Effective Immunotherapy Research Articles

The Dual Role of B Cells in the Tumor Microenvironment: Implications for Cancer Immunology and Therapy.

The tumor microenvironment (TME) is a complex and heterogeneous tissue composed of various cell types, including tumor cells, stromal cells, and immune cells, as well as non-cellular elements. Given their pivotal role in humoral immunity, B cells have emerged as promising targets for anti-tumor therapies. The dual nature of B cells, exhibiting both tumor-suppressive and tumor-promoting functions, has garnered significant attention. Understanding the distinct effects of various B cell subsets on different tumors could pave the way for novel targeted tumor therapies. This review provides a comprehensive overview of the heterogeneous B cell subsets and their multifaceted roles in tumorigenesis, as well as the therapeutic potential of targeting B cells in cancer treatment. To develop more effective cancer immunotherapies, it is essential to decipher the heterogeneity of B cells and their roles in shaping the TME.

Triggered Cascade-Activation Nanoplatform to Alleviate Hypoxia for Effective Tumor Immunotherapy Guided by NIR-II Imaging.

Hypoxia is one of the most typical features among various types of solid tumors, which creates an immunosuppressive tumor microenvironment (TME) and limits the efficacy of cancer treatment. Alleviating hypoxia becomes a key strategy to reshape hypoxic TME which improves cancer immunotherapy. However, it remains challenging to perform tumor precision therapy with controllable switches through hypoxia-activated gene editing and prodrugs to alleviate hypoxia. In this study, silica-coated second near-infrared window (NIR-II) emitting silver sulfide quantum dots are used as the carrier to load the Clustered Regularly Interspaced Short Palindromic Repeats/Cas9 (CRISPR/Cas9) system to target hypoxia-inducible factor-1 (HIF-1α) and guide tumor-targeted imaging. To reduce the off-target effects in nontumor cells and better control safety risks, a TME-triggered cascade-activation nanodiagnostic and therapeutic platform (AA@Cas-H@HTS) is designed, which achieves the hypoxia activation of prodrug tirapazamine (TPZ) and spatiotemporal release of CRISPR/Cas9 ribonucleoprotein. Tumor hypoxia is greatly alleviated by the synergistic function of HIF-1α depletion by gene editing and TPZ activation. Importantly, targeting HIF-1α disrupts the programmed cell death 1/programmed cell death ligand 1 (PD-1/PD-L1) signaling pathway, which effectively reshapes the immune-suppressive TME and activates T cell-mediated antitumor immunity. Taken together, we have provided a TME-triggered cascade-activation nanoplatform to alleviate hypoxia for improved cancer immunotherapy.

Full-active pharmaceutical ingredient nanosensitizer for augmented photoimmunotherapy by synergistic mitochondria targeting and immunogenic death inducing.

The precise and effective activation of the immune response is crucial in promising therapy curing cancer. Photoimmunotherapy (PIT) is an emerging strategy for precise regulation and highly spatiotemporal selectivity. However, this approach faces a significant challenge due to the off-target effect and the immunosuppressive microenvironment. To address this challenge, a nanoscale full-active pharmaceutical ingredient (API) photo-immune stimulator was developed. This formulation overcomes the limitations of PIT by strengthening the ability to penetrate tumors deeply and inducing precise and potent mitochondria-targeted dual-mode photodynamic therapy and photothermal therapy. Along with inhibiting overexpressed Hsp90, this nanosensitizer in turn improves the immunosuppressive microenvironment. Ultimately, this mitochondria-targeted PIT demonstrated potent antitumor efficacy, achieving a remarkable inhibition rate of ≥95% for both established primary tumors and distant abscopal tumors. In conclusion, this novel self-delivery full-API nanosystem enhances the efficacy of phototherapy and reprograms the immunosuppressive microenvironment, thereby holding great promise in the development of precise and effective immunotherapy.

