Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome

Computers in Biology and Medicine, Год журнала: 2023, Номер 165, С. 107417 - 107417

Опубликована: Сен. 1, 2023

Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, progression, invasion, metastasis. However, effect Tregs TME OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used identify various other cell clusters Gene set variation analysis (GSVA) investigate signaling pathways from adjacent tissues. CellChat iTALK packages were analyze cellular communication. addition, prognostic model established based on Tregs-specific genes using bulk RNA-seq TARGET database, it verified Expression Omnibus dataset. pRRophetic package predict drug sensitivity. Immunohistochemistry verify expression candidate Based above methods, we showed that samples infiltrated Tregs. GSVA revealed oxidative phosphorylation, angiogenesis mammalian target rapamycin complex 1 (mTORC1) activated compared those Using communication analysis, found interacted osteoblastic, endothelial, myeloid via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected receptor 4 (CXCR4) through CXCL12/transforming growth factor β1 (TGFB1) collectively enable progression. Subsequently, two genes-CD320 MAF-were screened univariate, least absolute shrinkage selection operator regression (LASSO) multivariate construct model, which excellent accuracy independent cohorts. sensitivity demonstrated patients at high risk sensitive sunitinib, sorafenib, axitinib. We also immunohistochemistry validate CD320 MAF significantly upregulated tissues Overall, study reveals heterogeneity TME, providing new insights into invasion treatment cancer.

Язык: Английский

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Identification of anoikis-related molecular patterns to define tumor microenvironment and predict immunotherapy response and prognosis in soft-tissue sarcoma

Frontiers in Pharmacology, Год журнала: 2023, Номер 14

Опубликована: Март 1, 2023

Background: Soft-tissue sarcoma (STS) is a massive threat to human health due its high morbidity and malignancy. STS also represents more than 100 histologic molecular subtypes, with different prognosis. There growing evidence that anoikis play key role in the proliferation invasion of tumors. However, effects immune landscape prognosis remain unclear. Methods: We analyzed genomic transcriptomic profiling 34 anoikis-related genes (ARGs) patient cohort pan-cancer from The Cancer Genome Atlas (TCGA) database. Single-cell transcriptome was used disclose expression patterns ARGs specific cell types. Gene further validated by real-time PCR our own sequencing data. established Anoikis cluster subtypes using unsupervised consensus clustering analysis. An scoring system built based on differentially expressed (DEGs) between clusters. clinical biological characteristics groups were evaluated. Results: expressions most significantly normal tissues. found some common profiles across pan-cancers. Network demonstrated regulatory pattern association infiltration. Patients clusters or displayed distinct characteristics. efficient prediction In addition, could be predict immunotherapy response. Conclusion: Overall, study thoroughly depicted interactions STS. score model guide individualized management.

Язык: Английский

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Dissecting prostate Cancer: Single-Cell insight into Macrophage Diversity, molecular Prognosticators, and the role of Peptidylprolyl Isomerase F

International Immunopharmacology, Год журнала: 2024, Номер 138, С. 112599 - 112599

Опубликована: Июль 2, 2024

Язык: Английский

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CFLAR: A novel diagnostic and prognostic biomarker in soft tissue sarcoma, which positively modulates the immune response in the tumor microenvironment

Oncology Letters, Год журнала: 2024, Номер 27(4)

Опубликована: Фев. 14, 2024

Anoikis is highly associated with tumor cell apoptosis and prognosis; however, the specific role of anoikis‑related genes (ARGs) in soft tissue sarcoma (STS) remains to be fully elucidated. The present study aimed use a variety bioinformatics methods determine differentially expressed STS healthy tissues. Subsequently, three machine learning algorithms, Least Absolute Shrinkage Selection Operator, Support Vector Machine Random Forest, were used screen highest importance score. results analyses demonstrated that CASP8 FADD‑like regulator (CFLAR) exhibited diagnostic prognostic value CFLAR development was determined using multiple public in‑house cohorts. may considered marker STS, which acts as an independent factor development. also explore potential microenvironment, significantly enhanced immune response exerted positive effect on infiltration CD8⁺ T cells M1 macrophages microenvironment. Notably, aforementioned verified multiplex immunofluorescence analysis. Collectively, act novel for positively regulate STS. Thus, provided theoretical basis diagnosis, predicting clinical outcomes tailoring individualized treatment options.

