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.

Construction of lymph nodes-targeting tumor vaccines by using the principle of DNA base complementary pairing to enhance anti-tumor cellular immune response.

Tumor vaccines, a crucial immunotherapy, have gained growing interest because of their unique capability to initiate precise anti-tumor immune responses and establish enduring immune memory. Injected tumor vaccines passively diffuse to the adjacent draining lymph nodes, where the residing antigen-presenting cells capture and present tumor antigens to T cells. This process represents the initial phase of the immune response to the tumor vaccines and constitutes a pivotal determinant of their effectiveness. Nevertheless, the granularity paradox, arising from the different requirements between the passive targeting delivery of tumor vaccines to lymph nodes and the uptake by antigen-presenting cells, diminishes the efficacy of lymph node-targeting tumor vaccines. This study addressed this challenge by employing a vaccine formulation with a tunable, controlled particle size. Manganese dioxide (MnO2) nanoparticles were synthesized, loaded with ovalbumin (OVA), and modified with A50 or T20 DNA single strands to obtain MnO2/OVA/A50 and MnO2/OVA/T20, respectively. Administering the vaccines sequentially, upon reaching the lymph nodes, the two vaccines converge and simultaneously aggregate into MnO2/OVA/A50-T20 particles through base pairing. This process enhances both vaccine uptake and antigen delivery. In vitro and in vivo studies demonstrated that, the combined vaccine, comprising MnO2/OVA/A50 and MnO2/OVA/T20, exhibited robust immunization effects and remarkable anti-tumor efficacy in the melanoma animal models. The strategy of controlling tumor vaccine size and consequently improving tumor antigen presentation efficiency and vaccine efficacy via the DNA base-pairing principle, provides novel concepts for the development of efficient tumor vaccines.

Chimeric antigen receptor-natural killer cell therapy: current advancements and strategies to overcome challenges.

Chimeric antigen receptor-natural killer (CAR-NK) cell therapy is a novel immunotherapy targeting cancer cells via the generation of chimeric antigen receptors on NK cells which recognize specific cancer antigens. CAR-NK cell therapy is gaining attention nowadays owing to the ability of CAR-NK cells to release potent cytotoxicity against cancer cells without side effects such as cytokine release syndrome (CRS), neurotoxicity and graft-versus-host disease (GvHD). CAR-NK cells do not require antigen priming, thus enabling them to be used as "off-the-shelf" therapy. Nonetheless, CAR-NK cell therapy still possesses several challenges in eliminating cancer cells which reside in hypoxic and immunosuppressive tumor microenvironment. Therefore, this review is envisioned to explore the current advancements and limitations of CAR-NK cell therapy as well as discuss strategies to overcome the challenges faced by CAR-NK cell therapy. This review also aims to dissect the current status of clinical trials on CAR-NK cells and future recommendations for improving the effectiveness and safety of CAR-NK cell therapy.

Exploring dendritic cell subtypes in cancer immunotherapy: unraveling the role of mature regulatory dendritic cells.

Dendritic cells (DCs) possess a specialized function in presenting antigens and play pivotal roles in both innate and adaptive immune responses. Their ability to cross-present antigens from tumor cells to naïve T cells is instrumental in generating specific T-cell-mediated antitumor responses, crucial for controlling tumor growth and preventing tumor cell dissemination. However, within a tumor immune microenvironment (TIME), the functions of DCs can be significantly compromised. This review focuses on the profile, function, and activation of DCs, leveraging recent studies that reveal insights into their phenotype acquisition, transcriptional state, and functional programs through single-cell RNA sequence (scRNA-seq) analysis. Additionally, the therapeutic potential of DC-mediated tumor antigen sensing in priming antitumor immunity is discussed.

Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines.

