Revealing the transcriptional heterogeneity of organ-specific metastasis in human gastric cancer using single-cell RNA Sequencing

Role of m7G modification regulators as biomarkers in gastric cancer subtyping and precision immunotherapy

This study investigated the role of N7-methylguanosine (m7G) modification regulators as biomarkers in subtyping and precision immunotherapy of gastric cancer (GC). Through multi-omics analyses, including RNA sequencing, proteomics, and single-cell measurement, the study revealed heterogeneity in the m7G regulatory landscape among GC patients. Three m7G subtypes were identified, each with distinct pathways and phenotypes. Patients with low m7Gscores, based on an established scoring system, showed better survival outcomes and increased antitumor immune cell infiltration, as well as higher tumor mutation loads and lower PD-L1 expression. The predictive value of m7Gscore was confirmed in two immunotherapy cohorts. These findings highlight the potential of m7G modification in shaping the tumor microenvironment and provide new insights for immunotherapeutic strategies in GC patients.

Single-cell sequencing reveals PHLDA1-positive smooth muscle cells promote local invasion in head and neck squamous cell carcinoma

BACKGROUND

Smooth muscle cells within the tumor microenvironment play a crucial role in cancer progression. However, their involvement in the local invasion of head and neck squamous cell carcinoma remains poorly understood. In this research, we aim to investigate the role of smooth muscle cells-mediated cell interactions in facilitating the local invasion of head and neck squamous cell carcinoma.

METHODS

Single-cell sequencing data from the public databases GSE164690 and GSE181919 were utilized to identify a specific smooth muscle cells cluster. Smooth muscle cells were isolated from tumor microenvironment of head and neck squamous cell carcinoma. PHLDA1 expression in smooth muscle cells was assessed through immunofluorescence staining. The role of THBS1 was investigated through in vitro studies.

RESULTS

PHLDA1-positive smooth muscle cells were significantly enriched in head and neck squamous cell carcinoma. PHLDA1 promoted the expression of THBS1 in smooth muscle cells. In vitro, THBS1 facilitated head and neck squamous cell carcinoma migration and invasion through SDC1 receptor.

CONCLUSION

PHLDA1-positive smooth muscle cells play a critical role in head and neck squamous cell carcinoma invasion through THBS1. Targeting PHLDA1-positive smooth muscle cells or THBS1 may offer a promising therapeutic approach for head and neck squamous cell carcinoma treatment.

NR2F2 and its contribution to lymph node metastasis in oral squamous cell carcinoma

OBJECTIVES

To investigate the role of cancer stem cells (CSCs) in lymph node metastasis (LNM) of oral squamous cell carcinoma (OSCC), focusing on the expression and biological significance of nuclear receptor subfamily 2 group F member 2 (NR2F2).

METHODS

Single-cell RNA sequencing data from OSCC patients were analyzed using the CytoTRACE algorithm to assess stemness. Gene set scores were calculated with the irGSEA and GSVA R packages. GO and KEGG analyses identified enriched pathways. NR2F2 and CD44 expression in OSCC and lymph nodes (LNs) were validated via immunohistochemistry and immunofluorescence. NR2F2/Nr2f2 overexpression and knockdown cell lines were established, with stemness markers confirmed by Western blot. Functional assays evaluated stemness, proliferation, migration, and invasion capabilities of OSCC cells. In vivo experiments evaluated the ability of NR2F2 to promote tumor growth and metastasis. Bulk RNA sequencing and drug sensitivity analyses explored NR2F2-related mechanisms and drug responses.

RESULTS

CSCs in OSCC were divided into five subgroups, with NR2F2 identified as the key gene in CSC4, the subgroup with the highest stemness, and found to be overexpressed in metastatic LNs. Immunohistochemistry showed NR2F2 overexpression in OSCC, associated with LNM. Immunofluorescence confirmed co-expression of NR2F2 and CD44 in metastatic OSCC and LNs. Overexpression of NR2F2 enhanced stemness, proliferation, and migration of OSCC cells. In vivo experiments showed that NR2F2 promoted the growth and LNM of OSCC. Bulk RNA sequencing revealed that NR2F2 is involved in multiple pathways and plays a role in LNM. Trametinib was identified as a sensitive drug.

CONCLUSION

NR2F2 is associated with the maintenance of tumor stemness and may influence LNM in OSCC by promoting tumor cell proliferation and migration.

COL1A1-positive endothelial cells promote gastric cancer progression via the ANGPTL4-SDC4 axis driven by endothelial-to-mesenchymal transition

Gastric cancer (GC) is an aggressive and heterogeneous disease with poor survival outcomes. The progression of GC involves complex, multi-step processes. Endothelial cells (ECs) play a crucial role in tumor angiogenesis, proliferation, invasion, and metastasis, particularly through the process of endothelial-to-mesenchymal transition (EndoMT). However, the specific role and mechanisms of EndoMT in gastric cancer remain unclear. Based on 6 GC single-cell RNA-sequencing (scRNA-seq) cohorts (samples = 97), we established an EndoMT-related gene signature, termed EdMTS. Leveraging this gene signature, ssGSEA was applied to calculate sample scores across multiple bulk RNA-seq datasets, which include information on immunotherapy, metastasis, GC progression, and survival. Moreover, we applied the Monocle2 method to calculate cell pseudotime and used CellChat to analyze interactions between malignant and EC cells. We verified the molecular mechanism by multiple immunofluorescence and cell function experiments. Findings In this study, we established a single-cell atlas of ECs in GC and identified a subpopulation of COL1A1+ ECs that play a critical role in tumor progression and metastasis. These COL1A1+ ECs were significantly associated with worse clinical outcomes in GC patients. Further analysis revealed that COL1A1+ ECs originated from lymphatic ECs and underwent EndoMT through the upregulation of CEBPB, driving tumor invasiveness. Moreover, COL1A1+ ECs interacted with malignant cells via ANGPTL4-SDC4 axis, enhancing invasion and migration. These findings provide a deeper understanding of the role of COL1A1+ ECs in GC progression and highlight potential therapeutic targets for disrupting the EndoMT process in these cells to provide a benefit for GC patients.

PTPRG-AS1 regulates the KITLG/KIT pathway through the ceRNA axis to promote the malignant progression of gastric cancer and the intervention effect of Compound Kushen injection on it

Gastric cancer (GC) is a common malignant tumor with high mortality, recurrence, and metastasis rates. Compound Kushen injection (CKI) combination chemotherapy has been clinically used for the treatment of GC in China for many years, but its underlying mechanisms of action remain unclear. Recent reports have highlighted the important role of the competing endogenous RNA (ceRNA) mechanism of noncoding RNA (ncRNA) and messenger RNA (mRNA) formation in GC and other tumors. This study aimed to investigate the effects of CKI on GC from the ceRNA perspective. We confirmed the inhibitory effect of CKI on GC in mouse models and cell lines. By examining the GC cell lines sensitive to CKI treatment, we developed the CNScore method to analyze the ceRNA network, revealing that the CKI-GC ceRNA network promotes GC proliferation and metastasis through the PTPRG-AS1/hsa-miR-421/KITLG axis. Finally, we constructed GC cell models with PTPRG-AS1 overexpression or knockdown and GC liver metastasis models and found that PTPRG-AS1 can sponge hsa-miR-421, releasing KITLG and promoting GC proliferation and metastasis through the KITLG/KIT pathway. Taken together, CKI can suppress these malignant phenotypes by regulating the PTPRG-AS1/hsa-miR-421/KITLG axis.

Novel molecular mechanisms of immune evasion in hepatocellular carcinoma: NSUN2-mediated increase of SOAT2 RNA methylation

BACKGROUND

Hepatocellular carcinoma (HCC) is a deadly malignancy known for its ability to evade immune surveillance. NOP2/Sun RNA methyltransferase family member 2 (NSUN2), an RNA methyltransferase involved in carcinogenesis, has been associated with immune evasion and energy metabolism reprogramming. This study aimed to examine the molecular mechanisms underlying the involvement of NSUN2 in immune evasion and metabolic reprogramming of HCC.

METHODS

Single-cell transcriptomic sequencing was applied to examine cellular composition changes, particularly immune cell dynamics, in HCC and adjacent normal tissues. Bulk RNA-seq and proteomics identified key genes and proteins. Methylation sequencing and methylated RNA immunoprecipitation (MeRIP) were carried out to characterize the role of NSUN2 in 5-methylcytosine (m5C) modification of sterol O-acyltransferase 2 (SOAT2). Clinical samples from 30 HCC patients were analyzed using reverse transcription-quantitative polymerase chain reaction and Western blotting. Gene expression was manipulated using CRISPR/Cas9 and lentiviral vectors. In vitro co-culture models and metabolomics were used to study HCC cell-T cell interactions, energy metabolism, and immune evasion. Tumor growth in an orthotopic mouse model was monitored by bioluminescence imaging, with subsequent measurements of tumor weight, volume, and immunohistochemical staining.

RESULTS

Single-cell transcriptomic analysis identified a marked increase in malignant cells in HCC tissues. Cell communication analysis indicated that tumor cells might promote cancer progression by evading immune clearance. Multi-omics analyses identified NSUN2 as a key regulator in HCC development. MeRIP confirmed that NSUN2 facilitated the m5C modification of SOAT2. Analysis of human HCC tissue samples demonstrated pronounced upregulation of NSUN2 and SOAT2, along with elevated m5C levels in HCC tissues. In vitro experiments uncovered that NSUN2 augmented the reprogramming of energy metabolism and repressed the activity and cytotoxicity of CD8+ T cells, contributing to immune evasion. In vivo studies further substantiated the role of NSUN2 in fostering immune evasion and tumor formation of HCC by modulating the m5C modification of SOAT2.

CONCLUSIONS

The findings highlight the critical role of NSUN2 in driving HCC progression through the regulation of m5C modification on SOAT2. These findings present potential molecular markers for HCC diagnosis and therapeutic targets for its treatment.

