Utility of Gene Expression Profiling in Skin Cancer: A Comprehensive Review

May 2023 | Volume 22 | Issue 5 | 451 | Copyright © May 2023


Published online April 19, 2023

Ryan Jay DOa, Benjamin Witkoff DOb, Nedyalko Ivanov DOc, Sean Kirk (MS III)d, Michael McBride DOe, Brian Martin PhDf, Shannon Trotter DOa,d,f,g

aOhioHealth Riverside Community Hospital, Columbus, OH
bLarkin Community Hospital Palm Springs Campus Dermatology Residency Program, Hialeah, FL
cBeaumont Health Systems-Department of Dermatology Farmington Hills Campus, Farmington Hills, MI
dOhio Heritage College of Osteopathic Medicine, Athens, OH
eHonorHealth Dermatology Residency Program, Scottsdale, AZ
fCastle Biosciences, Friendswood, TX
gDermatologists of Central States, Springfield, OH

Abstract
Understanding the metastatic potential of a skin cancer is essential to effective management. Gene expression profiling (GEP) is an innovative technology that has allowed for a better understanding of tumor biology in various skin cancers. Current methods focus on identifying and quantifying ribonucleic acid (RNA) transcripts in tissue samples. Using reverse transcriptase-polymerase chain reaction, specific RNA transcripts are reverted into deoxyribonucleic acid (DNA) for quantification. The addition of RNA-seq has further enhanced our knowledge of genomes not only by measuring known sequences, but also by identifying novel genes in various skin cancers. GEP requires only a small amount of RNA and has a high level of reproducibility. Using this technology, several GEPs for skin cancers have been developed to augment diagnosis and prognosis of skin cancer. This article reviews the process of gene expression profiling and the current GEPs that are available or under investigation for skin cancer.

J Drugs Dermatol. 2023;22(5): doi:10.36849/JDD.7017

Jay R, Witkoff B, Ivanov N, et al. Utility of gene expression profiling in skin cancer: a comprehensive review. J Drugs Dermatol. 2023;22(5):451-456. doi:10.36849/JDD.7017

INTRODUCTION

Current Staging Methods and the Need for Gene Expression Profiling
Skin cancer is the most prevalent malignancy in the United States.1 By current estimations, 1 in 5 Americans will develop skin cancer by the age of 70.2 Skin cancers are broadly divided into melanoma and non-melanoma skin cancers (NMSC), with melanoma, considered the deadliest - a predicted 7,180 deaths in the United States in 2021.3 

The 5-year survival rate for pathologically staged I-II melanoma is approximately 82% to 99%, and rates plummet with more advanced stages.4 Staging of melanoma using the American Joint Committee on Cancer (AJCC) criteria classifies tumors as stage 0 through IV based on tumor thickness (T in-situ to T4), ulceration status, sentinel lymph node involvement, and distant metastasis.4 However, this widely used staging system still presents limitations. Despite progression to later stages having a worse prognosis for patients, early-stage melanoma still represents the highest mortality burden; and subdividing this category into tumor depth quartiles did not present an expected worsening prognosis with increased depth.5 When using the AJCC guidelines, these conflicting outcomes and the inherent variability between pathologists when analyzing tumor histopathology indicate the need for additional avenues for the diagnosis and prognosis of melanoma and evaluation of tumor biology.6
 
For non-melanoma skin cancers, there were an estimated 3.3 million patients treated in 2012,1 and about 20% to 50% represent cutaneous squamous cell carcinoma (cSCC).7 The AJCC and the Brigham Women’s Hospital (BWH) are 2 main staging systems that use clinicopathologic criteria and high-risk factors for classifying cSCC (T1 to T4 in the AJCC and T1 to T3 in the BWH), but they too possess limitations.7,8  The AJCC 7 staging criteria was criticized for its high percentage of poor outcomes in earlier stages since its higher stages were too narrow in criteria. While the newer AJCC 8 has shown improvement in identifying higher stage cSCC that was not previously classified, the system still displays the limitation of having equivalent risks of nodal metastasis and disease-specific death in patients with stage T2 and T3, resulting in a heterogeneous T2/T3 group that has proved hard to differentiate by prognosis.8 BWH classifies 
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