Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus

BACKGROUND Breast cancer is regarded as a highly malignant neoplasm in the female population,posing a significant risk to women’s overall well-being.The prevalence of breast cancer has been observed to rise in China,accompanied by an earlier age of onset when compared to Western countries.Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women,primarily due to its limited responsiveness to conventional treatment modalities.The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests.There is a prevailing uncertainty regarding the most effective screening method and target populations,as well as the specificities and execution of screening programs.AIM To identify diagnostic and prognostic biomarkers for breast cancer.METHODS Overlapping differentially expressed genes were screened based on Gene Expression Omnibus(GSE36765,GSE10810,and GSE20086)and The Cancer Genome Atlas datasets.A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses,as well as gene set enrichment analyses,were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer.For clarification of the diagnostic and prognostic roles of these genes,Kaplan–Mei-er and Cox proportional hazards analyses were conducted.RESULTS This study demonstrated that calreticulin,heat shock protein family B member 1,insulin-like growth Factor 1,interleukin-1 receptor 1,Krüppel-like factor 4,suppressor of cytokine signaling 3,and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications.CONCLUSION The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.

Analysis of differentially expressed genes related to cerebral ischaemia in young rats based on the Gene Expression Omnibus database

BACKGROUND The incidence rate of cerebral infarction in young people is increasing day by day,the age of onset tends to be younger,and its internal pathogenesis and mechanism are very complicated,which leads to greater difficulties in treatment.Therefore,it is essential to analyze the key pathway that affects the onset of cerebral infarction in young people from the perspective of genetics.AIM To compare the differentially expressed genes in the brain tissue of young and aged rats with middle cerebral artery occlusion and to analyse their effect on the key signalling pathway involved in the development of cerebral ischaemia in young rats.METHODS The Gene Expression Omnibus 2R online analysis tool was used to analyse the differentially expressed genes in the GSE166162 dataset regarding the development of cerebral ischaemia in young and aged groups of rats.DAVID 6.8 software was further used to filter the differentially expressed genes.These genes were subjected to Gene Ontology(GO)function analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis to determine the key gene pathway that affects the occurrence of cerebral ischaemia in young rats.RESULTS Thirty-five differentially expressed genes(such as Igf2,Col1a2,and Sfrp1)were obtained;73 GO enrichment analysis pathways are mainly involved in biological processes such as drug response,amino acid stimulation response,blood vessel development,various signalling pathways,and enzyme regulation.They are involved in molecular functions such as drug binding,protein binding,dopamine binding,metal ion binding,and dopamine neurotransmitter receptor activity.KEGG pathway enrichment analysis showed a significantly enriched pathway:The cyclic adenosine monophosphate(c-AMP)signalling pathway.CONCLUSION The c-AMP signalling pathway might be the key pathway in the intervention of cerebral infarction in young people.

Identification and validation of a new prognostic signature based on cancer-associated fibroblast-driven genes in breast cancer

BACKGROUND Breast cancer(BC),a leading malignant disease,affects women all over the world.Cancer associated fibroblasts(CAFs)stimulate epithelial-mesenchymal transition,and induce chemoresistance and immunosuppression.AIM To establish a CAFs-associated prognostic signature to improve BC patient out-come estimation.METHODS We retrieved the transcript profile and clinical data of 1072 BC samples from The Cancer Genome Atlas(TCGA)databases,and 3661 BC samples from the The Gene Expression Omnibus.CAFs and immune cell infiltrations were quantified using CIBERSORT algorithm.CAF-associated gene identification was done by weighted gene co-expression network analysis.A CAF risk signature was established via univariate,least absolute shrinkage and selection operator regression,and mul-tivariate Cox regression analyses.The receiver operating characteristic(ROC)and Kaplan-Meier curves were employed to evaluate the predictability of the model.Subsequently,a nomogram was developed with the risk score and patient clinical signature.Using Spearman's correlations analysis,the relationship between CAF risk score and gene set enrichment scores were examined.Patient samples were collected to validate gene expression by quantitative real-time polymerase chain reaction(qRT-PCR).RESULTS Employing an 8-gene(IL18,MYD88,GLIPR1,TNN,BHLHE41,DNAJB5,FKBP14,and XG)signature,we attemp-ted to estimate BC patient prognosis.Based on our analysis,high-risk patients exhibited worse outcomes than low-risk patients.Multivariate analysis revealed the risk score as an independent indicator of BC patient prognosis.ROC analysis exhibited satisfactory nomogram predictability.The area under the curve showed 0.805 at 3 years,and 0.801 at 5 years in the TCGA cohort.We also demonstrated that a reduced CAF risk score was strongly associated with enhanced chemotherapeutic outcomes.CAF risk score was significantly correlated with most hallmark gene sets.Finally,the prognostic signature were further validated by qRT-PCR.CONCLUSION We introduced a newly-discovered CAFs-associated gene signature,which can be employed to estimate BC patient outcomes conveniently and accurately.

