicing machinery to phosphorylation changes in response to LB-100 in colorectal adenocarcinoma. We observe enrichment for differentially phosphorylated sites within cancer-critical splicing nodes of U2 snRNP, SRSF and hnRNP proteins. Altered phosphorylation endows LB-100-treated colorectal adenocarcinoma cells with differential splicing patterns. In PP2A-inhibited cells, over 1000 events of exon skipping and intron retention affect regulators of genomic integrity. Finally, we show that LB-100-evoked alternative splicing leads to neoantigens that are presented by MHC class 1 at the cell surface. Our findings provide a potential explanation for the pre-clinical and clinical observations that LB-100 sensitizes cancer cells to immune checkpoint blockade.

Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.

Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex (MHC), via the recognition of specific portions of their structure known as epitopes. More specifically, MHC class I introduces TTCAs to T-cell receptors (TCR) which are located on the surface of CD8+ T cells. However, TTCA sequences are varied and lead to struggles in vaccine design. Recently, Machine learning (ML) models have been developed to predict TTCA sequences which could aid in fast and correct TTCA identification. During the construction of the TTCA predictor, the peptide encoding strategy is an important step. Previous studies have used biological descriptors for encoding TTCA sequences. However, there have been no studies that use natural language processing (NLP), a potential approach for this purpose. As sentences have their own words with diverse properties, biological sequences also hold unique characteristics that reflect evolutionary information, physicochemical values, and structural information. We hypothesized that NLP methods would benefit the prediction of TTCA. To develop a new identifying TTCA model, we first constructed a based model with widely used ML algorithms and extracted features from biological descriptors. Then, to improve our model performance, we added extracted features from biological language models (BLMs) based on NLP methods. Besides, we conducted feature selection by using Chi-square and Pearson Correlation Coefficient techniques. Then, SMOTE, Up-sampling, and Near-Miss were used to treat unbalanced data. Finally, we optimized Sa-TTCA by the SVM algorithm to the four most effective feature groups. The best performance of Sa-TTCA showed a competitive balanced accuracy of 87.5% on a training set, and 72.0% on an independent testing set. Our results suggest that integrating biological descriptors with natural language processing has the potential to improve the precision of predicting protein/peptide functionality, which could be beneficial for developing cancer vaccines.

A new high-throughput screening methodology for the discovery of cancer-testis antigen using multi-omics data.

BACKGROUND: Cancer/testis antigens (CTAs), also known as tumor-specific antigens (TSAs) are specifically expressed in cancer cells and exhibit high immunogenicity, making them promising targets for immunotherapy and cancer vaccines. METHODS: A new integrated high-throughput screening methodology for CTAs was proposed in this study through combining DNA methylation and RNA sequencing data. Briefly, the genes with increased transcript level and decreased DNA methylation were identified by multi-omics analysis. RNA sequencing studies in cell lines exposed to DNA methyltransferase (DNMT) inhibitors were performed to validate the inherent causal relationship between DNA hypomethylation and gene expression upregulation. RESULTS: We proposed a new integrated high-throughput screening methodology for identification of CTAs using multi-omics analysis. In addition, we tested the feasibility of this method using gastric cancer (GC) as an example. In GC, we identified over 2000 primary candidate CTAs and ultimately identified 20 CTAs with significant tissue-specificity, including a testis-specific serine protease TESSP1/PRSS41. Integrated analysis confirmed that PRSS41 expression was reactivated in gastrointestinal cancers by promoter DNA hypomethylation at the CpG site (cg08104780). Additionally, DNA hypomethylation of PRSS41 predicted a poor prognosis in GC. CONCLUSION: We propose a new high-throughput screening method for the identification of CTAs in cancer and validate its effectiveness. Our work emphasizes that serine protease PRSS41 is a novel TSA that is reactivated in GC due to promoter DNA hypomethylation.

Identification and validation of regulatory T cell-associated gene signatures to predict colon adenocarcinoma prognosis.

Colon adenocarcinoma (COAD) is a common cause of cancer-related death. Due to the difficulty in early diagnosis and drug resistance, conventional treatments are difficult to be effective. Some studies have found that the functional recovery of T cells in the tumor microenvironment, especially regulatory T cells (Tregs), plays an important role in the progression of cancer. This study used the TCGA data set, clinical information and RNA-seq data of COAD patients to construct a Tregs-related risk score (TRS) through methods such as WGCNA, single-factor Cox, multi-factor Cox and random survival forest (RSF). Moreover, we also used the TCGA test set and internal validation set to verify the predictive ability of TRS, and used functional enrichment analysis and somatic mutation analysis to mine genes related to TRS, such as like thrombin/trypsin receptor 2 (F2RL2), inhibin subunit beta B (INHBB) and melanoma antigen family A12 (MAGEA12). Moreover, this study confirmed the expression of these prognostic genes using scRNA-seq data. We also performed qPCR analysis of various genes in normal and cancerous colon cancer cell lines to verify that these genes indeed play a role in CODA patients. We also constructed a mouse CODA model to study and evaluate the impact of key genes such as MAGEA12 on tumor growth in mice. This study explores the important role of Treg cells in the prognosis of COAD and discovers some potential biomarkers for the occurrence and development of COAD, which provides some new ideas for the treatment of COAD.

