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Deep learning for cancer type classification

Genetic information is becoming more readily available and is increasingly being used to predict patient cancer types as well as their subtypes. Most classification methods thus far utilize somatic mutations as independent features for classification and are limited by study power. To address these limitations, we propose DeepCues, a deep learning model that utilizes convolutional neural networks to derive features from DNA sequencing data for disease classification and relevant gene discovery. Using whole-exome sequencing, germline variants and somatic mutations, including insertions and deletions, are interactively amalgamated as features. In this study, we applied DeepCues to a dataset from TCGA to classify seven different types of major cancers and obtained an overall accuracy of 77.6%. We compared DeepCues to conventional methods and demonstrated a significant overall improvement (p=8.8E-25). Using DeepCues, we found that the top 20 genes associated with breast cancer have a 40% overlap with the top 20 breast cancer genes in the COSMIC database. These data support DeepCues as a novel method to improve the representational resolution of both germline variants and somatic mutations interactively and their power in predicting cancer types, as well the genes involved in each cancer.

cancer biology

3,3′-Diindolylmethane Dose-Dependently Prevents Advanced Prostate Cancer

3,3'-Diindolylmethane (DIM) is an acid-derived dimer of indole-3-carbinol, found in many cruciferous vegetables, such as broccoli, and has been shown to inhibit prostate cancer (PCa) in several in vitro and in vivo models. We demonstrated that DIM stimulated both estrogen receptor alpha (ER) and estrogen receptor beta (ER{beta}) transcriptional activities and propose that ER{beta} plays a role in mediating DIMs inhibition on cancer cell growth. To further study the effects of DIM on inhibiting advanced PCa development, we tested DIM in TRAMP (TRansgenic Adenocarcinoma of the Mouse Prostate) mice. The control group of mice were fed a high fat diet. Three additional groups of mice were fed the same high fat diet supplemented with 0.04%, 0.2% and 1% DIM. Incidence of advanced PCa, poorly differentiated carcinoma (PDC), in the control group was 60%. 1% DIM dramatically reduced PDC incidence to 24% (p=0.0012), while 0.2% and 0.04% DIM reduced PDC incidence to 38% (p=0.047) and 45% (p=0.14) respectively. Though DIM did affect mice weights, statistical analysis showed a clear negative association between DIM concentration and PDC incidence with p=0.004, while the association between body weight and PDC incidence was not significant (p=0.953). In conclusion, our results show that dietary DIM can inhibit the most aggressive stage of prostate cancer at concentration lower than previously demonstrated, possibly working through an estrogen receptor mediated mechanism.

cancer biology

Early urine proteome changes in an implanted bone cancer rat model

In this study, Walker 256 cells were implanted into rat tibiae. Urine samples were then collected on days 3, 5, 7, and 13 and were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). With label-free quantification, 25 proteins were found to change significantly in the urine of the tumor group mice compared with the proteins in the urine of the control group mice; this was even the case when there were no significant lesions identified in the Computed Tomography(CT) examination. Among these differentially proteins, 7 were reported to be associated with tumor bone metastasis. GO analysis shows that the differential proteins on day 3 were involved in several responses, including the acute phase response, the adaptive immune response and the innate immune response. The differentially proteins on day 7 were involved in the mineral absorption pathway. The differentially proteins on day 13 were involved in vitamin D binding and calcium ion binding. These processes may be associated with bone metastasis. Our results demonstrate that urine could sensitively reflect the changes in the early stage of implanted bone cancer; this provides valuable clues for future studies of urine biomarkers for tumor bone metastasis.

cancer biology

A CRISPR Knockout Screen Identifies Foxf1 as a Suppressor of Colorectal Cancer Metastasis That Acts Through Reduced mTOR Signalling