Comparative efficacy of anthracycline-free and anthracycline-containing neoadjuvant chemoimmunotherapy regimens for triple-negative breast cancer

BackgroundThe selection of appropriate chemotherapy backbone agents in combination with neoadjuvant immunotherapy for triple-negative breast cancer (TNBC) remains unclear. Herein, we aimed to evaluate the efficacy and safety of anthracycline-free and anthracycline-containing regimens coupled with neoadjuvant immunotherapy. MethodThis retrospective study included 87 patients with TBNC who received neoadjuvant immunotherapy combined with various chemotherapy regimens at three research centers from November 2020 to November 2023. The primary objective was pathological complete response (pCR), while secondary objectives included overall response rates, event-free survival (EFS), and the incidence of adverse events. A subgroup analysis was performed to delineate patients who may substantially benefit from distinct therapeutic strategies. ResultsCoupled with immunotherapy, anthracycline-free regimens achieved comparable pCR rates (55.1 % vs. 51.4 %; Odds ratio, 1.16; 95 % confidence interval [CI], 0.49–2.74; p = 0.73) and EFS (Hazard ratio, 0.66; 95 % CI, 0.18–2.45; p = 0.53) to anthracycline-containing regimens. According to subgroup analyses, the tumor stage (p = 0.017) and lymph node stage (p = 0.011) exhibit contradictory predictive power for the pCR rate of anthracycline-free regimens when compared with that of anthracycline-containing regimens. Specifically, anthracycline-free regimens yielded significantly higher pCR rates in patients without lymph node metastasis than anthracycline-containing regimens (p = 0.021). Pooled analyses further confirmed the results of both total and subgroup analyses. Most adverse events were grades 1–2, and no new adverse reactions were observed. ConclusionAnthracycline-free neoadjuvant chemotherapy regimens could serve as an effective and safe alternative immunotherapy partner for patients with TNBC, particularly in those without lymph node metastasis.

BTN2A1: A Novel Target to Boost Tumor Killing Capacity of Human γδ T Cells.

γδ T cells have recently raised great interest as effector cells in cancer immunotherapy because of their HLA-independent mode of action and their broad tumor reactivity. To translate the application of γδ T cells into clinically effective immunotherapies, specific tumor targeting and/or boosting of γδ T-cell activation in vivo seem to be a critical step. In this issue, Le Floch and colleagues report a new strategy for enabling γδ T cells to be specifically activated to kill acute lymphoblastic leukemia cells and solid tumor cells using agonistic BTN2A1 antibodies. See related article by Le Floch et al., p. XX .

Disrupting Intracellular Homeostasis by Copper-Based Nanoinducer with Multiple Enzyme-Mimicking Activities to Induce Disulfidptosis-Enhanced Pyroptosis for Tumor Immunotherapy.

Given the crucial role of abnormal homeostasis in tumor cells for maintaining their growth, it may be more efficient with less effort to develop anti-tumor strategies that target multiple combined mechanisms by disrupting intracellular homeostasis. Here, a copper-based nanoinducer (CGBH NNs) with multiple enzyme-like activities is designed and constructed to induce disulfidptosis-enhanced pyroptosis through disrupting multiple intracellular homeostasis for effective tumor immunotherapy. Within the tumor microenvironment (TME), CGBH NNs can disrupt intracellular glucose homeostasis and inhibit NADPH production, leading to accumulation of cystine, which further blocked the substrate and key enzyme for synthesizing glutathione. Subsequently, through cascade catalytic reactions involving enzyme activities (glutathione peroxidase-like, glucose oxidase and peroxidase-like activities), CGBH NNs can produce massive reactive oxygen species(ROS) and further disrupt intracellular redox homeostasis, resulting in the disulfidptosis-enhanced pyroptosis. The tumor cells undergoing immunogenic pyroptosis can release various cytosolic contents and inflammatory factors, eliciting robust immune responses by facilitating immune cell infiltration, and reprogramming the immunosuppressive TME. After the combination with immune checkpoint blockade therapy, CGBH NNs can effectively suppress the tumor growth and prolong the survival time of tumor-bearing mice. This work presents a novel paradigm to trigger disulfidptosis-enhanced pyroptosis by destroying intracellular homeostasis for anti-tumor immunotherapy.

