Accessories to the crime: functions of cells recruited to the tumor microenvironment

Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT

Bone metastasis from breast cancer significantly elevates patient morbidity and mortality, making early detection crucial for improving outcomes. This study utilizes radiomics to analyze changes in the thoracic vertebral bone marrow microenvironment from chest computerized tomography (CT) images prior to bone metastasis in breast cancer, and constructs a model to predict metastasis.

METHODS

This study retrospectively gathered data from breast cancer patients who were diagnosed and continuously monitored for five years from January 2013 to September 2023. Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. The effectiveness of this combined model was assessed through receiver operating characteristic (ROC) analysis as well as decision curve analysis (DCA).

RESULTS

The study included a total of 106 patients diagnosed with breast cancer, among whom 37 developed bone metastases within five years. The radiomics model's area under the curve (AUC) for the test set, calculated using logistic regression, is 0.929, demonstrating superior predictive performance compared to alternative machine learning models. Furthermore, DCA demonstrated the potential of radiomics models in clinical application, with a greater clinical benefit in predicting bone metastasis than clinical model and nomogram.

CONCLUSION

CT-based radiomics can capture subtle changes in the thoracic vertebral bone marrow before breast cancer bone metastasis, offering a predictive tool for early detection of bone metastasis in breast cancer.

Up-regulated ITGB4 promotes hepatocellular carcinoma metastasis by activating hypoxia-mediated glycolysis and cancer-associated fibroblasts

The pre-metastatic niche constructed by cancer-associated fibroblasts (CAFs) plays a key role in the hypoxic tumor microenvironment (TME), promoting hepatocellular carcinoma (HCC) metastasis. Integrin, which is involved in cell-to-cell or cell-to-matrix interactions and TME regulation, affects tumor metastasis. However, the complex interactions between integrin-mediated HCC cells and CAFs remain unclear. Co-culture experiments were used to assess the behaviors of HCC cells and CAFs, demonstrating HCC metastatic traits and CAFs activation in vitro. Transcriptome sequencing analysis and molecular detection identified key genes, with overexpression and knockdown experiments further confirming their roles in HCC progression. Xenograft models validated these findings in vivo. We showed that HCC cells induced the conversion of normal hepatic stellate cells (HSCs) into CAFs and recruit additional CAFs, driven by lactate produced by HCC. Integrin beta 4 (ITGB4) was identified as a key gene in the process. Inhibiting ITGB4 reduced lactate secretion, reversed CAFs activation and recruitment, and decreased HCC metastasis, while overexpressing ITGB4 significantly enhanced these malignant phenotypes. ITGB4 influences glycolysis and HCC metastasis through the AKT/HK2 signaling pathway, and CAFs activation and recruitment through the TGF-β/Smads signaling pathway. Compared to tumors derived from control cells, ITGB4-knockdown tumors showed fewer and smaller intrahepatic metastatic nodules, reduced lactate production and CAFs formation, along with inhibition of AKT/HK2 and TGF-β/Smads signaling pathways. Our findings highlighted the impact of hypoxia on HCC progression, revealing the roles of ITGB4-mediated glycolysis and lactate-induced CAFs in the pre-metastatic niche on HCC metastasis.

TDO2 + cancer-associated fibroblasts mediate cutaneous squamous cell carcinoma immune escape via impeding infiltration of CD8 + T cells

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer, originating from the malignant proliferation of squamous epithelial cells. However, its pathogenesis remains unclear. To further explore the mechanisms underlying cSCC, we analyzed the data from one single-cell RNA sequencing study and discovered a significant upregulation of tryptophan 2,3-dioxygenase (TDO2) in the cancer-associated fibroblasts (CAFs). Nonetheless, the specific expression and potential biological significance of TDO2 in cSCC have not yet been reported. In this study, we confirmed that TDO2 is highly expressed in CAFs of cSCC. Clinical correlation analysis indicated that high TDO2 expression was significantly associated with poor tumor differentiation. Furthermore, increased TDO2 expression in cSCC correlated with reduced CD8 + T cell infiltration, suggesting its role in modulating immune responses. TDO2 inhibitors significantly reduced the size and number of tumors in mice and effectively increased CD8 + T cell infiltration. RNA sequencing analysis revealed that TDO2 inhibitors modulate immune cell activity and downregulate the PI3K-Akt signaling pathway. In summary, our study demonstrates that TDO2 + CAFs induce immune evasion by inhibiting CD8 + T cell infiltration in cSCC. Inhibiting TDO2 could enhance antitumor immune responses, providing a promising strategy to improve treatment outcomes in cSCC.

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

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

Immune regulation and the tumor microenvironment in anti-PD-1/PDL-1 and anti-CTLA-4 therapies for cancer immune evasion: A bibliometric analysis

This study aims to conduct a bibliometric analysis, employing visualization tools to examine literature pertaining to tumor immune evasion related to anti-CTLA-4 and anti-PD-1/PD-L1 therapy from 1999 to 2022. A special emphasis is placed on the interplay between tumor microenvironment, signaling pathways, immune cells and immune evasion, with data sourced from the Web of Science core collection (WoSCC). Advanced tools, including VOSviewer, Citespace, and Scimago Graphica, were utilized to analyze various parameters, such as co-authorship/co-citation patterns, regional contributions, journal preferences, keyword co-occurrences, and significant citation bursts. Out of 4778 publications reviewed, there was a marked increase in research focusing on immune evasion, with bladder cancer being notably prominent. Geographically, China, the USA, and Japan were the leading contributors. Prestigious institutions like MD Anderson Cancer Center, Harvard Medical School, Fudan University, and Sun Yat Sen University emerged as major players. Renowned journals in this domain included Frontiers in Immunology, Cancers, and Frontiers in Oncology. Ehen LP and Wang W were identified as prolific authors on this topic, while Topalian SL stood out as one of the most cited. Research current situation is notably pivoting toward challenges like immunotherapy resistance and the intricate signaling pathways driving drug resistance. This bibliometric study seeks to provide a comprehensive overview of past and current research trends, emphasizing the potential role of tumor microenvironment, signaling pathways and immune cells in the context of immune checkpoint inhibitors (ICIs) and tumor immune evasion.

Polyphenol-Mediated Assembly of Toll-like Receptor 7/8 Agonist Nanoparticles for Effective Tumor Immunotherapy

Toll-like receptor (TLR) 7/8 agonists have shown significant potential in tumor immunotherapy. However, the limited pharmacokinetic properties and systemic toxicity resulting from off-target effects limits their biomedical applications. We here report the polyphenol-mediated assembly of resiquimod (R848, a TLR7/8 agonist) nanoparticles (RTP NPs) to achieve tumor-selective immunotherapy while avoiding systemic adverse effects. Upon intravenous administration, the prepared RTP NPs are effectively accumulated at tumor sites, which increase their bioavailability and reduce systemic inflammation. RTP NPs can trigger a potent antitumor immune response in a mouse tumor model to inhibit tumor growth. Additionally, after subcutaneous injection at the tail base, RTP NPs efficiently migrate to the lymph nodes, where they elicit immune memory to prevent tumorigenesis. This study underscores the potential application of polyphenol-mediated assembly in developing nanomedicines with reduced toxicity for tumor-specific immunotherapy. STATEMENT OF SIGNIFICANCE: Toll-like receptor agonist (R848) nanoparticles for tumor-selective immunotherapy were synthesized through polyphenol-mediated assembly, a method that simplifies preparation process and minimizes potential side effects. Intravenously administered these nanoparticles effectively extended circulation time, enhanced tumor enrichment, and reduced systemic inflammation, thus augmenting the bioavailability and minimizing the side effects of R848. The nanoparticles significantly inhibited tumor growth by triggering a potent antitumor immune response, including dendritic cell maturation, macrophage polarization, T-cell infiltration, and cytokine secretion. Moreover, after subcutaneous injection at the tail base, they can elicit immune memory to prevent tumorigenesis.

