The co-evolution of the genome and epigenome in colorectal cancer.

Colorectal malignancies are a leading cause of cancer-related death1 and have undergone extensive genomic study2,3. However, DNA mutations alone do not fully explain malignant transformation4-7. Here we investigate the co-evolution of the genome and epigenome of colorectal tumours at single-clone resolution using spatial multi-omic profiling of individual glands. We collected 1,370 samples from 30 primary cancers and 8 concomitant adenomas and generated 1,207 chromatin accessibility profiles, 527 whole genomes and 297 whole transcriptomes. We found positive selection for DNA mutations in chromatin modifier genes and recurrent somatic chromatin accessibility alterations, including in regulatory regions of cancer driver genes that were otherwise devoid of genetic mutations. Genome-wide alterations in accessibility for transcription factor binding involved CTCF, downregulation of interferon and increased accessibility for SOX and HOX transcription factor families, suggesting the involvement of developmental genes during tumourigenesis. Somatic chromatin accessibility alterations were heritable and distinguished adenomas from cancers. Mutational signature analysis showed that the epigenome in turn influences the accumulation of DNA mutations. This study provides a map of genetic and epigenetic tumour heterogeneity, with fundamental implications for understanding colorectal cancer biology.

Phenotypic plasticity and genetic control in colorectal cancer evolution.

Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, we find that the majority of intratumour variation in gene expression is not strongly heritable but rather 'plastic'. Somatic expression quantitative trait loci analysis identified a number of putative genetic controls of expression by cis-acting coding and non-coding mutations, the majority of which were clonal within a tumour, alongside frequent structural alterations. Consistently, computational inference on the spatial patterning of tumour phylogenies finds that a considerable proportion of CRCs did not show evidence of subclonal selection, with only a subset of putative genetic drivers associated with subclone expansions. Spatial intermixing of clones is common, with some tumours growing exponentially and others only at the periphery. Together, our data suggest that most genetic intratumour variation in CRC has no major phenotypic consequence and that transcriptional plasticity is, instead, widespread within a tumour.

Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data.

Quantification of the effect of spatial tumour sampling on the patterns of mutations detected in next-generation sequencing data is largely lacking. Here we use a spatial stochastic cellular automaton model of tumour growth that accounts for somatic mutations, selection, drift and spatial constraints, to simulate multi-region sequencing data derived from spatial sampling of a neoplasm. We show that the spatial structure of a solid cancer has a major impact on the detection of clonal selection and genetic drift from both bulk and single-cell sequencing data. Our results indicate that spatial constrains can introduce significant sampling biases when performing multi-region bulk sampling and that such bias becomes a major confounding factor for the measurement of the evolutionary dynamics of human tumours. We also propose a statistical inference framework that incorporates spatial effects within a growing tumour and so represents a further step forwards in the inference of evolutionary dynamics from genomic data. Our analysis shows that measuring cancer evolution using next-generation sequencing while accounting for the numerous confounding factors remains challenging. However, mechanistic model-based approaches have the potential to capture the sources of noise and better interpret the data.

Multiregion human bladder cancer sequencing reveals tumour evolution, bladder cancer phenotypes and implications for targeted therapy.

We present an evolutionary analysis of the relative time of genetic events underlying tumorigenesis in human bladder cancers from 10 whole cystectomy specimens using multiregional whole-exome sequencing. We timed bladder cancer drivers, mutational signatures, ploidy and copy number alterations, provided evidence for kataegis and correlated alterations with tumour areas and histological phenotypes. We found that: (1) heterogeneous tumour areas/phenotypes had distinct driver mutations, (2) papillary-invasive tumours divided early into two parallel evolving branches and (3) parallel evolution of subclonal driver mutations occurred. APOBEC mutational signatures were found to be very early events, active in carcinoma in situ, and often remained a dominant source of mutations throughout tumour evolution. Genetic progression from carcinoma in situ followed driver mutations in NA13/FAT1, ZBTB7B or EP300/USP28/KMT2D. Our results point towards a more diverse mutational trajectory of bladder tumorigenesis and underpin the importance of timing of mutational processes and clonal architecture in bladder cancer as important aspects for successful prognostication and therapy. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

ITIH5 mediates epigenetic reprogramming of breast cancer cells.

