Edward A Levine1, Konstantinos I Votanopoulos2, Shadi A Qasem3, John Philip4, Kathleen A Cummins2, Jeff W Chou5, Jimmy Ruiz6, Ralph D'Agostino7, Perry Shen2, Lance D Miller8. 1. Surgical Oncology Service, Department of General Surgery, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC. Electronic address: elevine@wakehealth.edu. 2. Surgical Oncology Service, Department of General Surgery, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC. 3. Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC. 4. Department of Pathology, Wake Forest School of Medicine, Winston-Salem, NC. 5. Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC. 6. Department of Medicine, Section on Hematology and Oncology, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC. 7. Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC. 8. Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC; Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC.
Abstract
BACKGROUND: Appendiceal cancer (AC) patients treated with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) often demonstrate an unpredictable variability in their survival outcomes. Biomarkers predictive of CRS/HIPEC efficacy could better guide treatment decisions. We hypothesized that variation in the transcriptional programming of AC tumors might distinguish molecular subtypes with differential outcomes after CRS/HIPEC. STUDY DESIGN: Gene expression profiles of 2 AC cohorts were analyzed using Affymetrix whole-genome expression microarrays. Hierarchical clustering methods, Kaplan-Meier analysis, and Cox regression models were used to discover and validate prognostic molecular subtypes of AC. Gene set enrichment analysis was used to infer pathologic attributes of the molecular subtypes. RESULTS: Unsupervised hierarchical clustering analysis of tumor expression profiles revealed a 139-gene cassette that distinguished 2 molecular subtypes (based on low vs high expression of the gene cassette) with statistically significant survival differences (disease-specific survival, p = 0.0075; progression-free survival, p = 0.0072). In a second AC cohort, the 139-gene cassette reproducibly partitioned tumors into subtypes with significant survival differences. Tumors showing high relative expression of the genes comprising the cassette associated with poor survival outcomes (disease-specific survival, p = 0.047; progression-free survival, p = 0.0079), and exhibited gene expression patterns enriched for oncogenic processes and pathways. The prognostic value of the molecular subtypes was specific for low-grade appendiceal tumors (disease-specific survival, p = 0.028; progression-free survival, p = 0.0016), and remained significant in the presence of conventional prognostic markers, including grade, surgical resection score, Eastern Cooperative Oncology Group status, and age. CONCLUSIONS: The 139-gene cassette can have actionable clinical utility for identifying low-grade appendiceal tumor molecular subtypes predictive of therapeutic efficacy of CRS/HIPEC.
BACKGROUND:Appendiceal cancer (AC) patients treated with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) often demonstrate an unpredictable variability in their survival outcomes. Biomarkers predictive of CRS/HIPEC efficacy could better guide treatment decisions. We hypothesized that variation in the transcriptional programming of AC tumors might distinguish molecular subtypes with differential outcomes after CRS/HIPEC. STUDY DESIGN: Gene expression profiles of 2 AC cohorts were analyzed using Affymetrix whole-genome expression microarrays. Hierarchical clustering methods, Kaplan-Meier analysis, and Cox regression models were used to discover and validate prognostic molecular subtypes of AC. Gene set enrichment analysis was used to infer pathologic attributes of the molecular subtypes. RESULTS: Unsupervised hierarchical clustering analysis of tumor expression profiles revealed a 139-gene cassette that distinguished 2 molecular subtypes (based on low vs high expression of the gene cassette) with statistically significant survival differences (disease-specific survival, p = 0.0075; progression-free survival, p = 0.0072). In a second AC cohort, the 139-gene cassette reproducibly partitioned tumors into subtypes with significant survival differences. Tumors showing high relative expression of the genes comprising the cassette associated with poor survival outcomes (disease-specific survival, p = 0.047; progression-free survival, p = 0.0079), and exhibited gene expression patterns enriched for oncogenic processes and pathways. The prognostic value of the molecular subtypes was specific for low-grade appendiceal tumors (disease-specific survival, p = 0.028; progression-free survival, p = 0.0016), and remained significant in the presence of conventional prognostic markers, including grade, surgical resection score, Eastern Cooperative Oncology Group status, and age. CONCLUSIONS: The 139-gene cassette can have actionable clinical utility for identifying low-grade appendiceal tumor molecular subtypes predictive of therapeutic efficacy of CRS/HIPEC.
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