---
title: "RNA-guided contrastive learning improves histology-based ER/PR/HER2 prediction"
id: "biorxiv-1-rna-guided-contrastive-learning-enhances-patient-level-prediction-from-histology"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-1-rna-guided-contrastive-learning-enhances-patient-level-prediction-from-histology"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1?rss=1"
published_at: "2026-09-30T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# RNA-guided contrastive learning improves histology-based ER/PR/HER2 prediction
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-1-rna-guided-contrastive-learning-enhances-patient-level-prediction-from-histology
- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1?rss=1)
- **Published At:** 2026-09-30T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The study pairs a whole-slide vision transformer (GigaPath) with bulk **RNA-sequencing** using a training-time contrastive objective to improve molecular receptor classification from routine H&E whole-slide images (WSIs). - RNA supervision is applied only during training so inference requires **histology-only** WSIs and no transcriptomic data. - Instead of building a dedicated transcriptomics encoder, the authors applied a **BioBERT** pretrained text encoder and a gene-sentence encoding to TCGA-BRCA bulk RNA-seq profiles. - Under five-fold cross-validation, this RNA-guided pretraining consistently increased AUROC for **estrogen receptor (ER)**, **progesterone receptor (PR)**, and **HER2** compared with a baseline without contrastive pretraining. - The RNA-guided approach also reproducibly introduced receptor-relevant structure into the learned slide representations, suggesting biologically meaningful alignment between transcriptomic programs and histologic features. - External cohort evaluation revealed a receptor-dependent divergence in generalization: improvements for **ER** and **PR**, which are governed by broad, multi-gene luminal transcriptional programs, generalized robustly to independent datasets. - By contrast, the apparent AUROC gain for **HER2**, which reflects focal ERBB2 amplification rather than a broad transcriptional program, concealed a marked loss of classification sensitivity at the chosen operating threshold on external cohorts. - The authors conclude that training-time transcriptomic supervision is a practical method to enhance histology-only molecular subtyping, but that **gene-selection strategy** and the biological basis of the molecular alteration (broad transcriptional program versus focal genomic event) determine what the vision model can learn to recognize. - No competing interests were declared. - The work is reported as a preprint and has not yet been peer reviewed.
## Clinical Analysis & Structured Key Points
[](https://www.biorxiv.org/cdn-cgi/content?id=YLlJsie.kK6LGsEOnR7Sa9JD2RiKmuwRitE66SFAwSY-1790820113.427096-1.2.1.1-P2qLOG_u0bsmQ3plSIuC9FDPK7dFpGJU.lRcbEsgAM1gTtMJX.aJ3vtb3wELcCOz) [Skip to main content](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1?rss=1#main-content) [![bioRxiv](https://www.biorxiv.org/sites/default/files/biorxiv_article_logo.jpg)](https://www.biorxiv.org/) * [Home](https://www.biorxiv.org/) * [Submit](https://www.biorxiv.org/submit-a-manuscript) * [FAQ](https://www.biorxiv.org/about/FAQ) * [Blog](https://connect.biorxiv.org/news/) * [ALERTS / RSS](https://www.biorxiv.org/content/alertsrss) * [Resources](https://connect.biorxiv.org/resources/) * [About](https://www.biorxiv.org/content/about-biorxiv) * [Channels](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1?rss=1) * [4D Nucleome](https://connect.biorxiv.org/relate/content/66) * [Academia Sinica](https://connect.biorxiv.org/group/content/38) * [Advances in Genome Biology and Technology (AGBT) General Meeting 2016 #AGBT16](https://connect.biorxiv.org/relate/content/10) * [Albert Einstein College of Medicine](https://connect.biorxiv.org/group/content/4) * [Aligning Science Across Parkinson's (ASAP)](https://connect.biorxiv.org/relate/content/195) * [Allen Institute for Cell Science](https://connect.biorxiv.org/relate/content/71) * [Arc Institute](https://connect.biorxiv.org/relate/content/224) * [Babraham