Comprehensive bioinformatics analysis identified HMGB3 as a promising immunotherapy target for glioblastoma multiforme

OBJECTIVE

Glioblastoma multiforme (GBM) presents significant therapeutic challenges due to its heterogeneous tumorigenicity, drug resistance, and immunosuppression. Although several molecular markers have been developed, there still lack of sensitive molecular for accurately detection. Studying the mechanisms underlying the development of GBM and finding relevant prognostic biomarkers remains crucial.

METHODS

Single-cell RNA sequencing, bulk RNA-seq, and cancer immune cycle activities of GBM were used to assess the expression of different molecular related to GBM. Bioinformatics analyses were carried to evaluate the functional of the high mobility group protein B3 (HMGB3) in GBM.

RESULTS

HMGB3 was highly expressed in GBM tissues and influenced the interpatient and intratumoral transcriptomic heterogeneity as well as immunosuppression in GBM. HMGB3 also contributes to a no inflamed tumor microenvironment (TME) and has an inhibitory effect on tumor-associated immune cell infiltration. Besides, HMGB3 participated GBM chemotherapeutic sensitivity and negative correlation with 140 medicines.

CONCLUSION

HMGB3 as a heterogeneous and immunosuppressive molecule in the GBM TME, making it a potential target for precision therapy for GBM.

Zn‐DHM Nanozymes Enhance Muscle Regeneration Through ROS Scavenging and Macrophage Polarization in Volumetric Muscle Loss Revealed by Single‐Cell Profiling

Volumetric muscle loss (VML) is a severe condition in which the loss of skeletal muscle surpasses the body's intrinsic repair capabilities, leading to irreversible functional deficits and potential disability, with persistent inflammation and impaired myogenic differentiation. To address these challenges, a novel zinc‐dihydromyricetin (Zn‐DHM) nanozyme with superoxide dismutase (SOD)‐like activity is developed, designed to neutralize excessive reactive oxygen species (ROS) and restore oxidative balance. Zn‐DHM mitigates oxidative stress and promotes polarization of macrophages from the proinflammatory M1 phenotype to the anti‐inflammatory M2 phenotype, thereby reducing chronic inflammation and creating a conducive environment for muscle repair. Further, Zn‐DHM significantly enhances the myogenic differentiation of C2C12 cells, accelerating wound healing processes. These studies confirm the biosafety and low toxicity of Zn‐DHM. As per a murine tibialis anterior VML model, Zn‐DHM effectively suppresses inflammation and markedly improves skeletal muscle repair outcomes. Single‐cell RNA sequencing reveals that Zn‐DHM treatment increases the expression of M2 macrophage markers and enhances the proliferation and differentiation capacity of muscle stem cells (MuSCs). In addition, intercellular communication analysis reveals interactions between MuSCs and macrophages in the Zn‐DHM treatment group, suggesting that these interactions may drive tissue regeneration through the activation of the GAS and Notch signaling pathways.

Recursive Clustering of Cellular Diversity in scRNA-Seq Data

In scRNA-seq analysis, cell clusters are typically defined by a single round of feature extraction and clustering. This approach may miss phenotypic differences in cell types that are characterized by genes not sufficiently represented in the feature set derived using all cells, such as rare cell types. This work explores an alternative approach, where cell clusters are identified by recursively performing feature extraction and clustering on previously identified clusters, such that each subclustering step uses features that are more specific to distinguishing the higher-resolution subclusters. We benchmark this recursive approach against the conventional, nonrecursive clustering approach and demonstrate that the recursive method results in robust improvement in cell type detection on four scRNA-seq datasets across a wide range of clustering resolution parameters. We apply the recursive approach to cluster scRNA-seq data obtained from patients with Crohn's disease belonging to three clinical phenotypes and observe that recursive clustering captures phenotypic differences only visible at specific levels of granularity within an interpretable hierarchical framework while defining cell clusters within a gene expression feature space more specific to each cluster.

Identification and validation of mitochondrial endoplasmic reticulum membrane-related genes in atherosclerosis

The mitochondria-associated endoplasmic reticulum membrane is implicated in atherosclerosis (AS). However, its precise molecular mechanisms remain undefined. This study identified KLRC1 and SOCS2 as key protective genes against AS through transcriptomic analysis integrated with Mendelian randomization. Both genes exhibited significantly reduced expression in the AS group. Immune infiltration analysis revealed a strong positive correlation between activated CD8+ T cells and these genes, while eosinophils displayed the most pronounced negative correlation with KLRC1, and regulatory T cells exhibited the strongest negative association with SOCS2. Notably, SOCS2 emerged as a pivotal protective factor, offering novel insights into AS pathogenesis and providing a robust theoretical foundation for early diagnosis and potential therapeutic strategies.

Integrative analysis of bulk and single-cell sequencing reveals TNFSF9 as a potential regulator in microsatellite instability stomach adenocarcinoma

BACKGROUND

Stomach adenocarcinoma (STAD) with microsatellite instability (MSI) is associated with a better prognosis compared to Non-MSI. This study aims to elucidate the differences in the tumor microenvironment (TME) of MSI and explore its underlying mechanisms in STAD.

METHODS

TME differences between MSI and Non-MSI were analyzed using single-cell RNA sequencing (MSI = 7, Non-MSI = 19) and bulk RNA sequencing (MSI = 39, Non-MSI = 198). Differentially expressed genes (DEGs) were used to identify enriched pathways and hub genes. TNFSF9 expression was validated by immunohistochemistry (IHC) on 23 STAD sections (MSI = 13, Non-MSI = 10) and confirmed in tumor epithelial cells using SNU-1 (MSI) and AGS (Non-MSI) cell lines through quantitative polymerase chain reaction (qPCR) and Western blot (WB).

RESULTS

The results showed MSI was significantly associated with a better prognosis (P < 0.05). Within the TME, MSI was associated with a higher abundance of antigen-presenting cells, including M1 macrophages (40.1% vs. 27.9%) and activated dendritic cells (22.1% vs. 10.5%), as well as pro-inflammatory Th1-like CD4⁺ T cells (15% vs. 11%). However, MSI also showed an increase in exhausted T cells, indicating a complex immune landscape. Signaling pathway and cell communication analyses revealed an enrichment of cytokine-related pathways in MSI. Hub gene analysis revealed that TNFSF9 was predominantly expressed in stromal cells and partially in tumor epithelial cells in MSI, with its upregulation further confirmed through IHC, qPCR, and WB. Correlation analysis demonstrated a positive relationship between TNFSF9 expression and the abundance of M1 macrophages.

CONCLUSIONS

These findings provide new insights into the TME of MSI in STAD, emphasizing the significant role of TNFSF9 in shaping MSI-specific TME, enhancing immunotherapy efficacy, and improving patient survival.

Targeting both the enzymatic and non-enzymatic functions of DHODH as a therapeutic vulnerability in c-Myc-driven cancer

c-Myc (Myc)-driven cancers exhibit aggressive phenotypes and therapeutic resistance. Here, integrating CRISPR-Cas9 screening, we identify dihydroorotate dehydrogenase (DHODH) as a promising target in Myc-driven cancer. Mechanistically, DHODH interacts with Myc to stabilize it independently of its enzymatic activity, thereby antagonizing SKP2-mediated polyubiquitination and proteasomal degradation. EN4, a Myc transcriptional activity inhibitor, disrupts DHODH-Myc interaction, promoting Myc degradation via SKP2. Additionally, Myc transcriptionally activates DHODH, enhancing pyrimidine biosynthesis and ferroptosis defense, processes dependent on DHODH enzymatic activity. Clinically, DHODH positively correlates with Myc, activating pyrimidine metabolism and ferroptosis defense in Myc-driven cancers. Hyperactivation of the DHODH-Myc axis is linked to colorectal cancer progression and poor prognosis. Therapeutically, combining EN4 with a DHODH enzymatic inhibitor demonstrates potent antitumor efficacy in Myc-driven colorectal cancer. Overall, our findings elucidate the metabolic and non-metabolic roles of DHODH in Myc-driven cancer, underscoring its dual potential as a therapeutic target addressing both enzymatic and non-enzymatic functions.

Single-cell RNA sequencing and spatial transcriptomics reveal the heterogeneity and intercellular communication of cancer-associated fibroblasts in gastric cancer

BACKGROUND

Gastric cancer is a highly aggressive malignancy characterized by a complex tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are a key component of the TME, exhibit significant heterogeneity and play crucial roles in tumor progression. Therefore, a comprehensive understanding of CAFs is essential for developing novel therapeutic strategies for gastric cancer.

METHODS

This study investigates the characteristics and functional information of CAF subtypes and explores the intercellular communication between CAFs and malignant epithelial cells (ECs) in gastric cancer by analyzing single-cell sequencing data from 24 gastric cancer samples. CellChat was employed to map intercellular communication, and Seurat was used to integrate single-cell sequencing data with spatial transcriptome data to reconstruct a comprehensive single-cell spatial map. The spatial relationship between apCAFs and cancer cells was analyzed using multicolor immunohistochemistry.

RESULTS

Cells were categorized into nine distinct categories, revealing a positive correlation between the proportions of epithelial cells (ECs) and fibroblasts. Furthermore, six fibroblast subpopulations were identified: inflammatory (iCAFs), pericytes, matrix (mCAFs), antigen-presenting (apCAFs), smooth muscle cells (SMCs), and proliferative CAFs (pCAFs). Each of these subpopulations was linked to various biological processes and immune responses. Malignant ECs exhibited heightened intercellular communication, particularly with CAF subpopulations, through specific ligand-receptor interactions. High-density regions of CAF subpopulations displayed spatial exclusivity, with pericytes serving as a source for iCAFs, mCAFs, and apCAFs. Notably, malignant ECs and apCAFs showed increased interactions, with certain ligand-receptor pairs potentially impacting the prognosis of gastric cancer. Multiplex immunohistochemistry (mIHC) confirmed the close spatial proximity of apCAFs to cancer cells in gastric cancer.

