Genetic and Non-Genetic Breast Cancer Risk Prediction Evaluation in Indonesian Samples

Breast cancer is the most common cancer and cause of cancer- related deaths among women, accounting for 1.67 million (25.2%) new cases and 521,907 (14.7%) deaths worldwide. The prevalence and survival rates of breast cancer differ per country. In Indonesia, majority of patients (70.9%) go to the clinic with advanced stages of breast cancer. Five-year survival rate is 51.07%. One of the most important determinants of survival is education level and stage of breast cancer.

Current screening methods include mammography and radiology assessments, both of which have disadvantages specifically in Asian population. Mammography is less useful in Asian population because the population has denser breast, resulting to failure to diagnose cases of breast cancer in this population in 37-70% of cases. Moreover, screening methods provide binary answers, and therefore does not inform risk profile of the patients.

Traditionally, risk prediction algorithms such as the GAIL model, BODACIEA, and Tyler-Cuzick use medical history and clinical factors of patients. However recently, genetics have grown in importance due to the heritability nature of cancer and availability of testing services and guidelines. About 10-30% of all cases are attributed to familial breast cancers, and of these, only 5%-10% correlate with hereditary factors linked with high penetrance. The most common genetic test to screen today is BRCA 1 and 2, and then other 22 genes curated by expert opinions on NCCN and other guidelines.

The prevalences estimated for carriers of mutations in BRCA1/2 are, respectively, 0.11% and 0.12% in the general population, and between 12.8%-16% in high risk families with three or more cases of breast or ovarian cancer. Approximately 10-15% of ovarian cancer cases are believed to be due to a BRCA1/2 mutation, however ~50% of individuals with a pathogenic BRCA mutation may not report a strong family history of cancer. NCCN, ASCO, St Gallen and has established guidelines to screen patients, but the low awareness in patients to go screening in the first place is hard.

Genetic testing using polygenic risk scores (PRS) combines the effects of low penetrance genes that together creates predictive value as strong as high-penetrance genes, but is much more common than high-penetrance gene testing. A PRS is most commonly calculated as a weighted sum of the number of risk alleles carried by an individual, where the risk alleles and their weights are defined by the loci and their measured effects as detected by genome wide association studies.