Construction of TME and Identification of crosstalk between malignant cells and macrophages by SPP1 in hepatocellular carcinoma

SPP1 could be an immunological and prognostic biomarker: From pan-cancer comprehensive analysis to osteosarcoma validation

Secreted phosphoprotein 1 (SPP1), also known as osteopontin, is a phosphorylated protein. High SPP1 expression levels have been detected in multiple cancers and are associated with poor prognosis and reduced survival rates. However, only a few pan-cancer analyses have targeted SPP1. We conducted a comprehensive analysis using multiple public databases, including TIMER and TCGA, to investigate the expression levels of SPP1 in 33 different tumor types. In addition, we verified the effect of SPP1 on osteosarcoma. To assess the impact of SPP1 on patient outcomes, we employed univariate Cox regression and Kaplan-Meier survival analyses to analyze overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in these tumor patients. We also explored SPP1 gene alterations in various tumor tissues using cBioPortal. We then examined the relationship between SPP1 and clinical characteristics, TME, immune regulatory genes, immune checkpoints, TMB, and MSI using R language. In addition, we used GSEA to investigate the molecular mechanisms underlying the role of SPP1. Bioinformatics analysis indicated that SPP1 was upregulated in 17 tumors. Overexpression of SPP1 results in poor OS, DSS, and PFI in CESC, ESCA, GBM, LGG, LIHC, PAAD, PRAD, and skin cutaneous melanoma. SPP1 expression was positively associated with immunocyte infiltration, immune regulatory genes, immune checkpoints, TMB, MSI, and drug sensitivity in certain cancers. We found that high expression of SPP1 in osteosarcoma was related to drug resistance and metastasis and further demonstrated that SPP1 can stimulate osteosarcoma cell proliferation via CCND1 by activating the PI3K/Akt pathway. These findings strongly suggest that SPP1 is a potential prognostic marker and novel target for cancer immunotherapy.

Novel molecular subtypes of METex14 non-small cell lung cancer with distinct biological and clinical significance

Not all MET exon 14 skipping (METex14) NSCLC patients benefited from MET inhibitors. We hypothesized an inter-tumoral heterogeneity in METex14 NSCLC. Investigations at genomic and transcriptomic level were conducted in METex14 NSCLC samples from stage I-III and recurrent/metastatic patients as discovery and validation cohort. Four molecular subtypes were discovered. MET-Driven subtype, with the worst prognosis, displayed MET overexpression, enrichment of MET-related pathways, and higher infiltration of fibroblast and regulatory T cells. Immune-Activated subtype having the most idea long-term survival, had higher tertiary lymphoid structures, spatial co-option of PD-L1+ cancer cells, and GZMK+ CD8+ T cell. FGFR- and Bypass-Activated subtypes displayed FGFR2 overexpression and enrichments of multiple oncogenic pathways respectively. In the validation cohort, patients with MET-Driven subtype had better response to MET inhibitors than those with MET overexpression. Thus, molecular subtypes of METex14 NSCLC with distinct biological and clinical significance may indicate more precise therapeutic strategies for METex14 NSCLC patients.

Surgical resection versus thermal ablation after intra-arterial conversion therapy for unresectable hepatocellular carcinoma: a multicenter retrospective one as per the STROBE guidelines

PURPOSE

Intra-arterial conversion therapy (ICT) is a promising option for patients with unresectable hepatocellular carcinoma (uHCC). However, the selection of sequential therapeutic modalities is still controversial. This study compared the efficacy and safety of surgical resection (SR) versus thermal ablation (TA) after patients with uHCC received ICT.

METHODS

From May 2008 to November 2021, 3553 consecutive patients were reviewed and 791 patients were downstaged to receive TA or SR. Among them, 340 patients received SR, and 451 received TA after ICTs. The propensity score matching (PSM) method was applied to reduce selection bias between groups. Cumulative overall survival (OS) and progression-free survival (PFS) were compared using the Kaplan-Meier method with the log-rank test. The occurrence of complications and adverse events (AEs) were compared using chi-square test.

RESULTS

After PSM 1:1 (n = 185 in both groups), the 10-year OS and PFS rates for patients who underwent SR were comparable to those of patients who underwent TA (OS: 45.2% vs. 36.1%; p = 0.190; PFS: 19.3% vs. 15.9%; p = 0.533). A total of 237 (29.9%) patients (203 males; mean age:57.1 ± 11.0 years) received downstaging therapy, and long-term OS and PFS remained comparable between the two groups (p = 0.718, 0.636, respectively). However, the cumulative OS and PFS rates in the downstaged cohort were significantly higher than those in the nondownstaged cohort (both ps < 0.001). Additionally, there was no difference in major complications between the two groups (SR: 6.3% vs. TA: 8.6%; p = 0.320).

CONCLUSIONS

TA might be an acceptable first-line alternative to SR after patients with uHCC receive ICT, especially patients unsuitable for SR. Better long-term survival was observed among patients in the downstaged cohort compared to those who failed to downstage.

Osteopontin: A Key Multifaceted Regulator in Tumor Progression and Immunomodulation

The tumor microenvironment (TME) is composed of various cellular components such as tumor cells, stromal cells including fibroblasts, adipocytes, mast cells, lymphatic vascular cells and infiltrating immune cells, macrophages, dendritic cells and lymphocytes. The intricate interplay between these cells influences tumor growth, metastasis and therapy failure. Significant advancements in breast cancer therapy have resulted in a substantial decrease in mortality. However, existing cancer treatments frequently result in toxicity and nonspecific side effects. Therefore, improving targeted drug delivery and increasing the efficacy of drugs is crucial for enhancing treatment outcome and reducing the burden of toxicity. In this review, we have provided an overview of how tumor and stroma-derived osteopontin (OPN) plays a key role in regulating the oncogenic potential of various cancers including breast. Next, we dissected the signaling network by which OPN regulates tumor progression through interaction with selective integrins and CD44 receptors. This review addresses the latest advancements in the roles of splice variants of OPN in cancer progression and OPN-mediated tumor-stromal interaction, EMT, CSC enhancement, immunomodulation, metastasis, chemoresistance and metabolic reprogramming, and further suggests that OPN might be a potential therapeutic target and prognostic biomarker for the evolving landscape of cancer management.

Single-cell transcriptome sequencing reveals SPP1-CD44-mediated macrophage-tumor cell interactions drive chemoresistance in TNBC

Triple-negative breast cancer (TNBC) is often considered one of the most aggressive subtypes of breast cancer, characterized by a high recurrence rate and low overall survival (OS). It is notorious for posing challenges related to drug resistance. While there has been progress in TNBC research, the mechanisms underlying chemotherapy resistance in TNBC remain largely elusive. We collect single-cell RNA sequencing (scRNA-seq) data from five TNBC patients susceptible to chemotherapy and five resistant cases. Comprehensive analyses involving copy number variation (CNV), pseudotime trajectory, cell-cell interactions, pseudospace analysis, as well as transcription factor and functional enrichment are conducted specifically on macrophages and malignant cells. Furthermore, we performed validation experiments on clinical samples using multiplex immunofluorescence. We identified a subset of SPP1+ macrophages that secrete SPP1 signals interacting with CD44 on malignant cell surfaces, potentially activating the PDE3B pathway within malignant cells via the integrin pathway, leading to chemotherapy resistance. The abnormally enhanced SPP1 signal between macrophages and malignant cells may serve as a factor promoting chemotherapy resistance in TNBC patients. Therefore, SPP1+ macrophages could potentially serve as a therapeutic target to reduce chemotherapy resistance.

Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals a tumor-associated endothelial tip cell phenotype

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer, accounting for over 75% of cases. The asymptomatic nature of the disease contributes to late-stage diagnoses and poor survival. Highly vascularized and immune infiltrated microenvironment are prominent features of ccRCC, yet the interplay between vasculature and immune cells, disease progression and response to therapy remains poorly understood. Using droplet-based single-cell RNA sequencing we profile 50,236 transcriptomes from paired tumor and healthy adjacent kidney tissues. Our analysis reveals significant heterogeneity and inter-patient variability of the tumor microenvironment. Notably, we discover a previously uncharacterized vasculature subpopulation associated with epithelial-mesenchymal transition. The cell-cell communication analysis reveals multiple modes of immunosuppressive interactions within the tumor microenvironment, including clinically relevant interactions between tumor vasculature and stromal cells with immune cells. The upregulation of the genes involved in these interactions is associated with worse survival in the TCGA KIRC cohort. Our findings demonstrate the role of tumor vasculature and stromal cell populations in shaping the ccRCC microenvironment and uncover a subpopulation of cells within the tumor vasculature that is associated with an angiogenic phenotype.

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.

