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Expression of p53 protein isoforms predicts survival in patients with multiple myeloma.

ABSTRACT: Loss and/or mutation of the TP53 gene are associated with short survival in multiple myeloma, but the p53 landscape goes far beyond. At least 12 p53 protein isoforms have been identified as a result of a combination of alternative splicing, alternative promoters and/or alternative transcription site starts, which are grouped as α, β, γ, from transactivation domain (TA), long, and short isoforms. Nowadays, there are no studies evaluating the expression of p53 isoforms and its clinical relevance in multiple myeloma (MM). We used capillary nanoimmunoassay to quantify the expression of p53 protein isoforms in CD138-purified samples from 156 patients with newly diagnosed MM who were treated as part of the PETHEMA/GEM2012 clinical trial and investigated their prognostic impact. Quantitative real-time polymerase chain reaction was used to corroborate the results at RNA levels. Low and high levels of expression of short and TAp53β/γ isoforms, respectively, were associated with adverse prognosis in MM patients. Multivariate Cox models identified high levels of TAp53β/γ (hazard ratio [HR], 4.49; p < .001) and high-risk cytogenetics (HR, 2.69; p < .001) as independent prognostic factors associated with shorter time to progression. The current cytogenetic-risk classification was notably improved when expression levels of p53 protein isoforms were incorporated, whereby high-risk MM expressing high levels of short isoforms had significantly longer survival than high-risk patients with low levels of these isoforms. This is the first study that demonstrates the prognostic value of p53 isoforms in MM patients, providing new insights on the role of p53 protein dysregulation in MM biology.

SUBMITTER: Rojas EA

PROVIDER: S-EPMC9313569 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Expression of p53 protein isoforms predicts survival in patients with multiple myeloma.

Rojas Elizabeta A EA Corchete Luis A LA De Ramón Cristina C Krzeminski Patryk P Quwaider Dalia D García-Sanz Ramón R Martínez-López Joaquín J Oriol Albert A Rosiñol Laura L Bladé Joan J Lahuerta Juan José JJ San Miguel Jesús F JF González Marcos M Mateos María Victoria MV Bourdon Jean-Christophe JC Misiewicz-Krzeminska Irena I Gutiérrez Norma C NC

American journal of hematology 20220301 6

Loss and/or mutation of the TP53 gene are associated with short survival in multiple myeloma, but the p53 landscape goes far beyond. At least 12 p53 protein isoforms have been identified as a result of a combination of alternative splicing, alternative promoters and/or alternative transcription site starts, which are grouped as α, β, γ, from transactivation domain (TA), long, and short isoforms. Nowadays, there are no studies evaluating the expression of p53 isoforms and its clinical relevance i ...[more]

PMID: 35188691

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Project description:BackgroundMultiple myeloma (MM) is the second most common refractory hematologic cancer. Searching for new targets and prognostic markers for MM is significant.MethodsGSE39754, GSE6477 and GSE24080 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in MM versus healthy people from GSE39754 and GSE6477 were screened using limma package, and MM-related module genes were chosen with the use of Weighted gene co-expression network analysis (WGCNA), and the two were intersected using ggVennDiagram for obtaining MM-related DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out. Then, protein-protein interactions (PPI) analysis in String database was used to obtain hub genes, while prognosis was analyzed by survival package in GSE24080. Receiver operating characteristic (ROC) curve was adopted for evaluating diagnostic value of hub genes. Besides, univariable/multivariable Cox regression were employed to screen independent prognostic biomarkers. Gene set enrichment analysis (GSEA) was used to find possible mechanism. Finally, western-blotting and reverse transcription-polymerase chain reaction (RT-PCR) verify TYROBP expression within MM and healthy people. We performed cell adhesion and transwell assays for investigating TYROBP function in MM cell adhesion and migration.ResultsThrough differential analyses, 92 MM-related DEGs were obtained. 10 hub genes were identified by PPI and CytoHubba. Their diagnostic and prognostic significance was analyzed. Down-regulation of genes like TYROBP, ELANE, MNDA, and MPO related to dismal MM prognosis. Upon univariable/multivariable Cox regression, TYROBP independently predicted MM prognosis. GSEA pathway was enriched, indicating that TYROBP expression affected MM development via cell adhesion molecular pathway. Upon Western-blotting and RT-PCR assays, TYROBP expression among MM patients decreased relative to healthy donors. Cell adhesion and transwell migration assays revealed increased MM cell adhesion and decreased migration upon TYROBP up-regulation.ConclusionIn summary, TYROBP is a potential prognostic marker for MM.

Project description:BackgroundMultiple myeloma (MM) is a clonal plasma cell disorder which still lacks sufficient prognostic factors. The serine/arginine-rich splicing factor (SRSF) family serves as an important splicing regulator in organ development. Among all members, SRSF1 plays an important role in cell proliferation and renewal. However, the role of SRSF1 in MM is still unknown.MethodsSRSF1 was selected from the primary bioinformatics analysis of SRSF family members, and then we integrated 11 independent datasets and analyzed the relationship between SRSF1 expression and MM clinical characteristics. Gene set enrichment analysis (GSEA) was conducted to explore the potential mechanism of SRSF1 in MM progression. ImmuCellAI was used to estimate the abundance of immune infiltrating cells between the SRSF1high and SRSF1low groups. The ESTIMATE algorithm was used to evaluate the tumor microenvironment in MM. The expression of immune-related genes was compared between the groups. Additionally, SRSF1 expression was validated in clinical samples. SRSF1 knockdown was conducted to explore the role of SRSF1 in MM development.ResultsSRSF1 expression showed an increasing trend with the progression of myeloma. Besides, SRSF1 expression increased as the age, ISS stage, 1q21 amplification level, and relapse times increased. MM patients with higher SRSF1 expression had worse clinical features and poorer outcomes. Univariate and multivariate analysis indicated that upregulated SRSF1 expression was an independent poor prognostic factor for MM. Enrichment pathway analysis confirmed that SRSF1 takes part in the myeloma progression via tumor-associated and immune-related pathways. Several checkpoints and immune-activating genes were significantly downregulated in the SRSF1high groups. Furthermore, we detected that SRSF1 expression was significantly higher in MM patients than that in control donors. SRSF1 knockdown resulted in proliferation arrest in MM cell lines.ConclusionThe expression value of SRSF1 is positively associated with myeloma progression, and high SRSF1 expression might be a poor prognostic biomarker in MM patients.

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Expression of p53 protein isoforms predicts survival in patients with multiple myeloma.

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Expression of p53 protein isoforms predicts survival in patients with multiple myeloma.

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