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One\nin eight women will develop breast cancer over the course of a lifetime. Breast\ncancer is the most common cancer in women worldwide, as well as the most\ncommonly-occurring cancer in women in Macao. In view of this alarming trend,\nhow can medical research prevent breast cancer?<\/p>\n\n
The Threat of Breast\nCancer<\/b><\/p>\n\n
Breast cancer is a significant threat to women\u2019s health. In\n2018, over 2 million women worldwide, and over 250,000 in China, were diagnosed\nwith breast cancer. Around 10 to 15 per cent of breast cancer cases are caused\nby hereditary genetic mutations transmitted following Mendelian genetics. The\nmajority of the mutations are located in BRCA1 and BRCA2 genes (BRCA), which\nare the essential genes for maintaining genome stability. Women carrying\npathogenic mutations in BRCA1 have up to 80 per cent of lifetime risk of developing\nbreast cancer. Mutations in BRCA genes also increase the risk of developing\nother types of cancer, including ovarian, prostate, and pancreatic cancers.<\/p>\n\n
Effective Prevention\nMethod<\/b><\/p>\n\n
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Identification\nof BRCA mutation carriers before cancer occurrence is the most effective way to\nprevent mutation carriers from cancer, as it allows early cancer surveillance, targeted\ndrug prevention, preventive surgery, and interrupts mutation transmission to\nthe next generation through in vitro fertilisation. With the known cause of\ngenetic mutation, available methods to identify the genetic mutation, and multiple\neffective prevention and treatment options, BRCA mutation-caused cancers are\nthe most preventable cancers among all cancer types in humans. The story of the\nAmerican actress Angelina Jolie provides a vivid example of the relationship\nbetween BRCA mutation and breast cancer prevention.<\/p>\n\n
Studies of BRCA\nMutations<\/b><\/p>\n\n
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Recent\nstudies have revealed that BRCA mutation in humans is highly ethnic-specific,\nthat is, different ethnicities have very different mutations in BRCA genes. For\nexample, BRCA mutations in Latin Americans are highly heterogeneous, whereas\nBRCA mutations in Asians differ substantially from those in Caucasians.\nEthnic-specific BRCA mutation is important, as it reflects the genetic basis\nfor the cancer occurring in different ethnic populations, and provides specific\nmutation targets for precise identification of the mutation carriers for prevention,\ndiagnosis and treatment of the cancer in given ethnic populations. However, the\nBRCA mutation data widely used in clinical applications are mostly derived from\nCaucasian populations in Europe and North America, which account for only a small\nportion of the total human population, whereas the data from non-Caucasian\nethnicities, which account for 80 per cent of world population, are rare.<\/p>\n\n
BRCA Mutation\nDatabase<\/b><\/p>\n\n
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Our\nlaboratory has been studying BRCA mutations in the Chinese population. Through\ncomprehensive data analysis, we have collected over 1,000 BRCA mutations from\nover 30,000 Chinese cancer patients. This is the most comprehensive BRCA\nmutation data that originated from the Chinese population, and one of the\nlargest from a non-Caucasian population. We have developed an open-access\ndatabase, Chinese BRCA mutation database, for public use\n(https:\/\/dbBRCA-Chinese. fhs.umac.mo). Through comprehensive comparison with\nBRCA mutation data from non-Chinese populations around the world, we have\ndetermined that 40 per cent of the Chinese BRCA mutations are only present in\nthe Chinese population but not in non-Chinese populations. <\/p>\n\n
BRCA Mutations in\nMacao<\/b><\/p>\n\n
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We\nfurther analysed BRCA mutations in Macao. Macao has a population of over\n600,000, in which over 50 per cent are female, and 95 per cent are of Chinese\nethnicity and predominantly Cantonese. Breast cancer is the most commonly\noccurring cancer of all cancer types in females in Macao, with 1,353 breast\ncancer cases diagnosed between 2003 and 2013. Through analysing 2,000\nindividuals in Macao, we observed a higher frequency of BRCA mutations in the\nMacao population than in other populations. This suggests that BRCA mutations\ncan play a more significant role in breast cancer in the Macao population than\nin other populations (Fig.1). A significance of studying the population in\nMacao is that the data can be readily applicable to the population in the\nGreater Bay Area, including Guangdong, Hong Kong, and Macao. The population in\nthe Greater Bay Area is a subgroup of the Chinese population known as Lingnan,\nwhose genetic background is known to be substantially different from that of\nthe inland Chinese population. As Macao\u2019s population is genetically the same as\npeople in the Greater Bay Area, the ethnic-specific BRCA mutation identified in\nthe Macao population should be the same as the population in the Greater Bay Area.\nTherefore, Macao\u2019s population provides a perfect model to study BRCA mutation\nin the population of the Greater Bay Area, and the BRCA mutations identified in\nthe Macao population are readily applicable for cancer prevention and treatment\nin the entire area inhabited by a population of over 100 million, in which\nsystematic investigations into BRCA mutations have been very limited. We are\nworking hard in this direction, including expanding the coverage of testing in\nthe Macao population and conducting large-scale verification work in the\nGuangdong population. Our work should lay a solid foundation for cancer\nprevention through promoting BRCA gene mutation screening for the population in\nthe Greater Bay Area. <\/p>\n\n
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Note:\nThis is the first large open-access Chinese BRCA mutation database, which\ncontains data on almost all known BRCA mutations found in the Chinese\npopulation. This is also one of the largest non-Caucasian single-country BRCA mutation\ndatabases. It is the hope of the Faculty of Health Sciences that this database\nwill promote the study of BRCA-related cancers in the Chinese population and the\nclinical applications of the research results, and enhance domestic and\ninternational collaboration in the field.<\/p>
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