Immunometabolic Interplay in the Tumor Microenvironment

HMGCS2 serves as a potential biomarker for inhibition of renal clear cell carcinoma growth

3-Hydroxymethylglutaryl-CoA synthase 2 (HMGCS2) is the rate-limiting enzyme for ketone body synthesis, and most current studies focus on mitochondrial maturation and metabolic reprogramming. The role of HMGCS2 was evaluated in a pan-cancer multi-database using R language, and HMGCS2 was lowly expressed or not differentially expressed in all tumor tissues compared with normal tissues. Correlation analysis of clinical case characteristics, genomic heterogeneity, tumor stemness, and overall survival revealed that HMGCS2 is closely related to clear cell renal cell carcinoma (KIRC). Single-cell sequencing data from normal human kidneys revealed that HMGCS2 is specifically expressed in proximal tubular cells of normal adults. In addition, HMGCS2 is associated with tumor immune infiltration and microenvironment, and KIRC patients with low expression of HMGCS2 have worse prognosis. Finally, the results of cell counting kit 8 assays, colony formation assays, flow cytometry, and Western blot analysis suggested that upregulation of HMGCS2 increased the expression of key tumor suppressor proteins, inhibited the proliferation of clear cell renal cell carcinoma cells and promoted cell apoptosis. In conclusion, HMGCS2 is abnormally expressed in pan-cancer, may play an important role in anti-tumor immunity, and is expected to be a potential tumor prognostic marker, especially in clear cell renal cell carcinoma.

PI3K/AKT/mTOR signaling transduction pathway and targeted therapies in cancer

The PI3K/AKT/mTOR (PAM) signaling pathway is a highly conserved signal transduction network in eukaryotic cells that promotes cell survival, cell growth, and cell cycle progression. Growth factor signalling to transcription factors in the PAM axis is highly regulated by multiple cross-interactions with several other signaling pathways, and dysregulation of signal transduction can predispose to cancer development. The PAM axis is the most frequently activated signaling pathway in human cancer and is often implicated in resistance to anticancer therapies. Dysfunction of components of this pathway such as hyperactivity of PI3K, loss of function of PTEN, and gain-of-function of AKT, are notorious drivers of treatment resistance and disease progression in cancer. In this review we highlight the major dysregulations in the PAM signaling pathway in cancer, and discuss the results of PI3K, AKT and mTOR inhibitors as monotherapy and in co-administation with other antineoplastic agents in clinical trials as a strategy for overcoming treatment resistance. Finally, the major mechanisms of resistance to PAM signaling targeted therapies, including PAM signaling in immunology and immunotherapies are also discussed.

Neutrophil elastase as a potential biomarker related to the prognosis of gastric cancer and immune cell infiltration in the tumor immune microenvironment

Exploring biomarkers interrelated the tumor immune microenvironment (TIME) provides novel ideas for predicting the prognosis of gastric cancer (GC) and developing new treatment strategies. We analyzed the differential gene expression levels between the high and low StromalScore and ImmuneScore groups. Neutrophil elastase (ELANE) was evaluated as a potential biomarker by conducting intersection analysis of the protein-protein interaction network and univariate Cox regression analysis. The expression of ELANE was evaluated by immunohistochemistry. Its prognostic value was evaluated using Kaplan-Meier (K-M) survival curves and multivariate Cox regression analysis and its potential biological molecular mechanism was examined by gene set enrichment analysis (GSEA). We applied the CIBERSORT computing method to analyze the relationship between ELANE and tumor immune-infiltrating cells (TIICs). K-M survival curve showed that higher ELANE expression was closely related to shorter overall survival. The Cox regression analysis indicated that the high expression of ELANE was an independent prognostic risk factor in patients with GC. The GSEA revealed that genes in the ELANE high-expression group were involved in the signaling pathways regulating immune response; genes in the ELANE low-expression group were involved in the signaling pathways that regulate metabolism. ELANE might be participate in the change of TIME from immunodominant to metabolically dominant and its expression was closely related to tumor mutation burden and multiple TIICs. ELANE is a potential biomarker for predicting the GC patients' survival and prognosis. It influences the tumor immune cell infiltration in the TIME, and affects the TIME to maintain their immune status.

Integrated transcriptomics, proteomics and metabolomics-based analysis uncover TAM2-associated glycolysis and pyruvate metabolic remodeling in pancreatic cancer

Introduction

Tumor-associated macrophage 2 (TAM2) abundantly infiltrates pancreatic ductal adenocarcinoma (PAAD), and its interaction with malignant cells is involved in the regulation of tumor metabolism. In this study, we explored the metabolic heterogeneity involved in TAM2 by constructing TAM2-associated metabolic subtypes in PAAD.

Materials and methods

PAAD samples were classified into molecular subtypes with different metabolic characteristics based on a multi-omics analysis strategy. 20 PAAD tissues and 10 normal pancreatic tissues were collected for proteomic and metabolomic analyses. RNA sequencing data from the TCGA-PAAD cohort were used for transcriptomic analyses. Immunohistochemistry was used to assess TAM2 infiltration in PAAD tissues.

Results

The results of transcriptomics and immunohistochemistry showed that TAM2 infiltration levels were upregulated in PAAD and were associated with poor patient prognosis. The results of proteomics and metabolomics indicated that multiple metabolic processes were aberrantly regulated in PAAD and that this dysregulation was linked to the level of TAM2 infiltration. WGCNA confirmed pyruvate and glycolysis/gluconeogenesis as co-expressed metabolic pathways of TAM2 in PAAD. Based on transcriptomic data, we classified the PAAD samples into four TAM2-associated metabolic subtypes (quiescent, pyruvate, glycolysis/gluconeogenesis and mixed). Metabolic subtypes were each characterized in terms of clinical prognosis, tumor microenvironment, immune cell infiltration, chemotherapeutic drug sensitivity, and functional mechanisms.

Conclusion

Our study confirmed that the metabolic remodeling of pyruvate and glycolysis/gluconeogenesis in PAAD was closely related to TAM2. Molecular subtypes based on TAM2-associated metabolic pathways provided new insights into prognosis prediction and therapy for PAAD patients.

Exosomal miR-200b-3p induce macrophage polarization by regulating transcriptional repressor ZEB1 in hepatocellular carcinoma

PURPOSE

Accumulating evidence has elucidated that the interaction between cancer cells and M2 macrophages plays an important role in the tumorigenesis of hepatocellular carcinoma (HCC). However, the mechanism connecting tumor-derived exosomes, M2 polarization of macrophages, and liver metastasis remain unclear. Therefore, it is necessary to explore their influence on the tumor microenvironment of HCC.

METHODS

Transmission electron microscopy, nanometer particle testing, and special biomarker analysis were utilized to characterize exosomes, while the differential expression of microRNAs was evaluated using high-throughput sequencing technology. The functions of miR-200b-3p exosomes were confirmed using in vitro and in vivo assays. The interactions between microRNAs and ZEB1 as well as cancer cells and macrophages were measured using RNA pull-down and luciferase gene reporter assays.

RESULTS

Using in silico analysis, we identified high levels of miR-200b-3p exosome expression in patients with HCC, particularly with relapsed HCC. We demonstrated that HCC cell-derived miR-200b-3p exosomes were internalized by M0 macrophages and induced M2 polarization by downregulating ZEB1 and upregulating interleukin-4. As a result, the JAK/STAT signaling pathway was activated in M2 macrophages, leading to increased PIM1 and VEGFα expression. These cell factors accelerated the proliferation and metastasis of HCC, resulting in a feedback loop between HCC cells and M2 macrophages.

CONCLUSION

The study illustrates that HCC cell-derived miR-200b-3p exosomes facilitate the proliferation and polarization of macrophages by modulating cytokine secretion and the JAK/STAT signaling pathway, leading to the metastasis of HCC. These findings demonstrate the existence of a novel feedback loop between cancer cells and immune cells in the tumor microenvironment, presenting a new concept in cancer research.

