Cancer-associated fibroblast phenotypes are associated with patient outcome in non-small cell lung cancer

Tumor organoids in cancer medicine: from model systems to natural compound screening

CONTEXT

The advent of tissue engineering and biomedical techniques has significantly advanced the development of three-dimensional (3D) cell culture systems, particularly tumor organoids. These self-assembled 3D cell clusters closely replicate the histopathological, genetic, and phenotypic characteristics of primary tissues, making them invaluable tools in cancer research and drug screening.

OBJECTIVE

This review addresses the challenges in developing in vitro models that accurately reflect tumor heterogeneity and explores the application of tumor organoids in cancer research, with a specific focus on the screening of natural products for antitumor therapies.

METHODS

This review synthesizes information from major databases, including Chemical Abstracts, Medicinal and Aromatic Plants Abstracts, ScienceDirect, Google Scholar, Scopus, PubMed and Springer Link. Publications were selected without date restrictions, using terms such as 'organoid', 'natural product', 'pharmacological', 'extract', 'nanomaterial' and 'traditional uses'. Articles related to agriculture, ecology, synthetic work or published in languages other than English were excluded.

RESULTS AND CONCLUSIONS

The review identifies key challenges related to the efficiency and variability of organoid generation and discusses ongoing efforts to enhance their predictive capabilities in drug screening and personalized medicine. Recent studies utilizing patient-derived organoid models for natural compound screening are highlighted, demonstrating the potential of these models in developing new classes of anticancer agents. The integration of natural products with patient-derived organoid models presents a promising approach for discovering novel anticancer compounds and elucidating their mechanisms of action.

A microfluidic co-culture platform for lung cancer cells electrotaxis study under the existence of stromal cells

Tumor metastasis is an important reason for the poor prognosis and high mortality in cancer patients. As major component of stromal cells in tumor microenvironment, cancer-associated fibroblasts (CAFs) secreted various factors to promote tumor metastasis. Studies have indicated that endogenous direct current electric field (dcEF) around tumor tissue induced directional migration of cancer cells. However, the regulatory effect of CAFs on cancer migration under dcEF stimulation is still unknown. In this study, a two-layers polydimethylsiloxane (PDMS)-based microfluidic chip was fabricated. The introduction of concave structures achieved the non-contacted co-culture of different cell types, and parallel channels in the chip provided stable and homogeneous dcEF. Cells electrotactic response was evaluated under co-culture circumstance. The results showed that CAFs exhibited directional migration towards anode under dcEF stimulation, while A549 cells had a trend of directional migration towards cathode. The co-existence of CAFs and dcEF significantly enhanced the motility and cathodal migration of A549 cells, suggesting synergistic influences of chemotaxis from CAFs and electrotaxis from dcEF stimulation. Moreover, we demonstrated that lung normal fibroblasts acquired CAFs properties after stimulated by dcEF, characterizing by increasing gene expression of α-SMA and IL-6. Overall, Our device and study provide new insight for tumor electrotaxis in complex microenvironment.

Genetic variants of FER and SULF1 in the fibroblast-related genes are associated with non-small-cell lung cancer survival

Fibroblasts are important components in the tumor microenvironment and can affect tumor progression and metastasis. However, the roles of genetic variants of the fibroblast-related genes (FRGs) in the prognosis of non-small-cell lung cancer (NSCLC) patients have not been reported. Therefore, we investigated the associations between 26,544 single nucleotide polymorphisms (SNPs) in 291 FRGs and survival of NSCLC patients from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. In Cox regression multivariable analysis, we found that 661 SNPs were associated with NSCLC overall survival (OS). Then we validated these SNPs in another independent replication dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. Finally, we identified two independent SNPs (i.e., FER rs7716388 A>G and SULF1 rs11785839 G>C) that remained significantly associated with NSCLC survival with hazards ratios (HRs) of 0.87 (95% confidence interval [CI] = 0.77-0.98, p = 0.018) and 0.88 (95% CI = 0.79-0.99, p = 0.033), respectively. Combined analysis for these two SNPs showed that the number of protective alleles was associated with better OS and disease-specific survival. Expression quantitative trait loci analysis indicated that the FER rs7716388 G allele was associated with the up-regulation of FER mRNA expression levels in lung tissue. Our results indicated that these two functional SNPs in the FRGs may be prognostic biomarkers for the prognosis of NSCLC patients, and the possible mechanism may be through modulating the expression of their corresponding genes.

The function of microRNA related to cancer-associated fibroblasts in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant tumor characterized by a poor prognosis. A prominent feature of PDAC is the rich and dense stroma present in the tumor microenvironment (TME), which significantly hinders drug penetration. Cancer-associated fibroblasts (CAFs), activated fibroblasts originating from various cell sources, including pancreatic stellate cells (PSCs) and mesenchymal stem cells (MSCs), play a critical role in PDAC progression and TME formation. MicroRNAs (miRNAs) are small, single-stranded non-coding RNA molecules that are frequently involved in tumorigenesis and progression, exhibiting either oncolytic or oncogenic activity. Increasing evidence suggests that aberrant expression of miRNAs can mediate interactions between cancer cells and CAFs, thereby providing novel therapeutic targets for PDAC treatment. In this review, we will focus on the potential roles of miRNAs that target CAFs or CAFs-derived exosomes in PDAC progression, highlighting the feasibility of therapeutic strategies aimed at restoring aberrantly expressed miRNAs associated with CAFs, offering new pathways for the clinical management of PDAC.

High content imaging shows distinct macrophage and dendritic cell phenotypes for psoriasis and atopic dermatitis

Psoriasis (Pso) and atopic dermatitis (AD) are chronic inflammatory skin diseases with distinct but also shared immunological features. Assessment of the feasibility of high content immunohistochemistry to identify distinct immune responses in skin biopsies from patients with chronic inflammatory skin diseases. While principal component analysis (PCA) based on the inflammatory marker profile discriminated healthy subjects from patients, it did not differ between Pso and AD. Single-cell phenotyping of high content immunohistochemistry images showed modest disease-specific differences for T cell populations in the number of Th1 T cells and γδT cells. Strong differences in macrophage and dendritic cell (DC) populations were observed whereby in AD disease-specific DCs with antiviral properties and anti-inflammatory macrophages were seen. Additional differences between Pso and AD were seen with the more frequent epidermal localization of CD8+ T cells in Pso and DCs in AD. Consequently, high content immunohistochemistry clearly discriminated AD from Pso based on macrophage and DC phenotype. Due to their phenotypic flexibility macrophages and DCs strongly reflect the immunological environment and serve to highlight disease-specific and -defining pathomechanisms and may serve to identify new drug targets.

Interpretable niche-based cell‒cell communication inference using multi-view graph neural networks

Cell‒cell communication (CCC) is a fundamental biological process for the harmonious functioning of biological systems. Increasing evidence indicates that cells of the same type or cluster may exhibit different interaction patterns under varying niches, yet most prevailing methods perform CCC inference at the cell type or cluster level while disregarding niche heterogeneity. Here we introduce the Spatial Transcriptomics-based cell‒cell Communication And Subtype Exploration (STCase) tool, which can describe CCC events at the single-cell/spot level based on spatial transcriptomics (ST). STCase includes an interpretable multi-view graph neural network via CCC-aware attention to identify niches for each cell type and uncover niche-specific CCC events. We show that STCase outperforms state-of-the-art approaches and accurately captures reported immune-related CCC events in human bronchial glands. We also identify three distinct niches of oral squamous cell carcinoma that may be obscured by agglomerative methods, and discover niche-specific CCC events that could influence tumor prognosis.

