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肿瘤浸润淋巴细胞是与高级别浆液性卵巢癌致病变异相关的病理特征的关键决定因素。

Tumor-infiltrating lymphocytes are the key determinants of pathological features associated with pathogenic variants in high-grade serous ovarian carcinoma.

作者信息

Nguyen-Phan Dang H, Dang Tin, Dang Anh N, Huynh Loc T H, Nguyen Phuong T B, Tran Vu Q, Ngo Hanh T T, Doan Thao T P, Thai Tu A, Chen Chien-Chin

机构信息

Department of Pathology and Forensic Medicine, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam.

Department of Pathology, Ho Chi Minh City Oncology Hospital, Ho Chi Minh City, Vietnam.

出版信息

Front Med (Lausanne). 2025 Jun 3;12:1555883. doi: 10.3389/fmed.2025.1555883. eCollection 2025.

Abstract

BACKGROUND

High-grade serous ovarian carcinoma (HGSOC), an aggressive cancer associated with pathogenic variants, causes genomic instability and sensitivity to poly (ADP-ribose) polymerase inhibitors. Identifying pathogenic variants is crucial for the treatment of HGSOC; however, genetic testing is expensive and time-consuming. This study aimed to explore pathological features, particularly the presence of tumor-infiltrating lymphocytes (TILs), as potential surrogates to streamline patient selection for genetic testing.

METHODS

We retrospectively analyzed 58 cases of HGSOC with known variant profiles. Tumors were categorized as TIL-positive or TIL-negative based on the presence of > 40 or ≤ 40 intraepithelial lymphocytes in a single high-power field (HPF), respectively. Key pathological features, including solid, endometrioid, and transitional (SET) architecture patterns; necrosis; and mitotic activity, were evaluated within these subgroups. Statistical analyses were used to determine the associations between these features and variant status.

RESULTS

In TIL-negative HGSOCs, SET patterns were strongly associated with pathogenic or likely pathogenic variants ( = 0.028), emerging as the most reliable morphological marker in this group. In TIL-positive HGSOCs, low mitotic activity (≤7 mitotic figure per 10 HPFs) was significantly correlated with pathogenic variants ( = 0.0002), underscoring its diagnostic significance. Necrosis and mitotic activity in TIL-negative cases and SET patterns in TIL-positive cases were not significantly associated with pathogenic variants. Combined analysis of both TIL subgroups diluted these associations, underscoring the significance of stratifying cases by the immune context.

DISCUSSION

The presence of TILs affects the diagnostic value of pathological features for variant status in HGSOC. Regarding pathogenic variants, SET patterns and low mitotic activity were identified as critical markers in TIL-negative tumors and TIL-positive tumors, respectively. These associations likely stem from interactions among genomic instability, immune response, and tumor growth. Our framework leverages these insights to prioritize high-risk cases for genetic testing, thereby optimizing resource allocation.

CONCLUSION

The presence of TILs is critical for understanding the association between pathological features and pathogenic variants in HGSOC. To improve pathogenic variant prediction, optimize genetic testing, and guide tailored intervention, our framework integrates immune context and morphological markers. This approach is especially useful in resource-limited settings and can enhance diagnostic efficiency and clinical decision-making.

摘要

背景

高级别浆液性卵巢癌(HGSOC)是一种与致病变异相关的侵袭性癌症,会导致基因组不稳定以及对聚(ADP - 核糖)聚合酶抑制剂敏感。识别致病变异对于HGSOC的治疗至关重要;然而,基因检测既昂贵又耗时。本研究旨在探索病理特征,特别是肿瘤浸润淋巴细胞(TILs)的存在,作为简化基因检测患者选择的潜在替代指标。

方法

我们回顾性分析了58例已知变异谱的HGSOC病例。根据单个高倍视野(HPF)中上皮内淋巴细胞数量>40或≤40,将肿瘤分别分类为TIL阳性或TIL阴性。在这些亚组中评估关键病理特征,包括实性、子宫内膜样和移行性(SET)结构模式、坏死和有丝分裂活性。采用统计分析来确定这些特征与变异状态之间的关联。

结果

在TIL阴性的HGSOC中,SET模式与致病或可能致病的变异密切相关(P = 0.028),成为该组中最可靠的形态学标志物。在TIL阳性的HGSOC中,低有丝分裂活性(每10个HPF中≤7个有丝分裂象)与致病变异显著相关(P = 0.0002),突出了其诊断意义。TIL阴性病例中的坏死和有丝分裂活性以及TIL阳性病例中的SET模式与致病变异无显著关联。对两个TIL亚组的联合分析淡化了这些关联,强调了按免疫背景对病例进行分层的重要性。

讨论

TILs的存在影响了HGSOC中病理特征对变异状态的诊断价值。关于致病变异,SET模式和低有丝分裂活性分别被确定为TIL阴性肿瘤和TIL阳性肿瘤中的关键标志物。这些关联可能源于基因组不稳定、免疫反应和肿瘤生长之间的相互作用。我们的框架利用这些见解对基因检测的高风险病例进行优先排序,从而优化资源分配。

结论

TILs的存在对于理解HGSOC中病理特征与致病变异之间的关联至关重要。为了改善致病变异预测、优化基因检测并指导个性化干预,我们的框架整合了免疫背景和形态学标志物。这种方法在资源有限的环境中特别有用,并且可以提高诊断效率和临床决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d290/12172505/f237f9c5760d/fmed-12-1555883-g001.jpg

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