Phenotype molding of stromal cells in the lung tumor microenvironment

IL6 mediated cFLIP downregulation increases the migratory and invasive potential of triple negative breast cancer cell

c-FLIP (cellular FLICE-Like Inhibitor of Apoptotic protein) alias CFLAR (Cellular FADD-like apoptosis regulator) is an inhibitor of Caspase 8 and thus plays a key role in the regulation of extrinsic apoptotic pathway. However, the mechanisms of cFLIP regulation during the course of progression of cancer and it's involvement in tumour cell migration and invasion is yet to be known. Our TCGA data analysis has shown that cFLIP is downregulated in many cancers, including breast cancer, especially at the later stages. Next, we have analysed the role of cFLIP in breast cancer progression in In-vitro study. In doing so, we have used luminal breast cancer cell line MCF7 as non-aggressive and non-invasive breast cancer model and triple negative breast cancer cell lines MDA-MB-231, MDA-MB-468 and MDA-MB-453 as highly aggressive and invasive breast cancer cell model. When, we analysed and compared MCF7 and triple negative cell lines, we found a negative correlation between cFLIP expression pattern and metastasis which supported our In-silico study. Moreover, we found that Il6, one of the most prominent cytokines inside tumour microenvironment, helped in cFLIP downregulation via activation of p38 in MDA-MB-231 cell line. Not only that we have shown that cFLIP negatively regulated autophagy and this autophagy down-regulation resulted in decrease in metastasis. Thus, we have shown in an In-vitro model, for the first time, a complete interconnecting pathway in which IL6 mediated p38 activation directly influences metastasis by regulating autophagy via cFLIP downregulation.

A coagulation-related long non-coding RNA signature to predict prognosis and immune features of breast cancer

Breast cancer (BC) remains one of the most common malignancies among women worldwide, with persistently poor prognosis despite advancements in diagnostics and therapies. Long non-coding RNAs (lncRNAs) and coagulation-related genes (CRGs) are increasingly recognized for their roles in prognosis and immune modulation. Using transcriptomic data from 1,045 BC patients in TCGA, we identified CRG-associated lncRNAs via coexpression analysis (Pearson |R|> 0.4, p < 0.001) and constructed a prognostic model through univariate Cox analysis, LASSO regression with tenfold cross-validation (λ = 0.05), and multivariate Cox analysis. The model stratified patients into high- and low-risk groups with distinct overall survival (HR = 3.21, p < 0.001) and demonstrated robust predictive accuracy (AUC = 0.795 at 1 year). Functional enrichment revealed immune-related pathways (e.g., cytokine signaling, PD-L1 regulation), and high-risk patients exhibited elevated tumor mutational burden (TMB) and PD-L1 expression, suggesting enhanced immunotherapy responsiveness. Drug sensitivity analysis identified 5 targeted agents (e.g., BIBW2992) with differential efficacy between risk groups. This CRG-lncRNA signature provides a novel tool for prognosis prediction and personalized immunotherapy in BC, illuminating crosstalk between coagulation and immune pathways.

A multi-omics analysis of effector and resting treg cells in pan-cancer

Regulatory T cells (Tregs) are critical for maintaining the stability of the immune system and facilitating tumor escape through various mechanisms. Resting T cells are involved in cell-mediated immunity and remain in a resting state until stimulated, while effector T cells promote immune responses. Here, we investigated the roles of two gene signatures, one for resting Tregs (FOXP3 and IL2RA) and another for effector Tregs (FOXP3, CTLA-4, CCR8 and TNFRSF9) in pan-cancer. Using data from The Cancer Genome Atlas (TCGA), The Cancer Proteome Atlas (TCPA) and Gene Expression Omnibus (GEO), we focused on the expression profile of the two signatures, the existence of single nucleotide variants (SNVs) and copy number variants (CNVs), methylation, infiltration of immune cells in the tumor and sensitivity to different drugs. Our analysis revealed that both signatures are differentially expressed across different cancer types, and correlate with patient survival. Furthermore, both types of Tregs influence important pathways in cancer development and progression, like apoptosis, epithelial-to-mesenchymal transition (EMT) and the DNA damage pathway. Moreover, a positive correlation was highlighted between the expression of gene markers in both resting and effector Tregs and immune cell infiltration in adrenocortical carcinoma, while mutations in both signatures correlated with enrichment of specific immune cells, mainly in skin melanoma and endometrial cancer. In addition, we reveal the existence of widespread CNVs and hypomethylation affecting both Treg signatures in most cancer types. Last, we identified a few correlations between the expression of CCR8 and TNFRSF9 and sensitivity to several drugs, including COL-3, Chlorambucil and GSK1070916, in pan-cancer. Overall, these findings highlight new evidence that both Treg signatures are crucial regulators of cancer progression, providing potential clinical outcomes for cancer therapy.

Unveiling the immune microenvironment of complex tissues and tumors in transcriptomics through a deconvolution approach

Accurately resolving the composition of tumor-infiltrating leukocytes is pivotal for advancing cancer immunotherapy strategies. Despite the success of some clinical trials, applying these strategies remains limited due to the challenges in deciphering the immune microenvironment. In this study, we developed a streamlined, two-step workflow to address the complexity of bioinformatics processes involved in analyzing immune cell composition from transcriptomics data. Our dockerized toolkit, DOCexpress_fastqc, integrates the hisat2-stringtie pipeline with customized scripts within Galaxy/Docker environments, facilitating RNA sequencing (RNA-seq) gene expression profiling. The output from DOCexpress_fastqc is seamlessly formatted with mySORT, a web application that employs a deconvolution algorithm to determine the immune content across 21 cell subclasses. We validated mySORT using synthetic pseudo-bulk data derived from single-cell RNA sequencing (scRNA-seq) datasets. Our predictions exhibit strong concordance with the ground-truth immune cell composition, achieving Pearson's correlation coefficients of 0.871 in melanoma patients and 0.775 in head and neck cancer patients. Additionally, mySORT outperforms existing methods like CIBERSORT in accuracy and provides a wide range of data visualization features, such as hierarchical clustering and cell complexity plots. The toolkit and web application are freely available for the research community, providing enhanced resolution for conventional bulk RNA sequencing data and facilitating the analysis of immune microenvironment responses in immunotherapy. The mySORT demo website and Docker image are free at https://mysort.iis.sinica.edu.tw and https://hub.docker.com/r/lsbnb/mysort_2022 .

A tumour necrosis factor-α responsive cryptic promoter drives overexpression of the human endogenous retrovirus ERVK-7

Endogenous retroviruses (ERVs) shape human genome functionality and influence disease pathogenesis, including cancer. ERVK-7, a significant ERV, acts as an immune modulator and prognostic marker in lung adenocarcinoma (LUAD). Although ERVK-7 overexpression has been linked to the amplification of the 1q22 locus in approximately 10% of LUAD cases, it predominantly arises from alternative regulatory mechanisms. Our findings indicate that the canonical 5' long terminal repeat (LTR) of ERVK-7 is methylated and inactive, necessitating the use of alternative upstream promoters. We identified two novel transcripts, ERVK-7.long and ERVK-7.short, arising from distinct promoters located 2.8 kb and 13.8 kb upstream of the 5'LTR of ERVK-7, respectively. ERVK-7.long is predominantly overexpressed in LUAD. Through comprehensive epigenetic mapping and single-cell transcriptomics, we demonstrate that ERVK-7.long activation is predetermined by cell lineage, specifically in small airway epithelial cells (SAECs), where its promoter displays tumor-specific H3K4me3 modifications. Single-cell RNA sequencing further reveals a distinct enrichment of ERVK-7.long in LUAD tumor cells and alveolar type 2 epithelial cells, underscoring a cell-type-specific origin. Additionally, inflammatory signaling significantly influences ERVK-7 expression; TNF-α enhances ERVK-7.long, while interferon signaling preferentially augments ERVK-7.short by differential recruitment of NF-κB/RELA and IRF to their respective promoters. This differential regulation clarifies the elevated ERVK-7 expression in LUAD compared to lung squamous cell carcinoma (LUSC). Our study elucidates the complex regulatory mechanisms governing ERVK-7 in LUAD and proposes these transcripts as potential biomarkers and therapeutic targets, offering new avenues to improve patient outcomes.