IntroductionA greater understanding of molecular mechanisms underlying metastasis is necessary for development of new strategies to prevent and treat cancer.\n\nMethodsWe performed a genome-wide CRISPR/Cas9 knockout screen in MC38 colorectal cancer (CRC) cells transplanted orthotopically into mice to identify genes that promote metastasis. We undertook focussed molecular analyses to identify mechanisms underlying metastasis.\n\nResultsThe screen identified several gene knockouts over-represented in lung metastases, including Dptor (mTOR signalling) and Foxf1 (gastrointestinal tumour predisposition). We validate that loss of Foxf1 promotes metastasis, increased Foxf1 expression restrained cellular migration in-vitro and human CRC metastases express lower Foxf1 than paired primary tumours. Analysis of gene expression changes downstream of Foxf1 identified increased mTOR signalling as a possible mechanism of metastasis caused by Foxf1 loss, consistent with Dptor identification. We confirmed this mechanism demonstrating that mTOR inhibitor sirolimus reduced lung metastasis burden in xenografts.\n\nConclusionMesenchymal Foxf1 plays a major role in intestinal development. We have shown for the first time, through an unbiased genetic screen, that reduced epithelial Foxf1 results in raised mTOR signalling and metastasis.\n\nAuthorship statementLennard Lee-study concept and design, acquisition of data, analysis, interpretation of data, drafting of the manuscript, statistical analysis and obtained funding. Connor Woolley-acquisition of data, analysis and interpretation of data. Thomas Starkey-acquisition of data, analysis, interpretation of data, drafting of the manuscript. Luke Freeman-Mills-interpretation of data. Andrew Bassett-technical and material support. Fanny Fanchini-technical support. Lai Mun Wang-acquisition of data and study supervision. Annabelle Lewis-study supervision. Roland Arnold-analysis, interpretation of data, statistical analysis. Ian Tomlinson-study supervision and critical revision of the manuscript.\n\nConflict of InterestThe authors whose names are listed above declare that they have no conflict of interest.

cancer biology

Machine learning predicts rapid relapse of triple negative breast cancer

PurposeMetastatic relapse of triple-negative breast cancer (TNBC) within 2 years of diagnosis is associated with particularly aggressive disease and a distinct clinical course relative to TNBCs that relapse beyond 2 years. We hypothesized that rapid relapse TNBCs (rrTNBC; metastatic relapse or death <2 years) reflect unique genomic features relative to late relapse (lrTNBC; >2 years).\n\nPatients and MethodsWe identified 453 primary TNBCs from three publicly-available datasets and characterized each as rrTNBc, lrTNBC, or no relapse (nrTNBC: no relapse/death with at least 5 years follow-up). We compiled primary tumor clinical and multi-omic data, including transcriptome (n=453), copy number alterations (CNAs; n=317), and mutations in 171 cancer-related genes (n=317), then calculated published gene expression and immune signatures.\n\nResultsPatients with rrTNBC were higher stage at diagnosis (Chi-square p<0.0001) while lrTNBC were more likely to be non-basal PAM50 subtype (Chi-square p=0.03). Among 125 expression signatures, five immune signatures were significantly higher in nrTNBCs while lrTNBC were enriched for eight estrogen/luminal signatures (all FDR p<0.05). There was no significant difference in tumor mutation burden or percent genome altered across the groups. Among mutations, only TP53 mutations were significantly more frequent in rrTNBC compared to lrTNBC (Fisher exact FDR p=0.009). To develop an optimal classifier, we used 77 significant clinical and omic features to evaluate six modeling approaches encompassing simple, machine learning, and artificial neural network (ANN). Support vector machine outperformed other models with average receiver-operator characteristic area under curve >0.75.\n\nConclusionsWe provide a new approach to define TNBCs based on timing of relapse. We identify distinct clinical and genomic features that can be incorporated into machine learning models to predict rapid relapse of TNBC.

cancer biology

Interaction between DNA damage response, translation and apoptosome determines cancer susceptibility to TOP2 poisons

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We show that glioblastoma (GBM), the most malignant of all primary brain tumors in adults is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 impaired the induction of pro-apoptotic gene APAF1 following etoposide treatment, and led to resistance to this drug and doxorubicin. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from multiple cancers.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC=\"FIGDIR/small/614024v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (14K):\norg.highwire.dtl.DTLVardef@310f7org.highwire.dtl.DTLVardef@14ed578org.highwire.dtl.DTLVardef@a0d9c0org.highwire.dtl.DTLVardef@37f59a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology

Germline genomic patterns are associated with cancer risk, oncogenic pathways and clinical outcomes

