Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis

Abstract

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell–cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER+/luminal subtype had lower fibroblast and endothelial content, while triple-negative breast cancer/basal metastases showed a decrease in B and T cells. In 17% of metastases, DNA hypermethylation and/or focal deletions were identified near HLA-A and were associated with reduced expression and lower immune cell infiltrates, especially in brain and liver metastases. These findings could have implications for treating individuals with metastatic breast cancer with immune- and HER2-targeting therapies.

Loss of NAT10 disrupts enhancer organization via p300 mislocalization and suppresses transcription of genes necessary for metastasis progression

“…To determine whether NAT10 contributes to breast cancer metastasis, publicly available human breast cancer patient expression datasets were analyzed. Expression analysis of the primary tumor and metastases from the AURORA US Metastasis Project 39 revealed that NAT10 expression was significantly higher in breast cancer metastases compared to the primary tumor (Fig. 1a, b).…”

De Novo Oligometastatic Breast Cancer

“…10 Comparison of primary tumors and metastatic lesions also revealed that synchronous metastases have a more similar genomic architecture to the primary tumors, presumably due to shorter divergence time and lack of therapeutic selective pressure, whereas asynchronous metastases show a larger number of genomic differences compared with the primary tumor. [7][8][9][10][11] This observation raises the possibility that synchronous metastases have similar treatment sensitivities to the primary tumor. This hypothesis is supported by clinical observations including high rates of pathologic complete response (pCR) in biopsy-proven synchronous lymph node metastases in patients who achieve pCR in the breast with neoadjuvant chemotherapy 12,13 and longer progression-free survival (PFS) with initial therapy in patients with de novo compared with recurrent metastatic disease.…”

“…Phylogenetic analysis of primary tumors and metastatic lesions from the same individual revealed three distinct paths to metastatic dissemination with clinical implications. [7][8][9] First, metastatic spread can occur early from a common ancestor of both the primary tumor and distant metastases, resulting in lesions evolving simultaneously. This phenomenon may explain why small primary tumors could present as micrometastatic disease.…”

Research autopsy programmes in oncology: shared experience from 14 centres across the world

“…Regions with consistent methylation show enrichment for cancer-related genes [47] Metastatic lesions within patients and between patients with urothelial carcinoma shared actionable mutations [48] Many of the genetic changes conferring treatment resistance were shared between metastases in the same patient with melanoma [49] No correlation between ERG and expression of PSA or androgen receptor in individual metastases in prostate cancer [71] Prognostic and predictive biomarker expression differs between primary breast cancer and matched metastases and might depend on the organ of metastasis. Immune profiles were heterogeneous too [77] Characterisation and comparison of non-ossified bone metastases to non-osseous metastases from the same prostate cancer patients [78] Immune activation varies by organ site of involvement in metastatic breast cancer [79] Multi-omic analyses on primary breast tumours versus during-life (mostly liver) and after-death (many other soft tissues) metastases reveal events that may explain metastatic tumour behaviours [79] Mechanisms of metastatic evolution and spread, including phylogenetic reconstruction Almost all targetable drivers in metastases in patients with breast cancer are already present in the primary tumour. Multiclonal seeding is often seen [50] Two possible scenarios of dissemination patterns of breast cancer (monoclonal and multiclonal) are observed, as well as cross-seeding between metastases [51] While some patients with metastatic breast cancer presented with predominantly monoclonal seeding patterns, others showed predominantly multiclonal seeding [52] Clonal dynamics as assessed on multiple metastases at autopsy confirms different modes of metastatic dissemination in clear-cell renal cell carcinoma [53] Phylogenetic trees in metastatic pancreatic cancer show organ-specific branches [54] Copy number and cell ploidy changes drive evolution to end-stage disease in melanoma (compared with SNVs driving transformation in early disease) [55] Most genetic drivers in metastases in breast cancer were already established in the primary tumour.…”