Nucleolar RNA polymerase II drives ribosome biogenesis.

Proteins are manufactured by ribosomes-macromolecular complexes of protein and RNA molecules that are assembled within major nuclear compartments called nucleoli1,2. Existing models suggest that RNA polymerases I and III (Pol I and Pol III) are the only enzymes that directly mediate the expression of the ribosomal RNA (rRNA) components of ribosomes. Here we show, however, that RNA polymerase II (Pol II) inside human nucleoli operates near genes encoding rRNAs to drive their expression. Pol II, assisted by the neurodegeneration-associated enzyme senataxin, generates a shield comprising triplex nucleic acid structures known as R-loops at intergenic spacers flanking nucleolar rRNA genes. The shield prevents Pol I from producing sense intergenic noncoding RNAs (sincRNAs) that can disrupt nucleolar organization and rRNA expression. These disruptive sincRNAs can be unleashed by Pol II inhibition, senataxin loss, Ewing sarcoma or locus-associated R-loop repression through an experimental system involving the proteins RNaseH1, eGFP and dCas9 (which we refer to as 'red laser'). We reveal a nucleolar Pol-II-dependent mechanism that drives ribosome biogenesis, identify disease-associated disruption of nucleoli by noncoding RNAs, and establish locus-targeted R-loop modulation. Our findings revise theories of labour division between the major RNA polymerases, and identify nucleolar Pol II as a major factor in protein synthesis and nuclear organization, with potential implications for health and disease.

Exploration and analysis of R-loop mapping data with RLBase.

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. In 2012, Ginno et al. introduced the first R-loop mapping method. Since that time, dozens of R-loop mapping studies have been conducted, yielding hundreds of publicly available datasets. Current R-loop databases provide only limited access to these data. Moreover, no web tools for analyzing user-supplied R-loop datasets have yet been described. In our recent work, we reprocessed 810 R-loop mapping samples, building the largest R-loop data resource to date. We also defined R-loop consensus regions and developed a framework for R-loop data analysis. Now, we introduce RLBase, a user-friendly database that provides the capability to (i) explore hundreds of public R-loop mapping datasets, (ii) explore R-loop consensus regions, (iii) analyze user-supplied data and (iv) download standardized and reprocessed datasets. RLBase is directly accessible via the following URL: https://gccri.bishop-lab.uthscsa.edu/shiny/rlbase/.

TATDN2 resolution of R-loops is required for survival of BRCA1-mutant cancer cells.

BRCA1-deficient cells have increased IRE1 RNase, which degrades multiple microRNAs. Reconstituting expression of one of these, miR-4638-5p, resulted in synthetic lethality in BRCA1-deficient cancer cells. We found that miR-4638-5p represses expression of TATDN2, a poorly characterized member of the TATD nuclease family. We discovered that human TATDN2 has RNA 3' exonuclease and endonuclease activity on double-stranded hairpin RNA structures. Given the cleavage of hairpin RNA by TATDN2, and that BRCA1-deficient cells have difficulty resolving R-loops, we tested whether TATDN2 could resolve R-loops. Using in vitro biochemical reconstitution assays, we found TATDN2 bound to R-loops and degraded the RNA strand but not DNA of multiple forms of R-loops in vitro in a Mg2+-dependent manner. Mutations in amino acids E593 and E705 predicted by Alphafold-2 to chelate an essential Mg2+ cation completely abrogated this R-loop resolution activity. Depleting TATDN2 increased cellular R-loops, DNA damage and chromosomal instability. Loss of TATDN2 resulted in poor replication fork progression in the presence of increased R-loops. Significantly, we found that TATDN2 is essential for survival of BRCA1-deficient cancer cells, but much less so for cognate BRCA1-repleted cancer cells. Thus, we propose that TATDN2 is a novel target for therapy of BRCA1-deficient cancers.

Author Correction: EWS-FLI1 increases transcription to cause R-loops and block BRCA1 repair in Ewing sarcoma.

In this Letter, the sentence beginning "This work was funded…." in the Acknowledgements should have read "CPRIT (RP140105) to J.C.R." rather than "CPRIT (RP150445) to J.C.R." This error has been corrected online.

