Elaboration and validation of a prognostic signature associated with disulfidoptosis in lung adenocarcinoma, consolidated with integration of single-cell RNA sequencing and bulk RNA sequencing techniques

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

Published: Oct. 27, 2023

Background Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), remains a pervasive global public health concern. Disulfidoptosis, nascent form regulated death (RCD), presents an emerging field inquiry. Currently, investigations into disulfidoptosis are in their initial stages. Our undertaking sought to integrate single-cell RNA sequencing (scRNA-seq) conjunction with traditional bulk (bulk RNA-seq) methodologies, objective delineating genes associated and subsequently prognosticating clinical outcomes LUAD patients. Methods Initially, we conducted in-depth examination cellular composition disparities existing between normal samples using scRNA-seq data sourced from GSE149655. Simultaneously, scrutinized expression patterns disulfidoptosis-associated gene sets across diverse types. Subsequently, leveraging RNA-seq data, formulated disulfidoptosis-related prognostic risk signatures (DRPS) employing LASSO-Cox regression. This was accomplished by focusing on implicated that exhibited differential within endothelial cells (ECs). Sequentially, robustness precision DRPS model were rigorously verified through both internal external validation datasets. In parallel, executed trajectory analysis delve differentiation dynamics ECs. Concluding our study, undertook comprehensive investigation encompassing various facets. These included comparative assessments enrichment pathways, clinicopathological parameters, immune abundance, response-associated genes, impacts immunotherapy, drug predictions among distinct cohorts. Results The scrutiny underscored discernible samples. Furthermore, marked discrepancies Consequently, Disulfidoptosis-Related Prognostic Signature facilitate prediction. nomogram based score effectively demonstrated DRPS’s robust capacity prognosticate survival outcomes. assertion corroborated rigorous utilizing sets, thus affirming commendable predictive accuracy enduring stability DRPS. Functional shed light significant correlation pathways intrinsic cycle. Subsequent unveiled correlations mutations characteristic LUAD, as well indications immunosuppressive status. Through prediction, explored potential therapeutic agents for low-risk investigation, qRT-PCR experiments confirmed heightened levels EPHX1, LDHA, SHC1, MYO6, TLE1 lines.

Language: Английский

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Machine learning-driven prognostic analysis of cuproptosis and disulfidptosis-related lncRNAs in clear cell renal cell carcinoma: a step towards precision oncology

European journal of medical research, Journal Year: 2024, Volume and Issue: 29(1)

Published: March 16, 2024

Cuproptosis and disulfidptosis, recently discovered mechanisms of cell death, have demonstrated that differential expression key genes long non-coding RNAs (lncRNAs) profoundly influences tumor development affects their drug sensitivity. Clear renal carcinoma (ccRCC), the most common subtype kidney cancer, presently lacks research utilizing cuproptosis disulfidptosis-related lncRNAs (CDRLRs) as prognostic markers. In this study, we analyzed RNA-seq data, clinical information, mutation data from The Cancer Genome Atlas (TCGA) on ccRCC cross-referenced it with known (CDRGs). Using LASSO machine learning algorithm, identified four CDRLRs-ACVR2B-AS1, AC095055.1, AL161782.1, MANEA-DT-that are strongly associated prognosis used them to construct a risk model. To verify model's reliability validate these CDRLRs significant factors, performed dataset grouping validation, followed by RT-qPCR external database validation for in ccRCC. Gene function pathway analysis were conducted using Ontology (GO) Set Enrichment Analysis (GSEA) high- low-risk groups. Additionally, burden (TMB) immune microenvironment (TME), employing oncoPredict Immunophenoscore (IPS) algorithms assess sensitivity diverse categories targeted therapeutics immunosuppressants. Our predominant objective is refine predictions patients inform treatment decisions conducting an exhaustive study disulfidptosis.

