Faculty Opinions recommendation of TP53 mutations in low-risk myelodysplastic syndromes with del(5q) predict disease progression.

2011 ◽  
Author(s):  
Michael Williams
Keyword(s):  
Disease Progression ◽  
Myelodysplastic Syndromes ◽  
Low Risk ◽  
Tp53 Mutations ◽  
Predict Disease Progression

TP53 Mutations in Low-Risk Myelodysplastic Syndromes With del(5q) Predict Disease Progression

2011 ◽  
Vol 29 (15) ◽  
pp. 1971-1979 ◽  
Author(s):  
Martin Jädersten ◽  
Leonie Saft ◽  
Alexander Smith ◽  
Austin Kulasekararaj ◽  
Sabine Pomplun ◽  
...  
Keyword(s):  
Disease Progression ◽  
Myelodysplastic Syndromes ◽  
Clinical Decision Making ◽  
P53 Protein ◽  
Low Risk ◽  
Disease Stage ◽  
International Prognostic Scoring System ◽  
P53 Overexpression ◽  
Tp53 Mutations ◽  
Increased Risk

Purpose To determine the frequency of TP53 mutations and the level of p53 protein expression by immunohistochemistry (IHC) in low-risk myelodysplastic syndromes (MDS) with del(5q) and to assess their impact on disease progression. Patients and Methods Pre- and postprogression bone marrow (BM) samples from 55 consecutive patients with International Prognostic Scoring System low risk (n = 32) or intermediate-1 risk (n = 23) were studied by next-generation sequencing of TP53. IHC for p53 was performed on 148 sequential BM samples. Results TP53 mutations with a median clone size of 11% (range, 1% to 54%) were detected in 10 patients (18%) already at an early phase of the disease. Mutations were equally common in low-risk and intermediate-1–risk patients and were associated with evolution to acute myeloid leukemia (5 of 10 v 7 of 45; P = .045). Nine of 10 patients carrying mutations showed more than 2% BM progenitors with strong p53 staining. The probability of a complete cytogenetic response to lenalidomide was lower in mutated patients (0 of 7 v 12 of 24; P = .024). Conclusion By using sensitive deep-sequencing technology, we demonstrated that TP53 mutated populations may occur at an early disease stage in almost a fifth of low-risk MDS patients with del(5q). Importantly, mutations were present years before disease progression and were associated with an increased risk of leukemic evolution. TP53 mutations could not be predicted by common clinical features but were associated with p53 overexpression. Our findings indicate a previously unrecognized heterogeneity of the disease which may significantly affect clinical decision making.

scholarly journals TP53 mutation and MET amplification in circulating tumor DNA analysis predict disease progression in patients with advanced gastric cancer

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11146
Author(s):  
Jia Li ◽  
Zhaoyan Li ◽  
Yajie Ding ◽  
Yan Xu ◽  
Xiaohong Zhu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Disease Progression ◽  
Tp53 Mutation ◽  
Circulating Tumor Dna ◽  
Tp53 Mutations ◽  
Kaplan Meier ◽  
Met Amplification ◽  
Mutant Genes ◽  
Tumor Dna ◽  
Predict Disease Progression

