Research progress in tumor angiogenesis and drug resistance in breast cancer

Angiogenesis is considered a hallmark pathophysiological process in tumor development. Aberrant vasculature resulting from tumor angiogenesis plays a critical role in the development of resistance to breast cancer treatments, via exacerbation of tumor hypoxia, decreased effective drug concentrations within tumors, and immune-related mechanisms. Antiangiogenic therapy can counteract these breast cancer resistance factors by promoting tumor vascular normalization. The combination of antiangiogenic therapy with chemotherapy, targeted therapy, or immunotherapy has emerged as a promising approach for overcoming drug resistance in breast cancer. This review examines the mechanisms associated with angiogenesis and the interactions among tumor angiogenesis, the hypoxic tumor microenvironment, drug distribution, and immune mechanisms in breast cancer. Furthermore, this review provides a comprehensive summary of specific antiangiogenic drugs, and relevant studies assessing the reversal of drug resistance in breast cancer. The potential mechanisms underlying these interventions are discussed, and prospects for the clinical application of antiangiogenic therapy to overcome breast cancer treatment resistance are highlighted.

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.

Predicting the Prognosis and Immunotherapeutic Response of Triple-Negative Breast Cancer by Constructing a Prognostic Model Based on CD8+T Cell-Related Immune Genes

Objective Triple-negative breast cancer(TNBC)poses a significant challenge for treatment efficacy.CD8+T cells,which are pivotal immune cells,can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology.By leveraging these genes,our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy.Methods Sample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases.In the initial stage,we identified 67 differentially expressed genes associated with immune response in CD8+T cells.Subsequently,we narrowed our focus to three key genes,namely CXCL13,GBP2,and GZMB,which were used to construct a prognostic model.The accuracy of the model was assessed using the validation set data and receiver operating characteristic(ROC)curves.Furthermore,we employed various methods,including Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,immune infiltration,and correlation analyses with CD274(PD-L1)to explore the model's predictive efficacy in immunotherapeutic responses.Additionally,we investigated the potential underlying biological pathways that contribute to divergent treatment responses.Results We successfully developed a model capable of predicting the prognosis of patients with TNBC.The areas under the curve(AUC)values for the 1-,3-,and 5-year survival predictions were 0.618,0.652,and 0.826,respectively.Employing this risk model,we stratified the samples into high-and low-risk groups.Through KEGG enrichment analysis,we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism,whereas the low-risk group demonstrated significant enrichment in cytokine pathways.Furthermore,immune landscape analysis revealed noteworthy variations between(PD-L1)expression and risk scores,indicating that our model effectively predicted the response of patients to immune-based treatments.Conclusion Our study demonstrates the potential of CXCL13,GBP2,and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC.These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.

A Prognostic Model Based on Colony Stimulating Factors-related Genes in Triple-negative Breast Cancer

Objective Triple-negative breast cancer(TNBC)is the breast cancer subtype with the worst prognosis,and lacks effective therapeutic targets.Colony stimulating factors(CSFs)are cytokines that can regulate the production of blood cells and stimulate the growth and development of immune cells,playing an important role in the malignant progression of TNBC.This article aims to construct a novel prognostic model based on the expression of colony stimulating factors-related genes(CRGs),and analyze the sensitivity of TNBC patients to immunotherapy and drug therapy.Methods We downloaded CRGs from public databases and screened for differentially expressed CRGs between normal and TNBC tissues in the TCGA-BRCA database.Through LASSO Cox regression analysis,we constructed a prognostic model and stratified TNBC patients into high-risk and low-risk groups based on the colony stimulating factors-related genes risk score(CRRS).We further analyzed the correlation between CRRS and patient prognosis,clinical features,tumor microenvironment(TME)in both high-risk and low-risk groups,and evaluated the relationship between CRRS and sensitivity to immunotherapy and drug therapy.Results We identified 842 differentially expressed CRGs in breast cancer tissues of TNBC patients and selected 13 CRGs for constructing the prognostic model.Kaplan-Meier survival curves,time-dependent receiver operating characteristic curves,and other analyses confirmed that TNBC patients with high CRRS had shorter overall survival,and the predictive ability of CRRS prognostic model was further validated using the GEO dataset.Nomogram combining clinical features confirmed that CRRS was an independent factor for the prognosis of TNBC patients.Moreover,patients in the high-risk group had lower levels of immune infiltration in the TME and were sensitive to chemotherapeutic drugs such as 5-fluorouracil,ipatasertib,and paclitaxel.Conclusion We have developed a CRRS-based prognostic model composed of 13 differentially expressed CRGs,which may serve as a useful tool for predicting the prognosis of TNBC patients and guiding clinical treatment.Moreover,the key genes within this model may represent potential molecular targets for future therapies of TNBC.