Institute](https://connect.biorxiv.org/relate/content/197) * [BICCN/BICAN](https://connect.biorxiv.org/relate/content/208) * [BioImaging North America](https://connect.biorxiv.org/relate/content/194) * [Biology of Genomes 2016 #BOG16](https://connect.biorxiv.org/relate/content/19) * [Breakthrough Discoveries for Thriving with Bipolar Disorder](https://connect.biorxiv.org/relate/content/236) * [Brown University](https://connect.biorxiv.org/group/content/9) * [California Institute of Technology](https://connect.biorxiv.org/group/content/32) * [Carnegie Mellon University](https://connect.biorxiv.org/group/content/19) * [Case Western Reserve University](https://connect.biorxiv.org/group/content/36) * [Central Oxford Structural Microscopy and Imaging](https://connect.biorxiv.org/relate/content/143) * [Centre for Microbiology and Environmental Systems Science](https://connect.biorxiv.org/relate/content/190) * [Chan Zuckerberg Biohub](https://connect.biorxiv.org/relate/content/121) * [Columbia University](https://connect.biorxiv.org/group/content/27) * [Donders Institute for Brain, Cognition and Behaviour](https://connect.biorxiv.org/relate/content/184) * [DREAM](https://connect.biorxiv.org/relate/content/153) * [Drug Development and Clinical Therapeutics](https://connect.biorxiv.org/relate/content/52) * [ENCODE](https://connect.biorxiv.org/relate/content/177) * [Ernst Strüngmann Institute (ESI) for Neuroscience](https://connect.biorxiv.org/relate/content/211) * [European Molecular Biology Laboratory (EMBL)](https://connect.biorxiv.org/relate/content/159) * [Francis Crick Institute](https://connect.biorxiv.org/relate/content/88) * [Fred Hutchinson Cancer Center](https://connect.biorxiv.org/group/content/28) * [Georgia Institute of Technology](https://connect.biorxiv.org/group/content/20) * [Harvard Program in Therapeutic Sciences](https://connect.biorxiv.org/relate/content/151) * [The Howard Hughes Medical Institute (HHMI)](https://connect.biorxiv.org/relate/content/227) * [Human Cell Atlas](https://connect.biorxiv.org/relate/content/163) * [Human Pangenome Reference Consortium (HPRC)](https://connect.biorxiv.org/relate/content/215) * [IMO Workshop](https://connect.biorxiv.org/relate/content/8) * [Impact of Genomic Variation on Function (IGVF)](https://connect.biorxiv.org/relate/content/214) * [Institut Pasteur](https://connect.biorxiv.org/relate/content/235/channel) * [Institute of Science and Technology Austria](https://connect.biorxiv.org/group/content/12) * [International Human Epigenome Consortium (IHEC)](https://connect.biorxiv.org/relate/content/219) * [International Mouse Phenotyping Consortium (IMPC)](https://connect.biorxiv.org/relate/content/185) * [Iowa State University](https://connect.biorxiv.org/group/content/6) * [Johns Hopkins University](https://connect.biorxiv.org/group/content/47) * [Mathematical Oncology](https://connect.biorxiv.org/relate/content/1) * [Micron Oxford](https://connect.biorxiv.org/relate/content/116) * [Michigan State University](https://connect.biorxiv.org/group/content/7) * [Morgridge Institute](https://connect.biorxiv.org/group/content/57) * [National Taiwan University](https://connect.biorxiv.org/group/content/39) * [NCI Cancer Systems Biology Consortium](https://connect.biorxiv.org/relate/content/210) * [NF Open Science Initiative](https://connect.biorxiv.org/relate/content/213) * [NCI Human Tumor Atlas Network](https://connect.biorxiv.org/relate/content/171) * [Neuromatch Conference](https://connect.biorxiv.org/relate/content/209) * [NeurotechEU](https://connect.biorxiv.org/relate/content/189) * [North Carolina State University](https://connect.biorxiv.org/group/content/37) * [Northeastern University](https://connect.biorxiv.org/group/content/54) * [Oregon Health & Sciences University](https://connect.biorxiv.org/group/content/22) * [RNA Therapeutics Institute at UMass Chan Med School](https://connect.biorxiv.org/relate/content/243) * [Rosetta Commons](https://connect.biorxiv.org/relate/content/191) * [Rutgers University](https://connect.biorxiv.org/group/content/31) * [SeroNet](https://connect.biorxiv.org/relate/content/192) * [Simons Foundation Autism Research Initiative (SFARI)](https://connect.biorxiv.org/relate/content/74) * [Society for Molecular Biology and Evolution #SMBE2016](https://connect.biorxiv.org/relate/content/29) * [Somatic Cell Genome Editing Program](https://connect.biorxiv.org/relate/content/167) * [Somatic Mosaicism across the Human Tissues Network](https://connect.biorxiv.org/relate/content/222) * [SPARC](https://connect.biorxiv.org/relate/content/187) * [Stowers Institute for Medical Research](https://connect.biorxiv.org/group/content/3) * [Stockholm University](https://connect.biorxiv.org/group/content/14) * [Tel Aviv University](https://connect.biorxiv.org/group/content/8) * [The Michael J. Fox Foundation](https://connect.biorxiv.org/relate/content/207) * [The Rockefeller University](https://connect.biorxiv.org/group/content/2) * [The Sainsbury Laboratory](https://connect.biorxiv.org/relate/content/98) * [The Whitehead Institute](https://connect.biorxiv.org/relate/content/212) * [University of Connecticut Health Center](https://connect.biorxiv.org/group/content/16) * [University of California, Berkeley](https://connect.biorxiv.org/group/content/13) * [University of California, San Diego](https://connect.biorxiv.org/group/content/41) * [University of California, San Francisco](https://connect.biorxiv.org/group/content/10) * [University of Chicago](https://connect.biorxiv.org/group/content/42) * [University of Geneva](https://connect.biorxiv.org/group/content/26) * [University of Guelph](https://connect.biorxiv.org/group/content/23) * [University of Hong Kong](https://connect.biorxiv.org/group/content/29) * [University of Illinois Chicago](https://connect.biorxiv.org/group/content/43) * [University of Iowa](https://connect.biorxiv.org/group/content/24) * [University of Kansas](https://connect.biorxiv.org/group/content/33) * [University of Massachusetts Chan Medical School](https://connect.biorxiv.org/group/content/44) * [University of New South Wales](https://connect.biorxiv.org/group/content/25) * [University of Ottawa](https://connect.biorxiv.org/group/content/35) * [University of Sydney](https://connect.biorxiv.org/group/content/50) * [Vanderbilt University](https://connect.biorxiv.org/group/content/30) * [Vienna BioCenter](https://connect.biorxiv.org/relate/content/186) * [Washington University in St. Louis](https://connect.biorxiv.org/group/content/11) * [Weizmann Institute of Science](https://connect.biorxiv.org/group/content/15) * [Yale University](https://connect.biorxiv.org/group/content/53) Search for this keyword [Advanced Search](https://www.biorxiv.org/search) New Results Follow this preprint # RNA-guided contrastive learning enhances patient-level prediction from histology [ View ORCID Profile](http://orcid.org/0009-0008-1663-1962)Anqi Zou, Elaine Huang, Qiyou Wu, Mollie E. Barnard, [ View ORCID Profile](http://orcid.org/0000-0001-8019-7998)Chao Zhang doi: https://doi.org/10.64898/2026.09.24.754149 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. Anqi Zou 1 Boston University Chobanian & Avedisian School of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Anqi%2BZou%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Zou%20A&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AAnqi%2BZou%2B) * [ORCID record for Anqi Zou](http://orcid.org/0009-0008-1663-1962 "Open in new tab") Elaine Huang 1 Boston University Chobanian & Avedisian School of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Elaine%2BHuang%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Huang%20E&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AElaine%2BHuang%2B) Qiyou Wu 2 Northeastern University * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Qiyou%2BWu%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Wu%20Q&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AQiyou%2BWu%2B) Mollie E. Barnard 1 Boston University Chobanian & Avedisian School of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Mollie%2BE.%2BBarnard%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Barnard%20ME&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AMollie%2BE.