3. Microbiome Analysis
The role of the microbiota in CTCL is not well understood yet. The recent establishment of next-generation sequencing methods and reference databases puts the skin microbiome and its role in the pathogenesis of CTCL in the spotlight.
Very recently, two studies on the skin microbiome in CTCL were published. These studies are focused on MF, and a further one on parapsoriasis, respectively. The literature was also checked for data on rarer subtypes of CTCL, e.g., CD4+ small/medium-sized lymphoproliferation and primary cutaneous CD30+ lymphoproliferative disorders. However, there is no evidence published about the microbiome in these entities.
Harkins et al. analyzed skin swabs from four MF patients (stages IA to IIIA) and two SS patients (stage IVA1), matched with samples from age- and sex-matched healthy volunteers. Via “shotgun metagenomic sequencing”, only slight shifts in the skin microbiota were noticed. They observed increasing trends in the mean relative abundances of
Corynebacterium species and decreasing trends in
Cutibacterium species without statistical significance. The authors suggested that the bacterial shifts may correlate with disease stage or treatment status
[21].
Another group, Salava et al., analyzed skin swabs from 20 Patients with MF at stages IA-IIB. They matched their data from both 16S rRNA gene sequencing” and “whole-genome shotgun sequencing” to swabs from contralateral healthy-appearing body sites on the same patients. This group also could not detect significant differences at the genus level or in the microbial diversity in the composition of the skin microbiome in their analyzed patients
[24].
In 2017 the same group already looked into microbiome changes in parapsoriasis-affected skin. In comparison to healthy-appearing, contra-lateral skin, there were not any statistically significant differences detectable
[25]. Parapsoriasis is primarily considered an inflammatory disease. However, it was discussed that parapsoriasis might represent a precursor to the development of lymphoma. Clinically, patients present persistent, finely scaling, and mildly eczematic lesions that might resemble early stage MF
[26].
In summary, the CTCL skin microbiome analyses did not yield statistically significant results, probably due to the small number of patients. CTCL is a rare disease; hence, multicenter analyses, the inclusion of larger patient numbers and investigations according to the same study protocol, should be considered to find statistically significant differences in the future.
3.1. Location Sites
Human skin sites provide diverse microenvironments that vary in pH, temperature, moisture, sebum content, and ultraviolet light exposure. Due to these characteristics, the sites can be grouped in sebaceous (face, chest and back), moist (bend of elbow, back of knee and groin), and dry (volar forearm and palm). Dependent on the physiology of the skin site, the composition of microbial communities changes in the relative abundance of bacterial taxa
[2][27][28]. Despite constant environmental change, skin microbial communities are quite stable at least over a two-year time period
[29].
3.2. Methods
The skins’ microorganisms are analyzed either by “amplicon sequencing” or “shotgun metagenomics”. In “amplicon sequencing”, the unique “16S ribosomal RNA gene” is sequenced for bacteria, which is called “16S rRNA gene sequencing/analysis”. For fungi, the internal transcribed spacer 1 (ITS1) region of the eukaryotic ribosomal gene is used. This follows assembly or mapping to a reference database. The “16S rRNA gene sequence” is like a unique “barcode” for every microbe. In contrast, “shotgun metagenomics/whole genome sequencing” captures the entire complement of genetic material in a sample without a previous targeted amplification step, either for DNA or RNA, which also includes the hosts’ genetic information
[2][27]. An overview of the methods that were applied to CTCL/parapsoriasis samples in recent studies is given in
Table 1.
Table 1. Methods and controls used in recent skin microbiome studies.
Author/Year |
Patients |
Skin Swabs |
16S rRNA Gene Sequencing |
Shotgun Metagenomics |
Control Skin Swabs |
Statistically Significant Differences |
Salava et al./2020 [24] |
20 |
lymphoma-affected (MF) |
completed |
completed |
healthy-appearing, contra-lateral |
none detected |
Salava et al./2017 [25] |
13 |
parapsoriasis-affected |
completed |
not completed |
healthy-appearing, contra-lateral |
none detected |
Harkins et al./2020 [21] |
6 |
lymphoma-affected (MF/SS) |
not completed |
completed |
healthy volunteer (lower back, thigh) |
none detected |
3.3. Healthy Controls
Matching the results from the microbiome analysis with the contralateral healthy-appearing skin or with the results from a healthy volunteer is essential because the ecological body site is a greater determinant of the microbiota composition than individual genetic variation. This means that the antecubital fossa, back, and plantar heel are more similar to the same site on another individual than to any other site on the same individual
[1][27][30]. This knowledge is important for any kind of microbiome analysis and not specific for CTCL patients.
3.4. General Limitations of Skin Microbiome Analyses
It is important to note that there are still limitations in the current microbiome analyses performed by “amplicon sequencing” or “whole-genome metagenomis”. Both cannot differentiate between living and dead microorganisms. To resolve this issue, it might be feasible to pre-digest and remove dead microbial cells from the analysis, to obtain a more accurate assessment of the living microbiome
[28].
Skin microbiome analysis usually relies on skin swabs; however, some microorganisms are variably present at the surface compared with deeper skin layers. These issues need to be addressed in future study protocols and are the topic of a recent review by Byrd et al.
[2].