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The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor–normal genomic DNA (gDNA) samples derived from a breast cancer cell line—which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations—and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies., Measurement(s)Somatic Mutation AnalysisTechnology Type(s)whole genome sequencing • Whole Exome SequencingFactor Type(s)sequencing platform • sample prepration • library preparation • bioinformatics methodSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16713655

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies. Background & Summary The NGS technology has become a powerful tool for precision medicine. More researchers and clinicians are utilizing NGS to identify clinically actionable mutations in cancer patients and to establish targeted therapies for patients based on the patient’s genetic makeup or genetic variants of their tumor1, there is a critical need to have a full understanding of the many different variables affecting the NGS analysis output. The rapid growing number of sample processing protocols, library preparation methods, sequencing platforms, and bioinformatics pipelines to detect mutations in cancer genome, presents great technical challenges for the accuracy and reproducibility of utilizing NGS for cancer genome mutation detections. To investigate how these experimental and analytical elements may affect mutation detection accuracy, recently we carried out a comprehensive benchmarking study using both whole-genome (WGS) and whole-exome sequencing (WES) data sets generated from two well-characterized reference samples: a human breast cancer cell line (HCC1395) and a B lymphocytes cell line (HCC1395BL) derived from the same donor (NBT-RS47789). We generated WGS and WES data using various NGS library preparation protocols, seven NGS platforms at six centers (NBT-A46164B).

We characterized two reference samples for NGS technologies: a human triple-negative breast cancer cell line and a matched normal cell line. Leveraging several whole-genome sequencing (WGS) platforms, multiple sequencing replicates, and orthogonal mutation detection bioinformatics pipelines, we minimized the potential biases from sequencing technologies, assays, and informatics. Thus, our “truth sets” were defined using evidence from 21 repeats of WGS runs with coverages ranging from 50X to 100X (a total of 140 billion reads). These “truth sets” present many relevant variants/mutations including 193 COSMIC mutations and 9,016 germline variants from the ClinVar database, nonsense mutations inBRCA1/2and missense mutations inTP53andFGFR1.Independent validation in three orthogonal experiments demonstrated a successful stress test of the truth set. We expect these reference materials and “truth sets” to facilitate assay development, qualification, validation, and proficiency testing. In addition, our methods can be extended to establish new fully characterized reference samples for the community.

Long noncoding RNAs (lncRNAs) are prevalent genes with frequently precise regulation but mostly unknown functions. Here we demonstrate that lncRNAs guide the organismal DNA damage response. DNA damage activated transcription of the DINO (Damage Induced Noncoding) lncRNA via p53. DINO was required for p53-dependent gene expression, cell cycle arrest and apoptosis in response to DNA damage, and DINO expression was sufficient to activate damage signaling and cell cycle arrest in the absence of DNA damage. DINO bound to p53 protein and promoted its stabilization, mediating a p53 auto-amplification loop. Dino knockout or promoter inactivation in mice dampened p53 signaling and ameliorated acute radiation syndrome in vivo. Thus, inducible lncRNA can create a feedback loop with its cognate transcription factor to amplify cellular signaling networks.

An Aluring new autoantibody target Autoimmunity is the immune system's ultimate act of betrayal. Cells designed to protect against invading microbes suddenly target the host instead. In the autoimmune disease systemic lupus erythematosus, antibodies target DNA and host proteins, including the RNA binding protein Ro60. Hung et al. discovered that Ro60 bound to endogenous Alu retroelements. They detected antibody-Ro60-Alu RNA immune complexes in the blood of individuals with lupus and an enrichment of Alu transcripts. Ro60 bound to Alu probably primes RNA-binding innate immune receptors within B cells, leading these cells to make antibodies that target Ro60-Alu RNA and drive disease-causing inflammation. Science , this issue p. 455

Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR–validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control., National Institutes of Health (U.S.), National Institute of Arthritis and Musculoskeletal and Skin Diseases (U.S.) (NIAMS) (K08-AR054615)), National Cancer Institute (U.S.) (NIH/(NCI) (R01-CA118750)), National Cancer Institute (U.S.) (NIH/(NCI) R01-CA130795)), Juvenile Diabetes Research Foundation International, American Cancer Society, Howard Hughes Medical Institute (Early career scientist), Stanford University (Graduate Fellowship), National Science Foundation (U.S.) (Graduate Research Fellowship), United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)

