Applied models and molecular characteristics of small cell lung cancer.

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

CDK-independent role of D-type cyclins in regulating DNA mismatch repair.

Although mismatch repair (MMR) is essential for correcting DNA replication errors, it can also recognize other lesions, such as oxidized bases. In G0 and G1, MMR is kept in check through unknown mechanisms as it is error-prone during these cell cycle phases. We show that in mammalian cells, D-type cyclins are recruited to sites of oxidative DNA damage in a PCNA- and p21-dependent manner. D-type cyclins inhibit the proteasomal degradation of p21, which competes with MMR proteins for binding to PCNA, thereby inhibiting MMR. The ability of D-type cyclins to limit MMR is CDK4- and CDK6-independent and is conserved in G0 and G1. At the G1/S transition, the timely, cullin-RING ubiquitin ligase (CRL)-dependent degradation of D-type cyclins and p21 enables MMR activity to efficiently repair DNA replication errors. Persistent expression of D-type cyclins during S-phase inhibits the binding of MMR proteins to PCNA, increases the mutational burden, and promotes microsatellite instability.

D-type cyclins regulate DNA mismatch repair in the G1 and S phases of the cell cycle, maintaining genome stability.

The large majority of oxidative DNA lesions occurring in the G1 phase of the cell cycle are repaired by base excision repair (BER) rather than mismatch repair (MMR) to avoid long resections that can lead to genomic instability and cell death. However, the molecular mechanisms dictating pathway choice between MMR and BER have remained unknown. Here, we show that, during G1, D-type cyclins are recruited to sites of oxidative DNA damage in a PCNA- and p21-dependent manner. D-type cyclins shield p21 from its two ubiquitin ligases CRL1SKP2 and CRL4CDT2 in a CDK4/6-independent manner. In turn, p21 competes through its PCNA-interacting protein degron with MMR components for their binding to PCNA. This inhibits MMR while not affecting BER. At the G1/S transition, the CRL4AMBRA1-dependent degradation of D-type cyclins renders p21 susceptible to proteolysis. These timely degradation events allow the proper binding of MMR proteins to PCNA, enabling the repair of DNA replication errors. Persistent expression of cyclin D1 during S-phase increases the mutational burden and promotes microsatellite instability. Thus, the expression of D-type cyclins inhibits MMR in G1, whereas their degradation is necessary for proper MMR function in S.

SIRT1 Prevents R-Loops during Chronological Aging by Modulating DNA Replication at rDNA Loci.

In metazoans, the largest sirtuin, SIRT1, is a nuclear protein implicated in epigenetic modifications, circadian signaling, DNA recombination, replication, and repair. Our previous studies have demonstrated that SIRT1 binds replication origins and inhibits replication initiation from a group of potential initiation sites (dormant origins). We studied the effects of aging and SIRT1 activity on replication origin usage and the incidence of transcription-replication collisions (creating R-loop structures) in adult human cells obtained at different time points during chronological aging and in cancer cells. In primary, untransformed cells, SIRT1 activity declined and the prevalence of R-loops rose with chronological aging. Both the reduction in SIRT1 activity and the increased abundance of R-loops were also observed during the passage of primary cells in culture. All cells, regardless of donor age or transformation status, reacted to the short-term, acute chemical inhibition of SIRT1 with the activation of excessive replication initiation events coincident with an increased prevalence of R-loops. However, cancer cells activated dormant replication origins, genome-wide, during long-term proliferation with mutated or depleted SIRT1, whereas, in primary cells, the aging-associated SIRT1-mediated activation of dormant origins was restricted to rDNA loci. These observations suggest that chronological aging and the associated decline in SIRT1 activity relax the regulatory networks that protect cells against excess replication and that the mechanisms protecting from replication-transcription collisions at the rDNA loci manifest as differentially enhanced sensitivities to SIRT1 decline and chronological aging.

Integrative epigenomic analyses of small cell lung cancer cells demonstrates the clinical translational relevance of gene body methylation.

