We aimed to clarify the role of PD-L1 promoter methylation in bladder cancer by analyzing PD-L1 methylation and mRNA expression in FFPE samples, along with PD-L1 mRNA and protein levels in urine samples from bladder urothelial carcinoma patients. We analyzed PD-L1 promoter methylation in 43 bladder urothelial carcinoma tissue samples and 41 non-malignant bladder tissues using methylation-sensitive high-resolution melting analysis to assess two CpG islands (cg15837913, cg19724470). PD-L1 mRNA expression in tissues and urine samples, along with PD-L1 protein levels in urine, were evaluated. The bladder urothelial carcinoma group showed significantly higher methylation rates for cg19724470 and cg15837913 compared to controls (P = 0.016, P = 0.049 respectively). In the patient group, tissue PD-L1 mRNA expression was 15.22 times higher and urinary PD-L1 mRNA expression 6.56 times higher in the cg19724470 unmethylated group compared to the methylated group. Urinary PD-L1 protein concentration was twice as high in the cg19724470 unmethylated group compared to the methylated group. In the patients, tissue PD-L1 mRNA expression was 4.58 times higher and urinary PD-L1 mRNA expression 2.58 times higher in the cg15837913 unmethylated group compared to the methylated group. Moreover, the urinary PD-L1 protein concentration was 1.7 times higher in the cg15837913 unmethylated group than in the methylated group (P = 0.036). A positive correlation was observed between tissue PD-L1 mRNA and both urine PD-L1 mRNA and protein levels and between urine PD-L1 mRNA and protein levels. This study suggests that PD-L1 methylation may be a key epigenetic regulator influencing PD-L1 expression and disease pathogenesis in bladder urothelial carcinoma.

Peptide-based therapeutics have gained attention in cancer treatment because of their good specificity, low toxicity, and ability to modulate immune responses. However, challenges such as enzymatic degradation and poor bioavailability limit their clinical application. Peptide-functionalized poly(lactic-co-glycolic acid) (PLGA) systems have emerged as a transformative platform in cancer therapy that offers unique advantages, including enhanced stability, sustained release, and precise delivery of therapeutic agents. This review highlights the synergistic integration of peptides with PLGA and addresses key challenges of peptide-based therapeutics. The application of peptide-functionalized PLGA systems encompasses a diverse range of strategies for cancer therapy. In chemotherapy, peptides disrupt critical tumor pathways, induce apoptosis, and inhibit angiogenesis, demonstrating their versatility in targeting various aspects of tumor progression. In immunotherapy, peptides act as antigens to stimulate robust immune responses or as immune checkpoint inhibitors to restore T cell activity, overcoming tumor immune evasion. These systems also harness the enhanced permeability and retention effect, facilitating preferential accumulation in tumor tissues while leveraging tumor microenvironment (TME)-responsive mechanisms, such as pH-sensitive or enzyme-triggered drug release, to achieve controlled, localized delivery. Collectively, peptide-functionalized PLGA systems represent a promising, versatile approach for precise cancer therapy that integrates innovative delivery strategies with highly specific, potent therapeutic agents.

The enrichment of antigens in lymph nodes and the ensuing antigen presentation constitute crucial steps in determining the efficacy of tumor vaccines. However, antigen delivery is restricted by enzyme degradation, immune system clearance, and the difficulty of crossing biological barriers. In this study, mesoporous silica nanoparticles (MSNPs) were prepared for antigen loading and were further coated with a phospholipid bilayer membrane (named silicasomes) to improve the delivery efficiency to lymph nodes. Our results showed that silicasomes exhibited superior lymph node enrichment compared to the bare MSNPs following subcutaneous injection. Moreover, their efficacy as a tumor vaccine was validated in the B16-OVA tumor model by loading the ovalbumin antigens (OVA257-264). Besides, the toll-like receptor 4 (TLR4) agonist monophosphoryl lipid A (MPLA), a component of bacterial lipopolysaccharides, was incorporated into the phospholipid membrane on the surface of silicasomes as an adjuvant. The silicasome-OVA257-264 with the addition of MPLA exhibited a more potent antitumor effect, triggering the infiltration of specific T cells into the tumor. These results demonstrated that lipid coating on MSNPs significantly enhanced their delivery efficiency to lymph nodes and enabled synergistic immune activation of tumor antigens and adjuvants, highlighting their potential as effective vehicles for cancer immunotherapy.

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Circular RNAs (circRNAs) are a type of non coding RNA that possess unique single stranded circular structures formed through reverse splicing mechanisms. Due to the lack of a free end that is typically susceptible to degradation by nucleases, circular RNAs exhibit resistance to ribonuclease R, making them highly stable in eukaryotic cells. The complex relationship between circRNA dysregulation and various pathophysiological conditions, especially cancer. Tumor microenvironment (TME) is a collective term for various components surrounding tumors and is an important factor affecting tumor development. Simultaneous infiltration of TME by different types of immune cells; These immune cells interact with the TME, collectively forming the so-called "tumor immune microenvironment". The complex interactions between tumor cells and TME profoundly affect the behavior of malignant tumors, and circRNAs derived from tumor cells and TME cell components have become important mediators of immune response and evasion within the TME. CircRNAs can directly or indirectly regulate immune cells, thereby modulating anti-tumor immunity. This review highlights how circRNAs, especially those encapsulated in extracellular vesicles like exosomes, influence the differentiation, chemotaxis, and anti-tumor immune functions of immune cells within the TME. Metabolic reprogramming plays an important role in this process. The process of circRNAs regulating tumor immunity is affected by multiple factors, such as hypoxia and viral infection. This review emphasizes the roles of the interaction between circRNAs and the TME in tumor immune regulation and prospects the guiding significance of circRNAs in tumor immune checkpoint therapy.

