| Literature DB >> 32246161 |
Bruna Ferreira1, Joana Caetano2, Filipa Barahona1, Raquel Lopes1, Emilie Carneiro1, Bruno Costa-Silva3, Cristina João4.
Abstract
Multiple myeloma (MM) is a challenging, progressive, and highly heterogeneous hematological malignancy. MM is characterized by multifocal proliferation of neoplastic plasma cells in the bone marrow (BM) and sometimes in extramedullary organs. Despite the availability of novel drugs and the longer median overall survival, some patients survive more than 10 years while others die rapidly. This heterogeneity is mainly driven by biological characteristics of MM cells, including genetic abnormalities. Disease progressions are mainly due to the inability of drugs to overcome refractory disease and inevitable drug-resistant relapse. In clinical practice, a bone marrow biopsy, mostly performed in one site, is still used to access the genetics of MM. However, BM biopsy use is limited by its invasive nature and by often not accurately reflecting the mutational profile of MM. Recent insights into the genetic landscape of MM provide a valuable opportunity to implement precision medicine approaches aiming to enable better patient profiling and selection of targeted therapies. In this review, we explore the use of the emerging field of liquid biopsies in myeloma patients considering current unmet medical needs, such as assessing the dynamic mutational landscape of myeloma, early predictors of treatment response, and a less invasive response monitoring.Entities:
Keywords: Biomarkers; Liquid biopsy; Multiple myeloma; Precision medicine
Mesh:
Substances:
Year: 2020 PMID: 32246161 PMCID: PMC7198642 DOI: 10.1007/s00109-020-01897-9
Source DB: PubMed Journal: J Mol Med (Berl) ISSN: 0946-2716 Impact factor: 4.599
Overview of specific miRNA as potential biomarkers for MM and other monoclonal gammopathies
| Study design | Upregulated | Downregulated | Reference |
|---|---|---|---|
| MM patients vs healthy controls | miR-142-5p | miR-17 | [ |
| miR-29a | miR-19a | ||
| miR-660 | miR-19b | ||
| miR-202 | miR-20a | ||
| miR-148 | miR-92a | ||
| miR-181a | miR-1308 | ||
| miR-20a | miR-191 | ||
| miR-221 | miR-130a | ||
| miR-99b | let-7d | ||
| miR-146a | miR-103 | ||
| miR-16 | let-7e | ||
| miR-186 | miR-744 | ||
| miR-454 | miR-151-5p | ||
| miR-483-5p | |||
| miR-720 | |||
| miR-1246 | |||
| miR-218 | |||
| miR-34a | |||
| miR-1274A | |||
| miR-138 | |||
| miR-10b | |||
| miR-1243 | |||
| Newly diagnosed MM patients vs healthy controls | miR-135b-5p | miR-19a | [ |
miR-214-3p miR-33b | miR-92a miR-20a | ||
| miR-3658 | |||
| miR-4254 | |||
| miR-483-5p | |||
| MGUS vs healthy controls | miR720 | miR-19a | [ |
| miR-1246 | miR-1308 | ||
| miR-34a | miR-744 | ||
| miR-130a | |||
| let-7d | |||
| let-7e | |||
| miR-16 | |||
| miR-25 | |||
| miR-20a | |||
| miR-25 | |||
| miR-660 | |||
| MGUS vs MM patients | miR-19a | [ | |
| miR-25 | |||
| MM patients at relapse vs diagnosis | miR-34a | let-7e | [ |
| MM patients at diagnosis vs patients in complete response | – | miR-16 | [ |
| miR-25 | |||
| miR-20a | |||
| miR-25 | |||
| miR-660 |
Correlation of miRNA and cytogenetic abnormalities
| miRNA | Upregulation/Downregulation | Cytogenetic abnormalities | Reference |
|---|---|---|---|
| miR-19a | Downregulation | del(13q14) and 1q21 amplification | [ |
| miR-99b | Upregulation | t(4;14) | [ |
| miR-211 | Downregulation | del(13q) | [ |
| let-7e and miR-744 | Downregulation | del(13q) | [ |
| miR-744 | Downregulation | 1q12 amplification or t(4;14) | [ |
| miR-15 and miR-16 | Downregulation/ Loss | del(13q14) | [ |
Correlation between miRNA and drug resistance in MM
| miRNA | Upregulation/downregulation | Treatment | Indicator | Reference |
|---|---|---|---|---|