Identification of potential immune-related prognostic biomarkers of lung cancer using gene co-expression network analysis

Objective The objective of this study was to identify new carcinogenetic hub genes and develop the integration of differentially expressed genes to predict the prognosis of lung cancer.Methods GSE139032 microarray data packages were downloaded from the Gene Expression Omnibus for planning,testing,and review of data.We identified KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV from a key module for validation.Results We found that the five genes were related to a poor prognosis,and the expression levels of these genes were associated with tumor stage.Furthermore,Kaplan-Meier plotter showed that the five hub genes had better prognostic values.The mean levels of methylation in lung adenocarcinoma(LUAD)were significantly lower than those in healthy lung tissues for the hub genes.However,gene set enrichment analysis(GSEA)for single hub genes showed that all of them were immune-related.Conclusion Our findings demonstrated that KRT6C,LAMC2,LAMB3,KRT6A,and MYEOV are all candidate diagnostic and prognostic biomarkers for LUAD.They may have clinical implications in LUAD patients not only for the improvement of risk stratification but also for therapeutic decisions and prognosis prediction.

Huanglian decoction suppresses the growth of hepatocellular carcinoma cells by reducing CCNB1 expression

BACKGROUND Hepatocellular carcinoma(HCC)is one of the most prevalent cancers in human populations worldwide.Huanglian decoction is one of the most important Chinese medicine formulas,with the potential to treat cancer.AIM To investigate the role and mechanism of Huanglian decoction on HCC cells.METHODS To identify differentially expressed genes(DEGs),we downloaded gene expression profile data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma and Gene Expression Omnibus(GSE45436)databases.We obtained phytochemicals of the four herbs of Huanglian decoction from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform.We also established a regulatory network of DEGs and drug target genes and subsequently analyzed key genes using bioinformatics approaches.Furthermore,we conducted in vitro experiments to explore the effect of Huanglian decoction and to verify the predictions.In particular,the CCNB1 gene was knocked down to verify the primary target of this decoction.Through the identification of the expression levels of key proteins,we determined the primary mechanism of Huanglian decoction in HCC.RESULTS Based on the results of the network pharmacological analysis,we revealed 5 bioactive compounds in Huanglian decoction that act on HCC.In addition,a protein-protein interaction network analysis of the target genes of these five compounds as well as expression and prognosis analyses were performed in tumors.CCNB1 was confirmed to be the primary gene that may be highly expressed in tumors and was significantly associated with a worse prognosis.We also noted that CCNB1 may serve as an independent prognostic indicator in HCC.Moreover,in vitro experiments demonstrated that Huanglian decoction significantly inhibited the growth,migration,and invasiveness of HCC cells and induced cell apoptosis and G2/M phase arrest.Further analysis showed that the decoction may inhibit the growth of HCC cells by downregulating the CCNB1 expression level.After Huanglian decoction treatment,the expression levels of Bax,caspase 3,caspase 9,p21 and p53 in HCC cells were increased,while the expression of CDK1 and CCNB1 was significantly decreased.The p53 signaling pathway was also found to play an important role in this process.CONCLUSION Huanglian decoction has a significant inhibitory effect on HCC cells.CCNB1 is a potential therapeutic target in HCC.Further analysis showed that Huanglian decoction can inhibit HCC cell growth by downregulating the expression of CCNB1 to activate the p53 signaling pathway.

