Abstract
Pancreatic ductal adenocarcinoma (PDAC) patients, who often present with stage III or IV disease, face a dismal prognosis as the 5-year survival rate remains below 10%. Recent studies have revealed that CD4\(^+\) T, CD8\(^+\) T, and/or B cells in specific spatial arrangements relative to intratumoral regions correlate with clinical outcome for patients, but the complex functional states of those immune cell types remain to be incorporated into prognostic biomarker studies. Here, we developed an interpretable machine learning model to analyze the functional relationship between leukocyte-leukocyte or leukocyte-tumor cell spatial proximity, correlated with clinical outcome of 46 therapy-naïve PDAC patients following surgical resection. Using a multiplex immunohistochemistry imaging data set focused on profiling leukocyte functional status, our model identified features that distinguished patients in the fourth quartile from those in the first quartile of survival. The top ranked important features identified by our model, all of which were positive prognostic stratifiers, included CD4 T helper cell frequency among CD45\(^+\) immune cells, frequency of Granzyme B-positivity among CD4 and CD8 T cells, as well as the frequency of PD-1 positivity among CD8 T cells. The spatial proximity of CD4 T- to B cells, and between CD8 T cells and epithelial cells, were also identified as important prognostic features. While spatial proximity features provided valuable prognostic information, the best model required both spatial and phenotypic information about tumor infiltrating leukocytes. Our analysis links the immune microenvironment of PDAC tumors to outcome of patients, thus identifying features associated with more progressive disease.
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Funding
YHC acknowledges funding from the NIH (U54CA209988, 1U01 CA224012). The study and analyses were funded by an AACR Stand Up to Cancer grant funded by the Lustgarten Foundation, and the Brenden-Colson Center for Pancreatic Care at OHSU. LMC acknowledges funding from the National Institutes of Health (1U01 CA224012, U2C CA233280, R01 CA223150, R01 CA226909, R21 HD099367), the Knight Cancer Institute, and the Brenden-Colson Center for Pancreatic Care at OHSU. RCS acknowledges funding from the NIH (1U01 CA224012, U2C CA233280, U54 CA209988, R01 CA196228, and R01 CA186241) and the Brenden-Colson Center for Pancreatic Care at OHSU. This study was also made possible with support from the Oregon Clinical & Translational Research Institute (OCTRI), which is supported by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant Award Number UL1TR002369. Human PDAC surgical resection specimens were obtained in accordance with the Declaration of Helsinki and acquired with IRB approval from Dana-Farber/Harvard Cancer Center, and the Oregon Pancreas Tissue Registry under OHSU IRB protocol # 3609. Additional PDAC archival surgical resection specimens were collected from consented patients enrolled in the multi-center phase 1b PRINCE clinical trial (NCT03214250, sponsored by Parker Institute for Cancer Immunotherapy).
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Gray, E. et al. (2020). Activation vs. Organization: Prognostic Implications of T and B Cell Features of the PDAC Microenvironment. In: Bebis, G., Alekseyev, M., Cho, H., Gevertz, J., Rodriguez Martinez, M. (eds) Mathematical and Computational Oncology. ISMCO 2020. Lecture Notes in Computer Science(), vol 12508. Springer, Cham. https://doi.org/10.1007/978-3-030-64511-3_5
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