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Browsing by Author "Henry, Jill E."
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Item Characterizing the heterogeneity of triple-negative breast cancers using microdissected normal ductal epithelium and RNA-sequencing(Springer, 2014-01) Radovich, Milan; Clare, Susan E.; Atale, Rutuja; Pardo, Ivanesa; Hancock, Bradley A.; Solzak, Jeffrey P.; Kassem, Nawal; Mathieson, Theresa; V. Storniolo, Anna Maria; Rufenbarger, Connie; Lillemoe, Heather A.; Blosser, Rachel J.; Choi, Mi Ran; Sauder, Candice A.; Doxey, Diane; Henry, Jill E.; Hilligoss, Eric E.; Sakarya, Onur; Hyland, Fiona C.; Hickenbotham, Matthew; Zhu, Jin; Glasscock, Jarret; Badve, Sunil; Ivan, Mircea; Liu, Yunlong; Sledge, George W.; Schneider, Bryan P.; Department of Surgery, IU School of MedicineTriple-negative breast cancers (TNBCs) are a heterogeneous set of tumors defined by an absence of actionable therapeutic targets (ER, PR, and HER-2). Microdissected normal ductal epithelium from healthy volunteers represents a novel comparator to reveal insights into TNBC heterogeneity and to inform drug development. Using RNA-sequencing data from our institution and The Cancer Genome Atlas (TCGA) we compared the transcriptomes of 94 TNBCs, 20 microdissected normal breast tissues from healthy volunteers from the Susan G. Komen for the Cure Tissue Bank, and 10 histologically normal tissues adjacent to tumor. Pathway analysis comparing TNBCs to optimized normal controls of microdissected normal epithelium versus classic controls composed of adjacent normal tissue revealed distinct molecular signatures. Differential gene expression of TNBC compared with normal comparators demonstrated important findings for TNBC-specific clinical trials testing targeted agents; lack of over-expression for negative studies and over-expression in studies with drug activity. Next, by comparing each individual TNBC to the set of microdissected normals, we demonstrate that TNBC heterogeneity is attributable to transcriptional chaos, is associated with non-silent DNA mutational load, and explains transcriptional heterogeneity in addition to known molecular subtypes. Finally, chaos analysis identified 146 core genes dysregulated in >90 % of TNBCs revealing an over-expressed central network. In conclusion, use of microdissected normal ductal epithelium from healthy volunteers enables an optimized approach for studying TNBC and uncovers biological heterogeneity mediated by transcriptional chaos.Item DNA methylation age is elevated in breast tissue of healthy women(Springer, 2017-07) Sehl, Mary E.; Henry, Jill E.; Storniolo, Anna Maria; Ganz, Patricia A.; Horvath, Steve; Medicine, School of MedicineBACKGROUND: Limited evidence suggests that female breast tissue ages faster than other parts of the body according to an epigenetic biomarker of aging known as the "epigenetic clock." However, it is unknown whether breast tissue samples from healthy women show a similar accelerated aging effect relative to other tissues, and what could drive this acceleration. The goal of this study is to validate our initial finding of advanced DNA methylation (DNAm) age in breast tissue, by directly comparing it to that of peripheral blood tissue from the same individuals, and to do a preliminary assessment of hormonal factors that could explain the difference. METHODS: We utilized n = 80 breast and 80 matching blood tissue samples collected from 40 healthy female participants of the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center who donated these samples at two time points spaced at least a year apart. DNA methylation levels (Illumina 450K platform) were used to estimate the DNAm age. RESULTS: DNAm age was highly correlated with chronological age in both peripheral blood (r = 0.94, p < 0.0001) and breast tissues (r = 0.86, p < 0.0001). A measure of epigenetic age acceleration (age-adjusted DNAm Age) was substantially increased in breast relative to peripheral blood tissue (p = 1.6 × 10-11). The difference between DNAm age of breast and blood decreased with advancing chronologic age (r = -0.53, p = 4.4 × 10-4). CONCLUSIONS: Our data clearly demonstrate that female breast tissue has a higher epigenetic age than blood collected from the same subject. We also observe that the degree of elevation in breast diminishes with advancing age. Future larger studies will be needed to examine associations between epigenetic age acceleration and cumulative hormone exposure.Item The effects of lifetime estrogen exposure on breast epigenetic age(American Association for Cancer Research, 2021) Sehl, Mary E.; Henry, Jill E.; Storniolo, Anna M.; Horvath, Steve; Ganz, Patricia A.; Medicine, School of MedicineBackground: Estrogens are thought to contribute to breast cancer risk through cell cycling and accelerated breast aging. We hypothesize that lifetime estrogen exposure drives early epigenetic breast aging observed in healthy women. In this study, we examined associations between hormonal factors and epigenetic aging measures in healthy breast tissues. Methods: We extracted DNA from breast tissue specimens from 192 healthy female donors to the Susan G. Komen Tissue Bank at the Indiana University Simon Cancer Center. Methylation experiments were performed using the Illumina EPIC 850K array platform. Age-adjusted