Exome Sequencing of ABCB5 Identifies Recurrent Melanoma Mutations that Result in Increased Proliferative and Invasive Capacities

Sana, Géraldine; Madigan, James P.; Gartner, Jared J.; Fourrez, Marie; Lin, Jimmy C.; Qutob, Nouar; Narayan, Jitendra; Shukla, Suneet; Ambudkar, Suresh V.; Xia, Di; Rosenberg, Steven A.; Gottesman, Michael M.; Samuels, Yardena; Gillet, Jean Bernard

doi:10.1016/j.jid.2019.01.036

Cited by 8 publications

(5 citation statements)

References 31 publications

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“…ABCB5 is predominantly expressed in melanocytes and studies have indicated its involvement in tumor progression and resistance to various drugs in malignant tumors, including melanoma. [ 31 , 32 ] It affects the proliferative activity of melanoma cells and participates in VM. [ 33 ] Additionally, ABCB5 has been shown to promote tumor invasion by regulating EMT-related transcription factors.…”

Section: Discussionmentioning

confidence: 99%

Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Wang,

Zou,

Song

et al. 2024

Medicine

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Studies have indicated that Vascular mimicry (VM) could contribute to the unfavorable prognosis of skin cutaneous melanoma (SKCM). Thus, the objective of this study was to identify therapeutic targets associated with VM in SKCM and develop a novel prognostic model. Gene expression data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were utilized to identify differentially expressed genes (DEGs). By intersecting these DEGs with VM genes, we acquired VM-related DEGs specific to SKCM, and then identified prognostic-related VM genes. A VM risk score system was established based on these prognosis-associated VM genes, and patients were then categorized into high- and low-score groups using the median score. Subsequently, differences in clinical characteristics, gene set enrichment analysis (GSEA), and other analyses were further presented between the 2 groups of patients. Finally, a novel prognostic model for SKCM was established using the VM score and clinical characteristics. 26 VM-related DEGs were identified in SKCM, among the identified DEGs associated with VM in SKCM, 5 genes were found to be prognostic-related. The VM risk score system, comprised of these genes, is an independent prognostic risk factor. There were significant differences between the 2 patient groups in terms of age, pathological stage, and T stage. VM risk scores are associated with epithelial biological processes, angiogenesis, regulation of the SKCM immune microenvironment, and sensitivity to targeted drugs. The novel prognostic model demonstrates excellent predictive ability. Our study identified VM-related prognostic markers and therapeutic targets for SKCM, providing novel insights for clinical diagnosis and treatment.

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Section: Discussionmentioning

confidence: 99%

Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Wang,

Zou,

Song

et al. 2024

Medicine

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“…Previous studies have reported the role of these genes in the progression of GC and other cancers. Adenosine triphosphate ATP-binding cassette (ABCB5), as an ABC transporter, has shown linked to the development of drug resistance in many kinds of cancers, such as melanoma, human retinoblastoma, and acute leukemia [ 34 – 36 ]. Accumulating evidence revealed that the inhibition of ABCB5 had an impact on the malignant potential of cancer cells both in vitro and in vivo [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

et al. 2023

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Gastric cancer (GC) has been a common tumor type with high mortality. Distal metastasis is one of the main causes of death in GC patients, which is also related to poor prognosis. The mRNA profiles and clinical information of GC patients were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. Univariate Cox and LASSO Cox analyses were used to screen the optimal metastasis-related genes (MRGs) to establish a prognostic Risk Score model for GC patients. The nomogram was used to visualize the Risk Score and predict the 1-, 3-, 5-year survival rate. The immune cell infiltration was analyzed by CIBERSORT and the ratio of immune–stromal component was calculated by the ESTIMATE algorithm. A total of 142 differentially expressed genes were identified between metastatic and non-metastatic GC samples. The optimal 8 genes, comprising GAMT (guanidinoacetate N-methyltransferase), ABCB5 (ATP-binding cassette subfamily B member 5), ITIH3 (inter-alpha-trypsin inhibitor heavy chain 3), GDF3 (growth differentiation factor 3), VSTM2L (V-set and transmembrane domain-containing 2 like), CIDEA (cell death inducing DFFA like effector a), NPTX1 (neuronal pentraxin-1), and UMOD (uromodulin), were further screened to establish a prognostic Risk Score, which proved to be an independent prognostic factor. Patients in high-risk group had a poor prognosis. There were significant differences in the proportion of 11 tumor-infiltrating immune cells between high-risk and low-risk subgroups. In addition, the StromalScore, ImmuneScore, and ESTIMATEScore in high-risk group were higher than those in low-risk group, indicating that the tumor microenvironment of the high-risk group was more complex. A Risk Score model based on eight metastasis-related genes could clearly distinguish the prognosis of GC patients. The poor prognosis of patients with high-Risk Score might be associated with the complex tumor microenvironments.

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“…Anti-PD-1 drugs such as pembrolizumab and nivolumab can achieve long-term survival for patients with metastatic melanoma [ 52 ]. PTEN , as a tumour suppressor gene [ 53 ], was found only in the normal class, suggesting that PTEN mutations may be a factor affecting immune properties. Therefore, we suggest that they are potential therapeutic targets to improve the immune response.…”

Section: Discussionmentioning

confidence: 99%

Identification of Immune Function-Related Subtypes in Cutaneous Melanoma

Liu

Zhu

Jin

et al. 2021

Life

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Tumour immunotherapy combined with molecular typing is a new therapy to help select patients. However, molecular typing algorithms related to tumour immune function have not been thoroughly explored. We herein proposed a single sample immune signature network (SING) method to identify new immune function-related subtypes of cutaneous melanoma of the skin. A sample-specific network and tumour microenvironment were constructed based on the immune annotation of cutaneous melanoma samples. Then, the differences and heterogeneity of immune function among different subtypes were analysed and verified. A total of 327 cases of cutaneous melanoma were divided into normal and immune classes; the immune class had more immune enrichment characteristics. After further subdividing the 327 cases into three immune-related subtypes, the degree of immune enrichment in the “high immune subtype” was greater than that in other subtypes. Similar results were validated in both tumour samples and cell lines. Sample-specific networks and the tumour microenvironment based on immune annotation contribute to the mining of cutaneous melanoma immune function-related subtypes. Mutations in B2M and PTEN are considered potential therapeutic targets that can improve the immune response. Patients with a high immune subtype can generally obtain a better immune prognosis effect, and the prognosis may be improved when combined with TGF-β inhibitors.

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Exome Sequencing of ABCB5 Identifies Recurrent Melanoma Mutations that Result in Increased Proliferative and Invasive Capacities

Cited by 8 publications

References 31 publications

Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Establishment of skin cutaneous melanoma prognosis model based on vascular mimicry risk score

Development of a Signature Based on Eight Metastatic-Related Genes for Prognosis of GC Patients

Identification of Immune Function-Related Subtypes in Cutaneous Melanoma

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