Peptide antigens derived from tumors have been observed to elicit protective immune responses, categorized as either tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs). Subunit cancer vaccines incorporating these antigens have shown promise in inducing protective immune responses, leading to cancer prevention or eradication. Over recent years, peptide-based cancer vaccines have gained popularity as a treatment modality and are often combined with other forms of cancer therapy. Several clinical trials have explored the safety and efficacy of peptide-based cancer vaccines, with promising outcomes. Advancements in techniques such as whole-exome sequencing, next-generation sequencing, and in silico methods have facilitated the identification of antigens, making it increasingly feasible. Furthermore, the development of novel delivery methods and a deeper understanding of tumor immune evasion mechanisms have heightened the interest in these vaccines among researchers. This article provides an overview of novel insights regarding advancements in the field of peptide-based vaccines as a promising therapeutic avenue for cancer treatment. It summarizes existing computational methods for tumor neoantigen prediction, ongoing clinical trials involving peptide-based cancer vaccines, and recent studies on human vaccination experiments.

RNA aggregates harness the danger response for potent cancer immunotherapy.

Cancer immunotherapy remains limited by poor antigenicity and a regulatory tumor microenvironment (TME). Here, we create "onion-like" multi-lamellar RNA lipid particle aggregates (LPAs) to substantially enhance the payload packaging and immunogenicity of tumor mRNA antigens. Unlike current mRNA vaccine designs that rely on payload packaging into nanoparticle cores for Toll-like receptor engagement in immune cells, systemically administered RNA-LPAs activate RIG-I in stromal cells, eliciting massive cytokine/chemokine response and dendritic cell/lymphocyte trafficking that provokes cancer immunogenicity and mediates rejection of both early- and late-stage murine tumor models. In client-owned canines with terminal gliomas, RNA-LPAs improved survivorship and reprogrammed the TME, which became "hot" within days of a single infusion. In a first-in-human trial, RNA-LPAs elicited rapid cytokine/chemokine release, immune activation/trafficking, tissue-confirmed pseudoprogression, and glioma-specific immune responses in glioblastoma patients. These data support RNA-LPAs as a new technology that simultaneously reprograms the TME while eliciting rapid and enduring cancer immunotherapy.

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.

Engineered Bacteriophage-Based In Situ Vaccine Remodels a Tumor Microenvironment and Elicits Potent Antitumor Immunity.

In situ vaccines (ISVs) utilize the localized delivery of chemotherapeutic agents or radiotherapy to stimulate the release of endogenous antigens from tumors, thereby eliciting systemic and persistent immune activation. Recently, a bioinspired ISV strategy has attracted tremendous attention due to its features such as an immune adjuvant effect and genetic plasticity. M13 bacteriophages are natural nanomaterials with intrinsic immunogenicity, genetic flexibility, and cost-effectiveness for large-scale production, demonstrating the potential for application in cancer vaccines. In this study, we propose an ISV based on the engineered M13 bacteriophage targeting CD40 (M13CD40) for dendritic cell (DC)-targeted immune stimulation, named H-GM-M13CD40. We induce immunogenic cell death and release tumor antigens through local delivery of (S)-10-hydroxycamptothecin (HCPT), followed by intratumoral injection of granulocyte-macrophage colony stimulating factor (GM-CSF) and M13CD40 to enhance DC recruitment and activation. We demonstrate that this ISV strategy can result in significant accumulation and activation of DCs at the tumor site, reversing the immunosuppressive tumor microenvironment. In addition, H-GM-M13CD40 can synergize with the PD-1 blockade and induce abscopal effects in cold tumor models. Overall, our study verifies the immunogenicity of the engineered M13CD40 bacteriophage and provides a proof of concept that the engineered M13CD40 phage can function as an adjuvant for ISVs.

Serum Mac-2 binding protein glycosylation isomer and galectin-3 levels in adult-onset Still's disease and their association with cytokines.

