Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy ¹ . Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study ^2,3 . Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic–transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary–metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

Aberrant miRNA expression has been previously established in breast cancer and has clinical relevance. However, no studies so far have defined miRNAs deregulated in hereditary breast tumors. In this study we investigated the role of miRNAs in hereditary breast tumors comparing with normal breast tissue. Global miRNA expression profiling using Exiqon microarrays was performed on 22 hereditary breast tumors and 15 non-tumoral breast tissues. We identified 19 miRNAs differentially expressed, most of them down-regulated in tumors. An important proportion of deregulated miRNAs in hereditary tumors were previously identified commonly deregulated in sporadic breast tumors. Under-expression of these miRNAs was validated by qRT-PCR in additional 18 sporadic breast tumors and their normal breast tissue counterparts. Pathway enrichment analysis revealed that deregulated miRNAs collectively targeted a number of genes belonging to signaling pathways such as MAPK, ErbB, mTOR, and those regulating cell motility or adhesion. In silico prediction detected KRAS oncogene as target of several deregulated miRNAs. In particular, we experimentally validated KRAS as a miR-30c target. Luciferase assays confirmed that miR-30c binds the 3′UTR of KRAS transcripts and expression of pre-miR-30c down-regulated KRAS mRNA and protein. Furthermore, miR-30c overexpression inhibited proliferation of breast cancer cells. Our results identify miRNAs associated to hereditary breast cancer, as well as miRNAs commonly miss-expressed in hereditary and sporadic tumors, suggesting common underlying mechanisms of tumor progression. In addition, we provide evidence that KRAS is a target of miR-30c, and that this miRNA suppresses breast cancer cell growth potentially through inhibition of KRAS signaling.

Screening for germline mutations in breast cancer‐associated genes BRCA1 and BRCA2 is indicated for patients with breast cancer from high‐risk breast cancer families and influences both treatment options and clinical management. However, only 25% of selected patients test positive for BRCA1/2 mutation, indicating that additional diagnostic biomarkers are necessary. We analyzed 124 formalin‐fixed paraffin‐embedded (FFPE) tumor samples from patients with hereditary (104) and sporadic (20) invasive breast cancer, divided into two series (A and B). Microarray expression profiling of 829 human miRNAs was performed on 76 samples (Series A), and bioinformatics tool Prophet was used to develop and test a microarray classifier. Samples were stratified into a training set (n = 38) for microarray classifier generation and a test set (n = 38) for signature validation. A 35‐miRNA microarray classifier was generated for the prediction of BRCA1/2 mutation status with a reported 95% (95% CI = 0.88–1.0) and 92% (95% CI: 0.84–1.0) accuracy in the training and the test set, respectively. Differential expression of 12 miRNAs between BRCA1/2 mutation carriers versus noncarriers was validated by qPCR in an independent tumor series B (n = 48). Logistic regression model based on the expression of six miRNAs (miR‐142‐3p, miR‐505*, miR‐1248, miR‐181a‐2*, miR‐25* and miR‐340*) discriminated between tumors from BRCA1/2 mutation carriers and noncarriers with 92% (95% CI: 0.84–0.99) accuracy. In conclusion, we identified miRNA expression signatures predictive of BRCA1/2 mutation status in routinely available FFPE breast tumor samples, which may be useful to complement current patient selection criteria for gene testing by identifying individuals with high likelihood of being BRCA1/2 mutation carriers.

Since introducing the concept of epigenome-wide association studies (EWAS) in 2011, there has been a vast increase in the number of published EWAS studies in common diseases, including in cancer. These studies have increased our understanding of epigenetic events underlying carcinogenesis and have enabled the discovery of cancer-specific methylation biomarkers. In this mini-review, we have focused on the state of the art in EWAS applied to cell-free circulating DNA for epigenetic biomarker discovery in cancer and discussed associated technical advances and challenges, and our expectations for the future of the field.