Identification of ITGA3 as an Oncogene in Human Tongue Cancer via Integrated Bioinformatics Analysis

Human tongue cancer （TC） is an aggressive malignancy with a very poor prognosis. There is an urgent need to elucidate the underlying molecular mechanisms involved in TC progression, mRNA expression profiles play a vital role in the exploration of cancer-related genes. Therefore, the purpose of our study was to identify the progression associated candidate genes of TC by bioinformatics analysis. Five microarray datasets of TC samples were downloaded from the Gene Expression Onmibus （GEO） database and the data of 133 TC patients were screened from The Cancer Genome Atlas （TCGA） head and neck squamous cell carcinoma （HNSC） database. The integrated analysis of five microarray datasets and the RNA sequencing data of TC samples in TCGA-HNSC was performed to obtain 1023 overlapping differentially expressed genes （DEGs） in TC and adjacent normal tissue （ANT） samples. Next, Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway analysis was conducted to enrich the significant pathways of the 1023 DEGs and PI3K- Akt signaling pathway （P=0.011） was selected to be the candidate pathway. A total of 23 DEGs with ｜log2 fold change （FC）｜ ≥1.0 in phosphatidylinositol 3-kinase-serine/threonine kinase （PI3K-Akt） signaling pathway were subjected to survival analysis of 125 eligible TC samples in TCGA database, indicating increased integrin-α3 gene （ITGA3） expression was significantly associated with poorer prognosis. Taken together, our study suggested ITGA3 may facilitate the development of TC via activating PI3K-Akt signaling pathway.

Analysis of differential genes of ischemic stroke-induced heart tissue in mice based on GEO database

Objective:The differential genes of left ventricle in middle cerebral artery occlusion model(MCAO)mice and Sham mice(Sham)mice at 24h and 72h after ischemia were compared respectively,and the differential genes and their regulated functional pathways were analyzed at different time points after ischemic stroke,so as to analyze the mechanism of inducing cardiac dysfunction after ischemic stroke and provide evidence for its treatment.Methods:Gene-chip data from the left ventricle of MCAO mice and Sham mice were downloaded from the GEO database at the National Center for Biotechnology Information(NCBI).The differentially expressed genes were obtained by R language software programming.The GO functional enrichment and KEGG pathway enrichment analysis of the obtained differential genes were performed using DAVID 6.8 online analysis tool,and the Omicshare online analysis tool was used to visualize the enrichment analysis results.Results:At 24h after ischemia,187 differentially expressed genes were obtained,including 56 GO enrichment pathways and 5 KEGG enrichment pathways with significant significance.After 72h after ischemia,51 differentially expressed genes were obtained,14 GO enrichment pathways and 3 KEGG enrichment pathways with significant significance.The two time points involved Aplnr and Itgb6 gene targets and PI3K-Akt signaling pathway.Conclusion:①By analyzing the gene expression profile data,the differentially expressed genes and related pathways of cardiac dysfunction induced by ischemic stroke were obtained.②PI3K-AKT signaling pathway is closely related to the regulation of cardiac function,and regulation of PI3K-AKT signaling pathway may be an important direction for the treatment of cardiac dysfunction after ischemic stroke.

