Tumor Microenvironment Research Articles

Identification of molecular subtypes based on bile acid metabolism in cholangiocarcinoma

BackgroundCholangiocarcinoma is a highly heterogeneous tumor with bile acid metabolism involving in its development. The aim of this study was to characterize bile acid metabolism and identify specific subtypes to better stratify cholangiocarcinoma patients for individualized treatment and prognostic assessment.MethodsA total of 30 bile acids were quantified using the ultra-performance liquid chromatography tandem mass spectrometry. Using Consensus clustering, the molecular subtypes related to bile acid metabolism were identified. The prognosis, clinicopathologic characteristics, immune landscape, and therapeutic response were compared between these subtypes. The single-cell RNA sequencing (scRNA-seq) analysis and preliminary cell experiment were also conducted to verify our findings.ResultsThe altered bile acid profile and genetic variation of bile acid metabolism-related genes in cholangiocarcinoma were demonstrated. The cholangiocarcinoma was categorized into bile acid metabolism-active and -inactive subtypes with different prognoses, clinicopathologic characteristics, tumor microenvironments (TME) and therapeutic responses. This categorization was reproducible and predictable. Specifically, the bile acid metabolism-active subtype showed a poor prognosis with an immunosuppressive microenvironment and an inactive response to immunotherapy, while the bile acid metabolism-inactive subtype showed the opposite characteristics. Moreover, the scRNA-seq revealed that immunotherapy altered bile acid metabolism in TME of cholangiocarcinoma. Finally, a prognostic signature related to bile acid metabolism was developed, which exhibited strong power for prognostic assessment of cholangiocarcinoma. Consistently, these results were verified by immunohistochemistry, cell proliferation, migration, and apoptosis assays.ConclusionIn conclusion, a novel cholangiocarcinoma classification based on bile acid metabolism was established. This classification was significant for the estimation of TME and prognosis.

Efficacy, Safety, and Influence on Tumor Microenvironment of Neoadjuvant Pembrolizumab plus Ramucirumab for PD-L1 Positive NSCLC: A Phase 2 Trial (EAST ENERGY).

Angiogenesis inhibitors are known to modify tumor immunity. Combination of angiogenesis inhibitors with immune checkpoint inhibitors (ICIs) has shown efficacy against many types of cancers, including non-small cell lung cancer (NSCLC). We investigated the feasibility of neoadjuvant therapy with pembrolizumab and ramucirumab, a vascular endothelial growth factor (VEGF) receptor-2 antagonist for patients with PD-L1-positive NSCLC and its influence on the tumor microenvironment (TME). Patients with pathologically proven NSCLC with PD-L1-positive, clinical stage IB-IIIA were eligible. Patients received two cycles of pembrolizumab (200 mg/body) and ramucirumab (10 mg/kg) every three weeks. Surgery was scheduled 4 to 8 weeks after the last dose. The primary endpoint was the major pathologic response (MPR) rate by a blinded independent pathology review. The sample size was 24 patients. Exploratory endpoints were evaluated to elucidate the effects of neoadjuvant therapy on TME. The 24 eligible patients were enrolled between July 2019 and April 2022. The MPR rate was 50.0% (90% confidence interval, 31.9-68.1%). Six patients showed pathological complete response. Grade 3 adverse events (AEs) occurred in 9 patients (37.5%), including 3 immune-related AEs (acute tubulointerstitial nephritis in 2 cases and polymyalgia rheumatica in one). There were no grade 4 or 5 AEs. The transcriptome and multiplexed immunohistochemistry results suggested that tumors with greater CD8+ T-cell infiltration and higher expression of effector molecules at the baseline could show better sensitivity to treatment. This new neoadjuvant combination of pembrolizumab plus ramucirumab was feasible and anti-VEGF agents may enhance the effects of ICIs.

Machine learning-based new classification for immune infiltration of gliomas.

Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited efficacy of immunotherapy. The characteristics of the immunosuppressive tumor microenvironment (TME) are one of the important factors hindering the effectiveness of immunotherapy. Therefore, this study aims to reveal the immune microenvironment (IME) characteristics of glioma and predict different immune subtypes using machine learning methods, providing guidance for immune therapy in glioma. We first performed unsupervised cluster analysis on the genes and arrays of 693 gliomas in CGGA database and 702 gliomas in TCGA database. Then establish and verify the classification model through Machine Learning (ML). Then, use DAVID to perform functional enrichment analysis for different immune subtypes. Next step, analyze the immune cell distribution, stemness maintenance, mesenchymal phenotype, neuronal phenotype, tumorigenic cytokines, molecular and clinical characteristics of different immune subtypes of gliomas. Firstly, we divide the IME of gliomas in the CGGA database into four different subtypes, namely IM1, IM2, IM3, and IM4; similarly, the IME of gliomas in the TCGA database can also be divided into four different subtypes (IMA, IMB, IMC, and IMD). Next, based on ML, we developed a highly reliable model for predicting different immune subtypes of glioma. Then, we found that Monocytic lineage, Myeloid dendritic cells, NK cells and CD8 T cells had the highest enrichment in the IM1/IMD subtypes. Cytotoxic lymphocytes were highest expressed in the IM4/IMA subtypes. Next step, Enrichment analysis revealed that the IM1-IMD subtypes were mainly closely related to the production and secretion of IL-8 and TNF signaling pathway. The IM2-IMB subtypes were strongly associated with leukocyte activation and NK cell mediated cytotoxicity. The IM3-IMC subtypes were closely related to mitotic nuclear division and mitotic cell cycle process. The IM4-IMA subtypes were strongly associated with Central Nervous System (CNS) development and striated muscle tissue development. Afterwards, Single sample gene set enrichment analysis (ssGSEA) showed that stemness maintenance phenotypes were mainly enriched in the IM4/IMA subtypes; Neuronal phenotypes were closely associated with the IM2/IMB subtypes; and mesenchymal phenotypes and tumorigenic cytokines were highly correlated with the IM2 /IMB subtypes. Finally, we found that compared with patients in the IM2/IMB and IM4/IMA subtypes, the IM1/IMD and IM3/IMC subtypes have the highest proportion of GBM patients, the shortest average overall survival of patients and the lowest proportion of patients with IDH mutation and 1p36/19q13 co-deletion. We developed a highly reliable model for predicting different immune subtypes of glioma by ML. Then, we comprehensively analyzed the immune infiltration, molecular and clinical features of different immune subtypes of gliomas and defined gliomas into four subtypes: immunogenic subtype, adaptive immune resistance subtype, mesenchymal subtype, and immune tolerance subtype, which represent different TMEs and different stages of tumor development.

Comprehensive pan-cancer analysis reveals ENC1 as a promising prognostic biomarker for tumor microenvironment and therapeutic responses

Accumulating research showed that ENC1 plays a critical role in maintaining the physiological functions. However, little is known about its role in predicting prognosis and immunotherapy response across cancers. In our results, compared to normal tissues, most cancer tissues exhibit increased ENC1 expression. We found that the most common type of genetic variation was gene mutation. In addition, a positive correlation was found between CNV and ENC1 expression. Moreover, the overexpression of ENC1 was positively correlated with poor clinical outcomes. The GSEA results showed that ENC1 is closely correlated with tumor-promoting biological functions in most cancers. ENC1 is also closely negatively associated with the infiltration levels of T cells, activated NK cells, and B cells. Most immunomodulators are positively associated with ENC1. Further, we verified that inhibition of ENC1 expression suppressed the proliferation and migration of breast cancer, pancreatic cancer and glioma cells. In conclusion, our study demonstrated that ENC1 plays a protumorigenic role in most cancers. Additionally, ENC1 is closely correlated with tumor microenvironment features and immune checkpoint inhibitors expression. Overall, ENC1 could serve as a promising potential prognostic biomarker in various tumors.

Photocrosslinkable, Low-Affinity Affibodies Show Improved Transport and Retention in 3D Tumor Spheroids.

The efficacy of affinity-based treatments for cancer and other diseases is often limited by poor distribution throughout the targeted tissue. Although lower-affinity antibodies will penetrate more uniformly, these often reach lower concentrations because of their rapid clearance from the tissue. To increase retention and improve distribution, we created low-affinity photocrosslinkable affibodies that can diffuse into dense tumor matrices with limited tumor barrier formation and then be photocrosslinked in place to cell receptors to increase retention. In testing with 3D tumor spheroids, the addition of a 50 nM photocrosslinkable affibody showed a similar level of accumulation at the edges of the spheroid but a higher level near the middle of the spheroid than the wild-type (non-photocrosslinkable) affibody. These results show that target affinity affects protein transport in tumor microenvironments and that covalently cross-linking the ligands to cells may improve both their transport and retention.

Enhanced Antitumor Efficacy of Oncolytic Vaccinia Virus Therapy Through Keratin-Mediated Delivery in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) represents an aggressive subtype characterized by high rates of recurrence and metastasis, necessitating the exploration of alternative treatment strategies. Oncolytic vaccinia virus (OVV) therapy has emerged as a promising approach, selectively infecting and destroying tumor cells. However, its efficacy is often hampered by inadequate viral distribution within the tumor microenvironment. Here, we investigate the potential of keratin (KTN) as a carrier for OVV delivery to enhance viral distribution and antitumor efficacy. In vitro assays revealed that KTN significantly improves OVV stability, leading to increased tumor cell apoptosis and necrosis. Furthermore, KTN effectively inhibits cancer cell migration by suppressing the epithelial–mesenchymal transition (EMT) process and downregulating metastasis-related proteins. These findings are corroborated in a syngeneic TNBC mouse model, where KTN-mediated OVV delivery enhances cytotoxic T cell-mediated antitumor immune responses without compromising the anti-angiogenic effects of the virus. Notably, KTN alone exhibits antitumor effects by suppressing tumor growth and metastasis, underscoring its potential as a standalone therapeutic agent. In conclusion, our study underscores the promise of KTN-mediated OVV delivery as a promising therapeutic strategy for TNBC. By improving viral distribution, suppressing EMT, and enhancing antitumor immunity, this approach holds significant potential for enhancing patient outcomes in TNBC treatment. Further investigation is warranted to explore the broader utility of KTN in various cancer therapy approaches.

Lactylation in cancer: Mechanisms in tumour biology and therapeutic potentials.

Lactylation, a recently identified form of protein post-translational modification (PTM), has emerged as a key player in cancer biology. The Warburg effect, a hallmark of tumour metabolism, underscores the significance of lactylation in cancer progression. By regulating gene transcription and protein function, lactylation facilitates metabolic reprogramming, enabling tumours to adapt to nutrient limitations and sustain rapid growth. Over the past decade, extensive research has revealed the intricate regulatory network underlying lactylation in tumours. Large-scale sequencing and machine learning have confirmed the widespread occurrence of lactylation sites across the tumour proteome. Targeting lactylation enzymes or metabolic pathways has demonstrated promising anti-tumour effects, highlighting the therapeutic potential of this modification. This review comprehensively explores the mechanisms of lactylation in cancer cells and the tumour microenvironment. We expound on the application of advanced omics technologies for target identification and data modelling within the lactylation field. Additionally, we summarise existing anti-lactylation drugs and discuss their clinical implications. By providing a comprehensive overview of recent advancements, this review aims to stimulate innovative research and accelerate the translation of lactylation-based therapies into clinical practice. KEY POINTS: Lactylation significantly influences tumour metabolism and gene regulation, contributing to cancer progression. Advanced sequencing and machine learning reveal widespread lactylation sites in tumours. Targeting lactylation enzymes shows promise in enhancing anti-tumour drug efficacy and overcoming chemotherapy resistance. This review outlines the clinical implications and future research directions of lactylation in oncology.