13C metabolite tracing reveals glutamine and acetate as critical in vivo fuels for CD8+ T cells

Infusion of 13C-labeled metabolites provides a gold-standard for understanding the metabolic processes used by T cells during immune responses in vivo. Through infusion of 13C-labeled metabolites (glucose, glutamine, acetate) in Listeria monocytogenes (Lm)-infected mice, we demonstrate that CD8+ T effector (Teff) cells utilize metabolites for specific pathways during specific phases of activation. Highly proliferative early Teff cells in vivo shunt glucose primarily towards nucleotide synthesis and leverage glutamine anaplerosis in the tricarboxylic acid (TCA) cycle to support ATP and de novo pyrimidine synthesis. Additionally, early Teff cells rely on glutamic-oxaloacetic transaminase 1 (Got1)-which regulates de novo aspartate synthesis-for effector cell expansion in vivo. Importantly, Teff cells change fuel preference over the course of infection, switching from glutamine- to acetate-dependent TCA cycle metabolism late in infection. This study provides insights into the dynamics of Teff metabolism, illuminating distinct pathways of fuel consumption associated with Teff cell function in vivo.

Machine learning immune-related gene based on KLRB1 model for predicting the prognosis and immune cell infiltration of breast cancer

Objective

Breast cancer is a prevalent malignancy that predominantly affects women. The development and progression of this disease are strongly influenced by the tumor microenvironment and immune infiltration. Therefore, investigating immune-related genes associated with breast cancer prognosis is a crucial approach to enhance the diagnosis and treatment of breast cancer.

Methods

We analyzed data from the TCGA database to determine the proportion of invasive immune cells, immune components, and matrix components in breast cancer patients. Using this data, we constructed a risk prediction model to predict breast cancer prognosis and evaluated the correlation between KLRB1 expression and clinicopathological features and immune invasion. Additionally, we investigated the role of KLRB1 in breast cancer using various experimental techniques including real-time quantitative PCR, MTT assays, Transwell assays, Wound healing assays, EdU assays, and flow cytometry.

Results

The functional enrichment analysis of immune and stromal components in breast cancer revealed that T cell activation, differentiation, and regulation, as well as lymphocyte differentiation and regulation, play critical roles in determining the status of the tumor microenvironment. These DEGs are therefore considered key factors affecting TME status. Additionally, immune-related gene risk models were constructed and found to be effective predictors of breast cancer prognosis. Further analysis through KM survival analysis and univariate and multivariate Cox regression analysis demonstrated that KLRB1 is an independent prognostic factor for breast cancer. KLRB1 is closely associated with immunoinfiltrating cells. Finally, in vitro experiments confirmed that overexpression of KLRB1 inhibits breast cancer cell proliferation, migration, invasion, and DNA replication ability. KLRB1 was also found to inhibit the proliferation of breast cancer cells by blocking cell division in the G1/M phase.

Conclusion

KLRB1 may be a potential prognostic marker and therapeutic target associated with the microenzymic environment of breast cancer tumors, providing a new direction for breast cancer treatment.

Comprehensive characterization of tumor microenvironment in colorectal cancer via molecular analysis

Colorectal cancer (CRC) remains a challenging and deadly disease with high tumor microenvironment (TME) heterogeneity. Using an integrative multi-omics analysis and artificial intelligence-enabled spatial analysis of whole-slide images, we performed a comprehensive characterization of TME in colorectal cancer (CCCRC). CRC samples were classified into four CCCRC subtypes with distinct TME features, namely, C1 as the proliferative subtype with low immunogenicity; C2 as the immunosuppressed subtype with the terminally exhausted immune characteristics; C3 as the immune-excluded subtype with the distinct upregulation of stromal components and a lack of T cell infiltration in the tumor core; and C4 as the immunomodulatory subtype with the remarkable upregulation of anti-tumor immune components. The four CCCRC subtypes had distinct histopathologic and molecular characteristics, therapeutic efficacy, and prognosis. We found that the C1 subtype may be suitable for chemotherapy and cetuximab, the C2 subtype may benefit from a combination of chemotherapy and bevacizumab, the C3 subtype has increased sensitivity to the WNT pathway inhibitor WIKI4, and the C4 subtype is a potential candidate for immune checkpoint blockade treatment. Importantly, we established a simple gene classifier for accurate identification of each CCCRC subtype. Collectively our integrative analysis ultimately established a holistic framework to thoroughly dissect the TME of CRC, and the CCCRC classification system with high biological interpretability may contribute to biomarker discovery and future clinical trial design.

A Novel Defined PANoptosis-Related miRNA Signature for Predicting the Prognosis and Immune Characteristics in Clear Cell Renal Cell Carcinoma: A miRNA Signature for the Prognosis of ccRCC

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers, and PANoptosis is a distinct, inflammatory-programmed cell death regulated by the PANoptosome. The essential regulators of cancer occurrence and progression are microRNAs (miRNAs). However, the potential function of PANoptosis-related microRNAs (PRMs) in ccRCC remains obscure. This study retrieved ccRCC samples from The Cancer Genome Atlas database and three Gene Expression Omnibus datasets. PRMs were recognized based on previous reports in the scientific literature. Regression analyses were used to identify the prognosis PRMs and construct a PANoptosis-related miRNA prognostic signature based on the risk score. We discovered that high-risk patients had poorer survival prognoses and were significantly linked to high-grade and advanced-stage tumors, using a variety of R software packages and web analysis tools. Furthermore, we demonstrated that the low-risk group had significant changes in their metabolic pathways. In contrast, the high-risk group was characterized by high immune cell infiltration, immune checkpoint expression, and low half-maximum inhibition concentration (IC50) values of chemotherapeutic agents. This suggests that high-risk patients may benefit more from immunotherapy and chemotherapy. In conclusion, we constructed a PANoptosis-related microRNA signature and revealed its potential significance in clinicopathological features and tumor immunity, thereby providing new precise treatment strategies.

Therapeutic targeting of the tumor microenvironments with cannabinoids and their analogs: Update on clinical trials

Cancer is a major global public health concern that affects both industrialized and developing nations. Current cancer chemotherapeutic options are limited by side effects, but plant-derived alternatives and their derivatives offer the possibilities of enhanced treatment response and reduced side effects. A plethora of recently published articles have focused on treatments based on cannabinoids and cannabinoid analogs and reported that they positively affect healthy cell growth and reverse cancer-related abnormalities by targeting aberrant tumor microenvironments (TMEs), lowering tumorigenesis, preventing metastasis, and/or boosting the effectiveness of chemotherapy and radiotherapy. Furthermore, TME modulating systems are receiving much interest in the cancer immunotherapy field because it has been shown that TMEs have significant impacts on tumor progression, angiogenesis, invasion, migration, epithelial to mesenchymal transition, metastasis and development of drug resistance. Here, we have reviewed the effective role of cannabinoids, their analogs and cannabinoid nano formulations on the cellular components of TME (endothelial cells, pericytes, fibroblast and immune cells) and how efficiently it retards the progression of carcinogenesis is discussed. The article summarizes the existing research on the molecular mechanisms of cannabinoids regulation of the TME and finally highlights the human studies on cannabinoids' active interventional clinical trials. The conclusion outlines the need for future research involving clinical trials of cannabinoids to demonstrate their efficacy and activity as a treatment/prevention for various types of human malignancies.

Immunometabolism at the crossroads of obesity and cancer-a Keystone Symposia report

Immunometabolism considers the relationship between metabolism and immunity. Typically, researchers focus on either the metabolic pathways within immune cells that affect their function or the impact of immune cells on systemic metabolism. A more holistic approach that considers both these viewpoints is needed. On September 5-8, 2022, experts in the field of immunometabolism met for the Keystone symposium "Immunometabolism at the Crossroads of Obesity and Cancer" to present recent research across the field of immunometabolism, with the setting of obesity and cancer as an ideal example of the complex interplay between metabolism, immunity, and cancer. Speakers highlighted new insights on the metabolic links between tumor cells and immune cells, with a focus on leveraging unique metabolic vulnerabilities of different cell types in the tumor microenvironment as therapeutic targets and demonstrated the effects of diet, the microbiome, and obesity on immune system function and cancer pathogenesis and therapy. Finally, speakers presented new technologies to interrogate the immune system and uncover novel metabolic pathways important for immunity.

