Actions and Uncertainty: How Prenatally Diagnosed Variants of Uncertain Significance Become Actionable

Establishing a universally applicable protocol to assess the impact of BRCA1 variants of uncertain significance (VUS) expression is a problem which has yet to be resolved despite major progresses have been made. The numerous difficulties which must be overcome include the choices of cellular models and functional assays. We hypothesised that the use of induced pluripotent stem (iPS) cells might facilitate the standardisation of protocols for classification, and could better model the disease process. We generated eight iPS cell lines from patient samples expressing either BRCA1 pathogenic variants, non-pathogenic variants, or BRCA1 VUSs. The impact of these variants on DNA damage repair was examined using a ɣH2AX foci formation assay, a Homologous Repair (HR) reporter assay, and a chromosome abnormality assay. Finally, all lines were tested for their ability to differentiate into mammary lineages in vitro. While the results obtained from the two BRCA1 pathogenic variants were consistent with published data, some other variants exhibited differences. The most striking of these was the BRCA1 variant Y856H (classified as benign), which was unexpectedly found to present a faulty HR repair pathway, a finding linked to the presence of an additional variant in the ATM gene. Finally, all lines were able to differentiate first into mammospheres, and then into more advanced mammary lineages expressing luminal- or basal-specific markers. This study stresses that BRCA1 genetic analysis alone is insufficient to establish a reliable and functional classification for assessment of clinical risk, and that it cannot be performed without considering the other genetic aberrations which may be present in patients. The study also provides promising opportunities for elucidating the physiopathology and clinical evolution of breast cancer, by using iPS cells.

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Multi gene panel testing for hereditary breast cancer - is it ready to be used?

Medicine and Pharmacy Reports ◽

10.15386/mpr-1083 ◽

2019 ◽

Cited By ~ 1

Author(s):

Andreea Catana ◽

Adina Patricia Apostu ◽

Razvan-Geo Antemie

Keyword(s):

Breast Cancer ◽

Hereditary Breast Cancer ◽

Gene Panel ◽

Variants Of Uncertain Significance ◽

Panel Testing ◽

Brca Genes ◽

Prophylactic Measures ◽

Gene Panel Testing ◽

Uncertain Significance ◽

High Level

Breast cancer is one of the most common malignancies and the leading cause of death among women worldwide. About 20% of breast cancers are hereditary. Approximately 30% of the mutations have remained negative after testing BRCA1/2 even in families with a Mendelian inheritance pattern for breast cancer. Additional non-BRCA genes have been identified as predisposing for breast cancer. Multi gene panel testing tries to cover and explain the BRCA negative inherited breast cancer, improving efficiency, speed and costs of the breast cancer screening. We identified 23 studies reporting results from individuals who have undergone multi gene panel testing for hereditary breast cancer and noticed a prevalence of 1-12% of non-BRCA genes, but also a high level of variants of uncertain significance. A result with a high level of variants of uncertain significance is likely to be more costly than bring benefits, as well as increase the anxiety for patients. Regarding further development of multi gene panel testing, more research is required to establish both the optimal care of patients with cancer (specific treatments like PARP inhibitors) and the management of unaffected individuals (chemoprevention and/or prophylactic surgeries). Early detection in these patients as well as prophylactic measures will significantly increase the chance of survival. Therefore, multi gene panel testing is not yet ready to be used outside clear guidelines. In conclusion, studies on additional cohorts will be needed to better define the real prevalence, penetrance and the variants of these genes, as well as to describe clear evidence-based guidelines for these patients.

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Network-based pathogenicity prediction for variants of uncertain significance

10.1101/2021.07.15.452566 ◽

2021 ◽

Author(s):

Mayumi Kamada ◽

Atsuko Takagi ◽

Ryosuke Kojima ◽

Yoshihisa Tanaka ◽

Masahiko Nakatsui ◽

...

Keyword(s):

Computational Method ◽

Major Barrier ◽

Clinical Interpretation ◽

Individual Gene ◽

Variants Of Uncertain Significance ◽

Uncertain Significance ◽

Benchmark Datasets ◽

Genomic Scale ◽

Molecular Relationships ◽

Potential Pathogenicity

While the number of genome sequences continues to increase, the functions of many detected gene variants remain to be identified. These variants of uncertain significance constitute a major barrier to precision medicine. Although many computational methods have been developed to predict the function of these variants, they all rely on individual gene features and do not consider complex molecular relationships. Here we develop PathoGN, a molecular network-based approach for predicting variant pathogenicity. PathoGN significantly outperforms existing methods using benchmark datasets. Moreover, PathoGN successfully predicts the pathogenicity of 3,994 variants of uncertain significance in the real-world database ClinVar and designates potential pathogenicity. This is the first computational method for the clinical interpretation of variants using biomolecular networks, and we anticipate our method to be broadly useful for the clinical interpretation of variants and for assigning biological function to unknown variants at the genomic scale.

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