FOXP3 Transcriptionally Activates Fatty Acid Scavenger Receptor CD36 in Tumour-Induced Treg Cells

The host immune system is adapted in a variety of ways by tumour microenvironment and growing tumour interacts to promote immune escape. One of these adaptations is manipulating the metabolic processes of cells in the tumour microenvironment. The growing tumour aggressively utilise glucose, its primary energy source available in tumour site, and produce lactate by Warburg effect. In such a hostile environment, tumour-infiltrating immune cells are unable to survive metabolically. Tumour-infiltrating CD4+ Treg cells, on the other hand, adapted to an alternative energy-generating system, switching from the highly-competitive glucose to the fatty-acid metabolic pathway, by down-regulating glucose-metabolising genes and up-regulating fatty-acid metabolising genes. Tregs with high-levels of the fatty acid scavenger receptor CD36, a key component of the fatty-acid metabolic pathway, aided this metabolic shift. Treg cell formation was hampered when the fatty-acid metabolic pathway was disrupted, showing that it is necessary for Treg cell development. FOXP3, the Treg lineage-specific transcription factor, regulates fatty-acid metabolism by inducing CD36 transcription. A high-fat diet enhanced Treg development while suppressing anti-tumour immunity, whereas a low-fat diet suppressed Treg development. The altered metabolism of tumour-infiltrating Treg cells enables their rapid generation and survival in the hostile tumour microenvironment, aiding cancer progression. Fascinatingly, mice fed with a low-fat diet showed a positive prognosis with chemotherapy than mice fed with a high-fat diet. Thus, a maximum efficacy of chemotherapy might be achieved by altering diet composition during chemotherapy, providing a promising indication for future cancer treatment.

A comprehensive analysis of vasculogenic mimicry related genes to predict the survival rate of HCC and its influence on the tumor microenvironment

Objectives

Investigate the predictive value of Vasculogenic mimicry (VM) related genes for the survival and prognosis of Hepatocellular carcinoma (HCC) patients and its role in the tumor microenvironment (TME).

Methods

VM-related genes were obtained from previous literature, the expression profiles, single-cell data and clinical information of HCC patients were downloaded from public databases. The HCC patients were divided into different clusters by unsupervised clustering, the differences in prognosis and immune characteristics of VM-related clusters were analyzed. A prognostic model related to VM (VM Score) was constructed based on LASSO regression and univariate and multivariate Cox regression, the correlation between this model and chemotherapy drugs and immunotherapy was studied. Seurat package was used to standardize single-cell data for single-cell level analysis. The expression of risk factors in VM Score was verified by RT-qPCR.

Results

VM Score composed of SPP1, ADAMTS5 and ZBP1 was constructed and validated. VM Score was an independent prognostic factor for HCC. Through the analysis of single cell data further reveals the VM Score influence on TME. In addition, VM Score could provide ideas for the selection of immunotherapy and chemotherapy drugs. RT-qPCR showed that the expression of risk factors was different in HCC cell lines.

Conclusion

Our results suggest that VM Score may serve as a promising prognostic biomarker for HCC and provide new ideas for immunotherapy in HCC patients.

Annexin A2: the feasibility of being a therapeutic target associated with cancer metastasis and drug resistance in cancer microenvironment

At present, there is still a lack of effective treatment strategies for cancer metastasis and drug resistance, so finding effective biomarkers is particularly important. AnnexinA2 (ANXA2), a vital membrane protein, critically influences cancer progression, tumor invasion, and tumor microenvironment modulation. To assess the possible application of ANXA2 as a therapeutic target against cancer cell metastasis and drug resistance to chemotherapeutic drugs in the tumor microenvironment, we elucidated the functionality of ANXA2 in stromal cells, angiogenic vascular cells, and infiltrated immune cells that mediate metastasis and drug resistance, as well as its potential as a therapeutic target. ANXA2 shows a high expression level in many tissues, and its expression level is even higher in several tumors and their microenvironments. ANXA2 is a crucial regulator of many factors and may serve as a target against drug-resistant cancers.

The Two Faces of Angiopoietin-Like Protein 2 in Cancer

The tumor microenvironment is composed of tumor cells and various stromal cell types, such as immune cells, fibroblasts, and vascular cells. Signaling interactions between tumor and stromal cells orchestrate the tumor microenvironment's contribution to tumor progression. Angiopoietin-like protein 2 (ANGPTL2) is a secreted glycoprotein homologous to angiopoietins. Previous studies indicate that tumor cell-derived ANGPTL2 serves as a tumor promoter. However, recent studies suggest that tumor stroma-derived ANGPTL2 shows tumor-suppressive activity by enhancing anti-tumor immune responses, supporting a dual function for ANGPTL2 in cancer pathology. Such complexity can complicate development of effective therapeutic strategies targeting ANGPTL2. In this Review, we focus on ANGPTL2 activity in the tumor microenvironment and its function in anti-cancer immunity.

Machine learning-based selection of immune cell markers in osteosarcoma: prognostic determination and validation of CLK1 in disease progression

Introduction

Osteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the tumor microenvironment (TME) is critical for enhancing outcomes in OS patients.

Methods

The clinical and RNA expression data of OS patients were extracted from the TARGET database. The single-cell RNA sequencing (scRNA-seq) data of 11 OS samples was retrieved from the GEO database, and analyzed using the Seurat package of R software. Copy number variation (CNV) was analyzed using the InferCNV software. The potential interactions between the different cells in the TME was analyzed with the CellChat package. A multi-algorithm-based computing framework was used to calculate the tumor-infiltrating immune cell (TIIC) scores. A prognostic model was constructed using 20 machine learning algorithms. Maftools R package was used to characterize the genomic variation landscapes in the patient groups stratified by TIIC score. The human OS cell lines MG63 and U2OS were used for the functional assays. Cell proliferation and migration were analyzed by the EdU assay and Transwell assay respectively. CLK1 protein expression was measured by immunoblotting.

Results

We observed higher CNV in the OS cells compared to endothelial cells. In addition, there was distinct transcriptional heterogeneity across the OS cells, and cluster 1 was identified as the terminal differentiation state. S100A1, TMSB4X, and SLPI were the three most significantly altered genes along with the pseudo-time trajectory. Cell communication analysis revealed an intricate network between S100A1+ tumor cells and other TME cells. Cluster 1 exhibited significantly higher aggressiveness features, which correlated with worse clinical outcomes. A prognostic model was developed based on TIIC-related genes that were screened using machine learning algorithms, and validated in multiple datasets. Higher TIIC signature score was associated with lower cytotoxic immune cell infiltration and generally inferior immune response and survival rate. Moreover, TIIC signature score was further validated in the datasets of other cancers. CLK1 was identified as a potential oncogene that promotes the proliferation and migration OS cells.

Conclusion

A TIIC-based gene signature was developed that effectively predicted the prognosis of OS patients, and was significantly associated with immune infiltration and immune response. Moreover, CLK1 was identified as an oncogene and potential therapeutic target for OS.

Cancer-associated fibroblasts: heterogeneity, tumorigenicity and therapeutic targets

Cancer, characterized by its immune evasion, active metabolism, and heightened proliferation, comprises both stroma and cells. Although the research has always focused on parenchymal cells, the non-parenchymal components must not be overlooked. Targeting cancer parenchymal cells has proven to be a formidable challenge, yielding limited success on a broad scale. The tumor microenvironment(TME), a critical niche for cancer cell survival, presents a novel way for cancer treatment. Cancer-associated fibroblast (CAF), as a main component of TME, is a dynamically evolving, dual-functioning stromal cell. Furthermore, their biological activities span the entire spectrum of tumor development, metastasis, drug resistance, and prognosis. A thorough understanding of CAFs functions and therapeutic advances holds significant clinical implications. In this review, we underscore the heterogeneity of CAFs by elaborating on their origins, types and function. Most importantly, by elucidating the direct or indirect crosstalk between CAFs and immune cells, the extracellular matrix, and cancer cells, we emphasize the tumorigenicity of CAFs in cancer. Finally, we highlight the challenges encountered in the exploration of CAFs and list targeted therapies for CAF, which have implications for clinical treatment.

