Gene Expression Profile Test Research Articles

Use of prognostic gene expression profiling tests in primary breast cancer treatment: a German real-world patient survey.

Aims: In primary breast cancer, gene expression profiling tests can support adjuvant chemotherapy treatment decisions. Real-world test use in Germany was investigated in an online survey of female breast cancer patients (n=475). Materials & methods: Relationships between three groups were examined for clinical and statistical relevance: no test indication (n=353), test indication and tested (n=65) and test indication but not tested (n=57). Results: Atotal of 47% of participants with a test indication were not tested. Test rates increased by 23% from 2012-2018 (49%) to 2019-2021 (60%). Atotal of 65% of patients without testing received chemotherapy, whereas only 38% of tested patients received chemotherapy. Conclusion: The use of gene expression profiling tests correlates with a real-world chemotherapy reduction. Gene expression profiling testing may improve patient confidence in the decision for or against chemotherapy.

A comparison of DNA sequencing and gene expression profiling to assist tissue of origin diagnosis in cancer of unknown primary.

Cancer of unknown primary (CUP) is a syndrome defined by clinical absence of a primary cancer after standardised investigations. Gene expression profiling (GEP) and DNA sequencing have been used to predict primary tissue of origin (TOO) in CUP and find molecularly guided treatments; however, a detailed comparison of the diagnostic yield from these two tests has not been described. Here, we compared the diagnostic utility of RNA and DNA tests in 215 CUP patients (82% received both tests) in a prospective Australian study. Based on retrospective assessment of clinicopathological data, 77% (166/215) of CUPs had insufficient evidence to support TOO diagnosis (clinicopathology unresolved). The remainder had either a latent primary diagnosis (10%) or clinicopathological evidence to support a likely TOO diagnosis (13%) (clinicopathology resolved). We applied a microarray (CUPGuide) or custom NanoString 18-class GEP test to 191 CUPs with an accuracy of 91.5% in known metastatic cancers for high-medium confidence predictions. Classification performance was similar in clinicopathology-resolved CUPs - 80% had high-medium predictions and 94% were concordant with pathology. Notably, only 56% of the clinicopathology-unresolved CUPs had high-medium confidence GEP predictions. Diagnostic DNA features were interrogated in 201 CUP tumours guided by the cancer type specificity of mutations observed across 22 cancer types from the AACR Project GENIE database (77,058 tumours) as well as mutational signatures (e.g. smoking). Among the clinicopathology-unresolved CUPs, mutations and mutational signatures provided additional diagnostic evidence in 31% of cases. GEP classification was useful in only 13% of cases and oncoviral detection in 4%. Among CUPs where genomics informed TOO, lung and biliary cancers were the most frequently identified types, while kidney tumours were another identifiable subset. In conclusion, DNA and RNA profiling supported an unconfirmed TOO diagnosis in one-third of CUPs otherwise unresolved by clinicopathology assessment alone. DNA mutation profiling was the more diagnostically informative assay. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The Integrated 31-Gene Expression Profile (i31-GEP) Test for Cutaneous Melanoma Outperforms a Clinicopathologic-only Nomogram at Identifying Patients who can Forego Sentinel Lymph Node Biopsy

Introduction: National guidelines for cutaneous melanoma suggest avoiding sentinel lymph node biopsy (SLNB) if the risk of SLN positivity is <5% (T1a with no high-risk features), considering SLNB if the risk is 5-10% (T1a with additional high-risk features (T1aHR) and T1b), and offering SLNB if the risk is >10% (T2-T4). Because most patients (88%) who undergo an SLNB have a negative result, novel tools to identify patients who can safely forgo SLNB are critical. The integrated 31-gene expression profile (i31-GEP for SLNB) test for cutaneous melanoma combines tumor molecular biology with clinicopathologic features to provide a precise risk of SLN positivity. The Melanoma Institute of Australia (MIA) developed a nomogram that uses only clinicopathologic features to predict SLN positivity.
 Methods: We compared the i31-GEP for SLNB to the MIA nomogram in patients with T1-T2 tumors with complete data (n=582). The precision of each tool to identify patients with <5% SLN positivity risk was analyzed using 95% confidence intervals. To be considered low risk, the predicted risk must be <5% and the upper 95% confidence interval must be ≤10%, and to be considered high-risk, the predicted risk must be >10% and the lower 95% CI ≥5%.
 Results: The i31-GEP for SLNB identified 28.5% (166/582) of patients as having a <5% risk of SLN positivity while also having an upper 95% CI ≤10% compared with 0.9% (5/582, p<0.001) using the MIA nomogram. In patients with a pre-test likelihood of SLN positivity of 5-10% (T1aHR-T1b), the i31-GEP reclassified risk in 60.2% (171/284) of patients as being <5% or >10% compared to 13.7% (39/284, p<0.001) using the MIA nomogram. In patients with a known SLN status (n=466), the i31-GEP for SLNB identified 22.1% (103/466) of patients as having <5% risk, with a 3.9% (4/103) SLN positivity rate compared to 0.6% (3/466, p<0.001) identified by the MIA as having a <5% risk with a 33.3% (1/3) SLN positivity rate.
 Conclusions: The i31-GEP test outperformed the MIA nomogram in identifying patients who could safely forego SLNB. Integrating the 31-GEP molecular risk stratification tool with clinicopathologic features provides precise SLN positivity risk to better guide patient management in patients with T1-T2 tumors, for whom SLNB guidance could be most impactful.