Long noncoding RNAs (lncRNAs) are pervasively transcribed and critical regulators of the epigenome[1, 2]. These long, polyadenylated RNAs do not code for proteins, but function directly as RNAs, recruiting chromatin modifiers to mediate transcriptional changes in processes ranging from X-inactivation (XIST) to imprinting (H19)[3]. The recent discovery that lncRNA HOTAIR can link chromatin changes to cancer metastasis[4] furthers the relevance of lncRNAs to human disease. Here, we discuss lncRNAs as regulatory modules and explore the implications for disease pathogenesis. Although large-scale analyses of mammalian transcriptomes have revealed that more than 50% of transcripts have no protein coding potential[2, 5, 6], the functions of these putative transcripts are largely unknown. A subset of these noncoding transcripts are termed long noncoding RNAs (lncRNAs), based on an arbitrary minimum length of 200 nucleotides. LncRNAs are roughly classified based on their position relative to protein-coding genes: intergenic (between genes), intragenic/intronic (within genes), and antisense[2]. Initial efforts to characterize these molecules demonstrated that they function in cis, regulating their immediate genomic neighbors. Examples include AIR, XIST, and Kcnq1ot (reviewed in [1, 7, 8]), which recruit chromatin modifying complexes to silence adjacent sites. The scope of lncRNAs in gene regulation was advanced with the finding that lncRNA HOTAIR exhibited trans regulatory capacities. HOTAIR is transcribed at the intersection of opposing chromatin domains in the HOXC locus, but targets Polycomb Repressive Complex 2 (PRC2) to silence 40 kilobases of HOXD[9], a locus involved in developmental patterning. A subsequent study revealed that HOTAIR is overexpressed in approximately one quarter of human breast cancers, directing PRC2 to approximately 800 ectopic sites in the genome, which leads to histone H3 lysine 27 trimethylation and changes in gene expression[4]. The impacts of lncRNA-mediated chromatin changes are noteworthy: not only did HOTAIR drive metastasis in a mouse model, but HOTAIR expression in human breast cancer was found to be an independent prognostic marker for death and metastasis[4]. The fact that HOTAIR drives chromatin reprogramming genome-wide suggests that long-range regulation by lncRNAs may be a widespread mechanism. This is supported by a study showing that20% of tested lncRNAs are bound by PRC2 and other chromatin modifiers[10]. Furthermore, this is an underestimate of the total RNAs involved in chromatin modification, as PRC2 target genes also transcribe smaller 50-200 nt RNAs that interact with SUZ12 to mediate gene repression[11]. These findings provoke questions regarding the initial triggers for HOTAIR overexpression and whether understanding of lncRNA mechanics may have clinical relevance.

Large intervening non-coding RNAs (lincRNAs) are pervasively transcribed in the genome(1-3) yet their potential involvement in human disease is not well understood(4,5). Recent studies of dosage compensation, imprinting, and homeotic gene expression suggest that individual lincRNAs can function as the interface between DNA and specific chromatin remodelling activities(6-8). Here we show that lincRNAs in the HOX loci become systematically dys-regulated during breast cancer progression. The lincRNA termed HOTAIR is increased in expression in primary breast tumours and metastases, and HOTAIR expression level in primary tumours is a powerful predictor of eventual metastasis and death. Enforced expression of HOTAIR in epithelial cancer cells induced genome-wide re-targeting of Polycomb repressive complex 2 (PRC2) to an occupancy pattern more resembling embryonic fibroblasts, leading to altered histone H3 lysine 27 methylation, gene expression, and increased cancer invasiveness and metastasis in a manner dependent on PRC2. Conversely, loss of HOTAIR can inhibit cancer invasiveness, particularly in cells that possess excessive PRC2 activity. These findings indicate that lincRNAs have active roles in modulating the cancer epigenome and may be important targets for cancer diagnosis and therapy

Aberrations in chromatin dynamics play a fundamental role in tumorigenesis, yet relatively little is known of the molecular mechanisms linking histone lysine methylation to neoplastic disease. ING4 (Inhibitor of Growth 4) is a native subunit of an HBO1 histone acetyltransferase (HAT) complex and a tumor suppressor protein. Here we show a critical role for the specific read-out of histone H3 trimethylated at lysine 4 (H3K4me3) by the ING4 PHD finger in mediating ING4 gene expression and tumor suppressor functions. The interaction between ING4 and H3K4me3 augments the acetylation activity of HBO1 on H3 tails, and drives H3 acetylation at ING4 target promoters to effect a DNA damage-dependent gene expression program. Further, ING4 facilitates apoptosis in response to genotoxic stress and inhibits anchorage-independent cell growth, and these functions are dependent on ING4 interactions with H3K4me3. Together, our results demonstrate a mechanism for brokering crosstalk between H3K4 methylation and histone H3 acetylation, and reveal a new molecular link between chromatin modulation and tumor suppressor mechanisms.

