A nine-gene signature predicting clinical outcome in cutaneous melanoma

Brunner, Georg; Reitz, Martina; Heinecke, Achim; Lippold, A.; Berking, Carola; Suter, L.; Atzpodien, Jens

doi:10.1007/s00432-012-1322-z

Cited by 68 publications

(58 citation statements)

References 35 publications

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“…Five genes from a combined list from Conway et al and Jewell et al overlap with Winnepenninckx et al, and osteopontin overlapped between the Conway/Jewell and Gschaider et al studies. None of the 92 genes originally reported to be associated with OS in Brunner et al [58] and further assessed in a follow-up study [59] overlapped with genes reported in the other studies, though we note that none of the other studies defined genes directly associated with OS.…”

Section: Expression Of Protein-coding Genesmentioning

confidence: 57%

“…Interestingly, another recent study, which defined a pro-invasive HOXA1 transcriptional signature, found that patients from the Winnepenninckx et al study with a ‘high’ HOXA1 signature had poor DMFS, adding an intriguing underlying transcriptional mechanism to those original expression findings, though they did not note if DNA repair pathway genes were highly represented in their signature [57]. A second primary cutaneous melanoma expression profiling study identified 92 genes associated with OS [58], and a subsequent follow-up study, which further assessed these 92 genes, reported a 9-gene signature (6 protective and 3 unfavorable) associated with OS in a 91 patient cohort [59]. A recent report utilized serial analysis of gene expression (SAGE) to identify differentially expressed transcripts between 116 primary tumors that had not metastasized (stage I/II) and 72 primary tumors that had already spread at initial diagnosis (stage III/IV) [60].…”

Section: Expression Of Protein-coding Genesmentioning

confidence: 99%

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Revisiting determinants of prognosis in cutaneous melanoma

Weiss

Hanniford

Hernando

et al. 2015

Cancer

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The American Joint Committee on Cancer staging system for cutaneous melanoma is based on primary tumor thickness and the presence of ulceration, mitoses, lymph node spread, and distant metastases as determinants of prognosis. Although this cutaneous melanoma staging system has evolved over time to more accurately reflect patient prognosis, improvements are still needed, because current understanding of the particular factors (genetic mutation, expression alteration, host response, etc) that are critical for predicting patient outcomes is incomplete. Given the clinical and biologic heterogeneity of primary melanomas, new prognostic tools are needed to more precisely identify patients who are most likely to develop advanced disease. Such tools would affect clinical surveillance strategies and aid in patient selection for adjuvant therapy. The authors reviewed the literature on prognostic molecular and immunologic markers in primary cutaneous melanoma, their associations with clinicopathologic and survival outcomes, and their potential for incorporation into current staging models. Overall, the studies considered in this review did not define prognostic markers that could be readily incorporated into the current staging system. Therefore, efforts should be continued in these and other directions to maximize the likelihood of identifying clinically useful prognostic biomarkers for cutaneous melanoma. Cancer 2015;121:4108–4123. © 2015 American Cancer Society.

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Section: Expression Of Protein-coding Genesmentioning

confidence: 57%

Section: Expression Of Protein-coding Genesmentioning

confidence: 99%

Revisiting determinants of prognosis in cutaneous melanoma

Weiss

Hanniford

Hernando

et al. 2015

Cancer

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“…Web-based gene ontology analysis tools revealed that genes related to the biologic processes of tissue development and epithelial differentiation, as well as cell junction-related genes, are highly represented. In comparison, a subsequently reported signature discovered by Harbst and colleagues reflects genes related to wound/immune responses, DNA repair, and cell-cycle, whereas a subsequently reported 9-gene signature from Brunner and colleagues contains genes encoding small secretory peptides and cell invasion-related extracellular and cytoskeletal genes (24,25). Of note when directly comparing the gene panels is that CXCL14 was the only gene identified in the current analysis that was included in those genetic signatures.…”

Section: Discussionmentioning

confidence: 99%

Development of a Prognostic Genetic Signature to Predict the Metastatic Risk Associated with Cutaneous Melanoma

Gerami

Cook²,

Wilkinson

et al. 2015

Clinical Cancer Research

240

232

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Purpose: The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis.Experimental Design: A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis.Results: RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC ¼ 0.93) and validation (ROC ¼ 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis.Conclusions: The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented.

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“…The queried genes are KRT9, KBTBD10, DCD, ECRG2, PIP, SCGB1D2, SCGB2A2, COL6A6, and HES6, and the genetic signatures were validated among a cohort of 44 additional melanomas (Brunner et al 2013). Several of the genes associated with metastasis encode stromal proteins, suggesting the importance of the tumor's microenvironment in the clinical course of melanoma.…”

Section: Genomic Expression Patterns Associated With Aggressive Clinimentioning

confidence: 99%

Melanoma: Clinical Features and Genomic Insights

Hawryluk

Tsao

2014

Cold Spring Harbor Perspectives in Medicine

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Recent efforts in genomic research have enabled the characterization of molecular mechanisms underlying many types of cancers, ushering novel approaches for diagnosis and therapeutics. Melanoma is a molecularly heterogeneous disease, as many genetic alterations have been identified and the clinical features can vary. Although discoveries of frequent mutations including BRAF have already made clinically significant impact on patient care, there is a growing body of literature suggesting a role for additional mutations, driver and passenger types, in disease pathophysiology. Although some mutations have been strongly associated with clinical phenotypes of melanomas (such as physical distribution or morphologic subtype), the function or implications of many of the recently identified mutations remains less clear. The phenotypic and clinical impact of genomic mutations in melanoma remains a promising opportunity for progress in the care of melanoma patients. There have been many recent advances in our understanding of melanoma, from a greater appreciation of epidemiologic trends and risk factors to an increased understanding of the molecular genomics and biology of melanoma. Studies suggest that a number of molecularly distinct changes have a role in the pathophysiology of melanoma, and melanomas encompass a heterogeneous group when considering many known genomic alterations and diverse clinical phenotypes. To date, there are clinical subtypes or "phenotypes" of melanoma that are associated with specific genomic changes, in addition to many identified genomic mutations that lack a clear clinical correlation.Genomic studies are able to inform us about the disease phenotype, in addition to improving our understanding of disease pathogenesis. The various phenotypes of melanoma are characterized by clinical features, such as bodily distribution or risk factors. Cutaneous, uveal, acral, and mucosal melanomas (Fig. 1) have divergent clinical courses and are associated with distinct mutations, and risk factors such as skin phototype or UV exposure pattern are also associated with distinct alterations in genetic mutations. A melanoma phenotype can also be classified based on histopathologic morphology such as superficial spreading, nodular, desmoplastic, etc. In this review, we examine a number of Editors: Anthony E. Oro and Fiona M. Watt Additional Perspectives on The Skin and Its Diseases available at www.perspectivesinmedicine.org

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A nine-gene signature predicting clinical outcome in cutaneous melanoma

Abstract: Our gene score defines patient risk and need for therapy in melanoma. The score has the potential to be utilized in clinical routine, since it is quantitative, robust, simple, and independent of AJCC stage and sample purity.

Cited by 68 publications

References 35 publications

Revisiting determinants of prognosis in cutaneous melanoma

Revisiting determinants of prognosis in cutaneous melanoma

Development of a Prognostic Genetic Signature to Predict the Metastatic Risk Associated with Cutaneous Melanoma

Melanoma: Clinical Features and Genomic Insights

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