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Despite being the hallmark of cancer that is responsible for the highest number of deaths, very little is known about the biology of metastasis. Metastatic disease typically manifests after a protracted period of undetectable disease following surgery or systemic therapy, owing to relapse or recurrence. In the case of breast cancer, metastatic relapse can occur months to decades after initial diagnosis and treatment. In this review, we provide an overview of the known key factors that influence metastatic recurrence, with the goal of highlighting the critical unanswered questions that still need to be addressed to make a difference in the mortality of breast cancer patients.

The methylation of cytosines in CpG dinucleotides is essential for cellular differentiation and the progression of many cancers, and it plays an important role in gametic imprinting. To assess variation and inheritance of genome-wide patterns of DNA methylation simultaneously in humans, we applied reduced representation bisulfite sequencing (RRBS) to somatic DNA from six members of a three-generation family. We observed that 8.1% of heterozygous SNPs are associated with differential methylation in cis, which provides a robust signature for Mendelian transmission and relatedness. The vast majority of differential methylation between homologous chromosomes (>92%) occurs on a particular haplotype as opposed to being associated with the gender of the parent of origin, indicating that genotype affects DNA methylation of far more loci than does gametic imprinting. We found that 75% of genotype-dependent differential methylation events in the family are also seen in unrelated individuals and that overall genotype can explain 80% of the variation in DNA methylation. These events are under-represented in CpG islands, enriched in intergenic regions, and located in regions of low evolutionary conservation. Even though they are generally not in functionally constrained regions, 22% (twice as many as expected by chance) of genes harboring genotype-dependent DNA methylation exhibited allele-specific gene expression as measured by RNA-seq of a lymphoblastoid cell line, indicating that some of these events are associated with gene expression differences. Overall, our results demonstrate that the influence of genotype on patterns of DNA methylation is widespread in the genome and greatly exceeds the influence of imprinting on genome-wide methylation patterns.

The c-Myc protooncogene places a demand on glucose uptake to drive glucose-dependent biosynthetic pathways. To meet this demand, c-Myc protein (Myc henceforth) drives the expression of glucose transporters, glycolytic enzymes, and represses the expression of thioredoxin interacting protein (TXNIP), which is a potent negative regulator of glucose uptake. A Myc high /TXNIP low gene signature is clinically significant as it correlates with poor clinical prognosis in triple-negative breast cancer (TNBC) but not in other subtypes of breast cancer, suggesting a functional relationship between Myc and TXNIP. To better understand how TXNIP contributes to the aggressive behavior of TNBC, we generated TXNIP null MDA-MB-231 (231:TKO) cells for our study. We show that TXNIP loss drives a transcriptional program that resembles those driven by Myc and increases global Myc genome occupancy. TXNIP loss allows Myc to invade the promoters and enhancers of target genes that are potentially relevant to cell transformation. Together, these findings suggest that TXNIP is a broad repressor of Myc genomic binding. The increase in Myc genomic binding in the 231:TKO cells expands the Myc-dependent transcriptome we identified in parental MDA-MB-231 cells. This expansion of Myc-dependent transcription following TXNIP loss occurs without an apparent increase in Myc’s intrinsic capacity to activate transcription and without increasing Myc levels. Together, our findings suggest that TXNIP loss mimics Myc overexpression, connecting Myc genomic binding and transcriptional programs to the nutrient and progrowth signals that control TXNIP expression.

Cancer genomes are composed of many complex structural alterations on chromosomes and extrachromosomal DNA (ecDNA), making it difficult to identify non-coding enhancer regions that are hijacked to activate oncogene expression. Here, we describe a 3D genomics-based analysis called HAPI (Highly Active Promoter Interactions) to characterize enhancer hijacking. HAPI analysis of HiChIP data from 34 cancer cell lines identified enhancer hijacking events that activate both known and potentially novel oncogenes such as MYC, CCND1 , ETV1 , CRKL , and ID4 . Furthermore, we found enhancer hijacking among multiple oncogenes from different chromosomes, often including MYC , on the same complex amplicons such as ecDNA. We characterized a MYC - ERBB2 chimeric ecDNA, in which ERBB2 heavily hijacks MYC ’s enhancers. Notably, CRISPRi of the MYC promoter led to increased interaction of ERBB2 with MYC enhancers and elevated ERBB2 expression. Our HAPI analysis tool provides a robust strategy to detect enhancer hijacking and reveals novel insights into oncogene activation. Here the authors describe a 3D genomic strategy that uncovers novel enhancer hijacking events, including a MYC-ERBB2 chimeric ecDNA, providing new insights into oncogene activation and potential therapeutic targets.

