Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Apr 3;18(2):185-195.
doi: 10.1007/s12195-025-00846-1. eCollection 2025 Apr.

High-Throughput Metabolomic Profiling of Skin Lesions: Comparative Study of Cutaneous Squamous Cell Carcinoma, Basal Cell Carcinoma, and Normal Skin Via e-Biopsy Sampling

Affiliations

High-Throughput Metabolomic Profiling of Skin Lesions: Comparative Study of Cutaneous Squamous Cell Carcinoma, Basal Cell Carcinoma, and Normal Skin Via e-Biopsy Sampling

Leetal Louie et al. Cell Mol Bioeng. .

Abstract

Purpose: Rising rates of cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) make standard histopathology diagnostic methods a bottleneck. Using tissue molecular information for diagnostics offers a promising alternative. Faster specimen collection and high-throughput molecular identification can improve the processing of the increasing number of tumors. This study aims (i) to confirm the ability of e-biopsy technique to harvest metabolites, (ii) to obtain high-resolution metabolomic profiles of cSCC, BCC, and healthy skin tissues, and (iii) to perform a comparative analysis of the collected profiles.

Methods: Tumor specimens were collected with electroporation-based biopsy (e-biopsy), a minimally invasive sampling collection tool, from 13 tissue samples (cSCC, BCC, and healthy skin) from 12 patients. Ultra performance liquid chromatography and tandem mass spectrometry (UPLC-MS-MS) was used for molecular identification and quantification of resulting metabolomic profiles.

Results: Here we report measurements of 2325 small metabolites identified (301 with high confidence) in 13 tissue samples from 12 patients. Comparative analysis identified 34 significantly (p < 0.05) differentially expressed high-confidence metabolites. Generally, we observed a greater number of metabolites with higher expression, in cSCC and in BCC compared to healthy tissues, belonging to the subclass amino acids, peptides, and analogues.

Conclusions: These findings confirm the ability of e-biopsy technique to obtain high-resolution metabolomic profiles suitable to downstream bioinformatics analysis. This highlights the potential of e-biopsy coupled with UPLC-MS-MS for rapid, high-throughput metabolomic profiling in skin cancers and supports its utility as a promising diagnostic alternative to standard histopathology.

Supplementary information: The online version contains supplementary material available at 10.1007/s12195-025-00846-1.

Keywords: Basal cell carcinoma; Cutaneous squamous cell carcinoma; E-Biopsy; Electroporation-based biopsy; High-throughput metabolomics; Metabolomic profiles.

PubMed Disclaimer

Conflict of interest statement

Conflicts of InterestEV, AS, JW, AG, ZY [49] are consultants to Elsy Medical.

Figures

Fig. 1.
Fig. 1.
Study workflow: A pulsed electric field (PEF) is delivered to a tissue sample for extraction of water-soluble molecules and sample extracts are stored in 1.5 mL tubes until ready for UPLC-MS-MS analysis. Data from UPLC-MS-MS is used for differential expression analysis
Fig. 2.
Fig. 2.
al Overabundance plots comparing the distribution of metabolites differential expression (both over- and under-expression) p-values between control (normal skin tissue), cSCC, BCC tumor samples. Results from 2 chromatography column types and mode is shown by the background color. A total of 13 samples, and 301 metabolites extracted by e-biopsy were analyzed. ad cSCC vs. Healthy, eh BCC vs. healthy and il cSCC vs. BCC
Fig. 3.
Fig. 3.
al Volcano plots showing the fold-change difference of metabolite intensities. ad cSCC vs. Healthy. b BCC vs. Healthy. c cSCC vs. BCC. Numbered datapoints correspond to metabolite names found in the table below the plots. Fold-change and p-value data for the metabolites identified in the table can be found in Tables 2, S5–S7. High-resolution plots can be found in Figs. S1–S12

Similar articles

References

    1. Lim, H. W., et al. The burden of skin disease in the United States. J Am Acad Dermatol. 76:958-972.e2, 2017. - PubMed
    1. Zhang, W., et al. Global, regional and national incidence, mortality and disability-adjusted life-years of skin cancers and trend analysis from 1990 to 2019: An analysis of the Global Burden of Disease Study 2019. Cancer Med. 10:4905–4922, 2021. - PMC - PubMed
    1. Perera, E., N. Gnaneswaran, C. Staines, A. K. Win, and R. Sinclair. Incidence and prevalence of non-melanoma skin cancer in Australia: A systematic review. Australasian Journal of Dermatology. 56:258–267, 2015. - PubMed
    1. Tang, E., K. Fung, and A.-W. Chan. Incidence and mortality rates of keratinocyte carcinoma from 1998–2017: a population-based study of sex differences in Ontario, Canada. CMAJ. 193:E1516–E1524, 2021. - PMC - PubMed
    1. Rogers, H. W., M. A. Weinstock, S. R. Feldman, and B. M. Coldiron. Incidence Estimate of Nonmelanoma Skin Cancer (Keratinocyte Carcinomas) in the US Population, 2012. JAMA Dermatol. 151:1081–1086, 2015. - PubMed

LinkOut - more resources