Tumour and microenvironment crosstalk in NSCLC progression and response to therapy

The treatment landscape of non-small-cell lung cancer (NSCLC) is evolving rapidly, driven by advances in the development of targeted agents and immunotherapies. Despite this progress, some patients have suboptimal responses to treatment, highlighting the need for new therapeutic strategies. In the past decade, the important role of the tumour microenvironment (TME) in NSCLC progression, metastatic dissemination and response to treatment has become increasingly evident. Understanding the complexity of the TME and its interactions with NSCLC can propel efforts to improve current treatment modalities, overcome resistance and develop new treatments, which will ultimately improve the outcomes of patients. In this Review, we provide a comprehensive view of the NSCLC TME, examining its components and highlighting distinct archetypes characterized by spatial niches within and surrounding tumour nests, which form complex neighbourhoods. Next, we explore the interactions within these components, focusing on how inflammation and immunosuppression shape the dynamics of the NSCLC TME. We also address the emerging influences of patient-related factors, such as ageing, sex and health disparities, on the NSCLC-TME crosstalk. Finally, we discuss how various therapeutic strategies interact with and are influenced by the TME in NSCLC. Overall, we emphasize the interconnectedness of these elements and how they influence therapeutic outcomes and tumour progression.

Cancer-on-a-chip for precision cancer medicine

Many cancer therapies fail in clinical trials despite showing potent efficacy in preclinical studies. One of the key reasons is the adopted preclinical models cannot recapitulate the complex tumor microenvironment (TME) and reflect the heterogeneity and patient specificity in human cancer. Cancer-on-a-chip (CoC) microphysiological systems can closely mimic the complex anatomical features and microenvironment interactions in an actual tumor, enabling more accurate disease modeling and therapy testing. This review article concisely summarizes and highlights the state-of-the-art progresses in CoC development for modeling critical TME compartments including the tumor vasculature, stromal and immune niche, as well as its applications in therapying screening. Current dilemma in cancer therapy development demonstrates that future preclinical models should reflect patient specific pathophysiology and heterogeneity with high accuracy and enable high-throughput screening for anticancer drug discovery and development. Therefore, CoC should be evolved as well. We explore future directions and discuss the pathway to develop the next generation of CoC models for precision cancer medicine, such as patient-derived chip, organoids-on-a-chip, and multi-organs-on-a-chip with high fidelity. We also discuss how the integration of sensors and microenvironmental control modules can provide a more comprehensive investigation of disease mechanisms and therapies. Next, we outline the roadmap of future standardization and translation of CoC technology toward real-world applications in pharmaceutical development and clinical settings for precision cancer medicine and the practical challenges and ethical concerns. Finally, we overview how applying advanced artificial intelligence tools and computational models could exploit CoC-derived data and augment the analytical ability of CoC.

Conserved spatial subtypes and cellular neighborhoods of cancer-associated fibroblasts revealed by single-cell spatial multi-omics

Cancer-associated fibroblasts (CAFs) are a multifaceted cell population essential for shaping the tumor microenvironment (TME) and influencing therapy responses. Characterizing the spatial organization and interactions of CAFs within complex tissue environments provides critical insights into tumor biology and immunobiology. In this study, through integrative analyses of over 14 million cells from 10 cancer types across 7 spatial transcriptomics and proteomics platforms, we discover, validate, and characterize four distinct spatial CAF subtypes. These subtypes are conserved across cancer types and independent of spatial omics platforms. Notably, they exhibit distinct spatial organizational patterns, neighboring cell compositions, interaction networks, and transcriptomic profiles. Their abundance and composition vary across tissues, shaping TME characteristics, such as levels, distribution, and state composition of tumor-infiltrating immune cells, tumor immune phenotypes, and patient survival. This study enriches our understanding of CAF spatial heterogeneity in cancer and paves the way for novel approaches to target and modulate CAFs.

Stromal barriers to the abscopal effect

In this issue of Cancer Cell, Zhang et al. reveal that PAI-1-induced SFRP2high cancer-associated fibroblasts reduce the abscopal effect of radioimmunotherapy. Targeting PAI-1 or SFRP2 enhances T cell recruitment and prevents the formation of an immunosuppressive perivascular niche, improving radioimmunotherapy's abscopal effect.

Emerging clinical applications of single-cell RNA sequencing in oncology

Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of complex tissues both in health and in disease. Over the past decade, scRNA-seq has been applied to tumour samples obtained from patients with cancer in hundreds of studies, thereby advancing the view that each tumour is a complex ecosystem and uncovering the diverse states of both cancer cells and the tumour microenvironment. Such studies have primarily investigated and provided insights into the basic biology of cancer, although considerable research interest exists in leveraging these findings towards clinical applications. In this Review, we summarize the available data from scRNA-seq studies investigating samples from patients with cancer with a particular focus on findings that are of potential clinical relevance. We highlight four main research objectives of scRNA-seq studies and describe some of the most relevant findings towards such goals. We also describe the limitations of scRNA-seq, as well as future approaches in this field that are anticipated to further advance clinical applicability.

Characterization of cancer-associated fibroblasts and their spatial architecture reveals heterogeneity and survival associations in classic Hodgkin lymphoma

Cancer-associated fibroblasts (CAFs) are a heterogeneous population of stromal cells, which modulate the immune system and can have both pro- and anti-tumorigenic effects. In classic Hodgkin lymphoma (cHL), the role of CAFs has remained largely undefined. We applied multiplexed immunofluorescence imaging and spatial analysis on tumor samples from two independent cHL patient cohorts (n = 131 and n = 148) to study CAFs and their interactions with Hodgkin Reed-Sternberg (HRS) and tumor microenvironment (TME) cells at the single-cell resolution. We show that higher proportions of CAFs are associated with favorable outcomes, independent of the clinical covariables. In contrast, a subset of CD45+ immune cells with strong fibroblast-activation protein positivity, classified as macrophages, was less abundant in nodular sclerosis subtype and associated with worse outcomes. Neighborhood analysis allowed for the identification of colocalization or regional exclusion of phenotypically defined cell types and recurrent cellular neighborhoods. Despite the positive impact of CAF proportions on survival, patients with enrichment of platelet-derived growth factor receptor beta (PDGFRB)-positive CAFs in the vicinity of HRS cells had worse survival in both cohorts, independent of the clinical determinants. Our findings distinguish various subsets of CAFs and macrophages impacting survival in cHL and underscore the importance of the spatial arrangements in the TME.