DNA methylation is a key regulator of gene expression and a clinical therapeutic predictor. We examined global DNA methylation beyond the generally used promoter areas in human small cell lung cancer (SCLC) and find that gene body methylation is a robust positive predictor of gene expression. Combining promoter and gene body methylation better predicts gene expression than promoter methylation alone including genes involved in the neuroendocrine classification of SCLC and the expression of therapeutically relevant genes including MGMT, SLFN11, and DLL3. Importantly, for super-enhancer (SE) covered genes such as NEUROD1 or MYC, using H3K27ac and NEUROD1, ASCL1, and POU2F3 ChIP-seq data, we show that genic methylation is inversely proportional to expression, thus providing a new approach to identify potential SE regulated genes involved in SCLC pathogenesis. To advance SCLC transitional research, these data are integrated into our web portal (https://discover.nci.nih.gov/SclcCellMinerCDB/) for open and easy access to basic and clinical investigators.

Convergence of SIRT1 and ATR signaling to modulate replication origin dormancy.

During routine genome duplication, many potential replication origins remain inactive or 'dormant'. Such origin dormancy is achieved, in part, by an interaction with the metabolic sensor SIRT1 deacetylase. We report here that dormant origins are a group of consistent, pre-determined genomic sequences that are distinguished from baseline (i.e. ordinarily active) origins by their preferential association with two phospho-isoforms of the helicase component MCM2. During normal unperturbed cell growth, baseline origins, but not dormant origins, associate with a form of MCM2 that is phosphorylated by DBF4-dependent kinase (DDK) on serine 139 (pS139-MCM2). This association facilitates the initiation of DNA replication from baseline origins. Concomitantly, SIRT1 inhibits Ataxia Telangiectasia and Rad3-related (ATR)-kinase-mediated phosphorylation of MCM2 on serine 108 (pS108-MCM2) by deacetylating the ATR-interacting protein DNA topoisomerase II binding protein 1 (TOPBP1), thereby preventing ATR recruitment to chromatin. In cells devoid of SIRT1 activity, or challenged by replication stress, this inhibition is circumvented, enabling ATR-mediated S108-MCM2 phosphorylation. In turn, pS108-MCM2 enables DDK-mediated phosphorylation on S139-MCM2 and facilitates replication initiation at dormant origins. These observations suggest that replication origin dormancy and activation are regulated by distinct post-translational MCM modifications that reflect a balance between SIRT1 activity and ATR signaling.

Exploring the Significance of the Exon 4-Skipping Isoform of the ZNF217 Oncogene in Breast Cancer.

Oncogene alternative splicing events can create distinct functional transcripts that offer new candidate prognostic biomarkers for breast cancer. ZNF217 is a well-established oncogene but its exon 4-skipping isoform (ZNF217-ΔE4) has never been investigated in terms of clinical or biological relevance. Using in silico RNA-seq and RT-qPCR analyses, we demonstrated for the first time the existence of ZNF217-ΔE4 transcripts in primary breast tumors, and a positive correlation between ZNF217-ΔE4 mRNA levels and those of the wild-type oncogene (ZNF217-WT). A pilot retrospective analysis revealed that, in the Luminal subclass, the combination of the two ZNF217 variants (the ZNF217-ΔE4-WT gene-expression signature) provided more information than the mRNA expression levels of each isoform alone. Ectopic overexpression of ZNF217-ΔE4 in breast cancer cells promoted an aggressive phenotype and an increase in ZNF217-WT expression levels that was inversely correlated with DNA methylation of the ZNF217 gene. This study provides new insights into the possible role of the ZNF217-ΔE4 splice variant in breast cancer and suggests a close interplay between the ZNF217-WT and ZNF217-ΔE4 isoforms. Our data suggest that a dual signature combining the expression levels of these two isoforms may serve as a novel prognostic biomarker allowing better stratification of breast cancers with good prognosis and aiding clinicians in therapeutic decisions.

Dynamics of replication origin over-activation.

Safeguards against excess DNA replication are often dysregulated in cancer, and driving cancer cells towards over-replication is a promising therapeutic strategy. We determined DNA synthesis patterns in cancer cells undergoing partial genome re-replication due to perturbed regulatory interactions (re-replicating cells). These cells exhibited slow replication, increased frequency of replication initiation events, and a skewed initiation pattern that preferentially reactivated early-replicating origins. Unlike in cells exposed to replication stress, which activated a novel group of hitherto unutilized (dormant) replication origins, the preferred re-replicating origins arose from the same pool of potential origins as those activated during normal growth. Mechanistically, the skewed initiation pattern reflected a disproportionate distribution of pre-replication complexes on distinct regions of licensed chromatin prior to replication. This distinct pattern suggests that circumventing the strong inhibitory interactions that normally prevent excess DNA synthesis can occur via at least two pathways, each activating a distinct set of replication origins.