BACKGROUND: Extracellular matrix (ECM) is known to maintain epithelial integrity. In carcinogenesis ECM degradation triggers metastasis by controlling migration and differentiation including cancer stem cell (CSC) characteristics. The ECM-modulator inter- α-trypsin inhibitor heavy chain family member five (ITIH5) was recently identified as tumor suppressor potentially involved in impairing breast cancer progression but molecular mechanisms underlying its function are still elusive. METHODS: ITIH5 expression was analyzed using the public TCGA portal. ITIH5-overexpressing single-cell clones were established based on T47D and MDA-MB-231 cell lines. Colony formation, growth, apoptosis, migration, matrix adhesion, traction force analyses and polarization of tumor cells were studied in vitro. Tumor-initiating characteristics were analyzed by generating a metastasis mouse model. To identify ITIH5-affected pathways we utilized genome wide gene expression and DNA methylation profiles. RNA-interference targeting the ITIH5-downstream regulated gene DAPK1 was used to confirm functional involvement. RESULTS: ITIH5 loss was pronounced in breast cancer subtypes with unfavorable prognosis like basal-type tumors. Functionally, cell and colony formation was impaired after ITIH5 re-expression in both cell lines. In a metastasis mouse model, ITIH5 expressing MDA-MB-231 cells almost completely failed to initiate lung metastases. In these metastatic cells ITIH5 modulated cell-matrix adhesion dynamics and altered biomechanical cues. The profile of integrin receptors was shifted towards ß1-integrin accompanied by decreased Rac1 and increased RhoA activity in ITIH5-expressing clones while cell polarization and single-cell migration was impaired. Instead ITIH5 expression triggered the formation of epithelial-like cell clusters that underwent an epigenetic reprogramming. 214 promoter regions potentially marked with either H3K4 and /or H3K27 methylation showed a hyper- or hypomethylated DNA configuration due to ITIH5 expression finally leading to re-expression of the tumor suppressor DAPK1. In turn, RNAi-mediated knockdown of DAPK1 in ITIH5-expressing MDA-MB-231 single-cell clones clearly restored cell motility. CONCLUSIONS: Our results provide evidence that ITIH5 triggers a reprogramming of breast cancer cells with known stem CSC properties towards an epithelial-like phenotype through global epigenetic changes effecting known tumor suppressor genes like DAPK1. Therewith, ITIH5 may represent an ECM modulator in epithelial breast tissue mediating suppression of tumor initiating cancer cell characteristics which are thought being responsible for the metastasis of breast cancer.

Epigenome and early selection determine the tumour-immune evolutionary trajectory of colorectal cancer.

Immune system control is a major hurdle that cancer evolution must circumvent. The relative timing and evolutionary dynamics of subclones that have escaped immune control remain incompletely characterized, and how immune-mediated selection shapes the epigenome has received little attention. Here, we infer the genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers (CRCs). We utilise our existing CRC multi-region multi-omic dataset that we supplement with high-resolution spatially-resolved neoantigen sequencing data and highly multiplexed imaging of the tumour microenvironment (TME). Analysis of somatic chromatin accessibility alterations (SCAAs) reveals frequent somatic loss of accessibility at antigen presenting genes, and that SCAAs contribute to silencing of neoantigens. We observe that strong immune escape and exclusion occur at the outset of CRC formation, and that within tumours, including at the microscopic level of individual tumour glands, additional immune escape alterations have negligible consequences for the immunophenotype of cancer cells. Further minor immuno-editing occurs during local invasion and is associated with TME reorganisation, but that evolutionary bottleneck is relatively weak. Collectively, we show that immune evasion in CRC follows a "Big Bang" evolutionary pattern, whereby genetic, epigenetic and TME-driven immune evasion acquired by the time of transformation defines subsequent cancer-immune evolution.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer.

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Long-term Multimodal Recording Reveals Epigenetic Adaptation Routes in Dormant Breast Cancer Cells.