Colorectal cancer (CRC) remains a challenge for current immunotherapies. Vδ1+ γδ T cells offer a promising alternative because of their HLA-I-independent cytotoxicity and natural tissue tropism. We developed Delta One T (DOT) cells, a Vδ1+ γδ T cell-based adoptive cell therapy clinically explored for hematological malignancies but not yet for solid tumors. Here we demonstrate the capacity of DOT cells to target CRC cell lines and patient-derived specimens and organoids in vitro and to control tumor growth in an orthotopic xenograft model of CRC. Notwithstanding, we found tumor-infiltrating DOT cells to exhibit a dysregulated balance of cytotoxic and inhibitory receptors that paralleled that of endogenous Vδ1+ tumor-infiltrating lymphocytes and limited their cytotoxicity. To maximize efficacy, we unveil two strategies, increasing targeting through upregulation of NKG2D ligands upon butyrate administration and blocking the checkpoints TIGIT and PD1, which synergistically unleashed DOT cell cytotoxicity. These findings support DOT cell-based combinatorial approaches for CRC treatment.

Integrin β3 (ITGB3) acts as a crucial regulator and target within the tumor immune microenvironment (TIME) and is highly expressed in the TIME of various tumors. The TIMER, TCGA, GTEx, and CCLE databases were utilized to comprehensively analyze the differential expression of ITGB3 in tumor tissues. Kaplan-Meier analysis, forest plots, and univariate and multivariate Cox regression were used to assess the genetic alterations, clinicopathological characteristics, and prognostic value of ITGB3. Additionally, the R software package was used to evaluate the relationship between ITGB3 expression and immune cell infiltration, immunomodulatory genes, and immune checkpoints, and potential signaling pathways were examined through differential expression and enrichment analysis. We found that the high expression of ITGB3 is a significant risk factor for six types of cancer, including adrenocortical carcinoma (ACC), and is closely associated with a lower survival rate. Anti-tumor immune cells (CD8 + T cells, CD4 + Th1 cells, and NKT cells) were significantly reduced. By contrast, pro-tumor immune cells (Tregs and CD4 + Th2 cells), immune checkpoints (CTLA4 and PD-CD1), and negatively regulated co-stimulators of T-cell activation (CTLA4, PD-CD1, and IL10) were significantly elevated in most types of cancer with high ITGB3 expression. Overall, our preliminary results indicate that ITGB3 plays an important role in immunosuppression in the tumor microenvironment. Elevated levels of ITGB3 inhibit tumor immunity, facilitate tumor immune escape, and affect patient prognosis, and it may be a prognostic biomarker.

Immunotherapy has been at the forefront of cancer treatment research in recent years due to an increased understanding of the immune system's role in cancer and the substantial benefits it has demonstrated compared to conventional treatment methods. In particular, immune cell-based approaches utilizing T cells, natural killer (NK) cells, macrophages, and more have shown great potential as cancer treatments. While these treatments hold promise, there are still numerous issues that limit their clinical translation, including a lack of understanding of their mechanisms and inconsistent responses to treatment. Traditionally, tissue or blood samples are collected as a means of monitoring treatment progression. However, these in vitro diagnostics are invasive and provide limited information about the real-time status of the treatment or its long-term effectiveness. To address these limitations, novel non-invasive imaging modalities have been developed. These include optical imaging, X-ray computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and single-photon emission computed tomography (SPECT), and photoacoustic (PA) imaging. This review focuses on methods for tracking cell-based cancer immunotherapies using these in vivo imaging modalities, thereby enhancing real-time monitoring of their therapeutic effect and predictions of their long-term efficacy.

Overexpression of checkpoint proteins, such as programmed death ligand one (PD-L1), prevents immune recognition and enables cancer growth. Current monoclonal antibodies that block PD-L1 tend to be fragile, unable to penetrate tumors, and target cancer at later stages, thus leading to inconsistent patient outcomes. Antisense oligonucleotides (ASOs) provide an alternative to decrease PD-L1 expression, but require frequent high dosing due to fast degradation, rapid clearance, and poor cell uptake. To overcome these issues, we harnessed biocompatible metal-organic framework (MOF) nanoparticles, porous nanomaterials comprising metal nodes and organic linkers, to deliver ASOs. Encapsulating ASOs into MOFs enhances their stability and protection during intracellular delivery, leading to reduced PD-L1 expression and downstream immune recognition. Herein, we synthesized three distinct PD-L1-specific ASOs and loaded them individually into zirconium-based nano-sized NU-1000 MOFs, averaging ∼80% encapsulation efficiency. Release of encapsulated ASOs was sustained up to 7 days ex cellulo . MOF encapsulation increased ASO potency and reduced PD-L1 expression ∼ 3-fold and 2-fold in triple negative breast cancer EMT6 and melanoma B16-F10 cells, respectively. We evaluated the impact of MOF-delivered ASOs on PD-L1-expressing immune cells, where we observed ca. 12-fold increases in dendritic cell co-stimulatory marker expression, and amplified T cell activation and proliferation compared to untreated cells (4-fold and 10-fold, respectively). Notably, these changes drove a 3-fold increase in tumor caspase-3 expression, a key mediator for apoptosis. This research highlights how MOFs can be harnessed to bypass ASO limitations without requiring sequence modifications, and offers a broadly applicable platform for improved oligonucleotide delivery for various genes of interest.

Programmed cell death protein 1 (PD-1) plays a critical role in immune tolerance and evasion within the tumor microenvironment, and anti-PD-1 immunotherapy has shown efficacy in treating advanced melanoma. However, response rates vary significantly among patients, necessitating the identification of reliable biomarkers to predict treatment efficacy. Based on within-sample relative expression orderings, we analyzed RNA sequencing data from melanoma patients to construct a predictive model comprising gene pairs associated with treatment response. The model's performance was validated across multiple independent datasets and assessed for correlations with immune infiltration and survival outcomes. The constructed 15-pair model achieved a prediction accuracy of 100% in training datasets and 89.47% in validation sets. Validation in melanoma patients lacking treatment response data revealed significant differences between predicted responders and non-responders across datasets, with the model being an independent prognostic factor. Increased immune cell infiltration was observed in responders, correlating with higher expression levels of key immune checkpoint genes. The relative expression orderings-based model shows promise as a tool for predicting responses to anti-PD-1 therapy in melanoma patients, supporting personalized treatment strategies.

