Gene expression profiling for molecular staging of cutaneous melanoma in patients undergoing sentinel lymph node biopsy Pedram Gerami, MD,a,b Robert W. Cook, PhD,d Maria C. Russell, MD,e Jeff Wilkinson, PhD,f Rodabe N. Amaria, MD,g Rene Gonzalez, MD,h Stephen Lyle, MD,i Gilchrist L. Jackson, MD,j Anthony J. Greisinger, PhD,k Clare E. Johnson, RN,d Kristen M. Oelschlager, RN,d John F. Stone, PhD,f Derek J. Maetzold, BS,d Laura K. Ferris, MD, PhD,l Jeffrey D. Wayne, MD,a,c Chelsea Cooper, BA,a Roxana Obregon, BA,a Keith A. Delman, MD,e and David Lawson, MDe Chicago, Illinois; Friendswood and Houston, Texas; Atlanta, Georgia; Phoenix, Arizona; Denver, Colorado; Worcester, Massachusetts; and Pittsburgh, Pennsylvania Background: A gene expression profile (GEP) test able to accurately identify risk of metastasis for patients with cutaneous melanoma has been clinically validated. Objective: We aimed for assessment of the prognostic accuracy of GEP and sentinel lymph node biopsy (SLNB) tests, independently and in combination, in a multicenter cohort of 217 patients. Methods: Reverse transcription polymerase chain reaction (RT-PCR) was performed to assess the expression of 31 genes from primary melanoma tumors, and SLNB outcome was determined from clinical data. Prognostic accuracy of each test was determined using Kaplan-Meier and Cox regression analysis of disease-free, distant metastasisefree, and overall survivals. Results: GEP outcome was a more significant and better predictor of each end point in univariate and multivariate regression analysis, compared with SLNB (P \ .0001 for all). In combination with SLNB, GEP improved prognostication. For patients with a GEP high-risk outcome and a negative SLNB result, KaplanMeier 5-year disease-free, distant metastasisefree, and overall survivals were 35%, 49%, and 54%, respectively. Limitations: Within the SLNB-negative cohort of patients, overall risk of metastatic events was higher (;30%) than commonly found in the general population of patients with melanoma. Conclusions: In this study cohort, GEP was an objective tool that accurately predicted metastatic risk in SLNB-eligible patients. ( J Am Acad Dermatol 2015;72:780-5.) Key words: cutaneous melanoma; gene expression profiling; metastasis; prognostic; sentinel lymph node biopsy; staging.
From the Department of Dermatology,a Robert H. Lurie Cancer Center,b and Department of Surgery-Surgical Oncology,c Feinberg School of Medicine, Northwestern University, Chicago; Castle Biosciences Inc, Friendswoodd; Winship Cancer Institute of Emory University, Atlantae; St Joseph’s Hospital and Medical Center, Phoenixf; University of Texas MD Anderson Cancer Center, Houstong; University of Colorado Denverh; University of Massachusetts Medical Centeri; Kelsey-Seybold Clinic, Houstonj; Kelsey Research Foundation, Houstonk; and Department of Dermatology, University of Pittsburgh Medical Center.l Partially supported by Castle Biosciences Inc. Disclosure: Drs Gerami, Ferris, and Wayne served as consultants to and speakers for Castle Biosciences. Dr Cook, Ms Johnson, Ms Oelschlager, and Mr Maetzold are employees of Castle Biosciences Inc. Drs Russell, Wilkinson, Amaria, Gonzalez, Lyle,
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Jackson, Greisinger, Stone, Delman, and Lawson, Ms Cooper, and Ms Obregon have no conflicts of interest to declare. Tables and supplementary figures are available at http://www. jaad.org. Previously presented at the 2014 American Society for Clinical Oncology Annual Meeting, Chicago, IL, June 2, 2014. Accepted for publication January 5, 2015. Reprint requests: Pedram Gerami, MD, Department of Dermatology, Feinberg School of Medicine, Northwestern University, 676 N Saint Clair St, Suite 1765, Chicago, IL 60611. E-mail: [email protected]. Published online March 4, 2015. 0190-9622/$36.00 Ó 2015 by the American Academy of Dermatology, Inc. http://dx.doi.org/10.1016/j.jaad.2015.01.009
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Molecular diagnostics and prognostics have protumor on the skin to classify melanomas as class 1 (low vided great advancements, both independently and risk) or class 2 (high risk) based on risk of distant when used in combination with therapeutics as metastasis in 5 years after diagnosis.10 Through August companion diagnostics, that were previously not 2013, 217 archival tissue samples from invasive melapossible using traditional histologic classification. nomas, in which a documented SLNB procedure was This includes Oncotype Dx (Genomic Health Inc, performed, were analyzed using the GEP assay under Redwood City, CA) for assessment of breast cancer a multicenter, prospectively planned, institutional retreatment response, gene view boardeapproved protoprofiling for germinal cencol. The predictive accuracy of CAPSULE SUMMARY ter cell versus nongerminal the 2 prognostic tools was evalcenter cell signatures in Buated individually and in comSentinel lymph node biopsy identifies cell lymphoma, fluorescent bination to assess disease-free approximately one in three patients who in situ hybridization (FISH) survival (DFS), distant metastawill die from melanoma. for epidermal growth facsisefree survival (DMFS), and The prognostic accuracy of a gene tor receptor (EGFR) amplioverall survival (OS). The study expression profile test in biopsy-eligible fication in a number of highlights the potential value of patients is reported. solid tumors, and, recently, GEP for improving current stagmessenger RNA expresing protocols. Combined use of the two tests could sion profiling for uveal identify greater than 80% of patients at melanoma.1-3 In addition, METHODS risk for metastasis. a gene expression profile Sample and clinical data (GEP) assay stratifying collection uveal melanomas according to risk of metastasis, as Archived formalin-fixed, paraffin-embedded pripredicted by a 15-gene signature, has recently been mary CM tissue and associated de-identified clinical included in the American Joint Committee on Cancer data were collected after institutional review board (AJCC) guidelines for patient treatment.4 approval at 7 US centers. Inclusion in the study Importantly, each of these novel tools have provided required biopsy-confirmed stage I, II, III, or IV CM additive benefit to the treatment of patients in with at least 5 years of follow-up, with the exception contrast to replacing traditional informational assays. that fewer than 5 years was acceptable if there was a Although there have been considerable advancedocumented metastatic event. Clinical chart and ments in the staging of cutaneous melanoma (CM) in pathology report review was conducted on all the last decade, including recognition of the progsamples with successful GEP classification. Upon nostic value of ulceration status, mitotic rate, and source documentation review, a