VolitionRx Limited · AMEX:VNRX
VolitionRx — ESMO 2023
9 slides from VolitionRx's conference presentation, Oct 22, 2023
Slide 1: Differentiation of Malignant and Benign Lung Nodules using Epigenetically Modified Nucleosomes in Plasma
Differentiation of Malignant and Benign Lung Nodules using Epigenetically Modified Nucleosomes in Plasma Pei-Hsing Chen, MD National Taiwan University Hospital, Taiwan October 22nd, 2023
Slide 2: Declaration of Interests
DECLARATION OF INTERESTS Pei-Hsing Chen This research was conducted in collaboration with Belgian Volition SRL. The results presented here were partially funded by a research grant from Belgian Volition SRL. Pei-Hsing Chen, MD Content of this presentation is copyright and responsibility of the autho
Slide 3: Introduction
Introduction - In Taiwan, the initiation of the LDCT screening program led to an increase in the detection of nodules. - An unmet clinical need for accurate noninvasive tests to differentiate between malignant and benign nodules following LDCT screening. - Novel blood-based tests could provide a str
Slide 4: Epigenetic biomarkers: a valuable tool from target identification to validation in clinical studies
Epigenetic biomarkers: a valuable tool from target identification to validation in clinical studies Measuring and monitoring nucleosome levels and modifications in circulating blood has the potential to aid diagnosis, prognosis and monitoring of lung cancer Levels of circulating nucleosome were eval
Slide 5: Study Design
Study Design Pathology confirmed (94.4 %) or lesion disappeared in the follow-up image. Benign nodule Cancer / Pre-cancer (BN, n=158) (LA, n=648) K2-EDTA Plasma samples Circulating Nucleosomes and their histone modifications (Nu.Q® immunoassay, Volition SRL). Pei-Hsing Chen, MD Content of this prese
Slide 6: Statistical model for differentiation
Statistical model for differentiation Logistic regression model for simple algorithm Based on histone modifications, Including H3K27Me3/H3K36Me3 and the H3.1 histone isoform 561 (70%) training / 245 (30%) validation 100 100 80 91.5% Sensitivity 81.9% Specificity 80 Sensitivity% Sensitivity% 60 60 60
Slide 7: Combined model from training set: subgroup analysis
Combined model from training set : subgroup analysis • Component Performance is superior in part-solid and non-solid lesions • Size Performance was maintained with a cutoff of 3 cm, but diminished with a cutoff of 1 cm, though it remained Sensitivity at 80% Specificity satisfactory for differentiati
Slide 8: Conclusions
Conclusions • Epigenetic features of nucleosomes in blood plasma offer potential for identifying cancer/pre-cancer, potentially reducing the false-positive rates of LDCT. • Epigenetic features of nucleosomes allow for precise differentiation between cancer/pre-cancer and benign nodules using a combi
Slide 9: Acknowledgment
Acknowledgment Research Team Members and Co-authors Tung-Ming Tsai, Dorian Pamart, Tom Bygott, Marielle Herzog, Jake Micallef, Jin-Shing Chen Pei-Hsing Chen b96401034@ntu.edu.tw