Feasibility of a large multi-center translational research project for newly diagnosed breast and ovarian cancer patients with affiliated biobank: the BRandO biology and outcome (BiO)-project

Gregorio, Amelie de; Nagel, Gabriële; Möller, Peter; Rempen, A.; Schlicht, Erik M.; Fritz, S; Flock, Felix; Kühn, Thorsten; Thiel, Falk; Felberbaum, R.; Ebner, Florian; Gregorio, Nikolaus de; Friedl, Thomas; Wiesmüller, Lisa; Kühn, Peter; Schmitt, M.; Janni, Wolfgang; Rothenbacher, Dietrich; Huober, Jens

doi:10.1007/s00404-019-05395-3

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…Recent studies related to gynaecological cancer biobanking and data harmonisation, including living biobanks of ex vivo cultures of OC models [18]; the Canadian Ovarian Experimental Unified Resource (COEUR) [19] to provide access to biological material and data for biomarker research in OC; the BRandOBio [20] large multicentre translational project for newly diagnosed OC patients with affiliated biobank; the prospective Australian National Gynae-Oncology Registry (NGOR) [3]; the development of tools for harmonisation of biobanking standards in endometrial cancer research (HASTEN study) [21]; and The Cancer Genome Atlas (TCGA) project, are further discussed below.…”

Section: Discussionmentioning

confidence: 99%

Prospective Real-World Gynaecological Cancer Clinical Registry with Associated Biospecimens: A Collaborative Model to Promote Translational Research between GEICO and the Spanish Biobank Network

López-Guerrero

Mendiola

Fidalgo

et al. 2022

Cancers

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Patient registries linked to biorepositories constitute a valuable asset for clinical and translational research in oncology. The Spanish Group of Ovarian Cancer Research (GEICO), in collaboration with the Spanish Biobank Network (RNBB), has developed a multicentre, multistakeholder, prospective virtual clinical registry (VCR) associated with biobanks for the collection of real-world data and biological samples of gynaecological cancer patients. This collaborative project aims to promote research by providing broad access to high-quality clinical data and biospecimens for future research according to the needs of investigators and to increase diagnostic and therapeutic opportunities for gynaecological cancer patients in Spain. The VCR will include the participation of more than 60 Spanish hospitals entering relevant clinical information in harmonised electronic case report forms (eCRFs) in four different cohorts: ovarian, endometrial, cervical, and rare gynaecological cancers (gestational trophoblastic disease). Initial data for the cases included till December 2021 are presented. The model described herein establishes a real-world win-win collaboration between multicentre structures, promoted and supported by GEICO, that will contribute to the success of translational research in gynaecological cancer.

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Section: Discussionmentioning

confidence: 99%

Prospective Real-World Gynaecological Cancer Clinical Registry with Associated Biospecimens: A Collaborative Model to Promote Translational Research between GEICO and the Spanish Biobank Network

López-Guerrero

Mendiola

Fidalgo

et al. 2022

Cancers

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“…Meanwhile, biobanks accelerate human research, with less reliance on animal models and advancing research based on human biospecimen resources. Biobanks have been previously established for several tumors, including prostate (16), breast (17), gastric (18), glioblastoma (19), lung (20), and ovarian cancer (21), which provided valuable resources for translational and molecular studies. Given the lack of ocular tumor biobanks in China, we established an ocular tumor biobank to provide a resource from different patients covering 21 kinds of eye tumors, including blood, plasma, and tissue samples (Figure 2 and Table 1).…”

Section: A Dedicated Ocular Tumor Biobank Containing Biological Specimens and Associated Clinical Datamentioning

confidence: 99%

The Xiangya Ocular Tumor Bank: A Disease-Specific Biobank for Advancing Translational Research Into Ocular Tumors

et al. 2022

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The pathogenesis and etiology of various ocular tumors remain largely unclear, limiting the development of diagnostic and treatment approaches for such tumors. Tissue samples from patients are also valuable resource to elucidate mechanisms underlying tumorigenesis. Here we present the early phase setup of an ocular tumor biobank at Xiangya Hospital. Blood and tissue samples along with associated clinical data were obtained from patients who underwent surgery in the Department of Ophthalmology of Xiangya Hospital from December 1, 2018 to January 31, 2020. Standardized operating protocols were developed for the collection, transportation, processing and preservation of ocular tumor samples. A total of 92 clinical cases suffered from 21 types of eye tumors and several undiagnosed eye diseases were covered. A total of 846 samples were preserved in the ocular tumor biobank, including 356 blood samples (42.1%), 324 plasma samples (38.3%), and 166 tissue samples (19.6%). Using the clinical data, we analyzed the prevalence of malignant ocular tumors in association with variables of age, gender, tumors' location and size, and presenting complaints of lump and proptosis. The factors predictive of malignant ocular tumors, included gender (B = 1.599; P = 0.025) and the symptom of proptosis (B = −2.534; P = 0.001). Overall, the setup of clinically-based ophthalmologic biobank could support pathological and translational research into ocular tumors.

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Clinical and Research Informatics Data Strategy for Precision Oncology

Hartman

Chandran

Davis

et al. 2022

Holland‐Frei Cancer Medicine

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Overview Oncology informatics in the era of precision oncology is challenging because no unified comprehensive system exists linking Health Information Technology (HIT) deployed in clinical settings to the translational needs of researchers. Many advanced informatics solutions have been developed for clinical trials, biobanking, cancer imaging, and high‐throughput‐omic technologies. These are fundamentally transforming the treatment and management of cancer patients. However, the lack of fully developed interoperable cancer research informatics and HIT technologies to move between the bench and the bedside remains a significant challenge. Oncologists and translational cancer investigators require knowledge of informatics, data science, and advanced machine learning (artificial intelligence) as these are the major change agents influencing the development of new therapies, especially in the era of Precision Medicine and Learning Health Systems for oncology. In addition, cancer care delivery is very dependent on new developments in clinical practice and requires a thorough, systematic reevaluation of the electronic health records (EHRs) in use today. The ability (through mobile computing) to have information “on demand” during daily oncology practice is reshaping our thinking of how we record, document, and share data toward the common purpose of improving cancer outcomes for the patients we serve. This article looks at HIT and clinical, translational, and research informatics for oncologists and cancer researchers and begins to paint a picture of what an “ideal” environment for cancer care delivery would look like to support Precision Oncology and Learning Health Systems.

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Feasibility of a large multi-center translational research project for newly diagnosed breast and ovarian cancer patients with affiliated biobank: the BRandO biology and outcome (BiO)-project

Cited by 4 publications

References 14 publications

Prospective Real-World Gynaecological Cancer Clinical Registry with Associated Biospecimens: A Collaborative Model to Promote Translational Research between GEICO and the Spanish Biobank Network

Prospective Real-World Gynaecological Cancer Clinical Registry with Associated Biospecimens: A Collaborative Model to Promote Translational Research between GEICO and the Spanish Biobank Network

The Xiangya Ocular Tumor Bank: A Disease-Specific Biobank for Advancing Translational Research Into Ocular Tumors

Clinical and Research Informatics Data Strategy for Precision Oncology

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