subset of nonmetasentinel lymph node status, molecular diagnostics static samples were identified that had less than 5 offers an opportunity for further progress. For years of follow-up (n = 13 with \3 years of followexample, for stage II and III patients, 10-year survival up). All cases were originally diagnosed between varies between 43% and 80%.5 At present, sentinel 1998 and 2009 and had a documented SLNB procelymph node biopsy (SLNB) has been shown to be the dure. Clinical follow-up and SLNB were performed most accurate independent prognostic parameter for according to the standards of care at contributing patients with CM.6-8 Although the risk of recurrence institutions. Patients younger than 18 years or for node-negative patients is significantly lower than previously given the diagnosis of another malignant for node-positive patients, the initial Multicenter tumor type were excluded. A hematoxylin and Selective Lymphadenectomy Trial-1 analysis for eosinestained tissue section was requested for intermediate-thickness melanomas observed that 2 each case for independent confirmation of: (1) of 3 patients who developed metastatic disease and melanoma and (2) a dissectible area of tissue with ultimately died had a negative SLNB.9 As recently tumor density that met protocol requirement. published in the final report, that ratio was maintained over a 10-year follow-up period.8 Although Study end points these data are not unexpected because the majority Primary end points for the study were: DFS, or of patients are sentinel lymph node negative and time to any event, including regional or distant represent most patients who are at risk for recurmetastasis; DMFS, or time to any distant metastatic rence, it implies that there are opportunities to garner event; and OS, or time to death from any cause. The improved information for clinical decision-making. secondary end point was analysis of the GEP preWe evaluated a recently validated messenger RNA diction in combination with SLNB status to deterGEP assay that assesses the biology of the primary mine prognostic value added by the GEP. d
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Abbreviations used: AJCC: CI: CM: DFS: DMFS: GEP: OS: SLNB:
American Joint Committee on Cancer confidence interval cutaneous melanoma disease-free survival distant metastasisefree survival gene expression profile overall survival sentinel lymph node biopsy
Tumor tissue preparation, RT-PCR CM tumor specimens arranged in 5-m sections on microscope slides were macro-dissected. RNA isolation was performed using the Ambion RecoverAll Total Nucleic Acid Isolation Kit (Life Technologies, Carlsbad, CA), and RNA quantity and quality were assessed using the NanoDrop 1000 (Thermo Scientific, Wilmington, DE) system and the Agilent Bioanalyzer 2100 (Santa Clara, CA). RNA was converted to complementary DNA (cDNA) using the Applied Biosystems High Capacity cDNA Reverse Transcription Kit (Life Technologies). cDNA samples underwent a 14cycle preamplification step before loading to microfluidics gene cards containing primers specific for 28 discriminating gene targets and 3 endogenous control genes.11,12 The gene expression assay was performed in triplicate on an Applied Biosystems HT7900 (Life Technologies). Statistical analysis Radial basis machine predictive modeling with JMP Genomics SAS-based software (SAS, Cary, NC) was the analytical method used for providing classification of CM tumors as class 1 (low risk of metastasis) or class 2 (high risk of metastasis). Kaplan-Meier survival analysis and Cox proportional hazards analysis were performed using JMP Genomics (SAS) and WinSTAT version 2012.1 (R. Fitch Software, Cambridge, MA) for Microsoft Excel (Redmond, WA).
RESULTS Cohort demographics A subset of 217 patients with melanoma who had undergone a SLNB procedure were identified as a convenience sample set from a database of 406 cases previously tested with the GEP assay. The AJCC staging parameters of the SLNB-positive and -negative patients are summarized in Table I.* The number of patients in each T stage are shown in Table II. *Tables and supplementary figures are available at http://www. jaad.org.
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Accuracy of risk prediction A total of 58 patients had a positive SLNB result whereas 159 patients had a negative SLNB result. Five of 58 (9%) SLNB-positive patients, and 18 of 159 (11%) SLNB-negative patients developed a regional or in-transit disease without evidence of distant metastasis. Thus, 37 of 58 (64%) SLNB-positive patients experienced a metastatic event, 32 of 58 (55%) developed a distant metastasis, and 18 of the 58 (31%) died from all causes. A total of 70 of 159 SLNB-negative patients experienced a metastatic event, 53 of 159 (33%) developed distant metastasis, and 44 of 159 (28%) died from all causes. According to the GEP prediction of risk, 141 tumors were classified as high risk (class 2) whereas 76 tumors were classified as low risk (class 1). In all, 91 of the 141 (65%) class-2 patients progressed to metastatic disease, 71 of 141 (50%) developed distant metastasis, and 53 (38%) died from all causes. Sixteen of 76 (21%) class-1 patients developed metastatic disease, 14 of 76 (18%) had a distant metastatic event, and 9 (12%) died from all causes. The positive predictive value of SLNB for predicting distant metastasis was 55% (95% confidence interval [CI] 42%-68%) and the negative predictive value was 67% (95% CI 59%-74%). In comparison, the positive predictive value according to GEP test prediction was 50% (95% CI 42%-59%) for distant metastasis, and the negative predictive value was 82% (95% CI 71%-89%) (Table III). Supplementary Fig 1 shows the Kaplan-Meier survival curves for DFS, DMFS, and OS, with groups stratified according to SLNB outcome. Comparison of SLNB-negative and -positive patients resulted in significant differences in DFS, DMFS, and OS (P value for DFS and DMFS \.0001; for OS = .006). Importantly, OS at 5 years for all SLNB-positive patients was 62% compared with 70% for SLNBnegative cases. Supplementary Fig 2 shows the Kaplan-Meier curve for DFS, DMFS, and OS for the patients classified by GEP. Significant differences in survival were observed for all end points (P value for all \.0001). OS at 5 years was 55% for all cases with a class-2 GEP classification compared with 89% for all class-1 cases. SLNB positivity and GEP class 2 were significant predictors of DFS, DMFS, and OS (P \ .01 for all) in Cox univariate regression analysis (Table IV). For each end point, GEP class had a higher hazard ratio compared with SLNB. Similarly, SLNB and GEP prediction were statistically significant predictors of DFS and DMFS using multivariate regression analysis (P \ .008 for both), whereas only GEP prediction of OS was statistically significant (P \.0001).
