Overview

Cancer genomics studies how mutations, gene expression, copy-number changes, and other molecular features shape tumor development, patient outcomes, and treatment response. Common approaches include statistical driver and mutation-signature analysis, multi-omics integration, and pathway or regulatory-network models, alongside machine learning on sequencing, pathology images, and scans. Researchers evaluate these methods on resources such as TCGA and clinical cohorts, with tasks including subtype classification, survival prediction, biomarker discovery, and drug response. A central challenge is making predictions that generalize across cancers and incomplete datasets while remaining biologically interpretable and reliable enough for clinical use.

Latest papers

CardsList

34 papers1 paper in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.

  1. Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels

    Oct 9, 2026Ali Anaissi, Yuanzhe Jia, Qishun Peng +3Clinical Risk PredictionMultimodal Fusion

  2. Semi-Supervised Learning-Based Genetic Biomarkers Dataset for Multiple-Stage Hepatocellular Carcinoma Prediction

    Sep 15, 2026Ahmed Ammar Kubba, Manar Abu Talib, Jibran Sualeh Muhammad +4Cancer GenomicsGenomics

  3. Potential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer

    Sep 14, 2026Ali Bou Nassif, Darko Castven, Manar Abu Talib +4Cancer GenomicsMedical Diagnosis

  4. Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation

    Aug 31, 2026Bahar İlgen, Yiannos Tolias, Denise Kühnert +5Cancer GenomicsOncology

  5. PerturbRx: Learning Treatment-Conditioned Latent Transitions for Patient Drug Response Prediction

    Aug 21, 2026Yoshitaka Inoue, Minoh Jeong, Alfred Hero +2Cancer Drug Response PredictionPredictive Representation Learning

  6. DNA Methylation Profiling in Melanoma: From Lesion Classification to Therapeutic Stratification

    Aug 19, 2026Jana T. Winterstein, Lukas Heinlein, Günter Raddatz +34Skin Lesion ClassificationCancer Genomics

  7. PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning

    Aug 10, 2026Mona Furukawa, Sai Hyne, Daniel R. McGowan +1Cancer GenomicsMulti-Label Classification

  8. Foundation-model-guided radiogenomic discovery linking cancer genomes to cancer scans

    Jul 22, 2026Frederik Hauke, Jeremias Krause, Patrick Wienholt +6Cancer GenomicsOncology

  9. Predicting Therapeutic Outcome via Aligning Patient-Specific Knowledge Graph and Gene-Level Perturbation Representations

    Jul 6, 2026Dongmin Bang, Sugyun An, Inyoung Sung +3Cancer GenomicsHealthcare

  10. SHIFT: Survival Prediction from Incomplete and Heterogeneous Genomic Data

    Jul 4, 2026Muhammet Sami Yavuz, Ayhan Can Erdur, Sabri Mustafa Kahya +2Cancer GenomicsCancer Survival Prediction

  11. Explainable AI for Cancer Drug Response Prediction: Beyond Univariate Feature Attributions

    Jul 1, 2026Martino Ciaperoni, Margherita Lalli, Simone Piaggesi +6Cancer GenomicsFeature Attribution

  12. JASPR: Joint Spatial Representation learning of histology and spatial genomics for improved virtual genomic screening and clinical prognostication

    Jun 24, 2026Marija Pizurica, Eric Zimmermann, Neil Tenenholtz +5Cancer GenomicsComputational Pathology

  13. A Bayesian Boolean Matrix Factorization with Application to Copy Number Analysis in Cancer

    Jun 16, 2026Adolphus Wagala, Mehmet Samur, Giovanni ParmigianiCancer GenomicsBayesian Inference

  14. TRAPS: Therapeutic Response Analysis via Pathway-informed Stratification

    Jun 5, 2026Sujoy Banik, Sayantan Chakraborty, Boishakhi Das Toma +4Cancer GenomicsCancer Survival Prediction

  15. Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks

    May 8, 2026Kyle Higgins, Ivan Laponogov, Dennis Veselkov +1Cancer GenomicsFeature Attribution

  16. PPI-Net connects molecular protein interactions to functional processes in disease

    May 8, 2026Kyle Higgins, Guadalupe Gonzalez, Dennis Veselkov +2Cancer GenomicsGraph Neural Networks

  17. PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction

    Apr 27, 2026Di Wang, Chupei Tang, Junxiao Kong +3Survival AnalysisGraph Neural Networks

  18. Graph Transformer-Based Pathway Embedding for Cancer Prognosis

    Apr 17, 2026Koushik Howlader, Md Tauhidul Islam, Wei LeCancer GenomicsCancer Survival Prediction

  19. Mamba-SSM with LLM Reasoning for Feature Selection: Faithfulness-Aware Biomarker Discovery

    Apr 15, 2026Pushpa Kumar Balan, Aijing FengFeature SelectionScientific Discovery

  20. Dictionary-based Pathology Mining with Hard-instance-assisted Classifier Debiasing for Genetic Biomarker Prediction from WSIs

    Mar 26, 2026Ling Zhang, Boxiang Yun, Ting Jin +3Computational PathologyHistopathology Image Classification

  21. SynLeaF: A Dual-Stage Multimodal Fusion Framework for Synthetic Lethality Prediction Across Pan- and Single-Cancer Contexts

    Mar 23, 2026Zheming Xing, Siyuan Zhou, Ruinan Wang +9Multimodal FusionCancer Genomics

  22. Contextual Invertible World Models: A Neuro-Symbolic Agentic Framework for Colorectal Cancer Drug Response

    Mar 1, 2026Christopher Baker, Tianyu Ren, Karen Rafferty +1Cancer Drug Response PredictionWorld Models