Osteopontin/SPP1: a potential mediator between immune cells and vascular calcification

Vascular calcification (VC) is considered a common pathological process in various vascular diseases. Accumulating studies have confirmed that VC is involved in the inflammatory response in heart disease, and SPP1+ macrophages play an important role in this process. In VC, studies have focused on the physiological and pathological functions of macrophages, such as pro-inflammatory or anti-inflammatory cytokines and pro-fibrotic vesicles. Additionally, macrophages and activated lymphocytes highly express SPP1 in atherosclerotic plaques, which promote the formation of fatty streaks and plaque development, and SPP1 is also involved in the calcification process of atherosclerotic plaques that results in heart failure, but the crosstalk between SPP1-mediated immune cells and VC has not been adequately addressed. In this review, we summarize the regulatory effect of SPP1 on VC in T cells, macrophages, and dendritic cells in different organs' VC, which could be a potential therapeutic target for VC.

Safety and Preliminary Efficacy of Pembrolizumab Following Transarterial Chemoembolization for Hepatocellular Carcinoma: The PETAL Phase Ib Study

PURPOSE

Transarterial chemoembolization (TACE) may prime adaptive immunity and enhance immunotherapy efficacy. PETAL evaluated safety, preliminary activity of TACE plus pembrolizumab and explored mechanisms of efficacy.

PATIENTS AND METHODS

Patients with liver-confined hepatocellular carcinoma (HCC) were planned to receive up to two rounds of TACE followed by pembrolizumab 200 mg every 21 days commencing 30 days post-TACE until disease progression or unacceptable toxicity for up to 1 year. Primary endpoint was safety, with assessment window of 21 days from pembrolizumab initiation. Secondary endpoints included progression-free survival (PFS) and evaluation of tumor and host determinants of response.

RESULTS

Fifteen patients were included in the safety and efficacy population: 73% had nonviral cirrhosis; median age was 72 years. Child-Pugh class was A in 14 patients. Median tumor size was 4 cm. Ten patients (67%) received pembrolizumab after one TACE; 5 patients after two (33%). Pembrolizumab yielded no synergistic toxicity nor dose-limiting toxicities post-TACE. Treatment-related adverse events occurred in 93% of patients, most commonly skin rash (40%), fatigue, and diarrhea (27%). After a median follow-up of 38.5 months, objective response rate 12 weeks post-TACE was 53%. PFS rate at 12 weeks was 93% and median PFS was 8.95 months [95% confidence interval (CI): 7.30-NE (not estimable)]. Median duration of response was 7.3 months (95% CI: 6.3-8.3). Median overall survival was 33.5 months (95% CI: 11.6-NE). Dynamic changes in peripheral T-cell subsets, circulating tumor DNA, serum metabolites, and in stool bacterial profiles highlight potential mechanisms of action of multimodal therapy.

CONCLUSIONS

TACE plus pembrolizumab was tolerable with no evidence of synergistic toxicity, encouraging further clinical development of immunotherapy alongside TACE.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

Distinct cuproptosis patterns in hepatocellular carcinoma patients correlate with unique immune microenvironment characteristics and cell-cell communication, contributing to varied overall survival outcomes

Background

Hepatocellular carcinoma (HCC), a prevalent cancer, is linked to cuproptosis in tumor progression. However, cuproptosis's impact on HCC prognosis and its role in the tumor microenvironment remain unclear. We aimed to explore the correlation between cellular cuproptosis and the immune microenvironment in HCC, providing potential immunotherapeutic insights.

Methods

Examining cuproptosis-related genes and the immune microenvironment through consensus clustering and WGCNA. Risk models were constructed using LASSO Cox analysis and validated in an independent cohort. Gene expression data from The Cancer Genome Atlas (TCGA) database and single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database were utilized. We scored cuproptosis expression and explored immunoinfiltration and cell-cell communication. Differential signals in T_memory cells were compared across different cuproptosis levels.

Results

Cuproptosis genes associated with fibroblast recruitment (GLS) and macrophage infiltration (FDX1). Liver cancer patients categorized into two subtypes based on cuproptosis gene expression. High expression of DLAT, GLS, and CDKN2A linked to immunosuppression (TGF-β), while high FDX1, MTF1, LIAS, and LIPT1 expression enhanced communication with non-immune cells. Developed reliable prognostic signature score and nomogram using cuproptosis-related genes. Single-cell analysis revealed differences in T_memory and TAM infiltration based on cuproptosis scores, with SPP1 and MIF as dominant signaling molecules. Finally, the results of in vitro experiments showed that when DLAT or CDKN2A was knocked down, the proliferation, migration, and invasion of HCC cells were significantly decreased.

Conclusion

Our study demonstrates that cuproptosis affects the immune microenvironment and cell-cell communication. Identified 9 genetic markers predicting survival outcomes and immunotherapy responses. Evaluating cuproptosis signaling can optimize immunotherapeutic strategies for hepatocellular carcinoma.

Tumor-associated macrophage subtypes on cancer immunity along with prognostic analysis and SPP1-mediated interactions between tumor cells and macrophages

Tumor-associated macrophages (TAM) subtypes have been shown to impact cancer prognosis and resistance to immunotherapy. However, there is still a lack of systematic investigation into their molecular characteristics and clinical relevance in different cancer types. Single-cell RNA sequencing data from three different tumor types were used to cluster and type macrophages. Functional analysis and communication of TAM subpopulations were performed by Gene Ontology-Biological Process and CellChat respectively. Differential expression of characteristic genes in subpopulations was calculated using zscore as well as edgeR and Wilcoxon rank sum tests, and subsequently gene enrichment analysis of characteristic genes and anti-PD-1 resistance was performed by the REACTOME database. We revealed the heterogeneity of TAM, and identified eleven subtypes and their impact on prognosis. These subtypes expressed different molecular functions respectively, such as being involved in T cell activation, apoptosis and differentiation, or regulating viral bioprocesses or responses to viruses. The SPP1 pathway was identified as a critical mediator of communication between TAM subpopulations, as well as between TAM and epithelial cells. Macrophages with high expression of SPP1 resulted in poorer survival. By in vitro study, we showed SPP1 mediated the interactions between TAM clusters and between TAM and tumor cells. SPP1 promoted the tumor-promoting ability of TAM, and increased PDL1 expression and stemness of tumor cells. Inhibition of SPP1 attenuated N-cadherin and β-catenin expression and the activation of AKT and STAT3 pathway in tumor cells. Additionally, we found that several subpopulations could decrease the sensitivity of anti-PD-1 therapy in melanoma. SPP1 signal was a critical pathway of communication between macrophage subtypes. Some specific macrophage subtypes were associated with immunotherapy resistance and prognosis in some cancer types.

Pan-cancer and single-cell analyses identify CD44 as an immunotherapy response predictor and regulating macrophage polarization and tumor progression in colorectal cancer

Introduction

Cluster of differentiation (CD) 44 is a non-kinase cell surface transmembrane glycoprotein critical for tumor maintenance and progression.

Methods

We conducted a systematic analysis of the expression profile and genomic alteration profile of CD44 in 33 types of cancer. The immune characteristics of CD44 were comprehensively explored by TIMER2.0 and CIBERSORT. In addition, the CD44 transcriptional landscape was examined at the single-cell level. Then, Pseudotime trajectory analysis of CD44 gene expression was performed using Monocle 2, and CellChat was utilized to compare the crosstalk differences between CD44+monocytes and CD44- monocytes. Tumor immune dysfunction and exclusion (TIDE) was used to evaluate the predictive ability of CD44 for immune checkpoint blockade (ICB) responses. The effects of CD44 on colorectal cancer (CRC) and macrophage polarization were investigated by knocking down the expression of CD44 in HCT-116 cell and macrophages in vitro.

Results

The expression of CD44 elevated in most cancers, predicting unfavorable prognosis. In addditon, CD44 was correlation with immune cell infiltration and key immune regulators. CD44+ monocytes had a higher information flow intensity than CD44- monocytes. CD44 had good predictive ability for immune checkpoint blockade responses. Knockdown of CD44 inhibited the proliferation, migration, and invasion of HCT-116 cell in vitro. Knockdown of CD44 inhibited M2 macrophage polarization.

Discussion

These findings suggest that CD44 is involved in regulating tumor development, macrophage polarization, and has certain predictive value for patient clinical prognosis and response to immunotherapy.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Integrative single-cell transcriptomic analyses reveal the cellular ontological and functional heterogeneities of primary and metastatic liver tumors

BACKGROUND

The global cellular landscape of the tumor microenvironment (TME) combining primary and metastatic liver tumors has not been comprehensively characterized.

METHODS

Based on the scRNA-seq and spatial transcriptomic data of non-tumor liver tissues (NTs), primary liver tumors (PTs) and metastatic liver tumors (MTs), we performed the tissue preference, trajectory reconstruction, transcription factor activity inference, cell-cell interaction and cellular deconvolution analyses to construct a comprehensive cellular landscape of liver tumors.

