In silico bioinformatics analysis for identification of differentially expressed genes and therapeutic drug molecules in Glucocorticoid-resistant Multiple myeloma

Ghosal, Somnath; Banerjee, Subrata

doi:10.1007/s12032-022-01651-w

Cited by 3 publications

(2 citation statements)

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“…NOTCH3 mutation may regulate the transcription of pTa and the activity of the NF-kB signaling pathway to promote tumor progression [ 19 ]. RELN mutation plays a role by enhancing glycolysis and activating the Akt/STAT3 pathway [ 20 , 21 ]. The detection of specific gene mutation mutations may assist in stratifying patients more accurately, providing information for prognosis and laying the basis for treatment strategies.…”

Section: Discussionmentioning

confidence: 99%

Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study

Chen²,

Xu³

et al. 2022

Cancers

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A proportion of patients with somatic variants show resistance or intolerance to TKI therapy, indicating additional mutations other than BCR∷ABL1 may lead to TKI treatment failure or disease progression. We retrospectively evaluated 151 CML patients receiving TKI therapy and performed next-generation sequencing (NGS) analysis of 22 CML patients at diagnosis to explore the mutation spectrum other than BCR∷ABL1 affecting the achievement of molecular responses. The most frequently mutated gene was ASXL1 (40.9%). NOTCH3 and RELN mutations were only carried by subjects failing to achieve a major molecular response (MMR) at 12 months. The distribution frequency of ASXL1 mutations was higher in the group that did not achieve MR4.0 at 36 months (p = 0.023). The achievement of MR4.5 at 12 months was adversely impacted by the presence of >2 gene mutations (p = 0.024). In the analysis of clinical characteristics, hemoglobin concentration (HB) and MMR were independent factors for deep molecular response (DMR), and initial 2GTKI therapy was better than 1GTKI in the achievement of molecular response. For the scoring system, we found the ELTS score was the best for predicting the efficacy of TKI therapy and the Socal score was the best for predicting mutations other than BCR∷ABL.

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Section: Discussionmentioning

confidence: 99%

Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study

Chen²,

Xu³

et al. 2022

Cancers

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“…To date, the focus of MM research has been bioinformatics modelling of large genomics and transcriptomics datasets, as well as pharmacokinetic and pharmacodynamic (PKPD) simulations of drug interactions. These have led to significant findings, including identifying novel signalling pathways [ 38 , 39 ], genetic risk factors [ 40 , 41 ], biomarkers [ 42 , 43 ], RNA interactions [ 44 , 45 , 46 , 47 ], and oncogenic inflammation and microenvironments [ 48 , 49 ]. Similarly, these large datasets can be used to develop models of the effects and side effects of drug interventions [ 50 ] by modelling the signalling interactions of different cell types [ 48 ].…”

Section: Three-dimensional Models Of Multiple Myelomamentioning

confidence: 99%

Utilizing 3D Models to Unravel the Dynamics of Myeloma Plasma Cells’ Escape from the Bone Marrow Microenvironment

Verbruggen,

Freeman,

Freeman

2024

Cancers

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Recent therapeutic advancements have markedly increased the survival rates of individuals with multiple myeloma (MM), doubling survival compared to pre-2000 estimates. This progress, driven by highly effective novel agents, suggests a growing population of MM survivors exceeding the 10-year mark post-diagnosis. However, contemporary clinical observations indicate potential trends toward more aggressive relapse phenotypes, characterized by extramedullary disease and dominant proliferative clones, despite these highly effective treatments. To build upon these advances, it is crucial to develop models of MM evolution, particularly focusing on understanding the biological mechanisms behind its development outside the bone marrow. This comprehensive understanding is essential to devising innovative treatment strategies. This review emphasizes the role of 3D models, specifically addressing the bone marrow microenvironment and development of extramedullary sites. It explores the current state-of-the-art in MM modelling, highlighting challenges in replicating the disease’s complexity. Recognizing the unique demand for accurate models, the discussion underscores the potential impact of these advanced 3D models on understanding and combating this heterogeneous and still incurable disease.

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Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma

Zheng,

Chen,

et al. 2023

CBM

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BACKGROUND: Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease. OBJECTIVE: We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value. METHODS: Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database. RESULTS: Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223–2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744. CONCLUSIONS: The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.

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In silico bioinformatics analysis for identification of differentially expressed genes and therapeutic drug molecules in Glucocorticoid-resistant Multiple myeloma

Cited by 3 publications

References 50 publications

Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study

Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study

Utilizing 3D Models to Unravel the Dynamics of Myeloma Plasma Cells’ Escape from the Bone Marrow Microenvironment

Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma

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