Michael Datto

Overview:

Dr. Datto is an AP/CP/MGP board certified pathologist who specializes in molecular pathology. He is the Associate Vice President for Duke University Health System Clinical Laboratories, the Vice Chair for Clinical Pathology and Medical Director for Duke University Health System Clinical Laboratories.  

In these roles, he is responsible for maintaining the standards of the College of American Pathologists and CLIA/CMS within all Clinical Laboratories at Duke.  Specifically, Dr. Datto oversees clinical testing and reporting, develops quality management systems and proficiency testing programs, provides consultation with ordering physicians, ensures educational programs, develops strategic plans that are in line with the needs of our patient population, physicians and health system leadership, coordinates research and development, ensures adequate and appropriately trained personnel, and provides profession interpretation for molecular diagnostic testing including the wide range of PCR, quantitative PCR, sequencing and FISH based tests for inherited genetic diseases, hematologic malignancies, solid tumors and infectious diseases.

Dr. Datto also serves as the chair of the Accreditation Committee (AC) for the College of American Pathologists (CAP).  The CAP is the largest accreditor of hospital based laboratories in the US and serves as a ‘deemed entity’ by the Center for Medicare Services. In his role of chair of the AC, Dr. Datto oversees the committee that makes clinical accreditation decisions for approximately 7,000 clinical domestic and international laboratories.

Finally, Dr. Datto has an active academic program developing data system to aggregate, normalize and utilize high complexity and high volume laboratory data.  Dr. Datto and his team have developed the Molecular Registry of Tumors (Mr.T); a software solution that supports clinical trials matching, engagement with the AACR GENIE Project and the Molecular Tumor Board for Duke University Health System.  The ultimate goal of this work is to ensure that the vast amount of laboratory data generated on our Duke patients can be put to use, driving better patient care, research and education.

Positions:

Associate Professor of Pathology

Pathology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

B.A. 1991

Johns Hopkins University

Ph.D. 1998

Duke University

M.D. 1999

Duke University

Post-Doctoral Fellow, Pharmacology

Duke University

Resident, Pathology

Duke University

Grants:

Non Muscle Myosin II Contractility Putatively Regulates Scar Contracture

Administered By
Surgery
Awarded By
National Institutes of Health
Role
Collaborator
Start Date
End Date

Publications:

Next-Generation Sequencing Concordance Analysis of Comprehensive Solid Tumor Profiling between a Centralized Specialty Laboratory and the Decentralized Personal Genome Diagnostics elio Tissue Complete Kitted Solution.

Genomic tumor profiling by next-generation sequencing (NGS) allows for large-scale tumor testing to inform targeted cancer therapies and immunotherapies, and to identify patients for clinical trials. These tests are often underutilized in patients with late-stage solid tumors and are typically performed in centralized specialty laboratories, thereby limiting access to these complex tests. Personal Genome Diagnostics Inc., elio tissue complete NGS solution is a comprehensive DNA-to-report kitted assay and bioinformatics solution. Comparison of 147 unique specimens from >20 tumor types was performed using the elio tissue complete solution and Foundation Medicine's FoundationOne test, which is of similar size and gene content. The analytical performance of all genomic variant types was evaluated. In general, the overall mutational profile is highly concordant between the two assays, with agreement in sequence variants reported between panels demonstrating >95% positive percentage agreement for single-nucleotide variants and insertions/deletions in clinically actionable genes. Both copy number alterations and gene translocations showed 80% to 83% positive percentage agreement, whereas tumor mutation burden and microsatellite status showed a high level of concordance across a range of mutation loads and tumor types. The Personal Genome Diagnostics Inc., elio tissue complete assay is comparable to the FoundationOne test and will allow more laboratories to offer a diagnostic NGS assay in house, which will ultimately reduce time to result and increase the number of patients receiving molecular genomic profiling and personalized treatment.
Authors
Deak, KL; Jackson, JB; Valkenburg, KC; Keefer, LA; Robinson Gerding, KM; Angiuoli, SV; Datto, MB; McCall, SJ
URI
https://scholars.duke.edu/individual/pub1489694
PMID
34314880
Source
pubmed
Published In
J Mol Diagn
Volume
23
Published Date
Start Page
1324
End Page
1333
DOI
10.1016/j.jmoldx.2021.07.004

Implementation of a Molecular Tumor Registry to Support the Adoption of Precision Oncology Within an Academic Medical Center: The Duke University Experience.

