Project details

Our previous single-cell transcriptomic study on circulating white cells demonstrated that immune cell crosstalk is an indicator of metastatic fate, and can be used to diagnose stable versus progressive metastatic disease (Mangiola et al., Biorxiv, 2022).

This project will integrate multimodal data from single-cell proteomics, transcriptomics, multiplex cytokine blood profiling and spatial transcriptomics to track the metastatic spread in breast cancer patients using immune markers.

You will use data integration and inference methods to estimate associations in cell-type abundance, surface and secreted protein abundance with the disease state and other clinical factors. You will have the opportunity to use public methods, and develop new methodologies. 

About our research group

The Papenfuss lab undertakes computational biology and bioinformatics research in the Bioinformatics division at WEHI. We develop and apply mathematical, statistical and computational approaches to make sense of different types of omics data from cancer in order to drive discoveries. A key focus of the lab’s understanding is the molecular changes in cancers as they develop and progress. 

Dr Mangiola’s work includes the development of statistical models to analyse single-cell omics compositional data (Mangiola et al., 2022). He introduced the concept of tidy transcriptomics (Mangiola et al., 2021), led a study on immuno-diagnostics of metastatic breast cancer (Mangiola et al., 2022) and lead/contributed to the study of immune profiles and metastatic evolution in breast and prostate cancer.

We collaborate with local leading biologists (e.g. Dr Pal, Professors Bedoui and Kallies), and local and international statisticians and machine learning experts (e.g. Professor Speed, Associate Professor Vehtari).