Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas.
Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas.
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DOI：
10.1001/jamaoncol.2017.0595
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发表时间：
2017-12-01
期刊：
影响因子：
28.4
通讯作者：
Olopade OI
中科院分区：
文献类型：
--
作者：
Huo D;Hu H;Rhie SK;Gamazon ER;Cherniack AD;Liu J;Yoshimatsu TF;Pitt JJ;Hoadley KA;Troester M;Ru Y;Lichtenberg T;Sturtz LA;Shelley CS;Benz CC;Mills GB;Laird PW;Shriver CD;Perou CM;Olopade OI
非裔美国人的乳腺癌死亡率最高。虽然已知乳腺癌固有亚型分布的种族差异，但尚不清楚是否存在其他固有基因组差异导致生存差异。探讨乳腺癌分子特征和生存的种族差异，并估计乳腺癌亚型的遗传力。在一个方便的浸润性乳腺癌患者队列中，乳腺癌和匹配的正常组织样本数据（截至2015年9月18日）来自The cancer Genome Atlas。乳腺癌无癌间隔、肿瘤分子特征和基因变异。研究对象为930例乳腺癌患者，其中非洲裔黑人患者154例（诊断时平均年龄55.66[13.01]岁，女性98.1% [n = 151]），欧洲裔白人患者776例（诊断时平均年龄59.51[13.11]岁，女性99.0% [n = 768]）。与白人患者相比，黑人患者无乳腺癌间期较差（HR=1.67, 95 CI: 1.02-2.74; P = 0.043）。以Luminal a亚型为参照，她们患基底样（优势比为3.80,95% CI为2.46-5.87,P < 0.001）和人表皮生长因子受体2 （ERBB2[原HER2]）富集（优势比为2.22,95% CI为1.10-4.47，P= 0.027）乳腺癌亚型的可能性更高。黑人比白人有更多的TP53突变和更少的PIK3CA突变。虽然在调整固有亚型后消除了大多数分子差异，但研究发现16个DNA甲基化探针、4个DNA拷贝数片段、1个蛋白质和142个基因存在差异表达，基于基因的标记具有很好的区分黑人和白人乳腺癌患者的能力（交叉验证C指数，0.878）。使用种系基因型，乳腺癌亚型（基础型与非基础型）的遗传率估计为0.436 （P = 1.5 × 10−14）。由89个已知易感变异构建的雌激素受体阳性多基因风险评分黑人高于白人（差异0.24,P = 2.3 × 10−5），而雌激素受体阴性多基因风险评分黑人远高于白人（差异0.48,P = 2.8 × 10−11）。在分子水平上，在调整了固有亚型频率差异后，本研究发现，在癌症基因组图谱数据集中，黑人和白人之间存在少量基因组差异，但临床生存结果存在显著差异。此外，超过40%的乳腺癌亚型频率差异可以用基因变异来解释。这些数据可以为分子靶向治疗的发展奠定基础，以改善对黑人妇女影响不成比例的特定亚型乳腺癌的临床结果。研究结果还表明，个性化的风险评估和最佳治疗可以减少黑人妇女因侵袭性乳腺癌死亡的人数。
African Americans have the highest breast cancer mortality rate. Although racial difference in the distribution of intrinsic subtypes of breast cancer is known, it is unclear if there are other inherent genomic differences that contribute to the survival disparities. To investigate racial differences in breast cancer molecular features and survival and to estimate the heritability of breast cancer subtypes. Among a convenience cohort of patients with invasive breast cancer, breast tumor and matched normal tissue sample data (as of September 18, 2015) were obtained from The Cancer Genome Atlas. Breast cancer-free interval, tumor molecular features, and genetic variants. Participants were 930 patients with breast cancer, including 154 black patients of African ancestry (mean [SD] age at diagnosis, 55.66 [13.01] years; 98.1% [n = 151] female) and 776 white patients of European ancestry (mean [SD] age at diagnosis, 59.51 [13.11] years; 99.0% [n = 768] female). Compared with white patients, black patients had a worse breast cancer-free interval (hazard ratio, HR=1.67, 95 CI: 1.02–2.74; P = .043). They had a higher likelihood of basal-like (odds ratio, 3.80; 95% CI, 2.46–5.87; P < .001) and human epidermal growth factor receptor 2 (ERBB2 [formerly HER2])-enriched (odds ratio, 2.22; 95% CI, 1.10–4.47; P= .027) breast cancer subtypes, with the Luminal A subtype as the reference. Blacks had more TP53 mutations and fewer PIK3CA mutations than whites. While most molecular differences were eliminated after adjusting for intrinsic subtype, the study found 16 DNA methylation probes, 4 DNA copy number segments, 1 protein, and 142 genes that were differentially expressed, with the gene-based signature having an excellent capacity for distinguishing breast tumors from black vs white patients (cross-validation C index, 0.878). Using germline genotypes, the heritability of breast cancer subtypes (basal vs nonbasal) was estimated to be 0.436 (P = 1.5 × 10−14). The estrogen receptor-positive polygenic risk score built from 89 known susceptibility variants was higher in blacks than in whites (difference, 0.24; P = 2.3 × 10−5), while the estrogen receptor-negative polygenic risk score was much higher in blacks than in whites (difference, 0.48; P = 2.8 × 10−11). On the molecular level, after adjusting for intrinsic subtype frequency differences, this study found a modest number of genomic differences but a significant clinical survival outcome difference between blacks and whites in The Cancer Genome Atlas data set. Moreover, more than 40% of breast cancer subtype frequency differences could be explained by genetic variants. These data could form the basis for the development of molecular targeted therapies to improve clinical outcomes for the specific subtypes of breast cancers that disproportionately affect black women. Findings also indicate that personalized risk assessment and optimal treatment could reduce deaths from aggressive breast cancers for black women.