Background: Autoinflammation with cytokine dysregulation may be implicated in the pathophysiology of adult-onset Still's disease (AOSD); however, the relationship between galectins and cytokines in patients with active AOSD remains unknown. We aimed to examine the relationship between circulating cytokines/chemokines and galectin-3 (Gal-3) or its ligand, Mac-2 binding protein glycosylation isomer (M2BPGi), in Japanese patients with AOSD. Methods: We recruited 44 consecutive patients diagnosed with AOSD according to the Yamaguchi criteria, 50 patients with rheumatoid arthritis (RA) as disease controls, and 27 healthy participants. Serum M2BPGi levels were directly measured using a HISCL M2BPGi reagent kit and an automatic immunoanalyzer (HISCL-5000). Serum Gal-3 concentrations were measured by enzyme-linked immunosorbent assay. The serum levels of 69 cytokines were analyzed in patients with AOSD using a multi-suspension cytokine array. We performed a cluster analysis of each cytokine expressed in patients with AOSD to identify specific molecular networks. Results: Significant increases in the serum concentrations of Gal-3 and M2BPGi were found in the serum of patients with AOSD compared with patients with RA and healthy participants (both p <0.001). There were significant positive correlations between serum Gal-3 levels and AOSD disease activity score (Pouchot score, r=0.66, p <0.001) and serum ferritin levels. However, no significant correlations were observed between serum M2BPGi levels and AOSD disease activity scores (Pouchot score, r = 0.32, p = 0.06) or serum ferritin levels. Furthermore, significant correlations were observed between the serum levels of Gal-3 and various inflammatory cytokines, including interleukin-18, in patients with AOSD. Immunosuppressive treatment in patients with AOSD significantly reduced serum Gal-3 and M2BPGi levels (p = 0.03 and 0.004, respectively). Conclusions: Although both Gal-3 and M2BPGi were elevated in patients with AOSD, only Gal-3 was a useful biomarker for predicting disease activity in AOSD. Our findings suggest that circulating Gal-3 reflects the inflammatory component of AOSD, which corresponds to proinflammatory cytokine induction through inflammasome activation cascades.

Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy.

BACKGROUND: Tumor-associated antigens and their derived peptides constitute an opportunity to design off-the-shelf mainline or adjuvant anti-cancer immunotherapies for a broad array of patients. A performant and rational antigen selection pipeline would lay the foundation for immunotherapy trials with the potential to enhance treatment, tremendously benefiting patients suffering from rare, understudied cancers. METHODS: We present an experimentally validated, data-driven computational pipeline that selects and ranks antigens in a multipronged approach. In addition to minimizing the risk of immune-related adverse events by selecting antigens based on their expression profile in tumor biopsies and healthy tissues, we incorporated a network analysis-derived antigen indispensability index based on computational modeling results, and candidate immunogenicity predictions from a machine learning ensemble model relying on peptide physicochemical characteristics. RESULTS: In a model study of uveal melanoma, Human Leukocyte Antigen (HLA) docking simulations and experimental quantification of the peptide-major histocompatibility complex binding affinities confirmed that our approach discriminates between high-binding and low-binding affinity peptides with a performance similar to that of established methodologies. Blinded validation experiments with autologous T-cells yielded peptide stimulation-induced interferon-γ secretion and cytotoxic activity despite high interdonor variability. Dissecting the score contribution of the tested antigens revealed that peptides with the potential to induce cytotoxicity but unsuitable due to potential tissue damage or instability of expression were properly discarded by the computational pipeline. CONCLUSIONS: In this study, we demonstrate the feasibility of the de novo computational selection of antigens with the capacity to induce an anti-tumor immune response and a predicted low risk of tissue damage. On translation to the clinic, our pipeline supports fast turn-around validation, for example, for adoptive T-cell transfer preparations, in both generalized and personalized antigen-directed immunotherapy settings.

State of the Art in CAR-T Cell Therapy for Solid Tumors: Is There a Sweeter Future?

