Spatiotemporal Immune Landscape of Colorectal Cancer Liver Metastasis at Single-Cell Level

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.

Integrating bulk RNA-seq and scRNA-seq analyses revealed the function and clinical value of thrombospondins in colon cancer

Background

Acting as mediators in cell-matrix and cell-cell communication, matricellular proteins play a crucial role in cancer progression. Thrombospondins (TSPs), a type of matricellular glycoproteins, are key regulators in cancer biology with multifaceted roles. Although TSPs have been implicated in anti-tumor immunity and epithelial-mesenchymal transition (EMT) in several malignancies, their specific roles to colon cancer remain elusive. Addressing this knowledge gap is essential, as understanding the function of TSPs in colon cancer could identify new therapeutic targets and prognostic markers.

Methods

Analyzing 1981 samples from 10 high-throughput datasets, including six bulk RNA-seq, three scRNA-seq, and one spatial transcriptome dataset, our study investigated the prognostic relevance, risk stratification value, immune heterogeneity, and cellular origin of TSPs, as well as their influence on cancer-associated fibroblasts (CAFs). Utilizing survival analysis, unsupervised clustering, and functional enrichment, along with multiple correlation analyses of the tumor-microenvironment (TME) via Gene Set Variation Analysis (GSVA), spatial localization, Monocle2, and CellPhoneDB, we provided insights into the clinical and cellular implications of TSPs.

Results

First, we observed significant upregulation of THBS2 and COMP in colon cancer, both of which displayed significant prognostic value. Additionally, we detected a significant positive correlation between TSPs and immune cells, as well as marker genes of EMT. Second, based on TSPs expression, patients were divided into two clusters with distinct prognoses: the high TSPs expression group (TSPs-H) was characterized by pronounced immune and stromal cell infiltration, and notably elevated T-cell exhaustion scores. Subsequently, we found that THBS2 and COMP may be associated with the differentiation of CAFs into pan-iCAFs and pan-dCAFs, which are known for their heightened matrix remodeling activities. Moreover, THBS2 enhanced CAFs communication with vascular endothelial cells and monocyte-macrophages. CAFs expressing THBS2 (THBS2+ CAFs) demonstrated higher scores across multiple signaling pathways, including angiogenic, EMT, Hedgehog, Notch, Wnt, and TGF-β, when compared to THBS2- CAFs. These observations suggest that THBS2 may be associated with stronger pro-carcinogenic activity in CAFs.

Conclusions

This study revealed the crucial role of TSPs and the significant correlation between THBS2 and CAFs interactions in colon cancer progression, providing valuable insights for targeting TSPs to mitigate cancer progression.

Immune modulation of the liver metastatic colorectal cancer microenvironment via the oral CAPOX-mediated cGAS-STING pathway

We evaluated modulation of the immunosuppressive tumor microenvironment in both local and liver metastatic colorectal cancer (LMCC), focusing on tumor-associated macrophages, which are the predominant immunosuppressive cells in LMCC. We developed an orally administered metronomic chemotherapy regimen, oral CAPOX. This regimen combines capecitabine and a nano-micelle encapsulated, lysine-linked deoxycholate and oxaliplatin complex (OPt/LDC-NM). The treatment effectively modulated immune cells within the tumor microenvironment by activating the cGAS-STING pathway and inducing immunogenic cell death. This therapy modulated immune cells more effectively than did capecitabine monotherapy, the current standard maintenance chemotherapy for colorectal cancer. The macrophage-modifying effect of oral CAPOX was mediated via the cGAS-STING pathway. This is a newly identified mode of immune cell activation induced by metronomic chemotherapy. Moreover, oral CAPOX synergized with anti-PD-1 antibody (αPD-1) to enhance the T-cell-mediated antitumor immune response. In the CT26. CL25 subcutaneous model, combination therapy achieved a 91 % complete response rate with a confirmed memory effect against the tumor. This combination also altered the immunosuppressive tumor microenvironment in LMCC, which αPD-1 monotherapy could not achieve. Oral CAPOX and αPD-1 combination therapy outperformed the maximum tolerated dose for treating LMCC, suggesting metronomic therapy as a promising strategy.

Spatial landscapes of cancers: insights and opportunities

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Single-cell transcriptomic analysis of immune cell dynamics in the healthy human endometrium

The microenvironment of the endometrial immune system is crucial to the success of placental implantation and healthy pregnancy. However, the functionalities of immune cells across various stages of the reproductive cycle have yet to be fully comprehended. To address this, we conducted advanced bioinformatic analysis on 230,049 high-quality single-cell transcriptomes from healthy endometrial samples obtained during the proliferative, secretory, early pregnancy, and late pregnancy stages. Our investigation has unveiled that proliferative natural killer (NK) cells, a potential source of endometrial NK cells, exhibit the most robust proliferative and differentiation potential during non-pregnant stages. We have also identified similar differentiation trajectories of NK cells originating from proliferative NK cells across four stages. Notably, during early pregnancy, NK cells demonstrate the highest oxidative phosphorylation metabolism activity, and, in conjunction with macrophages and T cells, exhibit the strongest type II interferon response. With spatial transcriptome data, we have discerned that the most robust immune-non-immune interactions are associated with the promotion and inhibition of cell proliferation, differentiation and migration during four stages. Furthermore, we have compiled lists of stage-specific risk genes implicated in reproductive diseases, which hold promise as potential disease biomarkers. Our study provides insights into the dynamics of the endometrial immune microenvironment during different reproductive cycle stages, thus serving as a reference for detecting pathological changes during pregnancy.

Immunomodulatory molecules in colorectal cancer liver metastasis

Colorectal cancer (CRC) ranks as the third most common cancer and the second leading cause of cancer-related deaths. According to clinical diagnosis and treatment, liver metastasis occurs in approximately 50 % of CRC patients, indicating a poor prognosis. The unique immune tolerance of the liver fosters an immunosuppressive tumor microenvironment (TME). In the context of tumors, numerous membrane and secreted proteins have been linked to tumor immune evasion as immunomodulatory molecules, but much remains unknown about how these proteins contribute to immune evasion in colorectal cancer liver metastasis (CRLM). This article reviews recently discovered membrane and secreted proteins with roles as both immunostimulatory and immunosuppressive molecules within the TME that influence immune evasion in CRC primary and metastatic lesions, particularly their mechanisms in promoting CRLM. This article also addresses screening strategies for identifying proteins involved in immune evasion in CRLM and provides insights into potential protein targets for treating CRLM.

Comprehensive analysis of shared risk genes and immunity-metabolisms between non-alcoholic fatty liver disease and atherosclerosis via bulk and single-cell transcriptome analyses

Objective

and design: Considering the clinical link between non-alcoholic fatty liver disease (NAFLD) and atherosclerosis (AS), we performed bioinformatics analysis to uncover their pathogenic interrelationship.

Methods and results

Data from the U.S. National Health and Nutritional Examination Survey (NHANES) 1999-2018 were included. Among 4851 participants in NHANES, NAFLD was significantly associated with atherosclerotic cardiovascular disease risk (ASCVD risk) (OR = 2.32, 95%CI: 2.04-2.65, P < 0.0001). We conducted WGCNA analysis for NAFLD (GSE130970) and AS (GSE28829) and identified three modules positively related to NAFLD severity and two modules accelerating atherosclerosis plaque progression. 198 key-modules genes were obtained via overlapping these modules. Next, we mined the disease-controlled differentially expressed genes (DEGs) from NAFLD (GSE89632) and AS (GSE100927), respectively. The final common risk genes (ACP5, TP53I3, RPS6KA1, TYMS, TREM2, CA12, and IFI27) were defined by intersecting the upregulated DEGs with 198 genes and validated in new datasets (GSE48452 and GSE43292). Importantly, they showed good diagnostic ability for NAFLD and AS. Immune infiltration analysis showed both illnesses have dysregulated immunity. Analysis of single-cell sequencing datasets NAFLD (GSE179886) and AS (GSE159677) uncovered different abnormal expressions of seven common genes in different immune cells while highlighting metabolic disturbances including upregulation of fatty acid biosynthesis, downregulation of fatty acid degradation and elongation.

Conclusion

We found 7 shared hub genes with good diagnostic ability and depicted the landscapes of immune and metabolism involved in NAFLD and AS. Our results provided a comprehensive association between them and may contribute to developing potential intervention strategies for targeting both disorders based on these risk factors.

Exploring the prognostic value of BRMS1 + microglia based on single-cell anoikis regulator patterns in the immunologic microenvironment of GBM

BACKGROUND

Anoikis is a specialized form of programmed cell death induced by the loss of cell adhesion to the extracellular matrix (ECM). Acquisition of anoikis resistance is a significant marker for cancer cell invasion, metastasis, therapy resistance, and recurrence. Although current research has identified multiple factors that regulate anoikis resistance, the pathological mechanisms of anoikis-mediated tumor microenvironment (TME) in glioblastoma (GBM) remain largely unexplored.

