Independent education resourceInformation here does not replace care from a qualified health professional.
Peptide Therapy GuideClear peptide education

Educational guide

Researchers link 9 blood proteins to breast cancer and suggest 3 drugs for repurposing

Can proteins in your blood predict and help treat breast cancer? A new large-scale study uncovers key biomarkers and connects them to existing drugs, offering hope for targeted therapies. Study: Genetic associations of plasma proteins and breast cancer identif

Written by Peptide Therapy Guide Editorial Team
For education only

This guide cannot diagnose a condition or recommend a personal treatment plan. Discuss medical questions with a qualified professional.

Can proteins in your blood predict and help treat breast cancer? A new large-scale study uncovers key biomarkers and connects them to existing drugs, offering hope for targeted therapies.

In a recent study in the journal Communication Biology, researchers employed a novel combined Mendelian randomization (MR) analysis to identify 62 plasma proteins (including 9 with robust support, 13 with medium support, and 40 with limited support) associated with breast cancer and its Luminal A or B subtypes.

Unlike previous approaches using only a single MR analysis on limited cohorts, this research used both two-sample MR (TSMR) and summary-data-based MR (SMR) on a cohort of nearly 250,000 participants.

Findings from both human models revealed 9 robust and 13 medium-confidence plasma protein genes. Robustly associated proteins include: 1. Breast cancer – ULK3, ASIP, CSK, TLR1; 2. Luminal A – ADH5, ULK3, SARS2, UBE2N; 3. Luminal B – PEX14. Six of the nine robust proteins were supported by murine phenotype data, confirming their relevance to immune and hematopoietic systems.

However, the reduction in CSK and ULK3 expression in cancer versus healthy tissue was observed in human tissue via immunohistochemistry.

Three existing drugs (TG100801, Hydrochlorothiazide, and Imatinib) were identified as genetically or biologically linked to these proteins, but their mechanisms of action and therapeutic relevance in breast cancer remain to be elucidated.

Background

Breast cancer (BC) is a serious non-communicable disease caused by uncontrolled breast cell growth. BC and its four subtypes cause the most cancer-related deaths among women globally (24.5% incidence; 15.5% mortality, 685,000 deaths).

Recent research has turned to plasma proteins for insight due to their roles in disease biomarker identification. Past studies have shown plasma protein dysregulation in diseases like IBD and CVD.

Mendelian randomization (MR) studies use gene variation to identify causal effects between exposures and outcomes. Despite progress, past BC research has struggled with small sample sizes, limited durations, and over-reliance on single MR methods.

About the Study

This study overcomes previous limitations by integrating MR methods to examine plasma protein variation, drug discovery, and biological mechanisms.

Genotyping data came from the Breast Cancer Association Consortium (247,173 samples), and plasma proteome data came from deCODE (4,907 proteins from 35,559 individuals). Inclusion criteria for pQTLs were: (i) Genome-wide significance (P < 5 × 10⁻⁸); (ii) Outside MHC region (chr6, 25.5–34.0 Mb); (iii) Distinct LD clumping (r² < 0.01, 10,000 kb window); (iv) Cis-acting pQTLs.

MR analyses treated plasma proteins as exposures and BC subtypes as outcomes. Associations were validated via colocalization to test robustness. GeneMANIA was used for interaction mapping; pathway analysis clarified biological functions.

Mouse Genome Informatics and TICI databases provided mouse knockout and immune infiltration data. Notably, while mouse models supported gene relevance, CSK and ULK3 expression changes were seen only in human tissues. Drug candidates were matched using DrugBank, DGIdb, CheMBL, and the Therapeutic Target Database.

Study Findings

Of 4,907 proteins, 1,815 met pQTL criteria and were analyzed. Sixty-two showed an association with breast cancer or its subtypes.

Colocalization revealed: - 9 robust proteins (e.g., ULK3, ASIP, CSK, TLR1, ADH5, SARS2, UBE2N, PEX14), - 13 medium, - 40 limited. These genes play roles in immunity and blood cell regulation.

