Investigation on molecular mechanism underlying the dynamic evolution from preneoplasia to invasive lung adenocarcinoma
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1189476 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31443327_1.fastq.gz | Fastqsanger.gz | |||
| SRR31443327_2.fastq.gz | Fastqsanger.gz | |||
| SRR31443328_1.fastq.gz | Fastqsanger.gz | |||
| SRR31443328_2.fastq.gz | Fastqsanger.gz | |||
| SRR31443329_1.fastq.gz | Fastqsanger.gz |
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Project description:The cell ecology and spatial niche implicated in the dynamic and sequential process of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) have not yet been elucidated. Here, we performed an integrative analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to characterize the cell atlas of the invasion trajectory of LUAD. We found that the UBE2C + cancer cell subpopulation constantly increased during the invasive process of LUAD with remarkable elevation in IAC, and its spatial distribution was in the peripheral cancer region of the IAC, representing a more malignant phenotype. Furthermore, analysis of the TME cell type subpopulation showed a constant decrease in mast cells, monocytes, and lymphatic endothelial cells, which were implicated in the whole process of invasive LUAD, accompanied by an increase in NK cells and MALT B cells from AIS to MIA and an increase in Tregs and secretory B cells from MIA to IAC. Notably, for AIS, cancer cells, NK cells, and mast cells were colocalized in the cancer region; however, for IAC, Tregs colocalized with cancer cells. Finally, communication and interaction between cancer cells and TME cell-induced constitutive activation of TGF-β signaling were involved in the invasion of IAC. Therefore, our results reveal the specific cellular information and spatial architecture of cancer cells and TME subpopulations, as well as the cellular interaction between them, which will facilitate the identification and development of precision medicine in the invasive process of LUAD from AIS to IAC.
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Project description:Immune evolution from preneoplasia to invasive lung adenocarcinomas and underlying molecular features
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Project description:The mechanism by which anti-cancer immunity shapes early carcinogenesis of lung adenocarcinoma (ADC) is unknown. In this study, we characterize the immune contexture of invasive lung ADC and its precursors by transcriptomic immune profiling, T cell receptor (TCR) sequencing and multiplex immunofluorescence (mIF). Our results demonstrate that anti-tumor immunity evolved as a continuum from lung preneoplasia, to preinvasive ADC, minimally-invasive ADC and frankly invasive lung ADC with a gradually less effective and more intensively regulated immune response including down-regulation of immune-activation pathways, up-regulation of immunosuppressive pathways, lower infiltration of cytotoxic T cells (CTLs) and anti-tumor helper T cells (Th), higher infiltration of regulatory T cells (Tregs), decreased T cell clonality, and lower frequencies of top T cell clones in later-stages. Driver mutations, chromosomal copy number aberrations (CNAs) and aberrant DNA methylation may collectively impinge host immune responses and facilitate immune evasion, promoting the outgrowth of fit subclones in preneoplasia into dominant clones in invasive ADC.
| S-EPMC8113327 | biostudies-literature
Project description:The cell ecology and spatial niche implicated in the dynamic and sequential process of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) have not yet been elucidated. Here, we performed an integrative analysis of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to characterize the cell atlas of the invasion trajectory of LUAD. We found that the UBE2C + cancer cell subpopulation constantly increased during the invasive process of LUAD with remarkable elevation in IAC, and its spatial distribution was in the peripheral cancer region of the IAC, representing a more malignant phenotype. Furthermore, analysis of the TME cell type subpopulation showed a constant decrease in mast cells, monocytes, and lymphatic endothelial cells, which were implicated in the whole process of invasive LUAD, accompanied by an increase in NK cells and MALT B cells from AIS to MIA and an increase in Tregs and secretory B cells from MIA to IAC. Notably, for AIS, cancer cells, NK cells, and mast cells were colocalized in the cancer region; however, for IAC, Tregs colocalized with cancer cells. Finally, communication and interaction between cancer cells and TME cell-induced constitutive activation of TGF-β signaling were involved in the invasion of IAC. Therefore, our results reveal the specific cellular information and spatial architecture of cancer cells and TME subpopulations, as well as the cellular interaction between them, which will facilitate the identification and development of precision medicine in the invasive process of LUAD from AIS to IAC.
