Clinicopathological correlations in 38 cases of gastroenteropancreatic high-grade neuroendocrine neoplasms.

IF 3.5 3区 医学 Q2 ONCOLOGY Frontiers in Oncology Pub Date : 2024-10-17 eCollection Date: 2024-01-01 DOI:10.3389/fonc.2024.1399079
Na Li, Yanping Hu, Linguo Wu, Jianduo An
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Abstract

Objective: Diagnosis and treatment of gastroenteropancreatic high-grade neuroendocrine neoplasms (GEP-HG-NENs), particularly G3 well-differentiated neuroendocrine tumours (NETs) and poorly differentiated neuroendocrine carcinomas (NECs) relies on histopathological morphology, immunohistochemistry, and molecular biological markers, which are lacking especially in cases with ambiguous histomorphology. In this study to contribute to the development of more targeted treatment strategies, we examined various immunohistochemical and molecular biological markers and their association with clinicopathological features in GEP-HG-NENs.

Methods: We included 38 patients with GEP-HG-NENs in this study, with their retrospective follow-up data. The expression of tumour protein p53 (TP53), RB transcriptional corepressor 1 (RB1), somatostatin receptor 2 (SSTR2), clusterin (CLU), and marker of proliferation Ki-67 (MKI67) was immunohistochemically analysed. KRAS proto-oncogene, GTPase (KRAS) and B-Raf proto-oncogene, serine/threonine kinase (BRAF) V600E expression was evaluated using quantitative real-time polymerase chain reaction (qRT-PCR). The relationships between immunohistochemical and molecular biological markers and clinicopathological characteristics were examined using a Cox risk regression model, receiver operating characteristic (ROC) curve, and Kaplan-Meier survival analyses.

Results: SSTR2, RB, TP53, and CLU expression differed between NET G3 and NECs, with variations among the NET G3 and small- and large-cell NEC (SCNEC and LCNEC, respectively) groups (p < 0.05). The median MKI67 proliferative index was approximately 40% and 70% in G3 NETs and NECs, respectively. The NET G3 group exhibited a median survival of 25 months, indicating a relatively better prognosis than that of the NECs group (median survival, 11 months). Both Kaplan-Meier survival analysis and the Cox risk regression model indicated a statistical correlation among treatment methods, CLU expression, and prognosis (p < 0.05). The BRAF V600E mutation rate was 32.4% in G3 NETs and SCNEC, demonstrating a significant difference between both types (p = 0.0086). Furthermore, ROC curve analysis highlighted the diagnostic significance of the positive expression of the immunohistochemical markers CLU, SSTR2, and RB in identifying NET G3.

Conclusion: To guide more suitable treatment strategies, it is essential to develop and apply valuable and more targeted immunohistochemical and molecular pathological markers for a comprehensive analysis.

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38 例胃肠胰高级别神经内分泌肿瘤的临床病理相关性。
目的:胃肠胰高级别神经内分泌肿瘤(GEP-HG-NENs),尤其是G3分化良好的神经内分泌肿瘤(NETs)和分化不良的神经内分泌癌(NECs)的诊断和治疗依赖于组织病理形态学、免疫组化和分子生物学标记物,而这些标记物尤其在组织形态学不明确的病例中缺乏。为了帮助制定更有针对性的治疗策略,我们研究了 GEP-HG-NENs 的各种免疫组化和分子生物学标记物及其与临床病理特征的关系:本研究纳入了 38 例 GEP-HG-NENs 患者及其回顾性随访数据。对肿瘤蛋白 p53 (TP53)、RB 转录核心抑制因子 1 (RB1)、体生长激素受体 2 (SSTR2)、集束蛋白 (CLU) 和增殖标志物 Ki-67 (MKI67) 的表达进行免疫组化分析。使用定量实时聚合酶链反应(qRT-PCR)评估了 KRAS 原癌基因 GTPase(KRAS)和 B-Raf 原癌基因丝氨酸/苏氨酸激酶(BRAF)V600E 的表达。采用 Cox 风险回归模型、接收器操作特征曲线(ROC)和 Kaplan-Meier 生存分析,研究了免疫组化和分子生物学标志物与临床病理特征之间的关系:结果:SSTR2、RB、TP53和CLU的表达在G3型NET和NEC之间存在差异,G3型NET组与小细胞NEC组和大细胞NEC组(分别为SCNEC组和LCNEC组)之间也存在差异(P 0.05)。G3 NET 和 NEC 的中位 MKI67 增殖指数分别约为 40% 和 70%。G3 NET 组的中位生存期为 25 个月,表明其预后相对优于 NECs 组(中位生存期为 11 个月)。Kaplan-Meier 生存分析和 Cox 风险回归模型均表明,治疗方法、CLU 表达和预后之间存在统计学相关性(P 0.05)。G3 NETs和SCNEC的BRAF V600E突变率为32.4%,两种类型之间存在显著差异(P = 0.0086)。此外,ROC曲线分析强调了免疫组化标记物CLU、SSTR2和RB的阳性表达在鉴别G3型NET中的诊断意义:为了指导更合适的治疗策略,有必要开发和应用更有价值、更有针对性的免疫组化和分子病理学标志物进行综合分析。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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