Bioinformatics screening of breast cancer-related genes and potential drug research

Objective:To search the the differentially expressed genes between breast cell carcinoma tissues and normal tissues by using bioinformatics technology,and the potential therapeutic drugs for breast cancer were identified,which can provide reference for clinical immune targeted therapy and drug therapy of breast cancer in the future.Methods:"Breast cancer"was searched by using Gene Expression Omnibus(GEO),and GSE79586 chip data was downloaded.The differentially expressed genes in the control group and the breast cancer model group were screened by using bio-communication technology and subjected to GO function analysis,KEGG pathway analysis,differential gene characteristic expression analysis and protein-protein interaction network(PPI)analysis,and the analysis results were further visualized.Prognosis analysis,related function prediction and immune infiltration analysis were performed using the GEPIA,GeneMANIA,and Timer2.0 databases,respectively.Finally,the compounds with potential therapeutic effects on breast cancer are identified through Connectivity Map(CMap).Western blotting and real-time PCR(RT-PCR)were used to verify the core genes and potential therapeutic agents with the highest correlation in vitro.Results:A total of 3916 differentially expressed genes including 1786 up-regulated genes and 2130 down-regulated genes were screened.GO analysis showed that the differential genes were mainly involved in the positive regulation of phosphorylation,secretory vesicles,racemase and epimerase activities.KEGG analysis showed that differential genes were involved in systemic lupus erythematosus,alcoholism,sticky spots,amoebic dysentery Ras signal pathways and other disease pathways.The characteristic expression analysis of differential genes showed that MEK inhibitors,HSP90 inhibitors and signal transduction pathway kinase inhibitors were drugs similar to the differential genes.PPI results showed that H2AFJ,TFF1,GATA3,FOXA1,and CDH1 were core genes related to breast cancer.Two core genes of H2AFJ and TFF1 with the highest correlation were further selected for GEPIA analysis.The results of the analysis showed that the mRNA expression levels of H2AFJ and TFF1 in breast cancer cells were significantly higher than those in normal tissues,and there was a significant correlation with the pathological staging,overall survival rate and disease-free survival rate of breast cancer patients.H2AFJ and TFF1 may be potential prognostic biomarkers for survival of breast cancer patients.The functions of differentially expressed H2AFJ and TFF1 are mainly related to hormone receptor binding,epithelial structure maintenance and epigenetic negative regulation of genes,chromatin tissue involved in negative regulation of transcription,etc.The results of immune infiltration showed that the expressions of H2AFJ and TFF1 had a significant correlation with the infiltration of macrophages,neutrophils,monocytes,CD4+T,CD8+T,B lymphocytes and other immune cells.CMap results showed that compounds such as Gefitinib,Alpelisib,Sorafenib,and Sunitinib had potential therapeutic effects on breast cancer.Western blot and RT-PCR results showed that H2AFJ and TFF1 were significantly overexpressed in breast cancer cells.Gefitinib significantly inhibited the expression of H2AFJ and TFF1 in breast cancer cells(P<0.05,P<0.01).Conclusion:In this study,differentially expressed genes between breast cell carcinoma tissues and normal tissues were screened out by bioinformatics means to further identify key genes and compounds with potential therapeutic effects in the onset process of breast cancer and to further verify the effectiveness of the screened drugs on breast cancer through experiments.It will provide reference for clinical research and development of new drugs against breast cancer in the future in order to develop more effective treatment options.

