Gene Expression Profile Test Research Articles

Response to a Letter to the Editor regarding “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”

Response to a Letter to the Editor regarding “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”

Clinical Utility of the 31-Gene Expression Profile Test on the Management of Cutaneous Melanoma by Nurse Practitioners and Physician Assistants.

The 31-gene expression profile (31-GEP) can predict the risk of recurrence and metastasis in cutaneous melanoma (CM). We assessed the viewpoints and use of 31-GEP testing by physician assistants (PAs) and nurse practitioners (NPs) for patients with CM. NPs and PAs (n = 369) completed an 18-question online survey about their viewpoints and use of the 31-GEP risk-stratification test. Most practitioners (n = 334, 90.5%) felt prognostic testing improved patient care and would recommend the 31-GEP to a colleague (n = 333, 90.2%) or a friend or family member (n = 289, 78.3%) who was diagnosed with CM. The 31-GEP test was used by 176 respondents in the preceding 12 months (53%). Among users of the 31-GEP test, 78% stated that the results would impact follow-up schedule and referral, 66% overall treatment decisions, 62% sentinel lymph node biopsy recommendations, and 50% surveillance imaging. In thin tumors (≤ 1 mm), 82% of 31-GEP users and 44% of nonusers stated that the 31-GEP results would impact their treatment plan decisions. The 31-GEP test significantly impacts treatment plans in CM, particularly for thin and stage I melanomas. Importantly, even nonusers stated that 31-GEP test results would impact treatment plans as well as recommendations to a friend or family member.

43858 The 31-gene expression profile test for cutaneous melanoma identifies patients with stage IB- IIA disease who have recurrence risk similar to that of stage IIB-IIC disease

43858 The 31-gene expression profile test for cutaneous melanoma identifies patients with stage IB- IIA disease who have recurrence risk similar to that of stage IIB-IIC disease

Combining the 31-gene expression profile test for cutaneous melanoma with the American Joint Committee on Cancer staging identifies the highest-risk patients with stage I-II disease

Introduction: Management guidelines for cutaneous melanoma (CM) are based on patients’ recurrence risk by stage. Most newly diagnosed patients (88%) will be categorized as node-negative (stage I-II) and will be considered low-risk. However, because of the size of this group, the small percentage of stage I-II individuals who do die of melanoma account for the majority of melanoma-associated deaths. In collaboration with the Surveillance, Epidemiology, and End Results (SEER) program, we demonstrated, in a large, unselected cohort of clinically tested patients, that the 31-GEP test identifies those individuals with stage I-II disease, who have higher risk of melanoma-specific death and who may benefit from more aggressive management. 
 Methods: SEER registries linked individuals diagnosed with CM between 2013-2018 were linked to data for 31-GEP-tested patients (N=9,207 after exclusions). For this study, analysis focused on the subset reported as node-negative (N=6,301). Patient 5-year melanoma-specific survival (MSS) was estimated using Kaplan-Meier analysis and the log-rank test for patients considered by the 31-GEP to be low-risk (Class 1A), intermediate-risk (Class 1B/2A), or high-risk (Class 2B). Multivariable Cox regression analysis was used to evaluate significant predictors of melanoma-specific death. Notably, at the time of diagnosis, none of the immune checkpoint inhibitor or targeted signal transduction therapies were approved for use in node-negative patients, providing a largely contemporary therapy naïve cohort. 
 Results: Patients with a Class 2B 31-GEP result had significantly lower 5-year MSS than patients with Class 1B/2A or Class 1A results (85.0% vs. 95.6% vs. 97.9%, p<0.001). The 31-GEP Class 2B result (HR=4.08, p<0.001) was the strongest predictor of melanoma-specific death. Breslow thickness (HR=1.16, p=0.002), presence of ulceration (HR=2.10, p=0.006), and age (HR=1.05, p<0.001) were also significant predictors of melanoma-specific death. The 31-GEP had a sensitivity of 78.4% and a negative predictive value (NPV) of 99.4%. Combining the 31-GEP Class result with AJCC staging could increase the sensitivity to 82.0% while maintaining a high NPV (99.4%). 
 Conclusion: In a large, unselected cohort of patients with stage I-II CM, the 31-GEP Class 2B identified patients with a high risk of progression and death from melanoma who should be considered for more aggressive management. Conversely, the high NPV suggests that the 31-GEP reliably identifies patients at low risk of tumor progression who could safely avoid intensive surveillance and intervention.

