The impact of integrated genomic analysis on molecular classifications and prognostic risk stratification in endometrial cancer: a Chinese experience

TL;DR

This study explores how genomic analysis improves endometrial cancer classification and treatment decisions in Chinese patients.

Contribution

The study provides insights into molecular subtypes and treatment relevance in a Chinese endometrial cancer cohort using large-scale sequencing.

Findings

NSMP was the most common molecular subtype among 200 Chinese endometrial cancer patients.

CTNNB1 mutations were frequent in the POLEmut group but rare in the TP53mut group.

Genomic analysis improved risk stratification and identified genes linked to metastasis and treatment response.

Abstract

The molecular classification of endometrial cancer (EC), as proposed by The Cancer Genome Atlas (TCGA), has transformed tumor classification, but there is a lack of extensive research on the molecular profiles and subtyping of endometrial cancer patients in China.

200 EC patients were classified into the following four molecular types: (i) POLEmut; (ii) MSI-H; (iii) TP53mut; (iv) NSMP. This study aimed to investigate the molecular characteristics of EC patients at a single center by large-scale next generation sequencing(NGS), including clinicopathological features and gene mutations in patients with distinct molecular types, and to assess the relevance of molecular subtyping for postoperative adjuvant therapy.

NSMP group was the most prevalent, comprising 46.0% (92/200) of cases, followed by the TP53mut group at 17.5% (35/200), the MSI-H group at 23.5% (47/200), and the POLEmut group at 13.0% (26/200). CTNNB1 mutations were common in the POLEmut group but rare in the TP53mut group. With the application of the new European Society for Medical Oncology (ESMO) 2022 classification, 27 patients (14.1%) were reclassified. Concordance between the two classifications regarding postoperative risk was observed in 85.9% (165/192) of cases. Seven patients (3.6%) were downstaged, and twenty patients (10.4%) were upgraded. Additionally, the analysis revealed that eleven genes were significantly mutated in patients with lymphovascular space invasion (LVSI) compared to those without LVSI. Notably, NSD3 and POLD1 were highly mutated in patients with lymphatic metastasis compared to those without lymphatic metastasis. Conclusively, large-scale NGS has revolutionized EC management by facilitating rapid molecular subtype identification, guiding tailored adjuvant therapies, targeted treatments, and immunotherapies, and efficiently screening for Lynch syndrome, thereby significantly improving patient outcomes.

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