Jeffrey Marks

Overview:

I have been engaged in basic and applied cancer research for over 28 years beginning with my post-doctoral fellowship under Arnold Levine at Princeton. Since being appointed to the faculty in the Department of Surgery at Duke, my primary interest has been towards understanding breast and ovarian cancer. I am a charter member of the NCI-Early Detection Research Network (EDRN) and have been an integral scientist in the breast and gynecologic collaborative group for 15 years including leading this group for a 5 year period. I am also a major contributor to the Cancer Genome Atlas and have worked in this context for the past 4 years. My research interests are in the molecular etiology of these diseases and understanding how key genetic events contribute to their onset and progression. My work has been very multi-disciplinary incorporating quantitative, population, genetic, and behavioral approaches.  I consider my specialty to be in the area of using human breast and ovarian cancer as the primary and only authentic model system to understand these diseases.  

Positions:

Joseph W. and Dorothy W. Beard Distinguished Professor of Experimental Surgery

Surgery, Surgical Sciences
School of Medicine

Professor in Surgery

Surgery, Surgical Sciences
School of Medicine

Professor of Pathology

Pathology
School of Medicine

Member of the Duke Cancer Institute

Duke Cancer Institute
School of Medicine

Education:

Ph.D. 1985

University of California - San Diego

Grants:

Genomic Diversity and the Microenvironment as Drivers of Progression in DCIS

Administered By
Surgical Oncology
Awarded By
Department of Defense
Role
Co Investigator
Start Date
End Date

(PQC3) Genomic Diversity and the Microenvironment as Drivers of Metastasis in DCIS

Administered By
Surgical Oncology
Awarded By
National Institutes of Health
Role
Co Investigator
Start Date
End Date

Developing Biomarker-Based Prognostics in Breast Cancer

Awarded By
National Institutes of Health
Role
Consultant
Start Date
End Date

Improving genomic prediction models in breast cancer.

Awarded By
National Institutes of Health
Role
Investigator
Start Date
End Date

PPARy: Biomarker for Breast Cancer in Older Women

Administered By
Medicine, Geriatrics
Awarded By
National Institutes of Health
Role
Mentor
Start Date
End Date

Publications:

DCIS AI-TIL: Ductal Carcinoma In Situ Tumour Infiltrating Lymphocyte Scoring Using Artificial Intelligence

Tumour infiltrating lymphocytes (TIL) influence the prognosis of Ductal carcinoma in situ (DCIS). Currently, manual assessment of TIL by expert pathologists is considered a gold standard. However, there are issues with a shortage of expert pathologists and inter-observer variability. A reliable automated scoring method is yet to be developed due to the inherent complexity of DCIS duct morphology and the assessment strategy. We developed a new deep learning and spatial analysis pipeline to automatically score DCIS stromal TIL (AI-TIL) from 243 diagnostic haematoxylin and eosin-stained whole slide images from 127 patients. To automatically identify and segment DCIS ducts, we implemented a generative adversarial network. To identify lymphocytes, we used a pre-trained deep learning model. Our DCIS segmentation model achieved a dice overlap of 0.94 (± 0.01 ) and the cell classifier model achieved 92% accuracy compared to pathologists’ annotations. Subsequently, we automatically delineated a stromal boundary and computed the percentage of the boundary area occupied by lymphocytes for each DCIS duct. Finally, we computed TIL score as the average of all duct level scores within the slide. We observe a higher correlation between AI-TIL and pathologists (average) score for wider stomal boundaries (r = 0.66, p = 6.0 × 10 - 7, W = 0.3 mm) compared with smaller boundary (r = 0.23, p = 0.12, W = 0.03 mm). Using multivariate analysis, a low AI-TIL score was associated with an increased risk of recurrence independent of age, grade, estrogen receptor (ER) status, progesterone receptor (PR) status, and necrosis (hazard ratio = 0.14, 95% CI 0.038–0.51, p = 0.003, W = 0.03 mm). These results suggest that our pipeline could be used to automatically quantify stromal TIL in DCIS and integrating AI-TIL with pathologists’ visual assessment may improve DCIS recurrence risk estimation.
Authors
Hagos, YB; Sobhani, F; Castillo, SP; Hall, AH; AbdulJabbar, K; Salgado, R; Harmon, B; Gallagher, K; Kilgore, M; King, LM; Marks, JR; Maley, C; Horlings, HM; West, R; Hwang, ES; Yuan, Y
MLA Citation
Hagos, Y. B., et al. “DCIS AI-TIL: Ductal Carcinoma In Situ Tumour Infiltrating Lymphocyte Scoring Using Artificial Intelligence.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13602 LNCS, 2022, pp. 164–75. Scopus, doi:10.1007/978-3-031-19660-7_16.
URI
https://scholars.duke.edu/individual/pub1560992
Source
scopus
Published In
Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
13602 LNCS
Published Date
Start Page
164
End Page
175
DOI
10.1007/978-3-031-19660-7_16

Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American cancer epidemiology study (AACES).

PURPOSE: The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC. METHODS: AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010-2015) are presented. RESULTS: Thus far, ~ 650 patients with EOC have been enrolled in the AACES. The five-year OS of AACES participants approximates those of Black women in the Surveillance Epidemiology and End Results (SEER) registry who survive at least 10-month past diagnosis and is worse compared to white women in SEER, 49 vs. 60%, respectively. A high proportion of women in AACES have low levels of household income (45% < $25,000 annually), education (51% ≤ high school education), and insurance coverage (32% uninsured or Medicaid). Those followed annually differ from those without follow-up with higher levels of localized disease (28 vs 24%) and higher levels of optimal debulking status (73 vs 67%). CONCLUSION: AACES is well positioned to evaluate the contribution of social determinants of health to the poor survival of Black women with EOC and advance understanding of the multi-factorial causes of the ovarian cancer survival disparity in Black women.
Authors
Schildkraut, JM; Johnson, C; Dempsey, LF; Qin, B; Terry, P; Akonde, M; Peters, ES; Mandle, H; Cote, ML; Peres, L; Moorman, P; Schwartz, AG; Epstein, M; Marks, J; Bondy, M; Lawson, AB; Alberg, AJ; Bandera, EV
MLA Citation
Schildkraut, Joellen M., et al. “Survival of epithelial ovarian cancer in Black women: a society to cell approach in the African American cancer epidemiology study (AACES).Cancer Causes Control, Dec. 2022, pp. 1–15. Pubmed, doi:10.1007/s10552-022-01660-0.
URI
https://scholars.duke.edu/individual/pub1559960
PMID
36520244
Source
pubmed
Published In
Cancer Causes Control
Published Date
Start Page
1
End Page
15
DOI
10.1007/s10552-022-01660-0

Spatial interplay of tissue hypoxia and T-cell regulation in ductal carcinoma in situ.

Hypoxia promotes aggressive tumor phenotypes and mediates the recruitment of suppressive T cells in invasive breast carcinomas. We investigated the role of hypoxia in relation to T-cell regulation in ductal carcinoma in situ (DCIS). We designed a deep learning system tailored for the tissue architecture complexity of DCIS, and compared pure DCIS cases with the synchronous DCIS and invasive components within invasive ductal carcinoma cases. Single-cell classification was applied in tandem with a new method for DCIS ductal segmentation in dual-stained CA9 and FOXP3, whole-tumor section digital pathology images. Pure DCIS typically has an intermediate level of colocalization of FOXP3+ and CA9+ cells, but in invasive carcinoma cases, the FOXP3+ (T-regulatory) cells may have relocated from the DCIS and into the invasive parts of the tumor, leading to high levels of colocalization in the invasive parts but low levels in the synchronous DCIS component. This may be due to invasive, hypoxic tumors evolving to recruit T-regulatory cells in order to evade immune predation. Our data support the notion that hypoxia promotes immune tolerance through recruitment of T-regulatory cells, and furthermore indicate a spatial pattern of relocalization of T-regulatory cells from DCIS to hypoxic tumor cells. Spatial colocalization of hypoxic and T-regulatory cells may be a key event and useful marker of DCIS progression.
Authors
Sobhani, F; Muralidhar, S; Hamidinekoo, A; Hall, AH; King, LM; Marks, JR; Maley, C; Horlings, HM; Hwang, ES; Yuan, Y
MLA Citation
Sobhani, Faranak, et al. “Spatial interplay of tissue hypoxia and T-cell regulation in ductal carcinoma in situ.Npj Breast Cancer, vol. 8, no. 1, Sept. 2022, p. 105. Pubmed, doi:10.1038/s41523-022-00419-9.
URI
https://scholars.duke.edu/individual/pub1548456
PMID
36109587
Source
pubmed
Published In
Npj Breast Cancer
Volume
8
Published Date
Start Page
105
DOI
10.1038/s41523-022-00419-9

Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts.

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.
Authors
Strand, SH; Rivero-Gutiérrez, B; Houlahan, KE; Seoane, JA; King, LM; Risom, T; Simpson, LA; Vennam, S; Khan, A; Cisneros, L; Hardman, T; Harmon, B; Couch, F; Gallagher, K; Kilgore, M; Wei, S; DeMichele, A; King, T; McAuliffe, PF; Nangia, J; Lee, J; Tseng, J; Storniolo, AM; Thompson, AM; Gupta, GP; Burns, R; Veis, DJ; DeSchryver, K; Zhu, C; Matusiak, M; Wang, J; Zhu, SX; Tappenden, J; Ding, DY; Zhang, D; Luo, J; Jiang, S; Varma, S; Anderson, L; Straub, C; Srivastava, S; Curtis, C; Tibshirani, R; Angelo, RM; Hall, A; Owzar, K; Polyak, K; Maley, C; Marks, JR; Colditz, GA; Hwang, ES; West, RB
MLA Citation
Strand, Siri H., et al. “Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts.Cancer Cell, vol. 40, no. 12, Dec. 2022, pp. 1521-1536.e7. Pubmed, doi:10.1016/j.ccell.2022.10.021.
URI
https://scholars.duke.edu/individual/pub1556629
PMID
36400020
Source
pubmed
Published In
Cancer Cell
Volume
40
Published Date
Start Page
1521
End Page
1536.e7
DOI
10.1016/j.ccell.2022.10.021

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer.

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.
Authors
Lips, EH; Kumar, T; Megalios, A; Visser, LL; Sheinman, M; Fortunato, A; Shah, V; Hoogstraat, M; Sei, E; Mallo, D; Roman-Escorza, M; Ahmed, AA; Xu, M; van den Belt-Dusebout, AW; Brugman, W; Casasent, AK; Clements, K; Davies, HR; Fu, L; Grigoriadis, A; Hardman, TM; King, LM; Krete, M; Kristel, P; de Maaker, M; Maley, CC; Marks, JR; Menegaz, BA; Mulder, L; Nieboer, F; Nowinski, S; Pinder, S; Quist, J; Salinas-Souza, C; Schaapveld, M; Schmidt, MK; Shaaban, AM; Shami, R; Sridharan, M; Zhang, J; Stobart, H; Collyar, D; Nik-Zainal, S; Wessels, LFA; Hwang, ES; Navin, NE; Futreal, PA; Grand Challenge PRECISION consortium,; Thompson, AM; Wesseling, J; Sawyer, EJ
MLA Citation
Lips, Esther H., et al. “Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer.Nat Genet, vol. 54, no. 6, June 2022, pp. 850–60. Pubmed, doi:10.1038/s41588-022-01082-3.
URI
https://scholars.duke.edu/individual/pub1524174
PMID
35681052
Source
pubmed
Published In
Nat Genet
Volume
54
Published Date
Start Page
850
End Page
860
DOI
10.1038/s41588-022-01082-3