Genomic Symphony: Unraveling Statistical Threads in the Deadliest Cancer Types

Angel Hunter, Andrew Ulton, Luke Argenton

Angel Hunter, Andrew Ulton, Luke Argenton Department of Material Science and Engineering, Oregon State University

Keywords: Genomics, Cancer, Gene Expression, Statistical Analysis, Bioinformatics, Differential Expression, Pathway Enrichment, Network Analysis, Diagnostic Markers, Therapeutic Targets

Abstract

The intricate landscape of genomic alterations in the deadliest cancer types poses a complex puzzle that demands deciphering. This study orchestrates a genomic symphony, unraveling statistical threads woven within the genomic fabric of lethal cancers. Leveraging advanced bioinformatics and statistical analyses, we navigate through vast datasets to elucidate patterns, similarities, and differences in gene expression profiles across various lethal cancers.

Our approach involves comprehensive genomic profiling of high-fatality cancers, including but not limited to lung, pancreatic, liver, and ovarian cancers. By employing cutting-edge statistical methodologies, we identify key genetic signatures associated with malignancy, metastasis, and treatment resistance. The study delves into the intricate interplay of genetic aberrations, seeking patterns that may serve as diagnostic markers or therapeutic targets.

Through a multi-faceted analysis, encompassing differential gene expression, pathway enrichment, and network analyses, we aim to paint a vivid portrait of the genomic landscapes in deadly cancers. This exploration not only enhances our understanding of the molecular underpinnings of malignancy but also holds the potential to reshape diagnostic paradigms and inform targeted therapeutic interventions.