Emerging Role of Genomic Rearrangements in Breast Cancer: Applying Knowledge from Other Cancers

Expanding the Clinical Utility of Targeted RNA Sequencing Panels beyond Gene Fusions to Complex, Intragenic Structural Rearrangements

Gene fusions are a form of structural rearrangement well established as driver events in pediatric and adult cancers. The identification of such events holds clinical significance in the refinement, prognostication, and provision of treatment in cancer. Structural rearrangements also extend beyond fusions to include intragenic rearrangements, such as internal tandem duplications (ITDs) or exon-level deletions. These intragenic events have been increasingly implicated as cancer-promoting events. However, the detection of intragenic rearrangements may be challenging to resolve bioinformatically with short-read sequencing technologies and therefore may not be routinely assessed in panel-based testing. Within an academic clinical laboratory, over three years, a total of 608 disease-involved samples (522 hematologic malignancy, 86 solid tumors) underwent clinical testing using Anchored Multiplex PCR (AMP)-based RNA sequencing. Hematologic malignancies were evaluated using a custom Pan-Heme 154 gene panel, while solid tumors were assessed using a custom Pan-Solid 115 gene panel. Gene fusions, ITDs, and intragenic deletions were assessed for diagnostic, prognostic, or therapeutic significance. When considering gene fusions alone, we report an overall diagnostic yield of 36% (37% hematologic malignancy, 41% solid tumors). When including intragenic structural rearrangements, the overall diagnostic yield increased to 48% (48% hematologic malignancy, 45% solid tumor). We demonstrate the clinical utility of reporting structural rearrangements, including gene fusions and intragenic structural rearrangements, using an AMP-based RNA sequencing panel.

Recovering rearranged cancer chromosomes from karyotype graphs

BACKGROUND

Many cancer genomes are extensively rearranged with highly aberrant chromosomal karyotypes. Structural and copy number variations in cancer genomes can be determined via abnormal mapping of sequenced reads to the reference genome. Recently it became possible to reconcile both of these types of large-scale variations into a karyotype graph representation of the rearranged cancer genomes. Such a representation, however, does not directly describe the linear and/or circular structure of the underlying rearranged cancer chromosomes, thus limiting possible analysis of cancer genomes somatic evolutionary process as well as functional genomic changes brought by the large-scale genome rearrangements.

RESULTS

Here we address the aforementioned limitation by introducing a novel methodological framework for recovering rearranged cancer chromosomes from karyotype graphs. For a cancer karyotype graph we formulate an Eulerian Decomposition Problem (EDP) of finding a collection of linear and/or circular rearranged cancer chromosomes that are determined by the graph. We derive and prove computational complexities for several variations of the EDP. We then demonstrate that Eulerian decomposition of the cancer karyotype graphs is not always unique and present the Consistent Contig Covering Problem (CCCP) of recovering unambiguous cancer contigs from the cancer karyotype graph, and describe a novel algorithm CCR capable of solving CCCP in polynomial time. We apply CCR on a prostate cancer dataset and demonstrate that it is capable of consistently recovering large cancer contigs even when underlying cancer genomes are highly rearranged.

CONCLUSIONS

CCR can recover rearranged cancer contigs from karyotype graphs thereby addressing existing limitation in inferring chromosomal structures of rearranged cancer genomes and advancing our understanding of both patient/cancer-specific as well as the overall genetic instability in cancer.

RET rearrangements are actionable alterations in breast cancer

Fusions involving the oncogenic gene RET have been observed in thyroid and lung cancers. Here we report RET gene alterations, including amplification, missense mutations, known fusions, novel fusions, and rearrangements in breast cancer. Their frequency, oncogenic potential, and actionability in breast cancer are described. Two out of eight RET fusions (NCOA4-RET and a novel RASGEF1A-RET fusion) and RET amplification were functionally characterized and shown to activate RET kinase and drive signaling through MAPK and PI3K pathways. These fusions and RET amplification can induce transformation of non-tumorigenic cells, support xenograft tumor formation, and render sensitivity to RET inhibition. An index case of metastatic breast cancer progressing on HER2-targeted therapy was found to have the NCOA4-RET fusion. Subsequent treatment with the RET inhibitor cabozantinib led to a rapid clinical and radiographic response. RET alterations, identified by genomic profiling, are promising therapeutic targets and are present in a subset of breast cancers.