Understanding the modulation of specific immune cells within the tumor microenvironment (TME) offers new hope in cancer treatments, especially in cancer immunotherapies. In recent years, immune modulation and resistance to immunotherapy have become critical challenges in cancer treatments. However, novel strategies for immune modulation have emerged as promising approaches for oncology due to the vital roles of the immunomodulators in regulating tumor progression and metastasis and modulating immunological responses to standard of care in cancer treatments. With the progress in immuno-oncology, a growing number of novel immunomodulators and mechanisms are being uncovered, offering the potential for enhanced clinical immunotherapy in the near future. Thus, gaining a comprehensive understanding of the broader context is essential. Herein, we particularly summarize the paradoxical role of tumor-related immune cells, focusing on how targeted immune cells and their actions are modulated by immunotherapies to overcome immunotherapeutic resistance in tumor cells. We also highlight the molecular mechanisms employed by tumors to evade the long-term effects of immunotherapeutic agents, rendering them ineffective.

Resistance to immune checkpoint inhibitors (ICI) in cancer patients is not fully understood, and predictive biomarkers are lacking. MELANFα (NCT03348891) is an open-label, prospective, multicenter cohort of 60 patients with advanced melanoma receiving ICI (bitherapy: ipilimumab + nivolumab; monotherapy: pembrolizumab or nivolumab). The primary objective was to evaluate whether changes in plasma TNF between baseline (W0) and week 12 (W12) identified patients with non-progressive disease at W12. Secondary and exploratory objectives were to assess the association between plasma TNF, tumor response, and changes in circulating T cells. Plasma TNF increased along therapy, but its W12/W0 fold change was not associated with non-progressive disease at W12. However, plasma TNF levels at W12 were significantly higher in non-responders than in responders across therapies (p = .0129). The remodeling of circulating T cell subpopulations was mostly triggered by bitherapy. Increased proportions of circulating central memory and effector memory CD8 T cells after bitherapy were positively and negatively associated with response to treatment, respectively. In this cohort, circulating T cells from responders and non-responders also displayed distinct molecular characteristics. Indeed, responders showed an increased proportion of CD8 T cells with low enrichment of TNF-related pathways and high cytotoxic potential, while non-responders displayed increased proportions of circulating CD8 EM T cells enriched for TNF-related pathways and directed toward cytokine expression. In conclusion, our study shows that elevated plasma TNF and enriched TNF pathways in T cells are associated with poorer clinical outcomes, reinforcing the notion that TNF may dampen ICI efficacy.

Mutations in the exonuclease domains of the replicative nuclear DNA polymerases POLD1 and POLE are associated with increased cancer incidence, elevated tumor mutation burden (TMB), and enhanced response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond, highlighting the need for a better understanding of how TMB affects tumor biology and subsequently immunotherapy response. To address this, we generated mice with germline and conditional mutations in the exonuclease domains of Pold1 and Pole. Engineered mice with Pold1 and Pole mutator alleles presented with spontaneous cancers, primarily lymphomas, lung cancer, and intestinal tumors, whereas Pold1 mutant mice also developed tail skin carcinomas. These cancers had highly variable tissue type-dependent increased TMB with mutational signatures associated with POLD1 and POLE mutations found in human cancers. The Pold1 mutant tail tumors displayed increased TMB; however, only a subset of established tumors responded to ICB. Similarly, introducing the mutator alleles into mice with lung cancer driven by mutant Kras and Trp53 deletion did not improve survival, whereas passaging these tumor cells in vitro without immune editing and subsequently implanting them into immunocompetent mice caused tumor rejection in vivo. These results demonstrated the efficiency by which cells with antigenic mutations are eliminated in vivo. Finally, ICB treatment of mutator mice earlier, before observable tumors had developed delayed cancer onset, improved survival and selected for tumors without aneuploidy, suggesting the potential of ICB in high-risk individuals for cancer prevention. Significance: Treating high-mutation burden mice with immunotherapy prior to cancer onset significantly improves survival, raising the possibility of utilizing immune checkpoint blockade for cancer prevention, especially in individuals with increased risk.

The emergence of immunotherapy has revolutionized the paradigm of cancer treatment with immune checkpoint blockades (ICB) in solid cancers, including colorectal cancer (CRC). However, only a small subset of CRC patients harboring deficient mismatch repair (dMMR) or microsatellite instability-high (MSI-H) benefits from ICB therapy. A very limited response to ICB therapy has been achieved in MMR-proficient CRC, representing a significant challenge limiting the clinical application of immunotherapy. MMR is the critical DNA repair pathway that maintains genomic integrity by correcting DNA mismatches, which is mediated by the MutSα or MutSβ complex consisting of MSH2 with MSH6 and MSH3, respectively. Given that MMR status directs effective immune response, we sought to determine whether targeting MMR capacity boosts ICB efficacy.

Azoxymethane/dextran sodium sulfate (AOM/DSS)-induced CRC and xenograft model were used to evaluate the function of PRMT6 and response to PRMT6 inhibitor EPZ020411 and combination therapy of PD1 and EPZ020411. Biochemical assays were performed to elucidate the underlying mechanism of PRMT6-mediated MSH2 methylation and immune evasion.

We have identified PRMT6 as a crucial regulator of MMR capacity via MSH2 dimethylation at R171 and R219. Such a modification abrogates its MMR capacity and prevents the recruitment of MSH3 and MSH6. PRMT6 loss or inhibition triggers cytosolic DNA accumulation and cGAS-STING signaling activation, leading to enhanced immune response in PRMT6-deficient colon tumors or xenografts. Pharmacological inhibition of PRMT6 using EPZ020411 promotes mutagenesis and destabilizes MutSα or MutSβ assembly, and prolonged EPZ020411 exposure maintains an MSI-like phenotype in microsatellite stability (MSS) cells. EPZ020411 treatment sensitizes ICB efficacy of MSS cells, but not MSI cells in vivo. Similar effects have been observed in MSS colon tumors induced by AOM/DSS.

