Influence of tumour micro-environment heterogeneity on therapeutic response

Atomic force microscopy as a nanomechanical tool for cancer liquid biopsy

Liquid biopsies have been receiving tremendous attention for their potential to reshape cancer management. Though current studies of cancer liquid biopsy primarily focus on applying biochemical assays to characterize the genetic/molecular profiles of circulating tumor cells (CTCs) and their secondary products shed from tumor sites in bodily fluids, delineating the nanomechanical properties of tumor-associated materials in liquid biopsy specimens yields complementary insights into the biology of tumor dissemination and evolution. Particularly, atomic force microscopy (AFM) has become a standard and versatile toolbox for characterizing the mechanical properties of living biological systems at the micro/nanoscale, and AFM has been increasingly utilized to probe the nanomechanical properties of various tumor-derived analytes in liquid biopsies, including CTCs, tumor-associated cells, circulating tumor DNA (ctDNA) molecules, and extracellular vesicles (EVs), offering additional possibilities for understanding cancer pathogenesis from the perspective of mechanobiology. Herein, the applications of AFM in cancer liquid biopsy are summarized, and the challenges and future directions of AFM as a nanomechanical analysis tool in cancer liquid biopsy towards clinical utility are discussed and envisioned.

Sertraline/chloroquine combination therapy to target hypoxic and immunosuppressive serine/glycine synthesis-dependent glioblastomas

The serine/glycine (ser/gly) synthesis pathway branches from glycolysis and is hyperactivated in approximately 30% of cancers. In ~13% of glioblastoma cases, we observed frequent amplifications and rare mutations in the gene encoding the enzyme PSPH, which catalyzes the last step in the synthesis of serine. This urged us to unveil the relevance of PSPH genetic alterations and subsequent ser/gly metabolism deregulation in the pathogenesis of glioblastoma. Primary glioblastoma cells overexpressing PSPH and PSPHV116I showed an increased clonogenic capacity, cell proliferation, and migration, supported by elevated nucleotide synthesis and utilization of reductive NAD(P). We previously identified sertraline as an inhibitor of ser/gly synthesis and explored its efficacy at suboptimal dosages in combination with the clinically pretested chloroquine to target ser/glyhigh glioblastoma models. Interestingly, ser/glyhigh glioblastomas, including PSPHamp and PSPHV116I, displayed selective synergistic inhibition of proliferation in response to combination therapy. PSPH knockdown severely affected ser/glyhigh glioblastoma clonogenicity and proliferation, while simultaneously increasing its sensitivity to chloroquine treatment. Metabolite landscaping revealed that sertraline/chloroquine combination treatment blocks NADH and ATP generation and restricts nucleotide synthesis, thereby inhibiting glioblastoma proliferation. Our previous studies highlight ser/glyhigh cancer cell modulation of its microenvironment at the level of immune suppression. To this end, high PSPH expression predicts poor immune checkpoint therapy responses in glioblastoma patients. Interestingly, we show that PSPH amplifications in glioblastoma facilitate the expression of immune suppressor galectin-1, which can be inhibited by sertraline treatment. Collectively, we revealed that ser/glyhigh glioblastomas are characterized by enhanced clonogenicity, migration, and suppression of the immune system, which could be tackled using combined sertraline/chloroquine treatment, revealing novel therapeutic opportunities for this subgroup of GBM patients.

The Research Progress of Metformin Regulation of Metabolic Reprogramming in Malignant Tumors

BACKGROUND

Metabolism reprogramming is a crucial hallmark of malignant tumors. Tumor cells demonstrate enhanced metabolic efficiency, converting nutrient inputs into glucose, amino acids, and lipids essential for their malignant proliferation and progression. Metformin, a commonly prescribed medication for type 2 diabetes mellitus, has garnered attention for its potential anticancer effects beyond its established hypoglycemic benefits.

METHODS

This review adopts a comprehensive approach to delineate the mechanisms underlying metabolite abnormalities within the primary metabolic processes of malignant tumors.

RESULTS

This review examines the abnormal activation of G protein-coupled receptors (GPCRs) in these metabolic pathways, encompassing aerobic glycolysis with increased lactate production in glucose metabolism, heightened lipid synthesis and cholesterol accumulation in lipid metabolism, and glutamine activation alongside abnormal protein post-translational modifications in amino acid and protein metabolism. Furthermore, the intricate metabolic pathways and molecular mechanisms through which metformin exerts its anticancer effects are synthesized and analyzed, particularly its impacts on AMP-activated protein kinase activation and the mTOR pathway. The analysis reveals a multifaceted understanding of how metformin can modulate tumor metabolism, targeting key nodes in metabolic reprogramming essential for tumor growth and progression. The review compiles evidence that supports metformin's potential as an adjuvant therapy for malignant tumors, highlighting its capacity to interfere with critical metabolic pathways.

CONCLUSION

In conclusion, this review offers a comprehensive overview of the plausible mechanisms mediating metformin's influence on tumor metabolism, fostering a deeper comprehension of its anticancer mechanisms. By expanding the clinical horizons of metformin and providing insight into metabolism-targeted tumor therapies, this review lays the groundwork for future research endeavors aimed at refining and advancing metabolic intervention strategies for cancer treatment.

The Rational Engineered Bacteria Based Biohybrid Living System for Tumor Therapy

Living therapy based on bacterial cells has gained increasing attention for their applications in tumor treatments. Bacterial cells can naturally target to tumor sites and active the innate immunological responses. The intrinsic advantages of bacteria attribute to the development of biohybrid living carriers for targeting delivery toward hypoxic environments. The rationally engineered bacterial cells integrate various functions to enhance the tumor therapy and reduce toxic side effects. In this review, the antitumor effects of bacteria and their application are discussed as living therapeutic agents across multiple antitumor platforms. The various kinds of bacteria used for cancer therapy are first introduced and demonstrated the mechanism of antitumor effects as well as the immunological effects. Additionally, this study focused on the genetically modified bacteria for the production of antitumor agents as living delivery system to treat cancer. The combination of living bacterial cells with functional nanomaterials is then discussed in the cancer treatments. In brief, the rational design of living therapy based on bacterial cells highlighted a rapid development in tumor therapy and pointed out the potentials in clinical applications.

[18F]AlF-NOTA-FAPI-04 PET/CT for Predicting Pathologic Response of Resectable Esophageal Squamous Cell Carcinoma to Neoadjuvant Camrelizumab and Chemotherapy: A Phase II Clinical Trial

This single-center, single-arm, phase II trial (ChiCTR2100050057) investigated the ability of 18F-labeled fibroblast activation protein inhibitor ([18F]AlF-NOTA-FAPI-04, denoted as 18F-FAPI) PET/CT to predict the response to neoadjuvant camrelizumab plus chemotherapy (nCC) in locally advanced esophageal squamous cell carcinoma (LA-ESCC). Methods: This study included 32 newly diagnosed LA-ESCC participants who underwent 18F-FAPI PET/CT at baseline, of whom 23 also underwent scanning after 2 cycles of nCC. The participants underwent surgery after 2 cycles of nCC. Recorded PET parameters included maximum, peak, and mean SUVs and tumor-to-background ratios (TBRs), metabolic tumor volume, and total lesion FAP expression. PET parameters were compared between patient groups with good and poor pathologic responses, and the predictive performance for treatment response was analyzed. Results: The good and poor response groups each included 16 participants (16/32, 50.0%). On 18F-FAPI PET/CT, the posttreatment SUVs were significantly lower in good responders than in poor responders, whereas the changes in SUVs with treatment were significantly higher (all P < 0.05). SUVmax (area under the curve [AUC], 0.87; P = 0.0026), SUVpeak (AUC, 0.89; P = 0.0017), SUVmean (AUC, 0.88; P = 0.0021), TBRmax (AUC, 0.86; P = 0.0031), and TBRmean (AUC, 0.88; P = 0.0021) after nCC were significant predictors of pathologic response to nCC, with sensitivities of 63.64%-81.82% and specificities of 83.33%-100%. Changes in SUVmax (AUC, 0.81; P = 0.0116), SUVpeak (AUC, 0.82; P = 0.0097), SUVmean (AUC, 0.81; P = 0.0116), and TBRmean (AUC, 0.74; P = 0.0489) also were significant predictors of the pathologic response to nCC, with sensitivities and specificities in similar ranges. Conclusion: 18F-FAPI PET/CT parameters after treatment and their changes from baseline can predict the pathologic response to nCC in LA-ESCC participants.