Fusions of the gene RET have been described in thyroid and lung cancers. Here, the AUs identify RET gene alterations, including known fusions, novel fusions, and rearrangements in breast cancer (BC) that are involved in the tumorigenic process and show the benefit of RET therapy in a recurrent BC patient carrying the NCOA4-RET fusion.

CRISPR Technology for Breast Cancer: Diagnostics, Modeling, and Therapy

Molecularly, breast cancer represents a highly heterogenous family of neoplastic disorders, with substantial interpatient variations regarding genetic mutations, cell composition, transcriptional profiles, and treatment response. Consequently, there is an increasing demand for alternative diagnostic approaches aimed at the molecular annotation of the disease on a patient-by-patient basis and the design of more personalized treatments. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) technology enables the development of such novel approaches. For instance, in diagnostics, the use of the RNA-specific C2c2 system allows ultrasensitive nucleic acid detection and could be used to characterize the mutational repertoire and transcriptional breast cancer signatures. In disease modeling, CRISPR/Cas9 technology can be applied to selectively engineer oncogenes and tumor-suppressor genes involved in disease pathogenesis. In treatment, CRISPR/Cas9 can be used to develop gene-therapy, while its catalytically-dead variant (dCas9) can be applied to reprogram the epigenetic landscape of malignant cells. As immunotherapy becomes increasingly prominent in cancer treatment, CRISPR/Cas9 can engineer the immune cells to redirect them against cancer cells and potentiate antitumor immune responses. In this review, CRISPR strategies for the advancement of breast cancer diagnostics, modeling, and treatment are highlighted, culminating in a perspective on developing a precision medicine-based approach against breast cancer.

Perspective Insight into Future Potential Fusion Gene Transcript Biomarker Candidates in Breast Cancer

Next generation sequencing has accelerated the discovery of a variety of new fusion gene types in clinical breast cancer samples by analyzing cancer genomes and transcriptomes. Although previous studies have focused on a few clinically validated oncogenic fusion genes as diagnostic and therapeutic targets in breast cancer, a perspective consideration has not been given thus far for a plethora of breast cancer fusion genes, which are being newly identified at an overwhelmingly increasing pace. In this perspective review, we discuss diverse fusion gene types recently identified in a variety of breast cancer subtypes, including breast clinical cancer samples in TCGA (The Cancer Genome Atlas) database. This perspective review will confer fresh and promising guidance onto breast cancer surgeons, clinical oncologists, and tumor biologists in determining research directions for seeking and developing novel fusion gene biomarkers for breast cancer diagnostics and therapeutic treatment in upcoming years.

Rat models of 17β-estradiol-induced mammary cancer reveal novel insights into breast cancer etiology and prevention

Numerous laboratory and epidemiologic studies strongly implicate endogenous and exogenous estrogens in the etiology of breast cancer. Data summarized herein suggest that the ACI rat model of 17β-estradiol (E2)-induced mammary cancer is unique among rodent models in the extent to which it faithfully reflects the etiology and biology of luminal types of breast cancer, which together constitute ~70% of all breast cancers. E2 drives cancer development in this model through mechanisms that are largely dependent upon estrogen receptors and require progesterone and its receptors. Moreover, mammary cancer development appears to be associated with generation of oxidative stress and can be modified by multiple dietary factors, several of which may attenuate the actions of reactive oxygen species. Studies of susceptible ACI rats and resistant COP or BN rats provide novel insights into the genetic bases of susceptibility and the biological processes regulated by genetic determinants of susceptibility. This review summarizes research progress resulting from use of these physiologically relevant rat models to advance understanding of breast cancer etiology and prevention.