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Fig 1. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by sentinel lymph node biopsy (SLNB) procedure in combination with gene expression profile (GEP) testing. Four subgroups of patients are described and shown after assignment of SLNB and GEP prognostic prediction.
Combining GEP class with sentinel lymph node status Combining GEP classification and SLNB status further improved metastasis risk prognostication, as shown in Fig 1. The individual overall 5-year DFS and DMFS was 79% and 82% for class-1 patients, respectively, and 55% and 64% for SLNB-negative patients, respectively. The 31% of patients with a GEP class 1 and a negative SLNB result had an overall 5-year DFS and DMFS of 83% and 86%, respectively. Similarly, OS prognostication was slightly improved in this cohort, as illustrated by 5-year rate of 91% in patients who were both SLNB negative and GEP class 1. In the small cohort of 9 patients (representing 4%) with a class-1 GEP score but positive SLNB result the prognosis did appear to be intermediate between all patients with a class-1 GEP score and all patients with a class-2 GEP score. The 5-year DFS, DMFS, and OS for this group were 53%, 53%, and 77%, respectively. The respective P values for the difference between the 4 combined GEP and SLNB groups was less than .0001 for all parameters measured. The 5-year DFS, DMFS, and OS for GEP class-2 patients are 34%, 46%, and 55%, respectively, and for SLNB-positive patients are 37%, 42%, and 62%, respectively. The 23% of patients with a GEP class 2 and a positive SLNB had 5-year rates of 33%, 42%, and 57%, respectively. Significantly, 42% of patients had a GEP class 2 and a negative SLNB result. Of these patients, the 5-year DFS, DMFS, and OS were 35%, 49%, and 55%, respectively, which statistically
was not different from those patients who were class 2 with a positive SLNB status.
DISCUSSION Despite success in other cancers, little progress has been made in molecular prognostics for CM. SLNB status is the single most powerful prognostic parameter for melanoma skin cancer. A positive SLNB upstages a patient to stage III disease, with 5-year melanoma-specific survival of 38% to 80%. However, only 17% of patients will have a positive sentinel node, making the majority of patients who eventually metastasize sentinel lymph node negative. We recently validated in a multicenter study a noninvasive GEP assay that assesses primary CM tumor biology and found it to be an independent predictor of prognosis. National Comprehensive Cancer Network treatment guidelines view the risk associated with a positive SLNB outcome as worrisome enough to warrant high-risk clinical management, including imaging-based surveillance, adjuvant therapy, or enrollment in clinical trials.13 Despite traditional staging methodology providing statistically valid and accurate information regarding groups of patients with similar disease patterns, there is clinically significant variability for some individuals within these groups. Although some stage-IIB and -IIC patients receive adjuvant therapy or clinical trial entry, some SLNB-negative patients who may actually be at individual risk of metastasis do not receive treatment because the approach to therapeutic decision-making remains based on statistical
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groupings of large sets of patients. GEP classification appears to identify a significant proportion of patients with melanoma at high risk for metastasis, but maintained as lower risk stage I or II. AJCC data suggest that, although the overall risk of dying is greater for patients with high-risk stage IIB, IIC, or III compared with those with low-risk stage I and IIA disease, more patients at low risk will die of melanoma. This ratio was also reported for intermediate and thick melanomas in the final Multicenter Selective Lymphadenectomy Trial-1 report. Although patients in our overall data set are at greater risk of disease than those patients enrolled in Multicenter Selective Lymphadenectomy Trial-1, outcome in our patients are similar in that 44 patients who had a negative SLNB status and 18 patients who had a positive SLNB status died. In this multicenter study of 217 patients, both SLNB result and GEP classification were independent predictors of DFS and DMFS, and GEP classification was an independent predictor of OS. Independently, GEP classification more accurately stratified high- and low-risk patient DFS, DMFS, and OS (Supplementary Figs 1 and 2). Among the SLNB-negative patients with a class-2 GEP signature, 5-year DFS, DMFS, and OS were 35%, 49%, and 55%, respectively, event rates that are more closely aligned with SLNB-positive status alone. In fact, there was no statistical difference in DFS or OS for patients with class-2 GEP signature and a negative SLNB result and patients with a class-2 GEP score and a positive SLNB result. Within the study cohort reported, the GEP test provides information that would be valuable in combination with the results of SLNB outcomes. Adding the GEP prediction of risk to the SLNB outcome more effectively identified a true low-risk group. A limitation of the study is the analysis of a convenience cohort of cases, which resulted in a higher rate of distant metastasis than commonly observed or reported in the SLNB-negative group. However, GEP identified the majority of patients who were at risk for metastasis as high risk class 2. The results indicate that 1 application of the test is to identify SLNB-negative, high-risk melanoma cases to enable upstaging and implementation of management plans consistent with their biological risk, including more aggressive clinical follow-up and clinical trial eligibility. Recent guideline updates recommend the use of SLNB for melanomas greater than 0.75 mm, and for melanomas less than 0.76 mm with adverse features (ulceration or mitosis [1/mm2). Unfortunately, studies show that the presence of mitotic activity or ulceration is not a reliable predictive indicator of SLNB positivity in patients with thin melanoma.14
