A systematic RNAi synthetic interaction screen reveals a link between p53 and snoRNP assembly

Antisense oligonucleotide-mediated TRA2β poison exon inclusion induces the expression of a lncRNA with anti-tumor effects

Upregulated expression of the oncogenic splicing factor TRA2β occurs in human tumors partly through decreased inclusion of its autoregulatory non-coding poison exon (PE). Here, we reveal that low TRA2β-PE inclusion negatively impacts patient survival across several tumor types. We demonstrate the ability of splice-switching antisense oligonucleotides (ASOs) to promote TRA2β-PE inclusion and lower TRA2β protein levels in pre-clinical cancer models. TRA2β-PE-targeting ASOs induce anti-cancer phenotypes and widespread transcriptomic alterations with functional impact on RNA processing, mTOR, and p53 signaling pathways. Surprisingly, the effect of TRA2β-PE-targeting ASOs on cell viability are not phenocopied by TRA2β knockdown. Mechanistically, we find that the ASO functions by both decreasing TRA2β protein and inducing the expression of TRA2β-PE-containing transcripts that act as long non-coding RNAs to sequester nuclear proteins. Finally, TRA2β-PE-targeting ASOs are toxic to preclinical 3D organoid and in vivo patient-derived xenograft models. Together, we demonstrate that TRA2β-PE acts both as a regulator of protein expression and a long-noncoding RNA to control cancer cell growth. Drugging oncogenic splicing factors using PE-targeting ASOs is a promising therapeutic strategy.

T7 phage display reveals NOLC1 as a GM3 binding partner in human breast cancer MCF-7 cells

Ganglioside GM3 is a simple monosialoganglioside (NeuAc-Gal-Glc-ceramide) that modulates cell adhesion, proliferation, and differentiation. Previously, we reported isolation of GM3-binding vascular endothelial growth factor receptor and transforming growth factor-β receptor by the T7 phage display method (Chung et al., 2009; Kim et al., 2013). To further identify novel proteins interacting with GM3, we extended the T7 phage display method in this study. After T7 phage display biopanning combined with immobilized biotin-labeled 3'-sialyllactose prepared on a streptavidin-coated microplate, we isolated 100 candidate sequences from the human lung cDNA library. The most frequently detected clones from the blast analysis were the human nucleolar and coiled-body phosphoprotein 1 (NOLC1) sequences. We initially identified NOLC1 as a molecule that possibly binds to GM3 and confirmed this binding ability using the glutathione S-transferase fusion protein. Herein, we report another GM3-interacting protein, NOLC1, that can be isolated by the T7 phage display method. These results are expected to be helpful for elucidating the functional roles of ganglioside GM3 with NOLC1. When human breast cancer MCF-7 cells were examined for subcellular localization of NOLC1, immunofluorescence of NOLC1 was observed in the intracellular region. In addition, NOLC1 expression was increased in the nucleolus after treatment with the anticancer drug doxorubicin. GM3 and NOLC1 levels in the doxorubicin-treated MCF-7 cells were correlated, indicating possible associations between GM3 and NOLC1. Therefore, direct interactions between carbohydrates and cellular proteins can pave the path for new signaling phenomena in biology.

Genetic alterations in juvenile cervical clear cell adenocarcinoma unrelated to human papillomavirus

Clear cell adenocarcinoma of the cervix (CCAC) is a special type of HPV-independent cervical cancer. It has a low incidence rate, can be difficult to diagnose early, has a poor prognosis. Its peak incidence is in adolescence, which poses a great threat to women's health. Therefore, it is very important to explore the pathogenesis of cervical clear cell adenocarcinoma to guide subsequent treatment and prevention. This study analyzed 3 juvenile patients with CCAC diagnosed at the First Affiliated Hospital of Zhengzhou University. Using next-generation sequencing methods, we analyzed the pathogenesis of the patients and their close relatives by analyzing the genetic alterations of patients. CMTM5 was identified as the only shared mutated gene. Using published literature and comparative analyses of related disease-causing genes, 6 of the 19 genes (ALKBH7, MYCBP, MZF1, RNF207, RRS1, and TUSC2) were screened as genes with mutations in patients and had higher mutation rates in reproductive cancers. Pathway analysis showed that downregulated genes in non-HPV cervical cancer were mainly related to the immune system response, suggesting that non-HPV cervical cancer differs from HPV-infected cervical cancer in that the immune response is weaker, which is consistent with the weak correlation with viral infection.

snoRNAs in hematopoiesis and blood malignancies: A comprehensive review

Small nucleolar RNAs (snoRNAs) are noncoding RNA molecules of highly variable size, usually ranging from 60 to 150 nucleotides. They are classified into H/ACA box snoRNAs, C/D box snoRNAs, and scaRNAs. Their functional profile includes biogenesis of ribosomes, processing of rRNAs, 2'-O-methylation and pseudouridylation of RNAs, alternative splicing and processing of mRNAs and the generation of small RNA molecules like miRNA. The snoRNAs have been observed to have an important role in hematopoiesis and malignant hematopoietic conditions including leukemia, lymphoma, and multiple myeloma. Blood malignancies arise in immune system cells or the bone marrow due to chromosome abnormalities. It has been estimated that annually over 1.25 million cases of blood cancer occur worldwide. The snoRNAs often show a differential expression profile in blood malignancies. Recent reports associate the abnormal expression of snoRNAs with the inhibition of apoptosis, uncontrolled cell proliferation, angiogenesis, and metastasis. This implies that targeting snoRNAs could be a potential way to treat hematologic malignancies. In this review, we describe the various functions of snoRNAs, their role in hematopoiesis, and the consequences of their dysregulation in blood malignancies. We also evaluate the potential of the dysregulated snoRNAs as biomarkers and therapeutic targets for blood malignancies.

Using Bland-Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques

OBJECTIVE

Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays.

METHODS

Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (<150 colonies/well) and high-growth (>150 colonies/well) cell lines. Correlational and Bland-Altman analyses were performed using SPSS software.

RESULTS

Interobserver manual pen count correlation R2 value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R2 to 0.660. Correlation of microscopic versus pen counts R2 values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland-Altman revealed potential bias with respect to the magnitude of measurement (P < .001) for both observers. Correlation of microscopic counts for both interobserver (R2 = 0.902) and intraobserver (R2 = 0.916) were analyzed. Bland-Altman revealed no bias (P = .489). Automated versus microscopic counts revealed no bias between methodologies (P = .787) and a lower correlation coefficient (R2 = 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer (P = .327, .229); Pearson correlation was 0.985 (R2 = 0.970) and 0.965 (R2 = 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement (P < .001).