The Integrated 31-Gene Expression Profile Test (i31-GEP) for Cutaneous Melanoma Outperforms the CP-GEP at Identifying Patients who can Forego Sentinel Lymph Node Biopsy when Applying NCCN Guidelines

Introduction: Eighty-eight percent of patients who receive a sentinel lymph node biopsy (SLNB) receive a negative result. Current guidelines suggest avoiding SLNB if the risk of positivity is <5%. A low threshold for performing SLNB indicates worry about missing positive nodes but results in many unnecessary biopsies. The integrated 31-gene expression profile (i31-GEP) test combines the 31-GEP with Breslow thickness, age, ulceration, and mitotic rate using a validated neural network algorithm to identify patients with <5% risk by reporting a precise, individualized likelihood score. Using logistic regression, a separate GEP (8 genes plus Breslow thickness and age; CP-GEP) also aims to identify patients who can forego SLNB by binning patients into low- and high-risk categories. This study compared the i31-GEP for SLNB with the CP-GEP to identify patients who can safely forego SLNB. Methods: This study evaluated the genes, gene pathways, and relative contribution of the two gene signatures relative to clinical and pathologic factors and further analyzed patients with T1b-T2 tumors from previously published studies in U.S. cohorts for the i31-GEP (n=763) and CP-GEP (n=153). A ratio of true-to-false-negative i31-GEP for SLNB and CP-GEP test results was compared to the guideline-established ratio of 19 negatives to one missed positive (19:1) if foregoing SLNB using a 5% risk threshold. Results: The i31-GEP had a 30:1 true-to-false-negative ratio, compared to 15:1 using CP-GEP. In T1b tumors, the i31-GEP ratio increased to 35:1 compared to 14:1 using CP-GEP. Limitations: Retrospective design, which could lead to bias. Patients included in both analyses were primarily from institutional surgical centers, and referral bias may not make the result generalizable. Conclusion: Only the i31-GEP provided benefit over guideline-established care for identifying patients with low risk of SLN positivity.

The integrated 31-gene expression profile (i31-GEP) test for cutaneous melanoma outperforms a clinicopathologic-only nomogram at identifying patients who can safely forego sentinel lymph node biopsy

The integrated 31-gene expression profile (i31-GEP) test for cutaneous melanoma outperforms a clinicopathologic-only nomogram at identifying patients who can safely forego sentinel lymph node biopsy

The integrated 31-gene expression profile (i31-GEP) test for cutaneous melanoma outperforms CP-GEP at identifying patients who can safely forego sentinel lymph node biopsy

The integrated 31-gene expression profile (i31-GEP) test for cutaneous melanoma outperforms CP-GEP at identifying patients who can safely forego sentinel lymph node biopsy

Clinical Utility of Dermoscopy and 31-Gene Expression Profiling by Dermatology Providers in Melanoma Management Care.

