ResMarkerDB: a database of biomarkers of response to antibody therapy in breast and colorectal cancer

Abstract

The clinical efficacy of therapeutic monoclonal antibodies for breast and colorectal cancer has greatly contributed to the improvement of patients’ outcomes by individualizing their treatments according to their genomic background. However, primary or acquired resistance to treatment reduces its efficacy. In this context, the identification of biomarkers predictive of drug response would support research and development of new alternative treatments. Biomarkers play a major role in the genomic revolution, supporting disease diagnosis and treatment decision-making. Currently, several molecular biomarkers of treatment response for breast and colorectal cancer have been described. However, information on these biomarkers is scattered across several resources, and needs to be identified, collected and properly integrated to be fully exploited to inform monitoring of drug response in patients. Therefore, there is a need of resources that offer biomarker data in a harmonized manner to the user to support the identification of actionable biomarkers of response to treatment in cancer. ResMarkerDB was developed as a comprehensive resource of biomarkers of drug response in colorectal and breast cancer. It integrates data of biomarkers of drug response from existing repositories, and new data extracted and curated from the literature (referred as ResCur). ResMarkerDB currently features 266 biomarkers of diverse nature. Twenty-five percent of these biomarkers are exclusive of ResMarkerDB. Furthermore, ResMarkerDB is one of the few resources offering non-coding DNA data in response to drug treatment. The database contains more than 500 biomarker-drug-tumour associations, covering more than 100 genes. ResMarkerDB provides a web interface to facilitate the exploration of the current knowledge of biomarkers of response in breast and colorectal cancer. It aims to enhance translational research efforts in identifying actionable biomarkers of drug response in cancer.

GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas

“…We compared GlioMarker with other specialized, open-access molecular biomarker databases, including The Tuberculosis Biomarker Database ( 11 ), LiverCancerMarkerRIF ( 12 ), CBD ( 15 ), CancerLivER ( 13 ), ExoBCD ( 14 ), the Urinary Protein Biomarker Database (UPBD) ( 60 ), and the Therapeutic Response Biomarker Database (ResMarkerDB) ( 61 ), and the strengths of GlioMarker are summarized below.…”

MarkerDB: an online database of molecular biomarkers

“…As a result, unlike with chemical biomarkers, no attempt was made to independently calculate or regenerate protein biomarker data from ‘partial’ or incomplete protein biomarker data in published papers. All of the protein biomarker data in MarkerDB was extracted from the primary literature with sources such as OncoMX ( 5 ), CBD ( 6 ), and UPBD ( 7 ) providing useful reference leads. The annotation of protein biomarkers was done manually and facilitated by an in-house protein annotation tool called BioSummarizer ( 12 ).…”

“…and information content (no data on biomarker cut-off values, sensitivity, specificity, receiver-operating characteristic [ROC] curves, disease/condition descriptions, etc.). In addition to these commercial tools, there are a small number of very specialized, open-access molecular biomarker databases such as OncoMX ( 4 ), which specializes in cancer biomarkers, the colorectal cancer biomarker database or CBD ( 5 ), which focuses on colorectal cancer biomarkers, ResMarkerDB ( 6 ), which specializes in therapeutic response biomarkers and the urinary protein biomarker database or UPBD ( 7 ), which is limited to urinary protein biomarkers. Most of the biomarkers described in these databases are very specific (protein only, gene only), limited to investigational or pre-clinical biomarkers and provide relatively little information about the molecular marker itself or the specific condition/disease associated with those biomarkers.…”

BIONDA: a free database for a fast information on published biomarkers

“…However, most biomarker databases are not generally applicable. For example, the disease-specific OncoMX ( Dingerdissen et al , 2020 ), CIViCmine ( Lever et al , 2019 ) and ResMarkerDB ( Pérez-Granado et al , 2019 ) for cancer and the biomarker-specific OMIM ( Amberger et al , 2019 ; genes and genetic disorders) provide no general view on biomarkers and diseases. Some databases like GOBIOM ( https://gobiomdbplus.com , 11 July 2021, date last accessed) are not free and/or require a registration.…”