Germline genetic polymorphism is prevalent and inheritable. So far mutations of a handful of genes have been associated with cancer risks. For example, women who harbor BRCA1/2 germline mutations have a 70% of cumulative breast cancer risk; individuals with congenital germline APC mutations have nearly 100% of cumulative colon cancer by the age of fifty. At present, gene-centered cancer predisposition knowledge explains only a small fraction of the inheritable cancer cases. Here we conducted a systematic analysis of the germline genomes of cancer patients (n=9,712) representing 22 common cancer types along with non-cancer individuals (n=16,670), and showed that seven germline genomic patterns, or significantly repeatedly occurring sequential mutation profiles, could be associated with both carcinogenesis processes and cancer clinical outcomes. One of the genomic patterns was significantly enriched in the germline genomes of patients who smoked than in those of non-smoker patients of 13 common cancer types, suggesting that the germline genomic pattern was likely to confer an elevated carcinogenesis sensitivity to tobacco smoke. Several patterns were also associated with somatic mutations of key oncogenic genes and somatic-mutational signatures which are associated with higher genome instability in tumors. Furthermore, subgroups defined by the germline genomic patterns were significantly associated with distinct oncogenic pathways, tumor histological subtypes and prognosis in 12 common cancer types, suggesting that germline genomic patterns enable to inform treatment and clinical outcomes. These results demonstrated that genetic cancer risk and clinical outcomes could be encoded in germline genomes in the form of not only mutated genes, but also specific germline genomic patterns, which provided a novel perspective for further investigation.

cancer biology

Identification of Host Biomarkers of EBV Latency IIb and Latency III

Deciphering the molecular pathogenesis of virally induced cancers is challenging due, in part, to the heterogeneity of both viral and host gene expression. Epstein-Barr Virus (EBV) is a ubiquitous herpesvirus prevalent in B-cell lymphomas of the immune suppressed. EBV infection of primary human B cells leads to their immortalization into lymphoblastoid cell lines (LCLs) serving as a model of these lymphomas. In previous studies, our lab has described a temporal model for immortalization with an initial phase characterized by expression of the Epstein-Barr Nuclear Antigens (EBNAs), high c-Myc activity, and hyper-proliferation in the absence of the Latent Membrane Proteins (LMPs), called latency IIb. This is followed by the long-term outgrowth of LCLs expressing the EBNAs along with the LMPs, particularly the NF{kappa}B-activating LMP1, defining latency III. LCLs, however, express a broad distribution of LMP1 such that a subset of these cells expresses LMP1 at levels seen in latency IIb, making it difficult to distinguish these two latency states. In this study, we performed mRNA-Seq on early EBV-infected latency IIb cells and latency III LCLs sorted by NF{kappa}B activity. We found that latency IIb transcriptomes clustered independently from latency III independent of NF{kappa}B. We identified and validated mRNAs defining these latency states. Indeed, we were able to distinguish latency IIb cells from LCLs expressing low levels of LMP1 using multiplex RNA-FISH targeting EBV EBNA2, LMP1, and human CCR7. This study defines latency IIb as a bona fide latency state independent from latency III and identifies biomarkers for understanding EBV-associated tumor heterogeneity.\n\nIMPORTANCEEBV is a ubiquitous pathogen with >95% of adults harboring a life-long latent infection in memory B cells. In immunocompromised individuals, latent EBV infection can result in lymphoma. The established expression profile of these lymphomas is latency III, which includes expression of all latency genes. However, single cell analysis of EBV latent gene expression in these lymphomas suggests heterogeneity where most cells express the transcription factor, EBNA2, and only a fraction express the membrane protein LMP1. Our work describes an early phase after infection where the EBNAs are expressed without LMP1, called latency IIb. However, LMP1 levels within latency III vary widely making these states hard to discriminate. This may have important implications for therapeutic responses. It is crucial to distinguish these states to understand the molecular pathogenesis of these lymphomas. Ultimately, better tools to understand the heterogeneity of these cancers will support more efficacious therapies in the future.