Our study provides a preclinical proof of concept to overcome resistance to immunotherapy by targeting PRMT6 in CRC with MSS.

Objective: T cell exhaustion (TEX) is a critical determinant of immune resistance. This study was performed to investigate the key genes linked to TEX in cholangiocarcinoma (CCA) and construct a TEX-associated gene signature to forecast the prognosis of patients with CCA. Methods: Based on the expression data acquired from the E-MTAB-6389 dataset, the TEX-related modules and module genes were identified using weighted coexpression network analysis (WGCNA). Subsequently, a TEX-related prognostic signature was built by using the univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. The immune cell infiltration in each CCA sample was evaluated using the single-sample gene set enrichment analysis (ssGSEA) package, followed by single-cell RNA sequencing (scRNA-seq) analysis. Furthermore, the expression of TEX-related genes in the gene signature was experimentally validated in CCA cells by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and western blot analysis. Results: A total of 15 TEX-associated modules and 23 module genes were identified. Then, a four-gene signature related to TEX was established, containing Palladin, Cytoskeletal Associated Protein (PALLD), Member RAS Oncogene Family (RAB31), ADAM Metallopeptidase With Thrombospondin Type 1 Motif 2 (ADAMTS2), and WISP1, which could predict prognosis of patients with CCA. Moreover, neutrophils, endothelial cells, B cells, and T cells exhibited significant infiltration in CCA samples, and these four TEX-related genes were both significantly positively correlated with T cells, endothelial cells, and B cells while negatively correlated with neutrophils. Moreover, a total of 13 cell types were annotated after scRNA-seq analysis. Notably, RAB31 was mainly highly expressed in monocytes, macrophages, DC2 (Dendritic Cells 2), and DC3 (Dendritic Cells 3), and PALLD, ADAMTS2, and WISP1 were mainly overexpressed in fibroblasts. Furthermore, experimental validation revealed that the expression levels of PALLD, RAB31, ADAMTS2, and WISP1 were consistent with the trend results of bioinformatics analysis. Conclusion: A prognostic signature was developed by four TEX-related genes, including PALLD, RAB31, ADAMTS2, and WISP1, which might be a powerful predictor for the prognosis of patients with CCA. These TEX-related genes were related to the infiltration of neutrophils, endothelial cells, B cells, and T cells in CCA.

The management of Lung cancer, especially non-small cell lung cancer has undergone a paradigm shift recently with the advent of new treatment approaches including focused radiotherapy as well as evolution of a newer class of immunotherapy agents. Treatment efficacy and survival rates have improved and it is now even more important that patients are selected for appropriate interventions on the basis of a comprehensive assessment including a range of imaging as well as in-vitro tests such as immunohistochemistry. A new class of tracers targeting programmed cell death such as PD1 and PDL1 (broadly classed as Immuno PET) are being increasingly used in the molecular characterisation of patients deemed resistant to standard treatment approaches and being considered for additional interventions such as immunotherapy. In this review, we review the latest evidence in the field and propose a summary of clinical usefulness and provide a review of the research trends in this exciting and evolving field.

In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mutations to identify key mutations that are most significantly correlated to ICB response. We proposed a classifier, Gene mutation-based Predictive Signature (GPS), to categorize patients based on their predicted response and clinical outcomes post-ICB therapy. GPS outperformed conventional predictors when validated in independent cohorts. Multi-omics analysis and multiplex immunohistochemistry (mIHC) revealed insights into tumor immunogenicity, immune responses, and the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) across different GPS groups. Finally, we validated distinct responses of different GPS samples to ICB in an ex-vivo tumor organoid-PBMC co-culture model. Overall, our findings highlight a simple, robust classifier for accurate ICB response prediction, which could reduce costs, shorten testing times, and facilitate clinical implementation.

Background: Tubulin alpha 1b (TUBA1B) is a key microtubule protein essential for maintaining cellular structure and function. This protein contributes significantly to cytoskeletal formation and is implicated in various diseases. Despite its fundamental roles, TUBA1B's impact on tumor prognosis and the tumor immune microenvironment across cancer types remains inadequately understood. Methods To elucidate TUBA1B's role in cancer prognosis and immune response, we conducted a comprehensive analysis, integrating data from established databases such as The Cancer Genome Atlas, Genotype Tissue Expression, Cancer Cell Lineage Encyclopedia, Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal, TIMER, and ImmuCellAI, along with a large-scale clinical study and immunotherapy cohort. We also conducted in vitro functional assays to assess TUBA1B's functional role in tumor cells, allowing for a detailed examination of its relationship with cancer prognosis and immune modulation. Results: Our findings indicate that TUBA1B expression is dysregulated across multiple cancers, correlating strongly with poor survival outcomes and advanced pathological stages. Functional enrichment analyses further revealed that TUBA1B regulates key cell cycle processes, driving tumor proliferation, migration, and invasion. It also influences immune functions within both the innate and adaptive immune systems, affecting immune-related signaling pathways. These insights underscore TUBA1B's multifaceted role in cancer progression and immune response. Conclusion: This study highlights TUBA1B's potential as a human oncogene with substantial roles in tumorigenesis and immune regulation. Elevated TUBA1B levels are associated with an immunosuppressive tumor microenvironment, impacting cancer progression and treatment outcomes. Targeting TUBA1B may offer promising therapeutic avenues for enhancing cancer treatment, offering new perspectives for innovative anti-tumor strategies with high clinical impact.

Blood inflammation index has been shown to correlate with the prognosis of patients with gastric cancer. However, few studies have compared the efficacy of existing blood inflammatory markers in predicting the prognosis of patients with locally advanced gastric cancer in combination with neoadjuvant chemotherapy and immunotherapy.

The objective of this study was to compare the prognostic value of existing commonly used blood inflammatory index in patients with advanced gastric cancer treated with neoadjuvant chemotherapy combined with immunotherapy.

