The heterogeneous immune landscape between lung adenocarcinoma and squamous carcinoma revealed by single-cell RNA sequencing

Mapping the rapid growth of multi-omics in tumor immunotherapy: Bibliometric evidence of technology convergence and paradigm shifts

This study aims to fill the knowledge gap in systematically mapping the evolution of omics-driven tumor immunotherapy research through a bibliometric lens. While omics technologies (genomics, transcriptomics, proteomics, metabolomics)provide multidimensional molecular profiling, their synergistic potential with immunotherapy remains underexplored in large-scale trend analyses. A comprehensive search was conducted using the Web of Science Core Collection for literature related to omics in tumor immunotherapy, up to August 2024. Bibliometric analyses, conducted using R version 4.3.3, VOSviewer 1.6.20, and Citespace 6.2, examined publication trends, country and institutional contributions, journal distributions, keyword co-occurrence, and citation bursts. This analysis of 9,494 publications demonstrates rapid growth in omics-driven tumor immunotherapy research since 2019, with China leading in output (63% of articles) yet exhibiting limited multinational collaboration (7.9% vs. the UK's 61.8%). Keyword co-occurrence and citation burst analyses reveal evolving frontiers: early emphasis on "PD-1/CTLA-4 blockade" has transitioned toward "machine learning," "multi-omics," and "lncRNA," reflecting a shift to predictive modeling and biomarker discovery. Multi-omics integration has facilitated the development of immune infiltration-based prognostic models, such as TIME subtypes, which have been validated across multiple tumor types, which inform clinical trial design (e.g. NCT06833723). Additionally, proteomic analysis of melanoma patients suggests that metabolic biomarkers, particularly oxidative phosphorylation and lipid metabolism, may stratify responders to PD-1 blockade therapy. Moreover, spatial omics has confirmed ENPP1 as a potential novel therapeutic target in Ewing sarcoma. Citation trends underscore clinical translation, particularly mutation-guided therapies. Omics technologies are transforming tumor immunotherapy by enhancing biomarker discovery and improving therapeutic predictions. Future advancements will necessitate longitudinal omics monitoring, AI-driven multi-omics integration, and international collaboration to accelerate clinical translation. This study presents a systematic framework for exploring emerging research frontiers and offers insights for optimizing precision-driven immunotherapy.

The cancer stem cells characteristics analysis of LGR5 + cells that influence lung cancer risk by using single cell RNA-seq analysis

Lung adenocarcinoma (LUAD) is the most popular lung cancer type with highly mortality. We performed a single cell RNA-seq analysis to explore characteristic of cancer stem cells in LUAD. We downloaded the single cell RNA-seq data (GSE149655) from the GEO database, the scRNA-seq analysis was performed by using the "Seurat" and "harmony" R package. The FindMarkers function and "ClusterProlifer" package was used for differentially expressed genes (DEGs) and function enrichment analysis. The protein-protein interaction and transcriptional regulatory network were performed by STRING and ChIPBase database. Immunohistochemistry tests to be used to observe differences in the expression of specific genes in LUAD and paracancerous tissue samples. BEAS-2B and A549 cells was used for vitro assay and the qRT-PCR, western blotting, wound healing, trans-well assays, EdU tests, and flow cytometry were performed. A total of 9 cell clusters were obtained after scRNA-seq analysis, in which the cancer stem cells had higher proportion in LUAD samples. Subsequently, function enrichment analysis revealed that the amino sugar and nucleotide sugar metabolism and DNA replication pathways were activated in cancer stem cells (CSCs), which were further sub-divided into 3 subtypes, the LGR5 + stem cell is a major contributor to cancer progression, its hub genes, such as HLA-DPB1, CD74, CTSH and HLA-DRB5 mediated the unique transcriptional state. In addition, the marker genes of three CSCs were also overexpressed in LUAD cells and the CXCL3 played an important role in mediating cell proliferation, apoptosis, migration and invasion of tumor. We performed a scRNA-seq analysis and identified the LGR5 + stem cell as a major contributor in LUAD progression, our findings are expected to provide new insights into the pathogenesis of LUAD.

Macrophage-derived exosomes in cancer: a double-edged sword with therapeutic potential

Solid cancer contains a complicated communication network between cancer cells and components in the tumor microenvironment (TME), significantly influencing the progression of cancer. Exosomes function as key carriers of signaling molecules in these communications, including the intricate signalings of tumor-associated macrophages (TAMs) on cancer cells and the TME. With their natural lipid bilayer structures and biological activity that relates to their original cell, exosomes have emerged as efficient carriers in studies on cancer therapy. Intrigued by the heterogeneity and plasticity of both macrophages and exosomes, we regard macrophage-derived exosomes in cancer as a double-edged sword. For instance, TAM-derived exosomes, educated by the TME, can promote resistance to cancer therapies, while macrophage-derived exosomes generated in vitro have shown favorable potential in cancer therapy. Here, we depict the reasons for the heterogeneity of TAM-derived exosomes, as well as the manifold roles of TAM-derived exosomes in cancer progression, metastasis, and resistance to cancer therapy. In particular, we emphasize the recent advancements of modified macrophage-derived exosomes in diverse cancer therapies, arguing that these modified exosomes are endowed with unique advantages by their macrophage origin. We outline the challenges in translating these scientific discoveries into clinical cancer therapy, aiming to provide patients with safe and effective treatments.

Tumor microenvironment-driven resistance to immunotherapy in non-small cell lung cancer: strategies for Cold-to-Hot tumor transformation

Non-small cell lung cancer (NSCLC) represents a formidable challenge in oncology due to its molecular heterogeneity and the dynamic suppressive nature of its tumor microenvironment (TME). Despite the transformative impact of immune checkpoint inhibitors (ICIs) on cancer therapy, the majority of NSCLC patients experience resistance, necessitating novel approaches to overcome immune evasion. This review highlights shared and subtype-specific mechanisms of immune resistance within the TME, including metabolic reprogramming, immune cell dysfunction, and physical barriers. Beyond well-characterized components such as regulatory T cells, tumor-associated macrophages, and myeloid-derived suppressor cells, emerging players - neutrophil extracellular traps, tertiary lymphoid structures, and exosomal signaling networks - underscore the TME's complexity and adaptability. A multi-dimensional framework is proposed to transform cold, immune-excluded tumors into hot, immune-reactive ones. Key strategies include enhancing immune infiltration, modulating immunosuppressive networks, and activating dormant immune pathways. Cutting-edge technologies, such as single-cell sequencing, spatial transcriptomics, and nanomedicine, are identified as pivotal tools for decoding TME heterogeneity and personalizing therapeutic interventions. By bridging mechanistic insights with translational innovations, this review advocates for integrative approaches that combine ICIs with metabolic modulators, vascular normalizers, and emerging therapies such as STING agonists and tumor vaccines. The synergistic potential of these strategies is poised to overcome resistance and achieve durable antitumor immunity. Ultimately, this vision underscores the importance of interdisciplinary collaboration and real-time TME profiling in refining precision oncology for NSCLC, offering a blueprint for extending these advances to other malignancies.

Single-cell and spatial transcriptomic analyses revealing tumor microenvironment remodeling after neoadjuvant chemoimmunotherapy in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) represents the most common pathological type of lung cancer, and the combination of neoadjuvant immunotherapy with chemotherapy has emerged as the first-line treatment for NSCLC. Nevertheless, the efficacy of this therapeutic approach remains variable. The present study aims to examine the impact of chemoimmunotherapy in NSCLC patients, with a view to identifying key molecules, critical cell subpopulations, communication patterns and spatial distributions that potentially correlate with therapeutic sensitivity. A total of 16 lung cancer tissue samples were collected from a cohort of 12 NSCLC patients and subjected to single-cell RNA and spatial transcriptome sequencing. Our data demonstrated that the distribution of CD4 + Treg T cells and mCAFs indicated an immunosuppressive tumor microenvironment, while the accumulation of CD4 + Th17 T cells and iCAFs could act as a positive marker for the sensitivity to chemoimmunotherapy. Furthermore, a significant high level of SELENOP-macrophages was observed in tissues from positive responders, and a strong co-localization between SELENOP-macrophages and antigen-presenting cancer associated fibroblasts (CAFs) in the tumor boundaries was identified, indicating the cooperative roles of these two cell types in response to combined therapy. Moreover, SELENOP-macrophages were observed to be accumulated in tertiary lymphoid structures, which further suggested its critical role in recruiting lymphocytes. Furthermore, analysis of cell-cell communication, based on spatial transcriptomics, suggests that the interactions between SELENOP-macrophages, apCAFs, CD4 + and CD8 + T cells were significantly enhanced in responders. In addition, SELENOP-macrophages recruited CD4 + Naïve, Helper and CD8 + Naïve T cells through pathways such as the cholesterol, interleukin, chemokine and HLA when responding to combined therapy. The present study further unveils the dynamic spatial and transcriptional changes in the tumor microenvironment of non-small cell lung cancer in response to combination therapy.