Genome-Wide Analysis Unveils DNA Helicase RECQ1 as a Regulator of Estrogen Response Pathway in Breast Cancer Cells.

Susceptibility to breast cancer is significantly increased in individuals with germ line mutations in RECQ1 (also known as RECQL or RECQL1), a gene encoding a DNA helicase essential for genome maintenance. We previously reported that RECQ1 expression predicts clinical outcomes for sporadic breast cancer patients stratified by estrogen receptor (ER) status. Here, we utilized an unbiased integrative genomics approach to delineate a cross talk between RECQ1 and ERα, a known master regulatory transcription factor in breast cancer. We found that expression of ESR1, the gene encoding ERα, is directly activated by RECQ1. More than 35% of RECQ1 binding sites were cobound by ERα genome-wide. Mechanistically, RECQ1 cooperates with FOXA1, the pioneer transcription factor for ERα, to enhance chromatin accessibility at the ESR1 regulatory regions in a helicase activity-dependent manner. In clinical ERα-positive breast cancers treated with endocrine therapy, high RECQ1 and high FOXA1 coexpressing tumors were associated with better survival. Collectively, these results identify RECQ1 as a novel cofactor for ERα and uncover a previously unknown mechanism by which RECQ1 regulates disease-driving gene expression in ER-positive breast cancer cells.

Currently favored sampling practices for tumor sequencing can produce optimal results in the clinical setting.

Tumor heterogeneity is a consequence of clonal evolution, resulting in a fractal-like architecture with spatially separated main clones, sub-clones and single-cells. As sequencing an entire tumor is not feasible, we ask the question whether there is an optimal clinical sampling strategy that can handle heterogeneity and hypermutations? Here, we tested the effect of sample size, pooling strategy as well as sequencing depth using whole-exome sequencing of ovarian tumor specimens paired with normal blood samples. Our study has an emphasis on clinical application-hence we compared single biopsy, combined local biopsies and combined multi-regional biopsies. Our results show that sequencing from spatially neighboring regions show similar genetic compositions, with few private mutations. Pooling samples from multiple distinct regions of the primary tumor did not increase the overall number of identified mutations but may increase the robustness of detecting clonal mutations. Hypermutating tumors are a special case, since increasing sample size can easily dilute sub-clonal private mutations below detection thresholds. In summary, we compared the effects of sampling strategies (single biopsy, multiple local samples, pooled global sample) on mutation detection by next generation sequencing. In view of the limitations of present tools and technologies, only one sequencing run per sample combined with high coverage (100-300 ×) sequencing is affordable and practical, regardless of the number of samples taken from the same patient.

BAMscale: quantification of next-generation sequencing peaks and generation of scaled coverage tracks.

BACKGROUND: Next-generation sequencing allows genome-wide analysis of changes in chromatin states and gene expression. Data analysis of these increasingly used methods either requires multiple analysis steps, or extensive computational time. We sought to develop a tool for rapid quantification of sequencing peaks from diverse experimental sources and an efficient method to produce coverage tracks for accurate visualization that can be intuitively displayed and interpreted by experimentalists with minimal bioinformatics background. We demonstrate its strength and usability by integrating data from several types of sequencing approaches. RESULTS: We have developed BAMscale, a one-step tool that processes a wide set of sequencing datasets. To demonstrate the usefulness of BAMscale, we analyzed multiple sequencing datasets from chromatin immunoprecipitation sequencing data (ChIP-seq), chromatin state change data (assay for transposase-accessible chromatin using sequencing: ATAC-seq, DNA double-strand break mapping sequencing: END-seq), DNA replication data (Okazaki fragments sequencing: OK-seq, nascent-strand sequencing: NS-seq, single-cell replication timing sequencing: scRepli-seq) and RNA-seq data. The outputs consist of raw and normalized peak scores (multiple normalizations) in text format and scaled bigWig coverage tracks that are directly accessible to data visualization programs. BAMScale also includes a visualization module facilitating direct, on-demand quantitative peak comparisons that can be used by experimentalists. Our tool can effectively analyze large sequencing datasets (~ 100 Gb size) in minutes, outperforming currently available tools. CONCLUSIONS: BAMscale accurately quantifies and normalizes identified peaks directly from BAM files, and creates coverage tracks for visualization in genome browsers. BAMScale can be implemented for a wide set of methods for calculating coverage tracks, including ChIP-seq and ATAC-seq, as well as methods that currently require specialized, separate tools for analyses, such as splice-aware RNA-seq, END-seq and OK-seq for which no dedicated software is available. BAMscale is freely available on github (https://github.com/ncbi/BAMscale).