The clinicopathological data of patients with advanced gastric cancer from three centers in China were analyzed retrospectively. Univariate COX regression analysis was used to analyze the independent risk factors of poor tumor regression and overall survival (OS) in this part of patients, and the predictive value of different inflammatory indexes on prognosis was compared by C-index index. Finally, Inflammatory burden index(IBI) was grouped by X-tile software, and Kaplan-Meier method was used to compare the survival difference between groups.

A total of 163 patients were enrolled in this study. The median age was 63 years(56-68). The median cycle of neoadjuvant therapy was 4(3-4). The median survival time was 85.1%(1 years), 65.6%(2 years), and 47.4%(3 years).Univariate analysis showed that IBI was an independent risk factor for non-TR(residual tumor cells>50%) (HR=1.08,95%CI:1.00-1.45,p<0.001)and OS(HR=1.04,95%CI:1.03-1.05,p<0.001). IBI is the best predictor of OS (C-index: 0.82, 95% CI: 0.78-0.87) among all inflammatory indexes. The IBI cutoff value was 52.1. It was found that the high IBI group had a higher incidence of postoperative complications(32.1%vs14.3%, p=0.001), the proportion of non-TR patients was significantly higher than that of the low IBI group(64.3%vs35.7%, p =0.001), and the high IBI group had a significantly lower OS((47.6% vs 87.6%, p < 0.001).

IBI is the best inflammatory index to predict the prognosis of advanced gastric cancer treated with neoadjuvant chemotherapy combined with immunotherapy, which will help guide patients' treatment decisions. This result still needs to be verified by large prospective studies.

H3 lysine 4 trimethylation (H3K4me3) modification and related regulators extensively regulate various crucial transcriptional courses in health and disease. However, the regulatory relationship between H3K4me3 modification and anti-tumor immunity has not been fully elucidated. We identified 72 independent prognostic genes of lung adenocarcinoma (LUAD) whose transcriptional expression were closely correlated with known 27 H3K4me3 regulators. We constructed three H3K4me3 modification patterns utilizing the expression profiles of the 72 genes, and patients classified in each pattern exhibited unique tumor immune infiltration characteristics. Using the principal component analysis (PCA) of H3K4me3-related patterns, we constructed a H3K4me3 risk score (H3K4me3-RS) system. The deep learning analysis using 12,159 cancer samples from 26 cancer types and 725 cancer samples from 5 immunotherapy cohorts revealed that H3K4me3-RS was significantly correlated with cancer immune tolerance and sensitivity. Importantly, this risk-score system showed satisfactory predictive performance for the ICB therapy responses of patients suffering from several cancer types, and we identified that SLAMF9 was one of the immunosuppressive phenotype and immunotherapy resistance-determined genes of H3K4me3-RS. The mice melanoma model showed Slamf9 knockdown remarkably restrained cancer progression and enhanced the efficacy of anti-CTLA-4 and anti-PD-L1 therapies by elevating CD8 + T cell infiltration. This study provided a new H3K4me3-associated biomarker system to predict tumor immunotherapy response and suggested the preclinical rationale for investigating the roles of SLAMF9 in cancer immunity regulation and treatment.

Ferroptosis is a cell death mode caused by excessive accumulation of lipid peroxides caused by disturbance of intracellular metabolic pathway, which is closely related to iron and cholesterol metabolism homeostasis. Its regulation within the hypoxic metabolic tumor microenvironment (TME) has the potential to improve the effectiveness of tumor immunotherapy. The predictive role of ferroptosis in gastric cancer (GC) hypoxia TME, particularly in relation to TME immune cell infiltration, has not been fully explained.

By analyzing the mRNA expression data of ferroptosis and hypoxia-related genes, a prediction model was constructed to evaluate further the predictive value of immune cell infiltration, clinical characteristics, and immunotherapy efficacy of gastric cancer, and the essential genes were validated.

Two distinct molecular states of ferroptosis-hypoxia were identified in GC. Notably, patients with high ferroptosis-hypoxia risk scores (FHRS) displayed significant levels of hypoxia and epithelial-mesenchymal transition (EMT), which were associated with unfavorable prognosis, increased chemoresistance, and heightened immunosuppression.

This study demonstrates that ferroptosis under hypoxic conditions significantly affects the modulation of the tumor immune microenvironment. The FHRS can independently predict prognosis in gastric cancer. Assessing the molecular status of ferroptosis-hypoxia in individual patients will help in selecting more suitable immunotherapy regimens by providing a better understanding of TME characteristics and predicting immunotherapeutic outcomes.

Ferroptosis, triggered by membrane lipid peroxidation (LPO) and diminished antioxidants, can be induced by intracellular iron (II, Fe2+). However, the role of nitric oxide (NO) in causing Fe2+ overload for ferroptosis remains uncertain. This study reveals that NO can stimulate endogenous Fe2+ release by upregulating heme oxygenase 1 (HMOX1) expression. Here, ferritin heavy chain (FHC) siRNA and hyaluronic acid (HA)-modified Arg-stabilized zinc peroxide (AZOSH), a non-ferrous-based nanoagent, is synthesized to trigger ferroptosis by inducing intracellular Fe2+ overload. AZOSH, a self-catalyzed NO nanocomplex, effectively generates NO through a reaction of self-supplied Arginine (Arg) and hydrogen peroxide (H2O2), which promotes glutathione (GSH) consumption to downregulate glutathione peroxidase 4 (GPX4) expression and produces peroxynitrite (ONOO-) to enhance LPO. Meanwhile, NO promotes endo/lysosomal escape of siRNA by damaging membrane structures. Moreover, AZOSH significantly triggers Fe2+ overload through the synergistic effects of NO-activated HMOX1 expression and FHC siRNA-mediated ferritin sequestration. Additionally, the released Zn2+ from AZOSH induces oxidative stress by inhibiting mitochondrial function, further promoting ferroptosis. Consequently, AZOSH-mediated ferroptosis exhibits a strong cellular immunogenic response for T-cell activation and infiltration. Importantly, the integration of AZOSH with an anti-PD-1 antibody results in notable antitumor efficacy in vivo. Therefore, this study provides a novel concept of NO-induced ferroptosis, highlighting its role in enhancing PD-1-based immunotherapeutic efficacy.

