Methylation Markers in Cutaneous Melanoma: Unravelling the Potential Utility of Their Tracking by Liquid Biopsy

Aleotti, Valentina; Catoni, Cristina; Poggiana, Cristina; Rosato, Antonio; Facchinetti, Antonella; Scaini, Maria Chiara

doi:10.3390/cancers13246217

Cited by 14 publications

(14 citation statements)

References 199 publications

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“…Malignant melanoma frequently occurs in the skin and has become one of the common malignant tumors of the skin [2,3]. Although the incidence rate of CMM is lower than that of cutaneous basal cell carcinoma and squamous cell carcinoma of the skin, its malignant degree is significantly higher than the former [1][2][3]. The incidence rate of CMM increases year by year, with a younger disease onset [2].…”

Section: Discussionmentioning

confidence: 99%

LINC01296 promotes proliferation of cutaneous malignant melanoma by regulating miR-324-3p/MAPK1 axis

Wang¹,

Luo

Zhang³

et al. 2022

Aging

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Objective: To investigate the functions and potential molecular mechanism of LINC01296 regarding the progression of cutaneous malignant melanoma (CMM) by the regulation of miR-324-3p/MAPK1 axis. Methods: The candidate differential lncRNAs of CMM were selected from GEPIA database, and quantitative realtime PCR (qRT-PCR) was utilized to assess the expression level of LINC01296 in human CMM tissues and cell lines. Cell proliferation assay, Colony formation assay, Ethynyl-2'-deoxyuridine (EDU) assay in vitro and tumorigenicity assays in nude mice in vivo were performed to examine the functions of LINC01296. Bioinformatics analysis, luciferase reporter assay and rescue experiments were also gained an insight into the underlying mechanisms of LINC01296 in CMM cell lines by miR-324-3p/MAPK1 axis. Results: In this study, the up-regulation of LINC01296 was found in CMM tissues and cell lines. Functionally, the over-expression of LINC01296 promoted the proliferation in CMM cell lines. In addition, immunochemistry analysis confirmed that the levels of MAPK1 and Ki-67 in sh-LINC01296-xenografted tumors was weaker than that in sh-NCxenografted tumors. Then, bioinformatics analysis confirmed that LINC01296 interacted with miR-324-3p. Further investigations showed that MAPK1, which collected from the potential related genes of LINC01296, was the conjugated mRNA of miR-324-3p by luciferase reporter assay. Finally, the rescue experiments suggested the positive regulatory association among LINC01296 and MAPK1, which showed that MAPK1 could reverse the promoting-effect of LINC01296 in CMM cells in vitro. Conclusions: Therefore, our findings provided insight into the mechanisms of LINC01296 via miR-324-3p/MAPK1 axis in CMM, and revealed an alternative target for the diagnosis and treatment of CMM.

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Section: Discussionmentioning

confidence: 99%

LINC01296 promotes proliferation of cutaneous malignant melanoma by regulating miR-324-3p/MAPK1 axis

Wang¹,

Luo

Zhang³

et al. 2022

Aging

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“…Finally, as therapy induces a selection pressure on the tumor, the clone carrying the driver mutation present at the beginning may not be the most informative to be tracked at all of the time points [ 56 ]. In this regard, although our NGS panel monitors most of the genes involved in melanoma progression and resistance to treatment ( Table S1, Supplementary Materials ), we cannot exclude that an epigenetic mutation [ 57 ] or one affecting the transcript expression could have guided the tumor proliferation in the final, highly advanced phase. That is currently why the timing of intervention, whether guided by a real-time approach such as liquid biopsy, could be of extreme importance for preventing the tumor outgrowth and uncontrolled proliferation of the newborn resistant clones.…”

Section: Discussionmentioning

confidence: 99%

Investigating the Retained Inhibitory Effect of Cobimetinib against p.P124L Mutated MEK1: A Combined Liquid Biopsy and in Silico Approach

Catoni

Poggiana

Facchinetti

et al. 2022

Cancers

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The systemic treatment of metastatic melanoma has radically changed, due to an improvement in the understanding of its genetic landscape and the advent of targeted therapy. However, the response to BRAF/MEK inhibitors is transitory, and big efforts were made to identify the mechanisms underlying the resistance. We exploited a combined approach, encompassing liquid biopsy analysis and molecular dynamics simulation, for tracking tumor evolution, and in parallel defining the best treatment option. The samples at different time points were collected from a BRAF-mutant melanoma patient who developed an early resistance to dabrafenib/trametinib. The analysis of the circulating tumor DNA (ctDNA) identified the MEK1 p.P124L mutation that confers resistance to trametinib. With an in silico modeling, we identified cobimetinib as an alternative MEK inhibitor, and consequently suggested a therapy switch to vemurafenib/cobimetinib. The patient response was followed by ctDNA tracking and circulating melanoma cell (CMC) count. The cobimetinib administration led to an important reduction in the BRAF p.V600E and MEK1 p.P124L allele fractions and in the CMC number, features suggestive of a putative response. In summary, this study emphasizes the usefulness of a liquid biopsy-based approach combined with in silico simulation, to track real-time tumor evolution while assessing the best treatment option.

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“…Aleotti et al. authored a review article that covers many of the key roles of global loss of DNA methylation with promoter CpG island hypermethylation for tumor promotion and lists many hypermethylated and hypomethylated genes that are associated with melanoma ( 79 ).…”

Section: Key Players In Resistance Against Immune Checkpoint Inhibito...mentioning

confidence: 99%

Mechanisms of Immunotherapy Resistance in Cutaneous Melanoma: Recognizing a Shapeshifter

et al. 2022

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Melanoma is one of the seven most common cancers in the United States, and its incidence is still increasing. Since 2011, developments in targeted therapies and immunotherapies have been essential for significantly improving overall survival rates. Prior to the advent of targeted and immunotherapies, metastatic melanoma was considered a death sentence, with less than 5% of patients surviving more than 5 years. With the implementation of immunotherapies, approximately half of patients with metastatic melanoma now survive more than 5 years. Unfortunately, this also means that half of the patients with melanoma do not respond to current therapies and live less than 5 years after diagnosis. One major factor that contributes to lower response in this population is acquired or primary resistance to immunotherapies via tumor immune evasion. To improve the overall survival of melanoma patients new treatment strategies must be designed to minimize the risk of acquired resistance and overcome existing primary resistance. In recent years, many advances have been made in identifying and understanding the pathways that contribute to tumor immune evasion throughout the course of immunotherapy treatment. In addition, results from clinical trials focusing on treating patients with immunotherapy-resistant melanoma have reported some initial findings. In this review, we summarize important mechanisms that drive resistance to immunotherapies in patients with cutaneous melanoma. We have focused on tumor intrinsic characteristics of resistance, altered immune function, and systemic factors that contribute to immunotherapy resistance in melanoma. Exploring these pathways will hopefully yield novel strategies to prevent acquired resistance and overcome existing resistance to immunotherapy treatment in patients with cutaneous melanoma.

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Methylation Markers in Cutaneous Melanoma: Unravelling the Potential Utility of Their Tracking by Liquid Biopsy

Cited by 14 publications

References 199 publications

LINC01296 promotes proliferation of cutaneous malignant melanoma by regulating miR-324-3p/MAPK1 axis

LINC01296 promotes proliferation of cutaneous malignant melanoma by regulating miR-324-3p/MAPK1 axis

Investigating the Retained Inhibitory Effect of Cobimetinib against p.P124L Mutated MEK1: A Combined Liquid Biopsy and in Silico Approach

Mechanisms of Immunotherapy Resistance in Cutaneous Melanoma: Recognizing a Shapeshifter

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