A 31-gene expression profile (31-GEP) test that predicts metastatic risk in patients with cutaneous malignant melanoma (CMM) has previously been validated and is available for clinical use. The test dichotomizes patients into lower risk and higher risk groups based on differences that correspond to unique genetic expression patterns. Although the impact of such a test on dermatology providers' clinical decision-making has been studied, little is known about whether there exists an association between certain clinical features, such as dermoscopy, and 31-GEP results. In this retrospective analysis of 31-GEP test results ordered by dermatologists, we evaluated the frequency of dermoscopic features, using a modified dermoscopy three-point checklist, in 17 cases (n=17) and compared these findings to other key clinicopathologic features including tumor thickness, ulceration, and mitotic rate to 31-GEP results. Additionally, we evaluated the dermatologist's perspective and incorporation of GEP testing as part of patient discussion on melanoma management. 31-GEP stratified patients into 4 groups; groups 1A and 1B are considered low risk of metastasis or recurrence, while 2A and 2B are considered high risk. Of the 17 cases, we had fifteen group 1A (88.23%), one 1B (5.88%), and one 2B (5.88%) result. Overall frequency of dermoscopic features is as follows; 100% of lesions presented with asymmetry, 47% with round structures, and 70.6% with blue-white color. The average time providers spent explaining and ordering the test was 15 minutes, with a range of 10 to 20 minutes. This study represents our experience and understanding of the dermatologist’s role ordering 31-GEP in the care pathway of melanoma patients and we recommend that dermatology providers consider ordering the test for newly diagnosed CMM patients. J Drugs Dermatol. 2022;21(12): doi:10.36849/JDD.6889.

Direct Gene Expression Profile Prediction for Uveal Melanoma from Digital Cytopathology Images via Deep Learning and Salient Image Region Identification

To demonstrate that deep learning (DL) methods can produce robust prediction of gene expression profile (GEP) in uveal melanoma (UM) based on digital cytopathology images. Evaluation of a diagnostic test or technology. Deidentified smeared cytology slides stained with hematoxylin and eosin obtained from a fine needle aspirated from UM. Digital whole-slide images were generated by fine-needle aspiration biopsies of UM tumors that underwent GEP testing. A multistage DL system was developed with automatic region-of-interest (ROI) extraction from digital cytopathology images, an attention-based neural network, ROI feature aggregation, and slide-level data augmentation. The ability of our DL system in predicting GEP on a slide (patient) level. Data were partitioned at the patient level (73% training; 27% testing). In total, our study included 89 whole-slide images from 82 patients and 121 388 unique ROIs. The testing set included 24 slides from 24 patients (12 class 1 tumors; 12 class 2 tumors; 1 slide per patient). Our DL system for GEP prediction achieved an area under the receiver operating characteristic curve of 0.944, an accuracy of 91.7%, a sensitivity of 91.7%, and a specificity of 91.7% on a slide-level analysis. The incorporation of slide-level feature aggregation and data augmentation produced a more predictive DL model (P= 0.0031). Our current work established a complete pipeline for GEP prediction in UM tumors: from automatic ROI extraction from digital cytopathology whole-slide images to slide-level predictions. Our DL system demonstrated robust performance and, if validated prospectively, could serve as an image-based alternative to GEP testing.

32344 The 31-gene expression profile stratifies recurrence and metastasis risk in patients with cutaneous melanoma

Background: Sentinel node biopsy is a prognostic indicator of melanoma recurrence. We hypothesized that the addition of the primary melanoma molecular signature from the 31-gene expression profile (31-GEP) test could refine the risk of recurrence for patients with a negative, positive, or no sentinel node biopsy, respectively. Materials and methods: Kaplan-Meier, Cox regression, and accuracy metrics were retrospectively analyzed for 438 patients with stage I-III melanoma from 2 surgical oncology centers and 1 dermatology center, consecutively tested with the 31-GEP test. Patients were stratified by the 31-GEP as low-risk (Class 1A), intermediate-risk (Class 1B/2A), and high-risk (Class 2B) of recurrence or metastasis. Results: The 31-GEP significantly stratified patient risk for RFS (P < .001), DMFS (P < .001), and MSS (P < .001), and was a significant, independent predictor of metastatic recurrence (HR 5.38, P = .014). Combining the 31-GEP with sentinel lymph node status identified patients with higher (26.7%; Class 2B/node-positive) or lower (2.0%; Class 1A/node-negative) recurrence risk than if using SLN status alone. Conclusions: The 31-GEP improves prognostic accuracy in stage I-III melanoma.

