Immunity has vital research value and promising applications in triple-negative breast cancer (TNBC). Nevertheless, few bibliometric analyses have systematically investigated this area. This study aimed to comprehensively review the collaboration and impact of countries, institutions, authors, and journals on the role of immunity in TNBC from a bibliometric perspective, evaluate the keyword co-occurrence of the knowledge structure, and identify hot trends and emerging topics. Articles and reviews related to immunity in TNBC were retrieved from the Web of Science core collection using subject search. A bibliometric study was conducted primarily using CiteSpace and VOSviewer. A total of 3,104 articles and reviews were included from January 1, 2014, through December 31, 2024. The number of articles on immunization in TNBC is rising. These publications are mainly from 415 institutions in 82 countries, led by China and the USA. Among these publications, Lajos Pusztai published the most papers, while Peter Schmid was co-cited the most. The most productive journals focused on molecular biology, biological immunology, and clinical medicine. Furthermore, co-citation analysis revealed that tumor microenvironment, biomarkers, and immune checkpoint inhibitors are current and developing research areas. The keywords "immunotherapy" and "nanoparticles" are also likely to be new trends and focal points for future research. This study adopted bibliometric and visualization methods to provide a comprehensive review of the research on immunization in TNBC. This article will help researchers better understand the dynamic evolution of the role of immunity in TNBC and identify areas for future research.

Heat shock proteins have been implicated in the process of carcinogenesis. HSPA14, a member of the heat shock protein family, remains poorly understood in terms of its significance and pathomechanisms in breast cancer.

We analyzed the expression levels of HSPA14 and its prognostic significance in breast cancer using TCGA data. TCGA data was used to investigate the association between HSPA14 expression and clinicopathological features in breast cancer patients. GSEA analysis was conducted to identify the biological function of HSPA14. Spearman's correlation analysis was performed to examine the correlation between HSPA14 expression and immune cell infiltration, as well as immune checkpoint genes. Single cell transcriptomic data from GSE114727 was utilized to calculate the expression of HSPA14 in different cell subpopulations. The data on HSPA14 levels and drug sensitivity were extracted from the CellMiner dataset. The mRNA expression of HSPA14 was validated through cell experiments.

HSPA14 expression is elevated in breast cancer, which is associated with poor overall survival. It can serve as a diagnostic biomarker for breast cancer patients. Pathway analysis revealed that HSPA14-associated differential genes are involved in cell cycle, apoptosis, cellular response to heat stress, and more. Additionally, HSPA14 expression is significantly correlated with the immune microenvironment. The expression of HSPA14 may also indicate drug sensitivity.

Our study elucidates the involvement of HSPA14 in tumorigenesis, particularly in modulating the immune response, shaping the immune microenvironment, and contributing to drug resistance, which are pivotal for the development of personalized breast cancer therapies.

Hepatocellular carcinoma (HCC) recurrence was previously characterized into four types, and patients with progression/hyper-progression recurrence (type III-IV) have an extremely poor prognosis. However, the immune background of resectable HCC, particularly in patients who experience recurrence, remains underexplored. Therefore, this study aimed to describe the immune landscape of resectable HCC, especially postoperative type III-IV recurrent HCC, and explore potential immune-targeted anti-relapse strategies for treated populations.

The differences in gene expression in patients with recurrent HCC (type I-II (solitary or multi-intrahepatic oligo recurrence) vs. type III-IV) were investigated using bulk sequencing. Multiple immune infiltration methods (single-sample gene set enrichment analysis (GSEA), Microenvironment Cell Populations-counter and ESTIMATE) were used, and patients were divided into four groups to identify four distinct immune subtypes: immune-enrichment/matrix-poor (IE1), immune-enrichment/matrix-rich (IE2), immune intermediate/matrix-rich (ITM) and immune desert/matrix-poor (ID). Co-expression and protein interaction analyses were used to identify characteristic genes in ITM closely associated with type III-IV recurrence, which was matched with drug targets for Huaier granules (HG) and lenvatinib. Virtual docking was used to identify potential therapeutic targets, and the results were verified using single-nuclei RNA sequencing and histological analysis.

ITM was closely related to type III-IV recurrence and exhibited immunotherapy potential. The potential efficacy of inhibiting CCNA2, VEGFA, CXCL8, PLK2, TIMP1, ITGB2, ALDOA, ANXA5 and CSK in ITM reversal was determined. Molecular docking demonstrated that the proteins of these genes could bind to HG or lenvatinib. The immunohistochemical findings demonstrated differential VEGFA (p < .01) and PLK2 (p < .001) expression in ITM type and ID in type III-IV recurrent HCC.

Three primary immunotypes of resectable HCC (IE2, ITM and ID) were identified, and HG and lenvatinib could potentially overcome immune checkpoint blockade (ICB) resistance in ITM patients with HCC, particularly those classified as type III-IV.

The clinical relevance of T cell-related molecules at single-cell resolution in laryngeal cancer (LC) has not been clarified.

Three LC tissues and matching adjoining normal tissues from the hospital were used to perform 10X single-cell RNA sequencing. Hub T cell-related genes (TCRGs) were detected by applying ten machine learning (ML) techniques based TCGA and GEO databases, which were also utilized to create a prediction model (TCRG classifier) and a multicenter validation model. Lastly, we conducted a comprehensive analysis of the TCRG's correlation with immunological properties.

The analysis of single-cell RNA-seq data revealed that T cells are the primary components of the tumor microenvironment (TME), are significantly involved in cell differentiation pathways, and play a considerable role in intercellular communication. Based on 10 ML approaches, TCRG classifier were identified to develop and validate. The TCRG classifier exhibited excellent prognostic values with a mean C-index of 0.66 in six cohorts, serving as an independent risk factor (p < 0.01). Additionally, the TCRG exhibited a significant relationship with immune score, immune cell infiltration, immune-associated pathways, immune checkpoint inhibitors, human leukocyte antigen, and immunogenicity. Lastly, IPS, TCIC, TIDE, and IMvigor210 cohort analysis illustrated that the immunotherapy response may be accurately predicted using TCRG.