Magnetic resonance imaging (MRI)-based intratumoral and peritumoral radiomics for prognosis prediction in glioma patients

AIM

The purpose of this study was to identify robust radiological features from intratumoral and peritumoral regions, evaluate MRI protocols, and machine learning methods for overall survival stratification of glioma patients, and explore the relationship between radiological features and the tumour microenvironment.

MATERIAL AND METHODS

A retrospective analysis was conducted on 163 glioma patients, divided into a training set (n=113) and a testing set (n=50). For each patient, 2135 features were extracted from clinical MRI. Feature selection was performed using the Minimum Redundancy Maximum Relevance method and the Random Forest (RF) algorithm. Prognostic factors were assessed using the Cox proportional hazards model. Four machine learning models (RF, Logistic Regression, Support Vector Machine, and XGBoost) were trained on clinical and radiological features from tumour and peritumoral regions. Model evaluations on the testing set used receiver operating characteristic curves.

RESULTS

Among the 163 patients, 96 had an overall survival (OS) of less than three years postsurgery, while 67 had an OS of more than three years. Univariate Cox regression in the validation set indicated that age (p=0.003) and tumour grade (p<0.001) were positively associated with the risk of death within three years postsurgery. The final predictive model incorporated 13 radiological and 7 clinical features. The RF model, combining intratumor and peritumor radiomics, achieved the best predictive performance (AUC = 0.91; ACC = 0.86), outperforming single-region models.

CONCLUSION

Combined intratumoral and peritumoral radiomics can improve survival prediction and have potential as a practical imaging biomarker to guide clinical decision-making.

Characterization of an orthotopic mouse transplant model reveals early changes in the tumor microenvironment of lung cancer

To understand the cellular and molecular dynamics in the early stages of lung cancer, we explored a mouse model of orthotopic tumor transplant created from the Lewis Lung Carcinoma (LLC) cell line. Employing single-cell RNA sequencing, we analyzed the cellular landscape during tumor engraftment, focusing particularly on LLC cells harboring the Kras G12C mutation. This allowed us to identify LLC tumor cells via the detection of mutant Kras transcripts and observe elevated levels of Myc and mesenchymal gene expression. Moreover, our study revealed significant alterations in the lung microenvironment, including the activation of tissue remodeling genes in fibroblasts and the downregulation of MHC class II genes in myeloid subsets. Additionally, T/NK cell subsets displayed more regulatory phenotypes, coupled with reduced proliferation in CD8+ T cells. Collectively, these findings enhance our understanding of lung cancer progression, particularly in a tumor microenvironment with low immunogenicity. [BMB Reports 2024; 57(11): 484-489].

Closed-Loop Control of Macrophage Engineering Enabled by Focused-Ultrasound Responsive Mechanoluminescence Nanoplatform for Precise Cancer Immunotherapy

Macrophage engineering has emerged as a promising approach for modulating the anti-tumor immune response in cancer therapy. However, the spatiotemporal control and real-time feedback of macrophage regulatory process is still challenging, leading to off-targeting effect and delayed efficacy monitoring therefore raising risk of immune overactivation and serious side effects. Herein, a focused ultrasound responsive immunomodulator-loaded optical nanoplatform (FUSION) is designed to achieve spatiotemporal control and status reporting of macrophage engineering in vivo. Under the stimulation of focused ultrasound (FUS), the immune agonist encapsulated in FUSION can be released to induce selective macrophage M1 phenotype differentiation at tumor site and the near-infrared mechanoluminescence of FUSION is generated simultaneously to indicate the initiation of immune activation. Meanwhile, the persistent luminescence of FUSION is enhanced due to hydroxyl radical generation in the pro-inflammatory M1 macrophages, which can report the effectiveness of macrophage regulation. Then, macrophages labeled with FUSION as a living immunotherapeutic agent (FUSION-M) are utilized for tumor targeting and focused ultrasound activated, immune cell-based cancer therapy. By combining the on-demand activation and feedback to form a closed loop, the nanoplatform in this work holds promise in advancing the controllability of macrophage engineering and cancer immunotherapy for precision medicine.

Synergistic anticancer immunity in metastatic triple-negative breast cancer through an in situ amplifying Peptide-Drug Conjugate

Despite significant progress in combining cancer immunotherapy with chemotherapy to treat triple negative breast cancer (TNBC), challenges persist due to target depletion and tumor heterogeneity, especially in metastasis. Chemotherapy lacks precise targeting abilities, and targeted therapy is inadequate in addressing the diverse heterogeneity of tumors. To address these challenges, we introduce RGDEVD-DOX as a tumor-specific immunogenic agent, namely TPD1, which targets integrin αvβ3 and gets continuously activated by apoptosis. TPD1 facilitates the caspase-3-mediated in situ amplification that results in tumor-specific accumulation of doxorubicin. This local concentration of doxorubicin induces immunogenic cell death and promotes the recruitment of immune cells to the tumor site. Notably, the tumor-targeting capabilities of TPD1 help bypass the systemic immunotoxicity of doxorubicin. Consequently, this alters the tumor microenvironment, converting it into a 'hot' tumor that is more susceptible to immune checkpoint inhibition. We demonstrated the anti-metastatic and anti-cancer efficacy of this treatment using various xenograft and metastatic models. This study underscores the high potential of caspase-3 cleavable peptide-drug conjugates to be used in conjunction with anti-cancer immunotherapies.

Hydroxyacid Oxidase 1, a Glutamine Metabolism-Associated Protein, Predicts Poor Patient Outcome in Luminal Breast Cancer

Breast cancer (BC), which remains the most prevalent malignancy among women, is characterised by significant heterogeneity across its molecular subtypes. Oestrogen receptor-positive (ER+) (luminal) BC represents approximately 75% of cases, and despite advancements in treatment there remains around a 40% recurrence rate. Cellular uptake of glutamine is conducted by solute carriers (SLCs), which are significantly associated with outcome in luminal BC. In this study, differential gene expression analysis was carried out using The Cancer Genome Atlas BC dataset. This identified hydroxyacid oxidase 1 (HAO1) as significantly overexpressed in luminal BC with a high expression of SLCs. Extended analysis in the METABRIC (n = 1980) and Breast Cancer Gene-Expression Miner (n = 4421) transcriptomic databases and the Nottingham (n = 952) BC tissue cohort showed a varied survival outcome for HAO1 expression at the genomic, transcriptomic, and proteomic levels. HAO1 copy number (CN) gain (p = 0.002) and high HAO1 protein expression (p = 0.019) were associated with poor prognosis in luminal BC, whereas high HAO1 mRNA expression correlated with better survival outcomes (p = 0.023) suggesting a complex regulatory mechanism affecting HAO1 at different biological levels. Importantly, in luminal BC patients treated with endocrine therapy, high protein expression of HAO1 predicted shorter distant-metastasis free survival (p = 0.042). The knockdown of SLC1A5 and SLC7A5 significantly reduced HAO1 expression in MCF-7 and ZR-751 BC cell lines. Protein analysis confirmed significant associations between HAO1 and SLC7A5 and SLC1A5, emphasising a potential role for the enzyme in glutamine metabolism and its potential as a therapeutic target. This study underscores the prognostic significance of HAO1 in luminal BC and its relationship with patient outcomes.

Development and validation of a gene expression-based Breast Cancer Purity Score

The prevalence of malignant cells in clinical specimens, or tumour purity, is affected by both intrinsic biological factors and extrinsic sampling bias. Molecular characterization of large clinical cohorts is typically performed on bulk samples; data analysis and interpretation can be biased by tumour purity variability. Transcription-based strategies to estimate tumour purity have been proposed, but no breast cancer specific method is available yet. We interrogated over 6000 expression profiles from 10 breast cancer datasets to develop and validate a 9-gene Breast Cancer Purity Score (BCPS). BCPS outperformed existing methods for estimating tumour content. Adjusting transcriptomic profiles using the BCPS reduces sampling bias and aids data interpretation. BCPS-estimated tumour purity improved prognostication in luminal breast cancer, correlated with pathologic complete response in on-treatment biopsies from triple-negative breast cancer patients undergoing neoadjuvant treatment and effectively stratified the risk of relapse in HER2+ residual disease post-neoadjuvant treatment.

