The 31-Gene Expression Profile Test Outperforms AJCC in Stratifying Risk of Recurrence in Patients with Stage I Cutaneous Melanoma.

BACKGROUND: Patients with stage I cutaneous melanoma (CM) are considered at low risk for metastasis or melanoma specific death; however, because the majority of patients are diagnosed with stage I disease, they represent the largest number of melanoma deaths annually. The 31-gene expression profile (31-GEP) test has been prospectively validated to provide prognostic information independent of staging, classifying patients as low (Class 1A), intermediate (Class 1B/2A), or high (Class 2B) risk of poor outcomes. METHODS: Patients enrolled in previous studies of the 31-GEP were combined and evaluated for recurrence-free (RFS) and melanoma-specific survival (MSS) (n = 1261, "combined"). A second large, unselected real-world cohort (n = 5651) comprising clinically tested patients diagnosed 2013-2018 who were linked to outcomes data from the NCI Surveillance, Epidemiology, and End Results (SEER) Program registries was evaluated for MSS. RESULTS: Combined cohort Class 1A patients had significantly higher RFS than Class 1B/2A or Class 2B patients (97.3%, 88.6%, 77.3%, p < 0.001)-better risk stratification than AJCC8 stage IA (97.5%) versus IB (89.3%). The SEER cohort showed better MSS stratification by the 31-GEP (Class 1A = 98.0%, Class 1B/2A = 97.5%, Class 2B = 92.3%; p < 0.001) than by AJCC8 staging (stage IA = 97.6%, stage IB = 97.9%; p < 0.001). CONCLUSIONS: The 31-GEP test significantly improved patient risk stratification, independent of AJCC8 staging in patients with stage I CM. The 31-GEP provided greater separation between high- (Class 2B) and low-risk (Class 1A) groups than seen between AJCC stage IA and IB. These data support integrating the 31-GEP into clinical decision making for more risk-aligned management plans.

The Integrated i31-GEP Test Outperforms the MSKCC Nomogram at Predicting SLN Status in Melanoma Patients.

BACKGROUND/AIM: Sentinel lymph node biopsy (SLNB) for patients with cutaneous melanoma is primarily a prognostic procedure that broadly identifies patients who may have disease progression and may warrant additional intervention. However, 88% of patients undergoing SLNB receive a negative result and of those, some will succumb to their disease. One clinical utility of the integrated 31-GEP test, which combines gene expression data with clinicopathologic factors to provide a personalized, precise risk of SLN positivity, is SLNB guidance. This study compared the i31-GEP for SLNB to a nomogram that predicts SLN positivity using only clinicopathologic factors. PATIENTS AND METHODS: Patients with T1-T2 tumors and known SLN status (N=465) were analyzed by the i31-GEP for SLNB and a nomogram developed at Memorial Sloan Kettering Cancer Center (MSKCC). A 5% risk threshold was used to conform with national guidelines. RESULTS: In patients with <5% predicted risk, SLN positivity was 2.7% (3/111) for i31-GEP versus 10.0% (11/110, p=0.026) for MSKCC. In each T-category, the i31-GEP maintained a false-negative rate below the 5% risk threshold in those predicted to have a <5% risk, while the MSKCC nomogram did not. CONCLUSION: Integrating the 31-GEP with traditional factors outperformed a nomogram that uses clinicopathologic factors alone to predict SLN status. Incorporating the i31-GEP into clinical practice could improve identification of patients for SLNB, resulting in better risk-aligned management.

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

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: In a population-based, clinically tested melanoma cohort, the 31-GEP stratified patients by their risk of dying from melanoma.

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

BACKGROUND: Many patients with low-stage cutaneous melanoma will experience tumor recurrence, metastasis, or death, and many higher staged patients will not. OBJECTIVE: 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. METHODS: 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. RESULTS: 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. LIMITATIONS: Multicenter, retrospective study. CONCLUSION: Integrating clinicopathologic features with the 31-GEP optimizes patient risk stratification compared to clinicopathologic features alone.

Improved cutaneous melanoma survival stratification through integration of 31-gene expression profile testing with the American Joint Committee on Cancer 8th Edition Staging.

