Improved Outcome Prediction for Appendiceal Pseudomyxoma Peritonei by Integration of Cancer Cell and Stromal Transcriptional Profiles.
Claudio IsellaMarco VairaManuela RobellaSara Erika BellomoGabriele PiccoAlice BorsanoAndrea MignoneConsalvo PettiRoberta PorporatoAlexandra Ambra UllaAlberto PisacaneAnna SapinoMichele De SimoneEnzo MedicoPublished in: Cancers (2020)
In recent years, cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) have substantially improved the clinical outcome of pseudomyxoma peritonei (PMP) originating from mucinous appendiceal cancer. However, current histopathological grading of appendiceal PMP frequently fails in predicting disease outcome. We recently observed that the integration of cancer cell transcriptional traits with those of cancer-associated fibroblasts (CAFs) improves prognostic prediction for tumors of the large intestine. We therefore generated global expression profiles on a consecutive series of 24 PMP patients treated with CRS plus HIPEC. Multiple lesions were profiled for nine patients. We then used expression data to stratify the samples by a previously published "high-risk appendiceal cancer" (HRAC) signature and by a CAF signature that we previously developed for colorectal cancer, or by a combination of both. The prognostic value of the HRAC signature was confirmed in our cohort and further improved by integration of the CAF signature. Classification of cases profiled for multiple lesions revealed the existence of outlier samples and highlighted the need of profiling multiple PMP lesions to select representative samples for optimal performances. The integrated predictor was subsequently validated in an independent PMP cohort. These results provide new insights into PMP biology, revealing a previously unrecognized prognostic role of the stromal component and supporting integration of standard pathological grade with the HRAC and CAF transcriptional signatures to better predict disease outcome.
Keyphrases
- low grade
- high grade
- papillary thyroid
- transcription factor
- end stage renal disease
- gene expression
- bone marrow
- ejection fraction
- squamous cell
- machine learning
- minimally invasive
- poor prognosis
- chronic kidney disease
- single cell
- newly diagnosed
- peritoneal dialysis
- deep learning
- genome wide
- heat shock
- prognostic factors
- randomized controlled trial
- big data
- patient reported outcomes
- electronic health record
- locally advanced
- artificial intelligence
- radiation therapy
- dna methylation
- coronary artery disease
- cross sectional
- extracellular matrix
- childhood cancer
- binding protein
- heat stress
- young adults
- atrial fibrillation