Deciphering cell lineage specification of human lung adenocarcinoma with single-cell RNA sequencing

APOBEC affects tumor evolution and age at onset of lung cancer in smokers

Most solid tumors harbor somatic mutations attributed to off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B). However, how APOBEC3A/B enzymes affect tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, multi-omics profiling of 309 lung cancers from smokers identifies two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations; HAS for A3A-like mutagenesis and TP53 mutations. Compared to LAS, HAS have older age at onset and high proportions of newly generated progenitor-like cells likely due to the combined tobacco smoking- and APOBEC3A-associated DNA damage and apoptosis. Consistently, HAS exhibit high expression of pulmonary healing signaling pathway, stemness markers, distal cell-of-origin, more neoantigens, slower clonal expansion, but no smoking-associated genomic/epigenomic changes. With validation in 184 lung tumor samples, these findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development.

Spatial and multiomics analysis of human and mouse lung adenocarcinoma precursors reveals TIM-3 as a putative target for precancer interception

How tumor microenvironment shapes lung adenocarcinoma (LUAD) precancer evolution remains poorly understood. Spatial immune profiling of 114 human LUAD and LUAD precursors reveals a progressive increase of adaptive response and a relative decrease of innate immune response as LUAD precursors progress. The immune evasion features align the immune response patterns at various stages. TIM-3-high features are enriched in LUAD precancers, which decrease in later stages. Furthermore, single-cell RNA sequencing (scRNA-seq) and spatial immune and transcriptomics profiling of LUAD and LUAD precursor specimens from 5 mouse models validate high TIM-3 features in LUAD precancers. In vivo TIM-3 blockade at precancer stage, but not at advanced cancer stage, decreases tumor burden. Anti-TIM-3 treatment is associated with enhanced antigen presentation, T cell activation, and increased M1/M2 macrophage ratio. These results highlight the coordination of innate and adaptive immune response/evasion during LUAD precancer evolution and suggest TIM-3 as a potential target for LUAD precancer interception.

Translating premalignant biology to accelerate non-small-cell lung cancer interception

Over the past decade, substantial progress has been made in the development of targeted and immune-based therapies for patients with advanced non-small-cell lung cancer. To further improve outcomes for patients with lung cancer, identifying and intercepting disease at the earliest and most curable stages are crucial next steps. With the recent implementation of low-dose computed tomography scan screening in populations at high risk, there is an emerging unmet need for new diagnostic, prognostic and therapeutic tools to help treat patients suspected of harbouring premalignant lesions and minimally invasive non-small-cell lung cancer. Continued advances in the identification of the earliest drivers of lung carcinogenesis are poised to address these unmet needs. Employing multimodal approaches to chart the temporal and spatial maps of the molecular events driving lung premalignant lesion progression will refine our understanding of early carcinogenesis. Elucidating the molecular drivers of premalignancy is critical to the development of biomarkers to detect those incubating a premalignant lesion, to stratify risk for progression to invasive cancer and to identify novel therapeutic targets to intercept that process. In this Review, we summarize emerging insights into the earliest cellular and molecular events associated with lung squamous and adenocarcinoma carcinogenesis and highlight the growing opportunity for translating these insights into clinical tools for early detection and disease interception to transform the outcomes for those at risk for lung cancer.

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.

The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma

Objective

Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. This study aims to investigate the relationship between gene expression and mitophagy in LUAD, with an emphasis on identifying key biomarkers and elucidating their roles in tumorigenesis and immune cell infiltration.

Methods

We utilized datasets GSE151101 and GSE203609 from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) associated with lung cancer and mitophagy. DEGs were identified using GEO2R, filtered based on criteria of P < 0.05 and log2 fold change ≥ 1. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to classify DEGs into modules. Functional annotation of these modules was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Gene Set Enrichment Analysis (GSEA) was applied to the most relevant module, designated as the greenyellow module. To identify critical biomarkers, machine learning algorithms including Random Forest, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Support Vector Machine (SVM) were employed. Validation of the findings was conducted using The Cancer Genome Atlas (TCGA) database, Human Protein Atlas (HPA), quantitative PCR (qPCR), and immune cell infiltration analysis via CIBERSORTx.

Results

Our analysis identified 11,012 overlapping DEGs between the two datasets. WGCNA revealed 11 modules, with the green-yellow module exhibiting the highest correlation. Functional enrichment analysis highlighted significant associations with FOXM1 signaling pathways and retinoblastoma in cancer. Machine learning algorithms identified COASY, FTSJ1, and MOGS as pivotal genes. These findings were validated using TCGA data, qPCR experiments, which demonstrated high expression levels in LUAD samples. Immunohistochemistry from HPA confirmed consistency between protein levels and RNA-seq data. Furthermore, pan-cancer analysis indicated that these genes are highly expressed across various cancer types. Immune infiltration analysis suggested significant correlations between these genes and specific immune cell populations.

Conclusion

COASY, FTSJ1 and MOGS have emerged as critical biomarkers in LUAD, potentially influencing tumorigenesis through mitophagy-related mechanisms and immune modulation. These findings provide promising avenues for future research into targeted therapies and diagnostic tools, thereby enhancing LUAD management.

Integrated radiomics and immune infiltration analysis to decipher immunotherapy efficacy in lung adenocarcinoma

Background

Research in recent years has witnessed unprecedented improvements in immunotherapy, especially immune checkpoint blockade (ICB) for the treatment of lung adenocarcinoma (LUAD) patients. Nevertheless, due to the heterogeneity of immunotherapy response, reliable biomarkers are urgently needed to guide precision cancer therapy. In this study, we aimed to identify immune subtypes in LUAD and develop a radiogenomic model to improve immunotherapy predictive accuracy.

Methods

In this study, clinical data of LUAD patients were downloaded from The Cancer Genome Atlas (TCGA) databases, and immune subtypes were identified using the ConsensusClusterPlus package in R. Biological, genomic, and epigenomic distinctions were compared. The TCGA cohort and clinical cohort from the Third Xiangya Hospital were utilized to demonstrate no significant differences of survival probability between sexes. Feature extraction and definition were conducted from 103 computed tomography (CT) images from The Cancer Imaging Archive (TCIA) dataset via the "PyRadiomics" embedded in Python. A series of machine learning techniques were applied to build a radiogenomic model.

Results

Two LUAD subtypes with different molecular and immune characteristics were identified. Significant differences in biological, genomic, and epigenomic distinctions among the two subtypes were observed (P<0.05). The immune subtype A participated in pathways related to immune activation and displayed a higher tumor microenvironment (TME) score (P<0.001) with a better prognosis of LUAD [overall survival (OS), P=0.037; disease-specific survival (DSS), P=0.034]. Besides, the model appears to show better fit for females (P=0.015) than for males (P=0.641). Our constructed radiogenomic model incorporating 12 radiomics features displayed satisfactory potential to facilitate the predictive accuracy of immunotherapy in LUAD [test area under the curve (AUC) =0.89; train AUC =0.95].

Conclusions

Our study presented a promising avenue to harness the rich radiomics data to identify the specific immune subtype and integrate it into the existing clinical decision-making system to facilitate the predictive accuracy of immunotherapy in LUAD.

Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) presents significant challenges in prognosis and treatment efficacy evaluation. While post-translational modifications are known to influence tumor progression, their prognostic value in LUAD remains largely unexplored.