Molecular signatures bidirectionally link myocardial infarction and lung cancer

Myocardial Infarction (MI) and lung cancers are major contributors to mortality worldwide. While seemingly diverse, the two share common risk factors, such as smoking and hypertension. There is a pressing need to identify bidirectional molecular signatures that link MI and lung cancer, in order to improve clinical outcomes for patients. In this study, we identified common differentially expressed genes between MI and lung cancer. Specifically, we identified 1,496 upregulated and 1,482 downregulated genes in the MI datasets. By focusing on the 1,000 most upregulated and downregulated genes in Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC), we identified 35 genes that are common across MI, LUAD, and LUSC. Functional enrichment analysis revealed shared biological processes, such as "inflammatory response" and "cell differentiation." The Cox proportional hazards model demonstrated a significant association between the shared genes and overall survival in lung cancer patients, as well as with smoking history in these patients. In addition, a machine learning model based on the expression of the shared genes distinguished MI patients from controls, achieving an AUROC of 0.72 and an AUPRC of 0.86. Finally, based on drug repurposing analysis, we proposed FDA-approved drugs potentially targeting the upregulated genes as novel therapeutic options for the co-occurring conditions of MI and lung cancer. Overall, our findings highlight the similarities in molecular makeup between lung cancer and MI.

Effects of circulating RNAs on tumor metabolism in lung cancer (Review)

During the development and progression of lung cancer, cell metabolism function is altered. Thus, cells rely on aerobic glycolysis and abnormal lipid and amino acid metabolism to obtain energy and nutrients for growth, proliferation and drug resistance. Circular RNAs (circRNAs), a class of non-coding RNAs, serve important biological roles in the growth and development of tumors. Functionally, circRNAs act as molecular sponges that absorb microRNAs (miRNAs) and RNA-binding proteins and as protein scaffolds that regulate gene transcription and translation through the maintenance of mRNA stability. In addition, circRNAs are important regulators of tumor metabolism and promote tumor progression through mediating tumor cell proliferation, metastasis and the induction of chemoresistance. Results of previous studies reveal that circRNAs may serve a key role in regulating tumor metabolic processes in lung cancer, through miRNA sponging and alternative mechanisms. Thus, circRNAs demonstrate potential as therapeutic targets for lung cancer. The present study aimed to review the effects of circRNAs on lung cancer cell metabolism and provide novel insights into the clinical treatment of lung cancer. The present review may also provide a novel theoretical basis for the development of lung cancer drug targets.

A novel tumor-associated macrophage risk signature predicts prognosis and immunotherapy response in lung adenocarcinoma

OBJECTIVE

To systematically characterize tumor-associated macrophage (TAM) subsets in lung adenocarcinoma (LUAD) and establish a TAM-based prognostic risk signature for LUAD patients.

METHODS

Single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data were integrated to identify TAM subsets linked to LUAD prognosis. Prognostic genes were screened using univariate Cox regression, refined via Least Absolute Shrinkage and Selection Operator (LASSO) regression, and used to construct a 10-gene risk signature. The signature's performance was validated in independent cohorts through receiver operating characteristic curves, Kaplan-Meier survival analysis, and a nomogram. Its predictive ability for immune checkpoint inhibitor (ICI) therapy response was assessed in the IMvigor210 and GSE78220 datasets.

RESULTS

Six distinct TAM subpopulations were identified, with two subsets significantly correlated with poor prognosis. The 10-gene risk signature, derived from TAM-related genes, demonstrated strong prognostic performance in both training and validation cohorts. High-risk patients exhibited markedly worse overall survival compared to low-risk patients. Additionally, the signature effectively stratified patients based on their response to anti-PD-L1 therapy, with high-risk patients exhibiting reduced clinical benefit. A nomogram combining the risk signature with clinicopathological parameters further enhanced survival prediction accuracy, supporting its clinical applicability.

CONCLUSION

This study established a novel TAM-based prognostic risk signature with robust predictive power for both survival outcomes and immunotherapy response in LUAD. These findings enhance our understanding of TAMs' clinical significance and provide a foundation for personalized immunotherapy strategies in LUAD.

Single cell transcriptomic analysis reveals tumor immune infiltration by macrophage cells gene signature in lung adenocarcinoma

BACKGROUND

Tumor-associated macrophages (TAMs) play pivotal roles in innate immunity and contribute to the advancement of lung cancer. We aimed to identify novel TAM-related biomarkers and significance of macrophage infiltration in lung adenocarcinoma (LUAD) through an integrative analysis of single-cell RNA-sequencing (scRNA-seq) data. To describe the cell atlas and construct a novel prognostic signature in LUAD.

METHODS

The gene signature linked to TAMs was identified utilizing Scanpy from the scRNA-seq dataset GSE131907. Subsequent analysis involved evaluating the expression levels of these genes, their potential molecular mechanisms, and prognostic significance in LUAD using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We also constructed a risk score models through LASSO Cox regression for these genes. The underlying mechanism was further elucidated through the application of GSEA, ESTIMATE, TIDE, and other bioinformatic algorithms.

RESULTS

Single-cell atlas was described by analyze 29 scRNA-seq samples from 19 LUAD patients. The TAMs-related gene signature (TGS) was identified as an independent prognostic factor by LASSO Cox regression analysis using differential expression genes (DEGs) derived from pro- and anti-inflammatory macrophage cells. Risk score model including nine TAMs-related genes (FOSL1, ZNF697, ADM, UBE2S, TICAM1, S100P, BIRC3, TLE1, and DEFB1) were obtained for prognosis construction. Moreover, the risk model underwent additional validation in four external GEO cohorts: GSE31210, GSE72094, GSE26939, and GSE30219. Interestingly, TGS-high tumors revealed enrichments in TGF-β signaling and hypoxia pathways, which shown low immune infiltration and immunosuppression by ESTIMATE and TIDE algorithm. The TGS-high risk group exhibited lower richness and diversity in the T-cell receptor (TCR) repertoire.

CONCLUSION

This study introduces a novel TGS score developed through LASSO Cox regression analysis, utilizing DEGs in pro- and anti-inflammatory macrophage cells. High TGS tumors exhibited enrichment in TGF-β signaling and hypoxia pathways, suggesting their potential utility in predicting prognosis and immune responses in patients with LUAD. These results offer promising implications for the development of therapeutic strategies for LUAD.

Single-cell RNA sequencing in ovarian cancer: Current progress and future prospects

Ovarian cancer is one of the most prevalent gynaecological malignancies. The rapid development of single-cell RNA sequencing (scRNA-seq) has allowed scientists to use this technique to study ovarian cancer development, heterogeneity, and tumour environment. Although multiple original research articles have reported the use of scRNA-seq in understanding ovarian cancer and how therapy resistance occurs, there is a lack of a comprehensive review that could summarize the findings from multiple studies. Therefore, this review aimed to fill this gap by comparing and summarizing the results from different studies that have used scRNA-seq in understanding ovarian cancer development, heterogeneity, tumour microenvironment, and treatment resistance. This review will begin with an overview of scRNA-seq workflow, followed by a discussion of various applications of scRNA-seq in studying ovarian cancer. Next, the limitations and future directions of scRNA-seq in ovarian cancer research will be presented.

Differential expression of the MYC-Notch axis drives divergent responses to the front-line therapy in central and peripheral extensive-stage small-cell lung cancer

Central and peripheral extensive-stage small-cell lung cancer (ES-SCLC) are reported to be two distinct tumor entities, but their responses to the front-line therapies and underlying biological mechanisms remain elusive. In this study, we first compared the outcomes of central and peripheral ES-SCLC receiving front-line chemotherapy or chemo-immunotherapy with a cohort of 265 patients. Then we performed single-cell RNA sequencing (scRNA-seq) on nine treatment-naïve ES-SCLC samples to investigate potential mechanisms underlying the response differences. Under chemotherapy, the peripheral type had a lower objective response rate (44.8% vs. 71.2%, p = 0.008) and shorter progression-free survival (median 3.4 vs. 5.1 months, p = 0.001) than the central type. When comparing chemo-immunotherapy with chemotherapy, the peripheral type showed a greater potential to reduce progression (HR, 0.18 and 0.52, respectively) and death (HR, 0.44 and 0.91 respectively) risks than the central type. Concerning the scRNA-seq data, the peripheral type was associated with chemo-resistant and immune-responsive tumoral and microenvironmental features, including a higher expression level of MYC-Notch-non-neuroendocrine (MYC-Notch-non-NE) axis and a more potent antigen presentation and immune activation status. Our results revealed that central and peripheral ES-SCLC had distinct responses to front-line treatments, potentially due to differential activation statuses of the MYC-Notch-non-NE axis.

