Construction And Clinical Values Of A Hemoglobin Chaperone Factor-related LncRNAs Prognostic Risk Model In Lung Adenocarcinoma

Objective: Lung adenocarcinoma(LUAD)is one of the most common cancers globally,characterized by unique biological features,that result in high mortality and poor prognosis.Currently there is still a lack of accurate diagnostic methods,leading to the majority of patients being diagnosed at late stages.Normal lung function relies on the support of hemoglobin,and its precise structural modifications and related normal expression require relevant partner factors.Lnc RNAs plays a crucial role in the modification expression of key proteins and disease progression.Therefore,it is necessary to investigate the lncRNA expression related to hemoglobin partner factors in LUAD,and use lncRNAs expression to establish a prediction model for LUAD to explore the precise prognosis and targeted therapy of the disease.Methods: 1.In this study,we first utilized the cancer genome atlas(TCGA)to extract standardized hemoglobin partner gene and lncRNAs expression data from LUAD patient samples and gene expression information for subsequent analysis.2.Key lncRNAs were screened using single-factor Cox regression analysis and Lasso regression analysis,and a risk model was further established using multiple-factor Cox regression analysis.3.The dataset was divided into training and validation groups to verify the model,and patients were classified into high-and low-risk groups based on the risk model score.The efficiency of the established model was analyzed using single-factor and multiple-factor Cox analysis.4.ROC curves,consistency index curves,and principal component analysis were used to further validate the prognostic value of model evaluation features.5.Differential genes between high-and low-risk groups were analyzed,and gene ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG),immunological related function,and tumor mutation burden analyses were conducted.6.Drug screening based on TMB analysis was conducted to determine potential drugs with sensitivity to LUAD.7.Independent datasets were used to verify the prognostic significance of target screening.Results: 1.The study extracted mRNA and lncRNA data from LUAD transcriptome data,obtained the expression of 13 hemoglobin partner factor genes,and conducted correlation calculations between 16,200 lncRNAs and 13 hemoglobin partner factor genes.The screening standards were set as |R| > 0.4and P < 0.001,resulting in the identification of 7 genes correlated with 41 lncRNAs.2.Using single-factor Cox regression analysis,Lasso regression analysis,and multiple-factor Cox regression analysis,the study constructed a risk model that included three hemoglobin partner factor-related lncRNAs.The risk score model was calculated as follows: AL022162.1 *(-0.15815891)+RPARP-AS1 *(-0.39354077)+ AL365181.3 *(0.159957353).3.To evaluate the prognostic value of the risk features,LUAD patients were divided into highrisk and low-risk groups based on the median risk score.The survival time was evaluated in the training,testing,and all patient groups,and the OS of the highrisk group in all three groups was significantly shorter than that of the low-risk group(P < 0.05).In addition,in all patient groups,the PFS of the high-risk group was also significantly shorter than that of the low-risk group(P < 0.05).Results of single-factor and multiple-factor Cox regression analysis showed that the risk score was independently associated with survival time(P < 0.05),indicating that the risk score model could serve as an independent prognostic factor for LUAD patients.4.ROC curve analysis showed that the AUC of risk score was 0.671.In addition,the AUC of risk score for predicting 1-year,3-year and 5-year overall survival rates were 0.671,0.651,and 0.551,respectively,indicating good predictive ability of the model.The consistency index was used to evaluate the predictive performance of the model,and the fluctuation range of risk score results was between 0.6 and 0.7,indicating that the constructed prognostic model had good prediction ability.In addition,PCA under different conditions was performed on all patients,and the results showed that the PCA distribution of lncRNAs in the model was clear,indicating that these lncRNAs could be reliably used for model construction.5.First,differentially expressed genes(DEGs)between high-and low-risk groups were screened.Then,functional enrichment analysis of DEGs was conducted.GO analysis results showed that related biological processes(BPs)enriched in signaling pathways based on microtubule movement,cilia movement signaling pathway,and signal pathway of microtubule bundle formation.Related cellular components(CCs)enriched in collagen-containing extracellular matrix,motile cilium,and secretory granule lumen.Related molecular functions(MFs)enriched in monooxygenase activity,serine-type endopeptidase inhibitor activity,and calcium-dependent phospholipid binding.KEGG analysis showed genes involved in complement and coagulation cascades,amoebiasis,and steroid hormone biosynthesis.The study evaluated the differences in immune status between the low-risk and high-risk groups,and found significant differences in immune functions such as type I interferon response,human leukocyte antigen biology,antigen presentation cells,sub-inflammation,cell-killing activity,and T cells.6.The maftools algorithm was used to observe the mutations in highand low-risk groups.The results showed that for most genes,the mutation frequency in the high-risk group was higher than that in the low-risk group.Based on TMB analysis,the gene mutation frequency of TP53,TTN,and MUC16 were inconsistent in different risk groups.Drugs targeting TP53 included Fluorouracil,Doxorubicin,and Cisplatin.Bisphenol A and Doxorubicin were related drugs for TTN,and Necrostatin-1,Cisplatin,and Estradiol were related compounds for MUC16.Overall,Doxorubicin and Cisplatin were potential therapeutic drugs for high-risk hemoglobin partner factor-related LUAD.Conclusion: Based on bioinformatics analysis,this study constructed a risk assessment model for hemoglobin partner factor-related lncRNAs that can be used to evaluate the prognosis of LUAD patients.According to the risk model,we also found several potential drugs for the treatment of LUAD.This provides a new method for prognostic evaluation of LUAD and a new perspective for the development of clinical drug treatment plans for LUAD.