Real world validation of an adjunctive gene expression–profiling assay for melanoma diagnosis and correlation with clinical outcomes at an academic center

A commercially available diagnostic gene expression profiling (GEP) assay (MyPath™) reportedly has high sensitivity and specificity in distinguishing nevi from melanoma based on manufacturer-conducted studies. However, data regarding the performance of this GEP assay in routine clinical practice are lacking. The purpose of this study was to better assess the real-world performance of GEP in a large academic practice. Retrospective review of GEP scores were compared with final histomorphologic interpretation on a wide spectrum of melanocytic lesions demonstrating some degree of atypia. In a sample of 369 lesions, the sensitivity (76.1%) and specificity (83.9%) of the GEP test as compared with final dermatopathologist-rendered diagnosis in our dataset was appreciably lower than that reported in the prior manufacturer-conducted validation studies. Limitations of this study were that it was a single-center study, its retrospective nature, nonblinded nature of GEP test result, concordance of only two pathologists, and limited follow-up time.The sensitivity and specificity of a commercially available GEP diagnostic assay for melanoma may be lower in routine clinical practice, where melanocytic lesions typically exhibit some degree of histomorphologic atypia. Reported cost effectiveness of GEP testing is questionable if all ambiguous lesions that undergo such testing are re-excised in clinical practice.

Real-world impact of TAILORx on chemotherapy use and SOFT/TEXT on ovarian function suppression uptake in a population based-cohort of women 40 years and under with HR-positive, HER2-negative, axillary lymph node negative breast cancer.

534 Background: Gene expression profiling (GEP) testing is prognostic for distant recurrence risk in women with hormone receptor positive (HR+), human epidermal growth factor receptor-2 negative (HER2-), axillary lymph node negative (LN-) breast cancer (BC). The TAILORx trial generated prospective evidence demonstrating the 21-gene recurrence score (RS) is also predictive of chemotherapy (CT) benefit. The literature suggests that GEP testing reduces adjuvant CT prescription and is cost-effective. In the same era, the SOFT/TEXT trials demonstrated disease-free survival benefit for the addition of ovarian function suppression (OFS) to endocrine therapy in premenopausal women. Real-world uptake and impact of these advances in the management of HR+, HER2-, LN- BC in young women may be limited due to complex reasons. This retrospective study evaluated GEP and CT use post TAILORx and OFS use post SOFT/TEXT in women 40 years old or younger diagnosed with HR+, HER2-, LN BC from 2011 to 2020 in Alberta, Canada. Methods: Clinical variables were retrieved from the Alberta Health Services Cancer Care Breast Data Mart and through review of the electronic medical record. GEP testing and CT use were compared between 3 cohorts of women defined by diagnosis: pre RS funding/pre TAILORx (before April 2014), post RS funding/pre TAILORx (April 2014-May 2018), post TAILORx (June 2018 and beyond). OFS use was compared between 2 cohorts of women defined by diagnosis pre- and post SOFT/TEXT (May 2015). In subgroup analyses, we compared CT use by GEP status and RS category and OFS use by CT status. Results: Among the 291 women identified, GEP testing increased by 37% post GEP funding (pre 2% vs. post 39%; P = < .0001) and by additional 15% post TAILORx (pre 39% vs. post 54%; P < .0001) whereas overall CT use declined by 15% post GEP funding (pre 85% vs. post 70%; P = .01) and by additional 16% post TAILORx (pre 70% vs. post 54%; P = .01). Although not significant, OFS use increased by 8% post SOFT/TEXT (pre 13% vs. post 21%; P = .08). In subgroup analyses, post TAILORx was associated with a significant reduction in CT use of 19.5% in non-GEP tested women (pre 85% vs. post 65% P = .01) and non-significant increase in CT use of 6% in RS tested women (pre 40% vs. post 46%; P = .61) mainly driven by high mid range RS 21-25 and lower high range RS 26-30. There was no significant change in OFS use in non-CT treated women post SOFT/TEXT (Pre 5.3% vs. Post 8%, P = .68) whereas OFS use increased by 15% in women treated with CT post SOFT/TEXT (pre 15% vs. post 30%; P = .01). Conclusions: Public GEP funding and TAILORx led to widespread adoption of GEP and real-world decline in CT use in women 40 years of age or younger diagnosed with HR+, HER2-, LN- BC in Alberta. SOFT/TEXT led to real-world incline in OFS use in those treated with CT but adoption remained suboptimal.

