Shannon McCall

Overview:

As Vice Chair for Translational Research in the Department of Pathology, I am involved in numerous translational cancer research projects that rely on the study of human biological samples.  I am the director of the Duke BioRepository & Precision Pathology Center (Duke BRPC), a shared resource of the School of Medicine and the Duke Cancer Institute.  I serve as the PI for the National Cancer Institute's Cooperative Human Tissue Network Southern Division (a five-year UM1 grant), which lives in the Duke BRPC.  My own area of research interest is gastrointestinal tract metaplasias and their relationship to carcinogenesis, particularly in the upper GI tract.

Positions:

Associate Professor of Pathology

Pathology
School of Medicine

Associate Professor in Surgery

Surgery, Surgical Sciences
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

B.S. 1996

North Carolina State University

M.D. 2000

Duke University

Anatomic and Clinical Pathology, American Board of Pathology (ABPath)

American Board of Pathology

Clinical Informatics, American Board of Pathology (ABPath)

American Board of Pathology

Resident, Pathology

Duke University

Chief Resident, Pathology

Duke University

Grants:

Mutation analysis of pap smear samples and associated tissues for ovarian cancer diagnostics

Administered By
Pathology
Awarded By
Genendeavor LLC
Role
Principal Investigator
Start Date
End Date

Cooperative Human Tissue Network Support through Duke's BioRepository & Precision Pathology Center

Administered By
Pathology
Awarded By
National Institutes of Health
Role
Principal Investigator
Start Date
End Date

The genetics of hepatosplenic T cell lymphoma

Administered By
Medicine, Hematologic Malignancies and Cellular Therapy
Awarded By
National Institutes of Health
Role
Co Investigator
Start Date
End Date

Empowering Duke's Precision Pathology Center with Quantitative Image Analysis to Support Discovery, Diagnostic Assay Development, and Immune Cell Monitoring

Administered By
Pathology
Awarded By
North Carolina Biotechnology Center
Role
Principal Investigator
Start Date
End Date

Lung Squamous Cell Carcinoma: Validation of Molecular Signatures of Prognosis

Awarded By
University of Colorado - Denver
Role
Pathologist
Start Date
End Date

Publications:

Patient-derived micro-organospheres enable clinical precision oncology.

Patient-derived xenografts (PDXs) and patient-derived organoids (PDOs) have been shown to model clinical response to cancer therapy. However, it remains challenging to use these models to guide timely clinical decisions for cancer patients. Here, we used droplet emulsion microfluidics with temperature control and dead-volume minimization to rapidly generate thousands of micro-organospheres (MOSs) from low-volume patient tissues, which serve as an ideal patient-derived model for clinical precision oncology. A clinical study of recently diagnosed metastatic colorectal cancer (CRC) patients using an MOS-based precision oncology pipeline reliably assessed tumor drug response within 14 days, a timeline suitable for guiding treatment decisions in the clinic. Furthermore, MOSs capture original stromal cells and allow T cell penetration, providing a clinical assay for testing immuno-oncology (IO) therapies such as PD-1 blockade, bispecific antibodies, and T cell therapies on patient tumors.
Authors
Ding, S; Hsu, C; Wang, Z; Natesh, NR; Millen, R; Negrete, M; Giroux, N; Rivera, GO; Dohlman, A; Bose, S; Rotstein, T; Spiller, K; Yeung, A; Sun, Z; Jiang, C; Xi, R; Wilkin, B; Randon, PM; Williamson, I; Nelson, DA; Delubac, D; Oh, S; Rupprecht, G; Isaacs, J; Jia, J; Chen, C; Shen, JP; Kopetz, S; McCall, S; Smith, A; Gjorevski, N; Walz, A-C; Antonia, S; Marrer-Berger, E; Clevers, H; Hsu, D; Shen, X
MLA Citation
Ding, Shengli, et al. “Patient-derived micro-organospheres enable clinical precision oncology.Cell Stem Cell, vol. 29, no. 6, June 2022, pp. 905-917.e6. Pubmed, doi:10.1016/j.stem.2022.04.006.
URI
https://scholars.duke.edu/individual/pub1520416
PMID
35508177
Source
pubmed
Published In
Cell Stem Cell
Volume
29
Published Date
Start Page
905
End Page
917.e6
DOI
10.1016/j.stem.2022.04.006

Automated next-generation profiling of genomic alterations in human cancers.