This study aimed to systematically investigate the value of the pre-treatment neutrophil-to-lymphocyte ratio (NLR) in prognosticating the outcome of patients with advanced cancer receiving immunotherapy. We searched Embase, PubMed, Web of Science, and Cochrane Library to identify studies about cancer patients with immunotherapy until November 29, 2024. Retrospective or prospective cohort studies with pretreatment NLR data were included. The odds ratio (OR) and 95% confidence interval (CI) were calculated to evaluate the predictive value of NLR in prognosis and immunotherapy efficacy. The random effect model was applied for meta-analysis and the risk of bias was assessed by Egger test and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method. A total of 129 articles involving 18780 cases were finally selected. Most cases were advanced cancers with the median follow-up period ranged 2-48.6 months. The high pretreatment NLR level was associated with the significantly reduced OS (HR (95%CI) = 2.26 (2.03, 2.53)), PFS (HR (95% CI) = 1.83 (1.69, 1.98)), ORR (OR (95%CI) = 0.53 (0.46, 0.61)) and DCR (OR (95% CI) = 0.36 (0.29, 0.43)) in patients with advanced cancer receiving immunotherapy. The quality of evidence was low, attributed to the serious risk of bias and incon¬sistency. An elevated NLR before immunotherapy was significantly associated with poor clinical outcomes in patients with advanced cancer.

The T cell immunoglobulin and ITIM domain (TIGIT) blockade immunotherapy response is directly associated with individual differences of TIGIT expression on tumour-infiltrating lymphocytes (TILs) in tumour immune microenvironment (TIME) of non-small cell lung cancer (NSCLC). Here, we developed a TIGIT-targeted PET tracer to evaluate its feasibility in predicting immunotherapy efficacy, aiming to manage NSCLC patients accurately.

We synthesised a 18F-labeled TIGIT-targeted D-peptide, [18F]TTDP, and investigated the specificity of [18F]TTDP both to murine TIGIT and human TIGIT by a series of in vitro and in vivo assays. [18F]TTDP PET imaging was performed in humanised immune system (HIS) mice models bearing NSCLC patient-derived xenografts (PDXs) to evaluate the predictive value of FDA-approved combination immunotherapy of atezolizumab plus tiragolumab. Lastly, rhesus macaque was applied for [18F] TTDP PET to explore the tracer's in vivo distribution and translational potential in non-human primates.

[18F]TTDP showed high specificity for both murine TIGIT and human TIGIT in vitro and in vivo. The HIS NSCLC PDX platform was successfully established for [18F]TTDP PET imaging, and tumour uptake of [18F]TTDP was significantly correlated with the TIGIT expression of TILs in the TIME. [18F]TTDP PET imaging, in predicting treatment response to the combination immunotherapy in NSCLC HIS-PDX models, showed a sensitivity of 83.33% and a specificity of 100%. In addition, [18F]TTDP PET also showed cross-species consistency of the tracer biodistribution between non-human primate and murine animals, and no adverse events were observed.

The combined implementation of the [18F]TTDP and HIS-PDX model creates a state-of-the-art preclinical platform that will impact the identification and validation of TIGIT-targeted PET image-guided diagnosis, treatment response prediction, beneficial patient screening, novel immunotherapies, and ultimately the outcome of NSCLC patients. We first provided in vivo biodistribution of [18F]TTDP PET imaging in rhesus macaque, indicating its excellent translational potential in the clinic.

It is known, that different metastatic organ systems respond differently to immune checkpoint inhibitors (ICIs). In this study, we aimed to investigate the extent to which skin/subcutaneous metastases respond to ICI or targeted therapies (TTs) and whether the response rate differs from that of distant metastases in the same patient. Patients with melanoma diagnosed between January 2021 and September 2023 with at least one skin/subcutaneous metastasis who had received therapy with ICI or TT in an advanced setting were included in the analysis. Best overall response (BOR) was classified according to the revised response evaluation criteria in solid tumors (RECIST). The BOR of skin metastases and visceral metastases to ICI and TT was compared using the chi-square test. Skin metastases treated with ICI a first-line setting showed an overall response rate (ORR) of 44.1%. In contrast, visceral metastases had a higher ORR of 51.1%. However, the difference was not statistically significant (p = .77). Regarding TT, the ORR for skin metastases was 57.1%, compared to 38.5% for visceral metastases (p = .59). Interestingly, the ORR for skin/subcutaneous metastases was notably lower with ICI compared to visceral metastases, in contrast to patients who underwent TT. Skin metastases showed a poorer response to ICI than visceral metastases. Therefore, careful monitoring is recommended to detect non-response early in patients with skin metastases as skin metastases may have a worse response than TT. A larger cohort is needed for a comprehensive analysis and confirmation of our results.

Kidney renal clear cell carcinoma (KIRC) is recognized as an immunogenic tumor, and immunotherapy is incorporated into its treatment landscape for decades. The acquisition of a tumor mesenchymal phenotype through epithelial-to-mesenchymal transition (EMT) is associated with immune evasion and can contribute to immunotherapy resistance. Here, the involvement of STAM Binding Protein Like 1 (STAMBPL1) is reported in the development of mesenchymal and immune evasion phenotypes in KIRC cells. Mechanistically, STAMBPL1 elevated protein abundance and surface accumulation of TAM Receptor AXL through diminishing the TRIM21-mediated K63-linked ubiquitination and subsequent lysosomal degradation of AXL, thereby enhancing the expression of mesenchymal genes while suppressing chemokines CXCL9/10 and HLA/B/C. In addition, STAMBPL1 enhanced PD-L1 transcription via facilitating nuclear translocation of p65, and knockdown (KD) of STAMBPL1 augmented antitumor effects of PD-1 blockade. Furthermore, STAMBPL1 silencing and the tyrosine kinase inhibitor (TKI) sunitinib also exhibited a synergistic effect on the suppression of KIRC. Collectively, targeting the STAMBPL1/TRIM21/AXL axis can decrease mesenchymal phenotype and potentiate anti-tumor efficacy of cancer therapy.