Decoding the role of lipid metabolism in NSCLC: From macrophage subtype identification to prognostic model development

Lipid metabolism plays a pivotal role in shaping the tumor microenvironment, particularly by influencing macrophage function. This study aimed to identify lipid-associated macrophage (LAM) marker genes involved in the onset and progression of non-small cell lung cancer (NSCLC) through integrated single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) analyses. Mutation and RNA-seq data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed to explore the relationship between lipid metabolism pathways and NSCLC progression. scRNA-seq analysis revealed macrophage subtypes closely associated with lipid metabolism, with three key marker genes-S100A10, HLA-DMB, and CTSL-identified as predictive factors for patient prognosis. A prognostic risk scoring model was constructed and validated using survival analysis and ROC curves, demonstrating high accuracy in stratifying NSCLC patients by risk. Further in vivo experiments using subcutaneous tumor xenografts and lung metastasis models showed that S100A10 and CTSL promoted tumor growth and metastasis, while HLA-DMB inhibited these processes. Immune infiltration analysis highlighted the immunological relevance of the identified marker genes, providing insights into their functional roles. This study underscores the critical influence of LAMs in NSCLC progression and highlights a robust prognostic model that offers potential therapeutic targets for improving patient outcomes.

CAF-mediated tumor vascularization: From mechanistic insights to targeted therapies

Cancer-associated fibroblasts (CAFs) are a major component of the tumor microenvironment (TME) and play a crucial role in tumor progression. The biological properties of tumors, such as drug resistance, vascularization, immunosuppression, and metastasis are closely associated with CAFs. During tumor development, CAFs contribute to tumor progression by remodeling the extracellular matrix (ECM), inhibiting immune cell function, promoting angiogenesis, and facilitating tumor cell growth, invasion, and metastasis. Studies have shown that CAFs can promote endothelial cell proliferation by directly secreting cytokines such as vascular endothelial growth factor (VEGF) and fibroblast Growth Factor (FGF), as well as through exosomes. CAFs also secrete the chemokine stromal cell-derived factor 1 (SDF-1) to recruit endothelial progenitor cells (EPCs) into the peripheral blood and guide their migration to the tumor periphery. Additionally, CAFs can induce tumor cells to transform into "endothelial cells" that participate in vascular wall formation. However, the precise mechanisms remain to be further investigated. Due to their widespread presence in various solid tumors and their tumor-promoting function, CAFs are emerging as therapeutic targets. In this review, we summarize the specific mechanisms through which CAFs promote angiogenesis and outline current therapeutic strategies targeting CAF-induced vascularization, ongoing clinical trials targeting CAFs, and discuss potential future treatment approaches. We hope this will contribute to the advancement of CAF-targeted tumor treatment strategies.

Single-cell profiling in ovarian germ cell and sex cord-stromal tumours

BACKGROUND

The tumour microenvironment of rare ovarian germ cell tumours (OGCT) and sex-cord stromal tumours (SCST) remains unexplored. To better understand their immune and stromal landscape, we constructed a blueprint using single-cell RNA sequencing (scRNA-seq).

METHODS

We performed scRNA-seq of 66, 919 cells from twelve fresh tumour samples: seven adult granulosa cell tumour (aGSCT), one juvenile GSCT (jGSCT), one Sertoli-Leydig (SL) tumour, two immature teratoma (IT) and one dysgerminoma (DG). We characterised immune cell subtypes and fibroblasts based on their specific marker genes. Validation included combined positive score (CPS) of 46 OGCTs and 66 SCSTs, and bulk RNA sequencing (n = 32).

RESULTS

Cell clustering and annotation revealed a immune-activated microenvironment in DG, driven by PD-1- exhausted T cells, reflected in high CPS (≥10) and upregulated immune pathways. IT samples displayed no immunoreactive profile, consistent with a negative CPS. aGSCTs exhibited a fibroblast-enriched, immune-desert phenotype, with low T cell infiltration and increased immunosuppressive LYVE1 and CX3CR1+ macrophages, corresponding to negative CPS.

CONCLUSION

We constructed a detailed blueprint of the OGCT and SCSTs microenvironment of, elucidating potential modulators that shape their immune landscape. The immune-suppressive environment in aGSCTs likely limits immunotherapy response, as immunosuppressive macrophages inhibit T cell expansion along with EMT activation and fibroblast predominance.

Cancer-associated fibroblasts as a potential novel liquid biopsy marker in cancer patients

Cancer-associated fibroblasts (CAFs) are tissue residing cells within the tumor microenvironment (TME). Stromal CAFs have been shown to be associated with poor prognosis and tumor progression in several solid tumor entities. Although the molecular mechanisms are not fully understood yet, a critical role within the TME through direct interaction with the tumor cells as well as other cells has been proposed. While most studies on CAFs focus on stromal CAFs, recent reports highlight the possibility of detecting circulating CAFs (cCAFs) in the blood. In contrast to invasive tissue biopsies for stromal CAF characterization, liquid biopsy allows a minimally invasive isolation of cCAFs. Furthermore, liquid biopsy methods could enable continuous monitoring of cCAFs in cancer patients and therefore may present a novel biomarker for solid tumors. In this work, we present an overview of cCAF studies currently available and summarize the liquid biopsy techniques for cCAF isolation and detection. Moreover, the future research directions in the emerging field are highlighted and the potential applications of cCAFs as novel biomarkers for solid tumor patients discussed.

Mechanistic insight for T-cell exclusion by cancer-associated fibroblasts in human lung cancer

The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.

Combining spatial transcriptomics and ECM imaging in 3D for mapping cellular interactions in the tumor microenvironment

Tumors are complex ecosystems composed of malignant and non-malignant cells embedded in a dynamic extracellular matrix (ECM). In the tumor microenvironment, molecular phenotypes are controlled by cell-cell and ECM interactions in 3D cellular neighborhoods (CNs). While their inhibition can impede tumor progression, routine molecular tumor profiling fails to capture cellular interactions. Single-cell spatial transcriptomics (ST) maps receptor-ligand interactions but usually remains limited to 2D tissue sections and lacks ECM readouts. Here, we integrate 3D ST with ECM imaging in serial sections from one clinical lung carcinoma to systematically quantify molecular states, cell-cell interactions, and ECM remodeling in CN. Our integrative analysis pinpointed known immune escape and tumor invasion mechanisms, revealing several druggable drivers of tumor progression in the patient under study. This proof-of-principle study highlights the potential of in-depth CN profiling in routine clinical samples to inform microenvironment-directed therapies. A record of this paper's transparent peer review process is included in the supplemental information.

