scholarly journals Molecular Classification and Therapeutic Targets in Ependymoma

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6218
Author(s):  
Thomas Larrew ◽  
Brian Saway ◽  
Stephen Lowe ◽  
Adriana Olar

Ependymoma is a biologically diverse tumor wherein molecular classification has superseded traditional histological grading based on its superior ability to characterize behavior, prognosis, and possible targeted therapies. The current, updated molecular classification of ependymoma consists of ten distinct subgroups spread evenly among the spinal, infratentorial, and supratentorial compartments, each with its own distinct clinical and molecular characteristics. In this review, the history, histopathology, standard of care, prognosis, oncogenic drivers, and hypothesized molecular targets for all subgroups of ependymoma are explored. This review emphasizes that despite the varied behavior of the ependymoma subgroups, it remains clear that research must be performed to further elucidate molecular targets for these tumors. Although not all ependymoma subgroups are oncologically aggressive, development of targeted therapies is essential, particularly for cases where surgical resection is not an option without causing significant morbidity. The development of molecular therapies must rely on building upon our current understanding of ependymoma oncogenesis, as well as cultivating transfer of knowledge based on malignancies with similar genomic alterations.

2018 ◽  
Vol 31 (05) ◽  
pp. 295-300 ◽  
Author(s):  
Katherine Kelley ◽  
Raphael Byrne ◽  
Kim Lu

AbstractGastrointestinal stromal tumors (GISTs) are rare in occurrence, but comprise the most common mesenchymal tumors of the gastrointestinal tract and affect between 15 and 20 individuals per million per year. Due to recent advancements in molecular classification of these tumors, medical therapy has provided improved outcomes to a historically surgically managed disease. This review article briefly discusses the molecular characteristics, medical and surgical therapies, and future of GIST management.


Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 274-274
Author(s):  
Georgina L Ryland ◽  
Ashish Bajel ◽  
Michael Dickinson ◽  
Paul G Ekert ◽  
Oliver Hofmann ◽  
...  

Abstract Genomic markers define molecular subtypes and measurable residual disease (MRD) targets in B-cell acute lymphoblastic leukemia/lymphoma (B-ALL) and are essential determinants of treatment. Current diagnostic approaches typically involve serial multi-step testing utilizing conventional cytogenetics (CC)/FISH and molecular genetic (RT-qPCR, MLPA, clonality PCR, NGS panel) techniques which are time and sample consuming and ultimately may not adequately identify genomically complex B-ALL subtypes. In contrast, single-step comprehensive genomic profiling by whole genome and whole transcriptome sequencing (WGS/WTS) may be more efficient for the molecular classification of established and newly described entities which are of increasing therapeutic relevance. We have instituted a multimodal platform for molecular testing in B-ALL performing WGS/WTS in parallel with deep NGS-based immunoglobulin (IG) rearrangement MRD and exploratory DNA-breakpoint based MRD assays. We aimed to determine the utility of this approach for subtype classification compared to a standard-of-care diagnostic approach of CC/FISH testing. Forty-two consecutive adult patients underwent both standard-of-care diagnostic testing and WGS/WTS. 20/42 (48%) patients had an abnormal CC/FISH result supporting classification into recognized molecular subgroups. WGS/WTS assessment incorporating somatic coding and non-coding mutations, structural variants, fusions, copy number abnormalities and gene expression subtype prediction (ALLSorts, https://github.com/Oshlack/ALLSorts) was performed with concordant results in all 20 patients. 16/22 patients that were unclassified by CC/FISH were successfully reclassified by WGS/WTS including subtypes enriched for cryptic rearrangements (Ph-like, DUX4, MEF2D) and groups characterized by heterogeneous genomic alterations or a distinctive gene expression signature (PAX5alt, ZEB2/CEBP). A low hypodiploid karyotype was observed in two cases with an apparently normal karyotype by CC. The six patients who remained without a subtype defining driver genetic alteration after comprehensive testing frequently harbored novel IGH translocations or a Ph-like expression signature but without a described fusion. In order to understand the relative contribution from WGS versus WTS, analysis of 36 patients was performed using a truth classification. WGS and WTS produced equivalent classifications for 22 cases. Two cases were based solely on WGS findings (iAMP21 and ZEB2/CEBP) and three cases were based solely on WTS findings (DUX4). Importantly the combination of both WGS and WTS was critical to correctly classify nine cases (Ph-like and PAX5alt). MRD was assessed by a sensitive NGS assay to IG rearrangements (Adaptive Biotechnologies) and by quantitative probe-based droplet digital PCR (ddPCR) assays designed to structural rearrangement DNA breakpoints from genome data (analytical sensitivity 10 -4). Patient-specific ddPCR assays were designed to eight structural variants (KMT2A and IGH translocations, and IKZF1 deletions) in seven patients and assessed in 36 remission samples with parallel testing by multiparametric flow cytometry (MFC). Concordant MFC and ddPCR was observed in 30/36 samples (19 MRD pos, 11 MRD neg). Discordances included two MRD pos by MFC-only and four MRD pos by ddPCR-only; the latter often occurring in the setting of antigen directed therapy or in ALL with a less informative immunophenotype, demonstrating the additional utility of non-MFC based MRD assessment in specific clinical settings. 27/42 patients in our cohort had ≥1 genomic structural rearrangement identified by WGS that could be used for patient-specific MRD monitoring to complement existing MRD assessment. In conclusion WGS/WTS provided a molecular subtype classification in 86% of our cohort compared to 48% by standard-of-care diagnostic testing highlighting that CC/FISH alone is inadequate for contemporary molecular classification of B-ALL, which may have implications for treatment decisions. Importantly, the combination of WGS and WTS was superior to WGS-only or WTS-only for correct molecular subtype assignment. This approach has the potential to improve risk assessment in adult B-ALL and the routine feasibility, improvement in clinical outcomes and health economic impact warrant further assessment. Disclosures Bajel: Abbvie, Amgen, Novartis, Pfizer: Honoraria; Amgen: Speakers Bureau. Dickinson: Janssen: Consultancy, Honoraria; Amgen: Honoraria; Celgene: Research Funding; Gilead Sciences: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Other: travel, accommodation, expenses, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Tiong: Servier: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Pfizer: Consultancy.