Cholesterol: The driving force behind the remodeling of tumor microenvironment in colorectal cancer

Essential membrane components and metabolites with a wide range of biological roles are both produced by cholesterol metabolism. Cell-intrinsic and cell-extrinsic stimuli alter cholesterol metabolism in the tumor microenvironment (TME), which in turn encourages colorectal carcinogenesis. Metabolites produced from cholesterol play intricate roles in promoting the development of colorectal cancer (CRC) and stifling immunological responses. By altering the extracellular matrix of the main tumor, redesigning its immunological environment, and altering its mechanical stiffness, cholesterol can encourage the epithelial-mesenchymal transition of the primary tumor, opening up a pathway for tumor metastasis. Its functions in TME remodeling and tumor prevention have been recently identified. In this review we address the function of cholesterol in TME remodeling and therapeutic techniques designed to block cholesterol metabolism, and discuss how combining these strategies with already available anti-CRC medicines can have combined effects and open up new therapeutic avenues.

Prediction of bladder cancer prognosis and immune microenvironment assessment using machine learning and deep learning models

Bladder cancer (BCa) is a heterogeneous malignancy characterized by distinct immune subtypes, primarily due to differences in tumor-infiltrating immune cells and their functional characteristics. Therefore, understanding the tumor immune microenvironment (TIME) landscape in BCa is crucial for prognostic prediction and guiding precision therapy. In this study, we integrated 10 machine learning algorithms to develop an immune-related machine learning signature (IRMLS) and subsequently created a deep learning model to detect the IRMLS subtype based on pathological images. The IRMLS proved to be an independent prognostic factor for overall survival (OS) and demonstrated robust and stable performance (p < 0.01). The high-risk group exhibited an immune-inflamed phenotype, associated with poorer prognosis and higher levels of immune cell infiltration. We further investigated the cancer immune cycle and mutation landscape within the IRMLS model, confirming that the high-risk group is more sensitive to immune checkpoint immunotherapy (ICI) and adjuvant chemotherapy with cisplatin (p = 2.8e-10), docetaxel (p = 8.8e-13), etoposide (p = 1.8e-07), and paclitaxel (p = 6.2e-13). In conclusion, we identified and validated a machine learning-based molecular characteristic, IRMLS, which reflects various aspects of the BCa biological process and offers new insights into personalized precision therapy for BCa patients.

Crosstalk between miRNAs and signaling pathways in the development of drug resistance in breast cancer

One of the biggest challenges of today's society is cancer, which imposes a significant financial, emotional and spiritual burden on human life. Breast cancer (BC) is one of the most common cancers that affects people in society, especially women, and due to advanced treatment strategies and primary prevention, it is still the second cause of cancer-related deaths in society. Various genetic and environmental factors are involved in the development of BC. MicroRNAs (miRNA)s are non-coding RNAs, that the degradation or inhibition of them plays an important role in the prevention or development of cancer by modulating many cellular pathways including apoptosis, drug resistance, and tumorigenesis. Drug resistance is one of the important defense mechanisms of cancer cells against anticancer drugs and is considered one of the main causes of cancer treatment failure. Different miRNAs, including mir-7, mir-21, mir-31, and mir-124 control different cell activities, including drug resistance, through different pathways, including PI3K/AKT/mTOR, TGF-β, STAT3, and NF-kB. Therefore, cell signaling pathways are one of the important factors that miRNAs control cellular activities. Hence, in this study, we decided to highlight an overview of the relationship between miRNAs and signaling pathways in the development of drug resistance in BC.

Hypoxia as a critical player in extracellular vesicles-mediated intercellular communication between tumor cells and their surrounding microenvironment

In the past years, increasing attention has been paid to the role of extracellular vesicles (EVs) as mediators of intercellular communication in cancer. These small size particles mediate the intercellular transfer of important bioactive molecules involved in malignant initiation and progression. Hypoxia, or low partial pressure of oxygen, is recognized as a remarkable feature of solid tumors and has been demonstrated to exert a profound impact on tumor prognosis and therapeutic efficacy. Indeed, the high-pitched growth rate and chaotic neovascular architecture that embodies solid tumors results in a profound reduction in oxygen pressure within the tumor microenvironment (TME). In response to oxygen-deprived conditions, tumor cells and their surrounding milieu develop homeostatic adaptation mechanisms that contribute to the establishment of a pro-tumoral phenotype. Latest evidence suggests that the hypoxic microenvironment that surrounds the tumor bulk may be a clincher for the observed elevated levels of circulating EVs in cancer patients. Thus, it is proposed that EVs may play a role in mediating intercellular communication in response to hypoxic conditions. This review focuses on the EVs-mediated crosstalk that is established between tumor cells and their surrounding immune, endothelial, and stromal cell populations, within the hypoxic TME.

Tumor-Infiltrating Lymphocytes as Mediators of the Obesity and Papillary Thyroid Carcinoma Lymph Node Metastasis Association: An Observational Retrospective Cohort Study

BACKGROUND

Obesity increases the risk of papillary thyroid carcinoma (PTC) and lymph node metastasis (LNM), possibly via modulation of the tumor immunological microenvironment.

MATERIALS AND METHODS

The STROCSS guideline was followed to conduct a retrospective cohort study. Binary logistic regression analysis with odds ratios (OR) was performed to assess the association between tumor-infiltrating lymphocytes (TILs), obesity, and LNM. Using The Cancer Genome Atlas (TCGA) data, we examined the relationship between immune cell subsets and obesity-regulating molecules in thyroid cancer tissues. The Cox regression risk model was used to analyze the prognosis of thyroid cancer.

RESULTS

After adjusting for confounding factors, our findings revealed that overweight and obesity were associated with a decrease in TIL infiltration (OR 0.876, p = 0.005 and OR 0.795, p = 0.001, respectively). Furthermore, these conditions were observed to be correlated with increased likelihood of LNM (OR 1.134, p = 0.005 and OR 1.307, p < 0.001, respectively). On the contrary, TIL infiltration was inversely associated with LNM (OR 0.868, p < 0.001). When controlling for TIL infiltration as the sole variable, the combination of obesity and TIL infiltration did not independently predict LNM (adjusted OR 1.442, p = 0.113). However, obesity alone was found to elevate the likelihood of LNM (adjusted OR 1.539, p = 0.02). Additionally, adiponectin (a crucial adipokine) was reduced in obesity and demonstrated a negative correlation with the abundance of infiltrated dendritic cells and regulatory T cells, as evidenced by TCGA data analysis. Furthermore, ADIPOR2 expression negatively correlated with LNM and positively associated with unfavorable prognosis in PTC, with a hazard ratio of 0.480 (p = 0.007).

CONCLUSIONS

TIL infiltration may affect obesity-associated PTC LNM. Obesity may affect LNM and result in poor prognosis through ADIPOR2 regulation of antitumor immune cells.

Advancing tumor microenvironment and lymphoid tissue research through 3D bioprinting and biofabrication

Cancer progression is significantly influenced by the complex interactions within the tumor microenvironment (TME). Immune cells, in particular, play a critical role by infiltrating tumors from the circulation and surrounding lymphoid tissues in an attempt to control their spread. However, they often fail in this task. Current in vivo and in vitro preclinical models struggle to fully capture these intricate interactions affecting our ability to understand immune evasion and predict drugs behaviour in the clinic. To address this challenge, biofabrication and particularly 3D bioprinting has emerged as a promising tool for modeling both tumors and the immune system. Its ability to incorporate multiple cell types into 3D matrices, enable tissue compartmentalization with high spatial accuracy, and integrate vasculature makes it a valuable approach. Nevertheless, limited research has focused on capturing the complex tumor-immune interplay in vitro. This review highlights the composition and significance of the TME, the architecture and function of lymphoid tissues, and innovative approaches to modeling their interactions in vitro, while proposing the concept of an extended TME.

Integrative multi-omics analysis reveals a novel subtype of hepatocellular carcinoma with biological and clinical relevance

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.

Methods

We integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.

Results

Our analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.