Unraveling immune heterogeneity across pan-cancer and deep insights in lung adenocarcinoma based on alternative splicing

Alternative splicing (AS) participates in tumor development and tumor microenvironment formation. However, the landscape of immune-infiltrating AS events in pan-cancer and mechanisms of AS in lung adenocarcinoma (LUAD) have not been comprehensively characterized. We systematically profiled the immune-infiltrating AS event landscape of pan-cancer using data from The Cancer Genome Atlas, analyzing both commonalities and specific characteristics among different cancer types. We found that AS events tend to occur specifically in one cancer type rather than in multiple cancer types. AS events were used to classify 512 LUAD samples into 2 subtypes by unsupervised clustering: the aberrant splicing subtype and the immune-infiltrating subtype. The 2 subtypes showed significant differences in clinicopathology, prognosis, transcriptomics, genomics, and immune microenvironment. We constructed a classification signature comprising 10 genes involved in 14 AS events using logistic regression. The robustness of the signature was validated in 3 independent datasets using survival analysis. To explore AS mechanisms in LUAD, we constructed subtype-specific coexpression networks using Pearson correlation analysis. AS event of AKT3 regulated by splicing factor ENOX1 was associated with poor prognosis in LUAD. Overall, we outline AS events associated with immune infiltration in pan-cancer, and this study provides insights into AS mechanisms in LUAD patient classification.

Bioinformatics Analysis of coagulation-related genes in lung adenocarcinoma: unveiling prognostic indicators and treatment pathways

Lung adenocarcinoma (LUAD) frequently precipitates a hypercoagulable state, resulting in venous thromboembolism and associated hemostatic complications. Furthermore, the coagulation cascade holds a pivotal role within the tumor microenvironment (TME) of LUAD. Utilizing unsupervised clustering of coagulation-related genes (CRG) and integrating clinical attributes, distinctions and correlations in clustering across various groups were assessed. Principal component analysis (PCA) was employed to derive the CRGscore for LUAD patients. Subsequently, a prognostic signature was established to contrast the impacts of immunological and pharmacological treatments across groups. The expression of PIK3CA, posited as a potential biomarker, was corroborated via immunohistochemistry(IHC) and Western blotting. This research delineated pronounced variances in immune signatures and prognostic categorizations among four coagulation-related subtypes, and delved into their associations with three gene cluster subtypes. A prognostic model based on coagulation-related scores was formulated for risk stratification and prognosis estimation. Disparities in immune infiltration, treatment modalities, and drug responsiveness among risk cohorts were discerned. Notably, an augmented expression of the coagulation-associated gene PIK3CA was observed in tumor samples. Coagulatory function is intimately linked with LUAD and its immune microenvironment, offering predictive potential for LUAD survival prognosis. Specifically, subgroups manifesting elevated PIK3CA expression might serve as foundational indicators for optimal treatment selection.

Spatially mapping the tumour immune microenvironments of non-small cell lung cancer

Lung cancer is the leading cause of cancer-related deaths. An enhanced understanding of the immune microenvironments within these tumours may foster more precise and efficient treatment, particularly for immune-targeted therapies. The spatial architectural differences between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are relatively unexplored. Here, we applied imaging mass cytometry to a balanced cohort of LUAD and LUSC patients, matched for clinical factors such as age, sex, and smoking history, to analyze 204 histopathology images of tumours from 102 individuals with non-small cell lung cancer (NSCLC). By analyzing interactions and broader cellular networks, we interrogate the tumour microenvironment to understand how immune cells are spatially organized in clinically matched adenocarcinoma and squamous cell carcinoma subsets. This spatial analysis revealed distinct patterns of immune cell aggregation, particularly among macrophage populations, that correlated with patient prognosis differentially in adenocarcinoma and squamous cell carcinoma, suggesting potential new strategies for therapeutic intervention. Our findings underscore the importance of analyzing NSCLC histological subtypes separately when investigating the spatial immune landscape, as microenvironmental characteristics and cellular interactions differed by subtype. Recognizing these distinctions is essential for designing precision therapies tailored to each subtype's unique immune architecture, ultimately enhancing patient outcomes.

Deregulated methylation and expression of PCDHGB7 in patients with non-small cell lung cancer: a novel prognostic and immunological biomarker

Backgrounds

Protocadherin gamma subfamily B, 7 (PCDHGB7), a member of the protocadherin family, plays critical roles in neuronal connections and has been implicated in female reproductive system cancers. Its function in lung cancer has not been elucidated.

Methods

We comprehensively investigated PCDHGB7 expression, prognosis, biological function, methylation patterns, and it's relationship with immune infiltration and immunotherapy response through public datasets (HPA, TCGA, GEO, OncoDB and MEXPRESS). Two lung cancer immunotherapy cohorts from our clinical center were enrolled to detect the relationship between methylation and protein levels of PCDHGB7 in plasma and immunotherapy outcomes.

Results

PCDHGB7 expression was downregulated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) and associated with tumor prognosis. PCDHGB7 demonstrated a positive correlation with inhibitory immune cells and a negative correlation with tumor mutational burden (TMB) and homologous recombination deficiency (HRD). The methylation level of PCDHGB7 was upregulated in tumor tissue and negatively correlated with PCDHGB7 mRNA level. In immunotherapy cohort studies, patients with higher PCDHGB7 tissue expression showed worse prognosis. Patients with PCDHGB7 hypermethylation in baseline plasma had shorter progression-free survival (PFS) and overall survival (OS), while those with early reduction of PCDHGB7 methylation had the best prognosis. Plasma PCDHGB7 protein levels could predict responses to immune checkpoint inhibitors and function as a prognostic marker for PFS.

Conclusion

PCDHGB7 expression and methylation are prognostic and immunological biomarkers in non-small cell lung cancer. Plasma PCDHGB7 methylation and protein levels can be used as novel biomarkers for predicting the efficacy of immunotherapy in lung cancer.

Dissecting macrophage heterogeneity and kaempferol in lung adenocarcinoma: a single-cell transcriptomic approach and network pharmacology

BACKGROUND

Lung adenocarcinoma (LUAD) is a leading form of non-small cell lung cancer characterized by a complex tumor microenvironment (TME) that influences disease progression and therapeutic response. Tumor-associated macrophages (TAMs) within the TME promote tumorigenesis and evasion of immune surveillance, though their heterogeneity poses challenges in understanding their roles and therapeutic targeting. Additionally, traditional Chinese medicine (TCM) offers potential anti-cancer agents that could modulate the immune landscape.

METHODS

We conducted single-cell RNA sequencing (scRNA-seq) on LUAD samples, performing an in-depth analysis of macrophage populations and their expression signatures. Network pharmacology was used to identify TCM components with potential TAM-modulatory effects, focusing on Astragalus membranaceus. Pseudotime trajectory analysis, immunofluorescence staining, and in vitro assays examined the functional roles of TAMs and the effects of selected compounds on macrophage polarization.

RESULTS

Our scRNA-seq analysis identified notable heterogeneity among macrophages, revealing predominant M2-like phenotypes within TAMs. Network pharmacology highlighted active TCM ingredients, including quercetin, isorhamnetin, and kaempferol, targeting genes related to macrophage function. Survival analysis implicated AHSA1, CYP1B1, SPP1, and STAT1 as prognostically significant factors. Further experiments demonstrated kaempferol's efficacy in inhibiting M2 polarization, underlining a selective influence on TAM functionality.

CONCLUSIONS

This study delineates the diverse macrophage landscape in LUAD and suggests a pivotal role for STAT1 in TAM-mediated immunosuppression. Kaempferol, identified from TCM, emerges as an influential agent capable of altering TAM polarization, potentially enhancing anti-tumoral immunity. These findings underscore the translational potential of integrating TCM-derived compounds into immunotherapeutic strategies for LUAD.

Multi-Omics Analysis Reveals Immune Infiltration and Clinical Significance of Phosphorylation Modification Enzymes in Lung Adenocarcinoma

Protein phosphorylation is a dynamic and reversible modification involved in almost all cellular processes. Numerous investigations have shown that protein phosphorylation modification enzymes (PPMEs) that regulate protein phosphorylation play an important role in the occurrence and treatment of tumors. However, there is still a lack of effective insights into the value of PPMEs in the classification and treatment of patients with lung adenocarcinoma (LUAD). Here, four topological algorithms identified 15 hub PPMEs from a protein-protein interaction (PPI) network. This PPI network was constructed using 124 PPMEs significantly correlated with 35 cancer hallmark-related pathways. Our study illustrates that these hub PPMEs can affect the survival of patients with LUAD in the form of somatic mutation or expression perturbation. Consistency clustering based on hub PPMEs recognized two phosphorylation modification subtypes (namely cluster1 and cluster2) from LUAD. Compared with patients in cluster1, the survival prognosis of patients in cluster2 is worse. This disparity is probably attributed to the higher tumor mutation burden, the higher male proportion, and the more significant expression disturbance in patients in cluster2. Moreover, phosphorylation modification subtypes also have different characteristics in terms of immune activity, immune infiltration level, immunotherapy response, and drug sensitivity. We constructed a PSig scoring system by using a principal component analysis algorithm to estimate the level of phosphorylation modification in individual LUAD patients. Patients in the high and low PSig score groups demonstrated different characteristics in terms of survival rate, tumor mutation burden, somatic gene mutation rate, immune cell abundance, and sensitivity to immunotherapy and drug treatment. This work reveals that phosphorylation plays a non-negligible role in the tumor microenvironment and immunotherapy of LUAD. Evaluating the phosphorylation status of individual LUAD patients by the PSig score can contribute to enhancing our cognition of the tumor microenvironment and guiding the formulation of more effective personalized treatment strategies.