31-Gene Expression Profile Testing in Cutaneous Melanoma and Survival Outcomes in a Population-Based Analysis: A SEER Collaboration.

The DecisionDx-Melanoma 31-gene expression profile (31-GEP) test is validated to classify cutaneous malignant melanoma (CM) patient risk of recurrence, metastasis, or death as low (class 1A), intermediate (class 1B/2A), or high (class 2B). This study aimed to examine the effect of 31-GEP testing on survival outcomes and confirm the prognostic ability of the 31-GEP at the population level. Patients with stage I-III CM with a clinical 31-GEP result between 2016 and 2018 were linked to data from 17 SEER registries (n = 4,687) following registries' operation procedures for linkages. Melanoma-specific survival (MSS) and overall survival (OS) differences by 31-GEP risk category were examined using Kaplan-Meier analysis and the log-rank test. Crude and adjusted hazard ratios (HRs) were calculated using Cox regression model to evaluate variables associated with survival. 31-GEP tested patients were propensity score-matched to a cohort of non-31-GEP tested patients from the SEER database. Robustness of the effect of 31-GEP testing was assessed using resampling. Patients with a 31-GEP class 1A result had higher 3-year MSS and OS than patients with a class 1B/2A or class 2B result (MSS: 99.7% v 97.1% v 89.6%, P < .001; OS: 96.6% v 90.2% v 79.4%, P < .001). A class 2B result was an independent predictor of MSS (HR, 7.00; 95% CI, 2.70 to 18.00) and OS (HR, 2.39; 95% CI, 1.54 to 3.70). 31-GEP testing was associated with a 29% lower MSS mortality (HR, 0.71; 95% CI, 0.53 to 0.94) and 17% lower overall mortality (HR, 0.83; 95% CI, 0.70 to 0.99) relative to untested patients. In a population-based, clinically tested melanoma cohort, the 31-GEP stratified patients by their risk of dying from melanoma.

Integrating the 31-gene expression profile test into clinical decision-making to guide risk-aligned care decisions for patients with stage I-III cutaneous melanoma: NCI-SEER Analysis.

6601 Background: Cutaneous melanoma (CM) management depends on an estimate of recurrence risk or death. Because of recognized disease risk and drug efficacy, pembrolizumab immunotherapy has been approved for stage IIB-C patients. However, it is a treatment with potential financial and biological toxicities with 16% of patients experiencing severe treatment related adverse events. Improved risk stratification could identify individuals for whom more selective management would be appropriate. In collaboration with the NCI Surveillance, Epidemiology, and End Results (SEER) program, which includes information on patients tested with a 31-gene expression profile (31-GEP) test in an unbiased and unselected manner, we confirm the 31-GEP adds independent prognostic value in patients with stage I-III CM, and investigated whether the 31-GEP could identify stage IIB-C patients who might reasonably avoid adjuvant therapy while also identifying patients with stage I disease who might benefit from more aggressive diagnostic and/or therapeutic intervention. Methods: SEER registries linked CM cases diagnosed 2013-2018 to 31-GEP test results provided by Castle Biosciences (9,207 matched) using a registry trusted third party (honest broker), including subsets of stage IIB-IIC (n=775) and stage I (n=5,651) melanoma. The primary endpoint was melanoma-specific survival (MSS). The 31-GEP risk-groups included Class 1A (low), Classes 1B/2A (intermediate), and Class 2B (high). Each was compared using Kaplan-Meier analysis and the log-rank test. Results: In the overall cohort, patients with a Class 1A result had a significantly higher 5-year MSS than a Class 1B/2A or Class 2B result (97.4% vs. 93.5% vs. 83.3%, p&lt;0.001). In multivariable analysis, a Class 2B result (HR=3.26, p&lt;0.001) and positive lymph node status (HR=3.41, p&lt;0.001) were the strongest predictors of diminished MSS. In stage IIB-C, 18.8% (146/775) of patients received a Class 1A result with an associated 5-year MSS of 89.1% (vs. Class 2B: 76.6%, p=0.001), despite the absence of pembrolizumab approval for the evaluated SEER population. Alternatively, 4.6% (260/5,651) of patients with stage I disease had a Class 2B result, with an associated 5-year MSS of 92.3% (vs. Class 1A: 98.0%, p&lt;0.001). Conclusions: The SEER database allowed a non-biased analysis of a large cohort of patients with stage I-III CM who were tested with the 31-GEP. The 31-GEP identifies patients, including those with stage IIB-C disease, with favorable outcomes and could help physicians and patients decide whether to pursue adjuvant therapy. Moreover, the 31-GEP identities high-risk patients, including those with stage I disease, for whom more aggressive follow-up and early intervention should be considered.