Systems Immunology Approaches to Metabolism

Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.

Prognostic significance of the preoperative alkaline phosphatase‑to‑albumin ratio in patients with hepatocellular carcinoma after hepatic resection

This study aimed to investigate the prognostic value of the preoperative alkaline phosphatase-to-albumin ratio (APAR) in patients with hepatocellular carcinoma (HCC) who underwent radical hepatectomy. The clinicopathological data from 330 patients was retrospectively analyzed. Receiver operating characteristic curves of APAR for diagnostic tumor recurrence were plotted with a cut-off value of 1.74. A high preoperative APAR value was significantly associated with hepatitis B surface antigen level, tumor diameter, and tumor-node-metastasis stage. The disease-free survival (DFS) and overall survival (OS) of patients with a high preoperative APAR were shorter than those with a low APAR. The independent risk factors for DFS were an APAR ≥1.74, and macrovascular invasion or tumor thrombus. The independent risk factors for OS were an APAR ≥1.74, existing clinical symptoms, α-fetoprotein level ≥20 ng/ml, macrovascular invasion or tumor thrombus, and family history of cancer. In conclusion, a preoperative APAR (≥1.74) is an independent risk factor influencing the poor prognosis of patients with HCC after curative hepatectomy, and patients with such a result should be closely monitored.

Integrative analysis of a novel super-enhancer-associated lncRNA prognostic signature and identifying LINC00945 in aggravating glioma progression

BACKGROUND

Super-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target.

METHODS

Combined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model.

RESULTS

6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo.

CONCLUSION

Our study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

Breast density and estradiol are associated with distinct different expression patterns of metabolic proteins in normal human breast tissue in vivo

Background

Breast density and exposure to sex steroids are major risk factors for breast cancer. The local microenvironment plays an essential role in progression of breast cancer. Metabolic adaption is a major hallmark of cancer. Whether proteins from the extracellular space regulating metabolism are affected in breast cancer, dense breasts or by estrogen exposure are not yet fully elucidated.

Methods

Women with breast cancer, postmenopausal women with normal breast tissue with varying breast density or premenopausal women with breasts exposed to high levels of estradiol were included in the study. Microdialysis was used to collect proteins from the extracellular space in vivo in 73 women; 12 with breast cancer, 42 healthy postmenopausal women with different breast densities, and 19 healthy premenopausal women. Breast density was determined as lean tissue fraction (LTF) using magnetic resonance imaging. Data were evaluated in a murine breast cancer model. We quantified a panel of 92 key proteins regulating metabolism using proximity extension assay.

Results

We report that 29 proteins were upregulated in human breast cancer. In dense breasts 37 proteins were upregulated and 17 of these were similarly regulated as in breast cancer. 32 proteins correlated with LTF. In premenopausal breasts 19 proteins were up-regulated and 9 down-regulated. Of these, 27 correlated to estradiol, a result that was confirmed for most proteins in experimental breast cancer. Only two proteins, pro-cathepsin H and galanin peptide, were similarly regulated in breast cancer, dense- and estrogen exposed breasts.

Conclusions

Metabolic proteins may be targetable for breast cancer prevention. Depending on risk factor, this may, however, require different approaches as breast density and estradiol induce distinct different expression patterns in the breast. Additionally, metabolic proteins from the extracellular space may indeed be further explored as therapeutic targets for breast cancer treatment.

Novel m7G-related lncRNA signature for predicting overall survival in patients with gastric cancer

Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan-Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model's reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS' correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.

Radiomics: A review of current applications and possibilities in the assessment of tumor microenvironment

With the recent success in the application of immunotherapy for treating various advanced cancers, the tumor microenvironment has rapidly become an important field of research. The tumor microenvironment is complex and its characteristics strongly influence disease biology and potentially responses to systemic therapy. Accurate preoperative assessment of tumor microenvironment is of great significance for the formulation of an immunotherapy strategy and evaluation of patient prognosis. As a research hotspot in medical image analysis technology, radiomics has been applied in the auxiliary diagnosis of the tumor microenvironment. This article reviews the current status of radiomics in the elective application on tumor microenvironment and discusses potential prospects.

Decellularized brain extracellular matrix slice glioblastoma culture model recapitulates the interaction between cells and the extracellular matrix without a nutrient-oxygen gradient interference

Decellularized extracellular matrix (dECM) is a valuable tool for generating three-dimensional in vitro tumor models that effectively recapitulate tumor-extracellular matrix (ECM) interactions. However, in current culture models, the components and structures of dECM are enzymatically disrupted to form hydrogels, making it difficult to recapitulate the native ECM. Additionally, when studying ECM-cell interactions, large-volume tumor culture models are incompatible with traditional experimental techniques and the nutrient-oxygen concentration gradient, which is a significant confounding factor. To address these issues, we developed a decellularized brain extracellular matrix slice (dBECMS) glioblastoma (GBM) culture model. This model possesses good light transmittance and substance diffusivity, making it compatible with traditional experimental techniques without forming nutrient-oxygen concentration gradients. Through transcriptomic analysis, we found that native brain ECM has a broad impact on glioma cells; the impact involves the ECM-ECM receptor interactions and the ECM and metabolic reprogramming. Further experiments demonstrated that dBECMS promoted glucose consumption and lactate production in GBM cells. Silver staining experiments revealed abundant proteins in the media of dBECMS, suggesting the degradation of the brain ECM by GBM cells. Transcriptome analysis also showed that the dBECMS-GBM culture model more accurately recapitulated the transcriptional profile of GBM than the two-dimensional culture. We experimentally demonstrated that the dBECMS-GBM model enhanced the resistance of GBM cells to temozolomide and increased the stemness of GBM cells. Additionally, we demonstrated the feasibility of the dBECMS-GBM model as a platform for drug response modeling. STATEMENT OF SIGNIFICANCE: The decellularized brain extracellular matrix (ECM) slice glioblastoma culture model mimics the interaction between native brain ECM and glioblastoma when glioblastoma infiltrates the brain and reveals the effects of native brain ECM on glioblastoma metabolism, ECM reprogramming, drug responsiveness, and stemness.

Single-cell sequencing of ascites fluid illustrates heterogeneity and therapy-induced evolution during gastric cancer peritoneal metastasis

Peritoneal metastasis is the leading cause of death for gastrointestinal cancers. The native and therapy-induced ascites ecosystems are not fully understood. Here, we characterize single-cell transcriptomes of 191,987 ascites cancer/immune cells from 35 patients with/without gastric cancer peritoneal metastasis (GCPM). During GCPM progression, an increase is seen of monocyte-like dendritic cells (DCs) that are pro-angiogenic with reduced antigen-presenting capacity and correlate with poor gastric cancer (GC) prognosis. We also describe the evolution of monocyte-like DCs and regulatory and proliferative T cells following therapy. Moreover, we track GC evolution, identifying high-plasticity GC clusters that exhibit a propensity to shift to a high-proliferative phenotype. Transitions occur via the recently described, autophagy-dependent plasticity program, paligenosis. Two autophagy-related genes (MARCKS and TXNIP) mark high-plasticity GC with poorer prognosis, and autophagy inhibitors induce apoptosis in patient-derived organoids. Our findings provide insights into the developmental trajectories of cancer/immune cells underlying GCPM progression and therapy resistance.

The Evolution of Single-Cell RNA Sequencing Technology and Application: Progress and Perspectives

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has become a powerful tool for describing cell subpopulation classification and cell heterogeneity by achieving high-throughput and multidimensional analysis of individual cells and circumventing the shortcomings of traditional sequencing for detecting the average transcript level of cell populations. It has been applied to life science and medicine research fields such as tracking dynamic cell differentiation, revealing sensitive effector cells, and key molecular events of diseases. This review focuses on the recent technological innovations in scRNA-Seq, highlighting the latest research results with scRNA-Seq as the core technology in frontier research areas such as embryology, histology, oncology, and immunology. In addition, this review outlines the prospects for its innovative application in traditional Chinese medicine (TCM) research and discusses the key issues currently being addressed by scRNA-Seq and its great potential for exploring disease diagnostic targets and uncovering drug therapeutic targets in combination with multiomics technologies.