A TCRG classifier is an excellent resource for predicting a patient's prognosis, potentially guiding the preservation of laryngeal function, and identifying patients who may have a positive response to immunotherapy, which might have profound effects on therapeutic practice.

T cells that recognize tumor-specific mutations are crucial for cancer immunosurveillance and in adoptive transfer of TILs or transgenic-TCR T cell products. However, their challenging identification and isolation limits their use in clinical practice. Therefore, novel approaches to isolate tumor-specific T cells are needed. Here, we report the isolation of neoantigen-specific CD8+ T cells from a vaccination site of a metastatic breast cancer patient who received a personalized vaccine. Based on the somatic mutations, potential MHC binding epitopes were predicted, of which 17 were selected to generate a peptide vaccine. Cutaneous biopsies were processed after the fifth vaccination cycle to obtain infiltrating lymphocytes from the vaccination site (VILs). IFNγ ELISpot revealed reactivity to four peptides used in the vaccine. Reactive T cells from VILs were non-overlapping with those detected in the blood and the tumor-microenvironment. ScTCR Seq analysis revealed the presence of a clonotype in VILs that further expanded after a round of in vitro stimulation and validated to be specific against a private mutation, namely NCOR1L1475R, presented in the context of HLA-B * 07:02, with no reactivity to the wild-type peptide. Our study shows, for the first time, that tumor mutation - specific T cells are generated at high frequencies in the vaccination site and can be isolated with standard methods for TCR screening. The easy and safe accessibility of skin biopsies overcomes the major hurdles of current TCR screening approaches and present exciting opportunities for the development of innovative immunotherapeutic strategies.

Colorectal cancer (CRC) is a leading health issue and treatments to eradicate it, such as conventional chemotherapy, are non‑selective and come with a number of complications. The present review focuses on the relatively new area of precision oncolytic viral therapy (OVT), with genetic targeting and immune modifications that offer a new future for CRC treatment. In the present review, an overview of the selection factors that are considered optimal for an oncolytic virus, mechanisms of oncolysis and immunomodulation applied to the OVT, as well as new strategies to improve the efficacy of this method are described. Additionally, cause‑and‑effect relationships are examined for OVT efficacy, mediated by the tumor microenvironment, and directions for genetic manipulation of viral specificity are explored. The possibility of synergy between OVT and immune checkpoint inhibitors and other treatment approaches are demonstrated. Incorporating the details of the present review, biomarker‑guided combination therapies in precision OVT for individualized CRC care, significant issues and future trends in this required area of medicine are highlighted. Increasingly, OVT is leaving the experimental stage and may become routine practice; it provides a new perspective on overcoming CRC and highlights the importance of further research and clinical work.

The mesenchymal-epithelial transition factor (MET) proto-oncogene plays important roles during tumor development. Recently, evidence has revealed MET signaling may impact tumor immunogenicity and regulate the immune response. Here we conducted a comprehensive bioinformatic and clinical analysis to explore the characteristics of MET mutation and its association with the outcomes in pan-cancer immunotherapy. In 4149 patients with 12 tumor types treated with immune checkpoint inhibitors, MET mutation indicated favorable overall survival (hazard ratio = 0.61; 95% CI, 0.50-0.74; P < 0.001), progression-free survival (hazard ratio = 0.74; 95% CI, 0.60-0.92; P = 0.01), and objective response rate (40.3% vs. 28.1%; P = 0.003). Moreover, we developed a nomogram to estimate the 12-month and 24-month survival probabilities after the initiation of immunotherapy. Further multi-omics analysis on both intrinsic and extrinsic immune landscapes revealed that MET mutation enhanced tumor immunogenicity, enriched infiltration of immune cells, and improved immune responses. In summary, MET mutation improves cancer immunity and is an independent biomarker for favorable outcomes in pan-cancer immunotherapy. These results may influence clinical practices, guide treatment decision-making, and develop immunotherapy for personalized care.

EARP and GARP complex-interacting protein 1 (EIPR1) may be a new oncogene in tumors, influencing the prognosis and invasion of cancer. However, a systematic analysis of the function of EIPR1 in various cancers remains vacant. Thus, we proceeded with a comprehensive analysis to ascertain the role of EIPR1 among various cancers.

We explored EIPR1 expression in pan-cancer, and its association with clinical stage, survival, gene mutations and methylation by the TIMER 2.0, GEPIA2, cBioPortal, and UALCAN. The protein-protein interaction (PPI) network, immune infiltration, and immune checkpoint assessments of EIPR1 was performed using the STRING and SangerBox. The role of EIPR1 expression in lung adenocarcinoma (LUAD) was explored by the R software. The impact of EIPR1 expression on LUAD progression was studied through in vitro assays.

EIPR1 was overexpressed in most cancers and revealed as a potential prognostic biomarker in tumors, involving in tumorigenesis by affecting its methylation and gene mutations. The immune infiltration and immune checkpoints of tumors were related to the expression of EIPR1. Additionally, EIPR1 expression affected the survival, diagnosis, clinicopathological features, tumor microenvironment, and drug sensitivity of LUAD patients. Validation studies demonstrated that EIPR1 knockdown suppressed the malignant growth, invasion, and migration of LUAD cells.

This study delivers an extensive landscape for the oncogenesis and immunological characteristics of EIPR1, which reveals that EIPR1 may serve as a potential biological target for future prognosis and immune treatment in tumors, especially in LUAD.

