Abstract 5514
Background
Colorectal Cancer (CRC) is the second leading cause of cancer mortality worldwide. An effective and convenient blood test for early detection of CRC is urgently needed to increase screening compliance and reduce mortality. The development of a new blood test for early CRC detection was initiated that leverage the transcriptome analysis of circulating immune cells (ImmunoTranscriptomics) using artificial intelligence and machine learning tools.
Methods
To identify new transcriptional biomarkers for CRC and adenoma detections, peripheral blood mononuclear cells (PBMC) transcriptome were analyzed by RNA-sequencing of 561 subjects (300 Caucasians and 261 Asians) enrolled in the DGNP-COL-0310 study (Ciarloni et al., 2016), a multi-centers case-control study. The cohort included 189 subjects with CRC, 115 with advanced adenoma (AA), 39 with other types of cancer (OC) as well as 218 individuals without any colorectal lesions (CON). Several univariate and multivariate methods were applied to the discovery set (n = 282) and results were integrated into a ranking system. Top ranked genes were selected for further validation and algorithm development in an independent set (n = 279).
Results
A large panel of differentially expressed genes were identified in non-metastatic CRC (I-II-III) and AA compared to CON and OC with significantly high power of discrimination (P-value = 10-13). The novel developed data analytics pipeline was used to analyse the transcriptomic data measurements and the diagnostic accuracy of the new gene signature for CRC, through application of Machine Learning (ML) and bootstrap, was 82% sensitivity and 88% specificity and AUC of 90%. The signature was enriched in genes associated with myeloid cells activation, inflammation and hemostasis, suggesting a key role of the innate immunity in the early response to cancer.
Conclusions
Mapping the reaction of the immune system to onset of cancer and disease identification through application ML methods is a new approach to ensure an unbiased, genome-wide, unsupervised gene expression analysis for a highly specific biomarker identification.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Novigenix SA.
Funding
Novigenix SA.
Disclosure
S. Hosseinian Ehrensberger: Shareholder / Stockholder / Stock options: Novigenix SA. L. Ciarloni: Shareholder / Stockholder / Stock options: Novigenix. All other authors have declared no conflicts of interest.
Resources from the same session
4290 - Characterization of the mechanism of action and efficacy of MEN1611 (PA799), a novel PI3K inhibitor, in breast cancer preclinical models.
Presenter: Alessio Fiascarelli
Session: Poster Display session 3
Resources:
Abstract
2167 - Neat-1: culprit lnRNA tying PIG-C, MSLN, CD80 in TNBC
Presenter: Nada Hussein
Session: Poster Display session 3
Resources:
Abstract
1829 - A novel RAF/MEK inhibitor CH5126766 in phase 1 clinical trial has an effectiveness in the combination with eribulin for the treatment of triple negative breast cancer
Presenter: Hisako Ono
Session: Poster Display session 3
Resources:
Abstract
4357 - Identification of a stemness-related gene panel associated with BET inhibition in triple negative breast cancer
Presenter: Eva Galan-Moya
Session: Poster Display session 3
Resources:
Abstract
5163 - Preclinical Evaluation targeting both IGF1R and IR in Triple Negative Breast Cancer
Presenter: Alex Eustace
Session: Poster Display session 3
Resources:
Abstract
832 - Monospecific antibody targeting of CDH11 inhibits epithelial-to-mesenchymal transition and represses cancer stem cell-like phenotype by up-regulating miR-335 in metastatic breast cancer, in vitro and in vivo.
Presenter: Jia-Hong Chen
Session: Poster Display session 3
Resources:
Abstract
3781 - Pharmacological screening with Chk1 inhibitors identify synergistic agents to overcome resistance to platinums in basal breast and ovarian cancer
Presenter: Ana Lucia Sanabria
Session: Poster Display session 3
Resources:
Abstract
3275 - Comparison of 11 circulating miRNAs and CA125 kinetics in ovarian cancer during first line treatment: data from the randomized CHIVA trial (a GINECO-GCIG study)
Presenter: Patrick Robelin
Session: Poster Display session 3
Resources:
Abstract
3391 - Inhibiting Ehmt2 and Ezh2 histone methyltransferases alters the immune microenvironment in a Trp53-/- murine ovarian cancer model
Presenter: Pavlina Spiliopoulou
Session: Poster Display session 3
Resources:
Abstract
3839 - Fenofibrate impairs pro-tumorigenic potential of cancer stem cell-like cells within drug-resistant prostate cancer cell populations.
Presenter: Tomasz Wróbel
Session: Poster Display session 3
Resources:
Abstract