ILC2-driven innate immune checkpoint mechanism antagonizes NK cell antimetastatic function in the lung.

Metastasis constitutes the primary cause of cancer-related deaths, with the lung being a commonly affected organ. We found that activation of lung-resident group 2 innate lymphoid cells (ILC2s) orchestrated suppression of natural killer (NK) cell-mediated innate antitumor immunity, leading to increased lung metastases and mortality. Using multiple models of lung metastasis, we show that interleukin (IL)-33-dependent ILC2 activation in the lung is involved centrally in promoting tumor burden. ILC2-driven innate type 2 inflammation is accompanied by profound local suppression of interferon-γ production and cytotoxic function of lung NK cells. ILC2-dependent suppression of NK cells is elaborated via an innate regulatory mechanism, which is reliant on IL-5-induced lung eosinophilia, ultimately limiting the metabolic fitness of NK cells. Therapeutic targeting of IL-33 or IL-5 reversed NK cell suppression and alleviated cancer burden. Thus, we reveal an important function of IL-33 and ILC2s in promoting tumor metastasis via their capacity to suppress innate type 1 immunity.

NRG1 fusions in breast cancer.

BACKGROUND: NRG1 gene fusions may be clinically actionable, since cancers carrying the fusion transcripts can be sensitive to tyrosine kinase inhibitors. The NRG1 gene encodes ligands for the HER2(ERBB2)-ERBB3 heterodimeric receptor tyrosine kinase, and the gene fusions are thought to lead to autocrine stimulation of the receptor. The NRG1 fusion expressed in the breast cancer cell line MDA-MB-175 serves as a model example of such fusions, showing the proposed autocrine loop and exceptional drug sensitivity. However, its structure has not been properly characterised, its oncogenic activity has not been fully explained, and there is limited data on such fusions in breast cancer. METHODS: We analysed genomic rearrangements and transcripts of NRG1 in MDA-MB-175 and a panel of 571 breast cancers. RESULTS: We found that the MDA-MB-175 fusion-originally reported as a DOC4(TENM4)-NRG1 fusion, lacking the cytoplasmic tail of NRG1-is in reality a double fusion, PPP6R3-TENM4-NRG1, producing multiple transcripts, some of which include the cytoplasmic tail. We hypothesise that many NRG1 fusions may be oncogenic not for lacking the cytoplasmic domain but because they do not encode NRG1's nuclear-localised form. The fusion in MDA-MB-175 is the result of a very complex genomic rearrangement, which we partially characterised, that creates additional expressed gene fusions, RSF1-TENM4, TPCN2-RSF1, and MRPL48-GAB2. We searched for NRG1 rearrangements in 571 breast cancers subjected to genome sequencing and transcriptome sequencing and found four cases (0.7%) with fusions, WRN-NRG1, FAM91A1-NRG1, ARHGEF39-NRG1, and ZNF704-NRG1, all splicing into NRG1 at the same exon as in MDA-MB-175. However, the WRN-NRG1 and ARHGEF39-NRG1 fusions were out of frame. We identified rearrangements of NRG1 in many more (8% of) cases that seemed more likely to inactivate than to create activating fusions, or whose outcome could not be predicted because they were complex, or both. This is not surprising because NRG1 can be pro-apoptotic and is inactivated in some breast cancers. CONCLUSIONS: Our results highlight the complexity of rearrangements of NRG1 in breast cancers and confirm that some do not activate but inactivate. Careful interpretation of NRG1 rearrangements will therefore be necessary for appropriate patient management.

Identification of Subtypes of Barrett's Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data.