Intratumoral heterogeneity (ITH)-defined as genetic and cellular diversity within a tumor-is linked to failure of immunotherapy and an inferior anti-tumor immune response. We modeled heterogeneous tumors comprised of "hot" and "cold" tumor populations (giving rise to T cell-rich and T cell-poor tumors, respectively) and introduced fluorescent labels to enable precise spatial tracking. We found the cold tumor cell population exerted a "dominant cold" effect in mixed tumors. Strikingly, spatial analysis revealed that the tumor cells themselves created distinct local microenvironments within heterogeneous tumors: regions occupied by cold tumor cells showed pronounced immunosuppression, harboring increased CD206Hi macrophages and diminished local T cell function. This inferior T cell activity in cold regions persisted even after immunotherapy and mechanistically was mediated by CX3CL1 produced by the cold tumor cells. An immune cold tumor population within a heterogeneous tumor thus impairs tumor immunity on both a tumor-wide and a highly localized spatial scale.

The response rate of programmed cell death protein-1 (PD-1) inhibitors in breast cancer remains unsatisfactory, primarily due to the limited infiltration and activity of tumor-infiltrating T lymphocytes (TILs). Previous studies demonstrated that oxymatrine (Om) and astragaloside IV (As) could enhance TIL infiltration and function by inhibiting cancer-associated fibroblasts (CAFs) and promoting mitochondrial activity in TILs, respectively. Thus, combining Om and As may be a promising strategy to improve the antitumor effects of PD-1 inhibitors in breast cancer. However, co-delivery above drugs into breast cancer tissue is challenging due to their low bioavailability and distinct physicochemical properties. This study addresses this challenge by formulating Om and As co-loaded liposomes (Om-As-Lip) and comparing the scale-up production methods: high-pressure homogenization (EP-HPH) and microfluidics. Om-As-Lip prepared via microfluidics demonstrated superior entrapment efficiency (As: 99.03 ± 0.04 %, Om: 67.01 ± 0.02 %) and a significantly higher production rate (22.12 mL/min) compared to EP-HPH (1.19 mL/min). Additionally, Om-As-Lip produced by microfluidics increased the area under the curve (AUC) (Om: 6.17-fold, As: 2.07-fold) and maximum concentration (Cmax) (Om: 1.58-fold, As: 3.49-fold) compared to the free drugs. Importantly, Om-As-Lip enhanced the antitumor efficacy of α-PD-1 by inhibiting CAF activation and boosting TIL activity, resulting in a tumor inhibition rate of 61.2 % and extended survival in mice. This work presents a novel perspective for scaling up co-delivered formulations of drugs with differing polarities to improve breast cancer immunotherapy.

The composition of the tumor immune microenvironment has become a major determinant of response to therapy, particularly immunotherapy. Clinically, a tumor microenvironment lacking lymphocytes, so-called "cold" tumors, are considered poor candidates for immune checkpoint inhibition. In this review, we describe the diversity of the tumor immune microenvironment in breast cancer and how radiation exposure alters carcinogenesis. We review the development and use of a radiation-genetic mammary chimera model to clarify the mechanism by which radiation acts. Using the chimera model, we demonstrate that systemic inflammation elicited by a low dose of radiation is key to the construction of an immunosuppressive tumor microenvironment, resulting in aggressive, rapidly growing tumors lacking lymphocytes. Our experimental studies inform the non-mutagenic mechanisms by which radiation affects cancer and provide insight into the genesis of cold tumors.

Constitutive activation of NRF2 provides a selective advantage to malignant tumour clones through the hijacking of the NRF2-dependent cytoprotective transcriptional program, which allows the cancer cells to survive and thrive in the chemically stressful tumour niche, whilst also providing resistance to anti-cancer drugs due to the upregulation of xenobiotic metabolizing enzymes and drug efflux pumps. Through a small-molecule epigenetic screen carried out in KEAP1 mutant lung cancer cells, in this study, we identified CCS1477 (Inobrodib) to be an inhibitor of the global NRF2-dependent transcription program. Mechanistically, CCS1477 is able to repress NRF2's cytoprotective response through the inhibition of its obligate transcriptional activator partner CBP/p300. Importantly, in addition to repressing NRF2-dependent anti-oxidative stress and xenobiotic metabolizing enzyme gene expression, CCS1477 treatment is also able to reverse the chemoresistance phenotype and re-sensitize NRF2-activated tumour cells to anti-cancer drugs. Furthermore, in co-culture experiments of KEAP1 mutant cancer cells with primary human T cells, CCS1477 treatment suppressed the acquisition of the T cell exhaustion transcriptional state, which should function to augment the anti-cancer immune response. Thus, CCS1477-mediated inhibition of CBP/p300 represents a novel therapeutic strategy with which to target the currently untreatable tumours with aberrant NRF2 activation.

Acute myeloid leukemia (AML) is a highly heterogeneous malignancy, presenting significant challenges in accurately predicting patient prognosis. Dysregulation of endoplasmic reticulum (ER) stress and resistance to programmed cell death (PCD) are hallmarks of AML cells. However, the prognostic significance of the interplay between ER stress and cell death pathways in AML remains largely unexplored.

We analyzed RNA sequencing and clinical data from 887 AML patients across 4 cohorts to develop an ER stress-related cell death index (ERCDI) using 10 machine-learning algorithms with 117 unique combinations. Survival and time-dependent Receiver Operating Characteristic Curve (ROC) analyses were performed to assess the model's efficacy. Clinical characteristics, the tumor immune microenvironment, and drug sensitivity differences between the high- and low-risk groups were also analyzed. The CMap database was used to identify potential therapeutic drugs. In vitro and in vivo experiments, including CCK-8, colony formation, flow cytometry, Transwell assays, and xenograft mouse models, were conducted to evaluate the effects of the target genes and candidate drugs.