Identification of lncRNA dual targeting PD-L1 and PD-L2 as a novel prognostic predictor for gastric cancer

BackgroundAlthough breakthroughs have been achieved in gastric cancer (GC) therapy with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1), the acquisition of high response rate remains a huge challenge for clinicians. It is imperative to identify novel biomarkers for predicting response to immunotherapy and explore alternative therapeutic strategy for GC.MethodsThe transcriptomic profiles and clinical information of GC patients from The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) database was used to screen differentially expressed lncRNAs between the tumor specimens and the paracancerous tissues. The TargetScan, miRDB and miRcode database were then utilized to construct competing endogenous RNA (ceRNA) networks and identify pivotal lncRNAs. An independent dataset from GEO (GSE70880) and 23 pairs of GC specimens of our cohort were subsequently performed for external validity. The relationship between clinical variables and gene expression were evaluated by Kruskal–wallis test and Wilcoxon signed-rank. The prognostic value of the candidate genes was assessed using Kaplan-Meier analysis and Cox regression models. CIBERSORT and Gene set enrichment analysis (GSEA) were used to determine immune cell infiltration. Gastric adenocarcinoma AGS cells and human embryonic kidney 293T (HEK293T) cells with knockdown of LINC01094 were generated by siRNA transfection, followed by detecting the alteration of the target miRNA and PD-L1/PD-L2 by RT-qPCR. Besides, the interaction between lncRNA and the miRNA–PD-L1/PD-L2 axis were verified by dual luciferase reporter assay.ResultsTwenty-two intersecting lncRNAs were identified to be PD-L1/PD-L2-related lncRNAs and LINC01094–miR-17-5p–PD-L1/PD-L2 was constructed as a potential ceRNA network. LINC01094 was increased in tumor specimens than adjacent normal samples and was positively associated with advanced tumor stages and EBV and MSI status. Furthermore, LINC01094 expression was an independent risk factor for poor overall survival (OS) in GC patients. CD8+ T cell exhaustion-related genes were enriched in high-LINC01094 tissues and high-PD-L2 group. A strong positive association of LINC01094 expression was established with M2 macrophages, IL-10+ TAM, as well as PD-L1 and PD-L2 levels, therefore a LINC01094–miR-17-5p–IL-10 network was proposed in macrophages. Using the exoRBase database, LINC01094 was assumed in blood exosomes of GC patients The results of knockdown experiments and luciferase reporter assays revealed that LINC01094 interacted with miR-17-5p and served as a miRNA sponge to regulate the expression of PD-L1 and PD-L2.ConclusionLINC01094 dually regulates the expression of PD-L1 and PD-L2 and shapes the immunosuppressive tumor microenvironment via sponging miR-17-5p. LINC01094 may serve as a potential prognostic predictor and therapeutic target in GC.

Intratumoral microbiota: an emerging force in diagnosing and treating hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) ranks among the most prevalent types of cancer in the world and its incidence and mortality are increasing year by year, frequently diagnosed at an advanced stage. Traditional treatments such as surgery, chemotherapy, and radiotherapy have limited efficacy, so new diagnostic and treatment strategies are urgently needed. Recent research has discovered that intratumoral microbiota significantly influences the development, progression, and metastasis of HCC by modulating inflammation, immune responses, and cellular signaling pathways. Intratumoral microbiota contributes to the pathologic process of HCC by influencing the tumor microenvironment and altering the function of immune system. This article reviews the mechanism of intratumoral microbiota in HCC and anticipates the future possibilities of intratumoral microbiota-based therapeutic strategies for HCC management. This emerging field provides fresh insights into early diagnosis and personalized approaches for HCC while holding substantial clinical application potential to improve patient outcomes and tailor interventions to individual tumor profiles.

Integrating single cell and bulk RNA sequencing data identifies RBM17 as a novel response biomarker for immunotherapy in bladder cancer.