The RepID-CRL4 ubiquitin ligase complex regulates metaphase to anaphase transition via BUB3 degradation.

The spindle assembly checkpoint (SAC) prevents premature chromosome segregation by inactivating the anaphase promoting complex/cyclosome (APC/C) until all chromosomes are properly attached to mitotic spindles. Here we identify a role for Cullin-RING ubiquitin ligase complex 4 (CRL4), known for modulating DNA replication, as a crucial mitotic regulator that triggers the termination of the SAC and enables chromosome segregation. CRL4 is recruited to chromatin by the replication origin binding protein RepID/DCAF14/PHIP. During mitosis, CRL4 dissociates from RepID and replaces it with RB Binding Protein 7 (RBBP7), which ubiquitinates the SAC mediator BUB3 to enable mitotic exit. During interphase, BUB3 is protected from CRL4-mediated degradation by associating with promyelocytic leukemia (PML) nuclear bodies, ensuring its availability upon mitotic onset. Deficiencies in RepID, CRL4 or RBBP7 delay mitotic exit, increase genomic instability and enhance sensitivity to paclitaxel, a microtubule stabilizer and anti-tumor drug.

Wanted DEAD/H or Alive: Helicases Winding Up in Cancers.

Cancer is one of the most studied areas of human biology over the past century. Despite having attracted much attention, hype, and investments, the search to find a cure for cancer remains an uphill battle. Recent discoveries that challenged the central dogma of molecular biology not only further increase the complexity but also demonstrate how various types of noncoding RNAs such as microRNA and long noncoding RNA, as well as their related processes such as RNA editing, are important in regulating gene expression. Parallel to this aspect, an increasing number of reports have focused on a family of proteins known as DEAD/H-box helicases involved in RNA metabolism, regulation of long and short noncoding RNAs, and novel roles as "editing helicases" and their association with cancers. This review summarizes recent findings on the roles of RNA helicases in various cancers, which are broadly classified into adult solid tumors, childhood solid tumors, leukemia, and cancer stem cells. The potential small molecule inhibitors of helicases and their therapeutic value are also discussed. In addition, analyzing next-generation sequencing data obtained from public portals and reviewing existing literature, we provide new insights on the potential of DEAD/H-box helicases to act as pharmacological drug targets in cancers.

Predictors of Chemosensitivity in Triple Negative Breast Cancer: An Integrated Genomic Analysis.

BACKGROUND: Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive disease, and although no effective targeted therapies are available to date, about one-third of patients with TNBC achieve pathologic complete response (pCR) from standard-of-care anthracycline/taxane (ACT) chemotherapy. The heterogeneity of these tumors, however, has hindered the discovery of effective biomarkers to identify such patients. METHODS AND FINDINGS: We performed whole exome sequencing on 29 TNBC cases from the MD Anderson Cancer Center (MDACC) selected because they had either pCR (n = 18) or extensive residual disease (n = 11) after neoadjuvant chemotherapy, with cases from The Cancer Genome Atlas (TCGA; n = 144) and METABRIC (n = 278) cohorts serving as validation cohorts. Our analysis revealed that mutations in the AR- and FOXA1-regulated networks, in which BRCA1 plays a key role, are associated with significantly higher sensitivity to ACT chemotherapy in the MDACC cohort (pCR rate of 94.1% compared to 16.6% in tumors without mutations in AR/FOXA1 pathway, adjusted p = 0.02) and significantly better survival outcome in the TCGA TNBC cohort (log-rank test, p = 0.05). Combined analysis of DNA sequencing, DNA methylation, and RNA sequencing identified tumors of a distinct BRCA-deficient (BRCA-D) TNBC subtype characterized by low levels of wild-type BRCA1/2 expression. Patients with functionally BRCA-D tumors had significantly better survival with standard-of-care chemotherapy than patients whose tumors were not BRCA-D (log-rank test, p = 0.021), and they had significantly higher mutation burden (p < 0.001) and presented clonal neoantigens that were associated with increased immune cell activity. A transcriptional signature of BRCA-D TNBC tumors was independently validated to be significantly associated with improved survival in the METABRIC dataset (log-rank test, p = 0.009). As a retrospective study, limitations include the small size and potential selection bias in the discovery cohort. CONCLUSIONS: The comprehensive molecular analysis presented in this study directly links BRCA deficiency with increased clonal mutation burden and significantly enhanced chemosensitivity in TNBC and suggests that functional RNA-based BRCA deficiency needs to be further examined in TNBC.

