Recurrent and functional regulatory mutations in breast cancer

Transcriptional regulation of normal human mammary cell heterogeneity and its perturbation in breast cancer

The mammary gland in adult women consists of biologically distinct cell types that differ in their surface phenotypes. Isolation and molecular characterization of these subpopulations of mammary cells have provided extensive insights into their different transcriptional programs and regulation. This information is now serving as a baseline for interpreting the heterogeneous features of human breast cancers. Examination of breast cancer mutational profiles further indicates that most have undergone a complex evolutionary process even before being detected. The consequent intra-tumoral as well as inter-tumoral heterogeneity of these cancers thus poses major challenges to deriving information from early and hence likely pervasive changes in potential therapeutic interest. Recently described reproducible and efficient methods for generating human breast cancers de novo in immunodeficient mice transplanted with genetically altered primary cells now offer a promising alternative to investigate initial stages of human breast cancer development. In this review, we summarize current knowledge about key transcriptional regulatory processes operative in these partially characterized subpopulations of normal human mammary cells and effects of disrupting these processes in experimentally produced human breast cancers.

Passenger hotspot mutations in cancer driven by APOBEC3A and mesoscale genomic features

Cancer drivers require statistical modeling to distinguish them from passenger events, which accumulate during tumorigenesis but provide no fitness advantage to cancer cells. The discovery of driver genes and mutations relies on the assumption that exact positional recurrence is unlikely by chance; thus, the precise sharing of mutations across patients identifies drivers. Examining the mutation landscape in cancer genomes, we found that many recurrent cancer mutations previously designated as drivers are likely passengers. Our integrated bioinformatic and biochemical analyses revealed that these passenger hotspot mutations arise from the preference of APOBEC3A, a cytidine deaminase, for DNA stem-loops. Conversely, recurrent APOBEC-signature mutations not in stem-loops are enriched in well-characterized driver genes and may predict new drivers. This demonstrates that mesoscale genomic features need to be integrated into computational models aimed at identifying mutations linked to diseases.

MicroRNA-138-5p inhibits cell migration, invasion and EMT in breast cancer by directly targeting RHBDD1

BACKGROUND

Accumulating studies have identified that microRNAs (miRNAs) are novel regulators acting as tumor suppressors or oncogenes in tumor progression. The aim of the study is to investigate the functional roles of miR-138-5p in breast cancer (BC) cells and explore the underlying mechanisms by identifying its target gene.

METHODS AND RESULTS

Our results first showed that miR-138-5p expression was remarkably decreased in BC tissues and cells using quantitative real-time PCR analysis. Forced expression of miR-138-5p significantly suppressed cell migration and invasion ability of BC using transwell assay. Moreover, miR-138-5p overexpression suppressed cell epithelial-mesenchymal transition (EMT) phenomenon of BC by upregulating E-cadherin expression, but downregulating N-cadherin and Vimentin expression. More importantly, rhomboid domain-containing protein 1 (RHBDD1) was predicted as the direct target of miR-138-5p by TargetScan and miRanda, which was subsequently confirmed by luciferase reporter assay in BC cells. RHBDD1 was up-regulated in BC tissues and negatively correlated with miR-138-5p expression. Furthermore, forced expression of miR-138-5p could down-regulate the expression of RHBDD1, but overexpression of RHBDD1 reversed the suppressive effects of miR-138-5p in BC cell migration, invasion and EMT.

CONCLUSIONS

Our findings revealed the tumor-suppressive role of miR-138-5p in regulating BC migration by targeting RHBDD1, suggesting that miR-138-5p negatively regulating EMT might be a therapeutic target in BC.

Computational Biology Solutions to Identify Enhancers-target Gene Pairs

Enhancers are non-coding regulatory elements that are distant from their target gene. Their characterization still remains elusive especially due to challenges in achieving a comprehensive pairing of enhancers and target genes. A number of computational biology solutions have been proposed to address this problem leveraging the increasing availability of functional genomics data and the improved mechanistic understanding of enhancer action. In this review we focus on computational methods for genome-wide definition of enhancer-target gene pairs. We outline the different classes of methods, as well as their main advantages and limitations. The types of information integrated by each method, along with details on their applicability are presented and discussed. We especially highlight the technical challenges that are still unresolved and hamper the effective achievement of a satisfactory and comprehensive solution. We expect this field will keep evolving in the coming years due to the ever-growing availability of data and increasing insights into enhancers crucial role in regulating genome functionality.

Drug resistance: origins, evolution and characterization of genomic clones and the tumor ecosystem to optimize precise individualized therapy

Progress in understanding and overcoming fatal intrinsic and acquired resistance is slow, with only a few exceptions. Despite advances in modern genome and transcriptome analysis, the controversy of the three different theories on drug resistance and tumor progression, namely dynamic intratumor heterogeneity, pre-existing minor genomic clones and tumor ecosystem, is unresolved. Moreover, evidence on transcriptional heterogeneity suggests the necessity of a drug bank for individualized, precise drug-sensitivity prediction. We propose a cancer type- and stage-specific clinicogenomic and tumor ecosystemic concept toward cancer precision medicine, focusing on early therapeutic resistance and relapse.

