Abstract Library

#4487 Fast pancreatic cancer diagnosis using lightweight Mamba framework

Introduction: Pancreatic cancer is a deadly malignancy often diagnosed too late for effective treatment. Fast and precise identification of pathological regions in histopathology images is essential but limited by current slow methods. We present a framework to accelerate this process and enhance diagnostic support.

Conference:

Presenting Author:

Authors: Shengzhe Y, Yan K,

Keywords: Pancreatic Cancer, Lightweight Mamba Architecture, Pathology Region Classification and Recognition,

#4462 Clustering of gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) using machine learning (ML) and comparison with tumour, node, metastasis (TNM) staging: A population-based study using surveillance, epidemiology, and end results (SEER)

Introduction: TNM 8 is the staging system for GEP-NEN, guiding prognosis and treatment. However, it does not include important prognostic factors such as age, sex, race, and morphology.

Conference:

Presenting Author: Mortagy M

Authors: Mortagy M, El Asmar M, White B, Chandrakumaran K, Ramage J,

Keywords: Clustering, Machine learning, GEP-NEN, TNM Staging, Survival Analysis, SEER,

#4068 YAP-1 as prognostic marker for immunochemotherapy response in SCLC patients

Introduction: Small-cell lung cancer (SCLC) represents about 15% of all lung cancers and is an exceptionally lethal malignancy for which more effective therapies are urgently needed. Previous studies have classified SCLC patients by RNA-sequencing (RNA-seq) clustering analysis to identify who could benefit from immune checkpoint blockades.

Conference:

Presenting Author:

Authors: Sabella G,

Keywords: neuroendocrine, immunochemotherapy, SCLC, YAP-1,

#3576 Patterns of family history of cancer and associated risk of developing neuroendocrine tumors: A cross-sectional study

Introduction: Except for known hereditary syndromes (mostly, multiple endocrine neoplasia type I and von Hippel Lindau), familial clustering of cancers in patients (pts) with neuroendocrine neoplasms (NEN) is scarcely reported.

Conference:

Presenting Author: Viapiana P

Authors: Viapiana P, Dias C, Cruz Formiga M, Simões Riechelmann R,

Keywords: neuroendocrine tumor, family history,

#3430 Comprehensive transcriptomic and methylomic analysis of NENs from multiple origins show subgroups of patients with clinical relevance

Introduction: Neuroendocrine neoplasms (NENs) are a heterogeneous group of tumors with a wide anatomical distribution that share common neuro and endocrine properties. Although some studies have assessed the NET molecular landscape of certain primary sites, none of them have evaluated cross-sites molecular studies.

Conference:

Presenting Author: Carretero C

Authors: Carretero C, Soldevilla B, Gil B, La Salvia A, Lens-Pardo A,

Keywords: neuroendocrine tumor, multiomics, subtypes,