An insight into the role of innate immune cells in breast tumor microenvironment.

The immune background of breast cancer is highly heterogeneous and the immune system of the human body plays a dual role by both promoting and suppressing its progression. Innate immune cells are the first line of defense in the immune system and impart protection by identifying and interacting with foreign pathogens and cancer cells. Different innate immune cells like natural killer cells, macrophages, dendritic cells, and myeloid suppressor cells take part in hosting the cancer cells. Autophagy is another key component inside the tumor microenvironment and is linked to the disintegration and recycling of cellular components. Within the tumor microenvironment autophagy is involved with Pattern Recognition Receptors and inflammation. Various clinical studies have shown prominent results where innate immune cells and autophagy in combination are used for pathogen as well as cancer cell clearance. However, it is necessary to comprehend the complex tumor microenvironment so that different therapeutic approaches can be developed to enhance the suppressive actions of the cells toward breast cancer cells. In this review article, the complex interaction between immune cells and breast cancer cells and their role in developing effective immunotherapies to improve patient outcomes are discussed in detail.

Subverting Attachment to Prevent Attacking: Alteration of Effector Immune Cell Migration and Adhesion as a Key Mechanism of Tumor Immune Evasion.

Cell adhesion regulates specific migratory patterns, location, communication with other cells, physical interactions with the extracellular matrix, and the establishment of effector programs. Proper immune control of cancer strongly depends on all these events occurring in a highly accurate spatiotemporal sequence. In response to cancer-associated inflammatory signals, effector immune cells navigating the bloodstream shift from their patrolling exploratory migration mode to establish adhesive interactions with vascular endothelial cells. This interaction enables them to extravasate through the blood vessel walls and access the cancer site. Further adhesive interactions within the tumor microenvironment (TME) are crucial for coordinating their distribution in situ and for mounting an effective anti-tumor immune response. In this review, we examine how alterations of adhesion cues in the tumor context favor tumor escape by affecting effector immune cell infiltration and trafficking within the TME. We discuss the mechanisms by which tumors directly modulate immune cell adhesion and migration patterns to affect anti-tumor immunity and favor tumor evasion. We also explore indirect immune escape mechanisms that involve modifications of TME characteristics, such as vascularization, immunogenicity, and structural topography. Finally, we highlight the significance of these aspects in designing more effective drug treatments and cellular immunotherapies.

In silico assessment of CAR macrophages activity against SARS-CoV-2 infection

Macrophage engineering with chimeric antigen receptor is a promising technique first applied to the treatment of tumours and recently suggested as a possible immunotherapeutic route against the COVID-19 disease. Four immunotherapies based on engineered macrophages have been tested in vitro revealing promising, with one of them acting without increasing the cytokines level. We present a mathematical model aimed at the evaluation of both the SARS-CoV-2 virions dynamics and the cytokines production induced, while such newly developed constructs interact with the immune system once administered. The importance of the study lies both in monitoring the dynamics of the infection and in evaluating the cytokine production, since clinical studies show that in critical COVID-19 patients an abnormal cytokines production occurs, a concern to be accounted for in designing appropriate therapeutic strategies. The mathematical model was built in the context of the continuum approach of the mass conservation, while the numerical simulations have been performed introducing parameters deduced from the experiments, using the finite element method. The model simulations allow to analyse and to compare the immune mechanisms underlying the virus dynamics, deepening the investigation for two selected immunotherapies, suggesting that a synergistic work of involved cytokines with phagocytic activity of macrophages occurs. The best SARS-CoV-2 clearance relies not only on the phagocytic capacity of the engineered macrophages, but also on the production of T-lymphocytes, pro- and anti-inflammatory cytokines which in the two cases examined in depth can decrease by 99.7 %, 99.6 % and 69 % respectively, passing from the most effective immunotherapy to the least effective one. This study is the first mathematical model that analyses the dynamics of macrophages engineered to fight the COVID-19, and paves the way for their possible exploitation against such a challenging disease, going beyond existing models involving other immune cells.