Comparative Metastatic Rates in GEP Class 1A versus 1B Posterior Uveal Melanoma: Results Contrary to Expectations

Purpose: The purpose of this study was to determine whether the metastatic rates in patients with gene expression profile (GEP) class 1A versus 1B posterior uveal malignant melanoma supported or contradicted predictions of very low metastatic rate in GEP 1A cases and moderate rate in GEP 1B cases. Patients/Methods: 164 patients with a cytopathologically confirmed primary posterior uveal malignant melanoma classified by GEP testing as class 1 (100 GEP 1A, 64 GEP 1B) were evaluated. Kaplan-Meier rates of metastasis were computed and plotted for the GEP class 1 subgroups. Median follow-up of patients who were still alive without metastasis on the date of data analysis was 100.5 months for the GEP 1A patients and 97.2 months for the GEP 1B patients. Results: The actuarial 5-year rate of uveal melanoma metastasis was 10.8% (std. error = 3.2%) in the GEP 1A patients versus 0% in the GEP 1B patients, and the actuarial 10-year rate of metastasis was 12.2% (std. error = 3.5%) in the GEP 1A patients versus 2.1% (std. error 2.1%) in the GEP 1B patients. Conclusion: The results of this retrospective single-center study cast doubt on the validity of the prognostic stratification of GEP class 1 posterior uveal malignant melanomas into very low risk (GEP 1A) versus intermediate risk (GEP 1B) of metastasis subgroups provided by the commercially available GEP test.

Hospital Rurality and Gene Expression Profiling for Early-Stage Breast Cancer among Iowa Residents (2010-2018).

Objective Given the challenges rural cancer patients face in accessing cancer care as well as the slower diffusion and adoption of new medical technologies among rural providers, the aim of our study was to examine trends in gene expression profiling (GEP) testing and evaluate the association between hospital rurality and receipt of GEP testing. Methods Data from the Iowa Cancer Registry (ICR) were used to identify women with newly diagnosed, histologically confirmed breast cancer from 2010 through 2018 who met eligibility criteria for GEP testing. Patients were allocated to the hospitals where their most definitive surgical treatment was received, and Rural-Urban Commuting Area codes were used to categorize hospitals into urban (N = 43), large rural (N = 16), and small rural (N = 48). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression to evaluate the association between hospital rurality and GEP test use, adjusting for demographic and clinical characteristics. The association between test result and treatment received was assessed among patients who received Oncotype DX (ODX) testing. Results Of 6,726 patients eligible for GEP test use, 46% (N = 3,069) underwent testing with 95% receiving ODX. While overall GEP testing rates increased over time from 42% between 2010 and 2012 to 51% between 2016 and 2018 (Ptrend < 0.0001), use continued to be the lowest among patients treated at hospitals in small rural areas. The odds of GEP testing remained significantly lower among patients treated at hospitals located in small rural areas (aOR 0.55; 95% CI 0.43–0.71), after adjusting for demographic and clinical characteristics. ODX recurrence scores were highly correlated with chemotherapy use across all strata of hospital rurality. Conclusions GEP testing continues to be underutilized, especially among those treated at small rural hospitals. Targeted interventions aimed at increasing rates of GEP testing to ensure the appropriate use of adjuvant chemotherapy may improve health outcomes and lower treatment-related costs.

Adjuvant crizotinib in high-risk uveal melanoma following definitive therapy.

IntroductionApproximately 40% of patients with uveal melanoma (UM) will develop metastatic disease. Tumors measuring at least 12mm in basal diameter with a class 2 signature, as defined by a widely used gene expression-profiling test, are associated with significantly higher risk of metastasis, with a median time to recurrence of 32 months. No therapy has been shown to reduce this risk.Materials and MethodsThis was a single-arm, multicenter study in patients with high-risk UM who received definitive treatment of primary disease and had no evidence of metastasis. Patients were consecutively enrolled to receive 12 four-week cycles of adjuvant crizotinib at a starting dose of 250mg twice daily and were subsequently monitored for 36 months. The primary outcome of this study was to assess recurrence-free survival (RFS) of patients with high-risk UM who received adjuvant crizotinib.Results34 patients enrolled and received at least one dose of crizotinib. Two patients were unevaluable due to early withdrawal and loss to follow-up, leaving 32 patients evaluable for efficacy. Eight patients (25%) did not complete the planned 48-week course of treatment due to disease recurrence (n=5) or toxicity (n=3). All patients experienced at least one adverse event (AE), with 11/34 (32%) experiencing a Common Terminology Criteria for Adverse Events (CTCAE) grade 3 or 4 AE. After a median duration of follow up of 47.1 months, 21 patients developed distant recurrent disease. The median RFS was 34.9 months (95% CI (Confidence Interval), 23-55 months), with a 32-month recurrence rate of 50% (95% CI, 33-67%). Analysis of protein contents from peripheral blood extracellular vesicles in a subset of patient samples from baseline, on-treatment, and off-treatment, revealed a change in protein content associated with crizotinib exposure, however without a clear association with disease outcome.ConclusionsThe use of adjuvant crizotinib in patients with high-risk UM did not result in improved RFS when compared to historical controls. Analysis of blood extracellular vesicles revealed changes in protein content associated with treatment, raising the possibility of future use as a biomarker. Further investigation of adjuvant treatment options are necessary for this challenging disease.

