Decoding the tumor microenvironment and molecular mechanism: unraveling cervical cancer subpopulations and prognostic signatures through scRNA-Seq and bulk RNA-seq analyses

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Feb. 28, 2024

Background Cervical carcinoma (CC) represents a prevalent gynecological neoplasm, with discernible rise in prevalence among younger cohorts observed recent years. Nonetheless, the intrinsic cellular heterogeneity of CC remains inadequately investigated. Methods We utilized single-cell RNA sequencing (scRNA-seq) transcriptomic analysis to scrutinize tumor epithelial cells derived from four specimens cervical patients. This method enabled identification pivotal subpopulations and elucidation their contributions progression. Subsequently, we assessed influence associated molecules bulk (Bulk RNA-seq) performed experiments for validation purposes. Results Through our analysis, have discerned C3 PLP2+ Tumor Epithelial Progenitor Cells as noteworthy subpopulation (CC), exerting on differentiation progression CC. established an independent prognostic indicator—the EPCs score. By stratifying patients into high low score groups based median score, that high-score group exhibits diminished survival rates compared low-score group. The correlations between these immune infiltration, enriched pathways, single-nucleotide polymorphisms (SNPs), drug sensitivity, other factors, further underscore impact prognosis. Cellular validated significant ATF6 proliferation migration cell lines. Conclusion study enriches comprehension determinants shaping CC, elevates cognizance microenvironment offers valuable insights prospective therapies. These discoveries contribute refinement diagnostics formulation optimal therapeutic approaches.

Language: Английский

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Molecular mechanisms of pancreatic cancer liver metastasis: the role of PAK2

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Jan. 26, 2024

Background Pancreatic cancer remains an extremely malignant digestive tract tumor, posing a significant global public health burden. Patients with pancreatic cancer, once metastasis occurs, lose all hope of cure, and prognosis is poor. It important to investigate liver in depth, not just because it the most common form but also crucial for treatment planning assessment. This study aims delve into mechanisms metastasis, goal providing scientific groundwork development future methods drugs. Methods We explored using single-cell sequencing data (GSE155698 GSE154778) bulk (GSE71729, GSE19279, TCGA-PAAD). Initially, Seurat package was employed processing obtain expression matrices primary lesions metastatic lesions. Subsequently, high-dimensional weighted gene co-expression network analysis (hdWGCNA) used identify genes associated metastasis. Machine learning algorithms COX regression models were further screen related patient prognosis. Informed by both biological understanding outcomes algorithms, we meticulously identified ultimate set metastasis-related (LRG). In LRG genes, various databases utilized validate their association order analyze effects these agents on tumor microenvironment, conducted in-depth analysis, including changes signaling pathways (GSVA), cell differentiation (pseudo-temporal analysis), communication networks (cell downstream transcription factors (transcription factor activity prediction). Additionally, drug sensitivity metabolic performed reveal gemcitabine resistance pathways. Finally, functional experiments silencing PANC-1 Bx-PC-3 cells its influence proliferation invasiveness cells. Results Through series algorithmic filters, PAK2 as key promoting GSVA elucidated activation TGF-beta pathway promote occurrence Pseudo-temporal revealed correlation between lower status Cell that overexpression promotes microenvironment. Transcription prediction displayed regulated PAK2. Drug impact CCK8 showed led decrease proliferative capacity scratch demonstrated low decreased invasion capability Flow cytometry reveals significantly inhibited apoptosis lines. Molecules inhibition PAK2, there corresponding molecules EMT. Conclusion facilitated angiogenic potential epithelial-mesenchymal transition process activating pathway. Simultaneously, level cells, consequently enhancing malignancy. fostered augments chemoresistance, modulates energy metabolism summary, emerged pivotal orchestrating Intervening may offer promising therapeutic strategy preventing improving

Language: Английский

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Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: Dec. 1, 2022

Despite the many benefits immunotherapy has brought to patients with different cancers, its clinical applications and improvements are still hindered by drug resistance. Fostering a reliable approach identifying sufferers who sensitive certain immunotherapeutic agents is of great relevance.We propose an ELISE (Ensemble Learning for Immunotherapeutic Response Evaluation) pipeline generate robust highly accurate predicting individual responses immunotherapies. employed iterative univariable logistic regression select genetic features patients, using Monte Carlo Tree Search (MCTS) tune hyperparameters. In each trial, selected multiple models integration based on add or concatenate stacking strategies, including deep neural network, automatic feature interaction learning via self-attentive networks, factorization machine, compressed linear then adopted best trial final approach. SHapley Additive exPlanations (SHAP) algorithm was applied interpret ELISE, which validated in independent test set.Regarding prediction atezolizumab within esophageal adenocarcinoma (EAC) demonstrated superior accuracy (Area Under Curve [AUC] = 100.00%). AC005786.3 (Mean [|SHAP value|] 0.0097) distinguished as most valuable contributor output, followed SNORD3D (0.0092), RN7SKP72 (0.0081), EREG (0.0069), IGHV4-80 (0.0063), MIR4526 (0.0063). Mechanistically, immunoglobulin complex, production, adaptive immune response, antigen binding others, were downregulated ELISE-neg EAC subtypes resulted unfavorable responses. More encouragingly, could be extended accurately estimate responsiveness various against other PD1/PD-L1 suppressor metastatic urothelial cancer (AUC 88.86%), MAGE-A3 melanoma 100.00%).This study presented insights into integrating ensemble self-attention mechanism human highlighting potential tool approaches individualized treatment.