Extracellular vesicles (EVs) are considered as promising candidates for predicting patients who respond to immunotherapy. Nevertheless, simultaneous detection of multiple EVs markers still presents significant technical challenges. In this work, we developed a high-throughput microdroplet-enhanced chip (MEC) platform, which utilizes thousands of individual microchambers (∼pL) as reactors, accelerating the detection efficiency of the CRISPR/Cas systems and increasing the sensitivity by up to 100-fold (aM level). Ten biomarkers (including 5 RNAs and 5 proteins) from patients' EVs are successfully detected on one chip, and the comprehensive markers show increased accuracy (AUC 0.911) than the individual marker for the efficacy prediction of immunotherapy. This platform provides a high-throughput yet sensitive strategy for screening immunotherapy markers in clinical.

Immune checkpoint inhibitors (ICIs) have dramatically transformed the treatment landscape for various malignancies, achieving notable clinical outcomes across a wide range of indications. Despite these advances, resistance to immune checkpoint blockade (ICB) remains a critical clinical challenge, characterized by variable response rates and non-durable benefits. However, growing research into the complex intrinsic and extrinsic characteristics of tumors has advanced our understanding of the mechanisms behind ICI resistance, potentially improving treatment outcomes. Additionally, robust predictive biomarkers are crucial for optimizing patient selection and maximizing the efficacy of ICBs. Recent studies have emphasized that multiple rational combination strategies can overcome immune checkpoint resistance and enhance susceptibility to ICIs. These findings not only deepen our understanding of tumor biology but also reveal the unique mechanisms of action of sensitizing agents, extending clinical benefits in cancer immunotherapy. In this review, we will explore the underlying biology of ICIs, discuss the significance of the tumor immune microenvironment (TIME) and clinical predictive biomarkers, analyze the current mechanisms of resistance, and outline alternative combination strategies to enhance the effectiveness of ICIs, including personalized strategies for sensitizing tumors to ICIs.

Immune checkpoint blockade (ICB) has revolutionized the current immuno-oncology and significantly improved clinical outcome for cancer treatment. Despite the advancement in clinics, only a small subset of patients derives immune response to the ICB therapy. Therefore, a robust predictive biomarker that identifies potential candidate becomes increasingly crucial in delivering this technology to the public. In this review, we first discuss the biomarkers that focus on tumor genome, tumor microenvironment and tumor-host interaction. Then, we compare existing databases for biomarker discovery for ICB response. We also present IOhub - an interactive web portal that incorporates 36 bulk and 10 single-cell transcriptome datasets for benchmark analysis of the current biomarkers. Finally, we highlight the trending interest in antibody drug conjugate and combination treatment and their use in precision immuno-oncology.

Lung cancer is a severe malignant tumor. This study aims to more comprehensively characterize lung cancer patients and identify combination markers for immunotherapy.

We gathered data from 166 lung cancer patients at the Cancer Hospital Affiliated with Xinjiang Medical University. The collected samples underwent NGS sequencing using a panel of 616 genes associated with cancer. Subsequently, data analysis was conducted to identify markers that are more suitable for lung cancer immunotherapy.

In this study, the most common variant genes in LUAD were TP53, EGFR, MST1, KMT2C, RBM10, LRP1B. Meanwhile, the highest mutation frequency genes in LUSC samples were TP53, KMT2D, LRP1B, FAT1, MST1, KMT2C. Mutation frequencies, tumor mutation burden (TMB), PD-L1 expression, and mutant-allele tumor heterogeneity (MATH) values differed between LUAD and LUSC, with LUSC exhibiting higher values than LUAD. Irrespective of LUAD or LUSC, patients with TMB≥10 demonstrated better immunotherapy efficacy compared to patients with TMB<10. Similarly, when PD-L1≥50%, whether in LUAD or LUSC, the immunotherapy effect was superior to that of patients with PD-L1<50%. Combining TMB≥10 and PD-L1≥50% as immunotherapy markers, in both LUAD and LUSC, resulted in a very favorable immunotherapy effect, with the overall response rate (ORR) reaching 100%.

We observed distinct mutation patterns and clinical factors between LUAD and LUSC, and noted that patients with TMB≥10 and PD-L1≥50% exhibited enhanced immunotherapy effects. Combining TMB≥10 and PD-L1≥50% proved to be a more effective predictor of immunotherapy efficacy.

The expression level of immune checkpoint proteins detected by tissue biopsy is currently used as a predictive biomarker for immune checkpoint blockade (ICB) therapy. However, tissue biopsy is susceptible to invasive sample collection procedures, significant sampling heterogeneity, and the difficulty of repeated sampling. Therefore, liquid biopsy of blood samples is becoming an alternative choice for immune checkpoint protein detection. Among various vesicles in blood, platelets can obtain cancer information to form a specific group called tumor-educated platelets (TEPs). The platelet-derived proteins in TEPs may have a predictive potential in ICB therapy.

In this study, a photo-cleavable mass-tagged self-assembled (SAMT) nanoprobe with signal amplification was developed for the quantitative detection of PD-L1. The SAMT probe was assembled by photo-cleavable mass tags, PD-L1 aptamer, and amphiphilic polymer. After binding with PD-L1 on the platelet, the probe can release mass tags with UV light exposure. The amount of the mass tag, representing that of PD-L1, was subsequently determined by mass spectrometry. The assay sensitivity can be greatly improved by up to four orders of magnitude, achieving a detection limit of 10 fM. This assay was subsequently applied to cancer cells and platelet samples from non-small cell lung cancer (NSCLC) patients. The patients with higher tumor stages, higher degrees of lymph node invasion, and better ICB response had higher PD-L1 levels on platelets. Further investigation revealed that PD-L1 on the platelets was transported from cancer cells, providing evidence for the existence of TEPs.

The SAMT probe can amplify the signal of the target molecule into that of multiple mass tags, achieving ultrasensitive ICB protein quantitative detection in platelets. Moreover, the employed SAMT assay not only revealed PD-L1 transport from cancer cells to platelets but also confirmed the presence of TEPs.

