High intratumoral heterogeneity is thought to be a poor prognostic indicator. However, the source of heterogeneity may also be important, as genomic heterogeneity is not always reflected in histologic or ‘visual’ heterogeneity. We aimed to develop a predictor of histologic heterogeneity and evaluate its association with outcomes and molecular heterogeneity. We used VGG16 to train an image classifier to identify unique, patient-specific visual features in 1655 breast tumors (5907 core images) from the Carolina Breast Cancer Study (CBCS). Extracted features for images, as well as the epithelial and stromal image components, were hierarchically clustered, and visual heterogeneity was defined as a greater distance between images from the same patient. We assessed the association between visual heterogeneity, clinical features, and DNA-based molecular heterogeneity using generalized linear models, and we used Cox models to estimate the association between visual heterogeneity and tumor recurrence. Basal-like and ER-negative tumors were more likely to have low visual heterogeneity, as were the tumors from younger and Black women. Less heterogeneous tumors had a higher risk of recurrence (hazard ratio = 1.62, 95% confidence interval = 1.22–2.16), and were more likely to come from patients whose tumors were comprised of only one subclone or had a TP53 mutation. Associations were similar regardless of whether the image was based on stroma, epithelium, or both. Histologic heterogeneity adds complementary information to commonly used molecular indicators, with low heterogeneity predicting worse outcomes. Future work integrating multiple sources of heterogeneity may provide a more comprehensive understanding of tumor progression.
高肿瘤内异质性通常被认为是预后不良的指标。然而，异质性的来源同样至关重要，因为基因组异质性并不总是体现在组织学或“视觉”异质性上。本研究旨在开发一种组织学异质性预测因子，并评估其与临床结局及分子异质性的关联。我们利用VGG16架构训练图像分类器，从卡罗莱纳乳腺癌研究（CBCS）的1655例乳腺肿瘤（5907张组织芯片图像）中识别患者特异性的独特视觉特征。通过对完整图像及其上皮与间质组分的特征进行层次聚类，将同一患者不同图像间的较大距离定义为视觉异质性。采用广义线性模型评估视觉异质性、临床特征与DNA分子异质性的关联，并通过Cox模型分析视觉异质性与肿瘤复发的相关性。结果显示：基底样与ER阴性肿瘤、年轻女性及黑人女性的肿瘤更易呈现低视觉异质性。异质性较低的肿瘤具有更高的复发风险（风险比=1.62，95%置信区间=1.22–2.16），且更可能来源于仅含单一亚克隆或携带TP53突变的患者。无论基于间质、上皮或完整图像的分析，上述关联性均保持一致。组织学异质性为常用分子指标提供了补充信息，其中低异质性预示着更差的临床结局。未来整合多源异质性的研究有望更全面地揭示肿瘤进展机制。
Visual Intratumor Heterogeneity and Breast Tumor Progression
肿瘤(癌症)患者之家