METHODS

We developed a post-translational modification learning signature (PTMLS) using machine learning techniques, analyzing data from 1231 LUAD patients across seven global cohorts. The signature's efficacy in predicting immunotherapy response was evaluated using 12 immunotherapy cohorts spanning multiple cancer types (n=1201). An in-house LUAD tissue cohort (n=171) was used to validate beta-1,4-galactosyltransferase 2's (B4GALT2's) prognostic significance. The role of B4GALT2 in immune exclusion was investigated through in vivo and in vitro experiments.

RESULTS

The established PTMLS exhibited exceptional predictive capabilities in LUAD patient outcomes, surpassing the efficacy of 98 existing LUAD prognostic indicators. The system's predictive value was validated across diverse malignancy categories for immunotherapeutic response assessment. From a biological perspective, significant correlations were observed between PTMLS and immunological parameters, whereby elevated PTMLS levels were characterized by attenuated immune responses and immunologically cold neoplastic features. Within the PTMLS framework, B4GALT2 was identified as a crucial molecular component (r=0.82, p<0.05), and its heightened expression was linked to unfavorable clinical outcomes in LUAD cases, particularly in specimens exhibiting CD8-depleted phenotypes. The spatial distribution patterns between B4GALT2 and immune cell populations, specifically CD8+ T lymphocytes and CD20+ B lymphocytes, were elucidated through multiplexed immunofluorescence analysis. Laboratory investigations subsequently established B4GALT2's regulatory influence on LUAD cellular expansion in both laboratory cultures and animal models. Significantly, suppression of B4GALT2 was found to enhance CD8+ T lymphocyte populations and their functional status, thereby potentiating anti-programmed cell death protein 1 immunotherapeutic efficacy in animal studies. This phenomenon was characterized by reduced CD62L+CD8 T lymphocyte levels alongside elevated GZMB+/CD44+/CD69+CD8 T cell populations.

CONCLUSION

The developed PTMLS system represents an effective instrument for individualized prognostic evaluation and immunotherapy stratification in both LUAD and diverse cancer populations. The identification of B4GALT2 as a previously unrecognized oncogenic factor involved in immune exclusion presents a novel therapeutic avenue for LUAD treatment and immunotherapy optimization.

Resolving the spatial and cellular architecture of intra-tumor heterogeneity by multi-region dissection of lung adenocarcinoma

Although the spatial characteristics within the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) have been identified, the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear. Using spatial transcriptomics (ST) and single-cell RNA-sequencing (scRNA-seq) data from multi-regional LUAD biopsies consisting of tumor core, tumor edge, and normal area, we sought to delineate the spatial heterogeneity and driving factors of cell colocalization. Two cancer cell sub-clusters (Cancer_c1 and Cancer_c2), associated with LUAD initiation and metastasis, respectively, exhibit distinct spatial distributions and immune cell colocalizations. In particular, Cancer_c1, enriched within the tumor core, could directly interact with B cells or indirectly recruit B cells through macrophages. Conversely, Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8+ T cells. Collectively, our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD, providing insights for developing therapeutic strategies for cancer intervention.

Multi-omics analyses reveal biological and clinical insights in recurrent stage I non-small cell lung cancer

Post-operative recurrence rates of stage I non-small cell lung cancer (NSCLC) range from 20% to 40%. Nonetheless, the molecular mechanisms underlying recurrence hitherto remain largely elusive. Here, we generate genomic, epigenomic and transcriptomic profiles of paired tumors and adjacent tissues from 122 stage I NSCLC patients, among which 57 patients develop recurrence after surgery during follow-up. Integrated analyses illustrate that the presence of predominantly solid or micropapillary histological subtypes, increased genomic instability, and APOBEC-related signature are associated with recurrence. Furthermore, TP53 missense mutation in DNA-binding domain could contribute to shorter time to recurrence. DNA hypomethylation is pronounced in recurrent NSCLC, and PRAME is the significantly hypomethylated and overexpressed gene in recurrent lung adenocarcinoma (LUAD). Mechanistically, hypomethylation at TEAD1 binding site facilitates the transcriptional activation of PRAME. Inhibition of PRAME restrains the tumor metastasis via downregulation of epithelial-mesenchymal transition-related genes. We also identify that enrichment of AT2 cells with higher copy number variation burden, exhausted CD8 + T cells and Macro_SPP1, along with the reduced interaction between AT2 and immune cells, is essential for the formation of ecosystem in recurrent LUAD. Finally, multi-omics clustering could stratify the NSCLC patients into 4 subclusters with varying recurrence risk and subcluster-specific therapeutic vulnerabilities. Collectively, this study constitutes a promising resource enabling insights into the biological mechanisms and clinical management for post-operative recurrence of stage I NSCLC.

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.

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.

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

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

InTraSeq: A Multimodal Assay that Uncovers New Single-Cell Biology and Regulatory Mechanisms

Single-cell RNA sequencing (scRNA-seq) has revolutionized cell biology by enabling the profiling of transcriptomes at a single-cell resolution, leading to important discoveries that have advanced our understanding of cellular and tissue heterogeneity, developmental trajectories, and disease progression. Despite these important advances, scRNA-seq is limited to measuring the transcriptome providing a partial view of cellular function. To address this limitation, multimodal scRNA-seq assays have emerged, allowing for the simultaneous measurement of RNA expression and protein. Intracellular Transcriptomic and Protein Sequencing (InTraSeq), a novel multimodal scRNA-seq technology described here, enables the concurrent measurement of mRNA, surface markers, cytoplasmic proteins, and nuclear proteins within individual cells through oligo-barcoded antibodies. This method offers a comprehensive approach to studying cellular function by combining RNA and protein pro ling from the same sample and utilizing a relatively simple protocol. The InTraSeq method enables researchers to expand their view of critical intracellular protein expression including post-translational modifications (PTMs) and transcription factors, allowing for the identification of novel cellular subtypes and states that may be obscured by RNA-based analyses alone. This is particularly valuable in understanding the heterogeneity of cell populations and identifying distinct functional states. In this report, we used InTraSeq to characterize the complex cellular states and regulatory mechanisms during Th17 cell differentiation. We simultaneously pro led RNA and protein expression in over 85,000 cells, capturing transcriptional changes, changes in protein expression and the dynamics of signaling pathways at a high resolution. Our results revealed novel insights into Th17 cell differentiation, including the identification of key regulatory factors and their target genes. By simultaneously measuring mRNA, extra and intra-cellular proteins, signaling proteins, and PTMs, InTraSeq offers a comprehensive understanding of cellular processes and enables the identification of novel regulatory mechanisms.

Emerging strategies to investigate the biology of early cancer

Early detection and intervention of cancer or precancerous lesions hold great promise to improve patient survival. However, the processes of cancer initiation and the normal-precancer-cancer progression within a non-cancerous tissue context remain poorly understood. This is, in part, due to the scarcity of early-stage clinical samples or suitable models to study early cancer. In this Review, we introduce clinical samples and model systems, such as autochthonous mice and organoid-derived or stem cell-derived models that allow longitudinal analysis of early cancer development. We also present the emerging techniques and computational tools that enhance our understanding of cancer initiation and early progression, including direct imaging, lineage tracing, single-cell and spatial multi-omics, and artificial intelligence models. Together, these models and techniques facilitate a more comprehensive understanding of the poorly characterized early malignant transformation cascade, holding great potential to unveil key drivers and early biomarkers for cancer development. Finally, we discuss how these new insights can potentially be translated into mechanism-based strategies for early cancer detection and prevention.