RESULTS

Our analyses depicted the heterogeneous cellular ecosystems in NTs, PTs and MTs. The activated memory B cells and effector T cells were shown to gradually shift to inhibitory B cells, regulatory or exhausted T cells in liver tumors, especially in MTs. Among them, we characterized a unique group of TCF7+ CD8+ memory T cells specifically enriched in MTs that could differentiate into exhausted T cells likely driven by the p38 MAPK signaling. With regard to myeloid cells, the liver-resident macrophages and inflammatory monocyte/macrophages were markedly replaced by tumor-associated macrophages (TAMs), with TREM2+ and UBE2C+ TAMs enriched in PTs, while SPP1+ and WDR45B+ TAMs in MTs. We further showed that the newly identified WDR45B+ TAMs exhibit an M2-like polarization and are associated with adverse prognosis in patients with liver metastases. Additionally, we addressed that endothelial cells display higher immune tolerance and angiogenesis capacity, and provided evidence for the source of the mesenchymal transformation of fibroblasts in tumors. Finally, the malignant hepatocytes and fibroblasts were prioritized as the pivotal cell populations in shaping the microenvironments of PTs and MTs, respectively. Notably, validation analyses by using spatial or bulk transcriptomic data in clinical cohorts concordantly emphasized the clinical significance of these findings.

CONCLUSIONS

This study defines the ontological and functional heterogeneities in cellular ecosystems of primary and metastatic liver tumors, providing a foundation for future investigation of the underlying cellular mechanisms.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

SPP1+ TAM subpopulations in tumor microenvironment promote intravasation and metastasis of head and neck squamous cell carcinoma

Macrophages are heterogeneous cells that play multifaceted roles in cancer progression and metastasis. However, the phenotypic diversity of tumor-associated macrophages (TAMs) in head and neck squamous carcinomas (HNSCC) remains poorly characterized. Here, we comprehensively analyzed the HNSCC single-cell transcriptomic dataset (GSE172577) and identified 5 subsets of myeloid-driven cells as TAMs using Seurat. Deciphering the lineage trajectory of TAMs, we revealed that FCN1+ TAMs could give rise to pro-angiogenesis SPP1+CCL18+ and SPP1+FOLR2+ populations through SPP1-CCL18+ and CXCL9+CXCL10+ TAMs. SPP1+CCL18+ and SPP1+FOLR2+ TAMs harbored pro-angiogenic and metastatic transcriptional programs and were correlated with poor survival of HNSCC patients. Our immunostaining examination revealed that infiltration of SPP1+ TAMs is associated with lymph node metastasis and poor prognosis in patients with HNSCC. Cell-cell communication analysis implied that SPP1+ TAM populations may employ SPP1 signaling to activate metastasis-related ECs. In vitro and in vivo studies, we demonstrated that SPP1hi TAMs enhanced tumor intravasation and metastasis in HNSCC in a manner dependent on the secretion of SPP1, CCL18, and CXCL8. Taken together, our study characterized the cellular heterogeneity of TAM populations and identified two SPP1+ TAM populations that play key roles in HNSCC intravasation and metastasis and serve as predictive markers for patients with HNSCC.

Novel tumor-associated macrophage populations and subpopulations by single cell RNA sequencing

Tumor-associated macrophages (TAMs) are present in almost all solid tumor tissues. 16They play critical roles in immune regulation, tumor angiogenesis, tumor stem cell activation, tumor invasion and metastasis, and resistance to therapy. However, it is unclear how TAMs perform these functions. With the application of single-cell RNA sequencing (scRNA-seq), it has become possible to identify TAM subpopulations associated with distinct functions. In this review, we discuss four novel TAM subpopulations in distinct solid tumors based on core gene signatures by scRNA-seq, including FCN1 +, SPP1 +, C1Q + and CCL18 + TAMs. Functional enrichment and gene expression in scRNA-seq data from different solid tumor tissues found that FCN1 + TAMs may induce inflammation; SPP1 + TAMs are potentially involved in metastasis, angiogenesis, and cancer cell stem cell activation, whereas C1Q + TAMs participate in immune regulation and suppression; And CCL18 + cells are terminal immunosuppressive macrophages that not only have a stronger immunosuppressive function but also enhance tumor metastasis. SPP1 + and C1Q + TAM subpopulations can be further divided into distinct populations with different functions. Meanwhile, we will also present emerging evidence highlighting the separating macrophage subpopulations associated with distinct functions. However, there exist the potential disconnects between cell types and subpopulations identified by scRNA-seq and their actual function.

Comprehensive scRNA-seq Analysis and Identification of CD8_+T Cell Related Gene Markers for Predicting Prognosis and Drug Resistance of Hepatocellular Carcinoma

BACKGROUND

Tumor heterogeneity of immune infiltration of cells plays a decisive role in hepatocellular carcinoma (HCC) therapy response and prognosis. This study investigated the effect of different subtypes of CD8+T cells on the HCC tumor microenvironment about its prognosis.

METHODS

Single-cell RNA sequencing, transcriptome, and single-nucleotide variant data from LUAD patients were obtained based on the GEO, TCGA, and HCCD18 databases. CD8+ T cells-associated subtypes were identified by consensus clustering analysis, and genes with the highest correlation with prognostic CD8+ T cell subtypes were identified using WGCNA. The ssGSEA and ESTIMATE algorithms were used to calculate pathway enrichment scores and immune cell infiltration levels between different subtypes. Finally, the TIDE algorithm, CYT score, and tumor responsiveness score were utilized to predict patient response to immunotherapy.

RESULTS

We defined 3 CD8+T cell clusters (CD8_0, CD8_1, CD8_2) based on the scRNA- seq dataset (GSE149614). Among, CD8_2 was prognosis-related risk factor with HCC. We screened 30 prognosis genes from CD8_2, and identified 3 molecular subtypes (clust1, clust2, clust3). Clust1 had better survival outcomes, higher gene mutation, and enhanced immune infiltration. Furthermore, we identified a 12 genes signature (including CYP7A1, SPP1, MSC, CXCL8, CXCL1, GCNT3, TMEM45A, SPP2, ME1, TSPAN13, S100A9, and NQO1) with excellent prediction performance for HCC prognosis. In addition, High-score patients with higher immune infiltration benefited less from immunotherapy. The sensitivity of low-score patients to multiple drugs including Parthenolide and Shikonin was significantly higher than that of high-score patients. Moreover, high-score patients had increased oxidative stress pathways scores, and the RiskScore was closely associated with oxidative stress pathways scores. And the nomogram had good clinical utility.

CONCLUSION

To predict the survival outcome and immunotherapy response for HCC, we developed a 12-gene signature based on the heterogeneity of the CD8+ T cells.

SPP1 is associated with adverse prognosis and predicts immunotherapy efficacy in penile cancer

BACKGROUND

The effect of SPP1 in squamous cell carcinoma of the penis (PSCC) remained unknown. We attempted to clarify the function of the SPP1 gene in PSCC.

METHOD

Eight paired penile cancer specimens (including penile cancer tissue, paracancerous tissue, and positive lymph node tissue) subjected to whole transcriptome sequencing were analysed to identify differentially expressed genes. We used immunohistochemistry to detect the expression of SPP1 protein and immune cell related proteins in penile cancer tissue. Then, we performed weighted gene coexpression network analysis (WGCNA) to identify the genes related to SPP1 in penile cancer tissue and positive lymph node tissue. Based on the GSE57955 dataset, the CIBERSORT and ssGSEA algorithms were carried out to investigate the immune environment of PSCC. GSVA analysis was conducted to identify the signaling pathways related to SPP1 subgroups. Enzyme-linked immunosorbent assay (ELISA) method was adopted to detect SPP1 level in the serum of 60 patients with penile cancer.

RESULTS

Differential analysis indicated that SPP1 was the most differentially upregulated gene in both penile cancer tissues and positive lymph node tissues. Survival analysis suggested that the prognosis of the low-SPP1 group was significantly poorer than that of the high-SPP1 group. Subsequently, immune-related bioinformatics showed that SPP1 was significantly associated with B cells, CD8 + T cells, CD4 + T cells, macrophages, helper T cells, neutrophils and dendritic cells. The immunohistochemical results showed that the high-SPP1 group was characterized by relatively high expression of CD16 and relatively low expression of CD4. GSVA analysis indicated that high-SPP1 group was significantly associated with immune-related pathways such as PD-L1 expression and the PD-1 checkpoint pathway in cancer and the TNF signaling pathway. ELISA demonstrated that the serum level of SPP1 in patients with positive lymph node metastasis of penile cancer was significantly higher than that in patients with negative lymph node metastasis of penile cancer.

CONCLUSION

Our study shows that the SPP1 gene might be an effective biomarker for predicting the prognosis and the efficacy of immunotherapy in PSCC patients.

The role of tumor-associated macrophages in hepatocellular carcinoma progression: A narrative review

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, with complex etiology and mechanism, and a high mortality rate. Tumor-associated macrophages (TAMs) are an important part of the HCC tumor microenvironment. Studies in recent years have shown that TAMs are involved in multiple stages of HCC and are related to treatment and prognosis in HCC. The specific mechanisms between TAMs and HCC are gradually being revealed. This paper reviews recent advances in the mechanisms associated with TAMs in HCC, concentrating on an overview of effects of TAMs on drug resistance in HCC and the signaling pathways linked with HCC, providing clues for the treatment and prognosis determination of HCC.

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy

BACKGROUND

The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patients' prognosis after hepatic arterial infusion chemotherapy (HAIC).

