Harnessing DNA replication stress to target RBM10 deficiency in lung adenocarcinoma.

The splicing factor RNA-binding motif protein 10 (RBM10) is frequently mutated in lung adenocarcinoma (LUAD) (9-25%). Most RBM10 cancer mutations are loss-of-function, correlating with increased tumorigenesis and limiting the efficacy of current LUAD targeted therapies. Remarkably, therapeutic strategies leveraging RBM10 deficiency remain unexplored. Here, we conduct a CRISPR-Cas9 synthetic lethality (SL) screen and identify ~60 RBM10 SL genes, including WEE1 kinase. WEE1 inhibition sensitizes RBM10-deficient LUAD cells in-vitro and in-vivo. Mechanistically, we identify a splicing-independent role of RBM10 in regulating DNA replication fork progression and replication stress response, which underpins RBM10-WEE1 SL. Additionally, RBM10 interacts with active DNA replication forks, relying on DNA Primase Subunit 1 (PRIM1) that synthesizes Okazaki RNA primers. Functionally, we demonstrate that RBM10 serves as an anchor for recruiting Histone Deacetylase 1 (HDAC1) to facilitate H4K16 deacetylation and R-loop homeostasis to maintain replication fork stability. Collectively, our data reveal a role of RBM10 in fine-tuning DNA replication and provide therapeutic arsenal for targeting RBM10-deficient tumors.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations.

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

A Cyclic Permutation Approach to Removing Spatial Dependency between Clustered Gene Ontology Terms.

Traditional gene set enrichment analysis falters when applied to large genomic domains, where neighboring genes often share functions. This spatial dependency creates misleading enrichments, mistaking mere physical proximity for genuine biological connections. Here we present Spatial Adjusted Gene Ontology (SAGO), a novel cyclic permutation-based approach, to tackle this challenge. SAGO separates enrichments due to spatial proximity from genuine biological links by incorporating the genes' spatial arrangement into the analysis. We applied SAGO to various datasets in which the identified genomic intervals are large, including replication timing domains, large H3K9me3 and H3K27me3 domains, HiC compartments and lamina-associated domains (LADs). Intriguingly, applying SAGO to prostate cancer samples with large copy number alteration (CNA) domains eliminated most of the enriched GO terms, thus helping to accurately identify biologically relevant gene sets linked to oncogenic processes, free from spatial bias.

Both cell autonomous and non-autonomous processes modulate the association between replication timing and mutation rate.

Cancer somatic mutations are the product of multiple mutational and repair processes, some of which are tightly associated with DNA replication. Mutation rates (MR) are known to be higher in late replication timing (RT) regions, but different processes can affect this association. Systematic analysis of the mutational landscape of 2787 tumors from 32 tumor types revealed that approximately one third of the tumor samples show weak association between replication timing and mutation rate. Further analyses revealed that those samples have unique mutational signatures and are enriched with mutations in genes involved in DNA replication, DNA repair and chromatin structure. Surprisingly, analysis of differentially expressed genes between weak and strong RT-MR association groups revealed that tumors with weak association are enriched with genes associated with cell-cell communication and the immune system, suggesting a non-autonomous response to DNA damage.

Mutational signatures association with replication timing in normal cells reveals similarities and differences with matched cancer tissues.

Mutational signatures' association with replication timing (RT) has been studied in cancer samples, but the RT distribution of somatic mutations in non-cancerous cells was only minimally explored. Here, we performed comprehensive analyses of mutational signatures in 2.9 million somatic mutations across multiple non-cancerous tissues, stratified by early and late RT regions. We found that many mutational processes are active mainly or solely in early RT, such as SBS16 in hepatocytes and SBS88 in the colon, or in late RT, such as SBS4 in lung and hepatocytes, and SBS18 across many tissues. The two ubiquitous signatures, SBS1 and SBS5, showed late and early bias, respectively, across multiple tissues and in mutations representing germ cells. We also performed a direct comparison with cancer samples in 4 matched tissue-cancer types. Unexpectedly, while for most signatures the RT bias was consistent in normal tissue and in cancer, we found that SBS1's late RT bias is lost in cancer.