The untold stories of the speech gene, the FOXP2 cancer gene

FOXP2 encodes a transcription factor involved in speech and language acquisition. Growing evidence now suggests that dysregulated FOXP2 activity may also be instrumental in human oncogenesis, along the lines of other cardinal developmental transcription factors such as DLX5 and DLX6 [1-4]. Several FOXP familymembers are directly involved during cancer initiation, maintenance and progression in the adult [5-8]. This may comprise either a pro-oncogenic activity or a deficient tumor-suppressor role, depending upon cell types and associated signaling pathways. While FOXP2 is expressed in numerous cell types, its expression has been found to be down-regulated in breast cancer [9], hepatocellular carcinoma [8] and gastric cancer biopsies [10]. Conversely, overexpressed FOXP2 has been reported in multiple myelomas, MGUS (Monoclonal Gammopathy of Undetermined Significance), several subtypes of lymphomas [5,11], as well as in neuroblastomas [12] and ERG fusion-negative prostate cancers [13]. According to functional evidences reported in breast cancer [9] and survey of recent transcriptomic and proteomic analyses of different tumor biopsies, we postulate that FOXP2 dysregulation may play a main role throughout cancer initiation and progression. In some cancer conditions, FOXP2 levels are now considered as a critical diagnostic marker of neoplastic cells, and in many situations, they even bear strong prognostic value [5]. Whether FOXP2 may further become a therapeutic target is an actively explored lead. Knowledge reviewed here may help improve our understanding of FOXP2 roles during oncogenesis and provide cues for diagnostic, prognostic and therapeutic analyses.

Impact of multi-gene mutational profiling on clinical trial outcomes in metastatic breast cancer

Purpose

Next-generation sequencing (NGS) has identified recurrent genomic alterations in metastatic breast cancer (MBC); however, the clinical utility of incorporating routine sequencing to guide treatment decisions in this setting is unclear. We examine the frequency of genomic alterations in MBC patients from academic and community hospitals and correlate with clinical outcomes.

Methods

MBC patients with good performance status were prospectively recruited at the Princess Margaret Cancer Centre (PM) in Canada. Molecular profiling on DNA extracted from FFPE archival tissues was performed on the Sequenom MassArray platform or the TruSeq Amplicon Cancer Panel (TSACP) on the MiSeq platform. Clinical trial outcomes by RECIST 1.1 and time on treatment were reviewed retrospectively.

Results

From January 2012 to November 2015, 483 MBC patients were enrolled and 440 were genotyped. At least one somatic mutation was identified in 46% of patients, most commonly in PIK3CA (28%) or TP53 (13%). Of 203 patients with ≥ 1 mutation(s), 15% were treated on genotype-matched and 9% on non-matched trials. There was no significant difference for median time on treatment for patients treated on matched vs. non-matched therapies (3.6 vs. 3.8 months; p = 0.89).

Conclusions

This study provides real-world outcomes on hotspot genotyping and small targeted panel sequencing of MBC patients from academic and community settings. Few patients were matched to clinical trials with targeted therapies. More comprehensive profiling and improved access to clinical trials may increase therapeutic options for patients with actionable mutations. Further studies are needed to evaluate if this approach leads to improved clinical outcomes.

Electronic supplementary material

The online version of this article (10.1007/s10549-017-4580-2) contains supplementary material, which is available to authorized users.

De novo assembly and characterization of breast cancer transcriptomes identifies large numbers of novel fusion-gene transcripts of potential functional significance

Background

Gene-fusion or chimeric transcripts have been implicated in the onset and progression of a variety of cancers. Massively parallel RNA sequencing (RNA-Seq) of the cellular transcriptome is a promising approach for the identification of chimeric transcripts of potential functional significance. We report here the development and use of an integrated computational pipeline for the de novo assembly and characterization of chimeric transcripts in 55 primary breast cancer and normal tissue samples.

Methods

An integrated computational pipeline was employed to screen the transcriptome of breast cancer and control tissues for high-quality RNA-sequencing reads. Reads were de novo assembled into contigs followed by reference genome mapping. Chimeric transcripts were detected, filtered and characterized using our R-SAP algorithm. The relative abundance of reads was used to estimate levels of gene expression.

Results

De novo assembly allowed for the accurate detection of 1959 chimeric transcripts to nucleotide level resolution and facilitated detailed molecular characterization and quantitative analysis. A number of the chimeric transcripts are of potential functional significance including 79 novel fusion-protein transcripts and many chimeric transcripts with alterations in their un-translated leader regions. A number of chimeric transcripts in the cancer samples mapped to genomic regions devoid of any known genes. Several ‘pro-neoplastic’ fusions comprised of genes previously implicated in cancer are expressed at low levels in normal tissues but at high levels in cancer tissues.

Conclusions

Collectively, our results underscore the utility of deep sequencing technologies and improved bioinformatics workflows to uncover novel and potentially significant chimeric transcripts in cancer and normal somatic tissues.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-017-0289-7) contains supplementary material, which is available to authorized users.