Single-cell transcriptomic analyses provide insights into the cellular origins and drivers of brain metastasis from lung adenocarcinoma

Cancer-associated fibroblast-derived SEMA3C facilitates colorectal cancer liver metastasis via NRP2-mediated MAPK activation

Liver metastasis remains the predominant cause of mortality in patients with colorectal cancer (CRC). Nevertheless, the mechanisms underlying the initiation of colorectal cancer liver metastasis remain poorly elucidated. During the metastatic process of CRC cells from the primary site to the liver, we performed time-resolved analyses and identified a subset of tumor cells spatially located in the primary tumor and temporally distributed in the early stages of liver metastasis. These cells were termed liver metastasis-initiating cells (LMICs). LMICs exhibit high stemness, low proliferation, active interaction with surrounding stromal components, and a close association with liver metastasis. Notably, we found significant interactions between cancer-associated fibroblasts (CAFs) and LMICs via the SEMA3C-NRP2 receptor-ligand pair. Further in vivo and in vitro experiments confirmed that CAF-secreted SEMA3C could bind to the NRP2 receptor, which activates the MAPK pathway and promotes colorectal cancer liver metastasis. Our findings suggest potential therapeutic strategies for the early prevention of colorectal cancer liver metastasis.

Exploring the level of metabolic reprogramming and the role of prognostic factor SF3A3 in hepatocellular carcinoma through integrated single-cell landscape analysis

This study aims to investigate metabolic reprogramming heterogeneity in hepatocellular carcinoma (HCC) cells and identify novel therapeutic targets for HCC treatment. Single-cell RNA sequencing data from public databases were used to analyze the TME of HCC and reveal the characteristics of different cell subsets, including mononuclear phagocytes, epithelial cells, endothelial cells, NK/T cells, B cells, and unknown cells. The analysis revealed that these cell subsets play their own unique roles in tumor progression and immune escape. Analysis of copy number variations (CNVs) was performed on tumor-derived epithelial cells, with the epithelial cells in Cluster 3 subgroup showing the highest CNV levels. Gene Ontology (GO) enrichment analysis revealed that these cell subsets were involved in a variety of biological processes such as immune response, cell communication, and metabolic pathways, which were consistent with their functional roles. Pseudotemporal analysis further delineated the malignant trajectory of HCC cells, with Cluster 3 exhibiting enhanced phosphatidylinositol metabolism, suggesting a critical role for metabolic reprogramming in tumor invasion and proliferation. Furthermore, a diagnostic model incorporating metabolic reprogramming-associated gene signatures was established, which effectively distinguished HCC from normal tissues. Among these signatures, splicing factor 3a subunit 3 (SF3A3) was identified as both diagnostic and independent prognostic biomarker. Mechanistically, SF3A3 knockdown in HCC cell lines significantly suppressed proliferation, migration, PI3K/AKT signaling, and EMT marker expression, thereby demonstrating its role in driving HCC aggressiveness. In conclusion, these findings elucidate novel molecular characteristics of HCC based on metabolic reprogramming, while establishing SF3A3 as a promising multi-faceted target for HCC diagnosis, prognostic assessment, and therapeutic intervention.

The MYC/TXNIP axis mediates NCL-Suppressed CD8+T cell immune response in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma is a deadly malignancy with immune evasion playing a key role in tumor progression. Glucose metabolism is crucial for T cell function, and the nucleolar protein NCL may influence T cell glucose metabolism. This study aims to investigate NCL's role in T cell glucose metabolism and immune evasion by lung adenocarcinoma cells.

METHODS

Utilizing single-cell RNA sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we analyzed cell clustering, annotation, and prognosis. In vitro experiments involved manipulating NCL expression in CD8+ T cells to study immune function and glucose metabolism. In vivo studies using an orthotopic transplant mouse model monitored NCL's impact on CD8+ T cell glucose metabolism and anti-tumor immune function.

RESULTS

NCL was associated with T cell dysfunction and glucose metabolism. NCL silencing enhanced CD8+ T cell glucose metabolism, cytotoxicity, and infiltration, while NCL overexpression had the opposite effect. NCL overexpression relieved MYC-mediated transcriptional repression of TXNIP, reducing CD8+ T cell glucose metabolism. In vivo, NCL inhibited CD8+ T cell glucose metabolism through the MYC/TXNIP axis, hindering anti-tumor immune function.

CONCLUSIONS

NCL overexpression suppresses CD8+ T cell glucose metabolism and anti-tumor immune function, promoting lung adenocarcinoma progression via the MYC/TXNIP axis.

Immune atlas of pituitary neuroendocrine tumors highlights endocrine-driven immune signature and therapeutic implication

Whether the tumor microenvironment is shaped by endocrine hormone secretion, as well as its cellular heterogeneity and therapeutic implications in pituitary neuroendocrine tumors (pitNETs), remains poorly understood. We demonstrate that pitNETs exhibit a sparse immune infiltration. Mass cytometry of 97,418 immune cells from 56 pitNETs establishes a high-resolution atlas, with macrophages and T cells comprising the predominant populations. Hormone secretion status dictates the immune composition and cellular phenotype. Functioning pitNETs are enriched with T cells, with robust expression of immune-suppressive markers CD38, programmed death (PD)-1, and PD-L1. The lymphoid-enriched microenvironment is associated with shorter progression-free survival in patients with pitNETs. Integrating PD-1 blockade with tumor-targeted therapy in functioning pitNETs demonstrates synergistic efficacy with enhanced apoptosis, induces cell-cycle arrest, and suppresses hormone secretion using patient-derived primary cell cultures. Altogether, our findings provide an extended resource on the cellular and functional heterogeneity of the pitNET immune microenvironment and offer a conceptual framework for rational therapeutic strategies.