Reconstruction of cancer marker analysis with holistic anatomical precision implicates heterogeneity development during breast tumor progression

Biomarkers are not only of significant importance for cancer diagnosis and selection of treatment plans but also recently increasingly used for the evaluation of malignancy development and tumor heterogeneity. Large-size tumors from clinical patients can be unique and valuable sources for the study of cancer progression, particularly to the extent of intratumoral heterogeneity. In the present study, we obtained a series of post-surgery puncture samples from a breast cancer patient with a 4 × 3.5 × 2 cm tumor in its original size. Immunohistochemistry for Ki-67, COX-2, and CA IX was performed and the expression levels within the breast cancer tumor mass were evaluated in the reconstructed 3D models. To further evaluate the intratumoral heterogeneity, we performed high throughput whole transcriptome sequencing of 12 samples from different spatial positions within the tumor tissue. Comparing the reconstructed 3D distribution of biomarkers with projected tumor growth models, asymmetric and heterogeneous expansion of tumor mass was found to be possibly influenced by factors such as blood supply, inflammation and/or hypoxia stimulations, as suggested from the correlation between the results of Ki-67 and CA IX or COX-2 staining. Furthermore, high-throughput RNA sequencing data provided additional information for profiling the intratumoral heterogeneity and expanded the understanding of cancer progression. Digital technology for medical imaging once properly integrated with molecular pathology examinations will become particularly helpful in dissecting out in-depth information for precision medicine. We prospect that this approach, facilitated by rapidly advancing artificial intelligence, could provide new insights for clinical decision-making in the future. Strategies for the continuous development from the present study for better performance and application were discussed.

Spatial oncology: Translating contextual biology to the clinic

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

Multi-Omics Profiling Unveils the Complexity and Dynamics of Immune Infiltrates in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is a highly heterogeneous malignancy. The reasons behind the global rise in the incidence of ICC remain unclear, and there exists limited knowledge regarding the immune cells within the tumor microenvironment (TME). In this study, a more comprehensive analysis of multi-omics data was performed using machine learning methods. The study found that the immunoactivity of B cells, macrophages, and T cells in the infiltrating immune cells of ICC exhibits a significantly higher level of immunoactivity in comparison to other immune cells. During the immune sensing and response, the effect of antigen-presenting cells (APCs) such as B cells and macrophages on activating NK cells was weakened, while the effect of activating T cells became stronger. Simultaneously, four distinct subpopulations, namely BLp, MacrophagesLp, BHn, and THn, have been identified from the infiltrating immune cells, and their corresponding immune-related marker genes have been identified. The immune sensing and response model of ICC has been revised and constructed based on our current comprehension. This study not only helps to deepen the understanding the heterogeneity of infiltrating immune cells in ICC, but also may provide valuable insights into the diagnosis, evaluation, treatment, and prognosis of ICC.

A Versatile Microfluidic Device System that Lacks a Synthetic Extracellular Matrix Recapitulates the Blood-Brain Barrier and Dynamic Tumor Cell Interaction

Microfluidic systems offer controlled microenvironments for cell-to-cell and cell-to-stroma interactions, which have precise physiological, biochemical, and mechanical features. The optimization of their conditions to best resemble tumor microenvironments constitutes an experimental modeling challenge, particularly regarding carcinogenesis in the central nervous system (CNS), given the specific features of the blood-brain barrier (BBB). Gel-free 3D microfluidic cell culture systems (gel-free 3D-mFCCSs), including features such as self-production of extracellular matrices, provide significant benefits, including promoting cell-cell communication, interaction, and cell polarity. The proposed microfluidic system consisted of a gel-free culture device inoculated with human brain microvascular endothelial cells (HBEC5i), glioblastoma multiforme cells (U87MG), and astrocytes (ScienCell 1800). The gel-free 3D-mFCCS showed a diffusion coefficient of 4.06 × 10-9 m2·s-1, and it reconstructed several features and functional properties that occur at the BBB, such as the vasculogenic ability of HBEC5i and the high duplication rate of U87MG. The optimized conditions of the gel-free 3D-mFCCS allowed for the determination of cellular proliferation, invasion, and migration, with evidence of both physical and biochemical cellular interactions, as well as the production of pro-inflammatory cytokines. In conclusion, the proposed gel-free 3D-mFCCSs represent a versatile and suitable alternative to microfluidic systems, replicating several features that occur within tumor microenvironments in the CNS. This research contributes to the characterization of microfluidic approaches and could lead to a better understanding of tumor biology and the eventual development of personalized therapies.

Exosomal PDL1 Suppresses the Anticancer Activity of CD8+ T Cells in Hepatocellular Carcinoma

Tumor microenvironment (TME) is essential for the development and progression of hepatocellular carcinoma (HCC). Exosomes participate in constructing TME by passing biological information, but the regulatory effect of PDL1 in exosomes on anticancer activity of CD8+ T cells in HCC still needs to be further explored. In this study, high level of PDL1 was found in plasma exosomes of HCC patients, which turned out to be significantly associated with the increased number of tumor nodules, the upregulated level of serum AFP, the raised tendency of TNM stage, and the poor prognosis of HCC. The expression of CD8 may be inhibited in HCC that is characterized with high level of PDL1, and the protein level of exosomal PDL1 was determined by intracellular PDL1 abundance. High level of exosomal PDL1 inhibited the proliferation and activation of CD8+ T cells, but exhibited limited effect on the proliferation of hepatic cancer cells. Moreover, the growth of tumors formed by hepatic cancer cells Hepa1-6 in C57L mice was significantly promoted by the exosomal PDL1, which might be caused by the inhibitory effect of exosomal PDL1 on CD8+ T cells. Thus, exosomal PDL1 promotes the development and progression of HCC through inhibiting the anticancer activity of CD8+ T cells. This study provides sights for understanding the oncogenic role of PDL1 and a reasonable explanation for the low efficacy of anti-PD1/PDL1 immunotherapies in HCC.

Application of spatial omics in gastric cancer

Gastric cancer (GC), a globally prevalent and lethal malignancy, continues to be a key research focus. However, due to its considerable heterogeneity and complex pathogenesis, the treatment and diagnosis of gastric cancer still face significant challenges. With the rapid development of spatial omics technology, which provides insights into the spatial information within tumor tissues, it has emerged as a significant tool in gastric cancer research. This technology affords new insights into the pathology and molecular biology of gastric cancer for scientists. This review discusses recent advances in spatial omics technology for gastric cancer research, highlighting its applications in the tumor microenvironment (TME), tumor heterogeneity, tumor genesis and development mechanisms, and the identification of potential biomarkers and therapeutic targets. Moreover, this article highlights spatial omics' potential in precision medicine and summarizes existing challenges and future directions. It anticipates spatial omics' continuing impact on gastric cancer research, aiming to improve diagnostic and therapeutic approaches for patients. With this review, we aim to offer a comprehensive overview to scientists and clinicians in gastric cancer research, motivating further exploration and utilization of spatial omics technology. Our goal is to improve patient outcomes, including survival rates and quality of life.

Imaging-Based Efficacy Evaluation of Cancer Immunotherapy in Engineered Tumor Platforms and Tumor Organoids

Cancer immunotherapy is used to treat tumors by modulating the immune system. Although the anticancer efficacy of cancer immunotherapy has been evaluated prior to clinical trials, conventional in vivo animal and endpoint models inadequately replicate the intricate process of tumor elimination and reflect human-specific immune systems. Therefore, more sophisticated models that mimic the complex tumor-immune microenvironment must be employed to assess the effectiveness of immunotherapy. Additionally, using real-time imaging technology, a step-by-step evaluation can be applied, allowing for a more precise assessment of treatment efficacy. Here, an overview of the various imaging-based evaluation platforms recently developed for cancer immunotherapeutic applications is presented. Specifically, a fundamental technique is discussed for stably observing immune cell-based tumor cell killing using direct imaging, a microwell that reproduces a confined space for spatial observation, a droplet assay that facilitates cell-cell interactions, and a 3D microphysiological system that reconstructs the vascular environment. Furthermore, it is suggested that future evaluation platforms pursue more human-like immune systems.

Augmenting CAR T-cell Functions with LIGHT

Chimeric antigen receptor (CAR) T-cell therapy has resulted in remarkable clinical success in the treatment of B-cell malignancies. However, its clinical efficacy in solid tumors is limited, primarily by target antigen heterogeneity. To overcome antigen heterogeneity, we developed CAR T cells that overexpress LIGHT, a ligand of both lymphotoxin-β receptor on cancer cells and herpes virus entry mediator on immune cells. LIGHT-expressing CAR T cells displayed both antigen-directed cytotoxicity mediated by the CAR and antigen-independent killing mediated through the interaction of LIGHT with lymphotoxin-β receptor on cancer cells. Moreover, CAR T cells expressing LIGHT had immunostimulatory properties that improved the cells' proliferation and cytolytic profile. These data indicate that LIGHT-expressing CAR T cells may provide a way to eliminate antigen-negative tumor cells to prevent antigen-negative disease relapse.