Chimeric antigen receptor (CAR)-T cell therapy has proven to be a powerful treatment for hematological malignancies. The situation is very different in the case of solid tumors, for which no CAR-T-based therapy has yet been approved. There are many factors contributing to the absence of response in solid tumors to CAR-T cells, such as the immunosuppressive tumor microenvironment (TME), T cell exhaustion, or the lack of suitable antigen targets, which should have a stable and specific expression on tumor cells. Strategies being developed to improve CAR-T-based therapy for solid tumors include the use of new-generation CARs such as TRUCKs or bi-specific CARs, the combination of CAR therapy with chemo- or radiotherapy, the use of checkpoint inhibitors, and the use of oncolytic viruses. Furthermore, despite the scarcity of targets, a growing number of phase I/II clinical trials are exploring new solid-tumor-associated antigens. Most of these antigens are of a protein nature; however, there is a clear potential in identifying carbohydrate-type antigens associated with tumors, or carbohydrate and proteoglycan antigens that emerge because of aberrant glycosylations occurring in the context of tumor transformation.

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.

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.

Unlocking the paracrine crosstalk: adipocyte-derived factors affect carbonic anhydrase IX expression in colon and breast cancer cells.

Obesity is a major public health concern because it increases the risk of several diseases, including cancer. Crosstalk between obesity and cancer seems to be very complex, and the interaction between adipocytes and cancer cells leads to changes in adipocytes' function and their paracrine signaling, promoting a microenvironment that supports tumor growth. Carbonic anhydrase IX (CA IX) is a tumor-associated enzyme that not only participates in pH regulation but also facilitates metabolic reprogramming and supports the migration, invasion, and metastasis of cancer cells. In addition, CA IX expression, predominantly regulated via hypoxia-inducible factor (HIF-1), serves as a surrogate marker of hypoxia. In this study, we investigated the impact of adipocytes and adipocyte-derived factors on the expression of CA IX in colon and breast cancer cells. We observed increased expression of CA9 mRNA as well as CA IX protein in the presence of adipocytes and adipocyte-derived conditioned medium. Moreover, we confirmed that adipocytes affect the hypoxia signaling pathway and that the increased CA IX expression results from adipocyte-mediated induction of HIF-1α. Furthermore, we demonstrated that adipocyte-mediated upregulation of CA IX leads to increased migration and decreased adhesion of colon cancer cells. Finally, we brought experimental evidence that adipocytes, and more specifically leptin, upregulate CA IX expression in cancer cells and consequently promote tumor progression.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. OBJECTIVE: This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. DESIGN: A retrospective case control, diagnostic accuracy study. METHODS: This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. RESULTS: The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. CONCLUSION: This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

A new tool to predict aggressive lung cancer types before surgeryWe developed a tool to help doctors determine whether lung cancer is one of the more dangerous types, called micropapillary (MPP) or solid (SOL) patterns, before surgery. These patterns can be more harmful and spread quickly, so knowing they are there can help doctors plan the best treatment. We looked at the cases of 273 lung cancer patients who had surgery and found that 61 of them had these aggressive cancer types. To predict these patterns, we used a computer process known as logistic regression, analyzing CT scan details, health information, and blood tests for cancer markers. Based on CT scans, our tool was very good at predicting whether these patterns were present in two patient groups. However, predictions using only basic health information like the size of the tumor and whether the patient smoked needed to be more accurate. We found a way to make our predictions even better. Combining all information into one chart, known as a nomogram, significantly improved our ability to predict these dangerous cancer patterns. This combined chart could be a big help for doctors. It gives them a clearer picture of the cancer's aggressiveness before surgery, which can guide them to choose the best treatment options. This approach aims to offer a better understanding of the tumor, leading to more tailored and effective treatments for patients facing lung cancer.

Inhibitors of dermatan sulfate epimerase 1 decreased accumulation of glycosaminoglycans in mucopolysaccharidosis type I fibroblasts.