The lack of validated, distributed comprehensive genomic profiling assays for patients with cancer inhibits access to precision oncology treatment. To address this, we describe elio tissue complete, which has been FDA-cleared for examination of 505 cancer-related genes. Independent analyses of clinically and biologically relevant sequence changes across 170 clinical tumor samples using MSK-IMPACT, FoundationOne, and PCR-based methods reveals a positive percent agreement of >97%. We observe high concordance with whole-exome sequencing for evaluation of tumor mutational burden for 307 solid tumors (Pearson r = 0.95) and comparison of the elio tissue complete microsatellite instability detection approach with an independent PCR assay for 223 samples displays a positive percent agreement of 99%. Finally, evaluation of amplifications and translocations against DNA- and RNA-based approaches exhibits >98% negative percent agreement and positive percent agreement of 86% and 82%, respectively. These methods provide an approach for pan-solid tumor comprehensive genomic profiling with high analytical performance.
Authors
Keefer, LA; White, JR; Wood, DE; Gerding, KMR; Valkenburg, KC; Riley, D; Gault, C; Papp, E; Vollmer, CM; Greer, A; Hernandez, J; McGregor, PM; Zingone, A; Ryan, BM; Deak, K; McCall, SJ; Datto, MB; Prescott, JL; Thompson, JF; Cerqueira, GC; Jones, S; Simmons, JK; McElhinny, A; Dickey, J; Angiuoli, SV; Diaz, LA; Velculescu, VE; Sausen, M
MLA Citation
Keefer, Laurel A., et al. “Automated next-generation profiling of genomic alterations in human cancers.Nat Commun, vol. 13, no. 1, May 2022, p. 2830. Pubmed, doi:10.1038/s41467-022-30380-x.
URI
https://scholars.duke.edu/individual/pub1521745
PMID
35595835
Source
pubmed
Published In
Nature Communications
Volume
13
Published Date
Start Page
2830
DOI
10.1038/s41467-022-30380-x

Pre-existing Castration-resistant Prostate Cancer-like Cells in Primary Prostate Cancer Promote Resistance to Hormonal Therapy.

