Towards a Global Cancer Knowledge Network: Dissecting the current international cancer genomic sequencing landscape. - PubMed - NCBI
Ann Oncol. 2017 Feb 3. doi: 10.1093/annonc/mdx037. [Epub ahead of print]
Towards a Global Cancer Knowledge Network: Dissecting the current international cancer genomic sequencing landscape.
Vis DJ1,
Lewin J2,
Liao RG3,
Mao M4,
Andre F5,
Ward RL6,
Calvo F7,
Teh BT8,
Camargo AA9,
Knoppers BM10,
Sawyers C11,
Wessels LF1,12,
Lawler M13,
Siu LL2,
Voest E1;
behalf of the Clinical Working Group of the Global Alliance for Genomics and Health.
Abstract
BACKGROUND:
While next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community. METHODS:
A multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (Clinical Diagnostic, Research or Combination). RESULTS:
Of 107 initiatives invited to participate, 59 responded (response rate=55%). Whole Exome Sequencing ( p =0.03) and Whole Genome Sequencing ( p = 0.01), were utilized less frequently in Clinical Diagnostic than in Research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common however; other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonisation were the lack of financial support ( p < 0.01) and bioinformatics concerns (e.g. lack of interoperability)( p = 0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives ( p = 0.01). CONCLUSIONS:
These results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need for greater harmonisation of technical, ethical and data capture processes in cancer sample sequencing worldwide, in order to support effective and responsible data sharing for the benefit of patients. KEYWORDS:
Cancer; Data Sharing;; Genomics; Molecular Profiling; Survey
No hay comentarios:
Publicar un comentario