CONCLUSION

Our study provided a comprehensive characterization of CAF heterogeneity in gastric cancer and revealed the intricate intercellular networks within the TME. The identified CAF subpopulations and their interactions with malignant cells could serve as potential therapeutic targets.

New insights into cancer immune checkpoints landscape from single-cell RNA sequencing

Immune checkpoint blockade (ICB) therapy represents a pivotal advancement in tumor immunotherapy by restoring the cytotoxic lymphocytes' anti-tumor activity through the modulation of immune checkpoint functions. Nevertheless, many patients experience suboptimal therapeutic outcomes, likely due to the immunosuppressive tumor microenvironment, drug resistance, and other factors. Single-cell RNA sequencing has assisted to precisely investigate the immune infiltration patterns before and after ICB treatment, enabling a high-resolution depiction of previously unrecognized functional interaction among immune checkpoints. This review addresses the heterogeneity between tumor microenvironments that respond to or resist ICB therapy, highlighting critical factors underlying the variation in immunotherapy efficacy and elucidating treatment failure. Furthermore, a comprehensive examination is provided of how specific ICBs modulate immune and tumor cells to achieve anti-tumor effects and generate treatment resistance, alongside a summary of emerging immune checkpoints identified as promising targets for cancer immunotherapy through single-cell RNA sequencing applications.

A dataset of single-cell transcriptomic atlas of Bama pig and potential marker genes across seven tissues

The use of single-cell sequencing technology for single-cell transcriptomics studies in pigs is expanding progressively. However, the comprehensive classification of cell types across different anatomical tissues and organs of pig in multiple datasets remains relatively limited. This study employs single-cell and single-nucleus sequencing technologies in Bama pig to identify unique marker genes and their corresponding transcriptomic profiles across diverse cell types in various anatomical tissues and organs, including subcutaneous fat, visceral fat, psoas major muscle, liver, spleen, lung, and kidney. Through detailed data analyses, we observed widespread cellular diversity across various anatomical tissues and organs of Bama pig. This work contributes a comprehensive dataset that supports physiological studies and aids in the identification and prediction of potential marker genes through single-cell transcriptomics of these tissues. The methodologies and data employed in this study are designed to improve the accuracy of cell type identification and ensure consistent cell type allocation.

Exposing the cellular situation: findings from single cell RNA sequencing in breast cancer

Background

Breast Cancer (BC) ranks among the top three most prevalent cancers globally and stands as the principal contributor to cancer-related fatalities among women. In spite of the substantial occurrence rate of BC, the early stage of this disease is generally regarded as curable. However, intra-tumor heterogeneity presents a formidable obstacle to the success of effective treatment.

Method

In this research, single cell RNA sequencing was utilized to dissect the tumor microenvironment within BC. Slingshot, CytoTRACE and Monocle 2 were applied to illustrate the differentiation process of each subpopulation in the pseudotime sequence. To comprehensively comprehend the tumor cells (TCs) in BC, an analysis of upstream transcription factors was carried out via pySCENIC, while downstream pathway enrichment was conducted through KEGG, GO and GSEA. The prognosis model was established based on the bulk data obtained from TCGA and GEO databases. Knock-down experiments were also implemented to explore the function of the transcription factor CEBPD in the TCs.

Results

Our in-depth analysis identified eight principal cell types. Notably, TCs were predominantly found within epithelial cells. The classification of TCs further uncovered five unique subpopulations, with one subpopulation characterized by high UGDH expression. This subpopulation was shown to possess distinct metabolic features in metabolism-related investigations. The intricate communication modalities among different cell types were effectively demonstrated by means of CellChat. Additionally, a crucial transcription factor, CEBPD, was identified, which demonstrated a pronounced propensity towards tumors and harbored potential tumor-advancing characteristics. Its role in promoting cancer was subsequently verified through in vitro knock-down experiments. Moreover, a prognostic model was also developed, and a risk score was established based on the genes incorporated in the model. Through comparing the prognoses of different UTRS levels, it was determined that the group with a high UTRS had a less favorable prognosis.

Conclusion

These outcomes contributed to the elucidation of the complex interrelationships within the BC tumor microenvironment. By specifically targeting certain subpopulations of TCs, novel treatment strategies could potentially be devised. This study shed light on the direction that future research in BC should take, furnishing valuable information that can be utilized to enhance treatment regimens.

Blood TCTP as a potential biomarker associated with immunosuppressive features and poor clinical outcomes in metastatic gastric cancer

BACKGROUND

No established biomarker exists for specific myeloid cell populations or in gastric cancer. This study aimed to explore the prognostic and immunological relevance of plasma translationally controlled tumor protein (TCTP) in patients with advanced gastric cancer treated with an immune checkpoint inhibitor and/or cytotoxic chemotherapy.

METHODS

Plasma samples were prospectively collected from the cohorts of patients with gastric cancer treated with first-line fluoropyrimidine plus platinum chemotherapy (n=143, cohort 1) and third-line nivolumab (n=165, cohort 2). Plasma TCTP levels were quantified using ELISA, and multiplex proteomic analysis (Olink) was conducted to assess expression levels of immune-related proteins. External single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics datasets were employed to validate the findings.

RESULTS

Patients with high plasma TCTP levels (TCTP-high group) exhibited poor progression-free survival (PFS) and overall survival (OS) with first-line chemotherapy compared with those with low levels (TCTP-low group) in cohort 1 (HR: 1.73 for PFS; 1.77 for OS). In the TCTP-high group, proteins associated with immunosuppressive myeloid cells, angiogenesis, and immune exclusion of T/natural killer (NK) cell function were upregulated, whereas proteins involved in T-cell activation/exhaustion were significantly upregulated in the TCTP-low group. scRNA-seq analyses identified a myeloid subset with high TPT1 (encoding TCTP) expression and TCTP-related molecules, enriched with inhibitory myeloid inflammation gene signatures and providing inhibitory signals to T/NK cells (Macrophage-chemokine). Spatial transcriptomics analyses revealed a tumor-cell-enriched cluster co-localized with the Macrophage-chemokine subset, which exhibited the highest TPT1 expression and a positive correlation between its abundance and average TPT1 levels. In nivolumab-treated patients (cohort 2), the high TCTP group was associated with poor survival outcomes (HR: 1.39 for PFS; 1.47 for OS).

CONCLUSIONS

Plasma TCTP is a prognostic biomarker, reflecting clinically relevant immunosuppressive myeloid signals in patients with gastric cancer.

YTHDF2-mediated m6A modification of ONECUT2 promotes stemness and oxaliplatin resistance in gastric cancer through transcriptionally activating TFPI

AIMS

Chemoresistance results in poor outcomes of patients with gastric cancer (GC). This study aims to identify oxaliplatin resistance-related cell subpopulations in the tumor microenvironment (TME) and decipher the involved molecular mechanisms.

METHODS

Through single-cell RNA sequencing, a unique ONECUT2+TFPI+ GC cell subset was identified in the oxaliplatin-resistant TME. The functional roles and molecular mechanisms of ONECUT2 in oxaliplatin resistance were investigated in cellular and mouse models. Therapeutic efficacy of small molecule inhibitor of ONECUT2 was also evaluated.

RESULTS

The abundance of ONECUT2+TFPI+ GC cell subset was elevated in oxaliplatin-resistant GC tumors. ONECUT2 was up-regulated and associated with undesirable prognostic outcomes of patients with GC. ONECUT2 facilitated GC cell migration, stemness properties and oxaliplatin resistance. YTHDF2, an m6A "reader", was down-regulated in GC, and its overexpression facilitated ONECUT2 mRNA degradation through m6A modification. Furthermore, ONECUT2 transcriptionally activated TFPI through binding to its promoter. Small molecule inhibitor CSRM617 targeting ONECUT2 was well tolerated in GC mouse models, and could effectively improve therapeutic efficacy of oxaliplatin against GC.

CONCLUSIONS

Our study demonstrates that YTHDF2-mediated m6A modification of ONECUT2 results in stemness and oxaliplatin resistance in GC through transcriptionally activating TFPI, which provides a novel therapeutic target against oxaliplatin-resistant GC.

Liver Metastasis in Cancer: Molecular Mechanisms and Management

Liver metastasis is a leading cause of mortality from malignant tumors and significantly impairs the efficacy of therapeutic interventions. In recent years, both preclinical and clinical research have made significant progress in understanding the molecular mechanisms and therapeutic strategies of liver metastasis. Metastatic tumor cells from different primary sites undergo highly similar biological processes, ultimately achieving ectopic colonization and growth in the liver. In this review, we begin by introducing the inherent metastatic-friendly features of the liver. We then explore the panorama of liver metastasis and conclude the three continuous, yet distinct phases based on the liver's response to metastasis. This includes metastatic sensing stage, metastatic stress stage, and metastasis support stage. We discuss the intricate interactions between metastatic tumor cells and various resident and recruited cells. In addition, we emphasize the critical role of spatial remodeling of immune cells in liver metastasis. Finally, we review the recent advancements and the challenges faced in the clinical management of liver metastasis. Future precise antimetastatic treatments should fully consider individual heterogeneity and implement different targeted interventions based on stages of liver metastasis.

Single-cell transcriptomics reveals intratumor heterogeneity and the potential roles of cancer stem cells and myCAFs in colorectal cancer liver metastasis and recurrence

Metastasis and recurrence are the primary obstacles to long-term survival in colorectal cancer (CRC) patients. In this study, we employed single-cell RNA sequencing (scRNA-seq) to comprehensively delineate the transcriptomic landscape of primary and liver metastatic CRCs, and revealed novel cellular crosstalk between cancer cell subpopulation and myofibroblastic CAFs (myCAFs) at single-cell resolution. We identified a cancer cell subpopulation termed stem/transient amplifying-like (stem/TA-like) cells, which expressed genes associated with stem cell-like characteristics and metastatic potential. MyCAFs in their microenvironment showed the potential to remodel the extracellular matrix (ECM), regulate angiogenesis, and support a pro-metastatic microenvironment through paracrine signaling involving FN1, BGN, and other ECM components. Notably, we found that they may communicate through the ligand-receptor pairs FN1-CD44 and GDF15-TGFBR2, which may be linked to the liver metastatic process. Additionally, our findings suggest that both stem/TA-like cells and myCAFs could be involved in CRC recurrence following chemotherapy. A unique gene signature generated using the gene expression characteristics of stem/TA-like cells and myCAFs (SM signature) can be used to assess recurrence risk in CRC patients. Collectively, these findings highlight the intratumor heterogeneity and the potential roles of cancer stem cells and myCAFs in CRC liver metastasis and recurrence, providing new targets and insights for the prognostic assessment of CRC patients and the improved selection of effective treatment options.