Identification of Cancer Drivers at CTCF Insulators in 1,962 Whole Genomes

Recent studies have shown that mutations at non-coding elements, such as promoters and enhancers, can act as cancer drivers. However, an important class of non-coding elements, namely CTCF insulators, has been overlooked in the previous driver analyses. We used insulator annotations from CTCF and cohesin ChIA-PET and analyzed somatic mutations in 1,962 whole genomes from 21 cancer types. Using the heterogeneous patterns of transcription-factor-motif disruption, functional impact, and recurrence of mutations, we developed a computational method that revealed 21 insulators showing signals of positive selection. In particular, mutations in an insulator in multiple cancer types, including 16% of melanoma samples, are associated with TGFB1 up-regulation. Using CRISPR-Cas9, we find that alterations at two of the most frequently mutated regions in this insulator increase cell growth by 40%-50%, supporting the role of this boundary element as a cancer driver. Thus, our study reveals several CTCF insulators as putative cancer drivers.

Impact of cancer mutational signatures on transcription factor motifs in the human genome

Background

Somatic mutations in cancer genomes occur through a variety of molecular mechanisms, which contribute to different mutational patterns. To summarize these, mutational signatures have been defined using a large number of cancer genomes, and related to distinct mutagenic processes. Each cancer genome can be compared to this reference dataset and its exposure to one or the other signature be determined. Given the very different mutational patterns of these signatures, we anticipate that they will have distinct impact on genomic elements, in particular motifs for transcription factor binding sites (TFBS).

Methods

We used the 30 mutational signatures from the COSMIC database, and derived a theoretical framework to infer the impact of these signatures on the alteration of transcription factor (TF) binding motifs from the JASPAR database. Hence, we translated the trinucleotide mutation frequencies of the signatures into alteration frequencies of specific TF binding motifs, leading either to creation or disruption of these motifs.

Results

Motif families show different susceptibility to alterations induced by the mutational signatures. For certain motifs, a high correlation is observed between the TFBS motif creation and disruption events related to the information content of the motif. Moreover, we observe striking patterns regarding for example the Ets-motif family, for which a high impact of UV induced signatures is observed. Our model also confirms the susceptibility of specific transcription factor motifs to deamination processes.

Conclusion

Our results show that the mutational signatures have different impact on the binding motifs of transcription factors and that for certain high complexity motifs there is a strong correlation between creation and disruption, related to the information content of the motif. This study represents a background estimation of the alterations due purely to mutational signatures in the absence of additional contributions, e.g. from evolutionary processes.

Electronic supplementary material

The online version of this article (10.1186/s12920-019-0525-4) contains supplementary material, which is available to authorized users.

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

FOXA1+ regulatory T cells: A novel T cell subset that suppresses antitumor immunity in lung cancer

INTRODUCTION

Regulatory T cells (Tregs) are important in the tumor microenvironment. Many subpopulations of Tregs have participated in suppressing antitumor immunity. Recently, FOXA1⁺ Tregs were reported as a novel subset of Tregs that control autoimmune diseases. However, their clinical value in lung cancer is unknown.

METHODS

We included 92 subjects in this study. Peripheral blood samples were collected from 15 lung cancer patients. Another 45 advanced stage lung cancer patients with malignant pleural effusion were enrolled for the analysis of FOXA1⁺ Tregs in pleural effusions. Lung cancer tissues were collected from 3 patients. In vitro experiments were conducted to ascertain the influence of FOXA1⁺ Tregs on T cells. Tumor-bearing mice model was utilized to explore the effects of Foxa1⁺ Treg on tumor growth and the prognoses.

RESULTS

Our data demonstrated that FOXA1⁺ Tregs were increased in lung cancer. Moreover, patients with more FOXA1⁺ Tregs showed more liver metastases and poorer treatment responses. In vitro assays revealed that FOXA1⁺ Tregs inhibited the proliferation of T cells, the production of IFN-γ and IL-2 by T cells. FOXA1⁺ Tregs promoted tumor growth and indicated poor prognosis in the mice model of lung cancer.

DISCUSSION

Collectively, our study is the first to investigate the suppressive function of FOXA1⁺ Tregs against T cells in lung cancer, and the results showed that FOXA1⁺ Tregs are markers of poor treatment responses in lung cancer patients. The inhibition of FOXA1⁺ Tregs represents a promising new strategy to enhance antitumor immunity.

Pro-oncogene Pokemon Promotes Prostate Cancer Progression by Inducing STRN4 Expression

Pokemon, also known as leukemia/lymphoma-related factor (LRF) is a pro-oncogenic protein highly expressed in several cancers. There have been few in vitro and animal studies about its malignant biological behavior and function, however, its role especially in prostate cancer has not been completely elucidated. Therefore, in this study, we identified that Pokemon is overexpressed in human prostate cancer tissue samples, and its suppression inhibits proliferation of prostate cancer cells, along with promotion of apoptosis. Furthermore, to explore the mechanism by which Pokemon promotes tumor progression, we observed that it binds to the promoter of STRN4 (striatin 4), a downstream target, and subsequently regulates its expression. In conclusion, our study indicated that Pokemon through stimulation of STRN4 expression promotes prostate tumor progression via a Pokemon /STRN4 axis.