Overexpression of CSK and ULK3 in MCF-7 cells inhibited proliferation and migration, confirmed by in vitro tests. High ULK3 expression was also associated with prolonged recurrence-free survival, particularly in Luminal A breast cancer. GO analysis showed enrichment in nuclear transport, blood coagulation, and nucleocytoplasmic transport.

In cellular components (CC), the endoplasmic reticulum lumen was enriched (p = 0.001). For molecular functions (MF), serine-type endopeptidase inhibitor activity was significant (p = 0.0005). Disease Ontology (DO) analysis showed enrichment in nephritis (p = 0.026), glomerulonephritis (p = 0.014), lipid metabolism disorders (p = 0.007), and cervical squamous cell carcinoma (p = 0.017).

Three drugs (TG100801, Hydrochlorothiazide, and Imatinib) were flagged for their genetic associations with the robust proteins ULK3, CSK, and ADH5, but their clinical effectiveness in breast cancer has not been established and requires further study.

Limitations include data mostly from individuals of European ancestry and protein constraints limited to those in the deCODE database. Early-phase drugs might also have been missed.

Conclusions

This large-scale study identified 62 plasma proteins associated with breast cancer, including 9 with strong evidence. It outlined potential pathways and functions contributing to tumor behavior, such as cell migration and proliferation.

A comprehensive drug database search identified TG100801, Hydrochlorothiazide, and Imatinib as potential candidates for future breast cancer therapies.

High expression of ULK3 was associated with improved recurrence-free survival, suggesting potential prognostic value in Luminal A breast cancer. These discoveries deepen our understanding of BC biology and support the development of targeted, personalized therapies.

This study underscores the value of integrating genetic, functional, and pharmacological data in drug discovery.

  • Quan, L., Luo, X., Meng, C. et al. Genetic associations of plasma proteins and breast cancer identify potential therapeutic drug candidates. Commun Biol 8, 610 (2025). https://www.nature.com/articles/s42003-025-08046-3

Connected reading

Helpful context for this guide

Source-derived material selected through this article’s indexed topics.

Related questions

01What supplements really work?

The bulk of vitamins and supplements containing fish oil, biotin, and vitamins A, C, and E can potentially promote nail and hair growth. You can find dietary supplements with higher concentrations of vitamins and minerals that aid skin, hair, and nail health. Fish oil supplements make nails and hair shiny. Fish oil also serves as an agent that can decrease signs of aging. If sun exposure damages the skin, the omega-3 fatty acids in fish oil can help. Biotin, also known as B7, increases hair density and strengthens it. It is found naturally in bananas, eggs, and milk. Vitamins are vital for skin health as well. Vitamin A reduces acne flairs and helps with changes due to aging like wrinkling. A vitamin A deficiency may increase the risk of acne because it becomes difficult for dead skin to slough off hair follicles, blocking pores. Vitamin B lowers the risk of precancerous growths and nonmelanoma skin cancer. Vitamin C is an antioxidant. It leads the fight against free radicals to help stimulate collagen and brighten skin. It also helps to prevent the formation of unneeded melanin that causes uneven skin pigmentation.

Source: www.medicinenet.com ↗
02Please can you give an overview of the current drug discovery paradigm? In what ways do you think it needs to be leaner?

With the current drug discovery paradigm, it takes up to 15 years to translate an idea, such as hypothesizing a certain protein is important in a disease and testing this with targeting the protein with a drug, all the way through to proof of concept. The drug has to be filed with the regulatory authorities, having done all the safety and efficacy testing. It's a long process and it's also very costly. Estimates vary, but it's currently reckoned to cost over 1 billion dollars per drug. That’s partly because you have to pay for all the drugs that didn't make it. By the time you've taken a protein target and you've made a whole load of molecules that affect that target in the way you want them to, you've probably already spent a couple of years on it and then you have to take the best molecule through the appropriate safety testing in animals before proceeding to phase 1 testing in people. Even if you get to phase 1 testing, where you are just giving it to human volunteers for the first time, not even patients, about 95% of the compounds at the stage then fail to make it all the way through to the market. So, you’ve only got a 5% success rate. The odds are not good and, essentially, it is why so many companies have had to merge because, over time, this is becoming less and less sustainable as a business model.