The ERCDI demonstrated strong prognostic and predictive performance for prognosis in AML patients. Furthermore, the ERCDI effectively predicted immunotherapy and chemotherapy outcomes and was associated with the immune features of the different risk groups. DNA damage-inducible transcript 4 protein (DDIT4), a key gene associated with ERCDI, is related to poor prognosis in AML patients with high expression. Additionally, the knockdown of DDIT4 significantly inhibited AML cell proliferation, induced cell apoptosis, and promoted cell cycle arrest. Chaetocin was subsequently identified as a candidate compound for AML treatment. Subsequent experiments suggested that combining chaetocin and venetoclax is a potentially promising therapeutic strategy for AML.

The ERCDI provides personalized risk assessment and treatment recommendations for individual AML patients. The combined use of chaetocin and venetoclax can potentially be repurposed for AML therapy.

Neovascular age-related macular degeneration (NVAMD) is a common retinal disease causing vision loss in the elderly. Neuroinflammation significantly contributes to NVAMD's etiology. This study explores the role of Programmed cell death ligand 1 (PD-L1), an immune checkpoint (ICP) in microglia, known for limiting neuroinflammation in neurodegenerative diseases, and its potential function in NVAMD. This work finds increased PD-L1 expression in retinal microglia following laser injury. PD-L1 knockout (KO) or inhibitory PD-L1 antibody treatment worsens vascular leakage and neoangiogenesis in a laser-induced NVAMD mouse model, effects reversible by microglia depletion with PLX5622. This study underscores that choroidal neovascularization (CNV) may be regulated by multiple mechanisms, with PD-L1 modulation representing one of these pathways. Blocking PD-L1 elevated proinflammatory factors and p-ERK levels, indicating microglial overactivation in NVAMD. Conversely, enhancing PD-L1 signaling reduced neuroinflammation and neovascularization via ERK. These findings highlight PD-L1's role in neoangiogenesis and neuroinflammation in NVAMD, suggesting its potential as a target for immunomodulatory treatment in NVAMD.

Immune checkpoint blockade (ICB) therapy has become the first-line treatment for cancer patients. However, the low response rate remains a clinical pain-point. Anti-hyperglycemic drug metformin has shown remarkable anticancer effect with the unique characteristic of modulating tumor immune microenvironment (TIME). Therefore, combining ICB with metformin could be a promising strategy for enhanced cancer immunotherapy, which however remains challenged due to the low bioavailability and severe adverse effects of metformin. This work herein designs an amphiphilic reduction-responsive metformin prodrug, which could complex small interfering RNA (siRNA) and then co-assemble with an endosomal pH-responsive PEGylated polymer to form a dual-responsive immunomodulatory RNAi nanoplatform. Using the orthotopic and metastatic breast cancer (BCa) tumor models, this work demonstrates that this RNAi nanoplatform could silence PD-L1 expression on BCa cells and suppress their proliferation via activating AMP-activated protein kinase (AMPK). Moreover, this AMPK activation could suppress the secretion of tumor-derived transforming growth factor β (TGF-β) and interleukin 6 (IL-6), which could enhance the maturation of dendritic cells (DCs) and activation of CD8+ T cells and impair the tumor infiltration of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs), ultimately achieving the goal of enhanced cancer immunotherapy and significant inhibition of BCa tumor growth.

The immunosuppressive nature of the tumor microenvironment (TME) and the existence of cancer stem cells (CSCs) present significant hurdles in tumor therapy. The identification of therapeutic agents that can target both CSCs and the TME could be a potential approach to overcome treatment resistance.

We conducted an in vivo chemical screen to identify F1929-1458, which is capable of eliciting an organism-wide response to destroy stem cell tumors in Drosophila. We then performed functional validation using a mouse colorectal cancer graft tumor model established with the CT26 cell line characterized by its high content of CSCs. Single-cell sequencing was employed to analyze alterations in the TME. Small molecule pull-down mass spectrometry, cellular thermal shift assay, drug affinity experiment, and molecular docking were utilized to identify the target of F1929-1458. An in vitro co-culture system was applied to establish that the damage-associated molecular patterns (DAMPs) released by the tumor cells are accountable for the activation of dendritic cells (DCs).

We demonstrated that F1929-1458 treatment enhanced T cell infiltration and T cell mediated tumor regression, its anti-tumor effect was nullified in nude mice and was abolished after anti-CD3 neutralizing antibody treatment. We found that F1929-1458 binds NFKB1 to activate the NF-κB signaling pathway in tumor cells. The activation further elicits cellular stress, causing tumor cells to release DAMPs (HMGB1-gDNA complex, ATP, and OxLDL). These DAMPs, in turn, stimulate the cGAS-STING and NLRP3 inflammasome pathways in DCs, resulting in the generation of type I IFNs and IL-1β. These cytokines facilitate the maturation of DCs and antigen presentation, ultimately enhancing T cell-mediated anti-tumor immunity. Additionally, we showed that the combination of F1929-1458 and the anti-PD-1 antibody exhibited a synergistic anti-tumor effect.

Our study identified a novel NFKB1 agonist that promotes anti-tumor immunity by remodeling the TME and activating DCs and that may provide a new way to overcome resistance to current anti-tumor immunotherapy in colorectal cancer.

Immune checkpoint inhibition (ICI) has revolutionized oncology, offering extended survival and long-term remission in previously incurable cancers. While highly effective in tumors with high mutational burden, lowly mutated cancers, including pediatric malignancies, present low response rate and limited predictive biomarkers.

We present a framework for the identification and validation of tumor-reactive T cells as a biomarker to quantify ICI efficacy and as candidates for a personalized TCR-T cell therapy. Therefore, we profiled a pediatric malignant rhabdoid tumor patient with complete remission after ICI therapy using deep single-cell T cell receptor (TCR) repertoire sequencing of the tumor microenvironment (TME) and the peripheral blood.