Pulmonary Epithelium Cell Fate Determination: Chronic Obstructive Pulmonary Disease, Lung Cancer, or Both

The concurrence of chronic obstructive pulmonary disease (COPD) and lung cancer has been widely reported and extensively addressed by pulmonologists and oncologists. However, most studies have focused on shared risk factors, DNA damage pathways, immune microenvironments, inflammation, and imbalanced proteases/antiproteases. In the present review, we explore the association between COPD and lung cancer in terms of airway pluripotent cell fate determination and discuss the various cell types and signaling pathways involved in the maintenance of lung epithelium homeostasis and their involvement in the pathogenesis of co-occurring COPD and lung cancer.

Single-cell RNA sequencing reveals immune microenvironment niche transitions during the invasive and metastatic processes of ground-glass nodules and part-solid nodules in lung adenocarcinoma

BACKGROUND

Radiographically, ground-glass nodules (GGN) and part-solid nodules (PSN) in lung adenocarcinoma (LUAD) have significant heterogeneity in their clinical manifestations, biological characteristics, and prognosis. This study aimed to explore the heterogeneity of LUAD in different radiological phenotypes and associated factors influencing tumor evolution.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) on tumor tissues from eight and seven cases of GGN- and PSN-LUAD, respectively, at different disease stages, including minimally invasive adenocarcinoma (MIA), invasive adenocarcinoma (IAC), and metastatic lung cancer (MLC). Additionally, we analyzed adjacent normal tissues from four cases. Immunohistochemistry, multiplex immunofluorescence, and external scRNA-seq data were employed to confirm the expression of signature genes as well as the distribution patterns of CXCL9 + TAMs and TREM2 + TAMs. A LUAD mouse model was generated using gene editing, organoid culture, and orthotopic transplantation techniques, and comprehensive analyses such as histopathology, RNA sequencing, and Western blotting were performed to validate key pathways.

RESULTS

Diverse cellular compositions were observed in the tumor microenvironment (TME) during GGN- and PSN-LUAD invasion and metastasis. Notably, CXCL9 + and TREM2 + tumor-associated macrophages (TAMs) exhibited the most significant enrichment changes. It was found that GGN-LUAD exhibited a stronger immune response than PSN-LUAD, with increased interaction between CXCL9 + TAMs and CD8 + tissue-resident memory T cells during invasion stage (MIA-IAC). Conversely, greater interactions between TREM2 + TAMs and tumor cells were observed in PSN-LUAD during the MLC stage. Additionally, TREM2 + TAMs were found to differentiate into TREM2 + /SPP1 + and TREM2 + /SPP1- TAMs at different stages, which promotes tumor progression. This study also emphasizes that during the transdifferentiation process of GGN- and PSN-LUAD, IFN-γ activates the STAT1 signaling pathway to regulate the activation of CXCL9 + TAMs, and further recruiting CD8 + Trm cells and activating T cells through MHC class I antigen presentation. The role of the IFN-γ/STAT1 pathway in the occurrence and development of LUAD was further validated by animal experiments.

CONCLUSIONS

Our findings offer a potential therapeutic strategy to maintain a dynamic balance within the TME and improve the immunotherapy efficacy by modulating the relative proportions and functional states of CXCL9 + TAMs and TREM2 + TAMs.

Five-gene prognostic model based on autophagy-dependent cell death for predicting prognosis in lung adenocarcinoma

Non-small cell lung adenocarcinoma (LUAD) is the predominant form of lung cancer originating from lung epithelial cells, making it the most prevalent pathological type. Currently, reliable indicators for predicting treatment efficacy and disease prognosis are lacking. Despite extensive validation of autophagy-dependent cell death (ADCD) in solid tumor studies and its correlation with immunotherapy effectiveness and cancer prognosis, systematic research on ADCD-related genes in LUAD is limited. We utilized AddModuleScore, ssGSEA, and WGCNA to identify genes associated with ADCD across single-cell and bulk transcriptome datasets. The TCGA dataset, comprising 598 cases, was randomly divided into training and validation sets to develop an ADCD-related LUAD prediction model. Internal validation was performed using the TCGA validation set. For external validation, datasets GSE13213 (119 LUAD samples), GSE26939 (115 LUAD samples), GSE29016 (39 LUAD samples), and GSE30219 (86 LUAD samples) were employed. We evaluated the model's accuracy and effectiveness in predicting prognostic risk. Additionally, CIBERSORT, ESTIMATE, and ssGSEA techniques were used to explore immunological characteristics, drug response, and gene expression in LUAD. Real-time RT-PCR was conducted to assess variations in mRNA expression levels of the gene XCR1 between cancerous and normal tissues in 10 lung cancer patients. We identified 249 genes associated with autophagy-dependent cell death (ADCD) at both single-cell and bulk transcriptome levels. Univariate COX regression analysis revealed that 18 genes were significantly associated with overall survival (OS). Using LASSO-Cox analysis, we developed an ADCD signature based on five genes (BIRC3, TAP1, SLAMF1, XCR1, and HLA-DMB) and created the ADCD-related risk scoring system (ADCDRS). Validation of this model demonstrated its ability to predict disease prognosis and its correlation with clinical characteristics, immune cell infiltration, and the tumor microenvironment. To enhance clinical applicability, we integrated an ADCDRS nomogram. Furthermore, we identified potential drugs targeting specific risk subgroups. We successfully identified a model based on five ADCD genes to predict disease prognosis and treatment efficacy in LUAD, as well as to assess the tumor immune microenvironment. An efficient and practical ADCDRS nomogram was designed.

Histological transformation in lung adenocarcinoma: Insights of mechanisms and therapeutic windows

Histological transformation from lung adenocarcinoma (ADC) to small cell lung carcinoma (SCLC), large cell neuroendocrine carcinoma (LCNEC), squamous cell carcinoma (SCC), and sarcomatoid carcinoma (PSC) after targeted therapies is recognized as a mechanism of resistance in ADC treatments. Patients with transformed lung cancer typically experience a poor prognosis and short survival time. However, effective treatment options for these patients are currently lacking. Therefore, understanding the mechanisms underlying histological transformation is crucial for the development of effective therapies. Hypotheses including intratumoral heterogeneity, cancer stem cells, and alteration of suppressor genes have been proposed to explain the mechanism of histological transformation. In this review, we provide a comprehensive overview of the known molecular features and signaling pathways of transformed tumors, and summarized potential therapies based on previous findings.

Leveraging mitochondrial-programmed cell death dynamics to enhance prognostic accuracy and immunotherapy efficacy in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease, posing significant challenges to accurate prognosis prediction. Mitochondria play a central role in the energy metabolism of eukaryotic cells and can influence programmed cell death (PCD) mechanisms, which are critical in tumorigenesis and cancer progression. However, the prognostic significance of the interplay between mitochondrial function and PCD in LUAD requires further investigation.

METHODS

We analyzed data from 1231 LUAD patients across seven global cohorts to develop a mitochondrial-related PCD signature (MPCDS) using machine learning. Validation was done using six immunotherapy cohorts (LUAD, melanoma, clear cell renal cell carcinoma; n=935) and a pan-cancer cohort of 21 tumor types. An in-house LUAD tissue cohort (n=100) confirmed the prognostic significance of nucleoside diphosphate kinase 4 (NME4). In vivo and in vitro experiments explored NME4's role in immune exclusion.

RESULTS

The MPCDS demonstrated strong predictive performance for prognosis in LUAD patients, surpassing 114 previously published LUAD signatures. Additionally, MPCDS effectively predicted outcomes in immunotherapy patients (including those with LUAD, melanoma, and clear cell renal cell carcinoma). Biologically, MPCDS was significantly associated with immune features, with the high MPCDS group exhibiting reduced immune activity and a tendency towards cold tumors. NME4, a key gene within the MPCDS (correlation=0.55, p<0.05), was associated with poorer prognosis in LUAD patients with high expression, particularly in CD8 desert phenotypes, as validated by our in-house cohort. Multiplex immunofluorescence confirmed the spatial colocalization and exclusion relationship between NME4 and immune cells such as CD3+ T cells and CD20+ B cells. Further experiments revealed that NME4 regulated the proliferation and invasion of LUAD cells both in vitro and in vivo. Importantly, inhibiting NME4 increased the abundance and activity of CD8+ T cells and enhanced the antitumor immunity of anti-programmed cell death protein-1 therapy in vivo.