E2F7 upregulates MCM4 and fatty acid metabolism to advance lung adenocarcinoma metastasis

BACKGROUND

MCM4, a key protein in MCM, is frequently overexpressed in cancers, but its specific role in lung adenocarcinoma (LUAD) metastasis is unclear.

METHODS

Bioinformatics revealed the mRNA expression pattern of MCM4 in LUAD, which we confirmed in both normal lung epithelial and adenocarcinoma cell lines using qRT-PCR and western blot (WB). Cellular proliferation was gauged by cell counting kit-8 and colony formation assays, and the expression of epithelial-mesenchymal transition markers along with fatty acid synthase (FASN) was probed via WB. We employed Transwell to assess cellular migration and invasion, and utilized kits for quantifying intracellular triglycerides and phospholipids. Bioinformatics identified E2F7 as a potential transcriptional regulator of MCM4, prompting us to explore its relationship with MCM4, including predicted binding sites and E2F7 mRNA expression in LUAD. Chromatin immunoprecipitation and dual-luciferase reporter assays were conducted to validate the regulatory effects of E2F7 on MCM4.

RESULTS

MCM4 was found to be overexpressed in LUAD, and its knockdown inhibited cancer cell proliferation, migration, invasion, and metastasis, along with decreased FASN expression and declined levels of triglycerides and phospholipids within cells. Mechanistically, E2F7 transcriptionally activated MCM4, regulating fatty acid metabolism and promoting LUAD progression and metastasis.

CONCLUSION

Our study elucidates the mechanism by which E2F7 transcriptionally controls MCM4 to activate fatty acid metabolism, fueling LUAD metastasis. These discoveries emphasize the pivotal function of lipid metabolism in LUAD development and suggests new therapeutic targets for LUAD treatment.

Characteristics of the Dynamic Evolutionary Pathway of ADSCs Induced Differentiation into Astrocytes Based on scRNA-Seq Analysis

We employed single-cell transcriptome sequencing to reveal the dynamic gene expression changes during the differentiation of adipose-derived stromal cells (ADSCs) into astrocytes. Single-cell RNA sequencing was conducted on cells from the ADSCs group and the induced groups at 2, 7, 14, and 21 days using the 10 × Chromium platform. Data underwent quality control and dimensionality reduction. Cell differentiation trajectories were constructed using Monocle2, and differentially expressed genes (DEGs) in each cell cluster were identified using differential selection algorithms. DEGs at each time point were annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and regulatory intensities of transcription factors were analyzed using SCENIC. Integrating all groups, a total of five samples were divided into 13 cell clusters (0-12 clusters). DEGs between clusters and those compared with ADSCs at various induced time points showed distinct specificities. Monocle2 constructed cell differentiation trajectories; ADSCs can differentiate into mature astrocytes not only through the direct pathway from the 1 branch to the 3 branch but also through an indirect pathway, involving the 1 branch to the 2 branch before progressing to the 3 branch. SCENIC analysis highlighted the critical regulatory roles of STAT1, MYEF2, and SOX6 transcription factors during the differentiation of ADSCs into astrocytes. ADSCs can differentiate into mature astrocytes through two distinct pathways: direct and indirect. By the 14th day of induction, mature astrocytes have formed, characterized by a cell cycle arrest in mitosis. Further induction leads to degenerative senescence changes in differentiated cells.

Cancer brain metastasis: molecular mechanisms and therapeutic strategies

Brain metastases (BMs) are the most common intracranial tumors in adults and the major cause of cancer-related morbidity and mortality. The occurrence of BMs varies according to the type of primary tumors with most frequence in lung cancer, melanoma and breast cancer. Among of them, lung cancer has been reported to have a higher risk of BMs than other types of cancers with 40 ~ 50% of such patients will develop BMs during the course of disease. BMs lead to many neurological complications and result in a poor quality of life and short life span. Although the treatment strategies were improved for brain tumors in the past decades, the prognosis of BMs patients is grim. Poorly understanding of the molecular and cellular characteristics of BMs and the complicated interaction with brain microenvironment are the major reasons for the dismal prognosis of BM patients. Recent studies have enhanced understanding of the mechanisms of BMs. The newly identified potential therapeutic targets and the advanced therapeutic strategies have brought light for a better cure of BMs. In this review, we summarized the mechanisms of BMs during the metastatic course, the molecular and cellular landscapes of BMs, and the advances of novel drug delivery systems for overcoming the obstruction of blood-brain barrier (BBB). We further discussed the challenges of the emerging therapeutic strategies, such as synergistic approach of combining targeted therapy with immunotherapy, which will provide vital clues for realizing the precise and personalized medicine for BM patients in the future.