Tracking T cell dynamics longitudinally from the tumor to cells in circulation over a time course of 12 months revealed a systemic response and durable clonal expansion of tumor-resident and ICI-induced TCR clonotypes. We functionally validated tumor reactivity of TCRs identified from the TME and the blood by co-culturing patient-derived tumor cells with TCR-engineered autologous T cells. Here, we observed unexpectedly high frequencies of tumor-reactive TCR clonotypes in the TME and confirmed T cell dynamics in the blood post-ICI to predict tumor-reactivity.

These findings strongly support spatio-temporal tracking of T cell activity in response to ICI to inform therapy efficacy and to serve as a source of tumor-reactive TCRs for personalized TCR-T designs.

Bacterial outer membrane vesicles (OMVs) represent powerful immunoadjuvant nanocarriers with the capacity to reprogram the tumor microenvironment (TME) and activate immune responses. Here, we investigate a nanotherapeutic platform integrating immunostimulatory cytosine-phosphate-guanine oligodeoxynucleotides (CpG-ODNs, hereafter termed CpG) into mesoporous silica nanoparticles cloaked with OMVs (CpG@MSN-PEG/PEI@OMVs) for cancer immunotherapy. Systemic administration of these nanohybrids facilitates precise tumor targeting, induces antitumor cytokines such as IFNγ, and suppresses immunosuppressive cytokine TGF-β, reshaping the TME. Additionally, CpG@MSN-PEG/PEI@OMVs promote M1 macrophage polarization, dendritic cell maturation, and the generation of durable tumor-specific immune memory, resulting in pronounced tumor regression with minimal systemic toxicity. The platform demonstrates efficacy against metastatic and solid tumor models including 4T1 breast and MC38 colorectal cancers. Transcriptomic analyses reveal that CpG@MSN-PEG/PEI@OMVs enhance mitochondrial oxidative phosphorylation in T cells within tumor-draining lymph nodes, mitigating T cell exhaustion and restoring metabolic fitness. These results support the potential of CpG@MSN-PEG/PEI@OMVs as a modular nanoplatform to modulate innate and adaptive immunity in cancer immunotherapy.

Head and neck squamous cell carcinoma (HNSCC) shows variable response to anti-programmed cell death protein 1 (PD-1) therapy, which can be partially explained by a combined positive score (CPS) of tumor and immune cell expression of programmed death-ligand 1 (PD-L1) within the local tumor microenvironment (TME). To better define TME immune determinants associated with treatment efficacy, we conduct a study of n = 48 HNSCC tumors from patients prior to pembrolizumab therapy. Our investigation combines a rapid bioorthogonal multiplex staining method with computational analysis of whole-slide imaging to capture the single-cell spatial heterogeneity and complexity of the TME. Analyzing 6,316 fields of view (FOVs), we provide comprehensive PD-L1 phenotyping and cell proximity assays across the entirety of tissue sections. While none of the PD-L1 metrics adequately predict response, we find that the spatial organization of CCR7+ dendritic cells (DCs) in niches better predicts overall patient survival than CPS alone. This study highlights the importance of understanding the spatial context of immune networks for immunotherapy.

The rapid development of immunotherapy has shown preliminary clinical efficacy and significant anti-tumor effects in some cancer patients. Although immunotherapy has been approved for breast cancer, some breast cancer patients still do not benefit from it due to issues such as immunotherapy insensitivity and resistance. Mass cytometry, as a mature single-cell proteomic analysis method, with its high-throughput capabilities, has been widely used in the analysis of tumor immune microenvironments and immune cell subpopulations. Using mass cytometry to analyze the immune microenvironment of breast cancer and explore new immunotherapy targets can help improve the current status of breast cancer immunotherapy and develop personalized treatment plans for more patients. This review surveys the recent advancements in analyzing the single-cell components of breast cancer using mass cytometry technology and reviews the immune microenvironment of breast cancer as well as potential targets for immunotherapy. These results provide new insights for the subsequent research of the immune microenvironment of breast cancer and targeted immunotherapy.

Adrenocortical carcinoma (ACC) is a rare epithelial tumor originating from adrenal cortical cells, notable for its high degree of malignancy and poor prognosis. Owing to heterogeneity, patient outcomes vary significantly. Current biomarkers for ACC risk stratification have notable limitations. However, with the advancement of multi-omics sequencing technology, we can utilize multi-omics data to explore the heterogeneity of ACC, thereby identifying novel biomarkers. In this study, we establish multicenter transcriptomics and ATAC-seq data from the TCGA and GEO databases to perform weighted gene coexpression network analysis (WGCNA) clustering and conduct comprehensive analyses of various ACC samples. These findings are integrated with univariate Cox regression, receiver operating characteristic (ROC) curve analysis, and survival analysis to identify potential biomarkers. We establish FSCN1 as an independent risk factor associated with poor ACC prognosis. ATAC-seq data demonstrate higher chromatin accessibility of FSCN1 in ACC patients with progressive disease. Immunohistochemical analysis confirms the expression of FSCN1 at the protein level, while functional cell assays reveal its role in promoting tumor invasion and proliferation. Functional enrichment analyses highlight the biological characteristics of FSCN1, and estimation of TME-infiltrating cells suggests that FSCN1 expression contributes to poor prognosis by inhibiting CD8 + T-cell infiltration within the ACC microenvironment. Finally, multi-omics analyses elucidate the role of FSCN1 at the mutation level. Taken together, our findings highlight FSCN1 as a promising novel biomarker and potential therapeutic target, underscoring its value in guiding the strategic management of ACC.

