New collaboration with dutch experts
From left: Manohar Pradhan, Tarjei Svensgjerd Hveem, Krishanti Gunatasan, Andrea Goa, Miangela M. Lacle (T1 CRC WG), Hanne A. Askautrud, Lisa van der Schee (T1 CRC WG), Marna Lill Kjæreng, Andreas Kleppe and Ole Johan Skrede.
In the first week of October 2021 we had the pleasure of having a visit from our new collaborators, Drs. Miangela M. Lacle and Lisa van der Schee in the Dutch T1 Colorectal Cancer Working Group . Together, we will explore the possibility of applying deep learning to better identify the patients with early-stage colon or rectum cancer who actually need a surgical resection, as well as identifying patients who could be spared from the morbidities and occasional mortalities associated with this surgery. This could have a tremendous impact on the success of the screening programs for colorectal cancer, which have recently started or will soon start in many Western countries.
We are looking forward to working with leading experts on early-stage colorectal cancer to improve the quality of life and survival of people with this disease.
Patent application submitted
Recently a patent application for the DoMore-v1-CRC-marker was submitted. The DoMore-v1-CRC-marker is a machine-learning algorithm assisting clinicians to decide which patients may benefit from additional drug therapy following surgery for colorectal cancer.
Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The new method, which detects the DoMore-v1-CRC marker, is called histotyping, and is a result of the DoMore! project. The project is lead by Håvard E. Danielsen, director of the ICGI, and was in 2016 selected as one of the Norwegian Research Council's Lighthouse projects to solve large societal challenges using cutting-edge technology.
"Dagens medisin" is Norway's largest independent news channel within health and medicine. Click here to read their article on the topic (in norwegian).
Designing deep learning studies in cancer diagnostics
If artificial intelligence-based technology for cancer diagnostics exists, why is it still not in use? How can new knowledge in deep learning and artificial intelligence in diagnostics benefit cancer patients in the fastest and safest way?
Researchers at our institute have authored a perspective advocating performance estimation in external cohorts. They strongly advise that a primary analysis is predefined in a standardized protocol, preferentially stored in an online repository. They also recommend more careful and rigorous research to facilitate the successful use of AI in the clinic.
Read the article here
The article has received attention worldwide, and a selection of citations is listed below.
Podcast about Artificial Intelligence and Medicine
Listen to our Institute Director Håvard E. Danielsen explaining Domore! and the use of artificial intelligence in cancer prognostication and diagnostics.
NORA (Norwegian Artificial Intelligence Research Consortium) aims to strengthen Norwegian research, education and innovation within artificial intelligence, machine learning and robotics, as well as other relevant research that supports the development of artificial intelligence applications.
Listen to their podcast here.
ICGI's video presentation
Watch the video made by our colleagues at the section for Dissemination and Visualisation, presenting the Institute for Cancer Genetics and Informatics
ICGI Strategy Document for the upcoming years
Congratulations to Karolina Cyll
Karolina Cyll came to the ICGI as a MSc student in 2011, where her project entailed reviewing and increasing the efficiency of the ploidy preparation lab procedure.
In December 2020 she defended her thesis for the PhD degree, titled “High-resolution, high-throughput nuclear analysis as a prognostic marker in prostate cancer.” The study was dedicated to finding prognostic markers for patients with early and intermediate stage of prostate cancer. Investigated material comprised of formalin-fixed paraffin-embedded prostate tumor tissue from radical prostatectomies as well as biopsy materials from patients under surveillance. The main focus was genomic instability, resistance to cell death and immortality of cancer cells. The employed methods were DNA ploidy, nucleotyping, immunohistochemistry and FISH.
We are happy Karolina will continue at our Institute as Post.doc
Andreas Kleppe appointed Associate Professor at University of Oslo
We are so proud of the institutes' many young researchers and pleased to see everything they achieve. Congratulations to Post Doc Andreas Kleppe on his position as Associate Professor at the University of Oslo, Department of Informatics.
The position will involve teaching in image processing, image analysis and deep learning, as well as supervision of master's degree students and doctoral students. Andreas defended his dissertation in 2017 and was the year after the first author of the widely acclaimed article Chromatin organization and cancer prognosis: a pan-cancer study https://www.thelancet.com/.../PIIS1470-2045(17.../fulltext. We wish Andreas good luck with his new, exciting tasks!
The amount of stroma - a new prognostic marker for cancer?
Solid tumours contain many different cellular components in addition to tumour cells. The stroma is the supportive framework of an organ, usually composed of connective tissue, distinguished from the cells or tissues performing the special function of the organ. The manual assessment of the amount of reactive stroma has been shown, by us and others, to be a prognostic marker in both colorectal cancer and prostate cancer. This video describes how to perform an automated analysis of tumour stroma content using routine diagnostic H&E stained tissue sections. Stroma can be combined with DNA ploidy to identify patients at increased risk for poor outcome. The DNA Ploidy and Stroma biomarker are based on a research collaboration between ICGI and professor David Kerr and the University of Oxford.
AI benefits colorectal cancer patients
Professor David Kerr at Oxford University talks about the possible benefits for cancer patients, following the article "Deep learning for prediction of colorectal cancer outcome: a discovery and validation study" , published in "The Lancet" on February 1st 2020.