Cancer-associated fibroblasts promote EGFR-TKI resistance via the CTHRC1/glycolysis/H3K18la positive feedback loop

Acquired resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) remains a major challenge in the treatment of lung cancer. Cancer associated fibroblasts (CAFs) play a key role in promoting resistance to anti-cancer therapies. This study identified a subpopulation of CAFs characterized by the overexpression of collagen triple helix repeat-containing 1 (CTHRC1) through single-cell RNA sequencing of lung cancer patients undergoing EGFR-TKI treatment. These CTHRC1+ CAFs were enriched in drug-resistant tumors. Mechanistically, CTHRC1+ CAFs enhance the glycolytic activity of cancer cells by activating the TGF-β/Smad3 signaling pathway. Excess lactate produced in the process of glycolysis further upregulates CTHRC1 expression in CAFs through histone lactylation, creating a positive feedback loop that sustains EGFR-TKI resistance. The study also demonstrated that Gambogenic Acid, a natural compound, can disrupt this feedback loop, thereby improving the efficacy of EGFR-TKI therapy. Additionally, the presence of CTHRC1+ CAFs in tumor tissues could serve as a biomarker for predicting the response to EGFR-TKI therapy and patient prognosis. Overall, this study highlights the significant role of CAFs in EGFR-TKI resistance and suggests that targeting CTHRC1+ CAFs could be a promising strategy to overcome drug resistance in lung cancer.

From surfing to diving into the tumor microenvironment through multiparametric imaging mass cytometry

The tumor microenvironment (TME) is a complex ecosystem where malignant and non-malignant cells cooperate and interact determining cancer progression. Cell abundance, phenotype and localization within the TME vary over tumor development and in response to therapeutic interventions. Therefore, increasing our knowledge of the spatiotemporal changes in the tumor ecosystem architecture is of importance to better understand the etiologic development of the neoplastic diseases. Imaging Mass Cytometry (IMC) represents the elective multiplexed imaging technology enabling the in-situ analysis of up to 43 different protein markers for in-depth phenotypic and spatial investigation of cells in their preserved microenvironment. IMC is currently applied in cancer research to define the composition of the cellular landscape and to identify biomarkers of predictive and prognostic significance with relevance in mechanisms of drug resistance. Herein, we describe the general principles and experimental workflow of IMC raising the informative potential in preclinical and clinical cancer research.

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.

Development and Validation of a Prognostic Model for Lung Adenocarcinoma Based on CAF-Related Genes: Unveiling the Role of COX6A1 in Cancer Progression and CAF Infiltration

Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), presents significant challenges in early diagnosis and personalized treatment. Recent research has focused on the role of the tumor microenvironment, particularly tumor-associated fibroblasts (CAFs), in tumor progression. This study systematically analyzed CAF immune infiltration-related genes to construct a prognostic model for LUAD, confirming its predictive value for patient outcomes. The risk score derived from CAF-related genes (CAFRGs) was negatively correlated with immune microenvironment scores and linked to the expression of immune checkpoint genes, indicating that high-risk patients may exhibit immune escape characteristics. Analysis via the TIDE tool revealed that low-risk patients had more active T-cell immune responses. The risk score also correlated with anti-tumor drug sensitivity, particularly to doramapimod. Notably, COX6A1 emerged as a key gene in the model, with its upregulation associated with immune cell infiltration and immune escape. Further in vitro experiments demonstrated that COX6A1 regulates LUAD cell migration, proliferation, and senescence, suggesting its role in tumor immune evasion. Additionally, further co-culture studies of lung cancer cells and fibroblasts revealed that COX6A1 knockdown promotes the expression of CAF-related cytokines, enhancing CAF infiltration. Overall, this study provides a foundation for personalized treatment of LUAD and highlights COX6A1 as a promising therapeutic target within the tumor immune microenvironment, guiding future clinical research.

Antigen-presenting cancer-associated fibroblasts in murine pancreatic tumors differentially control regulatory T cell phenotype and function via CXCL9 and CCL22

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a complex tumor microenvironment (TME) including stromal cells that influence resistance to therapy. Recent studies have revealed that stromal cancer-associated fibroblasts (CAFs) are heterogeneous in origin, gene expression, and function. Antigen-presenting CAFs (apCAFs), are defined by major histocompatibility complex (MHC)-II expression and can activate effector CD4 + T cells that have the potential to contribute to the anti-cancer immune response, but also can induce regulatory T cell (Treg) differentiation. Whether apCAFs promote or restrain the antitumor response remains uncertain. Using tumor clones of the KPC murine PDAC model differing in sensitivity to immune checkpoint blockade (ICB), we found that immunosensitive (sKPC) tumors were characterized by higher immune cell and apCAF infiltration than resistant (rKPC) tumors. IMC analysis showed proximity of apCAFs and CD4 + T cells in both sKPC and rKPC tumors implicating interaction within the TME. apCAF-depleted sKPC tumor-bearing mice had diminished sensitivity to ICB. apCAFs from both sKPC and rKPC tumors activated tumor-infiltrating CD4 + T cells and induced Treg differentiation. However, transcriptomic analysis showed that Tregs induced by apCAFs were overexpressed for immunosuppressive genes in rKPCs relative to sKPCs, and that this is associated with differential chemokine signaling from apCAFs depending on tumor origin. Together these data implicate apCAFs as important mediators of the antitumor immune response, modulation of which could facilitate the development of more effective anti-tumor immune based approaches for PDAC patients.

Integrative analysis of genetic variability and functional traits in lung adenocarcinoma epithelial cells via single-cell RNA sequencing, GWAS, bayesian deconvolution, and machine learning

BACKGROUND

Lung adenocarcinoma remains a leading cause of cancer-related mortality worldwide, characterized by high genetic and cellular heterogeneity, especially within the tumor microenvironment.

OBJECTIVE

This study integrates single-cell RNA sequencing (scRNA-seq) with genome-wide association studies (GWAS) using Bayesian deconvolution and machine learning techniques to unravel the genetic and functional complexity of lung adenocarcinoma epithelial cells.

METHODS

We performed scRNA-seq and GWAS analysis to identify critical cell populations affected by genetic variations. Bayesian deconvolution and machine learning techniques were applied to investigate tumor progression, prognosis, and immune-epithelial cell interactions, particularly focusing on immune checkpoint markers such as PD-L1 and CTLA-4.

RESULTS

Our analysis highlights the importance of genes like SLC2A1, which regulates glucose metabolism and correlates with tumor invasiveness and poor prognosis. Immune-epithelial interactions suggest a suppressive tumor microenvironment, potentially hindering immune responses. Additionally, machine learning models identify core prognostic genes such as F12, GOLM1, and S100P, which are significantly associated with patient survival.

CONCLUSIONS

This comprehensive approach provides novel insights into lung adenocarcinoma biology, emphasizing the role of genetic and immune factors in tumor progression. The findings support the development of personalized therapeutic strategies targeting both tumor cells and the immune microenvironment.

Landscape of the intratumoral microbiota acting on the tumor immune microenvironment in LUAD and LUSC

Although the intratumoral microbiota has been discovered to have a close connection with tumor immunity, the specific role played by intratumoral microbiota in regulating the tumor immune microenvironment (TIME) of lung cancer remains largely unexplored. Here, we comprehensively investigated the association between intratumoral microbiota and the TIME in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). First, we found that intratumoral microbiota and host transcriptome profile significantly differed between LUAD and LUSC. Moreover, there were strong associations between the abundance of intratumoral microbes and the expression of host genes in both LUAD and LUSC. Furthermore, we found an association between intratumoral Lachnoclostridium and chemokine expression, suggesting a role for these species of microbiota in modulating tumor immunity. In addition, we found that tumors harbor distinct relative abundance of Lachnoclostridium presented variation in response to immunotherapy and sensitivity to potential drug candidates. Our study provided important insights into the regulation of intratumoral microbiota on the TIME in LUAD and LUSC, which may serve as a precursor for a hypothesis-driven study to better understand the causational relationship of intratumoral microbiota in lung cancer.NEW & NOTEWORTHY LUAD and LUSC exhibited significant differences in intratumoral microbiome and the TIME profile. The relative abundance of intratumoral Lachnoclostridium correlated with the tumor immune infiltration in both LUSC and LUAD. Intratumoral Lachnoclostridium impacted the patients' sensitivity to potential targeted drugs, especially in LUSC.

