Amy Hutchinson
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Amy Hutchinson has a total of 98 co-authors. Here are the top co-authors by number of shared publications:
- Belynda Hicks
Division of Cancer Epidemiology and Genetics, National Cancer Institute , Rockville, MD
5 shared publications - Kristine Jones
Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
3 shared publications - Stephen J. Chanock
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, USA
3 shared publications - Bin Zhu
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, USA
2 shared publications - Hela Koka
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
2 shared publications - Jianxin Shi
Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, USA
2 shared publications
Latest Publications
- Open Access
Rare Germline Variants in Chordoma-Related Genes and Chordoma Susceptibility
Background: Chordoma is a rare bone cancer with an unknown etiology. TBXT is the only chordoma susceptibility gene identified to date; germline single nucleotide variants and copy number variants in TBXT have been associated with chordoma susceptibility in familial and sporadic chordoma. However, the genetic susceptibility of chordoma remains largely unknown. In this study, we investigated rare germline genetic variants in genes involved in TBXT/chordoma-related signaling pathways and other biological processes in chordoma patients from North America and China. Methods: We identified variants that were very rare in general population and internal control datasets and showed evidence for pathogenicity in 265 genes in a whole exome sequencing (WES) dataset of 138 chordoma patients of European ancestry and in a whole genome sequencing (WGS) dataset of 80 Chinese patients with skull base chordoma. Results: Rare and likely pathogenic variants were identified in 32 of 138 European ancestry patients (23%), including genes that are part of notochord development, PI3K/AKT/mTOR, Sonic Hedgehog, SWI/SNF complex and mesoderm development pathways. Rare pathogenic variants in COL2A1, EXT1, PDK1, LRP2, TBXT and TSC2, among others, were also observed in Chinese patients. Conclusion: We identified several rare loss-of-function and predicted deleterious missense variants in germline DNA from patients with chordoma, which may influence chordoma predisposition and reflect a complex susceptibility, warranting further investigation in large studies.
Open AccessRare Germline Variants in Chordoma-Related Genes and Chordoma Susceptibility
Background: Chordoma is a rare bone cancer with an unknown etiology. TBXT is the only chordoma susceptibility gene identified to date; germline single nucleotide variants and copy number variants in TBXT have been associated with chordoma susceptibility in familial and sporadic chordoma. However, the genetic susceptibility of chordoma remains largely unknown. In this study, we investigated rare germline genetic variants in genes involved in TBXT/chordoma-related signaling pathways and other biological processes in chordoma patients from North America and China. Methods: We identified variants that were very rare in general population and internal control datasets and showed evidence for pathogenicity in 265 genes in a whole exome sequencing (WES) dataset of 138 chordoma patients of European ancestry and in a whole genome sequencing (WGS) dataset of 80 Chinese patients with skull base chordoma. Results: Rare and likely pathogenic variants were identified in 32 of 138 European ancestry patients (23%), including genes that are part of notochord development, PI3K/AKT/mTOR, Sonic Hedgehog, SWI/SNF complex and mesoderm development pathways. Rare pathogenic variants in COL2A1, EXT1, PDK1, LRP2, TBXT and TSC2, among others, were also observed in Chinese patients. Conclusion: We identified several rare loss-of-function and predicted deleterious missense variants in germline DNA from patients with chordoma, which may influence chordoma predisposition and reflect a complex susceptibility, warranting further investigation in large studies.
- Open Access
- 17 May 2019
- Published by Springer Nature in Breast Cancer Research
- Vol. 21 (1) , 1-9
Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies
Background: Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods: We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/−), and time since blood collection (< 5, 5–10, > 10 years). The false discovery rate (q value) was used to account for multiple testing. Results: The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions: Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.
- 17 May 2019
- Published by Springer Nature in Breast Cancer Research
- Vol. 21 (1) , 1-9
Open AccessBlood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies
Background: Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods: We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis (< 50, ≥ 50), estrogen receptor (ER) status (+/−), and time since blood collection (< 5, 5–10, > 10 years). The false discovery rate (q value) was used to account for multiple testing. Results: The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions: Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.
- Open Access
Immune gene expression profiling reveals heterogeneity in luminal breast tumors
Disease heterogeneity of immune gene expression patterns of luminal breast cancer (BC) has not been well studied. We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 Asian luminal BC patients and identified three distinct immune subtypes. Tumors in one subtype exhibited signs of T-cell activation, lower ESR1/ESR2 expression ratio and higher expression of immune checkpoint genes, nonsynonymous mutation burden, APOBEC -signature mutations, and increasing body mass index compared to other luminal tumors. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in cases drawn from The Cancer Genome Atlas and a Korean breast cancer study. Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification.