Comprehensive genomic profiling to inform targeted therapy selection is a central part of oncology care. However, the volume and complexity of alterations uncovered through genomic profiling make it difficult for oncologists to choose the most appropriate therapy for their patients. Here, we present a solution to this problem, The Molecular Registry of Tumors (MRT) and our Molecular Tumor Board (MTB). PATIENTS AND METHODS: MRT is an internally developed system that aggregates and normalizes genomic profiling results from multiple sources. MRT serves as the foundation for our MTB, a team that reviews genomic results for all Duke University Health System cancer patients, provides notifications for targeted therapies, matches patients to biomarker-driven trials, and monitors the molecular landscape of tumors at our institution. RESULTS: Among 215 patients reviewed by our MTB over a 6-month period, we identified 176 alterations associated with therapeutic sensitivity, 15 resistance alterations, and 51 alterations with potential germline implications. Of reviewed patients, 17% were subsequently treated with a targeted therapy. For 12 molecular therapies approved during the course of this work, we identified between two and 71 patients who could qualify for treatment based on retrospective MRT data. An analysis of 14 biomarker-driven clinical trials found that MRT successfully identified 42% of patients who ultimately enrolled. Finally, an analysis of 4,130 comprehensive genomic profiles from 3,771 patients revealed that the frequency of clinically significant therapeutic alterations varied from approximately 20% to 70% depending on the tumor type and sequencing test used. CONCLUSION: With robust informatics tools, such as MRT, and the right MTB structure, a precision cancer medicine program can be developed, which provides great benefit to providers and patients with cancer.
Authors
Green, MF; Bell, JL; Hubbard, CB; McCall, SJ; McKinney, MS; Riedel, JE; Menendez, CS; Abbruzzese, JL; Strickler, JH; Datto, MB
MLA Citation
URI
https://scholars.duke.edu/individual/pub1497103
PMID
34568718
Source
pubmed
Published In
Jco Precision Oncology
Volume
5
Published Date
DOI
10.1200/PO.21.00030

Predictive Value of Combining Biomarkers for Clinical Outcomes in Advanced Non-Small Cell Lung Cancer Patients Receiving Immune Checkpoint Inhibitors.

INTRODUCTION: A high tumor mutational burden (TMB) (≥10 mut/Mb) has been associated with improved clinical benefit in non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICI) and is a tumor agnostic indication for pembrolizumab across tumor types. We explored whether combining TMB with programmed cell death ligand 1 (PD-L1) and pretreatment neutrophil-lymphocyte ratio (NLR) was associated with improved outcomes in ICI-treated NSCLC. METHODS: We retrospectively analyzed patients treated with ICI with Foundation One genomic testing, including TMB. Optimal cutoff for prediction of response by TMB was determined by receiver operating characteristic analysis, and area under the curve (AUC) was calculated for all 3 biomarkers and combinations. Cox model was used to assess prognostic factors of overall survival (OS) and time to progression (TTP). Survival cutoffs calculated with Kaplan-Meier survival curves were TMB ≥10 mut/Mb, PD-L1 ≥50%, NLR <5, and combined biomarkers. RESULTS: Data from 88 patients treated were analyzed. The optimal TMB cutoff was 9.24 mut/Mb (AUC, 0.62), improving to 0.74 combining all 3 biomarkers. Adjusted Cox model showed that TMB ≥10 mut/Mb was an independent factor of OS (hazard ratio [HR], 0.31; 95% confidence interval; 0.14-0.69; P = .004) and TTP (HR, 0.46; 95% CI, 0.27-0.77; P = .003). The combination of high TMB with positive PD-L1 and low NLR was significantly associated with OS (P = .038) but not TTP. CONCLUSIONS: TMB has modest predictive and prognostic power for clinical outcomes after ICI treatment. The combination of TMB, PD-L1, and NLR status improves this power.
Authors
Kao, C; Powers, E; Wu, Y; Datto, MB; Green, MF; Strickler, JH; Ready, NE; Zhang, T; Clarke, JM
MLA Citation
URI
https://scholars.duke.edu/individual/pub1481799
PMID
33972172
Source
pubmed
Published In
Clin Lung Cancer
Published Date
DOI
10.1016/j.cllc.2021.03.017

Assessment of an Online Tool to Simulate the Effect of Pooled Testing for SARS-CoV-2 Detection in Asymptomatic and Symptomatic Populations.