METHODS

From June 2018 to March 2020, 158 eligible patients with HCC who underwent surgery were retrospectively enrolled in MTM related cohorts, and 752 HCC patients who underwent HAIC were included in HAIC related cohorts during the same period. DLR features were extracted from dual-phase (arterial phase and venous phase) contrast-enhanced computed tomography (CECT) of the entire liver region. Then, an MDLR model was used for the simultaneous prediction of the MTM subtype and patient prognosis after HAIC. The MDLR model for prognostic risk stratification incorporated DLR signatures, clinical variables and MTM subtype.

FINDINGS

The predictive performance of the DLR model for the MTM subtype was 0.968 in the training cohort [TC], 0.912 in the internal test cohort [ITC] and 0.773 in the external test cohort [ETC], respectively. Multivariable analysis identified portal vein tumor thrombus (PVTT) (p = 0.012), HAIC response (p < 0.001), HAIC sessions (p < 0.001) and MTM subtype (p < 0.001) as indicators of poor prognosis. After incorporating DLR signatures, the MDLR model yielded the best performance among all models (AUC, 0.855 in the TC, 0.805 in the ITC and 0.792 in the ETC). With these variables, the MDLR model provided two risk strata for overall survival (OS) in the TC: low risk (5-year OS, 44.9%) and high risk (5-year OS, 4.9%).

INTERPRETATION

A tool based on MDLR was developed to consider that the MTM is an important prognosis factor for HCC patients. MDLR showed outstanding performance for the prognostic risk stratification of HCC patients who underwent HAIC and may help physicians with therapeutic decision making and surveillance strategy selection in clinical practice.

Exploration of a screening model for intrahepatic cholangiocarcinoma patients prone to cuproptosis and mechanisms of the susceptibility of CD274-knockdown intrahepatic cholangiocarcinoma cells to cuproptosis

Intrahepatic cholangiocarcinoma (ICC) is a form of liver cancer with poor long-term survival rates that requires novel therapeutic methods. Our team's previous research found that ICC patients prone to cuproptosis possessed a more satisfactory long-term prognosis and a more sensitive response to copper carrier Elesclomol. Thus, we aimed to identify new diagnostic and treatment strategies for ICC patients prone to cuproptosis and further explore the associated intracellular and extracellular mechanisms of ICC cells prone to cuproptosis. We employed FU-ICC (n = 255) as the training dataset, and validated our findings using SRRSH-ICC (from our center, n = 65), GSE26566 (n = 104), E-MTAB-6389 (n = 78), and scRNA-seq (n = 14) datasets. Single sample gene set enrichment analysis and subsequent unsupervised cluster analysis was conducted on the training dataset for the pan-programmed cell death gene set (including apoptosis, autophagy, ferroptosis, pyroptosis, necroptosis, and cuproptosis) to define and screen ICC patients prone to cuproptosis. We constructed a nomogram model using weighted gene co-expression network analysis and machine learning algorithms to predict ICC patients prone to cuproptosis, then explored its clinical value with multi-center transcriptome profiling. Furthermore, we validated the hub genes with in vitro and animal experiments to define ICC cells prone to cuproptosis. Ultimately, bulk and single-cell transcriptome profiling were utilized to explore the immune microenvironment of ICC cells prone to cuproptosis. Our nomogram model could help predict ICC patients prone to cuproptosis and possessed excellent prediction efficiency and clinical significance via internal and external verification. In vitro experiments demonstrated that ICC cells with siRNA-mediated knockdown of CD274 (PD-L1) and stimulation with elescomol-CuCl2 were prone to cuproptosis, and CD274-negative ICC cells could be defined as ICC cells prone to cuproptosis. The safety and feasibility of lenti-sh CD274+Elesclomol-CuCl2 as a therapeutic approach for ICC were verified using bioinformatics analysis and animal experiments. Bulk and single-cell transcriptome profiling indicated that the interactions between ICC cells prone to cuproptosis and monocytes/macrophages were particularly relevant. In conclusion, this study systematically and comprehensively explored cuproptosis in ICC for the first time. We constructed precise diagnostic and treatment strategies for ICC patients prone to cuproptosis and further explored the intracellular and extracellular mechanisms of ICC cells prone to cuproptosis. Further work with large prospective cohorts will help verify these conclusions.

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq data reveals dynamic changes in tumor-associated neutrophils in the tumor microenvironment of hepatocellular carcinoma and leads to the establishment of a neutrophil-related prognostic model

BACKGROUND

Analysis of hepatocellular carcinoma (HCC) single-cell sequencing data was conducted to explore the role of tumor-associated neutrophils in the tumor microenvironment.

METHODS

Analysis of single-cell sequencing data from 12 HCC tumor cores and five HCC paracancerous tissues identified cellular subpopulations and cellular marker genes. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to establish and validate prognostic models. xCELL, TIMER, QUANTISEQ, CIBERSORT, and CIBERSORT-abs analyses were performed to explore immune cell infiltration. Finally, the pattern of tumor-associated neutrophil roles in tumor microenvironmental components was explored.

RESULTS

A total of 271 marker genes for tumor-associated neutrophils were identified based on single-cell sequencing data. Prognostic models incorporating eight genes were established based on TCGA data. Immune cell infiltration differed between the high- and low-risk groups. The low-risk group benefited more from immunotherapy. Single-cell analysis indicated that tumor-associated neutrophils were able to influence macrophage, NK cell, and T-cell functions through the IL16, IFN-II, and SPP1 signaling pathways.

CONCLUSION

Tumor-associated neutrophils regulate immune functions by influencing macrophages and NK cells. Models incorporating tumor-associated neutrophil-related genes can be used to predict patient prognosis and immunotherapy responses.

Integrative analysis identified two subtypes and a taurine-related signature to predict the prognosis and efficacy of immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent subtypes of primary liver cancer, with high mortality and poor prognosis. Immunotherapy has revolutionized treatment strategies for many cancers. However, only a subset of patients with HCC achieve satisfactory benefits from immunotherapy. Therefore, a reliable biomarker that could predict the prognosis and immunotherapy response in patients with HCC is urgently needed. Taurine plays an important role in many physiological processes. However, its participation in the occurrence and progression of liver cancer and regulation of the composition and function of various components of the immune microenvironment remains elusive. In this study, we identified and validated two heterogeneous subtypes of HCC with different taurine metabolic profiles, presenting distinct genomic features, clinicopathological characteristics, and immune landscapes, using multiple bulk transcriptome datasets. Subsequently, we constructed a risk model based on genes related to taurine metabolism to assess the prognosis, immune cell infiltration, immunotherapy response, and drug sensitivity of patients with HCC. The risk model was validated using several independent external cohorts and showed a robust predictive performance. In addition, we evaluated the expression patterns of taurine metabolism-related genes in the tumor microenvironment and the heterogeneity of taurine metabolism among cancer cells using a single-cell transcriptome. In conclusion, our study provides insights into the important role played by taurine metabolism in tumor progression and immune regulation. Furthermore, the risk model can serve as a biomarker to assess patient prognosis and immunotherapy response, potentially helping clinicians make more precise and personalized clinical decisions.

Targeting the Heterogeneous Tumour-Associated Macrophages in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that comprises a complex tumour microenvironment (TME). Tumour-associated macrophages (TAMs) are one of the most abundant immune cells present in the TME, and play a key role both in the development and in the progression of HCC. Thus, TAM-based immunotherapy has been presented as a promising strategy to complement the currently available therapies for HCC treatment. Among the novel approaches focusing on TAMs, reprogramming their functional state has emerged as a promising option for targeting TAMs as an immunotherapy in combination with the currently available treatment options. Nevertheless, a further understanding of the immunobiology of TAMs is still required. This review synthesizes current insights into the heterogeneous nature of TAMs in HCC and describes the mechanisms behind their pro-tumoural polarization focusing the attention on their interaction with HCC cells. Furthermore, this review underscores the potential involvement of TAMs' reprogramming in HCC therapy and highlights the urgency of advancing our understanding of these cells within the dynamic landscape of HCC.

Intratumoral CD103+ CD8+ T cells predict response to neoadjuvant chemoimmunotherapy in advanced head and neck squamous cell carcinoma

BACKGROUND

Immune cell heterogenicity is known to determine the therapeutic response to cancer progression. Neoadjuvant chemoimmunotherapy (NACI) has shown clinical benefits in some patients with advanced head and neck squamous cell carcinoma (HNSCC), but the underlying mechanism behind this clinical response is unknown. The efficacy of NACI needs to be potentiated by identifying accurate biomarkers to predict clinical responses. Here, we attempted to identify molecules predicting NACI response in advanced HNSCC.

METHODS

We performed combined single-cell RNA sequencing (scRNA-seq) and multiplex immunofluorescence (mIHC) staining with tumor samples derived from NACI-treated HNSCC patients to identify a new tumor-infiltrating cell (TIL) subtype, CD103+ CD8+ TILs, associated with clinical response, while both in vitro and in vivo assays were carried out to determine its antitumor efficiency. The regulatory mechanism of the CD103+ CD8+ TILs population was examined by performing cell-cell interaction analysis of the scRNA-seq data and spatial analysis of the mIHC images.

