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A Cancer-Related microRNA Signature Shows Biomarker Utility in Multiple Myeloma.

ABSTRACT: Multiple myeloma (MM) is the second most common hematological malignancy, arising from terminally differentiated B cells, namely plasma cells. miRNAs are small non-coding RNAs that participate in the post-transcriptional regulation of gene expression. In this study, we investigated the role of nine miRNAs in MM. CD138+ plasma cells were selected from bone marrow aspirates from MM and smoldering MM (sMM) patients. Total RNA was extracted and in vitro polyadenylated. Next, first-strand cDNA synthesis was performed using an oligo-dT-adapter primer. For the relative quantification of the investigated miRNAs, an in-house real-time quantitative PCR (qPCR) assay was developed. A functional in silico analysis of the miRNAs was also performed. miR-16-5p and miR-155-5p expression was significantly lower in the CD138+ plasma cells of MM patients than in those of sMM patients. Furthermore, lower levels of miR-15a-5p, miR-16-5p, and miR-222-3p were observed in the CD138+ plasma cells of MM patients with osteolytic bone lesions, compared to those without. miR-125b-5p was also overexpressed in the CD138+ plasma cells of MM patients with bone disease that presented with skeletal-related events (SREs). Furthermore, lower levels of miR-223-3p were associated with significantly worse overall survival in MM patients. In conclusion, we propose a miRNA signature with putative clinical utility in MM.

SUBMITTER: Papanota AM

PROVIDER: S-EPMC8658678 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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A Cancer-Related microRNA Signature Shows Biomarker Utility in Multiple Myeloma.

Papanota Aristea-Maria AM Karousi Paraskevi P Kontos Christos K CK Artemaki Pinelopi I PI Liacos Christine-Ivy CI Papadimitriou Maria-Alexandra MA Bagratuni Tina T Eleutherakis-Papaiakovou Evangelos E Malandrakis Panagiotis P Ntanasis-Stathopoulos Ioannis I Gavriatopoulou Maria M Kastritis Efstathios E Avgeris Margaritis M Dimopoulos Meletios-Athanasios MA Scorilas Andreas A Terpos Evangelos E

International journal of molecular sciences 20211205 23

Multiple myeloma (MM) is the second most common hematological malignancy, arising from terminally differentiated B cells, namely plasma cells. miRNAs are small non-coding RNAs that participate in the post-transcriptional regulation of gene expression. In this study, we investigated the role of nine miRNAs in MM. CD138+ plasma cells were selected from bone marrow aspirates from MM and smoldering MM (sMM) patients. Total RNA was extracted and in vitro polyadenylated. Next, first-strand cDNA synthe ...[more]

PMID: 34884950

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Project description:BackgroundMultiple myeloma (MM) is a highly malignant hematological tumor with a poor overall survival (OS). Due to the high heterogeneity of MM, it is necessary to explore novel markers for the prognosis prediction for MM patients. Ferroptosis is a form of regulated cell death, playing a critical role in tumorigenesis and cancer progression. However, the predictive role of ferroptosis-related genes (FRGs) in MM prognosis remains unknown.MethodsThis study collected 107 FRGs previously reported and utilized the least absolute shrinkage and selection operator (LASSO) cox regression model to construct a multi-genes risk signature model upon FRGs. The ESTIMATE algorithm and immune-related single-sample gene set enrichment analysis (ssGSEA) were carried out to evaluate immune infiltration level. Drug sensitivity was assessed based on the Genomics of Drug Sensitivity in Cancer database (GDSC). Then the synergy effect was determined with Cell counting kit-8 (CCK-8) assay and SynergyFinder software.ResultsA 6-gene prognostic risk signature model was constructed, and MM patients were divided into high and low risk groups. Kaplan-Meier survival curves showed that patients in the high risk group had significantly reduced OS compared with patients in the low risk group. Besides, the risk score was an independent predictor for OS. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of the risk signature. Combination of risk score and ISS stage had better prediction performance. Enrichment analysis revealed immune response, MYC, mTOR, proteasome and oxidative phosphorylation were enriched in high risk MM patients. We found high risk MM patients had lower immune scores and immune infiltration levels. Moreover, further analysis found that MM patients in high risk group were sensitive to bortezomib and lenalidomide. At last, the results of the in vitro experiment showed that ferroptosis inducers (RSL3 and ML162) may synergistically enhance the cytotoxicity of bortezomib and lenalidomide against MM cell line RPMI-8226.ConclusionThis study provides novel insights into roles of ferroptosis in MM prognosis prediction, immune levels and drug sensitivity, which complements and improves current grading systems.