Utilizing sc-linker to integrate single-cell RNA sequencing and human genetics to identify cell types and driver genes associated with non-small cell lung cancer

BACKGROUND

Genome-wide association studies (GWAS) provide a powerful method for identifying the loci and genes that contribute to disease. However, in many cases, the specific cell types and states that confer disease risk through these genes remain unknown. Determining this relationship is crucial for identifying pathogenic processes and developing therapeutic strategies.

METHODS

In this study, we utilized the sc-linker framework developed by Jagadeesh, which is an integrated framework that combines single-cell RNA sequencing (scRNA-seq), epigenomic single nucleotide polymorphism (SNP)-to-gene mapping, and GWAS summary statistics to infer potential cell types and diseases affected by genetic variations.

RESULTS

Using normal cell type programs in the sc-linker, we identified type 2 alveolar cells in normal lung tissues that are closely associated with non-small cell lung cancer (NSCLC). Additionally, we identified cancer-associated fibroblasts (CAFs) associated with lung cancer using disease-dependent programs. By integrating extensive single-cell data from NSCLC, we discerned heterogeneity among CAFs subgroups. Finally, using MAGMA, we identified RAB31 as a driver gene in disease-related fibroblasts. Proteins from the RAB family are involved in the dynamic regulation of cell membrane compartments and are dysregulated in various tumor types, potentially altering biological properties such as the proliferation, migration, and invasion of cancer cells. We found that the Ras-related protein Rab-31 (RAB31) was significantly overexpressed in tumor-associated fibroblasts compared to that in normal fibroblasts and was closely associated with poor prognosis in patients with NSCLC.

CONCLUSIONS

By integrating scRNA-seq, epigenomic, and GWAS datasets, we found that ACT2 and CAFs have specific disease heritability in lung cancer and identified the driver gene RAB31 as a potential therapeutic target.

Integrative multi-omics analysis for identifying novel therapeutic targets and predicting immunotherapy efficacy in lung adenocarcinoma

Aim: Lung adenocarcinoma (LUAD), the most prevalent subtype of non-small cell lung cancer (NSCLC), presents significant clinical challenges due to its high mortality and limited therapeutic options. The molecular heterogeneity and the development of therapeutic resistance further complicate treatment, underscoring the need for a more comprehensive understanding of its cellular and molecular characteristics. This study sought to delineate novel cellular subpopulations and molecular subtypes of LUAD, identify critical biomarkers, and explore potential therapeutic targets to enhance treatment efficacy and patient prognosis. Methods: An integrative multi-omics approach was employed to incorporate single-cell RNA sequencing (scRNA-seq), bulk transcriptomic analysis, and genome-wide association study (GWAS) data from multiple LUAD patient cohorts. Advanced computational approaches, including Bayesian deconvolution and machine learning algorithms, were used to comprehensively characterize the tumor microenvironment, classify LUAD subtypes, and develop a robust prognostic model. Results: Our analysis identified eleven distinct cellular subpopulations within LUAD, with epithelial cells predominating and exhibiting high mutation frequencies in Tumor Protein 53 (TP53) and Titin (TTN) genes. Two molecular subtypes of LUAD [consensus subtype (CS)1 and CS2] were identified, each showing distinct immune landscapes and clinical outcomes. The CS2 subtype, characterized by increased immune cell infiltration, demonstrated a more favorable prognosis and higher sensitivity to immunotherapy. Furthermore, a multi-omics-driven machine learning signature (MOMLS) identified ribonucleotide reductase M1 (RRM1) as a critical biomarker associated with chemotherapy response. Based on this model, several potential therapeutic agents targeting different subtypes were proposed. Conclusion: This study presents a comprehensive multi-omics framework for understanding the molecular complexity of LUAD, providing insights into cellular heterogeneity, molecular subtypes, and potential therapeutic targets. Differential sensitivity to immunotherapy among various cellular subpopulations was identified, paving the way for future immunotherapy-focused research.

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.

Integrin β8 Facilitates Macrophage Infiltration and Polarization by Regulating CCL5 to Promote LUAD Progression

The tumor microenvironment (TME) influences cancer progression and metastasis. Integrin β8 (ITGβ8), a member of the integrin family, is upregulated in various cancers. In this study, it is determined as a key factor that mediates the interaction between lung adenocarcinoma (LUAD) cells and macrophages. Increased expression levels of ITGβ8 are associated with increased numbers of CD163+ macrophages and poor prognosis in LUAD patients. The overexpression of ITGβ8 in LUAD cells promotes the polarization of THP-1 macrophages toward the M2 phenotype. In contrast, TCM (conditioned medium from the co-culture system) from THP-1 macrophages and ITGβ8-overexpressing A549 cells promoted the proliferation and invasion of A549 cells. Mechanistically, chemokine (C-C motif) ligand 5 (CCL5) plays an important role in mediating ITGβ8-induced macrophage polarization, and the phosphoinositide 3-kinase (PI3K)/AKT serine/threonine kinase (AKT)/interferon regulatory factor 9 (IRF9) pathway is involved in this process. Moreover, interleukin 8 (IL8) and interleukin 10 (IL10) produced by M2-like macrophages regulate the expression of ITGβ8 in LUAD cells through the spi-1 proto-oncogene (SPI1). This study elucidates the feedback mechanism of ITGβ8 between LUAD cells and macrophages.

Squamous cell carcinoma predicts worse prognosis in stage IA (≤ 2 cm) non-small cell lung cancer patients following sublobectomy: a population-based study

Recent studies recommend sublobectomy as a surgical approach for non-small cell lung cancer (NSCLC) tumors that are 2 cm or smaller. However, it remains unclear whether NSCLC patients with squamous cell carcinoma (SCC) have comparable outcomes to those with adenocarcinoma (ADC) following sublobectomy. To that end, this study aims to compare the survival outcomes between SCC and ADC in patients with stage IA NSCLC (≤ 2 cm) who have undergone sublobectomy. We identified stage IA (≤ 2 cm) NSCLC patients diagnosed with lung squamous cell carcinoma or adenocarcinoma pathology and underwent sublobectomy from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2020. Overall survival (OS) was determined using the Kaplan-Meier method, and Cox proportional hazards regression was employed to identify risk factors for OS. A total of 9,831 patients diagnosed with stage IA NSCLC (≤ 2 cm) were evaluated. Of these, 2,078 patients met the inclusion criteria, including 1,565 with adenocarcinoma (ADC) and 513 with squamous cell carcinoma (SCC). Notably, SCC was associated with worse overall survival compared to ADC (HR: 2.02, 95% CI: 1.34-3.05, P = 0.03). Subgroup analyses revealed that SCC was comparable to ADC in terms of OS for tumors ≤ 1 cm (HR: 1.22, 95% CI: 0.47-3.18, P = 0.83), while patients with SCC displayed worse OS compared to ADC for tumors > 1 to 2 cm (HR: 2.05, 95% CI: 1.31-3.23, P = 0.002). Cox proportional hazards regression analysis identified female sex (HR: 1.53, 95% CI: 1.08-2.19, P = 0.017), high tumor grade (HR: 1.76, 95% CI: 1.02-3.03, P = 0.011), and SCC (HR: 1.58, 95% CI: 1.08-2.30, P = 0.017) as independent risk factors for OS. In patients with stage IA (≤ 2 cm) NSCLC who underwent sublobectomy, SCC is associated with worse overall survival compared to ADC. Furthermore, being female, having a high tumor grade, and SCC pathology are independent risk factors for OS in these patients.

Toripalimab plus chemotherapy for first line treatment of advanced non-small cell lung cancer (CHOICE-01): final OS and biomarker exploration of a randomized, double-blind, phase 3 trial

A randomized double-blind phase 3 trial (CHOICE-01, NCT03856411) demonstrated that combining toripalimab with chemotherapy substantially improves progression-free survival (PFS) in advanced non-small cell lung cancer (NSCLC) patients without pretreatment. This study presents the prespecified final analysis of overall survival (OS) and biomarkers utilizing circulating tumor DNA (ctDNA) and tissue-based sequencing. Additionally, the analysis revealed a higher median overall survival (OS, 23.8 months) in the toripalimab group than that in the control group (17.0 months). (HR = 0.69, 95%CI: 0.57-0.93, nominal P = 0.01). This survival benefit was particularly notable in the non-squamous subgroup. As the first phase 3 study to perform both baseline tissue whole-exome sequencing (WES) and peripheral blood ctDNA testing, we investigated efficacy predictive biomarkers based on both tissue and ctDNA, Genomic sequencing of ctDNA showed high concordance with tumor tissue independently confirmed that individuals exhibiting a high tumor mutational burden, as well as mutations in the FA-PI3K-Akt and IL-7 signaling pathways benefited more from the toripalimab treatment. Furthermore, a ctDNA response observed on cycle 3 day 1, was associated with improved clinical outcomes for patients treated with the combination therapy. In conclusion, Toripalimab plus chemotherapy yields significant improvements in OS as a first-line treatment. The study highlights the utility of ctDNA as a proxy for tumor tissue, providing novel prospects for predicting efficacy of immuno-chemotherapy through continuous ctDNA monitoring.