EWS-FLI1 increases transcription to cause R-loops and block BRCA1 repair in Ewing sarcoma.

Ewing sarcoma is an aggressive paediatric cancer of the bone and soft tissue. It results from a chromosomal translocation, predominantly t(11;22)(q24:q12), that fuses the N-terminal transactivation domain of the constitutively expressed EWSR1 protein with the C-terminal DNA binding domain of the rarely expressed FLI1 protein. Ewing sarcoma is highly sensitive to genotoxic agents such as etoposide, but the underlying molecular basis of this sensitivity is unclear. Here we show that Ewing sarcoma cells display alterations in regulation of damage-induced transcription, accumulation of R-loops and increased replication stress. In addition, homologous recombination is impaired in Ewing sarcoma owing to an enriched interaction between BRCA1 and the elongating transcription machinery. Finally, we uncover a role for EWSR1 in the transcriptional response to damage, suppressing R-loops and promoting homologous recombination. Our findings improve the current understanding of EWSR1 function, elucidate the mechanistic basis of the sensitivity of Ewing sarcoma to chemotherapy (including PARP1 inhibitors) and highlight a class of BRCA-deficient-like tumours.

Quality-controlled R-loop meta-analysis reveals the characteristics of R-loop consensus regions.

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA. While the pathological consequences of R-loops have been well-studied to date, the locations, classes, and dynamics of physiological R-loops remain poorly understood. R-loop mapping studies provide insight into R-loop dynamics, but their findings are challenging to generalize. This is due to the narrow biological scope of individual studies, the limitations of each mapping modality, and, in some cases, poor data quality. In this study, we reprocessed 810 R-loop mapping datasets from a wide array of biological conditions and mapping modalities. From this data resource, we developed an accurate R-loop data quality control method, and we reveal the extent of poor-quality data within previously published studies. We then identified a set of high-confidence R-loop mapping samples and used them to define consensus R-loop sites called 'R-loop regions' (RL regions). In the process, we identified a stark divergence between RL regions detected by S9.6 and dRNH-based mapping methods, particularly with respect to R-loop size, location, and colocalization with RNA binding factors. Taken together, this work provides a much-needed method to assess R-loop data quality and offers novel context regarding the differences between dRNH- and S9.6-based R-loop mapping approaches.

Development and characterization of a mass cytometry panel for detecting the effect of acute doxorubicin exposure on murine cardiac nonmyocytes.

Childhood cancer survivors (CCSs) face lifelong side effects related to their treatment with chemotherapy. Anthracycline agents, such as doxorubicin (DOX), are important in the treatment of childhood cancers but are associated with cardiotoxicity. Cardiac toxicities represent a significant source of chronic disability that cancer survivors face; despite this, the chronic cardiotoxicity phenotype and how it relates to acute toxicity remains poorly defined. To address this critical knowledge gap, we studied the acute effect of DOX on murine cardiac nonmyocytes in vivo. Determination of the acute cellular effects of DOX on nonmyocytes, a cell pool with finite replicative capacity, provides a basis for understanding the pathogenesis of the chronic heart disease that CCSs face. To investigate the acute cellular effects of DOX, we present single-cell RNA sequencing (scRNAseq) data from homeostatic cardiac nonmyocytes and compare it with preexisting datasets, as well as a novel CyTOF datasets. SCANPY, a python-based single-cell analysis, was used to assess the heterogeneity of cells detected in scRNAseq and CyTOF. To further assist in CyTOF data annotation, joint analyses of scRNAseq and CyTOF data using an artificial neural network known as sparse autoencoder for clustering, imputation, and embedding (SAUCIE) are performed. Lastly, the panel is tested on a mouse model of acute DOX exposure at two time points (24 and 72 h) after the last dose of doxorubicin and examined with joint clustering. In sum, we report the first ever CyTOF study of cardiac nonmyocytes and characterize the effect of acute DOX exposure with scRNAseq and CyTOF.NEW & NOTEWORTHY We describe the first mass cytometry studies of murine cardiac nonmyocytes. The mass cytometry panel is compared with single-cell RNA sequencing data. Homeostatic cardiac nonmyocytes are characterized by mass cytometry to identify and quantify four major cell populations: endothelial cells, fibroblasts, leukocytes, and pericytes. The single-cell acute nonmyocyte response to doxorubicin is studied at 24 and 72 h after doxorubicin exposure given daily for 5 days at a dose of 4 mg/kg/day.

