Cancer cells tend to accumulate mutations, increasing tumour heterogeneity and complicating therapeutic interventions. Such genetic instability is frequently observed for example in breast, ovarian, prostate, and pancreatic cancers. Previously, we identified a long non-coding RNA, PNCTR, which is significantly upregulated in many advanced and metastatic cancers (https://doi.org/10.1016/j.molcel.2018.08.041). We demonstrated that PNCTR promotes cancer cell survival by sequestering the RNA-binding protein PTBP1 within the membraneless perinucleolar compartment (PNC; https://doi.org/10.1080/19491034.2024.2306777).
Building on our preliminary data, this PhD project will test the hypothesis that elevated expression of PNCTR in cancer cells is associated with a genetic rearrangement of its locus. The project includes three major aims:
Aim 1 (Rotation/Years 1-2): Elucidating genetic requirements for PNCTR expression in cancer. To identify mutations associated with increased PNCTR expression, we will mine publicly available cancer genome/exome and RNA sequencing data using bioinformatics and machine learning. We will initially focus on breast cancer datasets, due to the prevalence of genetic instability in this disease. This will be followed by systematic analyses of other tumour types to identify an extended set of PNCTR “driver” genes. Predictions will be validated using quantitative (q)PCR, fluorescence in situ hybridisation (FISH), and immunofluorescence (IF) assays in clinically relevant cancer cell lines.
Aim 2 (Years 2-3): Dissecting DNA repair pathways involved in PNCTR locus rearrangement. Our data suggest that tumours may acquire PNCTR-expressing cells through error-prone resealing of double-strand breaks that often occur in this DNA region. We will use CRISPR/Cas reagents to introduce DNA breaks in PNCTR-negative cells and then analyze expression and locus structure by qPCR, FISH, and deep sequencing. We will further probe the role of different DNA repair pathways by using appropriate inhibitors and knockdown approaches.
Aim 3 (Years 3-4): Understanding the functional role of PNCTR and PNC in metastasis. Using CRISPR/Cas- or Cre/Lox-based genetic tools, we will “turn on” or “turn off” PNCTR expression and assess effects on migration and invasion using 2D assays and organoid models. We will correlate these behaviours with PNC assembly using FISH, IF, and live imaging.
This project offers comprehensive training in bioinformatics, functional genomics, gene editing, molecular imaging, and cancer modelling. The student will gain expertise across computational and experimental approaches, develop critical thinking and interdisciplinary collaboration skills, and be well-prepared for successful careers in both fundamental research and translational biomedical science.