Armed with IL-2 based fusion protein improves CAR-T cell fitness and efficacy against solid tumors.

Chimeric antigen receptor T (CAR-T) cell therapy is regarded as a potent immunotherapy and has made significant success in hematologic malignancies by eliciting antigen-specific immune responses. However, response rates of CAR-T cell therapy against solid tumors with immunosuppressive microenvironments remain limited. Co-engineering strategies are advancing methods to overcome immunosuppressive barriers and enhance antitumor responses. Here, we engineered an IL-2 mutein co-engineered CAR-T for the improvement of CAR-T cells against solid tumors and the efficient inhibition of solid tumors. We equipped the CAR-T cells with co-expressing both tumor antigen-targeted CAR and a mutated human interleukin-2 (IL-2m), conferring enhanced CAR-T cells fitness in vitro, reshaped immune-excluded TME, enhanced CAR-T infiltration in solid tumors, and improved tumor control without significant systemic toxicity. Overall, this subject demonstrates the universal CAR-T cells armed strategy for the development and optimization of CAR-T cells against solid tumors.

TROP2 promotes PINK1-mediated mitophagy and apoptosis to accelerate the progression of senile chronic obstructive pulmonary disease by up-regulating DRP1 expression.

Chronic obstructive pulmonary disease (COPD) is a chronic airway inflammatory disease characterised by irreversible airflow limitation. The elderly are a vulnerable population for developing COPD. With the growth of age, physiological degenerative changes occur in the thorax, bronchus, lung and vascular wall, which can lead to age-related physiological attenuation of lung function in the elderly, so the prevalence of COPD increases with age. Its pathogenesis has not yet been truly clarified. Mitophagy plays an important role in maintaining the stability of mitochondrial function and intracellular environment by scavenging damaged mitochondria. Currently, studies have shown that trophoblast antigen 2 (TROP2) expression is up-regulated in airway basal cells of patients with COPD, suggesting that TROP2 is involved in the progression of COPD. However, whether it is involved in disease progression by regulating mitochondrial function remains unclear. In this study, compared with non-smoking non-COPD patients, the expression of TROP2 in lung tissues of smoking non-COPD patients and patients with COPD increased, and TROP2 expression in patients with COPD was higher than that in smoking non-COPD patients. To further explore the role of TROP2, we stimulated BEAS-2B with cigarette smoke to construct an in vitro model. We found that TROP2 expression increased, whereas TROP2 silencing reversed the cigarette smoke extract-induced decrease in mitochondrial membrane potential, increased reactive oxygen species content, decreased adenosine triphosphate (ATP) production, increased inflammatory factor secretion and increased apoptosis. In addition, we searched online bioinformatics and screened the gene dynamin-related protein 1 (DRP1) related to mitophagy as the research object. Co-IP assay verified the binding relationship between DRP1 and TROP2. Further study found that TROP2 promoted mitophagy and apoptosis of BEAS-2B cells by up-regulating the expression of DRP1. In addition, PTEN-induced putative kinase 1 (PINK1) is a potential binding protein of DRP1, and DRP1 accelerated mitophagy and apoptosis of BEAS-2B cells by promoting the expression of PINK1. We established a COPD SD rat model by cigarette smoke exposure and LPS instillation and treated it by intraperitoneal injection of si-TROP2. The results showed that TROP2 silencing restored lung function and reduced the secretion of inflammatory factors in bronchoalveolar lavage fluid. In conclusion, TROP2 can be used as a new reference for COPD treatment.

Autophagy degrades immunogenic endogenous retroelements induced by 5-azacytidine in acute myeloid leukemia.

