Data · dataset · 2022
Identification of FPR3 as a Unique Biomarker for Targeted Therapy in the Immune Microenvironment of Breast Cancer
Listed in ScienceDB
Although research into immunotherapy is growing, its use in the treatment of breast cancer remains limited.
Description
Thus, identification and evaluation of prognostic biomarkers of tissue microenvironments will reveal new immune-based therapeutic strategies for breast cancer. Using an in silico bioinformatic approach, we investigated the tumor microenvironmental and genetic factors related to breast cancer.
We calculated the Immune score, Stromal score, Estimate score, Tumor purity, TMB (Tumor mutation burden), and MATH (Mutant-allele tumor heterogeneity) of Breast cancer patients from the Cancer Genome Atlas (TCGA) using the ESTIMATE algorithm and Maftools. Significant correlations between Immune/Stromal scores with breast cancer subtypes and tumor stages were established. Importantly, we found that the Immune score, but not the Stromal score, was significantly related to the patient's prognosis.
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Weighted correlation network analysis (WGCNA) identified a pattern of gene function associated with Immune score, and that almost all of these genes (388 genes) are significantly upregulated in the higher Immune score group. Protein-protein interaction (PPI) network analysis revealed the enrichment of immune checkpoint genes, predicting a good prognosis for breast cancer. Among all the upregulated genes, FPR3, a G protein-coupled receptor essential for neutrophil activation, is the sole factor that predicts poor prognosis.
Gene set enrichment analysis analysis showed FRP3 upregulation synergizes with the activation of many pathways involved in carcinogenesis. In summary, this study identified FPR3 as a key immune-related biomarker predicting a poor prognosis for breast cancer, revealing it as a promising intervention target for immunotherapy.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.05920 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Cancer 75% · Oncology and carcinogenesis 74%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.05920 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:3211 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |