Identification of novel risk variants for sarcoma and other cancers by whole exome sequencing analysis in cancer cluster families

Rachel Maree Jones

doi:10.4225/23/59f13ee5d5573

Identification of novel risk variants for sarcoma and other cancers by whole exome sequencing analysis in cancer cluster families

Rachel Maree Jones

Research output: Thesis › Doctoral Thesis

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Abstract

This thesis describes whole exome sequencing of 19 individuals from three cancer families ascertained from a sarcoma proband; Identifying eight germline and 13 somatic candidate risk variants. Variant burden analyses were performed on the corresponding 21 candidate genes in 561 sarcoma cases and 1,144 controls validating six genomic loci (four novel) associated with risk of sarcoma. The results provide new targets of potential clinical utility and demonstrate the power of sequencing a small number of cancer families, with subsequent validation of findings in larger unrelated case and control cohorts, to Identify novel candidate risk genes.

Original language	English
Qualification	Doctor of Philosophy
Awarding Institution	The University of Western Australia
Supervisors/Advisors	Melton, Phillip, Supervisor Ingley, Evan, Supervisor Moses, Eric, Supervisor Wood, David, Supervisor Thomas, David , Supervisor, External person
Thesis sponsors	Australian Government Research Training Program
Award date	16 Oct 2017
DOIs	https://doi.org/10.4225/23/59f13ee5d5573
Publication status	Unpublished - 2017

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THESIS - DOCTOR OF PHILOSOPHY - JONES Rachel Maree - 2017
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title = "Identification of novel risk variants for sarcoma and other cancers by whole exome sequencing analysis in cancer cluster families",

abstract = "This thesis describes whole exome sequencing of 19 individuals from three cancer families ascertained from a sarcoma proband; Identifying eight germline and 13 somatic candidate risk variants. Variant burden analyses were performed on the corresponding 21 candidate genes in 561 sarcoma cases and 1,144 controls validating six genomic loci (four novel) associated with risk of sarcoma. The results provide new targets of potential clinical utility and demonstrate the power of sequencing a small number of cancer families, with subsequent validation of findings in larger unrelated case and control cohorts, to Identify novel candidate risk genes.",

keywords = "Sarcoma, hereditary, cancer-cluster family, Next generation sequencing, Whole Exome Sequencing, Cancer Genetics",

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N2 - This thesis describes whole exome sequencing of 19 individuals from three cancer families ascertained from a sarcoma proband; Identifying eight germline and 13 somatic candidate risk variants. Variant burden analyses were performed on the corresponding 21 candidate genes in 561 sarcoma cases and 1,144 controls validating six genomic loci (four novel) associated with risk of sarcoma. The results provide new targets of potential clinical utility and demonstrate the power of sequencing a small number of cancer families, with subsequent validation of findings in larger unrelated case and control cohorts, to Identify novel candidate risk genes.

AB - This thesis describes whole exome sequencing of 19 individuals from three cancer families ascertained from a sarcoma proband; Identifying eight germline and 13 somatic candidate risk variants. Variant burden analyses were performed on the corresponding 21 candidate genes in 561 sarcoma cases and 1,144 controls validating six genomic loci (four novel) associated with risk of sarcoma. The results provide new targets of potential clinical utility and demonstrate the power of sequencing a small number of cancer families, with subsequent validation of findings in larger unrelated case and control cohorts, to Identify novel candidate risk genes.

KW - Sarcoma

KW - hereditary

KW - cancer-cluster family

KW - Next generation sequencing

KW - Whole Exome Sequencing

KW - Cancer Genetics

U2 - 10.4225/23/59f13ee5d5573

DO - 10.4225/23/59f13ee5d5573

M3 - Doctoral Thesis

ER -

Identification of novel risk variants for sarcoma and other cancers by whole exome sequencing analysis in cancer cluster families

Abstract

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