Fibroblast atlas: Shared and specific cell types across tissues

Understanding the heterogeneity of fibroblasts depends on decoding the complexity of cell subtypes, their origin, distribution, and interactions with other cells. Here, we integrated 249,156 fibroblasts from 73 studies across 10 tissues to present a single-cell atlas of fibroblasts. We provided a high-resolution classification of 18 fibroblast subtypes. In particular, we revealed a previously undescribed cell population, TSPAN8+ chromatin remodeling fibroblasts, characterized by high expression of genes with functions related to histone modification and chromatin remodeling. Moreover, TSPAN8+ chromatin remodeling fibroblasts were detectable in spatial transcriptome data and multiplexed immunofluorescence assays. Compared with other fibroblast subtypes, TSPAN8+ chromatin remodeling fibroblasts exhibited higher scores in cell differentiation and resident fibroblast, mainly interacting with endothelial cells and T cells through ligand VEGFA and receptor F2R, and their presence was associated with poor prognosis. Our analyses comprehensively defined the shared and specific characteristics of fibroblast subtypes across tissues and provided a user-friendly data portal, Fibroblast Atlas.

Benign non-immune cells in tumor microenvironment

The tumor microenvironment (TME) is a highly complex and continuous evolving ecosystem, consisting of a diverse array of cellular and non-cellular components. Among these, benign non-immune cells, including cancer-associated fibroblasts (CAFs), adipocytes, endothelial cells (ECs), pericytes (PCs), Schwann cells (SCs) and others, are crucial factors for tumor development. Benign non-immune cells within the TME interact with both tumor cells and immune cells. These interactions contribute to tumor progression through both direct contact and indirect communication. Numerous studies have highlighted the role that benign non-immune cells exert on tumor progression and potential tumor-promoting mechanisms via multiple signaling pathways and factors. However, these benign non-immune cells may play different roles across cancer types. Therefore, it is important to understand the potential roles of benign non-immune cells within the TME based on tumor heterogeneity. A deep understanding allows us to develop novel cancer therapies by targeting these cells. In this review, we will introduce several types of benign non-immune cells that exert on different cancer types according to tumor heterogeneity and their roles in the TME.

Microwave ablation of non-small cell lung cancer enhances local T-cell abundance and alters monocyte interactions

BACKGROUND

Minimally invasive thermal therapies show great prospect in non-small cell lung cancer (NSCLC) treatment. However, changes in immune cell populations following microwave ablation (MWA) in NSCLC microenvironment are not fully revealed.

OBJECTIVE

The present study was conducted to identify changes in immune cell populations and analyse dysregulated genes in immune cells after MWA in NSCLC microenvironment.

METHODS

The patients received fractionated MWA in two treatments separated by 3 weeks. Tumor biopsy samples were obtained through core-needle biopsy before each fractionated MWA procedure at the same site and used for single-cell RNA sequencing with the 10x Genomics pipeline.

RESULTS

A total of 9 major cell types were identified after MWA, which include neutrophils, T cells, B cells, monocytes, epithelial cells, chondrocytes, macrophages, tissue stem cells, and endothelial cells. After MWA, the tumor tissue exhibited an increased proportion of T cells. MWA altered gene expression in each cell cluster at the single-cell level. Cell trajectory analysis revealed that the cells at the starting point were most like T helper cells, naïve T cells, and regulatory T cells; they then developed into anergic T cells, T follicular cells, natural killer T cells, T memory cells, and exhausted T cells, and finally ended as γδ T cells and cytotoxic T cells. Moreover, after MWA, more interaction between monocytes and T cells (or B cells) were identified.

CONCLUSIONS

MWA increases local T-cell abundance and alters monocyte interactions, thereby reshaping the tumor microenvironment. This study lays a foundation for investigating dysregulated genes that may contribute to the MWA-induced immune response in NSCLC.

WHAT IS ALREADY KNOWN ON THIS TOPIC

Thermal ablation may change the immune profiles of patients by activating various steps in the cancer immunity cycle. However, changes in immune cell populations following MWA of NSCLC have not been fully reported.

WHAT THIS STUDY ADDS

After MWA, an increase in interactions between monocytes and T cells intratumorally was observed, which promoted antitumor immunity.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

The current study illuminates the MWA-caused systemic immune response in NSCLC, which may help to identify the dysregulated genes involved in the MWA-caused immune response.

CORN 2.0 - Condition Orientated Regulatory Networks 2.0

Gene regulation is a fundamental process that allows organisms to adapt to their environment and increase complexity through the action of nucleic acid-binding proteins (NBPs), such as transcription factors (TFs), which regulate specific sets of genes under distinct conditions. These regulatory interactions form transcriptional regulatory networks (TRNs), which can be further broken down into transcriptional regulatory sub-networks (TRSNs) centered around individual TFs. TRSNs are more stable and practical for analysis, making them ideal for studying gene regulation under specific conditions. Condition-Oriented Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/corn/home) is a comprehensive library of condition-based TRSNs, including those induced by natural compounds, small molecules, drug treatments, and gene perturbations. CORN 2.0 represents a significant update, associating 7540 specific conditions with 71934 TRSNs across 52 human cell lines, involving 542 transcription factors (TFs). Notably, CORN 2.0 includes 1550 natural compound-triggered TRSNs, providing a valuable resource for studying the pharmacological effects of natural products. This study demonstrates the utility of CORN in three key areas: personalized medicine, induced pluripotency transitions, and natural compound-associated pharmacology. By linking specific conditions to their corresponding TRSNs, CORN enables researchers to explore how gene regulatory networks are altered under various conditions, offering insights into disease mechanisms and potential therapeutic interventions.

Epithelial-mesenchymal transition orchestrates tumor microenvironment: current perceptions and challenges

The epithelial-mesenchymal transition (EMT) is a critical process in cancer progression, facilitating tumor cells to develop invasive traits and augmenting their migratory capabilities. EMT is primed by tumor microenvironment (TME)-derived signals, whereupon cancer cells undergoing EMT in turn remodel the TME, thereby modulating tumor progression and therapeutic response. This review discusses the mechanisms by which EMT coordinates TME dynamics, including secretion of soluble factors, direct cell contact, release of exosomes and enzymes, as well as metabolic reprogramming. Recent evidence also indicates that cells undergoing EMT may differentiate into cancer-associated fibroblasts, thereby establishing themselves as functional constituents of the TME. Elucidating the relationship between EMT and the TME offers novel perspectives for therapeutic strategies to enhance cancer treatment efficacy. Although EMT-directed therapies present significant therapeutic potential, the current lack of effective targeting approaches-attributable to EMT complexity and its microenvironmental context dependency-underscores the necessity for mechanistic investigations and translational clinical validation.

The Impact of the Tumor Microenvironment on the Effect of IL-1β Blockade in NSCLC: Biomarker Analyses from CANOPY-1 and CANOPY-N Trials

SIGNIFICANCE

Patients with NSCLC with immunosuppressive tumor features and low T-cell infiltration derive less benefit from ICI-based treatment. Biomarker analyses presented here suggest that these patients may benefit from the addition of anti-IL-1β therapy to their treatment.

Identification of a long non-coding RNA signature associated with cuproptosis for prognosis and immunotherapy response prediction in patients with lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD), the most common histotype of lung cancer, exhibits high heterogeneity due to molecular variations. Cuproptosis is a newly discovered type of cell death that is linked to copper metabolism and long non-coding RNAs (lncRNAs) may play a significant role in this process. We conducted a comprehensive analysis of lncRNA related to cuproptosis and identified a CRLscore to predict the prognosis and immune landscape for LUAD patients.

METHODS

The LUAD patient cohort obtained from TCGA database was divided into training and validation sets. A range of statistical methods were employed to identify lncRNAs associated with cuproptosis. Multivariate Cox regression was then utilized to develop the CRLscore, which was further used to construct and evaluate a nomogram. Additionally, we investigated the biological functions, gene mutations, and immune landscape.