Conclusions

This study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

GLI3 Is Required for M2 Macrophage Polarization and M2-Mediated Waldenström Macroglobulinemia Growth and Survival

Waldenstrom macroglobulinemia (WM) is a non-Hodgkin B-cell lymphoma, characterized by bone marrow infiltration with plasma cells and lymphocytes. The tumor microenvironment (TME) plays an important role in mediating WM cell biology, but the effects of macrophages on WM biology remains unclear. Here, we investigated the effects of macrophages on WM growth and survival and identified a novel role for transcription factor GLI3 in macrophage polarization. We found that co-culture of M0 and M2 macrophages promoted WM cell growth and survival, and co-culture WM cells with M0 macrophages induced M2-like phenotypes. Interestingly, GLI3 expression was induced in M2 macrophages (not M1), leading us to perform analysis of macrophages from mice lacking Gli3 in myeloid cells (M-Gli3-/- mice). A subset of differentially expressed genes implicated a role for GLI3 in macrophage polarization. Macrophages from M-Gli3-/- mice did not induce WM cell proliferation and reduced survival compared to M2 macrophages from WT mice. In addition, in vitro polarization of M0 macrophages from M-Gli3-/- was not able to induce M2 markers such as CD163, despite inducing iNos expression (M1 marker). Taken together, these results suggest a role for M2 macrophages in promoting WM cell growth and identify GLI3 as a modulator of macrophage polarization.

Harnessing m1A modification: a new frontier in cancer immunotherapy

N1-methyladenosine (m1A) modification is an epigenetic change that occurs on RNA molecules, regulated by a suite of enzymes including methyltransferases (writers), demethylases (erasers), and m1A-recognizing proteins (readers). This modification significantly impacts the function of RNA and various biological processes by affecting the structure, stability, translation, metabolism, and gene expression of RNA. Thereby, m1A modification is closely associated with the occurrence and progression of cancer. This review aims to explore the role of m1A modification in tumor immunity. m1A affects tumor immune responses by directly regulating immune cells and indirectly modulating tumor microenvironment. Besides, we also discuss the implications of m1A-mediated metabolic reprogramming and its nexus with immune checkpoint inhibitors, unveiling promising avenues for immunotherapeutic intervention. Additionally, the m1AScore, established based on the expression patterns of m1A modification, can be used to predict tumor prognosis and guide personalized therapy. Our review underscores the significance of m1A modification as a burgeoning frontier in cancer biology and immuno-oncology, with the potential to revolutionize cancer treatment strategies.

The role of LPA receptor signaling in modulating cellular responses of colon cancer cells co-cultured with lymphoid endothelial cells under hypoxic stress

Solid tumors are formed by cancer cells and the surrounding non-cancer stromal cells under hypoxic conditions, collectively referred to as the tumor microenvironment (TME). Lysophosphatidic acid (LPA) receptor (LPA1 to LPA6) signaling is crucial in regulating tumor progression. This study investigated the impact of LPA receptor signaling on the biological behaviors of colon cancer DLD-1 cells co-cultured with lymphatic endothelial SVEC4-10 cells under hypoxic conditions. Expression levels of LPAR1, LPAR2 and LPAR5 genes were significantly higher in DLD-1 cells co-cultured with SVEC4-10 cells compared to those cultured alone. Co-culturing with SVEC4-10 cells increased the motility of DLD-1 cells at 21 % O2. LPA stimulated the motility of DLD-1 cells co-cultured with SVEC4-10 cells but had no effect on DLD-1 cells cultured alone. Furthermore, under 1 % O2 conditions, expression levels of LPAR1, LPAR2, and LPAR5 genes were markedly elevated in DLD-1 cells co-cultured with SVEC4-10 cells compared to 21 % O2. The motility of DLD-1 cells co-cultured with SVEC4-10 cells was enhanced under 1 % O2 conditions. Viability of DLD-1 cells to fluorouracil (5-FU) in SVEC4-10 cell supernatants increased at 21 % O2 and decreased at 1 % O2. Additionally, the LPA2 agonist GRI-977143 increased viability to 5-FU. These findings indicate that LPA receptor signaling plays a critical role in regulating the biological behaviors of DLD-1 cells co-cultured with SVEC4-10 cells under hypoxic conditions.

CAR T cells in solid tumors and metastasis: paving the way forward

CAR T cell therapy, hailed as a breakthrough in cancer treatment due to its remarkable outcomes in hematological malignancies, encounters significant hurdles when applied to solid tumors. While notable responses to CAR T cells remain sporadic in these patients, challenges persist due to issues such as on-target off-tumor toxicity, difficulties in their trafficking and infiltration into the tumor, and the presence of a hostile and immunosuppressive microenvironment. This review aims to explore recent endeavors aimed at overcoming these obstacles in CAR T cell therapy for solid tumors. Specifically, we will delve into promising strategies for enhancing tumor specificity through antigen targeting, addressing tumor heterogeneity, overcoming physical barriers, and counteracting the immune-suppressive microenvironment.

T cell landscape in the microenvironment of human solid tumors

T cells are the main effectors involved in anti-tumor immunity, mediating most of the adaptive response towards cancer. After priming in lymph nodes, tumor antigens-specific naïve T lymphocytes proliferate and differentiate into effector CD4+ and CD8+ T cells that migrate from periphery into tumor sites aiming to eliminate cancer cells. Then while most effector T cells die, a small fraction persists and recirculates as long-lived memory T cells which generate enhanced immune responses when re-encountering the same antigen. A number of T (and non-T) cell subsets, stably resides in non-lymphoid peripheral tissues and may provide rapid immune response independently of T cells recruited from blood, against the reemergence of cancer cells. When tumor grows, however, tumor cells have evaded immune surveillance of effector cells (NK and CTL cells) which are exhausted, thus favoring the local expansion of T (and non-T) regulatory cells. In this review, the current knowledge of features of T cells present in the tumor microenvironment (TME) of solid adult and pediatric tumors, the mechanisms upregulating immune-checkpoint molecules and transcriptional and epigenetic landscapes leading to dysfunction and exhaustion of T effector cells are reviewed. The interaction of T cells with cancer- or TME non-neoplastic cells and their secreted molecules shape the T cell profile compromising the intrinsic plasticity of T cells and, therefore, favoring immune evasion. In this phase regulatory T cells contribute to maintain a high immunosuppressive TME thus facilitating tumor cell proliferation and metastatic spread. Despite the advancements of cancer immunotherapy, many tumors are unresponsive to immune checkpoint inhibitors, or therapeutical vaccines or CAR T cell-based adoptive therapy: some novel strategies to improve these T cell-based treatments are lastly proposed.

Galectin-1 overexpression induces normal fibroblasts translate into cancer-associated fibroblasts and attenuates the sensitivity of anlotinib in lung cancer

We aimed to investigate galectin-1 overexpression induces normal fibroblasts (NFs) translates into cancer-associated fibroblasts (CAFs). Galectin-1 overexpression was conducted in Human embryonic lung fibroblasts (HFL1) cell. The motilities of H1299 and A549 cells were measured. Human umbilical vein endothelial cell (HUVEC) proliferation and tube formation ability were assessed. Tumor volume and tumor weight was recorded. Cells motilities were increased, while apoptosis rates were decreased after CMs co-cultured. B-cell lymphoma-2 (Bcl-2) expression level was increased, while Bcl2-associatedX (Bax) and cleaved-caspase3 decreased. CMs treatment enhanced HUVEC proliferation and tube formation. Tumor volume and weight in CMs treated mice were increased, and the sensitivity of anlotinib in co-cultured cells was decreased. Our results revealed that galectin-1 overexpression induced NFs translated into CAFs.

Artificial intelligence (AI) for tumor microenvironment (TME) and tumor budding (TB) identification in colorectal cancer (CRC) patients: A systematic review

Evaluation of the parameters such as tumor microenvironment (TME) and tumor budding (TB) is one of the most important steps in colorectal cancer (CRC) diagnosis and cancer development prognosis. In recent years, artificial intelligence (AI) has been successfully used to solve such problems. In this paper, we summarize the latest data on the use of artificial intelligence to predict tumor microenvironment and tumor budding in histological scans of patients with colorectal cancer. We performed a systematic literature search using 2 databases (Medline and Scopus) with the following search terms: ("tumor microenvironment" OR "tumor budding") AND ("colorectal cancer" OR CRC) AND ("artificial intelligence" OR "machine learning " OR "deep learning"). During the analysis, we gathered from the articles performance scores such as sensitivity, specificity, and accuracy of identifying TME and TB using artificial intelligence. The systematic review showed that machine learning and deep learning successfully cope with the prediction of these parameters. The highest accuracy values in TB and TME prediction were 97.7% and 97.3%, respectively. This review led us to the conclusion that AI platforms can already be used as diagnostic aids, which will greatly facilitate the work of pathologists in detection and estimation of TB and TME as instruments and second-opinion services. A key limitation in writing this systematic review was the heterogeneous use of performance metrics for machine learning models by different authors, as well as relatively small datasets used in some studies.

