Integrating Data and Unraveling the Tumor Microenvironment: Advancing Personalized Medicine Strategies in Triple-Negative Breast Cancer
Location
Hager-Lubbers Exhibition Hall
Description
PURPOSE: Triple-Negative Breast Cancer (TNBC) poses a significant clinical challenge due to its lack of targeted therapies resulting from the absence of three key receptors. Recognizing the critical need for a deeper understanding of TNBC's molecular heterogeneity, this study aims to elucidate the diverse genetic and molecular mechanisms at play. SUBJECTS: This ongoing study employs a meta-analytic approach to RNA-seq datasets to investigate TNBC. The sample includes TNBC-specific RNA-seq datasets obtained from various repositories, ensuring uniformity and comparability through normalization and re-processing. METHODS AND MATERIALS: The study systematically gathers TNBC-specific RNA-seq datasets and aggregates them into a meta-database. Data normalization and re-processing are performed using Zotero for reference management and MS-Excel for data aggregation. ANALYSES: Short-term objectives include identifying consistent gene expression patterns to pinpoint TNBC biomarkers and therapeutic targets. Long-term goals encompass exploring TNBC's interaction with the Tumor Microenvironment (TME) and constructing a predictive model for disease progression and treatment response. RESULTS: Preliminary analysis reveals the intricate complexity of TNBC's transcriptome. The study plans to expand the database and leverage advanced bioinformatics tools for further research. CONCLUSIONS: This study represents a pivotal step toward comprehending the nuances of TNBC. Through the power of meta-analysis, it aims to establish a foundation for future research, eventually translating into more effective diagnostic and therapeutic tools for TNBC, with the overarching goal of improving patient outcomes in this challenging landscape.
Integrating Data and Unraveling the Tumor Microenvironment: Advancing Personalized Medicine Strategies in Triple-Negative Breast Cancer
Hager-Lubbers Exhibition Hall
PURPOSE: Triple-Negative Breast Cancer (TNBC) poses a significant clinical challenge due to its lack of targeted therapies resulting from the absence of three key receptors. Recognizing the critical need for a deeper understanding of TNBC's molecular heterogeneity, this study aims to elucidate the diverse genetic and molecular mechanisms at play. SUBJECTS: This ongoing study employs a meta-analytic approach to RNA-seq datasets to investigate TNBC. The sample includes TNBC-specific RNA-seq datasets obtained from various repositories, ensuring uniformity and comparability through normalization and re-processing. METHODS AND MATERIALS: The study systematically gathers TNBC-specific RNA-seq datasets and aggregates them into a meta-database. Data normalization and re-processing are performed using Zotero for reference management and MS-Excel for data aggregation. ANALYSES: Short-term objectives include identifying consistent gene expression patterns to pinpoint TNBC biomarkers and therapeutic targets. Long-term goals encompass exploring TNBC's interaction with the Tumor Microenvironment (TME) and constructing a predictive model for disease progression and treatment response. RESULTS: Preliminary analysis reveals the intricate complexity of TNBC's transcriptome. The study plans to expand the database and leverage advanced bioinformatics tools for further research. CONCLUSIONS: This study represents a pivotal step toward comprehending the nuances of TNBC. Through the power of meta-analysis, it aims to establish a foundation for future research, eventually translating into more effective diagnostic and therapeutic tools for TNBC, with the overarching goal of improving patient outcomes in this challenging landscape.