Язык: Английский

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Transcriptome and single-cell analysis reveal disulfidptosis-related modification patterns of tumor microenvironment and prognosis in osteosarcoma

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Апрель 22, 2024

Abstract Osteosarcoma (OS) is the most common malignant bone tumor with high pathological heterogeneity. Our study aimed to investigate disulfidptosis-related modification patterns in OS and their relationship survival outcomes patients OS. We analyzed single-cell-level expression profiles of genes (DSRGs) both microenvironment subclusters, HMGB1 was found be crucial for intercellular regulation disulfidptosis. Next, we explored molecular clusters based on DSRGs related immune cell infiltration using transcriptome data. Subsequently, hub disulfidptosis were screened by applying multiple machine models. In vitro patient experiments validated our results. Three main defined OS, analysis suggested heterogeneity between distinct clusters. The experiment confirmed decreased viability after ACTB silencing higher lower scores. systematically revealed underlying at single-cell level, identified subtypes, potential role

Язык: Английский

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Anoikis and Mitophagy-Related Gene Signature for Predicting the Survival and Tumor Cell Progression in Colon Cancer

Critical Reviews in Immunology, Год журнала: 2024, Номер 45(1), С. 1 - 13

Опубликована: Апрель 8, 2024

Anoikis is a specialized form of programmed cell death and also related mitophagy process. We aimed to identify an anoikis mitophagy-related genes (AMRGs) prognostic model explore the role <i>SPHK1</i> in colon cancer (CC). Bioinformatic methods were used screen AMRGs. Based on these genes, all samples divided into different subtypes. Furthermore, LASSO was conducted optimize optimal risk score established evaluated. Finally, effects downregulated <i>SPHK1 </i>on CC proliferation, migration, invasion, investigated. AMRGs, subtype 1 2. An AMRGs signature containing three key (<i>SPHK1, CDC25C, </i>and <i>VPS37A</i>) that exhibiting predicting ability survival confirmed. Subtype2 low-risk groups exhibited better higher immune infiltration. Moreover, lower invasion ability, as well line (<i>P</i> &#60; 0.01). The exhibits promising patients with CC. might inhibit growth, through stimulating anoikis.

Язык: Английский

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Comprehensive bioinformatics analysis reveals the oncogenic role of FoxM1 and its impact on prognosis, immune microenvironment, and drug sensitivity in osteosarcoma

Journal of Applied Genetics, Год журнала: 2023, Номер 64(4), С. 779 - 796

Опубликована: Окт. 2, 2023

Язык: Английский

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Prognostic model for hepatocellular carcinoma based on anoikis-related genes: immune landscape analysis and prediction of drug sensitivity

Frontiers in Medicine, Год журнала: 2023, Номер 10

Опубликована: Июль 12, 2023

Background Hepatocellular carcinoma (HCC) represents a complex ailment characterized by an unfavorable prognosis in advanced stages. The involvement of immune cells HCC progression is significant importance. Moreover, metastasis poses substantial impediment to enhanced prognostication for patients, with anoikis playing indispensable role facilitating the distant tumor cells. Nevertheless, limited investigations have been conducted regarding utilization factors predicting and assessing infiltration. This present study aims identify hepatocellular carcinoma-associated anoikis-related genes (ANRGs), establish robust prognostic model HCC, delineate distinct characteristics based on signature. Cell migration cytotoxicity experiments were performed validate accuracy ANRGs model. Methods Consensus clustering was employed this investigation categorize samples obtained from both TCGA Gene Expression Omnibus (GEO) cohorts. To assess differentially expressed genes, Cox regression analysis conducted, subsequently, gene signatures constructed using LASSO-Cox methodology. External validation at International Cancer Genome Conference. microenvironment (TME) utilizing ESTIMATE CIBERSORT algorithms, while machine learning techniques facilitated identification potential target drugs. wound healing assay CCK-8 evaluate migratory capacity drug sensitivity cell lines, respectively. Results Utilizing TCGA-LIHC dataset, we devised nomogram integrating ten-gene signature diverse clinicopathological features. Furthermore, discriminative clinical utility substantiated through ROC DCA. Subsequently, framework leveraging expression data risk cohorts predict responsiveness subtypes. Conclusion In study, established promising model, which can serve as valuable tool clinicians selecting targeted therapeutic drugs, thereby improving overall patient survival rates. Additionally, has also revealed strong connection between cells, providing avenue elucidating mechanisms underlying infiltration regulated anoikis.

