Evidence map›Paper›PMID 31053105›Full record

ArticleBMC medical genetics2019

Identification of novel sarcoma risk genes using a two-stage genome wide DNA sequencing strategy in cancer cluster families and population case and control cohorts.

Rachel M Jones, Phillip E Melton, Mark Pinese, Alexander J Rea, Evan Ingley, Mandy L Ballinger, International Sarcoma Kindred Study, David J Wood, David M Thomas, Eric K Moses

Open access · goldAbstract read
In one paragraph

Article in BMC medical genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Whole exome sequencing identified a novelFrontiers in oncology · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Rachel M JonesThe Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University and Faculty of Health and Medical Sciences, M409 The University of Western Australia, 35 Stirling Hwy, Crawley, 6009, Western Australia.
Phillip E MeltonThe Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University and Faculty of Health and Medical Sciences, M409 The University of Western Australia, 35 Stirling Hwy, Crawley, 6009, Western Australia.
Mark PineseCancer Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.
Alexander J ReaThe Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University and Faculty of Health and Medical Sciences, M409 The University of Western Australia, 35 Stirling Hwy, Crawley, 6009, Western Australia.
Evan IngleySchool of Veterinary and Life Sciences, Murdoch University, Murdoch, Australia.
Mandy L BallingerCancer Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.
International Sarcoma Kindred Study
David J WoodMedical School, Faculty of Health and Medical Sciences, University of Western Australia, Crawley, Australia.
David M ThomasCancer Division, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia.
Eric K MosesThe Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University and Faculty of Health and Medical Sciences, M409 The University of Western Australia, 35 Stirling Hwy, Crawley, 6009, Western Australia. eric.moses@uwa.edu.au.ORCID 0000-0001-7781-4465
Garvan Institute of Medical Research · AUThe University of Western Australia · AUMurdoch University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough familial clustering of cancers is relatively common, only a small proportion of familial cancer risk can be explained by known cancer predisposition genes.

methodsIn this study we employed a two-stage approach to identify candidate sarcoma risk genes. First, we conducted whole exome sequencing in three multigenerational cancer families ascertained through a sarcoma proband (n = 19) in order to prioritize candidate genes for validation in an independent case-control cohort of sarcoma patients using family-based association and segregation analysis. The second stage employed a burden analysis of rare variants within prioritized candidate genes identified from stage one in 560 sarcoma cases and 1144 healthy ageing controls, for which whole genome sequence was available.

resultsVariants from eight genes were identified in stage one. Following gene-based burden testing and after correction for multiple testing, two of these genes, ABCB5 and C16orf96, were determined to show statistically significant association with cancer. The ABCB5 gene was found to have a higher burden of putative regulatory variants (OR = 4.9, p-value = 0.007, q-value = 0.04) based on allele counts in sarcoma cases compared to controls. C16orf96, was found to have a significantly lower burden (OR = 0.58, p-value = 0.0004, q-value = 0.003) of regulatory variants in controls compared to sarcoma cases.

conclusionsBased on these genetic association data we propose that ABCB5 and C16orf96 are novel candidate risk genes for sarcoma. Although neither of these two genes have been previously associated with sarcoma, ABCB5 has been shown to share clinical drug resistance associations with melanoma and leukaemia and C16orf96 shares regulatory elements with genes that are involved with TNF-alpha mediated apoptosis in a p53/TP53-dependent manner. Future genetic studies in other family and population cohorts will be required for further validation of these novel findings.

Indexed as

Genetic Predisposition to DiseaseAdolescentAdultAgedAged, 80 and overAllelesCohort StudiesDNAFemaleHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedPedigreeSarcomaYoung AdultDNACancer cluster familiesGenetic risk variantsSarcomaWhole exome sequencingWhole genome sequencing

Identifiers

PMID31053105
PMCPMC6499942
OpenAlexW2947385959

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.