RIF1-ASF1-mediated high-order chromatin structure safeguards genome integrity.

The 53BP1-RIF1 pathway antagonizes resection of DNA broken ends and confers PARP inhibitor sensitivity on BRCA1-mutated tumors. However, it is unclear how this pathway suppresses initiation of resection. Here, we identify ASF1 as a partner of RIF1 via an interacting manner similar to its interactions with histone chaperones CAF-1 and HIRA. ASF1 is recruited to distal chromatin flanking DNA breaks by 53BP1-RIF1 and promotes non-homologous end joining (NHEJ) using its histone chaperone activity. Epistasis analysis shows that ASF1 acts in the same NHEJ pathway as RIF1, but via a parallel pathway with the shieldin complex, which suppresses resection after initiation. Moreover, defects in end resection and homologous recombination (HR) in BRCA1-deficient cells are largely suppressed by ASF1 deficiency. Mechanistically, ASF1 compacts adjacent chromatin by heterochromatinization to protect broken DNA ends from BRCA1-mediated resection. Taken together, our findings identify a RIF1-ASF1 histone chaperone complex that promotes changes in high-order chromatin structure to stimulate the NHEJ pathway for DSB repair.

Cancer Mutational Processes Vary in Their Association with Replication Timing and Chromatin Accessibility.

Cancer somatic mutations are the product of multiple mutational and repair processes, both of which are tightly associated with DNA replication. Distinctive patterns of somatic mutation accumulation, termed mutational signatures, are indicative of processes sustained within tumors. However, the association of various mutational processes with replication timing (RT) remains an open question. In this study, we systematically analyzed the mutational landscape of 2,787 tumors from 32 tumor types separately for early and late replicating regions using sequence context normalization and chromatin data to account for sequence and chromatin accessibility differences. To account for sequence differences between various genomic regions, an artificial genome-based approach was developed to expand the signature analyses to doublet base substitutions and small insertions and deletions. The association of mutational processes and RT was signature specific: Some signatures were associated with early or late replication (such as SBS7b and SBS7a, respectively), and others had no association. Most associations existed even after normalizing for genome accessibility. A focused mutational signature identification approach was also developed that uses RT information to improve signature identification; this approach found that SBS16, which is biased toward early replication, is strongly associated with better survival rates in liver cancer. Overall, this novel and comprehensive approach provides a better understanding of the etiology of mutational signatures, which may lead to improved cancer prevention, diagnosis, and treatment. SIGNIFICANCE: Many mutational processes associate with early or late replication timing regions independently of chromatin accessibility, enabling development of a focused identification approach to improve mutational signature detection.

Chromosomal coordination and differential structure of asynchronous replicating regions.

Stochastic asynchronous replication timing (AS-RT) is a phenomenon in which the time of replication of each allele is different, and the identity of the early allele varies between cells. By taking advantage of stable clonal pre-B cell populations derived from C57BL6/Castaneous mice, we have mapped the genome-wide AS-RT loci, independently of genetic differences. These regions are characterized by differential chromatin accessibility, mono-allelic expression and include new gene families involved in specifying cell identity. By combining population level mapping with single cell FISH, our data reveal the existence of a novel regulatory program that coordinates a fixed relationship between AS-RT regions on any given chromosome, with some loci set to replicate in a parallel and others set in the anti-parallel orientation. Our results show that AS-RT is a highly regulated epigenetic mark established during early embryogenesis that may be used for facilitating the programming of mono-allelic choice throughout development.

Germline DNA replication timing shapes mammalian genome composition.