Development and validation of a nomogram to predicting the efficacy of PD-1/PD-L1 inhibitors in patients with nasopharyngeal carcinoma

PURPOSE

With the treatment of nasopharyngeal carcinoma (NPC) by PD-1/PD-L1 inhibitors used widely in clinic, it becomes very necessary to anticipate whether patients would benefit from it. We aimed to develop a nomogram to evaluate the efficacy of anti-PD-1/PD-L1 in NPC patients.

METHODS

Totally 160 NPC patients were enrolled in the study. Patients were measured before the first PD-1/PD-L1 inhibitors treatment and after 8-12 weeks of immunotherapy by radiological examinations to estimate the effect. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to screen hematological markers and establish a predictive model. The nomogram was internally validated by bootstrap resampling and externally validated. Performance of the model was evaluated using concordance index, calibration curve, decision curve analysis and receiver operation characteristic curve.

RESULTS

Patients involved were randomly split into training cohort ang validation cohort. Based on Lasso logistic regression, systemic immune-inflammation index (SII) and ALT to AST ratio (LSR) were selected to establish a predictive model. The C-index of training cohort and validating cohort was 0.745 and 0.760. The calibration curves and decision curves showed the precise predictive ability of this nomogram. The benefit of the model showed in decision curve was better than TNM stage. The area under the curve (AUC) value of training cohort and validation cohort was 0.745 and 0.878, respectively.

CONCLUSION

The predictive model helped evaluating efficacy with high accuracy in NPC patients treated with PD-1/PD-L1 inhibitors.

Cancer stem cells: advances in the glucose, lipid and amino acid metabolism

Cancer stem cells (CSCs) are a class of cells with self-renewal and multi-directional differentiation potential, which are present in most tumors, particularly in aggressive tumors, and perform a pivotal role in recurrence and metastasis and are expected to be one of the important targets for tumor therapy. Studies of tumor metabolism in recent years have found that the metabolic characteristics of CSCs are distinct from those of differentiated tumor cells, which are unique to CSCs and contribute to the maintenance of the stemness characteristics of CSCs. Moreover, these altered metabolic profiles can drive the transformation between CSCs and non-CSCs, implying that these metabolic alterations are important markers for CSCs to play their biological roles. The identification of metabolic changes in CSCs and their metabolic plasticity mechanisms may provide some new opportunities for tumor therapy. In this paper, we review the metabolism-related mechanisms of CSCs in order to provide a theoretical basis for their potential application in tumor therapy.

Spatial omics technologies for understanding molecular status associated with cancer progression

Cancer cells are generally exposed to numerous extrinsic stimulations in the tumor microenvironment. In this environment, cancer cells change their expression profiles to fight against circumstantial stresses, allowing their progression in the challenging tissue space. Technological advancements of spatial omics have had substantial influence on cancer genomics. This technical progress, especially that occurring in the spatial transcriptome, has been drastic and rapid. Here, we describe the latest spatial analytical technologies that have allowed omics feature characterization to retain their spatial and histopathological information in cancer tissues. Several spatial omics platforms have been launched, and the latest platforms finally attained single-cell level or even higher subcellular level resolution. We discuss several key papers elucidating the initial utility of the spatial analysis. In fact, spatial transcriptome analyses reveal comprehensive omics characteristics not only in cancer cells but also their surrounding cells, such as tumor infiltrating immune cells and cancer-associated fibroblasts. We also introduce several spatial omics platforms. We describe our own attempts to investigate molecular events associated with cancer progression. Furthermore, we discuss the next challenges in analyzing the multiomics status of cells, including their morphology and location. These novel technologies, in conjunction with spatial transcriptome analysis and, more importantly, with histopathology, will elucidate even novel key aspects of the intratumor heterogeneity of cancers. Such enhanced knowledge is expected to open a new path for overcoming therapeutic resistance and eventually to precisely stratify patients.

The sympathetic nervous system shapes the tumor microenvironment to impair chemotherapy response

The tumor microenvironment influences cancer progression and response to treatments, which ultimately impacts the survival of patients with cancer. The sympathetic nervous system (SNS) is a core component of solid tumors that arise in the body. In addition to influencing cancer progression, a role for the SNS in the effectiveness of cancer treatments is beginning to emerge. This review explores evidence that the SNS impairs chemotherapy efficacy. We review findings of studies that evaluated the impact of neural ablation on chemotherapy outcomes and discuss plausible mechanisms for the impact of neural signaling on chemotherapy efficacy. We then discuss implications for clinical practice, including opportunities to block neural signaling to improve response to chemotherapy.

Multi-omics features of immunogenic cell death in gastric cancer identified by combining single-cell sequencing analysis and machine learning

Gastric cancer (GC) is a prevalent malignancy with high mortality rates. Immunogenic cell death (ICD) is a unique form of programmed cell death that is closely linked to antitumor immunity and plays a critical role in modulating the tumor microenvironment (TME). Nevertheless, elucidating the precise effect of ICD on GC remains a challenging endeavour. ICD-related genes were identified in single-cell sequencing datasets and bulk transcriptome sequencing datasets via the AddModuleScore function, weighted gene co-expression network (WGCNA), and differential expression analysis. A robust signature associated with ICD was constructed using a machine learning computational framework incorporating 101 algorithms. Furthermore, multiomics analysis, including single-cell sequencing analysis, bulk transcriptomic analysis, and proteomics analysis, was conducted to verify the correlation of these hub genes with the immune microenvironment features of GC and with GC invasion and metastasis. We screened 59 genes associated with ICD and developed a robust ICD-related gene signature (ICDRS) via a machine learning computational framework that integrates 101 different algorithms. Furthermore, we identified five key hub genes (SMAP2, TNFAIP8, LBH, TXNIP, and PIK3IP1) from the ICDRS. Through single-cell analysis of GC tumor s, we confirmed the strong correlations of the hub genes with immune microenvironment features. Among these five genes, LBH exhibited the most significant associations with a poor prognosis and with the invasion and metastasis of GC. Finally, our findings were validated through immunohistochemical staining of a large clinical sample set, and the results further supported that LBH promotes GC cell invasion by activating the epithelial-mesenchymal transition (EMT) pathway.

Assessing Drug Uptake and Response Differences in 2D and 3D Cellular Environments Using Stimulated Raman Scattering Microscopy

The architecture of cell culture, two-dimensional (2D) versus three-dimensional (3D), significantly impacts various cellular factors, including cell-cell interactions, nutrient and oxygen gradients, metabolic activity, and gene expression profiles. This can result in different cellular responses during cancer drug treatment, with 3D-cultured cells often exhibiting higher resistance to chemotherapeutic drugs. While various genetic and proteomic analyses have been employed to investigate the underlying mechanisms of this increased resistance, complementary techniques that provide experimental evidence of spatial molecular profiling data are limited. Stimulated Raman scattering (SRS) microscopy has demonstrated its capability to measure both intracellular drug uptake and growth inhibition. In this work, we applied three-band (C-D, C-H, and fingerprint regions) SRS imaging to 2D and 3D cell cultures and performed a comparative analysis of drug uptake and response with the goal of understanding whether the difference in drug uptake explains the drug resistance in 3D culture compared to 2D. Our investigations revealed that despite similar intracellular drug levels in 2D and 3D A549 cells during lapatinib treatment, the growth of 3D spheroids was less impacted, supporting an enhanced drug tolerance in the 3D microenvironment. We further elucidated drug penetration patterns and the resulting heterogeneous cellular responses across different spheroid layers. Additionally, we investigated the role of the extracellular matrix in modulating drug delivery and cell response and discovered that limited drug penetration in 3D could also contribute to lower drug response. Our study provides valuable insights into the intricate mechanisms of increased drug resistance in 3D tumor models during cancer drug treatments.