Does RSClin provide additional information over classic clinico-pathologic scores (PREDICT 2.1, Influence, CTS-5)? A TEAM Pathology substudy.

533 Background: Gene-expression profiling tests (e.g. Oncotype, Mammaprint, Prosignia, Breast Cancer Index and EndoPredict) are widely used in the care of patients with early-stage hormone positive breast cancer (node negative or 1-3 lymph nodes). However, these tests are resource intensive, and few studies have compared their value with either free and widely available clinico-pathologic risk calculators (e.g. PREDICT 2.1, INFLUENCE 2.0, and CTS-5) or tools that combine genomic testing with clinico-pathologic data (e.g. RSClin). The TEAM pathology substudy population was used to compare these different predicted model scores with outcomes. Methods: The TEAM pathology study consists of 3284 postmenopausal hormone positive breast cancer patients treated with either exemestane or tamoxifen followed by exemestane. Accrual was from 2001 to 2006. Genes comprising the multi-parametric Oncotype Dx were used to train signatures to create true assay results. Patient data was then used to calculate recurrence scores through various tools. This included clinico-pathologic models and their respective endpoints PREDICT 2.1 (overall survival at 5 years), INFLUENCE 2.0 (distant metastasis at 5 years), CTS-5 (distant recurrence risk at year 5-10), the purely genomic Oncotype Dx trained results (distant recurrence risk at 9 years), as well as the new clinico-pathologic RSClin (distant recurrence risk at 10 years). We compared the level of association between these predictive model scores using Spearman correlation coefficients. The prognostic ability of each model was contrasted for each outcome using Harrell’s C-statistic. Results: Results were available for CTS-5 (3022 patients), INFLUENCE 2.0 (3485 patients), ODx-trained (3825 patients), and RSClin (3029 patients). Correlation coefficients showed low correlation between Influence ( r= 0.25) and CTS-5 ( r= 0.17) with Oncotype-Dx trained results, and high correlation between RSClin ( r = 0.84) and Oncotype-Dx trained results. The concordance index was similar (0.65 to 0.68) for all models with distant metastasis-free survival as the outcome. Analysis is ongoing and further results will be available at the time of presentation. Conclusions: Other clinico-pathologic tools such as Influence 2.0 and CTS-5 have good prognostic ability when compared to Oncotype Dx-trained results and RSClin. [Table: see text]

Cost-Effectiveness Analysis of MammaPrint® to Guide the Use of Endocrine Therapy in Patients with Early-Stage Breast Cancer.

Gene expression profiling tests can predict the risk of disease recurrence and select patients who are expected to benefit from therapy, while allowing other patients to forgo therapy. For breast cancers, these tests were initially designed to tailor chemotherapy decisions, but recent evidence suggests that they may also guide the use of endocrine therapy. This study evaluated the cost effectiveness of a prognostic test, MammaPrint®, to guide the use of adjuvant endocrine therapy in patients eligible according to Dutch treatment guidelines. We constructed a Markov decision model to calculate the lifetime costs (in 2020 Euros) and effects (survival and quality-adjusted life-years) of MammaPrint® testing versus usual care (endocrine therapy for all patients) in a simulated cohort of patients. The population of interest includes patients for whom MammaPrint® testing is currently not indicated, but for whom it may be possible to safely omit endocrine therapy. We applied both a health care perspective and a societal perspective and discounted costs (4%) and effects (1.5%). Model inputs were obtained from published research (including randomized controlled trials), nationwide cancer registry data, cohort data and publicly available data sources. Scenario and sensitivity analyses were conducted to explore the impact of uncertainty around input parameters. Additionally, threshold analyses were performed to identify under which circumstances MammaPrint® testing would be cost effective. Adjuvant endocrine therapy guided by MammaPrint® resulted in fewer side effects, more (quality-adjusted) life-years (0.10 and 0.07 incremental QALYS and LYs, respectively) and higher costs (€18,323 incremental costs) compared with the usual care strategy in which all patients receive endocrine therapy. While costs for hospital visits, medication costs and productivity costs were somewhat higher in the usual care strategy, these did not outweigh costs of testing in the MammaPrint® strategy. The incremental cost-effectiveness ratio was €185,644 per QALY gained from a healthcare perspective and €180,617 from a societal perspective. Sensitivity and scenario analyses showed that the conclusions remained the same under changed input parameters and assumptions. Our results show that MammaPrint® can become a cost-effective strategy when either the price of the test is reduced (>50%), or the proportion of patients for which treatment is altered (i.e. those with ultra-low risk) increases to >26%. Standard MammaPrint® testing to guide the use of endocrine therapy in our simulated patient population appears not to be a cost-effective strategy compared with usual care. The cost effectiveness of the test can be improved by reducing the price or preselecting a population more likely to benefit from the test.