CONCLUSION

The MPCDS provides personalized risk assessment and immunotherapy interventions for individual LUAD patients. NME4, a key gene within the MPCDS, has been identified as a novel oncogene associated with immune exclusion and may serve as a new target for LUAD intervention and immunotherapy.

Transcriptomic Heterogeneity of EGFR-Mutant Non-Small Cell Lung Cancer Evolution Toward Small-Cell Lung Cancer

PURPOSE

Histologic transformation from EGFR-mutant non-small cell lung cancer (NSCLC) to small-cell lung cancer (SCLC) is a key mechanism of resistance to EGFR tyrosine kinase inhibitors (TKI). However, transcriptomic changes between NSCLC and transformed SCLC (t-SCLC) remain unexplored.

EXPERIMENTAL DESIGN

We conducted whole-transcriptome analysis of 59 regions of interest through the spatial profiling of formalin-fixed, paraffin-embedded tissues obtained from 10 patients (lung adenocarcinoma, 22; combined SCLC/NSCLC, 7; and t-SCLC, 30 regions of interests). Transcriptomic profiles and differentially expressed genes were compared between pre- and post-transformed tumors.

RESULTS

Following EGFR-TKI treatment, 93.7% (15/16) of t-SCLC components evolved into neuroendocrine-high subtypes (SCLC-A or SCLC-N). The transition to t-SCLC occurred regardless of EGFR-TKI treatment and EGFR mutational status, with a notable decrease in EGFR expression (P < 0.001) at both mRNA and protein levels. Pathway analysis revealed that gene overexpression was related to epigenetic alterations in t-SCLC. Interestingly, histone deacetylase inhibitors restored EGFR expression in SNU-2962A cells and their organoid model. The synergistic effects of third-generation EGFR-TKI osimertinib and the histone deacetylase inhibitor fimepinostat were validated in both in vitro and in vivo models.

CONCLUSIONS

Our study demonstrated that most t-SCLC cases showed neuronal subtypes with low EGFR expression. Differentially expressed gene analysis and t-SCLC preclinical models identified an epigenetic modifier as a promising treatment strategy for t-SCLC.

Tumor immune microenvironment analysis of non-small cell lung cancer development through multiplex immunofluorescence

Background

Emerging evidence has underscored the crucial role of infiltrating immune cells in the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) development and progression. With the implementation of screening programs, the incidence of early-stage NSCLC is rising. However, the high risk of recurrence and poor survival rates associated with this disease necessitate a deeper understanding of the TIME and its relationship with driver alterations. The aim of this study was to provide an in-depth analysis of immune changes in early-stage NSCLC, highlighting the significant transitions in immune response during disease progression.

Methods

Tumor tissues were collected from 105 patients with precancerous lesions or stage I-III NSCLC. Next-generation sequencing (NGS) was used to detect cancer driver alterations. Multiplex immunofluorescence (mIF) was performed to evaluate immune cell density, percentage, and spatial proximity to cancer cells in the TIME. Next Among these patients, 64 had NGS results, including three with adenocarcinoma in situ (AIS), 10 with minimally invasive adenocarcinoma (MIA), and 51 with stage I invasive cancers. Additionally, three patients underwent neoadjuvant immuno-chemotherapy and tumor tissue specimens before and after treatment were obtained.

Results

Patients with stage I invasive cancer had significantly higher density (P=0.01) and percentage (P=0.02) of CD8+ T cells and higher percentages of M1 macrophages (P=0.04) and immature natural killer (NK) cells (P=0.041) in the tumor parenchyma compared to those with AIS/MIA. Patients with mutated epidermal growth factor receptor (EGFR) gene exhibited decreased NK cell infiltration, increased M2 macrophage infiltration, and decreased aggregation of CD4+ T cells near tumor cells compared to EGFR wild-type patients. As NSCLC progressed from stage I to III, CD8+ T cell density and proportion increased, while PD-L1+ tumor cells were in closer proximity to PD-1+CD8+ T cells, potentially inhibiting CD8+ T cell function. Furthermore, M1 macrophages decreased in density and proportion, and the number of NK cells, macrophages, and B cells around tumor cells decreased. Additionally, patients with tertiary lymphoid structures (TLSs) had significantly higher proportion of M1 macrophages and lymphocytes near tumor cells, whereas those without TLS had PD-L1+ tumor cells more densely clustered around PD-1+CD8+ T cells. Notably, neoadjuvant immuno-chemotherapy induced the development of TLS.

Conclusions

This study offers an in-depth analysis of immune changes in NSCLC, demonstrating that the transition from AIS/MIA to invasive stage I NSCLC leads to immune activation, while the advancement from stage I to stage III cancer results in immune suppression. These findings contribute to our understanding of the molecular mechanisms underlying early-stage NSCLC progression and pave the way for the identification of potential treatment options.

Alveolar type 2 cells marker gene SFTPC inhibits epithelial-to-mesenchymal transition by upregulating SOX7 and suppressing WNT/β-catenin pathway in non-small cell lung cancer

Introduction

Surfactant Protein C gene (SFTPC) is a marker gene of alveolar type 2 cells (AT2), which are the key structures of alveoli. Mutations or deletions in SFTPC cause idiopathic pulmonary fibrosis (IPF). Importantly, IPF is an independent risk factor for non-small cell lung cancer (NSCLC). It suggests that abnormal expression of SFTPC may be relevant to development of NSCLC. However, the function and mechanism of SFTPC in NSCLC are still poor understood until now.

Methods

The expression of SFTPC and the relationship between SFTPC and prognosis of NSCLC were analyzed in TCGA database and our collected clinical NSCLC tissues. Subsequently, the function and mechanism of SFTPC in NSCLC were explored by RNA-sequence, qRT-PCR, Western blot, Immunohistochemical, Wound-healing, Millicell, Transwell assays and mouse tumor xenograft model.

Results

SFTPC was dramatically downregulated in NSCLC tissues from TCGA database and 40 out of 46 collected clinical LUAD tissues compared with adjacent non-tumor tissues. Low expression of SFTPC was associated with poor prognosis of LUAD by TCGA database. Importantly, we confirmed that overexpression of SFTPC significantly inhibited Epithelial-to-Mesenchymal Transition (EMT) process of NSCLC cells by upregulating SOX7 and then inactivating WNT/β-catenin pathway in vitro and in vivo. Particularly, we discovered that low expression of SFTPC was associated with EMT process and low expression of SOX7 in NSCLC tissues.

Conclusion

Our study revealed a novel mechanism of SFTPC in NSCLC development. Meanwhile, it also might provide a new clue for exploring the molecular mechanism about NSCLC development in patients with IPF in the future.

