Neuroendocrine Neoplasm DNA Methylation Biomarker Study

Overview:

This project utilizes Jupyter Notebook for data visualization and analysis in support of research on lung neuroendocrine neoplasms (NENs), conducted under the supervision of Dr Hayan Lee at Fox Chase Cancer Center.

Summary:

Neuroendocrine neoplasms (NENs) are tumors that originate from neuroendocrine cells, which posses characteristics of both nerve and endocrine cells.There are two major challanges in NEN diagnosis: initial detection and subtype classification. NEN subtypes range between low-grade, well-differentiated neuroendocrine tumors (NETs) and high-grade, poorly differentiated neuroendocrine carcinomas (NECs) knowing the subtype is critical for effective patient treatment, but it is often difficult to achieve using histopathologically.

This research addresses that diagnostic gap by applying DNA methylation profiling to lung NEN samples. As an epigenetic marker, DNA methylation captures underlying tumor biology and shows promise as a reliable biomarker for tumor classification.

By integrating methylation data with machine learning models, the goal is to develop a cost effective and clinically applicable tool to improve the identification and classification of NENs and their subtypes.

Eric Eleam, Computer Science, Temple University

Lee Lab, Fox Chase Cancer Center