Checkpoint inhibitors (CPIs) have been widely applied in the treatment of patients with bladder cancer (BLCA). However, there is still unmet need to dissect response predict biomarkers. To uncover CPI response-related marker genes in cancer cells, we utilized SCISSOR, integrating single-cell RNA and bulk RNA sequencing data. Transcriptomic and clinical data from IMvigor210, UNC-108, and BCAN/HCRN datasets were collected to evaluate and validate the identified biomarkers and signatures. Additionally, we analyzed TCGA-BLCA and local-BLCA RNA-seq data to investigate alternative splicing events (ASEs). Cell viability was assessed in T24 and UMUC3 cells with RBM17 upregulation or downregulation. Through SCISSOR analysis, we discovered that the expression levels of RBM17, TAP1, and PSMB8 were significantly associated with CPI response. Since PSMB8 displayed a highly positive correlation with TAP1, we developed a CPI response score (CRS) signature based on the expression profiles of RBM17 and TAP1. The CRS demonstrated robust predictive capacity in IMvigor210, UNC-108, and BCAN/HCRN datasets and was associated with higher tumor mutational burden (TMB), PD-L1 expression, and unique genomic features. Notably, RBM17 was not linked to the clinical outcomes of BLCA patients but positively correlated with BLCA cell proliferation in vitro. In the meantime, RBM17 was correlated with higher activity in core biological pathways, including antigen processing machinery, CD8 + T effector cells, cell cycle, DNA damage repair, epithelial-mesenchymal transition, histone regulation, and immune checkpoints. Moreover, the high-RBM17 group showed enrichment of LumU/Ba/sq subtypes but fewer FGFR3 alterations. Lastly, RBM17 significantly upregulated ASEs in BLCA samples, leading to higher neoantigen levels, a more inflamed tumor microenvironment, and improved CPI response. RBM17 is associated with higher ASEs and neoantigen levels, thereby potentiating the efficacy of CPI in BLCA. The established predictive signature, utilizing only two genes, has the potential to streamline clinical applications, providing a cost-effective alternative to expensive genomic, transcriptomic, and biological feature tests.

Deep learning analysis of histopathological images predicts immunotherapy prognosis and reveals tumour microenvironment features in non-small cell lung cancer.

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.

A Systematic Review of Mesenchymal Stem Cell-Derived Extracellular Vesicles: A Potential Treatment for Glioblastoma

Background: Glioblastoma (GBM) is an extremely aggressive brain tumor that has few available treatment options and a dismal prognosis. Recent research has highlighted the potential of extracellular vesicles (MSC-EVs) produced from mesenchymal stem cells as a potential treatment approach for GBM. MSC-EVs, including exosomes, microvesicles, and apoptotic bodies, perform a significant function in cellular communication and have shown promise in mediating anti-tumor effects. Purpose: This systematic literature review aims to consolidate current findings on the therapeutic potential of MSC-EVs in GBM treatment. Methods: A systematic search was conducted across major medical databases (PubMed, Web of Science, and Scopus) up to September 2024 to identify studies investigating the use of MSC-derived EVs in GBM therapy. Keywords included “extracellular vesicles”, “mesenchymal stem cells”, “targeted therapies”, “outcomes”, “adverse events”, “glioblastoma”, and “exosomes”. Inclusion criteria were studies published in English involving GBM models both in vivo and in vitro and those reporting on therapeutic outcomes of MSC-EVs. Data were extracted and analyzed based on EV characteristics, mechanisms of action, and therapeutic efficacy. Results: The review identified several key studies demonstrating the anti-tumor effects of MSC-EVs in GBM models. A total of three studies were included, focusing on studies conducted between 2021 and 2023. The review included three studies that collectively enrolled a total of 18 patients. These studies were distributed across two years, with two trials published in 2023 (66.7%) and one in 2021 (33.3%). The mean age of the participants ranged from 37 to 57 years. In terms of gender distribution, males were the predominant group in all studies. Prior to receiving MSC-EV therapy, all patients had undergone standard treatments for GBM, including surgery, chemotherapy (CT), and, in some cases, radiation therapy (RT). In all three studies, the targeted treatment involved the administration of herpes simplex virus thymidine kinase (HSVtk) gene therapy delivered to the tumor site, then 14 days of ganciclovir treatment. Outcomes across the studies indicated varying levels of efficacy for the MSC-EV-based therapy. The larger 2023 study reported fewer encouraging outcomes, with a median PFS of 11.0 months (95% CI: 8.3–13.7) and a median OS of 16.0 months (95% CI: 14.3–17.7). Adverse effects were reported in only one of the studies, the 2021 trial, where patients experienced mild-to-moderate side effects, including fever, headache, and cerebrospinal fluid leukocytosis. A total of 11 studies on preclinical trials, using in vitro and in vivo models, were included, covering publications from 2010 to 2024. The studies utilized MSCs as delivery systems for various therapeutic agents (interleukin 12, interleukin 7, doxorubicin, paclitaxel), reflecting the versatility of these cells in targeted cancer therapies. Conclusions: MSC-derived EVs represent a promising therapeutic approach for GBM, offering multiple mechanisms to inhibit tumor growth and enhance treatment efficacy. Their ability to deliver bioactive molecules and modulate the tumor microenvironment underscores their potential as a novel, cell-free therapeutic strategy. Future studies should optimize EV production and delivery methods and fully understand their long-term effects in clinical settings to harness their therapeutic potential in GBM treatment.