METHODS

Utilizing single-cell RNA sequencing (scRNA-seq) data and employing non-negative matrix factorization (NMF), we identified and characterized TME cell clusters with distinct anoikis-associated gene signatures. Prognostic and therapeutic response analyses were conducted using TCGA and CGGA datasets to assess the clinical significance of different TME cell clusters. The spatial relationship between BRMS1 + microglia and tumor cells was inferred from spatial transcriptome RNA sequencing (stRNA-seq) data. To simulate the tumor immune microenvironment, co-culture experiments were performed with microglia (HMC3) and GBM cells (U118/U251), and microglia were transfected with a BRMS1 overexpression lentivirus. Western blot or ELISA were used to detect BRMS1, M2 macrophage-specific markers, PI3K/AKT signaling proteins, and apoptosis-related proteins. The proliferation and apoptosis capabilities of tumor cells were evaluated using CCK-8, colony formation, and apoptosis assays, while the invasive and migratory abilities of tumor cells were assessed using Transwell assays.

RESULTS

NMF-based analysis successfully identified CD8 + T cell and microglia cell clusters with distinct gene signature characteristics. Trajectory analysis, cell communication, and gene regulatory network analyses collectively indicated that anoikis-mediated TME cell clusters can influence tumor cell development through various mechanisms. Notably, BRMS1 + AP-Mic exhibited an M2 macrophage phenotype and had significant cell communication with malignant cells. Moreover, high expression of BRMS1 + AP-Mic in TCGA and CGGA datasets was associated with poorer survival outcomes, indicating its detrimental impact on immunotherapy. Upregulation of BRMS1 in microglia may lead to M2 macrophage polarization, activate the PI3K/AKT signaling pathway through SPP1/CD44-mediated cell interactions, inhibit tumor cell apoptosis, and promote tumor proliferation and invasion.

CONCLUSION

This pioneering study used NMF-based analysis to reveal the important predictive value of anoikis-regulated TME in GBM for prognosis and immunotherapeutic response. BRMS1 + microglial cells provide a new perspective for a deeper understanding of the immunosuppressive microenvironment of GBM and could serve as a potential therapeutic target in the future.

Single-cell analysis identified PDIA3 as regulator of malignant characteristics and macrophage function in human cancers

Protein disulfide isomerase A3 (PDIA3) is an endoplasmic reticulum (ER) protein. It has different functions including glycoprotein folding in the ER. The unfavorable prognosis of cancer patients was related to the abnormal PDIA3 expression level. However, it is unclear how PDIA3 correlates with the malignant characteristics of different tumors and its impact on tumor immunity. Pan-cancer data were downloaded from several databases for large-scale bioinformatics analysis. The immunological functions of PDIA3 were systematically explored at the single-cell sequencing level, including cell communication, cell metabolism, cell evolution and epigenetic modification. We performed immunofluorescence staining to visualize PDIA3 expression and infiltration of macrophages in pan-cancer samples. Further, we performed a loss-of-function assay of PDIA3 in vitro. The CCK8 assay, clone formation assay, and transwell assay were performed. M2 macrophages were co-cultured with different cell lines before the transwell assay was performed. The immunofluorescence staining of pan-cancer samples presented a higher expression of PDIA3 than those of the paired normal tissues. According to single-cell sequencing analysis, expression of PDIA3 was closely associated with cell communication, cell metabolism, cell evolution and epigenetic modification. The knockdown of PDIA3 in tumor cells inhibited cell proliferation and invasion, and restrained cocultured M2 macrophage migration. Furthermore, PDIA3 displayed predictive value in immunotherapy response in human cancer cohorts, indicating a potential therapeutic target. Our study showed that PDIA3 was associated with tumor malignant characteristics and could mediate the migration of M2 macrophages in various tumor types. PDIA3 could be a promising target to achieve tumor control and improve the immune response on a pan-cancer scale.

CCL19-producing fibroblasts promote tertiary lymphoid structure formation enhancing anti-tumor IgG response in colorectal cancer liver metastasis

Tertiary lymphoid structures (TLSs) are associated with enhanced immunity in tumors. However, their formation and functions in colorectal cancer liver metastasis (CRLM) remain unclear. Here, we reveal that intra- and peri-tumor mature TLSs (TLS+) are associated with improved clinical outcomes than TLS- tumors. Using single-cell-RNA-sequencing and spatial-enhanced-resolution-omics-sequencing (Stereo-seq), we reveal that TLS+ tumors are enriched with IgG+ plasma cells (PCs), while TLS- tumors are characterized with IgA+ PCs. By generating TLS-associated PC-derived monoclonal antibodies in vitro, we show that TLS-PCs secrete tumor-targeting antibodies. As the proof-of-concept, we demonstrate the anti-tumor activities of TLS-PC-mAb6 antibody in humanized mouse model of colorectal cancer. We identify a fibroblast lineage secreting CCL19 that facilitates lymphocyte trafficking to TLSs. CCL19 treatment promotes TLS neogenesis and prevents tumor growth in mice. Our data uncover the central role of CCL19+ fibroblasts in TLS formation, which in turn generates therapeutic antibodies to restrict CRLM.

Unraveling the Connection: Extracellular Vesicles and Non-Small Cell Lung Cancer

Extracellular vesicles (EVs) are nanoscale lipid bilayer vesicles released during cell activation, cellular damage, or apoptosis. They carry nucleic acids, proteins, and lipids facilitating intercellular communication and activate signaling pathways in target cells. In non-small cell lung cancer (NSCLC), EVs may contribute to tumor growth and metastasis by modulating immune responses, facilitating epithelial-mesenchymal transition, and promoting angiogenesis, while potentially contributing to resistance to chemotherapy drugs. EVs in liquid biopsies serve as non-invasive biomarkers for early cancer detection and diagnosis. Due to their small size, inherent molecular transport properties, and excellent biocompatibility, EVs also act as natural drug delivery vehicles in NSCLC therapy.

Consensus clustering and development of a risk signature based on trajectory differential genes of cancer-associated fibroblast subpopulations in colorectal cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) play a crucial role in the progression of colorectal cancer (CRC). However, the impact of CAF subpopulation trajectory differentiation on CRC remains unclear.

METHODS

In this study, we first explored the trajectory differences of CAFs subpopulations using bulk and integrated single-cell sequencing data, and then performed consensus clustering of CRC samples based on the trajectory differential genes of CAFs subpopulations. Subsequently, we analyzed the heterogeneity of CRC subtypes using bioinformatics. Finally, we constructed relevant prognostic signature using machine learning and validated them using spatial transcriptomic data.

RESULTS

Based on the differential genes of CAFs subpopulation trajectory differentiation, we identified two CRC subtypes (C1 and C2) in this study. Compared to C1, C2 exhibited worse prognosis, higher immune evasion microenvironment and high CAF characteristics. C1 was primarily associated with metabolism, while C2 was primarily associated with cell metastasis and immune regulation. By combining 101 combinations of 10 machine learning algorithms, we developed a High-CAF risk signatures (HCAFRS) based on the C2 characteristic gene. HCAFRS was an independent prognostic factor for CRC and, when combined with clinical parameters, significantly predicted the overall survival of CRC patients. HCAFRS was closely associated with epithelial-mesenchymal transition, angiogenesis, and hypoxia. Furthermore, the risk score of HCAFRS was mainly derived from CAFs and was validated in the spatial transcriptomic data.

CONCLUSION

In conclusion, HCAFRS has the potential to serve as a promising prognostic indicator for CRC, improving the quality of life for CRC patients.

A comprehensive single-cell RNA transcriptomic analysis identifies a unique SPP1+ macrophages subgroup in aging skeletal muscle

Senescence of skeletal muscle (SkM) has been a primary contributor to senior weakness and disability in recent years. The gradually declining SkM function associated with senescence has recently been connected to an imbalance between damage and repair. Macrophages (Mac) are involved in SkM aging, and different macrophage subgroups hold different biological functions. Through comprehensive single-cell transcriptomic analysis, we first compared the metabolic pathways and biological functions of different types of cells in young (Y) and old (O) mice SkM. Strikingly, the Mac population in mice SkM was also explored, and we identified a unique Mac subgroup in O SkM characterized by highly expressed SPP1 with strong senescence and adipogenesis features. Further work was carried out on the metabolic and biological processes for these Mac subgroups. Besides, we verified that the proportion of the SPP1+ Mac was increased significantly in the quadriceps tissues of O mice, and the senotherapeutic drug combination dasatinib + quercetin (D + Q) could dramatically reduce its proportion. Our study provides novel insight into the potential role of SPP1+ Mac in SkM, which may serve as a senotherapeutic target in SkM aging.