Single-cell analyses reveal metastasis mechanism and microenvironment remodeling of lymph node in intrahepatic cholangiocarcinoma

Background & Aims

Lymph node metastasis (LNM) is a major determinant of recurrence and prognosis in intrahepatic cholangiocarcinoma (iCCA). LNM disrupts T cell-mediated cytotoxicity, promotes tumor-specific immune tolerance, and facilitates distant metastasis. Despite its importance, extensive research on LMN in iCCA is lacking. This study aimed to systematically explore the heterogeneity of the LNM-associated microenvironment in iCCA by integrating single-cell and multi-omics analyses, identifying metastasis-associated cell subgroups, and validating these findings through multiple cohorts.

Methods

We analyzed single-cell transcriptomics data from primary tumors, cancer-adjacent liver tissues, and tumor-draining lymph nodes of four patients with iCCA who underwent radical surgery. Additionally, we collected 81 tumor and matched lymph node tissue sections from patients with iCCA. We performed single-cell RNA sequencing and multiplex immunohistochemistry, followed by differential gene expression analysis, functional enrichment analysis, single-cell copy number variation assessment, and pseudotime analysis.

Results

Our analysis revealed the complex heterogeneity of the iCCA LNM-associated microenvironment. We found a significant increase in stromal and mature immune cells in the metastatic lymph nodes. T cells constitute the predominant component, with diverse functional subtypes. We identified CD36+ macrophages and SAA1+ tumor cells as key players in the metastatic process. The SAA1-CD36 receptor‒ligand pair may be crucial in forming the LNM-associated microenvironment.

Conclusions

We identified several metastasis-associated cell subgroups. These findings provide new insights into the mechanisms underlying LNM in iCCA and lay the groundwork for the development of novel therapeutic strategies. Our study highlights the importance of single-cell technologies in understanding tumor microenvironment complexity and offers valuable resources for future research.

Impact and implications

The lack of single-cell transcriptome analysis of intrahepatic cholangiocarcinoma (iCCA) lymph node metastases has prevented us from understanding the underlying mechanisms of disease progression. To fill this knowledge gap, we elucidated the unique ecosystem of iCCA lymph node metastases, which is an important advance in clarifying the impact of the immune environment on the development of this disease. The results of this study identified several LNM-related therapeutic targets, which will not only be helpful to basic researchers, but also provide potential diagnostic and treatment ideas for physicians, thereby helping patients and their caregivers develop more personalized treatment plans. This finding is highly important for improving the prognosis of patients with advanced iCCA in the future.

Single-cell transcriptomics reveals the multidimensional dynamic heterogeneity from primary to metastatic gastric cancer

Reprogramming of the tumor microenvironment (TME) plays a critical role in gastric cancer (GC) progression and metastasis. However, the multidimensional features between primary tumors and organ-specific metastases remain poorly understood. In this study, we characterized the dynamic heterogeneity of GC from primary to metastatic stages. We identified seven major cell types and 27 immune and stromal subsets. Immune cells decreased, while immunosuppressive cells increased in ovarian and peritoneal metastases. A 30-gene signature for ovarian metastasis was validated in GC cohorts. Additionally, critical ligand-receptor interactions, including LGALS9-MET in liver metastasis and PVR-TIGIT in lymph node metastasis, were identified as potential therapeutic targets. Furthermore, CLOCK, a transcription factor, was associated with poor prognosis and influenced immune cell interactions and migration. Collectively, this study provides valuable insights into TME dynamics in GC and highlights potential avenues for targeted therapies.

Landscape of four different stages of human gastric cancer revealed by single-cell sequencing

BACKGROUND

Gastric cancer (GC) poses a substantial risk to human health due to its high prevalence and mortality rates. Nevertheless, current therapeutic strategies remain insufficient. Single-cell RNA sequencing (scRNA-seq) offers the potential to provide comprehensive insights into GC pathogenesis.

AIM

To explore the distribution and dynamic changes of cell populations in the GC tumor microenvironment using scRNA-seq techniques.

METHODS

Cancerous tissues and paracancerous tissues were obtained from patients diagnosed with GC at various stages (I, II, III, and IV). Single-cell suspensions were prepared and analyzed using scRNA-seq to examine transcriptome profiles and cell-cell interactions. Additionally, quantitative real-time polymerase chain reaction (qRT-PCR) and flow cytometry were applied for measuring the expression of cluster of differentiation (CD) 2, CD3D, CD3E, cytokeratin 19, cytokeratin 8, and epithelial cell adhesion molecules.

RESULTS

Transcriptome data from 73645 single cells across eight tissues of four patients were categorized into 25 distinct cell clusters, representing 10 different cell types. Variations were observed in these cell type distribution. The adjacent epithelial cells in stages II and III exhibited a degenerative trend. Additionally, the quantity of CD4 T cells and CD8 T cells were evidently elevated in cancerous tissues. Interaction analysis displayed a remarkable increase in interaction between B cells and other mast cells in stages II, III, and IV of GC. These findings were further validated through qRT-PCR and flow cytometry, demonstrating elevated T cells and declined epithelial cells within the cancerous tissues.

CONCLUSION

This study provides a comprehensive analysis of cell dynamics across GC stages, highlighting key interactions within the tumor microenvironment. These findings offer valuable insights for developing novel therapeutic strategies.

CT radiomics-based intratumoral and intertumoral heterogeneity indicators for prognosis prediction in gastric cancer patients receiving neoadjuvant chemotherapy

OBJECTIVES

CT-based intratumoral and intertumoral heterogeneity indicators were integrated to develop a prognostic model for locally advanced gastric cancer (LAGC) patients undergoing neoadjuvant chemotherapy (NACT).

METHODS

This retrospective study included 568 LAGC patients treated with NACT from two hospitals. The intratumor heterogeneity score (ITHscore) was developed to quantify the intratumoral heterogeneity of LAGCs on CT; intertumoral heterogeneity was characterized by combining the primary tumor (PT) and lymph node (LN) sizes on CT. CT indicators were measured on baseline and posttreatment CT scans; the reduction rates (%Δ) were calculated. The overall survival (OS) of all patients was recorded. Cox regression analysis was used to construct a preoperative survival prediction model (Pre-SPM) based on the baseline indicators and %Δ indicators. The predictive performance of Pre-SPM for OS was assessed. The clinicopathological data, including the ypTNM stage, were also collected to evaluate their impact on OS.

RESULTS

Patients with lower baseline ITHscore had better prognoses (p < 0.001). Approximately 13.01% of patients exhibited contradictory changes in PT and LN sizes. Cox regression analysis selected the baseline ITHscore, baseline PT area, %ΔPT, and %ΔLN to establish the Pre-SPM. In the external validation cohort, the c-index of Pre-SPM for predicting OS was 0.72, while the AUC for predicting 5-year OS was 0.73. After adjusting for the influence of clinicopathological features, including the ypTNM stage, Pre-SPM remained an independent prognostic factor.

CONCLUSION

The Pre-SPM model, combining intratumoral heterogeneity and intertumoral heterogeneity, has the potential to predict the OS of LAGC patients receiving NACT.

KEY POINTS

Question Increased tumor heterogeneity in LAGC affects prognosis, but effective non-invasive CT methods for assessing intratumoral and intertumoral heterogeneity are lacking. Findings ITHscore indicates intratumoral heterogeneity, while changes in PT and LN sizes reflect intertumoral heterogeneity. The Pre-SPM model, integrating both, independently predicts patient outcomes. Clinical relevance Pre-SPM enhances prognosis prediction by quantifying intratumoral and intertumoral heterogeneity, potentially guiding more personalized and effective treatment strategies for patients with LAGC.

NEDD4L inhibits epithelial-mesenchymal transition in gastric cancer by mediating BICC1 ubiquitination

Epithelial-mesenchymal transition (EMT) is a critical stage in the metastasis of gastric cancer (GC). Further clarification of the EMT process in GC is still needed. This study examined the effects of the NEDD4L/BICC1 axis on GC proliferation and the EMT process. Thirty GC patients were enrolled in this study to assess the expression of BICC1 and NEDD4L in tumor samples. A xenograft tumor model in mice was created to investigate BICC1's function in vivo. The proliferation, migration, and invasion of GC cells were evaluated using colony formation, transwell, and wound healing assays. Western blot determined the expression levels of EMT-associated proteins. Co-immunoprecipitation (Co-IP) elucidated the mechanism by which NEDD4L regulates BICC1. BICC1 was found to be overexpressed in tumors. Additionally, BICC1 knockdown inhibited the growth of GC cells in vivo and prevented their migration, invasion, proliferation, and EMT. Furthermore, BICC1 activated the PI3K/AKT pathway, which facilitated cancer progression. Tumor tissues and GC cells exhibited low expression levels of NEDD4L. Conversely, NEDD4L overexpression promoted the ubiquitination and degradation of BICC1 protein, thereby inhibiting GC cell proliferation, migration, invasion, and EMT processes. Our study demonstrated that NEDD4L acts as a tumor suppressor in GC, while BICC1 functions as a pro-tumorigenic factor. The NEDD4L/BICC1 axis plays a significant role in the metastasis and progression of GC.

Development and validation of a machine learning model to predict the risk of lymph node metastasis in early-stage supraglottic laryngeal cancer

Background

Cervical lymph node metastasis (LNM) is a significant factor that leads to a poor prognosis in laryngeal cancer. Early-stage supraglottic laryngeal cancer (SGLC) is prone to LNM. However, research on risk factors for predicting cervical LNM in early-stage SGLC is limited. This study seeks to create and validate a predictive model through the application of machine learning (ML) algorithms.