Polyphenols as Immunomodulators and Epigenetic Modulators: An Analysis of Their Role in the Treatment and Prevention of Breast Cancer

Breast cancer poses a substantial health challenge for women globally. Recently, there has been a notable increase in scholarly attention regarding polyphenols, primarily attributed to not only the adverse effects associated with conventional treatments but also their immune-preventive impacts. Polyphenols, nature-derived substances present in vegetation, including fruits and vegetables, have received considerable attention in various fields of science due to their probable wellness merits, particularly in the treatment and hindrance of cancer. This review focuses on the immunomodulatory effects of polyphenols in breast cancer, emphasizing their capacity to influence the reaction of adaptive and innate immune cells within the tumor-associated environment. Polyphenols are implicated in the modulation of inflammation, the enhancement of antioxidant defenses, the promotion of epigenetic modifications, and the support of immune functions. Additionally, these compounds have been shown to influence the activity of critical immune cells, including macrophages and T cells. By targeting pathways involved in immune evasion, polyphenols may augment the capacity of the defensive system to detect and eliminate tumors. The findings suggest that incorporating polyphenol-rich foods into the diet could offer a promising, collaborative (integrative) approach to classical breast cancer remedial procedures by regulating how the defense mechanism interacts with the disease.

Integrative Bioinformatics Analysis and Experimental Study of NLRP12 Reveal Its Prognostic Value and Potential Functions in Ovarian Cancer

NLRP12 plays a significant role in cellular functional behavior and immune homeostasis, influencing inflammation, tumorigenesis, and prognosis. This study aimed to explore its specific effects on the tumor microenvironment (TME) and its contribution to heterogeneity in ovarian cancer (OV) through bioinformatics analysis and experimental verification. Utilizing various bioinformatics databases and clinical specimens, we investigated NLRP12 expression and its relationship with OV prognosis and immune infiltration. In vitro assays were conducted to assess the impact of NLRP12 on the proliferation and invasion of OV cells. Our findings indicate that NLRP12 is upregulated in OV, with high expression correlating with a negative prognosis. Furthermore, NLRP12 expression demonstrated a positive correlation with the infiltration of various immune cells and the expression of immune checkpoint molecules in OV. Analysis of The Cancer Immunome Atlas (TCIA) database revealed that OV patients with lower NLRP12 expression may exhibit an enhanced response to immunotherapy, particularly CTLA4 blockers, a finding validated in animal experiments. Additionally, the study emphasized the role of NLRP12 in influencing the prognosis of OV patients by promoting epithelial-mesenchymal transition (EMT) in ovarian cancer cells. Finally, we identified a potential therapeutic compound, Schisandrin B (Schi B), which decreases NLRP12 expression in ovarian cancer cells by binding to the transcription factor SPI1 associated with NLRP12. Our findings suggest that NLRP12 serves as a crucial immune-related biomarker predicting poor outcomes in OV, and targeting NLRP12 may represent a promising therapeutic approach for OV patients in the future.

IL7 as a Risk Factor for Prostate Cancer: Implications for T Cell Apoptosis and Infiltration in the Tumor Microenvironment

BACKGROUND

Prostate cancer's complex interplay with the immune microenvironment prompted an investigation into immune-related pathogenic mechanisms and potential therapeutic targets.

METHODS

Within the GSE176031 data set, Seurat meticulously dissected single-cell profiles from radical prostatectomy patients. Leveraging CellMarker and SingleR cell identities were precisely annotated. Then, monocle traced pseudotime trajectories, illuminating cellular paths, complemented by CellChat's insights into intricate intercellular communications. Furthermore, mendelian randomization (MR) robustly substantiated causal associations within prostate cancer contexts.

RESULTS

Employing single-cell analysis on intraoperative tumor and normal tissue, we identified 15 distinct cell types, notably observing a significant T cell reduction in tumor samples. Intercellular communication analysis revealed multiple pathways between epithelial cells and T cells, highlighting interleukin (IL)-IL7R-IL2RG interactions. IL7R, crucial in T cell apoptosis, showed differential expression across T cell development stages. Patients with IL7 amplification had poorer outcomes (p < 0.05), supported by MR in two cohorts (ieu-b-4809 cohort: odds ratio [OR] = 1.005, p = 0.002, 95% confidence interval [CI] [1.002-1.008]; ebi-a-GCST90018905: OR = 1.063, p = 0.032, 95% CI [1.005-1.125]), confirming IL7 as a prostate cancer risk factor.

CONCLUSIONS

These findings suggest T cell depletion via IL7-IL7R signaling may drive prostate cancer progression, offering novel therapeutic insights.

Agent-based modeling for the tumor microenvironment (TME)

Cancer is a disease that arises from the uncontrolled growth of abnormal (tumor) cells in an organ and their subsequent spread into other parts of the body. If tumor cells spread to surrounding tissues or other organs, then the disease is life-threatening due to limited treatment options. This work applies an agent-based model to investigate the effect of intra-tumoral communication on tumor progression, plasticity, and invasion, with results suggesting that cell-cell and cell-extracellular matrix (ECM) interactions affect tumor cell behavior. Additionally, the model suggests that low initial healthy cell densities and ECM protein densities promote tumor progression, cell motility, and invasion. Furthermore, high ECM breakdown probabilities of tumor cells promote tumor invasion. Understanding the intra-tumoral communication under cellular stress can potentially lead to the design of successful treatment strategies for cancer.

Correlation of the abundance of MDSCs, Tregs, PD-1, and PD-L1 with the efficacy of chemotherapy and prognosis in gastric cancer

OBJECTIVE

The aim of this study was to investigate the relationship between tumor microenvironment markers (myeloid-derived suppressor cells [MDSCs], regulatory T cells [Tregs], programmed cell death 1 [PD-1], and programmed death ligand 1 [PD-L1]) and chemotherapy efficacy and prognosis in advanced gastric cancer, identifying potential monitoring indicators.

METHODS

Advanced gastric cancer patients' MDSC and Treg expression was measured by flow cytometry pre- and postchemotherapy; PD-1 and PD-L1 expression in cancer tissues was assessed by immunohistochemistry. Correlations with chemotherapy outcomes and prognosis were analyzed.

RESULTS

Postchemotherapy reductions in MDSC and Treg levels correlated with chemotherapy efficacy (P <.01). Negative PD-1 and PD-L1 expression in cancer tissues predicted better chemotherapy responses (P <.01). Patients with lower MDSC and Treg levels and negative PD-1 and PD-L1 had significantly longer median progression-free survival (PFS) and overall survival (OS) (P <.05).

CONCLUSION

In advanced gastric cancer, reduced peripheral blood MDSC and Treg levels postchemotherapy and negative PD-1 and PD-L1 expression in tissues are associated with improved chemotherapy efficacy and are independent prognostic factors for PFS and OS.

KanCell: dissecting cellular heterogeneity in biological tissues through integrated single-cell and spatial transcriptomics

KanCell is a deep learning model based on Kolmogorov-Arnold networks (KAN) designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data. ST technologies provide insights into gene expression within tissue context, revealing cellular interactions and microenvironments. To fully leverage this potential, effective computational models are crucial. We evaluate KanCell on both simulated and real datasets from technologies such as STARmap, Slide-seq, Visium, and Spatial Transcriptomics. Our results demonstrate that KanCell outperforms existing methods across metrics like PCC, SSIM, COSSIM, RMSE, JSD, ARS, and ROC, with robust performance under varying cell numbers and background noise. Real-world applications on human lymph nodes, hearts, melanoma, breast cancer, dorsolateral prefrontal cortex, and mouse embryo brains confirmed its reliability. Compared to traditional approaches, KanCell effectively captures non-linear relationships and optimizes computational efficiency through KAN, providing an accurate and efficient tool for ST. By improving data accuracy and resolving cell type composition, KanCell reveals cellular heterogeneity, clarifies disease microenvironments, and identifies therapeutic targets, addressing complex biological challenges.

