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Molecular Diagnostics for Melanoma

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Cover of 'Molecular Diagnostics for Melanoma'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Novel insights/translational implication from the emerging biology of melanoma.
  3. Altmetric Badge
    Chapter 2 Emerging clinical issues in melanoma in the molecularly targeted era.
  4. Altmetric Badge
    Chapter 3 Integrating molecular biomarkers into current clinical management in melanoma.
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    Chapter 4 Advances in adjuvant therapy: potential for prognostic and predictive biomarkers.
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    Chapter 5 Immunologic Monitoring of Cancer Vaccine Trials Using the ELISPOT Assay
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    Chapter 6 Markers for Anti-cytotoxic T-lymphocyte Antigen 4 (CTLA-4) Therapy in Melanoma.
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    Chapter 7 Marker utility for combination therapy.
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    Chapter 8 Assaying for BRAF V600E in Tissue and Blood in Melanoma.
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    Chapter 9 Selecting Patients for KIT Inhibition in Melanoma.
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    Chapter 10 Detecting Mechanisms of Acquired BRAF Inhibitor Resistance in Melanoma.
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    Chapter 11 Current status of diagnostic and prognostic markers in melanoma.
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    Chapter 12 Chromosomal copy number analysis in melanoma diagnostics.
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    Chapter 13 Construction and analysis of multiparameter prognostic models for melanoma outcome.
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    Chapter 14 Immunohistochemical diagnostic and prognostic markers for melanoma.
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    Chapter 15 Lymphatic Invasion as a Prognostic Biomarker in Primary Cutaneous Melanoma
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    Chapter 16 Tumor-infiltrating lymphocytes and their significance in melanoma prognosis.
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    Chapter 17 Pathological Staging of Melanoma
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    Chapter 18 Genotyping of Human Leukocyte Antigen (HLA) Ancestral Haplotypes as Prognostic Marker in Cancer Using PCR Analysis
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    Chapter 19 B7-h abnormalities in melanoma and clinical relevance.
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    Chapter 20 Melanoma susceptibility genes and risk assessment.
  22. Altmetric Badge
    Chapter 21 Clinical, pathologic, and imaging features and biological markers of uveal melanoma.
  23. Altmetric Badge
    Chapter 22 A prognostic test to predict the risk of metastasis in uveal melanoma based on a 15-gene expression profile.
  24. Altmetric Badge
    Chapter 23 Molecular karyotyping for detection of prognostic markers in fine needle aspiration biopsy samples of uveal melanoma.
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    Chapter 24 ERBB4 Mutation Analysis: Emerging Molecular Target for Melanoma Treatment.
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    Chapter 25 Epigenetic markers of prognosis in melanoma.
  27. Altmetric Badge
    Chapter 26 Isolation of melanoma cell subpopulations using negative selection.
  28. Altmetric Badge
    Chapter 27 Circulating tumor cells as prognostic biomarkers in cutaneous melanoma patients.
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    Chapter 28 Detection of Chondroitin Sulfate Proteoglycan 4 (CSPG4) in Melanoma.
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    Chapter 29 Targeting Damage-Associated Molecular Pattern Molecules (DAMPs) and DAMP Receptors in Melanoma
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    Chapter 30 The Clinical Use of PET/CT in the Evaluation of Melanoma.
  32. Altmetric Badge
    Chapter 31 Immune System Functional Pathway Analysis Using Single Cell Network Profiling (SCNP): A Novel Tool in Cancer Immunotherapy.
  33. Altmetric Badge
    Chapter 32 Quantitative and Spatial Image Analysis of Tumor and Draining Lymph Nodes Using Immunohistochemistry and High-Resolution Multispectral Imaging to Predict Metastasis
  34. Altmetric Badge
    Chapter 33 COLD-PCR Enriches Low-Level Variant DNA Sequences and Increases the Sensitivity of Genetic Testing.
  35. Altmetric Badge
    Chapter 34 Isolation of Circulating MicroRNAs from Microvesicles Found in Human Plasma.
  36. Altmetric Badge
    Chapter 35 Detection of circulating tumor cells by photoacoustic flowmetry.
  37. Altmetric Badge
    Chapter 36 Statistical Design and Evaluation of Biomarker Studies
  38. Altmetric Badge
    Chapter 37 Tissue resources for clinical use and marker studies in melanoma.
Attention for Chapter 22: A prognostic test to predict the risk of metastasis in uveal melanoma based on a 15-gene expression profile.
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Chapter title
A prognostic test to predict the risk of metastasis in uveal melanoma based on a 15-gene expression profile.
Chapter number 22
Book title
Molecular Diagnostics for Melanoma
Published in
Methods in molecular biology, January 2014
DOI 10.1007/978-1-62703-727-3_22
Pubmed ID
Book ISBNs
978-1-62703-726-6, 978-1-62703-727-3
Authors

J William Harbour, Harbour JW, J. William Harbour, Harbour, J. William

Abstract

Uveal (ocular) melanoma is an aggressive cancer that metastasizes in up to half of patients. Uveal melanoma spreads preferentially to the liver, and the metastatic disease is almost always fatal. There are no effective therapies for advanced metastatic disease, so the most promising strategy for improving survival is to detect metastasis at an earlier stage or to treat high-risk patients in an adjuvant setting. An accurate test for identifying high-risk patients would allow for such personalized management as well as for stratification of high-risk patients into clinical trials of adjuvant therapy.We developed a gene expression profile (GEP) that distinguishes between primary uveal melanomas that have a low metastatic risk (class 1 tumors) and those with a high metastatic risk (class 2 tumors). We migrated the GEP from a high-density microarray platform to a 15-gene, qPCR-based assay that is now performed in a College of American Pathologists (CAP)-accredited Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory on a routine clinical basis on very small samples obtained by fine needle aspiration and on archival formalin-fixed specimens. We collaborated with several centers to show that our specimen collection protocol was easily learned and performed and that it allowed samples to be safely and reliably transported from distant locations with a very low failure rate. Finally, we showed in a multicenter, prospective study that our GEP assay is highly accurate for predicting which patients will develop metastatic disease, and it was significantly superior to the previous gold standard, chromosome 3 testing for monosomy 3. This is the only prognostic test in uveal melanoma ever to undergo such extensive validation, and it is currently being used in a commercial format under the trade name DecisionDx-UM in over 100 centers in the USA and Canada.

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Mendeley readers

The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Canada 1 1%
Unknown 73 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 21%
Student > Ph. D. Student 12 16%
Student > Master 9 12%
Professor 4 5%
Student > Postgraduate 4 5%
Other 13 17%
Unknown 17 23%
Readers by discipline Count As %
Medicine and Dentistry 28 37%
Biochemistry, Genetics and Molecular Biology 11 15%
Agricultural and Biological Sciences 10 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Business, Management and Accounting 1 1%
Other 2 3%
Unknown 22 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 November 2013.
All research outputs
#20,211,690
of 22,733,113 outputs
Outputs from Methods in molecular biology
#9,850
of 13,085 outputs
Outputs of similar age
#264,719
of 305,170 outputs
Outputs of similar age from Methods in molecular biology
#402
of 594 outputs
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