BACKGROUND: Hormonal therapy targeting the androgen receptor inhibits prostate cancer (PCa), but the tumor eventually recurs as castration-resistant prostate cancer (CRPC). OBJECTIVE: To understand the mechanisms by which subclones within early PCa develop into CRPC. DESIGN, SETTING, AND PARTICIPANTS: We isolated epithelial cells from fresh human PCa cases, including primary adenocarcinoma, locally recurrent CRPC, and metastatic CRPC, and utilized single-cell RNA sequencing to identify subpopulations destined to become either CRPC-adeno or small cell neuroendocrine carcinoma (SCNC). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We revealed dynamic transcriptional reprogramming that promotes disease progression among 23226 epithelial cells using single-cell RNA sequencing, and validated subset-specific progression using immunohistochemistry and large cohorts of publically available genomic data. RESULTS AND LIMITATIONS: We identified a small fraction of highly plastic CRPC-like cells in hormone-naïve early PCa and demonstrated its correlation with biochemical recurrence and distant metastasis, independent of clinical characteristics. We show that progression toward castration resistance was initiated from subtype-specific lineage plasticity and clonal expansion of pre-existing neuroendocrine and CRPC-like cells in early PCa. CONCLUSIONS: CRPC-like cells are present early in the development of PCa and are not exclusively the result of acquired evolutionary selection during androgen deprivation therapy. The lethal CRPC and SCNC phenotypes should be targeted earlier in the disease course of patients with PCa. PATIENT SUMMARY: Here, we report the presence of pre-existing castration-resistant prostate cancer (CRPC)-like cells in primary prostate cancer, which represents a novel castration-resistant mechanism different from the adaptation mechanism after androgen deprivation therapy (ADT). Patients whose tumors harbor increased pre-existing neuroendocrine and CRPC-like cells may become rapidly resistant to ADT and may require aggressive early intervention.
Authors
Cheng, Q; Butler, W; Zhou, Y; Zhang, H; Tang, L; Perkinson, K; Chen, X; Jiang, XS; McCall, SJ; Inman, BA; Huang, J
MLA Citation
Cheng, Qing, et al. “Pre-existing Castration-resistant Prostate Cancer-like Cells in Primary Prostate Cancer Promote Resistance to Hormonal Therapy.Eur Urol, vol. 81, no. 5, May 2022, pp. 446–55. Pubmed, doi:10.1016/j.eururo.2021.12.039.
URI
https://scholars.duke.edu/individual/pub1506334
PMID
35058087
Source
pubmed
Published In
Eur Urol
Volume
81
Published Date
Start Page
446
End Page
455
DOI
10.1016/j.eururo.2021.12.039

A Hybrid Human-Machine Learning Approach for Screening Prostate Biopsies Can Improve Clinical Efficiency Without Compromising Diagnostic Accuracy.

CONTEXT.—: Prostate cancer is a common malignancy, and accurate diagnosis typically requires histologic review of multiple prostate core biopsies per patient. As pathology volumes and complexity increase, new tools to improve the efficiency of everyday practice are keenly needed. Deep learning has shown promise in pathology diagnostics, but most studies silo the efforts of pathologists from the application of deep learning algorithms. Very few hybrid pathologist-deep learning approaches have been explored, and these typically require complete review of histologic slides by both the pathologist and the deep learning system. OBJECTIVE.—: To develop a novel and efficient hybrid human-machine learning approach to screen prostate biopsies. DESIGN.—: We developed an algorithm to determine the 20 regions of interest with the highest probability of malignancy for each prostate biopsy; presenting these regions to a pathologist for manual screening limited the initial review by a pathologist to approximately 2% of the tissue area of each sample. We evaluated this approach by using 100 biopsies (29 malignant, 60 benign, 11 other) that were reviewed by 4 pathologists (3 urologic pathologists, 1 general pathologist) using a custom-designed graphical user interface. RESULTS.—: Malignant biopsies were correctly identified as needing comprehensive review with high sensitivity (mean, 99.2% among all pathologists); conversely, most benign prostate biopsies (mean, 72.1%) were correctly identified as needing no further review. CONCLUSIONS.—: This novel hybrid system has the potential to efficiently triage out most benign prostate core biopsies, conserving time for the pathologist to dedicate to detailed evaluation of malignant biopsies.
Authors
Dov, D; Assaad, S; Syedibrahim, A; Bell, J; Huang, J; Madden, J; Bentley, R; McCall, S; Henao, R; Carin, L; Foo, W-C
MLA Citation
Dov, David, et al. “A Hybrid Human-Machine Learning Approach for Screening Prostate Biopsies Can Improve Clinical Efficiency Without Compromising Diagnostic Accuracy.Arch Pathol Lab Med, vol. 146, no. 6, June 2022, pp. 727–34. Pubmed, doi:10.5858/arpa.2020-0850-OA.
URI
https://scholars.duke.edu/individual/pub1498438
PMID
34591085
Source
pubmed
Published In
Arch Pathol Lab Med
Volume
146
Published Date
Start Page
727
End Page
734
DOI
10.5858/arpa.2020-0850-OA

Plasma cells are essentially absent in the luminal gastrointestinal tract of patients with "complete" 22q11.2 deletion syndrome (DiGeorge syndrome).