RESULTS

A CRLscore, comprising six cuproptosis-related lncRNAs, was developed to stratify patients into high- and low-risk groups. The CRLscore demonstrated its ability to independently predict prognosis in both the training set and the validation set. Utilizing the CRLscore, we constructed a nomogram that exhibited favorable predictive efficiency. Furthermore, the cuproptosis-related lncRNAs exhibited associations with important signaling pathways such as p53 signaling, MYC Targets V1, and G2M Checkpoint. Notably, the CRLscore displayed substantial differences in somatic mutations and immune landscape. Finally, qRT-PCR results showed the significant differential expression of five cuproptosis-related lncRNAs between LUAD and normal cells.

CONCLUSION

The CRLscore could serve as a potential prognostic indicator and may predict the response to immunotherapy in LUAD patients.

Cancer associated fibroblasts in cancer development and therapy

Cancer-associated fibroblasts (CAFs) are key players in cancer development and therapy, and they exhibit multifaceted roles in the tumor microenvironment (TME). From their diverse cellular origins, CAFs undergo phenotypic and functional transformation upon interacting with tumor cells and their presence can adversely influence treatment outcomes and the severity of the cancer. Emerging evidence from single-cell RNA sequencing (scRNA-seq) studies have highlighted the heterogeneity and plasticity of CAFs, with subtypes identifiable through distinct gene expression profiles and functional properties. CAFs influence cancer development through multiple mechanisms, including regulation of extracellular matrix (ECM) remodeling, direct promotion of tumor growth through provision of metabolic support, promoting epithelial-mesenchymal transition (EMT) to enhance cancer invasiveness and growth, as well as stimulating cancer stem cell properties within the tumor. Moreover, CAFs can induce an immunosuppressive TME and contribute to therapeutic resistance. In this review, we summarize the fundamental knowledge and recent advances regarding CAFs, focusing on their sophisticated roles in cancer development and potential as therapeutic targets. We discuss various strategies to target CAFs, including ECM modulation, direct elimination, interruption of CAF-TME crosstalk, and CAF normalization, as approaches to developing more effective treatments. An improved understanding of the complex interplay between CAFs and TME is crucial for developing new and effective targeted therapies for cancer.

Single-cell RNA sequencing reveals potential therapeutic targets in the tumor microenvironment of lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC), accounting for 30% of lung cancer cases, lacks adequate research due to limited understanding of its molecular abnormalities. Our study analyzed public LUSC datasets to explore the tumor microenvironment (TME) composition using scRNA-seq from two cohorts. Applying non-negative matrix factorization, we identified unique malignant cell phenotypes, or meta-programs (MPs), based on gene expression patterns. Survival analysis revealed the clinical relevance of these MPs. Findings illuminated a TME landscape enriched with immune cells-CD8 + T, exhausted T, CD4 + T, and naive T cells-and suggested roles for myeloid cells, like cDC1 and pDCs, in LUSC progression. Different MPs highlighted the heterogeneity of malignant cells and their clinical implications. Targeting MP-specific genes may enable personalized therapy, especially for early-stage LUSC. This study offers insights into immune cell function in tumor dynamics, identifies MPs, and paves the way for novel LUSC strategies, enhancing early intervention, personalized treatment, and prognosis, ultimately improving patient outcomes.

Immune-featured stromal niches associate with response to neoadjuvant immunotherapy in oral squamous cell carcinoma

Tumor stromal cells (TSCs) play a crucial yet underexplored role in the tumor microenvironment (TME). This study uses single-cell sequencing and spatial transcriptomics on paired tumor specimens from 22 patients with oral squamous cell carcinoma (OSCC) enrolled in a randomized two-arm phase 2 trial, receiving neoadjuvant anti-PD-1 mono-immunotherapy or anti-PD-1 plus docetaxel-cisplatin-5-fluorouracil (TPF) immunochemotherapy. Single-cell analysis reveals increased TSCs within the TME of responders in immunochemotherapy. Notably, significant post-treatment upregulation of SELP+ high endothelial venules (HEVs) and APOD+ myofibroblastic cancer-associated fibroblasts (myCAFs), alongside a decline in STMN1+ capillary endothelial cells (cECs), is specific to the immunochemotherapy cohort. In contrast, MYF5+ muscle satellite cells (MSCs) are upregulated in non-responders to mono-immunotherapy. SELP+ HEVs and APOD+ myCAFs foster favorable immunomodulatory stromal niches for improved outcomes, while STMN1+ cECs and MYF5+ MSCs form immunosuppressive niches in tumor invasion regions, highlighting therapeutic targets. The trial was registered at ClinicalTrials.gov, and the registration number is NCT04649476.

The fibroinflammatory response in cancer

Fibroinflammation refers to the highly integrated fibrogenic and inflammatory responses mediated by the concerted function of fibroblasts and innate immune cells in response to tissue perturbation. This process underlies the desmoplastic remodelling of the tumour microenvironment and thus plays an important role in tumour initiation, growth and metastasis. More specifically, fibroinflammation alters the biochemical and biomechanical signalling in malignant cells to promote their proliferation and survival and further supports an immunosuppressive microenvironment by polarizing the immune status of tumours. Additionally, the presence of fibroinflammation is often associated with therapeutic resistance. As such, there is increasing interest in targeting this process to normalize the tumour microenvironment and thus enhance the treatment of solid tumours. Herein, we review advances made in unravelling the complexity of cancer-associated fibroinflammation that can inform the rational design of therapies targeting this.

ARP2/3 complex affects myofibroblast differentiation and migration in pancreatic ductal adenocarcinoma

The ARP2/3 complex, which orchestrates actin cytoskeleton organization and lamellipodia formation, has been implicated in the initiation of pancreatic ductal adenocarcinoma (PDAC). This study aims to clarify its impact on the activity of cancer-associated fibroblasts (CAFs), key players in PDAC progression, and patient outcomes. Early pancreatic carcinogenesis was modeled in p48Cre; LSL-KrasG12D mice with caerulein-induced pancreatitis, complemented by in vitro studies on human immortalized pancreatic stellate cells (PSCs) and primary PDAC-derived CAFs. Data were gained from microarray analysis, RNA sequencing (RNA-seq), and single-cell RNA sequencing (sc-RNA-seq), with subsequent bioinformatics analysis. We uncovered a specific transcriptional signature associated with fibroblast migration in early pancreatic carcinogenesis and linked it to poor survival in patients with PDAC. A pivotal role of the ARP2/3 complex in CAF migration was identified. Inhibition of the ARP2/3 complex markedly decreased CAF motility and induced significant morphological changes in vitro. Furthermore, its inhibition also hindered TGFβ1-mediated myofibroblastic CAF differentiation but had no effect on IL-1-mediated inflammatory CAF differentiation. Our findings position the ARP2/3 complex as central to the migration and differentiation of myofibroblastic CAF. Targeting this complex presents a promising new therapeutic avenue for PDAC treatment.

Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments

The tumor microenvironment (TME) plays a crucial role in orchestrating tumor cell behavior and cancer progression. Recent advances in spatial profiling technologies have uncovered novel spatial signatures, including univariate distribution patterns, bivariate spatial relationships, and higher-order structures. These signatures have the potential to revolutionize tumor mechanism and treatment. In this review, we summarize the current state of spatial signature research, highlighting computational methods to uncover spatially relevant biological significance. We discuss the impact of these advances on fundamental cancer biology and translational research, address current challenges and future research directions.