Mammalian DNA replication is a highly organized and regulated process. Large, Mb-sized regions are replicated at defined times along S-phase. Replication Timing (RT) is thought to play a role in shaping the mammalian genome by affecting mutation rates. Previous analyses relied on somatic RT profiles. However, only germline mutations are passed on to offspring and affect genomic composition. Therefore, germ cell RT information is necessary to evaluate the influences of RT on the mammalian genome. We adapted the RT mapping technique for limited amounts of cells, and measured RT from two stages in the mouse germline - primordial germ cells (PGCs) and spermatogonial stem cells (SSCs). RT in germline cells exhibited stronger correlations to both mutation rate and recombination hotspots density than those of RT in somatic tissues, emphasizing the importance of using correct tissues-of-origin for RT profiling. Germline RT maps exhibited stronger correlations to additional genetic features including GC-content, transposable elements (SINEs and LINEs), and gene density. GC content stratification and multiple regression analysis revealed independent contributions of RT to SINE, gene, mutation, and recombination hotspot densities. Together, our results establish a central role for RT in shaping multiple levels of mammalian genome composition.

Perturbations in the Replication Program Contribute to Genomic Instability in Cancer.

Cancer and genomic instability are highly impacted by the deoxyribonucleic acid (DNA) replication program. Inaccuracies in DNA replication lead to the increased acquisition of mutations and structural variations. These inaccuracies mainly stem from loss of DNA fidelity due to replication stress or due to aberrations in the temporal organization of the replication process. Here we review the mechanisms and impact of these major sources of error to the replication program.

Genome-wide Determination of Mammalian Replication Timing by DNA Content Measurement.

Replication of the genome occurs during S phase of the cell cycle in a highly regulated process that ensures the fidelity of DNA duplication. Each genomic region is replicated at a distinct time during S phase through the simultaneous activation of multiple origins of replication. Time of replication (ToR) correlates with many genomic and epigenetic features and is linked to mutation rates and cancer. Comprehending the full genomic view of the replication program, in health and disease is a major future goal and challenge. This article describes in detail the "Copy Number Ratio of S/G1 for mapping genomic Time of Replication" method (herein called: CNR-ToR), a simple approach to map the genome wide ToR of mammalian cells. The method is based on the copy number differences between S phase cells and G1 phase cells. The CNR-ToR method is performed in 6 steps: 1. Preparation of cells and staining with propidium iodide (PI); 2. Sorting G1 and S phase cells using fluorescence-activated cell sorting (FACS); 3. DNA purification; 4. Sonication; 5. Library preparation and sequencing; and 6. Bioinformatic analysis. The CNR-ToR method is a fast and easy approach that results in detailed replication maps.

Persistence to anti-cancer treatments in the stationary to proliferating transition.

The heterogeneous responses of clonal cancer cells to treatment is understood to be caused by several factors, including stochasticity, cell-cycle dynamics, and different micro-environments. In a tumor, cancer cells may encounter fluctuating conditions and transit from a stationary culture to a proliferating state, for example this may occur following treatment. Here, we undertake a quantitative evaluation of the response of single cancerous lymphoblasts (L1210 cells) to various treatments administered during this transition. Additionally, we developed an experimental system, a "Mammalian Mother Machine," that tracks the fate of thousands of mammalian cells over several generations under transient exposure to chemotherapeutic drugs. Using our developed system, we were able to follow the same cell under repeated treatments and continuously track many generations. We found that the dynamics of the transition between stationary and proliferative states are highly variable and affect the response to drug treatment. Using cell-cycle markers, we were able to isolate a subpopulation of persister cells with distinctly higher than average survival probability. The higher survival rate encountered with cell-cycle phase specific drugs was associated with a significantly longer time-till-division, and was reduced by a non cell-cycle specific drug. Our results suggest that the variability of transition times from the stationary to the proliferating state may be an obstacle hampering the effectiveness of drugs and should be taken into account when designing treatment regimens.

The mutation spectrum in genomic late replication domains shapes mammalian GC content.

Genome sequence compositions and epigenetic organizations are correlated extensively across multiple length scales. Replication dynamics, in particular, is highly correlated with GC content. We combine genome-wide time of replication (ToR) data, topological domains maps and detailed functional epigenetic annotations to study the correlations between replication timing and GC content at multiple scales. We find that the decrease in genomic GC content at large scale late replicating regions can be explained by mutation bias favoring A/T nucleotide, without selection or biased gene conversion. Quantification of the free dNTP pool during the cell cycle is consistent with a mechanism involving replication-coupled mutation spectrum that favors AT nucleotides at late S-phase. We suggest that mammalian GC content composition is shaped by independent forces, globally modulating mutation bias and locally selecting on functional element. Deconvoluting these forces and analyzing them on their native scales is important for proper characterization of complex genomic correlations.