Multi-omics in exploring the pathophysiology of diabetic retinopathy

Diabetic retinopathy (DR) is a leading global cause of vision impairment, with its prevalence increasing alongside the rising rates of diabetes mellitus (DM). Despite the retina's complex structure, the underlying pathology of DR remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) and recent advancements in multi-omics analyses have revolutionized molecular profiling, enabling high-throughput analysis and comprehensive characterization of complex biological systems. This review highlights the significant contributions of scRNA-seq, in conjunction with other multi-omics technologies, to DR research. Integrated scRNA-seq and transcriptomic analyses have revealed novel insights into DR pathogenesis, including alternative transcription start site events, fluctuations in cell populations, altered gene expression profiles, and critical signaling pathways within retinal cells. Furthermore, by integrating scRNA-seq with genetic association studies and multi-omics analyses, researchers have identified novel biomarkers, susceptibility genes, and potential therapeutic targets for DR, emphasizing the importance of specific retinal cell types in disease progression. The integration of scRNA-seq with metabolomics has also been instrumental in identifying specific metabolites and dysregulated pathways associated with DR. It is highly conceivable that the continued synergy between scRNA-seq and other multi-omics approaches will accelerate the discovery of underlying mechanisms and the development of novel therapeutic interventions for DR.

Dynamic transition of Tregs to cytotoxic phenotype amid systemic inflammation in Graves' ophthalmopathy

Graves' disease (GD) is an autoimmune condition that can progress to Graves' ophthalmopathy (GO), leading to irreversible damage to orbital tissues and potential blindness. The pathogenic mechanism is not fully understood. In this study, we conducted single-cell multi-omics analyses on healthy individuals, patients with GD without GO, newly diagnosed patients with GO, and treated patients with GO. Our findings revealed gradual systemic inflammation during GO progression, marked by overactivation of cytotoxic effector T cell subsets, and expansion of specific T cell receptor clones. Importantly, we observed a decline in the immunosuppressive function of activated Treg (aTreg) accompanied by a cytotoxic phenotypic transition. In vitro experiments revealed that dysfunction and transition of GO-autoreactive Treg were regulated by the yin yang 1 (YY1) upon secondary stimulation of thyroid stimulating hormone receptor (TSHR) under inflammatory conditions. Furthermore, adoptive transfer experiments of the GO mouse model confirmed infiltration of these cytotoxic Treg into the orbital lesion tissues. Notably, these cells were found to upregulate inflammation and promote pathogenic fibrosis of orbital fibroblasts (OFs). Our results reveal the dynamic changes in immune landscape during GO progression and provide direct insights into the instability and phenotypic transition of Treg, offering potential targets for therapeutic intervention and prevention of autoimmune diseases.

Cellular dynamics of tumor microenvironment driving immunotherapy resistance in non-small-cell lung carcinoma

Immune checkpoint inhibitors (ICIs) have profoundly reshaped the treatment paradigm for non-small cell lung cancer (NSCLC). Despite these advancements, primary and secondary resistance to ICIs remain prevalent challenges in managing advanced NSCLC. Recent studies have highlighted the significant role of the tumor microenvironment (TME) in modulating treatment responses. This review aims to comprehensively examine the interactive roles of immune/stromal cells-such as T cells, B cells, neutrophils, macrophages, and CAFs within the TME, elucidating how these diverse cellular interactions contribute to immunotherapy resistance. It focuses on the dynamic interactions among diverse cell types such as the varying states of T cells under the influence of TME constituents like immune cells and cancer-associated fibroblasts (CAFs). By exploring the mechanisms involved in the complex cellular interactions, we highlight novel therapeutic targets and strategies aimed at overcoming resistance, thereby enhancing the efficacy of ICIs in NSCLC. Our synthesis of recent research provides critical insights into the multifaceted mechanisms of resistance and paves the way for the development of more effective, personalized treatment approaches.

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

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

Investigating the role of prognostic mitophagy-related genes in non-small cell cancer pathogenesis via multiomics and network-based approach

As one of the most prevalent malignancies, lung cancer displays considerable biological variability in both molecular and clinical characteristics. Lung cancer is broadly categorized into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) with the latter being most prevalent. The primary histological subtypes of NSCLC are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In the present work, we primarily extracted mRNA count data from a publicly accessible database followed by differentially expressed genes (DEGs) and differentially expressed mitophagy-related genes (DEMRGs) identification in case of both LUAD and LUSC cohorts. Next, we identified important DEMRGs via clustering approach followed by enrichment, survival, and mutational analyses. Lastly, the finalized prognostic biomarker was validated using wet-lab experimentations. Primarily, we obtained 986 and 1714 DEGs across LUAD and LUSC cohorts. Only 7 DEMRGs from both cohorts had significant membership values as indicated by the clustering analysis. Most significant pathway, Gene Ontology (GO)-biological process (BP), GO-molecular function (MF), GO-cellular compartment (CC) terms were macroautophagy, GTP metabolic process, magnesium ion binding, mitochondrial outer membrane. Among all, only TDRKH reported significant overall survival (OS) and 14% amplification across LUAD patients. Lastly, we validated TDRKH via immunohistochemistry (IHC) and semi-quantitative polymerase chain reaction (PCR). In conclusion, our findings advocate for the exploration of TDRKH and their genetic alterations in precision oncology therapeutic approaches for LUAD, emphasizing the potential for target-driven therapy and early diagnostics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-04127-y.

Heterogeneity in peripheral blood immune lymphocyte subsets predicts the response of immunotherapy or chemoradiotherapy in advanced lung cancer: an analysis across different pathological types, treatment modalities and age

Background

The shaping of the tumor immune microenvironment does not only rely on tumor-infiltrating lymphocytes but on the recruitment of lymphocytes in peripheral blood. Monitoring peripheral blood lymphocyte subsets level (PBLSL) can predict treatment response and prognosis with immune checkpoint inhibitors. This study investigated the heterogeneity of PBLSL in response to chemoradiotherapy (CRT) or combined with immunotherapy (CRIT) in advanced lung cancer patients.

Methods

77 patients with advanced lung cancer receiving CRT or CRIT were divided into treatment-responsive and non-responsive groups based on efficacy. The study analyzed short-term efficacy and progression-free survival (PFS) according to baseline PBLSL and explored the impact under different stratifications, including treatment modality, pathology type, and age.

Results

In all patients, higher levels of B cells, higher CD4+/CD8+ T cell ratios, and lower CD8+ T cell levels were associated with better short-term outcomes (P = 0.0035, P = 0.044, P = 0.022). Subgroup analysis revealed that in the CRT group, higher B cell levels correlated with improved efficacy (P = 0.011) and superior PFS (P = 0.048, HR = 0.3886, 95% CI = 0.1696 to 0.8902). In the CRIT group, higher CD4+ T cell levels, lower CD8+ T cell levels, and higher CD4+/CD8+ T cell ratios were linked to better efficacy (P = 0.038, P = 0.047, P = 0.017). For adenocarcinoma patients, higher CD4+/CD8+ T cell ratios and lower CD8+ T cell levels predicted better efficacy (P = 0.0155, P = 0.0119). B cell levels were significant in squamous cell carcinoma (P = 0.0291), while no PBLSL was predictive for small cell lung cancer. Among patients under 65, higher B cell levels were linked to improved efficacy and prolonged PFS (P = 0.0036, P = 0.0332, HR = 0.4111, 95% CI = 0.1973 to 0.8563). For patients over 65, differences in CD4+ T cell levels and CD4+/CD8+ T cell ratios were significant (P = 0.0433, P = 0.0338).

Conclusion

PBLSL predicted efficacy and prognosis in various patient stratifications, suggesting PBLSL is a reliable predictor for CRT and CRIT in advanced lung cancer. Detecting different cellular subpopulations helps identify patients with significant treatment responses across different stratifications.

Neutrophils under the microscope: neutrophil dynamics in infection, inflammation, and cancer revealed using intravital imaging

Neutrophils rapidly respond to inflammation resulting from infection, injury, and cancer. Intravital microscopy (IVM) has significantly advanced our understanding of neutrophil behavior, enabling real-time visualization of their migration, interactions with pathogens, and coordination of immune responses. This review delves into the insights provided by IVM studies on neutrophil dynamics in various inflammatory contexts. We also examine the dual role of neutrophils in tumor microenvironments, where they can either facilitate or hinder cancer progression. Finally, we highlight how computational modeling techniques, especially agent-based modeling, complement experimental data by elucidating neutrophil kinetics at the level of individual cells as well as their collective behavior. Understanding the role of neutrophils in health and disease is essential for developing new strategies for combating infection, inflammation and cancer.