The Untranslated Regions of mRNAs in Cancer

The 5' and 3' untranslated regions (UTRs) regulate crucial aspects of post-transcriptional gene regulation that are necessary for the maintenance of cellular homeostasis. When these processes go awry through mutation or misexpression of certain regulatory elements, the subsequent deregulation of oncogenic gene expression can drive or enhance cancer pathogenesis. Although the number of known cancer-related mutations in UTR regulatory elements has recently increased markedly as a result of advances in whole-genome sequencing, little is known about how the majority of these genetic aberrations contribute functionally to disease. In this review we explore the regulatory functions of UTRs, how they are co-opted in cancer, new technologies to interrogate cancerous UTRs, and potential therapeutic opportunities stemming from these regions.

CRISPR links to long noncoding RNA function in mice: A practical approach

Next generation sequencing has uncovered a trove of short noncoding RNAs (e.g., microRNAs) and long noncoding RNAs (lncRNAs) that act as molecular rheostats in the control of diverse homeostatic processes. Meanwhile, the tsunamic emergence of clustered regularly interspaced short palindromic repeats (CRISPR) editing has transformed our influence over all DNA-carrying entities, heralding global CRISPRization. This is evident in biomedical research where the ease and low-cost of CRISPR editing has made it the preferred method of manipulating the mouse genome, facilitating rapid discovery of genome function in an in vivo context. Here, CRISPR genome editing components are updated for elucidating lncRNA function in mice. Various strategies are highlighted for understanding the function of lncRNAs residing in intergenic sequence space, as host genes that harbor microRNAs or other genes, and as natural antisense, overlapping or intronic genes. Also discussed is CRISPR editing of mice carrying human lncRNAs as well as the editing of competing endogenous RNAs. The information described herein should assist labs in the rigorous design of experiments that interrogate lncRNA function in mice where complex disease processes can be modeled thus accelerating translational discovery.

Whole-Genome Sequencing in Cancer

Genome sequencing of cancer has fundamentally advanced our understanding of the underlying biology of this disease, and more recently has provided approaches to characterize and monitor tumors in the clinic, guiding and evaluating treatment. Although cancer research is relying more on whole-genome characterization, the clinical application of genomics is largely limited to targeted sequencing approaches, tailored to capture specific clinically relevant biomarkers. However, as sequencing costs reduce, and the tools to effectively analyze complex and large-scale data improve, the ability to effectively characterize whole genomes at scale in a clinically relevant time frame is now being piloted. This ability effectively blurs the line between clinical cancer research and the clinical management of the disease. This leads to a new paradigm in cancer management in which real-time analysis of an individual's disease can have a rapid and lasting impact on our understanding of how clinical practices need to change to exploit novel therapeutic rationales. In this article, we will discuss how whole-genome sequencing (WGS), often combined with transcriptome analysis, has been used to understand cancer and how this approach is uniquely positioned to provide a comprehensive view of an evolving disease in response to therapy.

A Novel Carbon Quantum Dots Signal Amplification Strategy Coupled with Sandwich Electrochemiluminescence Immunosensor for the Detection of CA15-3 in Human Serum

A sensitive sandwich electrochemiluminescence immunosensor was established by employing graphene oxide-PEI-carbon quantum dots (CQDs)-Au nanohybrid as probe to measure carbohydrate antigen 15-3 (CA15-3), a breast cancer biomarker. In this work, nanocomposites of Ag nanoparticles and polydopamine (AgNPs-PDA) were synthesized by redox reaction between dopamine and Ag⁺. The nanocomposite with high surface area can provide an efficient substrate for immobilizing initial antibody (Ab1). Carbon quantum dots (CQDs) are fixed on polyethylenimine-functionalized graphene oxide (PEI-GO) by amide bonds. Au nanoparticles are modified on CQDs-decorated PEI-GO substrates. The secondary antibody (Ab2) was immobilized by AuNPs/CQDs-PEI-GO composite. CQDs can be assembled onto the surface of an electrode by incorporation of CA15-3 with Ab1 and Ab2. Under the synergistic action of AgNPs, polydopamine, AuNPs, and PEI-GO, the ECL signal of CQDs is greatly amplified as an excellent conductive material to facilitate electron transfer rate and further increase electrochemical detection capability. Under optimal conditions, the fabricated immunosensor showed a linear concentration range from 0.005 to 500 U mL^-1, with a detection limit of 0.0017 U mL^-1 (signal-to-noise ratio of 3) for CA15-3. The designed ECL immunosensor displayed receivable accuracy, excellent stability, and high specificity. The results of the detection of human serum samples are satisfactory, revealing that the method offers a potential application for the clinical diagnosis of tumor markers.

Mutational and Antigenic Landscape in Tumor Progression and Cancer Immunotherapy

Evolving neoplasms accumulate non-synonymous mutations at a high rate, potentially enabling the expression of antigenic epitopes that can be recognized by the immune system. Since they are not covered by central tolerance, such tumor neoantigens (TNAs) should be under robust immune control as they surge. However, genetic defects that impair cancer cell eradication by the immune system coupled with the establishment of local immunosuppression can enable TNA accumulation, which is generally associated with improved clinical sensitivity to various immunotherapies. Here, we explore how tumor-intrinsic factors and immunological processes shape the mutational and antigenic landscape of evolving neoplasms to influence clinical responses to immunotherapy, and propose strategies to achieve robust immunological control of the disease despite disabled immunosurveillance.