Language: Английский

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Revealing the role of regulatory T cells in the tumor microenvironment of lung adenocarcinoma: a novel prognostic and immunotherapeutic signature

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: Aug. 21, 2023

Regulatory T cells (Tregs), are a key class of cell types in the immune system. In tumor microenvironment (TME), presence Tregs has important implications for response and development. Relatively little is known about role lung adenocarcinoma (LUAD).Tregs were identified using but single-cell RNA sequencing (scRNA-seq) analysis interactions between other TME investigated. Next, we used multiple bulk RNA-seq datasets to construct risk models based on marker genes explored differences prognosis, mutational landscape, infiltration immunotherapy high- low-risk groups, finally, qRT-PCR function experiments performed validate model genes.The cellchat showed that MIF-(CD74+CXCR4) pairs play interaction with subpopulations, Tregs-associated signatures (TRAS) could well classify LUAD cohorts into groups. Immunotherapy may offer greater potential benefits group, as indicated by their superior survival, increased cells, heightened expression checkpoints. Finally, experiment verified LTB PTTG1 relatively highly expressed cancer tissues, while PTPRC was paracancerous tissues. Colony Formation assay confirmed knockdown reduced proliferation ability cells.TRAS constructed scRNA-seq distinguish patient subgroups, which provide assistance clinical management patients.

Language: Английский

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Comprehensive characterization of stemness-related lncRNAs in triple-negative breast cancer identified a novel prognostic signature related to treatment outcomes, immune landscape analysis and therapeutic guidance: a silico analysis with in vivo experiments

Journal of Translational Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: May 4, 2024

Abstract Background Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, drug resistance of tumor cells, particularly triple-negative breast cancer (TNBC). This study aims investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. Methods Utilizing RNA sequencing data corresponding clinical information from TCGA database, employing Weighted Gene Co-expression Network Analysis (WGCNA) on mRNAsi sourced an online genes (SRGs) SRlncRNAs were identified. A model was developed using univariate Cox LASSO-Cox analysis based SRlncRNAs. The performance evaluated Kaplan–Meier analysis, ROC curves, ROC-AUC. Additionally, delved into underlying signaling pathways immune status associated with divergent prognoses Results research identified signature six (AC245100.6, LINC02511, AC092431.1, FRGCA, EMSLR, MIR193BHG) TNBC. Risk scores derived this found correlate abundance plasma cells. Furthermore, nominated chemotherapy drugs exhibited considerable variability between different risk score groups. RT-qPCR validation confirmed abnormal expression patterns these affirming biomarker. Conclusion not only demonstrates predictive power terms patient outcomes but also provides insights biology, pathways, prognosis. findings suggest possibility guiding personalized treatments, including checkpoint gene therapy strategies, SRlncRNA signature. Overall, contributes valuable knowledge towards advancing precision medicine context

Language: Английский

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Unveiling efferocytosis-related signatures through the integration of single-cell analysis and machine learning: a predictive framework for prognosis and immunotherapy response in hepatocellular carcinoma

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: July 27, 2023

Hepatocellular carcinoma (HCC) represents a prominent gastrointestinal malignancy with grim clinical outlook. In this regard, the discovery of novel early biomarkers holds substantial promise for ameliorating HCC-associated mortality. Efferocytosis, vital immunological process, assumes central position in elimination apoptotic cells. However, comprehensive investigations exploring role efferocytosis-related genes (EFRGs) HCC are sparse, and their regulatory influence on immunotherapy targeted drug interventions remain poorly understood.RNA sequencing data characteristics patients were acquired from TCGA database. To identify prognostically significant HCC, we performed limma package conducted univariate Cox regression analysis. Subsequently, machine learning algorithms employed to hub genes. assess landscape different subtypes, CIBERSORT algorithm. Furthermore, single-cell RNA (scRNA-seq) was utilized investigate expression levels ERFGs immune cells explore intercellular communication within tissues. The migratory capacity evaluated using CCK-8 assays, while sensitivity prediction reliability determined through wound-healing assays.We have successfully identified set nine genes, termed EFRGs, that hold potential establishment hepatocellular carcinoma-specific prognostic model. leveraging individual risk scores derived model, able stratify into two distinct groups, unveiling notable disparities terms infiltration patterns response immunotherapy. Notably, model's accurately predict responses substantiated experimental investigations, encompassing assay, CCK8 experiments HepG2 Huh7 cell lines.We constructed an EFRGs model serves as valuable tools assessment decision-making support context chemotherapy.