Authors
Polage, CR; Lee, MJ; Hubbard, C; Rehder, C; Cardona, D; Denny, T; Datto, MB
MLA Citation
Polage, Christopher R., et al. “Assessment of an Online Tool to Simulate the Effect of Pooled Testing for SARS-CoV-2 Detection in Asymptomatic and Symptomatic Populations.Jama Netw Open, vol. 3, no. 12, Dec. 2020, p. e2031517. Pubmed, doi:10.1001/jamanetworkopen.2020.31517.
URI
https://scholars.duke.edu/individual/pub1468639
PMID
33301014
Source
pubmed
Published In
Jama Network Open
Volume
3
Published Date
Start Page
e2031517
DOI
10.1001/jamanetworkopen.2020.31517

Implementation of a Pooled Surveillance Testing Program for Asymptomatic SARS-CoV-2 Infections on a College Campus - Duke University, Durham, North Carolina, August 2-October 11, 2020.

On university campuses and in similar congregate environments, surveillance testing of asymptomatic persons is a critical strategy (1,2) for preventing transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). All students at Duke University, a private research university in Durham, North Carolina, signed the Duke Compact (3), agreeing to observe mandatory masking, social distancing, and participation in entry and surveillance testing. The university implemented a five-to-one pooled testing program for SARS-CoV-2 using a quantitative, in-house, laboratory-developed, real-time reverse transcription-polymerase chain reaction (RT-PCR) test (4,5). Pooling of specimens to enable large-scale testing while minimizing use of reagents was pioneered during the human immunodeficiency virus pandemic (6). A similar methodology was adapted for Duke University's asymptomatic testing program. The baseline SARS-CoV-2 testing plan was to distribute tests geospatially and temporally across on- and off-campus student populations. By September 20, 2020, asymptomatic testing was scaled up to testing targets, which include testing for residential undergraduates twice weekly, off-campus undergraduates one to two times per week, and graduate students approximately once weekly. In addition, in response to newly identified positive test results, testing was focused in locations or within cohorts where data suggested an increased risk for transmission. Scale-up over 4 weeks entailed redeploying staff members to prepare 15 campus testing sites for specimen collection, developing information management tools, and repurposing laboratory automation to establish an asymptomatic surveillance system. During August 2-October 11, 68,913 specimens from 10,265 graduate and undergraduate students were tested. Eighty-four specimens were positive for SARS-CoV-2, and 51% were among persons with no symptoms. Testing as a result of contact tracing identified 27.4% of infections. A combination of risk-reduction strategies and frequent surveillance testing likely contributed to a prolonged period of low transmission on campus. These findings highlight the importance of combined testing and contact tracing strategies beyond symptomatic testing, in association with other preventive measures. Pooled testing balances resource availability with supply-chain disruptions, high throughput with high sensitivity, and rapid turnaround with an acceptable workload.
Authors
Denny, TN; Andrews, L; Bonsignori, M; Cavanaugh, K; Datto, MB; Deckard, A; DeMarco, CT; DeNaeyer, N; Epling, CA; Gurley, T; Haase, SB; Hallberg, C; Harer, J; Kneifel, CL; Lee, MJ; Louzao, R; Moody, MA; Moore, Z; Polage, CR; Puglin, J; Spotts, PH; Vaughn, JA; Wolfe, CR
MLA Citation
Denny, Thomas N., et al. “Implementation of a Pooled Surveillance Testing Program for Asymptomatic SARS-CoV-2 Infections on a College Campus - Duke University, Durham, North Carolina, August 2-October 11, 2020.Mmwr Morb Mortal Wkly Rep, vol. 69, no. 46, Nov. 2020, pp. 1743–47. Pubmed, doi:10.15585/mmwr.mm6946e1.
URI
https://scholars.duke.edu/individual/pub1464818
PMID
33211678
Source
pubmed
Published In
Mmwr. Morbidity and Mortality Weekly Report
Volume
69
Published Date
Start Page
1743
End Page
1747
DOI
10.15585/mmwr.mm6946e1