Recurrent and functional regulatory mutations in breast cancer

DeTiN: overcoming tumor-in-normal contamination

A key step in achieving accurate detection of somatic mutations is comparison of sequencing data from a tumor sample to its matched germline control. Sensitivity to detect somatic variants is greatly reduced when the matched normal sample is contaminated with tumor cells. To overcome this limitation, we developed deTiN, a method that first estimates the tumor-in-normal contamination (TiN) level, and then, in contaminated cases, improves sensitivity by reclassifying initially discarded variants as somatic.

Rpp29 regulates histone H3.3 chromatin assembly through transcriptional mechanisms

The histone H3 variant H3.3 is a highly conserved and dynamic regulator of chromatin organization. Therefore, fully elucidating its nucleosome incorporation mechanisms is essential to understanding its functions in epigenetic inheritance. We previously identified the RNase P protein subunit, Rpp29, as a repressor of H3.3 chromatin assembly. Here, we use a biochemical assay to show that Rpp29 interacts with H3.3 through a sequence element in its own N terminus, and we identify a novel interaction with histone H2B at an adjacent site. The fact that archaeal Rpp29 does not include this N-terminal region suggests that it evolved to regulate eukaryote-specific functions. Oncogenic H3.3 mutations alter the H3.3-Rpp29 interaction, which suggests that they could dysregulate Rpp29 function in chromatin assembly. We also used KNS42 cells, an H3.3(G34V) pediatric high-grade glioma cell line, to show that Rpp29 1) represses H3.3 incorporation into transcriptionally active protein-coding, rRNA, and tRNA genes; 2) represses mRNA, protein expression, and antisense RNA; and 3) represses euchromatic post-translational modifications (PTMs) and promotes heterochromatic PTM deposition (i.e. histone H3 Lys-9 trimethylation (H3K9me3) and H3.1/2/3K27me3). Notably, we also found that K27me2 is increased and K36me1 decreased on H3.3(G34V), which suggests that Gly-34 mutations dysregulate Lys-27 and Lys-36 methylation in cis The fact that Rpp29 represses H3.3 chromatin assembly and sense and antisense RNA and promotes H3K9me3 and H3K27me3 suggests that Rpp29 regulates H3.3-mediated epigenetic mechanisms by processing a transcribed signal that recruits H3.3 to its incorporation sites.

Multi‑layered prevention and treatment of chronic inflammation, organ fibrosis and cancer associated with canonical WNT/β‑catenin signaling activation (Review)

β-catenin/CTNNB1 is an intracellular scaffold protein that interacts with adhesion molecules (E-cadherin/CDH1, N-cadherin/CDH2, VE-cadherin/CDH5 and α-catenins), transmembrane-type mucins (MUC1/CD227 and MUC16/CA125), signaling regulators (APC, AXIN1, AXIN2 and NHERF1/EBP50) and epigenetic or transcriptional regulators (BCL9, BCL9L, CREBBP/CBP, EP300/p300, FOXM1, MED12, SMARCA4/BRG1 and TCF/LEF). Gain-of-function CTTNB1 mutations are detected in bladder cancer, colorectal cancer, gastric cancer, liver cancer, lung cancer, pancreatic cancer, prostate cancer and uterine cancer, whereas loss-of-function CTNNB1 mutations are also detected in human cancer. ABCB1, ALDH1A1, ASCL2, ATF3, AXIN2, BAMBI, CCND1, CD44, CLDN1, CTLA4, DKK1, EDN1, EOMES, FGF18, FGF20, FZD7, IL10, JAG1, LEF1, LGR5, MITF, MSX1, MYC, NEUROD1, NKD1, NODAL, NOTCH2, NOTUM, NRCAM, OPN, PAX3, PPARD, PTGS2, RNF43, SNAI1, SP5, TCF7, TERT, TNFRSF19, VEGFA and ZNRF3 are representative β-catenin target genes. β-catenin signaling is involved in myofibroblast activation and subsequent pulmonary fibrosis, in addition to other types of fibrosis. β-catenin and NF-κB signaling activation are involved in field cancerization in the stomach associated with Helicobacter pylori (H. pylori) infection and in the liver associated with hepatitis C virus (HCV) infection and other etiologies. β-catenin-targeted therapeutics are functionally classified into β-catenin inhibitors targeting upstream regulators (AZ1366, ETC-159, G007-LK, GNF6231, ipafricept, NVP-TNKS656, rosmantuzumab, vantictumab, WNT-C59, WNT974 and XAV939), β-catenin inhibitors targeting protein-protein interactions (CGP049090, CWP232228, E7386, ICG-001, LF3 and PRI-724), β-catenin inhibitors targeting epigenetic regulators (PKF118-310), β-catenin inhibitors targeting mediator complexes (CCT251545 and cortistatin A) and β-catenin inhibitors targeting transmembrane-type transcriptional outputs, including CD44v6, FZD7 and LGR5. Eradicating H. pylori and HCV is the optimal approach for the first-line prevention of gastric cancer and hepatocellular carcinoma (HCC), respectively. However, β-catenin inhibitors may be applicable for the prevention of organ fibrosis, second-line HCC prevention and treating β-catenin-driven cancer. The multi-layered prevention and treatment strategy of β-catenin-related human diseases is necessary for the practice of personalized medicine and implementation of precision medicine.