Characterization of tumor heterogeneity through segmentation-free representation learning

The interaction between tumors and their microenvironment is complex and heterogeneous. Recent developments in high-dimensional multiplexed imaging have revealed the spatial organization of tumor tissues at the molecular level. However, the discovery and thorough characterization of the tumor microenvironment (TME) remains challenging due to the scale and complexity of the images. Here, we propose a self-supervised representation learning framework, CANVAS, that enables discovery of novel types of TMEs. CANVAS is a vision transformer that directly takes high-dimensional multiplexed images and is trained using self-supervised masked image modeling. In contrast to traditional spatial analysis approaches which rely on cell segmentations, CANVAS is segmentation-free, utilizes pixel-level information, and retains local morphology and biomarker distribution information. This approach allows the model to distinguish subtle morphological differences, leading to precise separation and characterization of distinct TME signatures. We applied CANVAS to a lung tumor dataset and identified and validated a monocytic signature that is associated with poor prognosis.

Engineered liver-derived decellularized extracellular matrix-based three-dimensional tumor constructs for enhanced drug screening efficiency

The decellularized extracellular matrix (dECM) has emerged as an effective medium for replicating the in vivo-like conditions of the tumor microenvironment (TME), thus enhancing the screening accuracy of chemotherapeutic agents. However, recent dECM-based tumor models have exhibited challenges such as uncontrollable morphology and diminished cell viability, hindering the precise evaluation of chemotherapeutic efficacy. Herein, we utilized a tailor-made microfluidic approach to encapsulate dECM from porcine liver in highly poly(lactic-co-glycolic acid) (PLGA) porous microspheres (dECM-PLGA PMs) to engineer a three-dimensional (3D) tumor model. These dECM-PLGA PMs-based microtumors exhibited significant promotion of hepatoma carcinoma cells (HepG2) proliferation compared to PLGA PMs alone, since the infusion of extracellular matrix (ECM) microfibers and biomolecular constituents within the PMs. Proteomic analysis of the dECM further revealed the potential effects of these bioactive fragments embedded in the PMs. Notably, dECM-PLGA PMs-based microtissues effectively replicated the drug resistance traits of tumors, showing pronounced disparities in half-maximal inhibitory concentration (IC50) values, which could correspond with certain aspects of the TME. Collectively, these dECM-PLGA PMs substantially surmounted the prevalent challenges of unregulated microstructure and suboptimal cell viability in conventional 3D tumor models. They also offer a sustainable and scalable platform for drug testing, holding promise for future pharmaceutical evaluations.

Single-cell and spatial transcriptome analyses reveal tertiary lymphoid structures linked to tumour progression and immunotherapy response in nasopharyngeal carcinoma

Tertiary lymphoid structures are immune cell aggregates linked with cancer outcomes, but their interactions with tumour cell aggregates are unclear. Using nasopharyngeal carcinoma as a model, here we analyse single-cell transcriptomes of 343,829 cells from 77 biopsy and blood samples and spatially-resolved transcriptomes of 31,316 spots from 15 tumours to decipher their components and interactions with tumour cell aggregates. We identify essential cell populations in tertiary lymphoid structure, including CXCL13+ cancer-associated fibroblasts, stem-like CXCL13+CD8+ T cells, and B and T follicular helper cells. Our study shows that germinal centre reaction matures plasma cells. These plasma cells intersperse with tumour cell aggregates, promoting apoptosis of EBV-related malignant cells and enhancing immunotherapy response. CXCL13+ cancer-associated fibroblasts promote B cell adhesion and antibody production, activating CXCL13+CD8+ T cells that become exhausted in tumour cell aggregates. Tertiary lymphoid structure-related cell signatures correlate with prognosis and PD-1 blockade response, offering insights for therapeutic strategies in cancers.

Dynamic changes in immune cells in humanized liver metastasis and subcutaneous xenograft mouse models

Preclinical drug efficacy and tumor microenvironment (TME) investigations often utilize humanized xenograft mouse models, yet these models typically fall short in replicating the intricate TME. We developed a humanized liver metastasis (LM) model by transplanting human peripheral blood mononuclear cells (PBMCs) and assessed it against the conventional subcutaneous (SC) xenograft model, focusing on immune cell dynamics post-transplantation and immunotherapy response. NOD-scid IL2Rgammanull(NSG) were inoculated with PBMCs to create humanized models. We induced SC and LM models using HCT116 cells, to investigate and compare the distributions and transformations of immune cell subsets, respectively. Both models were subjected to anti-PD-L1 therapy, followed by an analysis the TME analysis. The LM model demonstrated enhanced central tumor infiltration by tumor-infiltrating lymphocytes (TILs) compared to the peripheral pattern of SC model. TIL subpopulations in the LM model showed a progressive increase, contrasting with an initial rise and subsequent decline in the SC model. Post-anti-PD-L1 therapy, the LM model exhibited a significant rise in central and effector memory T cells, a response absents in the SC model. Our study highlights differential TME responses between SC and LM models and introduces a robust humanized LM model that swiftly indicates the potential efficacy of immunotherapies. These insights could streamline the preclinical evaluation of TME-targeting immunotherapeutic agents.

Investigation of tumour environments through advancements in microtechnology and nanotechnology

Cancer has a significant negative social and economic impact on both developed and developing countries. As a result, understanding the onset and progression of cancer is critical for developing therapies that can improve the well-being and health of individuals with cancer. With time, study has revealed, the tumor microenvironment has great influence on this process. Micro and nanoscale engineering techniques can be used to study the tumor microenvironment. Nanoscale and Microscale engineering use Novel technologies and designs with small dimensions to recreate the TME. Knowing how cancer cells interact with one another can help researchers develop therapeutic approaches that anticipate and counteract cancer cells' techniques for evading detection and fighting anti-cancer treatments, such as microfabrication techniques, microfluidic devices, nanosensors, and nanodevices used to study or recreate the tumor microenvironment. Nevertheless, a complicated action just like the growth and in cancer advancement, and their intensive association along the environment around it that has to be studied in more detail.

Mucin 1 expression is regulated by hsa_circ_0055054/microRNA‑122‑5p and promotes hepatocellular carcinoma development

The abnormal expression of mucin 1 (MUC1) is a major cause of poor prognosis in patients with hepatocellular carcinoma (HCC). Competitive endogenous RNA demonstrates a novel regulatory mechanism that can affect the biological behavior of tumors. In the present study, the regulatory functions of hsa_circ_0055054 as well as those of microRNA (miR/miRNA) 122-5p on MUC1 expression and its role in HCC cell proliferation, migration and invasion, were evaluated. MUC1 expression was assessed using western blotting and reverse transcription-quantitative PCR. The phenotypic functions of the HCC cell lines were evaluated following MUC1 knockdown using Cell Counting Kit-8, wound healing and Transwell assays. Bioinformatics tools were used to identify specific miRNAs and circular (circ)RNAs that interact with and can regulate MUC1. The stability of circRNAs was assessed using a Ribonuclease R assay. The binding of circRNA/miRNA/MUC1 was assessed using dual-luciferase reporter assays and cellular function tests. Finally, in vivo experiments were performed using animal models. The results demonstrated that in MHCC97L cells, MUC1 and hsa_circ_0055054 were expressed at high levels while miR-122-5p was downregulated. The proliferation, migration and invasion of MHCC97L cells were suppressed by low MUC1 expression. hsa_circ_0055054 knockdown or miR-122-5p overexpression both led to a decrease in MUC1 expression. In MHCC97L cells with a low MUC1 expression caused by hsa_circ_0055054 knockdown, miR-122-5p inhibition resulted in the increased proliferation, migration and invasion of MHCC97L cells. In combination, the results of the present study indicate that hsa_circ_0055054 knockdown in MHCC97L cells leads to an increased expression of miR-122-5p and decreased expression of MUC1, which results in the inhibition of MHCC97L cell proliferation, migration and invasion.

Path to bacteriotherapy: From bacterial engineering to therapeutic perspectives

The major reason for the failure of conventional therapies is the heterogeneity and complexity of tumor microenvironments (TMEs). Many malignant tumors reprogram their surface antigens to evade the immune surveillance, leading to reduced antigen-presenting cells and hindered T-cell activation. Bacteria-mediated cancer immunotherapy has been extensively investigated in recent years. Scientists have ingeniously modified bacteria using synthetic biology and nanotechnology to enhance their biosafety with high tumor specificity, resulting in robust anticancer immune responses. To enhance the antitumor efficacy, therapeutic proteins, cytokines, nanoparticles, and chemotherapeutic drugs have been efficiently delivered using engineered bacteria. This review provides a comprehensive understanding of oncolytic bacterial therapies, covering bacterial design and the intricate interactions within TMEs. Additionally, it offers an in-depth comparison of the current techniques used for bacterial modification, both internally and externally, to maximize their therapeutic effectiveness. Finally, we outlined the challenges and opportunities ahead in the clinical application of oncolytic bacterial therapies.

