Genetic and Non-Genetic Breast Cancer Risk Prediction Evaluation in Indonesian Samples
Condition: Breast Cancer
MeSH terms: Breast Neoplasms
Study type: Observational [Patient Registry]

Summary: 
      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.

      The investigators aim to implement PRS into the breast cancer screening process while
      observing the differences of genetic and non-genetic risk factor in patients with breast
      cancer and patients without any medical/family history of breast cancer in Indonesian
      population.
    

Detailed description: 
      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.

      For some common adult-onset diseases, the polygenic risk conveyed to a substantial segment
      (10-20%) of the population whose genomes are enriched in risk alleles is comparable to the
      risk conveyed by commonly used clinical risk factors. A recent large-scale comprehensive GWAS
      for breast cancer found that 45% of familial relative risk of breast cancer can be explained
      by genetic variants captured by genotyping and imputation. As genotyping technologies
      advance, and consortia build algorithms on more samples, the predictive values of PRS
      algorithms are maturing. After analysis of 120,000 patients and optimizing for highest
      predictability, a PRS score combining 313 SNPs and clinical factors have a predictive value
      of 68%, compared to only 58% using clinical risk factors. A study conducted in the Breast
      Cancer Association Consortium showed that PRS combined with environmental risk factors can be
      used to distinguish women at different levels of breast cancer risk in the general
      population.

      This score gives providers the opportunity to stratify the patients may result in some people
      with higher risk profile to start risk-reducing therapy earlier, start screening at a younger
      age, and modify their lifestyles with the aim of reducing their risk. For example, those who
      are at the top 1.5% of polygenic risk score have an odds ratio of 3 or more compared to the
      general population.

      Polygenic risk scores have been applied in leading institutions in the world as clinical
      trials and in the commercial settings. However, there has been little application in
      developing countries to use polygenic risk score to increase awareness of risk-reducing
      strategies of breast cancer in patients.

      One of the main concerns about the clinical implementation of population-based genetic
      screening is experts' availability post-test. A study in the UK for physicians' attitude
      towards risk stratification of ovarian cancer showed that 70% oncologists and 50% of GPs
      would be willing to offer genetic testing to their patients. About 60% believe that the test
      would give patients a sense of control, and over 80% of providers are willing to personalize
      recommendations based on risk stratification.

      The investigators aim to implement PRS into the breast cancer screening process while
      observing the differences of genetic and non-genetic risk factor in patients with breast
      cancer and patients without any medical/family history of breast cancer in Indonesian
      population.
    

Intervention name(s): Breast Cancer Risk Prediction Software
Intervention type(s): Diagnostic Test
Intervention description(s): Genotyping of known breast cancer-related markers (313 variants) will be conducted using a microarray genotyping chip (Genetic Risk). Survey answers will determine Gail Model scores and thus Clinical Risk Score.
Observational model: Case-Control
Time perspective: Prospective
Sampling method: Probability Sample
Study population: 
        Controls are taken from clients who visited Breast Cancer Care Alliance (BCCA) We will not
        impose any selection to age at diagnosis for both cases and controls
      
Biospecimen description: 
      gDNA extracted from Buccal Sample
    
Keywords: Breast Cancer; Polygenic Risk Score