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. 2023 Mar 28;16(1):62.
doi: 10.1186/s12920-023-01492-0.

Potential miRNA-gene interactions determining progression of various ATLL cancer subtypes after infection by HTLV-1 oncovirus

Mohadeseh Zarei Ghobadi  1 , Elaheh Afsaneh  2 , Rahman Emamzadeh  3 , Mona Soroush  4
Affiliations

Potential miRNA-gene interactions determining progression of various ATLL cancer subtypes after infection by HTLV-1 oncovirus

Mohadeseh Zarei Ghobadi et al. BMC Med Genomics. .

Abstract

Background: Adult T-cell Leukemia/Lymphoma (ATLL) is a rapidly progressing type of T-cell non-Hodgkin lymphoma that is developed after the infection by human T-cell leukemia virus type 1 (HTLV-1). It could be categorized into four major subtypes, acute, lymphoma, chronic, and smoldering. These different subtypes have some shared clinical manifestations, and there are no trustworthy biomarkers for diagnosis of them.

Methods: We applied weighted-gene co-expression network analysis to find the potential gene and miRNA biomarkers for various ATLL subtypes. Afterward, we found reliable miRNA-gene interactions by identifying the experimentally validated-target genes of miRNAs.

Results: The outcomes disclosed the interactions of miR-29b-2-5p and miR-342-3p with LSAMP in ATLL_acute, miR-575 with UBN2, miR-342-3p with ZNF280B, and miR-342-5p with FOXRED2 in ATLL_chronic, miR-940 and miR-423-3p with C6orf141, miR-940 and miR-1225-3p with CDCP1, and miR-324-3p with COL14A1 in ATLL_smoldering. These miRNA-gene interactions determine the molecular factors involved in the pathogenesis of each ATLL subtype and the unique ones could be considered biomarkers.

Conclusion: The above-mentioned miRNAs-genes interactions are suggested as diagnostic biomarkers for different ATLL subtypes.

Keywords: ATLL subtypes; Asymptomatic carriers; HTLV-1; Interaction; WGCNA.

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Conflict of interest statement

All authors declare that they have no conflicts of interest and have never published the manuscript.

Figures

Fig. 1
Fig. 1
Flowchart of the step-wise analyses in this study
Fig. 2
Fig. 2
Dendrogram of clustered genes constructed by WGCNA based on (1-TOM) for (a) ATLL acute subtype (ATLL_acute), (b) ATLL chronic subtype (ATLL_chronic), and (c) ATLL smoldering subtype (ATLL_smoldering) with the specified module colors. Each color denotes a module (group of genes) determined by the dynamic tree cut algorithm before and after merging modules
Fig. 3
Fig. 3
Dendrogram of clustered genes constructed by WGCNA based on (1-TOM) for miRNA dataset of ATLL with the specified module colors. Each color denotes a module (group of genes) determined by the dynamic tree cut algorithm before and after merging modules
Fig. 4
Fig. 4
Preservation Zsummary (a-c) and medianRank (d-e) versus module size for ATLL acute subtype (ATLL_acute), ATLL chronic subtype (ATLL_chronic), and ATLL smoldering subtype (ATLL_smoldering), respectively. The modules below the dashed line ( Zsummary<2 and medianRank ≥ 8) are the specific modules for each ATLL subtype
Fig. 5
Fig. 5
Preservation (a) Zsummary and (b) medianRank versus module size after constructing a weighted miRNA co-expression network. The modules below the dashed line ( Zsummary<2 and medianRank ≥ 8) are the specific modules for ATLL.
Fig. 6
Fig. 6
The unique miRNA-gene interactions for (a) ATLL_acute, (b) ATLL_chronic, (c) ATLL_smoldering.
See this image and copyright information in PMC

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