cancer biology

Mutant p53 Drives Clonal Hematopoiesis through Modulating Epigenetic Pathway

Clonal hematopoiesis of indeterminate potential (CHIP) increases with age and is associated with increased risks of hematological malignancies. While TP53 mutations have been identified in CHIP, the molecular mechanisms by which mutant p53 promotes hematopoietic stem and progenitor cell (HSPC) expansion are largely unknown. We discovered that mutant p53 confers a competitive advantage to HSPCs following transplantation and promotes HSPC expansion after radiation-induced stress. Mechanistically, mutant p53 interacts with EZH2 and enhances its association with the chromatin, thereby increasing the levels of H3K27me3 in genes regulating HSPC self-renewal and differentiation. Further, genetic and pharmacological inhibition of EZH2 decrease the repopulating potential of p53 mutant HSPCs. Thus, we have uncovered an epigenetic mechanism by which mutant p53 drives clonal hematopoiesis. Our work will likely establish epigenetic regulator EZH2 as a novel therapeutic target for preventing CHIP progression and treating hematological malignancies with TP53 mutations.

cancer biology

Tracking the cells of tumor origin in breast organoids by light sheet microscopy

How tumors arise from individual transformed cells within an intact epithelium is a central, yet unanswered question. Here, we developed a new methodology that combines breast tissue organoids, where oncogenes can be switched on in single cells, with light-sheet imaging that allows us to track cell fates using a big-image-data analysis workflow. The power of this integrated approach is illustrated by our finding that small local groups of transformed cells form tumors while isolated transformed cells do not.

cancer biology

Microarray screening of differentially expressed genes after up-regulating miR-205 or down-regulating miR-141 in cervical cancer cells

Cervical cancer is one of the most common gynecological malignancies. However,studies on the expression and molecular mechanism of miR-205 and miR-141 in CC are insufficient recently. Expression profile microarray with 21329 Oligo DNA were used to detect the expression of mRNAs in miR-205 up-regulated or miR-141 down-regulated HeLa and SiHa cells and mRNAs in normal HeLa and SiHa cells. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed to assess the potential pathways of miR-205 in SiHa cell.Compared with normal HeLa cell, there were 38 differentially expressed genes (DEGs) in miR-205 up-regulated HeLa cell. Nine were up-regulation genes and 29 were down-regulation genes. There were 23 DEGs in miR-141 down-regulated HeLa cell. One was up-regulated and 22 were down-regulated. Compared with normal SiHa cell, there were 128 DEGs in miR-205 up-regulated SiHa cell. One hundred and three were up-regulation genes and 25 were down-regulation genes. There were 80 DEGs in miR-141 down-regulated SiHa cell. Forty two were up-regulation genes and 28 were down-regulation genes. For miR-205 up-regulated SiHa cell, GO outcome showed that \"ubiquitin-protein ligase activity\", \"MAP kinase phosphatase activity\", were the most enriched terms (P < 0.05). And in KEGG analysis, \"Cell cycle\" was notably enriched, and Smad4 in this pathway was up-regulated (P < 0.05). Expression profile microarray technology can effectively screen out DEGs in cervical cancer cells after up-regulating miR-205 or down-regulating miR-141. Which may enable us to understand the pathogenesis and lay an important foundation for the prevention and treatment of cervical cancer.

cancer biology

Single-cell imaging reveals unexpected heterogeneity of TERT expression across cancer cell lines

Telomerase is pathologically reactivated in most human cancers, where it maintains chromosomal telomeres and allows immortalization. Because telomerase reverse transcriptase (TERT) is usually the limiting component for telomerase activation, numerous studies have measured TERT mRNA levels in populations of cells or in tissues. However, little is known about TERT expression at the single-cell and single-molecule level. Here we analyzed TERT expression across 10 human cancer lines using single-molecule RNA FISH and made several unexpected findings. First, there was substantial cell-to-cell variation in number of transcription sites and ratio of transcription sites to gene copies. Second, previous classification of lines as having monoallelic or biallelic TERT expression was found to be inadequate for capturing the TERT gene expression patterns. Finally, TERT mRNA had primarily nuclear localization in cancer cells and induced pluripotent stem cells (iPSCs), in stark contrast to the expectation that mature mRNA should be predominantly cytoplasmic. These data reveal unappreciated heterogeneity, complexity, and unconventionality in TERT expression across human cancer cells.

cancer biology

Genetic modification of primary human B cells generates translationally-relevant models of high-grade lymphoma