How to screen beneficiary populations has always been a clinical challenge in the treatment of non-small-cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs). Routine blood tests, due to their advantages of being minimally invasive, convenient, and capable of reflecting tumor dynamic changes, have potential value in predicting the efficacy of ICIs treatment. However, there are few models based on routine blood tests to predict the efficacy and prognosis of immunotherapy.

Patients were randomly divided into training cohort and validation cohort at a ratio of 2:1. The random forest algorithm was applied to select important variables based on routine blood tests, and a random forest (RF) model was constructed to predict the efficacy and prognosis of ICIs treatment. For efficacy prediction, we assessed receiver operating characteristic (ROC) curves, decision curve analysis (DCA) curves, clinical impact curve (CIC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) compared with the Nomogram model. For prognostic evaluation, we utilized the C-index and time-dependent C-index compared with the Nomogram model, Lung Immune Prognostic Index (LIPI) and Systemic Inflammatory Score (SIS). Patients were classified into high-risk and low-risk groups based on RF model, then the Kaplan-Meier (K-M) curve was used to analyze the differences in progression-free survival (PFS) and overall survival (OS) of patients between the two groups.

The RF model incorporated RDW-SD, MCV, PDW, CD3+CD8+, APTT, P-LCR, Ca, MPV, CD4+/CD8+ ratio, and AST. In the training and validation cohorts, the RF model exhibited an AUC of 1.000 and 0.864, and sensitivity/specificity of (100.0%, 100.0%) and (70.3%, 93.5%), respectively, which had superior performance compared to the Nomogram model (training cohort: AUC = 0.531, validation cohort: AUC = 0.552). The C-index of the RF model was 0.803 in the training cohort and 0.712 in the validation cohort, which was significantly higher than Nomogram model, LIPI and SIS. K-M survival curves revealed that patients in the high-risk group had significantly shorter PFS/OS than those in the low-risk group.

In this study, we developed a novel model (RF model) to predict the response to immunotherapy and prognosis in NSCLC patients. The RF model demonstrated better predictive performance for immunotherapy responses than the Nomogram model. Moreover, when predicting the prognosis of immunotherapy, it outperformed the Nomogram model, LIPI, and SIS.

Ovarian cancer (OC) is the most lethal gynecological malignancy worldwide, characterized by heterogeneity at the molecular, cellular and anatomical levels. Most patients are diagnosed at an advanced stage, characterized by widespread peritoneal metastasis. Despite optimal cytoreductive surgery and platinum-based chemotherapy, peritoneal spread and recurrence of OC are common, resulting in poor prognoses. The overall survival of patients with OC has not substantially improved over the past few decades, highlighting the urgent necessity of new treatment options. Unlike the classical lymphatic and hematogenous metastasis observed in other malignancies, OC primarily metastasizes through widespread peritoneal seeding. Tumor cells (the "seeds") exhibit specific affinities for certain organ microenvironments (the "soil"), and metastatic foci can only form when there is compatibility between the "seeds" and "soil." Recent studies have highlighted the tumor microenvironment (TME) as a critical factor influencing the interactions between the "seeds" and "soil," with ascites and the local peritoneal microenvironment playing pivotal roles in the initiation and progression of OC. Prior to metastasis, the interplay among tumor cells, immunosuppressive cells, and stromal cells leads to the formation of an immunosuppressive pre-metastatic niche in specific sites. This includes characteristic alterations in tumor cells, recruitment and functional anomalies of immune cells, and dysregulation of stromal cell distribution and function. TME-mediated crosstalk between cancer and stromal cells drives tumor progression, therapy resistance, and metastasis. In this review, we summarize the current knowledge on the onset and metastatic progression of OC. We provide a comprehensive discussion of the characteristics and functions of TME related to OC metastasis, as well as its association with peritoneal spread. We also outline ongoing relevant clinical trials, aiming to offer new insights for identifying potential effective biomarkers and therapeutic targets in future clinical practice.

Gene therapies and adoptive cell therapy (ACT) are promising strategies for cancer immunotherapy. Referring to their different mechanisms, the combination of these two might result in a strategy with potential collaborative and compensatory effects. However, it is challenging to combine gene therapies and ACT that work in a proper logical order. Here, we developed a double-layered spherical scaffold (DLS) to codeliver mRNA and T cells and constructed an implantable hydrogel formulation, named the GD-920 scaffold. With a diameter of 7 mm, this scaffold loaded primary T cells in the inner layer and the Bim mRNA nanocomplex in the outer layer. While maintaining their bioactivities, GD-920 released gene and cell payloads in a controllable and sequential manner. The mRNA complex from the outer layer was first released and induced immunogenic tumor cell death. The produced antigens then migrated into the scaffold with dendritic cells, triggering a tumor-specific immune response. Finally, activated T cells released by the inner layer attacked the tumor tissue via massive infiltration. We showed that in situ implantation of the GD-920 scaffold is capable of effectively inhibiting tumor growth and is far more potent than that of control scaffolds containing a single payload. Our results demonstrated the outstanding potential of this DLS in combining gene and cell therapeutic approaches to cancer immunotherapy.

CD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim of this study was to explore the potential role of CD8T cell-associated biomarkers in predicting prognosis and immunotherapy efficacy in ovarian cancer.

The single-cell sequencing data from the EMTAB8107 cohort were used to identify CD8 T-cell subtypes. The TCGA-OV cohort was involved in constructing a machine learning-based CD8T cell-associated index (CCAI). Additionally, independent ovarian cancer cohorts GSE26712 and GSE26193 were used to validate the predictive validity of CCAI. Multifactorial Cox regression and ROC analysis were applied to assess CCAI. The STRING database was used to clarify the interactions of CD8 T-cell-associated molecules. Furthermore, immune landscape analysis was performed using CIBERSORT, ssGSEA, TIMER, and ESTIMATE algorithms. Tumor mutation burden (TMB) analysis and drug sensitivity analysis were used to evaluate the potential predictive value of CCAI.

