Gould Rothberg BE, Bracken MB, Rimm DLTissue biomarkers for prognosis in cutaneous melanoma: a systematic review and meta-analysis. J Natl Cancer Inst 101: 452-474

Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA.
Journal of the National Cancer Institute (Impact Factor: 12.58). 05/2009; 101(7):452-74. DOI: 10.1093/jnci/djp038
Source: PubMed


In the clinical management of early-stage cutaneous melanoma, it is critical to determine which patients are cured by surgery alone and which should be treated with adjuvant therapy. To assist in this decision, many groups have made an effort to use molecular information. However, although there are hundreds of studies that have sought to assess the potential prognostic value of molecular markers in predicting the course of cutaneous melanoma, at this time, no molecular method to improve risk stratification is part of recommended clinical practice. To help understand this disconnect, we conducted a systematic review and meta-analysis of the published literature that reported immunohistochemistry-based protein biomarkers of melanoma outcome. Three parallel search strategies were applied to the PubMed database through January 15, 2008, to identify cohort studies that reported associations between immunohistochemical expression and survival outcomes in melanoma that conformed to the REMARK criteria. Of the 102 cohort studies, we identified only 37 manuscripts, collectively describing 87 assays on 62 distinct proteins, which met all inclusion criteria. Promising markers that emerged included melanoma cell adhesion molecule (MCAM)/MUC18 (all-cause mortality [ACM] hazard ratio [HR] = 16.34; 95% confidence interval [CI] = 3.80 to 70.28), matrix metalloproteinase-2 (melanoma-specific mortality [MSM] HR = 2.6; 95% CI = 1.32 to 5.07), Ki-67 (combined ACM HR = 2.66; 95% CI = 1.41 to 5.01), proliferating cell nuclear antigen (ACM HR = 2.27; 95% CI = 1.56 to 3.31), and p16/INK4A (ACM HR = 0.29; 95% CI = 0.10 to 0.83, MSM HR = 0.4; 95% CI = 0.24 to 0.67). We further noted incomplete adherence to the REMARK guidelines: 14 of 27 cohort studies that failed to adequately report their methods and nine studies that failed to either perform multivariable analyses or report their risk estimates were published since 2005.

