Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study

Patrick Leo, Andrew Janowczyk, Robin Elliott, Nafiseh Janaki, Kaustav Bera, Rakesh Shiradkar, Xavier Farré, Pingfu Fu, Ayah El-Fahmawi, Mohammed Shahait, Jessica Kim, David Lee, Kosj Yamoah, Timothy R. Rebbeck, Francesca Khani, Brian D. Robinson, Lauri Eklund, Ivan Jambor, Harri Merisaari, Otto EttalaPekka Taimen, Hannu J. Aronen, Peter J. Boström, Ashutosh Tewari, Cristina Magi-Galluzzi, Eric Klein, Andrei Purysko, Natalie NC Shih, Michael Feldman, Sanjay Gupta, Priti Lal, Anant Madabhushi

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03–3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40–3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests.

Original languageEnglish
Article number35
Journalnpj Precision Oncology
Volume5
Issue number1
DOIs
StatePublished - Dec 2021

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