Attitudes of patients with cutaneous melanoma toward prognostic testing using the 31-gene expression profile test.

Although most patients diagnosed with early-stage cutaneous melanoma (CM) have excellent outcomes, because of the large number diagnosed each year, many will experience recurrence or death. Prognostic testing for CM using the 31-gene expression profile (31-GEP) test can benefit patients by helping guide risk-appropriate treatment and surveillance plans. We sought to evaluate patients' attitudes toward prognostic testing with the 31-GEP and assess whether patients experience decision regret about having 31-GEP testing. A 43-question survey was distributed by the Melanoma Research Foundation in June-August 2021 to CM patients enrolled in their database. Patients were asked questions regarding their decision to undergo 31-GEP testing and the extent to which they experienced decision regret using a validated set of Decision Regret Scale questions. We analyzed responses from patients diagnosed in 2014 or later (n = 120). Of these, 28 had received 31-GEP testing. Most respondents (n = 108, 90%) desired prognostic information when diagnosed. Of those who received 31-GEP testing, most felt the results were useful (n = 22 out of 24) and had regret scores significantly less than neutral regret, regardless of their test results (Class 1: p < 0.001; Class 2: p = 0.036). Further, decision regret scores were not significantly different between patients who received a Class 1 31-GEP result and those who received a Class 2 result (mean Class 1=1.39 and mean Class 2=1.90, p = 0.058). Most newly diagnosed CM patients desired prognostic information about their tumors. Patients who received 31-GEP testing felt it was useful and did not regret their decision to undergo 31-GEP testing.

Predicted vs Observed Metastasis-Free Survival in Individuals With Uveal Melanoma

Accuracy of the predicted metastasis-free survival (MFS) by a commercially available gene expression profiling (GEP) test is not known. To compare the predicted MFS with the observed MFS in patients in this cohort and with those in published studies (published MFS, meta-analysis). This cohort study included consecutive patients from the University of Iowa and Cleveland Clinic who were diagnosed with uveal melanoma who underwent prognostic fine-needle aspiration biopsy at the time of primary treatment. Patients were recruited from December 2012 to December 2020. The predicted MFS for patients was extracted from the GEP report. The observed MFS was defined as time to metastasis. Cox proportional hazards models were fit to identify tumor variables impacting MFS in patients with class 2 tumors. The overall estimate of the published MFS was obtained by performing meta-analysis of data from published series. Analysis took place in August 2021. MFS. There were 92 patients from the University of Iowa and 255 patients from the Cleveland Clinic. The mean (SD) age at diagnosis was 59.4 (13.0) years. The median (IQR) follow-up interval was 38.0 (19.0-57.0) months. The observed MFS for patients with class 2 tumor in this cohort (3 years: 67% [95% CI, 59%-77%]; 5 years: 47% [95% CI, 37%-61%]) and in published studies (3 years: 62% [95% CI, 57%-66%]; 5 years: 40% [95% CI, 34%-46%]) were better than those predicted (50% and 28% for 3 and 5 years, respectively). Within patients with class 2 tumor, those with metastasis had larger tumors compared with nonmetastatic tumors (mean largest basal diameter difference, 1.7 [95% CI, 0.5-3.0] mm; P = .01; mean thickness ratio, 1.3 [95% CI, 1.04-1.5]; P = .01, respectively). An increasing tumor size was significantly associated with increased hazard ratio (1.16 [95% CI, 1.06-1.27]; P < .001) of metastasis. These findings suggest the predicted MFS for metastatic tumors (class 2) appears to be worse than that observed here and reported by others. Incorporation of tumor size in the prediction model may enhance its accuracy. Adjuvant therapy trials may not be able to rely on predicted MFS to calculate efficacy with a high degree of confidence.