Methods

The training set and internal validation set data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Data from 78 early-stage SGLC patients were collected from Fujian Provincial Hospital for independent external validation. We identified four variables associated with cervical LNM and developed six ML models based on these variables to predict LNM in early-stage SGLC patients.

Results

In the two cohorts, 167 (47.44%) and 26 (33.33%) patients experienced LNM, respectively. Age, T stage, grade, and tumor size were identified as independent predictors of LNM. All six ML models performed well, and in both internal and independent external validations, the eXtreme Gradient Boosting (XGB) model outperformed the other models, with AUC values of 0.87 and 0.80, respectively. The decision curve analysis demonstrated that the ML models have excellent clinical applicability.

Conclusions

Our study indicates that combining ML algorithms with clinical data can effectively predict LNM in patients diagnosed with early-stage SGLC. This is the first study to apply ML models in predicting LNM in early-stage SGLC patients.

Characterizing tumor biology and immune microenvironment in high-grade serous ovarian cancer via single-cell RNA sequencing: insights for targeted and personalized immunotherapy strategies

Background

High-grade serous ovarian cancer (HGSOC), the predominant subtype of epithelial ovarian cancer, is frequently diagnosed at an advanced stage due to its nonspecific early symptoms. Despite standard treatments, including cytoreductive surgery and platinum-based chemotherapy, significant improvements in survival have been limited. Understanding the molecular mechanisms, immune landscape, and drug sensitivity of HGSOC is crucial for developing more effective and personalized therapies. This study integrates insights from cancer immunology, molecular profiling, and drug sensitivity analysis to identify novel therapeutic targets and improve treatment outcomes. Utilizing single-cell RNA sequencing (scRNA-seq), the study systematically examines tumor heterogeneity and immune microenvironment, focusing on biomarkers influencing drug response and immune activity, aiming to enhance patient outcomes and quality of life.

Methods

scRNA-seq data was obtained from the GEO database in this study. Differential gene expression was analyzed using gene ontology and gene set enrichment methods. InferCNV identified malignant epithelial cells, while Monocle, Cytotrace, and Slingshot software inferred subtype differentiation trajectories. The CellChat software package predicted cellular communication between malignant cell subtypes and other cells, while pySCENIC analysis was utilized to identify transcription factor regulatory networks within malignant cell subtypes. Finally, the analysis results were validated through functional experiments, and a prognostic model was developed to assess prognosis, immune infiltration, and drug sensitivity across various risk groups.

Results

This study investigated the cellular heterogeneity of HGSOC using scRNA-seq, focusing on tumor cell subtypes and their interactions within the tumor microenvironment. We confirmed the key role of the C2 IGF2+ tumor cell subtype in HGSOC, which was significantly associated with poor prognosis and high levels of chromosomal copy number variations. This subtype was located at the terminal differentiation of the tumor, displaying a higher degree of malignancy and close association with stage IIIC tissue types. The C2 subtype was also associated with various metabolic pathways, such as glycolysis and riboflavin metabolism, as well as programmed cell death processes. The study highlighted the complex interactions between the C2 subtype and fibroblasts through the MK signaling pathway, which may be closely related to tumor-associated fibroblasts and tumor progression. Elevated expression of PRRX1 was significantly connected to the C2 subtype and may impact disease progression by modulating gene transcription. A prognostic model based on the C2 subtype demonstrated its association with adverse prognosis outcomes, emphasizing the importance of immune infiltration and drug sensitivity analysis in clinical intervention strategies.

Conclusion

This study integrates molecular oncology, immunotherapy, and drug sensitivity analysis to reveal the mechanisms driving HGSOC progression and treatment resistance. The C2 IGF2+ tumor subtype, linked to poor prognosis, offers a promising target for future therapies. Emphasizing immune infiltration and drug sensitivity, the research highlights personalized strategies to improve survival and quality of life for HGSOC patients.

Elucidating stearoyl metabolism and NCOA4-mediated ferroptosis in gastric cancer liver metastasis through multi-omics single-cell integrative mendelian analysis: advancing personalized immunotherapy strategies

BACKGROUND

The metabolism of stearoyl-GPE plays a key role in the liver metastasis of gastric cancer. This investigation delves into the mechanisms underlying the intricate tumor microenvironment (TME) heterogeneity triggered by stearoyl metabolism in gastric cancer with liver metastasis (LMGC), offering novel perspectives for LMGC.

OBJECTIVE

Utilizing Mendelian randomization, we determined that stearoyl metabolism significantly contributes to the progression of gastric cancer (GC). Following this, bulk transcriptome analyses and single-cell multiomics techniques to investigate the roles of stearoyl-GPE metabolism-related genes, particularly NCOA4, in regulating LMGC TME.

RESULTS

Our analysis highlights the crucial role of stearoyl metabolism in modulating the complex microenvironment of LMGC, particularly impacting monocyte cells. Through single-cell sequencing and spatial transcriptomics, we have identified key metabolic genes specific to stearoyl metabolism within the monocyte cell population, including NCOA4. Regarding the relationship between ferroptosis, stearoyl metabolism, and LMGC findings, it is plausible that stearoyl metabolism and LMGC pathways intersect with mechanisms involved in ferroptosis. Ferroptosis, characterized by iron-dependent lipid peroxidation, represents a regulated form of cell death. The activity of Stearoyl-CoA desaturase (SCD), a critical enzyme in stearoyl metabolism, has been associated with the modulation of lipid composition and susceptibility to ferroptosis. Furthermore, the LMGC is integral to cellular processes related to oxidative stress and lipid metabolism, both of which are significant factors in the context of ferroptosis.

CONCLUSION

This study enhances the understanding of the relationship between stearoyl metabolism and ferroptosis in promoting liver metastasis of gastric cancer and its role in the regulation of tumor heterogeneity. In addition, this study contributes to a deeper understanding of the dynamics of gastric cancer tumor microenvironment (TME) and provides a basis for the development of better interventions to combat cancer metastasis.

Integrated Multi-omics Data Analysis and In Vitro Validation Reveal the Crucial Role of Glycogen Metabolism in Gastric Cancer

Background: This study aimed to investigate glycogen metabolism in gastric cancer (GC) and develop a glycogen-based riskScore model for predicting GC prognosis. Methods: Patients' expression profiles for 33 tumor types were retrieved from TCGA. Four GC bulk and one single-cell sequencing datasets were obtained from GEO database. This study also enrolled a bladder urothelial carcinoma immunotherapeutic IMvigor210 cohort. The ssGSEA method was conducted to assess glycogen biosynthesis and degradation level. Consensus clustering analysis was conducted to identify different clusters. A glycogen riskScore signature was developed to evaluate prognostic value across different cohorts. Besides, in vitro experiments were conducted to further evaluate the role of glycogen metabolism related genes in GC. Results: Both glycogen biosynthesis and degradation were significantly associated with worse overall survival and were also related with malignant phenotype in GC at both bulk and single-cell levels. Differential outcomes and immune functions were verified in the three identified clusters. The constructed glycogen riskScore model accurately classified GC patients with different outcomes, genomic and immune landscape, and performed well in predicting prognosis through external validation, immunotherapy and pan-cancer cohorts. Furthermore, the riskScore could predict response to chemotherapy and immunotherapy. Functional analyses revealed the signature's connection to pro-tumor and immunosuppression related pathways across pan-cancer. Additionally, glycogen metabolism related genes were found to regulate the malignant phenotypes of GC cells. Conclusion: This study revealed important roles of glycogen metabolism in promoting progression of GC and presented a glycogen riskScore model as a novel tool for predicting prognosis and treatment response.

Effect of neutrophils on tumor immunity and immunotherapy resistance with underlying mechanisms

Neutrophils are key mediators of the immune response and play essential roles in the development of tumors and immune evasion. Emerging studies indicate that neutrophils also play a critical role in the immunotherapy resistance in cancer. In this review, firstly, we summarize the novel classification and phenotypes of neutrophils and describe the regulatory relationships between neutrophils and tumor metabolism, flora microecology, neuroendocrine and tumor therapy from a new perspective. Secondly, we review the mechanisms by which neutrophils affect drug resistance in tumor immunotherapy from the aspects of the immune microenvironment, tumor antigens, and epigenetics. Finally, we propose several promising strategies for overcoming tumor immunotherapy resistance by targeting neutrophils and provide new research ideas in this area.

RNA N6-Methyladenosine-Binding Protein YTHDFs Redundantly Attenuate Cancer Immunity by Downregulating IFN-γ Signaling in Gastric Cancer

Immunotherapy holds potential as a treatment for gastric cancer (GC), though immune checkpoint inhibitor (ICI) resistance remains an obstacle. One resistance mechanism involves defects in interferon-γ (IFN-γ) signaling, in which IFN-γ is linked to improved responsiveness to ICIs. Herein, the roles of RNA N6-methyladenosine (m6A) modifications in regulation of IFN-γ signaling and the responsiveness to ICIs are unveiled. The m6A-binding protein YTH N6-methyladenosine RNA-binding protein F1 (YTHDF1) is overexpressed in GC tissues, correlating with the suppression of cancer immunity and poorer survival rates. YTHDF1 overexpression impaired the responsiveness to IFN-γ in GC cells, and knockdown studies indicated the redundant effects of YTHDF2 and YTHDF3 with YTHDF1 in IFN-γ responsiveness. RNA immunoprecipitation sequencing revealed YTHDFs directly target interferon regulatory factor 1 (IRF1) mRNA, a master regulator of IFN-γ signaling, leading to reduced RNA stability and consequent downregulation of IFN-γ signaling. Furthermore, in mouse syngeneic tumor models, Ythdf1 depletion in cancer cells resulted in reduced tumor growth and increased tumor-infiltrating lymphocytes, which are attributed to the augmentation of IFN-γ signaling. Collectively, these findings highlight how YTHDFs modulate cancer immunity by influencing IFN-γ signaling through IRF1 regulation, suggesting their viability as therapeutic targets in cancer immunotherapy.

