Ian Glaxo Wellcome Plc Campbell - Genetic Mutations

Author Information

Ian G. Campbell is a prominent researcher affiliated with the Cancer Genetics Laboratory at the Peter MacCallum Cancer Centre in Melbourne, VIC, Australia. His research primarily focuses on genetics and genomics, particularly in relation to cancer.

Research Contributions

Ian G. Campbell has made significant contributions to the field of cancer genetics. His recent work includes the development of online decision aids for women considering risk-stratified breast screening and the assessment of germline and tumor genomics in newly diagnosed breast cancer cases. He has also been involved in studies on polygenic risk modeling for epithelial ovarian cancer and the analysis of large genomic rearrangements in the PALB2 gene concerning familial breast cancer. His research aims to improve genetic testing and risk prediction methodologies for cancer.

Aliases

Ian G. Campbell is also known by several aliases, including I Campbell, Ian G Campbell, I. Campbell, I.g. Campbell, Iang. Campbell, Ian Campbell, I G Campbell, Ian Glaxo Wellcome Plc Campbell, and I. G. Campbell.

Publication and Citation Metrics

Metric	Value
Citation Count	16918
h-index	71
Paper Count	353

Publications:

Development and pilot testing of an online decision aid for women considering risk-stratified breast screening

DOI: 10.1007/s12687-021-00571-y

Year: 2022

Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk.

DOI: 10.1038/s41431-022-01085-y

Year: 2022

Contribution of large genomic rearrangements in PALB2 to familial breast cancer: implications for genetic testing

DOI: 10.1136/jmedgenet-2021-108399

Year: 2022

Abstract P3-09-02: Mutational assessment of newly diagnosed breast cancer using Germline and tumor genomICs

DOI: 10.1158/1538-7445.sabcs21-p3-09-02

Year: 2022

Estimating the proportion of pathogenic variants from breast cancer case-control data: application to calibration of ACMG/AMP variant classification criteria.

DOI: 10.1002/humu.24357

Year: 2022

Integration of tumour sequencing and case–control data to assess pathogenicity of RAD51C missense variants in familial breast cancer

DOI: 10.1038/s41523-021-00373-y

Year: 2022

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

DOI: 10.1038/s41431-021-00987-7

Year: 2022

Evaluation of the association of heterozygous germline variants in NTHL1 with breast cancer predisposition: an international multi-center study of 47,180 subjects.

DOI: 10.17863/CAM.71280

Year: 2021

Validated biomarker assays confirm that ARID1A loss is confounded with MMR deficiency, CD8+ TIL infiltration, and provides no independent prognostic value in endometriosis‐associated ovarian carcinomas

DOI: 10.1002/path.5849

Year: 2021

Pharmacogenomics and functional imaging to predict irinotecan pharmacokinetics and pharmacodynamics: the predict IR study

DOI: 10.1007/s00280-021-04264-8

Year: 2021

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