Forkhead box protein A1 confers resistance to transforming growth factor-β-induced apoptosis in breast cancer cells through inhibition of Smad3 nuclear translocation

Transforming growth factor-β (TGF-β) induces apoptosis of normal epithelial cells, such as mammary epithelium. Although breast cancer progression associates with acquisition of resistance to TGF-β-induced apoptosis, the molecular mechanisms underlying this resistance are largely unknown. Here, we show that forkhead box protein A1 (FOXA1), which is known as a pioneer transcription factor, suppresses TGF-β-induced apoptosis of estrogen receptor-positive breast cancer cells. FOXA1 is found to inhibit nuclear translocation of Smad3, a key transcription factor downstream of TGF-β signaling, through suppression of the binding of Smad3 to the nuclear import receptor importin7. Furthermore, RNA sequencing analyses show that knockdown of FOXA1 upregulates Smad3-mediated proapoptotic gene expression. These results demonstrate that FOXA1 as a potent survival factor that suppresses TGF-β-induced apoptosis by inhibiting Smad3 signaling in estrogen receptor-positive breast cancer cells. Thus, we provide evidence for the first time that FOXA1 localizing to the cytoplasm negatively regulates Smad3-induced apoptosis in TGF-β-mediated signal transduction.

Systematic interrogation of human promoters

Despite much research, our understanding of the architecture and cis-regulatory elements of human promoters is still lacking. Here, we devised a high-throughput assay to quantify the activity of approximately 15,000 fully designed sequences that we integrated and expressed from a fixed location within the human genome. We used this method to investigate thousands of native promoters and preinitiation complex (PIC) binding regions followed by in-depth characterization of the sequence motifs underlying promoter activity, including core promoter elements and TF binding sites. We find that core promoters drive transcription mostly unidirectionally and that sequences originating from promoters exhibit stronger activity than those originating from enhancers. By testing multiple synthetic configurations of core promoter elements, we dissect the motifs that positively and negatively regulate transcription as well as the effect of their combinations and distances, including a 10-bp periodicity in the optimal distance between the TATA and the initiator. By comprehensively screening 133 TF binding sites, we find that in contrast to core promoters, TF binding sites maintain similar activity levels in both orientations, supporting a model by which divergent transcription is driven by two distinct unidirectional core promoters sharing bidirectional TF binding sites. Finally, we find a striking agreement between the effect of binding site multiplicity of individual TFs in our assay and their tendency to appear in homotypic clusters throughout the genome. Overall, our study systematically assays the elements that drive expression in core and proximal promoter regions and sheds light on organization principles of regulatory regions in the human genome.

The Identification and Interpretation of cis-Regulatory Noncoding Mutations in Cancer

In the need to characterise the genomic landscape of cancers and to establish novel biomarkers and therapeutic targets, studies have largely focused on the identification of driver mutations within the protein-coding gene regions, where the most pathogenic alterations are known to occur. However, the noncoding genome is significantly larger than its protein-coding counterpart, and evidence reveals that regulatory sequences also harbour functional mutations that significantly affect the regulation of genes and pathways implicated in cancer. Due to the sheer number of noncoding mutations (NCMs) and the limited knowledge of regulatory element functionality in cancer genomes, differentiating pathogenic mutations from background passenger noise is particularly challenging technically and computationally. Here we review various up-to-date high-throughput sequencing data/studies and in silico methods that can be employed to interrogate the noncoding genome. We aim to provide an overview of available data resources as well as computational and molecular techniques that can help and guide the search for functional NCMs in cancer genomes.

Non-Coding RNAs in Breast Cancer: Intracellular and Intercellular Communication

Non-coding RNAs (ncRNAs) are regulators of intracellular and intercellular signaling in breast cancer. ncRNAs modulate intracellular signaling to control diverse cellular processes, including levels and activity of estrogen receptor α (ERα), proliferation, invasion, migration, apoptosis, and stemness. In addition, ncRNAs can be packaged into exosomes to provide intercellular communication by the transmission of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) to cells locally or systemically. This review provides an overview of the biogenesis and roles of ncRNAs: small nucleolar RNA (snRNA), circular RNAs (circRNAs), PIWI-interacting RNAs (piRNAs), miRNAs, and lncRNAs in breast cancer. Since more is known about the miRNAs and lncRNAs that are expressed in breast tumors, their established targets as oncogenic drivers and tumor suppressors will be reviewed. The focus is on miRNAs and lncRNAs identified in breast tumors, since a number of ncRNAs identified in breast cancer cells are not dysregulated in breast tumors. The identity and putative function of selected lncRNAs increased: nuclear paraspeckle assembly transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), steroid receptor RNA activator 1 (SRA1), colon cancer associated transcript 2 (CCAT2), colorectal neoplasia differentially expressed (CRNDE), myocardial infarction associated transcript (MIAT), and long intergenic non-protein coding RNA, Regulator of Reprogramming (LINC-ROR); and decreased levels of maternally-expressed 3 (MEG3) in breast tumors have been observed as well. miRNAs and lncRNAs are considered targets of therapeutic intervention in breast cancer, but further work is needed to bring the promise of regulating their activities to clinical use.