Cellular Therapies for Multiple Myeloma: Engineering Hope

Multiple myeloma (MM) treatment remains challenging due to its relapsed/refractory disease course as well as intra- and inter-patient heterogeneity. Cellular immunotherapies, especially chimeric antigen receptor (CAR)-T cells targeting B cell maturation antigen (BCMA), mark a major breakthrough, achieving long-lasting remissions and instilling hope for a potential cure. While ongoing clinical trials are increasingly driving approved cellular products towards earlier lines of therapy, novel targets as well as advanced approaches employing natural killer (NK) cells or dendritic cell (DC) vaccines are currently under investigation. Treatment resistance, driven by tumor-intrinsic factors such as antigen escape and the intricate dynamics of the tumor microenvironment (TME), along with emerging side effects such as movement and neurocognitive treatment-emergent adverse events (MNTs), are the major limitations of approved cellular therapies. To improve efficacy and overcome resistance, cutting-edge research is exploring strategies to target the microenvironment as well as synergistic combinatorial approaches. Recent advances in CAR-T cell production involve shortened manufacturing protocols and "off-the-shelf" CAR-T cells, aiming at decreasing socioeconomic barriers and thereby increasing patient access to this potential lifesaving therapy. In this review, we provide an extensive overview of the evolving field of cellular therapies for MM, underlining the potential to achieve long-lasting responses.

SLITRK2 as a prognostic and immunological biomarker in gastric cancer

BACKGROUND

SLIT and NTRK-like protein 2 (SLITRK2) encodes a transmembrane protein that regulates neurite outgrowth. Some studies have demonstrated that SLITRK2 overexpressed in glioma. But the expression pattern, prognostic value and immunologic function of SLITRK2 in tumors remains unknown.

METHODS

The expression pattern of SLITRK2 among pan-cancers was examined through the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). We analyzed the association between SLITRK2 expression level and tumor stage among pan-cancers. Kaplan-Meier survival analysis was utilized to investigate the prognostic relevance of SLITRK2 across 33 different types of cancers. Moreover, the correlations among SLITRK2 expression, immune cell infiltration, immunomodulatory related genes, tumor mutation burden (TMB), microsatellite instability (MSI) were evaluated. The relationship between SLITRK2 expression and crucial genes mutations was also illustrated. By using tissue microarray (TMA), the expression of SLITRK2 in 89 paired gastric cancer (GC) tissues was investigated.

RESULTS

Our study indicated that SLITRK2 expression varied across cancers. Elevated SLITRK2 expression was positively related to advanced tumor stage, poor overall survival (OS) and reduced disease-free survival (DFS). Bioinformatic analyses underscore SLITRK2's role in immune response, with its expression significantly tied to immune cell infiltration and marker expression. Based on TMA data, SLITRK2 expression level was positively associated with differentiation, lymph node metastasis, AJCC stage, TNM stage, and poor survival outcome in GC patients.

CONCLUSION

Our findings provided that SLITRK2 may function as a biomarker by regulating immune cell infiltration. In addition, we verified that high SLITRK2 expression was correlated with poor prognosis in GC.

Research trends, hotspots and future directions of tertiary lymphoid structures in cancer: a comprehensive informatics analysis and visualization study

Many studies have reported the presence of tertiary lymphoid structures (TLSs) in cancer, but the research progress of TLSs in cancer has not been systematically analyzed. Therefore, we analyzed the global scientific knowledge in the field using informatics methods. The results showed that TLSs in cancer have received increasing attention since the 21st century, with an annual publication growth rate of 27.86%. Unsupervised hierarchical clustering based on machine learning further categorized the research features into four clusters, with the cluster related to immunotherapy being considered an emerging cluster. TLSs and immunotherapy were identified as the top two hotspots with the highest occurrence frequency and total link strength. The Walktrap algorithm indicated that "TLSs, carcinoma, prognostic value" and "high endothelial venules, germinal-centers, node-like structures" are important to TLSs but remain underexplored, representing promising research directions. These findings suggest that cancer-related TLSs have brought new insights into antitumor immunity, and targeting TLSs has the potential to transform the landscape of antitumor immunotherapy.

Metabolic Reprogramming of Immune Cells in the Tumor Microenvironment

Metabolic reprogramming of immune cells within the tumor microenvironment (TME) plays a pivotal role in shaping tumor progression and responses to therapy. The intricate interplay between tumor cells and immune cells within this ecosystem influences their metabolic landscapes, thereby modulating the immune evasion tactics employed by tumors and the efficacy of immunotherapeutic interventions. This review delves into the metabolic reprogramming that occurs in tumor cells and a spectrum of immune cells, including T cells, macrophages, dendritic cells, and myeloid-derived suppressor cells (MDSCs), within the TME. The metabolic shifts in these cell types span alterations in glucose, lipid, and amino acid metabolism. Such metabolic reconfigurations can profoundly influence immune cell function and the mechanisms by which tumors evade immune surveillance. Gaining a comprehensive understanding of the metabolic reprogramming of immune cells in the TME is essential for devising novel cancer therapeutic strategies. By targeting the metabolic states of immune cells, it is possible to augment their anti-tumor activities, presenting new opportunities for immunotherapeutic approaches. These strategies hold promise for enhancing treatment outcomes and circumventing the emergence of drug resistance.

Cell Segmentation With Globally Optimized Boundaries (CSGO): A Deep Learning Pipeline for Whole-Cell Segmentation in Hematoxylin-and-Eosin-Stained Tissues

Accurate whole-cell segmentation is essential in various biomedical applications, particularly in studying the tumor microenvironment. Despite advancements in machine learning for nuclei segmentation in hematoxylin and eosin (H&E)-stained images, there remains a need for effective whole-cell segmentation methods. This study aimed to develop a deep learning-based pipeline to automatically segment cells in H&E-stained tissues, thereby advancing the capabilities of pathological image analysis. The Cell Segmentation with Globally Optimized boundaries (CSGO) framework integrates nuclei and membrane segmentation algorithms, followed by postprocessing using an energy-based watershed method. Specifically, we used the You Only Look Once (YOLO) object detection algorithm for nuclei segmentation and U-Net for membrane segmentation. The membrane detection model was trained on a data set of 7 hepatocellular carcinomas and 11 normal liver tissue patches. The cell segmentation performance was extensively evaluated on 5 external data sets, including liver, lung, and oral disease cases. CSGO demonstrated superior performance over the state-of-the-art method Cellpose, achieving higher F1 scores ranging from 0.37 to 0.53 at an intersection over union threshold of 0.5 in 4 of the 5 external datasets, compared to that of Cellpose from 0.21 to 0.36. These results underscore the robustness and accuracy of our approach in various tissue types. A web-based application is available at https://ai.swmed.edu/projects/csgo, providing a user-friendly platform for researchers to apply our method to their own data sets. Our method exhibits remarkable versatility in whole-cell segmentation across diverse cancer subtypes, serving as an accurate and reliable tool to facilitate tumor microenvironment studies. The advancements presented in this study have the potential to significantly enhance the precision and efficiency of pathologic image analysis, contributing to better understanding and treatment of cancer.

The role of neutrophils in osteosarcoma: insights from laboratory to clinic

Osteosarcoma, a highly aggressive malignant bone tumor, is significantly influenced by the intricate interactions within its tumor microenvironment (TME), particularly involving neutrophils. This review delineates the multifaceted roles of neutrophils, including tumor-associated neutrophils (TANs) and neutrophil extracellular traps (NETs), in osteosarcoma's pathogenesis. TANs exhibit both pro- and anti-tumor phenotypes, modulating tumor growth and immune evasion, while NETs facilitate tumor cell adhesion, migration, and immunosuppression. Clinically, neutrophil-related markers such as the neutrophil-to-lymphocyte ratio (NLR) predict patient outcomes, highlighting the potential for neutrophil-targeted therapies. Unraveling these complex interactions is crucial for developing novel treatment strategies that harness the TME to improve osteosarcoma management.