Multiomics integration and machine learning reveal prognostic programmed cell death signatures in gastric cancer

Gastric cancer (GC) is characterized by notable heterogeneity and the impact of molecular subtypes on treatment and prognosis. The role of programmed cell death (PCD) in cellular processes is critical, yet its specific function in GC is underexplored. This study applied multiomics approaches, integrating transcriptomic, epigenetic, and somatic mutation data, with consensus clustering algorithms to classify GC molecular subtypes and assess their biological and immunological features. A machine learning model was developed to create the Gastric Cancer Multi-Omics Programmed Cell Death Signature (GMPS), targeting PCD-related genes. We verified the expression of the GMPS hub genes using the RT-qPCR method. The prognostic influence of GMPS on GC was then evaluated. Single-cell analysis was performed to examine the heterogeneity of PCD characteristics in GC. Findings indicate that GMPS notably correlates with patient survival rates, tumor mutational burden (TMB), and copy number variations (CNV), demonstrating substantial prognostic predictive power. Moreover, GMPS is closely associated with the tumor microenvironment (TME) and immune therapy response. This research elucidates the molecular subtypes of GC, highlighting PCD's critical role in prognosis assessment. The relationship between GMPS and immune therapy response, alongside gastric cancer's microenvironmental features, provides insights for personalized treatment.

Unveiling the NEFH+ malignant cell subtype: Insights from single-cell RNA sequencing in prostate cancer progression and tumor microenvironment interactions

Background

Prostate cancer (PCa) is a multifactorial and heterogeneous disease, ranking among the most prevalent malignancies in men. In 2020, there were 1,414,259 new cases of PCa worldwide, accounting for 7.3% of all malignant tumors. The incidence rate of PCa ranks third, following breast cancer and lung cancer. Patients diagnosed with high-grade PCa frequently present with existing or developing metastases, complicating their treatment and resulting in poorer prognoses, particularly for those with bone metastases. Utilizing single-cell RNA sequencing (scRNA-seq), we identified specific malignant cell subtypes that are closely linked to high-grade PCa. By investigating the mechanisms that govern interactions within the tumor microenvironment (TME), we aim to offer new theoretical insights that can enhance the prevention, diagnosis, and treatment of PCa, ultimately striving to improve patient outcomes and quality of life.

Methods

Data on scRNA-seq was obtained from the GEO database. The gene ontology and gene set enrichment analysis were employed to analyze differential expression genes. Using inferCNV analysis to identify malignant epithelial cells. We subsequently employed Monocle, Cytotrace, and Slingshot packages to infer subtype differentiation trajectories. The cellular communication between malignant cell subtypes and other cells was predicted using the CellChat package. Furthermore, we employed pySCENIC to analyze and identify the regulatory networks of transcription factors (TFs) in malignant cell subtypes. The MDA PCa 2b and VCap cell lines were employed to validate the analysis results through cellular functional experiments. In addition, a risk scoring model was developed to assess the variation in clinical characteristics, prognosis, immune infiltration, immune checkpoint, and drug sensitivity.

Results

A malignant cell subtype in PCa with high expression of NEFH was identified through scRNA-seq analysis. This subtype was situated at the differentiation terminal, exhibited a higher level of malignancy, and exhibited characteristics that were more prone to advanced tumor lesions. In addition, our research underscored the intricate interactions that exist within the TME, particularly the interaction between PTN secreted by this subtype and fibroblasts via the NCL receptor. This interaction may be closely associated with cancer-associated fibroblasts and tumor progression. Subsequently, we determined that the NEFH+ malignant cell subtype was significantly correlated with the TF IRX4. This TF is linked to a worse prognosis in PCa and may affect disease progression by regulating gene transcription. Our conclusions were additionally verified through cellular experiments. Furthermore, the prognostic model we developed demonstrated satisfactory predictive performance, with gene sets from the high NmRS group facilitating tumor progression and deterioration. The analysis of immune infiltration was instrumental in the development of clinical intervention strategies and patient prognosis.

Conclusion

By examining the cellular heterogeneity of a unique NEFH+ malignant cell subtype within the PCa microenvironment, we were able to disclose their reciprocal interaction with disease progression. This offers a novel viewpoint on the diagnosis and treatment of PCa.

Single-cell analysis identified key macrophage subpopulations associated with atherosclerosis

Background

Atherosclerosis is a lipid-driven inflammatory disease characterized by plaque formation in major arteries. These plaques contain lipid-rich macrophages that accumulate through monocyte recruitment, local macrophage differentiation, and proliferation.

Objective

We identify the macrophage subsets that are closely related to atherosclerosis and reveal the key pathways in the progression of atherosclerotic disease.

Materials and methods

In this study, we characterize the single-cell landscape of atherosclerosis, identifying macrophage subsets closely related to the disease and revealing key pathways in its progression. Using analytical methods like CytoTRACE, Monocle2, Slingshot, and CellChat, we study macrophage differentiation and infer cell trajectory.

Results

The 8,417 macrophages were divided into six subtypes, macrophages: C0 C1QC+ macrophages, C1 SPP1+ macrophages, C2 FCN1+ macrophages, C3 IGKC+ macrophages, C4 FCER1A+ macrophages, C5CALD1+ macrophages. The results of gene set enrichment analysis, Monocle2, and Slingshot suggest that C2 FCN1+ macrophages may play an important role in the progression of atherosclerosis. C2 FCN1+ macrophages interact with endothelial cells via CCL, CXCL, APP, and other pathways to regulate the progression of atherosclerosis.

Conclusion

We identify a key macrophage subgroup (C2 FCN1+ macrophages) associated with atherosclerosis, which interacts with endothelial cells via CCL, CXCL, APP, and other pathways to regulate disease progression.

Innovative strategies to optimise colorectal cancer immunotherapy through molecular mechanism insights

Background

Colorectal cancer (CRC) is a leading cause of cancer-related deaths globally. The heterogeneity of the tumor microenvironment significantly influences patient prognosis, while the diversity of tumor cells shapes its unique characteristics. A comprehensive analysis of the molecular profile of tumor cells is crucial for identifying novel molecular targets for drug sensitivity analysis and for uncovering the pathophysiological mechanisms underlying CRC.

Methods

We utilized single-cell RNA sequencing technology to analyze 13 tissue samples from 4 CRC patients, identifying key cell types within the tumor microenvironment. Intercellular communication was assessed using CellChat, and a risk score model was developed based on eight prognostic genes to enhance patient stratification for immunotherapeutic approaches. Additionally, in vitro experiments were performed on DLX2, a gene strongly associated with poor prognosis, to validate its potential role as a therapeutic target in CRC progression.

Results

Eight major cell types were identified across the tissue samples. Within the tumor cell population, seven distinct subtypes were recognized, with the C0 FXYD5+ tumor cells subtype being significantly linked to cancer progression and poor prognosis. CellChat analysis indicated extensive communication among tumor cells, fibroblasts, and immune cells, underscoring the complexity of the tumor microenvironment. The risk score model demonstrated high accuracy in predicting 1-, 3-, and 5-year survival rates in CRC patients. Enrichment analysis revealed that the C0 FXYD5+ tumor cell subtype exhibited increased energy metabolism, protein synthesis, and oxidative phosphorylation, contributing to its aggressive behavior. In vitro experiments confirmed DLX2 as a critical gene associated with poor prognosis, suggesting its viability as a target for improving drug sensitivity.

Conclusion

In summary, this study advances our understanding of CRC progression by identifying critical tumor subtypes, molecular pathways, and prognostic markers that can inform innovative strategies for predicting and enhancing drug sensitivity. These findings hold promise for optimizing immunotherapeutic approaches and developing new targeted therapies, ultimately aiming to improve patient outcomes in CRC.

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Combined single cell and spatial transcriptome analysis reveals cellular heterogeneity of hedgehog pathway in gastric cancer

Gastric cancer (GC) is one of the most common and deadly malignancies in the world. Abnormal activation of hedgehog pathway is closely related to tumor development and progression. However, potential therapeutic targets for GC based on the hedgehog pathway have not been clearly identified. In the present study, we combined single-cell sequencing data and spatial transcriptomics to deeply investigate the role of hedgehog pathway in GC. Based on a comprehensive scoring algorithm, we found that fibroblasts from GC tumor tissues were characterized by a highly enriched hedgehog pathway. By analyzing the development process of fibroblasts, we found that CCND1 plays an important role at the end stage of fibroblast development, which may be related to the formation of tumor-associated fibroblasts. Based on spatial transcriptome data, we deeply mined the role of CCND1 in fibroblasts. We found that CCND1-negative and -positive fibroblasts have distinct characteristics. Based on bulk transcriptome data, we verified that highly infiltrating CCND1 + fibroblasts are a risk factor for GC patients and can influence the immune and chemotherapeutic efficacy of GC patients. Our study provides unique insights into GC and hedgehog pathways and also new directions for cancer treatment strategies.

Mining single-cell data for cell type-disease associations

A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and time points. To better understand the associations between cell types and diseases, we leveraged previously developed tools to construct a standardized analysis pipeline and systematically explored associations across four single-cell datasets, spanning a range of tissue types, cell types and developmental time periods. We utilized a set of existing tools to identify co-expression modules and temporal patterns per cell type and then investigated these modules for known disease and phenotype enrichments. Our pipeline reveals known and novel putative cell type-disease associations across all investigated datasets. In addition, we found that automatically discovered gene co-expression modules and temporal clusters are enriched for drug targets, suggesting that our analysis could be used to identify novel therapeutic targets.