Cohesin SA1 and SA2 are RNA binding proteins that localize to RNA containing regions on DNA.

Cohesin SA1 (STAG1) and SA2 (STAG2) are key components of the cohesin complex. Previous studies have highlighted the unique contributions by SA1 and SA2 to 3D chromatin organization, DNA replication fork progression, and DNA double-strand break (DSB) repair. Recently, we discovered that cohesin SA1 and SA2 are DNA binding proteins. Given the recently discovered link between SA2 and RNA-mediated biological pathways, we investigated whether or not SA1 and SA2 directly bind to RNA using a combination of bulk biochemical assays and single-molecule techniques, including atomic force microscopy (AFM) and the DNA tightrope assay. We discovered that both SA1 and SA2 bind to various RNA containing substrates, including ssRNA, dsRNA, RNA:DNA hybrids, and R-loops. Importantly, both SA1 and SA2 localize to regions on dsDNA that contain RNA. We directly compared the SA1/SA2 binding and R-loops sites extracted from Chromatin Immunoprecipitation sequencing (ChIP-seq) and DNA-RNA Immunoprecipitation sequencing (DRIP-Seq) data sets, respectively. This analysis revealed that SA1 and SA2 binding sites overlap significantly with R-loops. The majority of R-loop-localized SA1 and SA2 are also sites where other subunits of the cohesin complex bind. These results provide a new direction for future investigation of the diverse biological functions of SA1 and SA2.

Correlation AnalyzeR: functional predictions from gene co-expression correlations.

BACKGROUND: Co-expression correlations provide the ability to predict gene functionality within specific biological contexts, such as different tissue and disease conditions. However, current gene co-expression databases generally do not consider biological context. In addition, these tools often implement a limited range of unsophisticated analysis approaches, diminishing their utility for exploring gene functionality and gene relationships. Furthermore, they typically do not provide the summary visualizations necessary to communicate these results, posing a significant barrier to their utilization by biologists without computational skills. RESULTS: We present Correlation AnalyzeR, a user-friendly web interface for exploring co-expression correlations and predicting gene functions, gene-gene relationships, and gene set topology. Correlation AnalyzeR provides flexible access to its database of tissue and disease-specific (cancer vs normal) genome-wide co-expression correlations, and it also implements a suite of sophisticated computational tools for generating functional predictions with user-friendly visualizations. In the usage example provided here, we explore the role of BRCA1-NRF2 interplay in the context of bone cancer, demonstrating how Correlation AnalyzeR can be effectively implemented to generate and support novel hypotheses. CONCLUSIONS: Correlation AnalyzeR facilitates the exploration of poorly characterized genes and gene relationships to reveal novel biological insights. The database and all analysis methods can be accessed as a web application at https://gccri.bishop-lab.uthscsa.edu/correlation-analyzer/ and as a standalone R package at https://github.com/Bishop-Laboratory/correlationAnalyzeR .

Phase 1/2 trial of talazoparib in combination with temozolomide in children and adolescents with refractory/recurrent solid tumors including Ewing sarcoma: A Children's Oncology Group Phase 1 Consortium study (ADVL1411).

