On August 16, 2021 Castle Biosciences, Inc. (Nasdaq: CSTL), a dermatologic diagnostics company providing personalized genomic information to inform treatment decisions, reported recent presentations on two of its skin cancer gene expression profile tests at the 2021 American Academy of Dermatology (AAD) Summer Meeting, held Aug. 5-8, 2021 (Press release, Castle Biosciences, AUG 16, 2021, View Source [SID1234586648]).

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DecisionDx-Melanoma:

DecisionDx-Melanoma is Castle’s gene expression profile test that uses an individual patient’s tumor biology to predict the risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node (SLN) positivity, independent of traditional staging factors.

"Integrating 31-gene expression profiling with clinicopathologic features improves prognostication of recurrence and metastasis in patients with stage I-III cutaneous melanoma" was presented by Nicholas Taylor, M.D., Ph.D., Zitelli and Brodland, P.C., Pittsburgh and Central Dermatology Center, Chapel Hill, N.C. in the Frontiers in Research, Science and Technology (FiRST) session on Saturday, Aug. 7.

"The study demonstrated that DecisionDx-Melanoma added significant prognostic value for a patient beyond traditional staging," said Taylor. "The study further showed that the ability to integrate a patient’s unique tumor biology with their personal clinical and pathologic risk factors helped both patients and clinicians."

Study methods and findings:

DecisionDx-Melanoma’s 31-gene expression profile (31-GEP) has been validated to both identify patients at low risk of sentinel lymph node positivity and refine risk of recurrence prognosis.
A new integrated algorithm (i31-GEP ROR (risk of recurrence) for outcomes prediction) was developed (n=1581) and validated (n=523) using Cox regression and 10×4-fold cross-validation on patients with stage I-III cutaneous melanoma from multiple centers.
The final integrated outcomes prediction algorithm combined DecisionDx-Melanoma’s continuous 31-GEP score and patient-specific clinicopathologic risk factors, including Breslow thickness, ulceration, mitotic rate, age, tumor location, sentinel lymph node (SLN) status and/or the presence of microsatellites.
Compared to American Joint Committee on Cancer Eighth Edition (AJCC8) staging, the i31-GEP ROR algorithm for outcomes prediction significantly improved the classification of overall risk for five-year recurrence-free survival (RFS), distant metastasis-free survival (DMFS) and melanoma-specific survival (MSS).
Integrating DecisionDx-Melanoma’s continuous 31-GEP score with clinicopathologic features improves risk stratification over staging guidelines alone.
Overall, the study demonstrated that DecisionDx-Melanoma’s i31-GEP ROR integrated test result was an independent, significant predictor of five-year RFS, DMFS and MSS, and that the i31-GEP ROR outcomes prediction algorithm provided an individualized risk estimate rather than an average, population-based risk estimate that can help personalize patient management decisions and overall risk assessments beyond standard melanoma staging.
DecisionDx-SCC:

DecisionDx-SCC is Castle’s prognostic 40-gene expression profile (GEP) test for patients diagnosed with high-risk cutaneous squamous cell carcinoma (SCC), designed to use a patient’s tumor biology to predict individual risk of metastasis for patients with SCC and one or more risk factors.

"Risk assessment by the 40-gene expression profile (40-GEP) test further stratifies risk of metastasis in a subset of high-risk cutaneous squamous cell carcinoma (cSCC) patients meeting T1 staging criteria​" was presented by Aaron Farberg, M.D., Baylor University Medical Center, Dallas in the Frontiers in Research, Science and Technology (FiRST) session on Saturday, Aug. 7.

"As a physician, it is important that I leverage all of the information available to me to make the best decisions for the care of each patient," said Farberg. "This study demonstrated that by incorporating DecisionDx-SCC into their clinical practice, physicians can more confidently identify patients with a higher risk of metastasis, who may have otherwise been considered low-risk using traditional staging systems alone, which provides the ability to adjust their treatment plans for improved patient outcomes."

Study methods and findings:

Previous validation of the DecisionDx-SCC test in a high-risk SCC cohort (n=420, all high-risk or very- high risk by the National Comprehensive Cancer Network (NCCN) guidelines v1.2021 or meeting Appropriate Use Criteria for Mohs Micrographic Surgery) demonstrated independent prognostic value when the result was incorporated into existing risk assessment methods.
Using this validation cohort, the objective of this study was to determine whether DecisionDx-SCC could identify biologically risky tumors within a subset of NCCN high-risk tumors comprehensively staged as T1 by either American Joint Committee on Cancer Eighth Edition (AJCC8) or Brigham and Women’s Hospital (BWH) staging (AJCC8 cohort n=222; BWH cohort n=200).
Kaplan-Meier analysis demonstrated a statistically significant difference in three-year metastasis-free survival rates between DecisionDx-SCC risk groups:
AJCC8 T1 cases – Class 1: 95.2%, Class 2A: 81.4%, Class 2B: 50%; p<0.001
BWH T1 cases – Class 1: 96.6%, Class 2A: 84.9%, Class 2B: 55.6%; p<0.001
Within these T1 subsets, DecisionDx-SCC accurately identified metastatic cases in approximately 80% of the cases:
AJCC8 T1 cases: 78.6% ​of metastatic cases ​received a Class 2A (moderate biological risk of metastasis) or 2B (high biological risk of metastasis) DecisionDx-SCC result
BWH T1 cases: 78.9%​ of metastatic cases ​received a Class 2A or 2B DecisionDx-SCC result
Overall, the study demonstrated that DecisionDx-SCC accurately identified tumors at risk of metastasis and can be incorporated into clinical assessments with traditional clinicopathological risk factors to help inform patient surveillance and treatment decisions.
About DecisionDx-Melanoma

DecisionDx-Melanoma is a gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous melanoma metastasis or recurrence, as well as sentinel lymph node positivity, independent of traditional staging factors, and has been studied in more than 5,700 patient samples. Using tissue from the primary melanoma, the test measures the expression of 31 genes. The test has been validated in four archival risk of recurrence studies of 901 patients and six prospective risk of recurrence studies including more than 1,600 patients. To predict likelihood of sentinel lymph node positivity, the Company utilizes its proprietary algorithm, i31-GEP, to produce an integrated test result. i31-GEP is an artificial intelligence-based neural network algorithm (independently validated in a cohort of 1,674 prospective, consecutively tested patients with T1-T4 cutaneous melanoma) that integrates the DecisionDx-Melanoma test result with the patient’s traditional clinicopathologic features. Impact on patient management plans for one of every two patients tested has been demonstrated in four multicenter and single-center studies including more than 560 patients. The consistent performance and accuracy demonstrated in these studies provides confidence in disease management plans that incorporate DecisionDx-Melanoma test results. Through June 30, 2021, DecisionDx-Melanoma has been ordered 78,277 times for use in patients with cutaneous melanoma.

More information about the test and disease can be found at www.CastleTestInfo.com.

About DecisionDx-SCC

DecisionDx-SCC is a 40-gene expression profile test that uses an individual patient’s tumor biology to predict individual risk of cutaneous squamous cell carcinoma metastasis for patients with one or more risk factors. The test result, in which patients are stratified into a Class 1 (low), 2A (moderate) or 2B (high) risk category, predicts individual metastatic risk to inform risk-appropriate management.

Peer-reviewed publications have demonstrated that DecisionDx-SCC is an independent predictor of metastatic risk and that integrating DecisionDx-SCC with current prognostic methods can add positive predictive value to clinician decisions regarding staging and management.

More information about the test and disease can be found at www.CastleTestInfo.com.