Author(s):  
Zhongyang Lv ◽  
Yannick Xiaofan Yang ◽  
Jiawei Li ◽  
Yuxiang Fei ◽  
Hu Guo ◽  
...  

Knee osteoarthritis (KOA) is the most common form of joint degeneration with increasing prevalence and incidence in recent decades. KOA is a molecular disorder characterized by the interplay of numerous molecules, a considerable number of which can be detected in body fluids, including synovial fluid, urine, and blood. However, the current diagnosis and treatment of KOA mainly rely on clinical and imaging manifestations, neglecting its molecular pathophysiology. The mismatch between participants’ molecular characteristics and drug therapeutic mechanisms might explain the failure of some disease-modifying drugs in clinical trials. Hence, according to the temporal alteration of representative molecules, we propose a novel molecular classification of KOA divided into pre-KOA, early KOA, progressive KOA, and end-stage KOA. Then, progressive KOA is furtherly divided into four subtypes as cartilage degradation-driven, bone remodeling-driven, inflammation-driven, and pain-driven subtype, based on the major pathophysiology in patient clusters. Multiple clinical findings of representatively investigated molecules in recent years will be reviewed and categorized. This molecular classification allows for the prediction of high-risk KOA individuals, the diagnosis of early KOA patients, the assessment of therapeutic efficacy, and in particular, the selection of homogenous patients who may benefit most from the appropriate therapeutic agents.


Author(s):  
Antonio Pico ◽  
Laura Sanchez-Tejada ◽  
Ruth Sanchez-Ortiga ◽  
Rosa Camara ◽  
Cristina Lamas ◽  
...  

2020 ◽  
Vol 14 ◽  
Author(s):  
Abhishek Kumar ◽  
Neeraj Masand ◽  
Vaishali M. Patil

Abstract: Breast cancer is the most common and highly heterogeneous neoplastic disease comprised of several subtypes with distinct molecular etiology and clinical behaviours. The mortality observed over the past few decades and the failure in eradicating the disease is due to the lack of specific etiology, molecular mechanisms involved in initiation and progression of breast cancer. Understanding of the molecular classes of breast cancer may also lead to new biological insights and eventually to better therapies. The promising therapeutic targets and novel anti-cancer approaches emerging from these molecular targets that could be applied clinically in the near future are being highlighted. In addition, this review discusses some of the details of current molecular classification and available chemotherapeutics


Author(s):  
Rodrigo Madurga ◽  
Noemí García-Romero ◽  
Beatriz Jiménez ◽  
Ana Collazo ◽  
Francisco Pérez-Rodríguez ◽  
...  

Abstract Molecular classification of glioblastoma has enabled a deeper understanding of the disease. The four-subtype model (including Proneural, Classical, Mesenchymal and Neural) has been replaced by a model that discards the Neural subtype, found to be associated with samples with a high content of normal tissue. These samples can be misclassified preventing biological and clinical insights into the different tumor subtypes from coming to light. In this work, we present a model that tackles both the molecular classification of samples and discrimination of those with a high content of normal cells. We performed a transcriptomic in silico analysis on glioblastoma (GBM) samples (n = 810) and tested different criteria to optimize the number of genes needed for molecular classification. We used gene expression of normal brain samples (n = 555) to design an additional gene signature to detect samples with a high normal tissue content. Microdissection samples of different structures within GBM (n = 122) have been used to validate the final model. Finally, the model was tested in a cohort of 43 patients and confirmed by histology. Based on the expression of 20 genes, our model is able to discriminate samples with a high content of normal tissue and to classify the remaining ones. We have shown that taking into consideration normal cells can prevent errors in the classification and the subsequent misinterpretation of the results. Moreover, considering only samples with a low content of normal cells, we found an association between the complexity of the samples and survival for the three molecular subtypes.


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