Exploring macrophage heterogeneity in IgA nephropathy: Mechanisms of renal impairment and current therapeutic targets

The lack of understanding of the mechanism of renal injury in IgA nephropathy (IgAN) hinders the development of personalized treatment plans and targeted therapies. Improved insight into the cause of renal dysfunction in IgAN is necessary to enhance the effectiveness of strategies for slowing the progression of the disease. This study examined single cell RNA sequencing (scRNA seq) and bulk-RNA seq data and found that the gene expression of renal intrinsic cells (RIC) was significantly changed in patients with renal impairment, with a primary focus on energy metabolism. We discovered a clear metabolic reprogramming of RIC during renal function impairment (RF) using the 'scMetabolism' package, which manifested as a weakening of oxidative phosphorylation, alterations in fatty acid metabolism, and changes in glycolysis. Cellular communication analysis revealed that communication between macrophages (Ma) and RIC became more active and impacted cell function through the ligand-receptor-transcription factor (L-R-TF) axis in patients with RF. Our studies showed a notable upsurge in the expression of gene CLU and the infiltration of CLU+ Ma in patients with RF. CLU is a multifunctional protein, extensively involved in processes such as cell apoptosis and immune responses. Data obtained from the Nephroseq V5 database and multiplex immunohistochemistry (mIHC) were used to validate the findings, which were found to be robustly correlated with estimated glomerular filtration rate (eGFR) of the IgAN patients, as demonstrated by linear regression (LR). This study provides new insights into the cellular and molecular changes that occur in IgAN during renal impairment, revealing that elevated expression of CLU and CLU+ Ma percolation are common features in patients with RF. These findings offer potential targets and strategies for personalized management and targeted therapy of IgAN.

Single-cell RNA sequencing reveals that an imbalance in monocyte subsets rather than changes in gene expression patterns is a feature of postmenopausal osteoporosis

The role of monocytes in postmenopausal osteoporosis is widely recognized; however, the mechanisms underlying monocyte reprogramming remain unknown. In this study, single-cell RNA sequencing (scRNA-seq) was conducted on CD14+ bone marrow monocytes obtained from 3 postmenopausal women with normal BMD and 3 women with postmenopausal osteoporosis (PMOP). Monocle2 was used to classify the monocytes into 7 distinct clusters. The proportion of cluster 1 significantly decreased in PMOP patients, while the proportion of cluster 7 increased. Further analysis via GSEA, transcription factor activity analysis, and sc-metabolic analysis revealed significant differences between clusters 1 and 7. Cluster 7 exhibited upregulated pathways associated with inflammation, immunity, and osteoclast differentiation, whereas cluster 1 demonstrated the opposite results. Monocle2, TSCAN, VECTOR, and scVelo data indicated that cluster 1 represented the initial subset and that cluster 7 represents one of the terminal subsets. BayesPrism and ssGSEA were employed to analyze the bulk transcriptome data obtained from the GEO database. The observed alterations in the proportions of 1 and 7 were validated and found to have diagnostic significance. CD16 serves as the marker gene for cluster 7, thus leading to an increased proportion of CD16+ monocytes in women with PMOP. Flow cytometry was used to assess the consistency of outcomes with those of the bioinformatic analysis. Subsequently, an additional scRNA-seq analysis was conducted on bone marrow mononuclear cells obtained from 3 patients with PMOP and 3 postmenopausal women with normal BMD. The differential proportions of cluster 1 and cluster 7 were once again confirmed, with the pathological effect of cluster 7 may attribute to cell-cell communication. The scRNA-seq findings suggest that an imbalance in monocyte subsets is a characteristic feature of PMOP. These findings elucidate the limitations of utilizing bulk transcriptome data for detecting alterations in monocytes, which may influence novel research inquiries.

Mechanism insights and therapeutic intervention of tumor metastasis: latest developments and perspectives

Metastasis remains a pivotal characteristic of cancer and is the primary contributor to cancer-associated mortality. Despite its significance, the mechanisms governing metastasis are not fully elucidated. Contemporary findings in the domain of cancer biology have shed light on the molecular aspects of this intricate process. Tumor cells undergoing invasion engage with other cellular entities and proteins en route to their destination. Insights into these engagements have enhanced our comprehension of the principles directing the movement and adaptability of metastatic cells. The tumor microenvironment plays a pivotal role in facilitating the invasion and proliferation of cancer cells by enabling tumor cells to navigate through stromal barriers. Such attributes are influenced by genetic and epigenetic changes occurring in the tumor cells and their surrounding milieu. A profound understanding of the metastatic process's biological mechanisms is indispensable for devising efficacious therapeutic strategies. This review delves into recent developments concerning metastasis-associated genes, important signaling pathways, tumor microenvironment, metabolic processes, peripheral immunity, and mechanical forces and cancer metastasis. In addition, we combine recent advances with a particular emphasis on the prospect of developing effective interventions including the most popular cancer immunotherapies and nanotechnology to combat metastasis. We have also identified the limitations of current research on tumor metastasis, encompassing drug resistance, restricted animal models, inadequate biomarkers and early detection methods, as well as heterogeneity among others. It is anticipated that this comprehensive review will significantly contribute to the advancement of cancer metastasis research.

Unraveling the connection between Hashimoto's Thyroiditis and non-alcoholic fatty liver disease: exploring the role of CD4+central memory T cells through integrated genetic approaches

PURPOSE

Exploring the connection between Hashimoto's thyroiditis (HT) and non-alcoholic fatty liver disease (NAFLD) through integrated genetic approaches.

METHODS

We utilized integrated genetic approaches, such as single-cell RNA sequencing (scRNA-seq) data analysis, Mendelian Randomization (MR), colocalization analysis, cell communication, and metabolic analyses, to investigate potential correlations between HT and NAFLD.

RESULTS

Through the integrated analysis of scRNA-seq data from individuals with HT, NAFLD, and healthy controls, we observed an upregulation in the proportion of CD4+central memory (CD4+CM) T cells among T cells in both diseases. A total of 63 differentially expressed genes (DEGs) were identified in the CD4+CM cells after the differential analysis. By using MR, 8 DEGs (MAGI3, CSGALNACT1, CAMK4, GRIP1, TRAT1, IL7R, ERN1, and MB21D2) were identified to have a causal relationship with HT, and 4 DEGs (MAGI3, RCAN3, DOCK10, and SAMD12) had a causal relationship with NAFLD. MAGI3 was found to be causally linked to both HT and NAFLD. Therefore, MAGI3 was designated as the marker gene. Reverse MR and Steiger filtering showed no evidence of reverse causality. Colocalization analyses further indicated close links between MAGI3 and HT as well as NAFLD. Finally, based on the expression levels of MAGI3, we stratified CD4+CM cells into two subsets: MAGI3+CD4+CM cells and MAGI3-CD4+CM cells. Functional analyses revealed significant differences between the two subsets, potentially related to the progression of the two diseases.

CONCLUSION

This study delves into the potential connections between HT and NAFLD through integrated genetic methods. Our research reveals an elevated proportion of CD4+CM cells within T cells in both HT and NAFLD. Through MR and colocalization analysis, we identify specific genes causally linked to HT and NAFLD, such as MAGI3. Ultimately, based on MAGI3 expression levels, we categorize CD4+CM cells into MAGI3+CD4+CM cells and MAGI3-CD4+CM cells, uncovering significant differences between them through functional analyses.

Prognostic Analysis Combining Histopathological Features and Clinical Information to Predict Colorectal Cancer Survival from Whole-Slide Images

BACKGROUND

Colorectal cancer (CRC) is a malignant tumor within the digestive tract with both a high incidence rate and mortality. Early detection and intervention could improve patient clinical outcomes and survival.

METHODS

This study computationally investigates a set of prognostic tissue and cell features from diagnostic tissue slides. With the combination of clinical prognostic variables, the pathological image features could predict the prognosis in CRC patients. Our CRC prognosis prediction pipeline sequentially consisted of three modules: (1) A MultiTissue Net to delineate outlines of different tissue types within the WSI of CRC for further ROI selection by pathologists. (2) Development of three-level quantitative image metrics related to tissue compositions, cell shape, and hidden features from a deep network. (3) Fusion of multi-level features to build a prognostic CRC model for predicting survival for CRC.

RESULTS

Experimental results suggest that each group of features has a particular relationship with the prognosis of patients in the independent test set. In the fusion features combination experiment, the accuracy rate of predicting patients' prognosis and survival status is 81.52%, and the AUC value is 0.77.

CONCLUSION

This paper constructs a model that can predict the postoperative survival of patients by using image features and clinical information. Some features were found to be associated with the prognosis and survival of patients.