LB1003 The 31-GEP stratifies risk of recurrence and metastasis in 894 medicare-eligible patients with cutaneous melanoma

Background: The incidence of cutaneous melanoma (CM) is rising, particularly among older patients who generally have worse outcomes than younger patients. The 31-gene expression profile (GEP) test stratifies patient risk of recurrence and metastasis into low (Class 1A), intermediate (Class 1B/2A), and high risk (Class 2B). The study goal was to demonstrate the 31-GEP provides critical risk information for Medicare-eligible patients, allowing providers to identify patients who may benefit from increased surveillance or therapeutic treatment. Methods: Retrospective analysis of patients over 65 years old enrolled in previous studies who received 31-GEP testing (n=894). Recurrence-free survival (RFS) and distant metastasis-free survival (DMFS) were assessed using Kaplan-Meier, log-rank test, and Cox regression multivariable analysis. Results: Patients with a Class 1A 31-GEP result had higher 5-year RFS (93.9% vs. 52.0%, p<0.001) and DMFS (96.3% vs. 64.8%, p<0.001) than patients with a Class 2B result. A Class 2B result was a significant predictor for RFS (HR=4.66, p<0.001) and DMFS (5.34, p<0.001) in multivariable analysis including AJCC 8th edition stage. Stage II (RFS: HR=2.37, p<0.001; DMFS: HR=1.83, p=0.033) and stage III disease (RFS: HR=6.22, p<0.001; DMFS: HR=6.20, p<0.001) were also significant. Older patients with a negative SLNB and a Class 1A 31-GEP result had higher 5-year RFS (88.2% vs. 53.0%, p<0.001) and DMFS (93.0% VS. 69.4%, p<0.001) than those with a Class 2B result. Class 1A patients who did not receive a SLNB had high RFS (98.2%) and DMFS (99.1%). Conclusions: The 31-GEP test stratified risk of recurrence and survival in Medicare-eligible patients and added independent prognostic information to current staging methods. In patients with a potentially large number of comorbidities, identifying those who can forego more extensive therapy is vital.

LB881 Clinical utility of dermoscopy and 31-gene expression profiling by dermatology providers in melanoma management care

A 31-gene expression profile (31-GEP) test that predicts metastatic risk in patients with cutaneous malignant melanoma (CMM) has previously been validated and is available for clinical use. The test dichotomizes patients into lower risk and higher risk groups based on differences that correspond to unique genetic expression pattern. Although the impact of such a test on dermatology provider’s clinical decision-making has been studied, little is known about whether there exists an association between certain clinical features, such as dermoscopy, and 31-GEP results.

Optimizing treatment approaches for patients with cutaneous melanoma by integrating clinical and pathologic features with the 31-gene expression profile test

Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher staged patients will not. To develop an algorithm by integrating the 31-gene expression profile test with clinicopathologic data for an optimized, personalized risk of recurrence (integrated 31 risk of recurrence [i31-ROR]) or death and use i31-ROR in conjunction with a previously validated algorithm for precise sentinel lymph node positivity risk estimates (i31-SLNB) for optimized treatment plan decisions. Cox regression models for ROR were developed (n=1581) and independently validated (n=523) on a cohort with stage I-III melanoma. Using National Comprehensive Cancer Network cut points, i31-ROR performance was evaluated using the midpoint survival rates between patients with stage IIA and stage IIB disease as a risk threshold. Patients with a low-risk i31-ROR result had significantly higher 5-year recurrence-free survival (91% vs 45%, P<.001), distant metastasis-free survival (95% vs 53%, P<.001), and melanoma-specific survival (98% vs 73%, P<.001) than patients with a high-risk i31-ROR result. A combined i31-SLNB/ROR analysis identified 44% of patients who could forego sentinel lymph node biopsy while maintaining high survival rates (>98%) or were restratified as being at a higher or lower risk of recurrence or death. Multicenter, retrospective study. Integrating clinicopathologic features with the 31-GEP optimizes patient risk stratification compared to clinicopathologic features alone.

