Melanoma Prognostic Factors: where we started, where are we going? Impact of Prognostic Factors Staging Management Surgical intervention Adjuvant treatment Suraj Venna, MD Assistant Clinical Professor, Dermatology Director, Pigmented Lesion Clinic UCSF DISCLOSURES: None Prognostic Factors Where we started 1969 Clark anatomic levels 1970 Breslow absolute thickness in mm 1978 Balch single institution, 1 st multivariate analysis of 13 factors 0.76mm 1981 Van Der Esch multi-institution, institution, multivariate 1997 Buzaid proposed revised staging Cox Regression Analysis for 13,581 Melanoma Patients Without Evidence of Nodal or Distant Metastases Variable P Risk Ratio Thickness.00001 1.558 Ulceration.00001 1.901 Age.00001 1.101 Site.00001 1.338 Level.00001 1.214 Sex.001 0.836 2002 AJCC staging currently in use Cox Regression 4,750 Melanoma Patients Without Clinical Evidence of Nodal Metastases Whose Regional Lymph Nodes Were Pathologically Staged After Sentinel or Elective Lymphadenectomy Several other histologic parameters have been shown to have prognostic value Variable P Risk Ratio Nodal status.00001 2.239 Thickness.00001 1.583 Ulceration.00001 1.938 Site.00001 1.483 Age.0002 1.095 Sex.1705 0.900 Level.9082 1.007 1. vascular invasion 2. tumor vascularity 3. regression 4. mitotic index 5. microsatellitosis Additional markers not included in the AJCC guidelines have validity
Melanoma Progression Melanocyte BRAF Nevus SSM Patch Radial Growth Phase Melanoma (SSM) 1 MM Raised Vertical Growth Phase Melanoma (SSM/NM) Nodular Microarray Technology Rudimentary methods to molecular methods Human genome project What the cell can possibly do Biomarkers DNA microarray technology What the cell is actually doing Genes contain the instructions for making messenger RNA At any moment each cell makes mrna from only a fraction of the genes it carries Gene Expression Microarrays If a gene is used to produce mrna, it is considered "on", otherwise "off Skin cells, liver cells and nerve cells turn on (express) somewhat different genes and that is in large part what makes them different ent Therefore, an expression profile allows one to deduce a cell's type, state, environment, and so forth Expression profiling experiments often involve measuring the relative amount of mrna expressed in two or more experimental conditions.
If breast cancer cells express higher levels of mrna associated with a particular receptor than normal cells do, it might be that this receptor plays a role in breast cancer A drug that interferes with this receptor may prevent or treat breast cancer Laser Scanning Cluster Analysis Molecular classification of Melanoma using gene profiling 1. Identify subsets of patients with melanoma: who will do well, who are at risk for progression of their disease, who will have metastatic disease 2. Understand the molecular basis of melanoma progression 3. Determine whether distinct signatures exist for the known clinical and histological stages in melanoma progression 4. What can we learn about melanoma biology by studying gene expression patterns? Molecular signatures of Melanoma Transitions Microarray analysis of RGP vs. VGP shows only loss of gene expression RGP to VGP Nevus to melanoma Primary to Green signals indicate losses of gene expression: genes coding for proteins involved in cell adhesion and extracellular matrix molecules CDH3 and MMP10 RGP Markers
Melanoma In Situ with Extensive Regression: primary and metastasis CDH3 Radial growth phase genes can give rise to metastatic melanoma MMP10 Primary Metastatic Melanoma is Two Diseases at the Molecular Level Molecular Model of Melanoma Progression RGP signatures 25% All patients died VGP signatures 75% 1/3 Alive Melanocyte Nevus Radial Growth Phase Melanoma CDH3, MMP10 Vertical Growth Phase Melanoma Microarray Analysis of Nevi Versus Melanomas Microarray Analysis Assigns Distinct Signatures to Different Phases of Melanoma Progression
The Challenge Novel Molecular Prognostic Markers for Melanoma Identify and validate relevant factors in melanoma progression Examine the prognostic impact of the expression of the highest ranked genes at the protein level Nuclear receptor coactivator 3 (NCOA3, AIB-1, SRC-3) Secreted phosphoprotein-1 1 (SPP1, osteopontin) Regulator of protein signaling 1 (RGS1) Correlate this with clinical and histologic information Develop clinically meaningful assays NCOA3 in Human Cancer (Nuclear receptor co-activator ctivator receptor protein 3) NCOA3 and Melanoma Oncogenic member of the steroid receptor activator or SRC gene family AIB1 or amplified in breast cancer 1 Breast, ovarian and endometrial cancer Differentially expressed in metastatic versus unrelated primary melanomas Primary melanoma exhibiting higher levels of NCOA3 expression would be expected to have a higher risk of relapse and death Implicated as poor prognostic factor in prostate, gastric and pancreatic cancer NCOA3 has novel tumorigenic functions Assessment of Prognostic Role of NCOA3 Univariate Analyses Retrospective cohort study Stained and scored 343 primary melanomas with 2 yrs follow-up, relapse or undergoing SLN biopsy Mean f/u 49 months; median 45 months RFS relapse intransits, satellites, subq, LN, distant sites DSS deaths attributed to melanoma SLN status High NCOA3 (defined as 0,1 vs. 2,3) increased risk of relapse (52.2% vs 35.9%, P=0.010, Fisher exact) High NCOA3 increased risk of death due to melanoma (31.9% vs 18.5%, P=0.021, Fisher exact) Increasing NCOA3 expression (defined as 0 vs. 1,2 vs. 3) correlated with SLN metastasis (P= 0.013, logistic regression) Increasing NCOA3 expression correlated with increased SLN burden (P= 0.0004, ANOVA)