A metabolic intervention strategy to break evolutionary adaptability of tumor for reinforced immunotherapy

The typical hallmark of tumor evolution is metabolic dysregulation. In addition to secreting immunoregulatory metabolites, tumor cells and various immune cells display different metabolic pathways and plasticity. Harnessing the metabolic differences to reduce the tumor and immunosuppressive cells while enhancing the activity of positive immunoregulatory cells is a promising strategy. We develop a nanoplatform (CLCeMOF) based on cerium metal-organic framework (CeMOF) by lactate oxidase (LOX) modification and glutaminase inhibitor (CB839) loading. The cascade catalytic reactions induced by CLCeMOF generate reactive oxygen species "storm" to elicit immune responses. Meanwhile, LOX-mediated metabolite lactate exhaustion relieves the immunosuppressive tumor microenvironment, preparing the ground for intracellular regulation. Most noticeably, the immunometabolic checkpoint blockade therapy, as a result of glutamine antagonism, is exploited for overall cell mobilization. It is found that CLCeMOF inhibited glutamine metabolism-dependent cells (tumor cells, immunosuppressive cells, etc.), increased infiltration of dendritic cells, and especially reprogrammed CD8⁺ T lymphocytes with considerable metabolic flexibility toward a highly activated, long-lived, and memory-like phenotype. Such an idea intervenes both metabolite (lactate) and cellular metabolic pathway, which essentially alters overall cell fates toward the desired situation. Collectively, the metabolic intervention strategy is bound to break the evolutionary adaptability of tumors for reinforced immunotherapy.

[Advances of Immunotherapy Resistance and Coping Strategies in Non-small Cell Lung Cancer]

Immunotherapy has significantly improved clinical outcomes of non-small cell lung cancer (NSCLC), however, along with the popularization of immunotherapy, immune resistance has become an unavoidable problem. Immunotherapy can induce extensive cellular and molecular alterations in the tumor microenvironment. Considering the mechanisms of immune resistance are not yet fully understood and the efficacy of standard chemotherapy regimens is limited, more effective coping strategies based on resistance mechanisms are urgently needed. In this review, we intend to summarize the known mechanisms of immune resistance and feasible strategies, so as to provide a foundation for clinicians to develop more individualized and precise regimens and finally improve patients' prognosis.
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Comprehensive characterization of endoplasmic reticulum stress in bladder cancer revealing the association with tumor immune microenvironment and prognosis

Background: This study constructs a molecular subtype and prognostic model of bladder cancer (BLCA) through endoplasmic reticulum stress (ERS) related genes, thus helping to clinically guide accurate treatment and prognostic assessment. Methods: The Bladder Cancer (BLCA) gene expression data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We clustered by ERS-related genes which obtained through GeneCards database, results in the establishment of a new molecular typing of bladder cancer. Further, we explored the characteristics of each typology in terms of immune microenvironment, mutations, and drug screening. By analyzing the ERS-related genes with univariate Cox, LASSO and multivariate Cox analyses, we also developed the four-gene signature, while validating the prognostic effect of the model in GSE32894 and GSE13507 cohorts. Finally, we evaluated the prognostic value of the clinical data in the high and low ERS score groups and constructed a prognostic score line graph by Nomogram. Results: We constructed four molecular subtypes (C1- C4) of bladder cancer, in which patients with C2 had a poor prognosis and those with C3 had a better prognosis. The C2 had a high degree of TP53 mutation, significant immune cell infiltration and high immune score. In contrast, C3 had a high degree of FGFR3 mutation, insignificant immune cell infiltration, and reduced immune checkpoint expression. After that, we built ERS-related risk signature to calculate ERS score, including ATP2A3, STIM2, VWF and P4HB. In the GSE32894 and GSE13507, the signature also had good predictive value for prognosis. In addition, ERS scores were shown to correlate well with various clinical features. Finally, we correlated the ERS clusters and ERS score. Patients with high ERS score were more likely to have the C2 phenotype, while patients with low ERS score were C3. Conclusion: In summary, we identified four novel molecular subtypes of BLCA by ERS-related genes which could provide some new insights into precision medicine. Prognostic models constructed from ERS-related genes can be used to predict clinical outcomes. Our study contributes to the study of personalized treatment and mechanisms of BLCA.

Vessels That Encapsulate Tumor Clusters (VETC) Predict cTACE Response in Hepatocellular Carcinoma

Background

To investigate the correlation between hepatocellular carcinoma (HCC) pathological types and conventional transarterial chemoembolization (cTACE), and to evaluate the predictive value of the pathological types for efficacy of cTACE.

Methods

We investigated 186 naive HCC patients from 2 hospitals, including 63 patients with recurrence after surgical resection, and 123 unresectable cases, who underwent at least one cTACE procedure as the first treatment. All patients were histologically diagnosed with HCC by surgical resection and/or liver biopsy. Lipiodol deposition rate, ORR (objective response rate), PFS (progression-free survival), OS (overall survival) were compared among different HCC pathological types.

Results

This study evaluated 186 naive HCC patients and 189 tumor nodules. Vessels that encapsulate tumor clusters (VETC), macrotrabecular-massive (MTM), CK19-positive types were identified in 38% (72/189), 40% (76/189), and 28% (53/189) of the whole cohort, respectively. VETC, MTM and CK19-negative HCCs derived significantly better lipiodol deposition rate and ORR. cTACE prolonged the PFS of VETC and CK19-negative HCCs compared with non-VETC and CK19-positive HCCs in the recurrence, liver biopsy and combining whole cohorts, whereas the OSs of different pathological types were not significantly different. Multivariate analysis showed that VETC (OR, 4.671, 95% CI [1.954, 11.166], P<0.001) and CK19-positive type (OR, 0.127, 95% CI [0.044, 0.362], P<0.001) were independent predictive factors for the first cTACE response. However, only VETC type was significantly associated with the second cTACE response in multivariate analysis (OR, 3.31, 95% CI [1.24, 8.83], P=0.017), suggesting that VETC might be a more useful predictor of cTACE response.

Conclusion

Our study suggests that VETC is an effective predictor of cTACE response in patients with HCC.

Evaluation of immunotherapy efficacy in gynecologic cancer

Various immunotherapies have demonstrated remarkable success over the past few decades, and have been approved for the treatment of different cancer types. However, patient responses to immunotherapy are variable, and approximately 50% of cases are refractory to these agents. Tumor biomarker-based stratification of cases may therefore help identify subpopulations that are sensitive/resistant to immunotherapy; it may also improve prediction of response in various cancers including gynecologic cancer. These biomarkers include the tumor mutational burden, microsatellite instability, mismatch repair deficiency, T cell-inflamed gene expression profile, programmed cell death protein 1 ligand 1, tumor-infiltrating lymphocytes, and numerous other genomic alterations. Future directions in the treatment of gynecologic cancer include the utilization of these biomarkers to select ideal candidates. This review focused on recent advances in the predictive ability of molecular biomarkers in patients with gynecologic cancer who undergo immunotherapy. The most recent developments in combined immunotherapy and targeted therapy strategies and novel immune interventions against gynecologic cancers have also been discussed.

Monocarboxylate transporter 4 inhibition potentiates hepatocellular carcinoma immunotherapy through enhancing T cell infiltration and immune attack

BACKGROUND AND AIMS

Monocarboxylate transporter (MCT) 4 is a high-affinity lactate transporter that is primarily involved in the maintenance of intracellular pH homeostasis and highly expressed in different tumors. However, the role of MCT4 in modulating immune responses against HCC remains unknown.

