The Scientific Reports team is pleased to announce the most read* articles from 2022 in Cancer. Featuring authors from around the world, these papers highlight valuable research from an international community.
Last year’s most-read articles covered a host of topics, from in vitro mechanistic studies to prognostic prediction and everything in between. Unsurprisingly, some of our most-read articles were on immunotherapy, such as this article discussing how T cell subtype profiling can be used to predict response to anti-PD-1 therapy and this article introducing a screening approach for functional chimeric antigen receptors. Several studies focused on the use of machine learning in clinical oncology, such as this study examining the potential of machine learning in identifying biomarkers and multiple studies using deep learning in imaging for diagnosis. Some of our most-read articles discuss how to improve preclinical research, including one on modeling the liver tumor microenvironment in a 3D culture system and one on mouse-derived cancer organoids. I hope you’ll head over to the collection to see these papers and so much more in what we published in cancer research last year.
Congratulations to all authors who contributed to these highly valuable research papers!
*Data obtained from SN Insights, which is based on Digital Science's Dimensions.
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