Inhibitor of growth 1 (ING1) is implicated in oncogenesis, DNA damage repair, and apoptosis. Mutations within the ING1 gene and altered expression levels of ING1 are found in multiple human cancers. Here, we show that both DNA repair and apoptotic activities of ING1 require the interaction of the C-terminal plant homeodomain (PHD) finger with histone H3 trimethylated at Lys4 (H3K4me3). The ING1 PHD finger recognizes methylated H3K4 but not other histone modifications as revealed by the peptide microarrays. The molecular mechanism of the histone recognition is elucidated based on a 2.1 A-resolution crystal structure of the PHD-H3K4me3 complex. The K4me3 occupies a deep hydrophobic pocket formed by the conserved Y212 and W235 residues that make cation-pi contacts with the trimethylammonium group. Both aromatic residues are essential in the H3K4me3 recognition, as substitution of these residues with Ala disrupts the interaction. Unlike the wild-type ING1, the W235A mutant, overexpressed in the stable clones of melanoma cells or in HT1080 cells, was unable to stimulate DNA repair after UV irradiation or promote DNA-damage-induced apoptosis, indicating that H3K4me3 binding is necessary for these biological functions of ING1. Furthermore, N216S, V218I, and G221V mutations, found in human malignancies, impair the ability of ING1 to associate with H3K4me3 or to induce nucleotide repair and cell death, linking the tumorigenic activity of ING1 with epigenetic regulation. Together, our findings reveal the critical role of the H3K4me3 interaction in mediating cellular responses to genotoxic stresses and offer new insight into the molecular mechanism underlying the tumor suppressive activity of ING1.

The HBO1 HAT protein is the major source of histone H4 acetylation in vivo and has been shown to play critical roles in gene regulation and DNA replication. A distinctive characteristic of HBO1 HAT complexes is the presence of three PHD finger domains in two different subunits: tumor suppressor proteins ING4/5 and JADE1/2/3. Biochemical and functional analyses indicate that these domains interact with histone H3 N-terminal tail region, but with a different specificity towards its methylation status. Their combinatorial action is essential in regulating chromatin binding and substrate specificity of HBO1 complexes, as well as cell growth. Importantly, localization analyses on the human genome indicate that HBO1 complexes are enriched throughout the coding regions of genes, supporting a role in transcription elongation. These results underline the importance and versatility of PHD finger domains in regulating chromatin association and histone modification cross-talk within a single protein complex.

Dynamic regulation of diverse nuclear processes is intimately linked to covalent modifications of chromatin1,2. Much attention has focused on methylation at lysine 4 of histone H3 (H3K4), owing to its association with euchromatic genomic regions3,4. H3K4 can be mono-, di- or tri-methylated. Trimethylated H3K4 (H3K4me3) is preferentially detected at active genes, and is proposed to promote gene expression through recognition by transcription-activating effector molecules5. Here we identify a novel class of methylated H3K4 effector domains—the PHD domains of the ING (for inhibitor of growth) family of tumour suppressor proteins. The ING PHD domains are specific and highly robust binding modules for H3K4me3 and H3K4me2. ING2, a native subunit of a repressive mSin3a–HDAC1 histone deacetylase complex6, binds with high affinity to the trimethylated species. In response to DNA damage, recognition of H3K4me3 by the ING2 PHD domain stabilizes the mSin3a–HDAC1 complex at the promoters of proliferation genes. This pathway constitutes a new mechanism by which H3K4me3 functions in active gene repression. Furthermore, ING2 modulates cellular responses to genotoxic insults, and these functions are critically dependent on ING2 interaction with H3K4me3. Together, our findings establish a pivotal role for trimethylation of H3K4 in gene repression and, potentially, tumour suppressor mechanisms.