CONCLUSION

Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels2) and shape (circularity) should be prioritized. Solely relying on Bland-Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction.

Maturation of small nucleolar RNAs: from production to function

Small Nucleolar RNAs (snoRNAs) are an abundant group of non-coding RNAs with well-defined roles in ribosomal RNA processing, folding and chemical modification. Besides their classic roles in ribosome biogenesis, snoRNAs are also implicated in several other cellular activities including regulation of splicing, transcription, RNA editing, cellular trafficking, and miRNA-like functions. Mature snoRNAs must undergo a series of processing steps tightly regulated by transiently associating factors and coordinated with other cellular processes including transcription and splicing. In addition to their mature forms, snoRNAs can contribute to gene expression regulation through their derivatives and degradation products. Here, we review the current knowledge on mechanisms of snoRNA maturation, including the different pathways of processing, and the regulatory mechanisms that control snoRNA levels and complex assembly. We also discuss the significance of studying snoRNA maturation, highlight the gaps in the current knowledge and suggest directions for future research in this area.

iSnoDi-LSGT: identifying snoRNA-disease associations based on local similarity constraints and global topological constraints

Growing evidence proves that small nucleolar RNAs (snoRNAs) have important functions in various biological processes, the malfunction of which leads to the emergence and development of complex diseases. However, identifying snoRNA-disease associations is an ongoing challenging task due to the considerable time- and money-consuming biological experiments. Therefore, it is urgent to design efficient and economical methods for the identification of snoRNA-disease associations. In this regard, we propose a computational method named iSnoDi-LSGT, which utilizes snoRNA sequence similarity and disease similarity as local similarity constraints. The iSnoDi-LSGT predictor further employs network embedding technology to extract topological features of snoRNAs and diseases, based on which snoRNA topological similarity and disease topological similarity are calculated as global topological constraints. To the best of our knowledge, the iSnoDi-LSGT is the first computational method for snoRNA-disease association identification. The experimental results indicate that the iSnoDi-LSGT predictor can effectively predict unknown snoRNA-disease associations. The web server of the iSnoDi-LSGT predictor is freely available at http://bliulab.net/iSnoDi-LSGT.

Overcoming biases in causal inference of molecular interactions

MOTIVATION

Computer inference of biological mechanisms is increasingly approachable due to dynamically rich data sources such as single-cell genomics. Inferred molecular interactions can prioritize hypotheses for wet-lab experiments to expedite biological discovery. However, complex data often come with unwanted biological or technical variations, exposing biases over marginal distribution and sample size in current methods to favor spurious causal relationships.

RESULTS

Considering function direction and strength as evidence for causality, we present an adapted functional chi-squared test (AdpFunChisq) that rewards functional patterns over non-functional or independent patterns. On synthetic and three biology datasets, we demonstrate the advantages of AdpFunChisq over 10 methods on overcoming biases that give rise to wide fluctuations in the performance of alternative approaches. On single-cell multiomics data of multiple phenotype acute leukemia, we found that the T-cell surface glycoprotein CD3 delta chain may causally mediate specific genes in the viral carcinogenesis pathway. Using the causality-by-functionality principle, AdpFunChisq offers a viable option for robust causal inference in dynamical systems.

AVAILABILITY AND IMPLEMENTATION

The AdpFunChisq test is implemented in the R package 'FunChisq' (2.5.2 or above) at https://cran.r-project.org/package=FunChisq. All other source code along with pre-processed data is available at Code Ocean https://doi.org/10.24433/CO.2907738.v1.

SUPPLEMENTARY INFORMATION

Supplementary materials are available at Bioinformatics online.

Loss of USP28 and SPINT2 expression promotes cancer cell survival after whole genome doubling

Background

Whole genome doubling is a frequent event during cancer evolution and shapes the cancer genome due to the occurrence of chromosomal instability. Yet, erroneously arising human tetraploid cells usually do not proliferate due to p53 activation that leads to CDKN1A expression, cell cycle arrest, senescence and/or apoptosis.

Methods

To uncover the barriers that block the proliferation of tetraploids, we performed a RNAi mediated genome-wide screen in a human colorectal cancer cell line (HCT116).

Results

We identified 140 genes whose depletion improved the survival of tetraploid cells and characterized in depth two of them: SPINT2 and USP28. We found that SPINT2 is a general regulator of CDKN1A transcription via histone acetylation. Using mass spectrometry and immunoprecipitation, we found that USP28 interacts with NuMA1 and affects centrosome clustering. Tetraploid cells accumulate DNA damage and loss of USP28 reduces checkpoint activation, thus facilitating their proliferation.

Conclusions

Our results indicate three aspects that contribute to the survival of tetraploid cells: (i) increased mitogenic signaling and reduced expression of cell cycle inhibitors, (ii) the ability to establish functional bipolar spindles and (iii) reduced DNA damage signaling.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13402-021-00654-5.

Small but Mighty-The Emerging Role of snoRNAs in Hematological Malignancies

Over recent years, the long known class of small nucleolar RNAs (snoRNAs) have gained interest among the scientific community, especially in the clinical context. The main molecular role of this interesting family of non-coding RNAs is to serve as scaffolding RNAs to mediate site-specific RNA modification of ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). With the development of new sequencing techniques and sophisticated analysis pipelines, new members of the snoRNA family were identified and global expression patterns in disease backgrounds could be determined. We will herein shed light on the current research progress in snoRNA biology and their clinical role by influencing disease outcome in hematological diseases. Astonishingly, in recent studies snoRNAs emerged as potent biomarkers in a variety of these clinical setups, which is also highlighted by the frequent deregulation of snoRNA levels in the hema-oncological context. However, research is only starting to reveal how snoRNAs might influence cellular functions and the connected disease hallmarks in hematological malignancies.

The HSP90/R2TP assembly chaperone promotes cell proliferation in the intestinal epithelium

The R2TP chaperone cooperates with HSP90 to integrate newly synthesized proteins into multi-subunit complexes, yet its role in tissue homeostasis is unknown. Here, we generated conditional, inducible knock-out mice for Rpap3 to inactivate this core component of R2TP in the intestinal epithelium. In adult mice, Rpap3 invalidation caused destruction of the small intestinal epithelium and death within 10 days. Levels of R2TP substrates decreased, with strong effects on mTOR, ATM and ATR. Proliferative stem cells and progenitors deficient for Rpap3 failed to import RNA polymerase II into the nucleus and they induced p53, cell cycle arrest and apoptosis. Post-mitotic, differentiated cells did not display these alterations, suggesting that R2TP clients are preferentially built in actively proliferating cells. In addition, high RPAP3 levels in colorectal tumors from patients correlate with bad prognosis. Here, we show that, in the intestine, the R2TP chaperone plays essential roles in normal and tumoral proliferation.