Prognostic implications and therapeutic opportunities related to CAF subtypes in CMS4 colorectal cancer: insights from single-cell and bulk transcriptomics

Cancer-associated fibroblasts (CAFs) significantly influence tumor progression and therapeutic resistance in colorectal cancer (CRC). However, the distributions and functions of CAF subpopulations vary across the four consensus molecular subtypes (CMSs) of CRC. This study performed single-cell RNA and bulk RNA sequencing and revealed that myofibroblast-like CAFs (myCAFs), tumor-like CAFs (tCAFs), inflammatory CAFs (iCAFs), CXCL14+CAFs, and MT+CAFs are notably enriched in CMS4 compared with other CMSs of CRC. Multiplex immunohistochemistry was used to validate the distribution of CAF subtypes in patients with different CMSs. Prognosis-related CAF subtypes were identified, leading to the selection of four key genes (COL3A1, COL1A2, GEM, and TMEM47). Through machine learning, we developed a CAF poor-prognosis gene (CAFPRG) model to predict outcomes of patients with CMS4. High levels of CAFPRGs were identified as independent poor-risk factors for prognosis (p < 0.001). Tumors with elevated CAFPRGs exhibited increased infiltration of immune-suppressive cells and resistance to chemotherapy. The expression of these key genes was confirmed to be significantly higher in CAFs than in normal fibroblasts (NFs). Therefore, CAFPRGs may be valuable for precisely predicting patient survival and may present potential therapeutic opportunities for CMS4 CRC.

Cancer-Associated Fibroblasts as the "Architect" of the Lung Cancer Immune Microenvironment: Multidimensional Roles and Synergistic Regulation with Radiotherapy

Cancer-associated fibroblasts (CAFs), as the "architect" of the immune microenvironment in lung cancer, play a multidimensional role in tumor progression and immune regulation. In this review, we summarize the heterogeneity of the origin and the molecular phenotype of CAFs in lung cancer, and explore the complex interactions between CAFs and multiple components of the tumor microenvironment, including the regulatory relationships with innate immune cells (e.g., tumor-associated macrophages, tumor-associated neutrophils), adaptive immune cells (e.g., T cells), and extracellular matrix (ECM). CAFs significantly influence tumor progression and immunomodulation through the secretion of cytokines, remodeling of the ECM, and the regulation of immune cell function significantly affects the immune escape and treatment resistance of tumors. In addition, this review also deeply explored the synergistic regulatory relationship between CAF and radiotherapy, revealing the key role of CAF in radiotherapy-induced remodeling of the immune microenvironment, which provides a new perspective for optimizing the comprehensive treatment strategy of lung cancer. By comprehensively analyzing the multidimensional roles of CAF and its interaction with radiotherapy, this review aims to provide a theoretical basis for the precise regulation of the immune microenvironment and clinical treatment of lung cancer.

A novel lactylation-related gene signature to predict prognosis and treatment response in lung adenocarcinoma

Background

Lactylation, a novel post-translational modification, has emerged as a critical regulatory mechanism in various biological processes, including tumor progression. However, its role and associated gene signatures in lung adenocarcinoma (LUAD) remain unclear.

Methods

RNA sequencing data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Unsupervised clustering was used to identify lactylation-related genes. A risk prognostic model was constructed using least absolute shrinkage and selection operator regression analysis and subsequently validated. A nomogram was then employed to optimize the clinical applicability of the risk score. Additionally, various algorithms were used to explore the relationship between the risk score and immune infiltration levels, with model genes analyzed based on single-cell sequencing. The effects of RCCD1 knockdown on LUAD cell proliferation and migration were evaluated through CCK8 and transwell assays.

Results

Higher risk scores were associated with poorer overall survival prognosis. Immune analysis revealed that the risk score may play a role in regulating the tumor microenvironment. Additionally, these risk scores were found to be associated with chemotherapy drug sensitivity. A series of experiments further demonstrated that RCCD1 promotes LUAD cell proliferation and migration in vitro.

Conclusion

This study highlights the critical role of lactylation-related gene signatures in LUAD and their association with immune cell infiltration, providing insights into potential therapeutic targets and biomarkers for clinical application.

Radiation-induced lung injury: from mechanism to prognosis and drug therapy

Radiation induced lung injury, known as the main complication of thoracic radiation, remains to be a major resistance to tumor treatment. Based on the recent studies on radiation-induced lung injury, this review collated the possible mechanisms at the level of target cells and key pathways, corresponding prognostic models including predictors, patient size, number of centers, radiotherapy technology, construction methods and accuracy, and pharmacotherapy including drugs, targets, therapeutic effects, impact on anti-tumor treatment and research types. The research priorities and limitations are summarized to provide a reference for the research and management of radiation-induced lung injury.

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.

Anlotinib may have a therapeutic effect on papillary craniopharyngiomas without the BRAFv600e mutation

BACKGROUND

Although successful treatment of papillary craniopharyngiomas (PCPs) with BRAFv600e inhibitors has been reported in clinical trials, studies have shown that approximately 10% of PCPs lack the BRAFv600e mutation and that BRAFv600e inhibitors may not be significantly effective against these tumors. However, no studies have focused specifically on BRAFv600e- PCPs.

METHODS

Spatial transcriptome sequencing was performed on calcified PCP tissue to identify novel subtypes of PCP cells. The findings were validated via pathological methods in 51 PCP samples. Primary PCP cells from BRAFv600e- PCP patients and BRAFv600e+ PCP patients were isolated and then injected into the brains of nude mice via stereotactic surgery to establish a stable mouse model of human-originated PCP. Model mice were treated with vemurafenib, a BRAF inhibitor, and anlotinib, an angiogenesis inhibitor. BRAFv600e-PCP patients were treated with anlotinib in a phase 1 clinical trial. Changes in the tumors of the model mice and patients were monitored via pathological methods, CT and MRI.

RESULTS

Most of calcified PCPs were negative for the BRAFv600e mutation, and findings from the mouse model confirmed that vemurafenib may not have a significant therapeutic effect on BRAFv600e- PCPs. However, the mouse model verified that, anlotinib may have a significant therapeutic effect on BRAFv600e- PCPs. Two patients with BRAFv600e- PCPs participated in a phase 1 clinical trial and received anlotinib therapy; their tumors disappeared after 3 months of therapy and did not recur within 24 months follow-up after stopping the treatment.

CONCLUSION

BRAFv600e- PCPs are characterized by calcification and do not respond to the BRAF inhibitor vemurafenib, and for which the angiogenesis inhibitor anlotinib may have a significant therapeutic effect.

