In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 16_Supplement ( 2020-08-15), p. 848-848
Abstract:
The developments in the field of genetic screening make high throughput sequencing of patient samples not only technically, but also financially feasible. However, this confronts physicians with a vast amount of information for one patient. Additionally, as more research is done on single variants, the knowledge about predictive biomarkers is also extensive and increasing steadily. To make information like the clinical relevance of single variants available to physicians, multiple databases are available. This adds to the enormous load of data physicians in a molecular Tumor Board (MTB) have to review on top of clinical data to find a suitable therapy for a specific patient. To support a MTB in making informed therapy decisions based on genomic data, relevant clinical data like the diagnosis and previous therapies is extracted from the electronic health record used by the physicians to document the patients and their course of disease. After sequencing, the variants get pre-filtered by bioinformaticians and their characteristic features like the specific amino acid exchange for SNVs or total copy number for CNVs are presented. With these data, knowledge bases are queried in the background and relevant information is displayed in the Knowledge Connector. For each variant, information about effect of the mutation on the protein, an assessment of oncogeneity, drugs targeting the specific variation or the gene and pathways the gene is involved in, are summarized in one view to grasp all important facts at a glance. Furthermore, the tool offers the opportunity to manually assess the variants according to evidences and automatically generates a report upon this curation, which can be sent to treating physicians. With this, physicians are supported in managing the huge amount of information referring to one patient in the whole process of a MTB. Additionally, the number of patients benefiting from this comprehensive analysis of specific characteristics can be increased by not only saving time of experienced specialists, but also by enabling physicians with less extensive knowledge about genetics to find therapies based on genetic variants. Citation Format: Katrin Glocker, Alexander Knurr, Janine Al-Hmad, Dennis-Immanuel Czogalla, Marvin Izzo, Christian Koch, Benjamin Roth, Frank Ückert. Taming numerous information on variants for better treatment decisions [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 848.
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2020-848
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2020
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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