ProCan Research
Deeper Insights | Mechanisms of Action | Biomarker Discovery
Supporting research outcomes globally with our world-leading proteomics capabilities.
ProCan Technologies helps biotech innovators determine mechanisms of action, develop biomarker panels, and discover new drug targets. We can analyse the proteomes of cell lines, organoids, and human or animal tissues. We also have an extensive database containing the proteomic profiles of over 30,000 human tumour samples. Talk to us about how we can enhance your oncology research projects.
Discover
New Drug Targets
ProCan’s unique and extensive database provides unprecedented opportunities for drug target discovery.
Develop
Biomarker Panels
We develop powerful biomarkers to offer extensive insights to complex research questions.
Determine
Mechanisms of Action
Our proteomics technology and expertise can analyse thousands of proteins simultaneously to elucidate complex networks and mechanisms.
Competitive Pricing
Why choose ProCan?
Included Services
Consultation
Start by consulting with ProCan’s team of medical oncologists, data scientists and technology experts who provide customised, affordable solutions.
Sample Preparation
Universal Sample Processing – small sample size, Fresh Frozen (FF) or Formalin Fixed Paraffin Embedded (FFPE) tissues, cell lines, patient-derived xenografts and organoids.
Data Generation
Using state-of-the-art mass spectrometers.
Data Analysis
ProCan bioinformaticians can answer specific questions—interrogating your data alone or providing insights from our powerful database which contains tens of thousands of clinically annotated cancer specimens.
Accelerate Your Research With Customised, World-leading Proteomics
Case Study
Immunotherapy Response in Melanoma
*AACR 2023. Manda S, Aref A et al. Abstract 5479: A six-protein signature predicts response and survival in patients with advanced cutaneous melanoma treated with immunotherapy
Study Design
ProCan has retrospectively analysed tissue samples
from two cohorts of patients with advanced
cutaneous melanoma, some of them treated with
immunotherapy.
Identifying the signature
The tissue samples were analysed using ProCan state-of-the-art technology to identify tissue proteins. Using one cohort as a training cohort, a list of proteins (proteomic signature) was selected using machine learning analyses that could
categorise patients into high- and low-risk groups
in terms of risk of death from melanoma. This
signature was validated in the second cohort and
showed similar prognostic power.
The proteomic signature is associated with response to immunotherapy
ProCan tested the predictive power of the proteomic signature. Using machine learning and sophisticated statistical modelling, the proteomic signature was found to be associated with response to immunotherapy and can therefore be used for immunotherapy regimen selection.