The hypomethylating agent 5-azacytidine (AZA) is the first-line treatment for AML patients unfit for intensive chemotherapy. The effect of AZA results in part from T-cell cytotoxic responses against MHC-I-associated peptides (MAPs) deriving from hypermethylated genomic regions such as cancer-testis antigens (CTAs), or endogenous retroelements (EREs). However, evidence supporting higher ERE MAPs presentation after AZA treatment is lacking. Therefore, using proteogenomics, we examined the impact of AZA on the repertoire of MAPs and their source transcripts. AZA-treated AML upregulated both CTA and ERE transcripts, but only CTA MAPs were presented at greater levels. Upregulated ERE transcripts triggered innate immune responses against double-stranded RNAs but were degraded by autophagy, and not processed into MAPs. Autophagy resulted from the formation of protein aggregates caused by AZA-dependent inhibition of DNMT2. Autophagy inhibition had an additive effect with AZA on AML cell proliferation and survival, increased ERE levels, increased pro-inflammatory responses, and generated immunogenic tumor-specific ERE-derived MAPs. Finally, autophagy was associated with a lower abundance of CD8+ T-cell markers in AML patients expressing high levels of EREs. This work demonstrates that AZA-induced EREs are degraded by autophagy and shows that inhibiting autophagy can improve the immune recognition of AML blasts in treated patients.

Identification and affinity enhancement of T-cell receptor targeting a KRASG12V cancer neoantigen.

Neoantigens derived from somatic mutations in Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS), the most frequently mutated oncogene, represent promising targets for cancer immunotherapy. Recent research highlights the potential role of human leukocyte antigen (HLA) allele A*11:01 in presenting these altered KRAS variants to the immune system. In this study, we successfully generate and identify murine T-cell receptors (TCRs) that specifically recognize KRAS8-16G12V from three predicted high affinity peptides. By determining the structure of the tumor-specific 4TCR2 bound to KRASG12V-HLA-A*11:01, we conduct structure-based design to create and evaluate TCR variants with markedly enhanced affinity, up to 15.8-fold. This high-affinity TCR mutant, which involved only two amino acid substitutions, display minimal conformational alterations while maintaining a high degree of specificity for the KRASG12V peptide. Our research unveils the molecular mechanisms governing TCR recognition towards KRASG12V neoantigen and yields a range of affinity-enhanced TCR mutants with significant potential for immunotherapy strategies targeting tumors harboring the KRASG12V mutation.

Personalized Cancer Vaccines Directed against Tumor Mutations: Building Evidence from Mice to Humans.

Personalized vaccines directed to tumor mutations have recently gained significant momentum. On the basis of the concept of stimulating T-cell responses against neoantigens encoded by a tumor's host of personal mutations, these vaccines utilize genome or exome sequencing, mutation calling, and epitope prediction followed by manufacturing of a customized vaccine for each patient. In their 2012 Cancer Research publication, Castle and colleagues provided evidence that vaccinating with long peptide vaccines encompassing neoantigens can generate robust immune responses and induce antitumor activity in a mouse B16F10 melanoma. This approach, harnessing the exquisite specificity of mutations to the tumor and thus providing an effective target for cancer vaccines, was subsequently shown to be safe and immunogenic in a series of small first in man trials in patients with melanoma. The field has accelerated and expanded substantially over the last 5 years, propelled by increasing evidence for vaccine-mediated clinical efficacy, leading to ongoing registrational trials using personalized RNA neoantigen vaccines in patients with melanoma and several other malignancies. See related article by Castle and colleagues, Cancer Res 2012;72:1081-91.

Untranslated regions (UTRs) are a potential novel source of neoantigens for personalised immunotherapy.

Background: Neoantigens, mutated tumour-specific antigens, are key targets of anti-tumour immunity during checkpoint inhibitor (CPI) treatment. Their identification is fundamental to designing neoantigen-directed therapy. Non-canonical neoantigens arising from the untranslated regions (UTR) of the genome are an overlooked source of immunogenic neoantigens. Here, we describe the landscape of UTR-derived neoantigens and release a computational tool, PrimeCUTR, to predict UTR neoantigens generated by start-gain and stop-loss mutations. Methods: We applied PrimeCUTR to a whole genome sequencing dataset of pre-treatment tumour samples from CPI-treated patients (n = 341). Cancer immunopeptidomic datasets were interrogated to identify MHC class I presentation of UTR neoantigens. Results: Start-gain neoantigens were predicted in 72.7% of patients, while stop-loss mutations were found in 19.3% of patients. While UTR neoantigens only accounted 2.6% of total predicted neoantigen burden, they contributed 12.4% of neoantigens with high dissimilarity to self-proteome. More start-gain neoantigens were found in CPI responders, but this relationship was not significant when correcting for tumour mutational burden. While most UTR neoantigens are private, we identified two recurrent start-gain mutations in melanoma. Using immunopeptidomic datasets, we identify two distinct MHC class I-presented UTR neoantigens: one from a recurrent start-gain mutation in melanoma, and one private to Jurkat cells. Conclusion: PrimeCUTR is a novel tool which complements existing neoantigen discovery approaches and has potential to increase the detection yield of neoantigens in personalised therapeutics, particularly for neoantigens with high dissimilarity to self. Further studies are warranted to confirm the expression and immunogenicity of UTR neoantigens.