RESULTS

We established intratumoral CD103+ CD8+ TILs density as a determinant of NACI efficacy in cancers. Our scRNA-seq results indicated that the population of CD103+ CD8+ TILs was dramatically increased in the responders of NACI-treated HNSCC patients, while mIHC analysis confirmed the correlation between intratumoral CD103+ CD8+ TILs density and NACI efficacy in HNSCC patients. Further receiver operating characteristic curve analysis defined this TIL subset as a potent marker to predict patient response to NACI. Functional assays showed that CD103+ CD8+ TILs were tumor-reactive T cells, while programmed cell death protein-1 (PD-1) blockade enhanced CD103+ CD8+ TILs cytotoxicity against tumor growth in vivo. Mechanistically, targeting the triggering receptor expressed on myeloid cells 2-positive (TREM2+ ) macrophages might enhance the population of CD103+ CD8+ TILs and facilitate antitumor immunity during NACI treatment.

CONCLUSIONS

Our study highlights the impact of intratumoral CD103+ CD8+ TILs density on NACI efficacy in different cancers, while the efforts to elevate its population warrant further clinical investigation.

RNA-Seq and Immune Repertoire Analysis of Normal and Hepatocellular Carcinoma Relapse After Liver Transplantation

Background

Hepatocellular carcinoma (HCC) relapse is the main reason for the poor prognosis of HCC after Liver transplantation (LT). This study aimed to explore the molecular mechanisms and immune repertoire profiles of HCC relapse.

Material and Methods

RNA-seq of blood samples from patients with normal (n=12) and HCC relapse (n=6) after LT was performed to identify differentially expressed genes (DEGs) and key signalling pathways. The DEGs and immune genes were further analyzed by bioinformatics. TRUST4 was used to analyze the differences in the immune repertoire between the two groups. Another 11 blood samples from patients with HCC who had received LT were collected for RT-qPCR verification of key genes.

Results

A total of 131 upregulated and 157 downregulated genes were identified using RNA-seq, and GO enrichment analysis revealed that the top 15 pathways were immune-related. The PPI network identified 10 key genes. Immune infiltration analysis revealed a significant difference in the five immune cell types between the two groups. A total of 83 intersecting genes were obtained by intersecting DEGs and immune genes. 6 key genes, including MX1, ISG15, OAS1, PRF1, SPP1, and THBS1 were obtained according to the intersection of DEGs, PPI network top 10 genes and immune intersecting genes. Immune repertoire analysis showed that the usage frequency of variable (V) and joining (J) genes in the normal group was higher than that in the relapse group. RT-qPCR validation showed that the expression levels of key genes were consistent with the RNA-seq results.

Conclusion

Our study identified key pathways and genes that could help determine whether transplant recipients are more prone to HCC relapse. Immune repertoire analysis revealed a difference in the usage frequency of VJ genes between the normal and relapse groups, providing a research direction for immunotherapy in patients with HCC relapse after liver transplantation.

Single-cell RNA sequencing reveals cell subpopulations in the tumor microenvironment contributing to hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is among the deadliest cancers worldwide, and advanced HCC is difficult to treat. Identifying specific cell subpopulations in the tumor microenvironment and exploring interactions between the cells and their environment are crucial for understanding the development, prognosis, and treatment of tumors. Methods: In this study, we constructed a tumor ecological landscape of 14 patients with HCC from 43 tumor tissue samples and 14 adjacent control samples. We used bioinformatics analysis to reveal cell subpopulations with potentially specific functions in the tumor microenvironment and to explore the interactions between tumor cells and the tumor microenvironment. Results: Immune cell infiltration was evident in the tumor tissues, and BTG1 ⁺ RGS1 ⁺ central memory T cells (Tcms) interact with tumor cells through CCL5-SDC4/1 axis. HSPA1B may be associated with remodeling of the tumor ecological niche in HCC. Cancer-associated fibroblasts (CAFs) and macrophages (TAMs) were closely associated with tumor cells. APOC1 ⁺ SPP1 ⁺ TAM secretes SPP1, which binds to ITGF1 secreted by CAFs to remodel the tumor microenvironment. More interestingly, FAP ⁺ CAF interacts with naïve T cells via the CXCL12-CXCR4 axis, which may lead to resistance to immune checkpoint inhibitor therapy. Conclusion: Our study suggests the presence of tumor cells with drug-resistant potential in the HCC microenvironment. Among non-tumor cells, high NDUFA4L2 expression in fibroblasts may promote tumor progression, while high HSPA1B expression in central memory T cells may exert anti-tumor effects. In addition, the CCL5-SDC4/1 interaction between BTG1 ⁺ RGS1 ⁺ Tcms and tumor cells may promote tumor progression. Focusing on the roles of CAFs and TAMs, which are closely related to tumor cells, in tumors would be beneficial to the progress of systemic therapy research.

Establishment and Validation of a Novel Risk Score for Hepatocellular Carcinoma Based on Bile Acid and Bile Salt Metabolism-Related Genes

Liver cancer is a public disease burden with an increasing incidence rate globally. Bile acid and bile salt's metabolic pathways participate in liver tumorigenesis and regulate the tumor microenvironment. However, there still remains a lack of systematic analysis of the genes related to bile acid and bile salt metabolic pathways in hepatocellular carcinoma (HCC). The mRNA expression data and clinical follow-up information of patients with HCC were obtained from public databases, including The Cancer Genome Atlas, Hepatocellular Carcinoma Database, Gene Expression Omnibus, and IMvigor210. The bile acid and bile salt metabolism-related genes were extracted from Molecular Signatures Database. Univariate Cox and logistic least absolute shrinkage and selection operator regression analyses were conducted to establish the risk model. Single sample gene set enrichment analysis, Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data, and Tumor Immune Dysfunction and Exclusion were adopted to analyze immune status. The efficiency of the risk model was tested using a decision tree and a nomogram. We determined two molecular subtypes based on bile acid and bile salt metabolism-related genes, with the prognosis of the S1 subtype being markedly superior to the S2 subtype. Next, we established a risk model based on the differentially expressed genes between the two molecular subtypes. The high-risk and low-risk groups showed significant differences in the biological pathways, immune score, immunotherapy response, and drug susceptibility. Our results demonstrated the good predictive performance of the risk model in immunotherapy datasets and established that it could be an essential factor affecting the prognosis of HCC. In conclusion, we identified two molecular subtypes based on bile acid and bile salt metabolism-related genes. The risk model established in our study could effectively predict the prognosis of patients with HCC and their immunotherapeutic response, which may contribute to targeted immunotherapy in HCC.

The Significance of SPP1 in Lung Cancers and Its Impact as a Marker for Protumor Tumor-Associated Macrophages

Macrophages are a representative cell type in the tumor microenvironment. Macrophages that infiltrate the cancer microenvironment are referred to as tumor-associated macrophages (TAMs). TAMs exhibit protumor functions related to invasion, metastasis, and immunosuppression, and an increased density of TAMs is associated with a poor clinical course in many cancers. Phosphoprotein 1 (SPP1), also known as osteopontin, is a multifunctional secreted phosphorylated glycoprotein. Although SPP1 is produced in a variety of organs, at the cellular level, it is expressed on only a few cell types, such as osteoblasts, fibroblasts, macrophages, dendritic cells, lymphoid cells, and mononuclear cells. SPP1 is also expressed by cancer cells, and previous studies have demonstrated correlations between levels of circulating SPP1 and/or increased SPP1 expression on tumor cells and poor prognosis in many types of cancer. We recently revealed that SPP1 expression on TAMs is correlated with poor prognosis and chemoresistance in lung adenocarcinoma. In this review, we summarize the significance of TAMs in lung cancers and discuss the importance of SPP1 as a new marker for the protumor subpopulation of monocyte-derived TAMs in lung adenocarcinoma. Several studies have shown that the SPP1/CD44 axis contribute to cancer chemoresistance in solid cancers, so the SPP1/CD44 axis may represent one of the most critical mechanisms for cell-to-cell communication between cancer cells and TAMs.

A key driver to promote HCC: Cellular crosstalk in tumor microenvironment

Liver cancer is the third greatest cause of cancer-related mortality, which of the major pathological type is hepatocellular carcinoma (HCC) accounting for more than 90%. HCC is characterized by high mortality and is predisposed to metastasis and relapse, leading to a low five-year survival rate and poor clinical prognosis. Numerous crosstalk among tumor parenchymal cells, anti-tumor cells, stroma cells, and immunosuppressive cells contributes to the immunosuppressive tumor microenvironment (TME), in which the function and frequency of anti-tumor cells are reduced with that of associated pro-tumor cells increasing, accordingly resulting in tumor malignant progression. Indeed, sorting out and understanding the signaling pathways and molecular mechanisms of cellular crosstalk in TME is crucial to discover more key targets and specific biomarkers, so that develop more efficient methods for early diagnosis and individualized treatment of liver cancer. This piece of writing offers insight into the recent advances in HCC-TME and reviews various mechanisms that promote HCC malignant progression from the perspective of mutual crosstalk among different types of cells in TME, aiming to assist in identifying the possible research directions and methods in the future for discovering new targets that could prevent HCC malignant progression.

