Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display session 3

5517 - Molecular fingerprinting in breast cancer (BC) screening using Quantum Optics (QO) technology combined with an artificial intelligence (AI) approach applying the concept of “molecular profiles at n variables (MPnV)”: a prospective pilot study.

Date

30 Sep 2019

Session

Poster Display session 3

Topics

Translational Research

Tumour Site

Breast Cancer

Presenters

Jean-Marc Nabholtz

Citation

Annals of Oncology (2019) 30 (suppl_5): v574-v584. 10.1093/annonc/mdz257

Authors

J.A. Nabholtz1, K.A. Alsaleh2, S. Kullab3, N. Abdel-Aziz4, A. Abdelwarith3, A. Al Diab3, M.A. Hilal3, F. Dabouz5, V. Bajic6, R. Incitti6, M.R.K. Bahadoor5, A.M. Azeer7

Author affiliations

  • 1 Oncology Center, King Saud University Medical City, 11411 - Riyadh/SA
  • 2 Oncology Center, King Saud University Medical City, 11472 - Riyadh/SA
  • 3 Oncology Center, King Saud University Medical City, Riyadh/SA
  • 4 Oncology Center, King Saud University Medical City, 94970 - Riyadh/SA
  • 5 Clinical Operations, International Cancer Research Group, ICRG, Sharjah/AE
  • 6 Cbrc, Computational Bioscience Research Centre, King Abdallah University for Science and Technology (KAUST), Thuwal/SA
  • 7 Physics & Astronomy Department / Attosecond Science Laboratory, King Saud University, Riyadh/SA

Resources

Login to access the resources on OncologyPRO.

If you do not have an ESMO account, please create one for free.

Abstract 5517

Background

BC screening by mammography is associated with a significant reduction in mortality (19 % overall reduction of the relative risk), however with significant limitations and debatable cost-effectiveness. Screening individuals for cancer using liquid biopsies (LB) represents an unmet need. We report the first prospective “proof of concept” study using the QO technology combined with an AI approach using the concept of “MPnV” applied to BC detection.

Methods

QO (femto/atto-second infrared laser spectroscopy) on LB is a simple, non-invasive and reproducible method allowing to identify individualized molecular spectra (MS). These highly detailed MS can be correlated to physiological or pathological changes allowing detection and translation of differences. Integrated into a super-computational approach using a non-hierarchical deep data mining strategy (MPnV concept), MS could discriminate individuals with and without BC. The plasma of 68 controls and 27 BC patients, accrued at the King Saud University BC screening program, Riyadh, Saudi Arabia (KSA), were studied by QO (Max Planck Institute of Quantum Optics /Ludwig Maximillian University Munich, Garching, Germany). The MS were analysed on the Shaheen II supercomputer at King Abdallah University for Science and Technology (KAUST), KSA, in order to generate comparative algorithms.

Results

The use of special feature selection, followed by class analysis allowed to differentiate profiles between the two groups with a sensitivity of 97% and a specificity of 72% (variables n = 1,100). A more in-depth analysis led to 99% sensitivity, but with a lower specificity of 64%. Further analysis of the series, using an age-matched approach led to 97% sensitivity with 98% specificity in differentiating women with or without BC.

Conclusions

These results warrant a large scale prospective validation BC screening trial (ongoing) and “proof of concept trials” in other frequent cancers, in particular those without existing screening programs.

Clinical trial identification

Editorial acknowledgement

Prof. Ferenc Krausz, Director, and Dr. Mihaela Zigman, Leader of the Broadband Infrared Diagnostics, Max Planck Institute of Quantum Optics (MPQ), Faculty of Physics at Ludwig-Maximilians Universität München (LMU), Garching, Germany.

Legal entity responsible for the study

Jean Marc Nabholtz, Oncology Centre, King Saud University, Riyadh, Saudi Arabia.

Funding

1. Oncology Centre, King Saud University Medical City, King Saud University, Saudi Arabia. 2. Max-Planck-Institut für Quantenoptik and Faculty of Physics at Ludwig-Maximilians Universität München, Garching, Germany. 3. Computational Bioscience Research Centre, King Abdallah University for Science and Technology (KAUST), Thuwal, Saudi Arabia.

Disclosure

M.R.K. Bahadoor: Travel / Accommodation / Expenses, ASCO Participation Funded: Pfizer; Advisory / Consultancy, Pancreas Expert Opinion Advisory: Baxter. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.