An inflammatory-related genes signature based model for prognosis prediction in breast cancer

Background:Breast cancer has become the most common malignant tumor in the world.It is vital to discover novel prognostic biomarkers despite the fact that the majority of breast cancer patients have a good prognosis because of the high heterogeneity of breast cancer,which causes the disparity in prognosis.Recently,inflammatory-related genes have been proven to play an important role in the development and progression of breast cancer,so we set out to investigate the predictive usefulness of inflammatory-related genes in breast malignancies.Methods:We assessed the connection between Inflammatory-Related Genes(IRGs)and breast cancer by studying the TCGA database.Following differential and univariate Cox regression analysis,prognosis-related differentially expressed inflammatory genes were estimated.The prognostic model was constructed through the Least Absolute Shrinkage and Selector Operation(LASSO)regression based on the IRGs.The accuracy of the prognostic model was then evaluated using the Kaplan-Meier and Receiver Operating Characteristic(ROC)curves.The nomogram model was established to predict the survival rate of breast cancer patients clinically.Based on the prognostic expression,we also looked at immune cell infiltration and the function of immune-related pathways.The CellMiner database was used to research drug sensitivity.Results:In this study,7 IRGs were selected to construct a prognostic risk model.Further research revealed a negative relationship between the risk score and the prognosis of breast cancer patients.The ROC curve proved the accuracy of the prognostic model,and the nomogram accurately predicted survival rate.The scores of tumorinfiltrating immune cells and immune-related pathways were utilized to calculate the differences between the low-and high-risk groups,and then explored the relationship between drug susceptibility and the genes that were included in the model.Conclusion:These findings contributed to a better understanding of the function of inflammatory-related genes in breast cancer,and the prognostic risk model provides a potentially promising prognostic strategy for breast cancer.

Bioinformatics analysis of key genes associated with the prognosis of breast cancer

Objective:We sought to identify potential therapeutic targets for breast cancer patients by employing a bioinformatics analysis to screen for genes linked with an unfavorable prognosis.Methods:The Gene Expression Omnibus(GEO)database was utilized to obtain three gene expression profile datasets,namely GSE42568,GSE86374,and GSE71053.To identify differentially expressed genes(DEGs),the GEO2R online tool was employed.Subsequently,a func-tional enrichment analysis was conducted.Moreover,a protein-protein interaction network was established using STRING,and DEGs were subjected to module analysis via Cytoscape software to identify pivotal genes.Additionally,the selected pivotal genes underwent further ex-amination and validation utilizing three databases:GEPIA,UALCAN,and Kaplan-Meier Plotter.Results:A total of 121 DEGs were detected,comprising 74 genes with increased expression and 47 genes with decreased expression.Ten key genes were identified:HMMR,RRM2,CDK1,TOP2A,AURKA,CCNB1,MAD2L1,KIF2C,BUB1B,UBE2C.Validation in the GEPIA database revealed high expression levels for all key genes except CDK1.A survival analysis conducted using the Kaplan-Meier Plotter database revealed noteworthy associations between nine crucial genes and the overall survival(OS)of individuals diagnosed with breast cancer.Moreover,these nine key genes exhibited significantly increased expression across different molecular subtypes of breast cancer according to the UALCAN data platform.Conclusions:We identified nine crucial genes significantly linked to the onset,progression,and unfavorable prognosis of breast cancer,providing potential targets for novel treatment options and biomarkers to predict patient outcomes.