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DOI：
10.1093/jnci/djv048
发表时间：
2015-06
期刊：
Journal of the National Cancer Institute
影响因子：
--
作者：
Kohler BA;Sherman RL;Howlader N;Jemal A;Ryerson AB;Henry KA;Boscoe FP;Cronin KA;Lake A;Noone AM;Henley SJ;Eheman CR;Anderson RN;Penberthy L
通讯作者：
Penberthy L
影响因子：
3.7
作者：
Martin, Damali N.;Boersma, Brenda J.;Yi, Ming;Reimers, Mark;Howe, Tiffany M.;Yfantis, Harry G.;Tsai, Yien Che;Williams, Erica H.;Lee, Dong H.;Stephens, Robert M.;Weissman, Allan M.;Ambs, Stefan
通讯作者：
Ambs, Stefan
影响因子：
254.7
作者：
DeSantis, Carol E.;Fedewa, Stacey A.;Jemal, Ahmedin
通讯作者：
Jemal, Ahmedin
影响因子：
3.8
作者：
Chavez-MacGregor, Mariana;Liu, Shuying;Gonzalez-Angulo, Ana M.
通讯作者：
Gonzalez-Angulo, Ana M.
影响因子：
30.8
作者：
Michailidou K;Beesley J;Lindstrom S;Canisius S;Dennis J;Lush MJ;Maranian MJ;Bolla MK;Wang Q;Shah M;Perkins BJ;Czene K;Eriksson M;Darabi H;Brand JS;Bojesen SE;Nordestgaard BG;Flyger H;Nielsen SF;Rahman N;Turnbull C;BOCS;Fletcher O;Peto J;Gibson L;dos-Santos-Silva I;Chang-Claude J;Flesch-Janys D;Rudolph A;Eilber U;Behrens S;Nevanlinna H;Muranen TA;Aittomäki K;Blomqvist C;Khan S;Aaltonen K;Ahsan H;Kibriya MG;Whittemore AS;John EM;Malone KE;Gammon MD;Santella RM;Ursin G;Makalic E;Schmidt DF;Casey G;Hunter DJ;Gapstur SM;Gaudet MM;Diver WR;Haiman CA;Schumacher F;Henderson BE;Le Marchand L;Berg CD;Chanock SJ;Figueroa J;Hoover RN;Lambrechts D;Neven P;Wildiers H;van Limbergen E;Schmidt MK;Broeks A;Verhoef S;Cornelissen S;Couch FJ;Olson JE;Hallberg E;Vachon C;Waisfisz Q;Meijers-Heijboer H;Adank MA;van der Luijt RB;Li J;Liu J;Humphreys K;Kang D;Choi JY;Park SK;Yoo KY;Matsuo K;Ito H;Iwata H;Tajima K;Guénel P;Truong T;Mulot C;Sanchez M;Burwinkel B;Marme F;Surowy H;Sohn C;Wu AH;Tseng CC;Van Den Berg D;Stram DO;González-Neira A;Benitez J;Zamora MP;Perez JI;Shu XO;Lu W;Gao YT;Cai H;Cox A;Cross SS;Reed MW;Andrulis IL;Knight JA;Glendon G;Mulligan AM;Sawyer EJ;Tomlinson I;Kerin MJ;Miller N;kConFab Investigators;AOCS Group;Lindblom A;Margolin S;Teo SH;Yip CH;Taib NA;Tan GH;Hooning MJ;Hollestelle A;Martens JW;Collée JM;Blot W;Signorello LB;Cai Q;Hopper JL;Southey MC;Tsimiklis H;Apicella C;Shen CY;Hsiung CN;Wu PE;Hou MF;Kristensen VN;Nord S;Alnaes GI;NBCS;Giles GG;Milne RL;McLean C;Canzian F;Trichopoulos D;Peeters P;Lund E;Sund M;Khaw KT;Gunter MJ;Palli D;Mortensen LM;Dossus L;Huerta JM;Meindl A;Schmutzler RK;Sutter C;Yang R;Muir K;Lophatananon A;Stewart-Brown S;Siriwanarangsan P;Hartman M;Miao H;Chia KS;Chan CW;Fasching PA;Hein A;Beckmann MW;Haeberle L;Brenner H;Dieffenbach AK;Arndt V;Stegmaier C;Ashworth A;Orr N;Schoemaker MJ;Swerdlow AJ;Brinton L;Garcia-Closas M;Zheng W;Halverson SL;Shrubsole M;Long J;Goldberg MS;Labrèche F;Dumont M;Winqvist R;Pylkäs K;Jukkola-Vuorinen A;Grip M;Brauch H;Hamann U;Brüning T;GENICA Network;Radice P;Peterlongo P;Manoukian S;Bernard L;Bogdanova NV;Dörk T;Mannermaa A;Kataja V;Kosma VM;Hartikainen JM;Devilee P;Tollenaar RA;Seynaeve C;Van Asperen CJ;Jakubowska A;Lubinski J;Jaworska K;Huzarski T;Sangrajrang S;Gaborieau V;Brennan P;McKay J;Slager S;Toland AE;Ambrosone CB;Yannoukakos D;Kabisch M;Torres D;Neuhausen SL;Anton-Culver H;Luccarini C;Baynes C;Ahmed S;Healey CS;Tessier DC;Vincent D;Bacot F;Pita G;Alonso MR;Álvarez N;Herrero D;Simard J;Pharoah PP;Kraft P;Dunning AM;Chenevix-Trench G;Hall P;Easton DF
通讯作者：
Easton DF