Establishment of potential lncRNA-related hub genes involved competitive endogenous RNA in lung adenocarcinoma DOI Creative Commons
Yong Li,

Danfei Shi,

Yan Jiang

et al.

BMC Cancer, Journal Year: 2024, Volume and Issue: 24(1)

Published: Nov. 9, 2024

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, associations between lncRNA-related hub genes (LRHGs) expression corresponding outcomes not been fully understood lung adenocarcinoma (LUAD). Here, total 71 patients diagnosed with LUAD 60 healthy volunteers at The First Affiliated Hospital Huzhou University from April, 2023 to December, were enrolled present study. A LRHGs model was established using least absolute shrinkage selection operator analyses Cancer Genome Atlas-LUAD datasets. underlying mechanisms investigated via Gene Set Enrichment Analysis Variation Analysis. Additionally, diagnostic serum HOXD cluster antisense RNA 2 (HOXD-AS2) assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples divided into high- low-HOXD-AS2 groups based on median expression. HOXD-AS2 miR-4538 as well Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels conducted through Pearson correlation comprehensive analysis identified 141 differentially expressed lncRNAs 539 tissues 59 normal samples. prognostic marker for overall survival constructing predictive signature consisting 9 LRHGs. Subsequently, 474 categorized high or low-risk group risk score. An independent constructed confirm validity this categorization. Further comparisons clinicopathological features LRHG-related pathways performed two groups. Examinations LRHG clusters association immune infiltration also conducted. shown be elevated compared matched tissues, level notably increased controls. results ROC indicated that sensitivity specificity higher than cytokeratin-19 fragment (CYFRA21-1), which is LUAD. negatively associated expression, but CAMK2B showed positive study therefore model, particularly HOXD-AS2, could independently diagnose predict LUAD, suggested mechanism HOXD-AS2/miR-4538/CAMK2B, might offer efficient strategies treatment.

Language: Английский

Development of m6A/m5C/m1A regulated lncRNA signature for prognostic prediction, personalized immune intervention and drug selection in LUAD DOI Creative Commons
Chao Ma,

Zhuoyu Gu,

Yang Yang

et al.

Journal of Cellular and Molecular Medicine, Journal Year: 2024, Volume and Issue: 28(8)

Published: April 1, 2024

Abstract Research indicates that there are links between m6A, m5C and m1A modifications the development of different types tumours. However, it is not yet clear if these involved in prognosis LUAD. The TCGA‐LUAD dataset was used as for signature training, while validation cohort created by amalgamating publicly accessible GEO datasets including GSE29013, GSE30219, GSE31210, GSE37745 GSE50081. study focused on 33 genes regulated or (mRG), which were to form mRGs clusters mRG differentially expressed (mRG‐DEG clusters). Our subsequent LASSO regression analysis trained m6A/m5C/m1A‐related lncRNA (mRLncSig) using lncRNAs exhibited differential expression among mRG‐DEG had prognostic value. model's accuracy underwent via Kaplan–Meier analysis, Cox regression, ROC tAUC evaluation, PCA examination nomogram predictor validation. In evaluating immunotherapeutic potential signature, we employed multiple bioinformatics algorithms concepts through various analyses. These included seven newly developed immunoinformatic algorithms, well evaluations TMB, TIDE immune checkpoints. Additionally, identified validated promising agents target high‐risk mRLncSig To validate real‐world pattern mRLncSig, real‐time PCR carried out human LUAD tissues. signature's ability perform pan‐cancer settings also evaluated. a 10‐lncRNA have power cohort. Real‐time applied verify actual manifestation each gene real world. immunotherapy revealed an association status. found be closely linked several checkpoints, such IL10, IL2, CD40LG, SELP, BTLA CD28, could appropriate targets Among patients, our 12 candidate drugs verified gemcitabine most significant one effective treating discovered some play crucial role certain cancer types, thus, may require further attention future studies. According findings this study, use has aid forecasting serve immunotherapy. Moreover, assist identifying therapeutic more effectively.

Language: Английский

Citations

5
RNA modifications in long non-coding RNAs and their implications in cancer biology DOI
Jiexin Li, Xiansong Wang, Hongsheng Wang

et al.

Bioorganic & Medicinal Chemistry, Journal Year: 2024, Volume and Issue: 113, P. 117922 - 117922

Published: Sept. 13, 2024

Language: Английский

Citations

4
YTHDC1 phase separation drives the nuclear export of m6A-modified lncNONMMUT062668.2 through the transport complex SRSF3–ALYREF–XPO5 to aggravate pulmonary fibrosis DOI Creative Commons
Sony Su Chen,

Yujie Wang,

Jinjin Zhang

et al.