Background Gastric cancer (GC) is a heterogeneous disease that encompasses various molecular subtypes. The molecular mutation characteristics of circulating tumor DNA (ctDNA) in advanced gastric cancer (AGC), especially the clinical utility of TP53 mutation and MET amplification in ctDNA need to be further explored. Objectives The aim of this study was mainly to assess the clinical utility of TP53 mutation and MET amplification in ctDNA as biomarkers for monitoring disease progression of AGC. Patients and Methods We used multigene NGS-panel technology to study the characteristics of ctDNA gene mutations and screen the key mutant genes in AGC patients. The Kaplan-Meier method was used to calculate the survival probability and log-rank test was used to compare the survival curves of TP53 mutation and MET amplification in ctDNA of AGC patients. The survival time was set from the blood test time to the follow-up time to observe the relationship between the monitoring index and tumor prognosis. Results We performed mutation detection on ctDNA in 23 patients with AGC and identified the top 20 mutant genes. The five most frequently mutated genes were TP53 (55%), EGFR (20%), ERBB2 (20%), MET (15%) and APC (10%). TP53 was the most common mutated gene (55%) and MET had a higher frequency of mutations (15%) in our study. Kaplan-Meier analysis showed that patients with TP53 mutant in ctDNA had shorter overall survival (OS) than these with TP53 wild (P < 0.001). The Allele frequency (AF) of TP53 mutations in patient number 1 was higher in the second time (0.94%) than in the first time (0.36%); the AF of TP53 mutations in patient number 16 was from scratch (0∼0.26%). In addition, the AF of TP53 mutations in patients who survive was relatively low (P = 0.047). Simultaneously, Kaplan-Meier analysis showed that patients with MET amplification also had shorter OS than these with MET without amplification (P < 0.001). Conclusion TP53 and MET are the two common frequently mutant genes in ctDNA of AGC patients.TP53 mutation and MET amplification in ctDNA could predict disease progression of AGC patients.

scholarly journals New risk model is able to identify patients with a low risk of progression in systemic sclerosis

RMD Open ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e001524
Author(s):  
Nina Marijn van Leeuwen ◽  
Marc Maurits ◽  
Sophie Liem ◽  
Jacopo Ciaffi ◽  
Nina Ajmone Marsan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Systemic Sclerosis ◽  
High Risk ◽  
Disease Progression ◽  
Risk Model ◽  
Immunosuppressive Drugs ◽  
Low Risk ◽  
Expert Assessment ◽  
Risk Of Progression

ObjectivesTo develop a prediction model to guide annual assessment of systemic sclerosis (SSc) patients tailored in accordance to disease activity.MethodsA machine learning approach was used to develop a model that can identify patients without disease progression. SSc patients included in the prospective Leiden SSc cohort and fulfilling the ACR/EULAR 2013 criteria were included. Disease progression was defined as progression in ≥1 organ system, and/or start of immunosuppression or death. Using elastic-net-regularisation, and including 90 independent clinical variables (100% complete), we trained the model on 75% and validated it on 25% of the patients, optimising on negative predictive value (NPV) to minimise the likelihood of missing progression. Probability cutoffs were identified for low and high risk for disease progression by expert assessment.ResultsOf the 492 SSc patients (follow-up range: 2–10 years), disease progression during follow-up was observed in 52% (median time 4.9 years). Performance of the model in the test set showed an AUC-ROC of 0.66. Probability score cutoffs were defined: low risk for disease progression (<0.197, NPV:1.0; 29% of patients), intermediate risk (0.197–0.223, NPV:0.82; 27%) and high risk (>0.223, NPV:0.78; 44%). The relevant variables for the model were: previous use of cyclophosphamide or corticosteroids, start with immunosuppressive drugs, previous gastrointestinal progression, previous cardiovascular event, pulmonary arterial hypertension, modified Rodnan Skin Score, creatine kinase and diffusing capacity for carbon monoxide.ConclusionOur machine-learning-assisted model for progression enabled us to classify 29% of SSc patients as ‘low risk’. In this group, annual assessment programmes could be less extensive than indicated by international guidelines.

scholarly journals Combination of Immune and Viral Factors Distinguishes Low-Risk versus High-Risk HIV-1 Disease Progression in HLA-B*5701 Subjects

2012 ◽  
Vol 86 (18) ◽  
pp. 9802-9816 ◽  
Author(s):  
Melissa M. Norström ◽  
Marcus Buggert ◽  
Johanna Tauriainen ◽  
Wendy Hartogensis ◽  
Mattia C. Prosperi ◽  
...  
Keyword(s):  
T Cell ◽  
High Risk ◽  
High Resolution ◽  
Disease Progression ◽  
T Cell Responses ◽  
Low Risk ◽  
Early Infection ◽  
Cell Responses ◽  
Cell Counts ◽  
Hiv 1

