PhD Project: Reprogramming the Cancer Cell Translatome to Overcome Chemotherapy Resistance

Supervisors: A/Prof Christine Chaffer, Dr Heloisa Zaccaron Milioli

Lab: Chaffer Lab - Cancer Plasticity & Dormancy Program

Overview:

Chemotherapy resistance remains one of the most significant unresolved challenges in oncology. Although many cancers initially respond to treatment, a subset of cells can survive by activating stress-adaptation programs. These resilient cells often acquire more aggressive behaviours and ultimately drive disease progression, metastasis and relapse. Preventing stress-adapting programs is likely to lead to therapeutic strategies to prevent the emergence of chemotherapy-resistant disease.

Our laboratory is positioned to uncover the non-genetic mechanisms that enable cancer cells to adapt and survive under therapeutic pressure. In particular, we focus on the largely underexplored cancer cell translatome – the machinery that determines how mRNAs are translated into proteins. Compared to genetic changes, translational regulation is rapid, dynamic, and uniquely capable of rewiring the proteome, giving cancer cells a powerful survival advantage during therapy exposure. By leveraging unique resistance models and state-of-the art technologies – including polysome profiling, Ribo/RNA-Seq, proteomics, and integrative bioinformatics – we are systematically mapping the translational rewiring events that drive therapy resistance. 

This project aims to (1) define the mRNA translational programs that enable cancer cells to resist therapeutic stress, and (2) identify and validate targetable vulnerabilities of the cancer cell translatome to prevent or overcome therapy resistance, leading to more effective strategies to eradicate cancer.

We are recruiting on a rolling basis, please reach out via email if you have any questions h.milioli@garvan.org.au.

Publications:

• San Juan et al (2022) Targeting phenotypic plasticity prevents metastasis and the development of chemotherapy-resistant disease. MedRxiv, 

• Burkhardt, et al (2022) Mapping phenotypic plasticity upon the cancer cell state landscape using manifold learning. Cancer discovery 

• Venkat et al. (2025) AAnet resolves a continuum of spatially-localized cell states to unveil intratumoral heterogeneity. Cancer Discovery

Opportunities:

• Supportive and collaborative research environment focused on impactful, publication-quality science.

• Collaborative multidisciplinary team of molecular biologists, computational scientists, and clinicians at the Garvan Institute

• Training in cutting-edge methods including Ribo/RNA-Seq and integrative bioinformatics, aligned with advanced therapy-resistant lab models.