Pathogenic germline variants in 10,389 adult cancers. Huang et al.

Published: 19 Apr 2018 | Version 1 | DOI: 10.17632/yt3gvjv2f7.1

Description of this data

Pathogenic Germline Variants in 10,389 Adult Cancers

We conducted the largest investigation of predispo- sition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large dele- tions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evi- dences involving case-control frequency, loss of het- erozygosity, expression effect, and co-localization with mutations and modified residues. Our integra- tive approach links rare predisposition variants to functional consequences, informing future guide- lines of variant classification and germline genetic testing in cancer.

Experiment data files

Steps to reproduce

Analyses scripts:

This data is associated with the following publication:

Pathogenic Germline Variants in 10,389 Adult Cancers

Published in: Cell

Latest version

  • Version 1


    Published: 2018-04-19

    DOI: 10.17632/yt3gvjv2f7.1

    Cite this dataset

    Huang, Kuan-lin (2018), “Pathogenic germline variants in 10,389 adult cancers. Huang et al.”, Mendeley Data, v1


Views: 525
Downloads: 119


Genomics, Cancer, Genetic Predisposition


CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?
You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.