Echium amoenum and Rosmarinic Acid Suppress the Growth and Metastasis of Gastric Cancer AGS Cells by Promoting Apoptosis and Inhibiting EMT

Gastric cancer (GC) ranks as the fifth most prevalent cancer globally. Owing to the absence of early manifest symptoms, it is difficult to diagnose GC until it has metastasized to other organs. Hence, the prevention and treatment of GC have become major concerns for patients. Echium amoenum, a traditional medicinal plant from the Boraginaceae family, exhibits various biological activities. Although recent studies have reported the anticancer properties of E. amoenum, its effects and mechanisms of action on GC cells are not yet fully understood. This study examined the anticancer effects of the ethyl acetate extract of E. amoenum (EAEC) and its main active ingredient, rosmarinic acid (RA), in GC AGS cells. EAEC and RA suppressed AGS cell growth by inducing apoptosis through caspase mediation and inhibited AGS cell metastasis by influencing the expression of crucial epithelial-mesenchymal transition (EMT) biomarkers. Furthermore, the anti-growth and anti-metastatic effects of EAEC and RA on AGS cells involved inactivation of the STAT3, AKT, and ERK1/2 pathways. Additionally, RA notably inhibited the in vivo tumor growth in AGS cells. Overall, these results indicate that EAEC and RA could serve as potential anticancer and anti-metastasis agents for GC.

Machine Learning Integration with Single-Cell Transcriptome Sequencing Datasets Reveals the Impact of Tumor-Associated Neutrophils on the Immune Microenvironment and Immunotherapy Outcomes in Gastric Cancer

The characteristics of neutrophils play a crucial role in defining the tumor inflammatory environment. However, the function of tumor-associated neutrophils (TANs) in tumor immunity and their response to immune checkpoint inhibitors (ICIs) remains incompletely understood. By analyzing single-cell RNA sequencing data from over 600,000 cells in gastric cancer (GSE163558 and GSE183904), colorectal cancer (GSE205506), and lung cancer (GSE207422), we identified neutrophil subsets in primary gastric cancer that are associated with the treatment response to ICIs. Specifically, we focused on neutrophils with high expression of CD44 (CD44_NEU), which are abundant during tumor progression and exert significant influence on the gastric cancer immune microenvironment. Machine learning analysis revealed 22 core genes associated with CD44_NEU, impacting inflammation, proliferation, migration, and oxidative stress. In addition, multiple immunofluorescence staining and gastric cancer spatial transcriptome data (GSE203612) showed a correlation between CD44_NEU and T-cell infiltration in gastric cancer tissues. A risk score model derived from seven essential genes (AQP9, BASP1, BCL2A1, PLEK, PDE4B, PROK2, and ACSL1) showed better predictive capability for patient survival compared to clinical features alone, and integrating these scores with clinical variables resulted in a prognostic nomogram. Overall, this study highlights the heterogeneity of TANs, particularly the CD44_NEU critical influence on immunotherapy outcomes, paving the way for personalized treatment strategies.

Single-cell analysis uncovers liver susceptibility to pancreatic cancer metastasis via myeloid cell characterization

The liver is the predominant metastatic site for diverse cancers, including pancreatic and colorectal cancers (CRC), etc. The high incidence of hepatic metastasis of pancreatic cancer is an important reason for its refractory and high mortality. Therefore, it is important to understand how metastatic pancreatic cancer affects the hepatic tumor immune microenvironment (TME) in patients. Here, we characterized the TME of liver metastases unique to pancreatic cancer by comparing them with CRC liver metastases. We integrated two single-cell RNA-seq (scRNA-seq) datasets including tumor samples of pancreatic cancer liver metastasis (P-LM), colorectal cancer liver metastasis (C-LM), primary pancreatic cancer (PP), primary colorectal cancer (PC), as well as samples of peripheral blood mono-nuclear cells (PBMC), adjacent normal pancreatic tissues (NPT), to better characterize the heterogeneities of the microenvironment of two kinds of liver metastases. We next performed comparative analysis on cellular compositions between P-LM and C-LM, found that Mph_SPP1, a subset of macrophages associated with angiogenesis and tumor invasion, was more enriched in the P-LM group, indicating this kind of macrophages provide a TME niche more vulnerable for pancreatic cancers. Analysis of the developmental trajectory implied that Mph_SPP1 may progressively be furnished with increased expression of genes regulating endothelium. Cell-cell communications analysis revealed that Mph_SPP1 potentially interacts with endothelial cells in P-LM via FN1/SPP1-ITGAV/ITGB1, implying this macrophage subset may construct an immunosuppressive TME for pancreatic cancer by regulating endothelial cells. We also found that Mph_SPP1 has a prognostic value in pancreatic adenocarcinoma that is not present in colon adenocarcinoma or rectum adenocarcinoma. This study provides a new perspective for understanding the characteristics of the hepatic TME in patients with liver metastatic cancer. And it provides a subset of macrophages specifically associated with the liver metastasis of pancreatic cancer, and its detection and intervention have potential value for preventing the metastasis of pancreatic cancer to the liver.

Single-cell transcriptomic analysis reveals that the APP-CD74 axis promotes immunosuppression and progression of testicular tumors

Testicular tumors represent the most common malignancy among young men. Nevertheless, the pathogenesis and molecular underpinning of testicular tumors remain largely elusive. We aimed to delineate the intricate intra-tumoral heterogeneity and the network of intercellular communication within the tumor microenvironment. A total of 40,760 single-cell transcriptomes were analyzed, encompassing samples from six individuals with seminomas, two patients with mixed germ cell tumors, one patient with a Leydig cell tumor, and three healthy donors. Five distinct malignant subclusters were identified in the constructed landscape. Among them, malignant 1 and 3 subclusters were associated with a more immunosuppressive state and displayed worse disease-free survival. Further analysis identified that APP-CD74 interactions were significantly strengthened between malignant 1 and 3 subclusters and 14 types of immune subpopulations. In addition, we established an aberrant spermatogenesis trajectory and delineated the global gene alterations of somatic cells in seminoma testes. Sertoli cells were identified as the somatic cell type that differed the most from healthy donors to seminoma testes. Cellular communication between spermatogonial stem cells and Sertoli cells is disturbed in seminoma testes. Our study delineates the intra-tumoral heterogeneity and the tumor immune microenvironment in testicular tumors, offering novel insights for targeted therapy. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Immunomodulation by endothelial cells: prospects for cancer therapy

Growing evidence highlights the importance of tumor endothelial cells (TECs) in the tumor microenvironment (TME) for promoting tumor growth and evading immune responses. Immunomodulatory endothelial cells (IMECs) represent a distinct plastic phenotype of ECs that exerts the ability to modulate immunity in health and disease. This review discusses our current understanding of IMECs in cancer biology, scrutinizing insights from single-cell reports to compare their characteristics and function dynamics across diverse tumor types, conditions, and species. We investigate possible implications of exploiting IMECs in the context of cancer treatment, particularly examining their influence on the efficacy of existing therapies and the potential to leverage them as targets in optimizing immunotherapeutic strategies.

SPP1+ macrophages and FAP+ fibroblasts promote the progression of pMMR gastric cancer

Immunotherapy has become a primary and secondary treatment for gastric cancer (GC) patients with mismatch repair deficiency (dMMR), and is used in both perioperative and advanced stages. The tumor immune microenvironment (TiME) is crucial for immunotherapy efficacy, yet the impact of MMR status on TiME remains understudied. We employed single-cell RNA sequencing (scRNA-seq) to analyze 33 fresh tissue samples from 25 patients, which included 10 normal tissues, 6 dMMR tumor tissues, and 17 pMMR tumor tissues, aiming to characterize the cellular and molecular components of the TiME. The proficient mismatch repair (pMMR) group displayed a significantly higher prevalence of a specific GC cell type, termed GC2, characterized by increased hypoxia, epithelial-mesenchymal transition (EMT), and angiogenic activities compared to the dMMR group. GC2 cells overexpressed BEX3 and GPC3, and they significantly correlated with poorer survival. The pMMR group also showed increased infiltration of SPP1 + macrophages and FAP + fibroblasts, exhibiting strong hypoxic and pro-angiogenic features. Furthermore, a higher proportion of E2 endothelial cells, involved in extracellular matrix (ECM) remodeling and showing heightened VEGF pathway, HIF pathway, and angiogenesis activity, were identified in pMMR patients. Intercellular communication analyses revealed that GC2 cells, SPP1 + macrophages, FAP + fibroblasts, and E2 endothelial cells interact through VEGF, SPP1, and MIF signals, forming a TiME characterized by hypoxia, pro-angiogenesis, and ECM remodeling. This study uncovered TiME heterogeneity among GC patients with different MMR states, highlighting that the pMMR TiME is distinguished by hypoxia, pro-angiogenesis, and ECM remodeling, driven by the presence of GC2 cells, SPP1 + macrophages, FAP + fibroblasts, and E2 endothelial cells. These findings are pivotal for developing targeted immunotherapies for GC patients with pMMR.

Identifying the signature of NAD+ metabolism-related genes for immunotherapy of gastric cancer

NAD (Nicotinamide Adenine Dinucleotide) -related metabolic reprogramming in tumor cells involves multiple vital cellular processes. However, the role of NAD metabolism in immunity and the prognosis of gastric cancer (GC) remains not elucidated. Here we identified and clustered 33 NAD + metabolism-related genes (NMRGs) based on 808 GC samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Survival analysis between different groups found a poor prognosis in the GC patients with high NMRGs expression. Gene SGCE, APOD, and PPP1R14A were identified and performed high expression in GC samples, while the qRT-PCR results further confirmed that their expression levels in GC cell lines were significantly higher than those from normal human gastric mucosa epithelial cells. Based on the single-cell analysis, Gene SGCE, APOD, and PPP1R14A can potentially be novel biomarkers of tumor-associated fibroblasts (CAFs). In parallel, the proliferation and migration of GC cells were significantly hampered following the knockdown of SGCE, APOD, and PPP1R14A, particularly APOD, we confirmed that APOD knockdown can inhibit β-catenin and N-cadherin expression, while promote E-cadherin expression. This study unveils a novel NMRGs-related gene signature, highlighting APOD as a prognostic biomarker linked to the tumor microenvironment. APOD drives GC cell proliferation and metastasis through the Wnt/β-catenin/EMT signaling pathway, establishing it as a promising therapeutic target for GC patients.

