Biomedical subjects

Stephen Yip

Publications and source records attributed to Stephen Yip.

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↗

PubMed2026

Molecular characterization of salivary cancers: Patterns of genomic alterations and potential for impact on therapeutic choices.

BACKGROUND: Salivary cancers are rare malignancies with diverse histologies, molecular landscape, and limited effective systemic therapy options. Recent tumour genomics research has identified driver alterations in salivary gland cancers that have led to personalized therapy approaches. The primary objective was to perform molecular characterization using next generation sequencing (NGS) panel and evaluate the potential impact of results on clinical decision-making and treatment outcomes. METHODS: Patients with locally advanced or incurable metastatic salivary cancers suitable for systemic therapy underwent NGS tumour testing with an amplicon-based DNA/RNA NGS panel. Patient demographics, baseline characteristics, treatment and treatment outcomes were retrospectively collected. RESULTS: From 2021 to 2024, 58 advanced salivary cancer patients underwent molecular characterization of their tumour. Baseline characteristics at diagnosis: male 60%, median age 67, most common histologies; adenoid cystic 27%, salivary duct 19% and mucoepidermoid 12%. PIK3CA alterations were the most common molecular finding across all subtypes 22% (13/58) and were enriched in salivary duct carcinoma 73% (8/11). Other alterations identified were: ERBB2 (4), EGFR (2), HRAS (3), NTRK3 (2), BRAF p.V600E (1), and RET (1). Immunohistochemistry identified androgen receptor positivity across salivary cancer subtypes in 8/19 and HER2 positivity in 2/20 tested. Twenty-two patients received systemic therapy prior to NGS results for incurable/metastatic disease, first line treatments included 69% chemotherapy, 18% anti-androgen, 9% lenvatinib, 4% trial. CONCLUSION: Molecular characterization of salivary cancers identified targetable alterations in 37% of patients. The identification of potential therapeutic targets offers the opportunity for expanded treatment options to benefit salivary gland cancer patients.

Metastatic salivary gland cancer↗

PubMed2025

Cross-Platform Methylation-Based Site of Origin Classification for Squamous Cell Carcinomas.

Squamous cell carcinomas (SCCs) are one of the most common cancer types and can arise at nearly any anatomic site. Because SCCs are one of the most common metastases, do not have reliable site-specific morphologic or genomic features, and have considerable morphologic and immunohistochemical overlap with urothelial carcinomas, distinguishing between primary and metastatic squamous-appearing tumors can be challenging. This distinction can be critical to clinical management. We present Squamous cell carcinoma Methylation for Origin Site (SquaMOS), a methylation-based classifier to predict site of origin of squamous-appearing carcinomas. Trained on publicly available array-based methylation data from 1062 primary SCCs (from lung, head and neck, cervix, and esophagus) and urothelial carcinomas, SquaMOS predicted site of origin in primary tumors with 96.1% accuracy in an internal test set (n = 458) and 97.4% accuracy in an external test set from 3 institutions (n = 78). On metastatic tumors (n = 51), SquaMOS predictions were 96.1% accurate. SquaMOS was directly applicable to shallow Nanopore sequencing data (CpG probe site coverage, 0.25-2.88×) with an accuracy of 91.7% (n = 36; 100% accurate for high-confidence predictions). When tested on SCCs outside the training set types (n = 15, including 3 metastases to lung), no cases were misclassified as of lung origin, supporting accuracy of lung vs nonlung origin classification for diverse SCC types. Overall, we demonstrate highly accurate performance of the SquaMOS classifier on primary and metastatic tumors from multiple data sources, robust to suboptimal tumor purity. We illustrate transferability of our array-based classifier to low-depth Nanopore sequencing data, a potentially rapid means of site of origin determination in a clinical setting.

Humans↗