Advances in nanotechnology for targeting cancer-associated fibroblasts: A review of multi-strategy drug delivery and preclinical insights

Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment by promoting tumor growth, immune evasion, and metastasis. Recently, drug delivery systems targeting CAFs have emerged as a promising long-term and effective approach to cancer treatment. Advances in nanotechnology, in particular, have led to the development of nanomedicine delivery systems designed specifically to target CAFs, offering new possibilities for precise and personalized cancer therapies. This article reviews recent progress in drug delivery using nanocarriers that target CAFs. Additionally, we explore the potential of combining multiple therapies, such as chemotherapy and immunotherapy, with nanocarriers to enhance efficacy and overcome drug resistance. Although many preclinical studies show promise, the clinical application of nanomedicine still faces considerable challenges, especially in terms of drug penetration and large-scale production. Therefore, this review aims to provide a fresh perspective on CAF-targeted drug delivery systems and highlight potential future research directions and clinical applications.

Tumor infiltration of inactive CD8 + T cells was associated with poor prognosis in Gastric Cancer

BACKGROUND

Gastric cancer (GC) shows limited response to immune checkpoint inhibitors due to its complex tumor immune microenvironment (TIME). This study explores the functions of various immune cells in the complex TIME in GC.

METHODS

We assessed CD8 + T-cell infiltration of GC tissues by immunohistochemistry, and performed single-cell RNA sequencing (scRNA-seq) of tumor and normal tissues from 34 patients with GC.

RESULTS

We categorized 157 GC patients into LOW, MID, and HIGH groups based on their CD8 + T-cell infiltration. Overall survival was notably lower for the HIGH and LOW groups compared with the MID group. Our scRNA-seq data analysis showed that CD8 + T-cell activity markers in the HIGH group were expressed at lower levels than in normal tissue, but the T-cell-attracting chemokine CCL5 was expressed at a higher level. Notably, CD8 + T-cells in the HIGH group displayed lower PD1 expression and higher CTLA4 expression. TCR repertoire analysis using only Epstein-Barr virus-negative cases showed that CD8 + T-cell receptor clonality was lower in the HIGH group than in the MID group. Furthermore, in the HIGH group, the antigen-presenting capacity of type 1 conventional dendritic cells was lower, the immunosuppressive capacity of myeloid-derived suppressor cells was higher, and the expression of CTLA4 in regulatory T-cells was higher.

CONCLUSION

The present data suggest that the infiltration of inactive CD8 + T-cells with low clonality is induced by chemotaxis in the HIGH group, possibly leading to a poor prognosis for patients with GC.

Simultaneous immunomodulation and epithelial-to-mesenchymal transition drives lung adenocarcinoma progression

Lung cancer remains the deadliest cancer in the United States, with lung adenocarcinoma (LUAD) as its most prevalent subtype. While computed tomography (CT)-based screening has improved early detection and enabled curative surgeries, the molecular and cellular dynamics driving early-stage LUAD progression remain poorly understood, limiting non-surgical treatment options. To address this gap, we profiled 2.24 million cells from 122 early-stage LUAD patients using multiplexed imaging mass cytometry (IMC). This analysis revealed the molecular, spatial, and temporal dynamics of LUAD development. Our findings uncover a binary progression model. LUAD advances through either inflammation, driven by a balance of cytotoxic and regulatory immune activity, or fibrosis, characterized by stromal activation. Surprisingly, tumor cell populations did not increase significantly. Instead, they displayed a mixed phenotypic profile consistent with epithelial-to-mesenchymal transition (EMT), effectively masking the expansion of malignant cells. Furthermore, we addressed discrepancies between CT-based and histology-based subtyping. CT scans, while non-invasive, often mischaracterize invasive fibrotic tumors-which account for 20.5% of LUAD cases-as mild, non-solid ground glass opacities (GGOs). Using high-content IMC imaging, we demonstrate that these tumors harbor significant risks and advocate for improved diagnostic strategies. These strategies should integrate molecular profiling to refine patient stratification and therapeutic decision-making. Altogether, our study provides a high-resolution, systems-level view of the tumor microenvironment in early-stage LUAD. We characterize key transitions in oncogenesis and propose a precision-driven framework to enhance the detection and management of aggressive disease subtypes.

A novel HVEM-Fc recombinant protein for lung cancer immunotherapy

BACKGROUND

The ubiquitously expressed transmembrane protein, Herpesvirus Entry Mediator (HVEM), functions as a molecular switch, capable of both activating and inhibiting the immune response depending on its interacting ligands. HVEM-Fc is a novel recombinant fusion protein with the potential to eradicate tumor cells.

METHODS

The anti-tumor efficacy of HVEM-Fc was evaluated in C57BL/6 mice-bearing lung cancer models: a syngeneic model and an orthotopic model of mouse lung cancer. Additionally, patient-derived organoids were employed in conjunction with T cell co-culture systems. To investigate the underlying mechanisms, a comprehensive array of techniques was utilized, including single-cell RNA sequencing, spatial transcriptomics, bulk RNA sequencing, and flow cytometry. Furthermore, the anti-tumor effects of HVEM-Fc in combination with Programmed Death-1 (PD-1) inhibitors were assessed. Finally, mouse immune cell depletion antibodies were used to elucidate the underlying mechanisms of action.

RESULTS

In vivo, 1 mg/kg HVEM-Fc demonstrated effective inhibition of tumor growth and metastasis in C57BL/6 mice bearing lung cancer model and a KP orthotopic model of mouse lung cancer. Multi-omics analysis showed that HVEM-Fc induced an immune-stimulatory microenvironment. Notably, the combination of HVEM-Fc with a PD-1 inhibitor demonstrated the most potent inhibition of tumor cell growth. In vitro, HVEM-Fc was validated to eradicate tumor cells through the activation of T cells in both non-small cell lung cancer (NSCLC) organoids and T cell co-culture models.

CONCLUSIONS

Our data demonstrate that HVEM-Fc exerts a strong signal that augments and prolongs T-cell activity in both murine models and human NSCLC organoid models. Moreover, the combination of HVEM-Fc with a PD-1 inhibitor yields the most effective anti-tumor outcomes.

Spatially resolved transcriptomics reveal the determinants of primary resistance to immunotherapy in NSCLC with mature tertiary lymphoid structures

Effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) has been linked to the presence of mature tertiary lymphoid structures (mTLSs) within the tumor microenvironment (TME). However, only a subset of mTLS-positive NSCLC derives benefit, thus highlighting the need to unravel ICI response determinants. The comprehensive analysis of ICI-treated patients with NSCLC (n = 509) from the Bergonié Institute Profiling (BIP) study (NCT02534649) reveals that the presence of mTLSs correlates with improved clinical outcomes, independently of programmed death ligand 1 (PD-L1) expression and genomic features. Employing spatial transcriptomics alongside multiplex immunofluorescence (mIF), we show that two distinct subsets of cancer-associated fibroblasts (CAFs) are essential factors in mediating primary resistance to ICIs in mTLS-positive NSCLC. These CAFs are associated with immune exclusion, CD8+ T cell exhaustion, and increased regulatory CD4+ T cell infiltration, underscoring an immunosuppressive TME. Our study highlights the pivotal role of specific CAF subsets in thwarting ICIs, proposing new therapeutic targets to enhance immunotherapy efficacy.