Single-cell transcriptomics reveals CD8+ T cell structure and developmental trajectories in idiopathic pulmonary fibrosis

Immune cells in the human lung are associated with idiopathic pulmonary fibrosis. However, the contribution of different immune cell subpopulations to the pathogenesis of pulmonary fibrosis remains unclear. We used single-cell RNA sequencing data to investigate the transcriptional profiles of immune cells in the lungs of 5 IPF patients and 3 subjects with non-fibrotic lungs. In an identifiable population of immune cells, we found increased percentage of CD8+ T cells in the T cell subpopulation in IPF. Monocle analyzed the dynamic immune status and cell transformation of CD8+ T cells, as well as the cytotoxicity and exhausted status of CD8+ T cell subpopulations at different stages. Among CD8+ T cells, we found differences in metabolic pathways in IPF and Ctrl, including lipid, amino acid and carbohydrate metabolic. By analyzing the metabolites of CD8+ T cells, we found that different populations of CD8+ T cells in IPF have unique metabolic characteristics, but they also have multiple identical up-regulated or down-regulated metabolites. In IPF, signaling pathways associated with fibrosis were enriched in CD8+ T cells, suggesting that CD8+ T cells may have an important contribution to fibrosis. Finally, we analyzed the interactions between CD8+ T cells and other cells. Together, these studies highlight key features of CD8+ T cells in the pathogenesis of IPF and help to develop effective therapeutic targets.

FASN-mediated fatty acid biosynthesis remodels immune environment in Clonorchis sinensis infection-related intrahepatic cholangiocarcinoma

BACKGROUND & AIMS

Intrahepatic cholangiocarcinoma (iCCA) is the second most common primary liver cancer and is highly lethal. Clonorchis sinensis (C. sinensis) infection is an important risk factor for iCCA. Here we investigated the clinical impact and underlying molecular characteristics of C. sinensis infection-related iCCA.

METHODS

We performed single-cell RNA sequencing, whole-exome sequencing, RNA sequencing, metabolomics and spatial transcriptomics in 251 patients with iCCA from three medical centers. Alterations in metabolism and the immune microenvironment of C. sinensis-related iCCAs were validated through an in vitro co-culture system and in a mouse model of iCCA.

RESULTS

We revealed that C. sinensis infection was significantly associated with iCCA patients' overall survival and response to immunotherapy. Fatty acid biosynthesis and the expression of fatty acid synthase (FASN), a key enzyme catalyzing long-chain fatty acid synthesis, were significantly enriched in C. sinensis-related iCCAs. iCCA cell lines treated with excretory/secretory products of C. sinensis displayed elevated FASN and free fatty acids. The metabolic alteration of tumor cells was closely correlated with the enrichment of tumor-associated macrophage (TAM)-like macrophages and the impaired function of T cells, which led to formation of an immunosuppressive microenvironment and tumor progression. Spatial transcriptomics analysis revealed that malignant cells were in closer juxtaposition with TAM-like macrophages in C. sinensis-related iCCAs than non-C. sinensis-related iCCAs. Importantly, treatment with a FASN inhibitor significantly reversed the immunosuppressive microenvironment and enhanced anti-PD-1 efficacy in iCCA mouse models treated with excretory/secretory products from C. sinensis.

CONCLUSIONS

We provide novel insights into metabolic alterations and the immune microenvironment in C. sinensis infection-related iCCAs. We also demonstrate that the combination of a FASN inhibitor with immunotherapy could be a promising strategy for the treatment of C. sinensis-related iCCAs.

IMPACT AND IMPLICATIONS

Clonorchis sinensis (C. sinensis)-infected patients with intrahepatic cholangiocarcinoma (iCCA) have a worse prognosis and response to immunotherapy than non-C. sinensis-infected patients with iCCA. The underlying molecular characteristics of C. sinensis infection-related iCCAs remain unclear. Herein, we demonstrate that upregulation of FASN (fatty acid synthase) and free fatty acids in C. sinensis-related iCCAs leads to formation of an immunosuppressive microenvironment and tumor progression. Thus, administration of FASN inhibitors could significantly reverse the immunosuppressive microenvironment and further enhance the efficacy of anti-PD-1 against C. sinensis-related iCCAs.

Single-Cell Analyses Reveal the Metabolic Heterogeneity and Plasticity of the Tumor Microenvironment during Head and Neck Squamous Cell Carcinoma Progression

Metabolic reprogramming is a hallmark of cancer. In addition to metabolic alterations in the tumor cells, multiple other metabolically active cell types in the tumor microenvironment (TME) contribute to the emergence of a tumor-specific metabolic milieu. Here, we defined the metabolic landscape of the TME during the progression of head and neck squamous cell carcinoma (HNSCC) by performing single-cell RNA sequencing on 26 human patient specimens, including normal tissue, precancerous lesions, early stage cancer, advanced-stage cancer, lymph node metastases, and recurrent tumors. The analysis revealed substantial heterogeneity at the transcriptional, developmental, metabolic, and functional levels in different cell types. SPP1+ macrophages were identified as a protumor and prometastatic macrophage subtype with high fructose and mannose metabolism, which was further substantiated by integrative analysis and validation experiments. An inhibitor of fructose metabolism reduced the proportion of SPP1+ macrophages, reshaped the immunosuppressive TME, and suppressed tumor growth. In conclusion, this work delineated the metabolic landscape of HNSCC at a single-cell resolution and identified fructose metabolism as a key metabolic feature of a protumor macrophage subpopulation. Significance: Fructose and mannose metabolism is a metabolic feature of a protumor and prometastasis macrophage subtype and can be targeted to reprogram macrophages and the microenvironment of head and neck squamous cell carcinoma.

Estrogen Receptor Blockade Potentiates Immunotherapy for Liver Metastases by Altering the Liver Immunosuppressive Microenvironment

Liver metastases (LM) remain a major cause of cancer-related death and are a major clinical challenge. LM and the female sex are predictors of a poorer response to immunotherapy but the underlying mechanisms remain unclear. We previously reported on a sexual dimorphism in the control of the tumor microenvironment (TME) of colorectal carcinoma liver metastases (CRCLM) and identified estrogen as a regulator of an immunosuppressive TME in the liver. Here we aimed to assess the effect of estrogen deprivation on the cytokine/chemokine profile associated with CRCLM, using a multiplex cytokine array and the RNAscope technology, and its effects on the innate and adaptive immune responses in the liver. We also evaluated the benefit of combining the selective estrogen-receptor degrader Fulvestrant with immune checkpoint blockade for the treatment of CRCLM. We show that estrogen depletion altered the cytokine/chemokine repertoire of the liver, decreased macrophage polarization, as reflected in reduced accumulation of tumor infiltrating M2 macrophages and increased the accumulation of CCL5+/CCR5+ CD8+ T and NKT cells in the liver TME. Similar results were obtained in a murine pancreatic ductal adenocarcinoma model. Importantly, treatment with Fulvestrant also increased the accumulation of CD8+CCL5+, CD8+CCR5+ T and NK cells in the liver TME and enhanced the therapeutic benefit of anti-PD1 immunotherapy, resulting in a significant reduction in the outgrowth of LM. Taken together, our results show that estrogen regulates immune cell recruitment to the liver and suggest that inhibition of estrogen action could potentiate the tumor-inhibitory effect of immunotherapy in hormone-independent and immunotherapy-resistant metastatic cancer.

SIGNIFICANCE

The immune microenvironment of the liver plays a major role in controlling the expansion of hepatic metastases and is regulated by estrogen. We show that treatment of tumor-bearing mice with an estrogen receptor degrader potentiated an anti-metastatic effect of immunotherapy. Our results provide mechanistic insight into clinical findings and a rationale for evaluating the efficacy of combination anti-estrogen and immunotherapy for prevention and/or treatment of hepatic metastases in female patients.

Comprehensive analysis of single-cell transcriptomics and genetic factors reveals the mechanisms and preventive strategies for the progression from pulmonary fibrosis to lung cancer

BACKGROUND

Pulmonary fibrosis (PF) leads to excessive deposition of fibrous connective tissue in the lungs, increasing the risk of lung cancer due to the enhanced activity of fibroblasts (FBs). Fibroblast-mediated collagen fiber deposition creates a tumor-like microenvironment, laying the foundation for tumorigenesis. Clinically, numerous cases of lung cancer induced by pulmonary fibrosis have been observed. In recent years, the study of nucleotide point mutations, which provide more detailed insights than gene expression, has made significant advancements, offering new perspectives for clinical research.

METHODS

We initially employed Mendelian randomization to ascertain that the initial stage of lung cancer induced by PF belongs to small cell lung cancer (SCLC). Subsequently, pulmonary neuroendocrine cells (PNECs) were identified by using pseudo-time series analysis as cell clusters with carcinogenic potential. We categorized FBs into four groups according to their cellular metabolism, and then analyzed the cellular communication between FBs and PNECs, as well as changes in intracellular pathways of PNECs. Additionally, we examined the characteristic genome of FBs which is significantly associated with PF and investigated the impact of FBs on immune cells in the PF microenvironment. Finally, we explored strategies for preventing the progression from PF to lung cancer.