%2BBarnard%2B) Chao Zhang 1 Boston University Chobanian & Avedisian School of Medicine; * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Chao%2BZhang%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Zhang%20C&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3AChao%2BZhang%2B) * [ORCID record for Chao Zhang](http://orcid.org/0000-0001-8019-7998 "Open in new tab") * For correspondence: chz2009@bu.edu * [Abstract](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5828838/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5828838/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5828838/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5828838/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## Abstract Predicting molecular receptor status, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), directly from routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) could reduce reliance on costly immunohistochemistry, but image-only models have no access to the transcriptomic programs that define these subtypes. Here we show that coupling a whole-slide vision transformer (GigaPath) with bulk RNA-sequencing profiles through a training-time-only contrastive objective improves receptor-status classification from WSIs alone, without requiring any RNA-seq data at inference. Rather than training a dedicated bulk-transcriptomics encoder, we purpose the gene-sentence encoding and pretrained text encoder from BioBERT1 and apply them to bulk RNA-seq profiles from The Cancer Genome Atlas breast cancer cohort (TCGA-BRCA). Under five-fold cross-validation, this RNA-guided pre-training consistently improved AUROC for ER, PR, and HER2 relative to a contrastive-pre-training-free baseline and reproducibly introduced receptor-relevant structure into the learned slide representation. However, evaluation on independent external cohorts revealed a striking, receptor-dependent divergence: gains for ER and PR, both governed by broad, multi-gene luminal transcriptional programs, generalized robustly, whereas the apparent AUROC improvement for HER2, driven by focal ERBB2 amplification rather than a coordinated transcriptional signature, masked a severe loss of classification sensitivity at the operating threshold. These findings establish training-time transcriptomic supervision as a practical route to enhancing histology-only molecular subtyping, while showing that gene-selection strategy, and not model architecture alone, determines which molecular alterations such supervision can teach a vision model to recognize. ### Competing Interest Statement The authors have declared no competing interest. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY-NC 4.0 International license](http://creativecommons.org/licenses/by-nc/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. [Donate to openRxiv ](https://www.zeffy.com/en-US/donation-form/donate-to-make-a-difference-10981) [ Back to top](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1?rss=1#page) [ Previous](https://www.biorxiv.org/content/10.64898/2026.09.26.754322v1 "Immune Reconstitution and Antigenic Exposure History Shape Virus-Specific Humoral Immunity in People with HIV") Posted September 30, 2026. [ Download PDF](https://www.biorxiv.org/content/10.64898/2026.09.24.754149v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/09/30/2026.09.24.754149.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) RNA-guided contrastive learning enhances patient-level prediction from histology Anqi Zou, Elaine Huang, Qiyou Wu, Mollie E. Barnard, Chao Zhang bioRxiv 2026.09.24.754149; doi: https://doi.org/10.64898/2026.09.24.754149 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. Share This Article: Copy [![Twitter logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/twitter.png)](https://www.biorxiv.org/highwire_log/share/twitter?link=http%3A%2F%2Ftwitter.com%2Fshare%3Furl%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.09.24.754149v1%26text%3DRNA-guided%2520contrastive%2520learning%2520enhances%2520patient-level%2520prediction%2520from%2520histology "Share this on Twitter") [![Facebook logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/fb-blue.png)](https://www.biorxiv.org/highwire_log/share/facebook?link=http%3A%2F%2Fwww.facebook.com%2Fsharer.php%3Fu%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.09.24.754149v1%26t%3DRNA-guided%2520contrastive%2520learning%2520enhances%2520patient-level%2520prediction%2520from%2520histology "Share on Facebook") [![LinkedIn logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/linkedin-32px.png)](https://www.biorxiv.org/highwire_log/share/linkedin?link=http%3A%2F%2Fwww.linkedin.com%2FshareArticle%3Fmini%3Dtrue%26url%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.09.24.754149v1%26title%3DRNA-guided%2520contrastive%2520learning%2520enhances%2520patient-level%2520prediction%2520from%2520histology%26summary%3D%26source%3DbioRxiv "Publish this post to LinkedIn") [![Mendeley logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/mendeley.png)](https://www.biorxiv.org/highwire_log/share/mendeley?link=http%3A%2F%2Fwww.mendeley.com%2Fimport%2F%3Furl%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.09.24.754149v1%26title%3DRNA-guided%2520contrastive%2520learning%2520enhances%2520patient-level%2520prediction%2520from%2520histology "Share on Mendeley") [ Citation Tools](https://www.biorxiv.org/ "Citation Tools") [ Get QR code](https://connect.biorxiv.org/qr/2026.09.24.754149) * [Tweet Widget](http://twitter.com/share?url=https%3A//www.biorxiv.org/content/10.64898/2026.09.24.754149v1&count=horizontal&via=&text=RNA-guided%20contrastive%20learning%20enhances%20patient-level%20prediction%20from%20histology&counturl=www.biorxiv.org/content/10.64898/2026.09.24.754149v1 "Tweet This") Reviews and Context 0 Comment 0 TRIP Peer Reviews 0 Community Reviews 0 Automated Services 0 Blogs/Media 0 Author Videos **Subject Areas** [**All Articles**](https://www.biorxiv.org/content/early/recent) * [Animal Behavior and Cognition](https://www.biorxiv.org/collection/animal-behavior-and-cognition) (8061) * [Biochemistry](https://www.biorxiv.org/collection/biochemistry) (18858) * [Bioengineering](https://www.biorxiv.org/collection/bioengineering) (15007) * [Bioinformatics](https://www.biorxiv.org/collection/bioinformatics) (44707) * [Biophysics](https://www.biorxiv.org/collection/biophysics) (22704) * [Cancer Biology](https://www.biorxiv.org/collection/cancer-biology) (19849) * [Cell Biology](https://www.biorxiv.org/collection/cell-biology) (27050) * [Clinical Trials](https://www.biorxiv.org/collection/clinical-trials) (138) * [Developmental Biology](https://www.biorxiv.org/collection/developmental-biology) (14036) * [Ecology](https://www.biorxiv.org/collection/ecology) (21147) * [Epidemiology](https://www.biorxiv.org/collection/epidemiology) (2067) * [Evolutionary Biology](https://www.biorxiv.org/collection/evolutionary-biology) (25544) * [Genetics](https://www.biorxiv.org/collection/genetics) (16228) * [Genomics](https://www.biorxiv.org/collection/genomics) (23602) * [Immunology](https://www.biorxiv.org/collection/immunology) (18799) * [Microbiology](https://www.b
## Related Clinical Research

- [Pope Leo XIV Diagnosed with Lung Adenocarcinoma: Key Insights](https://medichelpline.com/clinical-feed/medical-news-today-0-pope-leo-lung-cancer-diagnosis-what-to-know-about-lung-adenocarcinoma.md)
- [Structured aerobic exercise linked to lower cancer recurrence and improved survival](https://medichelpline.com/clinical-feed/medical-news-today-0-aerobic-exercise-could-help-improve-outlook-after-cancer-treatment.md)
- [ICOS blockade reduces intratumoral Treg suppression in triple-negative breast cancer](https://medichelpline.com/clinical-feed/biorxiv-2-icos-blockade-alleviates-immune-suppression-in-breast-tumor-microenvironment.md)
- [SHROOM3 regulates leading-edge protrusion stability and Wnt/PCP-driven migration in breast cancer](https://medichelpline.com/clinical-feed/biorxiv-5-shroom3-promotes-leading-edge-protrusion-stability-and-wnt-planar-cell-polarity.md)
- [Induced proximity therapies: PROTACs, molecular glues and RIPTACs in oncology](https://medichelpline.com/clinical-feed/nature-3-induced-proximity-comes-of-age.md)

## Navigation
- [← Back to Oncology Feed](https://medichelpline.com/clinical-feed/oncology.md)
- [← All Clinical Specialties](https://medichelpline.com/clinical-feed.md)
## Medical & Regulatory Disclaimer

> [!CAUTION]
> MedicHelpline content is structured for research, educational, and professional discovery purposes. It does not constitute individual medical advice, clinical diagnosis, or treatment recommendations.
> Always verify dosing, contraindications, and regulatory alerts against official product labeling and primary regulatory sources before clinical decision-making.