{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n CT47A2 is a member of the cancer/testis (CT) gene family, a group of genes normally expressed only in germ cells but aberrantly activated in a variety of cancers. Its expression in malignancies such as estrogen receptor–negative breast lesions, including ductal carcinoma in situ, has been associated with high‐risk pathological features and a pronounced stromal immune response, suggesting that CT47A2 may contribute to tumor immunogenicity and serve as an attractive target for immunotherapy approaches."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": " In the context of prostate cancer, where comprehensive antigen profiling is emerging for diagnostic and therapeutic biomarker discovery, CT47A2 and other CT antigens are being studied for their potential to distinguish malignant from benign prostate conditions and to inform ethnic group–specific molecular signatures."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": " In addition, large-scale transcriptome catalogs such as the CHESS database have expanded our understanding of the human transcriptional landscape by including novel protein-coding genes and previously unrecognized transcripts, highlighting the complex regulation and potential functional significance of CT antigens like CT47A2."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "3"}]}, {"type": "t", "text": " Finally, integrative genomic profiling combined with machine learning approaches in breast cancer survivors has identified potential biomarkers that may predict treatment outcomes and survivability, further underscoring the role of CT antigens in personalized oncology."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "4"}]}, {"type": "t", "text": "\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Otavia L Caballero, Sami Shousha, Qi Zhao, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Expression of Cancer/Testis genes in ductal carcinoma in situ and benign lesions of the breast."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Oncoscience (2013)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.18632/oncoscience.4"}], "href": "https://doi.org/10.18632/oncoscience.4"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "25593980"}], "href": "https://pubmed.ncbi.nlm.nih.gov/25593980"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Henry A Adeola, Muneerah Smith, Lisa Kaestner, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Oncotarget (2016)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.18632/oncotarget.7359"}], "href": "https://doi.org/10.18632/oncotarget.7359"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "26885621"}], "href": "https://pubmed.ncbi.nlm.nih.gov/26885621"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "Mihaela Pertea, Alaina Shumate, Geo Pertea, et al. "}, {"type": "b", "children": [{"type": "t", "text": "CHESS: a new human gene catalog curated from thousands of large-scale RNA sequencing experiments reveals extensive transcriptional noise."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Genome Biol (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s13059-018-1590-2"}], "href": "https://doi.org/10.1186/s13059-018-1590-2"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30486838"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30486838"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Ashraf Abou Tabl, Abedalrhman Alkhateeb, Waguih ElMaraghy, et al. "}, {"type": "b", "children": [{"type": "t", "text": "A Machine Learning Approach for Identifying Gene Biomarkers Guiding the Treatment of Breast Cancer."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Front Genet (2019)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.3389/fgene.2019.00256"}], "href": "https://doi.org/10.3389/fgene.2019.00256"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30972106"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30972106"}]}]}]}