Open AccessImmune gene expression profiling reveals heterogeneity in luminal breast tumors
Disease heterogeneity of immune gene expression patterns of luminal breast cancer (BC) has not been well studied. We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 Asian luminal BC patients and identified three distinct immune subtypes. Tumors in one subtype exhibited signs of T-cell activation, lower ESR1/ESR2 expression ratio and higher expression of immune checkpoint genes, nonsynonymous mutation burden, APOBEC -signature mutations, and increasing body mass index compared to other luminal tumors. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in cases drawn from The Cancer Genome Atlas and a Korean breast cancer study. Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification.
- 1 May 2018
- Published by Elsevier in Gastroenterology
- Vol. 154 (6)
Mo1923 - Prospective Cohort Study of the Oral Microbiota and Colorectal Cancer Risk
- 1 May 2018
- Published by Elsevier in Gastroenterology
- Vol. 154 (6)
Mo1923 - Prospective Cohort Study of the Oral Microbiota and Colorectal Cancer Risk
- Open Access
- 29 May 2011
- Published by Springer Nature in BMC Cancer
- Vol. 11 (1) , 209
A comprehensive candidate gene approach identifies genetic variation associated with osteosarcoma
Osteosarcoma (OS) is a bone malignancy which occurs primarily in adolescents. Since it occurs during a period of rapid growth, genes important in bone formation and growth are plausible modifiers of risk. Genes involved in DNA repair and ribosomal function may contribute to OS pathogenesis, because they maintain the integrity of critical cellular processes. We evaluated these hypotheses in an OS association study of genes from growth/hormone, bone formation, DNA repair, and ribosomal pathways. We evaluated 4836 tag-SNPs across 255 candidate genes in 96 OS cases and 1426 controls. Logistic regression models were used to estimate the odds ratios (OR) and 95% confidence intervals (CI). Twelve SNPs in growth or DNA repair genes were significantly associated with OS after Bonferroni correction. Four SNPs in the DNA repair gene FANCM (ORs 1.9-2.0, P = 0.003-0.004) and 2 SNPs downstream of the growth hormone gene GH1 (OR 1.6, P = 0.002; OR 0.5, P = 0.0009) were significantly associated with OS. One SNP in the region of each of the following genes was significant: MDM2, MPG, FGF2, FGFR3, GNRH2, and IGF1. Our results suggest that several SNPs in biologically plausible pathways are associated with OS. Larger studies are required to confirm our findings.
- 29 May 2011
- Published by Springer Nature in BMC Cancer
- Vol. 11 (1) , 209
Open AccessA comprehensive candidate gene approach identifies genetic variation associated with osteosarcoma
Osteosarcoma (OS) is a bone malignancy which occurs primarily in adolescents. Since it occurs during a period of rapid growth, genes important in bone formation and growth are plausible modifiers of risk. Genes involved in DNA repair and ribosomal function may contribute to OS pathogenesis, because they maintain the integrity of critical cellular processes. We evaluated these hypotheses in an OS association study of genes from growth/hormone, bone formation, DNA repair, and ribosomal pathways. We evaluated 4836 tag-SNPs across 255 candidate genes in 96 OS cases and 1426 controls. Logistic regression models were used to estimate the odds ratios (OR) and 95% confidence intervals (CI). Twelve SNPs in growth or DNA repair genes were significantly associated with OS after Bonferroni correction. Four SNPs in the DNA repair gene FANCM (ORs 1.9-2.0, P = 0.003-0.004) and 2 SNPs downstream of the growth hormone gene GH1 (OR 1.6, P = 0.002; OR 0.5, P = 0.0009) were significantly associated with OS. One SNP in the region of each of the following genes was significant: MDM2, MPG, FGF2, FGFR3, GNRH2, and IGF1. Our results suggest that several SNPs in biologically plausible pathways are associated with OS. Larger studies are required to confirm our findings.
- Open Access
- 28 November 2009
- Published by Springer Nature in BMC Genomics
- Vol. 10 (1) , 561
High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays
Background: Single nucleotide polymorphisms (SNPs) have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs) with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals). Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed. Results: We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC) - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours. Conclusion: Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs), which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA) studies.
- 28 November 2009
- Published by Springer Nature in BMC Genomics
- Vol. 10 (1) , 561
Open AccessHigh-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays
Background: Single nucleotide polymorphisms (SNPs) have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs) with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals). Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed. Results: We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC) - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours. Conclusion: Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs), which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA) studies.