Abstract
Mycosis fungoides (MF) is the most prevalent type of skin lymphoma. In its early stages, it has a favorable prognosis. However, in its late stages, it is associated with an increased risk of mortality. This systematic review aimed to identify the transcriptomic changes involved in MF pathogenesis and progression. A literature search was conducted using the database PubMed, followed by the extraction of 2245 genes which were further filtered to 150 recurrent genes that appeared in two or more publications. Categorization of these genes identified activated pathways involved in pathways such as cell cycle and proliferation, chromosomal instability, and DNA repair. We identified 15 genes implicated in MF progression, which were involved in cell proliferation, immune checkpoints, resistance to apoptosis, and immune response. In highlighting the discrepancies in the way MF transcriptomic data is obtained, further research can focus on not only unifying their approach but also focus on the 150 pertinent genes identified in this review.
Highlights
Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL)derived from CD4+ T-cells [1]
MF skin samples comprise most of our study, 4 out of the 10 publications included CTCL skin samples but did not specify whether these samples were explicitly derived from MF or Sézary syndrome (SS) [17,18,19,20]
It is hypothesized that IL-15 promotes tumor progression via induction of survival and anti-apoptotic signals in malignant T-cells [75], while IL-32 has been shown to accelerate the proliferation of CTCL cell lines through MAPK and NF-KB dependent mechanisms [76]
Summary
Derived from CD4+ T-cells [1]. MF initially presents as erythematous patches and plaques and, in those early stages (IA-IB), the disease has a favorable prognosis. Large open-access databases, such as The Cancer Genome Atlas (TCGA), allow exploration of the genomewide expression of individual genes in different tissues and cancers from thousands of patients and aids in identifying several prognostic biomarkers [5,6]. Those resources focus on common cancers and have been less helpful for rare malignancies, such as MF. We stratified the data according to the type of MF lesion (plaque or tumor) and the nature of the comparator used to determine the differentially expressed genes
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