Gastrointestinal symptoms are commonly reported in patients with 22q11.2 deletion syndrome or DiGeorge syndrome (DGS) in addition to the dominant cardiac manifestations and immunodeficiency. But literature providing specific morphologic details of the gastrointestinal tract pathology is very limited. Here, we provide the first comprehensive morphologic description of the luminal gastrointestinal tract changes in patients with DGS. Cytogenetically confirmed DGS patients were identified, clinical and laboratory data were reviewed to determine the severity of immunodeficiency, and patients were stratified into mildly immunocompromised, that is, partial DiGeorge anomaly or severely immunosuppressed, that is, complete DiGeorge anomaly groups. Gastrointestinal tract biopsies from these patients were retrospectively reviewed and compared with those from controls without the history of DGS. Patients with immunosuppressed DGS showed a near complete absence of plasma cells in the stomach, duodenum, and colon lamina propria by hematoxylin and eosin evaluation. Immunohistochemistry for CD138 used to highlight plasma cells confirmed this finding. The notable absence of plasma cells adds to the existing knowledge of the pathophysiology underlying DGS and expands the differential diagnostic considerations for this finding, which has been previously described in common variable immunodeficiency. It also provides a useful morphologic marker observable by the readily accessible light microscopy. Second, patients with DGS showed a mild increase in epithelial cell apoptosis in their colon. This finding is significant because of its overlap with morphologic features of gastrointestinal graft versus host disease as thymus transplantation is being used as a treatment option for patients with complete DGS.
Authors
Pendse, AA; Maule, JG; Neff, JL; McCall, S
MLA Citation
Pendse, Avani A., et al. “Plasma cells are essentially absent in the luminal gastrointestinal tract of patients with "complete" 22q11.2 deletion syndrome (DiGeorge syndrome).Hum Pathol, vol. 117, Nov. 2021, pp. 1–8. Pubmed, doi:10.1016/j.humpath.2021.08.002.
URI
https://scholars.duke.edu/individual/pub1494123
PMID
34391747
Source
pubmed
Published In
Hum Pathol
Volume
117
Published Date
Start Page
1
End Page
8
DOI
10.1016/j.humpath.2021.08.002

Research Areas:

Ampulla of Vater
Apoptosis
Bevacizumab
Bile Ducts
Biological Markers
Biopsy
Biopsy, Needle
Cell Differentiation
Cell Line
Cell Nucleus
Cell Proliferation
Cell Survival
Cells, Cultured
Colorectal Neoplasms
Colorectal Neoplasms, Hereditary Nonpolyposis
Cytochrome P-450 CYP2E1
Endocytosis
Epithelial Cells
Epithelial-Mesenchymal Transition
Gene Deletion
Gene Expression Profiling
Gene Expression Regulation
Gene Expression Regulation, Developmental
Gene Expression Regulation, Neoplastic
Genetic Predisposition to Disease
Hedgehog Proteins
Homeodomain Proteins
Humans
Hydroxyproline
Immunohistochemistry
Kruppel-Like Transcription Factors
Lasers
Mesenchymal Stromal Cells
Mesoderm
Microdissection
Mutation
Nuclear Proteins
Oligonucleotides, Antisense
Oligoribonucleotides, Antisense
Oncogenes
Organoplatinum Compounds
Pancreaticoduodenectomy
Pancreatitis
Pilot Projects
Prognosis
Protein Isoforms
Proteome
Proto-Oncogene Proteins
Proto-Oncogene Proteins B-raf
Pyrimidines
RNA, Messenger
Receptors, Cell Surface
Recombinant Proteins
Reverse Transcriptase Polymerase Chain Reaction
Signal Transduction
Stromal Cells
Thiazoles
Tissue Donors
Tumor Markers, Biological
Tumor Necrosis Factor-alpha
Wnt Proteins
Xenograft Model Antitumor Assays
ras Proteins