Hypoxia-induced factor-1 alpha upregulates vascular endothelial growth factor C to promote lymphangiogenesis and angiogenesis in breast cancer patients

Hypoxia-induced factor-1 alpha （HIF-1α） affects many effector molecules and regulates tumor lymphangio- genesis and angiogenesis during hypoxia. The aim of this study was to investigate the role of HIF-1α in the regu- lation of vascular endothelial growth factor C （VEGF-C） expression and its effect on lymphangiogenesis and an- giogenesis in breast cancer. Lymphatic vessel density （LVD）, microvessel density （MVD） and the expressions of HIF-1α and VEGF-C proteins were evaluated by immunohistochemistry in 75 breast cancer samples. There was a significant correlation between HIF-1α and VEGF-C （P = 0.014, r = 0.273, Spearman＇s coefficient of correlation）. HIF-1α and VEGF-C overexpression was significantly correlated with higher LVD （P = 0.003 and P = 0.017, re- spectively）, regional lymph nodal involvement （P = 0.002 and P = 0.004, respectively） and advanced tumor, node, metastasis （TNM） classification （P = 0.001 and P = 0.01, respectively）. Higher MVD was observed in the group expressing higher levels of HIF-1α and VEGF-C （P = 0.033 and P = 0.037, respectively）. Univariate analysis showed shorter survival time in patients expressing higher levels of HIF-1α and VEGF-C. HIF-1α was also found to be an independent prognostic factor of overall survival in multivariate analysis. The results suggest that HIF-1α may affect VEGF-C expression, thus acting as a crucial regulator of lymphangiogenesis and angiogenesis in breast cancer. This study highlights promising potential of HIF- 1α as a therapeutic target against tumor lymph node me- tastasis.

The mutation landscape of multiple cancer predisposition genes in Chinese familial/hereditary breast cancer families

Objective:Approximately 5%–10%of breast cancer(BC)patients display familial traits that are genetically inherited among the members of a family.The purpose of this study was to profile the germline mutations in 43 genes with different penetration rates and their correlations with phenotypic traits in Chinese familial BC families.Methods:Ion Torrent S5™-based next generation sequencing was conducted on 116 subjects from 27 Chinese familial BC families.Results:Eighty-one germline mutations in 27 BC predisposition genes were identified in 82.8%(96/116)of the cases.Among these,80.8%of the mutated genes were related to DNA damage repair.Fourteen possible disease-causing variants were identified in 13 of 27 BC families.Only 25.9%(7/27)of the BC families exhibited hereditary deficiency in BRCA1/2 genes,while 22.2%of the BC families exhibited defects in non-BRCA genes.In all,41.7%(40/96)of the mutation carriers had BRCA mutations,88.5%(85/96)had non-BRCA mutations,and 30.2%(29/96)had both BRCA and non-BRCA mutations.The BC patients with BRCA mutations had a higher risk of axillary lymph node metastases than those without mutations(P<0.05).However,the BC patients with non-BRCA mutations frequently had a higher occurrence of benign breast diseases than those without mutations(P<0.05).Conclusions:In addition to BRCA1/2,genetic variants in non-BRCA DNA repair genes might play significant roles in the development of familial/hereditary BC.Therefore,profiling of multiple BC predisposition genes should be more valuable for screening potential pathogenic germline mutations in Chinese familial/hereditary BC.