Anti-tumor mechanism of artesunate

Artesunate (ART) is a classic antimalarial drug with high efficiency, low toxicity and tolerance. It has been shown to be safe and has good anti-tumor effect. Existing clinical studies have shown that the anti-tumor mechanisms of ART mainly include inducing apoptosis and autophagy of tumor cells, affecting tumor microenvironment, regulating immune response, overcoming drug resistance, as well as inhibiting tumor cell proliferation, migration, invasion, and angiogenesis. ART has been proven to fight against lung cancer, hepatocarcinoma, lymphoma, multiple myeloma, leukemia, colorectal cancer, ovarian cancer, cervical cancer, malignant melanoma, oral squamous cell carcinoma, bladder cancer, prostate cancer and other neoplasms. In this review, we highlight the effects of ART on various tumors with an emphasis on its anti-tumor mechanism, which is helpful to propose the potential research directions of ART and expand its clinical application.

A Highly Tumor‐Permeating DNA Nanoplatform for Efficient Remodeling of Immunosuppressive Tumor Microenvironments

AbstractThe immunosuppressive tumor microenvironment and limited intratumoral permeation have largely constrained the outcome of tumor therapy. Herein, we report a tailored DNA structure‐based nanoplatform with striking tumor‐penetrating capability for targeted remodeling of the immunosuppressive tumor microenvironment in vivo. In our design, chemo‐immunomodulator (gemcitabine) can be precisely grafted on DNA sequences through a reactive oxygen species (ROS)‐sensitive linker. After self‐assembly, the gemcitabine‐grafted DNA structure can site‐specifically organize legumain‐activatable melittin pro‐peptide (promelittin) on each vertex for intratumoral delivery and further function as the template to load photosensitizers (methylene blue) for ROS production. The tailored DNA nanoplatform can achieve targeted accumulation, highly improved intratumoral permeation, and efficient immunogenic cell death of tumor cells by laser irradiation. Finally, the immunosuppressive tumor microenvironment can be successfully remodeled by reducing multi‐type immunosuppressive cells and enhancing the infiltration of cytotoxic lymphocytes in the tumor. This rationally developed multifunctional DNA nanoplatform provides a new avenue for the development of tumor therapy.

Multifunctional Nanocomposite Hydrogel with Enhanced Chemodynamic Therapy and Starvation Therapy for Inhibiting Postoperative Tumor Recurrence

Surgical resection is the primary treatment for melanoma; however, preventing tumor recurrence after resection remains a significant clinical challenge. To address this, we developed a multifunctional nanocomposite hydrogel (H-CPG) composed of glucose oxidase (GOx)-coated CuS@PDA@GOx (CPG) nanoparticles, aminated hyaluronic acid (HA-ADH), and oxidized rhizomatous polysaccharides (OBSP), which are interconnected through hydrogen bonds and dynamic Schiff base linkages. In the acidic tumor micro-environment, the hydrogel releases GOx, catalyzing the production of hydrogen peroxide (H2O2), which enhances chemokinetic activity through a Cu2+-mediated Fenton-like reaction. This process generates hydroxyl radicals that intensify oxidative stress and promote macrophage polarization from the M2 to M1 phenotype. This polarization triggers the release of pro-inflammatory cytokines, thereby inhibiting tumor recurrence. Additionally, the hydrogel induces photothermal effects that help eradicate residual bacteria at the wound site. Overall, the H-CPG hydrogel offers a dual mechanism to prevent melanoma recurrence and reduce resistance to monotherapy, presenting a promising strategy for postoperative tumor management.