The closely linked human protocadherin (Pcdh) α, β, and γ gene clusters encode 53 distinct protein isoforms, which are expressed in a combinatorial manner to generate enormous diversity on the surface of individual neurons. This diversity is a consequence of stochastic promoter choice and alternative pre-mRNA processing. Here, we show that Pcdhα promoter choice is achieved by DNA looping between two downstream transcriptional enhancers and individual promoters driving the expression of alternate Pcdhα isoforms. In addition, we show that this DNA looping requires specific binding of the CTCF/cohesin complex to two symmetrically aligned binding sites in both the transcriptionally active promoters and in one of the enhancers. These findings have important implications regarding enhancer/promoter interactions in the generation of complex Pcdh cell surface codes for the establishment of neuronal identity and self-avoidance in individual neurons.

Read-through fusion transcripts that result from the splicing of two adjacent genes in the same coding orientation are a recently discovered type of chimeric RNA. We sought to determine if read-through fusion transcripts exist in breast cancer. We performed paired-end RNA-seq of 168 breast samples, including 28 breast cancer cell lines, 42 triple negative breast cancer primary tumors, 42 estrogen receptor positive (ER+) breast cancer primary tumors, and 56 non-malignant breast tissue samples. We analyzed the sequencing data to identify breast cancer associated read-through fusion transcripts. We discovered two recurrent read-through fusion transcripts that were identified in breast cancer cell lines, confirmed across breast cancer primary tumors, and were not detected in normal tissues ( SCNN1A - TNFRSF1A and CTSD - IFITM10 ). Both fusion transcripts use canonical splice sites to join the last splice donor of the 5′ gene to the first splice acceptor of the 3′ gene, creating an in-frame fusion transcript. Western blots indicated that the fusion transcripts are translated into fusion proteins in breast cancer cells. Custom small interfering RNAs targeting the CTSD - IFITM10 fusion junction reduced expression of the fusion transcript and reduced breast cancer cell proliferation. Read-through fusion transcripts between adjacent genes with different biochemical functions represent a new type of recurrent molecular defect in breast cancer that warrant further investigation as potential biomarkers and therapeutic targets. Both breast cancer associated fusion transcripts identified in this study involve membrane proteins ( SCNN1A - TNFRSF1A and CTSD - IFITM10 ), which raises the possibility that they could be breast cancer-specific cell surface markers.

Amplification and overexpression of the SOX2 oncogene represent a hallmark of squamous cancers originating from diverse tissue types. Here, we find that squamous cancers selectively amplify a 3’ noncoding region together with SOX2 , which harbors squamous cancer-specific chromatin accessible regions. We identify a single enhancer e1 that predominantly drives SOX2 expression. Repression of e1 in SOX2 -high cells causes collapse of the surrounding enhancers, remarkable reduction in SOX2 expression, and a global transcriptional change reminiscent of SOX2 knockout. The e1 enhancer is driven by a combination of transcription factors including SOX2 itself and the AP-1 complex, which facilitates recruitment of the co-activator BRD4. CRISPR-mediated activation of e1 in SOX2 -low cells is sufficient to rebuild the e1- SOX2 loop and activate SOX2 expression. Our study shows that squamous cancers selectively amplify a predominant enhancer to drive SOX2 overexpression, uncovering functional links among enhancer activation, chromatin looping, and lineage-specific copy number amplifications of oncogenes. SOX2 amplification and overexpression represents a hallmark of squamous cancers with distinct distribution of chromatin accessible regions depending on cancer type. Here, the authors identify a single enhancer e1 that predominantly drives SOX2 expression in squamous cancer.

