The development of digital pathology and progression of state‐of‐the‐art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)‐based AI, in tumor pathology. The DL‐based algorithms have been developed to conduct all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction, as well as the identification of pathological features, biomarkers and genetic changes. The applications of AI in pathology not only contribute to improve diagnostic accuracy and objectivity but also reduce the workload of pathologists and subsequently enable them to spend additional time on high‐level decision‐making tasks. In addition, AI is useful for pathologists to meet the requirements of precision oncology. However, there are still some challenges relating to the implementation of AI, including the issues of algorithm validation and interpretability, computing systems, the unbelieving attitude of pathologists, clinicians and patients, as well as regulators and reimbursements. Herein, we present an overview on how AI‐based approaches could be integrated into the workflow of pathologists and discuss the challenges and perspectives of the implementation of AI in tumor pathology.

Examining plasma microRNA markers for colorectal cancer at different stages

Fascin is a F-actin bundling protein and its overexpression is correlated with poor prognosis and increases metastatic potential in a number of cancers. But underlying function and mechanism of fascin on tumorigenesis in melanoma remain elusive. The melanoma cell lines WM793 and WM39 were employed for the soft agar and sphere formation assay. Quantitative RT-PCR and Western blot were performed for identifying the gene expression at mRNA and protein levels, respectively. Co-IP and in vitro GST pulldown experiments were used to test the interaction between fascin and MST2. Fascin regulates tumorigenesis and cancer cell stemness in melanoma through inhibition of the Hippo pathway kinase MST2 and the activation of transcription factor TAZ. Our data showed that fascin interacts with the kinase domain of MST2 to inhibit its homodimer formation and kinase activity. Depletion of fascin led to increase of p-LATS level and decrease of TAZ, but not YAP. We also demonstrated that fascin regulates melanoma tumorigenesis independent of its actin-bundling activity. Fascin is a new regulator of the MST2-LATS-TAZ pathway and plays a critical role in melanoma tumorigenesis. Inhibition of fascin reduces melanoma tumorigenesis and stemness, and thus fascin could be a potential therapeutic target for this malignancy.