Intratumoral collagen signatures predict clinical outcomes in feline mammary carcinoma.
Suzanne RosenBecky K BrissonAmy C DurhamClare M MunroeConor J McNeillDarko StefanovskiKarin U SørenmoSusan W VolkPublished in: PloS one (2020)
Breast cancer is the most common cause of cancer-related deaths in women worldwide. Identification of reliable prognostic indicators and therapeutic targets is critical for improving patient outcome. Cancer in companion animals often strongly resembles human cancers and a comparative approach to identify prognostic markers can improve clinical care across species. Feline mammary tumors (FMT) serve as models for extremely aggressive triple negative breast cancer (TNBC) in humans, with high rates of local and distant recurrence after resection. Despite the aggressive clinical behavior of most FMT, current prognostic indicators are insufficient for accurately predicting outcome, similar to human patients. Given significant heterogeneity of mammary tumors, there has been a recent focus on identification of universal tumor-permissive stromal features that can predict biologic behavior and provide therapeutic targets to improve outcome. As in human and canine patients, collagen signatures appear to play a key role in directing mammary tumor behavior in feline patients. We find that patients bearing FMTs with denser collagen, as well as longer, thicker and straighter fibers and less identifiable tumor-stromal boundaries had poorer outcomes, independent of the clinical variables grade and surgical margins. Most importantly, including the collagen parameters increased the predictive power of the clinical model. Thus, our data suggest that similarities with respect to the stromal microenvironment between species may allow this model to predict outcome and develop novel therapeutic targets within the tumor stroma that would benefit both veterinary and human patients with aggressive mammary tumors.
Keyphrases
- end stage renal disease
- endothelial cells
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- healthcare
- stem cells
- bone marrow
- palliative care
- peritoneal dialysis
- rheumatoid arthritis
- type diabetes
- machine learning
- pregnant women
- pain management
- induced pluripotent stem cells
- gene expression
- adipose tissue
- insulin resistance
- electronic health record
- skeletal muscle
- big data
- case report
- artificial intelligence
- dna methylation
- free survival
- papillary thyroid