Sequencing studies of Diffuse Large B Cell Lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, we describe a novel co-culture system that enables the ex vivo expansion and viral transduction of primary human germinal center B cells. The incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC we have identified co-operating oncogenes that promote growth and survival, or even full transformation into synthetically engineered models of DLBCL. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and for the creation of mutation-directed, bespoke lymphoma models.

cancer biology

Genome-wide CRISPR Screens Reveal Genetic Mediators of Cereblon Modulator Toxicity in Primary Effusion Lymphoma

Genome-wide CRISPR/Cas9 screens represent a powerful approach to study mechanisms of drug action and resistance. Cereblon modulating agents (CMs) have recently emerged as candidates for therapeutic intervention in primary effusion lymphoma (PEL), a highly aggressive cancer caused by Kaposis sarcoma-associated herpesvirus. CMs bind to cereblon (CRBN), the substrate receptor of the cullin-RING type E3 ubiquitin ligase CRL4CRBN, and thereby trigger the acquisition and proteasomal degradation of neosubstrates. Downstream mechanisms of CM toxicity are incompletely understood, however. To identify novel CM effectors and mechanisms of CM resistance, we performed positive selection CRISPR screens using three CMs with increasing toxicity in PEL: lenalidomide (LEN), pomalidomide (POM), and CC-122. Results identified several novel modulators of the activity of CRL4CRBN. The number of genes whose inactivation confers resistance decreases with increasing CM efficacy. Only inactivation of CRBN conferred complete resistance to CC-122. Inactivation of the E2 ubiquitin conjugating enzyme UBE2G1 also conferred robust resistance against LEN and POM. Inactivation of additional genes, including the Nedd8-specific protease SENP8, conferred resistance to only LEN. SENP8 inactivation indirectly increased levels of unneddylated CUL4A/B, which limits CRL4CRBN activity in a dominant negative manner. Accordingly, sensitivity of SENP8-inactivated cells to LEN is restored by overexpression of CRBN. In sum, our screens identify several novel players in CRL4CRBN function and define pathways to CM resistance in PEL. These results provide rationale for increasing CM efficacy upon patient relapse from a less efficient CM. Identified genes could finally be developed as biomarkers to predict CM efficacy in PEL and other cancers.\n\nKey PointsO_LIGenome-wide CRISPR/Cas9 screens identify novel mediators of resistance to lenalidomide, pomalidomide and CC-122 in PEL cells.\nC_LIO_LIUBE2G1 and SENP8 are modulators of CRL4CRBN and their inactivation drives resistance to CMs in PEL-derived cell lines.\nC_LI

cancer biology

Bifunctional Small Molecule Ligands of K-Ras Induce Its Association with Immunophilin Proteins

Here we report the design, synthesis and characterization of bifunctional chemical ligands that induce the association of Ras with ubiquitously expressed immunophilin proteins such as FKBP12 and cyclophilin A. We show this approach is applicable to two distinct Ras ligand scaffolds, and that both the identity of the immunophilin ligand and the linker chemistry affect compound efficacy in biochemical and cellular contexts. These ligands bind to Ras in an immunophilin-dependent fashion and mediate the formation of tripartite complexes of Ras, immunophilin and the ligand. The recruitment of cyclophilin A to GTP-bound Ras blocks its interaction with B-Raf in biochemical assays. Our study demonstrates the feasibility of ligand-induced association of Ras with intracellular proteins and suggests it as a promising therapeutic strategy for Rasdriven cancers.

cancer biology

Immune Landscape of Invasive Ductal Carcinoma Tumour Microenvironment Identifies a Prognostic and Immunotherapeutically Relevant Gene Signature