Язык: Английский

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From Spheroids to Bioprinting: A Literature Review on Biomanufacturing Strategies of 3D In Vitro Osteosarcoma Models

Advanced Therapeutics, Год журнала: 2024, Номер unknown

Опубликована: Окт. 10, 2024

Abstract Osteosarcoma (OS) is a rare primary malignant bone cancer affecting mainly young individuals. Treatment typically consists of chemotherapy and surgical tumor resection, which has undergone few improvements since the 1970s. This therapeutic approach encounters several limitations attributed to tumor's inherent chemoresistance, marked heterogeneity metastatic potential. Therefore, development in vitro platforms that closely mimic OS pathophysiology crucial understand progression discover effective anticancer therapeutics. Contrary 2D monolayer cultures animal models, 3D show promise replicating macrostructure, cell‐cell cell‐extracellular matrix interactions. review provides an overview biomanufacturing strategies employed developing highlighting their role different aspects improving research drug screening. A variety models are explored, including both scaffold‐free scaffold‐based encompassing cell spheroids, hydrogels, innovative approaches like electrospun nanofibers, microfluidic devices bioprinted constructs. By examining distinctive features each model type, this offers insights into potential transformative impact on landscape innovation, addressing challenges future directions modeling.

Язык: Английский

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Identification and Validation of a Novel Anoikis-Related Gene Signature for Predicting Survival in Patients With Serous Ovarian Cancer

World Journal of Oncology, Год журнала: 2024, Номер 15(1), С. 45 - 57

Опубликована: Янв. 20, 2024

Background: Ovarian cancer is an extremely deadly gynecological malignancy, with a 5-year survival rate below 30%. Among the different histological subtypes, serous ovarian (SOC) most common. Anoikis significantly contributes to progression of cancer. Therefore, identifying anoikis-related signature that can serve as potential prognostic predictors for SOC great significance. Methods: We intersected 308 genes (ARGs) and identified those associated prognosis using univariate Cox regression. A LASSO regression model was constructed evaluated Kaplan-Meier receiver operating characteristic (ROC) analyses in TCGA (The Cancer Genome Atlas) GSE26193 cohorts. conducted quantitative real-time polymerase chain reaction (qPCR) assess mRNA levels applied bioinformatics investigate correlation between risk groups gene expression, mutations, pathways, tumor immune microenvironment (TIME), drug sensitivity SOC. Results: ARGs, 28 were prognosis. 13-gene established through cohort. High-risk group had poorer than low-risk (median overall (mOS): 34.2 vs. 57.1 months, hazard ratio (HR): 2.590, 95% confidence interval (CI): 0.159 - 6.00, P < 0.001). The area under curve (AUC) values 0.63, 0.65, 0.74 reflected predictive performance 3-, 5-, 8-year (OS) validation Functional enrichment, pathway analysis, TIME analysis distinct characteristics groups. Drug revealed advantages each group. Furthermore, qPCR once again confirmed effectiveness patients. Conclusions: developed validated robust ARG model, which could be used predict OS By systematically analyzing score ARGs various patterns, including sensitivity, our findings suggest this advancement personalized precise therapeutic strategies. Nevertheless, further studies investigations into underlying mechanisms are warranted. World J Oncol. 2024;15(1):45-57 doi: https://doi.org/10.14740/wjon1714

Язык: Английский

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