综合分析TCGA与GEO甲基化数据鉴定胆管癌预后相关基因SOX9和FZD10

目的鉴定胆管癌(cholangiocarcinoma,CCA)甲基化与表达谱综合生物标志物,预测CCA患者预后。方法从癌症基因组图谱(The Cancer Genome Atlas,TCGA)下载33例CCA样本和8例正常样本基因组甲基化数据及临床信息表达谱数据,同时从基因表达综合数据库(Gene Expression Omnibus,GEO)下载甲基化数据进行验证。鉴定差异甲基化基因(DMGs)与差异表达基因(DEGs)的交集基因,采用Cox比例风险回归模型鉴定甲基化生物标志物,并使用ROC曲线来评估该模型的性能。在验证组中对该模型进行验证,通过GO功能注释,探讨DNA甲基化标志物的生物学功能。结果通过对TCGA甲基化数据分析,共鉴定出600个差异甲基化基因和6876个差异表达基因,并从中筛选出与生存相关的2个甲基化基因(SOX9和FZD10),最终将SOX9和FZD10组合基因构建预后预测模型,作为CCA预后的生物标志物。ROC曲线下面积(AUC)为0.90。SOX9和FZD10组合生物标志物能够将CCA患者区分为高风险组和低风险组,低风险组患者总生存期明显高于高风险组(2.07年vs 0.92年)。多因素Cox回归分析表明,SOX9和FZD10组合生物标志物是CCA患者预后的独立预测因子。基因本体(GO)功能分析表明,SOX9和FZD10参与转录因子、转录调控、肿瘤蛋白多糖调节和干细胞的调控。结论本研究经过多组学分析,在TCGA数据中筛选出SOX9和FZD10基因组合的甲基化预后标志物,可以将CCA患者分为高风险组与低风险组,并且该组合基因是CCA独立的预后预测因子。

Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis

Colorectal cancer(CRC)is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients.In this study,mRNA microarray datasets GSE113513,GSE21510,GSE44076,and GSE32323 were obtained from the Gene Expression Omnibus(GEO)and analyzed with bioinformatics to identify hub genes in CRC development.Differentially expressed genes(DEGs)were analyzed using the GEO2 R tool.Gene ontology(GO)and KEGG analyses were performed through the DAVID database.STRING database and Cytoscape software were used to construct a protein-protein interaction(PPI)network and identify key modules and hub genes.Survival analyses of the DEGs were performed on GEPIA database.The Connectivity Map database was used to screen potential drugs.A total of 865 DEGs were identified,including 374 upregulated and 491 downregulated genes.These DEGs were mainly associated with metabolic pathways,pathways in cancer,cell cycle and so on.The PPI network was identified with 863 nodes and 5817 edges.Survival analysis revealed that HMMR,PAICS,ETFDH,and SCG2 were significantly associated with overall survival of CRC patients.And blebbistatin and sulconazole were identified as candidate drugs.In conclusion,our study found four hub genes involved in CRC,which may provide novel potential biomarkers for CRC prognosis,and two potential candidate drugs for CRC.

Why MUC16 mutations lead to a better prognosis:A study based on The Cancer Genome Atlas gastric cancer cohort

BACKGROUND MUC16,encoding cancer antigen 125,is a frequently mutated gene in gastric cancer.In addition,MUC16 mutations seem to result in a better prognosis in gastric cancer.However,the mechanisms that lead to a better prognosis by MUC16 mutations have not yet been clarified.AIM To delve deeper into the underlying mechanisms that explain why MUC16 mutations signal a better prognosis in gastric cancer.METHODS We used multi-omics data,including mRNA,simple nucleotide variation,copy number variation and methylation data from The Cancer Genome Atlas,to explore the relationship between MUC16 mutations and prognosis.Cox regression and random survival forest algorithms were applied to search for hub genes.Gene set enrichment analysis was used to elucidate the molecular mechanisms.Single-sample gene set enrichment analysis and“EpiDISH”were used to assess immune cells infiltration,and“ESTIMATE”for analysis of the tumor microenvironment.RESULTS Our study found that compared to the wild-type group,the mutation group had a better prognosis.Additional analysis indicated that the MUC16 mutations appear to activate the DNA repair and p53 pathways to act as an anti-tumor agent.We also identified a key gene,NPY1R(neuropeptide Y receptor Y1),which was significantly more highly expressed in the MUC16 mutations group than in the MUC16 wild-type group.The high expression of NPY1R predicted a poorer prognosis,which was also confirmed in a separate Gene Expression Omnibus cohort.Further susceptibility analysis revealed that NPY1R might be a potential drug target for gastric cancer.Furthermore,in the analysis of the tumor microenvironment,we found that immune cells in the mutation group exhibited higher anti-tumor effects.In addition,the tumor mutation burden and cancer stem cells index were also higher in the mutation group than in the wild-type group.CONCLUSION We speculated that the MUC16 mutations might activate the p53 pathway and DNA repair pathway:alternatively,the tumor microenvironment may be involved.