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors

Lung cancer is the leading cause of cancer mortality worldwide. KRAS oncogenes are responsible for at least a quarter of lung adenocarcinomas, the main subtype of lung cancer. After four decades of intense research, selective inhibitors of KRAS oncoproteins are finally reaching the clinic. Yet, their effect on overall survival is limited due to the rapid appearance of drug resistance, a likely consequence of the high intratumoral heterogeneity characteristic of these tumors. In this study, we have attempted to identify those functional alterations that result from KRAS oncoprotein expression during the earliest stages of tumor development. Such functional changes are likely to be maintained during the entire process of tumor progression regardless of additional co-occurring mutations. Single-cell RNA sequencing analysis of murine alveolar type 2 cells expressing a resident Kras oncogene revealed impairment of the type I interferon pathway, a feature maintained throughout tumor progression. This alteration was also present in advanced murine and human tumors harboring additional mutations in the p53 or LKB1 tumor suppressors. Restoration of type I interferon (IFN) signaling by IFN-β or constitutive active stimulator of interferon genes (STING) expression had a profound influence on the tumor microenvironment, switching them from immunologically "cold" to immunologically "hot" tumors. Therefore, enhancement of the type I IFN pathway predisposes KRAS mutant lung tumors to immunotherapy treatments, regardless of co-occurring mutations in p53 or LKB1.

Single-Cell Transcriptome Analysis Reveals 2 Subtypes of Tumor Cells of Sclerosing Pneumocytoma With Distinct Molecular Features and Clinical Implications

Pulmonary sclerosing pneumocytoma (PSP) is a rare, distinctive benign lung adenoma of pneumocyte origin. Despite its rarity, the tumor's unique cellular morphology has sparked ongoing debates regarding the origin of its constituent cells. This study aimed to elucidate the molecular features of PSP tumor cells and enhance our understanding of the cellular processes contributing to PSP formation and biological behavior. Tissue samples from PSP and corresponding normal lung tissues (n = 4) were collected. We employed single-cell RNA sequencing and microarray-based spatial transcriptomic analyses to identify cell types and investigate their transcriptomes, with a focus on transcription factors, enriched gene expression, and single-cell trajectory evaluations. Our analysis identified 2 types of tumor cells: mesenchymal-epithelial dual-phenotype (MEDP) cells and a distinct subpopulation of type II alveolar epithelial cells exhibiting characteristics slightly reminiscent of type I alveolar epithelial cells (AT2Cs) corresponding to histologic round stromal cells and surface cuboidal cells, respectively. MEDP cells displayed weak alveolar epithelial differentiation but strong collagen production capabilities, as indicated by the expression of both TTF-1 and vimentin. These cells played a pivotal role in forming the solid and sclerotic areas of PSP. Moreover, MEDP cells exhibited a pronounced propensity for epithelial-mesenchymal transition, suggesting a greater potential for metastasis compared with AT2Cs. The capillary endothelial cells of PSP displayed notable diversity. Overall, this study provides, for the first time, a comprehensive mapping of the single-cell transcriptome profile of PSP. Our findings delineate 2 distinct subtypes of tumor cells, MEDP cells and AT2Cs, each with its own biological characteristics and spatial distribution. A deeper understanding of these cell types promises insights into the histology and biological behaviors of this rare tumor.

Dynamic immunoediting by macrophages in homologous recombination deficiency-stratified pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.

Molecular characteristics and oncogenic role of CHD family genes: a pan-cancer analysis based on bioinformatic and biological analysis

Chromodomain helicase DNA-binding protein (CHD) gene family, an ATP (adenosine triphosphate) -dependent chromatin remodeler family, is involved in multiple developmental process and tumor development. However, there have been none pan-cancer analyses of this family. The expression levels, survival profiles, mutation profiles and immune infiltration of the CHD family genes from TCGA and TARGET database were analyzed using online tools or R packages. Interestingly, all types of CHD gene expressions were associated with the prognosis of Neuroblastoma, Acute lymphoblastic leukemia-Phase 3 and Acute Myeloid Leukemia (All P < 0.05). Knock down of CHD7 and CHD9 in K562 (human erythromyeloblastoid leukemia) and HEC-1-B (human endometrial adenocarcinoma) cells significantly inhibit cell proliferation and migration (P < 0.05). Proliferation, colony formation and migration assays were performed in CHD7 and CHD9 knockdown K562 and HBC-1-B cell lines. Mechanisms were also analyzed by PPI and GO ontology for our experiments. Histone modification, especially the methylation of H3K4, might be involved in CHD7 and CHD9 related oncogenesis. Through bioinformatic analysis, we showed CHD genes significantly affected the prognosis of different tumor types, including childhood tumor. Our findings provide new insights into the function and mechanism of CHD gene family, especially in CHD7 and CHD9.

The prognostic impact of pathogenic stromal cell-associated genes in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) stands as the most prevalent subtype among lung cancers. Interactions between stromal and cancer cells influence tumor growth, invasion, and metastasis. However, the regulatory mechanisms of stromal cells in the lung adenocarcinoma tumor microenvironment remain unclear. This study seeks to elucidate the regulatory connections among critical pathogenic genes and their associated expression variations within distinct stromal cell subtypes.

METHOD

Analysis and investigation were conducted on a total of 114,019 single-cell RNA data and 346 The Cancer Genome Atlas (TCGA) LUAD-related samples using bioinformatics and statistical algorithms. Differential gene expression analysis was performed for tumor samples and controls, followed by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Differential genes between stromal cells and other cell clusters were identified and intersected with the differential genes from TCGA. We employed a combination of LASSO regression and multivariable Cox regression to identify the ultimate set of pathogenic gene. Survival models were trained to predict the relationship between patient survival and these pathogenic genes. Analysis of transcription factor (TF) cell specificity and pseudotime trajectories within stromal cell subpopulations revealed that vascular endothelial cells (ECs) and matrix cancer-associated fibroblasts (CAFs) are key in regulation of the prognosis-associated genes CAV2, COL1A1, TIMP1, ETS2, AKAP12, ID1 and COL1A2.

RESULTS

Seven pathogenic genes associated with LUAD in stromal cells were identified and used to develop a survival model. High expression of these genes is linked to a greater risk of poor survival. Stromal cells were categorized into eight subtypes and one unannotated cluster. Mesothelial cells, vascular endothelial cells (ECs), and matrix cancer-associated fibroblasts (CAFs) showed cell-specific regulation of the pathogenic genes.

CONCLUSIONS

The seven disease-causing genes in vascular ECs and matrix CAFs can be used to detect the survival status of LUAD patients, providing new directions for future targeted drug design.

Machine learning-based integration of CD8 T cell-related gene signatures for comprehensive prognostic assessment in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) stands as the most prevalent histological subtype of lung cancer, exhibiting heterogeneity in outcomes and diverse responses to therapy. CD8 T cells are consistently present throughout all stages of tumor development and play a pivotal role within the tumor microenvironment (TME). Our objective was to investigate the expression profiles of CD8 T cell marker genes, establish a prognostic risk model based on these genes in LUAD, and explore its relationship with immunotherapy response.

Methods

By leveraging the expression data and clinical records from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts, we identified 23 consensus prognostic genes. Employing ten machine-learning algorithms, we generated 101 combinations, ultimately selecting the optimal algorithm to construct an artificial intelligence-derived prognostic signature named riskScore. This selection was based on the average concordance index (C-index) across three testing cohorts.

Results

RiskScore emerged as an independent risk factor for overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS) in LUAD. Notably, riskScore exhibited notably superior predictive accuracy compared to traditional clinical variables. Furthermore, we observed a positive correlation between the high-risk riskScore group and tumor-promoting biological functions, lower tumor mutational burden (TMB), lower neoantigen (NEO) load, and lower microsatellite instability (MSI) scores, as well as reduced immune cell infiltration and an increased probability of immune evasion within the TME. Of significance, the immunophenoscore (IPS) score displayed significant differences among risk subgroups, and riskScore effectively stratified patients in the IMvigor210 and GSE135222 immunotherapy cohort based on their survival outcomes. Additionally, we identified potential drugs that could target specific risk subgroups.