Patients with estrogen receptor-positive breast cancer receive adjuvant endocrine therapies (ET) that delay relapse by targeting clinically undetectable micrometastatic deposits. Yet, up to 50% of patients relapse even decades after surgery through unknown mechanisms likely involving dormancy. To investigate genetic and transcriptional changes underlying tumor awakening, we analyzed late relapse patients and longitudinally profiled a rare cohort treated with long-term neoadjuvant ETs until progression. Next, we developed an in vitro evolutionary study to record the adaptive strategies of individual lineages in unperturbed parallel experiments. Our data demonstrate that ETs induce nongenetic cell state transitions into dormancy in a stochastic subset of cells via epigenetic reprogramming. Single lineages with divergent phenotypes awaken unpredictably in the absence of recurrent genetic alterations. Targeting the dormant epigenome shows promising activity against adapting cancer cells. Overall, this study uncovers the contribution of epigenetic adaptation to the evolution of resistance to ETs. SIGNIFICANCE: This study advances the understanding of therapy-induced dormancy with potential clinical implications for breast cancer. Estrogen receptor-positive breast cancer cells adapt to endocrine treatment by entering a dormant state characterized by strong heterochromatinization with no recurrent genetic changes. Targeting the epigenetic rewiring impairs the adaptation of cancer cells to ETs. See related commentary by Llinas-Bertran et al., p. 704. This article is featured in Selected Articles from This Issue, p. 695.

Contribution of pks+ E. coli mutations to colorectal carcinogenesis.

The dominant mutational signature in colorectal cancer genomes is C > T deamination (COSMIC Signature 1) and, in a small subgroup, mismatch repair signature (COSMIC signatures 6 and 44). Mutations in common colorectal cancer driver genes are often not consistent with those signatures. Here we perform whole-genome sequencing of normal colon crypts from cancer patients, matched to a previous multi-omic tumour dataset. We analyse normal crypts that were distant vs adjacent to the cancer. In contrast to healthy individuals, normal crypts of colon cancer patients have a high incidence of pks + (polyketide synthases) E.coli (Escherichia coli) mutational and indel signatures, and this is confirmed by metagenomics. These signatures are compatible with many clonal driver mutations detected in the corresponding cancer samples, including in chromatin modifier genes, supporting their role in early tumourigenesis. These results provide evidence that pks + E.coli is a potential driver of carcinogenesis in the human gut.

Circulating tumour DNA sequencing to determine therapeutic response and identify tumour heterogeneity in patients with paediatric solid tumours.

OBJECTIVE: Clinical diagnostic sequencing of circulating tumour DNA (ctDNA) is well advanced for adult patients, but application to paediatric cancer patients lags behind. METHODS: To address this, we have developed a clinically relevant (67 gene) NGS capture panel and accompanying workflow that enables sensitive and reliable detection of low-frequency genetic variants in cell-free DNA (cfDNA) from children with solid tumours. We combined gene panel sequencing with low pass whole-genome sequencing of the same library to inform on genome-wide copy number changes in the blood. RESULTS: Analytical validity was evaluated using control materials, and the method was found to be highly sensitive (0.96 for SNVs and 0.97 for INDEL), specific (0.82 for SNVs and 0.978 for INDEL), repeatable (>0.93 [95% CI: 0.89-0.95]) and reproducible (>0.87 [95% CI: 0.87-0.95]). Potential for clinical application was demonstrated in 39 childhood cancer patients with a spectrum of solid tumours in which the single nucleotide variants expected from tumour sequencing were detected in cfDNA in 94.4% (17/18) of cases with active extracranial disease. In 13 patients, where serial samples were available, we show a close correlation between events detected in cfDNA and treatment response, demonstrate that cfDNA analysis could be a useful tool to monitor disease progression, and show cfDNA sequencing has the potential to identify targetable variants that were not detected in tumour samples. CONCLUSIONS: This is the first pan-cancer DNA sequencing panel that we know to be optimised for cfDNA in children for blood-based molecular diagnostics in paediatric solid tumours.

