Clinicopathologic and Genotypic Features of Lung Adenocarcinoma Characterized by the International Association for the Study of Lung Cancer Grading System

医学 分级(工程) 腺癌 肺癌 基因型 肿瘤科 肺腺癌 病理 内科学 癌症 基因 遗传学 生物 工程类 土木工程
作者
Ryo Fujikawa,Yuji Muraoka,Jumpei Kashima,Yukihiro Yoshida,Kimiteru Ito,Hirokazu Watanabe,Masahiko Kusumoto,Shun‐ichi Watanabe,Yasushi Yatabe
出处
期刊:Journal of Thoracic Oncology [Elsevier BV]
卷期号:17 (5): 700-707 被引量:78
标识
DOI:10.1016/j.jtho.2022.02.005
摘要

Abstract

Introduction

The new grading system proposed by the Pathology Committee of the International Association for the Study of Lung Cancer in 2020 was based on the combination of the histologically predominant subtype and high-grade component. Because the predominant subtypes are associated with characteristic subsets, unique subsets can be identified by this grading system.

Methods

We analyzed the clinicopathologic, genotypic, and prognostic features of a cohort of 781 consecutive patients with invasive nonmucinous adenocarcinoma of the lung.

Results

Grade 3 tumors were associated with younger age, male sex, a higher smoking dose, and aggressive features (tumor size, lymph node metastasis, stage, lymphovascular invasion, and pleural invasion). Recurrence-free survival and 3-year overall survival were well-stratified according to tumor grade, and the differences were confirmed with multivariate analysis using the Cox proportional hazard model. Radiologically, most grade 3 tumors exhibit a solid nodular pattern on computed tomography images and a high maximum standardized uptake value with positron emission tomography. Genotypically, 43% of the grade 3 adenocarcinomas lacked any driver mutations, although one of the driver mutations was detected in 79% of grade 1 or 2 tumors. Patient age, positive smoking history, solid nodule on computed tomography image, and higher maximum standardized uptake value were identified as significant preoperative predictive factors of grade 3 tumors, with a prediction rate greater than 90%.

Conclusions

Besides stratifying the patient outcomes, the new grading system characterized unique clinicopathologic subsets and this study suggested that grade 3 tumors could be predicted using the preoperative variables.
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