Enhancer Remodeling and MicroRNA Alterations Are Associated with Acquired Resistance to ALK Inhibitors

Anaplastic lymphoma kinase (ALK) inhibitors are highly effective in patients with ALK fusion-positive lung cancer, but acquired resistance invariably emerges. Identification of secondary mutations has received considerable attention, but most cases cannot be explained by genetic causes alone, raising the possibility of epigenetic mechanisms in acquired drug resistance. Here, we investigated the dynamic changes in the transcriptome and enhancer landscape during development of acquired resistance to ALK inhibitors. Histone H3 lysine 27 acetylation (H3K27ac) was profoundly altered during acquisition of resistance, and enhancer remodeling induced expression changes in both miRNAs and mRNAs. Decreased H3K27ac levels and reduced miR-34a expression associated with the activation of target genes such as AXL. Panobinostat, a pan-histone deacetylase inhibitor, altered the H3K27ac profile and activated tumor-suppressor miRNAs such as miR-449, another member of the miR-34 family, and synergistically induced antiproliferative effects with ALK inhibitors on resistant cells, xenografts, and EML4-ALK transgenic mice. Paired analysis of patient samples before and after treatment with ALK inhibitors revealed that repression of miR-34a or miR-449a and activation of AXL were mutually exclusive of secondary mutations in ALK. Our findings indicate that enhancer remodeling and altered expression of miRNAs play key roles in cancer drug resistance and suggest that strategies targeting epigenetic pathways represent a potentially effective method for overcoming acquired resistance to cancer therapy.Significance: Epigenetic deregulation drives acquired resistance to ALK inhibitors in ALK-positive lung cancer. Cancer Res; 78(12); 3350-62. ©2018 AACR.

Whole-genome sequencing of multiple myeloma reveals oncogenic pathways are targeted somatically through multiple mechanisms

Multiple myeloma (MM) is a biologically heterogeneous malignancy, however, the mechanisms underlying this complexity are incompletely understood. We report an analysis of the whole-genome sequencing of 765 MM patients from CoMMpass. By employing promoter capture Hi-C in naïve B-cells, we identify cis-regulatory elements (CREs) that represent a highly enriched subset of the non-coding genome in which to search for driver mutations. We identify regulatory regions whose mutation significantly alters the expression of genes as candidate non-coding drivers, including copy number variation (CNV) at CREs of MYC and single-nucleotide variants (SNVs) in a PAX5 enhancer. To better inform the interplay between non-coding driver mutations with other driver mechanisms, and their respective roles in oncogenic pathways, we extended our analysis identifying coding drivers in 40 genes, including 11 novel candidates. We demonstrate the same pathways can be targeted by coding and non-coding mutations; exemplified by IRF4 and PRDM1, along with BCL6 and PAX5, genes that are central to plasma cell differentiation. This study reveals new insights into the complex genetic alterations driving MM development and an enhanced understanding of oncogenic pathways.

Finding cancer driver mutations in the era of big data research

In the last decade, the costs of genome sequencing have decreased considerably. The commencement of large-scale cancer sequencing projects has enabled cancer genomics to join the big data revolution. One of the challenges still facing cancer genomics research is determining which are the driver mutations in an individual cancer, as these contribute only a small subset of the overall mutation profile of a tumour. Focusing primarily on somatic single nucleotide mutations in this review, we consider both coding and non-coding driver mutations, and discuss how such mutations might be identified from cancer sequencing datasets. We describe some of the tools and database that are available for the annotation of somatic variants and the identification of cancer driver genes. We also address the use of genome-wide variation in mutation load to establish background mutation rates from which to identify driver mutations under positive selection. Finally, we describe the ways in which mutational signatures can act as clues for the identification of cancer drivers, as these mutations may cause, or arise from, certain mutational processes. By defining the molecular changes responsible for driving cancer development, new cancer treatment strategies may be developed or novel preventative measures proposed.