Mapping the breast cancer metastatic cascade onto ctDNA using genetic and epigenetic clonal tracking.

Circulating tumour DNA (ctDNA) allows tracking of the evolution of human cancers at high resolution, overcoming many limitations of tissue biopsies. However, exploiting ctDNA to determine how a patient's cancer is evolving in order to aid clinical decisions remains difficult. This is because ctDNA is a mix of fragmented alleles, and the contribution of different cancer deposits to ctDNA is largely unknown. Profiling ctDNA almost invariably requires prior knowledge of what genomic alterations to track. Here, we leverage on a rapid autopsy programme to demonstrate that unbiased genomic characterisation of several metastatic sites and concomitant ctDNA profiling at whole-genome resolution reveals the extent to which ctDNA is representative of widespread disease. We also present a methylation profiling method that allows tracking evolutionary changes in ctDNA at single-molecule resolution without prior knowledge. These results have critical implications for the use of liquid biopsies to monitor cancer evolution in humans and guide treatment.

Subclonal reconstruction of tumors by using machine learning and population genetics.

Most cancer genomic data are generated from bulk samples composed of mixtures of cancer subpopulations, as well as normal cells. Subclonal reconstruction methods based on machine learning aim to separate those subpopulations in a sample and infer their evolutionary history. However, current approaches are entirely data driven and agnostic to evolutionary theory. We demonstrate that systematic errors occur in the analysis if evolution is not accounted for, and this is exacerbated with multi-sampling of the same tumor. We present a novel approach for model-based tumor subclonal reconstruction, called MOBSTER, which combines machine learning with theoretical population genetics. Using public whole-genome sequencing data from 2,606 samples from different cohorts, new data and synthetic validation, we show that this method is more robust and accurate than current techniques in single-sample, multiregion and longitudinal data. This approach minimizes the confounding factors of nonevolutionary methods, thus leading to more accurate recovery of the evolutionary history of human cancers.

Colorectal cancer residual disease at maximal response to EGFR blockade displays a druggable Paneth cell-like phenotype.

Blockade of epidermal growth factor receptor (EGFR) causes tumor regression in some patients with metastatic colorectal cancer (mCRC). However, residual disease reservoirs typically remain even after maximal response to therapy, leading to relapse. Using patient-derived xenografts (PDXs), we observed that mCRC cells surviving EGFR inhibition exhibited gene expression patterns similar to those of a quiescent subpopulation of normal intestinal secretory precursors with Paneth cell characteristics. Compared with untreated tumors, these pseudodifferentiated tumor remnants had reduced expression of genes encoding EGFR-activating ligands, enhanced activity of human epidermal growth factor receptor 2 (HER2) and HER3, and persistent signaling along the phosphatidylinositol 3-kinase (PI3K) pathway. Clinically, properties of residual disease cells from the PDX models were detected in lingering tumors of responsive patients and in tumors of individuals who had experienced early recurrence. Mechanistically, residual tumor reprogramming after EGFR neutralization was mediated by inactivation of Yes-associated protein (YAP), a master regulator of intestinal epithelium recovery from injury. In preclinical trials, Pan-HER antibodies minimized residual disease, blunted PI3K signaling, and induced long-term tumor control after treatment discontinuation. We found that tolerance to EGFR inhibition is characterized by inactivation of an intrinsic lineage program that drives both regenerative signaling during intestinal repair and EGFR-dependent tumorigenesis. Thus, our results shed light on CRC lineage plasticity as an adaptive escape mechanism from EGFR-targeted therapy and suggest opportunities to preemptively target residual disease.

A hierarchical testing strategy for micropollutants in drinking water regarding their potential endocrine-disrupting effects-towards health-related indicator values.