Conclusions

In summary, riskScore demonstrates its potential as a robust and promising tool for guiding clinical management and tailoring individualized treatments for LUAD patients.

Multi-omics analysis unveils immunosuppressive microenvironment in the occurrence and development of multiple pulmonary lung cancers

Multiple pulmonary lung cancers (MPLCs) are frequently encountered on computed tomography (CT) scanning of chest, yet their intrinsic characteristics associated with genomic features and radiological or pathological textures that may lead to distinct clinical outcomes remain largely unexplored. A total of 27 pulmonary nodules covering different radiological or pathological textures as well as matched adjacent normal tissues and blood samples were collected from patients diagnosed with MPLCs. Whole-exome sequencing (WES) and whole-transcriptome sequencing were performed. The molecular and immune features of MPLCs associated with distinct radiological or pathological textures were comprehensively investigated. Genomics analysis unveiled the distinct branches of pulmonary nodules originating independently within the same individual. EGFR and KRAS mutations were found to be prevalent in MPLCs, exhibiting mutual exclusivity. The group with KRAS mutations exhibited stronger immune signatures compared to the group with EGFR mutations. Additionally, MPLCs exhibited a pronounced immunosuppressive microenvironment, which was particularly distinct when compared with normal tissues. The expression of the FDSCP gene was specifically observed in MPLCs. When categorizing MPLCs based on radiological or pathological characteristics, a progressive increase in mutation accumulation was observed, accompanied by heightened chromatin-level instability as ground-glass opacity component declined or invasive progression occurred. A close association with the immunosuppressive microenvironment was also observed during the progression of pulmonary nodules. Notably, the upregulation of B cell and regulatory T cell marker genes occurred progressively. Immune cell abundance analysis further demonstrated a marked increase in exhausted cells and regulatory T cells during the progression of pulmonary nodules. These results were further validated by independent datasets including nCounter RNA profiling, single-cell RNA sequencing, and spatial transcriptomic datasets. Our study provided a comprehensive representation of the diverse landscape of MPLCs originating within the same individual and emphasized the significant influence of the immunosuppressive microenvironment in the occurrence and development of pulmonary nodules. These findings hold great potential for enhancing the clinical diagnosis and treatment strategies for MPLCs.

Early human fetal lung atlas reveals the temporal dynamics of epithelial cell plasticity

Studying human fetal lungs can inform how developmental defects and disease states alter the function of the lungs. Here, we sequenced >150,000 single cells from 19 healthy human pseudoglandular fetal lung tissues ranging between gestational weeks 10-19. We capture dynamic developmental trajectories from progenitor cells that express abundant levels of the cystic fibrosis conductance transmembrane regulator (CFTR). These cells give rise to multiple specialized epithelial cell types. Combined with spatial transcriptomics, we show temporal regulation of key signalling pathways that may drive the temporal and spatial emergence of specialized epithelial cells including ciliated and pulmonary neuroendocrine cells. Finally, we show that human pluripotent stem cell-derived fetal lung models contain CFTR-expressing progenitor cells that capture similar lineage developmental trajectories as identified in the native tissue. Overall, this study provides a comprehensive single-cell atlas of the developing human lung, outlining the temporal and spatial complexities of cell lineage development and benchmarks fetal lung cultures from human pluripotent stem cell differentiations to similar developmental window.

Early-stage lung cancer is driven by a transitional cell state dependent on a KRAS-ITGA3-SRC axis

Glycine-12 mutations in the GTPase KRAS (KRASG12) are an initiating event for development of lung adenocarcinoma (LUAD). KRASG12 mutations promote cell-intrinsic rewiring of alveolar type-II progenitor (AT2) cells, but to what extent such changes interplay with lung homeostasis and cell fate pathways is unclear. Here, we generated single-cell RNA-seq (scRNA-seq) profiles from AT2-mesenchyme organoid co-cultures, mice, and stage-IA LUAD patients, identifying conserved regulators of AT2 transcriptional dynamics and defining the impact of KRASG12D mutation with temporal resolution. In AT2WT organoids, we found a transient injury/plasticity state preceding AT2 self-renewal and AT1 differentiation. Early-stage AT2KRAS cells exhibited perturbed gene expression dynamics, most notably retention of the injury/plasticity state. The injury state in AT2KRAS cells of patients, mice, and organoids was distinguishable from AT2WT states via altered receptor expression, including co-expression of ITGA3 and SRC. The combination of clinically relevant KRASG12D and SRC inhibitors impaired AT2KRAS organoid growth. Together, our data show that an injury/plasticity state essential for lung repair is co-opted during AT2 self-renewal and LUAD initiation, suggesting that early-stage LUAD may be susceptible to interventions that target specifically the oncogenic nature of this cell state.

Smoking-induced CCNA2 expression promotes lung adenocarcinoma tumorigenesis by boosting AT2/AT2-like cell differentiation

Lung adenocarcinoma (LUAD), a type of non-small cell lung cancer (NSCLC), originates from not only bronchial epithelial cells but also alveolar type 2 (AT2) cells, which could differentiate into AT2-like cells. AT2-like cells function as cancer stem cells (CSCs) of LUAD tumorigenesis to give rise to adenocarcinoma. However, the mechanism underlying AT2 cell differentiation into AT2-like cells in LUAD remains unknown. We analyze genes differentially expressed and genes with significantly different survival curves in LUAD, and the combination of these two analyses yields 147 differential genes, in which 14 differentially expressed genes were enriched in cell cycle pathway. We next analyze the protein levels of these genes in LUAD and find that Cyclin-A2 (CCNA2) is closely associated with LUAD tumorigenesis. Unexpectedly, high CCNA2 expression in LUAD is restrictedly associated with smoking and independent of other driver mutations. Single-cell sequencing analyses reveal that CCNA2 is predominantly involved in AT2-like cell differentiation, while inhibition of CCNA2 significantly reverses smoking-induced AT2-like cell differentiation. Mechanistically, CCNA2 binding to CDK2 phosphorylates the AXIN1 complex, which in turn induces ubiquitination-dependent degradation of β-catenin and inhibits the WNT signaling pathway, thereby failing AT2 cell maintenance. These results uncover smoking-induced CCNA2 overexpression and subsequent WNT/β-catenin signaling inactivation as a hitherto uncharacterized mechanism controlling AT2 cell differentiation and LUAD tumorigenesis.

Cell of origin alters myeloid-mediated immunosuppression in lung adenocarcinoma

Solid carcinomas are often highly heterogenous cancers, arising from multiple epithelial cells of origin. Yet, how the cell of origin influences the response of the tumor microenvironment is poorly understood. Lung adenocarcinoma (LUAD) arises in the distal alveolar epithelium which is populated primarily by alveolar epithelial type I (AT1) and type II (AT2) cells. It has been previously reported that Gramd2 + AT1 cells can give rise to a histologically-defined LUAD that is distinct in pathology and transcriptomic identity from that arising from Sftpc + AT2 cells1,2. To determine how cells of origin influence the tumor immune microenvironment (TIME) landscape, we comprehensively characterized transcriptomic, molecular, and cellular states within the TIME of Gramd2 + AT1 and Sftpc + AT2-derived LUAD using KRASG12D oncogenic driver mouse models. Myeloid cells within the Gramd2 + AT1-derived LUAD TIME were increased, specifically, immunoreactive monocytes and tumor associated macrophages (TAMs). In contrast, the Sftpc + AT2 LUAD TIME was enriched for Arginase-1+ myeloid derived suppressor cells (MDSC) and TAMs expressing profiles suggestive of immunosuppressive function. Validation of immune infiltration was performed using flow cytometry, and intercellular interaction analysis between the cells of origin and major myeloid cell populations indicated that cell-type specific markers SFTPD in AT2 cells and CAV1 in AT1 cells mediated unique interactions with myeloid cells of the differential immunosuppressive states within each cell of origin mouse model. Taken together, Gramd2 + AT1-derived LUAD presents with an anti-tumor, immunoreactive TIME, while the TIME of Sftpc + AT2-derived LUAD has hallmarks of immunosuppression. This study suggests that LUAD cell of origin influences the composition and suppression status of the TIME landscape and may hold critical implications for patient response to immunotherapy.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