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Many centers have shown an extremely low yield of less than 5% SLNB positivity in IB patients.14-17 Thus, another indication for the GEP may be to determine which T1 patients should undergo SLNB, which would likely result in a significant increase in the yield of SLNB procedures performed in this patient population. In combination with sentinel lymph node biopsy the assay will help clinicians identify high-risk SLNB-negative patients with aggressive disease and patients labeled with high-risk disease by conventional parameters who are unlikely to have progression of their disease. Based on data from this study and the prior validation study, we propose that this noninvasive GEP assay be used in combination with sentinel lymph node biopsy to help clinicians further stratify patients as higher versus lower risk. The combined use of these 2 prognostic tests may identify the majority of patients who are at risk for metastasis compared with sentinel lymph node status aloneeproviding a significant opportunity for improved patient treatment. REFERENCES 1. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817-2826. 2. Gerami P, Jewell SS, Pouryazdanparast P, et al. Copy number gains in 11q13 and 8q24 [corrected] are highly linked to prognosis in cutaneous malignant melanoma. J Mol Diagn. 2011;13:352-358. 3. Onken MD, Worley LA, Char DH, et al. Collaborative Ocular Oncology Group report number 1: prospective validation of a multi-gene prognostic assay in uveal melanoma. Ophthalmology. 2012;119:1596-1603. 4. Harbour JW, Chen R. The DecisionDx-UM gene expression profile test provides risk stratification and individualized patient care in uveal melanoma. PLoS Curr. 2013 Apr 9;5. 5. Balch CM, Gershenwald JE, Soong SJ, et al. Final version of 2009 AJCC melanoma staging and classification. J Clin Oncol. 2009;27:6199-6206. 6. Balch CM, Gershenwald JE, Soong SJ, et al. Multivariate analysis of prognostic factors among 2,313 patients with stage III melanoma: comparison of nodal micrometastases versus macrometastases. J Clin Oncol. 2010;28:2452-2459. 7. Wong SL, Balch CM, Hurley P, et al. Sentinel lymph node biopsy for melanoma: American Society of Clinical Oncology and Society of Surgical Oncology joint clinical practice guideline. J Clin Oncol. 2012;30:2912-2918. 8. Morton DL, Thompson JF, Cochran AJ, et al. Final trial report of sentinel-node biopsy versus nodal observation in melanoma. N Engl J Med. 2014;370:599-609. 9. Morton DL, Thompson JF, Cochran AJ, et al. Sentinel-node biopsy or nodal observation in melanoma. N Engl J Med. 2006; 355:1307-1317. 10. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res. 2015;21:175-183. 11. Gokmen-Polar Y, Cook RW, Goswami CP, et al. A gene signature to determine metastatic behavior in thymomas. PLoS One. 2013;8:e66047.
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12. Onken MD, Worley LA, Tuscan MD, Harbour JW. An accurate, clinically feasible multi-gene expression assay for predicting metastasis in uveal melanoma. J Mol Diagn. 2010;12:461-468. 13. Coit DG, Andtbacka R, Anker CJ, Bichakjian CK, Carson WE III, Daud A, et al. Melanoma, version 2.2013: featured updates to the NCCN guidelines. JNCCN. 2013;11:395-407. 14. Cooper C, Wayne JD, Damstetter EM, et al. A 10-year, single-institution analysis of clinicopathologic features and sentinel lymph node biopsy in thin melanomas. J Am Acad Dermatol. 2013;69:693-699.
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15. Bartlett EK, Gimotty PA, Sinnamon AJ, et al. Clark level risk stratifies patients with mitogenic thin melanomas for sentinel lymph node biopsy. Ann Surg Oncol. 2014;21:643-649. 16. Hinz T, Ahmadzadehfar H, Wierzbicki A, et al. Prognostic value of sentinel lymph node biopsy in 121 low-risk melanomas (tumor thickness \1.00 mm) on the basis of a long-term follow-up. Eur J Nucl Med Mol Imaging. 2012;39:581-588. 17. Wright BE, Scheri RP, Ye X, et al. Importance of sentinel lymph node biopsy in patients with thin melanoma. Arch Surg. 2008; 143:892-900.
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Supplementary Fig 1. Survival for patients with sentinel lymph node biopsy (SLNB)-negative versus -positive outcomes. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by SLNB procedure.
Supplementary Fig 2. Survival for patients with gene expression profile (GEP) class-1 versus class-2 outcomes. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by the GEP testing.
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Table I. American Joint Committee on Cancer characteristics of sentinel lymph node biopsypositive and -negative melanoma cases Clinical characteristics
SLNB positive (n = 58)
SLNB negative (n = 159)
57 (23-94) 37 1.0/2.5
63 (31-89) 70 1.8/6.1
n/a n/a 58 n/a
46 112 0 1
4.0 (0.8-16) 4 51
2.3 (0.4-14) 27 132
2 48
44 100
20 33
93 58
Median age, y (range) Regional/distant mets Median time to metastasis/ follow-up for nonmets, y AJCC stage I II III IV Breslow thickness Median (range) #1 mm [1 mm Mitotic index \1/mm2 $1/mm2 Ulceration Absent Present
AJCC, American Joint Committee on Cancer; SLNB, sentinel lymph node biopsy.
Table II. T stage of sample cohort stratified by sentinel lymph node biopsy outcome T1a T1b T2a T2b T3a T3b T4a T4b
SLNB negative
SLNB positive
13 19 19 8 40 29 16 15
3 1 4 6 6 8 9 18
SLNB, Sentinel lymph node biopsy.
Table III. Positive and negative predictive values for sentinel lymph node biopsy and gene expression profiling for distant metastasis Prognostic tool
SLNB GEP
PPV, % (95% CI)
NPV, % (95% CI)
55 (42-68) 50 (42-59)
67 (59-74) 82 (71-89)
CI, Confidence interval; GEP, gene expression profiling; NPV, negative predictive value; PPV, positive predictive value; SLNB, sentinel lymph node biopsy.
