Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.
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Date
2016-11-01ICR Author
Author
Heindl, A
Lan, C
Rodrigues, DN
Koelble, K
Yuan, Y
Type
Journal Article
Metadata
Show full item recordAbstract
The tumor microenvironment is pivotal in influencing cancer progression and metastasis. Different cells co-exist with high spatial diversity within a patient, yet their combinatorial effects are poorly understood. We investigate the similarity of the tumor microenvironment of 192 local metastatic lesions in 61 ovarian cancer patients. An ecologically inspired measure of microenvironmental diversity derived from multiple metastasis sites is correlated with clinicopathological characteristics and prognostic outcome. We demonstrate a high accuracy of our automated analysis across multiple sites. A low level of similarity in microenvironmental composition is observed between ovary tumor and corresponding local metastases (stromal ratio r = 0.30, lymphocyte ratio r = 0.37). We identify a new measure of microenvironmental diversity derived from Shannon entropy that is highly predictive of poor overall (p = 0.002, HR = 3.18, 95% CI = 1.51-6.68) and progression-free survival (p = 0.0036, HR = 2.83, 95% CI = 1.41-5.7), independent of and stronger than clinical variables, subtype stratifications based on single cell types alone and number of sites. Although stromal influence in ovary tumors is known to have significant clinical implications, our findings reveal an even stronger impact orchestrated by diverse cell types. Quantitative histology-based measures can further enable objective selection of patients who are in urgent need of new therapeutic strategies such as combinatorial treatments targeting heterogeneous tumor microenvironment.
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Subject
Humans
Cystadenocarcinoma, Serous
Ovarian Neoplasms
Neoplasm Metastasis
Prognosis
Disease-Free Survival
Adult
Aged
Aged, 80 and over
Middle Aged
Female
Tumor Microenvironment
Research team
Prostate Cancer Targeted Therapy Group
Computational Pathology & Integrated Genomics
Language
eng
Date accepted
2016-08-24
License start date
2016-11
Citation
Oncotarget, 2016, 7 (44), pp. 71123 - 71135
Publisher
IMPACT JOURNALS LLC