APPROACH AND RESULTS

In this study, we demonstrated that MCT4 was overexpressed in HCC, which was associated with poor prognosis in patients. Genetic or pharmacological inhibition of MCT4 using VB124 (a highly potent MCT4 inhibitor) suppressed HCC tumor growth in immunocompetent mice model by enhancing CD8 + T cell infiltration and cytotoxicity. Such improved immunotherapy response by MCT4 targeting was due to combined consequences characterized by the alleviated acidification of tumor microenvironment and elevated the chemokine (C-X-C motif) ligand (CXCL) 9/CXCL10 secretion induced by reactive oxygen species/NF-κB signaling pathway. Combining MCT4 inhibition improved the therapeutic benefit of anti-programmed cell death 1 immunotherapy in HCC and prolonged mice survival. Moreover, higher MCT4 expression was observed in tumor tissues from nonresponder patients with HCC receiving neoadjuvant therapy with toripalimab.

CONCLUSIONS

Our results revealed that lactate exportation by MCT4 has a tumor-intrinsic function in generating an immunosuppressive HCC environment and demonstrated the proof of the concept of targeting MCT4 in tailoring HCC immunotherapeutic approaches.

Identification and validation of an anoikis-related lncRNA signature to predict prognosis and immune landscape in osteosarcoma

Background

Anoikis is a specialized form of programmed apoptosis that occurs in two model epithelial cell lines and plays an important role in tumors. However, the prognostic value of anoikis-related lncRNA (ARLncs) in osteosarcoma (OS) has not been reported.

Methods

Based on GTEx and TARGET RNA sequencing data, we carried out a thorough bioinformatics analysis. The 27 anoikis-related genes were obtained from the Gene Set Enrichment Analysis (GSEA). Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis were successively used to screen for prognostic-related ARLncs. To create the prognostic signature of ARLncs, we performed multivariate Cox regression analysis. We calculated the risk score based on the risk coefficient, dividing OS patients into high- and low-risk subgroups. Additionally, the relationship between the OS immune microenvironment and risk prognostic models was investigated using function enrichment, including Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), single-sample gene set enrichment analysis (ssGSEA), and GSEA analysis. Finally, the potential effective drugs in OS were found by immune checkpoint and drug sensitivity screening.

Results

A prognostic signature consisting of four ARLncs (AC079612.1, MEF2C-AS1, SNHG6, and TBX2-AS1) was constructed. To assess the regulation patterns of anoikis-related lncRNA genes, we created a risk score model. According to a survival analysis, high-risk patients have a poor prognosis as they progress. By using immune functional analysis, the lower-risk group demonstrated the opposite effects compared with the higher-risk group. GO and KEGG analysis showed that the ARLncs pathways and immune-related pathways were enriched. Immune checkpoints and drug sensitivity analysis might be used to determine the better effects of the higher group.

Conclusion

We identified a novel prognostic model based on a four-ARLncs signature that might serve as potential prognostic indicators that can be used to predict the prognosis of OS patients, and immunotherapy and drugs that may contribute to improving the overall survival of OS patients and advance our understanding of OS.

Identification of endoplasmic reticulum stress-related lncRNAs in lung adenocarcinoma by bioinformatics and experimental validation

BACKGROUND

Endoplasmic reticulum stress (ERs) is an important cellular self-defence mechanism, which is closely related to tumorigenesis and development. However, the role of endoplasmic reticulum stress state in the development of lung adenocarcinoma (LUAD) has not been clarified.

METHODS

The lncRNAs associated with endoplasmic reticulum stress were identified by co-expression analysis in public databases, and by the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression modelling, we constructed a prognostic model based on endoplasmic reticulum stress-related lncRNAs (ERs-related lncRNAs), performed immune analysis, TME, TMB and clinical drug prediction for model-related risk scores, and performed correlation validation in public databases and at the human tissue level.

RESULTS

Five ERs-related lncRNAs were used to construct an ERs-related lncRNA signature (ERs-related LncSig), which can predict the prognosis of LUAD. Patients in the high-risk group had worse survival, and differences existed in immune cell infiltration, immune function, immune checkpoint analysis, tumour microenvironment (TME), tumour mutational burden (TMB), immunotherapy efficacy, and sensitivity to some commonly used chemotherapeutic agents between high and low risk groups.

CONCLUSION

Our study demonstrated that ERs-related lncRNA signature can be used for the prognostic evaluation of LUAD patients and may provide new insights into clinical decision-making and personalised medicine for LUAD.

Prior metabolite extraction fully preserves RNAseq quality and enables integrative multi-'omics analysis of the liver metabolic response to viral infection

Here, we provide an in-depth analysis of the usefulness of single-sample metabolite/RNA extraction for multi-'omics readout. Using pulverized frozen livers of mice injected with lymphocytic choriomeningitis virus (LCMV) or vehicle (Veh), we isolated RNA prior (RNA) or following metabolite extraction (MetRNA). RNA sequencing (RNAseq) data were evaluated for differential expression analysis and dispersion, and differential metabolite abundance was determined. Both RNA and MetRNA clustered together by principal component analysis, indicating that inter-individual differences were the largest source of variance. Over 85% of LCMV versus Veh differentially expressed genes were shared between extraction methods, with the remaining 15% evenly and randomly divided between groups. Differentially expressed genes unique to the extraction method were attributed to randomness around the 0.05 FDR cut-off and stochastic changes in variance and mean expression. In addition, analysis using the mean absolute difference showed no difference in the dispersion of transcripts between extraction methods. Altogether, our data show that prior metabolite extraction preserves RNAseq data quality, which enables us to confidently perform integrated pathway enrichment analysis on metabolomics and RNAseq data from a single sample. This analysis revealed pyrimidine metabolism as the most LCMV-impacted pathway. Combined analysis of genes and metabolites in the pathway exposed a pattern in the degradation of pyrimidine nucleotides leading to uracil generation. In support of this, uracil was among the most differentially abundant metabolites in serum upon LCMV infection. Our data suggest that hepatic uracil export is a novel phenotypic feature of acute infection and highlight the usefulness of our integrated single-sample multi-'omics approach.

Cancer-associated fibroblasts in acute leukemia

Although the prognosis for acute leukemia has greatly improved, treatment of relapsed/refractory acute leukemia (R/R AL) remains challenging. Recently, increasing evidence indicates that the bone marrow microenvironment (BMM) plays a crucial role in leukemogenesis and therapeutic resistance; therefore, BMM-targeted strategies should be a potent protocol for treating R/R AL. The targeting of cancer-associated fibroblasts (CAFs) in solid tumors has received much attention and has achieved some progress, as CAFs might act as an organizer in the tumor microenvironment. Additionally, over the last 10 years, attention has been drawn to the role of CAFs in the BMM. In spite of certain successes in preclinical and clinical studies, the heterogeneity and plasticity of CAFs mean targeting them is a big challenge. Herein, we review the heterogeneity and roles of CAFs in the BMM and highlight the challenges and opportunities associated with acute leukemia therapies that involve the targeting of CAFs.

Stromal protein CCN family contributes to the poor prognosis in lower-grade gioma by modulating immunity, matrix, stemness, and metabolism

Background: The CCN family of stromal proteins is involved in the regulation of many important biological functions. However, the role of dysregulated CCN proteins in lower-grade glioma (LGG) remain less understand. Methods: The clinical significance of the CCN proteins was explored based on RNA-seq profiles from multiple cohorts. A CCNScore was constructed using LASSO regression analysis. The PanCanAtlas data and MEXPRESS database were employed to elucidate molecular underpinnings. Results: The expression of CCN4 was associated with poor prognosis in LGG. The CCNScore (CCN1 = 0.06, CCN4 = 0.86) showed implication in prognosis prediction, subtype assessment and therapy selection. The gene mutation pattern of the high-CCNScore group was similar with glioblastoma, including EGFR, PTEN, and NF1 mutation frequently. Besides, the high-CCNScore group was comprised of samples mainly classic-like and mesenchymal-like, had lower methylation levels, higher stemness, higher inflammation, higher levels of extracellular matrix remodel and dysfunction of metabolic pathways. On the other hand, the low-CCNScore group consisted mainly of IDH-mutation LGG, and was characterized by TP53, CIC, and ATRX gene mutations, hyper-methylation status, lower stemness, lower proliferation, immune quietness and low extracellular matrix stiffness. Conclusion: In summary, these results outlined the role of CCN family in LGG and provided a potential and promising therapeutic target.