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

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

Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature

We employed single-cell analysis techniques, specifically the inferCNV method, to dissect the complex progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) through minimally invasive adenocarcinoma (MIA) to invasive adenocarcinoma (IAC). This approach enabled the identification of Cluster 6, which was significantly associated with LUAD progression. Our comprehensive analysis included intercellular interaction, transcription factor regulatory networks, trajectory analysis, and gene set variation analysis (GSVA), leading to the development of the lung progression associated signature (LPAS). Interestingly, we discovered that the LPAS not only accurately predicts the prognosis of LUAD patients but also forecasts genomic alterations, distinguishes between 'cold' and 'hot' tumours, and identifies potential candidates suitable for immunotherapy. PSMB1, identified within Cluster 6, was experimentally shown to significantly enhance cancer cell invasion and migration, highlighting the clinical relevance of LPAS in predicting LUAD progression and providing a potential target for therapeutic intervention. Our findings suggest that LPAS offers a novel biomarker for LUAD patient stratification, with significant implications for improving prognostic accuracy and guiding treatment decisions.

Integrated single-cell transcriptome and T cell receptor profiling reveals defects of T cell exhaustion in pulmonary tuberculosis

Tuberculosis-affected lungs with chronic inflammation harbor abundant immunosuppressive immune cells but the nature of such inflammation is unclear. Dysfunction in T cell exhaustion, while implicated in chronic inflammatory diseases, remains unexplored in tuberculosis. Given that immunotherapy targeting exhaustion checkpoints exacerbates tuberculosis, we speculate that T cell exhaustion is dysfunctional in tuberculosis. Using integrated single-cell RNA sequencing and T cell receptor profiling we reported defects in exhaustion responses within inflamed tuberculosis-affected lungs. Tuberculosis lungs demonstrated significantly reduced levels of exhausted CD8+ T cells and exhibited diminished expression of exhaustion-related transcripts among clonally expanded CD4+ and CD8+ T cells. Additionally, clonal expansion of CD4+ and CD8+ T cells bearing T cell receptors specific for CMV was observed. Expanded CD8+ T cells expressed the cytolytic marker GZMK. Hence, inflamed tuberculosis-affected lungs displayed dysfunction in T cell exhaustion. Our findings likely hold implications for understanding the reactivation of tuberculosis observed in patients undergoing immunotherapy targeting the exhaustion checkpoint.

Integrated whole-exome and bulk transcriptome sequencing delineates the dynamic evolution from preneoplasia to invasive lung adenocarcinoma featured with ground-glass nodules

OBJECTIVE

The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC.

METHODS

Thirty-five patients with ground-glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA-Seq were subsequently analyzed.

RESULTS

The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co-mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD.

CONCLUSIONS

Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC.

Multidimensional biological characteristics of ground glass nodules

The detection rate of ground glass nodules (GGNs) has increased in recent years because of their malignant potential but relatively indolent biological behavior; thus, correct GGN recognition and management has become a research focus. Many scholars have explored the underlying mechanism of the indolent progression of GGNs from several perspectives, such as pathological type, genomic mutational characteristics, and immune microenvironment. GGNs have different major mutated genes at different stages of development; EGFR mutation is the most common mutation in GGNs, and p53 mutation is the most abundant mutation in the invasive stage of GGNs. Pure GGNs have fewer genomic alterations and a simpler genomic profile and exhibit a gradually evolving genomic mutation profile as the pathology progresses. Compared to advanced lung adenocarcinoma, GGN lung adenocarcinoma has a higher immune cell percentage, is under immune surveillance, and has less immune escape. However, as the pathological progression and solid component increase, negative immune regulation and immune escape increase gradually, and a suppressive immune environment is established gradually. Currently, regular computer tomography monitoring and surgery are the main treatment strategies for persistent GGNs. Stereotactic body radiotherapy and radiofrequency ablation are two local therapeutic alternatives, and systemic therapy has been progressively studied for lung cancer with GGNs. In the present review, we discuss the characterization of the multidimensional molecular evolution of GGNs that could facilitate more precise differentiation of such highly heterogeneous lesions, laying a foundation for the development of more effective individualized treatment plans.

Inflammation-based lung adenocarcinoma molecular subtype identification and construction of an inflammation-related signature with bulk and single-cell RNA-seq data

The role of inflammation is increasingly understood to have a central influence on therapeutic outcomes and prognosis in lung adenocarcinoma (LUAD). However, the detailed molecular divisions involved in inflammatory responses are yet to be fully elucidated. Our study identified two main inflammation-oriented LUAD grades: the inflammation-low (INF-low) and the inflammation-high (INF-high) subtypes. Both presented with unique clinicopathological features, implications for prognosis, and distinctive tumor microenvironment profiles. Broadly, the INF-low grade, marked by its dominant immunosuppressive tumor microenvironment, was accompanied by less favorable prognostic outcomes and a heightened prevalence of oncogenic mutations. In contrast, the INF-high grade exhibited more optimistic clinical trajectories, underscored by its immune-active environment. In addition, our efforts led to the conceptualization and empirical validation of an inflammation-centric predictive model with considerable predictive potency. Our study paves the way for a refined inflammation-centric LUAD classification and fosters a deeper understanding of tumor microenvironment intricacies.

CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

The evolution of lung adenocarcinoma precursors is associated with chromosomal instability and transition from innate to adaptive immune response/evasion

Studying lung adenocarcinoma (LUAD) early carcinogenesis is challenging, primarily due to the lack of LUAD precursors specimens. We amassed multi-omics data from 213 LUAD and LUAD precursors to identify molecular features underlying LUAD precancer evolution. We observed progressively increasing mutations, chromosomal aberrations, whole genome doubling and genomic instability from precancer to invasive LUAD, indicating aggravating chromosomal instability (CIN). Telomere shortening, a crucial genomic alteration linked to CIN, emerged at precancer stage. Moreover, later-stage lesions demonstrated increasing cancer stemness and decreasing alveolar identity, suggesting epithelial de-differentiation during early LUAD carcinogenesis. The innate immune cells progressively diminished from precancer to invasive LUAD, concomitant with a gradual recruitment of adaptive immune cells (except CD8+ and gamma-delta T cells that decreased in later stages) and upregulation of numerous immune checkpoints, suggesting LUAD precancer evolution is associated with a shift from innate to adaptive immune response and immune evasion mediated by various mechanisms.

Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis.

METHODS

Enzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed.

RESULTS

Methylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD.