Role of T Lymphocytes in Glioma Immune Microenvironment: Two Sides of a Coin.

Glioma is known for its immunosuppressive microenvironment, which makes it challenging to target through immunotherapies. Immune cells like macrophages, microglia, myeloid-derived suppressor cells, and T lymphocytes are known to infiltrate the glioma tumor microenvironment and regulate immune response distinctively. Among the variety of immune cells, T lymphocytes have highly complex and multifaceted roles in the glioma immune landscape. T lymphocytes, which include CD4+ helper and CD8+ cytotoxic T cells, are known for their pivotal roles in anti-tumor responses. However, these cells may behave differently in the highly dynamic glioma microenvironment, for example, via an immune invasion mechanism enforced by tumor cells. Therefore, T lymphocytes play dual roles in glioma immunity, firstly by their anti-tumor responses, and secondly by exploiting gliomas to promote immune invasion. As an immunosuppression strategy, glioma induces T-cell exhaustion and suppression of effector T cells by regulatory T cells (Tregs) or by altering their signaling pathways. Further, the expression of immune checkpoint inhibitors on the glioma cell surface leads to T cell anergy and dysfunction. Overall, this dynamic interplay between T lymphocytes and glioma is crucial for designing more effective immunotherapies. The current review provides detailed knowledge on the roles of T lymphocytes in the glioma immune microenvironment and helps to explore novel therapeutic approaches to reinvigorate T lymphocytes.

Ensemble transformer-based multiple instance learning to predict pathological subtypes and tumor mutational burden from histopathological whole slide images of endometrial and colorectal cancer

In endometrial cancer (EC) and colorectal cancer (CRC), in addition to microsatellite instability, tumor mutational burden (TMB) has gradually gained attention as a genomic biomarker that can be used clinically to determine which patients may benefit from immune checkpoint inhibitors. High TMB is characterized by a large number of mutated genes, which encode aberrant tumor neoantigens, and implies a better response to immunotherapy. Hence, a part of EC and CRC patients associated with high TMB may have higher chances to receive immunotherapy. TMB measurement was mainly evaluated by whole-exome sequencing or next-generation sequencing, which was costly and difficult to be widely applied in all clinical cases. Therefore, an effective, efficient, low-cost and easily accessible tool is urgently needed to distinguish the TMB status of EC and CRC patients. In this study, we present a deep learning framework, namely Ensemble Transformer-based Multiple Instance Learning with Self-Supervised Learning Vision Transformer feature encoder (ETMIL-SSLViT), to predict pathological subtype and TMB status directly from the H&E stained whole slide images (WSIs) in EC and CRC patients, which is helpful for both pathological classification and cancer treatment planning. Our framework was evaluated on two different cancer cohorts, including an EC cohort with 918 histopathology WSIs from 529 patients and a CRC cohort with 1495 WSIs from 594 patients from The Cancer Genome Atlas. The experimental results show that the proposed methods achieved excellent performance and outperforming seven state-of-the-art (SOTA) methods in cancer subtype classification and TMB prediction on both cancer datasets. Fisher’s exact test further validated that the associations between the predictions of the proposed models and the actual cancer subtype or TMB status are both extremely strong (p<0.001). These promising findings show the potential of our proposed methods to guide personalized treatment decisions by accurately predicting the EC and CRC subtype and the TMB status for effective immunotherapy planning for EC and CRC patients.