Genomic gain of RRS1 promotes hepatocellular carcinoma through reducing the RPL11-MDM2-p53 signaling

Hepatocellular carcinomas (HCCs) are characterized by frequent somatic genomic copy number alterations (CNAs), with most of them biologically unexplored. Here, we performed integrative analyses combining CNAs with the transcriptomic data to reveal the cis- and trans-effects of CNAs in HCC. We identified recurrent genomic gains of chromosome 8q, which exhibit strong trans-effects and are broadly associated with ribosome biogenesis activity. Furthermore, 8q gain-driven overexpression of ribosome biogenesis regulator (RRS1) promotes growth of HCC cells in vitro and in vivo. Mechanistically, RRS1 attenuates ribosomal stress through retaining RPL11 in the nucleolus, which, in turn, potentiates MDM2-mediated ubiquitination and degradation of p53. Clinically, higher RRS1 expression levels predict poor clinical outcomes for patients with HCC, especially in those with intact p53 Our findings established that the chromosome 8q oncogene RRS1 promotes HCC development through attenuating the RPL11-MDM2-p53 pathway and provided new potential targets for treatment of this malignancy.

Deep Learning and Transfer Learning for Automatic Cell Counting in Microscope Images of Human Cancer Cell Lines

In biology and medicine, cell counting is one of the most important elements of cytometry, with applications to research and clinical practice. For instance, the complete cell count could help to determine conditions for which cancer cells could grow or not. However, cell counting is a laborious and time-consuming process, and its automatization is highly demanded. Here, we propose use of a Convolutional Neural Network-based regressor, a regression model trained end-to-end, to provide the cell count. First, unlike most of the related work, we formulate the problem of cell counting as the regression task rather than the classification task. This allows not only to reduce the required annotation information (i.e., the number of cells instead of pixel-level annotations) but also to reduce the burden of segmenting potential cells and then classifying them. Second, we propose use of xResNet, a successful convolutional architecture with residual connection, together with transfer learning (using a pretrained model) to achieve human-level performance. We demonstrate the performance of our approach to real-life data of two cell lines, human osteosarcoma and human leukemia, collected at the University of Amsterdam (133 training images, and 32 test images). We show that the proposed method (deep learning and transfer learning) outperforms currently used machine learning methods. It achieves the test mean absolute error equal 12 (±15) against 32 (±33) obtained by the deep learning without transfer learning, and 41 (±37) of the best-performing machine learning pipeline (Random Forest Regression with the Histogram of Gradients features).

Knockdown of NOLC1 Inhibits PI3K-AKT Pathway to Improve the Poor Prognosis of Esophageal Carcinoma

Objective

Esophageal carcinoma (ESCA) is a common malignant gastrointestinal tumor. The abnormal expression of NOLC1 is involved in the tumorigenesis of various human tumors, whereas the function and mechanism of NOLC1 in ESCA remain unclear. In this study, we explored the relationship between NOLC1 and poor prognosis of ESCA, and its role and mechanism in the occurrence of ESCA.

Methods

The NOLC1 expression in ESCA tissues and cell lines was determined by qRT-PCR, immunohistochemistry, or western blot. The Kaplan–Meier method was conducted to estimate the overall survival. Cox regression analysis was carried out to examine the association between patient characteristics and prognosis. A recombined lentiviral vector containing NOLC1 was applied for transfecting ESCA cells (Eca109 and TE-13) and established a stable cell line with low NOLC1 expression or high NOLC1 expression, in the absence or presence of PI3K inhibitor (LY294002) treatment. Cell proliferation, apoptosis rate, invasion ability, migration ability, and PI3K/AKT pathway were detected by CCK8 assay, flow cytometry, Transwell assay, wound-healing assay, and western blot.

Results

NOLC1 overexpression was observed in ESCA tissues and ESCA cell lines (EC9706, Eca109, TE-13, Kyse170, T.TN) compared with adjacent normal tissues and normal esophageal cell line HEEC. NOLC1 overexpression was markedly associated with bigger tumor size, lymph node metastasis, and advanced TNM stage. Patients with NOLC1 overexpression have shorter overall survival than that of those with low NOLC1 expression. NOLC1 overexpression was considered to be an independent poor prognostic factor affecting overall survival. NOLC1 knockdown inhibited proliferation, migration, invasion, and cyclin B1 expression and promoted the apoptosis and cleaved-caspase-3 expression of Eca109 and TE-13 cells. NOLC1 overexpression accelerated proliferation, migration, invasion, and cyclin B1 expression and inhibited the apoptosis and cleaved-caspase-3 expression of ESCA cells via activating PI3K/AKT pathway. Rescue experiments showed that PI3K inhibitor (LY294002) could reverse the phenomenon caused by NOLC1 overexpression.

Conclusion

NOLC1 may be a marker for poor prognosis. It can participate in the occurrence and development of ESCA via the PI3K/AKT pathway.

A Zic2/Runx2/NOLC1 signaling axis mediates tumor growth and metastasis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies with rapid growth and high metastasis, but lacks effective therapeutic targets. Here, using public sequencing data analyses, quantitative real-time PCR assay, western blotting, and IHC staining, we characterized that runt-related transcription factor 2 (Runx2) was significantly upregulated in ccRCC tissues than that in normal renal tissues, which was associated with the worse survival of ccRCC patients. Overexpression of Runx2 promoted malignant proliferation and migration of ccRCC cells, and inversely, interfering Runx2 with siRNA attenuates its oncogenic ability. RNA sequencing and functional studies revealed that Runx2 enhanced ccRCC cell growth and metastasis via downregulation of tumor suppressor nucleolar and coiled-body phosphoprotein 1 (NOLC1). Moreover, increased Zic family member 2 (Zic2) was responsible for the upregulation of Runx2 and its oncogenic functions in ccRCC. Kaplan-Meier survival analyses indicated that ccRCC patients with high Zic2/Runx2 and low NOLC1 had the worst outcome. Therefore, our study demonstrates that Zic2/Runx2/NOLC1 signaling axis promotes ccRCC progression, providing a set of potential targets and prognostic indicators for patients with ccRCC.