Non-coding RNAs: long non-coding RNAs and microRNAs in endocrine-related cancers

The human genome is 'pervasively transcribed' leading to a complex array of non-coding RNAs (ncRNAs) that far outnumber coding mRNAs. ncRNAs have regulatory roles in transcription and post-transcriptional processes as well numerous cellular functions that remain to be fully described. Best characterized of the 'expanding universe' of ncRNAs are the ~22 nucleotide microRNAs (miRNAs) that base-pair to target mRNA's 3' untranslated region within the RNA-induced silencing complex (RISC) and block translation and may stimulate mRNA transcript degradation. Long non-coding RNAs (lncRNAs) are classified as >200 nucleotides in length, but range up to several kb and are heterogeneous in genomic origin and function. lncRNAs fold into structures that interact with DNA, RNA and proteins to regulate chromatin dynamics, protein complex assembly, transcription, telomere biology and splicing. Some lncRNAs act as sponges for miRNAs and decoys for proteins. Nuclear-encoded lncRNAs can be taken up by mitochondria and lncRNAs are transcribed from mtDNA. Both miRNAs and lncRNAs are dysregulated in endocrine cancers. This review provides an overview on the current understanding of the regulation and function of selected lncRNAs and miRNAs, and their interaction, in endocrine-related cancers: breast, prostate, endometrial and thyroid.

Applications of RNA Indexes for Precision Oncology in Breast Cancer

Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.

An integrative bioinformatics approach reveals coding and non-coding gene variants associated with gene expression profiles and outcome in breast cancer molecular subtypes

Background

Sequence variations in coding and non-coding regions of the genome can affect gene expression and signalling pathways, which in turn may influence disease outcome.

Methods

In this study, we integrated somatic mutations, gene expression and clinical data from 930 breast cancer patients included in the TCGA database. Genes associated with single mutations in molecular breast cancer subtypes were identified by the Mann-Whitney U-test and their prognostic value was evaluated by Kaplan-Meier and Cox regression analyses. Results were confirmed using gene expression profiles from the Metabric data set (n = 1988) and whole-genome sequencing data from the TCGA cohort (n = 117).

Results

The overall mutation rate in coding and non-coding regions were significantly higher in ER-negative/HER2-negative tumours (P = 2.8E–03 and P = 2.4E–07, respectively). Recurrent sequence variations were identified in non-coding regulatory regions of several cancer-associated genes, including NBPF1, PIK3CA and TP53. After multivariate regression analysis, gene signatures associated with three coding mutations (CDH1, MAP3K1 and TP53) and two non-coding variants (CRTC3 and STAG2) in cancer-related genes predicted prognosis in ER-positive/HER2-negative tumours.

Conclusions

These findings demonstrate that sequence alterations influence gene expression and oncogenic pathways, possibly affecting the outcome of breast cancer patients. Our data provide potential opportunities to identify non-coding variations with functional and clinical relevance in breast cancer.

Whole genome sequencing analysis for cancer genomics and precision medicine

Explosive advances in next-generation sequencer (NGS) and computational analyses have enabled exploration of somatic protein-altered mutations in most cancer types, with coding mutation data intensively accumulated. However, there is limited information on somatic mutations in non-coding regions, including introns, regulatory elements and non-coding RNA. Structural variants and pathogen in cancer genomes remain widely unexplored. Whole genome sequencing (WGS) approaches can be used to comprehensively explore all types of genomic alterations in cancer and help us to better understand the whole landscape of driver mutations and mutational signatures in cancer genomes and elucidate the functional or clinical implications of these unexplored genomic regions and mutational signatures. This review describes recently developed technical approaches for cancer WGS and the future direction of cancer WGS, and discusses its utility and limitations as an analysis platform and for mutation interpretation for cancer genomics and cancer precision medicine. Taking into account the diversity of cancer genomes and phenotypes, interpretation of abundant mutation information from WGS, especially non-coding and structure variants, requires the analysis of large-scale WGS data integrated with RNA-Seq, epigenomics, immuno-genomic and clinic-pathological information.

Identification of Single Nucleotide Non-coding Driver Mutations in Cancer

Recent whole-genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non-coding regions of the genome potentially affecting transcriptional and post-transcriptional gene regulation. Although a few hallmark examples of driver mutations in non-coding regions have been reported, the functional role of the vast majority of somatic non-coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non-coding variants and the experimental methods used for functional validation and characterization.

