Holly Dressman

Positions:

Research Professor in Molecular Genetics and Microbiology

Molecular Genetics and Microbiology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

B.S. 1988

North Carolina State University

Ph.D. 1994

Pennsylvania State University

Postdoctoral Fellow, Molecular Genetics

NIEHS

Grants:

Biodosimetry High-Throughput Test RFP-16-100-SOL-00010

Administered By
Medicine, Hematologic Malignancies and Cellular Therapy
Awarded By
DxTerity Diagnostics
Role
Co Investigator
Start Date
End Date

Point of Care Biodosimeter

Administered By
Medicine, Hematologic Malignancies and Cellular Therapy
Awarded By
Department of Health and Human Services
Role
Co Investigator
Start Date
End Date

Intellectual Property Challenges for the Development of Genomic Diagnostics

Administered By
University Institutes and Centers
Awarded By
National Institutes of Health
Role
Collaborator
Start Date
End Date

Novel Zebrafish Models to Study Toxicity of PCBs and Pesticides During Pregnancy

Administered By
Biomedical Engineering
Awarded By
National Institutes of Health
Role
Advisor
Start Date
End Date

Neurosciences Microarray Center

Administered By
Neurobiology
Awarded By
National Institutes of Health
Role
Mircroarray Manager
Start Date
End Date

Publications:

Rationale and design of "Hearts & Parks": study protocol for a pragmatic randomized clinical trial of an integrated clinic-community intervention to treat pediatric obesity.

BACKGROUND: The prevalence of child and adolescent obesity and severe obesity continues to increase despite decades of policy and research aimed at prevention. Obesity strongly predicts cardiovascular and metabolic disease risk; both begin in childhood. Children who receive intensive behavioral interventions can reduce body mass index (BMI) and reverse disease risk. However, delivering these interventions with fidelity at scale remains a challenge. Clinic-community partnerships offer a promising strategy to provide high-quality clinical care and deliver behavioral treatment in local park and recreation settings. The Hearts & Parks study has three broad objectives: (1) evaluate the effectiveness of the clinic-community model for the treatment of child obesity, (2) define microbiome and metabolomic signatures of obesity and response to lifestyle change, and (3) inform the implementation of similar models in clinical systems. METHODS: Methods are designed for a pragmatic randomized, controlled clinical trial (n = 270) to test the effectiveness of an integrated clinic-community child obesity intervention as compared with usual care. We are powered to detect a difference in body mass index (BMI) between groups at 6 months, with follow up to 12 months. Secondary outcomes include changes in biomarkers for cardiovascular disease, psychosocial risk, and quality of life. Through collection of biospecimens (serum and stool), additional exploratory outcomes include microbiome and metabolomics biomarkers of response to lifestyle modification. DISCUSSION: We present the study design, enrollment strategy, and intervention details for a randomized clinical trial to measure the effectiveness of a clinic-community child obesity treatment intervention. This study will inform a critical area in child obesity and cardiovascular risk research-defining outcomes, implementation feasibility, and identifying potential molecular mechanisms of treatment response. CLINICAL TRIAL REGISTRATION: NCT03339440 .
Authors
Armstrong, SC; Windom, M; Bihlmeyer, NA; Li, JS; Shah, SH; Story, M; Zucker, N; Kraus, WE; Pagidipati, N; Peterson, E; Wong, C; Wiedemeier, M; Sibley, L; Berchuck, SI; Merrill, P; Zizzi, A; Sarria, C; Dressman, HK; Rawls, JF; Skinner, AC
MLA Citation
Armstrong, Sarah C., et al. “Rationale and design of "Hearts & Parks": study protocol for a pragmatic randomized clinical trial of an integrated clinic-community intervention to treat pediatric obesity.Bmc Pediatr, vol. 20, no. 1, June 2020, p. 308. Pubmed, doi:10.1186/s12887-020-02190-x.
URI
https://scholars.duke.edu/individual/pub1448801
PMID
32590958
Source
pubmed
Published In
Bmc Pediatrics
Volume
20
Published Date
Start Page
308
DOI
10.1186/s12887-020-02190-x

Molecular signatures that predict response to anthracycline-taxane based neoadjuvant chemotherapy

Authors
Blackwell, KL; Dressman, H; Olson, J; Rosen, E; Marcom, PK; Liotcheva, V; Jones, E; Vujaskovic, Z; Huper, G; Marks, J; Dewhirst, M; West, M; Nevins, J
MLA Citation
Blackwell, K. L., et al. “Molecular signatures that predict response to anthracycline-taxane based neoadjuvant chemotherapy.” Breast Cancer Research and Treatment, vol. 88, SPRINGER, 2004, pp. S22–S22.
URI
https://scholars.duke.edu/individual/pub865907
Source
wos
Published In
Breast Cancer Research and Treatment
Volume
88
Published Date
Start Page
S22
End Page
S22

Implementation of genomic predictors of chemotherapy response for guiding preoperative therapy in a prospective breast cancer trial.

