Neha Anurag, Ridge Point High School
Breast cancer (BC) is globally the most diagnosed cancer, with 1 in 8 women facing a BC diagnosis in the United States. However, detecting tumors smaller than 1 mm remains a significant challenge in BC diagnosis. Liquid biopsies, which involve the non-invasive detection of circulating tumor-derived materials (such as DNA, RNA, protein, etc.) in biofluids like blood, have emerged as an innovative tool for cancer diagnosis and prognosis. They offer the potential to overcome identification limitations by exploring tumor predictors in the bloodstream of BC patients. I hypothesize that the liquid biopsy-based tumor-specific gene signature represents a promising non-invasive tool for early breast cancer diagnosis, treatment, and management. This study utilizes bioinformatics analysis on a dataset from the Gene Expression Omnibus with 57 BC patients and 31 healthy controls. Employing the Waikato Environment for Knowledge Analysis platform, the top circulating genes predicting BC diagnosis were identified. Thirteen genes-ACTR2, MYST2, SRRM1, ENC1, CLIC4, APPBP2,SIAH1, PTPN11, TNFRSF1A, RPL15, VAPA, EAF1, and PPP1R15A-significantly contributed to diagnostic prediction with an impressive 86% accuracy, coupled with a sensitivity and specificity of 0.86 and 0.87, respectively. Additionally, bioinformatics analysis revealed critical biological pathways that are linked to these diagnostic gene signatures. These findings not only pave the way for a non-invasive, cost-effective diagnostic tool for detecting breast tumors but also hold promise in identifying individuals at risk of BC. Early detection through liquid biopsy-based methods could lead to timely treatment, potentially improving BC survival rates.