Monoclonal antibody targeting CEACAM1 enhanced the response to anti-PD1 immunotherapy in non-small cell lung cancer

Carcinoembryonic antigen-related cellular adhesion molecule 1 (CEACAM1), an extensively studied cell surface molecule, mainly expressed by certain epithelial, endothelial, lymphoid and myeloid cells, and is an attractive target for cancer immunotherapy. Here, to investigate the anti-tumor effects and mechanisms of CEACAM1 antibody, we prepared the antibody and explored its anti-tumor effects on Non-small Cell Lung Cancer (NSCLC) in vitro and in vivo. Firstly, antigen of human CEACAM1 recombinant protein was immunized on BALB/c mice and the high-affinity mouse anti-human monoclonal antibody 3C11 was selected by hybridoma technique. Next, ELISA was applied to detect the blocking effects of 3C11 on CEACAM1-CEACAM1 and CEACAM1-CEACAM5. Then, cell assays and ELISA were used to evaluate the role of 3C11 in blocking CEACAM1-CEACAM1 immunosuppressive signal transduction between dendritic cells (DCs) and T cells or natural killer cells (NK) and tumor cells. Finally, the synergistic anti-tumor effect of 3C11 combined with anti-PD-1 antibody was evaluated through cell stimulation assays and NCI-H358-induced tumor models in mice. The results showed the EC50 of 3C11 binding to NCI-H358 or exhausted T cells were 0.04971 μg/mL and 0.03475 μg/mL, respectively. 3C11 activated the exhausted T cells and enhanced the killing effect of NK by blocking CEACAM1-CEACAM1. In addition, the combination of 3C11 and anti-PD1 antibody produced synergistic anti-tumor effect on NSCLC. Its improved tumor growth inhibition value (TGI) of anti-PD-1 from 18 % to 85 % in vivo. These findings suggest that 3C11 can be considered an effective immunotherapy drug for NSCLC.

NitraTh epitope-based neoantigen vaccines for effective tumor immunotherapy

Neoantigen vaccines represent an emerging and promising strategy in the field of tumor immunotherapy. Despite their potential, designing an effective neoantigen vaccine remains a challenge due to the current limitations in predicting CD4+ T cell epitopes with high accuracy. Here, we introduce a novel approach to neoantigen vaccine design that does not rely on computational prediction of CD4+ T cell epitopes. Utilizing nitrated helper T cell epitope containing p-nitrophenylalanine, termed “NitraTh epitope,” we have successfully engineered a series of tumor neoantigen vaccines capable of eliciting robust neoantigen-specific immune responses. With the help of NitraTh epitope, even mutations with low predicted affinity for MHC class I molecules were successfully induced to elicit neoantigen-specific responses. In H22 cell allograft and patient-derived xenograft (PDX) liver cancer mouse models, the NitraTh epitope-based neoantigen vaccines significantly suppressed tumor progression. More strikingly, through single-cell sequencing we found that the NitraTh epitope-based neoantigen vaccines regulate macrophage reprogramming and modulate macrophages to decrease the levels of the immunosuppressive molecule prostaglandin E2 (PGE2), which in turn reshapes the tumor immunosuppressive microenvironment. In summary, NitraTh epitope-based neoantigen vaccines possess the dual effects of potently activating neoantigen-specific immunity and alleviating immunosuppression, potentially providing a new paradigm for the design of tumor neoantigen vaccines.

Improved deep learning prediction of antigen–antibody interactions

Identifying antibodies that neutralize specific antigens is crucial for developing effective immunotherapies, but this task remains challenging for many target antigens. The rise of deep learning-based computational approaches presents a promising avenue to address this challenge. Here, we assess the performance of a deep learning approach through two benchmark tests aimed at predicting antibodies for the receptor-binding domain of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. Three different strategies for constructing input sequence alignments are employed for predicting structural models of antigen-antibody complexes. In our initial testing set, which comprises known experimental structures, these strategies collectively yield a significant top-ranked prediction for 61% of cases and a success rate of 47%. Notably, one strategy that utilizes the sequences of known antigen binders outperforms the other two, achieving a precision of 90% in a subsequent test set of ~1,000 antibodies, balanced between true and control antibodies for the antigen, albeit with a lower recall of 25%. Our results underscore the potential of integrating deep learning methods with single B cell sequencing techniques to enhance the prediction accuracy of antigen-antibody interactions.