11057 Background: Personalized approaches to breast cancer therapy depend on genomic assays. While assays based on fixed tissues offer greater convenience, the spectrum of biology interrogated is limited. Full-transcriptome assays using microarrays are more challenging, but have the advantage of providing multiple prognostic and predictive signatures in one assay. We have created a clinical infrastructure with the objective of obtaining full genome expression data on breast cancer samples as a clinical assay for use in a prospective trial. METHODS: "Performance of Genomic Expression Profiles to Direct the Use of Preoperative Chemotherapy for Early Stage Breast Cancer" is a prospective trial validating genomic signatures for predicting response to doxorubicin (A) or docetaxel (T) treatment in HER2 negative cancers. Fresh-frozen cores are reviewed by the study pathologist for tumor content. RNA is then extracted and probe generated to hybrize to an Affymetrix U133Plus2.0 microarray. Microarray data quality is determined using summary metrics for U133Plus2.0 arrays and principal component analysis (PCA) plots. The data is then used for predicting A or T sensitivity. RESULTS: Thirteen cancers have been analyzed in the context of the above trial. Histologic type was lobular for 1, and predominantly ductal for 12 (10 ER positive, 3 ER negative). Median tumor size was 3.4 cm (range, 1.8-5.7). Microarray analysis was successful on 11 tumors (84%), providing data of sufficient quality to make predictions of A and T sensitivity. One sample hybridization failed QC as detected by PCA analysis, and one sample had insufficient RNA. The median "tissue to array data" time and "study consent to initiation of treatment" time were 5 days (range, 3-8) and 14 days (range, 11-36), respectively. CONCLUSIONS: Our initial experience shows that full-genome expression analysis on frozen tumor using an Affymetrix platform is feasible as a clinical assay for breast cancer. The resulting data is being used in a prospective marker validation protocol for predicting chemosensitivity. The data can also be analyzed for a variety of other potential prognostic and predictive signatures for guiding therapy. No significant financial relationships to disclose.
Authors
Marcom, PK; Datto, MB; Barry, WT; Geradts, J; Foster, TL; Dressman, HK; Olson, J; Potti, A; Ginsburg, G; Nevins, JR
MLA Citation
URI
https://scholars.duke.edu/individual/pub1162750
PMID
27963164
Source
pubmed
Published In
Journal of Clinical Oncology
Volume
27
Published Date
Start Page
11057

Targeted approaches to the treatment of ovarian cancer.

Authors
Dressman, HK; Lancaster, JM; Chan, G; Cragun, JM; Bild, A; Sayer, R; Clarke, J; Marks, J; Potti, A; Nevins, JR; Berchuck, A
MLA Citation
Dressman, Holly K., et al. “Targeted approaches to the treatment of ovarian cancer.Cancer Research, vol. 66, no. 8, AMER ASSOC CANCER RESEARCH, 2006.
URI
https://scholars.duke.edu/individual/pub1365232
Source
wos
Published In
Cancer Research
Volume
66
Published Date

Integration of clinico-pathologic variables, mRNA, and microRNA profiles represents an optimal strategy to predict sensitivity to chemotherapeutic agents in breast cancer.

14567 A major challenge in oncology is the selection of the most effective chemotherapy agents for individual patients. This emphasizes the need to evaluate individual patients' probability of responding to each chemotherapeutic agent and thus limit the agents used to those most likely to be effective. Using gene expression data and corresponding drug sensitivity on the NCI-60 cell line panel, mRNA and miRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were first tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel (T), fluorouracil (F), adriamycin (A), and cyclophosphamide (C)) chemotherapy regimen. To further dissect the biology of chemotherapeutic resistance, we applied signatures of oncogenic pathway activation (Ras, Myc, E2F, beta-catenin, Src and PI3kinase). In our study, mRNA and miRNA profiles seem to represent critical mechanisms of resistance to cytotoxic agents. Specifically, we identified that certain miRNAs have unique biologic relevance, e.g. miR17, which with Myc promotes aggressive tumor growth, is associated with anthracycline resistance. The mRNA signatures for TFAC were validated in the dataset of 133 breast tumors (P=0.002, NPV=82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was independent of HER2 status but found to be greater in ER negative tumors (P=0.01), and triple negative 'basal' (P=0.03) tumors. Furthermore, we also show that the interplay between Myc and Rb/E2F pathways is critical to TFAC resistance. Finally, using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), a viable alternative therapy. Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding miRNA and mRNA expression profiles. We also present evidence to further support the concept that analysis of molecular variables presents a rational strategy to dissecting tumor biology and identifying alternative therapeutic opportunities. No significant financial relationships to disclose.
Authors
Salter, KH; Perez, BA; Acharya, CR; Walters, KS; Anguiano, A; Anders, CK; Dressman, HK; Marcom, PK; Nevins, JR; Potti, A
URI
https://scholars.duke.edu/individual/pub1161845
PMID
27949979
Source
pubmed
Published In
Journal of Clinical Oncology
Volume
26
Published Date
Start Page
14567