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Available from: Bonnie Gould Rothberg, Jun 23, 2014
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    • "Biomarkers could provide additional prognostic information based on the molecular mechanisms of transformation and disease progression. A systematic review summarizes the use of protein biomarkers visualized by immunohistochemistry to predict melanoma outcome (Rothberg et al., 2009). Gene expression profiling of melanoma has yielded an enormous amount of information leading to the definition of molecular signatures for disease progression (Haqq et al., 2005; Jaeger et al., 2007; Timar et al., 2010), recurrence, and survival (Bogunovic et al., 2009). "
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    ABSTRACT: Outcomes for melanoma patients with stage III disease, differ widely even within the same sub-category. Molecular signatures that more accurately predict prognosis are needed to stratify patients according to risk. Proteomic analyses were used to identify differentially abundant proteins in extracts of surgically excised samples from patients with stage IIIc melanoma lymph node metastases. Analysis of samples from patients with poor (n = 14, < 1 year) and good (n = 19, > 4 years) survival outcomes identified 84 proteins that were differentially abundant between prognostic groups. Subsequent selected reaction monitoring analysis verified 21 proteins as potential biomarkers for survival. Poor prognosis patients are characterized by increased levels of proteins involved in protein metabolism, nucleic acid metabolism, angiogenesis, deregulation of cellular energetics and methylation processes, and decreased levels of proteins involved in apoptosis and immune response. These proteins are able to classify stage IIIc patients into prognostic sub-groups (p < 0.02). This is the first report of potential prognostic markers from stage III melanoma using proteomic analyses. Validation of these protein markers in larger patient cohorts should define protein signatures that enable better stratification of stage III melanoma patients.This article is protected by copyright. All rights reserved.
    Pigment Cell & Melanoma Research 07/2014; 27(6). DOI:10.1111/pcmr.12290 · 4.62 Impact Factor
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    • "Comparison of the quality items of positive and negative studies show no statistically significant difference, allowing meaningful data aggregation. Although this is a relatively new tool, it has been used in other system reviews [127,128]. "
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    ABSTRACT: Esophageal cancer (EC) is a frequently occurring cancer with poor prognosis despite combined therapeutic strategies. Many biomarkers have been proposed as predictors of adverse events. We sought to assess the prognostic value of biomarkers in predicting the overall survival of esophageal cancer and to help guide personalized cancer treatment to give patients the best chance at remission. We conducted a systematic review and meta-analysis of the published literature to summarize evidence for the discriminatory ability of prognostic biomarkers for esophageal cancer. Relevant literature was identified using the PubMed database on April 11, 2012, and conformed to the REMARK criteria. The primary endpoint was overall survival and data were synthesized with hazard ratios (HRs). We included 109 studies, exploring 13 different biomarkers, which were subjected to quantitative meta-analysis. Promising markers that emerged for the prediction of overall survival in esophageal squamous cell cancer included VEGF (18 eligible studies, n = 1476, HR = 1.85, 95% CI, 1.55-2.21), cyclin D1 (12 eligible studies, n = 1476, HR = 1.82, 95% CI, 1.50-2.20), Ki-67 (3 eligible studies, n = 308, HR = 1.11, 95% CI, 0.70-1.78) and squamous cell carcinoma antigen (5 eligible studies, n = 700, HR = 1.28, 95% CI, 0.97-1.69); prognostic markers for esophageal adenocarcinoma included COX-2 (2 eligible studies, n = 235, HR = 3.06, 95% CI, 2.01-4.65) and HER-2 (3 eligible studies, n = 291, HR = 2.15, 95% CI, 1.39-3.33); prognostic markers for uncategorized ECs included p21 (9 eligible studies, n = 858, HR = 1.27, 95% CI, 0.75-2.16), p53 (31 eligible studies, n = 2851, HR = 1.34, 95% CI, 1.21-1.48), CRP (8 eligible studies, n = 1382, HR = 2.65, 95% CI, 1.64-4.27) and hemoglobin (5 eligible studies, n = 544, HR = 0.91, 95% CI, 0.83-1.00). Although some modest bias cannot be excluded, this review supports the involvement of biomarkers to be associated with EC overall survival.
    BMC Cancer 11/2013; 13(1):539. DOI:10.1186/1471-2407-13-539 · 3.36 Impact Factor
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    • "Our report was written to comply with REMARK criteria (McShane et al., 2005; Gould Rothberg et al., 2009b); therefore, we provide relevant information about study design, hypotheses, patient and specimen characteristics, assay methods, and statistical analysis methods. In addition, we conducted a replication study. "
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    ABSTRACT: The genetic alterations contributing to melanoma pathogenesis are incompletely defined, and few independent prognostic features have been identified beyond the clinicopathological characteristics of the primary tumor. We used transcriptome profiling of 46 primary melanomas, 12 melanoma metastases, and 16 normal skin samples to find novel genes associated with melanoma development and progression. Results were confirmed using immunohistochemistry and real-time PCR and replicated in an independent set of 330 melanomas using AQUA analysis of tissue microarray. Transcriptome profiling revealed that transcription factor HMGA2, previously unrecognized in melanoma pathogenesis, is significantly upregulated in primary melanoma and metastases (P-values=1.2 × 10(-7) and 9 × 10(-5)) compared to normal skin. HMGA2 overexpression is associated with BRAF/NRAS mutations (P=0.0002). Cox-proportional hazard regression model and log-rank test showed that HMGA2 is independently associated with DFS (hazard ratio (HR)=6.3, 95% confidence interval (CI)=1.8-22.3, P=0.004), OS (stratified log-rank P=0.008), and DMFS (HR=6.4, 95%CI=1.4-29.7, P=0.018) after adjusting for AJCC stage and age at diagnosis. Survival analysis in an independent replication tissue microarray (TMA) of 330 melanomas confirmed the association of HMGA2 expression with OS (P=0.0211). Our study implicates HMGA2 in melanoma progression and demonstrates that HMGA2 overexpression can serve as an independent predictor of survival in melanoma.Journal of Investigative Dermatology accepted article preview online, 30 April 2013; doi:10.1038/jid.2013.197.
    Journal of Investigative Dermatology 04/2013; 133(11). DOI:10.1038/jid.2013.197 · 7.22 Impact Factor
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