Resistance effect of flavonols and toxicology analysis of hexabromocyclododecane based on soil-microbe-plant system

The toxicity characteristics of HBCD and resistance mechanism of flavonols are investigated based on physiological and metagenomic analysis. Toxicology research of HBCD on Arabidopsis thaliana (Col and fls1-3) not only shows the toxic effect of HBCD on plants, but also indicates that flavonols could improve plant resistance to HBCD, including root length, shoot biomass and chlorophyll content. Analysis of eggNOG and GO enrichment demonstrates that HBCD has toxic effect on both gene expression and protein function, which concentrates on energy production - conversion and amino acid transport - metabolism. Differential expressed genes in flavonols-treated groups indicates that flavonols regulate the metabolism of amino acids, cofactors and vitamins, which is involved in plant defense system against oxidative damage caused by HBCD stress. HBCD is believed to affect the synthesis of proteins via genes expression of ribosome biogenesis process. Flavonols could strengthen the plant resistance and alleviate toxic effect under HBCD stress.

STRAP as a New Therapeutic Target for Poor Prognosis of Pancreatic Ductal Adenocarcinoma Patients Mainly Caused by TP53 Mutation

Pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate and poor prognosis. KRAS, TP53, CDKN2A, and SMAD4 are driver genes of PDAC and 30-75% patients have mutations in at least two of these four genes. Herein, we analyzed the relationship between these genes and prognosis of 762 patients in the absence of coexisting mutations, using data from three independent public datasets. Interestingly, we found that compared with mutations in other driver genes, TP53 mutation plays a significant role in leading to poor prognosis of PDAC. Additionally, we found that snoRNA-mediated rRNA maturation was responsible for the progression of cancer in PDAC patients with TP53 mutations. Inhibition of STRAP, which regulates the localization of SMN complexes and further affects the assembly of snoRNP, can effectively reduce maturation of rRNA and significantly suppress progression of TP53-mutant or low p53 expression pancreatic cancer cells in vitro and in vivo. Our study highlighted the actual contribution rate of driver genes to patient prognosis, enriching traditional understanding of the relationship between these genes and PDAC. We also provided a possible mechanism and a new target to combat progression of TP53-mutant PDAC patients.

A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

BACKGROUND

The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance.

METHODS

Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy.

RESULTS

Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. We analyzed human homologs of yeast genes exhibiting gene-doxorubicin interaction in cancer pharmacogenomics data to predict causality for differential gene expression associated with doxorubicin cytotoxicity in cancer cells. This analysis suggested conserved cellular responses to doxorubicin due to influences of homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, actin cortical patch localization, and other gene functions.

CONCLUSIONS

Warburg status alters the genetic network required for yeast to buffer doxorubicin toxicity. Integration of yeast phenomic and cancer pharmacogenomics data suggests evolutionary conservation of gene-drug interaction networks and provides a new experimental approach to model their influence on chemotherapy response. Thus, yeast phenomic models could aid the development of precision oncology algorithms to predict efficacious cytotoxic drugs for cancer, based on genetic and metabolic profiles of individual tumors.

Identification and validation of NOLC1 as a potential target for enhancing sensitivity in multidrug resistant non-small cell lung cancer cells

Adjuvant chemotherapy has become the frequently adopted standard therapeutic approach for non-small cell lung cancer (NSCLC). However, the development of multidrug resistance (MDR) is a major obstacle contributing to the failure of chemotherapy. This study aimed to identify genes associated with MDR development that predict tumor response to chemotherapy in NSCLC. In the present study, a multidrug-resistant NSCLC cell sub-line, A549/MDR, was established from the A549/DDP cell line and characterized. The resistance index (RI) of this subline was calculated according to the IC50 of A549/MDR relative to the parental A549/DDP cells. The gene expression profiles of A549/DDP and A549/MDR were obtained using an oligonucleotide microarray (Agilent SureHyb microarray chip). The microarray results were validated by qRT-PCR and selected genes were analyzed by in vitro loss-of-function experiments. Gene expression profiling identified 921 differentially expressed genes (DEGs) according to the selection criteria, in which 541 genes were upregulated and 380 genes were downregulated in A549/MDR compared with A549/DDP cells. We found that these DEGs are involved in diverse biological processes, including ribonucleoprotein complex, drug metabolism, the Hippo signaling pathway and transcriptional misregulation. NOLC1, as one of the identified DEGs, was confirmed to be overexpressed in A549/MDR cells and its knockdown significantly enhanced the drug sensitivity of A549/MDR cells in response to multidrug treatment. Furthermore, knockdown of NOLC1 downregulated the expression levels of drug resistance-associated molecules (LRP and MDR1) in A549/MDR cells. These findings provide a new and comprehensive expression profile of MDR in NSCLC cells. Identification and validation of NOLC1 might be a promising therapeutic strategy for the management of MDR of NSCLC patients.

Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls

Synthetic lethal interactions, in which the simultaneous loss of function of two genes produces a lethal phenotype, are being explored as a means to therapeutically exploit cancer-specific vulnerabilities and expand the scope of precision oncology. Currently, three Food and Drug Administration-approved drugs work by targeting the synthetic lethal interaction between BRCA1/2 and PARP. This review examines additional efforts to discover networks of synthetic lethal interactions and discusses both challenges and opportunities regarding the translation of new synthetic lethal interactions into the clinic.

Synthesizing a Genetic Sensor Based on CRISPR-Cas9 for Specifically Killing p53-Deficient Cancer Cells

Cancer is still one of the greatest medical challenges in the world. The p53 protein plays an important role in the process of cancer formation. In addition, p53 is found as the most common mutant gene in cancers. Because of the central role of p53 in oncology, it is necessary to construct effective sensors to detect this protein. However, there are few methods to detect wild type p53 protein (WTP53) or to distinguish the wild type and mutant p53 proteins. In our study, we designed and constructed a p53 genetic sensor that detected the expression of WTP53 in cells. Moreover, we combined the p53 sensor with diphtheria toxin using the CRISPR-Cas9 system to construct a p53 genetic sensor that specifically killed p53-deficient cells such as tumor cells. Our study therefore developed a new way to treat cancers by using an available genetic sensor based on p53 protein.

Turning Uridines around: Role of rRNA Pseudouridylation in Ribosome Biogenesis and Ribosomal Function

Ribosomal RNA (rRNA) is extensively edited through base methylation and acetylation, 2'-O-ribose methylation and uridine isomerization. In human rRNA, 95 uridines are predicted to by modified to pseudouridine by ribonucleoprotein complexes sharing four core proteins and differing for a RNA sequence guiding the complex to specific residues to be modified. Most pseudouridylation sites are placed within functionally important ribosomal domains and can influence ribosomal functional features. Information obtained so far only partially explained the degree of regulation and the consequences of pseudouridylation on ribosomal structure and function in different physiological and pathological conditions. This short review focuses on the available evidence in this topic, highlighting open questions in the field and perspectives that the development of emerging techniques is offering.