Tumor therapy utilizing dual-responsive nanoparticles: A multifaceted approach integrating calcium-overload and PTT/CDT/chemotherapy

The advancement of rational nano drug delivery systems offers robust tools for achieving synergistic therapeutic outcomes in tumor treatment. In this study, we present the development of pH and near-infrared laser dual-responsive nanoparticles (DOX-CuS@CaCO3@PL-PEG, DCCP NPs) based on calcium carbonate, utilizing a one-pot gas diffusion reaction. These nanoparticles enable combined photothermal therapy (PTT), chemodynamic therapy (CDT), chemotherapy, and Ca2+-overloading synergistic therapy. Doxorubicin (DOX) and copper sulfide (CuS) NPs were co-loaded in CaCO3, followed by PEG surface functionalization. The presence of PEG enhanced the stability of DCCP NPs in aqueous environments. Controlled release of DOX, CuS NPs, and Ca2+ occurs specifically in the acidic tumor microenvironment. Released DOX enhances chemotherapy efficiency, while CuS NPs, upon laser irradiation, induce thermal damage, promoting further drug release and cellular uptake. Additionally, CuS NPs in our system consume excess GSH and generate toxic hydroxyl radicals (·OH) through a Fenton-like reaction, contributing to CDT. These radicals not only directly eliminate tumor cells but also disrupt mitochondrial Ca2+ buffering capacity. Furthermore, Ca2+ released from CaCO3 induces Ca2+-overloading, intensifying mitochondrial disruption and oxidative damage. The synergistic combination of PTT, CDT, chemotherapy, and Ca2+-overloading showcases significant therapeutic potential, indicating broad applications in tumor therapy. This multifaceted approach holds promise for advancing the field of tumor therapeutics.

Convergent inducers and effectors of T cell paralysis in the tumour microenvironment.

Tumorigenesis embodies the formation of a heterotypic tumour microenvironment (TME) that, among its many functions, enables the evasion of T cell-mediated immune responses. Remarkably, most TME cell types, including cancer cells, fibroblasts, myeloid cells, vascular endothelial cells and pericytes, can be stimulated to deploy immunoregulatory programmes. These programmes involve regulatory inducers (signals-in) and functional effectors (signals-out) that impair CD8+ and CD4+ T cell activity through cytokines, growth factors, immune checkpoints and metabolites. Some signals target specific cell types, whereas others, such as transforming growth factor-β (TGFβ) and prostaglandin E2 (PGE2), exert broad, pleiotropic effects; as signals-in, they trigger immunosuppressive programmes in most TME cell types, and as signals-out, they directly inhibit T cells and also modulate other cells to reinforce immunosuppression. This functional diversity and redundancy pose a challenge for therapeutic targeting of the immune-evasive TME. Fundamentally, the commonality of regulatory programmes aimed at abrogating T cell activity, along with paracrine signalling between cells of the TME, suggests that many normal cell types are hard-wired with latent functions that can be triggered to prevent inappropriate immune attack. This intrinsic capability is evidently co-opted throughout the TME, enabling tumours to evade immune destruction.

4-Hydroxynonenal Promotes Colorectal Cancer Progression Through Regulating Cancer Stem Cell Fate.

Aims: Tumor microenvironment (TME) plays a crucial role in sustaining cancer stem cells (CSCs). 4-hydroxynonenal (4-HNE) is abundantly present in the TME of colorectal cancer (CRC). However, the contribution of 4-HNE to CSCs and cancer progression remains unclear. This study aimed to investigate the impact of 4-HNE on the regulation of CSC fate and tumor progression. Methods: Human CRC cells were exposed to 4-HNE, and CSC signaling was analyzed using quantitative real-time polymerase chain reaction, immunofluorescent staining, fluorescence-activated cell sorting, and bioinformatic analysis. The tumor-promoting role of 4-HNE was confirmed using a xenograft model. Results: Exposure of CRC cells to 4-HNE activated noncanonical hedgehog (HH) signaling and homologous recombination repair (HRR) pathways in LGR5+ CSCs. Furthermore, blocking HH signaling led to a significant increase in the expression of γH2AX, indicating that 4-HNE induces double-stranded DNA breaks (DSBs) and simultaneously activates HH signaling to protect CSCs from 4-HNE-induced damage via the HRR pathway. In addition, 4-HNE treatment increased the population of LGR5+ CSCs and promoted asymmetric division in these cells, leading to enhanced self-renewal and differentiation. Notably, 4-HNE also promoted xenograft tumor growth and activated CSC signaling invivo. Innovation and Conclusion: These findings demonstrate that 4-HNE, as a signaling inducer in the TME, activates the noncanonical HH pathway to shield CSCs from oxidative damage, enhances the proliferation and asymmetric division of LGR5+ CSCs, and thereby facilitates tumor growth. These novel insights shed light on the regulation of CSC fate within the oxidative TME, offering potential implications for understanding and targeting CSCs for CRC therapy.