MYBL1 rearrangements and MYB amplification in breast adenoid cystic carcinomas lacking the MYB-NFIB fusion gene

Breast adenoid cystic carcinoma (AdCC), a rare type of triple-negative breast cancer, has been shown to be driven by MYB pathway activation, most often underpinned by the MYB-NFIB fusion gene. Alternative genetic mechanisms, such as MYBL1 rearrangements, have been reported in MYB-NFIB-negative salivary gland AdCCs. Here we report on the molecular characterization by massively parallel sequencing of four breast AdCCs lacking the MYB-NFIB fusion gene. In two cases, we identified MYBL1 rearrangements (MYBL1-ACTN1 and MYBL1-NFIB), which were associated with MYBL1 overexpression. A third AdCC harboured a high-level MYB amplification, which resulted in MYB overexpression at the mRNA and protein levels. RNA-sequencing and whole-genome sequencing revealed no definite alternative driver in the fourth AdCC studied, despite high levels of MYB expression and the activation of pathways similar to those activated in MYB-NFIB-positive AdCCs. In this case, a deletion encompassing the last intron and part of exon 15 of MYB, including the binding site of ERG-1, a transcription factor that may downregulate MYB, and the exon 15 splice site, was detected. In conclusion, we demonstrate that MYBL1 rearrangements and MYB amplification probably constitute alternative genetic drivers of breast AdCCs, functioning through MYBL1 or MYB overexpression. These observations emphasize that breast AdCCs probably constitute a convergent phenotype, whereby activation of MYB and MYBL1 and their downstream targets can be driven by the MYB-NFIB fusion gene, MYBL1 rearrangements, MYB amplification, or other yet to be identified mechanisms. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Immuno-oncology from the perspective of somatic evolution

The past years have witnessed significant success for cancer immunotherapies that activate a patient's immune system against their cancer cells. At the same time our understanding of the genetic changes driving tumor evolution have progressed dramatically. The study of cancer genomes has shown that tumors are best understood as cell populations governed by the rules of evolution, leading to the emergence and spread of cell lineages with pathogenic mutations. Moreover, somatic evolution can explain the acquisition of mutations conferring drug resistance in the ever-lasting battle for reaching even fitter cell states. Here, we review the current state of the art of somatic cancer evolution and mechanisms of immune control and escape. We also revisit the principles of immunotherapy from the perspective of somatic evolution and discuss the basic rules of resistance to immunotherapies as dictated by evolution.

Pan-cancer analysis of long non-coding RNA NEAT1 in various cancers

Changes in the abundance and activity of long non-coding RNAs (lncRNAs) have an important impact on the development of cancer. The nuclear paraspeckle assembly transcript 1 (NEAT1) has been reported to be overexpressed in many types of cancer since its discovery. However, inconsistencies exist as NEAT1 can also function as a tumor suppressor in certain types of cancer, such as acute promyelocytic leukemia. Here we systematically describe our current understanding of NEAT1 in tumor initiation and progression. First, we analyzed the expression patterns of NEAT1 in various normal tissues and malignant cancers using data from public data portals, the Genotype-Tissue Expression Project (GTEx) and the Cancer Genome Atlas (TCGA), together with recent progress in the study of NEAT1 in various types of cancer. Second, we discussed the functions and mechanisms of NEAT1 in modulating tumor activity. Then, the upstream transcription factors and downstream microRNA targets of NEAT1 in the transcription cascade of cancers were also summarized. These data highlight the emerging role of NEAT1 in tumorigenesis, and present promising targetable pathways and clinical opportunities for tumor prevention and classifications.

An exome sequencing based approach for genome-wide association studies in the dog

Genome-wide association studies (GWAS) are widely used to identify loci associated with phenotypic traits in the domestic dog that has emerged as a model for Mendelian and complex traits. However, a disadvantage of GWAS is that it always requires subsequent fine-mapping or sequencing to pinpoint causal mutations. Here, we performed whole exome sequencing (WES) and canine high-density (cHD) SNP genotyping of 28 dogs from 3 breeds to compare the SNP and linkage disequilibrium characteristics together with the power and mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS. Using simulated phenotypes, we showed that EG-GWAS has a higher power than cHD to detect associations within target regions and less power outside target regions, with power being influenced further by sample size and SNP density. We analyzed two real phenotypes (hair length and furnishing), that are fixed in certain breeds to characterize mapping precision of the known causal mutations. EG-GWAS identified the associated exonic and 3'UTR variants within the FGF5 and RSPO2 genes, respectively, with only a few samples per breed. In conclusion, we demonstrated that EG-GWAS can identify loci associated with Mendelian phenotypes both within and across breeds.