Naringenin-loaded nanoparticles modulate HIF-driven oxygen-sensing pathways in lung adenocarcinoma cells

BACKGROUND

Hypoxia is a common symptom of lung cancer. Proliferation and neovascularization mediated by hypoxia-inducible factors (HIF) influence several adaptations. It has recently been established that naringenin (NAR) and its nanoparticles are chemo-preventive flavonoids in lung cancer.

AIM

Adjust HIF activity by reviving oxygen-sensing enzyme activity while considering possible therapeutic targets.

METHOD

The bindings of NAR to target proteins were examined using computational modeling techniques. Additionally, NAR nanoparticles (NARNPs) were synthesized and characterized. Normal fibroblast cells and A549 cells were used to determine cytotoxicity. Colorimetric analysis of α-ketoglutarate detection for hydroxylases.

RESULTS

According to molecular modeling, NAR and target proteins have a high affinity. The PHD and FIH activities in A549 are significantly stimulated.

CONCLUSION

NAR and NARNPs diminish hypoxia in lung cancer by stimulating oxygen-sensing hydroxylases.

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.

Development of delayed pulmonary toxicities and transcriptional changes in pre-existing interstitial lung disease mice after partial thoracic irradiation

BACKGROUND

Lung cancer patients with comorbid interstitial lung disease (LC-ILD) have an increased risk of developing severe or even fatal radiation pneumonitis after thoracic radiotherapy. However, the underlying mechanisms of its pathogenesis are still inconclusive. No approved biomarker or medicine is available to prevent pulmonary toxicities in LC-ILD patients. Appropriate management for them remains a challenge for clinicians due to treatment-related complications.

METHODS

To elucidate the histopathological characteristics and molecular mechanisms responsible for this severe toxicity in vivo, C57BL/6J mice were used to develop different lung injury models, including radiation-induced lung injury (RILI), bleomycin-induced pulmonary fibrosis (BIPF), and severe radiation-related lung injury (sRRLI) murine model. Biopsy examination was performed on hematoxylin and eosin (H&E), Masson's trichrome, and immunohistochemistry-stained lung tissue sections. Changes in lung function were measured. RNA extracted from mouse lung tissues was sequenced on the Illumina Novaseq platform.

RESULTS

A severe lung injury model after irradiation was built based on pre-existing ILD mice induced by BLM administration. Enhanced lung injury was observed in the sRRLI model, including higher mortality and pulmonary function loss within six months compared to the mono-treatment groups. Autopsy revealed that bilateral diffuse alveolar damage (DAD) with an overlap of exudative, proliferative, and fibrosing patterns was usually presented in the sRRLI model. The histological phenotypes manifested exudative predominated DAD phase in the early phase and proliferating DAD pattern in the late phase. Bioinformatic analysis showed signaling pathways relevant to immune cell migration, epithelial cell development, and extracellular structure organization were commonly activated in different models. Furthermore, the involvement of epithelial cells and the infiltration of macrophages and CD4 + lymphocytes were validated during extensive lung remodeling in the sRRLI group.

CONCLUSIONS

Delayed effects of significantly declined lung function and high mortality were observed in the sRRLI model. DAD with progressive inflammation and fibrosis in bilateral lungs contributed to severe or even fatal complications after partial thoracic irradiation. The hyperactivation of inflammatory responses was clarified during long-term pulmonary toxicities. More studies are needed to investigate potential strategies to prevent and rescue severe lung complications.

Integrated analysis of M2 macrophage-related gene prognostic model and single-cell sequence to predict immunotherapy response in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) patients have high heterogeneity. The significance and clinical value of M2 macrophage-related genes in LUAD require further exploration. We aimed to construct a prognostic signature to predict the immunotherapy efficacy and prognosis in LUAD.

Methods

GSE26939 and GSE19188 chips were downloaded from the Gene Expression Omnibus (GEO). Weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis were used to screen M2 macrophage-related prognostic genes. A signature based on M2 macrophage-related prognostic genes was established and used to predict the prognosis and immunotherapy efficacy in LUAD.

Results

Twenty-two M2 macrophage-related genes associated with the prognosis of LUAD were confirmed using WGCNA, and then two molecular subtypes were identified with significantly different survival, gene expressions, and clinic characteristics were classified. LASSO analysis identified nine M2 macrophage-related prognostic genes to establish a risk signature, classifying patients into low- and high-risk groups. Data indicated that low-risk patients had better survival. Moreover, the signature was an independent prognostic factor for LUAD and a potential biomarker for patients receiving immunotherapy. Single-cell transcriptome analysis may provide important information on molecular subtypes and heterogeneity.

Conclusion

Risk signature based on M2 macrophage-related genes is a valuable tool for predicting prognosis and immunotherapy response in patients with LUAD.

Multiomics Analysis Reveals Molecular Changes during Early Progression of Precancerous Lesions to Lung Adenocarcinoma in Never-Smokers

Lung cancer is the most common cause of cancer mortality globally, and the prevalence of lung adenocarcinoma, the most common lung cancer subtype, has increased sharply in East Asia. Early diagnosis leads to better survival rates, but this requires an improved understanding of the molecular changes during early tumorigenesis, particularly in nonsmokers. In this study, we performed whole-exome sequencing and RNA sequencing of samples from 94 East Asian patients with precancerous lesions [25 with atypical adenomatous hyperplasia (AAH); 69 with adenocarcinoma in situ (AIS)] and 73 patients with early invasive lesions [minimally invasive adenocarcinoma (MIA)]. Cellular analysis revealed that the activities of endothelial and stromal cells could be used to categorize tumors into molecular subtypes within pathologically defined types of lesions. The subtypes were linked with the radiologically defined type of lesions and corresponded to immune cell infiltration throughout the early progression of lung adenocarcinoma. Spatial transcriptomic analysis revealed the distribution of epithelial cells, endothelial cells, fibroblasts, and plasma cells within MIA samples. Characterization of the molecular lesion subtypes identified positively selected mutational patterns and suggested that angiogenesis in the late-stage AIS type potentially contributes to tissue invasion of the MIA type. This study offers a resource that may help improve early diagnosis and patient prognosis, and the findings suggest possible approaches for early disease interception. Significance: Integrative analysis of multiomics data revealed coordination between immune and nonimmune cells during early progression of precancerous lesions to lung adenocarcinomas and shed light on the molecular characteristics of clinically defined subtypes.

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.

Spatial Architecture of Single-Cell and Vasculature in Tumor Microenvironment Predicts Clinical Outcomes in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited treatment options, which warrants the identification of novel therapeutic targets. Deciphering nuances in the tumor microenvironment (TME) may unveil insightful links between antitumor immunity and clinical outcomes; however, such connections remain underexplored. Here, we employed a data set derived from imaging mass cytometry of 71 TNBC patient specimens at single-cell resolution and performed in-depth quantifications with a suite of multiscale computational algorithms. The TNBC TME reflected a heterogeneous ecosystem with high spatial and compositional heterogeneity. Spatial analysis identified 10 recurrent cellular neighborhoods-a collection of local TME characteristics with unique cell components. The prevalence of cellular neighborhoods enriched with B cells, fibroblasts, and tumor cells, in conjunction with vascular density and perivasculature immune profiles, could significantly enrich long-term survivors. Furthermore, relative spatial colocalization of SMAhi fibroblasts and tumor cells compared with B cells correlated significantly with favorable clinical outcomes. Using a deep learning model trained on engineered spatial data, we can predict with high accuracy (mean area under the receiver operating characteristic curve of 5-fold cross-validation = 0.71) how a separate cohort of patients in the NeoTRIP clinical trial will respond to treatment based on baseline TME features. These data reinforce that the TME architecture is structured in cellular compositions, spatial organizations, vasculature biology, and molecular profiles and suggest novel imaging-based biomarkers for the treatment development in the context of TNBC.