25. Sentinel Lymph Node Positivity in Cutaneous Melanoma and its Correlation to a 31 Gene-expression Profile Test and Two Lymph Node Risk Calculators

PURPOSE: Sentinel lymph node biopsy (SLNB) provides prognostic information and a therapeutic benefit for patients with melanoma. It is discussed at stage pT1b and is recommended for stage pT2a or higher.1 This study compared the use of available sentinel lymph node positivity risk calculators and a 31-gene expression profile test (DecisionDx) in melanoma patients undergoing SLNB. METHODS: Retrospective data of a tertiary care facility from 01/2016 to 12/2021 was analyzed of patients with melanoma that underwent a SLNB and had DecisionDx. The Melanoma Institute of Australia (MIA) and Memorial Sloan Kettering (MSK) online risk calculators were used to predict SLN positivity pre-operatively. Descriptive statistics were used to summarize major trends. Univariate statistics were used to compare subgroups. RESULTS: Two hundred and fifty-two (n=252) patients met inclusion criteria. Positive sentinel lymph nodes were identified in 12 (4.8%) patients. MSK median risk score was 10% [6%, 18%]. MIA median risk score was 12% [7%, 21%]. DecisionDx classified patients into four risk groups distributed as follows: 98 (38.9%) IA, 50 (19.8%) IB, 39 (15.5%) IIA, 65 (25.8%) IIB. Of the patients that had a positive SLNB, there was a relatively even distribution between DecisionDx classes: 3 (25%) IA, 2 (16.7%) IB, 4 (33.3%) IIA, 3 (25%) IIB. CONCLUSION: Our results indicated similar SLNB positivity rates in low- and high-risk DecisionDx profiles to existing literature.2 Most patients had similar MIA and MSK values. While a correlation between SLNB positivity and DecisionDx stage wasn’t seen, important prognostic information was still gained from obtaining the test.

A clinical impact study of dermatologists’ use of the 23- or 35-gene expression profile tests to guide surgical excision and enhance management plan confidence

Purpose: To understand how dermatologists utilize the results from ancillary diagnostic gene expression profile (dGEP) testing with the 23- or 35-GEP tests to determine optimal patient management strategies. Study: Dermatologists who regularly treat patients with difficult-to-diagnose melanocytic lesions who had previously initiated dGEP testing at least 3 times were eligible to complete the questionnaire in this Institutional Review Board-approved study. There were 24 randomized vignettes presented covering a spectrum of cases with diagnostic/clinical uncertainty such as atypical melanocytic proliferation, dysplastic nevus with regression, deep penetrating melanocytic neoplasm, and atypical intraepidermal melanocytic proliferation. Respondents were provided with a clinical impression and diagnosis in the context of a narrative pathology report with/without a re-excision recommendation; cases were also described without (baseline) and with a dGEP test result (likely benign or likely malignant). Anonymous responses concerning the patient management plan including excision and follow-up recommendations and confidence were captured. Statistical significance was calculated by nonparametric Wilcoxon signed-rank test with continuity correction. Results: In total, 32 dermatologists (84% in a private practice setting) completed the survey, with 50% indicating additional dermatopathology specialization. Approximately 44% of respondents indicated they performed 10-50 biopsies of melanocytic lesions per month, and 31%, greater than 100 per month. When dGEP results were provided, there was an overall increase in management plan confidence, regardless of which dGEP result was provided (benign dGEP 26.2%, malignant dGEP 24.7%). Also, when dGEP results were provided, changes in surgical excision recommendations were statistically significant in 75% of scenarios tested (p &lt; 0.02). Clinical impact was assessed by quantifying the directional shift in treatment in relation to the dGEP result. With regard to excision recommendations across vignettes, benign dGEP results prompted 29.7% of clinicians to decrease their margins or forgo excision altogether. Malignant dGEP results prompted 63.5% of clinicians to increase their surgical excision recommendations. Appropriate alterations in patient follow-up frequency were observed, with 18.8% of clinicians reducing and 43.2% increasing follow-up frequency for patients receiving benign or malignant dGEP results, respectively. Conclusion: The addition of dGEP testing to diagnostic scenarios with confounding clinical features and uncertainty in optimal management prompted important changes in recommendations regarding the need for excision, appropriate margins, and follow-up-frequency. Overall, dGEP tests help to guide clinical decision-making for dermatologists in a variety of otherwise diagnostically ambiguous or clinicopathologically discordant scenarios.