RESULTS

The genetic features of cells with carcinogenic potential in PF tissues were revealed, characterized by upregulation of Achaete-Scute Family BHLH Transcription Factor 1 (ASCL1), Homeobox B2 (HOXB2), Teashirt Zinc Finger Homeobox 2 (TSHZ2), Insulinoma-associated 1 (INSM1), and reduced activity of RE1 Silencing Transcription Factor (REST). FBs characterized by high glycolysis and low tricarboxylic acid (TCA) cycling played a key role in the progression of PF. The microenvironment of PF resembles the tumor microenvironment, providing a conducive immunosuppressive environment for the occurrence of cancer cells. In dendritic cells, rs9265808 is a susceptibility locus for progression from pulmonary fibrosis to lung cancer, mutations at this locus increase the expression of Complement Factor B (CFB), and excessive activation of the complement pathway is a crucial factor leading to lung cancer development in patients with pulmonary fibrosis. Ensuring adequate nutritional supply and physical function is one of the effective measures to prevent progression from pulmonary fibrosis to lung cancer.

CONCLUSION

CFB promotes lung cancer occurrence by inducing the accumulation and polarization of a large number of monocytes/macrophages in the lungs, driving disease progression by reducing the physical fitness of patients with pulmonary fibrosis.

Identification and validation of tryptophan-related gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma reveals a critical role for PTTG1

Introduction

Tryptophan metabolism is strongly associated with immunosuppression and may influence lung adenocarcinoma prognosis as well as tumor microenvironment alterations.

Methods

Sequencing datasets were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Two different clusters were identified by consensus clustering, and prognostic models were established based on differentially expressed genes (DEGs) in the two clusters. We investigated differences in mutational landscapes, enrichment pathways, immune cell infiltration, and immunotherapy between high- and low-risk scoring groups. Single-cell sequencing data from Bischoff et al. were used to identify and quantify tryptophan metabolism, and model genes were comprehensively analyzed. Finally, PTTG1 was analyzed at the pan-cancer level by the pan-TCGA cohort.

Results

Risk score was defined as an independent prognostic factor for lung adenocarcinoma and was effective in predicting immunotherapy response in patients with lung adenocarcinoma. PTTG1 is one of the key genes, and knockdown of PTTG1 in vitro decreases lung adenocarcinoma cell proliferation and migration and promotes apoptosis and down-regulation of tryptophan metabolism regulators in lung adenocarcinoma cells.

Discussion

Our study revealed the pattern and molecular features of tryptophan metabolism in lung adenocarcinoma patients, established a model of tryptophan metabolism-associated lung adenocarcinoma prognosis, and explored the roles of PTTG1 in lung adenocarcinoma progression, EMT process, and tryptophan metabolism.

Spatial transcriptome and single-cell reveal the role of nucleotide metabolism in colorectal cancer progression and tumor microenvironment

BACKGROUND

The intricacies of nucleotide metabolism within tumor cells specific to colorectal cancer (CRC) remain insufficiently characterized. A nuanced examination of particular tumor clusters and their dynamic interplay with the tumor microenvironment (TME) may yield profound insights into these therapeutically auspicious communicative networks.

METHODS

By integrating ten types of single-cell enrichment scoring methods, we carried out enrichment analysis on CRC cell types, which was validated through four additional single-cell cohorts. Groups of tumor cells were determined using the average values of the scores. Using cellphonedb, monocle, inferCNV, SCENIC, and Cytotrace, functional analyses were performed. Utilizing the RCTD approach, single-cell groupings were mapped onto spatial transcriptomics, analyzing cell dependency and pathway activity to distinguish between tumor cell subtypes. Differential expression analysis identified core genes in nucleotide metabolism, with single-cell and spatial transcriptomics analyses elucidating the function of these genes in tumor cells and the immune microenvironment. Prognostic models were developed from bulk transcriptome cohorts to forecast responses to immune therapy. Laboratory experiments were conducted to verify the biological function of the core gene.

RESULTS

Nucleotide metabolism is significantly elevated in tumor cells, dividing them into two groups: NUhighepi and NUlowepi. The phenotype NUhighepi was discerned to exhibit pronounced malignant attributes. Utilizing the analytical tool stlearn for cell-to-cell communication assessment, it was ascertained that NUhighepi engages in intimate interactions with fibroblasts. Corroborating this observation, spatial transcriptome cell interaction assessment through MISTy unveiled a particular reliance of NUhighepi on fibroblasts. Subsequently, we pinpointed NME1, a key gene in nucleotide metabolism, affirming its role in thwarting metastasis via in vitro examination. Utilizing multiple machine learning algorithms, a stable prognostic model (NRS) has been developed, capable of predicting survival and responses to immune therapy. In addition, targeted drugs have been identified for both high and low scoring groups. Laboratory experiments have revealed that NME1 can inhibit the proliferation and invasion of CRC tumor cells.

CONCLUSION

Our study elucidates the potential pro-tumor mechanism of NUhighepi and the role of NME1 in inhibiting metastasis, further deepening the understanding of the role of nucleotide metabolism in colorectal cancer, and providing valuable targets for disrupting its properties.

Decoding the spatiotemporal heterogeneity of tumor-associated macrophages

Tumor-associated macrophages (TAMs) are pivotal in cancer progression, influencing tumor growth, angiogenesis, and immune evasion. This review explores the spatial and temporal heterogeneity of TAMs within the tumor microenvironment (TME), highlighting their diverse subtypes, origins, and functions. Advanced technologies such as single-cell sequencing and spatial multi-omics have elucidated the intricate interactions between TAMs and other TME components, revealing the mechanisms behind their recruitment, polarization, and distribution. Key findings demonstrate that TAMs support tumor vascularization, promote epithelial-mesenchymal transition (EMT), and modulate extracellular matrix (ECM) remodeling, etc., thereby enhancing tumor invasiveness and metastasis. Understanding these complex dynamics offers new therapeutic targets for disrupting TAM-mediated pathways and overcoming drug resistance. This review underscores the potential of targeting TAMs to develop innovative cancer therapies, emphasizing the need for further research into their spatial characteristics and functional roles within the TME.

Molecular characterization and clinical relevance of metabolic signature subtypes in gastric cancer

Metabolic reprogramming dictates tumor molecular attributes and therapeutic potentials. However, the comprehensive metabolic characteristics in gastric cancer (GC) remain obscure. Here, metabolic signature-based clustering analysis identifies three subtypes with distinct molecular and clinical features: MSC1 showed better prognosis and upregulation of the tricarboxylic acid (TCA) cycle and lipid metabolism, combined with frequent TP53 and RHOA mutation; MSC2 had moderate prognosis and elevated nucleotide and amino acid metabolism, enriched by intestinal histology and mismatch repair deficient (dMMR); and MSC3 exhibited poor prognosis and enhanced glycan and energy metabolism, accompanied by diffuse histology and frequent CDH1 mutation. The Shandong Provincial Hospital (SDPH) in-house dataset with matched transcriptomic, metabolomic, and spatial-metabolomic analysis also validated these findings. Further, we constructed the metabolic subtype-related prognosis gene (MSPG) scoring model to quantify the activity of individual tumors and found a positive correlation with cuproptosis signaling. In conclusion, comprehensive recognition of the metabolite signature can enhance the understanding of diversity and heterogeneity in GC.

CD87-targeted BiTE and CAR-T cells potently inhibit invasive nonfunctional pituitary adenomas

Recently, bispecific T-cell engagers (BiTEs) and chimeric antigen receptor-modified T cells (CAR-Ts) have been shown to have high therapeutic efficacy in hematological tumors. CD87 is highly expressed in solid tumors with an oncogenic function. To assess their cytotoxic effects on invasive nonfunctioning pituitary adenomas (iNFPAs), we first examined CD87 expression and its effects on the metabolism of iNFPA cells. We generated CD87-specific BiTE and CAR/IL-12 T cells, and their cytotoxic effects on iNFPAs cells and in mouse models were determined. CD87 had high expression in iNFPA tissue and cell samples but was undetected in noncancerous brain samples. CD87×CD3 BiTE and CD87 CAR/IL-12 T-cells showed antigenic specificity and exerted satisfactory cytotoxic effects, decreasing tumor cell proliferation in vitro and reducing existing tumors in experimental mice. Overall, the above findings suggest that CD87 is a promising target for the immunotherapeutic management of iNFPAs using anti-CD87 BiTE and CD87-specific CAR/IL-12 T cells.

HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics

Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higherF 1 scores (averageF 1 Score=0.948), improved computational efficiency, scalability, and reduced false positives (FPs). Through analysis of twelve real datasets from various spatial transcriptomic technologies, HEARTSVG identifies a greater number of biologically significant SVGs (average AUC = 0.792) than other comparative methods without prespecifying spatial patterns. Furthermore, by clustering SVGs, we uncover two distinct tumor spatial domains characterized by unique spatial expression patterns, spatial-temporal locations, and biological functions in human colorectal cancer data, unraveling the complexity of tumors.