Association between 15 known or potential breast cancer susceptibility genes and breast cancer risks in Chinese women

Objective:There are many hereditary breast cancer patients in China,and multigene panel testing has been a new paradigm of genetic testing for these patients and their relatives.However,the magnitude of breast cancer risks related to multiple breast cancer susceptibility genes are largely unknown in Chinese women.Methods:We screened pathogenic variants in 15 established or potential breast cancer susceptibility genes from 8,067 consecutive Chinese female breast cancer patients and 13,129 Chinese cancer-free female controls.These breast cancer patients were unselected for age at diagnosis or family history.Results:We found that pathogenic variants in TP53[odds ratio(OR):16.9,95%confidence interval(CI):5.2–55.2];BRCA2(OR:10.4,95%CI:7.6–14.2);BRCA1(OR:9.7,95%CI:6.3–14.8);and PALB2(OR:5.2,95%CI:3.0–8.8)were associated with a high risk of breast cancer.ATM,BARD1,CHEK2,and RAD51D were associated with a moderate risk of breast cancer with ORs ranging from 2-fold to 4-fold.In contrast,pathogenic variants of NBN,RAD50,BRIP1,and RAD51C were not associated with increased risk of breast cancer in Chinese women.The pathogenic variants of PTEN,CDH1,and STK11 were very rare,so they had a limited contribution to Chinese breast cancer.Patients with pathogenic variants of TP53,BRCA1,BRCA2,and PALB2 more often had earlyonset breast cancer,bilateral breast cancer,and a family history of breast cancer and/or any cancer.Conclusions:This study provided breast cancer risk assessment data for multiple genes in Chinese women,which is useful for genetic testing and clinical management of Chinese hereditary breast cancer.

The biogenesis,function and clinical significance of circular RNAs in breast cancer

Circular RNAs(circ RNAs)are noncoding RNAs that form covalently closed loop structures.Circ RNAs are dysregulated in cancer and play key roles in tumorigenesis,diagnosis,and tumor therapy.Circ RNAs function as competing endogenous RNAs or micro RNA sponges that regulate transcription and splicing,binding to proteins,and translation.Circ RNAs may serve as novel biomarkers for cancer diagnosis,and they show potential as therapeutic targets in cancers including breast cancer(BC).In women,BC is the most common malignant tumor worldwide and the second leading cause of cancer death.Although evidence indicates that circ RNAs play a critical role in BC,the mechanisms regulating the function of circ RNAs in BC remain poorly understood.Here,we provide literature review aiming to clarify the role of circ RNAs in BC and summarize the latest research.We provide a systematic overview of the biogenesis and biological functions of circ RNAs,elaborate on the functional roles of circ RNAs in BC,and highlight the value of circ RNAs as diagnostic and therapeutic targets in BC.

Tea polyphenols inhibit the growth and angiogenesis of breast cancer xenografts in a mouse model

Objective:To investigate the anti-angiogenic effect of tea polyphenols(TPS)on breast cancer and normal tissues in a mouse model.Methods:Breast cancer was successfully implanted into 48 BALB/c mice,which were then randomly divided into a TP oral gavage group,a TP local injection group,a ginsenoside Rg3 group,and a model control group according to a random number table.The tumor inhibitory rates of each group were calculated,while microvessel density(MVD)and the expression of vascular endothelial growth factor(VEGF),basic fibroblast growth factor(bFGF),and tissue inhibitor of metalloproteinase(TIMP-2)were detected by immunohistochemistry.Results:TPs could inhibit the growth of breast cancer xenografts in the mouse model.The tumor inhibition rates of the TP oral gavage and TP local injection groups were 37.43%and 40.94%,respectively.Compared with the model control group,MVD and VEGF and bFGF expression was downregulated(all P<.05),whereas TIMP-2 expression was elevated in the TP oral gavage and TP local injection groups(P=.015 and P=.032).TPs showed no significant effect on MVD and VEGF and TIMP-2 expression in the heart,brain,and kidney of the mouse model.Conclusion:TPs can restrict the growth of breast cancer by specifically inhibiting the angiogenesis of breast tumor tissue while having little effect on the normal tissue of important organs including the heart,brain,and kidney.

ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

Objective： To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods： Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe, mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip.The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5〉3.5 meant significant up-regulation. Cy3/Cy5〈0.25 meant significant down-regulation. Results： The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion： Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

EXPRESSION OF THE RETINOIC ACID RECEPTORS(RARs)AND RETINOID X RECEPTOR(RXRs)GENES IN BREAST CANCER

A number of studies have been shown that retiniods can inhibit malignant cell growth including certain breast carcinoma cells. Its inhibitory effort is observed only in ER-positive but not in ER-negative breast cancer cells. We examined retinoic acid receptors (RARs) and retinoids X receptors (RXRs) levels in 6 breast carcinoma cell lines and 18 breast cancer biopsy specimens. We found that RAR-α mRNA level was significantly higher in ER positive cell lines and samples. RAR-γ mRNA was expressed at relatively high levels in majority of tumor samples independent of the ER-status while RAR-β mRNA was expressed at low levels. We also found high RXR-α mRNA levels in all of the tumor samples examined while RXR-γ mRNA could not be detected. Our study suggests a possibility that retinoids inhibit tumor cell growth through RAR-a and RAR-α levels may serve as a potential marker to determine responsiveness of patients to retinoids therapy.

The Role of HER2/Neu and BRCA1 Genes in the Diagnosis of Breast Cancer among Sudanese Women

Background: Knowledge of HER2/Neu and BRCA1 Genes might be helpful for development of strategies for decreasing the burden of risk of breast cancer. Therefore, the aim of this study to detect the role of HER2/Neu and BRCA1 Genes expression in diagnosis of breast cancer in Sudanese women. Methodology: A total of 100 tissue samples obtained from patients with breast cancer in addition to 50 tissue samples obtained from patients with benign breast lesions, were detected the expression of HER2/Neu and BRCA1 Genes by Polymerase Chain Reaction (PCR). Results: The prevalence of HER2/Neu and BRCA1 Genes, among cases was 6%, and 10% respectively. Conclusion: HER2/Neu and BRCA1 Genes have a considerable contribution to etiology of breast cancer in Sudan that requires further consideration.

Identification of overlapping differentially expressed genes in hepatocellular carcinoma,breast cancer,and depression by bioinformatics analysis

Objective:This study aimed to determine the presence of statistically significant relationships between these factors using bioinformatics analysis to identify overlapping differentially expressed genes(DEGs).Methods:The expression microarray data of GSE19665,GSE65194 and GSE12654 were obtained by GEO2R.Then,the overlapping DEGs of hepatocellular carcinoma(HCC),breast cancer(BC)and depression were analyzed by Gene Ontology,Kyoto Encyclopedia of Genes and Genomes and protein-protein interaction networks.Finally,the protein-protein interaction network was constructed by STRING and DEGs were sorted by Cytoscape.Results:The results indicated that multiple genes,including RNA-binding protein with multiple splicing,GATA binding protein 6,angiotensin II receptor type 1,ETS variant 6,TNF receptor superfamily member 17,aurora kinase A,integrin subunit alpha 6 and fibrinogen-like protein 2 might be common factors related to HCC,BC and depression.Conclusion:These results indicate that the genetic profile of HCC,BC and depression,may yield valuable insights for our understanding of the underlying mechanisms underlying synergistic genetic regulation and may provide novel ideas for developing homeopathic therapies based on bioinformatics data.

The prognostic genes of breast cancer and clinical significance

Breast cancer is one of the most frequent malignant tumors and is receiving more attention due to the increasing incidence and detection rate.Further studies regarding prognosis genes for biology are being conducted.The paper aims to review the prognostic indexes of breast cancer such as p16,Her-2,Ki-67,MCM7.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer

BACKGROUND A growing number of clinical examples suggest that coronavirus disease 2019(COVID-19)appears to have an impact on the treatment of patients with liver cancer compared to the normal population,and the prevalence of COVID-19 is significantly higher in patients with liver cancer.However,this mechanism of action has not been clarified.Gene sets for COVID-19(GSE180226)and liver cancer(GSE87630)were obtained from the Gene Expression Omnibus database.After identifying the common differentially expressed genes(DEGs)of COVID-19 and liver cancer,functional enrichment analysis,protein-protein interaction network construction and scree-ning and analysis of hub genes were performed.Subsequently,the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed.RESULTS Of 518 common DEGs were obtained by screening for functional analysis.Fifteen hub genes including aurora kinase B,cyclin B2,cell division cycle 20,cell division cycle associated 8,nucleolar and spindle associated protein 1,etc.,were further identified from DEGs using the“cytoHubba”plugin.Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation,cell cycle and other functions,and they may serve as potential molecular markers for COVID-19 and liver cancer.Finally,we selected 10 of the hub genes for in vitro expression validation in liver cancer cells.CONCLUSION Our study reveals a common pathogenesis of liver cancer and COVID-19.These common pathways and key genes may provide new ideas for further mechanistic studies.

Cyclooxygenase-2 and the inflammogenesis of breast cancer

Cohesive scientific evidence from molecular, animal, and human investigations supports the hypothesis that constitutive overexpression of cyclooxygenase-2(COX-2) is a ubiquitous driver of mammary carcinogenesis, and reciprocally, that COX-2 blockade has strong potential for breast cancer prevention and therapy. Key findings include the following:(1) COX-2 is constitutively expressed throughout breast cancer development and expression intensifies with stage at detection, cancer progression and metastasis;(2) essential features of mammary carcinogenesis(mutagenesis, mitogenesis, angiogenesis, reduced apoptosis, metastasis and immunosuppression) are linked to COX-2-driven prostaglandin E2(PGE-2) biosynthesis;(3) upregulation of COX-2 and PGE-2 expression induces transcription of CYP-19 and aromatase-catalyzed estrogen biosynthesis which stimulates unbridled mitogenesis;(4) extrahe-patic CYP-1B1 in mammary adipose tissue converts paracrine estrogen to carcinogenic quinones with mutagenic impact; and(5) agents that inhibit COX-2 reduce the risk of breast cancer in women without disease and reduce recurrence risk and mortality in women with breast cancer. Recent sharp increases in global breast cancer incidence and mortality are likely driven by chronic inflammation of mammary adipose and upregulation of COX-2 associated with the obesity pandemic. The totality of evidence clearly supports the supposition that mammary carcinogenesis often evolves as a progressive series of highly specific cellular and molecular changes in response to induction of constitutive overexpression of COX-2 and the prostaglandin cascade in the "inflammogenesis of breast cancer".

RNA-seq analysis identified hormone-related genes associated with prognosis of triple negative breast cancer

Triple negative breast cancer(TNBC) is an aggressive subtype of breast cancer that currently lacks effective biomarkers and therapeutic targets required to investigate the diagnosis and treatment of TNBC. Here we performed a comprehensive differential analysis of 165 TNBC samples by integrating RNA-seq data of breast tumor tissues and adjacent normal tissues from both our cohort and The Cancer Genome Atlas(TCGA). Pathway enrichment analysis was conducted to evaluate the biological function of TNBC-specific expressed genes. Further multivariate Cox proportional hazard regression was performed to evaluate the effect of these genes on TNBC prognosis. In this report, we identified a total of 148 TNBC-specific expressed genes that were primarily enriched in mammary gland morphogenesis and hormone levels related pathways, suggesting that mammary gland morphogenesis might play a unique role in TNBC patients differing from other breast cancer types. Further survival analysis revealed that nine genes(FSIP1, ADCY5, FSD1, HMSD, CMTM5, AFF3, CYP2 A7, ATP1 A2,and C11 orf86) were significantly associated with the prognosis of TNBC patients, while three of them(ADCY5,CYP2 A7, and ATP1 A2) were involved in the hormone-related pathways. These findings indicated the vital role of the hormone-related genes in TNBC tumorigenesis and may provide some independent prognostic markers as well as novel therapeutic targets for TNBC.