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Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis.

ABSTRACT: Myelofibrosis (MF) belongs to the family of classic Philadelphia-negative myeloproliferative neoplasms (MPNs). It can be primary myelofibrosis (PMF) or secondary myelofibrosis (SMF) evolving from polycythemia vera (PV) or essential thrombocythemia (ET). Despite the differences, PMF and SMF patients are currently managed in the same way, and prediction of survival is based on the same clinical and genetic features. In the last few years, interest has grown concerning the ability of gene expression profiles (GEPs) to provide valuable prognostic information. Here, we studied the GEPs of granulocytes from 114 patients with MF, using a microarray platform to identify correlations with patient characteristics and outcomes. Cox regression analysis led to the identification of 201 survival-related transcripts characterizing patients who are at high risk for death. High-risk patients identified by this gene signature displayed an inferior overall survival and leukemia-free survival, together with clinical and molecular detrimental features included in contemporary prognostic models, such as the presence of high molecular risk mutations. The high-risk group was enriched in post-PV and post-ET MF and JAK2V617F homozygous patients, whereas pre-PMF was more frequent in the low-risk group. These results demonstrate that GEPs in MF patients correlate with their molecular and clinical features, particularly their survival, and represent the proof of concept that GEPs might provide complementary prognostic information to be applied in clinical decision making.

SUBMITTER: Rontauroli S

PROVIDER: S-EPMC7948267 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

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Gene expression profile correlates with molecular and clinical features in patients with myelofibrosis.

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