PURPOSE: We conducted a phase 1/2 trial of the poly(ADP-ribose) polymerase 1/2 inhibitor talazoparib in combination with low-dose temozolomide (TMZ) to determine the dose-limiting toxicities (DLTs), recommended phase 2 dose (RP2D), and pharmacokinetics of this combination in children with recurrent/refractory solid tumors; and to explore clinical activity in Ewing sarcoma (EWS) (NCT02116777). METHODS: Talazoparib (400-600 µg/m2 /dose, maximum daily dose 800-1000 µg) was administered q.d. or b.i.d. orally on day 1 followed by q.d. dosing concomitant with q.d. dosing of oral TMZ (20-55 mg/m2 /day) on days 2 to 6, every 28 days. RESULTS: Forty patients, aged 4 to 25 years, were enrolled. Talazoparib was increased to 600 µg/m2 /dose b.i.d. on day 1, and q.d. thereafter, with 20 mg/m2 /day of TMZ, without DLTs. TMZ was subsequently increased, during which dose-limiting neutropenia and thrombocytopenia occurred in two of three subjects at 55 mg/m2 /day, two of six subjects at 40 mg/m2 /day, and one of six subjects at 30 mg/m2 /day. During dose-finding, two of five EWS and four of 25 non-EWS subjects experienced prolonged stable disease (SD), and one subject with malignant glioma experienced a partial response. In phase 2, 0 of 10 EWS subjects experienced an objective response; two experienced prolonged SD. CONCLUSIONS: Talazoparib and low-dose TMZ are tolerated in children with recurrent/refractory solid tumors. Reversible neutropenia and thrombocytopenia were dose limiting. The RP2D is talazoparib 600 µg/m2 b.i.d. on day 1 followed by 600 µg/m2 q.d. on days 2 to 6 (daily maximum 1000 µg) in combination with temozolomide 30 mg/m2 /day on days 2 to 6. Antitumor activity was not observed in EWS, and limited antitumor activity was observed in central nervous system tumors.

Cohesin SA2 is a sequence-independent DNA-binding protein that recognizes DNA replication and repair intermediates.

Proper chromosome alignment and segregation during mitosis depend on cohesion between sister chromatids, mediated by the cohesin protein complex, which also plays crucial roles in diverse genome maintenance pathways. Current models attribute DNA binding by cohesin to entrapment of dsDNA by the cohesin ring subunits (SMC1, SMC3, and RAD21 in humans). However, the biophysical properties and activities of the fourth core cohesin subunit SA2 (STAG2) are largely unknown. Here, using single-molecule atomic force and fluorescence microscopy imaging as well as fluorescence anisotropy measurements, we established that SA2 binds to both dsDNA and ssDNA, albeit with a higher binding affinity for ssDNA. We observed that SA2 can switch between the 1D diffusing (search) mode on dsDNA and stable binding (recognition) mode at ssDNA gaps. Although SA2 does not specifically bind to centromeric or telomeric sequences, it does recognize DNA structures often associated with DNA replication and double-strand break repair, such as a double-stranded end, single-stranded overhang, flap, fork, and ssDNA gap. SA2 loss leads to a defect in homologous recombination-mediated DNA double-strand break repair. These results suggest that SA2 functions at intermediate DNA structures during DNA transactions in genome maintenance pathways. These findings have important implications for understanding the function of cohesin in these pathways.

Musashi1 Impacts Radio-Resistance in Glioblastoma by Controlling DNA-Protein Kinase Catalytic Subunit.

The conserved RNA-binding protein Musashi1 (MSI1) has been characterized as a stem cell marker, controlling the balance between self-renewal and differentiation and as a key oncogenic factor in numerous solid tumors, including glioblastoma. To explore the potential use of MSI1 targeting in therapy, we studied MSI1 in the context of radiation sensitivity. Knockdown of MSI1 led to a decrease in cell survival and an increase in DNA damage compared to control in cells treated with ionizing radiation. We subsequently examined mechanisms of double-strand break repair and found that loss of MSI1 reduces the frequency of nonhomologous end-joining. This phenomenon could be attributed to the decreased expression of DNA-protein kinase catalytic subunit, which we have previously identified as a target of MSI1. Collectively, our results suggest a role for MSI1 in double-strand break repair and that its inhibition may enhance the effect of radiotherapy.

Potential relationship between inadequate response to DNA damage and development of myelodysplastic syndrome.

Hematopoietic stem cells (HSCs) are responsible for the continuous regeneration of all types of blood cells, including themselves. To ensure the functional and genomic integrity of blood tissue, a network of regulatory pathways tightly controls the proliferative status of HSCs. Nevertheless, normal HSC aging is associated with a noticeable decline in regenerative potential and possible changes in other functions. Myelodysplastic syndrome (MDS) is an age-associated hematopoietic malignancy, characterized by abnormal blood cell maturation and a high propensity for leukemic transformation. It is furthermore thought to originate in a HSC and to be associated with the accrual of multiple genetic and epigenetic aberrations. This raises the question whether MDS is, in part, related to an inability to adequately cope with DNA damage. Here we discuss the various components of the cellular response to DNA damage. For each component, we evaluate related studies that may shed light on a potential relationship between MDS development and aberrant DNA damage response/repair.