Comprehensive exploration of programmed cell death landscape in lung adenocarcinoma combining multi-omic analysis and experimental verification

The mortality and therapeutic failure in lung adenocarcinoma (LUAD) are mainly resulted from the wide metastasis and chemotherapy resistance. Up to now, accurate and stable predictive prognostic indicator for revealing the progress and novel therapeutic strategies of LUAD is infrequent, nonetheless. Diversified programmed cell death (PCD) has been widely confirmed that participated in the occurrence and development of various malignant tumors, respectively. In this research, we integrated fourteen types of PCD, bulk multi-omic data from TCGA-LUAD and other cohorts in gene expression omnibus (GEO) and clinical LUAD patients to develop our analysis. Consequently, pivotal fourteen PCD genes, especially CAMP, CDK5R1, CTSW, DAPK2, GAB2, GAPDH, GATA2, HGF, MAPT, NAPSA, NUPR1, PIK3CG, PLA2G3, and SLC7A11, were utilized to establish the prognostic signature, namely cell death index (CDI). The validation in several external cohorts indicated that CDI can be regarded as a potential risk factor of LUAD patients. Combined with other common clinical information, a nomogram with potential predictive ability was constructed. Besides, according to the CDI signature, the tumor microenvironment (TME) and sensitivity to some potential chemotherapeutic drugs were further and deeply explored. Notably, verification and functional experiments further demonstrated the remarkable correlation between CDI and unfold protein response. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of LUAD patients.

Applications and emerging challenges of single-cell RNA sequencing technology in tumor drug discovery

Current therapeutic drugs are inadequate for curing tumors, highlighting the need for novel tumor drugs. The advancement of single-cell RNA sequencing (scRNA-seq) technology offers new opportunities for tumor drug discovery. This technology allows us to explore tumor heterogeneity and developmental mechanisms at the single-cell level. In this review, we outline the application of scRNA-seq in tumor drug discovery stages, including elucidating tumor mechanisms, identifying targets, screening drugs, and understanding drug action and resistance. We also discuss the challenges and future prospects of using scRNA-seq in drug development, providing a scientific foundation for advancing tumor therapies.

Progress in personalized immunotherapy for patients with brain metastasis

Brain metastasis leads to poor outcomes and CNS injury, significantly reducing quality of life and survival rates. Advances in understanding the tumor immune microenvironment have revealed the promise of immunotherapies, which, alongside surgery, chemotherapy, and radiation, offer improved survival for some patients. However, resistance to immunotherapy remains a critical challenge. This review explores the immune landscape of brain metastases, current therapies, clinical trials, and the need for personalized, biomarker-driven approaches to optimize outcomes.

Single-cell and spatial transcriptomics reveal a potential role of ATF3 in brain metastasis of lung adenocarcinoma

Background

Brain metastasis (BrM) has been a challenge for lung cancer treatment, but the mechanisms underlying lung cancer BrM remain elusive. This study aims to dissect cellular components and their spatial distribution in human BrM tumors of lung adenocarcinoma (LUAD) and identify potential therapeutic targets.

Methods

We performed single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on three LUAD BrMs, and validated our findings using public scRNA-seq data of 10 LUAD BrMs. Western blotting, quantitative real-time polymerase chain reaction (qRT-PCR) and functional experiments were employed for experimental studies.

Results

By combining scRNA-seq and ST, our analysis revealed the inter- and intra-tumoral heterogeneity of cellular components and their spatial localization within LUAD BrMs. Through RNA velocity and transcription factor (TF) regulatory activity analyses, we identified ATF3 as a potential regulator of the mesenchymal-epithelial transition (MET) program, which plays crucial roles in the colonization of tumor cells at metastatic sites. Furthermore, we demonstrated that knockdown of ATF3 significantly inhibited cancer cell proliferation while promoting cancer cell migration. Mechanistically, ATF3 knockdown could reverse the MET program. Additionally, we revealed that LGALS3/ANXA2-mediated cell-cell interaction between macrophage and tumor cells may also promote the MET program.

Conclusions

Our study provides a single-cell atlas of the cellular composition in BrM of LUAD and identifies ATF3 as a potential therapeutic target for BrM treatment.

TIMP1 Mediates Astrocyte-Dependent Local Immunosuppression in Brain Metastasis Acting on Infiltrating CD8+ T Cells

Immunotherapies against brain metastases have shown clinical benefits when applied to asymptomatic patients, but they are largely ineffective in symptomatic cases for unknown reasons. Here, we dissect the heterogeneity in metastasis-associated astrocytes using single-cell RNA sequencing and report a population that blocks the antitumoral activity of infiltrating T cells. This protumoral activity is mediated by the secretion of tissue inhibitor of metalloproteinase-1 (TIMP1) from a cluster of pSTAT3+ astrocytes that acts on CD63+ CD8+ T cells to modulate their function. Using genetic and pharmacologic approaches in mouse and human brain metastasis models, we demonstrate that combining immune checkpoint blockade antibodies with the inhibition of astrocyte-mediated local immunosuppression may benefit patients with symptomatic brain metastases. We further reveal that the presence of tissue inhibitor of metalloproteinase-1 in liquid biopsies provides a biomarker to select patients for this combined immunotherapy. Overall, our findings demonstrate an unexpected immunomodulatory role for astrocytes in brain metastases with clinical implications. Significance: This study presents a significant advancement in understanding immune modulation in brain tumors and offers new insights into the potential therapeutic interventions for brain metastases. See related commentary by Lorger and James, p. 11.