A Genetic Variant of rs145204276 in the Promoter Region of Long Noncoding RNA GAS5 Is Associated With a Reduced Risk of Breast Cancer

INTRODUCTION

Growth arrest-specific 5 (GAS5), downregulated in breast cancer (BC), functions as a tumor suppressor by affecting tumor growth and cell apoptosis in vivo and in vitro. This study was designed to determine whether an insertion (ins)/deletion (del) polymorphism (rs145204276 AGGCA/-) in the promoter region of GAS5 was a susceptibility gene to the occurrence of BC.

PATIENTS AND METHODS

A hospital-based case-control study was conducted and the GAS5 rs145204276 genotype was analyzed in 575 sporadic BC patients and 602 controls to test the association between the polymorphism and BC risk. Further functional analysis was performed to evaluate the effect of the polymorphism on the promoter activity and GAS5 expression levels using quantitative polymerase chain reaction and dual luciferase reporter assay.

RESULTS

The prevalence of BC was lower in carriers with rs145204276 ins/del and del/del genotypes compared with those with ins/ins genotype (adjusted odds ratio [OR], 0.74; 95% confidence interval [CI], 0.58-0.92; P = .009). An allelic test for association with BC was also significant (del vs. ins: adjusted OR, 0.78; 95% CI, 0.65-0.93; P = .007). Genotype-phenotype analysis revealed that individuals with rs145204276 ins/del and del/del genotypes expressed significantly higher levels of GAS5. Luciferase reporter analysis revealed that rs145204276 del allele enhanced the promoter activity of GAS5.

CONCLUSION

The rs145204276 del allele might protect against the development of BC via inducing the promoter activity by binding to transcriptional factor specificity protein 1, and finally resulting in higher levels of GAS5.

Recurrent mutations at estrogen receptor binding sites alter chromatin topology and distal gene expression in breast cancer

BACKGROUND

The mutational processes underlying non-coding cancer mutations and their biological significance in tumor evolution are poorly understood. To get better insights into the biological mechanisms of mutational processes in breast cancer, we integrate whole-genome level somatic mutations from breast cancer patients with chromatin states and transcription factor binding events.

RESULTS

We discover that a large fraction of non-coding somatic mutations in estrogen receptor (ER)-positive breast cancers are confined to ER binding sites. Notably, the highly mutated estrogen receptor binding sites are associated with more frequent chromatin loop contacts and the associated distal genes are expressed at higher level. To elucidate the functional significance of these non-coding mutations, we focus on two of the recurrently mutated estrogen receptor binding sites. Our bioinformatics and biochemical analysis suggest loss of DNA-protein interactions due to the recurrent mutations. Through CRISPR interference, we find that the recurrently mutated regulatory element at the LRRC3C-GSDMA locus impacts the expression of multiple distal genes. Using a CRISPR base editor, we show that the recurrent C→T conversion at the ZNF143 locus results in decreased TF binding, increased chromatin loop formation, and increased expression of multiple distal genes. This single point mutation mediates reduced response to estradiol-induced cell proliferation but increased resistance to tamoxifen-induced growth inhibition.

CONCLUSIONS

Our data suggest that ER binding is associated with localized accumulation of somatic mutations, some of which affect chromatin architecture, distal gene expression, and cellular phenotypes in ER-positive breast cancer.

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data

Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consuming, costly, poorly standardized, and non-reproducible. Here, we systematized and standardized somatic variant refinement using a machine learning approach. The final model incorporates 41,000 variants from 440 sequencing cases. This model accurately recapitulated manual refinement labels for three independent testing sets (13,579 variants) and accurately predicted somatic variants confirmed by orthogonal validation sequencing data (212,158 variants). The model improves on manual somatic refinement by reducing bias on calls otherwise subject to high inter-reviewer variability.

Discovering novel valid biomarkers and drugs in patient-centric genomic trials: the new epoch of precision surgical oncology

Despite standardization of multimodal treatment and approval of several targeted drugs for resectable, non-metastatic cancer (M0 patients), intrinsic and acquired resistance and relapse rates remain high, even in early-stage aggressive tumors. Genome analysis could overcome these unmet needs. Our comprehensive review underlines the controversy on stable or spatiotemporally evolving clones as well as promising yet inconclusive data on genome-based biomarkers and drug development. We propose clinicogenomic trials in M0 patients for the validation of intratumor heterogeneity (ITH), circulating genomic subclones (cGSs) and intra-patient genomic heterogeneity (IPGH) as biomarkers and simultaneous discovery of novel oncotargets. This evidence-based strategy highlights the coming of precision surgical oncology with a future perspective of understanding and disrupting deregulated transcriptional networks.

Lobaplatin inhibits breast cancer progression, cell proliferation while it induces cell apoptosis by downregulating MTDH expression

Objective

Lobaplatin shows antitumor activity against a wide range of tumors, including metastatic breast cancer (BCa). The overexpression of metadherin (MTDH) is associated with poor prognosis of BCa patients. This study was designed to investigate the effect of lobaplatin on MCF-7 cell proliferation and its association with MTDH expression.

Patients and methods

Clinical treatment for BCa using lobaplatin, in combination with other general chemotherapy drugs, was administered to 32 BCa patients. The safety, effectiveness, and prognosis in lobaplatin-treated BCa patients were compared with those in controls (n=32). In vitro experiments were performed in MCF-7 cells to investigate the effect of lobaplatin on cell proliferation, apoptosis, and MTDH expression.