Identification of molecular subtypes and prognostic signatures based on transient receptor potential channel-related genes to predict the prognostic risk of hepatocellular carcinoma: A review

Abnormal transient receptor potential (TRP) channel function interferes with intracellular calcium-based signaling and causes malignant phenotypes. However, the effects of TRP channel-related genes on hepatocellular carcinoma (HCC) remain unclear. This study aimed to identify HCC molecular subtypes and prognostic signatures based on TRP channel-related genes to predict prognostic risks. Unsupervised hierarchical clustering was applied to identify HCC molecular subtypes using the expression data of TRP channel-related genes. This was followed by a comparison of the clinical and immune microenvironment characteristics between the resulting subtypes. After screening for differentially expressed genes among subtypes, prognostic signatures were identified to construct risk score-based prognostic and nomogram models and predict HCC survival. Finally, tumor drug sensitivities were predicted and compared between the risk groups. Sixteen TRP channel-related genes that were differentially expressed between HCC and non-tumorous tissues were used to identify 2 subtypes. Cluster 1 had higher TRP scores, better survival status, and lower levels of clinical malignancy. Immune-related analyses also revealed higher infiltration of M1 macrophages and higher immune and stromal scores in Cluster 1 than in Cluster 2. After screening differentially expressed genes between subtypes, 6 prognostic signatures were identified to construct prognostic and nomogram models. The potential of these models to assess the prognostic risk of HCC was further validated. Furthermore, Cluster 1 was more distributed in the low-risk group, with higher drug sensitivities. Two HCC subtypes were identified, of which Cluster 1 was associated with a favorable prognosis. Prognostic signatures related to TRP channel genes and molecular subtypes can be used to predict HCC risk.

Diagnostic and prognostic value of secreted phosphoprotein 1 for idiopathic pulmonary fibrosis: a systematic review and meta-analysis

BackgroundThere is an increasing number of studies on the diagnostic and prognostic biomarkers associated with IPF. The purpose of this study was to explore the diagnostic and prognostic value of secreted phosphoprotein 1 (SPP1) in IPF.MethodsUsing five database, appropriate studies were included. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and 95% confidence intervals (CIs) were calculated. Pooled hazard ratios (HRs) and 95% CIs related to prognosis were calculated.ResultsThirteen studies were included in the meta-analyses. The pooled sensitivity, specificity, PLR, NLR and DOR were 0.84 (95% CI 0.72-0.91), 0.89 (95% CI 0.83-0.94), 7.94 (95% CI 4.63-13.62), 0.18 (95% CI 0.10-0.33), 43.08 (95% CI 15.88-116.84) for SPP1 in the differential diagnosis of IPF and healthy people. The pooled sensitivity, specificity, PLR, NLR and DOR were 0.97 (95% CI 0.57-1.00), 0.93 (95% CI 0.73-0.98), 13.87 (95% CI 3.26-58.99), 0.03 (95% CI 0-0.68), 446.91 (95% CI 21.02-9504.41) for SPP1 to differentiate IPF and lung cancer patients. High SPP1 expression predicts poor prognosis for IPF patients (HR= 1.42, 95% CI = 1.27 and 1.58, P < 0.001).ConclusionsSPP1 is a potential diagnostic and prognostic biomarker for IPF patients.

Comprehensive genomic signature of pyroptosis-related genes and relevant characterization in hepatocellular carcinoma

Background

Currently, the most predominant type of liver cancer is hepatocellular carcinoma (HCC), which is also the fourth leading cause of cancer-related death in the global population. Pyroptosis is an emerging form of cell death that affects the prognosis of cancer patients by modulating tumor cell migration, proliferation and invasion. However, the evaluation of pyroptosis in the prognosis of HCC is still insufficient.

Methods

A total of 365 HCC patients from the TCGA-LIHC cohort were classified into two distinct subtypes using consensus clustering of pyroptosis-related genes (PRGs). Following univariate Cox analysis of differentially expressed genes between subtypes, we established a prognostic model (PRGs-score, PRGS) by LASSO Cox analysis. We further tested the predictive power of the prognostic model in the ICGC (LIRI-JP) and GEO (GSE14520) cohorts. The tumor microenvironment (TME) was studied using the CIBERSORT. The enrichment scores for immune cells and immune functions in low- and high-PRGS groups were assessed using ssGSEA. The IMvigor210 cohort was used to investigate the immunotherapy efficacy. Furthermore, we validated the expression of prognostic genes in PRGS by RT-qPCR in vitro.

Results

The subtyping of HCC based on PRGs exhibited distinct clinical characteristics. We developed a prognostic model PRGS by differentially expressed genes between different subtypes. The results showed that PRGS could well forecast the survival of HCC patients in different cohorts and was associated with the immune microenvironment. Moreover, PRGS was considered to be an independent prognostic risk factor and superior to other pyroptosis-related signatures. Low-PRGS implied greater immune cell infiltration and better overall survival with immunotherapy. The results of RT-qPCR also showed that prognostic genes were significantly dysregulated in HCC.

Conclusions

PRGS has promising application in forecasting the prognosis of HCC patients, and its relationship with the immune microenvironment provides a basis for the subsequent treatment and research of HCC.

A novel myeloid cell marker genes related signature can indicate immune infiltration and predict prognosis of hepatocellular carcinoma: Integrated analysis of bulk and single-cell RNA sequencing

Myeloid cells are physiologically related to innate immunity and inflammation. Tumor-associated myeloid cells gained increasing interest because of their critical roles in tumor progression and anticancer immune responses in human malignancies. However, the associations between tumor-associated myeloid cell-related genes and hepatocellular carcinoma have yet to be revealed. Here, through the integrating analysis of bulk and single-cell RNA (scRNA) sequencing of public HCC samples, we developed a gene signature to investigate the role of HCC-specific myeloid signature genes in HCC patients. We firstly defined 317 myeloid cell marker genes through analyzing scRNA data of HCC from the GEO dataset. After selecting the differentially expressed genes, eleven genes were also proved prognostic. Then we built a gene signature from the TCGA cohort and verified further with the ICGC dataset by applying the LASSO Cox method. An eight genes signature (FABP5, C15orf48, PABPC1, TUBA1B, AKR1C3, NQO1, AKR1B10, SPP1) was achieved finally. Patients in the high risk group correlated with higher tumor stages and poor survival than those in the low-risk group. The risk score was proved to be an independent risk factor for prognosis. The high risk group had higher infiltrations of dendritic cells, macrophages and Tregs. And the APC co-inhibition, T cell co-inhibition pathways were also activated. Besides, the risk score positively correlated with multidrug resistance proteins. In conclusion, our myeloid cell marker genes related signature can predict patients' survival and may also indicate the levels of immune infiltration and drug resistance.

Hepatocellular carcinoma subtypes based on metabolic pathways reveals potential therapeutic targets

Introduction

Hepatocellular carcinoma (HCC) is an aggressive malignancy with steadily increasing incidence rates worldwide and poor therapeutic outcomes. Studies show that metabolic reprogramming plays a key role in tumor genesis and progression. In this study, we analyzed the metabolic heterogeneity of epithelial cells in the HCC and screened for potential biomarkers.

Methods

The hepatic single-cell RNA sequencing (scRNA-seq) datasets of HCC patients and healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Based on data intergration and measurement of differences among groups, the metabolic epithelial cell subpopulations were identified. The single-cell metabolic pathway was analyzed and the myeloid subpopulations were identified. Cell-cell interaction analysis and single-cell proliferation analysis were performed. The gene expression profiles of HCC patients were obtained from the GSE14520 dataset of GEO and TCGA-LIHC cohort of the UCSC Xena website. Immune analysis was performed. The differentially expressed genes (DEGs) were identified and functionally annotated. Tumor tissues from HCC patients were probed with anti-ALDOA, anti-CD68, anti-CD163, anti-CD4 and anti-FOXP3 antibodies. Results We analyzed the scRNA-seq data from 48 HCC patients and 14 healthy controls. The epithelial cells were significantly enriched in HCC patients compared to the controls (p = 0.011). The epithelial cells from HCC patients were classified into two metabolism-related subpopulations (MRSs) - pertaining to amino acid metabolism (MRS1) and glycolysis (MRS2). Depending on the abundance of these metabolic subpopulations, the HCC patients were also classified into the MRS1 and MRS2 subtype distinct prognoses and immune infiltration. The MRS2 group had significantly worse clinical outcomes and more inflamed tumor microenvironment (TME), as well as a stronger crosstalk between MRS2 cells and immune subpopulations that resulted in an immunosuppressive TME. We also detected high expression levels of ALDOA in the MRS2 cells and HCC tissues. In the clinical cohort, HCC patients with higher ALDOA expression showed greater enrichment of immunosuppressive cells including M2 macrophages and T regulatory cells.

Discussion

The glycolytic subtype of HCC cells with high ALDOA expression is associated with an immunosuppressive TME and predicts worse clinical outcomes, providing new insights into the metabolism and prognosis of HCC.