Enhancing CAR-T cell therapy against solid tumor by drug-free triboelectric immunotherapy

Chimeric antigen receptor (CAR) T cell therapy is a highly effective immunotherapy for hematological tumors, but its efficacy against most solid tumors remains challenging. Herein, a novel synergistic combination therapy of drug-free triboelectric immunotherapy and CAR-T cell therapy against solid tumor was proposed. A triboelectric nanogenerator (TENG) that can generate pulsed direct-current by coupling triboelectrification effect and electrostatic breakdown effect was fabricated. The TENG can generate up to 30 pulse direct-current peaks with peak current output ≈35 μA in a single sliding to power the triboelectric immunotherapy. The pulsed direct-current stimulation induced immunogenic cell death of tumor cells (survival rate of 35.9 %), which promoted dendritic cells maturation, accelerated the process of antigen presentation to CAR-T cells and enhanced the systemic adaptive immune response. Furthermore, triboelectric immunotherapy promoted M1-like macrophage polarization, reduced regulatory T cells differentiation and reprogrammed the tumor immunosuppressive microenvironment, which ultimately enhanced the efficacy of CAR-T cells to eradicate nearly 60 % of NALM6 solid tumor mass. Notably, considering that triboelectric immunotherapy is a safe and effective drug-free antitumor strategy, the combined therapy did not increase the burden of double-medication on patients.

Integrating Bioinformatics and Experimental Validation to Identify Mitochondrial Permeability Transition-Driven Necrosis-Related lncRNAs that can Serve as Prognostic Biomarkers and Therapeutic Targets in Endometrial Carcinoma.

Endometrial carcinoma (EC) is a common malignant tumor in women with high mortality and relapse rates. Mitochondrial permeability transition (MPT)-driven necrosis is a novel form of programmed cell death. The MPT-driven necrosis related lncRNAs (MRLs) involved in EC development remain unclear. We aimed to predict the outcomes of patients with EC by constructing a novel prognostic model based on MRLs and explore potential molecular functions. A risk prognostic model was developed utilizing multi-Cox regression in conjunction with the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, which was based on MRLs. The predictive efficacy of the model was evaluated through receiver operating characteristic (ROC) curve analysis, as well as nomogram and concordance index (C-index) assessments. Patients were categorized into high- and low-risk groups based on their median risk scores. Notably, the high-risk group exhibited significantly poorer overall survival (OS) outcomes. Gene ontology (GO) and Gene set enrichment analysis (GSEA) demonstrated that Hedgehog and cell cycle pathways were enriched in the high-risk group. Tumor Immune Dysfunction and Exclusion (TIDE) displayed that patients in the high-risk group showed a high likelihood of immune evasion and less effective immunotherapy. A significant disparity in immune function was also observed between two groups. Based on the nine-MRLs, drug sensitivity analysis identified several anticancer drugs with potential efficacy in prognosis. Meanwhile, the results demonstrated that OGFRP1 plays a carcinogenic role by affecting mitochondrial membrane permeability in EC. Therefore, the risk model constructed by nine MRLs could be used to predict the clinical outcomes and therapeutic responses in patients with EC effectively.