Extracellular vesicles in cancer drug resistance: Mechanistic insights and therapeutic implications

AbstractDespite significant advancements in the treatment of cancer, therapeutic resistance remains a major hurdle for the achievement of full cures. Besides being typically driven by intratumoral heterogeneity, such acquired resistance also relies heavily on cell‐cell communication whereby extracellular vesicles (EVs) carrying resistance‐related components can be transferred from drug‐resistant cells or nontumorigenic members within tumor microenvironment (TME) to their sensitive neighbors. The cargo and membrane surface proteins of EVs derived from drug‐resistant cells and TME cells carry abundant biological information, transferring therapy‐resistant capacity to sensitive cancer cells. Hence, a deep understanding of the roles of EVs in cancer therapy resistance will facilitate identifying biomarkers and developing new approaches to restore therapy sensitivity. In this review, we summarize our current understanding regarding the causes and effects of EV‐mediated cell–cell communication in drug resistance, with a particular notice on how various kinds of cargoes derived from different cells within TME are linked to the resistant phenotype. We also discuss how this knowledge can contribute to improvements in clinical practice, that is, the opportunities and challenges of EVs in functioning as potential biomarkers in predicting therapeutic resistance and, by extension, EV‐based therapy in achieving deeper and longer‐lasting clinical responses.

18F]F-AraG Uptake in Vertebral Bone Marrow May Predict Survival in Patients with Non-Small Cell Lung Cancer Treated with Anti-PD-(L)1 Immunotherapy.

Despite the systemic impact of both cancer and the associated immune response, immuno-PET is predominantly centered on assessment of the immune milieu within the tumor microenvironment. The aim of this study was to assess the value of [18F]F-AraG PET imaging as a noninvasive method for evaluation of system-wide immune status of patients with non-small cell lung cancer before starting immunotherapy. Methods: Eleven patients with advanced non-small cell lung cancer were imaged with [18F]F-AraG before starting immunotherapy. Diagnostic [18F]FDG PET/CT scans were analyzed to assess differences in the extent of disease among patients. SUVmax, SUVmean, and total SUV (SUVtotal) from all tumor lesions, active lymph nodes, spleen, vertebral bone marrow, liver, thyroid, heart, and bowel were extracted from the baseline [18F]F-AraG scans, and discriminant and Kaplan-Meier analyses were performed to test their ability to predict patient response and overall survival. Results: The extent of the disease was variable in the patient cohort, but none of the [18F]FDG biomarkers associated with tumor burden (SUVmax, total metabolic tumor volume, and total lesion glycolysis) was predictive of patient survival. The differences in the [18F]F-AraG and [18F]FDG distribution were observed both within and between lesions, confirming that they capture distinct aspects of the tumor microenvironment. Of the 3 SUV parameters studied, [18F]F-AraG SUVtotal provided a dynamic range suitable for stratifying tumors or patients according to their immune activity. [18F]F-AraG SUVtotal measured in the lumbar and sacral vertebrae differentiated between patients who progressed on therapy and those who did not with 90.9% and 81.8% accuracy, respectively. The Kaplan-Meier analysis revealed that patients with high [18F]F-AraG SUVtotal in the lumbar bone marrow had significantly lower probability of survival than those with a low signal (P = 0.0003). Conclusion: This study highlights the significance of assessing systemic immunity and indicates the potential of the [18F]F-AraG bone marrow signal as a predictive imaging biomarker for patient stratification and treatment guidance.