BACKGROUND & AIMS: Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity. METHODS: In a retrospective cohort study, we collected tissue samples and clinical data from 150 BE and 285 EAC cases from the Oesophageal Cancer Classification and Molecular Stratification consortium in the United Kingdom. We analyzed methylation profiles of all BE and EAC tissues and assigned them to subgroups using non-negative matrix factorization with k-means clustering. Data from whole-genome sequencing and transcriptome studies were then incorporated; we performed integrative methylation and RNA-sequencing analyses to identify genes that were suppressed with increased methylation in promoter regions. Levels of different immune cell types were computed using single-sample gene set enrichment methods. We derived 8 organoids from 8 EAC tissues and tested their sensitivity to different drugs. RESULTS: BE and EAC samples shared genome-wide methylation features, compared with normal tissues (esophageal, gastric, and duodenum; controls) from the same patients and grouped into 4 subtypes. Subtype 1 was characterized by DNA hypermethylation with a high mutation burden and multiple mutations in genes in cell cycle and receptor tyrosine signaling pathways. Subtype 2 was characterized by a gene expression pattern associated with metabolic processes (ATP synthesis and fatty acid oxidation) and lack methylation at specific binding sites for transcription factors; 83% of samples of this subtype were BE and 17% were EAC. The third subtype did not have changes in methylation pattern, compared with control tissue, but had a gene expression pattern that indicated immune cell infiltration; this tumor type was associated with the shortest time of patient survival. The fourth subtype was characterized by DNA hypomethylation associated with structure rearrangements, copy number alterations, with preferential amplification of CCNE1 (cells with this gene amplification have been reported to be sensitive to CDK2 inhibitors). Organoids with reduced levels of MGMT and CHFR expression were sensitive to temozolomide and taxane drugs. CONCLUSIONS: In a comprehensive integrated analysis of methylation, transcriptome, and genome profiles of more than 400 BE and EAC tissues, along with clinical data, we identified 4 subtypes that were associated with patient outcomes and potential responses to therapy.

Transcriptomic profiling reveals three molecular phenotypes of adenocarcinoma at the gastroesophageal junction.

Cancers occurring at the gastroesophageal junction (GEJ) are classified as predominantly esophageal or gastric, which is often difficult to decipher. We hypothesized that the transcriptomic profile might reveal molecular subgroups which could help to define the tumor origin and behavior beyond anatomical location. The gene expression profiles of 107 treatment-naïve, intestinal type, gastroesophageal adenocarcinomas were assessed by the Illumina-HTv4.0 beadchip. Differential gene expression (limma), unsupervised subgroup assignment (mclust) and pathway analysis (gage) were undertaken in R statistical computing and results were related to demographic and clinical parameters. Unsupervised assignment of the gene expression profiles revealed three distinct molecular subgroups, which were not associated with anatomical location, tumor stage or grade (p > 0.05). Group 1 was enriched for pathways involved in cell turnover, Group 2 was enriched for metabolic processes and Group 3 for immune-response pathways. Patients in group 1 showed the worst overall survival (p = 0.019). Key genes for the three subtypes were confirmed by immunohistochemistry. The newly defined intrinsic subtypes were analyzed in four independent datasets of gastric and esophageal adenocarcinomas with transcriptomic data available (RNAseq data: OCCAMS cohort, n = 158; gene expression arrays: Belfast, n = 63; Singapore, n = 191; Asian Cancer Research Group, n = 300). The subgroups were represented in the independent cohorts and pooled analysis confirmed the prognostic effect of the new subtypes. In conclusion, adenocarcinomas at the GEJ comprise three distinct molecular phenotypes which do not reflect anatomical location but rather inform our understanding of the key pathways expressed.

Mobile element insertions are frequent in oesophageal adenocarcinomas and can mislead paired-end sequencing analysis.

BACKGROUND: Mobile elements are active in the human genome, both in the germline and cancers, where they can mutate driver genes. RESULTS: While analysing whole genome paired-end sequencing of oesophageal adenocarcinomas to find genomic rearrangements, we identified three ways in which new mobile element insertions appear in the data, resembling translocation or insertion junctions: inserts where unique sequence has been transduced by an L1 (Long interspersed element 1) mobile element; novel inserts that are confidently, but often incorrectly, mapped by alignment software to L1s or polyA tracts in the reference sequence; and a combination of these two ways, where different sequences within one insert are mapped to different loci. We identified nine unique sequences that were transduced by neighbouring L1s, both L1s in the reference genome and L1s not present in the reference. Many of the resulting inserts were small fragments that include little or no recognisable mobile element sequence. We found 6 loci in the reference genome to which sequence reads from inserts were frequently mapped, probably erroneously, by alignment software: these were either L1 sequence or particularly long polyA runs. Inserts identified from such apparent rearrangement junctions averaged 16 inserts/tumour, range 0-153 insertions in 43 tumours. However, many inserts would not be detected by mapping the sequences to the reference genome, because they do not include sufficient mappable sequence. To estimate total somatic inserts we searched for polyA sequences that were not present in the matched normal or other normals from the same tumour batch, and were not associated with known polymorphisms. Samples of these candidate inserts were verified by sequencing across them or manual inspection of surrounding reads: at least 85 % were somatic and resembled L1-mediated events, most including L1Hs sequence. Approximately 100 such inserts were detected per tumour on average (range zero to approximately 700). CONCLUSIONS: Somatic mobile elements insertions are abundant in these tumours, with over 75 % of cases having a number of novel inserts detected. The inserts create a variety of problems for the interpretation of paired-end sequencing data.

Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer.

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

Molecular landscape and functional characterization of centrosome amplification in ovarian cancer.

High-grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tissues and 73 cell lines models, here we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and strongly associated with CIN and genome subclonality. Cell-based studies showed that high-prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel, the commonest treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.

Rearrangement processes and structural variations show evidence of selection in oesophageal adenocarcinomas.

Oesophageal adenocarcinoma (OAC) provides an ideal case study to characterize large-scale rearrangements. Using whole genome short-read sequencing of 383 cases, for which 214 had matched whole transcriptomes, we observed structural variations (SV) with a predominance of deletions, tandem duplications and inter-chromosome junctions that could be identified as LINE-1 mobile element (ME) insertions. Complex clusters of rearrangements resembling breakage-fusion-bridge cycles or extrachromosomal circular DNA accounted for 22% of complex SVs affecting known oncogenes. Counting SV events affecting known driver genes substantially increased the recurrence rates of these drivers. After excluding fragile sites, we identified 51 candidate new drivers in genomic regions disrupted by SVs, including ETV5, KAT6B and CLTC. RUNX1 was the most recurrently altered gene (24%), with many deletions inactivating the RUNT domain but preserved the reading frame, suggesting an altered protein product. These findings underscore the importance of identification of SV events in OAC with implications for targeted therapies.

The mutREAD method detects mutational signatures from low quantities of cancer DNA.

Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings.

Genomic copy number predicts esophageal cancer years before transformation.

Recent studies show that aneuploidy and driver gene mutations precede cancer diagnosis by many years1-4. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett's esophagus as an exemplar5. Shallow whole-genome sequencing of 777 biopsies, sampled from 88 patients in Barrett's esophagus surveillance over a period of up to 15 years, shows that genomic signals can distinguish progressive from stable disease even 10 years before histopathological transformation. These findings are validated on two independent cohorts of 76 and 248 patients. These methods are low-cost and applicable to standard clinical biopsy samples. Compared with current management guidelines based on histopathology and clinical presentation, genomic classification enables earlier treatment for high-risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.

GCNA Interacts with Spartan and Topoisomerase II to Regulate Genome Stability.

GCNA proteins are expressed across eukarya in pluripotent cells and have conserved functions in fertility. GCNA homologs Spartan (DVC-1) and Wss1 resolve DNA-protein crosslinks (DPCs), including Topoisomerase-DNA adducts, during DNA replication. Here, we show that GCNA mutants in mouse and C. elegans display defects in genome maintenance including DNA damage, aberrant chromosome condensation, and crossover defects in mouse spermatocytes and spontaneous genomic rearrangements in C. elegans. We show that GCNA and topoisomerase II (TOP2) physically interact in both mice and worms and colocalize on condensed chromosomes during mitosis in C. elegans embryos. Moreover, C. elegans gcna-1 mutants are hypersensitive to TOP2 poison. Together, our findings support a model in which GCNA provides genome maintenance functions in the germline and may do so, in part, by promoting the resolution of TOP2 DPCs.

Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma.

The poor outcomes in esophageal adenocarcinoma (EAC) prompted us to interrogate the pattern and timing of metastatic spread. Whole-genome sequencing and phylogenetic analysis of 388 samples across 18 individuals with EAC showed, in 90% of patients, that multiple subclones from the primary tumor spread very rapidly from the primary site to form multiple metastases, including lymph nodes and distant tissues-a mode of dissemination that we term 'clonal diaspora'. Metastatic subclones at autopsy were present in tissue and blood samples from earlier time points. These findings have implications for our understanding and clinical evaluation of EAC.

The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic.

Esophageal adenocarcinoma (EAC) is a poor-prognosis cancer type with rapidly rising incidence. Understanding of the genetic events driving EAC development is limited, and there are few molecular biomarkers for prognostication or therapeutics. Using a cohort of 551 genomically characterized EACs with matched RNA sequencing data, we discovered 77 EAC driver genes and 21 noncoding driver elements. We identified a mean of 4.4 driver events per tumor, which were derived more commonly from mutations than copy number alterations, and compared the prevelence of these mutations to the exome-wide mutational excess calculated using non-synonymous to synonymous mutation ratios (dN/dS). We observed mutual exclusivity or co-occurrence of events within and between several dysregulated EAC pathways, a result suggestive of strong functional relationships. Indicators of poor prognosis (SMAD4 and GATA4) were verified in independent cohorts with significant predictive value. Over 50% of EACs contained sensitizing events for CDK4 and CDK6 inhibitors, which were highly correlated with clinically relevant sensitivity in a panel of EAC cell lines and organoids.