40 Years of Research Put p53 in Translation

Since its discovery in 1979, p53 has shown multiple facets. Initially the tumor suppressor p53 protein was considered as a stress sensor able to maintain the genome integrity by regulating transcription of genes involved in cell cycle arrest, apoptosis and DNA repair. However, it rapidly came into light that p53 regulates gene expression to control a wider range of biological processes allowing rapid cell adaptation to environmental context. Among them, those related to cancer have been extensively documented. In addition to its role as transcription factor, scattered studies reported that p53 regulates miRNA processing, modulates protein activity by direct interaction or exhibits RNA-binding activity, thus suggesting a role of p53 in regulating several layers of gene expression not restricted to transcription. After 40 years of research, it appears more and more clearly that p53 is strongly implicated in translational regulation as well as in the control of the production and activity of the translational machinery. Translation control of specific mRNAs could provide yet unsuspected capabilities to this well-known guardian of the genome.

Co-sequencing and novel delayed anti-correlation identify function for pancreatic enriched microRNA biomarkers in a rat model of acute pancreatic injury

Background

Co-sequencing of messenger ribonucleic acid (mRNA) and micro ribonucleic acid (miRNA) across a time series (1, 3, 6, 24, and 48 h post injury) was used to identify potential miRNA-gene interactions during pancreatic injury, associate serum and tissue levels of candidate miRNA biomarkers of pancreatic injury, and functionally link these candidate miRNA biomarkers to observed histopathology. RNAs were derived from pancreatic tissues obtained in experiments characterizing the serum levels of candidate miRNA biomarkers in response to acute pancreatic injury in rats.

Results

No correlation was discovered between tissue and serum levels of the miRNAs. A combination of differential gene expression, novel delayed anti-correlation analysis and experimental database interrogation was used to identify messenger RNAs and miRNAs that experienced significant expression change across the time series, that were negatively correlated, that were complementary in sequence, and that had experimentally supported relationships. This approach yielded a complex signaling network for future investigation and a link for the specific candidate miRNA biomarkers, miR-216a-5p and miR-217-5p, to cellular processes that were in fact the prominent histopathology observations in the same experimental samples. RNA quality bias by treatment was observed in the study samples and a statistical correction was applied. The relevance and impact of that correction on significant results is discussed.

Conclusion

The described approach allowed extraction of miRNA function from genomic data and defined a mechanistic anchor for these miRNAs as biomarkers. Functional and mechanistic conclusions are supported by histopathology findings.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4657-2) contains supplementary material, which is available to authorized users.

p53 Activity Results in DNA Replication Fork Processivity

p53 induces cell death upon DNA damage, but this may not confer all of its tumor suppressor activity. We report that p53 activation enhances the processivity of DNA replication, as monitored by multi-label fiber assays, whereas removal of p53 reduces fork progression. This is observed in tumor-derived U2OS cells but also in murine embryonic fibroblasts with heterozygous or homozygous p53 deletion and in freshly isolated thymocytes from mice with differential p53 status. Mdm2, a p53-inducible gene product, similarly supports DNA replication even in p53-deficient cells, suggesting that sustained Mdm2-expression is at least one of the mechanisms allowing p53 to prevent replicative stress. Thus, p53 helps to protect the genome during S phase, by preventing the occurrence of stalled or collapsed replication forks. These results expand p53's tumor-suppressive functions, adding to the ex-post model (elimination of damaged cells) an ex-ante activity; i.e., the prevention of DNA damage during replication.

Development of a genetic sensor that eliminates p53 deficient cells

The TP53 gene fulfills a central role in protecting cells from genetic insult. Given this crucial role it might be surprising that p53 itself is not essential for cell survival. Indeed, TP53 is the single most mutated gene across different cancer types. Thus, both a theoretical and a question of significant practical applicability arise: can cells be programmed to make TP53 an essential gene? Here we present a genetic p53 sensor, in which the loss of p53 is coupled to the rise of HSV-TK expression. We show that the sensor can distinguish both p53 knockout and cells expressing a common TP53 cancer mutation from otherwise isogenic TP53 wild-type cells. Importantly, the system is sensitive enough to specifically target TP53 loss-of-function cells with the HSV-TK pro-drug Ganciclovir both in vitro and in vivo. Our work opens new ways to programming cell intrinsic transformation protection systems that rely on endogenous components.

TP53 is mutated in many cancers, a system to detect and selectively eliminate p53 mutant cells is an attractive therapeutic strategy. Here, the authors present a genetic sensor that can detect p53 activity and is coupled to the thymidine kinase gene, which can activate the drug Ganciclovir, resulting in cell death.

Assembly and trafficking of box C/D and H/ACA snoRNPs

Box C/D and box H/ACA snoRNAs are abundant non-coding RNAs that localize in the nucleolus and mostly function as guides for nucleotide modifications. While a large pool of snoRNAs modifies rRNAs, an increasing number of snoRNAs could also potentially target mRNAs. ScaRNAs belong to a family of specific RNAs that localize in Cajal bodies and that are structurally similar to snoRNAs. Most scaRNAs are involved in snRNA modification, while telomerase RNA, which contains H/ACA motifs, functions in telomeric DNA synthesis. In this review, we describe how box C/D and H/ACA snoRNAs are processed and assembled with core proteins to form functional RNP particles. Their biogenesis involve several transport factors that first direct pre-snoRNPs to Cajal bodies, where some processing steps are believed to take place, and then to nucleoli. Assembly of core proteins involves the HSP90/R2TP chaperone-cochaperone system for both box C/D and H/ACA RNAs, but also several factors specific for each family. These assembly factors chaperone unassembled core proteins, regulate the formation and disassembly of pre-snoRNP intermediates, and control the activity of immature particles. The AAA+ ATPase RUVBL1 and RUVBL2 belong to the R2TP co-chaperones and play essential roles in snoRNP biogenesis, as well as in the formation of other macro-molecular complexes. Despite intensive research, their mechanisms of action are still incompletely understood.

A genome-wide siRNA screen for regulators of tumor suppressor p53 activity in human non-small cell lung cancer cells identifies components of the RNA splicing machinery as targets for anticancer treatment

Reinstating wild-type tumor suppressor p53 activity could be a valuable option for the treatment of cancer. To contribute to development of new treatment options for non-small cell lung cancer (NSCLC), we performed genome-wide siRNA screens for determinants of p53 activity in NSCLC cells. We identified many genes not previously known to be involved in regulating p53 activity. Silencing p53 pathway inhibitor genes was associated with loss of cell viability. The largest functional gene cluster influencing p53 activity was mRNA splicing. Prominent p53 activation was observed upon silencing of specific spliceosome components, rather than by general inhibition of the spliceosome. Ten genes were validated as inhibitors of p53 activity in multiple NSCLC cell lines: genes encoding the Ras pathway activator SOS1, the zinc finger protein TSHZ3, the mitochondrial membrane protein COX16, and the spliceosome components SNRPD3, SF3A3, SF3B1, SF3B6, XAB2, CWC22, and HNRNPL. Silencing these genes generally increased p53 levels, with distinct effects on CDKN1A expression, induction of cell cycle arrest and cell death. Silencing spliceosome components was associated with alternative splicing of MDM4 mRNA, which could contribute to activation of p53. In addition, silencing splice factors was particularly effective in killing NSCLC cells, albeit in a p53-independent manner. Interestingly, silencing SNRPD3 and SF3A3 exerted much stronger cytotoxicity to NSCLC cells than to lung fibroblasts, suggesting that these genes could represent useful therapeutic targets.

Tuning the ribosome: The influence of rRNA modification on eukaryotic ribosome biogenesis and function

rRNAs are extensively modified during their transcription and subsequent maturation in the nucleolus, nucleus and cytoplasm. RNA modifications, which are installed either by snoRNA-guided or by stand-alone enzymes, generally stabilize the structure of the ribosome. However, they also cluster at functionally important sites of the ribosome, such as the peptidyltransferase center and the decoding site, where they facilitate efficient and accurate protein synthesis. The recent identification of sites of substoichiometric 2'-O-methylation and pseudouridylation has overturned the notion that all rRNA modifications are constitutively present on ribosomes, highlighting nucleotide modifications as an important source of ribosomal heterogeneity. While the mechanisms regulating partial modification and the functions of specialized ribosomes are largely unknown, changes in the rRNA modification pattern have been observed in response to environmental changes, during development, and in disease. This suggests that rRNA modifications may contribute to the translational control of gene expression.

The importance of being (slightly) modified: The role of rRNA editing on gene expression control and its connections with cancer

In human ribosomal RNAs, over 200 residues are modified by specific, RNA-driven enzymatic complexes or stand-alone, RNA-independent enzymes. In most cases, modification sites are placed in specific positions within important functional areas of the ribosome. Some evidence indicates that the altered control in ribosomal RNA modifications may affect ribosomal function during mRNA translation. Here we provide an overview of the connections linking ribosomal RNA modifications to ribosome function, and suggest how aberrant modifications may affect the control of the expression of key cancer genes, thus contributing to tumor development. In addition, the future perspectives in this field are discussed.

High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection

Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays.

Malignancy of Cancers and Synthetic Lethal Interactions Associated With Mutations of Cancer Driver Genes

The mutation status of cancer driver genes may correlate with different degrees of malignancy of cancers. The doubling time and multidrug resistance are 2 phenotypes that reflect the degree of malignancy of cancer cells. Because most of cancer driver genes are hard to target, identification of their synthetic lethal partners might be a viable approach to treatment of the cancers with the relevant mutations.The genome-wide screening for synthetic lethal partners is costly and labor intensive. Thus, a computational approach facilitating identification of candidate genes for a focus synthetic lethal RNAi screening will accelerate novel anticancer drug discovery.We used several publicly available cancer cell lines and tumor tissue genomic data in this study.We compared the doubling time and multidrug resistance between the NCI-60 cell lines with mutations in some cancer driver genes and those without the mutations. We identified some candidate synthetic lethal genes to the cancer driver genes APC, KRAS, BRAF, PIK3CA, and TP53 by comparison of their gene phenotype values in cancer cell lines with the relevant mutations and wild-type background. Further, we experimentally validated some of the synthetic lethal relationships we predicted.We reported that mutations in some cancer driver genes mutations in some cancer driver genes such as APC, KRAS, or PIK3CA might correlate with cancer proliferation or drug resistance. We identified 40, 21, 5, 43, and 18 potential synthetic lethal genes to APC, KRAS, BRAF, PIK3CA, and TP53, respectively. We found that some of the potential synthetic lethal genes show significantly higher expression in the cancers with mutations of their synthetic lethal partners and the wild-type counterparts. Further, our experiments confirmed several synthetic lethal relationships that are novel findings by our methods.We experimentally validated a part of the synthetic lethal relationships we predicted. We plan to perform further experiments to validate the other synthetic lethal relationships predicted by this study.Our computational methods achieve to identify candidate synthetic lethal partners to cancer driver genes for further experimental screening with multiple lines of evidences, and therefore contribute to development of anticancer drugs.

Towards a compendium of essential genes - From model organisms to synthetic lethality in cancer cells

Essential genes are defined by their requirement to sustain life in cells or whole organisms. The systematic identification of essential gene sets not only allows insights into the fundamental building blocks of life, but may also provide novel therapeutic targets in oncology. The discovery of essential genes has been tightly linked to the development and deployment of various screening technologies. Here, we describe how gene essentiality was addressed in different eukaryotic model organisms, covering a range of organisms from yeast to mouse. We describe how increasing knowledge of evolutionarily divergent genomes facilitate identification of gene essentiality across species. Finally, the impact of gene essentiality and synthetic lethality on cancer research and the clinical translation of screening results are highlighted.

Collateral Lethality: A new therapeutic strategy in oncology

Genomic deletion of tumor suppressor genes (TSG) is a rite of passage for virtually all human cancers. The synthetic lethal paradigm has provided a framework for the development of molecular targeted therapeutics that are functionally linked to the loss of specific TSG functions. In the course of genomic events that delete TSGs, a large number of genes with no apparent direct role in tumor promotion also sustain deletion as a result of chromosomal proximity to the target TSG. In this perspective, we review the novel concept of "collateral lethality", which has served to identify cancer-specific therapeutic vulnerabilities resulting from co-deletion of passenger genes neighboring TSG. The large number of collaterally deleted genes, playing diverse functions in cell homeostasis, offers a rich repertoire of pharmacologically targetable vulnerabilities presenting novel opportunities for the development of personalized anti-neoplastic therapies.

Hitting cancers' weak spots: vulnerabilities imposed by p53 mutation

The tumor suppressor protein p53 plays a critical role in limiting malignant development and progression. Almost all cancers show loss of p53 function, through either mutation in the p53 gene itself or defects in the mechanisms that activate p53. While reactivation of p53 can effectively limit tumor growth, this is a difficult therapeutic goal to achieve in the many cancers that do not retain wild type p53. An alternative approach focuses on identifying vulnerabilities imposed on cancers by virtue of the loss of or alterations in p53, to identify additional pathways that can be targeted to specifically kill or inhibit the growth of p53 mutated cells. These indirect ways of exploiting mutations in p53 - which occur in more than half of all human cancers - provide numerous exciting therapeutic possibilities.

Ribosomal proteins as novel players in tumorigenesis

Ribosome biogenesis is the most demanding energetic and metabolic expenditure of the cell. The nucleolus, a nuclear compartment, coordinates rRNA transcription, maturation, and assembly into ribosome subunits. The transcription process is highly coordinated with ribosome biogenesis. In this context, ribosomal proteins (RPs) play a crucial role. In the last decade, an increasing number of studies have associated RPs with extraribosomal functions related to proliferation. Importantly, the expression of RPs appears to be deregulated in several human disorders due, at least in part, to genetic mutations. Although the deregulation of RPs in human malignancies is commonly observed, a more complex mechanism is believed to be involved, favoring the tumorigenic process, its progression and metastasis. This review explores the roles of the most frequently mutated oncogenes and tumor suppressor genes in human cancer that modulate ribosome biogenesis, including their interaction with RPs. In this regard, we propose a new focus for novel therapies.

Noncoding RNAs in eukaryotic ribosome biogenesis and function

The ribosome, central to protein synthesis in all cells, is a complex multicomponent assembly with rRNA at its functional core. During the process of ribosome biogenesis, diverse noncoding RNAs participate in controlling the quantity and quality of this rRNA. In this Review, I discuss the multiple roles assumed by noncoding RNAs during the different steps of ribosome biogenesis and how they contribute to the generation of ribosome heterogeneity, which affects normal and pathophysiological processes.

Analysis of the p53/CEP-1 regulated non-coding transcriptome in C. elegans by an NSR-seq strategy

In recent years, large numbers of non-coding RNAs (ncRNAs) have been identified in C. elegans but their functions are still not well studied. In C. elegans, CEP-1 is the sole homolog of the p53 family of genes. In order to obtain transcription profiles of ncRNAs regulated by CEP-1 under normal and UV stressed conditions, we applied the 'not-so-random' hexamers priming strategy to RNA sequencing in C. elegans, This NSR-seq strategy efficiently depleted rRNA transcripts from the samples and showed high technical replicability. We identified more than 1,000 ncRNAs whose apparent expression was repressed by CEP-1, while around 200 were activated. Around 40% of the CEP-1 activated ncRNAs promoters contain a putative CEP-1-binding site. CEP-1 regulated ncRNAs were frequently clustered and concentrated on the X chromosome. These results indicate that numerous ncRNAs are involved in CEP-1 transcriptional network and that these are especially enriched on the X chromosome in C. elegans.

Plk2 regulates mitotic spindle orientation and mammary gland development

Disruptions in polarity and mitotic spindle orientation contribute to the progression and evolution of tumorigenesis. However, little is known about the molecular mechanisms regulating these processes in vivo. Here, we demonstrate that Polo-like kinase 2 (Plk2) regulates mitotic spindle orientation in the mammary gland and that this might account for its suggested role as a tumor suppressor. Plk2 is highly expressed in the mammary gland and is required for proper mammary gland development. Loss of Plk2 leads to increased mammary epithelial cell proliferation and ductal hyperbranching. Additionally, a novel role for Plk2 in regulating the orientation of the mitotic spindle and maintaining proper cell polarity in the ductal epithelium was discovered. In support of a tumor suppressor function for Plk2, loss of Plk2 increased the formation of lesions in multiparous glands. Collectively, these results demonstrate a novel role for Plk2 in regulating mammary gland development.

Application of shotgun proteomics for discovery-driven protein-protein interaction

Affinity purification of protein complexes and identification of co-purified proteins by mass spectrometry is a powerful method to discover novel protein-protein interactions. Application of this method to the study of biological systems often requires the ability to process a large number of samples. Hence, there is great need to generate proteomic workflows compatible with large-scale studies. The major goal of this protocol is to present a fast, reliable, and scalable method to characterize protein complexes by mass spectrometry to overcome the limitations of conventional geLC-MS/MS or MudPIT protocols. This method was successfully employed for the discovery and characterization of novel protein complexes in cultured yeast, mammalian cells, and mice.

DON shares a similar mode of action as the ribotoxic stress inducer anisomycin while TBTO shares ER stress patterns with the ER stress inducer thapsigargin based on comparative gene expression profiling in Jurkat T cells

Previously, we studied the effects of deoxynivalenol (DON) and tributyltin oxide (TBTO) on whole genome mRNA expression profiles of human T lymphocyte Jurkat cells. These studies indicated that DON induces ribotoxic stress and both DON and TBTO induced ER stress which resulted into T-cell activation and apoptosis. The first goal of the present study was to provide final proof for these mode of actions by comparing the effects of 6 h exposure to DON and TBTO on mRNA expression to those of positive controls of ribotoxic stress (anisomycin), ER stress (thapsigargin) and T cell activation (ionomycin). Genes affected by anisomycin and the majority of genes affected by thapsigargin were affected in the same direction by DON and TBTO, respectively, confirming the expected modes of action. Pathway analysis further sustained that DON induces ribotoxic stress and both DON and TBTO induce unfolded protein response (UPR), ER stress, T cell activation and apoptosis. The second goal was to assess whether DON and/or TBTO affect other pathways above those detected before. TBTO induced groups of genes that are involved in DNA packaging and heat shock response that were not affected by thapsigargin. DON did not affect other genes than anisomycin indicating the effect of DON to be restricted to ribotoxic stress. This study also demonstrates that comparative gene expression analysis is a very promising tool for the identification of modes of action of immunotoxic compounds.

High-resolution network biology: connecting sequence with function

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein-protein, genetic and drug-gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

This study defines a network of synthetic sick/lethal interactions with a set of query genes in a series of isogenic cancer cell lines. Analysis of differential essentiality reveals general properties in genetic interaction networks derived from studies on model organisms.

This study defined about 200 negative genetic interactions in the isogenic cancer cell line background.

Mapping of negative genetic interactions in a systematic fashion in isogenic cancer cell lines has revealed novel functions for several uncharacterized genes.