Distinguishing between stochasticity and determinism: Examples from cell cycle duration variability.

We describe a recent approach for distinguishing between stochastic and deterministic sources of variability, focusing on the mammalian cell cycle. Variability between cells is often attributed to stochastic noise, although it may be generated by deterministic components. Interestingly, lineage information can be used to distinguish between variability and determinism. Analysis of correlations within a lineage of the mammalian cell cycle duration revealed its deterministic nature. Here, we discuss the sources of such variability and the possibility that the underlying deterministic process is due to the circadian clock. Finally, we discuss the "kicked cell cycle" model and its implication on the study of the cell cycle in healthy and cancerous tissues.

The p53 C terminus controls site-specific DNA binding and promotes structural changes within the central DNA binding domain.

DNA binding by numerous transcription factors including the p53 tumor suppressor protein constitutes a vital early step in transcriptional activation. While the role of the central core DNA binding domain (DBD) of p53 in site-specific DNA binding has been established, the contribution of the sequence-independent C-terminal domain (CTD) is still not well understood. We investigated the DNA-binding properties of a series of p53 CTD variants using a combination of in vitro biochemical analyses and in vivo binding experiments. Our results provide several unanticipated and interconnected findings. First, the CTD enables DNA binding in a sequence-dependent manner that is drastically altered by either its modification or deletion. Second, dependence on the CTD correlates with the extent to which the p53 binding site deviates from the canonical consensus sequence. Third, the CTD enables stable formation of p53-DNA complexes to divergent binding sites via DNA-induced conformational changes within the DBD itself.

Lineage correlations of single cell division time as a probe of cell-cycle dynamics.

Stochastic processes in cells are associated with fluctuations in mRNA, protein production and degradation, noisy partition of cellular components at division, and other cell processes. Variability within a clonal population of cells originates from such stochastic processes, which may be amplified or reduced by deterministic factors. Cell-to-cell variability, such as that seen in the heterogeneous response of bacteria to antibiotics, or of cancer cells to treatment, is understood as the inevitable consequence of stochasticity. Variability in cell-cycle duration was observed long ago; however, its sources are still unknown. A central question is whether the variance of the observed distribution originates from stochastic processes, or whether it arises mostly from a deterministic process that only appears to be random. A surprising feature of cell-cycle-duration inheritance is that it seems to be lost within one generation but to be still present in the next generation, generating poor correlation between mother and daughter cells but high correlation between cousin cells. This observation suggests the existence of underlying deterministic factors that determine the main part of cell-to-cell variability. We developed an experimental system that precisely measures the cell-cycle duration of thousands of mammalian cells along several generations and a mathematical framework that allows discrimination between stochastic and deterministic processes in lineages of cells. We show that the inter- and intra-generation correlations reveal complex inheritance of the cell-cycle duration. Finally, we build a deterministic nonlinear toy model for cell-cycle inheritance that reproduces the main features of our data. Our approach constitutes a general method to identify deterministic variability in lineages of cells or organisms, which may help to predict and, eventually, reduce cell-to-cell heterogeneity in various systems, such as cancer cells under treatment.

Genome-wide analysis of androgen receptor targets reveals COUP-TF1 as a novel player in human prostate cancer.