The CCAI, comprising LRP1, PLAUR, OGN, TAP1, ISG20, CXCR4, IL2RG, LCK, and CD3G, serves as a reliable prognostic marker for ovarian cancer patients, demonstrating robust predictive accuracy across various patient cohorts. Notably, individuals with low CCAI tend to exhibit immunoinflammatory tumor characteristics.

The developed CCAI serves as a promising prognostic biomarker for ovarian cancer, accurately predicting patient outcomes. Additionally, it differentiates between patients with distinct immune landscape profiles. This insight enables personalized treatment strategies and facilitates the exploration of underlying mechanisms involving CCAI-related molecules.

This study aims to assess the value of clinical and MRI radiomics features in noninvasively predicting programmed cell death protein 1 (PD-1) expression level and the response to anti-PD-1 immunotherapy combined with transcatheter arterial chemoembolization (TACE) in hepatocellular carcinoma (HCC). A total of 107 HCC patients (85 in training set and 22 in validation set) with PD-1 positive (n = 41) and negative (n = 66) were enrolled. Radiomics features were extracted from T2-weighted, fat suppression T2-weighted, contrast-enhanced, and diffusion-weighted images. A clinical model was constructed based on independent clinical risk factors (p < 0.05), while a radiomics model was developed utilizing the optimal radiomics signature. A radiomics nomogram model for predicting PD-1 integrated the significant clinical and radiomics features. The performance of nomogram was evaluated with respect to its discrimination and clinical utility and compared with that of clinical and radiomics prediction models. The radiomics nomogram, combining the clinical factors with the Rad-score, had best prediction performance (area under the curve [AUC]: 0.95 in the training set; AUC: 0.86 in the validation set). Decision curve analysis (DCA) showed that the nomogram exhibited superior accuracy in clinical assessment compared to the other models. The predicted high-risk group of PD-1 had longer overall survival (OS) than the predicted low-risk group after receiving anti-PD-1 therapy combined with TACE. The MRI-based radiomics nomogram performed well for identifying high-risk PD-1 group for combination therapy and may inform personalized treatment decision-making strategies.

Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations that develop in chronically inflamed tissues, including various solid tumours. In the context of gliomas, the presence of TLSs has recently attracted considerable attention because of their potential implications in tumour immunology and therapy. The tumour immune microenvironment (TIME) plays a crucial role in cancer progression, and tumour-infiltrating immune cells (TILs) are key players in this environment. These immune cell aggregates, known as TLSs, display distinct characteristics across different solid tumours. However, central nervous system (CNS) tumours are highly heterogeneous, and the immune environment within these tumours is often more deficient than that of peripheral tissue tumours. This leads to differences in the formation and function of TLSs in CNS tumours. These variations are particularly relevant in the context of glioma immunotherapy and could have important implications for treatment strategies. This review focuses on the composition and function of TLSs, examines the complexity of the glioblastoma (GBM) immune microenvironment, and highlights the unique characteristics of TLSs in GBM, providing new theoretical insights and practical foundations for targeting TLSs in glioma immunotherapy.

The widespread occurrence of microplastics (MPs) in the environment has raised significant concerns regarding their potential health impacts, particularly in relation to carcinogenesis. This study aimed to identify and analyze microplastics present in peritumoral and tumor tissues of patients diagnosed with colorectal cancer (CRC). Utilizing advanced scanning electron microscopy (SEM) and laser direct infrared (LDIR) imaging systems, we systematically examined tissue samples to detect and characterize the microplastics. Our findings revealed a diverse array of microplastic types, notably polyvinyl chloride (PVC) and polyethylene (PE), within both peritumoral and tumor regions. Compared to adjacent non-cancerous tissues, tumor tissues exhibited a greater variety and distribution of microplastics. Furthermore, Clathrin-a key protein involved in endocytosis-was found to be highly expressed in colorectal cancer specimens, facilitating the substantial uptake of microplastics. These results suggest a potential association between exposure to microplastics and the pathogenesis of colorectal cancer. This study highlights the urgent need for increased awareness and regulatory measures aimed at mitigating microplastic pollution along with its associated health risks.

Immune checkpoint inhibitors such as anti-Programmed Death-1 antibodies (aPD-1) can be effective in treating advanced cancers. However, many patients do not respond, and the mechanisms underlying these differences remain incompletely understood. In this study, we profile a cohort of patients with locally advanced or metastatic basal cell carcinoma undergoing aPD-1 therapy using single-cell RNA sequencing, high-definition spatial transcriptomics in tumors and draining lymph nodes, and spatial immunoreceptor profiling, with long-term clinical follow-up. We find that successful responses to PD-1 inhibition are characterized by an induction of B cell receptor (BCR) clonal diversity after treatment initiation. These induced BCR clones spatially colocalize with T cell clones, facilitate their activation, and traffic alongside them between tumor and draining lymph nodes to enhance tumor clearance. Furthermore, we validated aPD-1-induced BCR diversity as a predictor of clinical response in a larger cohort of glioblastoma, melanoma, and head and neck squamous cell carcinoma patients, suggesting that this is a generalizable predictor of treatment response across many types of cancers. We find that pretreatment tumors harbor a characteristic gene expression signature that portends a higher probability of inducing BCR clonal diversity after aPD-1 therapy, and we develop a machine learning model that predicts PD-1-induced BCR clonal diversity from baseline tumor RNA sequencing. These findings underscore a dynamic role of B cell diversity during immunotherapy, highlighting its importance as a prognostic marker and a potential target for intervention in non-responders.

Our investigation of the SOCS1 pathway in AML and T-cell interactions provides insights into potential mechanisms of resistance of AML to allogeneic hematopoietic stem cell transplantation and demonstrates the potential of targeting SOCS1 and its downstream mediators to enhance antileukemic T-cell activity. See related commentary by Fry, p. 157.