HLA-B*5701 is the host factor most strongly associated with slow HIV-1 disease progression, although rates can vary within this group. Underlying mechanisms are not fully understood but likely involve both immunological and virological dynamics. The present study investigated HIV-1in vivoevolution and epitope-specific CD8+T cell responses in six HLA-B*5701 patients who had not received antiretroviral treatment, monitored from early infection for up to 7 years. The subjects were classified as high-risk progressors (HRPs) or low-risk progressors (LRPs) based on baseline CD4+T cell counts. Dynamics of HIV-1 Gag p24 evolution and multifunctional CD8+T cell responses were evaluated by high-resolution phylogenetic analysis and polychromatic flow cytometry, respectively. In all subjects, substitutions occurred more frequently in flanking regions than in HLA-B*5701-restricted epitopes. In LRPs, p24 sequence diversity was significantly lower; sequences exhibited a higher degree of homoplasy and more constrained mutational patterns than HRPs. The HIV-1 intrahost evolutionary rate was also lower in LRPs and followed a strict molecular clock, suggesting neutral genetic drift rather than positive selection. Additionally, polyfunctional CD8+T cell responses, particularly to TW10 and QW9 epitopes, were more robust in LRPs, who also showed significantly higher interleukin-2 (IL-2) production in early infection. Overall, the findings indicate that HLA-B*5701 patients with higher CD4 counts at baseline have a lower risk of HIV-1 disease progression because of the interplay between specific HLA-linked immune responses and the rate and mode of viral evolution. The study highlights the power of a multidisciplinary approach, integrating high-resolution evolutionary and immunological data, to understand mechanisms underlying HIV-1 pathogenesis.

scholarly journals The Genetics of Myelodysplastic Syndromes: Clinical Relevance

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1144
Author(s):  
Chiara Chiereghin ◽  
Erica Travaglino ◽  
Matteo Zampini ◽  
Elena Saba ◽  
Claudia Saitta ◽  
...  
Keyword(s):  
Disease Progression ◽  
Myelodysplastic Syndromes ◽  
Clinical Relevance ◽  
Driver Mutations ◽  
Significant Information ◽  
Hematopoietic Stem ◽  
Probability Of Survival ◽  
Mutational Status ◽  
Increased Risk ◽  
Risk Of Disease

Myelodysplastic syndromes (MDS) are a clonal disease arising from hematopoietic stem cells, that are characterized by ineffective hematopoiesis (leading to peripheral blood cytopenia) and by an increased risk of evolution into acute myeloid leukemia. MDS are driven by a complex combination of genetic mutations that results in heterogeneous clinical phenotype and outcome. Genetic studies have enabled the identification of a set of recurrently mutated genes which are central to the pathogenesis of MDS and can be organized into a limited number of cellular pathways, including RNA splicing (SF3B1, SRSF2, ZRSR2, U2AF1 genes), DNA methylation (TET2, DNMT3A, IDH1/2), transcription regulation (RUNX1), signal transduction (CBL, RAS), DNA repair (TP53), chromatin modification (ASXL1, EZH2), and cohesin complex (STAG2). Few genes are consistently mutated in >10% of patients, whereas a long tail of 40–50 genes are mutated in <5% of cases. At diagnosis, the majority of MDS patients have 2–4 driver mutations and hundreds of background mutations. Reliable genotype/phenotype relationships were described in MDS: SF3B1 mutations are associated with the presence of ring sideroblasts and more recent studies indicate that other splicing mutations (SRSF2, U2AF1) may identify distinct disease categories with specific hematological features. Moreover, gene mutations have been shown to influence the probability of survival and risk of disease progression and mutational status may add significant information to currently available prognostic tools. For instance, SF3B1 mutations are predictors of favourable prognosis, while driver mutations of other genes (such as ASXL1, SRSF2, RUNX1, TP53) are associated with a reduced probability of survival and increased risk of disease progression. In this article, we review the most recent advances in our understanding of the genetic basis of myelodysplastic syndromes and discuss its clinical relevance.

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