Browsing by Subject "Prognostic"

Now showing 1 - 3 of 3
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    Inconsistent Associations Between Risk Factor Profiles and Adjuvant Radiation Therapy (ART) Treatment in Patients with Cutaneous Squamous Cell Carcinoma and Utility of the 40-Gene Expression Profile to Refine ART Guidance
    (Springer, 2024) Moody, Brent R.; Farberg, Aaron S.; Somani, Ally-Khan; Taylor, Walton A.; Dermatology, School of Medicine
    Introduction: National Comprehensive Cancer Network (NCCN) recommendations for adjuvant radiation therapy (ART) use are similar for High Risk and Very High Risk cutaneous squamous cell carcinoma (cSCC) with negative post-surgical margins. Although studies report reductions in disease progression following ART treatment, ART use is likely inconsistent when guided by available risk factors. This study evaluated the association of ART with clinical risk factors in ART-treated and untreated patients and showed the clinical utility of the 40-gene expression profile (40-GEP) for guiding ART. Methods: A multicenter study of 954 patients was conducted with institutional review board (IRB) approval. The 40-GEP test was performed using primary tumor tissue from patients with either a minimum of 3 years of follow-up or a documented regional or distant metastasis. Unsupervised hierarchical cluster analysis identified patterns of clinical risk factors for ART-treated patients, then identified untreated patients with matching risk factor profiles. Results were cross-referenced to 40-GEP test results to determine utility of the test to guide ART. Results: Analysis demonstrated inconsistent implementation of ART for eligible patients. Cluster analysis identified four patient profiles based on clusters of risk factors and, notably, matching profiles in ART-treated and untreated patients. Further, the analysis identified patients who received but could have deferred ART on the basis of 40-GEP test result and biologically low risk of metastasis, and untreated patients who likely would have benefitted from ART on the basis of their 40-GEP test result. Conclusions: ART guidance is not determined by the presence of specific clinicopathologic factors, with treated and untreated patients sharing the same risk factor profiles. cSCC risk determination based on NCCN recommendations for clinical factor assessment results in inconsistent use of ART. Including tumor biology-based prognostic information from the 40-GEP refines risk and identifies patients who are most appropriate and likely to benefit from ART, and those that can consider deferring ART.
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    Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients
    (Springer, 2024) Wysong, Ashley; Somani, Ally-Khan; Ibrahim, Sherrif F.; Cañueto, Javier; Fitzgerald, Alison L.; Siegel, Jennifer J.; Prasai, Anesh; Goldberg, Matthew S.; Farberg, Aaron S.; Regula, Christie; Bar, Anna; Kasprzak, Julia; Brodland, David G.; Koyfman, Shlomo A.; Arron, Sarah T.; Dermatology, School of Medicine
    Introduction: The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old. Methods: This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP. Results: Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models). Conclusion: The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions.
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    PROGgene: gene expression based survival analysis web application for multiple cancers
    (Springer, 2013-10-28) Goswami, Chirayu Pankaj; Nakshatri, Harikrishna
    Background Identification of prognostic mRNA biomarkers has been done for various cancer types. The data that are published from such studies are archived in public repositories. There are hundreds of such datasets available for multiple cancer types in public repositories. Wealth of such data can be utilized to study prognostic implications of mRNA in different cancers as well as in different populations or subtypes of same cancer. Description We have created a web application that can be used for studying prognostic implications of mRNA biomarkers in a variety of cancers. We have compiled data from public repositories such as GEO, EBI Array Express and The Cancer Genome Atlas for creating this tool. With 64 patient series from 18 cancer types in our database, this tool provides the most comprehensive resource available for survival analysis to date. The tool is called PROGgene and it is available at http://www.compbio.iupui.edu/proggene. Conclusions We present this tool as a hypothesis generation tool for researchers to identify potential prognostic mRNA biomarkers to follow up with further research. For this reason, we have kept the web application very simple and straightforward. We believe this tool will be useful in accelerating biomarker discovery in cancer and quickly providing results that may indicate disease-specific prognostic value of specific biomarkers.