Approaches for Mapping and Analysis of R-loops.

R-loops are nucleic acid structures composed of a DNA:RNA hybrid with a displaced non-template single-stranded DNA. Current approaches to identify and map R-loop formation across the genome employ either an antibody targeted against R-loops (S9.6) or a catalytically inactivated form of RNase H1 (dRNH1), a nuclease that can bind and resolve DNA:RNA hybrids via RNA exonuclease activity. This overview article outlines several ways to map R-loops using either methodology, explaining the differences and similarities among the approaches. Bioinformatic analysis of R-loops involves several layers of quality control and processing before visualizing the data. This article provides resources and tools that can be used to accurately process R-loop mapping data and explains the advantages and disadvantages of the resources as compared to one another. © 2024 Wiley Periodicals LLC.

RNA helicase DDX3 regulates RAD51 localization and DNA damage repair in Ewing sarcoma.

We previously demonstrated that RNA helicase DDX3X (DDX3) can be a therapeutic target in Ewing sarcoma (EWS), but its role in EWS biology remains unclear. The present work demonstrates that DDX3 plays a unique role in DNA damage repair (DDR). We show that DDX3 interacts with several proteins involved in homologous recombination, including RAD51, RECQL1, RPA32, and XRCC2. In particular, DDX3 colocalizes with RAD51 and RNA:DNA hybrid structures in the cytoplasm of EWS cells. Inhibition of DDX3 RNA helicase activity increases cytoplasmic RNA:DNA hybrids, sequestering RAD51 in the cytoplasm, which impairs nuclear translocation of RAD51 to sites of double-stranded DNA breaks, thus increasing sensitivity of EWS to radiation treatment, both in vitro and in vivo. This discovery lays the foundation for exploring new therapeutic approaches directed at manipulating DDR protein localization in solid tumors.

RNA Helicase DDX3 Regulates RAD51 Localization and DNA Damage Repair in Ewing Sarcoma.

We previously demonstrated that RNA helicase DDX3X (DDX3) can be a therapeutic target in Ewing sarcoma (EWS), but its role in EWS biology remains unclear. The present work demonstrates that DDX3 plays a unique role in DNA damage repair (DDR). We show that DDX3 interacts with several proteins involved in homologous recombination, including RAD51, RECQL1, RPA32, and XRCC2. In particular, DDX3 colocalizes with RAD51 and RNA:DNA hybrid structures in the cytoplasm of EWS cells. Inhibition of DDX3 RNA helicase activity increases cytoplasmic RNA:DNA hybrids, sequestering RAD51 in the cytoplasm, which impairs nuclear translocation of RAD51 to sites of double-stranded DNA breaks thus increasing sensitivity of EWS to radiation treatment, both in vitro and in vivo. This discovery lays the foundation for exploring new therapeutic approaches directed at manipulating DDR protein localization in solid tumors.

Epigenetic Control of Translation Checkpoint and Tumor Progression via RUVBL1-EEF1A1 Axis.

Epigenetic dysregulation is reported in multiple cancers including Ewing sarcoma (EwS). However, the epigenetic networks underlying the maintenance of oncogenic signaling and therapeutic response remain unclear. Using a series of epigenetics- and complex-focused CRISPR screens, RUVBL1, the ATPase component of NuA4 histone acetyltransferase complex, is identified to be essential for EwS tumor progression. Suppression of RUVBL1 leads to attenuated tumor growth, loss of histone H4 acetylation, and ablated MYC signaling. Mechanistically, RUVBL1 controls MYC chromatin binding and modulates the MYC-driven EEF1A1 expression and thus protein synthesis. High-density CRISPR gene body scan pinpoints the critical MYC interacting residue in RUVBL1. Finally, this study reveals the synergism between RUVBL1 suppression and pharmacological inhibition of MYC in EwS xenografts and patient-derived samples. These results indicate that the dynamic interplay between chromatin remodelers, oncogenic transcription factors, and protein translation machinery can provide novel opportunities for combination cancer therapy.