Cutaneous melanoma (CM) survival is assessed using averaged data from the American Joint Committee on Cancer 8th edition (AJCC8). However, subsets of AJCC8 stages I-III have better or worse survival than the predicted average value. The objective of this study was to determine if the 31-gene expression profile (31-GEP) test for CM can further risk-stratify melanoma-specific mortality within each AJCC8 stage. This retrospective multicenter study of 901 archival CM samples obtained from patients with stages I-III CM assessed 31-GEP test predictions of 5-year melanoma-specific survival (MSS) using Kaplan-Meier and Cox proportional hazards. In stage I-III CM population, patients with a Class 2B result had a lower 5-year MSS (77.8%) than patients with a Class 1A result (98.7%) and log-rank testing demonstrated significant stratification of MSS [χ2 (2df, n = 901) = 99.7, P < 0.001). Within each stage, 31-GEP data provided additional risk stratification, including in stage I [χ2 (2df, n = 415) = 11.3, P = 0.004]. Cox regression multivariable analysis showed that the 31-GEP test was a significant predictor of melanoma-specific mortality (MSM) in patients with stage I-III CM [hazard ratio: 6.44 (95% confidence interval: 2.61-15.85), P < 0.001]. This retrospective study focuses on Class 1A versus Class 2B results. Intermediate results (Class 1B/2A) comprised 21.6% of cases with survival rates between Class 1A and 2B, and similar to 5-year MSS AJCC stage values. Data from the 31-GEP test significantly differentiates MSM into lower (Class 1A) and higher risk (Class 2B) groups within each AJCC8 stage. Incorporating 31-GEP results into AJCC8 survival calculations has the potential to more precisely assess survival and enhance management guidance.

Circulating biomarkers associated with performance and resilience during military operational stress.

Adaptation to military operational stress is a complex physiological response that calls upon the sympathetic nervous system (SNS), hypothalamic pituitary adrenal (HPA) axis and immune system, to create a delicate balance between anabolism and catabolism and meet the demands of an ever-changing environment. As such, resilience, the ability to withstand and overcome the negative impact of stress on military performance, is likely grounded in an appropriate biological adaptation to encountered stressors. Neuroendocrine [i.e. cortisol, epinephrine (EPI), norepinephrine (NE), neuropeptide-Y (NPY), and brain derived neurotropic factor (BDNF)], inflammatory [i.e. interleukin 6 (IL-6), IL-1ß, IL-4, IL-10 and tumour necrosis factor (TNF)-α], as well as growth and anabolic [i.e. insulin-like growth factor-I (IGF-I), testosterone, and dehydroepiandrosterone (DHEA)] biomarkers independently and interactively function in stress adaptations that are associated with a soldier's physical and psychological performance. In this narrative review, we detail biomarkers across neuroendocrine, inflammatory, and growth stimulating domains to better elucidate the biological basis of a resilient soldier. The findings from the reviewed studies indicate that military readiness and resiliency may be enhanced through better homeostatic control, better regulated inflammatory responses, and balanced anabolic/catabolic processes. It is unlikely that one class of biomarkers is better for assessing physiological resilience. Therefore, a biomarker panel that can account for appropriate balance across these domains may be superior in developing monitoring frameworks. Real-time physiological monitoring to assess biomarkers associated with resilience will be possible pending more sophisticated technologies and provide a field-expedient application for early identification and intervention of at-risk soldiers to improve military resiliency.

Integrating 31-Gene Expression Profiling With Clinicopathologic Features to Optimize Cutaneous Melanoma Sentinel Lymph Node Metastasis Prediction.

National guidelines recommend sentinel lymph node biopsy (SLNB) be offered to patients with > 10% likelihood of sentinel lymph node (SLN) positivity. On the other hand, guidelines do not recommend SLNB for patients with T1a tumors without high-risk features who have < 5% likelihood of a positive SLN. However, the decision to perform SLNB is less certain for patients with higher-risk T1 melanomas in which a positive node is expected 5%-10% of the time. We hypothesized that integrating clinicopathologic features with the 31-gene expression profile (31-GEP) score using advanced artificial intelligence techniques would provide more precise SLN risk prediction. METHODS: An integrated 31-GEP (i31-GEP) neural network algorithm incorporating clinicopathologic features with the continuous 31-GEP score was developed using a previously reported patient cohort (n = 1,398) and validated using an independent cohort (n = 1,674). RESULTS: Compared with other covariates in the i31-GEP, the continuous 31-GEP score had the largest likelihood ratio (G2 = 91.3, P < .001) for predicting SLN positivity. The i31-GEP demonstrated high concordance between predicted and observed SLN positivity rates (linear regression slope = 0.999). The i31-GEP increased the percentage of patients with T1-T4 tumors predicted to have < 5% SLN-positive likelihood from 8.5% to 27.7% with a negative predictive value of 98%. Importantly, for patients with T1 tumors originally classified with a likelihood of SLN positivity of 5%-10%, the i31-GEP reclassified 63% of cases as having < 5% or > 10% likelihood of positive SLN, for a more precise, personalized, and clinically actionable SLN-positive likelihood estimate. CONCLUSION: These data suggest the i31-GEP could reduce the number of SLNBs performed by identifying patients with likelihood under the 5% threshold for performance of SLNB and improve the yield of positive SLNBs by identifying patients more likely to have a positive SLNB.

