298 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 in colorectal cancer, oncogenic APC/β-catenin/TCF signaling suppresses p38α MAPK activity, which in turn silences the expression of GUCY2C tumor-suppressor hormones (guanylin and uroguanylin), thereby identifying p38α as a critical intermediary that integrates these opposing oncogenic and tumor-suppressive axes.
This study characterizes novel murine bladder cancer cell lines, particularly the BBN966 sarcomatoid urothelial carcinoma (SUC) model, which recapitulates human SUC's aggressive EMT-driven biology and M2 macrophage infiltration, thereby providing a valuable preclinical platform for testing immunotherapies like anti-PD1.
This study demonstrates that a fully saturated C18 aminotriester lipid selectively enhances the antiproliferative activity of amonafide in human colorectal cancer cells by improving its membrane trafficking, without causing nonspecific cytotoxicity, while showing minimal effects with unsaturated analogues or in other cell lines.
This study utilizes spatial transcriptomics and multiplex immunostaining to reveal that the enrichment of TREM2+ macrophages and myofibroblastic cancer-associated fibroblasts in tumor-proximal niches of ductal carcinoma in situ (DCIS), mediated by specific ligand-receptor interactions, is significantly associated with subsequent recurrence as invasive breast cancer.
This study presents a systematic review and meta-analysis of four public datasets to identify common DNA methylation signatures across breast cancer subtypes, revealing significant deregulation in immune system and cell cycle pathways that could aid in discovering novel biomarkers and therapeutic targets.
This study reveals that gefitinib resistance in EGFR-mutated non-small-cell lung cancer is driven by aberrant ligand-free catalytic trimers, and demonstrates that genetically disrupting these trimers back into dimers reverses resistance and decelerates tumor progression.
This study reveals that glucocorticoid receptor activation reorganizes Wnt/LEF1 regulatory circuitry in B-cell acute lymphoblastic leukemia by shifting LEF1 from Wnt-responsive elements to glucocorticoid-responsive sites, a process that establishes distinct chromatin states determining therapeutic sensitivity and resistance.
This study demonstrates that breast cancer cells exhibit integrated morphological, spatial, and dynamic nucleolar alterations characterized by accelerated rRNA trafficking, which can be reversibly remodeled toward a normal profile through specific pharmacological or physicochemical perturbations.
This study reveals that dietary saturated fatty acid chain length critically shapes B-cell lymphoma progression, where medium-chain fatty acids promote tumor growth while long-chain fatty acids and obesogenic diets restrict dissemination by altering lipid metabolism and the immune microenvironment, identifying ACSL1 expression as a potential therapeutic target.
This study develops a mechanistic mathematical model integrating tumor-immune dynamics and ctDNA fluctuations to explain pseudoprogression and trains a random forest classifier that demonstrates superior early discrimination between true progression and pseudoprogression compared to standard imaging criteria.