Abstract 55P
Background
Biliary tract cancer (BTC) is an aggressive and highly lethal cancer arising from the epithelium lining the biliary tree. The mechanisms underlying cholangiocyte malignant transformation and BTC progression are largely unknown. Genomic and transcriptomic profiling can offer a deeper understanding of disease biology in BTC. We performed large-scale integrative analyses on a clinically-annotated cohort of BTC patients to identify novel key-genes driving BTC initiation and progression as well as drug-resistance.
Methods
We analyzed 100 resected specimens from a well-annotated cohort of BTC patients from the University of Modena. Overall, whole-exome sequencing (WES) was performed on 40 samples, RNA sequencing (RNAseq) on 80 samples, and small RNA sequencing on 30 samples. Somatic alterations, transcriptomic and epigenetic profiles of tumours and stromal area were identified for each sample, and searched for driver genes. By using a bio-informatic pipeline, we integrated somatic mutation patterns and epigenetic features defined at the spatial level to identify novel target genes in the tumour microenvironment. Functional studies in 2D and 3D culturing models were conducted to investigate candidate genes linked to BTC progression.
Results
A total of 3392 and 6315 DEGs (Differentially expressed genes) were respectively observed in BDC comparing tumour (T), normal (N) and stromal (ST) areas with the criterion of false discovery rate <0.05. In top-ranked differentially regulated gene sets, we identified primary cilium-associated genes (PC). OFD1, CNGB1, AURKA, CENPF, STIL, STK39, RAB23 and OSR1 were found based on the criteria of fold change >2.5 and P<0.01. We started also to clarify at molecular level the role of PC in BDC pathogenesis and progression. A therapeutic approach targeting OFD1 in BDC cells was also investigated.
Conclusions
We investigated the molecular mechanisms underlying the cilia loss and test whether may be potential therapeutic target. These findings could be useful to establish treatment and diagnostic strategies for BTCs based on genetic information.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
TIGEM.
Disclosure
All authors have declared no conflicts of interest.