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Table IV. Univariate and multivariate analysis of Cox proportional hazards gene expression profiling and sentinel lymph node biopsy Univariate
Local or distant recurrence Distant metastasis Death from all causes
Multivariate
Variable
HR
95% CI
P value
HR
95% CI
P value
GEP class 2 SLNB positive GEP class 2 SLNB positive GEP class 2 SLNB positive
5.5 2.4 4.5 2.8 5.8 2.1
3.2-9.4 1.6-3.6 2.5-8.1 1.8-4.3 2.8-12.0 1.2-3.6
\.0001 \.0001 \.0001 \.0001 \.0001 .0099
4.9 1.7 3.9 2.1 4.7 1.2
2.9-8.6 1.2-2.6 2.2-7.1 1.3-3.3 1.6-14.1 0.5-3.1
\.0001 .008 \.0001 .001 \.0001 .11
CI, Confidence interval; GEP, gene expression profiling; SLNB, sentinel lymph node biopsy.
From the Department of Dermatology,a Robert H. Lurie Cancer Center,b and Department of Surgery-Surgical Oncology,c Feinberg School of Medicine, Northwestern University, Chicago; Castle Biosciences Inc, Friendswoodd; Winship Cancer Institute of Emory University, Atlantae; St Joseph’s Hospital and Medical Center, Phoenixf; University of Texas MD Anderson Cancer Center, Houstong; University of Colorado Denverh; University of Massachusetts Medical Centeri; Kelsey-Seybold Clinic, Houstonj; Kelsey Research Foundation, Houstonk; and Department of Dermatology, University of Pittsburgh Medical Center.l Partially supported by Castle Biosciences Inc. Disclosure: Drs Gerami, Ferris, and Wayne served as consultants to and speakers for Castle Biosciences. Dr Cook, Ms Johnson, Ms Oelschlager, and Mr Maetzold are employees of Castle Biosciences Inc. Drs Russell, Wilkinson, Amaria, Gonzalez, Lyle,
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Jackson, Greisinger, Stone, Delman, and Lawson, Ms Cooper, and Ms Obregon have no conflicts of interest to declare. Tables and supplementary figures are available at http://www. jaad.org. Previously presented at the 2014 American Society for Clinical Oncology Annual Meeting, Chicago, IL, June 2, 2014. Accepted for publication January 5, 2015. Reprint requests: Pedram Gerami, MD, Department of Dermatology, Feinberg School of Medicine, Northwestern University, 676 N Saint Clair St, Suite 1765, Chicago, IL 60611. E-mail: [email protected]. Published online March 4, 2015. 0190-9622/$36.00 Ó 2015 by the American Academy of Dermatology, Inc. http://dx.doi.org/10.1016/j.jaad.2015.01.009
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Molecular diagnostics and prognostics have protumor on the skin to classify melanomas as class 1 (low vided great advancements, both independently and risk) or class 2 (high risk) based on risk of distant when used in combination with therapeutics as metastasis in 5 years after diagnosis.10 Through August companion diagnostics, that were previously not 2013, 217 archival tissue samples from invasive melapossible using traditional histologic classification. nomas, in which a documented SLNB procedure was This includes Oncotype Dx (Genomic Health Inc, performed, were analyzed using the GEP assay under Redwood City, CA) for assessment of breast cancer a multicenter, prospectively planned, institutional retreatment response, gene view boardeapproved protoprofiling for germinal cencol. The predictive accuracy of CAPSULE SUMMARY ter cell versus nongerminal the 2 prognostic tools was evalcenter cell signatures in Buated individually and in comSentinel lymph node biopsy identifies cell lymphoma, fluorescent bination to assess disease-free approximately one in three patients who in situ hybridization (FISH) survival (DFS), distant metastawill die from melanoma. for epidermal growth facsisefree survival (DMFS), and The prognostic accuracy of a gene tor receptor (EGFR) amplioverall survival (OS). The study expression profile test in biopsy-eligible fication in a number of highlights the potential value of patients is reported. solid tumors, and, recently, GEP for improving current stagmessenger RNA expresing protocols. Combined use of the two tests could sion profiling for uveal identify greater than 80% of patients at melanoma.1-3 In addition, METHODS risk for metastasis. a gene expression profile Sample and clinical data (GEP) assay stratifying collection uveal melanomas according to risk of metastasis, as Archived formalin-fixed, paraffin-embedded pripredicted by a 15-gene signature, has recently been mary CM tissue and associated de-identified clinical included in the American Joint Committee on Cancer data were collected after institutional review board (AJCC) guidelines for patient treatment.4 approval at 7 US centers. Inclusion in the study Importantly, each of these novel tools have provided required biopsy-confirmed stage I, II, III, or IV CM additive benefit to the treatment of patients in with at least 5 years of follow-up, with the exception contrast to replacing traditional informational assays. that fewer than 5 years was acceptable if there was a Although there have been considerable advancedocumented metastatic event. Clinical chart and ments in the staging of cutaneous melanoma (CM) in pathology report review was conducted on all the last decade, including recognition of the progsamples with successful GEP classification. Upon nostic value of ulceration status, mitotic rate, and source documentation review, a subset of nonmetasentinel lymph node status, molecular diagnostics static samples were identified that had less than 5 offers an opportunity for further progress. For years of follow-up (n = 13 with \3 years of followexample, for stage II and III patients, 10-year survival up). All cases were originally diagnosed between varies between 43% and 80%.5 At present, sentinel 1998 and 2009 and had a documented SLNB procelymph node biopsy (SLNB) has been shown to be the dure. Clinical follow-up and SLNB were performed most accurate independent prognostic parameter for according to the standards of care at contributing patients with CM.6-8 Although the risk of recurrence institutions. Patients younger than 18 years or for node-negative patients is significantly lower than previously given the diagnosis of another malignant for node-positive patients, the initial Multicenter tumor type were excluded. A hematoxylin and Selective Lymphadenectomy Trial-1 analysis