Improved prognostic guidance by the 31-gene expression profile test for clinical decisions after a negative lymph node for patients with cutaneous melanoma

Improved prognostic guidance by the 31-gene expression profile test for clinical decisions after a negative lymph node for patients with cutaneous melanoma

Validation of the Prognostic Usefulness of the Gene Expression Profiling Test in Patients with Uveal Melanoma

To validate the prognostic usefulness of gene expression profile (GEP) testing in patients with uveal melanoma. To determine whether combining tumor size with the GEP classification provides additional prognostic value. Retrospective analysis. Patients with a diagnosis of choroidal melanoma examined at Yale New Haven Hospital; University of California, San Diego; and Memorial Sloan Kettering Cancer Center. Patients' demographic and clinical data and tumor characteristics were collected. Univariate and multivariate Cox hazard regression analysis were used to assess the association between tumor characteristics and GEP classification with metastasis as an outcome. Metastasis-free survival (MFS). Of the 337 individuals included in the study, 87 demonstrated metastases. The mean follow-up time was 37.2 (standard deviation [SD], 40.2) months for patients with metastases and 55.0 (SD, 49.3) months for those without metastases. Tumors of larger thickness and GEP class 2 (vs. class 1) were associated significantly with increased risk of metastasis. Tumor thickness showed better prognostic usefulness than GEP classification (Wald statistic, 40.7 and 24.2, respectively). Class 2 tumors with a thickness of 7.0 mm or more were associated with increased risk of metastasis than tumors with a thickness of < 7.0 mm (hazard ratio [HR], 3.23; 95% confidence interval [CI], 1.61-6.51), whereas class 1 tumors with a thickness of 9.0 mm or more were associated with increased risk of metastasis than tumors with a thickness of < 9.0 mm (HR, 2.07; 95% CI, 0.86-4.99). No difference in MFS was found between patients with class 1A tumors compared with those with class 1B tumors (P= 0.8). Patients with class 2 tumors showed an observed 5-year MFS of 47.5% (95% CI, 36.0%-62.8%). Tumor size was the most significant predictor of metastasis and provided additional prognostic value independent of GEP classification. In addition, rates of metastasis for class 2 tumors were lower than estimates reported by Castle Bioscience, and no difference in rates of metastasis were found between class 1A and 1B tumors. This indicates that tumor size should be accounted for when relying on GEP for prognostication and that patients with GEP class 1A or 1B tumors may benefit from the same metastatic surveillance protocols. The author(s) have no proprietary or commercial interest in any materials discussed in this article.