Establishment of an ovarian cancer exhausted CD8+T cells-related genes model by integrated analysis of scRNA-seq and bulk RNA-seq

Ovarian cancer (OC) was the fifth leading cause of cancer death and the deadliest gynecological cancer in women. This was largely attributed to its late diagnosis, high therapeutic resistance, and a dearth of effective treatments. Clinical and preclinical studies have revealed that tumor-infiltrating CD8+T cells often lost their effector function, the dysfunctional state of CD8+T cells was known as exhaustion. Our objective was to identify genes associated with exhausted CD8+T cells (CD8TEXGs) and their prognostic significance in OC. We downloaded the RNA-seq and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. CD8TEXGs were initially identified from single-cell RNA-seq (scRNA-seq) datasets, then univariate Cox regression, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression were utilized to calculate risk score and to develop the CD8TEXGs risk signature. Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, time-dependent receiver operating characteristics (ROC), nomogram, and calibration were conducted to verify and evaluate the risk signature. Gene set enrichment analyses (GSEA) in the risk groups were used to figure out the closely correlated pathways with the risk group. The role of risk score has been further explored in the homologous recombination repair deficiency (HRD), BRAC1/2 gene mutations and tumor mutation burden (TMB). A risk signature with 4 CD8TEXGs in OC was finally built in the TCGA database and further validated in large GEO cohorts. The signature also demonstrated broad applicability across various types of cancer in the pan-cancer analysis. The high-risk score was significantly associated with a worse prognosis and the risk score was proven to be an independent prognostic biomarker. The 1-, 3-, and 5-years ROC values, nomogram, calibration, and comparison with the previously published models confirmed the excellent prediction power of this model. The low-risk group patients tended to exhibit a higher HRD score, BRCA1/2 gene mutation ratio and TMB. The low-risk group patients were more sensitive to Poly-ADP-ribose polymerase inhibitors (PARPi). Our findings of the prognostic value of CD8TEXGs in prognosis and drug response provided valuable insights into the molecular mechanisms and clinical management of OC.

Biomarkers to predict efficacy of immune checkpoint inhibitors in colorectal cancer patients: a systematic review and meta-analysis

Immune checkpoint inhibitors (ICIs) are approved to treat colorectal cancer (CRC) with mismatch-repair gene deficiency, but the response rate remains low. Value of current biomarkers to predict CRC patients' response to ICIs is unclear due to heterogeneous study designs and small sample sizes. Here, we aim to assess and quantify the magnitude of multiple biomarkers for predicting the efficacy of ICIs in CRC patients. We systematically searched MEDLINE, Embase, the Cochrane Library, and Web of Science databases (to June 2023) for clinical studies examining biomarkers for efficacy of ICIs in CRC patients. Random-effect models were performed for meta-analysis. We pooled odds ratio (OR) and hazard ratio (HR) with 95% confidence interval (CI) for biomarkers predicting response rate and survival. 36 studies with 1867 patients were included in systematic review. We found that a lower pre-treatment blood neutrophil-to-lymphocyte ratio (n=4, HR 0.37, 95%CI 0.21-0.67) predicts good prognosis, higher tumor mutation burden (n=10, OR 4.83, 95%CI 2.16-10.78) predicts response to ICIs, and liver metastasis (n=16, OR 0.32, 95%CI 0.16-0.63) indicates resistance to ICIs, especially when combined with VEGFR inhibitors. But the predictive value of tumor PD-L1 expression (n=9, OR 1.01, 95%CI 0.48-2.14) was insignificant in CRC. Blood neutrophil-to-lymphocyte ratio, tumor mutation burden, and liver metastasis, but not tumor PD-L1 expression, function as significant biomarkers to predict efficacy of ICIs in CRC patients. These findings help stratify CRC patients suitable for ICI treatments, improving efficacy of immunotherapy through precise patient management. (PROSPERO, CRD42022346716).

Single Nucleus Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Gliomas

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

Spatial Dissection of the Immune Landscape of Solid Tumors to Advance Precision Medicine

Chemotherapeutics, radiation, targeted therapeutics, and immunotherapeutics each demonstrate clinical benefits for a small subset of patients with solid malignancies. Immune cells infiltrating the tumor and the surrounding stroma play a critical role in shaping cancer progression and modulating therapy response. They do this by interacting with the other cellular and molecular components of the tumor microenvironment. Spatial multi-omics technologies are rapidly evolving. Currently, such technologies allow high-throughput RNA and protein profiling and retain geographical information about the tumor microenvironment cellular architecture and the functional phenotype of tumor, immune, and stromal cells. An in-depth spatial characterization of the heterogeneous tumor immune landscape can improve not only the prognosis but also the prediction of therapy response, directing cancer patients to more tailored and efficacious treatments. This review highlights recent advancements in spatial transcriptomics and proteomics profiling technologies and the ways these technologies are being applied for the dissection of the immune cell composition in solid malignancies in order to further both basic research in oncology and the implementation of precision treatments in the clinic.

Glycosylphosphatidylinositol anchor biosynthesis pathway-based biomarker identification with machine learning for prognosis and T cell exhaustion status prediction in breast cancer

As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical settings and promoting the efficacy of immune checkpoint blockade therapies. In eukaryotes, numerous cell surface proteins are tethered to the plasma membrane via Glycosylphosphatidylinositol (GPI) anchors, which play a crucial role in facilitating the proper translocation of membrane proteins. However, the available evidence is insufficient to support any additional functional involvement of GPI anchors. Here, we investigate the signature of GPI-anchor biosynthesis in the TME of breast cancer (BC)patients, particularly its correlation with TEX. GPI-anchor biosynthesis should be considered as a prognostic risk factor for BC. Patients with high GPI-anchor biosynthesis showed more severe TEX. And the levels of GPI-anchor biosynthesis in exhausted CD8 T cells was higher than normal CD8 T cells, which was not observed between malignant epithelial cells and normal mammary epithelial cells. In addition, we also found that GPI -anchor biosynthesis related genes can be used to diagnose TEX status and predict prognosis in BC patients, both the TEX diagnostic model and the prognostic model showed good AUC values. Finally, we confirmed our findings in cells and clinical samples. Knockdown of PIGU gene expression significantly reduced the proliferation rate of MDA-MB-231 and MCF-7 cell lines. Immunofluorescence results from clinical samples showed reduced aggregation of CD8 T cells in tissues with high expression of GPAA1 and PIGU.

Single-Cell and Spatial Transcriptome Profiling Identifies the Transcription Factor BHLHE40 as a Driver of EMT in Metastatic Colorectal Cancer

Colorectal cancer is one of the most common malignant tumors in humans, with liver metastasis being the primary cause of mortality. The epithelial-mesenchymal transition (EMT) process endows cancer cells with enhanced metastatic potential. To elucidate the cellular mechanisms driving EMT in colorectal cancer, we analyzed single-cell RNA sequencing data from 11 nonmetastatic primary tumors (TnM) and 11 metastatic primary tumors (TM) from colorectal cancer patients. Compared with the TnM group, the TM samples showed elevated numbers of malignant epithelial cell and cancer-associated fibroblast (CAF) subsets that displayed enrichments of EMT, angiogenesis, and TGFβ signaling pathways. One specific TM-enriched subgroup of malignant epithelial cells underwent EMT to transdifferentiate into CXCL1+ CAFs that subsequently differentiated into SFRP2+ CAFs, which was validated by spatial transcriptomic and pseudotime trajectory analyses. Furthermore, cell-cell communication analysis identified BHLHE40 as a probable key transcription factor driving EMT that was associated with poor prognosis. Finally, in vitro and in vivo experiments functionally substantiated that BHLHE40 promoted the proliferation, invasion, migration, EMT, and liver metastasis of colorectal cancer cells. In summary, this study identified BHLHE40 as a key transcription factor regulating EMT that promotes liver metastasis in colorectal cancer. Significance: Integrated analysis of single-cell RNA sequencing and spatial transcriptomics in metastatic colorectal cancer provides insights into the mechanisms underlying EMT and cancer-associated fibroblast differentiation, which could help improve patient diagnosis and treatment.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

Unravelling tumour cell diversity and prognostic signatures in cutaneous melanoma through machine learning analysis

Melanoma, a highly malignant tumour, presents significant challenges due to its cellular heterogeneity, yet research on this aspect in cutaneous melanoma remains limited. In this study, we utilized single-cell data from 92,521 cells to explore the tumour cell landscape. Through clustering analysis, we identified six distinct cell clusters and investigated their differentiation and metabolic heterogeneity using multi-omics approaches. Notably, cytotrace analysis and pseudotime trajectories revealed distinct stages of tumour cell differentiation, which have implications for patient survival. By leveraging markers from these clusters, we developed a tumour cell-specific machine learning model (TCM). This model not only predicts patient outcomes and responses to immunotherapy, but also distinguishes between genomically stable and unstable tumours and identifies inflamed ('hot') versus non-inflamed ('cold') tumours. Intriguingly, the TCM score showed a strong association with TOMM40, which we experimentally validated as an oncogene promoting tumour proliferation, invasion and migration. Overall, our findings introduce a novel biomarker score that aids in selecting melanoma patients for improved prognoses and targeted immunotherapy, thereby guiding clinical treatment decisions.

