Abstract 5820
Background
DNA sequencing to identify variants is becoming increasingly valuable in clinical settings; including matching patients to approved targeted therapies, immunotherapies, and/or clinical trials. However, accurate calling of genetic variants from sequencing still remains challenging. With little corroboration between the different tools available, patients are at risk of being treated with therapies that are unsuitable for their cancer.
Methods
Here we present a novel machine learning based method for the accurate identification of somatic variants in cancer patient tumour samples, with a neural network architecture from encoded raw sequencing read information of tumour/normal sample pairings into an image, enabling it to classify whether a variant is germline, somatic, or sequencing error. The model was trained and tested on in-silico spike-in data using bam-surgeon, and then validated on a multi-cancer and multi-center dataset and benchmarked against industry standard variant callers.
Results
The approach, called somaticNET, outperforms existing industry standard tools in sensitivity and specificity, achieving an AUROC of ∼1.00 on the bam-surgeon dataset and an AUROC of ∼0.99 on the multi-cancer multicenter dataset. The model also works faster than other variant callers, in minutes compared to hours.
Conclusions
Using the power of machine learning for accurate somatic variant calling can improve patient matching to approved therapies and clinical trials, thus ensuring patients are given the right therapy at the right time to treat their cancer.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Cambridge Cancer Genomics.
Disclosure
G. Dubourg-Felonneau: Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics. D. Rebergen: Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics. C. Parsons: Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics. H. Thompson: Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics. J.W. Cassidy: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment, Officer / Board of Directors: Cambridge Cancer Genomics. N. Patel: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics. H.W. Clifford: Leadership role, Shareholder / Stockholder / Stock options, Full / Part-time employment: Cambridge Cancer Genomics.
Resources from the same session
5389 - Two-weekly accelerated BEP (aBEP) regimen as induction chemotherapy (CT) in intermediate and poor prognosis patients (pts) with nonseminomatous germ cell tumors (NSGCT): final results of phase II trial.
Presenter: Alexey Tryakin
Session: Poster Display session 3
Resources:
Abstract
2934 - Differential expression of circulating miR375 and miR371 to detect teratoma and viable germ cell malignancy
Presenter: Lucia Nappi
Session: Poster Display session 3
Resources:
Abstract
3585 - Prognosis of anaemia in disseminated testicular germ cell tumours. On behalf of the Spanish Germ Cell Cancer Group (SGCCG)
Presenter: Esmeralda Garcia Torralba
Session: Poster Display session 3
Resources:
Abstract
2254 - The Effects Of Primary Testicular Tumor Localization On Prognosis In Patients With Nonseminomatous Testis Cancer
Presenter: Birol Yildiz
Session: Poster Display session 3
Resources:
Abstract
4505 - Initial Results of a Phase II study of Nivolumab and Ipilimumab in Metastatic Adrenal Tumors.
Presenter: Matthew Campbell
Session: Poster Display session 3
Resources:
Abstract
3369 - NEMIO: a randomized phase II trial evaluating efficacy and safety of dose dense MVAC (ddMVAC) + durvalumab +/- tremelimumab as neoadjuvant treatment in patients with bladder muscle-invasive urothelial carcinoma
Presenter: Constance Thibault
Session: Poster Display session 3
Resources:
Abstract
2075 - KEYNOTE-866: Phase 3 Study of Perioperative Pembrolizumab (pembro) or Placebo (pbo) in Combination With Neoadjuvant Chemotherapy in Cisplatin (cis)-Eligible Patients (pts) With Muscle-Invasive Bladder Cancer (MIBC)
Presenter: Arlene Siefker-Radtke
Session: Poster Display session 3
Resources:
Abstract
4824 - KEYNOTE-905: A Phase 3 Study of Cystectomy Plus Perioperative Pembrolizumab Versus Cystectomy Alone in Cisplatin (cis)-Ineligible Patients (pts) With Muscle-Invasive Bladder Cancer (MIBC)
Presenter: Matthew Galsky
Session: Poster Display session 3
Resources:
Abstract
2253 - Phase 3 LEAP-011 trial: First-Line Pembrolizumab With Lenvatinib in Patients With Advanced Urothelial Carcinoma Ineligible to Receive Platinum-Based Chemotherapy
Presenter: Yohann Loriot
Session: Poster Display session 3
Resources:
Abstract
4310 - PULSE : A Single Arm Trial Assessing The Activity and Safety of Avelumab Immunotherapy Maintenance among Patients With Locally Advanced or Metastatic Squamous Cell Penile Carcinoma (mSCPC).
Presenter: Noemie Gassian
Session: Poster Display session 3
Resources:
Abstract