Language: Английский

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Unveiling the role of regulatory T cells in the tumor microenvironment of pancreatic cancer through single-cell transcriptomics and in vitro experiments

Frontiers in Immunology, Journal Year: 2023, Volume and Issue: 14

Published: Sept. 11, 2023

In order to investigate the impact of Treg cell infiltration on immune response against pancreatic cancer within tumor microenvironment (TME), and identify crucial mRNA markers associated with cells in cancer, our study aims delve into role anti-tumor cancer.The ordinary transcriptome data for this was sourced from GEO TCGA databases. It analyzed using single-cell sequencing analysis machine learning. To assess level tissues, we employed CIBERSORT method. The identification genes most closely accomplished through implementation weighted gene co-expression network (WGCNA). Our involved various quality control methods, followed by annotation advanced analyses such as trajectory communication elucidate microenvironment. Additionally, categorized two subsets: Treg1 favorable prognosis, Treg2 poor based enrichment scores key genes. Employing hdWGCNA method, these subsets critical signaling pathways governing their mutual transformation. Finally, conducted PCR immunofluorescence staining vitro validate identified genes.Based results analysis, observed significant Subsequently, utilizing WGCNA learning algorithms, ultimately four cell-related (TRGs), among which exhibited correlations occurrence progression cancer. Among them, CASP4, TOB1, CLEC2B were poorer prognosis patients, while FYN showed a correlation better prognosis. Notably, differences found HIF-1 pathway between These conclusions further validated experiments.Treg played microenvironment, presence held dual significance. Recognizing characteristic vital understanding limitations cell-targeted therapies. FYN, close associations infiltrating suggesting involvement functions. Further investigation warranted uncover mechanisms underlying associations. emerged contributing duality cells. Targeting could potentially revolutionize existing treatment approaches

Language: Английский

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Expression pattern of cancer-associated cellular senescence genes in clear cell renal cell carcinoma distinguishes tumor subclasses with clinical implications

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 2, 2025

Language: Английский

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Bayesian‐optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers

Journal of Cellular and Molecular Medicine, Journal Year: 2025, Volume and Issue: 29(2)

Published: Jan. 1, 2025

Abstract Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating and developing mitophagy‐based treatments to combat drug resistance remains challenging. Herein, BayeDEM (Bayesian‐optimized Deep learning Essential of Mitophagy) was proposed such a task. After Bayesian optimization, demonstrated its excellent performance in critical osteosarcoma (area under curve [AUC] ROC: 98.96%; AUC PR curve: 100%). CERS1 identified as the most gene (mean (|SHAP value|): 4.14). Inhibition sensitized cisplatin‐resistant cells cisplatin, restricting their growth, proliferation, invasion, migration colony formation inducing apoptosis. Mechanistically, inhibition restricted destroy cells, including membrane potential loss unfavourable dynamics, rendering them susceptible cisplatin‐induced More importantly, facilitated immunosuppressive microenvironment by significantly modulating T‐cell differentiation, adhesion antigen presentation, mainly affects malignant osteoblasts early‐mid developmental stage. Immunologically, potentially modulated MIF signalling transmission between B DCs, CD8+ T NK monocytes through MIF‐(CD74 + CXCR4) receptor–ligand interaction, thereby biological functions these immune cells. Collectively, emerged promising tool oncologists identify pivotal governing mitophagy, enabling mitophagy‐centric therapeutic strategies counteract resistance.

Language: Английский

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Metabolic reprogramming and immune microenvironment characteristics in laryngeal carcinoma: advances in immunotherapy

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 30, 2025

Laryngeal squamous cell carcinoma (LSCC) is a prevalent malignancy with high mortality and recurrence rates, necessitating novel therapeutic strategies. Recent research highlights the pivotal role of metabolic reprogramming immune microenvironment alterations in LSCC pathogenesis, providing promising avenues for targeted therapy. This review summarizes characteristics LSCC, including glycolysis, lipid metabolism, amino acid biosynthesis, their implications tumor progression resistance. Additionally, this further describes microenvironment’s immunosuppressive landscape, checkpoint regulation, tumor-associated macrophages, T-cell dysfunction. The integration immune-targeted strategies represents frontier treatment, warranting investigation.

Language: Английский

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