Integrative analysis of Ewing's sarcoma reveals that the MIF-CD74 axis is a target for immunotherapy

BACKGROUND

Ewing's sarcoma (EwS), a common pediatric bone cancer, is associated with poor survival due to a lack of therapeutic targets for immunotherapy or targeted therapy. Therefore, more effective treatment options are urgently needed.

METHODS

Since novel immunotherapies may address this need, we performed an integrative analysis involving single-cell RNA sequencing, cell function experiments, and humanized models to dissect the immunoregulatory interactions in EwS and identify strategies for optimizing immunotherapeutic efficacy.

RESULTS

EwS is infiltrated by immunosuppressive myeloid populations, T and B lymphocytes, and natural killer cells. We found that SLC40A1 and C1QA macrophages were associated with a poor prognosis, whereas CD8+ T-cell infiltration was associated with a good prognosis. A comparative analysis of paired samples revealed that in tumors with a good chemotherapeutic response, macrophages presented increased antigen presentation and reduced release of protumor cytokines, whereas CD8+ T cells presented increased cytotoxicity and reduced exhaustion. An interaction analysis revealed a vast immunoregulatory network and identified MIF-CD74 as a crucial immunoregulatory target that can simultaneously promote M2 polarization of macrophages and inhibit CD8+ T-cell infiltration. Importantly, MIF blockade effectively reshaped the tumor immune microenvironment, turning cold tumors hot and inhibiting tumor growth.

CONCLUSIONS

Our integrative analysis revealed that the MIF/CD74 axis is a promising target for the treatment of Ewing sarcoma and provides a rationale for this novel immunotherapy.

Cancer associated fibroblasts drive epithelial to mesenchymal transition and classical to basal change in pancreatic ductal adenocarcinoma cells with loss of IL-8 expression

Pancreatic ductal adenocarcinoma (PDAC) carries an extremely poor prognosis, in part resulting from cellular heterogeneity that supports overall tumorigenicity. Cancer associated fibroblasts (CAF) are key determinants of PDAC biology and response to systemic therapy. While CAF subtypes have been defined, the effects of patient-specific CAF heterogeneity and plasticity on tumor cell behavior remain unclear. Here, multi-omics was used to characterize the tumor microenvironment (TME) in tumors from patients undergoing curative-intent surgery for PDAC. In these same patients, matched tumor organoid and CAF lines were established to functionally validate the impact of CAFs on the tumor cells. CAFs were found to drive epithelial-mesenchymal transition (EMT) and a switch in tumor cell classificiaton from classical to basal subtype. Furthermore, we identified CAF-specific interleukin 8 (IL-8) as an important modulator of tumor cell subtype. Finally, we defined neighborhood relationships between tumor cell and T cell subsets.

Highly proliferating cancer cells function as novel prognostic biomarkers for lung adenocarcinoma with particular usefulness for stage IA risk stratification

BACKGROUND

The refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA.

METHODS

We analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments. Then, we quantified the content of HPCs in nine LUAD datasets by single-sample gene set enrichment analysis and evaluated the relationship between the percentage of HPCs and overall survival (OS). Next, we analysed the OS predictive effect of HPCs at different LUAD stages, especially for stage I risk stratification. Furthermore, we established a prognostic prediction model based on HPC-associated genes for clinical application. The above findings were validated in another five LUAD datasets. Finally, we explored the relationship between HPCs and the progressive pathological evolution of early-stage LUAD and the driving mutations by scRNA-seq, bulk RNA-seq and IHC staining.

RESULTS

LUAD tissues carry a small proportion of HPCs, which show potential for malignant proliferation and intense interactions with the microenvironment. A high HPC content is an independent risk factor for OS in LUAD patients, even in stage IA patients. HPCs can be used to establish a cut-off point for the prognosis of stage IA disease, with patients with a higher risk showing a prognosis similar to that of patients with stage IB disease. We built an R package (HSurADs) based on HPC-associated genes, which exhibited good efficacy for the prognostic prediction of LUAD. HPCs gradually increase with the pathological evolution of early-stage LUAD, which may be affected by TP53 mutations.

CONCLUSION

The HPC content can be used as a novel prognostic factor for LUAD, especially for stage IA risk stratification.

Convergent inducers and effectors of T cell paralysis in the tumour microenvironment

Tumorigenesis embodies the formation of a heterotypic tumour microenvironment (TME) that, among its many functions, enables the evasion of T cell-mediated immune responses. Remarkably, most TME cell types, including cancer cells, fibroblasts, myeloid cells, vascular endothelial cells and pericytes, can be stimulated to deploy immunoregulatory programmes. These programmes involve regulatory inducers (signals-in) and functional effectors (signals-out) that impair CD8+ and CD4+ T cell activity through cytokines, growth factors, immune checkpoints and metabolites. Some signals target specific cell types, whereas others, such as transforming growth factor-β (TGFβ) and prostaglandin E2 (PGE2), exert broad, pleiotropic effects; as signals-in, they trigger immunosuppressive programmes in most TME cell types, and as signals-out, they directly inhibit T cells and also modulate other cells to reinforce immunosuppression. This functional diversity and redundancy pose a challenge for therapeutic targeting of the immune-evasive TME. Fundamentally, the commonality of regulatory programmes aimed at abrogating T cell activity, along with paracrine signalling between cells of the TME, suggests that many normal cell types are hard-wired with latent functions that can be triggered to prevent inappropriate immune attack. This intrinsic capability is evidently co-opted throughout the TME, enabling tumours to evade immune destruction.

Multiparameter quantitative analyses of diagnostic cells in brain tissues from tuberous sclerosis complex

The advent of high-dimensional imaging offers new opportunities to molecularly characterize diagnostic cells in disorders that have previously relied on histopathological definitions. One example case is found in tuberous sclerosis complex (TSC), a developmental disorder characterized by systemic growth of benign tumors. Within resected brain tissues from patients with TSC, detection of abnormally enlarged balloon cells (BCs) is pathognomonic for this disorder. Though BCs can be identified by an expert neuropathologist, little is known about the specificity and broad applicability of protein markers for these cells, complicating classification of proposed BCs identified in experimental models of this disorder. Here, we report the development of a customized machine learning pipeline (BAlloon IDENtifier; BAIDEN) that was trained to prospectively identify BCs in tissue sections using a histological stain compatible with high-dimensional cytometry. This approach was coupled to a custom 36-antibody panel and imaging mass cytometry (IMC) to explore the expression of multiple previously proposed BC marker proteins and develop a descriptor of BC features conserved across multiple tissue samples from patients with TSC. Here, we present a modular workflow encompassing BAIDEN, a custom antibody panel, a control sample microarray, and analysis pipelines-both open-source and in-house-and apply this workflow to understand the abundance, structure, and signaling activity of BCs as an example case of how high-dimensional imaging can be applied within human tissues.