A substantial fraction of the human genome is difficult to interrogate with short-read DNA sequencing technologies due to paralogy, complex haplotype structures, or tandem repeats. Long-read sequencing technologies, such as Oxford Nanopore’s MinION, enable direct measurement of complex loci without introducing many of the biases inherent to short-read methods, though they suffer from relatively lower throughput. This limitation has motivated recent efforts to develop amplification-free strategies to target and enrich loci of interest for subsequent sequencing with long reads. Here, we present CaBagE, a method for target enrichment that is efficient and useful for sequencing large, structurally complex targets. The CaBagE method leverages the stable binding of Cas9 to its DNA target to protect desired fragments from digestion with exonuclease. Enriched DNA fragments are then sequenced with Oxford Nanopore’s MinION long-read sequencing technology. Enrichment with CaBagE resulted in a median of 116X coverage (range 39–416) of target loci when tested on five genomic targets ranging from 4-20kb in length using healthy donor DNA. Four cancer gene targets were enriched in a single reaction and multiplexed on a single MinION flow cell. We further demonstrate the utility of CaBagE in two ALS patients with C9orf72 short tandem repeat expansions to produce genotype estimates commensurate with genotypes derived from repeat-primed PCR for each individual. With CaBagE there is a physical enrichment of on-target DNA in a given sample prior to sequencing. This feature allows adaptability across sequencing platforms and potential use as an enrichment strategy for applications beyond sequencing. CaBagE is a rapid enrichment method that can illuminate regions of the ‘hidden genome’ underlying human disease.

Background In preclinical studies, the expression of vascular endothelial growth factor (VEGF) in hormone receptor-positive breast cancer is associated with estrogen-independent tumor growth and resistance to endocrine therapies. This study investigated whether the addition of bevacizumab, a monoclonal antibody against VEGF, to letrozole enhanced the antitumor activity of the letrozole in the preoperative setting. Methods Postmenopausal women with newly diagnosed stage 2 or 3 estrogen and/or progesterone receptor-positive, HER2-negative breast cancer were randomly assigned (2:1) between letrozole 2.5 mg PO daily plus bevacizumab 15 mg/kg IV every 3 weeks (Let/Bev) and letrozole 2.5 mg PO daily (Let) for 24 weeks prior to definitive surgery. Primary objective was within-arm pathologic complete remission (pCR) rate. Secondary objectives were safety, objective response, and downstaging rate. Results Seventy-five patients were randomized (Let/Bev n  = 50, Let n  = 25). Of the 45 patients evaluable for pathological response in the Let/Bev arm, 5 (11%; 95% CI, 3.7–24.1%) achieved pCR and 4 (9%; 95% CI, 2.5–21.2%) had microscopic residual disease; no pCRs or microscopic residual disease was seen in the Let arm (0%; 95% CI, 0–14.2%). The rates of downstaging were 44.4% (95% CI, 29.6–60.0%) and 37.5% (95% CI, 18.8–59.4%) in the Let/Bev and Let arms, respectively. Adverse events typically associated with letrozole (hot flashes, arthralgias, fatigue, myalgias) occurred in similar frequencies in the two arms. Hypertension, headache, and proteinuria were seen exclusively in the Let/Bev arm. The rates of grade 3 and 4 adverse events and discontinuation due to adverse events were 18% vs 8% and 16% vs none in the Let/Bev and Let arms, respectively. A small RNA-based classifier predictive of response to preoperative Let/Bev was developed and confirmed on an independent cohort. Conclusion In the preoperative setting, the addition of bevacizumab to letrozole was associated with a pCR rate of 11%; no pCR was seen with letrozole alone. There was additive toxicity with the incorporation of bevacizumab. Responses to Let/Bev can be predicted from the levels of 5 small RNAs in a pretreatment biopsy. Trial registration This trial is registered with ClinicalTrials.gov (Identifier: NCT00161291 ), first posted on September 12, 2005, and is completed.

The base-calling algorithm SNPSeeker detects single-nucleotide polymorphisms with frequencies that are below the error rate of the sequencing platform. It is thus well suited to analyze data from large pooled samples and find rare variants that may contribute to diseases or complex traits. We report a targeted, cost-effective method to quantify rare single-nucleotide polymorphisms from pooled human genomic DNA using second-generation sequencing. We pooled DNA from 1,111 individuals and targeted four genes to identify rare germline variants. Our base-calling algorithm, SNPSeeker, derived from large deviation theory, detected single-nucleotide polymorphisms present at frequencies below the raw error rate of the sequencing platform.