TARGET DISCOVERY WITH
MULTI-OMICS MULTIVARIATE ANALYSES

We're excited to share our approach to transforming cancer drug development and advancing precision oncology at BioTechX Europe 2024. Join our speaker session and poster presentation to explore how our research enhances the understanding of tumor biology and accelerates the development of targeted cancer treatments.

9 - 10 October 2024 | Messe Basel, Switzerland

Join Our Live Presentation

A novel approach to evaluate multi-omic multivariate drug target identification algorithms

Date & Time - October 9, 2024 | 2:50 – 3:10 pm
Presenter - Dr. Andreas Bolleyer | Senior Data Scientist
Location - Theatre 8

The goal of our research is the identification of novel molecular therapeutic targets in solid tumors in a multivariate multi-omic setting.

Identifying active modules on a PPI network
We analyze differential entity expression between tumor and matching normal tissue at the DNA, mRNA, protein, and phospho-protein levels, which are mapped to a protein-protein interaction network (PPI). From this structure we identify active modules – small subsets in which differentially expressed entities are enriched which allow for biological and functional validation of contained potential drug targets.

Augmenting the established methods
There are many methods to identify active modules using single-omic data, recently using PPI embedding or random-field Ising models. We will discuss how to extend these methods to our multi-omic setting. Measuring the performance of active module identification methods is challenging due to the lack of a ground truth. We tackle this with a new performance metric, using the given differential expression results and PPI topology.

Our Poster Lets You Dive Even Deeper

Survival analysis for active modules using learned representations


Date & Time - October 9, 2024 | 10:40 – 11:40 am
Presenter - Daniel Beck | VP Biomathematics & Bioinformatics
Poster Board No. - 1

Active Modules  
In the multivariate multi-omic biomolecule analysis-based detection of novel pharmacological cancer treatment targets in cancer and matching normal tissues, the identification of active modules has been an evolving trend. Such modules are models of sets of proteins which physically interact to perform molecular functions and participate in cellular processes driving cancer phenotypes.

Detection
Active modules can be detected from T/N tissues by partitioning PPIs according to the degree of differential T/N biomolecule expression. To determine which modules are the most relevant for downstream validation and targeting steps, we show an approach to utilize the progression free survival (PFS) data of the patients from whom the tissues were obtained to rank the modules.

Representation
Active modules are of varying size but contain up to 60 biomolecules of three to four omics-analysis modalities which prevents a classical Cox survival regression. We therefore use a three-layer GCN with a linear readout layer on top to embed the molecule variables of the modules into fixed-size, low-dimensional representations.

Output
The output of the GCN is a module-specific embedding of the tissue data. The resulting low-dimensional embedding is used as the input for the Cox proportional hazards model. From it we obtain χ2 statistics for each module embedding along with coefficients for each predictor which enable a survival-based ordering of the modules.

Novel Target ID based on Unique Data

We are a biotech company specializing in precision oncology. Our high-quality tumor tissue collection methods enable the discovery of novel cancer targets. By integrating biomathematics, bioinformatics, and cell biology, we design drug screening assays and partner with the pharmaceutical industry to develop precision cancer therapeutics.

Our Target ID in a Nutshell

Rapid sample processing preserving the molecular reality of cancer and multivariate analytics are the cornerstones of our multi-omics target ID approach.

DIVE DEEPER

Advancing Target Discovery

In this interview, Dr. Jobst Landgrebe, our Head of R&D and Chief Technology Strategist, shares how we take a unique approach to target discovery.

LEARN MORE

Meet the Indivumed Team at BioTechX 2024

Meet our Team at BioTechX

We're eager to share insights into the technical details of our target ID process and explore collaborative opportunities. Feel free to reach out for an engaging discussion! Check out our videos, latest news, our publications, and connect with our team.