ESMO 2016: The NETwork! Translational Programme Facilitates Genomic Analysis of Neuroendocrine Tumours

Large-scale analyses reveal genomic alteration is more abundant than genetic mutation in pancreatic NETs

The first findings of genetic analyses performed within NETwork!, a clinical and ethical framework that was established to support, interpret, and return genomic analyses of neuroendocrine tumours (NETs) were reported at the ESMO 2016 Congress in Copenhagen, Denmark on 10 October.  

This framework includes a national New Zealand registry of NETs that allows clinical annotation and is tethered to a NET-specific multidisciplinary meeting, which facilitates tissue collection. Ben Lawrence, Discipline of Oncology, University of Auckland Faculty of Medical and Health Sciences in Auckland, New Zealand, explained that NETwork! is a newly developed translational programme for deep genomic analysis of NETs within an integrated scientific and clinical practice. According to Dr. Lawrence, pancreatic NETs (pNETs) carry relatively few mutations compared with other tumour types, but have genomic alterations including large scale copy number, plus changes in epigenetic and gene expression.

Results of the genomic analyses of the first 61 pNETs performed using this system were reported at ESMO 2016. Hybridisation capture DNA sequencing was done on 578 cancer associated genes, which yielded greater than 750 times coverage and microarray mRNA expression analysis was also done for all pNETs. Additionally, whole genome sequencing, RNA sequencing, methylation, and microRNA (miRNA) expression analysis were done on 12 tumours. Clinical, pathological and genomic data were compared using a customised bioinformatic platform.

pNETs show high rates of loss of heterozygosity

The genomic analyses done by Dr. Lawrence and colleagues detected mutations in 75 cancer-associated genes, with 64 of these mutations being exclusive to individual tumours. Recurrent mutations were found at frequencies of 39% in MEN1 and 7% in ATRX genes. According to the investigators, the driver genomic changes in pNETs were highly tumour-specific and included somatic mutations in the FANCA, APC, BRCA2, PTEN, EGFR, MDM4, MSH2 and VHL genes. They also found mutations in ten additional genes that are not traditionally associated with cancer.

A high rate of aneuploidy was observed in pNETs samples. Loss of heterozygosity (LOH) was detected 18% of pNETs, which also showed an identical and previously undescribed pattern of LOH that involved the same ten whole chromosomes.

In-depth analyses of the 12 tumours revealed gene expression profiles of immune activation. The investigators found that therapeutic choice as suggested using single biomarkers such as FANCA, and MSH2 could be further informed by multi-level genomics. He cited an example where the downstream activity could negate a treatment decision; in this instance, the impact of a PTEN single nucleotide variation (SNV) was negated by LOH in downstream mTOR, thus reducing pathway activity. He cited another example wherein mTOR hypomethylation and expression changes were consistent with pathway activation.

Kjell Öberg who discussed the study results said that DNA sequencing of pNETs can offer a genetic landscape. NGS and similar platforms offer a correlation between tumour grade differentiation and mutated genes. TP53, Rb1 is mutated in more aggressive tumours. MEN1 is most commonly mutated, often in combination with DAXX/ATRX. Further categorization of genetic alterations might unveil new subgroups of pNETs.

Conclusions

According to the authors, performing deep genomics of the carefully annotated and described pNETs, as allowed by the NETwork! programme, produced new insights into NET tumourigenesis, which enabled rational and perhaps unexpected therapeutic choice to be applied in clinical trials. Whereas mutations occur at a lower frequency in pNETs than other tumour types, the genomic variability uncovered in this study argues for multi-level sequencing of metastatic NETs.

Reference

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Pancreatic neuroendocrine tumour (pNET) profiles in the NETwork! programme: Clinic–enabled genomics for genomic-enabled clinical decisions

B. Lawrence, C. Blenkiron, K. Parker, S. Fitzgerald, P. Shields, P. Tsai, S. James, N. Poonawala, M.L. Yeong, N. Kramer, B. Robinson, S. Connor, R. Ramsaroop, M. Yozu, M. Elston, C. Jackson, R. Carroll, D. Harris, M. Findlay, C. Print

This study was perfomed by theUniversity of Auckland and funded by the Translational Medicine Trust.