Collection 

AI in precision oncology

Submission status
Closed
Submission deadline

The fields of cancer research and precision oncology are undergoing a massive transformation due to the application of artificial intelligence (AI). AI has enabled the detection of hidden patterns from multiple sources of information, including molecular profiling, pathology, and medical imaging, among others, as well as the integration of -omics data to provide a more comprehensive understanding of cancer. AI has also spurred the development of new assays for characterising cancer, prognostication, and predicting responses to specific treatments. These advances in tailoring treatment to the unique characteristics of a patient's cancer are a significant breakthrough. Despite the many opportunities that AI offers, challenges arise when translating these new tools from research settings to clinical practice.

The purpose of this Collection is to disseminate the most recent research and advancements in all facets of AI in cancer research, including basic, translational, and clinical studies. Additionally, the Collection seeks to provide a comprehensive review of the current applications of AI in precision oncology and offer expert insights on how to expedite AI tools from the laboratory to the clinic, with the ultimate goal of improving patient care. The Collection will prioritise articles which are using innovative methods, address a relevant real-world problem and at the same time provide high-quality evidence using multicentric datasets. 

The topics will include, but are not limited to:

  • Prognostic and predictive biomarkers in cancer
  • Molecular profiling (genomics, transcriptomics, proteomics)
  • Digital pathology 
  • Medical imaging 
  • Real-world data analysis
  • Multimodal data integration
  • Novel clinical trial designs

This is a joint collection between npj Precision Oncology and npj Breast Cancer. Topics of particular interest for npj Breast Cancer include:

  • AI systems for breast cancer diagnosis
  • AI systems for lymph node metastasis detection
  • Automation of the assessment of immunohistochemical biomarkers
  • HER2 and HER2-Low assessment
  • Tumour infiltrating lymphocytes and tumour microenvironment
  • Inference of breast cancer biomarkers from H&E-stained slides
  • Multimodal biomarkers

This Collection supports and amplifies research related to SDG 3.

photo of a masked doctor interacting with a high-tech digital computer; there is a robotic arm in the background

Editors

  • Raquel Perez-Lopez

    Team Leader, Radiomics Group, Vall d´Hebron Institute of Oncology (VHIO), Barcelona, Spain

  • Jorge S. Reis-Filho

    Director, Experimental Pathology and of the Experimental Pathology Fellowship Program Affiliate Member, Human Oncology & Pathogenesis Program, Memorial Sloan Kettering Cancer Center, NY, USA

  • Jakob Nikolas Kather

    Professor, Technical University of Dresden, Dresden, Germany

  • Fiona Kolbinger

    Surgical clinician scientist, National Center for Tumor Diseases, University Hospital Else Kroener Fresenius Center for Digital Health in Dresden, Dresden, Germany

Dr. Raquel Perez-Lopez is an experienced academic radiologist trained at Bellvitge University Hospital in Barcelona (Spain) and the Royal Marsden Hospital and the Institute of Cancer Research in London (UK). Her PhD studies enabled her to identify the value of whole-body diffusion-weighted MRI as a prognostic and response biomarker of bone metastases in prostate cancer, that in turn led to the completion of the first prospective clinical trial in this context. Raquel joined VHIO in late 2017 as Team Leader of the VHIO’s newly established Radiomics Group. The group’s efforts center on advancing precision imaging in personalized medicine, towards ultimately improving outcomes for cancer patients by applying mathematical methods to image processing and artificial intelligence in the biomedical field. Dr. Perez-Lopez contributes with her expertise in radiomics and imaging biomarkers in several international research consortia (ODELIA; DART https://cce-dart.com/; COLOSSUS  https://www.colossusproject.eu/) and is an active member of the Cancer Core Europe-Imaging Task Force.

Dr. Jorge S. Reis-Filho, MD PhD FRCPath, holds a joint medical degree from University of Porto, Portugal and Universidade Federal do Parana, Brazil. After finishing his histopathology training at the University of Porto, Portugal, he did his PhD on breast cancer molecular pathology at the Breakthrough Research Centre at The Institute of Cancer Research/ Royal Marsden Hospital in London, UK, where he was appointed Team Leader of the Molecular Pathology Laboratory in 2006 and, subsequently, the Professor and Chair of Molecular Pathology in 2010. In 2012, Dr. Reis-Filho took the position of Member at the Department of Pathology at Memorial Sloan Kettering Cancer Center in New York, USA, where he was appointed Director of Experimental Pathology and Director of the Experimental Pathology Fellowship Program in 2016. Dr. Reis-Filho has published over 600 peer reviewed articles, is a Deputy Editor a Deputy Editor of the Journal of the National Cancer Institute and of npj Breast Cancer, an Associate Editor of the Journal of Pathology, and a member of the expert panel of the World Health Organization for the classification of tumors of breast, soft tissue, skin and eyes. Dr. Reis-Filho has received several awards, including the CL Oakley Lectureship (2007) and the Goudie Medal and Lectureship (2023) by the Pathological Society of Great Britain and Ireland, the BACR Translational Research Award (2007), the Ramzi Cotran Young Investigator Award (2010) by the United States and Canadian Academy of Pathology and the Future Leaders Prize by Cancer Research UK (2010). Dr. Reis-Filho is the youngest ever Fellow of The Royal College of Pathologists to have become a member by published works. He has a long-standing interest and a track record in the genomic analysis of rare cancer types, as well as in characterization of the patterns of DNA repair defects and genetic instability in breast cancers. Dr. Reis-Filho co-leads the NIH MSKCC Genomics Instability in Breast Cancer SPORE, which seeks to deliver optimal treatments for cancer patients with specific types of DNA repair defects.

Dr. Jakob Kather is a physician with board certification in internal medicine and multiple years of clinical experience in oncology, in particular of gastrointestinal cancer. In parallel, he obtained a technical degree and established a research group of computational oncology. The focus of his interdisciplinary team is the development and validation of artificial intelligence and mechanistic modeling methods in oncology. Specific interests include image analysis of histopathology and radiology data, analysis of tabular data and multimodal data integration.

 

Dr. Fiona Kolbinger is a surgical clinician scientist at the University Hospital, the National Center for Tumor Diseases and the Else Kroener Fresenius Center for Digital Health in Dresden (Germany). She leads an interdisciplinary research group specializing in Artificial Intelligence in Surgical Oncology. Based on automated analysis of medical imaging such as radiological, endoscopic, or microscopic images, her work aims to improve clinical outcomes for cancer patients through more tailored interdisciplinary treatment approaches and better risk and outcome stratification. Dr. Kolbinger is particularly interested in the translation of computational approaches into practical applications in clinical medicine.