Back

Somatic chromosomal number alterations affecting driver genes inform in-vitro and clinical drug response in high-grade serous ovarian cancer

Correia Martins, F.; Couturier, D.-L.; Santiago, I.; Sauer, C.; Vias, M.; Angelova, M.; Sanders, D.; Piskorz, A.; Hall, J.; Hosking, K.; Amirthanayagam, A.; Cosulich, S.; Carnevalli, L.; Davies, B.; Watkins, T. B. K.; Funingana, G.; Bolton, H.; Haldar, K.; Latimer, J.; Baldwin, P.; Crawford, R.; Eldridge, M.; Basu, B.; Jimenez-Linan, M.; McGranahan, N.; Litchfield, K.; Shah, S.; McNeish, I.; Caldas, C.; Evan, G.; Swanton, C.; Brenton, J. D.

2020-10-04 cancer biology
10.1101/2020.10.04.325365 bioRxiv
Show abstract

The genomic complexity and heterogeneity of high-grade serous ovarian cancer (HGSOC) has hampered the realisation of successful therapies and effective personalised treatment is an unmet clinical need. Here we show that primary HGSOC spheroid models can be used to predict drug response and use them to demonstrate that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and drug response. These genes are often located in areas of the genome with frequent clonal SCNAs. MYC chromosomal copy number is associated with ex-vivo and clinical response to paclitaxel and ex-vivo response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context to MYC-amplified HGSOC is mostly due to increased prevalence of SCNAs in genes from the PI3K pathway. These results suggest that SCNAs encompassing driver genes could be used to inform therapeutic response in the context of clinical trials testing personalised medicines.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.