for eosinestained tissue section was requested for intermediate-thickness melanomas observed that 2 each case for independent confirmation of: (1) of 3 patients who developed metastatic disease and melanoma and (2) a dissectible area of tissue with ultimately died had a negative SLNB.9 As recently tumor density that met protocol requirement. published in the final report, that ratio was maintained over a 10-year follow-up period.8 Although Study end points these data are not unexpected because the majority Primary end points for the study were: DFS, or of patients are sentinel lymph node negative and time to any event, including regional or distant represent most patients who are at risk for recurmetastasis; DMFS, or time to any distant metastatic rence, it implies that there are opportunities to garner event; and OS, or time to death from any cause. The improved information for clinical decision-making. secondary end point was analysis of the GEP preWe evaluated a recently validated messenger RNA diction in combination with SLNB status to deterGEP assay that assesses the biology of the primary mine prognostic value added by the GEP. d
d
d
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Abbreviations used: AJCC: CI: CM: DFS: DMFS: GEP: OS: SLNB:
American Joint Committee on Cancer confidence interval cutaneous melanoma disease-free survival distant metastasisefree survival gene expression profile overall survival sentinel lymph node biopsy
Tumor tissue preparation, RT-PCR CM tumor specimens arranged in 5-m sections on microscope slides were macro-dissected. RNA isolation was performed using the Ambion RecoverAll Total Nucleic Acid Isolation Kit (Life Technologies, Carlsbad, CA), and RNA quantity and quality were assessed using the NanoDrop 1000 (Thermo Scientific, Wilmington, DE) system and the Agilent Bioanalyzer 2100 (Santa Clara, CA). RNA was converted to complementary DNA (cDNA) using the Applied Biosystems High Capacity cDNA Reverse Transcription Kit (Life Technologies). cDNA samples underwent a 14cycle preamplification step before loading to microfluidics gene cards containing primers specific for 28 discriminating gene targets and 3 endogenous control genes.11,12 The gene expression assay was performed in triplicate on an Applied Biosystems HT7900 (Life Technologies). Statistical analysis Radial basis machine predictive modeling with JMP Genomics SAS-based software (SAS, Cary, NC) was the analytical method used for providing classification of CM tumors as class 1 (low risk of metastasis) or class 2 (high risk of metastasis). Kaplan-Meier survival analysis and Cox proportional hazards analysis were performed using JMP Genomics (SAS) and WinSTAT version 2012.1 (R. Fitch Software, Cambridge, MA) for Microsoft Excel (Redmond, WA).
RESULTS Cohort demographics A subset of 217 patients with melanoma who had undergone a SLNB procedure were identified as a convenience sample set from a database of 406 cases previously tested with the GEP assay. The AJCC staging parameters of the SLNB-positive and -negative patients are summarized in Table I.* The number of patients in each T stage are shown in Table II. *Tables and supplementary figures are available at http://www. jaad.org.
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Accuracy of risk prediction A total of 58 patients had a positive SLNB result whereas 159 patients had a negative SLNB result. Five of 58 (9%) SLNB-positive patients, and 18 of 159 (11%) SLNB-negative patients developed a regional or in-transit disease without evidence of distant metastasis. Thus, 37 of 58 (64%) SLNB-positive patients experienced a metastatic event, 32 of 58 (55%) developed a distant metastasis, and 18 of the 58 (31%) died from all causes. A total of 70 of 159 SLNB-negative patients experienced a metastatic event, 53 of 159 (33%) developed distant metastasis, and 44 of 159 (28%) died from all causes. According to the GEP prediction of risk, 141 tumors were classified as high risk (class 2) whereas 76 tumors were classified as low risk (class 1). In all, 91 of the 141 (65%) class-2 patients progressed to metastatic disease, 71 of 141 (50%) developed distant metastasis, and 53 (38%) died from all causes. Sixteen of 76 (21%) class-1 patients developed metastatic disease, 14 of 76 (18%) had a distant metastatic event, and 9 (12%) died from all causes. The positive predictive value of SLNB for predicting distant metastasis was 55% (95% confidence interval [CI] 42%-68%) and the negative predictive value was 67% (95% CI 59%-74%). In comparison, the positive predictive value according to GEP test prediction was 50% (95% CI 42%-59%) for distant metastasis, and the negative predictive value was 82% (95% CI 71%-89%) (Table III). Supplementary Fig 1 shows the Kaplan-Meier survival curves for DFS, DMFS, and OS, with groups stratified according to SLNB outcome. Comparison of SLNB-negative and -positive patients resulted in significant differences in DFS, DMFS, and OS (P value for DFS and DMFS \.0001; for OS = .006). Importantly, OS at 5 years for all SLNB-positive patients was 62% compared with 70% for SLNBnegative cases. Supplementary Fig 2 shows the Kaplan-Meier curve for DFS, DMFS, and OS for the patients classified by GEP. Significant differences in survival were observed for all end points (P value for all \.0001). OS at 5 years was 55% for all cases with a class-2 GEP classification compared with 89% for all class-1 cases. SLNB positivity and GEP class 2 were significant predictors of DFS, DMFS, and OS (P \ .01 for all) in Cox univariate regression analysis (Table IV). For each end point, GEP class had a higher hazard ratio compared with SLNB. Similarly, SLNB and GEP prediction were statistically significant predictors of DFS and DMFS using multivariate regression analysis (P \ .008 for both), whereas only GEP prediction of OS was statistically significant (P \.0001).
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Fig 1. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by sentinel lymph node biopsy (SLNB) procedure in combination with gene expression profile (GEP) testing. Four subgroups of patients are described and shown after assignment of SLNB and GEP prognostic prediction.