Co-inhibition of PGF and VEGFA enhances the effectiveness of immunotherapy in bladder cancer

Background: Anti-angiogenic inhibitors and immune checkpoint blockade combination therapy offers a novel approach to circumvent the challenges associated with limited responsiveness to checkpoint inhibitors in bladder cancer. However, the effective strategies for inhibiting angiogenesis in bladder cancer need further elucidation. Objective: This work aims to identify key targets for the effective inhibition of angiogenesis in bladder cancer and to explore the potential benefits of combining anti-angiogenic therapies with immune checkpoint blockade strategies in the treatment of this disease. Methods: Cell-cell interaction analysis was performed using bladder cancer single-cell transcriptome datasets downloaded from the Gene Expression Omnibus (GEO) database to determine the regulatory network driving angiogenesis in bladder cancer. The bladder cancer cell line MBT2 was orthotopically transplanted into mice to investigate the impact of pro-angiogenic molecules on angiogenesis and tumor growth, and to evaluate the synergistic therapeutic potential of a combination therapy targeting angiogenesis and Programmed Cell Death Protein 1 (PD-1). Proliferation and tube formation assays with Human Umbilical Vein Endothelial Cells (HUVECs) were used to explore the regulatory functions of pro-angiogenic molecules in angiogenesis. Results: Placental growth factor (PGF) is a pro-angiogenic factor in bladder cancer, in addition to vascular endothelial growth factor A (VEGFA). Suppression of PGF reduced the tumor size and angiogenesis in bladder cancer. The expression level of vascular endothelial growth factor receptor 1 (VEGFR1) is higher than that of vascular endothelial growth factor receptor2 (VEGFR2) in the endothelial cells of bladder cancer. The pro-angiogenic activity of PGF is dependent on the expression level of VEGFR1 in endothelial cells. The combined inhibition of PGF and VEGFA exerts a synergistic effect on suppressing tumor growth and angiogenesis. The concurrent inhibition of PGF and VEGFA stands out as the only intervention capable of significantly enhancing the infiltration of CD8+ cytotoxic T cells within the bladder cancer microenvironment. In the bladder cancer mouse model, the introduction of an anti- programmed cell death protein 1 (PD-1) therapeutic regimen combined with the targeted inhibition of PGF and VEGFA, led to a significantly elevated survival rate compared to the outcome observed with anti-PD-1 monotherapy. Conclusion: PGF is a pro-angiogenic molecule in bladder cancer that requires significant expression levels of VEGFR1 in endothelial cells. Notably, the concurrent inhibition of PGF and VEGFA amplifies the therapeutic impact of anti-PD-1 treatment in bladder cancer. These findings provide further insights into the role of PGF in angiogenesis regulation and have conceptual implications for combining anti-angiogenic therapy with immune therapy in bladder cancer treatment.

SCYL1-mediated regulation of the mTORC1 signaling pathway inhibits autophagy and promotes gastric cancer metastasis

BACKGROUND

The SCY1-like (SCYL) family has been reported to be closely related to cancer metastasis, but it has not been reported in gastric cancer (GC), and its specific mechanism is not clear.

METHODS

We utilized databases like Deepmap, TCGA, and GEO to identify SCYL1's role in GC. Clinical samples were analyzed for SCYL1 expression and its correlation with patient prognosis. In vitro and in vivo experiments were conducted to assess SCYL1's function in GC cell migration, invasion, and autophagy.

RESULTS

SCYL1 showed an increased expression in GC tissues, which correlated with a negative prognosis. In vitro experiments demonstrated that SCYL1 promotes GC cell migration and invasion and inhibits autophagy. GSEA indicated an inverse relationship between SCYL1 and autophagy, while a direct relationship was observed with the mTORC1 signaling pathway. Knockdown of SCYL1 enhanced autophagy, while activation of mTORC1 reversed this effect.

CONCLUSIONS

SCYL1 is a significant contributor to GC progression, promoting metastasis by activating the mTORC1 signaling pathway and inhibiting autophagy. These findings suggest SCYL1 as a potential therapeutic target for GC treatment.

Mechanisms of HIF1A-mediated immune evasion in gastric cancer and the impact on therapy resistance

BACKGROUND

The high prevalence and detrimental effects on patient outcomes make gastric cancer (GC) a significant health issue that persists internationally. Existing treatment modalities exhibit limited efficacy, prompting the exploration of immune checkpoint inhibitors as a novel therapeutic approach. However, resistance to immunotherapy poses a significant challenge in GC management, necessitating a profound grasp of the intrinsic molecular pathways.

METHODS

This study focuses on investigating the immunosuppressive mechanisms of quiescent cancer cells (QCCs) in GC, particularly their resistance to T-cell-mediated immune responses. Utilizing mouse models, gene editing techniques, and transcriptome sequencing, we aim to elucidate the interactions between QCCs, immune cells, and key regulatory factors like HIF1A. Functional enrichment analysis will further underscore the role of glycolysis-related genes in mediating immunosuppression by QCCs.

RESULTS

The cancer cells that survived GC treated with T-cell therapy lost their proliferative ability. QCCs, as the main resistance force to immunotherapy, exhibit stronger resistance to CD8+ T-cell attack and possess higher cancer-initiating potential. Single-cell sequencing analysis revealed that the microenvironment in the QCCs region harbors more M2-type tumor-associated macrophages and fewer T cells. This microenvironment in the QCCs region leads to the downregulation of T-cell immune activation and alters macrophage metabolic function. Transcriptome sequencing of QCCs identified upregulated genes related to chemo-resistance, hypoxia, and glycolysis. In vitro cell experiments illustrated that HIF1A promotes the transcription of glycolysis-related genes, and silencing HIF1A in QCCs enhances T-cell proliferation and activation in co-culture systems, induces apoptosis in QCCs, and increases QCCs' sensitivity to immune checkpoint inhibitors. In vivo, animal experiments showed that silencing HIF1A in QCCs can inhibit GC growth and metastasis.

CONCLUSION

Unraveling the molecular mechanisms by which QCCs resist T-cell-mediated immune responses through immunosuppression holds promising implications for refining treatment strategies and enhancing patient outcomes in GC. By delineating these intricate interactions, this study contributes crucial insights into precision medicine and improved therapeutic outcomes in GC management.

Unraveling the ecological landscape of mast cells in esophageal cancer through single-cell RNA sequencing

Background

Esophageal cancer (EC) is a major health issue, ranking seventh in incidence and sixth in mortality worldwide. Despite advancements in multidisciplinary treatment approaches, the 5-year survival rate for EC remains low at 21%. Challenges in EC treatment arise from late-stage diagnosis, high malignancy, and poor prognosis. Understanding the tumor microenvironment is critical, as it includes various cellular and extracellular components that influence tumor behavior and treatment response. Mast cells (MCs), as tissue-resident immune cells, play dual roles in tumor dynamics. High-throughput single-cell RNA sequencing offers a powerful tool for analyzing tumor heterogeneity and immune interactions, although its application in EC is limited.

Methods

In this study, we investigated the immune microenvironment of EC using single-cell RNA sequencing and established a comprehensive immune profile. We also performed analysis of upstream transcription factors and downstream pathway enrichment to further comprehensively decipher MCs in EC. Besides, we performed knockdown experiments to explore the role of epidermal growth factor receptor (EGFR) signaling pathway in MCs-tumor cell interactions, highlighting its potential as a prognostic marker. Finally, we constructed a prognostic model for EC, which provided valuable suggestions for the diagnosis and prognosis of EC.

Results

Our analysis identified 11 major cell types, of which MCs were particularly present in pericarcinoma tissues. Further grouping of the 5,001 MCs identified 8 distinct subtypes, including SRSF7-highly expressed MCs, which showed strong tumor preference and potential tumor-promoting properties. Moreover, we identified the key signaling receptor EGFR and validated it by in vitro knockdown experiments, demonstrating its cancer-promoting effects. In addition, we established an independent prognostic indicator, SRSF7+ MCs risk score (SMRS), which showed a correlation between high SMRS group and poor prognosis.

Conclusion

These findings illuminate the complex interactions within the tumor microenvironment of EC and suggest that targeting specific MCs subtypes, particularly via the EGFR signaling pathway, may present novel therapeutic strategies. This study establishes a comprehensive immune map of EC, offering insights for improved treatment approaches.

Single-cell RNA transcriptomic analyses of tumor microenvironment of ovarian metastasis in gastric cancer

PURPOSE

Ovarian metastasis of gastric cancer (GC), commonly referred to as Krukenberg tumors, leads to a poor prognosis. However, the cause of metastasis remains unknown. Here, we present an integrated single-cell RNA sequencing (scRNA-Seq) analysis of the immunological microenvironment of two paired clinical specimens with ovarian metastasis of GC.

METHODS

scRNA-Seq was performed to determine the immunological microenvironment in ovarian metastasis of gastric cancer. CellChat was employed to analyze cell-cell communications across different cell types. Functional enrichment analysis was done by enrichKEGG in clusterProfiler. GEPIA2 was used to assess the influence of certain genes and gene signatures on prognosis.

RESULTS

The ovarian metastasis tissues exhibit a heterogenous immunological microenvironment compared to the primary tumors. Exhaustion of T and B cells is observed in the ovarian metastasis tissues. Compared to the paired adjacent non-tumoral and primary tumors, the ratio of endothelial cells and fibroblasts is high in the ovarian metastasis tissues. Compared to primary ovarian cancers, we identify a specific group of tumor-associated fibroblasts with MFAP4 and CAPNS1 expression in the ovarian metastatic tissues of GC. We further define metastasis-related-endothelial and metastasis-related-fibroblast signatures and indicate that patients with these high signature scores have a poor prognosis. In addition, the ovarian metastasis tissue has a lower level of intercellular communications compared to the primary tumor.

CONCLUSION

Our findings reveal the immunological microenvironment of ovarian metastasis of gastric cancer and will promote the discovery of new therapeutic strategies for ovarian metastasis in gastric cancer.