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Project description:Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.
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Project description:Background: Gastric cancer (GC) is often associated with a poor prognosis, due to its asymptomatic early stages. The current gold standard for diagnosing GC, upper endoscopy, is invasive and has limited sensitivity for detecting gastric preneoplasia such as dysplasia. Non-invasive biomarkers, such as circulating proteins in the blood, hold promise for the early detection of asymptomatic gastric lesions. Methods: During an exploratory study, plasma samples from 39 participants, including patients diagnosed with different gastric pathologies (gastritis, preneoplasia, GC) and healthy controls, were analyzed using mass spectrometry-based proteomics. Differentially abundant proteins were identified through pairwise comparisons and sparse Partial Least Squares Discriminant Analysis (sparse PLS-DA). Fifteen candidate proteins were selected and quantified by ELISA in plasma samples from the full cohort of 138 participants. Results: Proteomic profiling identified 691 proteins in plasma samples. Pairwise comparisons highlighted up to 213 candidate biomarkers distinguishing cancer patients from healthy controls, while distinguishing gastritis and preneoplasia proved challenging due to their similar proteomes. Sparse PLS-DA identified 85 proteins that distinguish all patient groups. Subsequent ELISA validation confirmed Leptin as a promising biomarker for detecting gastric preneoplasia, particularly in women. Nine additional proteins (ATAD3B, IGFALS, JUP, LBP, MAN2A1, ARG1, CA2, HPT, KRT14) showed differential plasma levels across patients groups, influenced by age and gender. Multi-biomarker prediction models that incorporated factors such as age, gender, and H. pylori status, outperformed single-protein models. Using 4-fold cross-validation repeated 10 times, the best-performing models achieved high predictive accuracy, with mean AUROC=85.3% for classifications cancer vs. non-cancer and 83.9% for cancer/preneoplasia vs. healthy/gastritis. On the full cohort, the best biomarker combinations reached AUROC values exceeding 94% for these classifications. Conclusions: This study introduces a novel, non-invasive approach for predicting GC based on plasma protein concentrations across a broad spectrum of gastric pathologies. Predictive models, validated through robust cross-validation, demonstrated high accuracy using a limited panel of biomarkers. By relying on simple blood sampling, this strategy holds promise for high-risk gastric mucosal lesions, including at asymptomatic stages. Such an approach could significantly improve early detection and clinical management of GC, offering direct benefit for patients outcomes.
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Project description:To assess the dynamic changes in the immune contexture during early lung carcinogenesis, we performed immune profiling using the nCounter PanCancer Immune Profiling Panel on resected lung ADCs and their precursors .
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Project description:Metabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies.
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Project description:To investigate changes in the tumor microenvironment (TME) during lung cancer progression, we interrogate tumors from two computer tomography (CT) defined groups. Pure non-solid (pNS) CT density nodules contain preinvasive/minimally invasive cancers and solid density nodules invasive cancers. Profiling data reveal a dynamic interaction between the tumor and its TME throughout progression. Alterations in genes regulating the extracellular matrix and genes regulating fibroblasts are central at the preinvasive state. T cell-mediated immune suppression is initiated in preinvasive nodules and sustained with rising intensity through progression to invasive tumors. Reduced T cell infiltration of the cancer cell nests is more frequently associated with preinvasive cancers, possibly until tumor evolution leads to a durable, viable invasive phenotype accompanied by more varied and robust immune suppression. Upregulation of immune checkpoints occurs only in the invasive nodules. Throughout progression an effector immune response is present but is effectively thwarted by the immune-suppressive elements.
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