Artificial intelligence: illuminating the depths of the tumor microenvironment

Artificial intelligence (AI) can acquire characteristics that are not yet known to humans through extensive learning, enabling to handle large amounts of pathology image data. Divided into machine learning and deep learning, AI has the advantage of handling large amounts of data and processing image analysis, consequently it also has a great potential in accurately assessing tumour microenvironment (TME) models. With the complex composition of the TME, in-depth study of TME contributes to new ideas for treatment, assessment of patient response to postoperative therapy and prognostic prediction. This leads to a review of the development of AI's application in TME assessment in this study, provides an overview of AI techniques applied to medicine, delves into the application of AI in analysing the quantitative and spatial location characteristics of various cells (tumour cells, immune and non-immune cells) in the TME, reveals the predictive prognostic value of TME and provides new ideas for tumour therapy, highlights the great potential for clinical applications. In addition, a discussion of its limitations and encouraging future directions for its practical clinical application is presented.

Establishment of advanced tumor organoids with emerging innovative technologies

Tumor organoids have emerged as a crucial preclinical model for multiple cancer research. Their high establishment rates, stability, and ability to replicate key biological features of original tumor cells in vivo render them invaluable for exploring tumor molecular mechanisms, discovering potential anti-tumor drugs, and predicting clinical drug efficacy. Here, we review the establishment of tumor organoid models and provide an extensive overview of organoid culturing strategies. We also emphasize the significance of integrating cellular components of the tumor microenvironment and physicochemical factors in the organoid culturing system, highlighting the importance of artificial intelligence technology in advancing organoid construction. Moreover, we summarize recent advancements in utilizing organoid systems for novel anti-cancer drug screening and discuss promising trends for enhancing advanced organoids in next-generation disease modeling.

Integration of Bioinformatics and Machine Learning to Identify CD8+ T Cell-Related Prognostic Signature to Predict Clinical Outcomes and Treatment Response in Breast Cancer Patients

The incidence of breast cancer (BC) continues to rise steadily, posing a significant burden on the public health systems of various countries worldwide. As a member of the tumor microenvironment (TME), CD8+ T cells inhibit cancer progression through their protective role. This study aims to investigate the role of CD8+ T cell-related genes (CTRGs) in breast cancer patients.

METHODS

We assessed the abundance of CD8+ T cells in the TCGA and METABRIC datasets and obtained CTRGs through WGCNA. Subsequently, a prognostic signature (CTR score) was constructed from CTRGs screened by seven machine learning algorithms, and the relationship between the CTR score and TME, immunotherapy, and drug sensitivity was analyzed. Additionally, CTRGs' expression in different cells within TME was identified through single-cell analysis and spatial transcriptomics. Finally, the expression of CTRGs in clinical tissues was verified via RT-PCR.

RESULTS

The CD8+ T cell-related prognostic signature consists of two CTRGs. In the TCGA and METABRIC datasets, the CTR score appeared to be negatively linked to the abundance of CD8+ T cells, and BC patients with higher risk score show a worse prognosis. The low CTR score group exhibits higher immune infiltration levels, closely associated with inhibiting the tumor microenvironment. Compared with the high CTR score group, the low CTR score group shows better responses to chemotherapy and immune checkpoint therapy. Single-cell analysis and spatial transcriptomics reveal the heterogeneity of two CTRGs in different cells. Compared with the adjacent tissues, CD163L1 and KLRB1 mRNA are downregulated in tumor tissues.

CONCLUSIONS

This study establishes a robust CD8+ T cell-related prognostic signature, providing new insights for predicting the clinical outcomes and treatment responses of breast cancer patients.

Cracking the Codes behind Cancer Cells' Immune Evasion

Immune evasion is a key phenomenon in understanding tumor recurrence, metastasis, and other critical steps in tumor progression. The tumor microenvironment (TME) is in constant flux due to the tumor's ability to release signals that affect it, while immune cells within it can impact cancer cell behavior. Cancer cells undergo several changes, which can change the enrichment of different immune cells and modulate the activity of existing immune cells in the tumor microenvironment. Cancer cells can evade immune surveillance by downregulating antigen presentation or expressing immune checkpoint molecules. High levels of tumor-infiltrating lymphocytes (TILs) correlate with better outcomes, and robust immune responses can control tumor growth. On the contrary, increased enrichment of Tregs, myeloid-derived suppressor cells, and M2-like anti-inflammatory macrophages can hinder effective immune surveillance and predict poor prognosis. Overall, understanding these immune evasion mechanisms guides therapeutic strategies. Researchers aim to modulate the TME to enhance immune surveillance and improve patient outcomes. In this review article, we strive to summarize the composition of the tumor immune microenvironment, factors affecting the tumor immune microenvironment (TIME), and different therapeutic modalities targeting the immune cells. This review is a first-hand reference to understand the basics of immune surveillance and immune evasion.

Injectable nano-in situ-thermosensitive-hydrogels based on halofuginone and silver for postoperative treatment against triple-negative breast cancer

Postoperative distant metastasis and high recurrence rate causes a dilemma in treating triple-negative breast cancer (TNBC) owing to its unforeseeable invasion into various organs or tissues. The wealth of nutrition provided by vascular may facilitate the proliferation and angiogenesis of cancer cells, which further enhance the rates of postoperative metastasis and recurrence. Chemotherapy, as a systemic postoperative adjuvant therapy, is generally applied to diminish recurrence and metastasis of TNBC. Herein, an halofuginone-silver nano thermosensitive hydrogel (HTPM&AgNPs-gel) was prepared via a physical swelling method. The in vitro anticancer efficacy of HTPM&AgNPs-gel was analyzed by investigating cell proliferation, migration, invasion, and angiogenesis capacity. Furthermore, the in vivo anti-cancer activity of HTPM&AgNPs-gel was further appraised through the tumor suppression, anti-metastatic, anti-angiogenic, and anti-inflammatory ability. The optimized HTPM&AgNPs-gel, a thermosensitive hydrogel, showed excellent properties, including syringeability, swelling behavior, and a sustained release effect without hemolysis. In addition, HTPM&AgNPs-gel was confirmed to effectively inhibit the proliferation, migration, invasion, and angiogenesis of MDA-MB-231 cells. An evaluation of the in vivo anti-tumor efficacy demonstrated that HTPM&AgNPs-gel showed a stronger tumor inhibition rate (68.17%) than did HTPM-gel or AgNPs-gel used alone and exhibited outstanding biocompatibility. Notably, HTPM&AgNPs-gel also inhibited lung metastasis induced by residual tumor tissue after surgery and further blocked angiogenesis-related inflammatory responses. Taken together, the suppression of inflammation by interdicting the blood vessels adjoining the tumor and inhibiting angiogenesis is a potential strategy to attenuate the recurrence and metastasis of TNBC. HTPM&AgNPs-gel is a promising anticancer agent for TNBC as a local postoperative treatment.

Quantitatively Evaluating Interactions between Patient-Derived Organoids and Autologous Immune Cells by Microfluidic Chip

The coculture of patient-derived tumor organoids (PDOs) and autologous immune cells has been considered as a useful ex vivo surrogate of in vivo tumor-immune environment. However, the immune interactions between PDOs and autologous immune cells, including immune-mediated killing behaviors and immune-related cytokine variations, have yet to be quantitatively evaluated. This study presents a microfluidic chip for quantifying interactions between PDOs and autologous immune cells (IOI-Chip). A baffle-well structure is designed to ensure efficient trapping, long-term coculturing, and in situ fluorescent observation of a limited amount of precious PDOS and autologous immune cells, while a microbeads-based immunofluorescence assay is designed to simultaneously quantify multiple kinds of immune-related cytokines in situ. The PDO apoptosis and 2 main immune-related cytokines, TNF-α and IFN-γ, are simultaneously quantified using samples from a lung cancer patient. This study provides, for the first time, a capability to quantify interactions between PDOs and autologous immune cells at 2 levels, the immune-mediated killing behavior, and multiple immune-related cytokines, laying the technical foundation of ex vivo assessment of patient immune response.

