203 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 reveals that the loss of the iron transporter DMT1 disrupts intracellular iron distribution and induces endoplasmic reticulum stress, which paradoxically enhances cancer cell invasion in 3D environments by destabilizing the extracellular matrix, challenging the assumption that reduced total iron levels uniformly suppress tumor aggressiveness.
This study demonstrates that a collagen-embedded 3D microphysiological system effectively recapitulates the metabolic heterogeneity of high-grade serous ovarian cancer tumors and reveals that the OXPHOS inhibitor atovaquone suppresses tumor progression by disrupting mitochondrial networks and the YAP/TAZ pathway while sparing biomimetic blood vessels.
This study introduces a functional data analysis framework to model T cell spatial clustering across continuous scales in ovarian cancer, revealing that the combination of high immune cell abundance and low spatial clustering (diffuse infiltration) provides superior prognostic value for overall survival compared to abundance or fixed-radius spatial metrics alone.
This study demonstrates that optical coherence tomography (OCT) radiomics provides a sensitive, reproducible, and label-free high-throughput method for quantifying radiation dose responses in tumor spheroids, significantly outperforming conventional brightfield morphology without requiring concurrent brightfield imaging.
This study establishes and characterizes a novel immunocompetent, syngeneic mouse model of osteoblastic breast cancer bone metastasis using intratibial injection of PyMT-CK(OB) cells in FVB/N mice, demonstrating that immune competence is essential for driving tumor-induced bone formation and providing a robust platform for investigating the mechanisms and therapies of this distinct skeletal disease.
This study repositions the historical prodrug CB1954 as a highly selective therapeutic for homologous recombination-deficient cancers by demonstrating its ability to exploit specific DNA repair dependencies via NQO2-mediated activation and DNA crosslinking, thereby offering a new precision oncology strategy through the biomarker-guided rediscovery of abandoned DNA-damaging agents.
This study introduces BANDOL, a multi-omics machine learning model that significantly improves breast cancer survival prediction by leveraging epigenetic features as the strongest predictors and identifying actionable biomarkers for personalized treatment.
This study reveals that succinate dehydrogenase-deficient cancer cells overcome aspartate limitation and restore proliferative fitness through two distinct adaptive mechanisms—suppression of respiratory complex I or upregulation of pyruvate carboxylase—highlighting a redox-constrained metabolic plasticity that offers potential therapeutic vulnerabilities.
This study reveals that RHNO1 forms a positive feedback loop with ATR/Chk1 signaling, where stress-induced stabilization of RHNO1 is essential for sustaining the DNA replication stress response and preventing genomic instability in cancer cells.
This study demonstrates that strong spatial associations between hypoxia and cytotoxic activity observed within a single breast cancer tissue section do not consistently reproduce across patients, highlighting the critical distinction between within-section correlations and patient-level biological effects in spatial transcriptomics.