Comparison of the mutational profiles of neuroendocrine breast tumours, invasive ductal carcinomas and pancreatic neuroendocrine carcinomas

Abstract

The pathophysiology and the optimal treatment of breast neuroendocrine tumours (NETs) are unknown. We compared the mutational profiles of breast NETs (n = 53) with those of 724 publicly available invasive ductal carcinoma (IDC) and 98 pancreatic NET (PNET) cases. The only significantly different pathogenetic or unknown variant rate between breast NETs and IDCs was detected in the TP53 (11.3% in breast NETs and 41% in IDCs, adjusted p value 0.027) and ADCK2 (9.4% in breast NETs vs. 0.28% in IDCs, adjusted p value 0.045) genes. Between breast NETs and PNETs, different pathogenetic or unknown variant frequencies were detected in 30 genes. For example, MEN1 was mutated in only 6% of breast NETs and 37% in PNETs (adjusted p value 0.00050), and GATA3 pathogenetic or unknown variants were only found in 17.0% of breast NETs and 0% in PNETs (adjusted p value 0.0010). The most commonly affected oncogenic pathways in the breast NET cases were PI3K/Akt/mTOR, NOTCH and RTK-RAS pathways. Breast NETs had typically clock-like mutational signatures and signatures associated with defective DNA mismatch repair in their mutational landscape. Our results suggest that the breast NET mutational profile more closely resembles that of IDCs than that of PNETs. These results also revealed several potentially druggable targets, such as MMRd, in breast NETs. In conclusion, breast NETs are indeed a separate breast cancer entity, but their optimal treatment remains to be elucidated.

Fig. 1. Summary of the filtered breast NET cohort variants.

Panels A–C show the distribution of variants. Panel D shows the number of variants in each sample. In panel E, variants per sample are demonstrated and panel F shows the six most common pathogenetic or unknown variants in the breast NET cohort. TTN variants are likely not associated with cancer. SNP single-nucleotide variant, ONP oligo-nucleotide polymorphism, INS insertion, DEL deletion.

Fig. 2. Somatic interaction analysis of the 30 most mutated genes in the breast NET cohort.

The most significant co-occurring pairs of genes were MYCBP2/FRAS1 and NEB/MECOM (p value for both 0.004). Statistically significant pairs are indicated with darker colours and dots or asterisks if the p value <0.05 or < 0.01, respectively.

Fig. 3

Co-bar plots comparing the top 5 most mutated genes. Co-bar plots comparing the top 5 most mutated genes from breast NET and IDC cohorts (A) and breast NET cohort and PNET cohorts (B). Especially CREBBP and JMJD1C especially were more commonly mutated in the breast NET cohort compared with the IDC cohort. Likewise, MEN1 and DAXX had rarely pathogenetic or unknown variants in breast NETs, with pathogenetic or unknown variant rates of 37% and 22% in PNETs. GATA3, CREBBP and JMJD1C pathogenetic or unknown variants were not found in PNETs, but they had an 11–17% frequency in breast NETs. TTN variants are likely not associated with cancer.

Fig. 4

Enriched oncogenic signalling pathways in breast NETs, invasive ductal carcinomas (IDCs) and pancreatic NETs (PNETs). The bar plots on the left side in panels (A–C) show the number of mutated genes in the pathway in each of the cohorts, and the bar plots on the right side in panels (A–C) show the fractions of samples having mutated genes in the pathway. Oncoplot panels (D–F) visualise the pathogenetic or unknown variants of RTK-RAS, PI3K and NOTCH pathways in breast NETs. Tumour suppressor genes are in red font and oncogenes are in blue font in panels D–F. As the main results, the most enriched oncogenic pathways in breast NET were PI3K and RTK-RAS. A very frequent TP53 pathway enrichment in IDCs was only rarely observed in breast NETs. In PNET cohort, none of the oncogenic pathway was prominently affected over others.