A novel prognostic model based on urea cycle-related gene signature for colorectal cancer

Background

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the world. This study aimed to develop a urea cycle (UC)-related gene signature that provides a theoretical foundation for the prognosis and treatment of patients with CRC.

Methods

Differentially expressed UC-related genes in CRC were confirmed using differential analysis and Venn diagrams. Univariate Cox and least absolute shrinkage and selection operator regression analyses were performed to identify UC-related prognostic genes. A UC-related signature was created and confirmed using distinct datasets. Independent prognostic predictors were authenticated using Cox analysis. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts algorithm and Spearman method were applied to probe the linkage between UC-related prognostic genes and tumor immune-infiltrating cells. The Human Protein Atlas database was used to determine the protein expression levels of prognostic genes in CRC and normal tissues. Verification of the expression levels of UC-related prognostic genes in clinical tissue samples was performed using real-time quantitative polymerase chain reaction (qPCR).

Results

A total of 49 DEUCRGs in CRC were mined. Eight prognostic genes (TIMP1, FABP4, MMP3, MMP1, CD177, CA2, S100P, and SPP1) were identified to construct a UC-related gene signature. The signature was then affirmed using an external validation set. The risk score was demonstrated to be a credible independent prognostic predictor using Cox regression analysis. Functional enrichment analysis revealed that focal adhesion, ECM-receptor interaction, IL-17 signaling pathway, and nitrogen metabolism were associated with the UC-related gene signature. Immune infiltration and correlation analyses revealed a significant correlation between UC-related prognostic genes and differential immune cells between the two risk subgroups. Finally, the qPCR results of clinical samples further confirmed the results of the public database.

Conclusion

Taken together, this study authenticated UC-related prognostic genes and developed a gene signature for the prognosis of CRC, which will be of great significance in the identification of prognostic molecular biomarkers, clinical prognosis prediction, and development of treatment strategies for patients with CRC.

TSH-SPP1/TRβ-TSH positive feedback loop mediates fat deposition of hepatocyte: Crosstalk between thyroid and liver

Aims

We conducted this study with two aims: (1) whether TRβ could be damaged by NAFLD, thereby represent thyroid hormone resistance-like manifestation and (2) to analyze the potential role of SPP1 in TH signaling pathway on the process of NAFLD. This study is expected to provide a new perspective on the therapeutic mechanism in the pathological course of NAFLD.

Methods

A total of 166 patients diagnosed with type 2 diabetes mellitus (T2DM) were enrolled in this study. All patients had a BMI above 24 kg/m2 and were stratified into two groups: NAFLD and Non-NAFLD groups. Ages, gender, BMI, duration of diabetes and biochemical markers were obtained from participants' records. We downloaded the dataset GSE48452 from GEO. The Pathview library was used to make the thyroid hormone signaling pathway visualization. The CIBERSORT algorithm was applied to calculate the infiltrated immune cells in obese NAFLD patients. C57BL/6 mice were randomly selected to constitute the normal control (NC) group and were fed a normal chow diet; the rest of the mice were fed a high-fat diet (HFD). After 12 weeks HFD feeding, the mice were sacrificed by cervical dislocation, and blood samples were collected. Mouse livers were also collected; one part of each liver was fixed in 10% formalin for histological analysis, and the other part was snap-frozen for subsequent molecular analyses. To explore the relationship between SPP1, TRβ and lipid deposition in hepatocytes, HepG2 cells were treated with 50 μ M concentration of PA and/or 20 ng/ml concentration of rh-SPP1 for 48h. In addition, the PC3.1-TRβ plasmid was constructed for further validation in HepG2 cells. We used THP-1 cells to construct an M1 macrophage model in vitro. We then analyzed THP-1 cells treated with various concentrations of PA or TSH.

Results

(1) After adjusting for all factors that appeared P value less than 0.1 in the univariate analysis, BMI, TSH, and FT3 were significant independent risk factors of NAFLD (ORs were 1.218, 1.694, and 2.259, respectively); (2) A further analysis with BMI stratification indiacted that both FT3 and TSH had a significant change between individuals with NAFLD and Non-NAFLD in obesity subgroup; however, there was no statistic difference in over-weight group; (3) Bioinformatics analysis of GSE48452 had shown that several key molecular (including TRβ) of thyroid hormone pathway affected by NAFLD induced transcriptomic changes and the expression levels of SPP1, FABP4 and RPS4Y1 were significantly higher, while the expression levels of PZP and VIL1 were significantly decreased in NAFLD patients(adjusted p < 0.05, |logFC| > 1.0). The CIBERSORT algorithm showed increased M0 and M1, decreased M2 macrophage infiltration in NAFLD with comparison to healthy obese group; (4) After 12 weeks of HFD-feeding, the obesity mice had significantly higher serum TSH and In IHC-stained liver sections of obesity group, the intensity of SPP1 had a significantly increased, while TRβ reduced; (5) In vitro studies have shown SPP1 aggravated lipid deposition in hepatic cells dependent on down-regulating the expression of TRβ and TSH acts to promote secretion of SPP1 in M1 macrophage cells.

Conclusions

SPP1 secretion induced by M1 macrophage polarization, which may down-regulates TRβ in hepatocytes via paracrine manner, on the one hand, the lipid deposition aggravating in liver, on the other hand, a compensatory increase of TSH in serum. The increased TSH can further lead to the following SPP1 secretion of M1 macrophage. The positive feedback crosstalk between thyroid and liver, may be plays an important role in maintaining and amplifying pathological process of NAFLD.

Evaluating the role of IDO1 macrophages in immunotherapy using scRNA-seq and bulk-seq in colorectal cancer

Background

Macrophage infiltration is crucial for colorectal cancer (CRC) immunotherapy. Detailed classification of macrophage subsets will facilitate the selection of patients suitable for immunotherapy. However, the classification of macrophages in CRC is not currently detailed.

Methods

In this study, we combined single-cell RNA sequencing (scRNA-seq) and bulk-seq to analyze patients with colorectal cancer. scRNA-seq data were used to study cell-cell communication and to differentiate immune-infiltrating cells and macrophage subsets. Bulk-seq data were used to further analyze immune infiltration, clinical features, tumor mutational burden, and expression of immune checkpoint molecules in patients with CRC having different macrophage subsets.

Results

Seven macrophage subpopulations were identified, among which indoleamine 2,3 dioxygenase 1 (IDO1) macrophages had the most significant difference in the degree of infiltration among normal, microsatellite-unstable, and microsatellite-stable populations. We then performed gene set variation analysis using 12 marker genes of IDO1 macrophages and divided the patients into two clusters: high-IDO1 macrophages (H-IDO1M) and low-IDO1 macrophages (L-IDO1M). H-IDO1M showed higher infiltration of immune cells, higher expression of immune checkpoints, and less advanced pathological stages than L-IDO1M (p < 0.05).

Conclusions

This study elucidated that IDO1-macrophage-based molecular subtypes can predict the response to immunotherapy in patients with CRC. The results provide new insights into tumor immunity and help in clinical decisions regarding designing effective immunotherapy for these patients.

The role of hypoxia-related genes in TACE-refractory hepatocellular carcinoma: Exploration of prognosis, immunological characteristics and drug resistance based on onco-multi-OMICS approach

Transcatheter arterial chemoembolization (TACE) is an effective treatment for hepatocellular carcinoma (HCC). During TACE, chemotherapeutic agents are locally infused into the tumor and simultaneously cause hypoxia in tumor cells. Importantly, the poor effect of TACE in some HCC patients has been shown to be related to dysregulated expression of hypoxia-related genes (HRGs). Therefore, we identified 33 HRGs associated with TACE (HRGTs) by differential analysis and characterized the mutational landscape of HRGTs. Among 586 HCC patients, two molecular subtypes reflecting survival status were identified by consistent clustering analysis based on 24 prognosis-associated HRGs. Comparing the transcriptomic difference of the above molecular subtypes, three molecular subtypes that could reflect changes in the immune microenvironment were then identified. Ultimately, four HRGTs (CTSO, MMP1, SPP1, TPX2) were identified based on machine learning approachs. Importantly, risk assessment can be performed for each patient by these genes. Based on the parameters of the risk model, we determined that high-risk patients have a more active immune microenvironment, indicating “hot tumor” status. And the Tumor Immune Dysfunction and Exclusion (TIDE), the Cancer Immunome Atlas (TCIA), and Genome of Drug Sensitivity in Cancer (GDSC) databases further demonstrated that high-risk patients have a positive response to immunotherapy and have lower IC50 values for drugs targeting cell cycle, PI3K/mTOR, WNT, and RTK related signaling pathways. Finally, single-cell level analysis revealed significant overexpression of CTSO, MMP1, SPP1, and TPX2 in malignant cell after PD-L1/CTLA-4 treatment. In conclusion, Onco-Multi-OMICS analysis showed that HRGs are potential biomarkers for patients with refractory TACE, and it provides a novel immunological perspective for developing personalized therapies.