Androgen activity plays a key role in prostate cancer progression. Androgen receptor (AR) is the main mediator of androgen activity in the prostate, through its ability to act as a transcription mediator. Here we performed a genome-wide analysis of human AR binding to promoters in the presence of an agonist or antagonist in an androgen dependent prostate cancer cell line. Many of the AR bound promoters are bound in all examined conditions while others are bound only in the presence of an agonist or antagonist. Several motifs are enriched in AR bound promoters, including the AR Response Element (ARE) half-site and recognition elements for the transcription factors OCT1 and SOX9. This suggests that these 3 factors could define a module of co-operating transcription factors in the prostate. Interestingly, AR bound promoters are preferentially located in AT rich genomic regions. Analysis of mRNA expression identified chicken ovalbumin upstream promoter-transcription factor 1 (COUP-TF1) as a direct AR target gene that is downregulated upon binding by the agonist liganded AR. COUP-TF1 immunostaining revealed nucleolar localization of COUP-TF1 in epithelium of human androgen dependent prostate cancer, but not in adjacent benign prostate epithelium. Stromal cells both in human and mouse prostate show nuclear COUP-TF1 staining. We further show that there is an inverse correlation between COUP-TF1 expression in prostate stromal cells and the rising levels of androgen with advancing puberty. This study extends the pool of recognized putative AR targets and identifies a negatively regulated target of AR - COUP-TF1 - which could possibly play a role in human prostate cancer.

DECOD: fast and accurate discriminative DNA motif finding.

MOTIVATION: Motif discovery is now routinely used in high-throughput studies including large-scale sequencing and proteomics. These datasets present new challenges. The first is speed. Many motif discovery methods do not scale well to large datasets. Another issue is identifying discriminative rather than generative motifs. Such discriminative motifs are important for identifying co-factors and for explaining changes in behavior between different conditions. RESULTS: To address these issues we developed a method for DECOnvolved Discriminative motif discovery (DECOD). DECOD uses a k-mer count table and so its running time is independent of the size of the input set. By deconvolving the k-mers DECOD considers context information without using the sequences directly. DECOD outperforms previous methods both in speed and in accuracy when using simulated and real biological benchmark data. We performed new binding experiments for p53 mutants and used DECOD to identify p53 co-factors, suggesting new mechanisms for p53 activation. AVAILABILITY: The source code and binaries for DECOD are available at http://www.sb.cs.cmu.edu/DECOD CONTACT: zivbj@cs.cmu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Modulation of the vitamin D3 response by cancer-associated mutant p53.

The p53 gene is mutated in many human tumors. Cells of such tumors often contain abundant mutant p53 (mutp53) protein, which may contribute actively to tumor progression via a gain-of-function mechanism. We applied ChIP-on-chip analysis and identified the vitamin D receptor (VDR) response element as overrepresented in promoter sequences bound by mutp53. We report that mutp53 can interact functionally and physically with VDR. Mutp53 is recruited to VDR-regulated genes and modulates their expression, augmenting the transactivation of some genes and relieving the repression of others. Furthermore, mutp53 increases the nuclear accumulation of VDR. Importantly, mutp53 converts vitamin D into an antiapoptotic agent. Thus, p53 status can determine the biological impact of vitamin D on tumor cells.

Chromatin immunoprecipitation-on-chip reveals stress-dependent p53 occupancy in primary normal cells but not in established cell lines.

The p53 tumor suppressor protein is a transcription factor that plays a key role in the cellular response to stress and cancer prevention. Upon activation, p53 regulates a large variety of genes causing cell cycle arrest, apoptosis, or senescence. We have developed a p53-focused array, which allows us to investigate, simultaneously, p53 interactions with most of its known target sequences using the chromatin immunoprecipitation (ChIP)-on-chip methodology. Applying this technique to multiple cell types under various growth conditions revealed a profound difference in p53 activity between primary cells and established cell lines. We found that, in peripheral blood mononuclear cells, p53 exists in a form that binds only a small subset of its target regions. Upon exposure to genotoxic stress, the extent of targets bound by p53 significantly increased. By contrast, in established cell lines, p53 binds to essentially all of its targets irrespective of stress and cellular fate (apoptosis or arrest). Analysis of gene expression in these established lines revealed little correlation between DNA binding and the induction of gene expression. Our results suggest that nonactivated p53 has limited binding activity, whereas upon activation it binds to essentially all its targets. Additional triggers are most likely required to activate the transcriptional program of p53.