🔬 Category

oncology

48 papers

Oncology is the dynamic field dedicated to understanding and treating cancer, a complex group of diseases where cells grow uncontrollably. This area of study spans everything from identifying genetic mutations that drive tumor formation to developing new therapies and improving patient care strategies. Because cancer research moves at a rapid pace, staying updated with the very latest findings is essential for both experts and the curious public.

At Gist.Science, we curate the most recent preprints in oncology directly from medRxiv, ensuring you have immediate access to cutting-edge research before it undergoes formal peer review. We process every new submission in this category, transforming dense scientific manuscripts into both plain-language overviews and detailed technical summaries. This dual approach makes critical discoveries accessible to everyone, regardless of their background in medicine or biology.

Below are the latest oncology papers added from medRxiv, complete with our simplified explanations and full technical breakdowns to help you navigate the latest breakthroughs in cancer science.

Virtual Spectral Decomposition with Dendritic Tile Selection: An Explainable AI Framework for Multimodal Tissue Composition Analysis and Immune Phenotyping Across Pancreatic, Lung, and Breast Cancer

This paper introduces Virtual Spectral Decomposition (VSD), an explainable AI framework that utilizes a modality-agnostic, interpretable-by-design approach and dendritic tile selection to analyze tissue composition and immune phenotyping across pancreatic, lung, and breast cancers, offering clinically verifiable insights without the opacity of traditional black-box deep learning models.

Chandra, S.2026-04-13🔬 oncology

Drug response profiling guides precision therapy in relapsed and refractory childhood acute lymphoblastic leukemia

This prospective, multicenter study demonstrates that a scalable Drug Response Profiling (DRP) framework successfully identifies individualized, effective treatment combinations for children with relapsed or refractory acute lymphoblastic leukemia, leading to significant clinical responses and improved survival outcomes.

Steffen, F. D., Lissat, A., Alten, J., Kriston, A., Scheidegger, N., Eckert, C., Bodmer, N., Schori, L., Schühle, S., Arpagaus, A., Gutnik, S., Manioti, D., Bruderer, N., Zeckanovic, A., Västrik, I. (…)2026-04-11🔬 oncology

Accelerometer-derived circadian rhythm and colorectal cancer risk in UK Biobank: a prospective cohort study

This prospective cohort study of 95,050 UK Biobank participants found that while specific accelerometer-derived physical activity patterns were nominally associated with reduced colorectal cancer risk, these associations largely disappeared after adjusting for lifestyle and metabolic factors, suggesting they are not independent predictors.

Ni Chan Chin, M., Berrio, J. A.2026-04-05🔬 oncology

PINK1 Expression as a Prognostic Biomarker in Glioblastoma Multiforme: An Observational Multicenter Study

This prospective, multicenter observational study in Bogotá, Colombia, aims to validate PINK1 expression as a prognostic biomarker for overall survival, progression-free survival, and functional outcomes in adults with newly diagnosed IDH-wild type glioblastoma multiforme.

Garcia Rairan, L. A., Corpus Gutierrez, v., Del castillo, m. a., Riveros Castillo, W., Saavedra Gerena, J., Turizo Smith, A. D., Arias Guatibonza, J.2026-04-05🔬 oncology

From Registration to Insight: How STRONG AYA Transforms Registry Data to Enhance Decision-Support Tools for Adolescent and Young Adult Oncology

The STRONG AYA consortium leverages federated learning to integrate registry data from the UK's Yorkshire Specialist Register of Cancer in Children and Young People with international datasets, transforming it into actionable insights via the PROMPT software to enhance clinical decision-making and patient consultations for adolescents and young adults with cancer.

Hughes, N., Hogenboom, J., Carter, R., Norman, L., Gouthamchand, V., Lindner, O., Connearn, E., Lobo Gomes, A., Sikora-Koperska, A., Rosinska, M., Pogoda, K., Wiechno, P., Jagodzinska-Mucha, P., Lugow (…)2026-04-04🔬 oncology

A Transformer-Based 2.5D Deep Learning Model for Preoperative Prediction of Lymph Node Metastasis in Papillary Thyroid Carcinoma

This study presents ThyLNT, a Transformer-based 2.5D deep learning model that significantly outperforms traditional imaging and radiomics methods in preoperatively predicting lymph node metastasis in papillary thyroid carcinoma, while multi-omics analyses validate its predictions by linking them to VEGFA-driven angiogenesis, epithelial-mesenchymal transition, and lipid metabolic reprogramming in the tumor microenvironment.

Xu, S., Yan, X., Su, Y., Qi, J., Chen, X., Li, Y., Xiong, H., Jiang, J., Wei, Z., Chen, Z., YALIKUN, Y., Li, H., Li, X., Xi, Y., Li, W., Li, X., Du, Y.2026-04-02🔬 oncology

Reproducible profiling of the gut microbiota using surplus clinical Faecal Immunochemical Test (FIT) samples

This study demonstrates that surplus Faecal Immunochemical Test (FIT) samples remain stable for up to 14 days and yield bacterial 16S rRNA sequencing results comparable to standard whole-stool samples, validating their use for large-scale, low-cost gut microbiota research.

van den Haak, M. A., Zbikowski, J. T., Moomin, A., Wilson, J., Halsey, C., Gourley, C., Din, F., McSorley, S. T., Collie-Duguid, E. S., Horgan, G., Walker, A. W., Johnstone, A. M., Kiltie, A. E.2026-03-30✓ Author reviewed ⓘ🔬 oncology

Artificial Intelligence and Circulating microRNA Signatures for Early Breast Cancer Detection: A Systematic Review and Meta-Analysis

This systematic review and meta-analysis demonstrates that AI/ML-based circulating microRNA signatures show promising diagnostic accuracy for early breast cancer detection, though their routine clinical implementation currently requires further validation through prospective, standardized, and externally validated studies.

Solanki, s., Solanki, N., Prasad, J., Prasad, R., Harsulkar, A.2026-03-30🔬 oncology

Multi-Omic Profiling Reveals Antibody-Drug Conjugate Targetability in Ovarian Cancer

By analyzing multi-omic data from 867 samples, this study demonstrates that antibody-drug conjugate targets in high-grade serous ovarian cancer are broadly stable across space and time, with TACSTD2 and FOLR1 emerging as highly expressed, homogeneous, and frequently co-expressed candidates suitable for therapeutic prioritization.

Pöllänen, E., Muranen, T., Lahtinen, A., Zhang, K., Afenteva, D., Pirttikoski, A., Holmström, S., Li, Y., Lavikka, K., Oikkonen, J., Söderlund, J., Hynninen, J., Virtanen, A., Hautaniemi, S.2026-03-27🔬 oncology

Activity of low dose nivolumab in patients with advanced squamous cell carcinomas and other cancers

A retrospective study of 53 patients with advanced cancers, primarily squamous cell carcinomas, found that low-dose nivolumab (20 mg every three weeks) demonstrated encouraging efficacy and manageable toxicity comparable to standard doses, particularly in a frail, elderly population.

Gauduchon, T., Fayette, J., Amini-Adle, M., Neidhart-Berard, E.-M., Brahmi, M., Dufresne, A., Dupont, M., Coutzac, C., De Bernardi, A., Toussaint, P., Mery, B., Crumbach, L., Ray-Coquard, I., Dutour (…)2026-03-27🔬 oncology