bioRxiv preprint doi: https://doi.org/10.1101/863852; this version posted December 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. 1 RESEARCH 1 2 2 3 3 4Integrated analyses of early responses to 4 5 5 6radiation in glioblastoma identify new alterations 6 7 7 8in RNA processing and candidate target genes to 8 9 9 10 10 11improve treatment outcomes 11 12 12 Saket Choudhary1y, Suzanne C. Burns2y^, Hoda Mirsafian1, Wenzheng Li1, Dat T. Vo4, Mei Qiao2, 13 13 Andrew D. Smith1 and Luiz O. Penalva2,3* 14 14 15 15 16 Abstract 16 17 Background: High-dose radiation is the main component of glioblastoma therapy. Unfortunately, 17 18 radio-resistance is a common problem and a major contributor to tumor relapse. Understanding the molecular 18 19 mechanisms driving response to radiation is critical for identifying regulatory routes that could be targeted to 19 20 improve treatment response. 20 21 21 Methods: We conducted an integrated analysis in the U251 and U343 glioblastoma cell lines to map early 22 22 alterations in the expression of genes at three levels: transcription, splicing, and translation in response to 23 23 ionizing radiation. 24 24 Results: Changes at the transcriptional level were the most prevalent response. Downregulated genes are 25 25 strongly associated with cell cycle and DNA replication and linked to a coordinated module of expression. 26 26 Alterations in this group are likely driven by decreased expression of the transcription factor FOXM1 and 27 27 members of the E2F family. Genes involved in RNA regulatory mechanisms were affected at the mRNA, 28 28 splicing, and translation levels, highlighting their importance in radiation-response. We identified a number of 29 29 oncogenic factors, with an increased expression upon radiation exposure, including BCL6, RRM2B, IDO1, 30 30 FTH1, APIP, and LRIG2 and lncRNAs NEAT1 and FTX. Several of these targets have been previously 31 31 implicated in radio-resistance. Therefore, antagonizing their effects post-radiation could increase therapeutic 32 32 efficacy. 33 33 34 Conclusions: Our integrated analysis provides a comprehensive view of early response to radiation in 34 35 glioblastoma. We identify new biological processes involved in altered expression of various oncogenic factors 35 36 and suggest new target options to increase radiation sensitivity and prevent relapse. 36 37 Keywords: glioblastoma; transcriptomics; radio-response; splicing; translation 37 38 38 39 39 bioRxiv preprint doi: https://doi.org/10.1101/863852; this version posted December 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Choudhary et al. Page 2 of 17 1Background pathways that could increase radio-sensitivity. A few1 2Glioblastoma is the most common intracranial malig- genomic studies [14, 15, 16] have explored this ques-2 3nant brain tumor with an aggressive clinical course. tion, but these analyses were restricted to describing3 4Standard of care entails maximally safe resection fol- changes in transcription. 4 5lowed by radiotherapy with concomitant and adjuvant 5 Gene expression is regulated at multiple levels, and 6temozolomide. Nonetheless, the median overall sur- 6 RNA-mediated mechanisms such as splicing and trans- 7vival remains approximately 16 months [1, 2], and the 7 lation are particularly relevant in cancer biology. A 8recent addition of tumor-treating fields to the stan- 8 growing number of inhibitors against regulators of 9dard of care has only increased median overall survival 9 splicing and translation are being identified [17]. Splic- 10to 20.5 months [1]. Recurrence occurs in part because 10 ing alterations are a common feature across cancer 11glioblastoma uses sophisticated cellular mechanisms 11 types and affect all hallmarks of cancer [18]. Numer- 12to repair DNA damage from double-stranded breaks 12 ous splicing regulators display altered expression in 13caused by ionizing radiation, specifically homologous 13 glioblastoma (e.g. PTBP1, hnRNPH, and RBM14) 14recombination and non-homologous end-joining. Thus, 14 and function as oncogenic factors [19]. Importantly, 15the repair machinery confers a mechanism for resis- 15 a genome-wide study using patient-derived models re- 16tance to radiation therapy. Ionizing radiation can also 16 vealed that transformation-specific depended on RNA 17cause base damage and single-strand breaks, which 17 splicing machinery. The SF3b-complex protein PHF5A 18are repaired by base excision and single-strand break 18 was required for glioblastoma cells to survive, but 19repair mechanisms, respectively [3]. A comprehensive 19 not neural stem cells (NSCs). Moreover, genome-wide 20analysis of molecular mechanisms driving resistance to 20 splicing alterations after PHF5A loss appear only 21chemotherapy and radiation is required to surpass ma- 21 in glioblastoma cells [20]. Translation regulation also 22jor barriers and advance treatments for glioblastoma. 