HER2 overexpression in gastroesophageal adenocarcinoma from immunohistochemstry imaging.

HER2 overexpression in gastroesophageal adenocarcinoma from immunohistochemstry imaging.

Primary dataset used in Predicting the HER2 status in esophageal cancer from tissue microarrays using convolutional neural networks [1].

This dataset is composed by HER2 immunohistochemistry images of gastroesophageal adenocarcinoma patients. We provide a train-test split of .jpg image files of individual tissue cores, which were labeled with an immunohistochemstry score (ranging from 0 to 3) and a HER2 overexpression status (positive or negative).

Detailed information

Train split comes from a multi-spot tissue microarray (TMA) with 165 tumor cases and a single-spot TMA with 428 tumor cases, as described elsewhere [2]. Test split comes from an independent single-spot TMA with 307 tumor cases as the test dataset. The test set consisted of tumor cases that occurred at a later time point compared to the training set cases. This dataset construction strategy mimics how such a model would be developed and deployed in a clinical routine. Coincidentally, the test set does not include tumor cases with an IHC score of 1. The multi-spot TMA was composed of eight tissue cores (1.2 mm diameter) of each tumor - four cores punched on the tumor margin and four in the tumor center. To construct the single-spot TMA, one tissue core per patient from the tumor center was punched. The cores were transferred to TMA receiver blocks. Each TMA block contained 72 tissue cores. Subsequently, 4 µm-thick sections from the TMA blocks were prepared and transferred to an adhesive-coated slide system (Instrumedics Inc., Hackensack, NJ).

We used a HER2 antibody (Ventana clone 4B5, Roche Diagnostics, Rotkreuz, Switzerland) on the automated Ventana/Roche slide stainer to perform immunohistochemistry (IHC) on the TMA slides. HER2 expression in carcinoma cells was assessed according to staining criteria listed in the Supplemental Table 1 of [1]. Scores 0 and 1 indicated negative HER2 status, and score 3 indicated positive HER2 status. Immunohistochemical expression evaluation was assessed manually by two pathologists according to [3]. Discrepant results, which occurred only in a small number of samples, were resolved by consensus review. Spots with a score of 2 were analyzed by fluorescence in situ hybridization (ISH) to resolve the HER2 status. The ISH analysis evaluated the HER2 gene amplification status using the Zytolight SPEC ERBB2/CEN 17 Dual Probe Kit (Zytomed Systems GmbH, Germany) according to the manufacturer's protocol. A fluorescence microscope (DM5500, Leica, Wetzlar, Germany) with a 63× objective was used for scanning the tumor tissue for amplification hotspots. We counted the signals in randomly chosen areas of homogeneously distributed signals. Twenty tumor cells were evaluated by counting green HER2 and orange centromere-17 (CEN17) signals. The reading strategy followed the recommendations of HER2/CEN17 ratio ≥ 2.0 or HER2 signals ≥ 6.0 for HER2 positive and a HER2/CEN17 ratio < 2.0 for HER2 negative samples.

Slides were digitised with a slide scanner (NanoZoomer S360, Hamamatsu Photonics, Japan) with 40-times magnification and used QuPath's [4] TMA dearrayer to slice the digitized slides into individual images.

[1] Pisula JI, Datta RR, Boerner-Valdez L, Avemarg JR, Jung JO, Plum P, Loeser H, Lohneis P, Meuschke M, dos Santos DP, Gebauer F, et al. Predicting the HER2 status in esophageal cancer from tissue microarrays using convolutional neural networks. bioRxiv: https://www.biorxiv.org/content/10.1101/2022.05.13.491769v1

[2] Plum PS, Gebauer F, Krämer M, Alakus H, Berlth F, Chon SH, Schiffmann L, Zander T, Büttner R, Hölscher AH, Bruns CJ. HER2/neu (ERBB2) expression and gene amplification correlates with better survival in esophageal adenocarcinoma. BMC cancer. 2019 Dec;19(1):1-9.

[3] Lordick F, Al-Batran SE, Dietel M, Gaiser T, Hofheinz RD, Kirchner T, Kreipe HH, Lorenzen S, Möhler M, Quaas A, Röcken C. HER2 testing in gastric cancer: results of a German expert meeting. Journal of cancer research and clinical oncology. 2017 May;143(5):835-41.

[4] Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD, McQuaid S, Gray RT, Murray LJ, Coleman HG, James JA. QuPath: Open source software for digital pathology image analysis. Scientific reports. 2017 Dec 4;7(1):1-7.