Epigenomic and Other Evidence for Cannabis-Induced Aging Contextualized in a Synthetic Epidemiologic Overview of Cannabinoid-Related Teratogenesis and Cannabinoid-Related Carcinogenesis

BACKGROUND

Twelve separate streams of empirical data make a strong case for cannabis-induced accelerated aging including hormonal, mitochondriopathic, cardiovascular, hepatotoxic, immunological, genotoxic, epigenotoxic, disruption of chromosomal physiology, congenital anomalies, cancers including inheritable tumorigenesis, telomerase inhibition and elevated mortality.

METHODS

Results from a recently published longitudinal epigenomic screen were analyzed with regard to the results of recent large epidemiological studies of the causal impacts of cannabis. We also integrate theoretical syntheses with prior studies into these combined epigenomic and epidemiological results.

RESULTS

Cannabis dependence not only recapitulates many of the key features of aging, but is characterized by both age-defining and age-generating illnesses including immunomodulation, hepatic inflammation, many psychiatric syndromes with a neuroinflammatory basis, genotoxicity and epigenotoxicity. DNA breaks, chromosomal breakage-fusion-bridge morphologies and likely cycles, and altered intergenerational DNA methylation and disruption of both the histone and tubulin codes in the context of increased clinical congenital anomalies, cancers and heritable tumors imply widespread disruption of the genome and epigenome. Modern epigenomic clocks indicate that, in cannabis-dependent patients, cannabis advances cellular DNA methylation age by 25-30% at age 30 years. Data have implications not only for somatic but also stem cell and germ line tissues including post-fertilization zygotes. This effect is likely increases with the square of chronological age.

CONCLUSION

Recent epigenomic studies of cannabis exposure provide many explanations for the broad spectrum of cannabis-related teratogenicity and carcinogenicity and appear to account for many epidemiologically observed findings. Further research is indicated on the role of cannabinoids in the aging process both developmentally and longitudinally, from stem cell to germ cell to blastocystoids to embryoid bodies and beyond.

Harnessing bioactive nanomaterials in modulating tumor glycolysis-associated metabolism

Glycolytic reprogramming is emerging as a hallmark of various cancers and a promising therapeutic target. Nanotechnology is revolutionizing the anti-tumor therapeutic approaches associated with glycolysis. Finely controlled chemical composition and nanostructure provide nanomaterials unique advantages, enabling an excellent platform for integrated drug delivery, biochemical modulation and combination therapy. Recent studies have shown promising potential of nanotherapeutic strategies in modulating tumor glycolytic metabolism alone or in combination with other treatments such as chemotherapy, radiotherapy and immunotherapy. To foster more innovation in this cutting-edge and interdisciplinary field, this review summarizes recent understandings of the origin and development of tumor glycolysis, then provides the latest advances in how nanomaterials modulate tumor glycolysis-related metabolism. The interplay of nanochemistry, metabolism and immunity is highlighted. Ultimately, the challenges and opportunities are presented.

Myeloid-derived itaconate suppresses cytotoxic CD8+ T cells and promotes tumour growth

The tumour microenvironment possesses mechanisms that suppress anti-tumour immunity. Itaconate is a metabolite produced from the Krebs cycle intermediate cis-aconitate by the activity of immune-responsive gene 1 (IRG1). While it is known to be immune modulatory, the role of itaconate in anti-tumour immunity is unclear. Here, we demonstrate that myeloid-derived suppressor cells (MDSCs) secrete itaconate that can be taken up by CD8+ T cells and suppress their proliferation, cytokine production and cytolytic activity. Metabolite profiling, stable-isotope tracing and metabolite supplementation studies indicated that itaconate suppressed the biosynthesis of aspartate and serine/glycine in CD8+ T cells to attenuate their proliferation and function. Host deletion of Irg1 in female mice bearing allografted tumours resulted in decreased tumour growth, inhibited the immune-suppressive activities of MDSCs, promoted anti-tumour immunity of CD8+ T cells and enhanced the anti-tumour activity of anti-PD-1 antibody treatment. Furthermore, we found a significant negative correlation between IRG1 expression and response to PD-1 immune checkpoint blockade in patients with melanoma. Our findings not only reveal a previously unknown role of itaconate as an immune checkpoint metabolite secreted from MDSCs to suppress CD8+ T cells, but also establish IRG1 as a myeloid-selective target in immunometabolism whose inhibition promotes anti-tumour immunity and enhances the efficacy of immune checkpoint protein blockade.

Hyaluronic acids mediate the infiltration, migration, and M2 polarization of macrophages: evaluating metabolic molecular phenotypes in gliomas

Gliomas cause high mortality around the world. The metabolic pattern of the tumor was previously suggested to be associated with the patient's survival outcome and immune activity. Yet, this relationship in glioma remains unknown. This study systematically evaluated the immune landscape in different phenotypes classified by metabolic-related pathways of 3068 glioma samples and 33 glioblastoma single-cell sequencing samples. Machine learning prediction analysis of microarray with R (pamr) was used for validating clustering results. A total of 5842 pan-cancer samples were used for external validation of the metabolic clusters. Cell Counting Kit-8 (CCK8) assay, cell clone assay, EdU assay, wound healing assay, Transwell assay, and co-culture assay were performed to verify the distinction in molecular characteristics among metabolic clusters. Metabolomics and RNA sequencing were performed on HS683 and U251 cells to annotate potential hyaluronic acid (HA)-mediated pathways. Three distinct metabolic phenotypes were identified. Metabolic cluster 1 correlated with a high number of immune infiltrating cells and poor survival of glioma patients. Metabolic clusters were proved with different levels of the macrophage markers CD68 and CD163 by multiplex immunofluorescence staining. Glioma cells from other metabolic clusters also expressed various levels of HA. HA was further found to mediate glioma proliferation, progression, and invasion. Moreover, HA potentially promoted macrophage recruitment and M2 polarization through the IL-1/CHI3L1 and TGF-b/CHI3L1 axes. HA also regulated the expression of PD-L1. This work revealed the significant connection between metabolic patterns, especially HA, and tumor immune infiltration in gliomas.

Development and validation of a combined metabolism and immune prognostic model in lung adenocarcinoma

Background

Tumor metabolism and immune response can affect the biological behavior of tumor cells. There is an obvious relationship between glycolysis and immune response. However, the association between metabolism and immune response and prognosis in lung adenocarcinoma (LUAD) has not yet been examined in a comprehensive and detailed manner. The establishment of reliable models for predicting the prognosis of LUAD based on glycolysis ability and immune status is still highly anticipated.

Methods

The expression of genes were obtained from online databases, and the differentially expressed genes in LUAD tissues and adjacent tissues were identified. We used LUAD samples in The Cancer Genome Atlas (TCGA) database as training set and the Gene Expression Omnibus (GEO) databases as validation sets. The best predictive model was constructed using least absolute selection and shrinkage operator (LASSO) regression and Cox regression. The receiver operator characteristic (ROC) curve is used to verify the accuracy of the model. The expression status of the Glycolysis-related genes (GRGs) and the status of the immune cells in LUCD patients were further analyzed. The protein levels of the 3 identified genes were then tested in LUAD patients.

Results

We identified 3 GRGs and immune-related genes (i.e., fibroblast growth factor 2, hyaluronan-mediated motor receptor, and nuclear receptor 0B2) and constructed a stable comprehensive index of glycolysis and immunity (CIGI) prediction model. The validation results for this CIGI model were quite stable across different datasets and patient subgroups and the CIGI score can be included as an independent prognostic factor for LUAD patients. The area under the curve (AUC) values of 1-, 3- and 5-year of the finally established nomogram model are 0.767, 0.735 and 0.769. Further analysis showed that LUAD patients in the low-risk group had lower levels of glycolytic gene expression than those in the high-risk group and exhibited an immunosuppressed state. Finally, hyaluronan-mediated motor receptor may play a role in inhibiting cancer, while fibroblast growth factor 2 and nuclear receptor 0B2 may play roles in promoting cancer.