Tumor-Activated Neutrophils Promote Lung Cancer Progression through the IL-8/PD-L1 Pathway

BACKGROUND

Lung cancer remains a major global health threat due to its complex microenvironment, particularly the role of neutrophils, which are crucial for tumor development and immune evasion mechanisms. This study aimed to delve into the impact of lung cancer cell-conditioned media on neutrophil functions and their potential implications for lung cancer progression.

METHODS

Employing in vitro experimental models, this study has analyzed the effects of lung cancer cell-conditioned media on neutrophil IL-8 and IFN-γ secretion, apoptosis, PD-L1 expression, and T-cell proliferation by using techniques, such as ELISA, flow cytometry, immunofluorescence, and CFSE proliferation assay. The roles of IL-8/PD-L1 in regulating neutrophil functions were further explored using inhibitors for IL-8 and PD-L1.

RESULTS

Lung cancer cell lines were found to secrete higher levels of IL-8 compared to normal lung epithelial cells. The conditioned media from lung cancer cells significantly reduced apoptosis in neutrophils, increased PD-L1 expression, and suppressed T-cell proliferation and IFN-γ secretion. These effects were partially reversed in the presence of IL-8 inhibitors in Tumor Tissue Culture Supernatants (TTCS), while being further enhanced by IL-8. Both apoptosis and PD-L1 expression in neutrophils demonstrated dose-dependency to TTCS. Additionally, CFSE proliferation assay results further confirmed the inhibitory effect of lung cancer cell-conditioned media on T-- cell proliferation.

CONCLUSION

This study has revealed lung cancer cell-conditioned media to modulate neutrophil functions through regulating factors, such as IL-8, thereby affecting immune regulation and tumor progression in the lung cancer microenvironment.

From darkness to light: Targeting CAFs as a new potential strategy for cancer treatment

Cancer-associated fibroblasts (CAFs), which are the most frequent stromal cells in the tumor microenvironment (TME), play a key role in the metastasis of tumor cells. Generally speaking, CAFs in cooperation with tumor cells can secrete various cytokines, proteins, growth factors, and metabolites to promote angiogenesis, mediate immune escape of tumor cells, enhance endothelial-to-mesenchymal transition, stimulate extracellular matrix remodeling, and preserve tumor cell stemness. These activities of CAFs provide a favorable exogenous pathway for tumor progression and metastasis, and a microenvironment that allows rapid growth of tumor cells, which always lead to poor prognosis for patients. More importantly, it seems that targeting CAFs is also a potential precision therapeutic strategy in clinical practice. Hence, this review outlines the origin of CAFs, the relationship between CAFs and cancer metastasis, and targeting CAFs as a potential strategy for cancer patients, which could give some inspirations for cancer treatment in clinic.

Integrative analysis of anoikis-related genes prognostic signature with immunotherapy and identification of CDKN3 as a key oncogene in lung adenocarcinoma

Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients.

Spatially-resolved analyses of muscle invasive bladder cancer microenvironment unveil a distinct fibroblast cluster associated with prognosis

Background

Muscle-invasive bladder cancer (MIBC) is a prevalent cancer characterized by molecular and clinical heterogeneity. Assessing the spatial heterogeneity of the MIBC microenvironment is crucial to understand its clinical significance.

Methods

In this study, we used imaging mass cytometry (IMC) to assess the spatial heterogeneity of MIBC microenvironment across 185 regions of interest in 40 tissue samples. We focused on three primary parameters: tumor (T), leading-edge (L), and nontumor (N). Cell gating was performed using the Cytobank platform. We calculated the Euclidean distances between cells to determine cellular interactions and performed single-cell RNA sequencing (scRNA-seq) to explore the molecular characteristics and mechanisms underlying specific fibroblast (FB) clusters. scRNA-seq combined with spatial transcriptomics (ST) facilitated the identification of ligand-receptor (L-R) pairs that mediate interactions between specific FB clusters and endothelial cells. Machine learning algorithms were used to construct a prognostic gene signature.

Results

The microenvironments in the N, L, and T regions of MIBC exhibited spatial heterogeneity and regional diversity in their components. A distinct FB cluster located in the L region-identified as S3-is strongly associated with poor prognosis. IMC analyses demonstrated a close spatial association between S3 and endothelial cells, with S3-positive tumors exhibiting increased blood vessel density and altered vascular morphology. The expression of vascular endothelial growth factor receptor and active vascular sprouting were significant in S3-positive tumors. scRNA-seq and ST analyses indicated that the genes upregulated in S3 were associated with angiogenesis. NOTCH1-JAG2 signaling pathway was identified as a significant L-R pair specific to S3 and endothelial cell interactions. Further analysis indicated that YAP1 was a potential regulator of S3. Machine learning algorithms and Gene Set Variation Analysis were used to establish an S3-related gene signature that was associated with the poor prognosis of tumors including MIBC, mesothelioma, glioblastoma multiforme, lower-grade glioma, stomach adenocarcinoma, uveal melanoma, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, and lung squamous cell carcinoma.

Conclusions

We assessed the spatial landscape of the MIBC microenvironment and revealed a specific FB cluster with prognostic potential. These findings offer novel insights into the spatial heterogeneity of the MIBC microenvironment and highlight its clinical significance.

Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images

Immune checkpoint inhibitors (ICI) have become integral to treatment of non-small cell lung cancer (NSCLC). However, reliable biomarkers predictive of immunotherapy efficacy are limited. Here, we introduce HistoTME, a novel weakly supervised deep learning approach to infer the tumor microenvironment (TME) composition directly from histopathology images of NSCLC patients. We show that HistoTME accurately predicts the expression of 30 distinct cell type-specific molecular signatures directly from whole slide images, achieving an average Pearson correlation of 0.5 with the ground truth on independent tumor cohorts. Furthermore, we find that HistoTME-predicted microenvironment signatures and their underlying interactions improve prognostication of lung cancer patients receiving immunotherapy, achieving an AUROC of 0.75 [95% CI: 0.61-0.88] for predicting treatment responses following first-line ICI treatment, utilizing an external clinical cohort of 652 patients. Collectively, HistoTME presents an effective approach for interrogating the TME and predicting ICI response, complementing PD-L1 expression, and bringing us closer to personalized immuno-oncology.

Cancer-associated fibroblasts: heterogeneity, tumorigenicity and therapeutic targets

Cancer, characterized by its immune evasion, active metabolism, and heightened proliferation, comprises both stroma and cells. Although the research has always focused on parenchymal cells, the non-parenchymal components must not be overlooked. Targeting cancer parenchymal cells has proven to be a formidable challenge, yielding limited success on a broad scale. The tumor microenvironment(TME), a critical niche for cancer cell survival, presents a novel way for cancer treatment. Cancer-associated fibroblast (CAF), as a main component of TME, is a dynamically evolving, dual-functioning stromal cell. Furthermore, their biological activities span the entire spectrum of tumor development, metastasis, drug resistance, and prognosis. A thorough understanding of CAFs functions and therapeutic advances holds significant clinical implications. In this review, we underscore the heterogeneity of CAFs by elaborating on their origins, types and function. Most importantly, by elucidating the direct or indirect crosstalk between CAFs and immune cells, the extracellular matrix, and cancer cells, we emphasize the tumorigenicity of CAFs in cancer. Finally, we highlight the challenges encountered in the exploration of CAFs and list targeted therapies for CAF, which have implications for clinical treatment.