Risk Stratification of Patients with Stage I Cutaneous Melanoma Using 31-Gene Expression Profiling.

BACKGROUND: While patients with localized cutaneous melanoma (CM) generally have good five-year melanoma-specific survival rates, identifying patients with localized disease at a high risk of recurrence could allow them access to additional follow-up or surveillance. OBJECTIVE: We sought to examine the prognostic value of the 31-gene expression profile (31-GEP) test for the risk of recurrence in stage I CM patients according to 31-GEP main class (low risk: Class 1 vs. high-risk: Class 2) and the lowest and highest risk 31-GEP subclasses (Class 1A vs. Class 2B). METHODS: Data from a previously described meta-analysis detailing the 31-GEP results for patients with stage I CM (N = 623) were re-analyzed to determine 31-GEP accuracy. RESULTS: Patients with stage I CM and a Class 1 31-GEP result were less likely to have a recurrence (15/556; 2.7% vs. 6/67; 9.0%; p=0.018) than patients with a Class 2 result and had a higher five-year recurrence-free survival (RFS) (96% vs. 85%). Patients with a Class 2 result were 2.8 times as likely to experience a recurrence (positive likelihood ratio: 2.82; 95% confidence interval: 1.38-5.77). In a subset of patients with stage I CM stratified further into 31-GEP subclasses (n = 206), patients with a Class 1A result had a higher five-year RFS than those with a Class 2B result (98% vs. 73%). Patients with a Class 2B result were also 6.5 times as likely to experience a recurrence (positive likelihood ratio: 6.45; 95% confidence interval: 2.44-17.00) than those with a Class 1A result, and the 31-GEP had a negative predictive value of 96.3% (95% confidence interval: 92.3%-98.4%). CONCLUSION: The 31-GEP test significantly differentiates between low and high recurrence risk in patients with stage I CM.

Effect of short-term, high-intensity exercise training on human skeletal muscle citrate synthase maximal activity: single versus multiple bouts per session.

The legs of 9 men (age 21 ± 2 years, 45 ± 4 mL/(kg·min)) were randomly assigned to complete 6 sessions of high-intensity exercise training, involving either one or four 5-min bouts of counterweighted, single-leg cycling. Needle biopsies from vastus lateralis revealed that citrate synthase maximal activity increased after training in the 4-bout group (p = 0.035) but not the 1-bout group (p = 0.10), with a significant difference between groups post-training (13%, p = 0.021). Novelty Short-term training using brief intense exercise requires multiple bouts per session to increase mitochondrial content in human skeletal muscle.

Effect of sex on the acute skeletal muscle response to sprint interval exercise.

NEW FINDINGS: What is the central question of this study? Are there sex-based differences in the acute skeletal muscle response to sprint interval training (SIT)? What is the main finding and its importance? In response to a SIT protocol that involved three 20 s bouts of 'all-out' cycling, the expression of multiple genes associated with mitochondrial biogenesis, metabolic control and structural remodelling was largely similar between men and women matched for fitness. Our findings cannot explain previous reports of sex-based differences in the adaptive response to SIT and suggest that the mechanistic basis for these differences remains to be elucidated. A few studies have reported sex-based differences in response to several weeks of sprint interval training (SIT). These findings may relate to sex-specific responses to an acute session of SIT. We tested the hypothesis that the acute skeletal muscle response to SIT differs between sexes. Sedentary but healthy men (n = 10) and women (n = 9) were matched for age (22 ± 3 versus 22 ± 3 years old) and cardiorespiratory fitness [45 ± 7 versus 43 ± 10 ml O2  (kg fat-free mass)-1  min-1 ], with women tested in the mid-follicular phase of their menstrual cycles. Subjects performed three 20 s 'all-out' cycling efforts against a resistance of 5% of body mass, interspersed with 2 min of recovery. Relative mean power outputs [7.6 ± 0.5 versus 7.5 ± 0.9 W (kg fat-free mass)-1 ] were similar between men and women (P > 0.05). Furthermore, there were no differences in the exercise-induced changes in mRNA expression of PGC-1α, PRC, PPARD, SIRT1, RIP140, HSL, HKII, PDK4, PDP1, FOXO3, MURF-1, Myf5, MyoD and VEGFA at 3 h of recovery versus rest (P < 0.05, main effect of time). The only sex-specific responses to exercise were an increase in the mRNA expression of GLUT4 and LPL in women only and Atrogin-1 in men only (P < 0.05). Women also had higher expression of HKII and lower expression of FOXO3 compared with men (P < 0.05, main effect of sex). We conclude that the acute skeletal muscle response to SIT is largely similar in young men and women. The mechanistic basis for sex-based differences in response to several weeks of SIT that has been previously reported remains to be elucidated.