Combining GEP class with sentinel lymph node status Combining GEP classification and SLNB status further improved metastasis risk prognostication, as shown in Fig 1. The individual overall 5-year DFS and DMFS was 79% and 82% for class-1 patients, respectively, and 55% and 64% for SLNB-negative patients, respectively. The 31% of patients with a GEP class 1 and a negative SLNB result had an overall 5-year DFS and DMFS of 83% and 86%, respectively. Similarly, OS prognostication was slightly improved in this cohort, as illustrated by 5-year rate of 91% in patients who were both SLNB negative and GEP class 1. In the small cohort of 9 patients (representing 4%) with a class-1 GEP score but positive SLNB result the prognosis did appear to be intermediate between all patients with a class-1 GEP score and all patients with a class-2 GEP score. The 5-year DFS, DMFS, and OS for this group were 53%, 53%, and 77%, respectively. The respective P values for the difference between the 4 combined GEP and SLNB groups was less than .0001 for all parameters measured. The 5-year DFS, DMFS, and OS for GEP class-2 patients are 34%, 46%, and 55%, respectively, and for SLNB-positive patients are 37%, 42%, and 62%, respectively. The 23% of patients with a GEP class 2 and a positive SLNB had 5-year rates of 33%, 42%, and 57%, respectively. Significantly, 42% of patients had a GEP class 2 and a negative SLNB result. Of these patients, the 5-year DFS, DMFS, and OS were 35%, 49%, and 55%, respectively, which statistically
was not different from those patients who were class 2 with a positive SLNB status.
DISCUSSION Despite success in other cancers, little progress has been made in molecular prognostics for CM. SLNB status is the single most powerful prognostic parameter for melanoma skin cancer. A positive SLNB upstages a patient to stage III disease, with 5-year melanoma-specific survival of 38% to 80%. However, only 17% of patients will have a positive sentinel node, making the majority of patients who eventually metastasize sentinel lymph node negative. We recently validated in a multicenter study a noninvasive GEP assay that assesses primary CM tumor biology and found it to be an independent predictor of prognosis. National Comprehensive Cancer Network treatment guidelines view the risk associated with a positive SLNB outcome as worrisome enough to warrant high-risk clinical management, including imaging-based surveillance, adjuvant therapy, or enrollment in clinical trials.13 Despite traditional staging methodology providing statistically valid and accurate information regarding groups of patients with similar disease patterns, there is clinically significant variability for some individuals within these groups. Although some stage-IIB and -IIC patients receive adjuvant therapy or clinical trial entry, some SLNB-negative patients who may actually be at individual risk of metastasis do not receive treatment because the approach to therapeutic decision-making remains based on statistical
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groupings of large sets of patients. GEP classification appears to identify a significant proportion of patients with melanoma at high risk for metastasis, but maintained as lower risk stage I or II. AJCC data suggest that, although the overall risk of dying is greater for patients with high-risk stage IIB, IIC, or III compared with those with low-risk stage I and IIA disease, more patients at low risk will die of melanoma. This ratio was also reported for intermediate and thick melanomas in the final Multicenter Selective Lymphadenectomy Trial-1 report. Although patients in our overall data set are at greater risk of disease than those patients enrolled in Multicenter Selective Lymphadenectomy Trial-1, outcome in our patients are similar in that 44 patients who had a negative SLNB status and 18 patients who had a positive SLNB status died. In this multicenter study of 217 patients, both SLNB result and GEP classification were independent predictors of DFS and DMFS, and GEP classification was an independent predictor of OS. Independently, GEP classification more accurately stratified high- and low-risk patient DFS, DMFS, and OS (Supplementary Figs 1 and 2). Among the SLNB-negative patients with a class-2 GEP signature, 5-year DFS, DMFS, and OS were 35%, 49%, and 55%, respectively, event rates that are more closely aligned with SLNB-positive status alone. In fact, there was no statistical difference in DFS or OS for patients with class-2 GEP signature and a negative SLNB result and patients with a class-2 GEP score and a positive SLNB result. Within the study cohort reported, the GEP test provides information that would be valuable in combination with the results of SLNB outcomes. Adding the GEP prediction of risk to the SLNB outcome more effectively identified a true low-risk group. A limitation of the study is the analysis of a convenience cohort of cases, which resulted in a higher rate of distant metastasis than commonly observed or reported in the SLNB-negative group. However, GEP identified the majority of patients who were at risk for metastasis as high risk class 2. The results indicate that 1 application of the test is to identify SLNB-negative, high-risk melanoma cases to enable upstaging and implementation of management plans consistent with their biological risk, including more aggressive clinical follow-up and clinical trial eligibility. Recent guideline updates recommend the use of SLNB for melanomas greater than 0.75 mm, and for melanomas less than 0.76 mm with adverse features (ulceration or mitosis [1/mm2). Unfortunately, studies show that the presence of mitotic activity or ulceration is not a reliable predictive indicator of SLNB positivity in patients with thin melanoma.14
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Many centers have shown an extremely low yield of less than 5% SLNB positivity in IB patients.14-17 Thus, another indication for the GEP may be to determine which T1 patients should undergo SLNB, which would likely result in a significant increase in the yield of SLNB procedures performed in this patient population. In combination with sentinel lymph node biopsy the assay will help clinicians identify high-risk SLNB-negative patients with aggressive disease and patients labeled with high-risk disease by conventional parameters who are unlikely to have progression of their disease. Based on data from this study and the prior validation study, we propose that this noninvasive GEP assay be used in combination with sentinel lymph node biopsy to help clinicians further stratify patients as higher versus lower risk. The combined use of these 2 prognostic tests may identify the majority of patients who are at risk for metastasis compared with sentinel lymph node status aloneeproviding a significant opportunity for improved patient treatment. REFERENCES 1. Paik S, Shak S, Tang G, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817-2826. 2. Gerami P, Jewell SS, Pouryazdanparast P, et al. Copy number gains in 11q13 and 8q24 [corrected] are highly linked to prognosis in cutaneous malignant melanoma. J Mol Diagn. 2011;13:352-358. 3. Onken MD, Worley LA, Char DH, et al. Collaborative Ocular Oncology Group report number 1: prospective validation of a multi-gene prognostic assay in uveal melanoma. Ophthalmology. 2012;119:1596-1603. 4. Harbour JW, Chen R. The DecisionDx-UM gene expression profile test provides risk stratification and individualized patient care in uveal melanoma. PLoS Curr. 2013 Apr 9;5. 5. Balch CM, Gershenwald JE, Soong SJ, et al. Final version of 2009 AJCC melanoma staging and classification. J Clin Oncol. 2009;27:6199-6206. 6. Balch CM, Gershenwald JE, Soong SJ, et al. Multivariate analysis of prognostic factors among 2,313 patients with stage III melanoma: comparison of nodal micrometastases versus macrometastases. J Clin Oncol. 2010;28:2452-2459. 7. Wong SL, Balch CM, Hurley P, et al. Sentinel lymph node biopsy for melanoma: American Society of Clinical Oncology and Society of Surgical Oncology joint clinical practice guideline. J Clin Oncol. 2012;30:2912-2918. 8. Morton DL, Thompson JF, Cochran AJ, et al. Final trial report of sentinel-node biopsy versus nodal observation in melanoma. N Engl J Med. 2014;370:599-609. 9. Morton DL, Thompson JF, Cochran AJ, et al. Sentinel-node biopsy or nodal observation in melanoma. N Engl J Med. 2006; 355:1307-1317. 10. Gerami P, Cook RW, Wilkinson J, et al. Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res. 2015;21:175-183. 11. Gokmen-Polar Y, Cook RW, Goswami CP, et al. A gene signature to determine metastatic behavior in thymomas. PLoS One. 2013;8:e66047.