Source: www.news-medical.net ↗
03You’ve experienced ApconiX both from within and as a biopharma collaborator through Redx. How has your experience in both biopharma and safety science influenced the way you develop AI tools for drug discovery teams?

The tools we are building and applying at ApconiX are currently internal-facing, supporting our scientists and collaborators in delivering thoroughly researched, evidence-based, and authoritative toxicology information in a timely manner. Even though I did not directly interact with ApconiX while I was at Redx, my experience in biopharma strongly shapes how I think about usability. At ApconiX, we constantly consider how others will interpret and use the data and insights we generate. For example, our early SAR work around seizure liability has identified preliminary relationships between chemical substructural patterns and seizure risk. Although this work is in its infancy, these are the kinds of insights that discovery chemists could interpret directly and apply from day one to help mitigate risk. For target safety assessments, the ApconiX data science team have collated a large data sets including our Acuity expression atlas for expression data, enabling our data scientists and bioinformaticians to generate highly informative, data-driven insights and visualizations. By leveraging AI tools, such as LLM workflows and agents, we can efficiently support consistent and thorough analyses, making safety information more accessible and actionable.

Source: www.news-medical.net ↗
04What are carbs?

Your weight loss plan should keep you healthy and strong as you lose the extra weight. Many plans include a diet low in carbohydrates. Carb cycling is a method of optimizing your carbohydrate intake to meet your needs while dieting, fasting, and working out. When you're carb cycling, you consume carbs to meet your needs on some days and avoid them on other days. The aim of carb cycling is to consume carbohydrates when your body needs them and exclude them at other times. Such strategies in your diet plan can help your weight loss efforts. Carbohydrates, or carbs, are a significant part of the average human diet. Along with proteins and fats, they make up the bulk of your daily meals. Most carbohydrates are broken down by your body into glucose to provide energy for your cells and tissues. Carbohydrates in your diet are of three types — sugars, starches, and fiber. Sugars are simple carbs. Glucose, sugar (sucrose), lactose found in milk, and fructose found in fruits, are naturally occurring sugars. Your body metabolizes these molecules rapidly to yield energy. Starches are complex carbs. They're large molecules that consist of hundreds of molecules of simple sugars joined together. Your body needs to break them down to release energy. Starches are found in bread, potatoes, peas, corn, cereals, and pasta. Fiber is also a complex carbohydrate. Human bodies can't break down these large molecules, so they provide no energy. They're usually excreted as they are in the feces. They add bulk to your meal, so you feel full. Fiber in the diet helps avoid constipation and lowers blood sugar and cholesterol levels. Carbohydrates are an essential part of your diet. A typical diet provides 45% to 65% of its calories from carbohydrates. If you have 2,000 calories a day, you should have about 275 grams of carbohydrates. Always try to choose healthy foods for your carb intake:

Source: www.medicinenet.com ↗
05Why are these clinical trial results so groundbreaking?

There are no targeted treatments approved for pancreas cancer, and we haven't had any significant progress for a long time. We've only come up with different chemotherapy combinations, and those are only moderately effective. This new treatment is staggeringly better than chemotherapy. Usually, when we think of an improvement in pancreatic cancer survival, we think of 25% improvement. This medication actually doubled survival in patients with advanced disease. We have patients who participated in the trial who are still alive, which is unheard of because the five-year survival rate for pancreatic cancer patients is only 13%-14%. If the drug is approved by the FDA, it will most likely become the new standard of care for advanced pancreatic cancer and could replace chemotherapy as a first-line treatment.

Source: www.news-medical.net ↗
P

About the author

Peptide Therapy Guide Editorial Team

Editorial team for Peptide Therapy Guide.

View all articles →