Decoding the immune microenvironment: unveiling CD8 + T cell-related biomarkers and developing a prognostic signature for personalized glioma treatment

BackgroundGliomas are aggressive brain tumors with poor prognosis. Understanding the tumor immune microenvironment (TIME) in gliomas is essential for developing effective immunotherapies. This study aimed to identify TIME-related biomarkers in glioma using bioinformatic analysis of RNA-seq data.MethodsIn this study, we employed weighted gene co-expression network analysis (WGCNA) on bulk RNA-seq data to identify TIME-related genes. To identify prognostic genes, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Based on these genes, we constructed a prognostic signature and delineated risk groups. To validate the prognostic signature, external validation was conducted.ResultsCD8 + T cell infiltration was strongly correlated with glioma patient prognosis. We identified 115 CD8 + T cell-related genes through integrative analysis of bulk-seq data. CDCA5, KIF11, and KIF4A were found to be significant immune-related genes (IRGs) associated with overall survival in glioma patients and served as independent prognostic factors. We developed a prognostic nomogram that incorporated these genes, age, gender, and grade, providing a reliable tool for clinicians to predict patient survival probabilities. The nomogram’s predictions were supported by calibration plots, further validating its accuracy.ConclusionIn conclusion, our study identifies CD8 + T cell infiltration as a strong predictor of glioma patient outcomes and highlights the prognostic value of genes. The developed prognostic nomogram, incorporating these genes along with clinical factors, provides a reliable tool for predicting patient survival probabilities and has important implications for personalized treatment decisions in glioma.

Biomimetic Nanomodulators With Synergism of Photothermal Therapy and Vessel Normalization for Boosting Potent Anticancer Immunity.

Combination therapy using photothermal therapy (PTT) and immunotherapy is one of the most promising approaches for eliciting host immune responses to ablate tumors. However, its therapeutic efficacy is limited due to inefficient immune cell infiltration and cellular immune responses. In this study, a biomimetic immunostimulatory nanomodulator, Tm@PDA-GA (4T1 membrane@polydopamine-gambogic acid), with homologous targeting is developed. The 4T1 membrane (Tm) coating reduced immunogenicity and facilitated uptake of Tm@PDA-GA by tumor cells. Polydopamine (PDA) as a drug carrier can induce PTT under near-infrared ray (NIR) irradiation and immunogenic cell death (ICD) to activate dendritic cells (DCs). Moreover, Tm@PDA-GA on-demand released gambogic acid (GA) in an acidic tumor microenvironment, inhibiting the expression of heat shock proteins (HSPs) for synergetic chemo-photothermal anti-tumor activity and increasing the ICD of 4T1 cells. More importantly, GA can normalize the vessels via HIF-1α and VEGF inhibition to enhance immune infiltration and alleviate hypoxia stress. Thus, Tm@PDA-GA induced ICD, activated DCs, stimulated cytotoxic T cells, and suppressed Tregs. Moreover, Tm@PDA-GA is combined with anti-PD-L1 to further augment the tumor immune response and effectively suppress tumor growth and lung metastasis. In conclusion, biomaterial-mediated PTT combined with vessel normalization is a promising strategy for effective immunotherapy of triple-negative breast cancer (TNBC).

Novel protein-based prognostic signature linked to immunotherapeutic efficiency in ovarian cancer