Causality Between Immune Cells, Metabolites and Breast Cancer: Mendelian Randomization and Mediation Analysis

Previous studies have shown that immune cells and metabolites are associated with the development of breast cancer, but the causal relationship is unclear. We use Mendelian randomization (MR) to explore potential connections between them. Based on two sample MR studies, we evaluated the causal relationship between 731 immune cell traits, 1400 metabolites and breast cancer. In addition, we evaluated the mediating role of metabolites between immune cells and breast cancer using two-step MR Studies. Pooled GWAS data on 731 immune cell traits (n = 3757), 1400 metabolites (n = 8299) and breast cancer (ncase = 122,977, ncontrol = 105,974) were obtained from publicly available authoritative databases. We mainly used inverse variance weighted (IVW) method combined with Bayesian weighted MR (BWMR), MR-Egger, weighted median, simple mode, and weighted mode methods. The results of MR Studies showed that 3 immune cells and 15 metabolites were associated with an increased risk of breast cancer. 8 immune cells and 11 metabolites are associated with a reduced risk of breast cancer. Mediating MR Analysis showed that 6 metabolites, Tricosanoyl sphingomyelin (d18:1/23:0) levels(Mediated proportion:17.5%), N-palmitoyl-heptadecasphingosine (d17:1/16:0) levels(8.74%), Inosine 5'-monophosphate (IMP) to phosphate ratio(11.3%), Glutamine to asparagine ratio(5.43%), Oleoyl-linoleoyl-glycerol (18:1/18:2) [2] levels(8.48%), and Sphinganine-1-phosphate levels(8.68%), were found to mediate the relationship between immune cells and breast cancer. Our study reveals a potential causal relationship among multiple immune cells traits, metabolites, and breast cancer. It provides valuable clues and potential therapeutic targets for breast cancer biomarker discovery and breast cancer treatment.

Sterile Alpha Motif Domain-Containing 5 Suppresses Malignant Phenotypes and Tumor Growth in Breast Cancer: Regulation of Polo-Like Kinase 1 and c-Myc Signaling in a Xenograft Model

Background Breast cancer, particularly the triple-negative breast cancer (TNBC) subtype, remains a significant clinical challenge due to its resistance to standard chemotherapy and high recurrence rate. In this study, we explored the role of Sterile Alpha Motif Domain-Containing 5 (SAMD5) as a potential regulatory partner with the c-Myc oncogenic signaling pathway in breast cancer. Materials and methods Functional assays were conducted to investigate the effects of SAMD5 overexpression on cell viability, colony formation, and invasive behavior in TNBC cell lines. This study further assessed the expression levels of proliferation and invasion markers, including Ki67 (a marker for cell proliferation), Matrix Metalloproteinase-2 (MMP2), and Matrix Metalloproteinase-9 (MMP9). Mechanistic analyses identified a negative correlation between SAMD5 and Polo-like Kinase 1 (PLK1), a gene frequently overexpressed in breast cancer, particularly in TNBC. The effects of PLK1 knockdown on cell viability, colony formation, and invasion were observed, along with the impact of PLK1 overexpression on SAMD5's inhibitory activity. In vivo studies were performed using a xenograft tumor model in nude mice to evaluate the impact of SAMD5 overexpression on tumor weight and volume. Results SAMD5 overexpression significantly reduced cell viability, colony formation, and invasion in TNBC cells, and downregulated key proteins in the c-Myc signaling pathway, including c-Myc itself, β-catenin, Cyclin-Dependent Kinase 4 (CDK4), Cyclin-Dependent Kinase 6 (CDK6), and Cyclin D1. PLK1 overexpression was found to counteract SAMD5's inhibitory effects. In vivo experiments demonstrated that SAMD5 overexpression led to a marked reduction in tumor weight and volume, effects that were partially reversed by PLK1 overexpression. Conclusions SAMD5 acts as a tumor suppressor in breast cancer, particularly in TNBC, by inhibiting critical cellular processes and downregulating the c-Myc signaling pathway. This effect appears to be mediated, in part, through its negative association with PLK1. Targeting the SAMD5/PLK1 axis offers a promising therapeutic strategy for addressing aggressive breast cancers.

TGF-β: an active participant in the immune and metabolic microenvironment of multiple myeloma : TGF-β in the microenvironment of multiple myeloma

Although substantial quantities of potent therapies for multiple myeloma (MM) have been established, MM remains an incurable disease. In recent years, our understanding of the initiation, development, and metastasis of cancers has made a qualitative leap. Cancers attain the abilities to maintain proliferation signals, escape growth inhibitors, resist cell death, induce angiogenesis, and more importantly, escape anti-tumor immunity and reprogram metabolism, which are the hallmarks of cancers. Besides, different cancers have different tumor microenvironments (TME), thus, we pay more attention to the TME in the pathogenesis of MM. Many researchers have identified that myeloma cells interact with the components of TME, which is beneficial for their survival, ultimately causing the formation of immunosuppressive and high-metabolism TME. In the process, transforming growth factor-β (TGF-β), as a pivotal cytokine in the TME, controls various cells' fates and influences numerous metabolic pathways, including inhibiting immune cells to infiltrate the tumors, suppressing the activation of anti-tumor immune cells, facilitating more immunosuppressive cells, enhancing glucose and glutamine metabolism, dysregulating bone metabolism and so on. Thus, we consider TGF-β as the tumor promoter. However, in healthy cells and the early stage of tumors, it functions as a tumor suppressor. Due to the effect of context dependence, TGF-β has dual roles in TME, which attracts us to further explore whether targeting it can overcome obstacles in the treatment of MM by regulating the progression of myeloma, molecular mechanisms of drug resistance, and various signaling pathways in the immune and metabolic microenvironment. In this review, we predominantly discuss that TGF-β promotes the development of MM by influencing immunity and metabolism.

Microdissected tumor cuboids: a microscale cancer model for large-scale testing that retains a complex tumor microenvironment

To bridge the gap between bench and bedside, there is a need for more faithful models of human cancers that can recapitulate key features of the human tumor microenvironment (TME) and simultaneously facilitate large-scale drug tests. Our recently developed microdissection method optimizes the yield of large numbers of cuboidal microtissues (″cuboids″, ~(400 µm) 3 ) from a tumor biopsy. Here we demonstrate that cuboids from syngeneic mouse tumor models and human tumors retain a complex TME, making them amenable for drug and immunotherapy evaluation. We characterize relevant TME parameters, such as cellular architecture, cytokine secretion, proteomics profiles, and response to drug panels in multi-well arrays. Despite the cutting procedure and the time spent in culture (up to 7 days), the cuboids display strong cytokine expression and drug responses, including to immunotherapy. Overall, our results suggest that cuboids could provide essential therapeutic information for personalized oncology applications and could help the development of TME-dependent therapeutics and cancer disease models, including for clinical trials.

ROS: A "booster" for chronic inflammation and tumor metastasis

Reactive oxygen species (ROS) are a group of highly active molecules produced by normal cellular metabolism and play a crucial role in the human body. In recent years, researchers have increasingly discovered that ROS plays a vital role in the progression of chronic inflammation and tumor metastasis. The inflammatory tumor microenvironment established by chronic inflammation can induce ROS production through inflammatory cells. ROS can then directly damage DNA or indirectly activate cellular signaling pathways to promote tumor metastasis and development, including breast cancer, lung cancer, liver cancer, colorectal cancer, and so on. This review aims to elucidate the relationship between ROS, chronic inflammation, and tumor metastasis, explaining how chronic inflammation can induce tumor metastasis and how ROS can contribute to the evolution of chronic inflammation toward tumor metastasis. Interestingly, ROS can have a "double-edged sword" effect, promoting tumor metastasis in some cases and inhibiting it in others. This article also highlights the potential applications of ROS in inhibiting tumor metastasis and enhancing the precision of tumor-targeted therapy. Combining ROS with nanomaterials strategies may be a promising approach to enhance the efficacy of tumor treatment.