22 plays a critical role in glioblastoma development. Many 23 The Cancer Genome Atlas (TCGA) was instrumen- 23 translation regulators such as elF4E, eEF2, Musashi1, 24tal in improving the classification and identification 24 HuR, IGF2BP3, and CPEB1 promote oncogenic acti- 25of tumor drivers [4], but its datasets provide limited 25 vation in glioblastoma, and pathways linked to trans- 26opportunities to investigate radiation response. Thus, 26 lation regulation (e.g., mTOR) promote cancer pheno- 27studies using cell and murine models are still the best 27 types [21]. 28alternatives to evaluate radiation response at the ge- 28 29nomic level. The list of biomarkers associated with To elucidate expression responses to radiation, we29 30radiation resistance in glioblastoma is still relatively conducted an integrated study in U251 and U34330 31small. Among the most relevant are FOXM1 [5, 6], glioblastoma cell lines covering transcription (mRNAs31 32STAT3 [6], L1CAM [7], NOTCH1 [8], RAD51 [9], and lncRNAs), splicing, and translation. We deter-32 33EZH2 [10], CHK1/ATR [11], COX-2 [12], and XIAP mined that the downregulation of FOXM1 and mem-33 34[13]. Dissecting how gene expression is altered by ion- bers of the E2F family are likely the major drivers34 35izing radiation is critical to identify possible genes and of observed alterations in cell cycle and DNA replica-35 36*Correspondence: [email protected] tion genes upon radiation exposure. Genes involved in36 2 37 Greheey Children's Research Institute, University of Texas Health Science RNA regulatory mechanisms were particularly affected37 Center at San Antonio, 78229 San Antonio USA 38 at the transcription, splicing, and translation levels. In38 Full list of author information is available at the end of the article 39yEqual contributor^In memoriam addition, we identified several oncogenic factors and39 bioRxiv preprint doi: https://doi.org/10.1101/863852; this version posted December 5, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Choudhary et al. Page 3 of 17 1genes associated with poor survival in glioblastoma Our strategy to identify the most relevant alterations1 2that displayed increased expression upon radiation ex- in expression with maximal statistical power was to2 3posure. Importantly, many have been implicated in combine all samples and use a design matrix with cell3 4radio-resistance, and therefore, their inhibition in com- type defined as a covariate with time points (Figure4 5bination with radiation could increase therapy efficacy. S1). 5 6 6 7Methods Sequence data pre-processing and mapping 7 8Cell culture and radiation treatment The quality of raw sequences reads from RNA-Seq and8 9 9 U251 and U343 cells were obtained from the Uni- Ribo-Seq datasets were assessed using FastQC [22]. 10 10 versity of Uppsala (Sweden) and maintained in Dul- Adaptor sequences and low-quality score (phred qual- 11 11 becco's Modified Eagle Medium (DMEM, Hyclone) ity score < 5) bases were trimmed from RNA-Seq and 12 12 supplemented with 10% fetal bovine serum, 1% Peni- Ribo-Seq datasets with TrimGalore (v0.4.3) [23]. The 13 ◦ 13 cillin/Streptomycin at 37 C in 5% CO2-humidified in- trimmed reads were then aligned to the human ref- 14 14 cubators and were sub-cultured twice a week. Cells erence genome sequence (Ensembl GRCh38.p7) using 15 15 were plated after appropriate dilution, and ionizing ra- STAR aligner (v.2.5.2b) [24] with GENCODE [25] v25 16 16 diation treatment was performed on the next day at a as a guided reference annotation, allowing a mismatch 17 17 dose of 5 Gray (Gy). A cabinet X-ray system (CP-160 of at most two positions. All the reads mapping to 18 18 Cabinet X-Radiator; Faxitron X-Ray Corp., Tucson, rRNA and tRNA sequences were filtered out before 19 19 AZ) was used. After exposure to ionizing radiation, downstream analysis. Most reads in the Ribo-seq sam- 20 20 cells were cultured for 1 and 24 hours (hrs). ples mapped to the coding domain sequence (CDS). 21 The distribution of fragment lengths for ribosome foot-21 22RNA preparation, RNA-seq and Ribosome Profiling prints was enriched in the 28-30 nucleotides range, as22 23(Ribo-seq) expected (Figure S2). The ribosome density profiles23 24RNA was purified using a GeneJet RNA kit from exhibit high periodicity as within the CDS, as expected24 25Thermo Scientific. The TruSeq Ribo Profile (Mam- since ribosomes traverse three nucleotides at a time25 26malian) kit from Illumina was used to prepare ma- (Figure S3). The periodicity analysis was performed26 27terial for ribosome profiling (Ribo-seq).