Cross-Talk Between Cancer and Its Cellular Environment-A Role in Cancer Progression

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

CENPF (+) cancer cells promote malignant progression of early-stage TP53 mutant lung adenocarcinoma

The prevention and precise treatment of early-stage lung adenocarcinoma (LUAD) characterized by small nodules (stage IA) remains a significant challenge for clinicians, which is due largely to the limited understanding of the oncogenic mechanisms spanning from preneoplasia to invasive adenocarcinoma. Our study highlights the pivotal role of cancer cells exhibiting high expression of centromere protein F (CENPF), driven by TP53 mutations, which become increasingly prevalent during the transition from preneoplasia to invasive LUAD. Biologically, cancer cells (CENPF+) exhibited robust proliferative and stem-like capabilities, thereby propelling the malignant progression of early-stage LUAD. Clinically, autoantibodies against CENPF in the serum and elevated cancer cells (CENPF+) in tissue correlated positively with the progression of early-stage LUAD, especially those in stage IA. Our findings suggest that cancer cells (CENPF+) play a central role in orchestrating the malignant evolution of LUAD and hold potential as a novel biomarker for early-stage detection and management of the disease.

Bistable dynamics of TAN-NK cells in tumor growth and control of radiotherapy-induced neutropenia in lung cancer treatment

Neutrophils play a crucial role in the innate immune response as a first line of defense in many diseases, including cancer. Tumor-associated neutrophils (TANs) can either promote or inhibit tumor growth in various steps of cancer progression via mutual interactions with cancer cells in a complex tumor microenvironment (TME). In this study, we developed and analyzed mathematical models to investigate the role of natural killer cells (NK cells) and the dynamic transition between N1 and N2 TAN phenotypes in killing cancer cells through key signaling networks and how adjuvant therapy with radiation can be used in combination to increase anti-tumor efficacy. We examined the complex immune-tumor dynamics among N1/N2 TANs, NK cells, and tumor cells, communicating through key extracellular mediators (Transforming growth factor (TGF-$ \beta $), Interferon gamma (IFN-$ \gamma $)) and intracellular regulation in the apoptosis signaling network. We developed several tumor prevention strategies to eradicate tumors, including combination (IFN-$ \gamma $, exogenous NK, TGF-$ \beta $ inhibitor) therapy and optimally-controlled ionizing radiation in a complex TME. Using this model, we investigated the fundamental mechanism of radiation-induced changes in the TME and the impact of internal and external immune composition on the tumor cell fate and their response to different treatment schedules.

SCANER: robust and sensitive identification of malignant cells from the scRNA-seq profiled tumor ecosystem

Single-cell RNA sequencing (scRNA-seq) has enabled the dissection of complex tumor ecosystems. Recognition of malignant cells as an essential step has a profound impact on downstream interpretation. However, most existing computational strategies are based on prior knowledge of canonical cell-type markers. We have developed a marker-free approach, the Seed-Cluster based Approach for NEoplastic cells Recognition (SCANER), to identify malignant cells based on significant gene expression variations caused by genomic instability. Upon analyzing different cancer types, SCANER achieved superior accuracy and robustness in identifying malignant cells, effectively addressing dropout events and tumor purity variations. Besides, SCANER can significantly detect copy number variations (CNVs) in malignant cells compared to nonmalignant cells, which is further confirmed through the paired whole exome sequencing data. In conclusion, SCANER has the potential to facilitate the biological exploration of the tumor ecosystem by accurately identifying malignant cells and it is applicable across various solid cancer types regardless of prior knowledge. SCANER is available at https://github.com/woolingxiang/SCANER.

Epigenetic modifications in early stage lung cancer: pathogenesis, biomarkers, and early diagnosis

The integration of liquid biopsy with epigenetic markers offers significant potential for early lung cancer detection and personalized treatment. Epigenetic alterations, including DNA methylation, histone modifications, and noncoding RNA changes, often precede genetic mutations and are critical in cancer progression. In this study, we explore how liquid biopsy, combined with epigenetic markers, can provide early detection of lung cancer, potentially predicting onset up to 4 years before clinical diagnosis. We discuss the challenges of targeting epigenetic regulators, which could disrupt cellular balance if overexploited, and the need for maintaining key gene expressions in therapeutic applications. This review highlights the promise and challenges of using liquid biopsy and epigenetic markers for early-stage lung cancer diagnosis, with a focus on optimizing treatment strategies for personalized and precision medicine.

scCrab: A Reference-Guided Cancer Cell Identification Method based on Bayesian Neural Networks

Cancer is a significant global public health concern, where early detection can greatly enhance curative outcomes. Therefore, the identification of cancer cells holds significant importance as the primary method for cancer diagnosis. The advancement of single-cell RNA sequencing (scRNA-seq) technology has made it possible to address the problem of cancer cell identification at the single-cell level more efficiently with computational methods, as opposed to the time-consuming and less reproducible manual identification methods. However, existing computational methods have shown suboptimal identification performance and a lack of capability to incorporate external reference data as prior information. Here, we propose scCrab, a reference-guided automatic cancer cell identification method, which performs ensemble learning based on a Bayesian neural network (BNN) with multi-head self-attention mechanisms and a linear regression model. Through a series of experiments on various datasets, we systematically validated the superior performance of scCrab in both intra- and inter-dataset predictions. Besides, we demonstrated the robustness of scCrab to dropout rate and sample size, and conducted ablation experiments to investigate the contributions of each component in scCrab. Furthermore, as a dedicated model for cancer cell identification, scCrab effectively captures cancer-related biological significance during the identification process.

Deciphering key roles of B cells in prognostication and tailored therapeutic strategies for lung adenocarcinoma: a multi-omics and machine learning approach towards predictive, preventive, and personalized treatment strategies

Background

Lung adenocarcinoma (LUAD) remains a significant global health challenge, with an urgent need for innovative predictive, preventive, and personalized medicine (PPPM) strategies to improve patient outcomes. This study leveraged multi-omics and machine learning approaches to uncover the prognostic roles of B cells in LUAD, thereby reinforcing the PPPM approach.

Methods

We integrated multi-omics data, including bulk RNA, ATAC-seq, single-cell RNA, and spatial transcriptomics sequencing, to characterize the B cell landscape in LUAD within the PPPM framework. Subsequently, we developed an integrative machine learning program that generated the Scissor+ related B cell score (SRBS). This score was validated in the training and validation sets, and its prognostic value was assessed along with clinical features to develop predictive nomograms. This study further assessed the role of SRBS and SRBS genes in response to immunotherapy and identified personalized drug targets for distinct risk subgroups, with gene expression verified experimentally to ensure tailored medical interventions.

Results

Our analysis identified 79 Scissor+ B cell genes linked to LUAD prognosis, supporting the predictive aspect of PPPM. The SRBS model, which utilizes multiple machine learning algorithms, performed excellently in predicting prognosis and clinical transformation, embodying the preventive and personalized aspects of PPPM. Multifactorial analysis confirmed that SRBS was an independent prognostic factor. We observed varying biological functions and immune cell infiltration in the tumor immune microenvironment (TIME) between the high- and low-SRBS groups, underscoring personalized treatment approaches. Notably, patients with elevated SRBS may exhibit resistance to immunotherapy but show increased sensitivity to chemotherapy and targeted therapies. Additionally, we found that LDHA, as an SRBS gene with significant clinical implications, may regulate the sensitivity of LUAD cells to cisplatin.

Conclusion

This study presents a B cell-associated gene signature that serves as a prognostic marker to facilitate personalized treatment for patients with LUAD, adhering to the principles of PPPM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00390-4.

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.

