Literature DB >> 30004988

Real-world performance and utility of a noninvasive gene expression assay to evaluate melanoma risk in pigmented lesions.

Laura K Ferris1, Pedram Gerami2, Maral K Skelsey3, Gary Peck4, Catherine Hren5, Christopher Gorman6, Tana Frumento7, Daniel M Siegel8.   

Abstract

About 3 million surgical pigmented skin lesion biopsies are performed each year in the USA alone to diagnose fewer than 200 000 new cases of invasive melanoma and melanoma in situ using the current standard of care that includes visual assessment and histopathology. A recently described noninvasive adhesive patch-based gene expression rule-out test [pigmented lesion assay (PLA)] may be helpful in identifying high-risk pigmented skin lesions to aid with surgical biopsy decisions. The main objective of this utility study was to determine the real-world clinical performance of PLA use and assess how the PLA changes physician behavior in an observational cohort analysis of 381 patients assessed with the PLA. All (100%) of 51 PLA(+) test results were clinically managed with surgical biopsy. Of these, 19 (37%) were melanomas, corresponding to a number needed to biopsy of 2.7 and a biopsy ratio of 1.7. All melanomas were histopathologically classified as melanoma in situ or stage 1. Nearly all (99%) of 330 PLA(-) test results were clinically managed with surveillance. None of the three follow-up biopsies performed in the following 3-6 months, were diagnosed as melanoma histopathologically. The estimated sensitivity and specificity of the PLA from these data sets are 95 and 91%, respectively. Overall, 93% of PLA results positive for both LINC00518 and PRAME were diagnosed histopathologically as melanoma. PRAME-only and LINC00518-only lesions were melanomas histopathologically in 50 and 7%, respectively. The PLA alters clinical management of pigmented lesions and shows high clinical performance. The likelihood of positive histopathologic diagnosis of melanoma is higher in PLA results that are positive for both LINC00518 and PRAME.

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Mesh:

Year:  2018        PMID: 30004988     DOI: 10.1097/CMR.0000000000000478

Source DB:  PubMed          Journal:  Melanoma Res        ISSN: 0960-8931            Impact factor:   3.599


  13 in total

1.  Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

Authors:  Prathamesh M Kulkarni; Eric J Robinson; Jing Wang; Yvonne M Saenger; Jaya Sarin Pradhan; Robyn D Gartrell-Corrado; Bethany R Rohr; Megan H Trager; Larisa J Geskin; Harriet M Kluger; Pok Fai Wong; Balazs Acs; Emanuelle M Rizk; Chen Yang; Manas Mondal; Michael R Moore; Iman Osman; Robert Phelps; Basil A Horst; Zhe S Chen; Tammie Ferringer; David L Rimm
Journal:  Clin Cancer Res       Date:  2019-10-21       Impact factor: 12.531

2.  Real-World Application of a Noninvasive Two-Gene Expression Test for Melanoma Diagnosis.

Authors:  Michael A Marchetti; Japbani K Nanda; Silvia E Mancebo; Stephen W Dusza
Journal:  J Invest Dermatol       Date:  2021-03-17       Impact factor: 7.590

3.  Use of the Pigmented Lesion Assay to rapidly screen a patient with numerous clinically atypical pigmented lesions.

Authors:  Aatman Shah; John Hyngstrom; Scott R Florell; Douglas Grossman
Journal:  JAAD Case Rep       Date:  2019-11-20

4.  Sensitive Immunofluorescent Detection of the PRAME Antigen Using a Practical Antibody Conjugation Approach.

Authors:  Ksenia A Sapozhnikova; Vsevolod A Misyurin; Dmitry Y Ryazantsev; Egor A Kokin; Yulia P Finashutina; Anastasiya V Alexeeva; Igor A Ivanov; Milita V Kocharovskaya; Nataliya A Tikhonova; Galina P Popova; Vera A Alferova; Alexey V Ustinov; Vladimir A Korshun; Vladimir A Brylev
Journal:  Int J Mol Sci       Date:  2021-11-27       Impact factor: 5.923

5.  Non-Invasive, Topical Sampling of Potential, Low-Molecular Weight, Skin Cancer Biomarkers: A Study on Healthy Volunteers.

Authors:  Skaidre Jankovskaja; Maxim Morin; Anna Gustafsson; Chris D Anderson; Boglarka Lehoczki; Johan Engblom; Sebastian Björklund; Melinda Rezeli; György Marko-Varga; Tautgirdas Ruzgas
Journal:  Anal Chem       Date:  2022-04-08       Impact factor: 8.008

Review 6.  The Contributions of Cancer-Testis and Developmental Genes to the Pathogenesis of Keratinocyte Carcinomas.

Authors:  Brandon Ramchatesingh; Jennifer Gantchev; Amelia Martínez Villarreal; Raman Preet Kaur Gill; Marine Lambert; Sriraam Sivachandran; Philippe Lefrançois; Ivan V Litvinov
Journal:  Cancers (Basel)       Date:  2022-07-26       Impact factor: 6.575

7.  Pigmented Lesion Assay for Suspected Melanoma Lesions: A Health Technology Assessment.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2021-06-04

8.  Response to Rigel et al.

Authors:  Michael A Marchetti; Stephen W Dusza
Journal:  J Invest Dermatol       Date:  2021-07-14       Impact factor: 8.551

9.  Reverse Iontophoretic Extraction of Skin Cancer-Related Biomarkers.

Authors:  Maxim Morin; Sebastian Björklund; Skaidre Jankovskaja; Kieran Moore; Maria Begoña Delgado-Charro; Tautgirdas Ruzgas; Richard H Guy; Johan Engblom
Journal:  Pharmaceutics       Date:  2021-12-29       Impact factor: 6.321

10.  Real-time high-resolution millimeter-wave imaging for in-vivo skin cancer diagnosis.

Authors:  Amir Mirbeik; Robin Ashinoff; Tannya Jong; Allison Aued; Negar Tavassolian
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.996

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