This study demonstrates that differential essentiality profiles derived from isogenic cancer cell lines can be used to classify genetic dependencies in non-isogenic cancer cell lines.

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN^−/− DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

Identification of potential synthetic lethal genes to p53 using a computational biology approach

BACKGROUND

Identification of genes that are synthetic lethal to p53 is an important strategy for anticancer therapy as p53 mutations have been reported to occur in more than half of all human cancer cases. Although genome-wide RNAi screening is an effective approach to finding synthetic lethal genes, it is costly and labor-intensive.

METHODS

To illustrate this approach, we identified potentially druggable genes synthetically lethal for p53 using three microarray datasets for gene expression profiles of the NCI-60 cancer cell lines, one next-generation sequencing (RNA-Seq) dataset from the Cancer Genome Atlas (TCGA) project, and one gene expression data from the Cancer Cell Line Encyclopedia (CCLE) project. We selected the genes which encoded kinases and had significantly higher expression in the tumors with functional p53 mutations (somatic mutations) than in the tumors without functional p53 mutations as the candidates of druggable synthetic lethal genes for p53. We identified important regulatory networks and functional categories pertinent to these genes, and performed an extensive survey of literature to find experimental evidence that support the synthetic lethality relationships between the genes identified and p53. We also examined the drug sensitivity difference between NCI-60 cell lines with functional p53 mutations and NCI-60 cell lines without functional p53 mutations for the compounds that target the kinases encoded by the genes identified.

RESULTS

Our results indicated that some of the candidate genes we identified had been experimentally verified to be synthetic lethal for p53 and promising targets for anticancer therapy while some other genes were putative targets for development of cancer therapeutic agents.

CONCLUSIONS

Our study indicated that pre-screening of potential synthetic lethal genes using gene expression profiles is a promising approach for improving the efficiency of synthetic lethal RNAi screening.

p53 acts as a safeguard of translational control by regulating fibrillarin and rRNA methylation in cancer

Ribosomes are specialized entities that participate in regulation of gene expression through their rRNAs carrying ribozyme activity. Ribosome biogenesis is overactivated in p53-inactivated cancer cells, although involvement of p53 on ribosome quality is unknown. Here, we show that p53 represses expression of the rRNA methyl-transferase fibrillarin (FBL) by binding directly to FBL. High levels of FBL are accompanied by modifications of the rRNA methylation pattern, impairment of translational fidelity, and an increase of internal ribosome entry site (IRES)-dependent translation initiation of key cancer genes. FBL overexpression contributes to tumorigenesis and is associated with poor survival in patients with breast cancer. Thus, p53 acts as a safeguard of protein synthesis by regulating FBL and the subsequent quality and intrinsic activity of ribosomes.

Elevated snoRNA biogenesis is essential in breast cancer

Hyperactive ribosomal biogenesis is widely observed in cancer, which has been partly attributed to the increased rDNA transcription by Pol I in cancer. However, whether small nucleolar RNAs (snoRNAs), a class of non-coding RNAs crucial in ribosomal RNA (rRNA) maturation and functionality, are involved in cancer remains elusive. We report that snoRNAs and fibrillarin (FBL, an enzymatic small nucleolar ribonucleoprotein, snoRNP) are frequently overexpressed in both murine and human breast cancer as well as in prostate cancers, and significantly, that this overexpression is essential for tumorigenicity in vitro and in vivo. We demonstrate that when the elevated snoRNA pathway is suppressed, the tumor suppressor p53 can act as a sentinel of snoRNP perturbation, the activation of which mediates the growth inhibitory effect. On the other hand, high level of FBL interferes with the activation of p53 by stress. We further show that p53 activation by FBL knockdown is not only regulated by the ribosomal protein-MDM2-mediated protein stabilization pathway, but also by enhanced PTB-dependent, cap-independent translation. Together, our data uncover an essential role of deregulated snoRNA biogenesis in tumors and a new mechanism of nucleolar modulation of p53.

p53 and translation attenuation regulate distinct cell cycle checkpoints during endoplasmic reticulum (ER) stress

Cell cycle checkpoints ensure that proliferation occurs only under permissive conditions, but their role in linking nutrient availability to cell division is incompletely understood. Protein folding within the endoplasmic reticulum (ER) is exquisitely sensitive to energy supply and amino acid sources because deficiencies impair luminal protein folding and consequently trigger ER stress signaling. Following ER stress, many cell types arrest within the G(1) phase, although recent studies have identified a novel ER stress G(2) checkpoint. Here, we report that ER stress affects cell cycle progression via two classes of signal: an early inhibition of protein synthesis leading to G(2) delay involving CHK1 and a later induction of G(1) arrest associated both with the induction of p53 target genes and loss of cyclin D(1). We show that substitution of p53/47 for p53 impairs the ER stress G(1) checkpoint, attenuates the recovery of protein translation, and impairs induction of NOXA, a mediator of cell death. We propose that cell cycle regulation in response to ER stress comprises redundant pathways invoked sequentially first to impair G(2) progression prior to ultimate G(1) arrest.

Designing efficient and specific endoribonuclease-prepared siRNAs

RNA interference (RNAi) has grown to be one of the main techniques for loss-of-function studies, leading to the elucidation of biological function of genes in various cellular systems and model organisms. While for many invertebrates such as Drosophila melanogaster (D. melanogaster) and Caenorhabditis elegans (C. elegans) long double-stranded RNA (dsRNA) can directly be used to induce a RNAi response, chemically synthesized small interfering RNAs (siRNAs) are typically employed in mammalian cells to avoid an interferon-like response triggered by long dsRNA (Reynolds et al., RNA 12:988-993, 2006). However, siRNAs are expensive and beset with unintentional gene targeting effects (off-targets) confounding the analysis of results from such studies. We, and others, have developed an alternative technology for RNAi in mammalian cells, termed endoribonuclease-prepared siRNA (esiRNA), which is based on the enzymatic generation of siRNA pools by digestion of long dsRNAs with recombinant RNase III in vitro (Yang et al., Proc Natl Acad Sci USA 99: 9942-9947, 2002; Myers et al., Nat Biotechnol 21:324-328; 2003). This technology has proven to be cost-efficient and reliable. Furthermore, several studies have demonstrated that complex pools of siRNAs, as inherent in esiRNAs, which target one transcript reduce off-target effects (Myers et al., J RNAi Gene Silencing 2:181, 2006; Kittler et al., Nat Methods 4:337-344, 2007). Within this chapter we describe design criteria for the generation of target-optimized esiRNAs.