Intratumoral Heterogeneity and Immune Microenvironment in Hepatoblastoma Revealed by Single-Cell RNA Sequencing

Hepatoblastoma (HB) is a common paediatric liver malignancy characterised by significant intratumoral heterogeneity and a complex tumour microenvironment (TME). Using single-cell RNA sequencing (scRNA-seq), we analysed 43,592 cells from three tumour regions and adjacent normal tissue of an HB patient. Our study revealed distinct cellular compositions and varying degrees of malignancy across different tumour regions, with the T1 region showing the highest malignancy and overexpression of HMGB2 and TOP2A. Survival analysis demonstrated that high HMGB2 expression is associated with poor prognosis and increased recurrence, suggesting its potential as a prognostic marker. Additionally, we identified a diverse immune microenvironment enriched with regulatory T cells (Tregs) and CD8+ effector memory T cells (Tem), indicating potential immune evasion mechanisms. Notably, CTLA-4 and PD-1 were highly expressed in Tregs and Tem cells, highlighting their potential as immunotherapy targets. Myeloid cells, including Kupffer cells and dendritic cells, also exhibited distinct functional roles in different tumour regions. This study provides the first comprehensive single-cell atlas of HB, revealing critical insights into its intratumoral heterogeneity and immune microenvironment. Our findings not only advance the understanding of HB biology but also offer new directions for precision medicine, including the development of targeted therapies and immunotherapeutic strategies to improve patient outcomes.

Dissecting tumor cell programs through group biology estimation in clinical single-cell transcriptomics

With the growth of clinical cancer single-cell RNA sequencing studies, robust differential expression methods for case/control analyses (e.g., treatment responders vs. non-responders) using gene signatures are pivotal to nominate hypotheses for further investigation. However, many commonly used methods produce a large number of false positives, do not adequately represent the patient-specific hierarchical structure of clinical single-cell RNA sequencing data, or account for sample-driven confounders. Here, we present a nonparametric statistical method, BEANIE, for differential expression of gene signatures between clinically relevant groups that addresses these issues. We demonstrate its use in simulated and real-world clinical datasets in breast cancer, lung cancer and melanoma. BEANIE outperforms existing methods in specificity while maintaining sensitivity, as demonstrated in simulations. Overall, BEANIE provides a methodological strategy to inform biological insights into unique and shared differentially expressed gene signatures across different tumor states, with utility in single-study, meta-analysis, and cross-validation across cell types.

Identifying macrophage-associated subtypes in patients with serous ovarian cancer and exploring potential personalized therapeutic drugs using combined single-cell and bulk RNA sequencing omics

Purpose

We aimed to analyze the sensitivity of patients to chemotherapy drugs and actively explore potential new intervention targets, providing an essential reference for personalized treatment.

Methods

Candidate markers with significant differential expression in macrophages were identified by analyzing gene expression at the single-cell level. A weighted gene co-expression network (WGCN) was constructed on the GSE26712 dataset to explore the modules most relevant to macrophages. Differentially expressed genes for specific markers were identified. A multi-factor regulatory network was constructed based on single-cell dataset markers screening, differentially expressed genes, and genes commonly present in WGCNA modules. Different macrophage subtypes were identified using this network. Machine learning was used to filter and predict the markers' drug sensitivity, and the potential therapeutic compounds for specific markers were screened.

Results

We identified 14 and 17 of M1 and M2 macrophage candidate markers, respectively. In the multi-factor regulatory network of M1 macrophages, 6 out of 14 markers recognized 159 transcription factors (TFs) and 48 micro RNAs (miRNAs), whereas 13 of 17 markers recognized 191 TFs and 182 miRNAs in the multi-factor regulatory network of M2 macrophages. Filtering of the identified differentially expressed genes using random forests yielded 15 M1 and M2 macrophage-specific markers. Drug sensitivity prediction analysis and in vitro experiments revealed the close association of these markers with common chemotherapy drug sensitivity.

Conclusion

We identified specific M1 and M2 macrophage markers and found potential therapeutic compounds (dasatinib and afatinib) in these specific markers. These potential therapeutic compounds provide insight into the underlying mechanisms of serous ovarian cancer (OC) and inspire more effective treatment methods.

ANLN promotes head and neck squamous cell carcinoma progression by upregulating PD-L1 via the ERK-MAPK pathway

Anillin (ANLN) is a highly conserved protein involved in cytokinesis and cytoskeletal remodeling. This study investigates the role of ANLN in head and neck squamous cell carcinoma (HNSCC) progression and its impact on the tumor immune microenvironment, with a focus on the combination of ANLN silencing and anti-programmed cell death protein 1 (PD-1) therapy. Through in vitro and in vivo experiments, along with clinical specimen analysis, we discovered that silencing ANLN not only inhibits the malignant progression of HNSCC but also reduces the activation of the extracellular signal-regulated kinase-mitogen-activated protein kinase (ERK-MAPK) signaling pathway and decreases programmed death ligand-1 (PD-L1) expression. Integrating ANLN silencing with anti-PD-1 monoclonal antibody treatment significantly enhances the activation of infiltrating CD8+ T cells, leading to marked tumor growth suppression. Our findings highlight the potential of ANLN as a therapeutic target in HNSCC, providing a foundation for developing innovative and effective combined treatment strategies.

A novel identified epithelial ligand-receptor-associated gene signature highlights POPDC3 as a potential therapy target for non-small cell lung cancer

The tumor microenvironment (TME) is pivotal in non-small cell lung cancer (NSCLC) progression, influencing drug resistance and immune cell behavior through complex ligand-receptor (LR) interactions. This study developed an epithelial LR-related prognostic risk score (LRrisk) to identify biomarkers and targets in NSCLC. We identified twenty epithelial LRs with significant prognostic implications and delineated three molecular NSCLC subtypes with distinct outcomes, pathological characteristics, biological pathways, and immune profiles. The LRrisk model was constructed using twelve differentially expressed ligand-receptor interaction-related genes (LRGs), with a focus on POPDC3 (popeye domain-containing protein 3), which was overexpressed in NSCLC cells. Functional assays revealed that POPDC3 knockdown reduced cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), while its overexpression promoted cancerous activities. In vivo, POPDC3 silencing hindered, and its overexpression accelerated the growth of NSCLC xenografts in nude mice. Additionally, high expression levels of POPDC3 in NSCLC tissues were associated with enhanced CD4+ T cell infiltration and increased PD-1 expression within the TME. Moreover, ectopic POPDC3 overexpression in C57BL/6 J mouse Lewis lung carcinoma (LLC) xenografts enhanced CD4+ T cell infiltration and PD-1 expression in the TME. This research establishes a robust epithelial LR-related signature, highlighting POPDC3 as a critical facilitator of NSCLC progression and a potential therapeutic target.

Single-cell transcriptomes reveal cell-type-specific and sample-specific gene function in human cancer

Accurate annotation of gene function in individual samples and even in each cell type is essential for understanding the pathogenesis of cancers. Single-cell RNA-sequencing (scRNA-seq) provides unprecedented resolution to decipher gene function. In order to explore how scRNA-seq contributes to the understanding of gene function in cancers, we constructed an assessment framework based on co-expression network and neighbor-voting method using 116,814 cells. Compared with bulk transcriptome, scRNA-seq recalled more experimentally verified gene functions. Surprisingly, scRNA-seq revealed cell-type-specific functions, especially in immune cells, whose expression profile recalled immune-related functions that were not discovered in cancer cells. Furthermore, scRNA-seq discovered sample-specific functions, highlighting that it provided sample-specific information. We also explored factors affecting the performance of gene function prediction. We found that 500 or more cells should be considered in the prediction with scRNA-seq, and that scRNA-seq datasets generated from 10x Genomics platform had a better performance than those from Smart-seq2. Collectively, we compared the prediction performance of bulk data and scRNA-seq data from multiple perspectives, revealing the irreplaceable role of single-cell sequencing in decoding the biological progresses in which the gene involved.