Multifunctional gold nanoparticles for cancer theranostics

The diagnosis and treatment of cancer can often be challenging requiring more attractive options. Some types of cancers are more aggressive than others and symptoms for many cancers are subtle, especially in the early stages. Nanotechnology provides high sensitivity, specificity and multimodal capability for cancer detection, treatment and monitoring. In particular, metal nanoparticles (NPs) such as gold nanoparticles (AuNPs) are attractive nanosystems for researchers interested in bioimaging and therapy. The size, shape and surface of AuNPs can be modified for improving targeting and accumulation in cancer cells, for example through introduction of ligands and surface charge. The interactions of AuNPs with electromagnetic radiation (e.g., visible-near-infrared, X-rays) can be used for photothermal therapy and radiation therapy, through heat generated from light absorption and emission of Auger electrons, respectively. The subsequent expansion and high X-ray attenuation from AuNPs can be used for enhancing contrast for tumor detection (e.g., using photoacoustic, computed tomography imaging). Multi-functionality can be further extended through covalent/non-covalent functionalization, for loading additional imaging/therapeutic molecules for combination therapy and multimodal imaging. In order to cover the important aspects for designing and using AuNPs for cancer theranostics, this review focuses on the synthesis, functionalization and characterization methods that are important for AuNPs, and presents their unique properties and different applications in cancer theranostics.

Inhibition of Notch enhances efficacy of immune checkpoint blockade in triple-negative breast cancer

Aberrant Notch, which is a defining feature of triple-negative breast cancer (TNBC) cells, regulates intercellular communication in the tumor immune microenvironment (TIME). This includes tumor-associated macrophage (TAM) recruitment through Notch-dependent cytokine secretion, contributing to an immunosuppressive TIME. Despite the low response rate of TNBC to immune checkpoint blockade (ICB), here, we report that inhibition of Notch-driven cytokine-mediated programs reduces TAMs and induces responsiveness to sequentially delivered ICB. This is characterized by the emergence of GrB+ cytotoxic T lymphocytes (CTLs) in the primary tumor. A more impressive effect of sequential treatment is observed in the lung where TAM depletion and increased CTLs are accompanied by near-complete abolition of metastases. This is due to (i) therapeutic reduction in Notch-dependent, prometastatic circulating factors released by the primary tumor, and (ii) elevated PD ligand 1 (PD-L1) in lung metastases, rendering them profoundly sensitive to ICB. These findings highlight the potential of combination cytokine inhibition and ICB as an immunotherapeutic strategy in TNBC.

Revealing molecular mechanisms of early-onset tongue cancer by spatial transcriptomics

Tongue cancer at a young age demonstrates an increase in incidence, aggressiveness, and poor response to therapy. Classic etiological factors for head and neck tumors such as tobacco, alcohol, and human papillomavirus are not related to early-onset tongue cancer. Mechanisms of development and progression of this cancer remain unclear. In this study, we performed spatial whole-transcriptome profiling of tongue cancer in young adults compared with older patients. Nine patients with tongue squamous cell carcinoma (T2-3N0-1M0) were included and divided into two groups: younger (n = 5) and older than 45 years (n = 4). Formalin-fixed paraffin-embedded (FFPE) and fresh frozen (FF) samples of tumor tissue from 4 young and 5 older patients, respectively, were used for spatial transcriptomic profiling using the 10 × Genomics Visium. The findings were validated using SeekGene single cell full-length RNA sequencing (1 young vs 1 older patient) and TCGA data (15 young vs 70 older patients). As a result, we performed the first successful integration of spatial transcriptomics data from FF and FFPE samples and revealed distinctive features of tongue cancer in young adults. Oxidative stress, vascular mimicry, and MAPK and JAK-STAT pathways were enriched in early-onset tongue cancer. Tumor microenvironment demonstrated increased gene signatures corresponding to myeloid-derived suppressor cells, tumor-associated macrophages, and plasma cells. The invasive front was accompanied by vascular mimicry with arrangement of tumor-associated macrophages and aggregations of plasma cells and lymphocytes organized into tertiary lymphoid structures. Taken together, these results indicate that early-onset tongue cancer has distinct transcriptomic features and molecular mechanisms compared to older patients.

The influence of biophysical niche on tumor-associated macrophages in liver cancer

HCC, the most common type of primary liver cancer, is a leading cause of cancer-related mortality worldwide. Although the advancement of immunotherapies by immune checkpoint inhibitors (ICIs) that target programmed cell death 1 or programmed cell death 1-ligand 1 has revolutionized the treatment for HCC, the majority is still not beneficial. Accumulating evidence has pointed out that the potent immunosuppressive tumor microenvironment in HCC poses a great challenge to ICI therapeutic efficacy. As a key component in tumor microenvironment, tumor-associated macrophages (TAMs) play vital roles in HCC development, progression, and ICI low responsiveness. Mechanistically, TAM can promote cancer invasion and metastasis, angiogenesis, epithelial-mesenchymal transition, maintenance of stemness, and most importantly, immunosuppression. Targeting TAMs, therefore, represents an opportunity to enhance the ICI therapeutic efficacy in patients with HCC. While previous research has primarily focused on biochemical cues influencing macrophages, emerging evidence highlights the critical role of biophysical signals, such as substrate stiffness, topography, and external forces. In this review, we summarize the influence of biophysical characteristics within the tumor microenvironment that regulate the phenotype and function of TAMs in HCC pathogenesis and progression. We also explore the possible mechanisms and discuss the potential of manipulating biophysical cues in regulating TAM for HCC therapy. By gaining a deeper understanding of how macrophages sense and respond to mechanical forces, we may potentially usher in a path toward a curative approach for combinatory cancer immunotherapies.

Advancements in nanotheranostics for glioma therapy

Gliomas are brain tumors mainly derived from glial cells that are difficult to treat and cause high mortality. Radiation, chemotherapy, and surgical excision are the conventional treatments for gliomas. Patients who have surgery or have undergone chemotherapy for glioma treatment have poor prognosis with tumor recurrence. In particular, for glioblastoma, the 5-year average survival rate is 4-7%, and the median survival is 12-18 months. A number of issues hinder effective treatment such as, poor surgical resection, tumor heterogeneity, insufficient drug penetration across the blood-brain barrier, multidrug resistance, and difficulties with drug specificity. Nanotheranostic-mediated drug delivery is becoming a well-researched consideration, and an efficient non-invasive method for delivering chemotherapeutic drugs to the target area. Theranostic nanomedicines, which incorporate therapeutic drugs and imaging agents for personalized therapies, can be used for preventing overdose of non-responders. Through the identification of massive and complicated information from next-generation sequencing, machine learning enables for precise prediction of therapeutic outcomes and post-treatment management for patients with cancer. This article gives a thorough overview of nanocarrier-mediated drug delivery with a brief introduction to drug delivery challenges. In addition, this assessment offers a current summary of preclinical and clinical research on nanomedicines for gliomas. In the future, nanotheranostics will provide personalized treatment for gliomas and other treatable cancers.

Piezo1: the key regulators in central nervous system diseases

The occurrence and development of central nervous system (CNS) diseases is a multi-factor and multi-gene pathological process, and their diagnosis and treatment have always posed a serious challenge in the medical field. Therefore, exploring the relevant factors in the pathogenesis of CNS and improving the diagnosis and treatment rates has become an urgent problem. Piezo1 is a recently discovered mechanosensitive ion channel that opens in response to mechanical stimuli. A number of previous studies have shown that the Piezo channel family plays a crucial role in CNS physiology and pathology, especially in diseases related to CNS development and mechanical stimulation. This article comprehensively describes the biological properties of Piezo1, focuses on the potential association between Piezo1 and CNS disorders, and explores the pharmacological roles of Piezo1 agonists and inhibitors in treating CNS disorders.

Prognostic value of neutrophil to lymphocyte ratio for patients with bladder cancer undergoing radical cystectomy: a systematic review and meta-analysis

Objectives

This study evaluated the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for survival outcomes in bladder cancer patients treated with radical cystectomy.

Methods

Studies assessing NLR's prognostic significance for bladder cancer after radical cystectomy were identified from PubMed, Embase, Web of Science, and Cochrane databases until April 2024. Survival outcomes analyzed included overall survival (OS), disease-free survival (DFS), relapse-free survival (RFS), cancer-specific survival (CSS), and progression-free survival (PFS).

Results

The meta-analysis comprised 15 cohort studies with 8,448 patients. Multivariate analysis showed significantly shorter OS, CSS, DFS, and RFS in the high NLR group compared to the low NLR group. However, no significant difference in PFS was observed between the groups.

Conclusions

NLR serves as an independent prognostic indicator for bladder cancer patients undergoing radical cystectomy, with elevated NLR associated with poorer survival. Further large-scale, prospective studies are warranted to validate the relationship between NLR and prognosis in bladder cancer.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024549573.