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature

The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promising therapeutic modality, demonstrating remarkable potential for substantially prolonging the overall survival of individuals afflicted with LUAD. However, there is currently a lack of reliable signatures for identifying patients who would benefit from immunotherapy. We conducted a comparative analysis of two immunotherapy cohorts (OAK and POPLAR) and utilized single-factor COX regression to identify genes that significantly impact the prognosis of LUAD. Based on the TCGA-LUAD dataset, we employed a combination of 101 machine learning algorithms to construct a model and selected the optimal model. The model was validated on five GEO datasets and compared with 144 previously published signatures to assess its performance. Subsequently, we explored the underlying biological mechanisms through tumor mutation burden analysis, enrichment analysis, and immune infiltration analysis. An immunotherapy prognostic prediction signature (IPPS) was constructed based on 13 genes, showing robust performance in the TCGA-LUAD dataset. IPPS exhibited consistent predictive accuracy in the validation cohorts. Compared to 144 previously published signatures, IPPS consistently ranked among the top in terms of C-index values. Further exploration revealed differences between high and low-IPPS groups in terms of tumor mutation burden, pathway enrichment, and immune infiltration. IPPS demonstrates strong predictive capabilities for the prognosis of LUAD patients, offering the potential to identify suitable candidates for immunotherapy and contribute to precision treatment strategies for LUAD.

A single-cell RNA-seq dataset describing macrophages in NSCLC tumor and peritumor tissues

Examining tumor-associated macrophages in the immune microenvironment of non-small cell lung cancer (NSCLC) is essential for gaining an understanding of the genesis and development of NSCLC as well as for identifying key clinical therapeutic targets. Although previous studies have reported the diverse phenotypes and functions of macrophages in tumor tissues, thereby highlighting their significant role in the tumor microenvironment, the characteristic differences and correlations between tumor and peritumor tissue-derived macrophages that are necessary for an understanding of NSCLC progression remain unclear. Based on single-cell RNA sequencing, we generated a comprehensive dataset of transcriptomes from NSCLC tumor and peritumor tissues, thereby facilitating comprehensive analysis and providing significant insights. In summary, our dataset will serve as a valuable transcriptomic resource for further studies investigating NSCLC development.

Mechanisms of radiation-induced tissue damage and response

Radiation-induced tissue injury (RITI) is the most common complication in clinical tumor radiotherapy. Due to the heterogeneity in the response of different tissues to radiation (IR), radiotherapy will cause different types and degrees of RITI, which greatly limits the clinical application of radiotherapy. Efforts are continuously ongoing to elucidate the molecular mechanism of RITI and develop corresponding prevention and treatment drugs for RITI. Single-cell sequencing (Sc-seq) has emerged as a powerful tool in uncovering the molecular mechanisms of RITI and for identifying potential prevention targets by enhancing our understanding of the complex intercellular relationships, facilitating the identification of novel cell phenotypes, and allowing for the assessment of cell heterogeneity and spatiotemporal developmental trajectories. Based on a comprehensive review of the molecular mechanisms of RITI, we analyzed the molecular mechanisms and regulatory networks of different types of RITI in combination with Sc-seq and summarized the targeted intervention pathways and therapeutic drugs for RITI. Deciphering the diverse mechanisms underlying RITI can shed light on its pathogenesis and unveil new therapeutic avenues to potentially facilitate the repair or regeneration of currently irreversible RITI. Furthermore, we discuss how personalized therapeutic strategies based on Sc-seq offer clinical promise in mitigating RITI.

Exploring the prognostic and therapeutic value of HIF1A in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains a challenge within the realm of non-small cell lung cancer (NSCLC), demanding innovative diagnostic and therapeutic solutions. In this study, we systematically detected the correlation between the expression of hypoxia-induced factor 1A (HIF1A) and the clinical characteristics of LUAD, alongside lung squamous cell carcinoma (LUSC). Our bioinformatic analysis reveals that HIF1A mRNA expression is significantly upregulated in both LUAD and LUSC samples compared to non-tumorous lung tissues. The overexpression is positively correlated with increased copy number variation and negatively associated with promoter methylation. However, meta-analysis and survival analyses revealed a pronounced association between elevated HIF1A expression and poor clinical outcome specifically within the LUAD subset, with no such correlation evident in LUSC. Additionally, we explored the interplay between HIF1A expression, leukocyte infiltration, and the presence of immunosuppressive markers, revealing HIF1A's suppressive role in cytotoxicity against cancer cells. Furthermore, we performed in silico prediction to explore the correlations between HIF1A and its interacting proteins, associated pathways, glycolysis, and m6A modification, and the feasibility of targeting HIF1A with specific drugs. In summary, our study revealed the prognostic significance and therapeutic potential of HIF1A in LUAD.

3D cell culture models in research: applications to lung cancer pharmacology

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, necessitating innovative research methodologies to improve treatment outcomes and develop novel strategies. The advent of three-dimensional (3D) cell cultures has marked a significant advancement in lung cancer research, offering a more physiologically relevant model compared to traditional two-dimensional (2D) cultures. This review elucidates the various types of 3D cell culture models currently used in lung cancer pharmacology, including spheroids, organoids and engineered tissue models, having pivotal roles in enhancing our understanding of lung cancer biology, facilitating drug development, and advancing precision medicine. 3D cell culture systems mimic the complex spatial architecture and microenvironment of lung tumours, providing critical insights into the cellular and molecular mechanisms of tumour progression, metastasis and drug responses. Spheroids, derived from commercialized cell lines, effectively model the tumour microenvironment (TME), including the formation of hypoxic and nutrient gradients, crucial for evaluating the penetration and efficacy of anti-cancer therapeutics. Organoids and tumouroids, derived from primary tissues, recapitulate the heterogeneity of lung cancers and are instrumental in personalized medicine approaches, supporting the simulation of in vivo pharmacological responses in a patient-specific context. Moreover, these models have been co-cultured with various cell types and biomimicry extracellular matrix (ECM) components to further recapitulate the heterotypic cell-cell and cell-ECM interactions present within the lung TME. 3D cultures have been significantly contributing to the identification of novel therapeutic targets and the understanding of resistance mechanisms against conventional therapies. Therefore, this review summarizes the latest findings in drug research involving lung cancer 3D models, together with the common laboratory-based assays used to study drug effects. Additionally, the integration of 3D cell cultures into lung cancer drug development workflows and precision medicine is discussed. This integration is pivotal in accelerating the translation of laboratory findings into clinical applications, thereby advancing the landscape of lung cancer treatment. By closely mirroring human lung tumours, these models not only enhance our understanding of the disease but also pave the way for the development of more effective and personalized therapeutic strategies.

Correlation of LOXL2 expression in non-small cell lung cancer with immunotherapy

Lung cancer is the most prevalent and lethal disease globally, with approximately 80% of cases being non-small cell lung cancer (NSCLC). NSCLC is primarily composed of lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Despite chemotherapy currently being the primary treatment for NSCLC, chemotherapy resistance remains a significant challenge for patients. Recent studies have proposed immunotherapy as a promising new avenue for treating NSCLC. The association between the lysyl oxidase-like 2 (LOXL2) gene and NSCLC was explored using multiple online tools and bioinformatics analysis software based on the available datasets from TCGA. The immune microenvironment of the tumor was explored by calculating ImmuneScore, StromalScore, and TumorPurity of LUAD and LUSC and analyzing the infiltration of 22 immune cells in lung cancer tissues. LOXL2-related loads were obtained from the Xena database for LUSC and LUAD patients, and relevant prognostic genes were identified by analyzing survival curves. Functional and pathway enrichment analyses of prognostic, predictive genes were performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of LOXL2 in NSCLC was detected by RT-qPCR. LOXL2 may be involved in the progression of LUAD and LUSC and is closely related to the T-lymphocyte subpopulation, T-reg cells. SEMA7A and VEGFC are identified as the genes that interact with LOXL2 and could be used as prognostic signature genes in NSCLC patients. LOXL2 may become a prognostic marker and a new target for immunotherapy.