Results

We found the intraoperative local chemotherapy using lobaplatin was safe and effective for BCa treatment, in comparison with the patients administered general chemotherapy drugs. Treatment of MCF-7 cell cultures with lobaplatin significantly reduced cell proliferation and increased cell apoptotic percentage. The expression of MTDH and Bcl-2 was inhibited by lobaplatin and that of Bax was increased by lobaplatin. Moreover, we observed the inhibition of MTDH by shRNA reduced cell proliferation and enhanced cell apoptosis.

Conclusion

Lobaplatin was a safe and effective adjuvant chemotherapy for BCa. The effect of lobaplatin on inhibiting MCF-7 cell proliferation and inducing cell apoptosis might be, as least in part, mediated by suppressing the expression of oncogene MTDH.

Long Non-coding RNA NEAT1: A Novel Target for Diagnosis and Therapy in Human Tumors

The nuclear paraspeckle assembly transcript 1 (NEAT1, a long non-coding RNA) is frequently overexpressed in human tumors, and higher NEAT1 expression is correlated with worse survival in cancer patients. NEAT1 drives tumor initiation and progression by modulating the expression of genes involved in the regulation of tumor cell growth, migration, invasion, metastasis, epithelial-to-mesenchymal transition, stem cell-like phenotype, chemoresistance and radioresistance, indicating the potential for NEAT1 to be a novel diagnostic biomarker and therapeutic target. Mechanistically, NEAT1 functions as a scaffold RNA molecule by interacting with EZH2 (a subunit of the polycomb repressive complex) to influence the expression of downstream effectors of EZH2, it also acts as a microRNA (miRNA) sponge to suppress the interactions between miRNAs and target mRNAs, and affects the expression of miR-129 by promoting the DNA methylation of the miR-129 promoter region. Knockdown of NEAT1 via small interfering RNA or short hairpin RNA inhibits the malignant behavior of tumor cells. In this review, we highlight the latest insights into the expression pattern, biological roles and mechanisms underlying the function and regulation of NEAT1 in tumors, and especially focus on its clinical implication as a new diagnostic biomarker and an attractive therapeutic target for cancers.

Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples

PURPOSE

Following automated variant calling, manual review of aligned read sequences is required to identify a high-quality list of somatic variants. Despite widespread use in analyzing sequence data, methods to standardize manual review have not been described, resulting in high inter- and intralab variability.

METHODS

This manual review standard operating procedure (SOP) consists of methods to annotate variants with four different calls and 19 tags. The calls indicate a reviewer's confidence in each variant and the tags indicate commonly observed sequencing patterns and artifacts that inform the manual review call. Four individuals were asked to classify variants prior to, and after, reading the SOP and accuracy was assessed by comparing reviewer calls with orthogonal validation sequencing.

RESULTS

After reading the SOP, average accuracy in somatic variant identification increased by 16.7% (p value = 0.0298) and average interreviewer agreement increased by 12.7% (p value < 0.001). Manual review conducted after reading the SOP did not significantly increase reviewer time.

CONCLUSION

This SOP supports and enhances manual somatic variant detection by improving reviewer accuracy while reducing the interreviewer variability for variant calling and annotation.

The high expression of FOXA1 is correlated with a favourable prognosis in salivary duct carcinomas: a study of 142 cases

AIMS

Salivary duct carcinoma (SDC) is an uncommon, aggressive tumour that, histologically, resembles high-grade mammary ductal carcinoma, and is characterised by the expression of androgen receptor (AR). The androgen signalling pathway, a potential therapeutic target, can be regulated by FOXA1. This study aimed to evaluate the clinicopathological implications of FOXA1 in SDC.

METHODS AND RESULTS

We examined the relationship between the immunoexpression of FOXA1 and FOXA1 mutations and clinicopathological factors, including the biomarker status and clinical outcome, in 142 SDCs. FOXA1 was expressed in 128 SDCs (90.1%); the immunoexpression was heterogeneous. SDCs with a higher FOXA1 labelling index (LI) (≥20%) more frequently showed less advanced tumors on T classification (P = 0.002). FOXA1 LI was correlated positively with the AR expression value (r = 0.430, P < 0.001). PI3K and p-mTOR positivity, and intact-PTEN, were associated with a higher FOXA1 LI. Twenty-two of 121 SDCs (18.2%) harboured FOXA1 gene mutations at the flanking regions in and around the forkhead DNA binding domain; however, the given gene mutation and the expression of FOXA1 were not significantly correlated. A multivariate analysis revealed that SDCs with a higher FOXA1 LI were associated with longer overall survival and progression-free survival (P = 0.029 and 0.016, respectively).

CONCLUSIONS

In SDC, FOXA1, which may biologically interact with the AR and PI3K signalling pathways, is a putative biomarker that may be associated with a favourable prognosis. Further studies are needed to apply the findings to the development of targeted personalised therapy for patients with SDC.

Promoter capture Hi-C-based identification of recurrent noncoding mutations in colorectal cancer

Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations^1-6. cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas^7,8. We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification¹. This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology.