The 31-gene expression profile test informs sentinel lymph node biopsy decisions in patients with cutaneous melanoma: results of a prospective, multicenter study

Background The 31-gene expression profile test (Class 1A: low-risk; 1B/2A: intermediate-risk; 2B: high-risk) is validated to identify patients with cutaneous melanoma who can safely forego sentinel lymph node biopsy (SLNB). The objective of the current study is to quantify SLNB reduction by clinicians using 31-GEP. Methods Patients with T1-T2 tumors eligible for SLNB were seen by surgical oncologists (89.1%), dermatologists (7.8%), and medical oncologists (3.1%). After receiving 31-GEP results but before SLNB, clinicians were asked which clinical and pathological features influenced SLNB decisions (n = 191). The Exact binomial test was used to compare SLNB procedure rates to a contemporary study (78% SLNB baseline rate). Logistic regression modeling (odds ratio [OR], 95% CI) was used to identify features associated with SLNB procedure rates. Results One hundred clinical decisions (52.4%) were influenced by the 31-GEP to forego SLNB and 70% (70/100) were not performed. Of the 30 performed, 0% (0/30) were positive. The 31-GEP influenced sixty-three clinical decisions (33.0%) to perform SLNB, and 92.1% (58/63) were performed. There was a clinically meaningful 29.4% reduction of SLNBs performed in patients with a Class 1A result relative to the baseline rate of 78.0% (p < .01). In patients ≥55 or ≥65-year-old, SLNB reduction was 32.3% (p < .01), 28.3% (p < .01), respectively. Overall, 85.3% of decisions relating to SLNB were influenced by 31-GEP results. Conclusion In this prospective, multicenter study, clinicians demonstrated clinically meaningful use of the 31-GEP test to forego or pursue SLNB in patients with T1-T2 tumors resulting in a significant, risk appropriate decrease in SLNBs.

Incorporating Prognostic Gene Expression Profile Assays into the Management of Cutaneous Melanoma: An Expert Consensus Panel

Background: Cutaneous melanoma (CM) guidelines put forth by the eighth edition of the American Joint Committee on Cancer (AJCC8) and the National Comprehensive Cancer Network (NCCN) do not currently account for lesion genomics when assessing prognosis. Gene Expression Profile (GEP) tests have become a widely adopted tool to help clinicians identify patients at higher risk for metastasis and recurrence.&#x0D; Objective: To review the available literature that has been published since a consensus panel in 2018 on three commercially available GEP tests used in the prognostic assessment of CM and create updated guidelines and consensus statements for their optimal use.&#x0D; Methods: A comprehensive literature search of PubMed and Google Scholar was conducted for relevant English-language original research articles, meta-analyses, and systematic reviews published from 2019 through 2022. A panel of 6 key opinion leaders in dermatology with specialized expertise in diagnosing and managing CM then convened to review the articles and create guidelines. A modified Delphi process was used to approve each statement. The panel assigned each article a level of evidence and each consensus statement a strength of recommendation using Strength of Recommendation Taxonomy (SORT) criteria.&#x0D; Results: The literature search identified 785 articles that met the search criteria. Of these, there were 22 articles that validated the 31-GEP test, 2 that validated the 11-GEP test, and 7 that validated the 8-GEP + CP test. The panel unanimously approved 6 usage guidelines and 5 consensus supporting statements for the appropriate use of these tests.&#x0D; Conclusion: Based on the currently available literature, GEP tests provide valuable information beyond AJCC8 and NCCN guidelines for the prognostic assessment of CM. There are significantly more validation studies supporting the use of the 31-GEP test compared to the 11-GEP test and the 8-GEP + CP test.

P128: Evaluating the utility of gene expression profile testing in pediatric melanoma: A case series

P128: Evaluating the utility of gene expression profile testing in pediatric melanoma: A case series

Tissue Biomarkers Predicting Lymph Node Status in Cutaneous Melanoma

Cutaneous melanoma is a severe neoplasm that shows early invasiveness of the lymph nodes draining the primary site, with increased risk of distant metastases and recurrence. The tissue biomarker identification could be a new frontier to predict the risk of early lymph node invasiveness, especially in cases considered by current guidelines to be at low risk of lymph node involvement and not requiring evaluation of the sentinel lymph node (SLN). For this reason, we present a narrative review of the literature, seeking to provide an overview of current tissue biomarkers, particularly vascular endothelium growth factors (VEGF), Tetraspanin CD9, lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), D2-40, and gene expression profile test (31-GEP). Among these, 31-GEP seems to be able to provide a distinction between low or high risk for positive SLN classes. VEGF receptor-3 and CD9 expression may be independent predictors of positive SLN. Lastly, LYVE-1 and D2-40 allow an easier assessment of lymph vascular invasion, which can be considered a good predictor of SLN status. In conclusion, biomarkers to assess the lymph node status of cutaneous melanoma patients may play an important role in those cases where the clinician is in doubt whether or not to perform SLN biopsy.

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.