Mapping genomic and transcriptomic alterations spatially in epithelial cells adjacent to human breast carcinoma

Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. Rather, we find a possibility of field cancerization surrounding the primary tumour by constructing a classifier that evaluates where epithelial samples were obtained relative to a tumour (cross-validated micro-averaged AUC = 0.74). We implement a spectral co-clustering algorithm to define biclusters. Relating to over-represented bicluster pathways, we further validate two genes with tissue microarrays and in vitro experiments. We highlight evidence suggesting that bicluster perturbation occurs early in tumour development.

Studying the spatial mutational and gene expression alterations in breast cancer could impact our understanding of breast cancer development. Here, the authors analyse a unique dataset of epithelial samples that highlight potential field cancerisation surrounding the primary tumour.

A prognostic 4-gene expression signature for patients with HER2-negative breast cancer receiving taxane and anthracycline-based chemotherapy

Breast cancer is a heterogeneous group of diseases with diverse clinicopathological and molecular features. At present, chemo-resistance still poses a major obstacle to successful treatment of HER-2 negative breast cancer. Reliable biomarkers are urgently needed to accurately predict the therapeutic sensitivity and prognosis of such patients. In this study, we identified 3145 distant relapse-free survival (DRFS) associated genes in 310 patients with HER-2 negative breast cancer receiving taxane and anthracycline-based chemotherapy in the GSE25055 dataset using univariate survival analysis. Four genes (SRPK1, PCCA, PRLR and FBP1) were further selected by a robust likelihood-based survival model. A risk score model was then constructed with the regression coefficients of the four signature genes. Patients in the training set were successfully divided into high- and low-risk groups with significant differences in DRFS between the two groups. The predictive value was further validated in GSE25065 dataset and similar results were observed. Moreover, the 4-gene signature was proved to have superior prognostic power compared with several clinical signatures such as tumor size, lymph node invasion, TNM stage and PAM50 signature. Our findings indicated that the 4-gene signature was a robust prognostic marker with a good prospect of clinical application for HER-2 negative breast cancer patients receiving taxane-anthracycline combination therapy.

Canonical and non-canonical WNT signaling in cancer stem cells and their niches: Cellular heterogeneity, omics reprogramming, targeted therapy and tumor plasticity (Review)

Cancer stem cells (CSCs), which have the potential for self-renewal, differentiation and de-differentiation, undergo epigenetic, epithelial-mesenchymal, immunological and metabolic reprogramming to adapt to the tumor microenvironment and survive host defense or therapeutic insults. Intra-tumor heterogeneity and cancer-cell plasticity give rise to therapeutic resistance and recurrence through clonal replacement and reactivation of dormant CSCs, respectively. WNT signaling cascades cross-talk with the FGF, Notch, Hedgehog and TGFβ/BMP signaling cascades and regulate expression of functional CSC markers, such as CD44, CD133 (PROM1), EPCAM and LGR5 (GPR49). Aberrant canonical and non-canonical WNT signaling in human malignancies, including breast, colorectal, gastric, lung, ovary, pancreatic, prostate and uterine cancers, leukemia and melanoma, are involved in CSC survival, bulk-tumor expansion and invasion/metastasis. WNT signaling-targeted therapeutics, such as anti-FZD1/2/5/7/8 monoclonal antibody (mAb) (vantictumab), anti-LGR5 antibody-drug conjugate (ADC) (mAb-mc-vc-PAB-MMAE), anti-PTK7 ADC (PF-06647020), anti-ROR1 mAb (cirmtuzumab), anti-RSPO3 mAb (rosmantuzumab), small-molecule porcupine inhibitors (ETC-159, WNT-C59 and WNT974), tankyrase inhibitors (AZ1366, G007-LK, NVP-TNKS656 and XAV939) and β-catenin inhibitors (BC2059, CWP232228, ICG-001 and PRI-724), are in clinical trials or preclinical studies for the treatment of patients with WNT-driven cancers. WNT signaling-targeted therapeutics are applicable for combination therapy with BCR-ABL, EGFR, FLT3, KIT or RET inhibitors to treat a subset of tyrosine kinase-driven cancers because WNT and tyrosine kinase signaling cascades converge to β-catenin for the maintenance and expansion of CSCs. WNT signaling-targeted therapeutics might also be applicable for combination therapy with immune checkpoint blockers, such as atezolizumab, avelumab, durvalumab, ipilimumab, nivolumab and pembrolizumab, to treat cancers with immune evasion, although the context-dependent effects of WNT signaling on immunity should be carefully assessed. Omics monitoring, such as genome sequencing and transcriptome tests, immunohistochemical analyses on PD-L1 (CD274), PD-1 (PDCD1), ROR1 and nuclear β-catenin and organoid-based drug screening, is necessary to determine the appropriate WNT signaling-targeted therapeutics for cancer patients.