Defining the regulatory logic of breast cancer using single-cell epigenetic and transcriptome profiling

Annotation of cis-regulatory elements that drive transcriptional dysregulation in cancer cells is critical to understanding tumor biology. Herein, we present matched chromatin accessibility (single-cell assay for transposase-accessible chromatin by sequencing [scATAC-seq]) and transcriptome (single-cell RNA sequencing [scRNA-seq]) profiles at single-cell resolution from human breast tumors and healthy mammary tissues processed immediately following surgical resection. We identify the most likely cell of origin for subtype-specific breast tumors and implement linear mixed-effects modeling to quantify associations between regulatory elements and gene expression in malignant versus normal cells. These data unveil cancer-specific regulatory elements and putative silencer-to-enhancer switching events in cells that lead to the upregulation of clinically relevant oncogenes. In addition, we generate matched scATAC-seq and scRNA-seq profiles for breast cancer cell lines, revealing a conserved oncogenic gene expression program between in vitro and in vivo cells. This work highlights the importance of non-coding regulatory mechanisms that underlie oncogenic processes and the ability of single-cell multi-omics to define the regulatory logic of cancer cells.

Single-Cell RNA Sequencing in Unraveling Acquired Resistance to EGFR-TKIs in Non-Small Cell Lung Cancer: New Perspectives

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have demonstrated remarkable efficacy in treating non-small cell lung cancer (NSCLC), but acquired resistance greatly reduces efficacy and poses a significant challenge to patients. While numerous studies have investigated the mechanisms underlying EGFR-TKI resistance, its complexity and diversity make the existing understanding still incomplete. Traditional approaches frequently struggle to adequately reveal the process of drug resistance development through mean value analysis at the overall cellular level. In recent years, the rapid development of single-cell RNA sequencing technology has introduced a transformative method for analyzing gene expression changes within tumor cells at a single-cell resolution. It not only deepens our understanding of the tumor microenvironment and cellular heterogeneity associated with EGFR-TKI resistance but also identifies potential biomarkers of resistance. In this review, we highlight the critical role of single-cell RNA sequencing in lung cancer research, with a particular focus on its application to exploring the mechanisms of EGFR-TKI-acquired resistance in NSCLC. We emphasize its potential for elucidating the complexity of drug resistance mechanism and its promise in informing more precise and personalized treatment strategies. Ultimately, this approach aims to advance NSCLC treatment toward a new era of precision medicine.

Promotion Mechanisms of Stromal Cell-Mediated Lung Cancer Development Within Tumor Microenvironment

Lung cancer, with its high incidence and mortality rates, has garnered significant attention in the medical community. The tumor microenvironment (TME), composed of tumor cells, stromal cells, extracellular matrix, surrounding blood vessels, and other signaling molecules, plays a pivotal role in the development of lung cancer. Stromal cells within the TME hold potential as therapeutic targets for lung cancer treatment. However, the precise and comprehensive mechanisms by which stromal cells contribute to lung cancer progression have not been fully elucidated. This review aims to explore the mechanisms through which stromal cells in the tumor microenvironment promote lung cancer development, with a particular focus on how immune cells, tumor-associated fibroblasts, and endothelial cells contribute to immune suppression, inflammation, and angiogenesis. The goal is to provide new insights and potential strategies for the diagnosis and treatment of lung cancer.

Transcriptomic profiles of single-cell autophagy-related genes (ATGs) in lung diseases

Autophagy related genes (ATGs) play essential roles in maintaining cellular functions, although biological and pathological alterations of ATG phenotypes remain poorly understood. To address this knowledge gap, we utilized the single-cell sequencing technology to elucidate the transcriptomic atlas of ATGs in lung diseases, with a focus on lung epithelium and lymphocytes. This study conducted a comprehensive investigation into RNA profiles of ATGs in the lung tissues obtained from healthy subjects and patients with different lung diseases through single-cell RNA sequencing (scRNA-seq), including COVID-19 related acute lung damage, idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD), systemic sclerosis (SSC), and lung adenocarcinoma (LUAD). Our findings revealed significant variations of ATGs expression across lung epithelial cell subsets, e.g., over-expression of MAPK8 in basal cells, ATG10 in club cells, and BCL2 in a goblet cell subset. The changes of autophagy-related pathways varied between lung epithelial and lymphocyte subsets. We identified the disease-associated changes in ATG expression, including significant alterations in BCL2, BCL2L1, PRKCD, and PRKCQ in inflammatory lung diseases (COPD and IPF), and MAP2K7, MAPK3, and RHEB in lung cancer (LUAD), as compared to normal lung tissues. Key ligand-receptor pairs (e.g., CD6-ALCAM, CD99-CD99) and signaling pathways (e.g., APP, CD74) might serve as biomarkers for lung diseases. To evaluate ATGs responses to external challenges, we examined ATGs expression in different epithelial cell lines exposed to cigarette smoking extract (CSE), lysophosphatidylcholine (lysoPC), lipopolysaccharide (LPS), and cholesterol at various doses and durations. Notable changes were observed in CFLAR, EIF2S1, PPP2CA, and PPP2CB in A549 and H1299 against CSE and LPS. The heterogeneity of ATGs expression was dependent on cell subsets, pathologic conditions, and challenges, as well as varied among cellular phenotypes, functions, and behaviors, and the severity of lung diseases. In conclusion, our data might provide new insights into the roles of ATGs in epithelial biology and pulmonary disease pathogenesis, with implications for disease progression and prognosis.

B cells in non-lymphoid tissues

B cells have long been understood to be drivers of both humoral and cellular immunity. Recent advances underscore this importance but also indicate that in infection, inflammatory disease and cancer, B cells function directly at sites of inflammation and form tissue-resident memory populations. The spatial organization and cellular niches of tissue B cells have profound effects on their function and on disease outcome, as well as on patient response to therapy. Here we review the role of B cells in peripheral tissues in homeostasis and disease, and discuss the newly identified cellular and molecular signals that are involved in regulating their activity. We integrate emerging data from multi-omic human studies with experimental models to propose a framework for B cell function in tissue inflammation and homeostasis.

Advancements in single-cell RNA sequencing and spatial transcriptomics: transforming biomedical research

In recent years, significant advancements in biochemistry, materials science, engineering, and computer-aided testing have driven the development of high-throughput tools for profiling genetic information. Single-cell RNA sequencing (scRNA-seq) technologies have established themselves as key tools for dissecting genetic sequences at the level of single cells. These technologies reveal cellular diversity and allow for the exploration of cell states and transformations with exceptional resolution. Unlike bulk sequencing, which provides population-averaged data, scRNA-seq can detect cell subtypes or gene expression variations that would otherwise be overlooked. However, a key limitation of scRNA-seq is its inability to preserve spatial information about the RNA transcriptome, as the process requires tissue dissociation and cell isolation. Spatial transcriptomics is a pivotal advancement in medical biotechnology, facilitating the identification of molecules such as RNA in their original spatial context within tissue sections at the single-cell level. This capability offers a substantial advantage over traditional single-cell sequencing techniques. Spatial transcriptomics offers valuable insights into a wide range of biomedical fields, including neurology, embryology, cancer research, immunology, and histology. This review highlights single-cell sequencing approaches, recent technological developments, associated challenges, various techniques for expression data analysis, and their applications in disciplines such as cancer research, microbiology, neuroscience, reproductive biology, and immunology. It highlights the critical role of single-cell sequencing tools in characterizing the dynamic nature of individual cells.