CONCLUSIONS

This study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

Single-cell and single-nucleus RNA-sequencing from paired normal-adenocarcinoma lung samples provide both common and discordant biological insights

Whether single-cell RNA-sequencing (scRNA-seq) captures the same biological information as single-nucleus RNA-sequencing (snRNA-seq) remains uncertain and likely to be context-dependent. Herein, a head-to-head comparison was performed in matched normal-adenocarcinoma human lung samples to assess biological insights derived from scRNA-seq versus snRNA-seq and better understand the cellular transition that occurs from normal to tumoral tissue. Here, the transcriptome of 160,621 cells/nuclei was obtained. In non-tumor lung, cell type proportions varied widely between scRNA-seq and snRNA-seq with a predominance of immune cells in the former (81.5%) and epithelial cells (69.9%) in the later. Similar results were observed in adenocarcinomas, in addition to an overall increase in cell type heterogeneity and a greater prevalence of copy number variants in cells of epithelial origin, which suggests malignant assignment. The cell type transition that occurs from normal lung tissue to adenocarcinoma was not always concordant whether cells or nuclei were examined. As expected, large differential expression of the whole-cell and nuclear transcriptome was observed, but cell-type specific changes of paired normal and tumor lung samples revealed a set of common genes in the cells and nuclei involved in cancer-related pathways. In addition, we showed that the ligand-receptor interactome landscape of lung adenocarcinoma was largely different whether cells or nuclei were evaluated. Immune cell depletion in fresh specimens partly mitigated the difference in cell type composition observed between cells and nuclei. However, the extra manipulations affected cell viability and amplified the transcriptional signatures associated with stress responses. In conclusion, research applications focussing on mapping the immune landscape of lung adenocarcinoma benefit from scRNA-seq in fresh samples, whereas snRNA-seq of frozen samples provide a low-cost alternative to profile more epithelial and cancer cells, and yield cell type proportions that more closely match tissue content.

A patient-specific lung cancer assembloid model with heterogeneous tumor microenvironments

Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by using droplet microfluidic technology based on a microinjection strategy. This method enables precise manipulation of clinical microsamples and rapid generation of LCAs with good intra-batch consistency in size and cell composition by evenly encapsulating patient tumor-derived TME cells and lung cancer organoids inside microgels. LCAs recapitulate the inter- and intratumoral heterogeneity, TME cellular diversity, and genomic and transcriptomic landscape of their parental tumors. LCA model could reconstruct the functional heterogeneity of cancer-associated fibroblasts and reflect the influence of TME on drug responses compared to cancer organoids. Notably, LCAs accurately replicate the clinical outcomes of patients, suggesting the potential of the LCA model to predict personalized treatments. Collectively, our studies provide a valuable method for precisely fabricating cancer assembloids and a promising LCA model for cancer research and personalized medicine.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Extracellular cancer‑associated fibroblasts: A novel subgroup in the cervical cancer microenvironment that exhibits tumor‑promoting roles and prognosis biomarker functions

Tumor invasion and metastasis are the processes that primarily cause adverse outcomes in patients with cervical cancer. Cancer-associated fibroblasts (CAFs), which participate in cancer progression and metastasis, are novel targets for the treatment of tumors. The present study aimed to assess the heterogeneity of CAFs in the cervical cancer microenvironment through single-cell RNA sequencing. After collecting five cervical cancer samples and obtaining the CAF-associated gene sets, the CAFs in the cervical cancer microenvironment were divided into myofibroblastic CAFs and extracellular (ec)CAFs. The ecCAFs appeared with more robust pro-tumorigenic effects than myCAFs according to enrichment analysis. Subsequently, through combining the ecCAF hub genes and bulk gene expression data for cervical cancer obtained from The Cancer Genome Atlas and Gene Ontology databases, univariate Cox regression and least absolute shrinkage and selection operator analyses were performed to establish a CAF-associated risk signature for patients with cancer. The established risk signature demonstrated a stable and strong prognostic capability in both the training and validation cohorts. Subsequently, the association between the risk signature and clinical data was evaluated, and a nomogram to facilitate clinical application was established. The risk score was demonstrated to be associated with both the tumor immune microenvironment and the therapeutic responses. Moreover, the signature also has predictive value for the prognosis of head and neck squamous cell carcinoma, and bladder urothelial carcinoma, which were also associated with human papillomavirus infection. In conclusion, the present study assessed the heterogeneity of CAFs in the cervical cancer microenvironment, and a subgroup of CAFs that may be closely associated with tumor progression was defined. Moreover, a signature based on the hub genes of ecCAFs was shown to have biomarker functionality in terms of predicting survival rates, and therefore this CAF subgroup may become a therapeutic target for cervical cancer in the future.

Investigation of cellular communication and signaling pathways in tumor microenvironment for high TP53-expressing osteosarcoma cells through single-cell RNA sequencing

Osteosarcoma (OS) stands as the most prevalent primary bone cancer in children and adolescents, and its limited treatment options often result in unsatisfactory outcomes, particularly for metastatic cases. The tumor microenvironment (TME) has been recognized as a crucial determinant in OS progression. However, the intercellular dynamics between high TP53-expressing OS cells and neighboring cell types within the TME are yet to be thoroughly understood. In our study, we harnessed the single-cell RNA sequencing (scRNA-seq) technology in combination with the computational tool-Cellchat, aiming to elucidate the intercellular communication networks present within OS. Through meticulous quantitative inference and subsequent analysis of these networks, we succeeded in identifying significant signaling pathways connecting high TP53-expressing OS cells with proximate cell types, namely Macrophages, Monocytes, Endothelial Cells, and PVLs. This research brings forth a nuanced understanding of the intricate patterns and coordination involved in the TME's intercellular communication signals. These findings not only provide profound insights into the molecular mechanisms underpinning OS but also indicate potential therapeutic targets that could revolutionize treatment strategies.

Single-cell RNA sequencing reveals recruitment of the M2-like CCL8high macrophages in Lewis lung carcinoma-bearing mice following hypofractionated radiotherapy

BACKGROUND

Tumor-associated macrophages (TAMs) play a pivotal role in reshaping the tumor microenvironment following radiotherapy. The mechanisms underlying this reprogramming process remain to be elucidated.

METHODS

Subcutaneous Lewis lung carcinoma (LLC) murine model was treated with hypofrationated radiotherapy (8 Gy × 3F). Single-cell RNA sequencing was utilized to identify subclusters and functions of TAMs. Multiplex assay and enzyme-linked immunosorbent assay (ELISA) were employed to measure serum chemokine levels. Bindarit was used to inhibit CCL8, CCL7, and CCL2. The infiltration of TAMs after combination treatment with hypofractionated radiotherapy and Bindarit was quantified with flow cytometry, while the influx of CD206 and CCL8 was assessed by immunostaining.

RESULTS

Transcriptome analysis identified a distinct subset of M2-like macrophages characterized by elevated Ccl8 expression level following hypofractionated radiotherapy in LLC-bearing mice. Remarkbly, hypofractionated radiotherapy not only promoted CCL8high macrophages infiltration but also reprogrammed them by upregulating immunosuppressive genes, thereby fostering an immunosuppressive tumor microenvironment. Additioinally, hypofractionated radiotherapy enhanced the CCL signaling pathway, augmenting the pro-tumorigenic functions of CCL8high macrophages and boosting TAMs recruitment. The adjunctive treatment combining hypofractionated radiotherapy with Bindarit effectively reduced M2 macrophages infiltration and prolonged the duration of local tumor control.

CONCLUSIONS

Hypofractionated radiotherapy enhances the infiltration of CCL8high macrophages and amplifies their roles in macrophage recruitment through the CCL signaling pathway, leading to an immunosuppressive tumor microenvironment. These findings highlight the potential of targeting TAMs and introduces a novel combination to improve the efficacy of hypofractionated radiotherapy.

A metabolomics study on carcinogenesis of ground-glass nodules

Objective

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer.

Material and Methods

Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure.

Results

Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples.

Conclusion

Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.