TP53 mutation hits energy metabolism and increases glycolysis in breast cancer.

Promising new hallmarks of cancer is alteration of energy metabolism that involves molecular mechanisms shifting cancer cells to aerobe glycolysis. Our goal was to evaluate the correlation between mutation in the commonly mutated tumor suppressor gene TP53 and metabolism. We established a database comprising mutation and RNA-seq expression data of the TCGA repository and performed receiver operating characteristics (ROC) analysis to compare expression of each gene between TP53 mutated and wild type samples. All together 762 breast cancer samples were evaluated of which 215 had TP53 mutation. Top up-regulated metabolic genes include glycolytic enzymes (e.g. HK3, GPI, GAPDH, PGK1, ENO1), glycolysis regulator (PDK1) and pentose phosphate pathway enzymes (PGD, TKT, RPIA). Gluconeogenesis enzymes (G6PC3, FBP1) were down-regulated. Oxygen consumption and extracellular acidification rates were measured in TP53 wild type and mutant breast cell lines with a microfluorimetric analyzer. Applying metabolic inhibitors in the presence and absence of D-glucose and L-glutamine in cell culture experiments resulted in higher glycolytic and mitochondrial activity in TP53 mutant breast cancer cell lines. In summary, TP53 mutation influences energy metabolism at multiple levels. Our results provide evidence for the synergistic activation of multiple hallmarks linking to these the mutation status of a key driver gene.

Fast and sensitive alignment of microbial whole genome sequencing reads to large sequence datasets on a desktop PC: application to metagenomic datasets and pathogen identification.

Next generation sequencing (NGS) of metagenomic samples is becoming a standard approach to detect individual species or pathogenic strains of microorganisms. Computer programs used in the NGS community have to balance between speed and sensitivity and as a result, species or strain level identification is often inaccurate and low abundance pathogens can sometimes be missed. We have developed Taxoner, an open source, taxon assignment pipeline that includes a fast aligner (e.g. Bowtie2) and a comprehensive DNA sequence database. We tested the program on simulated datasets as well as experimental data from Illumina, IonTorrent, and Roche 454 sequencing platforms. We found that Taxoner performs as well as, and often better than BLAST, but requires two orders of magnitude less running time meaning that it can be run on desktop or laptop computers. Taxoner is slower than the approaches that use small marker databases but is more sensitive due the comprehensive reference database. In addition, it can be easily tuned to specific applications using small tailored databases. When applied to metagenomic datasets, Taxoner can provide a functional summary of the genes mapped and can provide strain level identification. Taxoner is written in C for Linux operating systems. The code and documentation are available for research applications at http://code.google.com/p/taxoner.

HeurAA: accurate and fast detection of genetic variations with a novel heuristic amplicon aligner program for next generation sequencing.

Next generation sequencing (NGS) of PCR amplicons is a standard approach to detect genetic variations in personalized medicine such as cancer diagnostics. Computer programs used in the NGS community often miss insertions and deletions (indels) that constitute a large part of known human mutations. We have developed HeurAA, an open source, heuristic amplicon aligner program. We tested the program on simulated datasets as well as experimental data from multiplex sequencing of 40 amplicons in 12 oncogenes collected on a 454 Genome Sequencer from lung cancer cell lines. We found that HeurAA can accurately detect all indels, and is more than an order of magnitude faster than previous programs. HeurAA can compare reads and reference sequences up to several thousand base pairs in length, and it can evaluate data from complex mixtures containing reads of different gene-segments from different samples. HeurAA is written in C and Perl for Linux operating systems, the code and the documentation are available for research applications at http://sourceforge.net/projects/heuraa/