Conclusions

In this study, we established a new prognostic prediction model for LUAD patients that combines glycolysis ability and immune status.

Pan-cancer analyses reveal multi-omics and clinical characteristics of RIO kinase 2 in cancer

RIO kinase 2 has emerged as a critical kinase for ribosome maturation, and recently it has also been found to play a fundamental role in cancer, being involved in the occurrence and progression of glioblastoma, liver cancer, prostate cancer, non-small cell lung cancer, and acute myeloid leukemia. However, our knowledge in this regard is fragmented and limited and it is difficult to determine the exact role of RIO kinase 2 in tumors. Here, we conducted an integrated pan-cancer analysis comprising 33 cancer-types to determine the function of RIO kinase 2 in malignancies. The results show that RIO kinase 2 is highly expressed in all types of cancer and is significantly associated with tumor survival, metastasis, and immune cell infiltration. Moreover, RIO kinase 2 alteration via DNA methylation, and protein phosphorylation are involved in tumorigenesis. In summary, RIO kinase two serves as a promising target for the identification of cancer and increases our understanding of tumorigenesis and cancer progression and enhancing the ultimate goal of improved treatment for these diseases.

ADGRD1 as a Potential Prognostic and Immunological Biomarker in Non-Small-Cell Lung Cancer

ADGRD1 (GPR133), an adhesion G protein-coupled receptor (GPCR), has been linked to cancer. However, the prognostic value and regulatory function within non-small-cell lung cancer (NSCLC) is still unclear. This work adopted various bioinformatics methods, including publicly available databases as well as real-time PCR (RT-PCR), for detecting ADGRD1 expression level and investigating the correlation between ADGRD1 expression level and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltrating cells, immune-related genes, and targeted regulation mechanisms in NSCLC. According to the results, ADGRD1 expression decreased within NSCLC, which might be the factor predicting prognosis of NSCLC. Meanwhile, ADGRD1 showed significant correlation with TMB and MSI, respectively, as well as immune cell infiltrating levels in lung adenocarcinoma (LUAD), which were primarily linked to macrophage M1, mast cell resting, T cell CD4 memory activated, and T cell CD4 memory resting and were associated with mast cell activated and mast cell resting in lung squamous cell carcinoma (LUSC). The most promising upstream regulation pathways of ADGRD1 were likely miR-142-5p, miR-93-5p, and miR-17-5p, which were overexpressed and associated with poor prognosis in NSCLC. ADGRD1 and immune-related genes correlated with ADGRD1 were shown to be enriched in "positive regulation of leukocyte activation," "external side of plasma membrane," "receptor ligand activity," and "cytokine-cytokine receptor interaction" pathways. ADGRD1 expression and regulation may be critical in determining NSCLC prognosis.

Spatial multi-omics analyses of the tumor immune microenvironment

In the past decade, single-cell technologies have revealed the heterogeneity of the tumor-immune microenvironment at the genomic, transcriptomic, and proteomic levels and have furthered our understanding of the mechanisms of tumor development. Single-cell technologies have also been used to identify potential biomarkers. However, spatial information about the tumor-immune microenvironment such as cell locations and cell–cell interactomes is lost in these approaches. Recently, spatial multi-omics technologies have been used to study transcriptomes, proteomes, and metabolomes of tumor-immune microenvironments in several types of cancer, and the data obtained from these methods has been combined with immunohistochemistry and multiparameter analysis to yield markers of cancer progression. Here, we review numerous cutting-edge spatial ‘omics techniques, their application to study of the tumor-immune microenvironment, and remaining technical challenges.

Pan-cancer single-cell analysis reveals the heterogeneity and plasticity of cancer-associated fibroblasts in the tumor microenvironment

Cancer-associated fibroblasts (CAFs) are the predominant components of the tumor microenvironment (TME) and influence cancer hallmarks, but without systematic investigation on their ubiquitous characteristics across different cancer types. Here, we perform pan-cancer analysis on 226 samples across 10 solid cancer types to profile the TME at single-cell resolution, illustrating the commonalities/plasticity of heterogenous CAFs. Activation trajectory of the major CAF types is divided into three states, exhibiting distinct interactions with other cell components, and relating to prognosis of immunotherapy. Moreover, minor CAF components represent the alternative origin from other TME components (e.g., endothelia and macrophages). Particularly, the ubiquitous presentation of endothelial-to-mesenchymal transition CAF, which may interact with proximal SPP1⁺ tumor-associated macrophages, is implicated in endothelial-to-mesenchymal transition and survival stratifications. Our study comprehensively profiles the shared characteristics and dynamics of CAFs, and highlight their heterogeneity and plasticity across different cancer types. Browser of integrated pan-cancer single-cell information is available at https://gist-fgl.github.io/sc-caf-atlas/ .

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

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This review discusses the emerging single cell technologies and applications in Multiple myeloma (MM), population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction.

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The role(s) of epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of MM are also discussed.

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It is understood that ethnic component acts as a driver of variable response to chemotherapy in different sub-populations globally.

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This review augments our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, myeloma microenvironment at the molecular and cellular level, and developing precision medicine strategies to combat this malignancy.

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The emerging single cell technologies hold great promise for enhancing our understanding of MM tumor heterogeneity and clonal diversity.

Multiple myeloma (MM) is an aggressive cancer characterised by malignancy of the plasma cells and a rising global incidence. The gold standard for optimum response is aggressive chemotherapy followed by autologous stem cell transplantation (ASCT). However, majority of the patients are above 60 years and this presents the clinician with complications such as ineligibility for ASCT, frailty, drug-induced toxicity and differential/partial response to treatment. The latter is partly driven by heterogenous genotypes of the disease in different subpopulations. In this review, we discuss emerging single cell technologies and applications in MM, population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction, as well as the role(s) played by epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of the disease. Taken together, our discussions further our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, augment our understanding of the myeloma microenvironment at the molecular and cellular level and provide a basis for developing precision medicine strategies to combat this malignancy.

Tumor-associated macrophages are shaped by intratumoral high potassium via Kir2.1

The tumor microenvironment (TME) is a unique niche governed by constant crosstalk within and across all intratumoral cellular compartments. In particular, intratumoral high potassium (K⁺) has shown immune-suppressive potency on T cells. However, as a pan-cancer characteristic associated with local necrosis, the impact of this ionic disturbance on innate immunity is unknown. Here, we reveal that intratumoral high K⁺ suppresses the anti-tumor capacity of tumor-associated macrophages (TAMs). We identify the inwardly rectifying K⁺ channel Kir2.1 as a central modulator of TAM functional polarization in high K⁺ TME, and its conditional depletion repolarizes TAMs toward an anti-tumor state, sequentially boosting local anti-tumor immunity. Kir2.1 deficiency disturbs the electrochemically dependent glutamine uptake, engendering TAM metabolic reprogramming from oxidative phosphorylation toward glycolysis. Kir2.1 blockade attenuates both murine tumor- and patient-derived xenograft growth. Collectively, our findings reveal Kir2.1 as a determinant and potential therapeutic target for regaining the anti-tumor capacity of TAMs within ionic-imbalanced TME.

Cancer resistance to immunotherapy: What is the role of cancer stem cells?

Immunotherapy is an emerging form of cancer therapy that is associated with promising outcomes. However, most cancer patients either do not respond to immunotherapy or develop resistance to treatment. The resistance to immunotherapy is poorly understood compared to chemotherapy and radiotherapy. Since immunotherapy targets cells within the tumor microenvironment, understanding the behavior and interactions of different cells within that environment is essential to adequately understand both therapy options and therapy resistance. This review focuses on reviewing and analyzing the special features of cancer stem cells (CSCs), which we believe may contribute to cancer resistance to immunotherapy. The mechanisms are classified into three main categories: mechanisms related to surface markers which are differentially expressed on CSCs and help CSCs escape from immune surveillance and immune cells killing; mechanisms related to CSC-released cytokines which can recruit immune cells and tame hostile immune responses; and mechanisms related to CSC metabolites which modulate the activities of infiltrated immune cells in the tumor microenvironment. This review also discusses progress made in targeting CSCs with immunotherapy and the prospect of developing novel cancer therapies.