Validation of the 31-gene expression profile test to stratify melanoma-specific survival in an unselected, prospectively tested cohort of patients with stage IIB-III cutaneous melanoma.

e21538 Background: Given recent FDA extended approval of Pembrolizumab for stage IIB-IIC cutaneous melanoma (CM) patients, it is critical to risk-stratify patients to balance potential benefits versus toxicities of adjuvant therapy. The 31-gene expression profile (31-GEP) is a validated test for CM for risk of recurrence or metastasis prognosis in patients with stage I-III CM. A low-risk (Class 1A) 31-GEP result is associated with lower recurrence risk and higher melanoma-specific survival than an intermediate (Class 1B/2A) or high-risk (Class 2B) result. To validate the 31-GEP’s ability to stratify patients’ risk in an unselected, prospectively tested cohort of therapy-eligible CM patients, we collaborated with the National Cancer Institute and the Surveillance, Epidemiology, and End Results (SEER) program. Methods: A linkage was conducted between SEER registries’ CM cases diagnosed 2012-2018, and 31-GEP tested patients between 2013-2020. A de-identified dataset was used for the analysis. Kaplan-Meier analysis with log-rank test was used to analyze patient melanoma-specific survival (MSS) in the overall cohort and the subset of patients with potential adjuvant therapy access: stage IIB-III melanoma (n = 615). Results: In the overall cohort of patients (N = 5,225), those with a 31-GEP Class 1A result had higher 3-year MSS than patients with a Class 2B result (99.7% vs. 90.4%, p &lt; 0.001). In multivariable Cox regression analysis, a Class 2B result was an independent significant predictor of MSS (HR = 5.71, p = 0.01), as were age (HR = 1.05, p &lt; 0.001), SLN positivity (HR = 2.42, p = 0.02), and T2b (HR = 8.29, p = 0.025) and T4b (HR = 11.99, p = 0.009) tumors. In the subset of patients with stage IIB-III melanoma, those with a 31-GEP Class 1A result had higher 3-year MSS (98.8% vs. 82.4%, p = 0.02) than patients with a Class 2B result. Patients with a Class 2B result had a five and a half times higher event rate than those with a Class 1A result for MSS (5.5% [21/382] vs. 1.0% [1/105]). Conclusions: In a large, unselected, prospectively tested cohort of patients with stage I-III CM, the 31-GEP stratified patient risk of dying from melanoma, validating previous studies. While the 31-GEP identified a subgroup (Class 1A) of traditionally high-risk patients (stage IIB-III CM) who had a &gt; 98% MSS over three years, it can also facilitate identifying patients who could warrant earlier adjuvant therapy with a higher 31-GEP class designation.

Combining donor derived cell free DNA and gene expression profiling for non-invasive surveillance after heart transplantation.

Donor-derived cell free DNA (dd-cfDNA) and gene expression profiling (GEP) offer noninvasive alternatives to rejection surveillance after heart transplantation; however, there is little evidence on the paired use of GEP and dd-cfDNA for rejection surveillance. A single center, retrospective analysis of adult heart transplant recipients. A GEP cohort, transplanted from January 1, 2015 through December 31, 2017 and eligible for rejection surveillance with GEP was compared to a paired testing cohort, transplanted July 1, 2018 through June 30, 2020, with surveillance from both dd-cfDNA and GEP. The primary outcomes were survival and rejection-free survival at 1year post-transplant. In total 159 patients were included, 95 in the GEP and 64 in the paired testing group. There were no differences in baseline characteristics, except for less use of induction in the paired testing group (65.6%) compared to the GEP group (98.9%), P<.01. At 1-year, there were no differences between the paired testing and GEP groups in survival (98.4% vs. 94.7%, P=.23) or rejection-free survival (81.3% vs. 73.7% P=.28). Compared to post-transplant rejection surveillance with GEP alone, pairing dd-cfDNA and GEP testing was associated with similar survival and rejection-free survival at 1year while requiring significantly fewer biopsies.

238P Budget impact analysis for the health care package by using MammaPrint in Belgium

Gene expression profiling (GEP) tests are used to stratify breast cancer patients between those who benefit and those who have little or no benefit from chemotherapy. The MammaPrint® 70-gene signature can be used to support the treatment decisions for early-stage breast cancer patients and identifies genomic Low Risk patients who may safely forgo chemotherapy. As a result, a reduction of all costs related to chemotherapy and its side effects is expected. This analysis evaluates the budget impact of using MammaPrint® in Belgium.