Sc-ncDNAPred: A Sequence-Based Predictor for Identifying Non-coding DNA in Saccharomyces cerevisiae

With the rapid development of high-speed sequencing technologies and the implementation of many whole genome sequencing project, research in the genomics is advancing from genome sequencing to genome synthesis. Synthetic biology technologies such as DNA-based molecular assemblies, genome editing technology, directional evolution technology and DNA storage technology, and other cutting-edge technologies emerge in succession. Especially the rapid growth and development of DNA assembly technology may greatly push forward the success of artificial life. Meanwhile, DNA assembly technology needs a large number of target sequences of known information as data support. Non-coding DNA (ncDNA) sequences occupy most of the organism genomes, thus accurate recognizing of them is necessary. Although experimental methods have been proposed to detect ncDNA sequences, they are expensive for performing genome wide detections. Thus, it is necessary to develop machine-learning methods for predicting non-coding DNA sequences. In this study, we collected the ncDNA benchmark dataset of Saccharomyces cerevisiae and reported a support vector machine-based predictor, called Sc-ncDNAPred, for predicting ncDNA sequences. The optimal feature extraction strategy was selected from a group included mononucleotide, dimer, trimer, tetramer, pentamer, and hexamer, using support vector machine learning method. Sc-ncDNAPred achieved an overall accuracy of 0.98. For the convenience of users, an online web-server has been built at: http://server.malab.cn/Sc_ncDNAPred/index.jsp.

The Genomic Landscape of Endocrine-Resistant Advanced Breast Cancers

We integrated the genomic sequencing of 1,918 breast cancers, including 1,501 hormone receptor-positive tumors, with detailed clinical information and treatment outcomes. In 692 tumors previously exposed to hormonal therapy, we identified an increased number of alterations in genes involved in the mitogen-activated protein kinase (MAPK) pathway and in the estrogen receptor transcriptional machinery. Activating ERBB2 mutations and NF1 loss-of-function mutations were more than twice as common in endocrine resistant tumors. Alterations in other MAPK pathway genes (EGFR, KRAS, among others) and estrogen receptor transcriptional regulators (MYC, CTCF, FOXA1, and TBX3) were also enriched. Altogether, these alterations were present in 22% of tumors, mutually exclusive with ESR1 mutations, and associated with a shorter duration of response to subsequent hormonal therapies.

CRISPRa-mediated NEAT1 lncRNA upregulation induces formation of intact paraspeckles

Long noncoding RNAs (lncRNAs) are fundamental genomic regulatory factors under various physiological and pathological conditions. A class of lncRNAs termed architectural RNAs (arcRNAs) plays an essential scaffolding role in building nuclear bodies. NEAT1 arcRNA is an abundant, nuclear-retained lncRNA that constructs paraspeckle nuclear bodies. NEAT1 is upregulated in various developmental and disease conditions including cancer and virus infection. However, it remains unclear how elevated expression of NEAT1 influences such conditions. Here, we set up an experimental method to selectively increase NEAT1 expression. We applied the synergistic activation mediator (SAM) system using catalytically dead Cas9 (dCas9) proteins to activate transcription of the NEAT1 gene. We examined 10 pre-designed and 15 originally designed single-guide RNAs (sgRNAs) in the NEAT1 promoter region for CRISPR activation (CRISPRa). We validated several sgRNAs that we designed for the SAM system to strongly activate NEAT1 expression in two human cell lines and induced formation of paraspeckles with intact core-shell structures. Thus, this selective NEAT1 upregulation method using the SAM system would be useful for further functional analyses of NEAT1 lncRNA in both basic and applied research.

Frequent mutation of the FOXA1 untranslated region in prostate cancer

Prostate cancer has a low somatic mutation rate but non-coding regions remain underexplored. We sequenced the untranslated regions (UTRs) of 72 established driver genes in 428 patients with metastatic prostate cancer and identified FOXA1 3'-UTR mutations in 12% of patients. The mutations were predominantly insertions or deletions, covered the entire UTR without motif enrichment, and were not detected in other cancers. FOXA1 lies in head-on orientation with the androgen-regulated non-coding gene AL121790.1, resulting in strong prostate lineage-specific bidirectional transcription across the FOXA1 3'-UTR. This suggests transcriptional activity as a cause for the localized hypermutation. The indel-dominant pattern of somatic mutation extends into the FOXA1 coding region, where it is shaped by clonal selection to yield a cluster of non-frameshift indels inside the forkhead domain. Somatic FOXA1 3'-UTR mutations may prove useful for diagnostic and screening approaches, given their high frequency and lineage specificity.

Widespread Chromosomal Losses and Mitochondrial DNA Alterations as Genetic Drivers in Hürthle Cell Carcinoma

Hürthle cell carcinoma of the thyroid (HCC) is a form of thyroid cancer recalcitrant to radioiodine therapy that exhibits an accumulation of mitochondria. We performed whole-exome sequencing on a cohort of primary, recurrent, and metastatic tumors, and identified recurrent mutations in DAXX, TP53, NRAS, NF1, CDKN1A, ARHGAP35, and the TERT promoter. Parallel analysis of mtDNA revealed recurrent homoplasmic mutations in subunits of complex I of the electron transport chain. Analysis of DNA copy-number alterations uncovered widespread loss of chromosomes culminating in near-haploid chromosomal content in a large fraction of HCC, which was maintained during metastatic spread. This work uncovers a distinct molecular origin of HCC compared with other thyroid malignancies.

