This is the challenge design document for the "Automatic Lung Cancer Detection and Classification in Whole-slide Histopathology" Challenge, accepted for MICCAI 2020. Digital pathology has been gradually introduced in clinical practice. Although the digital pathology scanner could give very high resolution whole-slide images (WSI) (up to 160nm per pixel), the manual analysis of WSI is still a time-consuming task for the pathologists. Automatic analysis algorithms offer a way to reduce the burden for pathologists. Our proposed challenge will focus on automatic detection and classification of lung cancer using Whole-slide Histopathology. This subject is highly clinical relevant because lung cancer is the top cause of cancerrelated death in the world. The first stage of the challenge (ACDC2019) was already successfully held in 2019 in ISBI (https://acdc-lunghp.grand-challenge.org/). ACDC2019 mainly focused on the detection of lung cancer region in WSIs. ACDC2020 will focus on classifying the main lung cancer subtypes (e.g. squamous carcinoma, adenocarcinoma) using WSI.