# 基于免疫组化成像的胃食管腺癌HER2过表达数据集
本数据集为论文《基于卷积神经网络（convolutional neural networks, CNN）从组织微阵列（tissue microarray, TMA）预测食管癌HER2状态》[1]所使用的核心数据集。

本数据集包含胃食管腺癌患者的HER2免疫组化成像图片。我们提供了划分完成训练集与测试集的单组织芯JPG格式图像文件，所有图像均标注有免疫组化评分（取值范围0至3）以及HER2过表达状态（阳性或阴性）。

## 数据集详情
训练集来源于两类组织微阵列（TMA）：一类为多斑点TMA，包含165例肿瘤样本；另一类为单斑点TMA，包含428例肿瘤样本，具体构建方案详见文献[2]。测试集则来自独立的单斑点TMA，共包含307例肿瘤样本。测试集的肿瘤样本采集时间晚于训练集样本，该数据集的构建策略模拟了模型在临床常规场景中的开发与部署流程。值得注意的是，测试集未包含免疫组化评分为1的肿瘤样本。

多斑点TMA的每个肿瘤样本取8个组织芯（直径1.2mm）：4个取自肿瘤边缘，4个取自肿瘤中心。单斑点TMA则从每位患者的肿瘤中心取1个组织芯。将获取的组织芯移植至TMA受体蜡块中，每个TMA蜡块可容纳72个组织芯。随后，将TMA蜡块制作成4μm厚的切片，并转移至带黏附涂层的载玻片系统（Instrumedics Inc.，美国新泽西州哈肯萨克市）。

我们使用HER2抗体（Ventana克隆4B5，罗氏诊断公司，瑞士罗特克罗伊茨）在自动化Ventana/Roche染色仪上对TMA载玻片进行免疫组化（immunohistochemistry, IHC）染色。癌细胞的HER2表达水平按照文献[1]补充表1中的染色标准进行评估：免疫组化评分为0和1代表HER2状态为阴性，评分为3则代表阳性。免疫组化表达评估由两位病理学家按照文献[3]的标准手动完成，仅在少量样本中出现的结果不一致情况，通过共同复核予以解决。对于免疫组化评分为2的样本，通过荧光原位杂交（fluorescence in situ hybridization, ISH）分析以明确HER2状态。

ISH分析采用Zytolight SPEC ERBB2/CEN 17双探针试剂盒（Zytomed系统有限公司，德国），严格遵循制造商的操作流程。使用配备63×物镜的荧光显微镜（DM5500，徕卡公司，德国韦茨拉尔市）扫描肿瘤组织以寻找扩增热点区域，在信号分布均匀的随机区域计数信号：随机选取20个肿瘤细胞，分别计数绿色的HER2信号与橙色的17号染色体着丝粒（centromere-17, CEN17）信号。判读标准遵循相关指南：当HER2/CEN17比值≥2.0或HER2信号数≥6.0时，判定为HER2阳性；当HER2/CEN17比值<2.0时，判定为HER2阴性。

使用搭载40倍放大倍率的玻片扫描仪（NanoZoomer S360，滨松光子学株式会社，日本）对载玻片进行数字化扫描，并通过QuPath[4]的TMA阵列拆分工具将数字化后的整张玻片切片为单张组织芯图像。

## 参考文献
[1] Pisula JI, Datta RR, Boerner-Valdez L, Avemarg JR, Jung JO, Plum P, Loeser H, Lohneis P, Meuschke M, dos Santos DP, Gebauer F, et al. Predicting the HER2 status in esophageal cancer from tissue microarrays using convolutional neural networks. bioRxiv: https://www.biorxiv.org/content/10.1101/2022.05.13.491769v1
[2] Plum PS, Gebauer F, Krämer M, Alakus H, Berlth F, Chon SH, Schiffmann L, Zander T, Büttner R, Hölscher AH, Bruns CJ. HER2/neu (ERBB2) expression and gene amplification correlates with better survival in esophageal adenocarcinoma. BMC cancer. 2019 Dec;19(1):1-9.
[3] Lordick F, Al-Batran SE, Dietel M, Gaiser T, Hofheinz RD, Kirchner T, Kreipe HH, Lorenzen S, Möhler M, Quaas A, Röcken C. HER2 testing in gastric cancer: results of a German expert meeting. Journal of cancer research and clinical oncology. 2017 May;143(5):835-41.
[4] Bankhead P, Loughrey MB, Fernández JA, Dombrowski Y, McArt DG, Dunne PD, McQuaid S, Gray RT, Murray LJ, Coleman HG, James JA. QuPath: Open source software for digital pathology image analysis. Scientific reports. 2017 Dec 4;7(1):1-7.