Characterization of candidate factors associated with the metastasis and progression of high-grade serous ovarian cancer

Background:High-grade serous ovarian cancer(HGSOC)is the biggest cause of gynecological cancer-related mortality because of its extremely metastatic nature.This study aimed to explore and evaluate the characteristics of candidate factors associated with the metastasis and progression of HGSOC.Methods:Transcriptomic data of HGSOC patients’samples collected from primary tumors and matched omental metastatic tumors were obtained from three independent studies in the National Center for Biotechnology Information(NCBI)Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were selected to evaluate the effects on the prognosis and progression of ovarian cancer using data from The Cancer Genome Atlas(TCGA)database.Hub genes’immune landscapes were estimated by the Tumor Immune Estimation Resource(TIMER)database.Finally,using 25 HGSOC patients'cancer tissues and 10 normal fallopian tube tissues,immunohistochemistry(IHC)was performed to quantify the expression levels of hub genes associated with International Federation of Gynecology and Obstetrics(FIGO)stages.Results:Fourteen DEGs,ADIPOQ,ALPK2,BARX1,CD37,CNR2,COL5A3,FABP4,FAP,GPR68,ITGBL1,MOXD1,PODNL1,SFRP2,and TRAF3IP3,were upregulated in metastatic tumors in every database while CADPS,GATA4,STAR,and TSPAN8 were downregulated.ALPK2,FAP,SFRP2,GATA4,STAR,and TSPAN8 were selected as hub genes significantly associated with survival and recurrence.All hub genes were correlated with tumor microenvironment infiltration,especially cancer-associated fibroblasts and natural killer(NK)cells.Furthermore,the expression of FAP and SFRP2 was positively correlated with the International Federation of Gynecology and Obstetrics(FIGO)stage,and their increased protein expression levels in metastatic samples compared with primary tumor samples and normal tissues were confirmed by IHC(P=0.0002 and P=0.0001,respectively).Conclusions:This study describes screening for DEGs in HGSOC primary tumors and matched metastasis tumors using integrated bioinformatics analyses.We identified six hub genes that were correlated with the progression of HGSOC,particularly FAP and SFRP2,which might provide effective targets to predict prognosis and provide novel insights into individual therapeutic strategies for HGSOC.

Construction and Analysis of an LncRNA-miRNA-mRNA Network Based on Competitive Endogenous RNA Reveal miRNAs Potentially Involved in In-stent Restenosis after Percutaneous Coronary Intervention

Objective:Percutaneous coronary intervention is one of the most common procedures used for the invasive treatment of patients with coronary heart disease;the incidence of in-stent restenosis(ISR)after percutaneous coronary intervention is 5%to 15%.In this study,a competitive endogenous RNA(ceRNA)network was constructed to investigate potential mechanisms involved in ISR.Methods:The expression data for differentially expressed microRNAs(DEmiRNAs)and messenger RNAs(mRNAs)between patients with and without ISR were obtained using limma package.Long noncoding RNAs(lncRNAs)were predicted based on the DEmiRNAs using the miRDB,miRTarBase,and TargetScan databases.An ISR-specific ceRNA network was subsequently constructed and investigated.To verify the key miRNAs of ceRNA,patients with and without ISR were enrolled from Guangdong Provincial Hospital of Chinese Medicine between January 2017 and December 2018(n=8,respectively);plasma was collected from all enrolled patients.Results:Based on the raw data obtained from the Gene Expression Omnibus database,472 DEmiRNAs and 304 differentilly expressed messenger RNAs between patients with and without ISR were identified.A ceRNA network was constructed by combining 270 IncRNAs,3 miRNAs(miR-125,miR-140,and miR-206),and 4 mRNAs(STRADB,TKT,PCTP,and BTG2).The hub genes of the ceRNA network of ISR included the following:miR-125,miR-206,miR-140,PCDHB9,CASC2,BAK1P1,CSPG4P3Y,CSPG4P4Y,STRCP1,and GRIP2.Verification of miRNAs of ceRNA also showed that the expression of miR-206 was upregulated in patients with ISR vs.those without ISR(P<0.05).In contrast,the expression of miR-140 and miR-125 was downregulated in patients with ISR vs.those without ISR(P<0.05).Conclusions:This study constructed noncoding RNA-related ceRNA networks for ISR.The results indicated that miR-206,miR-125,and miR-140 may be biomarkers of ISR.

