161 papers
Cancer biology explores the complex ways cells grow out of control, investigating the genetic mutations and environmental factors that drive tumor formation. This field seeks to understand how healthy cells transform into malignant ones and how these rogue cells spread throughout the body. By decoding these fundamental mechanisms, researchers aim to develop more effective treatments that target the disease at its source while sparing healthy tissue.
At Gist.Science, we process every new preprint published in this category directly from bioRxiv to ensure you stay ahead of the curve. Our team provides both accessible plain-language overviews and detailed technical summaries for each study, bridging the gap between raw research data and practical understanding. Whether you are a specialist or a curious reader, our goal is to make these critical findings clear and actionable.
Below are the latest papers in cancer biology, offering fresh insights into the ongoing fight against this disease.
This study identifies nine cases where LINE-1 retrotransposition insertions cause MET exon 14 skipping in cancer, establishing this mechanism as a recurrent and clinically actionable driver of oncogenic signaling.
Using super-resolution microscopy, this study reveals that estrogen receptor activity dynamically regulates the structural conformation of H3K27ac-marked chromatin, transitioning between open, active states and compact, inactive states, thereby challenging the notion that this epigenetic mark alone is sufficient for enhancer activation and offering new insights into endocrine therapy resistance in breast cancer.
This study establishes a biopsy-compatible ex vivo drug sensitivity testing platform for rare solid tumors that successfully identifies actionable drug responses and demonstrates a significant correlation between high in vitro sensitivity and improved clinical outcomes, supporting its use as a complementary tool in precision oncology.
This study employs an integrative systems-level transcriptomic analysis to reveal that gastric cancer progression is driven by coordinated chromatin-level developmental reprogramming, characterized by the upregulation of HOX genes and loss of gastric differentiation markers, alongside FGFR-mediated oncogenic signaling and stage-dependent metabolic disruption.
This study proposes a hybrid framework combining Differential Evolution and Physics-Informed Neural Networks to accurately estimate parameters in tumor-immune ODE models for bladder cancer, enabling robust, data-driven personalization of treatment strategies despite sparse and noisy clinical data.
This study identifies the loss of piR-hsa-7221 regulation as a key driver of CASC9 oncogenic lncRNA expression in testicular germ cell tumors, revealing a novel epigenetic mechanism that promotes tumor progression and cisplatin resistance while highlighting potential new therapeutic targets.
This study reveals that lung cancer-enriched p53 mutants (specifically V157F and R158L) uniquely retain the ability to bind canonical target genes but fail to activate transcription, representing a distinct loss-of-function mechanism that occurs post-DNA binding and exerts a dominant-negative effect on wild-type p53.
This study demonstrates that a specific combination of fifteen NFAT3-regulated miRNAs, delivered via engineered extracellular vesicles, effectively suppresses tumor growth and invasion in aggressive cancers like triple-negative breast and pancreatic cancer, offering a promising therapeutic strategy where individual miRNAs fail.
The novel PDE10 inhibitor ADT-030 demonstrates potent antitumor activity against KRAS-mutant pancreatic ductal adenocarcinoma by inhibiting oncogenic signaling, inducing cell cycle arrest and apoptosis, and remodeling the tumor microenvironment to enhance anti-tumor immunity, all while showing efficacy in resistant models and reducing metastasis without systemic toxicity.
This paper establishes a benchmarking framework for comparing mouse neoantigen immunogenicity by demonstrating that experimental peptide-MHC complex stability () is a superior predictor of in vivo T cell responses than in silico binding affinity predictions.