Biomedical subjects

Zied Abdullaev

Publications and source records attributed to Zied Abdullaev.

3 recordsLinked to original sources

PubMed2026

High-grade astrocytoma with piloid features: a clinical and genomic analysis of prognostic factors using a large cohort.

BACKGROUND: High-grade astrocytoma with piloid features (HGAP) is a recently defined tumor type that is not well-understood. Prognostic factors of clinical outcomes are not well-established. METHODS: Methylation profiling was performed on tumor samples, many at the National Cancer Institute (NCI) Laboratory of Pathology, and others from publicly available sources. Methylation classifier scores of ≥ 0.90 to the HGAP class on the NCI-Bethesda classifier version 3 were included. Clinical features were collected from the medical record. Survival analyses were performed using the Kaplan-Meier and Cox-proportional hazards methods. RESULTS: The cohort comprised 421 patients. There were high rates of ATRX alteration (62%), CDKN2A/B homozygous loss (78%) and MGMT promoter methylation (53%). MAPK alterations were identified in 74% of evaluable samples. The median age was 46 years, and posterior fossa location was predominant (52%). The median overall survival (OS) was 88 months. Older age (p = 0.01) and the presence of an ATRX alteration (p = 0.04) were found to be negative prognostic factors. The presence of cystic features on magnetic resonance imaging (MRI) was found to be favorably prognostic (p = 0.01). Factors that were not significantly associated with prognosis included histologic high-grade features, CDKN2A/B homozygous deletion, MGMT promoter methylation, extent of resection, and presence of NF1 syndrome. CONCLUSIONS: This large cohort establishes relative frequencies of several important markers. Additionally, older age, the presence of an ATRX alteration, and cystic features on MRI were found to be prognostic. Our work may aid in optimizing treatment regimens for patients with this tumor type.

ATRX alteration↗

PubMed2025

DNA Methylation-Based Classification of Kidney Neoplasms.

Renal neoplasms are morphologically and molecularly heterogeneous, with their diagnosis often hindered by interobserver variability and overlapping microscopic features. A subset of cases is unclassifiable despite immunohistochemical, mutation, and cytogenetic-based diagnostic workup. Through examination of the genome-wide DNA methylation signatures of over 2000 renal neoplasms, we identified 23 coherent groups that correlate with known neoplasm types and identified novel clinically relevant subtypes of existing neoplasm types. We used machine learning models to develop and validate a classifier trained on DNA methylation profiles of 1284 samples. The classifier was tested on an external data set of 287 renal neoplasms with >90% concordance between expected neoplasm type and high-score DNA methylation-based classification. Discordance between the original histologic label and methylation class led to potential reclassification of some cases. This work demonstrates proof of principle for the feasibility of a DNA methylation classifier as a clinically useful tool to assist in the diagnosis of renal neoplasms.

Humans↗

PubMed2025

A tumorigenesis threshold for endogenous Myc revealed by dosage-compensation for Myc-haploinsufficiency in the absence of p53.

The MYC proto-oncogene is crucial for neoplasia in most tumors. Overexpressed, oncogenic MYC amplifies the flux through most major processes but does not specify a unique carcinogenic pathway. This "amplifier" model suggests that MYC must exceed an expression threshold to become oncogenic. We designed a genetic test of this model, using the mouse Trp53 null mutant (p53KO) as a highly robust tumor generator to examine the effect of a modest change in the endogenous Myc level (Myc +/-). Strikingly, tumor-free survival is greatly extended in p53KO mice with haploid Myc gene-dosage, yet in the tumors that do develop (mainly hemangiosarcomas and thymic lymphomas), their Myc deficit has been invariably compensated either by increasing Myc genomic dosage (hemangiosarcomas) or expression (lymphomas). Furthermore, acutely halving the endogenous Myc gene-dosage in established tumor allografts curtails growth rates. These results indicate that even an incremental reduction of MYC activity can be salutary in cancer and that one of the major tumor suppressor functions of p53 derives from its ability to prevent MYC overexpression. Myc generates acute DNA damage by several mechanisms and accordingly, p53's anti-Myc function may be inextricably linked to its role in genome integrity surveillance.

Myc haplo-insufficiency↗