Cognitive difficulties are frequently reported after cancer treatments, such as chemotherapy or hormone therapy, and have a negative impact on patients' quality of life. Recently, some studies have shown that new cancer treatments, such as immunotherapy agents, can induce cognitive changes.

This review presents the central neurological immune adverse events of immunotherapy treatments including Immune Checkpoint Inhibitors (ICI) and Chimeric Antigen Receptor (CAR) T-cell therapy. The physiopathological mechanisms and risk factors are developed and clinical studies on immunotherapy agents and cognition (among adult patients, using validated questionnaires and/or cognitive tests), psychological factors and quality of life were presented.

Neurological toxicities are frequently observed with CAR-T cell therapies at acute stage, such as the immune effector cell-associated neurotoxicity syndrome (ICANS), inducing cognitive disorders such as disorientation and aphasia. However, few studies have accurately assessed the impact of immunotherapy on cognition. The methodology of these studies is heterogeneous and they mainly included nonspecific self-report questionnaires of cognitive complaints. Variable results have been obtained concerning the cognitive impact of ICI and CAR-T cell several months following immunotherapy: overall, while some studies reported cognitive difficulties (mainly processing speed and executive functions), the majority has not. Although anxiety and depression are frequently reported in patients treated with ICI or CAR-T cells, these symptoms tend to decrease after the start of immunotherapy. The current neurobiological investigations are too fragmentary to explain neurological symptoms and potential cognitive alteration, but neuroinflammation, vascular inflammation, brain blood barrier disruption, and immune cell brain infiltration would constitute common mechanisms relayed by CAR-T and to a lesser degree, ICI.

Acute neurological toxicities following CAR-T cell therapies are a major issue. Further studies are needed to better assess cognitive difficulties after the initiation of immunotherapy, in particular ICI, to better understand the physiopathology, including imaging studies, and risk factors.

Immune checkpoint inhibitors (ICI) targeting CTLA-4 and PD-1 have shown remarkable antitumor efficacy, but can also cause immune-related adverse events, including checkpoint inhibitor-induced liver injury (ChILI). This multi-omic study aimed to investigate changes in blood samples from treated cancer patients who developed ChILI. PBMCs were sequenced for by transcriptomic and T cell receptor repertoire (bulk and single-cell immune profiling), and extracellular vesicle (EV) enrichment from plasma was analyzed by mass spectroscopy proteomics. Data were analyzed by comparing the ChILI patient group to the control group who did not develop ChILI and by comparing the onset of ChILI to pre-ICI treatment baseline. We identified significant changes in T cell clonality, gene expression, and proteins in peripheral blood mononuclear cells (PBMCs) and plasma in response to liver injury. Onset of ChILI was accompanied by an increase in T cell clonality. Pathway analysis highlighted the involvement of innate and cellular immune responses, mitosis, pyroptosis, and oxidative stress. Single-cell RNA sequencing revealed that these changes were primarily found in select T cell subtypes (including CD8 + effector memory cells), while CD16 + monocytes exhibited enrichment in metabolic pathways. Proteomic analysis of plasma extracellular vesicles showed enrichment in liver-associated proteins among differentially expressed proteins. Interestingly, an increase in PBMC PD-L1 gene expression and plasma PD-L1 protein was also found to be associated with ChILI onset. These findings provide valuable insights into the immune and molecular mechanisms underlying ChILI as well as potential biomarkers of ChILI.Trial registration number NCT04476563.

Cisplatin (DDP) resistance presents a major challenge in bladder cancer (BLCA) treatment. Recent evidence suggests that Astragalus polysaccharide (APS), extracted from Astragalus membranaceus, may sensitize tumors to DDP. However, the precise mechanisms by which APS modulates DDP sensitivity in BLCA are not fully elucidated. The study employed computational biology, bioinformatics, and both in vitro and in vivo experiments to explore the role of APS in BLCA. The results demonstrate that APS inhibits BLCA cell proliferation, induces apoptosis in vitro, and suppresses tumor growth in vivo. Additionally, APS induces G0/G1 cell cycle arrest in BLCA cells by downregulating CCND1 expression. Moreover, APS further enhances DDP-induced apoptosis by downregulating PI3K-p110β and p-AKT expression, while upregulating FoxO1 expression. Bioinformatics analysis indicates that APS may remodel the tumor microenvironment (TME) and influence cell-cell interactions, specifically through modulation of macrophage M2 polarization and CD8+ T cell exhaustion, thereby overcoming DDP resistance. In conclusion, APS potentiates DDP-induced apoptosis in BLCA cells via the PI3K/AKT/FoxO1 axis and may act as an immunomodulator to remodel the TME, offering a potential strategy to combat DDP resistance in BLCA.

T cell exhaustion is a critical obstacle for durable treatment response in hepatocellular carcinoma (HCC). Developing drugs that control tumor growth and simultaneously bolster immune function is of great significance. Although high-mobility group box 2 (HMGB2) has been reported to be crucial to HCC prognosis, its role in the tumor microenvironment remains unclear. Here, we found HMGB2+ CD8+ T cells as being associated with immune exhaustion and resistance to anti-PD-1 treatment through single-cell RNA sequencing. Mechanistically, HMGB2 impaired the oxidative phosphorylation in CD8+ T cells and inactivated the interferon-γ response in tumor cells, reducing the antitumor effector function. Tannic acid, a specific inhibitor of HMGB2, synergized with PD-1 antibody to attenuate tumor growth and reverse T cell exhaustion. Our findings highlight the unique role of HMGB2 as an immune exhaustion associated molecule. Targeting HMGB2 on both CD8+ T cells and tumor cells contributed to promising treatment strategies for HCC.