Single-Cell Transcriptomic Analysis Reveals Macrophage–Tumor Crosstalk in Hepatocellular Carcinoma

As one of the most malignant cancer, hepatocellular carcinoma (HCC) has a complex ecosystem featured by high heterogeneity. Cell crosstalk is demonstrated to be critical for HCC development. However, the cell communication orchestration in HCC remains largely unknown. Here, by analyzing the single-cell transcriptomes of the primary tumor tissues (n = 10) and tumor-adjacent tissues (n = 8) derived from 10 patients with HCC, we found that the proportions of plasmacytoid dendritic cells (pDCs) and natural killer (NK) cells were reduced and that the proportion of macrophages was increased in the immune component of the primary tumor, compared with those in the tumor-adjacent tissue. Furthermore, we found widespread communication between macrophage populations and other cell types, and this communication was remarkably strengthened in the primary tumor, especially with HCC malignant cells. In addition, the SPP1–CD44 axis was identified as a unique interaction between macrophages and HCC malignant cells. Our comprehensive portrait of cell communication patterns over the HCC ecosystem reveals further insights into immune infiltration.

SPP1 as a key gene in the lymph node metastasis and a potential predictor of poor prognosis in head and neck carcinoma

BACKGROUND

Lymph node metastasis (LNM) is an important cause leading to recurrence and development of head and neck carcinoma (HNC), with the precise mechanisms unclear. Thus, we aimed to identify the key genes involved in LNM and further evaluate their expressions and roles.

METHODS

A cohort of HNC in the TCGA was analyzed. The study involved three phases (one screening and two validation phases). First, the differentially expressed genes regarding LNM were screened, from which a key gene was identified by a series of data mining approaches. Then, the expressions and roles of the key gene were validated in HNC through bioinformatics. Afterward, the expression of the key gene was detected by qPCR, western blot, and Immunohistochemistry based on a cell model and a tissue microarray. Further, colony formation and transwell migration and invasion assays were used to evaluate the roles of the key gene.

RESULTS

SPP1 was overexpressed in HNC tissues and was identified as the key gene. Overexpression of SPP1 in HNC was correlated with advanced pathological stages and T-stage, as well as the presence of LNM, which predicted poor prognosis. The expression of SPP1 was closely associated with the infiltration of immune cells in HNC, especially M2 macrophages. Lab experiments confirmed that SPP1 silence in HNC cells resulted in weakened invasive and metastatic abilities.

CONCLUSION

This study reveals that SPP1 may be a key gene associated with LNM in HNC, raising the possibility of SPP1 as a target for HNC prevention and treatment. This article is protected by copyright. All rights reserved.

The Role of Chronic Liver Diseases in the Emergence and Recurrence of Hepatocellular Carcinoma: An Omics Perspective

Hepatocellular carcinoma (HCC) typically develops from a background of cirrhosis resulting from chronic inflammation. This inflammation is frequently associated with chronic liver diseases (CLD). The advent of next generation sequencing has enabled extensive analyses of molecular aberrations in HCC. However, less attention has been directed to the chronically inflamed background of the liver, prior to HCC emergence and during recurrence following surgery. Hepatocytes within chronically inflamed liver tissues present highly activated inflammatory signaling pathways and accumulation of a complex mutational landscape. In this altered environment, cells may transform in a stepwise manner toward tumorigenesis. Similarly, the chronically inflamed environment which persists after resection may impact the timing of HCC recurrence. Advances in research are allowing an extensive epigenomic, transcriptomic and proteomic characterization of CLD which define the emergence of HCC or its recurrence. The amount of data generated will enable the understanding of oncogenic mechanisms in HCC from the CLD perspective and provide the possibility to identify robust biomarkers or novel therapeutic targets for the treatment of primary and recurrent HCC. Importantly, biomarkers defined by the analysis of CLD tissue may permit the early detection or prevention of HCC emergence and recurrence. In this review, we compile the current omics based evidence of the contribution of CLD tissues to the emergence and recurrence of HCC.

Single-Cell RNA-seq Analysis Reveals Dysregulated Cell-Cell Interactions in a Tumor Microenvironment Related to HCC Development

The heterogeneity of tumor microenvironment (TME) of hepatocellular carcinoma (HCC) may relate to cell-cell interaction event (CCE) dysregulation and would affect therapeutic responses and clinical outcomes. To reveal the differentiation of CCEs in the liver tissue from healthy donors (HD) to HCC, scRNA-seq data of ~62000 cells from HD, paracancerous nontumor tissue (NT), and HCC were analyzed. The microenvironmental CCE landscape was constructed. Dysregulated cell types and changed molecular functions were identified with CCE alterations in HCC. Dysregulated CCEs which function as pivotal roles in tumorigenesis and development of HCC included SPP1-CD44, MIF-TNFRSF14, and VEGFA-NRP1. A CCE-based immune regulatory network was extracted to illustrate the mechanism of TME dysregulation. A prognostic signature based on CCE genes was identified and validated in independent datasets. Our study provided insights into the characteristics of the cross-talk between tumor cells and microenvironment in HCC and established a workflow strategy for CCE analyses based on scRNA-seq data.

Single-cell transcriptomics identifies premature aging features of TERC-deficient mouse brain and bone marrow

Aging is a progressive loss of physiological function and increased susceptibility to major pathologies. Degenerative diseases in both brain and bone including Alzheimer disease (AD) and osteoporosis are common in aging groups. TERC is RNA component of telomerase, and its deficiency accelerates aging-related phenotypes including impaired life span, organ failure, bone loss, and brain dysfunction. In this study, we investigated the traits of bone marrow-brain cross-tissue communications in young mice, natural aging mice, and premature aging (TERC deficient, TERC-KO) mice by single-cell transcriptome sequencing. Differentially expressed gene analysis of brain as well as bone marrow between premature aging mouse and young mouse demonstrated aging-related inflammatory response and suppression of neuron development. Further analysis of senescence-associated secretory phenotype (SASP) landscape indicated that TERC-KO perturbation was enriched in oligodendrocyte progenitor cells (OPCs) and hematopoietic stem and progenitor cells (HSPC). Series of inflammatory associated myeloid cells was activated in premature aging mice brain and bone marrow. Cross-tissue comparison of TERC-KO mice brain and bone marrow illustrated obvious ligand-receptor communications between brain glia cells, macrophages, and bone marrow myeloid cells in premature aging-induced inflammation. Enrichment of co-regulation modules between brain and bone marrow identified premature aging response genes such as Dusp1 and Ifitm3. Our study provides a rich resource for understanding premature aging-associated perturbation in brain and bone marrow and supporting myeloid cells and endothelial cells as promising therapy targeting for age-related brain-bone diseases.

Mapping and Validation of scRNA-Seq-Derived Cell-Cell Communication Networks in the Tumor Microenvironment

Recent advances in single-cell technologies, particularly single-cell RNA-sequencing (scRNA-seq), have permitted high throughput transcriptional profiling of a wide variety of biological systems. As scRNA-seq supports inference of cell-cell communication, this technology has and continues to anchor groundbreaking studies into the efficacy and mechanism of novel immunotherapies for cancer treatment. In this review, we will highlight methods developed to infer inter- and intracellular signaling from scRNA-seq and discuss how they have contributed to studies of immunotherapeutic intervention in the tumor microenvironment (TME). However, a central challenge remains in validating the hypothesized cell-cell interactions. Therefore, this review will also cover strategies for integration of these scRNA-seq-derived interaction networks with existing experimental and computational approaches. Integration of these networks with imaging, protein secretion measurements, and network analysis and mathematical modeling tools addresses challenges that remain with scRNA-seq to enhance studies of immunosuppressive and immunotherapy-altered signaling in the TME.

Depiction of the genomic and genetic landscape identifies CCL5 as a protective factor in colorectal neuroendocrine carcinoma

BACKGROUND

Colorectal neuroendocrine carcinomas (CRNECs) are highly aggressive tumours with poor prognosis and low incidence. To date, the genomic landscape and molecular pathway alterations have not been elucidated.

METHODS

Tissue sections and clinical information of CRNEC (n = 35) and CR neuroendocrine tumours (CRNETs) (n = 25) were collected as an in-house cohort (2010-2020). Comprehensive genomic and expression panels (AmoyDx® Master Panel) were applied to identify the genomic and genetic alterations of CRNEC. Through the depiction of the genomic landscape and transcriptome profile, we compared the difference between CRNEC and CRNET. Reverse transcription-polymerase chain reaction and immunofluorescence staining were performed to confirm the genetic alterations.

RESULTS

High tumour mutation load was observed in CRNEC compared with CRNET. CRNECs showed a "cold" immune landscape and increased endothelial cell activity compared with NETs. Importantly, PAX5 was aberrantly expressed in CRNEC and predicted a poor prognosis of CRNECs. CCL5, a factor that is considered an immunosuppressive factor in several tumour types, was strongly expressed in CRNEC patients with long-term survival and correlated with high CD8⁺ T cell infiltration.

CONCLUSION

Through the depiction of the genomic landscape and transcriptome profile, we demonstrated alterations in molecular pathways and potential targets for immunotherapy in CRNEC.