A Pathologically Friendly Strategy for Determining the Organ-specific Spatial Tumor Microenvironment Topology in Lung Adenocarcinoma Through the Integration of snRandom-seq and Imaging Mass Cytometry

Heterogeneous organ-specific responses to immunotherapy exist in lung cancer. Dissecting tumor microenvironment (TME) can provide new insights into the mechanisms of divergent responses, the process of which remains poor, partly due to the challenges associated with single-cell profiling using formalin-fixed paraffin-embedded (FFPE) materials. In this study, single-cell nuclei RNA sequencing and imaging mass cytometry (IMC) are used to dissect organ-specific cellular and spatial TME based on FFPE samples from paired primary lung adenocarcinoma (LUAD) and metastases. Single-cell analyses of 84 294 cells from sequencing and 250 600 cells from IMC reveal divergent organ-specific immune niches. For sites of LUAD responding well to immunotherapy, including primary LUAD and adrenal gland metastases, a significant enrichment of B, plasma, and T cells is detected. Spatially resolved maps reveal cellular neighborhoods recapitulating functional units of the tumor ecosystem and the spatial proximity of B and CD4+ T cells at immunogenic sites. Various organ-specific densities of tertiary lymphoid structures are observed. Immunosuppressive sites, including brain and liver metastases, are deposited with collagen I, and T cells at these sites highly express TIM-3. This study originally deciphers the single-cell landscape of the organ-specific TME at both cellular and spatial levels for LUAD, indicating the necessity for organ-specific treatment approaches.

Spatial distribution pattern of immune cells is associated with patient prognosis in colorectal cancer

BACKGROUND

The spatial context of tumor-infiltrating immune cells (TIICs) is important in predicting colorectal cancer (CRC) patients' clinical outcomes. However, the prognostic value of the TIIC spatial distribution is unknown. Thus, we aimed to investigate the association between TIICs in situ and patient prognosis in a large CRC sample.

METHODS

We implemented multiplex immunohistochemistry staining technology in 190 CRC samples to quantify 14 TIIC subgroups in situ. To delineate the spatial relationship of TIICs to tumor cells, tissue slides were segmented into tumor cell and microenvironment compartments based on image recognition technology, and the distance between immune and tumor cells was calculated by implementing the computational pipeline phenoptr.

RESULTS

MPO+ neutrophils and CD68+IDO1+ tumor-associated macrophages (TAMs) were enriched in the epithelial compartment, and myeloid lineage cells were located nearest to tumor cells. Except for CD68+CD163+ TAMs, other cells were all positively associated with favorable prognosis. The prognostic predictive power of TIICs was highly related to their distance to tumor cells. Unsupervised clustering analysis divided colorectal cancer into three subtypes with distinct prognostic outcomes, and correlation analysis revealed the synergy among B cells, CD68+IDO1+TAMs, and T lineage cells in producing an effective immune response.

CONCLUSIONS

Our study suggests that the integration of spatial localization with TIIC abundance is important for comprehensive prognostic assessment.

Exploring cellular diversity in lung adenocarcinoma epithelium: Advancing prognostic methods and immunotherapeutic strategies

Immunotherapy has brought significant advancements in the treatment of lung adenocarcinoma (LUAD), but identifying suitable candidates remains challenging. In this study, we investigated tumour cell heterogeneity using extensive single-cell data and explored the impact of different tumour cell cluster abundances on immunotherapy in the POPLAR and OAK immunotherapy cohorts. Notably, we found a significant correlation between CKS1B+ tumour cell abundance and treatment response, as well as stemness potential. Leveraging marker genes from the CKS1B+ tumour cell cluster, we employed machine learning algorithms to establish a prognostic and immunotherapeutic signature (PIS) for LUAD. In multiple cohorts, PIS outperformed 144 previously published signatures in predicting LUAD prognosis. Importantly, PIS reliably predicted genomic alterations, chemotherapy sensitivity and immunotherapy responses. Immunohistochemistry validated lower expression of immune markers in the low-PIS group, while in vitro experiments underscored the role of the key gene PSMB7 in LUAD progression. In conclusion, PIS represents a novel biomarker facilitating the selection of suitable LUAD patients for immunotherapy, ultimately improving prognosis and guiding clinical decisions.

Single-cell RNA sequencing elucidated the landscape of breast cancer brain metastases and identified ILF2 as a potential therapeutic target

Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single-cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi-omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer-binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM.

Single-cell transcriptomic profiling reveals decreased ER protein Reticulon3 drives the progression of renal fibrosis

Chronic kidney disease (CKD) poses a significant global health dilemma, emerging from complex causes. Although our prior research has indicated that a deficiency in Reticulon-3 (RTN3) accelerates renal disease progression, a thorough examination of RTN3 on kidney function and pathology remains underexplored. To address this critical need, we generated Rtn3-null mice to study the consequences of RTN3 protein deficiency on CKD. Single-cell transcriptomic analyses were performed on 47,885 cells from the renal cortex of both healthy and Rtn3-null mice, enabling us to compare spatial architectures and expression profiles across 14 distinct cell types. Our analysis revealed that RTN3 deficiency leads to significant alterations in the spatial organization and gene expression profiles of renal cells, reflecting CKD pathology. Specifically, RTN3 deficiency was associated with Lars2 overexpression, which in turn caused mitochondrial dysfunction and increased reactive oxygen species levels. This shift induced a transition in renal epithelial cells from a functional state to a fibrogenic state, thus promoting renal fibrosis. Additionally, RTN3 deficiency was found to drive the endothelial-to-mesenchymal transition process and disrupt cell-cell communication, further exacerbating renal fibrosis. Immunohistochemistry and Western-Blot techniques were used to validate these observations, reinforcing the critical role of RTN3 in CKD pathogenesis. The deficiency of RTN3 protein in CKD leads to profound changes in cellular architecture and molecular profiles. Our work seeks to elevate the understanding of RTN3's role in CKD's narrative and position it as a promising therapeutic contender.

Multiomic analysis of monocyte-derived alveolar macrophages in idiopathic pulmonary fibrosis

BACKGROUND

Monocyte-derived alveolar macrophages (Mo_AMs) are increasingly recognised as potential pathogenic factors for idiopathic pulmonary fibrosis (IPF). While scRNAseq analysis has proven valuable in the transcriptome profiling of Mo_AMs, the integration analysis of multi-omics may provide additional dimensions of understanding of these cellular populations.

METHODS

We performed multi-omics analysis on 116 scRNAseq, 119 bulkseq and five scATACseq lung tissue samples from IPF. We built a large-scale IPF scRNAseq atlas and conducted the Monocle 2/3 as well as the Cellchat to explore the developmental path and intercellular communication on Mo_AMs. We also reported the difference in metabolisms, tissue repair and phagocytosis between Mo_AMs and tissue-resident alveolar macrophages (TRMs). To determine whether Mo_AMs affected pulmonary function, we projected clinical phenotypes (FVC%pred) from the bulkseq dataset onto the scRNAseq atlas. Finally, we used scATATCseq to uncover the upstream regulatory mechanisms and determine key drivers in Mo_AMs.

RESULTS

We identified three Mo_AMs clusters and the trajectory analysis further validated the origin of these clusters. Moreover, via the Cellchat analysis, the CXCL12/CXCR4 axis was found to be involved in the molecular basis of reciprocal interactions between Mo_AMs and fibroblasts through the activation of the ERK pathway in Mo_AMs. SPP1_RecMacs (RecMacs, recruited macrophages) were higher in the low-FVC group than in the high-FVC group. Specifically, compared with TRMs, the functions of lipid and energetic metabolism as well as tissue repair were higher in Mo_AMs than TRMs. But, TRMs may have higher level of phagocytosis than TRMs. SPIB (PU.1), JUNB, JUND, BACH2, FOSL2, and SMARCC1 showed stronger association with open chromatin of Mo_AMs than TRMs. Significant upregulated expression and deep chromatin accessibility of APOE were observed in both SPP1_RecMacs and TRMs.

CONCLUSION

Through trajectory analysis, it was confirmed that SPP1_RecMacs derived from Monocytes. Besides, Mo_AMs may influence FVC% pred and aggravate pulmonary fibrosis through the communication with fibroblasts. Furthermore, distinctive transcriptional regulators between Mo_AMs and TRMs implied that they may depend on different upstream regulatory mechanisms. Overall, this work provides a global overview of how Mo_AMs govern IPF and also helps determine better approaches and intervention therapies.