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients

With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high-throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi-omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.

Metastatic brain tumors: from development to cutting-edge treatment

Metastatic brain tumors, also called brain metastasis (BM), represent a challenging complication of advanced tumors. Tumors that commonly metastasize to the brain include lung cancer and breast cancer. In recent years, the prognosis for BM patients has improved, and significant advancements have been made in both clinical and preclinical research. This review focuses on BM originating from lung cancer and breast cancer. We briefly overview the history and epidemiology of BM, as well as the current diagnostic and treatment paradigms. Additionally, we summarize multiomics evidence on the mechanisms of tumor occurrence and development in the era of artificial intelligence and discuss the role of the tumor microenvironment. Preclinically, we introduce the establishment of BM models, detailed molecular mechanisms, and cutting-edge treatment methods. BM is primarily treated with a comprehensive approach, including local treatments such as surgery and radiotherapy. For lung cancer, targeted therapy and immunotherapy have shown efficacy, while in breast cancer, monoclonal antibodies, tyrosine kinase inhibitors, and antibody-drug conjugates are effective in BM. Multiomics approaches assist in clinical diagnosis and treatment, revealing the complex mechanisms of BM. Moreover, preclinical agents often need to cross the blood-brain barrier to achieve high intracranial concentrations, including small-molecule inhibitors, nanoparticles, and peptide drugs. Addressing BM is imperative.

Single-cell transcriptomic analysis of the senescent microenvironment in bone metastasis

Bone metastasis (BM) is a mortality-related event of late-stage cancer, with non-small cell lung cancer (NSCLC) being a common origin for BM. However, the detailed molecular profiling of the metastatic bone ecosystem is not fully understood, hindering the development of effective therapies for advanced patients. In this study, we examined the cellular heterogeneity between primary tumours and BM from tissues and peripheral blood by single-cell transcriptomic analysis, which was verified using multiplex immunofluorescence staining and public datasets. Our results demonstrate a senescent microenvironment in BM tissues of NSCLC. BM has a significantly higher infiltration of malignant cells with senescent characteristics relative to primary tumours, accompanied by aggravated metastatic properties. The endothelial-mesenchymal transition involved with SOX18 activation is related to the cellular senescence of vascular endothelial cells from BM. CD4Tstr cells, with pronounced stress and senescence states, are preferentially infiltrated in BM, indicating stress-related dysfunction contributing to the immunocompromised environment during tumour metastasis to bone. Moreover, we identify the SPP1 pathway-induced cellular crosstalk among T cells, vascular ECs and malignant cells in BM, which activates SOX18 and deteriorates patient survival. Our findings highlight the roles of cellular senescence in modulating the microenvironment of BM and implicate anti-senescence therapy for advanced NSCLC patients.

Spotlight on the treatment of non-small cell lung cancer with rare genetic alterations and brain metastasis: Current status and future perspectives

In patients with non-small cell lung cancer (NSCLC), oncogenic variants present in <5% of cases are considered rare, the predominant of which include human epidermal growth factor receptor 2 (HER2) mutations, mesenchymal-epithelial transition (MET) alterations, c-ros oncogene 1 (ROS1) rearrangements, rearrangement during transfection (RET) fusions, v-raf mouse sarcoma virus oncogene homolog B1 (BRAF) mutations, and neurotrophic troponin receptor kinase (NTRK) fusions. Brain metastases (BMs) occur in approximately 10%-50% of patients with NSCLC harboring rare genetic variants. The recent advent of small-molecule tyrosine kinase inhibitors and macromolecular antibody-drug conjugates (ADCs) has conferred marked survival benefits to patients with NSCLC harboring rare driver alterations. Despite effective brain lesion control for most targeted agents and promising reports of intracranial remission associated with novel ADCs, BM continues to be a major therapeutic challenge. This review discusses the recent advances in the treatment of NSCLC with rare genetic variants and BM, with a particular focus on intracranial efficacy, and explores future perspectives on how best to treat these patients.

Rebooting the Adaptive Immune Response in Immunotherapy-Resistant Lung Adenocarcinoma Using a Supramolecular Albumin

Despite the availability of immune checkpoint inhibitors (ICBs) significantly prolonging the life expectancy of some lung adenocarcinoma (LUAD) patients, their implementation and long-term effectiveness are hampered by the growing issue of acquired resistance. Herein, the bioinformatics analysis of immunotherapy-resistant LUAD patients and the system analysis of Anti-PD1-resistant mice models once again validate that the resistance-associated Wnt/β-catenin pathway offers a promising avenue for ICB sensitization. Consequently, a mild and convenient self-assembly between albumin and carnosic acid (CA), a Wnt inhibitor is employed, to develop a supramolecular albumin known as ABCA, serving as a reactivator for ICB. As anticipated, ABCA effectively suppress the Wnt/β-catenin cascade in vitro and leads to significant inhibition of cell proliferation while promoting apoptosis. Most notably, ABCA restores the anticancer efficacy of Anti-PD1 in immunotherapy-resistant LUAD orthotopic allografting mice models by reinvigorating the adaptive immune response mediated by T lymphocytes. Furthermore, ABCA exhibits minimal adverse effects during treatment and high-dose toxicity tests, underscoring its excellent potential for clinical translation. Collectively, the present work possesses the potential to provide innovative perspectives on the advancement of optimized immunotherapies targeting drug resistance, while also presenting a promising avenue for translating Wnt inhibitors into immunotherapeutic drugs for their clinical application.