Green tea extract does not affect exogenous glucose appearance but reduces insulinemia with glucose ingestion in exercise recovery.

We reported that supplementation with green tea extract (GTE) lowered the glycemic response to an oral glucose load following exercise, but via an unknown mechanism (Martin BJ, MacInnis MJ, Gillen JB, Skelly LE, Gibala MJ. Appl Physiol Nutr Metab 41: 1057-1063, 2016. Here we examined the effect of supplementation with GTE on plasma glucose kinetics on ingestion of a glucose beverage during exercise recovery. Eleven healthy, sedentary men (21 ± 2 yr old; body mass index = 23 ± 4 kg/m2, peak O2 uptake = 38 ± 7 ml·kg-1·min-1; means ± SD) ingested GTE (350 mg) or placebo (PLA) thrice daily for 7 days in a double-blind, crossover design. In the fasted state, a primed constant infusion of [U-13C6]glucose was started, and 1 h later, subjects performed a graded exercise test (25 W/3 min) on a cycle ergometer. Immediately postexercise, subjects ingested a 75-g glucose beverage containing 2 g of [6,6-2H2]glucose, and blood samples were collected every 10 min for 3 h of recovery. The rate of carbohydrate oxidation was lower during exercise after GTE vs. PLA (1.26 ± 0.34 vs. 1.48 ± 0.51 g/min, P = 0.04). Glucose area under the curve (AUC) was not different between treatments after drink ingestion (GTE = 1,067 ± 133 vs. PLA = 1,052 ± 91 mM/180 min, P = 0.91). Insulin AUC was lower after GTE vs. PLA (5,673 ± 2,153 vs. 7,039 ± 2,588 µIU/180 min, P = 0.05), despite similar rates of glucose appearance (GTE = 0.42 ± 0.16 vs. PLA = 0.43 ± 0.13 g/min, P = 0.74) and disappearance (GTE = 0.43 ± 0.14 vs. PLA = 0.44 ± 0.14 g/min, P = 0.57). We conclude that short-term GTE supplementation did not affect glucose kinetics following ingestion of an oral glucose load postexercise; however, GTE was associated with attenuated insulinemia. These findings suggest GTE lowers the insulin required for a given glucose load during postexercise recovery, which warrants further mechanistic studies in humans.

Three minutes of all-out intermittent exercise per week increases skeletal muscle oxidative capacity and improves cardiometabolic health.

We investigated whether a training protocol that involved 3 min of intense intermittent exercise per week--within a total training time commitment of 30 min including warm up and cool down--could increase skeletal muscle oxidative capacity and markers of health status. Overweight/obese but otherwise healthy men and women (n = 7 each; age = 29±9 y; BMI = 29.8±2.7 kg/m2) performed 18 training sessions over 6 wk on a cycle ergometer. Each session began with a 2 min warm-up at 50 W, followed by 3×20 s "all-out" sprints against 5.0% body mass (mean power output: ∼450-500 W) interspersed with 2 min of recovery at 50 W, followed by a 3 min cool-down at 50 W. Peak oxygen uptake increased by 12% after training (32.6±4.5 vs. 29.1±4.2 ml/kg/min) and resting mean arterial pressure decreased by 7% (78±10 vs. 83±10 mmHg), with no difference between groups (both p<0.01, main effects for time). Skeletal muscle biopsy samples obtained before and 72 h after training revealed increased maximal activity of citrate synthase and protein content of cytochrome oxidase 4 (p<0.01, main effect), while the maximal activity of ß-hydroxy acyl CoA dehydrogenase increased in men only (p<0.05). Continuous glucose monitoring measured under standard dietary conditions before and 48-72 h following training revealed lower 24 h average blood glucose concentration in men following training (5.4±0.6 vs. 5.9±0.5 mmol/L, p<0.05), but not women (5.5±0.4 vs. 5.5±0.6 mmol/L). This was associated with a greater increase in GLUT4 protein content in men compared to women (138% vs. 23%, p<0.05). Short-term interval training using a 10 min protocol that involved only 1 min of hard exercise, 3x/wk, stimulated physiological changes linked to improved health in overweight adults. Despite the small sample size, potential sex-specific adaptations were apparent that warrant further investigation.