A Digital RNA Signature of Circulating Tumor Cells Predicting Early Therapeutic Response in Localized and Metastatic Breast Cancer

The multiplicity of new therapies for breast cancer presents a challenge for treatment selection. We describe a 17-gene digital signature of breast circulating tumor cell (CTC)-derived transcripts enriched from blood, enabling high-sensitivity early monitoring of response. In a prospective cohort of localized breast cancer, an elevated CTC score after three cycles of neoadjuvant therapy is associated with residual disease at surgery (P = 0.047). In a second prospective cohort with metastatic breast cancer, baseline CTC score correlates with overall survival (P = 0.02), as does persistent CTC signal after 4 weeks of treatment (P = 0.01). In the subset with estrogen receptor (ER)-positive disease, failure to suppress ER signaling within CTCs after 3 weeks of endocrine therapy predicts early progression (P = 0.008). Drug-refractory ER signaling within CTCs overlaps partially with presence of ESR1 mutations, pointing to diverse mechanisms of acquired endocrine drug resistance. Thus, CTC-derived digital RNA signatures enable noninvasive pharmacodynamic measurements to inform therapy in breast cancer.Significance: Digital analysis of RNA from CTCs interrogates treatment responses of both localized and metastatic breast cancer. Quantifying CTC-derived ER signaling during treatment identifies patients failing to respond to ER suppression despite having functional ESR1. Thus, noninvasive scoring of CTC-RNA signatures may help guide therapeutic choices in localized and advanced breast cancer. Cancer Discov; 8(10); 1286-99. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 1195.

Neat-en-ing up our understanding of p53 pathways in tumor suppression

Although the p53 transcription factor has a well-established role in tumor suppression, little is known about how the non-coding targets of p53 mediate its tumor suppression function. Analysis of ncRNAs regulated by p53 revealed Neat1 as a direct p53 target gene. Neat1 has physiological roles in the development and differentiation of the mammary gland and corpus luteum, but its roles in cancer have been conflicting. To unequivocally understand Neat1 function in cancer, we used Neat1 null mice. Interestingly, we found that Neat1 deficiency promotes transformation both in oncogene-expressing fibroblasts and in a mouse model for pancreatic cancer. Specifically, Neat1 loss in the pancreas results in the enhanced development of preneoplastic lesions associated with dampened expression of differentiation genes. While the exact mechanisms underlying tumor suppression are unknown, there are several described mechanisms that may be responsible for Neat1-mediated tumor suppression. Collectively, these findings suggest that Neat1 enforces differentiation to suppress pancreatic cancer.

Sputum Detection of Predisposing Genetic Mutations in Women with Pulmonary Nontuberculous Mycobacterial Disease

Nontuberculous mycobacterial lung disease (NTM), including Mycobacterium avium complex (MAC), is a growing health problem in North America and worldwide. Little is known about the molecular alterations occurring in the tissue microenvironment during NTM pathogenesis. Utilizing next generation sequencing, we sequenced sputum and matched lymphocyte DNA in 15 MAC patients for a panel of 19 genes known to harbor cancer susceptibility associated mutations. Thirteen of 15 NTM subjects had a diagnosis of breast cancer (BCa) before or after NTM infection. Thirty three percent (4/12) of these NTM-BCa cases exhibited at least 3 somatic mutations in sputa compared to matched lymphocytes. Twenty four somatic mutations were detected with at least one mutation in ATM, ERBB2, BARD1, BRCA1, BRCA2, AR, TP53, PALB2, CASP8, BRIP1, NBN and TGFB1 genes. All four NTM-BCa patients harboring somatic mutations also exhibited 15 germ line BRCA1 and BRCA2 mutations. The two NTM subjects without BCa exhibited twenty somatic mutations spanning BRCA1, BRCA1, BARD1, BRIP1, CHEK2, ERBB2, TP53, ATM, PALB2, TGFB1 and 3 germ line mutations in BRCA1 and BRCA2 genes. A single copy loss of STK11 and AR gene was noted in NTM-BCa subjects. Periodic screening of sputa may aid to develop risk assessment biomarkers for neoplastic diseases in NTM patients.

Chromatin reprogramming in breast cancer

Reprogramming of the chromatin landscape is a critical component to the transcriptional response in breast cancer. Effects of sex hormones such as estrogens and progesterone have been well described to have a critical impact on breast cancer proliferation. However, the complex network of the chromatin landscape, enhancer regions and mode of function of steroid receptors (SRs) and other transcription factors (TFs), is an intricate web of signaling and functional processes that is still largely misunderstood at the mechanistic level. In this review, we describe what is currently known about the dynamic interplay between TFs with chromatin and the reprogramming of enhancer elements. Emphasis has been placed on characterizing the different modes of action of TFs in regulating enhancer activity, specifically, how different SRs target enhancer regions to reprogram chromatin in breast cancer cells. In addition, we discuss current techniques employed to study enhancer function at a genome-wide level. Further, we have noted recent advances in live cell imaging technology. These single-cell approaches enable the coupling of population-based assays with real-time studies to address many unsolved questions about SRs and chromatin dynamics in breast cancer.