Oxidative stress-mediated epigenetic remodeling, metastatic progression and cell signaling in cancer

Cancer is a serious public health issue and cases are rising at a high rate around the world. Altered production of reactive oxygen species (ROS) causes oxidative stress (OS) which plays a vital role in cancer development by disrupting signaling pathways and genomic integrity in the cellular microenvironment. In this study, we reviewed the regulation of noncoding RNAs, histone modifications, and DNA methylation which OS is involved in. These mechanisms promote cancer growth, metastasis, and resistance to chemotherapeutic agents. There is significant potential to improve patient outcomes through the development of customized medications and interventions that precisely address the role of OS in the onset and progression of cancer. Redox-modulating drugs, antioxidant-based therapies, and measures to restore regular cellular activity and OS-modulated signaling pathways are some examples of these strategies. One other hypothesis rationalizes the cancer-suppressing effect of OS, which acts as a two-edged condition that warns against the use of antioxidants for cancer treatment and management. The present study was executed to review the impact of OS on epigenetic machinery, the evolution of metastatic cancer, and how OS mediates cellular signaling. Along with, insights into the potential of targeting OS-mediated mechanisms for cancer therapy.

Tumor-derived GLI1 promotes remodeling of the immune tumor microenvironment in melanoma

BACKGROUND

Melanoma progression is based on a close interaction between cancer cells and immune cells in the tumor microenvironment (TME). Thus, a better understanding of the mechanisms controlling TME dynamics and composition will help improve the management of this dismal disease. Work from our and other groups has reported the requirement of an active Hedgehog-GLI (HH-GLI) signaling for melanoma growth and stemness. However, the role of the downstream GLI1 transcription factor in melanoma TME remains largely unexplored.

METHODS

The immune-modulatory activity of GLI1 was evaluated in a syngeneic B16F10 melanoma mouse model assessing immune populations by flow cytometry. Murine polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) were differentiated from bone marrow cells and their immunosuppressive ability was assessed by inhibition of T cells. Conditioned media (CM) from GLI1-overexpressing mouse melanoma cells was used to culture PMN-MDSCs, and the effects of CM were evaluated by Transwell invasion assay and T cell inhibition. Cytokine array analysis, qPCR and chromatin immunoprecipitation were performed to explore the regulation of CX3CL1 expression by GLI1. Human monocyte-derived dendritic cells (moDCs) were cultured in CM from GLI1-silenced patient-derived melanoma cells to assess their activation and recruitment. Blocking antibodies anti-CX3CL1, anti-CCL7 and anti-CXCL8 were used for in vitro functional assays.

RESULTS

Melanoma cell-intrinsic activation of GLI1 promotes changes in the infiltration of immune cells, leading to accumulation of immunosuppressive PMN-MDSCs and regulatory T cells, and to decreased infiltration of dendric cells (DCs), CD8 + and CD4 + T cells in the TME. In addition, we show that ectopic expression of GLI1 in melanoma cells enables PMN-MDSC expansion and recruitment, and increases their ability to inhibit T cells. The chemokine CX3CL1, a direct transcriptional target of GLI1, contributes to PMN-MDSC expansion and recruitment. Finally, silencing of GLI1 in patient-derived melanoma cells promotes the activation of human monocyte-derived dendritic cells (moDCs), increasing cytoskeleton remodeling and invasion ability. This phenotype is partially prevented by blocking the chemokine CCL7, but not CXCL8.

CONCLUSION

Our findings highlight the relevance of tumor-derived GLI1 in promoting an immune-suppressive TME, which allows melanoma cells to evade the immune system, and pave the way for the design of new combination treatments targeting GLI1.

Recent advances in biomimetic cell membrane-camouflaged nanoparticles for cancer therapy

The emerging strategy of biomimetic nanoparticles (NPs) via cellular membrane camouflage holds great promise in cancer therapy. This scholarly review explores the utilization of cellular membranes derived from diverse cellular entities; blood cells, immune cells, cancer cells, stem cells, and bacterial cells as examples of NP coatings. The camouflaging strategy endows NPs with nuanced tumor-targeting abilities such as self-recognition, homotypic targeting, and long-lasting circulation, thus also improving tumor therapy efficacy overall. The comprehensive examination encompasses a variety of cell membrane camouflaged NPs (CMCNPs), elucidating their underlying targeted therapy mechanisms and delineating diverse strategies for anti-cancer applications. Furthermore, the review systematically presents the synthesis of source materials and methodologies employed in order to construct and characterize these CMCNPs, with a specific emphasis on their use in cancer treatment.

Tumor-associated macrophages: The key player in hepatoblastoma microenvironment and the promising therapeutic target

The tumor microenvironment of hepatoblastoma (HB), the most common pediatric liver tumor, predominantly exhibits a myeloid immune landscape. in which tumor-associated macrophages (TAMs) are considered the core component. The crosstalk between TAMs and HB cells markedly influences tumor behavior. TAM-derived factors are involved in tumor proliferation and vascular invasion. On the other hand, HB cell secretome attracts, stimulates, and reprograms TAMs to be immunosuppressive in favor of tumor invasion, rather than their innate role in combating tumor growth, such crosstalk sometimes forms bidirectional feedback loops, making the tumor more virulent and resistant to routine therapeutics. Consequently, TAMs are the common denominator of most suggested HB immunotherapeutic strategies. Macrophage immune checkpoint inhibitors, macrophage-mediated antibody-dependent cellular phagocytosis, and the novel chimeric antigen receptor macrophage therapy (CAR Mφ) are currently under trial. In this review, we will summarize the significance of TAMs and their potential role as a therapeutic target in HB.

Insight into the structure, function and the tumor suppression effect of gasdermin E

Gasdermin E (GSDME), which is also known as DFNA5, was first identified as a deafness-related gene that is expressed in cochlear hair cells, and mutation of this gene causes autosomal dominant neurogenic hearing loss. Later studies revealed that GSDME is mostly expressed in the kidney, placenta, muscle and brain cells, but it is expressed at low levels in tumor cells. The GSDME gene encodes the GSDME protein, which is a member of the gasdermin (GSDM) family and has been shown to participate in the induction of apoptosis and pyroptosis. The current literature suggests that Caspase-3 and Granzyme B (Gzm B) can cleave GSDME to generate the active N-terminal fragment (GSDME-NT), which integrates with the cell membrane and forms pores in this membrane to induce pyroptosis. Furthermore, GSDME also forms pores in mitochondrial membranes to release apoptosis factors, such as cytochrome c (Cyt c) and high-temperature requirement protein A2 (HtrA2/Omi), and subsequently activates the intrinsic apoptosis pathway. In recent years, GSDME has been shown to exert tumor-suppressive effects, suggesting that it has potential therapeutic effects on tumors. In this review, we introduce the structure and function of GSDME and the mechanism by which it induces cell death, and we discuss its tumor suppressive effect.

Comprehensive analysis of single cell and bulk RNA sequencing reveals the heterogeneity of melanoma tumor microenvironment and predicts the response of immunotherapy

BACKGROUND

Tumor microenvironment (TME) heterogeneity is an important factor affecting the treatment response of immune checkpoint inhibitors (ICI). However, the TME heterogeneity of melanoma is still widely characterized.

METHODS

We downloaded the single-cell sequencing data sets of two melanoma patients from the GEO database, and used the "Scissor" algorithm and the "BayesPrism" algorithm to comprehensively analyze the characteristics of microenvironment cells based on single-cell and bulk RNA-seq data. The prediction model of immunotherapy response was constructed by machine learning and verified in three cohorts of GEO database.

RESULTS

We identified seven cell types. In the Scissor+ subtype cell population, the top three were T cells, B cells and melanoma cells. In the Scissor- subtype, there are more macrophages. By quantifying the characteristics of TME, significant differences in B cells between responders and non-responders were observed. The higher the proportion of B cells, the better the prognosis. At the same time, macrophages in the non-responsive group increased significantly. Finally, nine gene features for predicting ICI response were constructed, and their predictive performance was superior in three external validation groups.

CONCLUSION

Our study revealed the heterogeneity of melanoma TME and found a new predictive biomarker, which provided theoretical support and new insights for precise immunotherapy of melanoma patients.

Integrated 68 Ga-FAPI-04 PET/MR in Pancreatic Cancer : Prediction of Tumor Response and Tumor Resectability After Neoadjuvant Therapy

PURPOSE

This study aimed to investigate the value of 68 Ga-fibroblast activation protein inhibitor (FAPI) PET/MR semiquantitative parameters in the prediction of tumor response and resectability after neoadjuvant therapy in patients with pancreatic cancer.

