UV-Induced Mutations in Seemingly Normal Skin May Predict Skin Cancer

By Marilynn Larkin

January 13, 2021

NEW YORK (Reuters Health) - A novel technique called ultradeep sequencing revealed clonal mutations (CMs) induced by ultraviolet (UV) light exposure in seemingly normal skin samples. Researchers say the findings could pave the way to assessing skin damage and skin cancer risk before any signs emerge.

"Our study not only confirmed the existence of microscopic groups of cells in the normal skin with DNA alterations, so-called 'mutations,' but also allowed us to discover systematic differences between the mutations caused by UV from the ones caused by aging or other environmental factors," Dr. Gyorgy Paragh and Dr. Lei Wei, both of Roswell Park Comprehensive Cancer Center in Buffalo, New York, told Reuters Health by email.

"The UV-induced mutations often occur in specific sites ('hotspots') of human genes," they said, "and interestingly, some of these sites are rarely mutated in non-sun-exposed skin even with aging or other factors."

"We knew that mutational hotspots exist, but our finding that over one-third of the difference between the mutations in sun-exposed (SE) and non-SE (NE) areas were due to mutations in just six codons was striking," they noted.

"Our work shows that sun exposure in the skin leads to specific patterns of UV-induced mutations," they added "We also showed that the burden of mutation could be determined from clinically relevant small skin samples, and the burden of mutations can be combined in a clinically meaningful way to compare individual skin mutation levels."

"These findings identify targeted ultradeep sequencing of skin DNA samples as a tool to assess potentially cancer-causing cumulatively skin damage before the appearance of visible skin changes," they conclude.

As reported in Science Advances, the researchers developed a sequencing panel to asses the 55 most commonly mutated segments from 12 genes in normal skin. They used the panel to characterize 450 individual-matched SE and NE normal human skin samples from 13 White postmortem donors over age 55; 360 samples made up the discovery cohort and 90, the validation cohort.

For an extended cohort, 20 skin samples were obtained eight patients (mean age, 78; half women) undergoing surgeries for cutaneous squamous cell carcinoma (cSCC).

Significantly more UV-related mutations were found in the SE skin samples (226 mutations) compared with the NE samples (72 mutations).

Only six of 55 original regions were found to harbor significantly enriched mutations in the SE samples, and the number and relative contribution of CMs were significantly different between SE and NE areas.

Hotspots were seen in TP53, NOTCH1, and GRM3, where mutations were significantly associated with UV exposure. In the normal skin from patients with cSCC, cancer burden was associated with the UV-induced mutations, with the difference mostly conferred by the low-frequency CMs.

The authors state, "These findings provide previously unknown information on UV's carcinogenic effect and pave the road for future development of quantitative assessment of subclinical UV damage and skin cancer risk."

Drs. Wei and Paragh added, "We are starting a human biospecimen research study to show the utility of the focused ultra-high depth sequencing method for predicting human skin cancer risk and skin cancer prevention efficacy. We are also developing a new, fast and inexpensive non-scarring skin sampling method to allow wide-scale adaptation and easy clinical translation of focused ultra-high depth sequencing."

Dr. Janice Mehnert, associate director for clinical research at NYU Langone's Perlmutter Cancer Center, commented in an email to Reuters Health, "Determining that the low frequency clonal mutations are associated with the development of cSCC is a step to understanding tumor initiation and promotion. This may ultimately help us identify which patients are at risk for the development of cSCC and may even potentially reveal new targets for systemic treatment. Further validation of these findings in a larger prospective dataset is a logical next step."

SOURCE: https://bit.ly/2LquVaz Science Advances, online January 1, 2021

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