Should multi-gene panel testing replace limited BRCA1/2 testing? A review of genetic testing for hereditary breast and ovarian cancers

A novel gene expression test method of minimizing breast cancer risk in reduced cost and time by improving SVM-RFE gene selection method combined with LASSO

Breast cancer is the leading diseases of death in women. It induces by a genetic mutation in breast cancer cells. Genetic testing has become popular to detect the mutation in genes but test cost is relatively expensive for several patients in developing countries like India. Genetic test takes between 2 and 4 weeks to decide the cancer. The time duration suffers the prognosis of genes because some patients have high rate of cancerous cell growth. In the research work, a cost and time efficient method is proposed to predict the gene expression level on the basis of clinical outcomes of the patient by using machine learning techniques. An improved SVM-RFE_MI gene selection technique is proposed to find the most significant genes related to breast cancer afterward explained variance statistical analysis is applied to extract the genes contain high variance. Least Absolute Shrinkage Selector Operator (LASSO) and Ridge regression techniques are used to predict the gene expression level. The proposed method predicts the expression of significant genes with reduced Root Mean Square Error and acceptable adjusted R-square value. As per the study, analysis of these selected genes is beneficial to diagnose the breast cancer at prior stage in reduced cost and time.

Improving attendance to genetic counselling services for gynaecological oncology patients

Background

Gynaecological cancers may be the sentinel malignancy in women who carry a mutation in BRCA1 or 2, a mis-match repair gene causing Lynch Syndrome or other genes. Despite published guidelines for referral to a genetics service, a substantial number of women do not attend for the recommended genetic assessment. The study aims to determine the outcomes of systematic follow-up of patients diagnosed with ovarian or endometrial cancer from Gynaecologic-oncology multidisciplinary meetings who were deemed appropriate for genetics assessment.

Methods

Women newly diagnosed with gynaecological cancer at the Royal Hospital for Women between 2010 and 2014 (cohort1) and 2015-2016 (cohort 2) who were identified as suitable for genetics assessment were checked against the New South Wales/Australian Capital Territory genetic database. The doctors of non-attenders were contacted regarding suitability for re-referral, and patients who were still suitable for genetics assessment were contacted by mail. Attendance was again checked against the genetics database.

Results

Among 462 patients in cohort 1, flagged for genetic assessment, 167 had not consulted a genetic service at initial audit conducted in 2014. 86 (18.6%) women whose referral was pending clarification of family history and/or immunohistochemistry did not require further genetic assessment. Letters were sent to 40 women. 7 women (1.5%) attended hereditary cancer clinic in the following 6 months.The audit conducted in 2016 identified 148 patients (cohort 2) appropriate for genetic assessment at diagnosis. 66 (44.6%) had been seen by a genetics service, 51 (34.5%) whose referral was pending additional information did not require further genetic assessment. Letters were sent to 15 women, of whom 9 (6.1%) attended genetics within 6 months.

Conclusions

To improve the effectiveness of guidelines for the genetic referral of women newly diagnosed with ovarian cancer, clinicians need to obtain a thorough family history at diagnosis; arrange for reflex MMR IHC according to guidelines; offer BRCA or panel testing to all women with non-mucinous ovarian cancer prior to discharge and systematically follow up all women referred to genetics at the post-op visit.