Cabazitaxel-Loaded Thermosensitive Hydrogel System for Suppressed Orthotopic Colorectal Cancer and Liver Metastasis

The treatment of colorectal cancer is always a major challenge in the field of cancer research. The number of estimated new cases of colorectal cancer worldwide in 2020 is 1 148 515, and the estimated number of deaths is 576 858, revealing that mortality accounted for approximately half of the disease incidence. The development of new drugs and strategies for colorectal cancer treatment is urgently needed. Thermosensitive injectable hydrogel PDLLA-PEG-PDLLA (PLEL) loaded with cabazitaxel (CTX) is used to explore its anti-tumor effect on mice with orthotopic colorectal cancer. CTX/PLEL is characterized by a solution state at room temperature and a hydrogel state at physiologic temperature. The excipients MPEG-PCL and PDLLA-PEG-PDLLA have good biocompatibility and biodegradability. The simple material synthesis and preparation process renders this system cost-effective and more conducive to clinical transformation. An orthotopic colorectal cancer model is established by transplantation subcutaneous tumors onto the cecum of mice. According to the results of experiments in vivo, CTX/PLEL significantly inhibits orthotopic colorectal cancer and liver metastasis in mice. The results indicate that CTX/PLEL nanoparticle preparations have high security and excellent anti-tumor effects, and have great application potential in colorectal cancer therapy.

Spatial transcriptomics in pancreatic cancer: advances, prospects and challenges

Pancreatic cancer remains one of the deadliest malignancies with an overall 5-year survival rate of 13%. This dismal fact can be partly attributed to currently limited understanding of tumor heterogeneity and immune microenvironment. Traditional bulk-sequencing techniques overlook the diversity of tumor cells, while single-cell sequencing disorganizes the position localizing of cells in tumor microenvironment. The advent of spatial transcriptomics (ST) presents a novel solution by integrating location and whole transcript expression information. This technology allows for detailed observation of spatio-temporal changes across various cell subtypes within the pancreatic tumor microenvironment, providing insights into their potential functions. This review offers an overview of recent studies implementing ST in pancreatic cancer research, highlighting its instrumental role in investigating the heterogeneity and functions of tumor cells, stromal cells, and immune cells. On the basis, we also prospected and summarized the clinical application scenarios, technical limitations and challenges of ST technology in pancreatic cancer.

Prognostic and therapeutic insights into colorectal carcinoma through immunogenic cell death gene profiling

While the significance of immunogenic cell death (ICD) in oncology is acknowledged, its specific impact on colorectal carcinoma remains underexplored. In this study, we delved into the role of ICD in colorectal carcinoma, a topic not yet comprehensively explored. A novel ICD quantification system was developed to forecast patient outcomes and the effectiveness of immunotherapy. Utilizing single-cell sequencing, we constructed an ICD score within the tumor immune microenvironment (TIME) and examined immunogenic cell death related genes (ICDRGs). Using data from TCGA and GEO, we discovered two separate molecular subcategories within 1,184 patients diagnosed with colon adenocarcinoma/rectum adenocarcinoma (COADREAD). The ICD score was established by principal component analysis (PCA), which classified patients into groups with low and high ICD scores. Further validation in three independent cohorts confirmed the model's accuracy in predicting immunotherapy success. Patients with higher ICD scores exhibited a "hot" immune phenotype and showed increased responsiveness to immunotherapy. Key genes in the model, such as AKAP12, CALB2, CYR61, and MEIS2, were found to enhance COADREAD cell proliferation, invasion, and PD-L1 expression. These insights offered a new avenue for anti-tumor strategies by targeting ICD, marking advances in colorectal carcinoma treatment.

Liver cancer from the perspective of single-cell sequencing: a review combined with bibliometric analysis

BACKGROUND

Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics.

METHOD

Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis.

RESULTS

A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'.

CONCLUSION

This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Multiomics integration-based immunological characterizations of adamantinomatous craniopharyngioma in relation to keratinization

Although adamantinomatous craniopharyngioma (ACP) is a tumour with low histological malignancy, there are very few therapeutic options other than surgery. ACP has high histological complexity, and the unique features of the immunological microenvironment within ACP remain elusive. Further elucidation of the tumour microenvironment is particularly important to expand our knowledge of potential therapeutic targets. Here, we performed integrative analysis of 58,081 nuclei through single-nucleus RNA sequencing and spatial transcriptomics on ACP specimens to characterize the features and intercellular network within the microenvironment. The ACP environment is highly immunosuppressive with low levels of T-cell infiltration/cytotoxicity. Moreover, tumour-associated macrophages (TAMs), which originate from distinct sources, highly infiltrate the microenvironment. Using spatial transcriptomic data, we observed one kind of non-microglial derived TAM that highly expressed GPNMB close to the terminally differentiated epithelial cell characterized by RHCG, and this colocalization was verified by asmFISH. We also found the positive correlation of infiltration between these two cell types in datasets with larger cohort. According to intercellular communication analysis, we report a regulatory network that could facilitate the keratinization of RHCG+ epithelial cells, eventually causing tumour progression. Our findings provide a comprehensive analysis of the ACP immune microenvironment and reveal a potential therapeutic strategy base on interfering with these two types of cells.

Advances in spatial transcriptomics and its applications in cancer research

Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent years, the spatial transcriptomics sequencing technologies have been developed rapidly and allow the quantification and illustration of gene expression in the spatial context of tissues. Compared with the traditional transcriptomics technologies, spatial transcriptomics technologies not only detect gene expression levels in cells, but also inform the spatial location of genes within tissues, cell composition of biological tissues, and interaction between cells. Here we summarize the development of spatial transcriptomics technologies, spatial transcriptomics tools and its application in cancer research. We also discuss the limitations and challenges of current spatial transcriptomics approaches, as well as future development and prospects.

Dysregulation of endometrial stromal serotonin homeostasis leading to abnormal phosphatidylcholine metabolism impairs decidualization in patients with recurrent implantation failure

STUDY QUESTION

Does abnormal serotonin homeostasis contribute to impaired endometrial decidualization in patients with recurrent implantation failure (RIF)?

SUMMARY ANSWER

Abnormal serotonin homeostasis in patients with RIF, which is accompanied by decreased monoamine oxidase (MAO) expression, affects the decidualization of endometrial stromal cells and leads to embryo implantation failure.

WHAT IS KNOWN ALREADY

Previous studies have indicated that the expression of MAO, which metabolizes serotonin, is reduced in the endometrium of patients with RIF, and serotonin can induce disruption of implantation in rats. However, whether abnormal serotonin homeostasis leads to impaired decidualization in patients with RIF and, if so, the mechanism involved, remains unclear.

STUDY DESIGN SIZE DURATION

Endometrial samples from 25 patients with RIF and 25 fertile patients were used to investigate the expression levels of monoamine oxidase A (MAOA), monoamine oxidase B (MAOB), and serotonin. We isolated human endometrial stromal cells to investigate the role of MAOA, MAOB, and serotonin in inducing decidualization in vitro and further explored the underlying mechanism using RNA-sequencing (RNA-seq) and liquid chromatography-mass spectrometry (LC/MS) analyses.

PARTICIPANTS/MATERIALS SETTING METHODS

The levels of serotonin in the endometrium of patients with RIF were detected by ELISA and immunohistofluorescence, and the key genes involved in abnormal serotonin metabolism were analyzed via combination with single-cell sequencing data. The effects of MAOA or MAOB on the decidualization of stromal cells were investigated using an in vitro human endometrial stromal cell-induced decidualization model and a mouse artificially induced decidualization model. The potential mechanisms by which MAOA and MAOB regulate decidualization were explored by RNA-seq and LC/MS analysis.

MAIN RESULTS AND THE ROLE OF CHANCE

We found that women with RIF have abnormal serotonin metabolism in the endometrium and attenuated MAO in endometrial stromal cells. Endometrial decidualization was accompanied by increased MAO in vivo and in vitro. However attenuated MAO caused an increased local serotonin content in the endometrium, impairing stromal cell decidualization. RNA-seq and LC/MS analyses showed that abnormal lipid metabolism, especially phosphatidylcholine metabolism, was involved in the defective decidualization caused by MAO deficiency. Furthermore, decidualization defects were rescued by phosphatidylcholine supplementation.

LARGE SCALE DATA

RNA-seq information and raw data can be found at NCBI Bioproject number PRJNA892255.

LIMITATIONS REASONS FOR CAUTION

This study revealed that impaired serotonin metabolic homeostasis and abnormally reduced MAO expression were among the reasons for RIF. However, the source and other potential functions of serotonin in the endometrium remain to be further explored.

WIDER IMPLICATIONS OF THE FINDINGS

This study provides new insights into the mechanisms of serotonin homeostasis in human endometrial decidualization and new biomarkers or targets for the treatment of patients with RIF.

STUDY FUNDING/COMPETING INTERESTS

X. Sheng is supported by grants from the National Natural Science Foundation of China (82001629), the Wenzhou Basic Public Welfare Research Project (Y20240030), the Youth Program of Natural Science Foundation of Jiangsu Province (BK20200116), and Jiangsu Province Postdoctoral Research Funding (2021K277B). H.S. is supported by grants from the National Natural Science Foundation of China (82030040). G.Y. is supported by grants from the National Natural Science Foundation of China (82171653). The authors declare no conflicts of interest.