Mutant p53 disrupts role of ShcA protein in balancing Smad protein-dependent and -independent signaling activity of transforming growth factor-ß (TGF-ß).

Biomarkers are lacking for identifying the switch of transforming growth factor-ß (TGF-ß) from tumor-suppressing to tumor-promoting. Mutated p53 (mp53) has been suggested to switch TGF-ß to a tumor promoter. However, we found that mp53 does not always promote the oncogenic role of TGF-ß. Here, we show that endogenous mp53 knockdown enhanced cell migration and phosphorylation of ERK in DU145 prostate cancer cells. Furthermore, ectopic expression of mp53 in p53-null PC-3 prostate cancer cells enhanced Smad-dependent signaling but inhibited TGF-ß-induced cell migration by down-regulating activated ERK. Reactivation of ERK by the expression of its activator, MEK-1, restored TGF-ß-induced cell migration. Because TGF-ß is known to activate the MAPK/ERK pathway through direct phosphorylation of the adaptor protein ShcA and MAPK/ERK signaling is pivotal to tumor progression, we investigated whether ShcA contributed to mp53-induced ERK inhibition and the conversion of the role of TGF-ß during carcinogenesis. We found that mp53 expression led to a decrease of phosphorylated p52ShcA/ERK levels and an increase of phosphorylated Smad levels in a panel of mp53-expressing cancer cell lines and in mammary glands and tumors from mp53 knock-in mice. By manipulating ShcA levels to regulate ERK and Smad signaling in human untransformed and cancer cell lines, we showed that the role of TGF-ß in regulating anchorage-dependent and -independent growth and migration can be shifted between growth suppression and migration promotion. Thus, our results for the first time suggest that mp53 disrupts the role of ShcA in balancing the Smad-dependent and -independent signaling activity of TGF-ß and that ShcA/ERK signaling is a major pathway regulating the tumor-promoting activity of TGF-ß.

Pathway Distiller - multisource biological pathway consolidation.

BACKGROUND: One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. METHODS: After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. RESULTS: We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. CONCLUSIONS: By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.

Reducing confounding and suppression effects in TCGA data: an integrated analysis of chemotherapy response in ovarian cancer.

BACKGROUND: Despite initial response in adjuvant chemotherapy, ovarian cancer patients treated with the combination of paclitaxel and carboplatin frequently suffer from recurrence after few cycles of treatment, and the underlying mechanisms causing the chemoresistance remain unclear. Recently, The Cancer Genome Atlas (TCGA) research network concluded an ovarian cancer study and released the dataset to the public. The TCGA dataset possesses large sample size, comprehensive molecular profiles, and clinical outcome information; however, because of the unknown molecular subtypes in ovarian cancer and the great diversity of adjuvant treatments TCGA patients went through, studying chemotherapeutic response using the TCGA data is difficult. Additionally, factors such as sample batches, patient ages, and tumor stages further confound or suppress the identification of relevant genes, and thus the biological functions and disease mechanisms. RESULTS: To address these issues, herein we propose an analysis procedure designed to reduce suppression effect by focusing on a specific chemotherapeutic treatment, and to remove confounding effects such as batch effect, patient's age, and tumor stages. The proposed procedure starts with a batch effect adjustment, followed by a rigorous sample selection process. Then, the gene expression, copy number, and methylation profiles from the TCGA ovarian cancer dataset are analyzed using a semi-supervised clustering method combined with a novel scoring function. As a result, two molecular classifications, one with poor copy number profiles and one with poor methylation profiles, enriched with unfavorable scores are identified. Compared with the samples enriched with favorable scores, these two classifications exhibit poor progression-free survival (PFS) and might be associated with poor chemotherapy response specifically to the combination of paclitaxel and carboplatin. Significant genes and biological processes are detected subsequently using classical statistical approaches and enrichment analysis. CONCLUSIONS: The proposed procedure for the reduction of confounding and suppression effects and the semi-supervised clustering method are essential steps to identify genes associated with the chemotherapeutic response.