| miR-15a and miR-16-1 | Upregulation | Cytotoxic agents | Increased growth and survival of MM cells | [ |
| miR-19a | Downregulation | Bortezomib | Improved PFS and OS | [ |
| miR-202 | Upregulation | Bortezomib | Increased sensitivity | [ |
| miR-513a-5p, miR-20b-3p, let-7d-3p | Upregulation | Bortezomib | Increased resistance | [ |
| miR-125b-5p, miR-19a-3p, miR-21-5p, miR-20a-5p, miR-17-5p, miR-15a-5p, miR-16-5p | Downregulation | Bortezomib | Increased resistance | [ |
| miR-19b and miR-331 | Upregulation | ASCT | Longer PFS | [ |
| miR-483-5p | Downregulation | TAD, VC, PAD, TD and VTD | Higher PFS | [ |
| miR-26a-5p, miR-29c-3p, miR-30b-5p, miR-30c-5p, miR-193a5p, miR-331-3p, | Downregulation | Lenalidomide with low dose Dexamethasone | Shorter TTP | [ |
Comparison between the different approaches to liquid biopsies
| Advantages | Limitations | |
|---|---|---|
| CTCs | -Several methods available for enumeration and characterization of CTCs (PCR, flow cytometry, image-based immunomagnetic, microchip) -Potential to consistently enumerate, track, and characterize CTCs throughout the course of disease -Possibility of assessing molecular characteristics of CTCs for clinical decision-making -Could be cultured to evaluate drug resistance in vitro or in vivo and used for functional assays | -Low number in blood requires very sensitive and robust methods -High sample volume or sample enrichment approaches needed to increase likelihood of detection -Costly, specifically if background blood profiling is needed -Lacks standardization and reproducibility -Need for large-scale clinical data for validation in clinical practice |
| ctDNA | -Can be sampled regularly to monitor response to treatment, clonal evolution, and acquisition of resistance -Wide range of techniques for analysis available (NGS, digital droplet PCR) -Represents tumor heterogeneity (genetic alterations, level of genetic instability, number and properties of sub-clones) -Found in larger quantities in blood than CTCs -More stable than miRNA -Analysis performed in other body fluids than blood (urine, CSF) | -Concentration of ctDNA variable among patients and according to type, location, and stage of disease -Half-life of ctDNA still unclear -Source of ctDNA not clear (lytic, apoptotic tumor cells or CTCs) -Presence of background of non-altered circulating free DNA (cfDNA) from other cellular sources -Requires previous knowledge of target of interest -Need to control preanalytic aspects (rapid processing of samples to avoid cell death and release of ctDNA not reflecting tumor cells) -Need for large-scale clinical data for validation in clinical practice |
| miRNA | -Stable in healthy individuals (age, gender, body mass) vs altered expression in disease -Various sources (plasma, serum, urine, saliva) -Sensitive detection methods for miRNAs (sensitive biomarker) -Dynamic expression pattern associated with stage and progression of disease -Potential target for MM treatment | -Sampling methods could impact miRNA detection -Level of miRNA in patients and healthy individuals overlap (increased possibility of false negative or positive diagnosis) -Altered expression patterns of the same miRNA in various types of cancers -No single miRNA biomarker but a combination needed for clinical application |
| EV | -Easy to access -Present in several body fluids -Longevity and stability within circulation -Potential biomarker for early detection and prognosis of MM -Potential drug delivery vehicle and vaccine -Potential target for MM treatment | -Lack of standardization protocols -Circulating EVs can be influenced by several patient factors -Time-consuming -High cost -Heterogeneity of EV recovery population between methods -Need for correlation with clinical data |