Lnc-H19-derived protein shapes the immunosuppressive microenvironment of glioblastoma

The immunosuppressive tumor microenvironment (TME) is a prominent feature of glioblastoma (GBM), the most lethal primary brain cancer resistant to current immunotherapies. The mechanisms underlying GBM-TME remain to be explored. We report that long non-coding RNA (LncRNA) H19 encodes an immune-related protein called H19-IRP. Functionally separated from H19 RNA, H19-IRP promotes GBM immunosuppression by binding to the CCL2 and Galectin-9 promoters and activating their transcription, thereby recruiting myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs), leading to T cell exhaustion and an immunosuppressive GBM-TME. H19-IRP, overexpressed in clinical GBM samples, acts as a tumor-associated antigen (TAA) presented by major histocompatibility complex class I (MHC-I). A circular RNA vaccine targeting H19-IRP (circH19-vac) triggers a potent cytotoxic T cell response against GBM and inhibits GBM growth. Our results highlight the unrevealed function of H19-IRP in creating immunosuppressive GBM-TME by recruiting MDSCs and TAMs, supporting the idea of targeting H19-IRP with cancer vaccine for GBM treatment.

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 RNA sequencing and spatial transcriptome reveal potential molecular mechanisms of lung cancer brain metastasis

BACKGROUND

Lung cancer is a highly aggressive and prevalent disease worldwide. By the time it is first diagnosed, distant metastases have usually already occurred. Among them, the prognosis of patients with brain metastasis from lung cancer is very poor. Therefore, it is particularly important to identify the evolutionary status of tumor cells during lung cancer brain metastases and discover the underlying mechanisms of lung cancer brain metastases.

METHODS

In this study, we analysed three types of data: single-cell RNA sequencing, bulk RNA sequencing, and spatial transcriptome. Firstly, we identified early metastatic epithelial cell clusters (EMEC) using CNV and trajectory analysis in scRNA-seq data. Secondly, we integrated scRNA-seq and spatial transcriptome data with the help of MIA (Multimodal intersection analysis) to explore the biological characteristics of EMEC. Finally, we used bulk RNA-seq data to validate the molecular characteristics of EMEC.

RESULT

A total of 55,763 single cells were obtained and divided into 9 cell types. In brain metastasis, we found a significantly higher proportion of epithelial cells. In addition, we identified a specific subpopulation of epithelial cells, which was named as "early metastatic epithelial cell clusters (EMEC)". It is enriched in oxidative phosphorylation, coagulation, complement. Moreover, we also found that EMEC underwent cellular communication with other immune cells through ligand-receptor pairs such as MIF-(CD74 + CXCR4) and MIF-(CD74 + CD44). Next, we validated that EMEC were associated with poor clinical prognosis using three independent external datasets. Finally, spatial transcriptome analysis revealed specificity in the spatial distribution of EMEC, which shifted from the peripheral regions to the central regions of the tumour as the depth of tumor invasion progressed.

CONCLUSION

This study reveals the potential molecular mechanisms of lung cancer brain metastasis from both single-cell and spatial transcriptomic perspectives, providing biological insights and clinical reference value for detecting patients suffering from lung cancer brain metastasis.

Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning

The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.

Deciphering Dormant Cells of Lung Adenocarcinoma: Prognostic Insights from O-glycosylation-Related Tumor Dormancy Genes Using Machine Learning

Lung adenocarcinoma (LUAD) poses significant challenges due to its complex biological characteristics and high recurrence rate. The high recurrence rate of LUAD is closely associated with cellular dormancy, which enhances resistance to chemotherapy and evasion of immune cell destruction. Using single-cell RNA sequencing (scRNA-seq) data from LUAD patients, we categorized the cells into two subclusters: dormant and active cells. Utilizing high-density Weighted Gene Co-expression Network Analysis (hdWGCNA) and pseudo-time cell trajectory, aberrant expression of genes involved in protein O-glycosylation was detected in dormant cells, suggesting a crucial role for O-glycosylation in maintaining the dormant state. Intercellular communication analysis highlighted the interaction between fibroblasts and dormant cells, where the Insulin-like Growth Factor (IGF) signaling pathway regulated by O-glycosylation was crucial. By employing Gene Set Variation Analysis (GSVA) and machine learning, a risk score model was developed using hub genes, which showed high accuracy in determining LUAD prognosis. The model also demonstrated robust performance on the training dataset and excellent predictive capability, providing a reliable basis for predicting patient clinical outcomes. The group with a higher risk score exhibited a propensity for adverse outcomes in the tumor microenvironment (TME) and tumor mutational burden (TMB). Additionally, the 50% inhibitory concentration (IC50) values for chemotherapy exhibited significant variations among the different risk groups. In vitro experiments demonstrated that EFNB2, PTTG1IP, and TNFRSF11A were upregulated in dormant tumor cells, which also contributed greatly to the diagnosis of LUAD. In conclusion, this study highlighted the crucial role of O-glycosylation in the dormancy state of LUAD tumors and developed a predictive model for the prognosis of LUAD patients.

Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning

The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently available methods and biomarkers in predicting the response of immunotherapy and prognosis of CM is limited. Programmed cell death (PCD) plays a significant role in the occurrence, development, and therapy of various malignant tumors. In this research, we integrated fourteen types of PCD, multi-omics data from TCGA-SKCM and other cohorts in GEO, and clinical CM patients to develop our analysis. Based on significant PCD patterns, two PCD-related CM clusters with different prognosis, tumor microenvironment (TME), and response to immunotherapy were identified. Subsequently, seven PCD-related features, especially CD28, CYP1B1, JAK3, LAMP3, SFN, STAT4, and TRAF1, were utilized to establish the prognostic signature, namely cell death index (CDI). CDI accurately predicted the response to immunotherapy in both CM and other cancers. A nomogram with potential superior predictive ability was constructed, and potential drugs targeting CM patients with specific CDI have also been identified. Given all the above, a novel CDI gene signature was indicated to predict the prognosis and exploit precision therapeutic strategies of CM patients, providing unique opportunities for clinical intelligence and new management methods for the therapy of CM.

Single-cell analyzing of tumor microenvironment and cell adhesion between early and late-stage lung cancer

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that threaten human life with serious incidence and high mortality. High heterogeneity of tumor microenvironment (TME) was reported in multiple studies. However, the factor of controlling the tumor migration progression between eary and late-stage LUAD is still not fully understood. In this study, we conducted a comprehensive analysis of single-cell RNA sequencing (scRNA-seq) data of LUAD obtained from the GEO database. The identification of cell clusters revealed significant expansion of epithelial cells in late-stage patients. Interpretation of the cell-cell communication results between early-stage and late-stage patient samples indicated that early tumor cells may interact with epithelial cells through the TGF-β pathway to promote tumor progression. The cell cycle analysis demonstrated a significant increase in the number of cells in the G2 and M phases in late-stage lung cancer. Further analysis using Non-negative Matrix Factorization (NMF) revealed early-stage cell-specific gene features involved in cell adhesion-related biological processes. Among these, the Tensin (TNS) gene family, particularly TNS1, showed high expression in epithelial cells and fibroblasts of early-stage samples, specifically associated with cell adhesion. Survival analysis using TCGA database for LUAD demonstrated that patients with high expression of TNS1 exhibited significantly higher overall survival rates compared to those with low expression. Immunofluorescence experiments have demonstrated co-expression of TNS1 with fibroblast and tumor cell markers (α-SMA and EPCAM). Immunohistochemistry experiments further validated the significantly higher expression levels of TNS1 in early-stage LUAD tissues compared to late-stage lung cancer tissues (P<0.05). Pathway experiments have shown that early-stage tumor patients with high expression of TNS1 exhibit stronger phosphorylation levels of Akt and mTOR, indicating a more potent activation of the Akt/mTOR signaling pathway. In conclusion, the results of this study demonstrate that TNS1 is an adhesive molecule in the immune microenvironment of early-stage tumor cells, and it may serve as a novel prognostic marker for lug cancer.

[Advancements in Single-cell RNA Sequencing Technology in the Study of the Tumor Microenvironment in Lung Cancer]

The immune microenvironment plays a key role in the development and progression of tumors. In recent years, with the rapid advancement of high-throughput sequencing technologies, researchers have gained a deeper understanding of the composition and function of immune cells in the tumor microenvironment. However, traditional bulk sequencing technologies are limited in resolving heterogeneity at the single-cell level, constraining a comprehensive understanding of the complexity of the tumor microenvironment. The advent of single-cell RNA sequencing technology has brought new opportunities to uncover the heterogeneity of the immune microenvironment in lung cancer. Currently, T-cell-centered immunotherapy in clinical settings is prone to side effects affecting prognosis, such as immunogenic drug resistance or immune-related pneumonia, with the key factor being changes in the interactions between immune cells and tumor cells in the tumor microenvironment. Single-cell RNA sequencing technology can reveal the origins and functions of different subgroups within the tumor microenvironment from perspectives such as intercellular interactions and pseudotime analysis, thereby discovering new cell subgroups or novel biomarkers, providing new avenues for uncovering resistance to immunotherapy and monitoring therapeutic efficacy. This review comprehensively discusses the newest research techniques and advancements in single-cell RNA sequencing technology for unveiling the heterogeneity of the tumor microenvironment after lung cancer immunotherapy, offering insights for enhancing the precision and personalization of immunotherapy.
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HIF2A mediates lineage transition to aggressive phenotype of cancer-associated fibroblasts in lung cancer brain metastasis

Brain metastasis is the most devasting form of lung cancer. Recent studies highlight significant differences in the tumor microenvironment (TME) between lung cancer brain metastasis (LCBM) and primary lung cancer, which contribute significantly to tumor progression and drug resistance. Cancer-associated fibroblasts (CAFs) are the major component of pro-tumor TME with high plasticity. However, the lineage composition and function of CAFs in LCBM remain elusive. By reanalyzing single-cell RNA sequencing (scRNA-seq) data (GSE131907) from lung cancer patients with different stages of metastasis comprising primary lesions and brain metastasis, we found that CAFs undergo distinctive lineage transition during LCBM under a hypoxic situation, which is directly driven by hypoxia-induced HIF-2α activation. Transited CAFs enhance angiogenesis through VEGF pathways, trigger metabolic reprogramming, and promote the growth of tumor cells. Bulk RNA sequencing data was utilized as validation cohorts. Multiplex immunohistochemistry (mIHC) assay was performed on four paired samples of brain metastasis and their primary lung cancer counterparts to validate the findings. Our study revealed a novel mechanism of lung cancer brain metastasis featuring HIF-2α-induced lineage transition and functional alteration of CAFs, which offers potential therapeutic targets.