Lactate from the tumor microenvironment - A key obstacle in NK cell-based immunotherapies

Recent findings about the new roles of lactate have changed our understanding of this end product of glycolysis or fermentation that was once considered only a waste product. It is now well accepted that lactate acts as a signaling molecule and fuel source for cancer cells in a glucose-restricted environment. Moreover, lactate and lactate dehydrogenase are markers of poor prognosis of many cancers and regulate many functions of immune cells. The presence of lactate in the tumor microenvironment (TME) leads to polarization of the immunosuppressive phenotypes of dendritic cells and impairs the cytotoxic abilities of T cells and NK cells, and as such lactate is a major obstacle to immune-cell effector functions and the efficacy of cell-based immunotherapies. Emerging evidence suggests that lactate in the TME might be a novel therapeutic target to enhance the immunotherapeutic potential of cell-based therapies. This review describes our current understanding of the role of lactate in tumor biology, including its detrimental effects on cell-based immunotherapy in cancer. We also highlight how the role of lactate in the TME must be considered when producing cell therapies designed for adoptive transfer and describe how targeted modulation of lactate in the TME might boost immune-cell functions and positively impact cellular immunotherapy, with a focus on NK cell.

The role of a cuproptosis-related prognostic signature in colon cancer tumor microenvironment and immune responses

Background: Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive tract with poor clinical outcomes. Cuproptosis is a novel cell death mechanism and linked to mitochondrial respiration. However, the role of cuproptosis in colon cancer tumor microenvironment (TME) and immune responses remains unknown.

Methods: We conducted difference analysis to identify the differential expressed cuproptosis-related genes (CRGs). According to the CRGs, the TCGA-COAD samples were categorized using consensus clustering. The LASSO regression analysis was utilized to develop the cuproptosis-related signature. We then verified the model reliability by Kaplan–Meier, PCA, and ROC analysis. The GES39582 cohort served as the validation set. GO and KEGG functional analyses were conducted to investigate the underlying mechanism. We compared the infiltration levels of immune cells, the expression levels of immune checkpoints, and microsatellite instability (MSI) status between the high- and low-risk groups. Additionally, the relationships between the risk signature and immune cells and cancer stem cell (CSC) were analyzed.

Results: Finally, we identified 9 differentially expressed CRGs in COAD. According to the expression of CRGs, the TCGA-COAD samples were separated into two clusters. The 11-gene signature was established by LASSO, and it had excellent predictive power for COAD prognosis. Besides, we used the GSE39582 cohort to validate the prognostic value of the model. GO and KEGG results demonstrated that the survival differences between two risk groups was mainly linked to the extracellular matrix (ECM). Further immune characterization analysis showed the significant differences in the immune cell infiltration and immune responses between two risk groups.

Conclusion: Overall, the novel cuproptosis-related signature was able to accurately predict COAD prognosis and played important roles in COAD tumor microenvironment and immune responses.

Lipid metabolic features of T cells in the Tumor Microenvironment

The tumor microenvironment (TME) is characterized by discrete changes in metabolic features of cancer and immune cells, with various implications. Cancer cells take up most of the available glucose to support their growth, thereby leaving immune cells with insufficient nutrients to expand. In the relative absence of glucose, T cells switch the metabolic program to lipid-based sources, which is pivotal to T-cell differentiation and activation in nutrient-stressed TME. Although consumption of lipids should provide an alternative energy source to starving T cells, a literature survey has revealed that it may not necessarily lead to antitumor responses. Different subtypes of T cells behave differently in various lipid overload states, which widely depends upon the kind of free fatty acids (FFA) engulfed. Key lipid metabolic genes provide cytotoxic T cells with necessary nutrients for proliferation in the absence of glucose, thereby favoring antitumor immunity, but the same genes cause immune evasion in T_mem and T_reg. This review aims to detail the complexity of differential lipid metabolism in distinct subtypes of T cells that drive the antitumor or pro-tumor immunity in specific TME states. We have identified key drug targets related to lipid metabolic rewiring in TME.

Comprehensive Analysis of the Immune Implication of AKAP12 in Stomach Adenocarcinoma

A kinase anchor protein 12 (AKAP12) as a tumor suppressor in various cancers has been extensively studied and confirmed. However, its immune implication in stomach adenocarcinoma (STAD) remains uncertain. Here, using The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Tumor Immune Estimation Resource (TIMER), Cancer Cell Line Encyclopedia (CCLE), integrated repository portal for tumor-immune system interactions (TISIDB), and Search Tool for the Retrieval of Interaction Gene/Proteins (STRING) database, we systematically analyzed the immune correlation of AKAP12 from three aspects including immune infiltration cells, immune-related pathways, and immunomodulators and developed a AKAP12-related 4-gene signature for prognosis prediction. Our results showed that AKAP12 mRNA and protein levels were downregulated in STAD patients, and its expression was positively related to CD4+ T cells and macrophages. In addition, the immune cell infiltration levels were associated with AKAP12 gene copy number deletion in STAD. Based on CCLE database, we found that AKAP12 coexpressed genes were enriched in several immune- and cancer-related pathways, which was further validated by Gene Set Enrichment Analysis (GSEA). Moreover, we identified 46 immunomodulators that were significantly related to AKAP12 expression using TISIDB database, and these immunomodulators were involved in immune-related pathways including Th17 cell differentiation and natural killer cell-mediated cytotoxicity. Additionally, based on the 46 AKAP12-related immunomodulators, a 4-gene risk prediction signature was developed using the Cox regression model. The risk signature was identified as an independent prognostic factor, which can accurately predict the prognosis of patients with STAD, showing good predictive performance. Furthermore, we constructed a prognostic nomogram and calibration to predict and assess patient survival probabilities by integrating the risk score and other clinical factors. In conclusion, our study provides strong evidence that AKAP12 is closely related to tumor immunity in STAD from three aspects: immune infiltration cells, immune pathways, and immunomodulators. More importantly, the AKAP12-related prognostic signature may have a good application prospect for clinical practice.

Carbon source availability drives nutrient utilization in CD8+ T cells

How environmental nutrient availability impacts T cell metabolism and function remains poorly understood. Here, we report that the presence of physiologic carbon sources (PCSs) in cell culture medium broadly impacts glucose utilization by CD8⁺ T cells, independent of transcriptional changes in metabolic reprogramming. The presence of PCSs reduced glucose contribution to the TCA cycle and increased effector function of CD8⁺ T cells, with lactate directly fueling the TCA cycle. In fact, CD8⁺ T cells responding to Listeria infection preferentially consumed lactate over glucose as a TCA cycle substrate in vitro, with lactate enhancing T cell bioenergetic and biosynthetic capacity. Inhibiting lactate-dependent metabolism in CD8⁺ T cells by silencing lactate dehydrogenase A (Ldha) impaired both T cell metabolic homeostasis and proliferative expansion in vivo. Together, our data indicate that carbon source availability shapes T cell glucose metabolism and identifies lactate as a bioenergetic and biosynthetic fuel for CD8⁺ effector T cells.

Recent advances in bacterial therapeutics based on sense and response

Intelligent drug delivery is a promising strategy for cancer therapies. In recent years, with the rapid development of synthetic biology, some properties of bacteria, such as gene operability, excellent tumor colonization ability, and host-independent structure, make them ideal intelligent drug carriers and have attracted extensive attention. By implanting condition-responsive elements or gene circuits into bacteria, they can synthesize or release drugs by sensing stimuli. Therefore, compared with traditional drug delivery, the usage of bacteria for drug loading has better targeting ability and controllability, and can cope with the complex delivery environment of the body to achieve the intelligent delivery of drugs. This review mainly introduces the development of bacterial-based drug delivery carriers, including mechanisms of bacterial targeting to tumor colonization, gene deletions or mutations, environment-responsive elements, and gene circuits. Meanwhile, we summarize the challenges and prospects faced by bacteria in clinical research, and hope to provide ideas for clinical translation.