Construction of Bone Metastasis-Specific Regulation Network Based on Prognostic Stemness-Related Signatures in Breast Invasive Carcinoma

Abstract

BackgroundBone is the most common metastatic site of Breast invasive carcinoma (BRCA). In this study, the bone metastasis-specific regulation network of BRCA was constructed based on prognostic stemness-related signatures (PSRSs), their upstream transcription factors (TFs) and downstream pathways.MethodsClinical information and RNA-seq data of 1,080 primary BRCA samples (1,048 samples without bone metastasis and 32 samples with bone metastasis) were downloaded from The Cancer Genome Atlas (TCGA). The edgeR method was performed to identify differential expressed genes (DEGs). Next, mRNA stemness index (mRNAsi) was calculated by one-class logistic regression (OCLR). To analyze DEGs by classification, similar genes were integrated into the same module by weighted gene co-expression network analysis (WGCNA). Then, univariate and multivariate Cox proportional hazard regression were applied to find the PSRSs. Furthermore, PSRSs, 318 TFs obtained from Cistrome database and 50 hallmark pathways quantified by GSVA were integrated into co-expression analysis. Significant co-expression patterns were used to construct the bone metastasis-specific regulation network. Finally, spatial single-cell RNA-seq and chromatin immunoprecipitation sequence (ChIP-seq) data and multi-omics databases were applied to validate the key scientific hypothesis in the regulation network. Additionally, Connectivity Map (CMap) was utilized to select the potential inhibitors of bone metastasis-specific regulation network in BRCA.ResultsBased on edgeR and WGCNA method, 43 PSRSs were identified. In the bone metastasis-specific regulation network, MAF positively regulated CD248 (R = 0.435, P < 0.001), and hallmark apical junction was the potential pathway of CD248 (R = 0.353, P < 0.001). This regulatory pattern was supported by spatial single-cell RNA sequence, ChIP-seq data and multi-omics online databases. Additionally, alexidine was identified as the possible inhibitor for bone metastasis of BRCA by CMap analysis.ConclusionPSRSs played important roles in bone metastasis of BRCA, and the prognostic model based on PSRSs showed good performance. Especially, we proposed that CD248 was the most significant PSRS, which was positively regulated by MAF, influenced bone metastasis via apical junction pathway. And this axis might be inhibited by alexidine, which providing a potential treatment strategy for bone metastasis of BRCA.

Implications of Stemness Features in 1059 Hepatocellular Carcinoma Patients from Five Cohorts: Prognosis, Treatment Response, and Identification of Potential Compounds

“…Compared with these studies, the OCLR machine learning algorithm was derived from a more comprehensive gene set and tissue origins [23]. Due to the fact of its flexibility and versatility, the OCLR machine learning algorithm has been used to investigate cancer stemness and relevant gene signatures in various tumor types including prostate cancer glioblastoma, breast cancer, and esophageal cancer [25,26,57,58].…”

The osteoblast in regulation of tumor cell dormancy and bone metastasis

“…Development of advanced techniques, including scRNA sequencing and bioinformatic tools are greatly expanding our knowledge on the bone metastatic environment. A bioinformatic approach was used to identify prognostic stemness-related signatures (PSRSs) and to study the “bone metastasis-specific regulation network” of invasive breast carcinomas [58] . The authors used clinical data and RNA sequencing data of human primary breast cancer samples with and without diagnosed bone metastasis from the Cancer Genome Atlas (TCGA) and identified differential expressed genes (DEG) using the edgeR method.…”

“…mRNA stemness index (mRNAsi) was determined with regression, DEGs identified with weighted gene co-expression network analysis. It was proposed that CD248 (endosialin) is positively regulated by MAF protein resulting in the upregulation of the apical junction pathway as the bone metastasis-specific regulation network as trifluoperazine as the possible inhibitor of this network identified using Connectivity Map [58] . These findings of the regulation network were confirmed with spatial scRNA sequencing, ChIP-Seq and multi-omics.…”

Endosialin in Cancer: Expression Patterns, Mechanistic Insights, and Therapeutic Approaches

“…In colon cancer, Park et al found that endosialin could regulate cell migration and drug resistance; overexpression of endosialin could promote cell migration, while downregulation of endosialin resulted in increased cell apoptosis in chemotherapy-resistant cells 46 . In breast cancer, Huang et al constructed a bone metastasis-specific regulatory network based on prognostic stemness-related signatures (PSRSs), their upstream transcription factors (TFs) and downstream pathways and found that MAF may positively regulate endosialin expression and that endosialin may influence breast cancer bone metastasis via the apical junction pathway 47 .…”