Comprehensive Analysis of Lung Adenocarcinoma and Brain Metastasis through Integrated Single-Cell Transcriptomics

Lung adenocarcinoma (LUAD) is a highly prevalent and lethal form of lung cancer, comprising approximately half of all cases. It is often diagnosed at advanced stages with brain metastasis (BM), resulting in high mortality rates. Current BM management involves complex interventions and conventional therapies that offer limited survival benefits with neurotoxic side effects. The tumor microenvironment (TME) is a complex system where cancer cells interact with various elements, significantly influencing tumor behavior. Immunotherapies, particularly immune checkpoint inhibitors, target the TME for cancer treatment. Despite their effectiveness, it is crucial to understand metastatic lung cancer and the specific characteristics of the TME, including cell-cell communication mechanisms, to refine treatments. Herein, we investigated the tumor microenvironment of brain metastasis from lung adenocarcinoma (LUAD-BM) and primary tumors across various stages (I, II, III, and IV) using single-cell RNA sequencing (scRNA-seq) from publicly available datasets. Our analysis included exploring the immune and non-immune cell composition and the expression profiles and functions of cell type-specific genes, and investigating the interactions between different cells within the TME. Our results showed that T cells constitute the majority of immune cells present in primary tumors, whereas microglia represent the most dominant immune cell type in BM. Interestingly, microglia exhibit a significant increase in the COX pathway. Moreover, we have shown that microglia primarily interact with oligodendrocytes and endothelial cells. One significant interaction was identified between DLL4 and NOTCH4, which demonstrated a relevant association between endothelial cells and microglia and between microglia and oligodendrocytes. Finally, we observed that several genes within the HLA complex are suppressed in BM tissue. Our study reveals the complex molecular and cellular dynamics of BM-LUAD, providing a path for improved patient outcomes with personalized treatments and immunotherapies.

Single-cell RNA sequencing reveals epithelial cells driving brain metastasis in lung adenocarcinoma

Brain metastases (BM) of lung adenocarcinoma (LUAD) are the most common intracranial malignancy leading to death. However, the cellular origins and drivers of BM from LUAD have not been clarified. Cellular composition was characterized by single-cell sequencing analysis of primary lung adenocarcinoma (pLUAD), BM and lymph node metastasis (LNM) samples in GSE131907. Our study briefly analyzed the tumor microenvironment (TME), focusing on the role of epithelial cells (ECs) in BM. We have discovered a population of brain metastasis-associated epithelial cells (BMAECs) expressing SPP1, SAA1, and CDKN2A, and it has been observed that this population is mainly composed of aneuploid cells from pLUAD, playing a crucial role in brain metastasis. Our study concluded that both LNM and BM in LUAD originated from pLUAD lesions, but there is currently insufficient evidence to prove a direct association between BM lesions and LNM lesions, which provides inspiration for further investigation of the TME in BM.

Bulk RNA-seq and scRNA-seq reveal SLC7A11, a key regulatory molecule of ferroptosis, is a prognostic-related biomarker and highly related to the immune system in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common pathological subtype of lung cancer. Ferroptosis is an iron-dependent, non-apoptotic cell death mode, highly correlated with the tumorigenesis and progression of multiple cancers. Solute carrier family 7 member 11 (SLC7A11) maintains the anti-porter activity of cysteine and glutamate to regulate ferroptosis. We collected bulk RNA-seq and scRNA-seq from The Cancer Genome Altas and Gene Expression Omnibus databases. Then, we extracted the expression level of SLC7A11 to perform the differential expression analysis between normal tissues and LUAD tissues. Then, we applied survival, univariate, and multivariate Cox regression analyses to investigate the predictive value of SLC7A11 in LUAD. Gene set enrichment analysis was used to explore the underlying molecular mechanisms of SLC7A11 in LUAD. Finally, we analyzed the relationship of SLC7A11 to the immune status and the curative effect of immunotherapy. The expression level of SLC7A11 in LUAD tissues was markedly increased. The survival analysis, univariate and multivariate Cox regression analysis showed that SLC7A11 was a negative factor for the prognosis of LUAD patients. Gene set enrichment analysis revealed that several immune-related pathways were enriched in the low-level group. The lower SLC7A11 level has a better therapeutic effect of immunotherapy and less probability of immune escape and dysfunction. SLC7A11 was a prognostic-related biomarker and closely correlated with the immune status and therapeutic effect of immunotherapy in LUAD, which could be an effective biomarker for evaluating the prognosis and the therapeutic efficacy of immunotherapy.