regression models were used to examine for associations between factors related to estrogen exposure and five DNA methylation-based estimates: Grim age, pan-tissue age, Hannum age, phenotypic age, and skin and blood clock age. Results: Women were aged 19-90 years, with 95 premenopausal, and 97 nulliparous women. The age difference (Grim age - chronologic age) was higher at earlier ages close to menarche. We found significant associations between earlier age at menarche and age-adjusted accelerations according to the Grim clock, the skin and blood clock, and between higher body mass index (BMI) and age-adjusted accelerations in the Grim clock, Hannum clock, phenotypic clock, and skin and blood clock. Conclusions: Earlier age at menarche and higher BMI are associated with elevations in DNA methylation-based age estimates in healthy breast tissues, suggesting that cumulative estrogen exposure drives breast epigenetic aging. Impact: Epigenetic clock measures may help advance inquiry into the relationship between accelerated breast tissue aging and an elevated incidence of breast cancer in younger women.Item The impact of reproductive factors on DNA methylation-based telomere length in healthy breast tissue(Springer Nature, 2022-04-13) Sehl, Mary E.; Henry, Jill E.; Storniolo, Anna Maria; Horvath, Steve; Ganz, Patricia A.; Medicine, School of MedicineEstrogen promotes breast tissue proliferation and telomerase activation. We investigated the effects of reproductive history on cell cycling and telomere length using a DNA methylation-based estimate of telomere length (DNAmTL) in breast and blood from healthy women donors. We demonstrate that DNAmTL is shorter in breast than in blood, and that nulliparous women have longer age-adjusted DNAmTL in both breast and blood, potentially explaining their higher risk of breast cancer.Item Serum Hormone Levels and Normal Breast Histology Among Premenopausal Women(Springer Nature, 2022) Sherman, Mark E.; de Bel, Thomas; Heckman, Michael G.; White, Launia J.; Ogony, Joshua; Stallings-Mann, Melody; Hilton, Tracy; Degnim, Amy C.; Vierkant, Robert A.; Hoskin, Tanya; Jensen, Matthew R.; Pacheco-Spann, Laura; Henry, Jill E.; Storniolo, Anna Maria; Carter, Jodi M.; Winham, Stacey J.; Radisky, Derek C.; van der Laak, Jeroenpeop; Medicine, School of MedicinePurpose: Breast terminal duct lobular units (TDLUs) are the main source of breast cancer (BC) precursors. Higher serum concentrations of hormones and growth factors have been linked to increased TDLU numbers and to elevated BC risk, with variable effects by menopausal status. We assessed associations of circulating factors with breast histology among premenopausal women using artificial intelligence (AI) and preliminarily tested whether parity modifies associations. Methods: Pathology AI analysis was performed on 316 digital images of H&E-stained sections of normal breast tissues from Komen Tissue Bank donors ages ≤ 45 years to assess 11 quantitative metrics. Associations of circulating factors with AI metrics were assessed using regression analyses, with inclusion of interaction terms to assess effect modification. Results: Higher prolactin levels were related to larger TDLU area (p < 0.001) and increased presence of adipose tissue proximate to TDLUs (p < 0.001), with less significant positive associations for acini counts (p = 0.012), dilated acini (p = 0.043), capillary area (p = 0.014), epithelial area (p = 0.007), and mononuclear cell counts (p = 0.017). Testosterone levels were associated with increased TDLU counts (p < 0.001), irrespective of parity, but associations differed by adipose tissue content. AI data for TDLU counts generally agreed with prior visual assessments. Conclusion: Among premenopausal women, serum hormone levels linked to BC risk were also associated with quantitative features of normal breast tissue. These relationships were suggestively modified by parity status and tissue composition. We conclude that the microanatomic features of normal breast tissue may represent a marker of BC risk.Item Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence(BMC, 2022-07-11) Ogony, Joshua; de Bel, Thomas; Radisky, Derek C.; Kachergus, Jennifer; Thompson, E. Aubrey; Degnim, Amy C.; Ruddy, Kathryn J.; Hilton, Tracy; Stallings‑Mann, Melody; Vachon, Celine; Hoskin, Tanya L.; Heckman, Michael G.; Vierkant, Robert A.; White, Launia J.; Moore, Raymond M.; Carter, Jodi; Jensen, Matthew; Pacheco‑Spann, Laura; Henry, Jill E.; Storniolo, Anna Maria; Winham, Stacey J.; van der Laak, Jeroen; Sherman, Mark E.; Medicine, School of MedicineBackground: Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described. Methods: Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors ≤ 45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean "capillary" area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fisher's exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [recent birth: ≤ 5 years versus remote birth: > 5 years]) using multivariable regression models. Results: Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p < 0.001). Differences in TDLU counts and average acini size persisted for > 5 years postpartum, whereas increases in immune cells were most marked ≤ 5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. Conclusions: Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.