BackgroundPersonalized medicine remains an unmet need in ovarian cancer due to its heterogeneous nature and complex immune microenvironments, which has gained increasing attention in the era of immunotherapy. A key obstacle is the lack of reliable biomarkers to identify patients who would benefit significantly from the therapy. While conventional clinicopathological factors have exhibited limited efficacy as prognostic indicators in ovarian cancer, multi-omics profiling presents a promising avenue for comprehending the interplay between the tumor and immune components. Here we aimed to leverage the individual proteomic and transcriptomic profiles of ovarian cancer patients to develop an effective protein-based signature capable of prognostication and distinguishing responses to immunotherapy.MethodsThe workflow was demonstrated based on the Reverse Phase Protein Array (RPPA) and RNA-sequencing profiles of ovarian cancer patients from The Cancer Genome Atlas (TCGA). The algorithm began by clustering patients using immune-related gene sets, which allowed us to identify immune-related proteins of interest. Next, a multi-stage process involving LASSO and Cox regression was employed to distill a prognostic signature encompassing five immune-related proteins. Based on the signature, we subsequently calculated the risk score for each patient and evaluated its prognostic performance by comparing this model with conventional clinicopathological characteristics.ResultsWe developed and validated a protein-based prognostic signature in a cohort of 377 ovarian cancer patients. The risk signature outperformed conventional clinicopathological factors, such as age, grade, stage, microsatellite instability (MSI), and homologous recombination deficiency (HRD) status, in terms of prognoses. Patients in the high-risk group had significantly unfavorable overall survival (p < 0.001). Moreover, our signature effectively stratified patients into subgroups with distinct immune landscapes. The high-risk group exhibited higher levels of CD8 T-cell infiltration and a potentially greater proportion of immunotherapy responders. The co-activation of the TGF-β pathway and cancer-associated fibroblasts could impair the ability of cytotoxic T cells to eliminate cancer cells, leading to poor outcomes in the high-risk group.ConclusionsThe protein-based signature not only aids in evaluating the prognosis but also provides valuable insights into the tumor immune microenvironments in ovarian cancer. Together our findings highlight the importance of a thorough understanding of the immunosuppressive tumor microenvironment in ovarian cancer to guide the development of more effective immunotherapies.

Survival advantage of native and engineered T cells is acquired by mitochondrial transfer from mesenchymal stem cells

BackgroundApoptosis, a form of programmed cell death, is critical for the development and homeostasis of the immune system. Chimeric antigen receptor T (CAR-T) cell therapy, approved for hematologic cancers, retains several limitations and challenges associated with ex vivo manipulation, including CAR T-cell susceptibility to apoptosis. Therefore, strategies to improve T-cell survival and persistence are required. Mesenchymal stem/stromal cells (MSCs) exhibit immunoregulatory and tissue-restoring potential. We have previously shown that the transfer of umbilical cord MSC (UC-MSC)-derived mitochondrial (MitoT) prompts the genetic reprogramming of CD3+ T cells towards a Treg cell lineage. The potency of T cells plays an important role in effective immunotherapy, underscoring the need for improving their metabolic fitness. In the present work, we evaluate the effect of MitoT on apoptotis of native T lymphocytes and engineered CAR-T cells.MethodsWe used a cell-free approach using artificial MitoT (Mitoception) of UC-MSC derived MT to peripheral blood mononuclear cells (PBMCs) followed by RNA-seq analysis of CD3+ MitoTpos and MitoTneg sorted cells. Target cell apoptosis was induced with Staurosporine (STS), and cell viability was evaluated with Annexin V/7AAD and TUNEL assays. Changes in apoptotic regulators were assessed by flow cytometry, western blot, and qRT-PCR. The effect of MitoT on 19BBz CAR T-cell apoptosis in response to electroporation with a non-viral transposon-based vector was assessed with Annexin V/7AAD.ResultsGene expression related to apoptosis, cell death and/or responses to different stimuli was modified in CD3+ T cells after Mitoception. CD3+MitoTpos cells were resistant to STS-induced apoptosis compared to MitoTneg cells, showing a decreased percentage in apoptotic T cells as well as in TUNEL+ cells. Additionally, MitoT prevented the STS-induced collapse of the mitochondrial membrane potential (MMP) levels, decreased caspase-3 cleavage, increased BCL2 transcript levels and BCL-2-related BARD1 expression in FACS-sorted CD3+ T cells. Furthermore, UC-MSC-derived MitoT reduced both early and late apoptosis in CAR-T cells following electroporation, and exhibited an increasing trend in cytotoxic activity levels.ConclusionsArtificial MitoT prevents STS-induced apoptosis of human CD3+ T cells by interfering with the caspase pathway. Furthermore, we observed that MitoT confers protection to apoptosis induced by electroporation in MitoTpos CAR T-engineered cells, potentially improving their metabolic fitness and resistance to environmental stress. These results widen the physiological perspective of organelle-based therapies in immune conditions while offering potential avenues to enhance CAR-T treatment outcomes where their viability is compromised.