Insight into the Progress in CAR-T Cell Therapy and Combination with Other Therapies for Glioblastoma

Glioblastoma (GBM) is the most common malignant primary brain cancer in adults. It is always resistant to existing treatments, including surgical resection, postoperative radiotherapy, and chemotherapy, which leads to a dismal prognosis and a high relapse rate. Therefore, novel curative therapies are urgently needed for GBM. Chimeric antigen receptor T (CAR-T) cell therapy has significantly improved life expectancy for hematological malignancies patients, and thus it increases the interest in applying CAR-T cell therapy for solid tumors. In the recently published research, it is indicated that there are numerous obstacles to achieve clinical benefits for solid tumors, especially for GBM, because of GBM anatomical characteristics (the blood-brain barrier and suppressive tumor microenvironment) and the tumor heterogeneity. CAR-T cells are difficult to penetrate blood-brain barrier, and immunosuppressive tumor microenvironment (TME), which induces CAR-T cell exhaustion, impairs CAR-T cell therapy response. Moreover, under the pressure of CAR-T cell therapy, the tumor heterogeneity and tumor plasticity drive tumor evolution and therapy resistance, such as antigen escape. Nonetheless, scientists strive for strategies to overcome these hurdles, including novel CAR-T cell designs and regional delivery. For instance, the structure of multi-antigen-targeted CAR-T cells can enrich CAR-T accumulation in tumor TME and eliminate abundant tumor cells to avoid tumor antigen heterogeneity. Additionally, paired with an immune modifier and one or more stimulating domains, different generation of innovations in the structure and manufacturing of CAR-T cells have improved efficacy and persistence. While single CAR-T cell therapy receives limited clinical survival benefit. Compared with single CAR-T cell therapy, the combination therapies have supplemented the treatment paradigm. Combinatorial treatment methods consolidate the CAR-T cells efficacy by regulating the tumor microenvironment, optimizing the CAR structure, targeting the CAR-T cells to the tumor cells, reversing the tumor-immune escape mechanisms, and represent a promising avenue against GBM, based on multiple impressive research. Moreover, exciting results are also reported to be realized through combining effective therapies with CAR-T cells in preclinical and clinical trials samples, have aroused inspiration to explore the antitumor function of combination therapies. In summary, this study aims to summarize the limitation of CAR-T cell therapies and introduces novel strategies to enhance CAR-T cell function as well as prospect the potential of the therapeutic combination.

A case of discordant histology and expression of programmed death ligand 1 between primary tumor and brain metastases in adenosquamous carcinoma of the lung

A patient presented with vomiting and gait disturbance. Investigation revealed a single cerebellar tumor and another tumor in the upper lobe of the left lung. Based on the severe vomiting and gait disturbance, we removed the cerebellar tumor first, achieving resolution of symptoms. The cerebellar tumor was pathologically diagnosed as metastatic lung adenocarcinoma. No other metastases were identified, including in the mediastinal lymph nodes. We therefore resected the primary lung tumor. On final pathological analysis, the tumor in the upper lobe of the left lung was diagnosed as adenosquamous carcinoma with no lymph node metastasis. PD-L1 expression was low in the primary lung adenosquamous carcinoma and high in the cerebellar metastasis. Furthermore, both tumors were KRASG12C -positive. Tumor PD-L1 expression is considered important for immune escape. In this case, adenocarcinoma cells in the primary adenosquamous carcinoma may have migrated to form a cerebellar metastasis. In advanced lung cancer, tumor growth may be observed in some lesions even when many other lesions are controlled by chemo- or immunotherapy. Biopsy to confirm histology and PD-L1 expression is worth considering, depending on the location of the metastases and the invasiveness of the biopsy procedure.

The expression and prognostic value of disulfidptosis progress in lung adenocarcinoma

Disulfidptosis is a new cell death model caused by accumulating intracellular disulfides bonding to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic value of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD). The data of expression profiles and scRNA-seq were collected from TCGA and GEO databases. The different expressions of DRGs between normal and LUAD tissues were compared. The LASSO analysis and multivariate Cox regression analysis were utilized to develop a DRGs model for the prognosis evaluation in LUAD. The model's predictive accuracy was evaluated with the area under the receiver operating characteristic curve (AUC) and C-index. Survival analysis, univariate and multivariate Cox regression analysis were used to assessing the predictive value of the DRGs model. ScRNA-seq data were analyzed with "Seurat" and "Monocle 2" packages. There were significant differences in 22 DRGs between normal and tumor tissues. A model with five DRGs (ACTB, FLNB, NCKAP1, SLC3A2, SLC7A11) was constructed. The AUC and C-index of the model were significantly higher than that based on clinical parameters. Survival analysis, univariate and multivariate Cox regression analysis demonstrated risk score was an independent prognostic predictor. In the scRNA-seq study, we identified 14 clusters and 11 cell types. Clusters 2, 8, and 13 were annotated into Epithelial cells. SLC7A11 and SLC3A2, NCKAP1 and FLNB, ACTB expressed most abundantly in Epithelial cells, Endothelial cells, Naive CD4 T, respectively. We explored the expression of DRGs in LUAD and constructed a predictive DRGs model, which was stable and reliable for predicting LUAD prognosis.