PATIENTS AND METHODS

This study was performed retrospectively in patients with borderline resectable or locally advanced pancreatic cancer who underwent 68 Ga-FAPI PET/MRI from June 2020 to June 2022. The SUV max , SUV mean , SUV peak , uptake tumor volume (UTV), and total lesion FAP expression (TLF) of the primary tumor were recorded. The target-to-background ratios (TBRs) of the primary tumor to normal tissue muscle (TBR muscle ) and blood (TBR blood ) were also calculated. In addition, the minimum apparent diffusion coefficient value of the tumor was measured. After 3-4 cycles of gemcitabine + nab-paclitaxel chemotherapy, patients were divided into responders and nonresponders groups according to RECIST criteria (v.1.1). They were also divided into resectable and unresectable groups according to the surgical outcome. The variables were compared separately between groups.

RESULTS

A total of 18 patients who met the criteria were included in this study. The UTV and TLF were significantly higher in nonresponders than in responders ( P < 0.05). The SUV max , SUV mean , and TBR muscle were significantly higher in unresectable patients than in resectable ones ( P < 0.05). Receiver operating characteristic curve analysis identified UTV (area under the curve [AUC] = 0.840, P = 0.015) and TLF (AUC = 0.877, P = 0.007) as significant predictors for the response to gemcitabine + nab-paclitaxel chemotherapy, with cutoff values of 25.05 and 167.38, respectively. In addition, SUV max (AUC = 0.838, P = 0.016), SUV mean (AUC = 0.812, P = 0.026), and TBR muscle (AUC = 0.787, P = 0.041) were significant predictors of the resectability post-NCT, with cutoff values of 14.0, 6.0, and 13.9, respectively. According to logistic regression analysis, TLF was found to be significantly associated with tumor response ( P = 0.032) and was an independent predictor of tumor response ( P = 0.032). In addition, apparent diffusion coefficient value was an independent predictor of tumor resectability ( P = 0.043).

CONCLUSIONS

This pilot study demonstrates the value of 68 Ga-FAPI PET/MR for the prediction of tumor response and resectability after neoadjuvant therapy. It may aid in individualized patient management by guiding the treatment regimens.

Pan-cancer analysis of SERPINE1 with a concentration on immune therapeutic and prognostic in gastric cancer

The serine protease inhibitor clade E member 1 (SERPINE1) is a key modulator of the plasminogen/plasminase system and has been demonstrated to promote tumor progression and metastasis in various tumours. However, although much literature has explored the cancer-promoting mechanism of SERPINE1, the pan-cancer analyses of its predictive value and immune response remain unexplored. The differential expression, and survival analysis of SERPINE1 expression in multiple cancers were analysed using The Cancer Genome Atlas and Genotype-Tissue Expression database. Kaplan-Meier (K-M) plotter and survival data analysis were used to analyze the prognostic value of SERPINE1 expression, including overall survival (OS), disease-specific survival, disease-free interval and progression-free interval and investigated the relationship of SERPINE1 expression with microsatellite instability. We further analysed the correlation between the expression of SERPINE1 and immune infiltration. The Kyoto Encyclopaedia of Genes and Genomes pathway was used for enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) database was used to perform pathway analysis. Finally, in vitro experiments demonstrated that knockdown or overexpression of SERPINE1 could alter the proliferation and migration of gastric cancer (GC) cells. The results indicated that SERPINE1 expression levels different significantly between cancer and normal tissues, meanwhile, it was highly expressed in various cancers. By analysing online data, it has been observed that the gene SERPINE1 exhibits heightened expression levels across a variety of human cancers, significantly impacting patient survival rates. Notably, the presence of SERPINE1 was strongly associated with decrease OS and disease-free survival in individuals diagnosed with GC. Furthermore, an observed link indicates that higher levels of SERPINE expression are associated with increased infiltration of immune cells in GC. Finally, in vitro experiments showed that knockdown or overexpression of SERPINE1 inhibited the growth, and migration, of GC cells. SERPINE1expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in GC. This study shows that SERPINE1 is an oncogene that participates in regulating the immune infiltration and affecting the prognosis of patients in multiple cancers, especially in GC. These findings underscore the importance of further investigating the role of SERPINE1 in cancer progression and offer a promising direction for the development of new therapeutic strategies.

Lactate-induced activation of tumor-associated fibroblasts and IL-8-mediated macrophage recruitment promote lung cancer progression

Alterations in the tumor microenvironment are closely associated with the metabolic phenotype of tumor cells. Cancer-associated fibroblasts (CAFs) play a pivotal role in tumor growth and metastasis. Existing studies have suggested that lactate produced by tumor cells can activate CAFs, yet the precise underlying mechanisms remain largely unexplored. In this study, we initially identified that lactate derived from lung cancer cells can promote nuclear translocation of NUSAP1, subsequently leading to the recruitment of the transcriptional complex JUNB-FRA1-FRA2 near the DESMIN promoter and facilitating DESMIN transcriptional activation, thereby promoting CAFs' activation. Moreover, DESMIN-positive CAFs, in turn, secrete IL-8, which recruits TAMs or promotes M2 polarization of macrophages, further contributing to the alterations in the tumor microenvironment and facilitating lung cancer progression. Furthermore, we observed that the use of IL-8 receptor antagonists, SB225002, or Navarixin, significantly reduced TAM infiltration and enhanced the therapeutic efficacy of anti-PD-1 or anti-PD-L1 treatment. This finding indicates that inhibiting IL-8R activity can attenuate the impact of CAFs on the tumor microenvironment, thus restraining the progression of lung cancer.

Comprehensive integrated single-cell RNA sequencing analysis of brain metastasis and glioma microenvironment: Contrasting heterogeneity landscapes

Understanding the specific type of brain malignancy, source of brain metastasis, and underlying transformation mechanisms can help provide better treatment and less harm to patients. The tumor microenvironment plays a fundamental role in cancer progression and affects both primary and metastatic cancers. The use of single-cell RNA sequencing to gain insights into the heterogeneity profiles in the microenvironment of brain malignancies is useful for guiding treatment decisions. To comprehensively investigate the heterogeneity in gliomas and brain metastasis originating from different sources (lung and breast), we integrated data from three groups of single-cell RNA-sequencing datasets obtained from GEO. We gathered and processed single-cell RNA sequencing data from 90,168 cells obtained from 17 patients. We then employed the R package Seurat for dataset integration. Next, we clustered the data within the UMAP space and acquired differentially expressed genes for cell categorization. Our results underscore the significance of macrophages as abundant and pivotal constituents of gliomas. In contrast, lung-to-brain metastases exhibit elevated numbers of AT2, cytotoxic CD4+ T, and exhausted CD8+ T cells. Conversely, breast-to-brain metastases are characterized by an abundance of epithelial and myCAF cells. Our study not only illuminates the variation in the TME between brain metastasis with different origins but also opens the door to utilizing established markers for these cell types to differentiate primary brain metastatic cancers.

A m6A regulators-related classifier for prognosis and tumor microenvironment characterization in hepatocellular carcinoma

Background

Increasing evidence have highlighted the biological significance of mRNA N6-methyladenosine (m6A) modification in regulating tumorigenicity and progression. However, the potential roles of m6A regulators in tumor microenvironment (TME) formation and immune cell infiltration in liver hepatocellular carcinoma (LIHC or HCC) requires further clarification.

Method

RNA sequencing data were obtained from TCGA-LIHC databases and ICGC-LIRI-JP databases. Consensus clustering algorithm was used to identify m6A regulators cluster subtypes. Weighted gene co-expression network analysis (WGCNA), LASSO regression, Random Forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) were applied to identify candidate biomarkers, and then a m6Arisk score model was constructed. The correlations of m6Arisk score with immunological characteristics (immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), and immune checkpoints) were systematically evaluated. The effective performance of nomogram was evaluated using concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic curve (ROC).

Results

Two distinct m6A modification patterns were identified based on 23 m6A regulators, which were correlated with different clinical outcomes and biological functions. Based on the constructed m6Arisk score model, HCC patients can be divided into two distinct risk score subgroups. Further analysis indicated that the m6Arisk score showed excellent prognostic performance. Patients with a high m6Arisk score was significantly associated with poorer clinical outcome, lower drug sensitivity, and higher immune infiltration. Moreover, we developed a nomogram model by incorporating the m6Arisk score and clinicopathological features. The application of the m6Arisk score for the prognostic stratification of HCC has good clinical applicability and clinical net benefit.

Conclusion

Our findings reveal the crucial role of m6A modification patterns for predicting HCC TME status and prognosis, and highlight the good clinical applicability and net benefit of m6Arisk score in terms of prognosis, immunophenotype, and drug therapy in HCC patients.