Predictive Breast Cancer Gene Testing Market Growth Drivers:
- Surging Investigations on the Genetics of Breast Cancer Involving High Penetrant Genes:
At
least eight candidate breast cancer susceptibility genes have been recognized.
Mutations in BRCA1, BRCA2, p53 and the Cowden disease gene are comparatively infrequent,
are highly penetrant and generate striking familial clusters of breast cancer.
BRCA1 and BRCA2 are the most critical of these, being responsible for a
supposed 80% of hereditary breast cancer and 5 to 6% of all breast cancers. Predictive
genetic testing for breast cancer hazards is underway. Oncologists and
primary-care physicians need to become familiar with these genetic ailments and
the issues encompassing predictive testing to make suitable management
decisions regarding women thought to bear a high genetic risk of breast cancer.
The surging investigations on the genetics of breast cancer involving high
penetrant genes are therefore driving the growth of the Predictive Breast
Cancer Gene Testing Market.
- Extensive Efforts on Comprehending the Clinical Implications of Low Penetrant Genes:
Numerous breast cancer genes are presently categorized
as limited-evidence genes by the National Comprehensive Cancer Network (NCCN). The
evolving management for these genes stresses the clinicians' requirement for
evidence-based comprehension of low penetrant breast cancer genes and their conclusions
for patient care. Four intermediate penetrant genes related to breast cancer have been recognized
through mutational screening of candidate genes: CHEK2, ATM, BRIP1 and PALB2.
Mutations in intermediate penetrant genes are rare and confer a comparative
risk of breast cancer of two to four. The extensive efforts in comprehending
the clinical implications of low penetrant genes are therefore propelling the
growth of the Predictive Breast Cancer Gene Testing Industry, thereby
contributing to the Predictive Breast Cancer Gene Testing Industry Outlook.
Product Launch:
In July 2021, Roche declared the research use only (RUO) introduction of
three novel automated digital pathology algorithms, uPath Ki-67 (30-9), uPath
ER (SP1) and uPath PR (1E2) image analysis for breast cancer. These are vital
biomarkers for breast cancer patients.
Predictive Breast
Cancer Gene Testing Market: Competitive Landscape