Prognostic biomarkers and immune cell infiltration characteristics in small cell lung cancer

Background Small cell lung cancer(SCLC)is a highly malignant and aggressive neuroendocrine tumor.With the rise of immunotherapy,it has provided a new direction for SCLC.However,due to the lack of prognostic biomarkers,the median overall survival of SCLC is still to be improved.This study aimed to explore novel biomarkers and tumor-infiltrating immune cell characteristics that may serve as potential diagnostic and prognostic markers in SCLC.Methods Gene expression profiles from patients with SCLC were downloaded from the Gene Expression Omnibus(GEO)database,and tumor microenvironment(TME)infiltration profile data were obtained using CIBERSORT.The robust rank aggregation(RRA)method was utilized to integrate three SCLC microarray datasets downloaded from the GEO database and identify robust differentially expressed genes(DEGs)between normal and tumor tissue samples.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were performed to explore the functions of the robust DEGs.Subsequently,protein-protein interaction networks and key modules were constructed by Cytoscape,and hub genes were selected from the whole network using the plugin cytoHubba.Survival analysis of hub genes was performed by Kaplan-Meier plotter in 18 patients with extensive-stage SCLC.Results A total of 312 robust DEGs,including 55 upregulated and 257 downregulated genes,were screened from 129 SCLC tissue samples and 44 normal tissue samples.GO and KEGG enrichment analyses revealed that the robust DEGs were predominantly involved in human T-cell leukemia virus 1 infection,focal adhesion,complement and coagulation cascades,tumor necrosis factor(TNF)signaling pathway,and ECM-receptor interaction,which are closely associated with the development and progression of SCLC.Subsequently,three DEGs modules and six hub genes(ITGA10,DUSP12,PTGS2,FOS,TGFBR2,and ICAM1)were identified through screening with the Cytoscape plugins MCODE and cytoHubba,respectively.Immune cell infiltration analysis by the CIBERSORT algorithm revealed that resting memory CD4+T cells were the predominant infiltrating immune cells in SCLC.In addition,Kaplan-Meier plotter revealed that the gene prostaglandin-endoperoxide synthase 2(PTGS2)was a potential prognostic biomarker of SCLC.Conclusions Hub genes and tumor-infiltrating immune cells may be the molecular mechanisms underlying the development of SCLC,and this finding could contribute to the formulation of individualized immunotherapy strategies for SCLC.

Long non-coding RNA SAP30-2:1 is downregulated in congenital heart disease and regulates cell proliferation by targeting HAND2

Congenital heart disease(CHD)is the most common birth defect worldwide.Long non-coding RNAs(lncRNAs)have been implicated in many diseases.However,their involvement in CHD is not well understood.This study aimed to investigate the role of dysregulated lncRNAs in CHD.We used Gene Expression Omnibus data mining,bioinformatics analysis,and analysis of clinical tissue samples and observed that the novel lncRNA SAP30-2:1 with unknown function was significantly downregulated in damaged cardiac tissues from patients with CHD.Knockdown of lncRNA SAP30-2:1 inhibited the proliferation of human embryonic kidney and AC16 cells and decreased the expression of heart and neural crest derivatives expressed 2(HAND2).Moreover,lncRNA SAP30-2:1 was associated with HAND2 by RNA immunoprecipitation.Overall,these results suggest that lncRNA SAP30-2:1 may be involved in heart development through affecting cell proliferation via targeting HAND2 and may thus represent a novel therapeutic target for CHD.