Development of a prognostic model for NSCLC based on differential genes in tumour stem cells

Non-small cell lung cancer (NSCLC) constitutes a significant portion of lung cancers and cytotoxic drugs (e.g. cisplatin) are currently the first-line treatment. However, NSCLC has developed resistance to this drug, which limits the therapeutic effect and thus affects prognosis. NSCLC sc-RNA-seq data were downloaded from the GEO database and Ku Leuven Laboratory for Functional Epigenetics, and bulk RNA-seq data were obtained from the TCGA database. The "Seurat" package was employed for scRNA-seq data processing, and the uniform manifold approximation and projection (UMAP) were applied for downscaling and cluster identification. Use the FindAllMarkers function to find differential genes (DEGs) for tumor stem cells. Then, we performed univariate regression analyses on the DEGs to identify potential prognostic genes. We created a machine learning framework based on potential prognostic genes, which combines 10 machine learning methods and their 101 combinations to get the optimal prognostic risk model. The model was evaluated in the training set and validation set. A nomogram was developed to provide physicians with a quantitative tool for prognosis prediction. Finally, we evaluated the expression and functionality of SLC2A1. We discovered 22 cell clusters containing 218379 cells by examining single-cell RNA sequencing datasets (GSE148071, KU_lom, GSE131907, GSE136246, GSE127465). Tumour cells were isolated for subpopulation analysis and 162 differential genes from SOX2_cancer were obtained. After univariate Cox analysis, we found 23 genes with prognostic potential prognostic value and utilized them to develop 101‑combination machine learning computational framework. We eventually picked the best performing 'StepCox[both] + RSF', which includes 8 genes. The model has a relatively high prediction accuracy in both TCGA and GEO datasets. In in vitro investigations, targeted suppression of the SLC2A1 gene resulted in significant reductions in proliferation, invasion and migration in A549 cells. In addition, a significant reduction in cisplatin resistance was seen in A549/DDP cells. The outcomes demonstrated the precision and credibility of the prognostic model for NSCLC, highlighting its potential significance in the treatment and prognosis of individuals affected by this disease. SLC2A1 may become a promising prognostic marker and a potential therapeutic target, offering valuable insights to inform clinical treatment decisions.

Tumor immune microenvironment of NSCLC with EGFR exon 20 insertions may predict efficacy of first-line ICI-combined regimen

OBJECTIVES

Non-small cell lung cancer (NSCLC) patients with exon 20 insertion mutations (ex20ins) of the epidermal growth factor receptor (EGFR) were resistant to monotherapy of immune checkpoint inhibitor (ICI). However, recent reports have shown that the combination of ICI and chemotherapy (ICI-combined regimen) exhibited certain efficacy for NSCLC with EGFR ex20ins. The mechanisms behind this phenomenon have not been thoroughly clarified. Hence, we conducted this study tofind correlations between the tumor immune microenvironment of EGFR ex20ins and the efficacy of ICI-combined regimen.

METHODS

We performed single-cell transcriptome sequencing and multiplex immunofluorescence staining (mIF) to investigate the immune microenvironment of NSCLC patients with EGFR ex20ins, L858R, and EGFR wild-type. We analyzed 15 treatment-naïve NSCLC samples utilizing single-cell RNA sequencing (scRNA-seq). Another 30 cases of EGFR L858R and 4 cases of wild-type were recruited to compare the immune microenvironment with that of EGFR ex20ins (28 cases) by mIF.

RESULTS

We observed that cell components, function and interactions varied between EGFR ex20ins, L858R, and wild-type NSCLC.We discovered similar T cell and CD8+ T cell distributions among groups but found noninferior or even better T cell activation in ex20ins patients. Infiltrating CD8+ FOXP3- T cells were significantly lower in the tumor region of EGFR ex20ins compared to wild-type. T cells from the ex20ins group had a greater tendency to promote cancer cell inflammation and epithelial-mesenchymal transition (EMT) compared to wild-type group. For macrophages, there were more M2-like macrophages in ex20ins patients. M1-like macrophages in ex20ins group produced fewer antitumor cytokines than in other groups.

CONCLUSIONS

The immune microenvironment of EGFR ex20ins is more suppressive than that of L858R and wild-type, suggesting that ICI monotherapy may not be sufficient for these patients. ICI-combined regimen might be a treatment option for EGFR ex20ins due to tumor-promoting inflammation and noninferior T cell functions in the immune microenvironment.

Differential prognostic impact and potential molecular mechanisms of PCDHGA12 expression in lung adenocarcinoma and squamous cell carcinoma

Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), subtypes of non-small cell lung cancer (NSCLC), exhibit distinct characteristics. The expression and prognostic significance of Protocadherin Gamma Subfamily A, 12 (PCDHGA12) in NSCLC remain unexplored. This study analyzed transcriptomic and genomic datasets from TCGA to investigate PCDHGA12 expression and its prognostic relevance in LUAD and LUSC. We found PCDHGA12 mRNA and protein levels were downregulated in both LUAD and LUSC tissues compared to adjacent non-cancerous tissues, with high PCDHGA12 expression correlating with lower overall survival in LUSC but not in LUAD. GSEA revealed a unique enrichment pattern associated with PCDHGA12 low expression in LUSC, especially in the DNA repair pathway. Co-expression analysis showed associations of PCDHGA12 with focal adhesion and the PI3K-AKT pathway in LUAD, and additionally with ECM-receptor interaction in LUSC. Hub gene prognosis analysis identified genes correlated with prognosis only in LUSC, reflecting PCDHGA12's influence. Mutation analysis linked with PCDHGA12 identified differential mutations in SPTA1, KEAP1, and TNR in LUAD, and a notable NAV3 mutation in LUSC. Additionally, immuno-infiltration analysis reveals a positive correlation between PCDHGA12 expression and immune cell infiltration. Specifically, lower PCDHGA12 expression in LUSC is associated with higher levels of CD8 T cells and DCs, lower levels of Tregs and M0 macrophages, and increased expression of HMGB1 and TNFRSF18. These genetic and immunological differences may account for the significant prognostic disparity of PCDHGA12 levels between LUAD and LUSC. Further experimental studies are essential to validate these associations and investigate potential targeted and immunotherapeutic strategies.

Lung Cancer Subtyping: A Short Review

As of 2022, lung cancer is the most commonly diagnosed cancer worldwide, with the highest mortality rate. There are three main histological types of lung cancer, and it is more important than ever to accurately identify the subtypes since the development of personalized, type-specific targeted therapies that have improved mortality rates. Traditionally, the gold standard for the confirmation of histological subtyping is tissue biopsy and histopathology. This, however, comes with its own challenges, which call for newer sampling techniques and adjunctive tools to assist in and improve upon the existing diagnostic workflow. This review aims to list and describe studies from the last decade (n = 47) that investigate three such potential omics techniques-namely (1) transcriptomics, (2) proteomics, and (3) metabolomics, as well as immunohistochemistry, a tool that has already been adopted as a diagnostic adjunct. The novelty of this review compared to similar comprehensive studies lies with its detailed description of each adjunctive technique exclusively in the context of lung cancer subtyping. Similarities between studies evaluating individual techniques and markers are drawn, and any discrepancies are addressed. The findings of this study indicate that there is promising evidence that supports the successful use of omics methods as adjuncts to the subtyping of lung cancer, thereby directing clinician practice in an economical and less invasive manner.

The tumor immune microenvironment remodeling and response to HER2-targeted therapy in HER2-positive advanced gastric cancer

Combination therapy with anti-HER2 agents and immunotherapy has demonstrated significant clinical benefits in gastric cancer (GC), but the underlying mechanism remains unclear. In this study, we used multiplex immunohistochemistry to assess the changes of the tumor microenvironment in 47 advanced GC patients receiving anti-HER2 therapy. Additionally, we performed single-cell transcriptional sequencing to investigate potential cell-to-cell communication and molecular mechanisms in four HER2-positive GC baseline samples. We observed that post-treated the infiltration of NK cells, CD8+ T cells, and B lymphocytes were significantly higher in patients who benefited from anti-HER2 treatment than baseline. Further spatial distribution analysis demonstrated that the interaction scores between NK cells and CD8+ T cells, B lymphocytes and M2 macrophages, B lymphocytes and Tregs were also significantly higher in benefited patients. Cell-cell communication analysis from scRNA sequencing showed that NK cells utilized CCL3/CCL4-CCR5 to recruit CD8+ T cell infiltration. B lymphocytes employed CD74-APP/COPA/MIF to interact with M2 macrophages, and utilized TNF-FAS/ICOS/TNFRSR1B to interact with Tregs. These cell-cell interactions contribute to inhibit the immune resistance of M2 macrophages and Tregs. Our research provides potential guidance for the use of anti-HER2 therapy in combination with immune therapy.

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

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

[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.
.

Heterogeneity of myeloid cells in common cancers: Single cell insights and targeting strategies

Tumor microenvironment (TME), is characterized by a complex and heterogenous composition involving a substantial population of immune cells. Myeloid cells comprising over half of the solid tumor mass, are undoubtedly one of the most prominent cell populations associated with tumors. Studies have unambiguously established that myeloid cells play a key role in tumor development, including immune suppression, pro-inflammation, promote tumor metastasis and angiogenesis, for example, tumor-associated macrophages promote tumor progression in a variety of common tumors, including lung cancer, through direct or indirect interactions with the TME. However, due to previous technological constraints, research on myeloid cells often tended to be conducted as studies with low throughput and limited resolution. For example, the conventional categorization of macrophages into M1-like and M2-like subsets based solely on their anti-tumor and pro-tumor roles has disregarded their continuum of states, resulting in an inadequate analysis of the high heterogeneity characterizing myeloid cells. The widespread adoption of single-cell RNA sequencing (scRNA-seq) in tumor immunology has propelled researchers into a new realm of understanding, leading to the establishment of novel subsets and targets. In this review, the origin of myeloid cells in high-incidence cancers, the functions of myeloid cell subsets examined through traditional and single-cell perspectives, as well as specific targeting strategies, are comprehensively outlined. As a result of this endeavor, we will gain a better understanding of myeloid cell heterogeneity, as well as contribute to the development of new therapeutic approaches.

