= 24.19, (F.E. 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 Glucagon (19-29), human 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. Introduction The heterogeneity of cancer at different levels, namely genetic, proteomic, morphological and even at the tumour microenvironment, poses challenges to its diagnosis and treatment (1). The development of therapeutic monoclonal antibodies (mAbs) for cancer treatment has improved patients outcomes by tailoring their treatments according to their genomic background (2). Currently, there are seven Food and Drug Administration (FDA)-approved mAbs for the treatment of breast and colorectal cancer, which are among the most commonly occurring cancer in women and men, respectively (3). While all the mAbs used Glucagon (19-29), human for breast cancer treatment (trastuzumab, pertuzumab and trastuzumab emtansine) target HER2, the mAbs currently used for colorectal cancer treatment target Epidermal Growth Factor Receptor (EGFR) (cetuximab, panitumumab) or Vascular Endothelial Growth Factor (VEGF) (bevacizumab and ramucirumab). Nonetheless, primary or acquired resistance is frequently observed for targeted therapies (4, 5). So far, the molecular mechanisms of resistance to anti-HER2 mAbs have not been identified yet. Thus, candidate patients are selected according to amplification or over-expression of HER2. Regarding colorectal cancer, the anti-EGFR antibodies cetuximab and panitumumab are used to treat RAS wild-type colorectal malignancy, but their effectiveness is limited due to the emergence of acquired drug resistance. Consequently, the availability of prognostic biomarkers of treatment response would promote a better management of individuals by means of more tailored treatments according to their needs (6). Although several databases contain info on genomic alterations Glucagon (19-29), human in malignancy, there is a lack of resources specifically focused on biomarkers of treatment response. Moreover, the data on biomarkers is not constantly organized, differs in the granularity of the information offered and is annotated with different terminologies. All these issues hinder the recognition and prioritization of biomarkers to improve treatment of individuals. To address these difficulties, we have developed ResMarkerDB like a centralized repository that Glucagon (19-29), human harmonizes data of biomarkers of response to FDA-approved mAbs for breast and colorectal malignancy. To this end, we have integrated data from four publicly available repositories with info extracted from your literature by text mining followed by expert curation. Biomarker info in ResMarkerDB can be browsed according to the level of evidence assisting it (e.g. preclinical versus medical studies) to aid in the prioritization of biomarkers of response to restorative mAbs. In addition, all the information is provided with their provenance (e.g. unique source of the data). ResMarkerDB seeks to promote the recognition of existing and fresh actionable biomarkers of drug response in breast and colorectal malignancy by making this knowledge accessible to both fundamental researchers and medical practitioners. This source is publicly available at http://www.resmarkerdb.org under the Creative Commons 4.0 license. Implementation.In addition, all the information is provided with their provenance (e.g. in malignancy. ResMarkerDB was developed as a comprehensive source of biomarkers of drug response in colorectal and breast tumor. It integrates data of biomarkers of drug response from existing repositories, and fresh data extracted and curated from your literature (referred as ResCur). ResMarkerDB currently features 266 biomarkers of varied nature. Twenty-five percent of these biomarkers are special of ResMarkerDB. Furthermore, ResMarkerDB is one of the few resources offering non-coding DNA data in response to drug treatment. The database consists of 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 malignancy. It aims to enhance translational research attempts in identifying actionable biomarkers of drug response in malignancy. Intro The heterogeneity of malignancy at different levels, namely genetic, proteomic, morphological and even in the tumour microenvironment, poses difficulties to its analysis and treatment (1). The development of restorative monoclonal antibodies (mAbs) for malignancy treatment offers improved patients results by tailoring their treatments according to their genomic background (2). Currently, you will find seven Food and Drug Administration (FDA)-authorized mAbs for the treatment of breast and colorectal malignancy, which are among the most generally happening cancer in men and women, respectively (3). While all the mAbs utilized for breast tumor treatment (trastuzumab, pertuzumab and trastuzumab emtansine) target HER2, the mAbs currently utilized for colorectal malignancy treatment target Epidermal Growth Element Receptor (EGFR) (cetuximab, panitumumab) or Vascular Endothelial Growth Element (VEGF) (bevacizumab and ramucirumab). Nonetheless, primary or acquired resistance is frequently observed for targeted therapies (4, 5). So far, the molecular mechanisms of resistance to anti-HER2 mAbs have not Glucagon (19-29), human been identified yet. Thus, candidate individuals are selected relating to amplification or over-expression of HER2. Concerning colorectal malignancy, the anti-EGFR antibodies cetuximab and panitumumab are used to treat RAS wild-type colorectal malignancy, but their effectiveness is limited due to the emergence of acquired drug resistance. Consequently, the availability of prognostic biomarkers of treatment response would promote a better management of individuals by means of more tailored treatments according to their needs (6). Although several databases contain info on genomic alterations in malignancy, there is a lack of resources specifically focused on biomarkers of treatment response. Moreover, the data on biomarkers is not always organized, differs in the granularity of the information provided and is annotated with different terminologies. All these issues hinder the recognition and prioritization of biomarkers to improve treatment of individuals. To address these challenges, we have developed ResMarkerDB like a centralized repository that harmonizes TCL1B data of biomarkers of response to FDA-approved mAbs for breast and colorectal malignancy. To this end, we have integrated data from four publicly available repositories with info extracted from your literature by text mining followed by expert curation. Biomarker info in ResMarkerDB can be browsed according to the level of evidence assisting it (e.g. preclinical versus medical studies) to aid in the prioritization of biomarkers of response to restorative mAbs. In addition, all the information is provided with their provenance (e.g. unique source of the data). ResMarkerDB seeks to promote the recognition of existing and fresh actionable biomarkers of drug response in breast and colorectal malignancy by making this knowledge accessible to both fundamental researchers and medical practitioners. This source is publicly available at http://www.resmarkerdb.org under the Creative Commons 4.0 license. Implementation Data collection We extracted info on biomarkers of treatment response from the following resources: Tumor Genome Interpreter or CGI (v.2018/07/16) (7), Clinical Interpretations of Variants in Malignancy or CIViC (v.2018/07/16) (8), JAX-Clinical Knowledgebase or JAX-CKB (v.2018/07/03) (9) and non-coding RNAs (ncRNAs) in Drug Resistance or ncDR (v.2016/06/28) (10) (Supplementary Table S1). Additionally, a new data arranged, ResCur, that contains expert-curated data extracted from your literature and ncDR by text mining was developed. The text mining info was extracted from PubMed abstracts using the tools Pubtator (11) and SCAIView (12). We focused on ncRNAs and point mutations. Publication retrieval and acknowledgement of drug titles, microRNA (miRNA), level of evidence and response were performed with SCAIView, while additional entities (tumour types, mutations, varieties and genes) were annotated using Pubtator. Finally, the text mining results were expert-curated by looking at if all the entities were properly annotated, adding additional information and critiquing if the.