Project description:Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown. Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR). Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro. Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.

Project description:BACKGROUND:The aim was to identify a novel prognostic miRNA signature for colon cancer (CC) in silico. METHODS:Data on the expression of miRNAs and relevant clinical information for 407 patients were obtained from The Cancer Genome Atlas (TCGA), and the samples were randomly split into a validation set (n = 203) and training set (n = 204). The differential expression of miRNAs between normal tissues and patients with CC was analyzed. We detected a miRNA expression signature in the training dataset by using a Cox proportional hazard regression model. Then, we verified the signature in the validation set. Association of the miRNA signature with overall survival was assessed in the validation cohort and combined cohort by log-rank test and based on Kaplan-Meier curves. The receiver operating characteristic and disease-free survival analyses were performed to evaluate the miRNA signature of CC in the combined cohort. Multivariate and univariate Cox analyses related to survival for the miRNA signature were performed, and a nomogram was built as a prognostic model for CC. To explore the function of target genes of the miRNA signature, Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used. RESULTS:Between the matched normal tissues and colon cancer tissues, 267 differentially expressed miRNAs were detected, and a single-factor CoxPH model showed that 13 miRNAs were related to overall survival in the training cohort. Then, a five-miRNA signature was identified using a CoxPH regression model with multiple factors. The five-miRNA signature had significant prognostic value in the training cohort and was validated in the validation cohort and combined cohort. A total of 193 target genes of the miRNA signature were identified. According to the results of functional analysis of the target genes, the signaling pathways MAPK, AMPK and PI3K-Akt, focal adhesion, and microRNAs in cancer were remarkably enriched. CONCLUSION:A five-miRNA signature had increased prognostic value for CC, which may provide important biological insights for the discovery and development of molecular predictors to improve the prognosis of patients with CC.

Project description:BackgroundNecroptosis is an inflammatory cell death mode, and its association with multiple myeloma (MM) remains unclear.MethodsThis prospective study first analyzed the association between necroptosis-related signature as well as prognosis and chemotherapy sensitivity in MM using the necroptosis score. Consensus clustering was used to identify necroptosis-related molecular clusters. Least absolute shrinkage and selection operator analysis and multivariate Cox regression analysis were performed to establish the prognostic model of necroptosis-related genes (NRGs).ResultsA high necroptosis score was associated with poor prognosis and abundant immune infiltration. Two molecular clusters (clusters A and B) significantly differed in terms of prognosis and tumor microenvironment. Cluster B had a worse prognosis and higher tumor marker pathway activity than cluster A. The risk score model based on four NRGs can accurately predict the prognosis of patients with MM, which was validated in two validation cohorts. Receiver operating characteristic curve analysis showed that the area under the curves of the risk score in predicting the 1-, 3-, and 5-year survival rates were 0.710, 0.758, and 0.834, respectively. Further, the activity of pathways related to proliferation and genetic regulation in the high-risk group significantly increased. The drug prediction results showed that the low-risk score group was more sensitive to bortezomib, cytarabine, and doxorubicin than the high-risk score group. Meanwhile, the high-risk score group was more sensitive to lenalidomide and vinblastine than the low-risk score group. Finally, the upregulation of model genes CHMP1A, FAS, JAK3, and HSP90AA1 in clinical samples collected from patients with MM was validated via real-time polymerase chain reaction.ConclusionA systematic analysis of NRGs can help identify potential necroptosis-related mechanisms and provide novel biomarkers for MM prognosis prediction, tumor microenvironment evaluation, and personalized treatment planning.

Dataset Information

A Cancer-Related microRNA Signature Shows Biomarker Utility in Multiple Myeloma.

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A Cancer-Related microRNA Signature Shows Biomarker Utility in Multiple Myeloma.

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