Author
Suleeporn Sangrajrang
Other affiliations: University of Cambridge
Bio: Suleeporn Sangrajrang is an academic researcher from University of Chicago. The author has contributed to research in topics: Breast cancer & Genome-wide association study. The author has an hindex of 31, co-authored 82 publications receiving 9683 citations. Previous affiliations of Suleeporn Sangrajrang include University of Cambridge.
Papers published on a yearly basis
Papers
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University of Cambridge1, National Institutes of Health2, University of Southern California3, International Agency for Research on Cancer4, Academia Sinica5, Princess Anne Hospital6, St Mary's Hospital7, University of London8, The Breast Cancer Research Foundation9, Wellcome Trust Sanger Institute10, Peter MacCallum Cancer Centre11, QIMR Berghofer Medical Research Institute12, University of Copenhagen13, Curie Institute14, Nofer Institute of Occupational Medicine15, University of Helsinki16, Seoul National University17, University of Ulsan18, Harvard University19, Karolinska Institutet20, Agency for Science, Technology and Research21, Hannover Medical School22, Leiden University23, Erasmus University Rotterdam24, University of Minnesota25, University of Sheffield26, Mayo Clinic27, VU University Amsterdam28, Carlos III Health Institute29, University of Melbourne30, Cancer Council New South Wales31, University of Otago32, Cancer Council Victoria33, University of Tübingen34, Bosch35, German Cancer Research Center36, University of Eastern Finland37
TL;DR: To identify further susceptibility alleles, a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls was conducted, followed by a third stage in which 30 single nucleotide polymorphisms were tested for confirmation.
Abstract: Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2.0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P,1027). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P,0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.
2,288 citations
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TL;DR: A meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, and identified 29,807 SNPs for further genotyping suggests that more than 1,000 additional loci are involved in breast cancer susceptibility.
Abstract: Breast cancer is the most common cancer among women Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC) The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10(-8)) Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility
1,048 citations
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Kyriaki Michailidou1, Kyriaki Michailidou2, Sara Lindström3, Sara Lindström4 +393 more•Institutions (127)
TL;DR: A genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry finds that heritability of Breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2–5-fold enriched relative to the genome- wide average.
Abstract: Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10-8. The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.
1,014 citations
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TL;DR: It is shown that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
Abstract: BACKGROUND: Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors. METHODS: We pooled tumor marker and epidemiological risk factor data from 35,568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case-case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case-control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided. RESULTS: In case-case analyses, of the epidemiological risk factors examined, early age at menarche (≤12 years) was less frequent in case patients with PR(-) than PR(+) tumors (P = .001). Nulliparity (P = 3 × 10(-6)) and increasing age at first birth (P = 2 × 10(-9)) were less frequent in ER(-) than in ER(+) tumors. Obesity (body mass index [BMI] ≥ 30 kg/m(2)) in younger women (≤50 years) was more frequent in ER(-)/PR(-) than in ER(+)/PR(+) tumors (P = 1 × 10(-7)), whereas obesity in older women (>50 years) was less frequent in PR(-) than in PR(+) tumors (P = 6 × 10(-4)). The triple-negative (ER(-)/PR(-)/HER2(-)) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6(+) and/or epidermal growth factor receptor [EGFR](+)) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case-control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER(+) or PR(+) tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors. CONCLUSIONS: This study shows that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.
619 citations
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University of Sheffield1, University of Cambridge2, National Institutes of Health3, Curie Institute4, Nofer Institute of Occupational Medicine5, University of Melbourne6, University of Otago7, Cancer Council Victoria8, University of London9, University of Copenhagen10, German Cancer Research Center11, University of Tübingen12, Bosch13, University of Ulm14, Hannover Medical School15, University of Helsinki16, International Agency for Research on Cancer17, QIMR Berghofer Medical Research Institute18, University of Eastern Finland19, Mayo Clinic20, Netherlands Cancer Institute21, Seoul National University22, University of Ulsan23, Karolinska Institutet24, Agency for Science, Technology and Research25, Carlos III Health Institute26, University of Minnesota27
TL;DR: It is demonstrated that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies, as well as the need for further studies to confirm putative genetic associations with breast cancer.