Genetic deficiency of alpha-L-iduronidase causes mucopolysaccharidosis type I (MPS-I) disease, due to accumulation of glycosaminoglycans (GAGs) including chondroitin/dermatan sulfate (CS/DS) and heparan sulfate (HS) in cells. Currently, patients are treated by infusion of recombinant iduronidase or by hematopoietic stem cell transplantation. An alternative approach is to reduce the L-iduronidase substrate, through limiting the biosynthesis of iduronic acid. Our earlier study demonstrated that ebselen attenuated GAGs accumulation in MPS-I cells, through inhibiting iduronic acid producing enzymes. However, ebselen has multiple pharmacological effects, which prevents its application for MPS-I. Thus, we continued the study by looking for novel inhibitors of dermatan sulfate epimerase 1 (DS-epi1), the main responsible enzyme for production of iduronic acid in CS/DS chains. Based on virtual screening of chemicals towards chondroitinase AC, we constructed a library with 1,064 compounds that were tested for DS-epi1 inhibition. Seventeen compounds were identified to be able to inhibit 27%-86% of DS-epi1 activity at 10 µM. Two compounds were selected for further investigation based on the structure properties. The results show that both inhibitors had a comparable level in inhibition of DS-epi1while they had negligible effect on HS epimerase. The two inhibitors were able to reduce iduronic acid biosynthesis in CS/DS and GAG accumulation in WT and MPS-I fibroblasts. Docking of the inhibitors into DS-epi1 structure shows high affinity binding of both compounds to the active site. The collected data indicate that these hit compounds may be further elaborated to a potential lead drug used for attenuation of GAGs accumulation in MPS-I patients.

Can hypoxia marker carbonic anhydrase IX serve as a potential new diagnostic marker and therapeutic target of non-small cell lung cancer?

Lung cancer represents the leading cause of cancer-related deaths. Non-small cell lung cancer (NSCLC), the most common form of lung cancer, is a molecularly heterogeneous disease with intratumoral heterogeneity and a significant mutational burden associated with clinical outcome. Tumor microenvironment (TME) plays a fundamental role in the initiation and progression of primary de novo lung cancer and significantly influences the response of tumor cells to therapy. Hypoxia, an integral part of the tumor microenvironment and a serious clinical phenomenon, is associated with increased genetic instability and a more aggressive phenotype of NSCLC, which correlates with the risk of metastasis. Low oxygen concentration influences all components of TME including the immune microenvironment. Hypoxia-inducible pathway activated in response to low oxygen supply mediates the expression of genes important for the adaptation of tumor cells to microenvironmental changes. A highly active transmembrane hypoxia-induced metalloenzyme - carbonic anhydrase IX (CAIX), as a part of transport metabolon, contributes to the maintenance of intracellular pH within physiological values and to the acidification of the extracellular space. CAIX supports cell migration and invasion and plays an important role in NSCLC tumor tissue and pleural effusion. Due to its high expression, it also represents a potential diagnostic differential biomarker and therapeutic target in NSCLC. To test new potential targeted therapeutic compounds, suitable models are required that more faithfully simulate tumor tissue, TME components, and spatial architecture.

Predictability of B cell clonal persistence and immunosurveillance in breast cancer.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Immunogenic cell death-based cancer vaccines: promising prospect in cancer therapy.

Tumor immunotherapy is a promising approach for addressing the limitations of conventional tumor treatments, such as chemotherapy and radiotherapy, which often have side effects and fail to prevent recurrence and metastasis. However, the effectiveness and sustainability of immune activation in tumor immunotherapy remain challenging. Tumor immunogenic cell death, characterized by the release of immunogenic substances, damage associated molecular patterns (DAMPs), and tumor associated antigens, from dying tumor cells (DTCs), offers a potential solution. By enhancing the immunogenicity of DTCs through the inclusion of more immunogenic antigens and stimulating factors, immunogenic cell death (ICD) based cancer vaccines can be developed as a powerful tool for immunotherapy. Integrating ICD nanoinducers into conventional treatments like chemotherapy, photodynamic therapy, photothermal therapy, sonodynamic therapy, and radiotherapy presents a novel strategy to enhance treatment efficacy and potentially improve patient outcomes. Preclinical research has identified numerous potential ICD inducers. However, effectively translating these findings into clinically relevant applications remains a critical challenge. This review aims to contribute to this endeavor by providing valuable insights into the in vitro preparation of ICD-based cancer vaccines. We explored established tools for ICD induction, followed by an exploration of personalized ICD induction strategies and vaccine designs. By sharing this knowledge, we hope to stimulate further development and advancement in the field of ICD-based cancer vaccines.