Lack of shared neoantigens in prevalent mutations in cancer.

Tumors are mostly characterized by genetic instability, as result of mutations in surveillance mechanisms, such as DNA damage checkpoint, DNA repair machinery and mitotic checkpoint. Defect in one or more of these mechanisms causes additive accumulation of mutations. Some of these mutations are drivers of transformation and are positively selected during the evolution of the cancer, giving a growth advantage on the cancer cells. If such mutations would result in mutated neoantigens, these could be actionable targets for cancer vaccines and/or adoptive cell therapies. However, the results of the present analysis show, for the first time, that the most prevalent mutations identified in human cancers do not express mutated neoantigens. The hypothesis is that this is the result of the selection operated by the immune system in the very early stages of tumor development. At that stage, the tumor cells characterized by mutations giving rise to highly antigenic non-self-mutated neoantigens would be efficiently targeted and eliminated. Consequently, the outgrowing tumor cells cannot be controlled by the immune system, with an ultimate growth advantage to form large tumors embedded in an immunosuppressive tumor microenvironment (TME). The outcome of such a negative selection operated by the immune system is that the development of off-the-shelf vaccines, based on shared mutated neoantigens, does not seem to be at hand. This finding represents the first demonstration of the key role of the immune system on shaping the tumor antigen presentation and the implication in the development of antitumor immunological strategies.

Multiplex genetic manipulations in Clostridium butyricum and Clostridium sporogenes to secrete recombinant antigen proteins for oral-spore vaccination.

BACKGROUND: Clostridium spp. has demonstrated therapeutic potential in cancer treatment through intravenous or intratumoral administration. This approach has expanded to include non-pathogenic clostridia for the treatment of various diseases, underscoring the innovative concept of oral-spore vaccination using clostridia. Recent advancements in the field of synthetic biology have significantly enhanced the development of Clostridium-based bio-therapeutics. These advancements are particularly notable in the areas of efficient protein overexpression and secretion, which are crucial for the feasibility of oral vaccination strategies. Here, we present two examples of genetically engineered Clostridium candidates: one as an oral cancer vaccine and the other as an antiviral oral vaccine against SARS-CoV-2. RESULTS: Using five validated promoters and a signal peptide derived from Clostridium sporogenes, a series of full-length NY-ESO-1/CTAG1, a promising cancer vaccine candidate, expression vectors were constructed and transformed into C. sporogenes and Clostridium butyricum. Western blotting analysis confirmed efficient expression and secretion of NY-ESO-1 in clostridia, with specific promoters leading to enhanced detection signals. Additionally, the fusion of a reported bacterial adjuvant to NY-ESO-1 for improved immune recognition led to the cloning difficulties in E. coli. The use of an AUU start codon successfully mitigated potential toxicity issues in E. coli, enabling the secretion of recombinant proteins in C. sporogenes and C. butyricum. We further demonstrate the successful replacement of PyrE loci with high-expression cassettes carrying NY-ESO-1 and adjuvant-fused NY-ESO-1, achieving plasmid-free clostridia capable of secreting the antigens. Lastly, the study successfully extends its multiplex genetic manipulations to engineer clostridia for the secretion of SARS-CoV-2-related Spike_S1 antigens. CONCLUSIONS: This study successfully demonstrated that C. butyricum and C. sporogenes can produce the two recombinant antigen proteins (NY-ESO-1 and SARS-CoV-2-related Spike_S1 antigens) through genetic manipulations, utilizing the AUU start codon. This approach overcomes challenges in cloning difficult proteins in E. coli. These findings underscore the feasibility of harnessing commensal clostridia for antigen protein secretion, emphasizing the applicability of non-canonical translation initiation across diverse species with broad implications for medical or industrial biotechnology.

Methods behind neoantigen prediction for personalized anticancer vaccines.

Next to conventional cancer therapies, immunotherapies such as immune checkpoint inhibitors have broadened the cancer treatment landscape over the past decades. Recent advances in next generation sequencing and bioinformatics technologies have made it possible to identify a patient's own immunogenic neoantigens. These cancer neoantigens serve as important targets for personalized immunotherapy which has the benefit of being more active and effective in targeting cancer cells. This paper is a step-by-step guide discussing the different analyses and challenges encountered during in-silico neoantigen prediction. The protocol describes all the tools and steps required for the identification of immunogenic neoantigens.