Cell Death and Disease, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 12, 2025

Fibroblast-to-myofibroblast differentiation is the main cytopathologic characteristic of pulmonary fibrosis. However, its underlying molecular mechanism remains poorly understood. This study elucidated that nuclear export lncNONMMUT062668.2 (lnc668) exacerbated fibrosis by activating fibroblast-to-myofibroblast differentiation. Mechanistic research revealed histone H3K9 lactylation in promoter region N6-methyladenosine (m6A) writer METTL3 was enriched to enhance transcription, leading lnc668 m6A modification. Meanwhile, reader YTHDC1 recognized m6A-modified and elevated METTL3-mediated Subsequently, phase-separating promoted lnc668. In this process, formed a pore complex with serine/arginine-rich splicing factor 3, Aly/REF factor, exportin-5 assist translocation from nucleus cytoplasm. After export, facilitated translation stability host gene phosphatidylinositol-binding clathrin assembly protein activate differentiation, aggravation fibrosis, which also depended on phase separation. first clarified separation crucial for modification, profibrotic role exacerbating These findings provide new insights into cytoplasmic lncRNAs identified potential targets therapy.

Language: Английский

Citations

0
G0 arrest gene patterns to predict the prognosis and drug sensitivity of patients with lung adenocarcinoma DOI Creative Commons
Yong Ma, Zhilong Li,

Dongbing Li

et al.

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(8), P. e0309076 - e0309076

Published: Aug. 19, 2024

G0 arrest (G0A) is widely recognized as a crucial factor contributing to tumor relapse. The role of genes related G0A in lung adenocarcinoma (LUAD) was unclear. This study aimed develop gene signature based on for LUAD patients and investigate its relationship with prognosis, immune microenvironment, therapeutic response LUAD. We use the TCGA-LUAD database discovery cohort, focusing specifically associated pathway. used various statistical methods, including Cox lasso regression, model. validated model using bulk transcriptome single-cell datasets (GSE50081, GSE72094, GSE127465, GSE131907 EMTAB6149). GSEA enrichment CIBERSORT algorithm gain insight into annotation signaling pathway characterization microenvironment. evaluated immunotherapy, chemotherapy, targeted therapy these patients. expression six cell lines by quantitative real-time PCR (qRT-PCR). Our successfully established six-gene (CHCHD4, DUT, LARP1, PTTG1IP, RBM14, WBP11) that demonstrated significant predictive power overall survival It independent prognostic value To enhance clinical applicability, we developed nomogram this signature, which showed high reliability predicting patient outcomes. Furthermore, observed association between G0A-related risk microenvironment well drug susceptibility, highlighting potential guide personalized treatment strategies. were significantly upregulated lines. holds contribute improved prediction new therapies

Language: Английский

Citations

1
Establishment of potential lncRNA-related hub genes involved competitive endogenous RNA in lung adenocarcinoma DOI Creative Commons
Yong Li,

Danfei Shi,

Yan Jiang

et al.

BMC Cancer, Journal Year: 2024, Volume and Issue: 24(1)

Published: Nov. 9, 2024

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, associations between lncRNA-related hub genes (LRHGs) expression corresponding outcomes not been fully understood lung adenocarcinoma (LUAD). Here, total 71 patients diagnosed with LUAD 60 healthy volunteers at The First Affiliated Hospital Huzhou University from April, 2023 to December, were enrolled present study. A LRHGs model was established using least absolute shrinkage selection operator analyses Cancer Genome Atlas-LUAD datasets. underlying mechanisms investigated via Gene Set Enrichment Analysis Variation Analysis. Additionally, diagnostic serum HOXD cluster antisense RNA 2 (HOXD-AS2) assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples divided into high- low-HOXD-AS2 groups based on median expression. HOXD-AS2 miR-4538 as well Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels conducted through Pearson correlation comprehensive analysis identified 141 differentially expressed lncRNAs 539 tissues 59 normal samples. prognostic marker for overall survival constructing predictive signature consisting 9 LRHGs. Subsequently, 474 categorized high or low-risk group risk score. An independent constructed confirm validity this categorization. Further comparisons clinicopathological features LRHG-related pathways performed two groups. Examinations LRHG clusters association immune infiltration also conducted. shown be elevated compared matched tissues, level notably increased controls. results ROC indicated that sensitivity specificity higher than cytokeratin-19 fragment (CYFRA21-1), which is LUAD. negatively associated expression, but CAMK2B showed positive study therefore model, particularly HOXD-AS2, could independently diagnose predict LUAD, suggested mechanism HOXD-AS2/miR-4538/CAMK2B, might offer efficient strategies treatment.

Language: Английский

Citations

0