Language: Английский

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Integrated analysis of disulfidoptosis-related genes identifies NRP1 as a novel biomarker promoting proliferation of gastric cancer via glutamine mediated energy metabolism

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: Aug. 7, 2024

The incidence and mortality of gastric cancer rank fifth fourth worldwide among all malignancies, respectively. Additionally, disulfidoptosis, a recently identified form cellular demise, is closely linked to the initiation advancement malignancies. This study aims create novel signature disulfidptosis-related genes (DRGs) further explore its association with tumor immune microenvironment. Based on our comprehensive study, prognostic consisting 31 DRGs in stomach adenocarcinoma (STAD) was characterized. Through integrative analyses involving gene expression profiling, machine learning algorithms, Cox regression models, significance these demonstrated. Our findings highlight their strong predictive power assessing overall survival across diverse patient datasets, better performance than traditional clinicopathological factors. Moreover, showed characteristics microenvironment, which has implications for modulation therapeutic strategies STAD. Specifically, NRP1 emerged as key DRG elevated STAD, showing correlation advanced stages diseases poorer outcomes. Functional studies revealed role promoting STAD cell proliferation through glutamine metabolism. Overall, underscores clinical relevance biomarker potential targets management, providing insights into disease biology personalized treatments.

Language: Английский

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A disulfidptosis-related lncRNAs signature in hepatocellular carcinoma: prognostic prediction, tumor immune microenvironment and drug susceptibility

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Jan. 7, 2024

Abstract Disulfidptosis, a novel type of programmed cell death, has attracted researchers’ attention worldwide. However, the role disulfidptosis-related lncRNAs (DRLs) in liver hepatocellular carcinoma (LIHC) not yet been studied. We aimed to establish and validate prognostic signature DRLs analyze tumor microenvironment (TME) drug susceptibility LIHC patients. RNA sequencing data, mutation clinical data were obtained from Cancer Genome Atlas Database (TCGA). Lasso algorithm cox regression analysis performed identify signature. Kaplan–Meier curves, principal component (PCA), nomogram calibration curve, function enrichment, TME, immune dysfunction exclusion (TIDE), burden (TMB), sensitivity analyses analyzed. External datasets used predictive value DRLs. qRT-PCR was also differential expression target tissue samples lines. established for (MKLN1-AS TMCC1-AS1) LIHC. The could divide patients into low- high-risk groups, with subgroup associated worse prognosis. observed discrepancies tumor-infiltrating cells, function, TIDE between two risk groups. group more sensitive several chemotherapeutic drugs. datasets, tissue, lines confirmed MKLN1-AS TMCC1-AS1 upregulated based on provide new insight prediction, potential therapeutic strategies.

Language: Английский

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Global research trends on biomarkers for cancer immunotherapy: Visualization and bibliometric analysis

Human Vaccines & Immunotherapeutics, Journal Year: 2025, Volume and Issue: 21(1)

Published: Jan. 8, 2025

The global burden of cancer continues to grow, posing a significant public health challenge. Although immunotherapy has shown efficacy, the response rate is not high. Therefore, objective our research was identify latest trends and hotspots on biomarkers from 1993 2023. Data were collected database Web Science core collection. Bibliometric analysis visualization conducted with CiteSpace(6.3.1), VOSviewer (v1.6.20), R-bibliometrix(v4.3.3), Microsoft Excel(2019). A total 2686 literatures retrieved. sheer annual volume publications rapid upward trend since 2015. United States generated most Harvard University ranked as leading institution. biomarker immune checkpoint inhibitors (ICIs) revealed regional differences in-depth explorations should be promoted in developing countries. China become second largest country terms publication, average citation per paper link strength both lower than other mainly concentrated upon following aspects: PD-1/PD-L1, CTLA-4, gene expression, adverse events, mutational (TMB), body mass index (BMI), gut microbiota, cd8(+)/cd4(+) t-cells, blood-related such lactate dehydrogenase (LDH), neutrophil–lymphocyte ratio (NLR), cytokines. Furthermore, "artificial intelligence" "machine learning" have important hotspot over last 2 y, which will help us useful complex big data provide basis for precise medicine malignant tumors.

Language: Английский

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