In Germany, micropollutants that (may) occur in drinking water are assessed by means of the health-related indicator value (HRIV concept), developed by the German Federal Environment Agency. This concept offers five threshold values (≤ 0.01 to ≤ 3 µg l-1) depending on availability and completeness of data regarding genotoxicity, neurotoxicity, and germ cell-damaging potential. However, the HRIV concept is yet lacking integration of endocrine disruptors as one of the most prominent toxicological concerns in water bodies, including drinking water. Thresholds and proposed bioassays hence urgently need to be defined. Since endocrine disruption of ubiquitary chemicals as pharmaceuticals, industrial by-products, or pesticides is a big issue in current ecotoxicology, the aim of this study was to explore endocrine effects, i.e., estrogenic and androgenic effects, as an important, additional toxicological mode of action for the HRIV concept using a hierarchical set of well-known but improved bioassays. Results indicate that all of the 13 tested substances, industrial chemicals and combustion products (5), pharmaceuticals and medical agents (4), and pesticides and metabolites (4), have no affinity to the estrogen and androgen receptor in human U2OS cells without metabolic activation, even when dosed at their water solubility limit, while in contrast some of these substances showed estrogenic effects in the RYES assay, as predicted in pre-test QSAR analysis. Using a specifically developed S9-mix with the U2OS cells, those micropollutants, i.e., Benzo[a]pyrene, 2,4-Dichlorophenol, 3,3-Dichlorbenzidin, 3,4-Dichloranilin, and diclofenac, they show estrogenic effects at the same concentration range as for the yeast cells. Three of the drinking water-relevant chemicals, i.e., atrazine, tributyltin oxide, and diclofenac, caused effects on hormone production in the H295R assay, which can be correlated with changes in the expression of steroidogenic genes. One chemical, 17α-Ethinylestradiol, caused an estrogenic or anti-androgenic effect in the reproduction test with Potamopyrgus antipodarum. Considering these results, a proposal for a test strategy for micropollutants in drinking water regarding potential endocrine effects (hormonal effects on reproduction and sexual development) will be presented to enhance the existing HRIV concept.

Author Correction: Quantification of subclonal selection in cancer from bulk sequencing data.

In the version of this article originally published, in the "Theoretical framework of subclonal selection" section of the main text, ref. 11 instead of ref. 19 should have been cited at the end of the phrase "Our previously presented frequentist approach to detect subclonal selection from bulk sequencing data involves an R2 test statistic." The error has been corrected in the HTML and PDF versions of the article.

Quantification of subclonal selection in cancer from bulk sequencing data.

Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumor subclones remain unknown. Here we measure clone dynamics in human cancers by using computational modeling of subclonal selection and theoretical population genetics applied to high-throughput sequencing data. Our method determined the detectable subclonal architecture of tumor samples and simultaneously measured the selective advantage and time of appearance of each subclone. We demonstrate the accuracy of our approach and the extent to which evolutionary dynamics are recorded in the genome. Application of our method to high-depth sequencing data from breast, gastric, blood, colon and lung cancer samples, as well as metastatic deposits, showed that detectable subclones under selection, when present, consistently emerged early during tumor growth and had a large fitness advantage (>20%). Our quantitative framework provides new insight into the evolutionary trajectories of human cancers and facilitates predictive measurements in individual tumors from widely available sequencing data.

Epigenetic loss of putative tumor suppressor SFRP3 correlates with poor prognosis of lung adenocarcinoma patients.

Secreted frizzled related protein 3 (SFRP3) contains a cysteine-rich domain (CRD) that shares homology with Frizzled CRD and regulates WNT signaling. Independent studies showed epigenetic silencing of SFRP3 in melanoma and hepatocellular carcinoma. Moreover, a tumor suppressive function of SFRP3 was shown in androgen-independent prostate and gastric cancer cells. The current study is the first to investigate SFRP3 expression and its potential clinical impact on non-small cell lung carcinoma (NSCLC). WNT signaling components present on NSCLC subtypes were preliminary elucidated by expression data of The Cancer Genome Atlas (TCGA). We identified a distinct expression signature of relevant WNT signaling components that differ between adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). Of interest, canonical WNT signaling is predominant in LUAD samples and non-canonical WNT signaling is predominant in LUSC. In line, high SFRP3 expression resulted in beneficial clinical outcome for LUAD but not for LUSC patients. Furthermore, SFRP3 mRNA expression was significantly decreased in NSCLC tissue compared to normal lung samples. TCGA data verified the reduction of SFRP3 in LUAD and LUSC patients. Moreover, DNA hypermethylation of SFRP3 was evaluated in the TCGA methylation dataset resulting in epigenetic inactivation of SFRP3 expression in LUAD, but not in LUSC, and was validated by pyrosequencing of our NSCLC tissue cohort and in vitro demethylation experiments. Immunohistochemistry confirmed SFRP3 protein downregulation in primary NSCLC and indicated abundant expression in normal lung tissue. Two adenocarcinoma gain-of-function models were used to analyze the functional impact of SFRP3 on cell proliferation and regulation of CyclinD1 expression in vitro. Our results indicate that SFRP3 acts as a novel putative tumor suppressor gene in adenocarcinoma of the lung possibly regulating canonical WNT signaling.

Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial.

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in RAS wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as RAS wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies.Significance: Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. Cancer Discov; 8(10); 1270-85. ©2018 AACR. See related commentary by Siravegna and Corcoran, p. 1213 This article is highlighted in the In This Issue feature, p. 1195.

Robust RNA-based in situ mutation detection delineates colorectal cancer subclonal evolution.

Intra-tumor heterogeneity (ITH) is a major underlying cause of therapy resistance and disease recurrence, and is a read-out of tumor growth. Current genetic ITH analysis methods do not preserve spatial context and may not detect rare subclones. Here, we address these shortfalls by developing and validating BaseScope-a novel mutation-specific RNA in situ hybridization assay. We target common point mutations in the BRAF, KRAS and PIK3CA oncogenes in archival colorectal cancer samples to precisely map the spatial and morphological context of mutant subclones. Computational modeling suggests that subclones must arise sufficiently early, or carry a considerable fitness advantage, to form large or spatially disparate subclones. Examples of putative treatment-resistant cells isolated in small topographical areas are observed. The BaseScope assay represents a significant technical advance for in situ mutation detection that provides new insight into tumor evolution, and could have ramifications for selecting patients for treatment.

Abundant NDRG2 Expression Is Associated with Aggressiveness and Unfavorable Patients' Outcome in Basal-Like Breast Cancer.

NDRG2, a member of the N-myc downstream-regulated gene family, is thought to be a putative tumor suppressor gene with promising clinical impact in breast cancer. Since breast cancer comprises heterogeneous intrinsic subtypes with distinct clinical outcomes we investigated the pivotal role of NDRG2 in basal-type breast cancers. Based on subtype classified tumor (n = 45) and adjacent normal tissues (n = 17) we examined NDRG2 mRNA expression and CpG-hypermethylation, whose significance was further validated by independent data sets from The Cancer Genome Atlas (TCGA). In addition, NDRG2 protein expression was evaluated immunohistochemically using a tissue micro array (TMA, n = 211). In vitro, we investigated phenotypic effects caused by NDRG2 silencing in the basal A-like HCC1806 as well as NDRG2 over-expression in basal A-like BT20 compared to luminal-type MCF7 breast cancer cells. Our tissue collections demonstrated an overall low NDRG2 mRNA expression in breast cancer subtypes compared to normal breast tissue in line with an increased CpG-hypermethylation in breast cancer tissue. Independent TCGA data sets verified a significant (P<0.001) expression loss of NDRG2 in breast tumors. Of interest, basal-like tumors more frequently retained abundant NDRG2 expression concordant with a lower CpG-hypermethylation. Unexpectedly, basal-like breast cancer revealed an association of NDRG2 expression with unfavorable patients' outcome. In line with this observation, in vitro experiments demonstrated reduced proliferation and migration rates (~20%) in HCC1806 cells following NDRG2 silencing. In contrast, NDRG2 over-expressing luminal-type MCF7 cells demonstrated a 26% decreased proliferation rate. Until now, this is the first study investigating the putative role of NDRG2 in depth in basal-type breast cancer. Our data indicate that the described putative tumor suppressive function of NDRG2 may be confined to luminal- and basal B-type breast cancers.