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer mortality worldwide. Immune checkpoint inhibitors (ICIs) have emerged as a crucial treatment option for patients with advanced NSCLC. However, only a subset of patients experience clinical benefit from ICIs. Therefore, identifying biomarkers that can predict response to ICIs is imperative for optimising patient selection.

Hematoxylin and eosin (H&E) images of NSCLC patients were obtained from the local cohort (n = 106) and The Cancer Genome Atlas (TCGA) (n = 899). We developed an ICI-related pathological prognostic signature (ir-PPS) based on H&E stained histopathology images to predict prognosis in NSCLC patients treated with ICIs using deep learning. To accomplish this, we employed a modified ResNet model (ResNet18-PG), a widely-used deep learning architecture well-known for its effectiveness in handling complex image recognition tasks. Our modifications include a progressive growing strategy to improve the stability of model training and the use of the AdamW optimiser, which enhances the optimisation process by adjusting the learning rate based on training dynamics.

The deep learning model, ResNet18-PG, achieved an area under the receiver operating characteristic curve (AUC) of 0.918 and a recall of 0.995 on the local cohort. The ir-PPS effectively risk-stratified NSCLC patients. Patients in the low-risk group (n = 40) had significantly improved progression-free survival (PFS) after ICI treatment compared to those in the high-risk group (n = 66, log-rank P = 0.004, hazard ratio (HR) = 3.65, 95%CI: 1.75-7.60). The ir-PPS demonstrated good discriminatory power for predicting 6-month PFS (AUC = 0.750), 12-month PFS (AUC = 0.677), and 18-month PFS (AUC = 0.662). The low-risk group exhibited increased expression of immune checkpoint molecules, cytotoxicity-related genes, an elevated abundance of tumour-infiltrating lymphocytes, and enhanced activity in immune stimulatory pathways.

The ir-PPS signature derived from H&E images using deep learning could predict ICIs prognosis in NSCLC patients. The ir-PPS provides a novel imaging biomarker that may help select optimal candidates for ICIs therapy in NSCLC.

Simultaneous detection of different biomarkers related to the spatiotemporally dynamic immune events is of particular importance for the accurate evaluation of antitumor immune effects. Here, we have developed an AND-gate logic dual resonance energy transfer nanoprobe (named DRET) for dynamic monitoring of programmed CD8+ T cell activation and tumor cell apoptosis. Immunotherapy-induced granzyme B secretion from CD8+ T cells and the subsequent caspase-3 release from apoptotic tumor cells individually activate one of the tiers of the "AND-gate" logic DRET. The resulting fluorescence recovery and magnetic resonance T1 enhancement can be used for precise immunomodulatory drug screening, early efficacy prediction, and immune stratification. Particularly, not only "Responders" can be distinguished from "Non-responders", but also "Acquired resistance" can be identified from "Maintain responders", providing a novel approach to put forward the accurate evaluation of antitumor immunity.

Tumor cell-originated events prevent efficient antitumor immune response and limit the application of anti-PD1 checkpoint immunotherapy. We show that syndecan-1 (SDC1) has a critical role in the regulation of T cell-mediated control of tumor growth. SDC1 inhibition increases the permeation of CD8+ T cells into tumors and triggers CD8+ T cell-mediated control of tumor growth, accompanied by increased proportions of progenitor-exhausted and effector-like CD8+ T cells. SDC1 deficiency alters multiple signaling events in tumor cells, including enhanced IFN-γ-STAT1 signaling, and augments antigen presentation and sensitivity to T cell-mediated cytotoxicity. Combinatory inhibition of SDC1 markedly potentiates the therapeutic effects of anti-PD1 in inhibiting tumor growth. Consistently, the findings are supported by the data from human tumors showing that SDC1 expression negatively correlates with T cell presence in tumor tissues and the response to immune checkpoint blockade therapy. Our findings suggest that SDC1 inhibits antitumor immunity, and that targeting SDC1 may promote anti-PD1 response for cancer treatment.

Cluster of differentiation 24 (CD24) is a highly glycosylated glycosylphosphatidylinositol (GPI)-anchored surface protein, expressed in various tumor cells, as a "don't eat me" signaling molecule in tumor immune. This study aimed to investigate the potential features of CD24 in pan-cancer.

The correlations between 22 immune cells and CD24 expression were using TIMER analysis. R package "ESTIMATE" was used to predict the proportion of immune and stromal cells in pan-cancer. Spearman's correlation analysis was performed to evaluate the relationships between CD24 expression and immune checkpoints, chemokines, mismatch repair, tumor mutation burden and microsatellite instability, and qPCR and western blot were conducted to assess CD24 expression levels in liver hepatocellular carcinoma (LIHC). In addition, loss of function was performed for the biological evaluation of CD24 in LIHC.

CD24 expression was positively correlated with myeloid cells, including neutrophils and myeloid-derived suppressor cells, in various tumors, such as BLCA, HNSC-HPV, HNSC, KICH, KIRC, KIRP, TGCT, THCA, THYM, and UCEC. In contrast, anti-tumor NK cells and NKT cells showed a negative association with CD24 expression in BRCA-Her2, ESCA, HNSC-HPV, KIRC, THCA, and THYM. The top three tumors with the highest correlation between CD24 and ImmuneScore were TGCT, THCA, and SKCM. Functional enrichment analysis revealed CD24 expression was negatively associated with various immune-related pathways. Immune checkpoints and chemokines also exhibited inverse correlations with CD24 in CESC, CHOL, COAD, ESCA, READ, TGCT, and THCA. Additionally, CD24 was overexpressed in most tumors, with high CD24 expression in BRCA, LIHC, and CESC correlating with poor prognosis. The TIDE database indicated tumors with high CD24 expression, particularly melanoma, were less responsive to PD1/PD-L1 immunotherapy. Finally, CD24 knockdown resulted in impaired proliferation and cell cycle progression in LIHC.

CD24 participates in regulation of immune infiltration, influences patient prognosis and serves as a potential tumor marker.