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12. Onken MD, Worley LA, Tuscan MD, Harbour JW. An accurate, clinically feasible multi-gene expression assay for predicting metastasis in uveal melanoma. J Mol Diagn. 2010;12:461-468. 13. Coit DG, Andtbacka R, Anker CJ, Bichakjian CK, Carson WE III, Daud A, et al. Melanoma, version 2.2013: featured updates to the NCCN guidelines. JNCCN. 2013;11:395-407. 14. Cooper C, Wayne JD, Damstetter EM, et al. A 10-year, single-institution analysis of clinicopathologic features and sentinel lymph node biopsy in thin melanomas. J Am Acad Dermatol. 2013;69:693-699.
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15. Bartlett EK, Gimotty PA, Sinnamon AJ, et al. Clark level risk stratifies patients with mitogenic thin melanomas for sentinel lymph node biopsy. Ann Surg Oncol. 2014;21:643-649. 16. Hinz T, Ahmadzadehfar H, Wierzbicki A, et al. Prognostic value of sentinel lymph node biopsy in 121 low-risk melanomas (tumor thickness \1.00 mm) on the basis of a long-term follow-up. Eur J Nucl Med Mol Imaging. 2012;39:581-588. 17. Wright BE, Scheri RP, Ye X, et al. Importance of sentinel lymph node biopsy in patients with thin melanoma. Arch Surg. 2008; 143:892-900.
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Supplementary Fig 1. Survival for patients with sentinel lymph node biopsy (SLNB)-negative versus -positive outcomes. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by SLNB procedure.
Supplementary Fig 2. Survival for patients with gene expression profile (GEP) class-1 versus class-2 outcomes. Kaplan-Meier estimates of disease-free survival (DFS ) (A), distant metastasisefree survival (DMFS ) (B), and overall survival (OS ) (C) in a cohort of 217 cutaneous melanoma cases with outcomes predicted by the GEP testing.
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Table I. American Joint Committee on Cancer characteristics of sentinel lymph node biopsypositive and -negative melanoma cases Clinical characteristics
SLNB positive (n = 58)
SLNB negative (n = 159)
57 (23-94) 37 1.0/2.5
63 (31-89) 70 1.8/6.1
n/a n/a 58 n/a
46 112 0 1
4.0 (0.8-16) 4 51
2.3 (0.4-14) 27 132
2 48
44 100
20 33
93 58
Median age, y (range) Regional/distant mets Median time to metastasis/ follow-up for nonmets, y AJCC stage I II III IV Breslow thickness Median (range) #1 mm [1 mm Mitotic index \1/mm2 $1/mm2 Ulceration Absent Present
AJCC, American Joint Committee on Cancer; SLNB, sentinel lymph node biopsy.
Table II. T stage of sample cohort stratified by sentinel lymph node biopsy outcome T1a T1b T2a T2b T3a T3b T4a T4b
SLNB negative
SLNB positive
13 19 19 8 40 29 16 15
3 1 4 6 6 8 9 18
SLNB, Sentinel lymph node biopsy.
Table III. Positive and negative predictive values for sentinel lymph node biopsy and gene expression profiling for distant metastasis Prognostic tool
SLNB GEP
PPV, % (95% CI)
NPV, % (95% CI)
55 (42-68) 50 (42-59)
67 (59-74) 82 (71-89)
CI, Confidence interval; GEP, gene expression profiling; NPV, negative predictive value; PPV, positive predictive value; SLNB, sentinel lymph node biopsy.
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Table IV. Univariate and multivariate analysis of Cox proportional hazards gene expression profiling and sentinel lymph node biopsy Univariate
Local or distant recurrence Distant metastasis Death from all causes
Multivariate
Variable
HR
95% CI
P value
HR
95% CI
P value
GEP class 2 SLNB positive GEP class 2 SLNB positive GEP class 2 SLNB positive
5.5 2.4 4.5 2.8 5.8 2.1
3.2-9.4 1.6-3.6 2.5-8.1 1.8-4.3 2.8-12.0 1.2-3.6
\.0001 \.0001 \.0001 \.0001 \.0001 .0099
4.9 1.7 3.9 2.1 4.7 1.2
2.9-8.6 1.2-2.6 2.2-7.1 1.3-3.3 1.6-14.1 0.5-3.1
\.0001 .008 \.0001 .001 \.0001 .11
CI, Confidence interval; GEP, gene expression profiling; SLNB, sentinel lymph node biopsy.