CXCL1/IGHG1 signaling enhances crosstalk between tumor cells and tumor-associated macrophages to promote MC-LR-induced colorectal cancer progression

Microcystin-leucine arginine (MC-LR) is a common cyantotoxin produced by hazardous cyanobacterial blooms, and eutrophication is increasing the contamination level of MC-LR in drinking water supplies and aquatic foods. MC-LR has been linked to colorectal cancer (CRC) progression associated with tumor microenvironment, however, the underlying mechanism is not clearly understood. In present study, by using GEO, KEGG, GESA and ImmPort database, MC-LR related differentially expressed genes (DEGs) and pathway- and gene set-enrichment analysis were performed. Of the three identified DEGs (CXCL1, GUCA2A and GDF15), CXCL1 was shown a positive association with tumor infiltration, and was validated to have a dominantly higher upregulation in MC-LR-treated tumor-associated macrophages (TAMs) rather than in MC-LR-treated CRC cells. Both CRC cell/macrophage co-culture and xenograft mouse models indicated that MC-LR stimulated TAMs to secrete CXCL1 resulting in promoted proliferation, migration, and invasion capability of CRC cells. Furtherly, IP-MS assay found that interaction between TAMs-derived CXCL1 and CRC cell-derived IGHG1 may enhance CRC cell proliferation and migration after MC-LR treatment, and this effect can be attenuated by silencing IGHG1 in CRC cell. In addition, molecular docking analysis, co-immunoprecipitation and immunofluorescence further proved the interactions between CXCL1 and IGHG1. In conclusion, CXCL1 secreted by TAMs can trigger IGHG1 expression in CRC cells, which provides a new clue in elucidating the mechanism of MC-LR-mediated CRC progression.

Effect of 23‑hydroxybetulinic acid on lung adenocarcinoma and its mechanism of action

The present study aimed to investigate the effect and mechanism of Pulsatilla compounds on lung adenocarcinoma. The representative drug chosen was the compound 23-HBA. GeneCards, Swiss target prediction, DisGeNET and TCMSP were used to screen out related genes, and MTT and flow cytometry assays were used to verify the inhibitory effect of Pulsatilla compounds on the proliferation of lung adenocarcinoma cells. Subsequently, the optimal target, peroxisome proliferator-activated receptor (PPAR)-γ, was selected using bioinformatics analysis, and its properties of low expression in lung adenocarcinoma cells and its role as a tumor suppressor gene were verified by western blot assay. The pathways related to immunity and inflammation, vascular function, cell proliferation, differentiation, development and apoptosis with the highest degree of enrichment and the mechanisms were explored through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Finally, the clinical prognosis in terms of the survival rate of patients in whom the drug is acting on the target was analyzed using the GEPIA database. The results indicated that Pulsatilla compounds can inhibit the proliferation of lung adenocarcinoma cells by blocking the cell cycle at the G1 phase. Subsequently, the related PPAR-γ gene was verified as a tumor suppressor gene. Further analysis demonstrated that this finding was related to the PPAR signaling pathway and mitochondrial reactive oxygen species (ROS) production. Finally, the clinical prognosis was found to be improved, as the survival rate of patients was increased. In conclusion, Pulsatilla compounds were indicated to inhibit the viability and proliferation of lung adenocarcinoma H1299 cells, and the mechanism of action was related to PPAR-γ, the PPAR signaling pathway and mitochondrial ROS. The present study provides novel insight to further explore the treatment of lung adenocarcinoma.

Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Bulk and single-cell RNA sequencing reveal the contribution of laminin γ2 -CD44 to the immune resistance in lymphocyte-infiltrated squamous lung cancer subtype

The high heterogeneity of lung squamous cell carcinomas (LUSC) and the complex tumor microenvironment lead to non-response to immunotherapy in many patients. Therefore, characterizing the heterogeneity of the tumor microenvironment in patients with LUSC and further exploring the immune features and molecular mechanisms that lead to immune resistance will help improve the efficacy of immunotherapy in such patients. Herein, we retrospectively analyzed the RNA sequencing (RNA-seq) data of 513 LUSC samples with other multiomics and single-cell RNA-seq data and validated key features using multiplex immunohistochemistry. We divided these samples into six subtypes (CS1-CS6) based on the RNA-seq data and found that CS3 activates the immune response with a high level of lymphocyte infiltration and gathers a large number of patients with advanced-stage disease but increases the expression of exhausted markers cytotoxic T-lymphocyte associated protein 4, lymphocyte-activation gene 3, and programmed death-1. The prediction of the response to immunotherapy showed that CS3 is potentially resistant to immune checkpoint blockade therapy, and multi-omic data analysis revealed that CS3 specifically expresses immunosuppression-related proteins B cell lymphoma 2, GRB2-associated binding protein, and dual-specificity phosphatase 4 and has a high mutation ratio of the driver gene ATP binding cassette subfamily A member 13. Furthermore, single-cell RNA-seq verified lymphocyte infiltration in the CS3 subtype and revealed a positive relationship between the expression of LAMC2-CD44 and immune resistance. LAMC2 and CD44 are epithelial-mesenchymal transition-associated genes that modulate tumor proliferation, and multicolor immunofluorescence validated the negative relationship between the expression of LAMC2-CD44 and immune infiltration. Thus, we identified a lymphocyte-infiltrated subtype (CS3) in patients with LUSC that exhibited resistance to immune checkpoint blockade therapy, and the co-hyperexpression of LAMC2-CD44 contributed to immune resistance, which could potentially improve immunological efficacy by targeting this molecule pair in combination with immunotherapy.

Single-cell and spatial transcriptomics reveal metastasis mechanism and microenvironment remodeling of lymph node in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is the most common primary malignant bone tumor and is highly prone to metastasis. OS can metastasize to the lymph node (LN) through the lymphatics, and the metastasis of tumor cells reestablishes the immune landscape of the LN, which is conducive to the growth of tumor cells. However, the mechanism of LN metastasis of osteosarcoma and remodeling of the metastatic lymph node (MLN) microenvironment is not clear.

METHODS

Single-cell RNA sequencing of 18 samples from paracancerous, primary tumor, and lymph nodes was performed. Then, new signaling axes closely related to metastasis were identified using bioinformatics, in vitro experiments, and immunohistochemistry. The mechanism of remodeling of the LN microenvironment in tumor cells was investigated by integrating single-cell and spatial transcriptomics.

RESULTS

From 18 single-cell sequencing samples, we obtained 117,964 cells. The pseudotime analysis revealed that osteoblast(OB) cells may follow a differentiation path from paracancerous tissue (PC) → primary tumor (PT) → MLN or from PC → PT, during the process of LN metastasis. Next, in combination of bioinformatics, in vitro and in vivo experiments, and immunohistochemistry, we determined that ETS2/IBSP, a new signal axis, might promote LN metastasis. Finally, single-cell and spatial dissection uncovered that OS cells could reshape the microenvironment of LN by interacting with various cell components, such as myeloid, cancer-associated fibroblasts (CAFs), and NK/T cells.

CONCLUSIONS

Collectively, our research revealed a new molecular mechanism of LN metastasis and clarified how OS cells influenced the LN microenvironment, which might provide new insight for blocking LN metastasis.

Single-cell profiling reveals the metastasis-associated immune signature of hepatocellular carcinoma

AIM

Metastasis is the leading cause of mortality in hepatocellular carcinoma (HCC). The metastasis-associated immune signature in HCC is worth exploring.

METHODS

Bioinformatic analysis was conducted based on the single-cell transcriptome data derived from HCC patients in different stages. Cellular composition, pseudotime state transition, and cell-cell interaction were further analyzed and verified.

RESULTS

Generally, HCC with metastasis exhibited suppressive immune microenvironment, while HCC without metastasis exhibited active immune microenvironment. Concretely, effector regulatory T cells (eTregs) were found to be enriched in HCC with metastasis. PHLDA1 was identified as one of exhaustion-specific genes and verified to be associated with worse prognosis in HCC patients. Moreover, A novel cluster of CCR7+ dendritic cells (DCs) was identified with high expression of maturation and migration marker genes. Pseudotime analysis showed that inhibition of differentiation occurred in CCR7+ DCs rather than cDC1 in HCC with metastasis. Furthermore, interaction analysis showed that the reduction of CCR7+ DCs lead to impaired CCR7/CCL19 interaction in HCC with metastasis.

CONCLUSIONS

HCC with metastasis exhibited upregulation of exhaustion-specific genes of eTregs and inhibition of CCL signal of a novel DC cluster, which added new dimensions to the immune landscape and provided new immune therapeutic targets in advanced HCC.