Enhanced detection of circulating tumor DNA by fragment size analysis.

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for noninvasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 patients with cancer using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90 and 150 bp and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90 and 150 bp improved detection of tumor DNA, with more than twofold median enrichment in >95% of cases and more than fourfold enrichment in >10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with area under the curve (AUC) >0.99 compared to AUC <0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC > 0.91 compared to AUC < 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection and could complement or provide an alternative to deeper sequencing of cfDNA.

Hi-C as a tool for precise detection and characterisation of chromosomal rearrangements and copy number variation in human tumours.

Chromosomal rearrangements occur constitutionally in the general population and somatically in the majority of cancers. Detection of balanced rearrangements, such as reciprocal translocations and inversions, is troublesome, which is particularly detrimental in oncology where rearrangements play diagnostic and prognostic roles. Here we describe the use of Hi-C as a tool for detection of both balanced and unbalanced chromosomal rearrangements in primary human tumour samples, with the potential to define chromosome breakpoints to bp resolution. In addition, we show copy number profiles can also be obtained from the same data, all at a significantly lower cost than standard sequencing approaches.

Whole-genome sequencing of nine esophageal adenocarcinoma cell lines.

Esophageal adenocarcinoma (EAC) is highly mutated and molecularly heterogeneous. The number of cell lines available for study is limited and their genome has been only partially characterized. The availability of an accurate annotation of their mutational landscape is crucial for accurate experimental design and correct interpretation of genotype-phenotype findings. We performed high coverage, paired end whole genome sequencing on eight EAC cell lines-ESO26, ESO51, FLO-1, JH-EsoAd1, OACM5.1 C, OACP4 C, OE33, SK-GT-4-all verified against original patient material, and one esophageal high grade dysplasia cell line, CP-D. We have made available the aligned sequence data and report single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number alterations, identified by comparison with the human reference genome and known single nucleotide polymorphisms (SNPs). We compare these putative mutations to mutations found in primary tissue EAC samples, to inform the use of these cell lines as a model of EAC.

The Early Effects of Rapid Androgen Deprivation on Human Prostate Cancer.

UNLABELLED: The androgen receptor (AR) is the dominant growth factor in prostate cancer (PCa). Therefore, understanding how ARs regulate the human transcriptome is of paramount importance. The early effects of castration on human PCa have not previously been studied 27 patients medically castrated with degarelix 7 d before radical prostatectomy. We used mass spectrometry, immunohistochemistry, and gene expression array (validated by reverse transcription-polymerase chain reaction) to compare resected tumour with matched, controlled, untreated PCa tissue. All patients had levels of serum androgen, with reduced levels of intraprostatic androgen at prostatectomy. We observed differential expression of known androgen-regulated genes (TMPRSS2, KLK3, CAMKK2, FKBP5). We identified 749 genes downregulated and 908 genes upregulated following castration. AR regulation of α-methylacyl-CoA racemase expression and three other genes (FAM129A, RAB27A, and KIAA0101) was confirmed. Upregulation of oestrogen receptor 1 (ESR1) expression was observed in malignant epithelia and was associated with differential expression of ESR1-regulated genes and correlated with proliferation (Ki-67 expression). PATIENT SUMMARY: This first-in-man study defines the rapid gene expression changes taking place in prostate cancer (PCa) following castration. Expression levels of the genes that the androgen receptor regulates are predictive of treatment outcome. Upregulation of oestrogen receptor 1 is a mechanism by which PCa cells may survive despite castration.

Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.

Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far been disappointing owing to a lack of robust stratification methods. Whole-genome sequencing (WGS) analysis of 129 cases demonstrated that this is a heterogeneous cancer dominated by copy number alterations with frequent large-scale rearrangements. Co-amplification of receptor tyrosine kinases (RTKs) and/or downstream mitogenic activation is almost ubiquitous; thus tailored combination RTK inhibitor (RTKi) therapy might be required, as we demonstrate in vitro. However, mutational signatures showed three distinct molecular subtypes with potential therapeutic relevance, which we verified in an independent cohort (n = 87): (i) enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) dominant T>G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) C>A/T mutational pattern with evidence of an aging imprint. These subtypes could be ascertained using a clinically applicable sequencing strategy (low coverage) as a basis for therapy selection.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.