BackgroundInvasive ductal carcinoma (IDC) is a clinically and molecularly distinct disease. Tumour microenvironment (TME) immune phenotypes play crucial roles in predicting clinical outcomes and therapeutic efficacy.\n\nMethodIn this study, we depict the immune landscape of IDC by using transcriptome profiling and clinical characteristics retrieved from The Cancer Genome Atlas (TCGA) data portal. Immune cell infiltration was evaluated via single-sample gene set enrichment (ssGSEA) analysis and systematically correlated with genomic characteristics and clinicopathological features of IDC patients. Furthermore, an immune signature was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm. A random forest algorithm was applied to identify the most important somatic gene mutations associated with the constructed immune signature. A nomogram that integrated clinicopathological features with the immune signature to predict survival probability was constructed by multivariate Cox regression.\n\nResultsThe IDC were clustered into low immune infiltration, intermediate immune infiltration, and high immune infiltration by the immune landscape. The high infiltration group had a favourable survival probability compared with that of the low infiltration group. The low-risk score subtype identified by the immune signature was characterized by T cell-mediated immune activation. Additionally, activation of the interferon- response, interferon-{gamma} response and TNF- signalling via the NF{kappa}B pathway was observed in the low-risk score subtype, which indicated T cell activation and may be responsible for significantly favourable outcomes in IDC patients. A random forest algorithm identified the most important somatic gene mutations associated with the constructed immune signature. Furthermore, a nomogram that integrated clinicopathological features with the immune signature to predict survival probability was constructed, revealing that the immune signature was an independent prognostic biomarker. Finally, the relationship of VEGFA, PD1, PDL-1 and CTLA-4 expression with the immune infiltration landscape and the immune signature was analysed to interpret the responses of IDC patients to immune checkpoint inhibitor therapy.\n\nConclusionTaken together, we performed a comprehensive evaluation of the immune landscape of IDC and constructed an immune signature related to the immune landscape. This analysis of TME immune infiltration patterns has shed light on how IDC respond to immune checkpoint therapy and may guide the development of novel drug combination strategies.

cancer biology

Sex discordance and risk of breast cancer

ObjectiveThe purpose of the study is to perform an analysis of the relationship between sex discordance and risk of breast cancer in female twins in the United States.\n\nMethodsA cross-sectional study of 14,462 female twins was conducted using data from Washington State Twin Registry (WSTR) in the USA. The variables collected included, BMI, age, race and zygosity. This study used Generalized Estimating Equation (GEE) modeling to determine the relationships between twin pairs and variables of interest such as breast cancer and sex concordance. Zygosity, BMI, age and race were used for adjustment. Proband wise concordance was done to ascertain the heritability of breast cancer in twins.\n\nResultsBeing a female-female twin pair increased the odds of breast cancer by 34% (95%CI: 1.18-1.53). After adjusting for zygosity, age, BMI, race, and childbirth, the odds of breast decreased by 31% in female-female twin pairs [AOR (95%CI):0.69 (0.53-0.90)]. The proband wise concordance was higher in monozygotic twins as compared to dizygotic twins. The values for dizygotic and monozygotic twins were 4 and 17 respectively.\n\nConclusionThe findings of the study show that there is a positive association between sex concordance and breast cancer in female twins though other factors such as zygosity, BMI and age can influence breast cancer diagnosis. From our study, the proband wise concordance for monozygotic twins was higher than that of dizygotic twins. Breast cancer is therefore considered heritable.

cancer biology

Inhibition of RNA Polymerase I Transcription Activates Targeted DNA Damage Response and Enhances the Efficacy of PARP Inhibitors in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) accounts for the majority of ovarian cancer and has a dismal prognosis. PARP inhibitors (PARPi) have revolutionized disease management of patients with homologous recombination (HR) DNA repair-deficient HGSOC. However, acquired resistance to PARPi by complex mechanisms including HR restoration and stabilisation of replication forks is a major challenge in the clinic. Here, we demonstrate CX-5461, an inhibitor of RNA polymerase I transcription of ribosomal RNA genes (rDNA), induces replication stress at rDNA leading to activation of DNA damage response and DNA damage involving MRE11-dependent degradation of replication forks. CX-5461 cooperates with PARPi in exacerbating DNA damage and enhances synthetic lethal interactions of PARPi with HR deficiency in HGSOC-patient-derived xenograft (PDX) in vivo. We demonstrate CX-5461 has a different sensitivity spectrum to PARPi and destabilises replication forks irrespective of HR pathway status, overcoming two well-known mechanisms of resistance to PARPi. Importantly, CX-5461 exhibits single agent efficacy in PARPi-resistant HGSOC-PDX. Further, we identify CX-5461-sensitivity gene expression signatures in primary and relapsed HGSOC. Therefore, CX-5461 is a promising therapy alone and in combination therapy with PARPi in HR-deficient HGSOC. CX-5461 is also an exciting treatment option for patients with relapsed HGSOC tumors that have poor clinical outcome.

cancer biology