SELP+ TEC:CD8+ T cell crosstalk associates with improved radiotherapy efficacy in cervical cancer

P-selectin (SELP) expression in tumor cells has been implicated in promoting tumor progression and treatment resistance across various cancers. However, our prior study identified SELP expression in a specific subpopulation of endothelial cells within cervical cancer (CC) and potentially linked to anti-cancer immune response. The precise mechanisms by which SELP influences anti-cancer immunity and its involvement in radiotherapy response in CC, however, remain elusive. To address these gaps, this study analyzed tumor tissue samples from 205 CC patients undergoing radiotherapy, scRNA-seq data from 42,159 cells of eight patients, and bulk RNA-sequencing data from 187 radiotherapy-treated patients. The results revealed that elevated SELP expression in tumor endothelial cells (TECs) was significantly correlated with improved survival outcomes in patients treated with radiotherapy. The SELPhigh group exhibited a prominent enrichment of immune-related pathways, coupled with a diminished enrichment in epithelial cell proliferation and angiogenesis pathways. Notably, this group demonstrated increased infiltration of CD8+ T cells and enhanced expression of chemokine receptors, including ACKR1. Furthermore, our data suggest that SELP+ TECs engage in crosstalk with CD8+ T cells via the ACKR1-CCL5 axis, which is associated with improved radiotherapy efficacy. In conclusion, these findings underscore the pivotal role of SELP+ TEC:CD8+ T cell interactions through the ACKR1-CCL5 pathway in enhancing radiotherapy response in CC. Targeting this crosstalk may offer novel therapeutic strategies to mitigate treatment resistance and improve patient survival.

Metabolic Singularities in Microsatellite-Stable Colorectal Cancer: Identifying Key Players in Immunosuppression to Improve the Immunotherapy Response

Although immune checkpoint inhibitor (ICI) therapy is currently the standard of care in microsatellite-unstable (MSI) metastatic colorectal cancer (CRC), ICI therapy, alone or in combination with other therapies, is not a treatment approach in microsatellite-stable (MSS) CRC, which is present in 95% of patients. In this review, we focus on metabolic singularities-at the transcriptomic (either bulk or single cell), proteomic, and post-translational modification levels-that induce immunosuppression in cancer and specifically in MSS CRC. First, we evaluate the current efficacy of ICIs in limited and metastatic disease in MSS CRC. Second, we discuss the latest findings on the potential biomarkers for evaluating ICI efficacy in MSS CRC using strict REMARK criteria. Third, we review the current evidence on metabolic patterns in CRC tumors and immune cell metabolism to advance our understanding of metabolic crosstalk and to pave the way for the development of combination strategies to enhance ICI efficacy.

Functional heterogeneity of fibroblasts in primary tumors and metastases

Cancer-associated fibroblasts (CAFs) are abundant components of the tumor microenvironment (TME) of most solid malignancies and have emerged as key regulators of cancer progression and therapy response. Although recent technological advances have uncovered substantial CAF molecular heterogeneity at the single-cell level, defining functional roles for most described CAF populations remains challenging. With the aim of bridging CAF molecular and functional heterogeneity, this review focuses on recently identified functional interactions of CAF subtypes with malignant cells, immune cells, and other stromal cells in primary tumors and metastases. Dissecting the heterogeneous functional crosstalk of specific CAF populations with other components is starting to uncover candidate combinatorial strategies for therapeutically targeting the TME and cancer progression.

Nicotinamide N-methyltransferase negatively regulates metastasis-promoting property of cancer-associated fibroblasts in lung adenocarcinoma

BACKGROUND

Recurrence and metastasis remain significant challenges in lung adenocarcinoma (LUAD) after radical resection. The mechanisms behind the recurrence and metastasis of LUAD remain elusive, and deregulated cellular metabolism is suspected to play a significant role. This study explores the metabolic and epigenetic regulation mediated by nicotinamide N-methyl transferase (NNMT) in LUAD.

METHODS

Untargeted metabolomic analyses were performed to detect metabolism irregularities. Single-cell RNA sequencing (RNA-seq) databases and multiplex immunofluorescence analysis were used to identify the location of NNMT within the tumor microenvironment. The biological functions of NNMT were investigated both in vitro and in vivo, with RNA-seq and chromatin immunoprecipitation-PCR providing insights into underlying mechanisms. Finally, single-cell RNA-seq data and immunohistochemistry of primary tumors were analyzed to validate the main findings.

RESULTS

Untargeted metabolomic analyses revealed metabolic aberrations in amino acids, organic acids, lipids, and nicotinamide pathways, which are linked to metastasis of non-small cell lung cancer. NNMT is a key enzyme in nicotinamide metabolism, and we found the bulk tissue mRNA level of NNMT gene was inversely associated with LUAD metastasis. NNMT was proved to be predominantly expressed in cancer-associated fibroblasts (CAFs) within the stromal regions of LUAD, and a low stromal NNMT expression was identified as a predictor of poor disease-free survival following radical resection of LUAD. The isolation and primary culture of CAFs from LUAD enabled in vitro and in vivo experiments, which confirmed that NNMT negatively regulated the metastasis-promoting properties of CAFs in LUAD. Mechanistically, the downregulation of NNMT led to an increase in intracellular methyl groups by reducing the activity of the methionine cycle, resulting in heightened methylation at H3K4me3. This alteration triggered the upregulation of genes involved in extracellular matrix remodeling in CAFs, including those encoding collagens, integrins, laminins, and matrix metalloproteinases, thereby facilitating cancer cell invasion and metastasis. Reanalysis of single-cell RNA-seq data and immunohistochemistry assays of primary LUAD tissues substantiated NNMT's negative regulation of these genes in CAFs.

CONCLUSIONS

This study provides novel insights into the metabolic and epigenetic regulatory functions of NNMT in CAFs, expanding the current understanding of LUAD metastasis regulation and suggesting potential avenues for future research and therapeutic development.

Identification of an Amino Acid Metabolism Reprogramming Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Colon Cancer

Colon cancer ranked third among the most frequently diagnosed cancers worldwide. Amino acid metabolic reprogramming was related to the occurrence and development of colon cancer. We looked for the amino acid metabolism genes (AMGs) associated with amino acid metabolism from molecular signatures database as prognostic markers and constructed amino acid metabolism scoring model (AMS). According to AMS, the patients were divided into high AMS and low AMS groups, and the prognostic characteristics, molecular phenotypes, somatic cell mutation characteristics, immune cell infiltration characteristics, and immunotherapy effect of the two groups were systematically analyzed. Finally, the compounds targeting AMGs were also screened. We screen out 6 prognostic AMGs (P < 0.05) and construct an AMS model based on them. K-M curve indicated that OS in low AMS group was significantly higher than that in high group (P < 0.05), which were validated in multiple datasets. And different AMS groups had different molecular phenotypes, somatic cell mutation characteristics and immune cell infiltration characteristics. Low AMS group had a better effect for immunotherapy. In addition, we predicted potential therapeutic compounds that could bind to AMGs target proteins. AMS model can be used as a hierarchical tool to evaluate the prognosis, immune infiltration characteristics and immunotherapy response ability of colon cancer. And the compounds screened based on AMGs may become new anti-tumor drugs.

Fibroblastic reticular cells generate protective intratumoral T cell environments in lung cancer

Stringent control of T cell activity in the tumor microenvironment is essential for the generation of protective antitumor immunity. However, the identity, differentiation, and functions of the cells that create critical fibroblastic niches promoting tumor-infiltrating T cells remain elusive. Here, we show that CCL19-expressing fibroblastic reticular cells (FRCs) generate interconnected T cell environments (TEs) in human non-small cell lung cancer, including tertiary lymphoid structures and T cell tracks. Analysis of the FRC-T cell interactome in TEs indicated molecular networks regulating niche-specific differentiation of CCL19-expressing fibroblasts and T cell activation pathways. Single-cell transcriptomics and cell fate-mapping analyses in mice confirmed that FRCs in TEs originate from mural and adventitial progenitors. Ablation of intratumoral FRC precursors decreased antitumor T cell activity, resulting in reduced tumor control during coronavirus vector-based immunotherapy. In summary, specialized FRC niches in the tumor microenvironment govern the quality and extent of antitumor T cell immunity.