📄 Category

cancer biology

256 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.

📄 cancer biology

Nuclear translocation of phosphorylated YB-1 via small extracellular vesicles contributes to the malignant phenotype of triple negative breast cancer

This study by co-senior authors Lorico and Sossey-Alaoui demonstrates that small extracellular vesicles (sEVs) derived from triple-negative breast cancer cells deliver phosphorylated YB-1 to the nuclei of recipient cells via the VOR complex, thereby driving malignant stemness and metastasis, a process that can be therapeutically inhibited by blocking nuclear translocation with PRR851.

Santos, M., Kim, Y., Feng, Z., Biebighauser, T., Lorico, A., Sossey-Alaoui, K.2026-07-15
📄 cancer biology

Integrative analysis of TCGA transcriptomic states and DepMap dependencies prioritizes candidate vulnerabilities in immune-cold microsatellite-stable colorectal cancer

By integrating TCGA transcriptomic data with DepMap CRISPR dependency profiles, this study characterizes distinct immune-cold, barrier-high, and intermediate molecular states in microsatellite-stable colorectal cancer to identify specific therapeutic vulnerabilities, such as ERBB2 and cell-cycle regulators, while distinguishing tumor-intrinsic targets from stromal barriers.

Tandon, A., Nagalla, D.2026-07-10
📄 cancer biology

Autonomous computational prioritisation of colorectal cancer vulnerabilities via multi-scale AI swarms

This paper introduces Octopus, a neuro-symbolic multi-agent framework that autonomously prioritizes colorectal cancer vulnerabilities by bridging agentic hypothesis generation with rigorous statistical validation, successfully identifying IGF2 as a target for 5-Fluorouracil resistance and validating its impact on tumor growth and patient survival.

Baker, C., Ren, T., Rafferty, K., Wang, H., McDade, S.2026-07-10
📄 cancer biology

Therapeutic targeting of MYC- and MYCN-driven medulloblastoma with a novel MYC degrader molecule

This study demonstrates that UNSW-SC-22, a novel brain-penetrant MYC/MYCN degrader, effectively suppresses tumor growth and prolongs survival in preclinical models of aggressive medulloblastoma, either as a monotherapy or in combination with HDAC inhibitors.

Ng, S. W., Gadde, S., Chung, N.-y., Wang, Q., Doughty, L., Nero, T. L., Jayatilleke, N., Seneviratne, J., Carter, D. R. (…)2026-07-10
📄 cancer biology

A single chromosome 3p break initiates clear cell renal cell carcinoma evolution

This study demonstrates that a single DNA double-strand break on chromosome 3p initiates clear cell renal cell carcinoma by creating a fitness bottleneck that drives adaptive genomic evolution, including recurrent aneuploidies and metabolic reprogramming, ultimately leading to malignant transformation.

Dahiya, R., van Belzen, I. A. E. M., Liao, C., Kumar, A., Lin, Y.-F., Ko, A., Mennie, A. K., Aleksandrovic, E., Zhou, J. (…)2026-07-10
📄 cancer biology

Quantifying target antigen-dependent CAR T-cell performance against AML

By integrating mathematical modeling with Bayesian inference and in vitro data, this study establishes a validated quantitative framework that reveals how specific target antigens (CD33, CD123, CD371) differentially influence CAR T-cell expansion dynamics and efficacy against TP53-deficient AML, challenging the assumption of uniform therapeutic performance.

Shah, S., Mueller, J., Vogel, E., Raatz, M., Boettcher, S., Traulsen, A., Manz, M. M., Altrock, P. M.2026-07-09
📄 cancer biology

Immunogenic tumor mass dormancy as a driver of persistent residual lesions in immunotherapy-treated melanoma

This study reveals that persistent residual lesions in melanoma patients treated with immunotherapy are driven by immunogenic tumor mass dormancy, characterized by a balance between ongoing tumor cell proliferation and immune-mediated cell death, rather than by cellular quiescence.

Shi, Y., Maliga, Z., Vallius, T., Pant, S. M., Pelletier, R., Kobs, B., Solanky, P., He, Y., Van Allen, E., Santagata, S (…)2026-07-09
📄 cancer biology

A DMT1-dependent iron-endoplasmic reticulum-extracellular matrix axis regulates cancer cell invasion

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.

Asif, A., Panjwani, K., Nair, K., Smith, P., Dancan, O., Crosbourne, I., DeLuca, J., Humphrey, T., Ramos, R. B., Corr, D (…)2026-07-09
📄 cancer biology

Modeling the metabolic heterogeneity of high-grade serous ovarian cancer solid tumors in 3D Microphysiological systems

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.

Manan Mejias, P. M., Boonpattrawong, N., Berube, M., Letts, E. K., Reed-McBain, F., Peraza Munuzuri, A. S., Vazquez, Y. (…)2026-07-09
📄 cancer biology

Functional Data Analysis of Spatial Clustering Identifies Prognostic T Cell Patterns in Ovarian Cancer

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.

Sakitis, C. J., Liao, D., Reid, B. M., Townsend, M. K., Schildkraut, J. M., Lawson, A. B., Tworoger, S. S., Terry, K. L. (…)2026-07-09