Abstract: The Breast Cancer Association Consortium (BCAC) has been established to conduct combined case-control analyses with augmented statistical power to try to confirm putative genetic associations with breast cancer. We genotyped nine SNPs for which there was some prior evidence of an association with breast cancer: CASP8 D302H (rs1045485), IGFBP3 -202 C --> A (rs2854744), SOD2 V16A (rs1799725), TGFB1 L10P (rs1982073), ATM S49C (rs1800054), ADH1B 3' UTR A --> G (rs1042026), CDKN1A S31R (rs1801270), ICAM5 V301I (rs1056538) and NUMA1 A794G (rs3750913). We included data from 9-15 studies, comprising 11,391-18,290 cases and 14,753-22,670 controls. We found evidence of an association with breast cancer for CASP8 D302H (with odds ratios (OR) of 0.89 (95% confidence interval (c.i.): 0.85-0.94) and 0.74 (95% c.i.: 0.62-0.87) for heterozygotes and rare homozygotes, respectively, compared with common homozygotes; P(trend) = 1.1 x 10(-7)) and weaker evidence for TGFB1 L10P (OR = 1.07 (95% c.i.: 1.02-1.13) and 1.16 (95% c.i.: 1.08-1.25), respectively; P(trend) = 2.8 x 10(-5)). These results demonstrate that common breast cancer susceptibility alleles with small effects on risk can be identified, given sufficiently powerful studies.
567 citations
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29 Sep 2017
TL;DR: Thank you very much for reading who classification of tumours of haematopoietic and lymphoid tissues, and maybe you have knowledge that, people have look hundreds of times for their chosen readings like this, but end up in malicious downloads.
Abstract: WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , WHO CLASSIFICATION OF TUMOURS OF HAEMATOPOIETIC AND LYMPHOID TISSUES , کتابخانه مرکزی دانشگاه علوم پزشکی تهران
13,835 citations
01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.
4,409 citations
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TL;DR: Gen expression profiles from 21 breast cancer data sets and identified 587 TNBC cases may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
Abstract: Triple-negative breast cancer (TNBC) is a highly diverse group of cancers, and subtyping is necessary to better identify molecular-based therapies. In this study, we analyzed gene expression (GE) profiles from 21 breast cancer data sets and identified 587 TNBC cases. Cluster analysis identified 6 TNBC subtypes displaying unique GE and ontologies, including 2 basal-like (BL1 and BL2), an immunomodulatory (IM), a mesenchymal (M), a mesenchymal stem–like (MSL), and a luminal androgen receptor (LAR) subtype. Further, GE analysis allowed us to identify TNBC cell line models representative of these subtypes. Predicted “driver” signaling pathways were pharmacologically targeted in these cell line models as proof of concept that analysis of distinct GE signatures can inform therapy selection. BL1 and BL2 subtypes had higher expression of cell cycle and DNA damage response genes, and representative cell lines preferentially responded to cisplatin. M and MSL subtypes were enriched in GE for epithelial-mesenchymal transition, and growth factor pathways and cell models responded to NVP-BEZ235 (a PI3K/mTOR inhibitor) and dasatinib (an abl/src inhibitor). The LAR subtype includes patients with decreased relapse-free survival and was characterized by androgen receptor (AR) signaling. LAR cell lines were uniquely sensitive to bicalutamide (an AR antagonist). These data may be useful in biomarker selection, drug discovery, and clinical trial design that will enable alignment of TNBC patients to appropriate targeted therapies.
4,215 citations
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TL;DR: This review focuses on biochemical concepts of lipidPeroxidation, production, metabolism, and signaling mechanisms of two main omega-6 fatty acids lipid peroxidation products: malondialdehyde (MDA) and, in particular, 4-hydroxy-2-nonenal (4-HNE), summarizing not only its physiological and protective function as signaling molecule stimulating gene expression and cell survival, but also its cytotoxic role inhibiting geneexpression and promoting cell death.
Abstract: Lipid peroxidation can be described generally as a process under which oxidants such as free radicals attack lipids containing carbon-carbon double bond(s), especially polyunsaturated fatty acids (PUFAs). Over the last four decades, an extensive body of literature regarding lipid peroxidation has shown its important role in cell biology and human health. Since the early 1970s, the total published research articles on the topic of lipid peroxidation was 98 (1970–1974) and has been increasing at almost 135-fold, by up to 13165 in last 4 years (2010–2013). New discoveries about the involvement in cellular physiology and pathology, as well as the control of lipid peroxidation, continue to emerge every day. Given the enormity of this field, this review focuses on biochemical concepts of lipid peroxidation, production, metabolism, and signaling mechanisms of two main omega-6 fatty acids lipid peroxidation products: malondialdehyde (MDA) and, in particular, 4-hydroxy-2-nonenal (4-HNE), summarizing not only its physiological and protective function as signaling molecule stimulating gene expression and cell survival, but also its cytotoxic role inhibiting gene expression and promoting cell death. Finally, overviews of in vivo mammalian model systems used to study the lipid peroxidation process, and common pathological processes linked to MDA and 4-HNE are shown.
3,647 citations
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Wellcome Trust Centre for Human Genetics1, University of Oxford2, University of Michigan3, Fred Hutchinson Cancer Research Center4, Duke University5, University of Ottawa6, Tufts University7, Foundation for Research & Technology – Hellas8, Boston Children's Hospital9, Harvard University10, Broad Institute11
TL;DR: This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
Abstract: The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
2,908 citations