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Long Non-coding RNA and mRNA Co-expression Network Reveals Novel Players in Pleomorphic Xanthoastrocytoma

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Abstract

Histological interpretation of the rare pleomorphic xanthoastrocytoma (PXA) has been the holy grail for treatment options. However, no stand-alone clinical interventions have been developed owing to the lack of gene expression profiling data in PXA/APXA patients. We first time report the comprehensive analyses of the coding as well as long non-coding RNA (lncRNA) signatures of PXA/APXA patients. Several genes such as IGFBP2, NF1, FOS, ERBB2, and lncRNAs such as NEAT1, HOTAIRM1, and GAS5 known to play crucial roles in glioma patients were also deregulated in PXA patients suggesting the commonality in the molecular signatures. PPI network, co-expression, and lncRNA-mRNA interaction studies unraveled hub genes (such as ERBB2, FOS, RPA1) and networks that may play a critical role in PXA biology. The most enriched pathways based on gene profiles were related to TLR, chemokine, MAPK, Rb, and PI3K-Akt signaling pathways. The lncRNA targets were enriched in glucuronidation, adipogenesis, TGF-beta signaling, EGF/EGFR signaling, and cell cycle pathways. Interestingly, several mRNAs like PARVG, and ABI2 were found to be targeted by multiple lncRNAs suggesting a tight control of their levels. Some of the most prominent lncRNA-mRNA pairs were LOC728730: MRPL9, XLOC_l2_011987: ASIC2, lnc-C1QTNF5-1: RNF26. Notably, several lncRNAs such as lnc-CETP-1, lnc-XRCC3-1, lnc-RPL31-1, lnc-USP13-1, and MAPKAPK5-AS1, and genes such as RPA1, NTRK3, and CNRP1 showed strong correlation to the progression-free survival of PXA patients suggesting their potential as novel biomarkers. Overall, the findings of this study may facilitate the development of a new realm of RNA biology in PXA that may have clinical significance in the future.

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Data Availability

The datasets analyzed during the current study are available in the GEO repository [GSE168904].

Code Availability

Not applicable.

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Funding

We are thankful for financial support for funds and support received from various funding agencies. R. K. is thankful to IIT Delhi internal grant. C. S. gratefully acknowledges the funding support received from the J C Bose Fellowship of the Department of Science and Technology (DST). I. D. is thankful to the Department of Biotechnology (DBT) for the Junior Research Fellowship. R. G. is thankful to IIT Delhi for Senior Research Fellowship. J. S. is thankful to the Indian Council of Medical Research (ICMR) for the Senior Research Fellowship.

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Author notes

  1. Rahul Gupta and Iman Dandapath are equal first authors.

Authors and Affiliations

  1. Neuropathology Laboratory, All India Institute of Medical Sciences, Neurosciences Centre, New Delhi, 110029, India

    Iman Dandapath, Jyotsna Singh, Nidhi Shukla, Prerana Jha, M. C. Sharma & Vaishali Suri

  2. Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, New Delhi, 110016, India

    Rahul Gupta & Ritu Kulshreshtha

  3. All India Institute of Medical Sciences, CCRF, New Delhi, 110029, India

    Vikas Sharma

  4. Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi, 110029, India

    Ashish Suri

  5. Department of Pathology, All India Institute of Medical Sciences, New Delhi, 110029, India

    Chitra Sarkar

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Contributions

C. S., R. K., and V. S. conceived this project and supervised the study. A. S. performed surgery and provided the tumor sections. P. J., J. S., I. D., C. S., M. C. S., and V. S. performed the histological analyses and harvested RNA for gene expression profiling. N. S. performed pre-processing of the microarray data. R. K., R. G., I. D., and J. S. analyzed and interpreted the gene expression data and were the major contributors to writing the manuscript. All authors were involved in the editing of the manuscript. R. G. and R. K. analyzed the lncRNA and lncRNA-mRNA co-expression data, and performed pathway and network analyses. V. S. and R.G. plotted the Kaplan–Meier curves. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Vaishali Suri, Chitra Sarkar or Ritu Kulshreshtha.

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Ethics approval was taken from AIIMS Ethics Institute (IEC-724, 04/10/2019).

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Yes.

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Yes.

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The authors declare no competing interests.

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Supplementary Information

Below is the link to the electronic supplementary material.

12035_2022_2893_MOESM1_ESM.xlsx

Supplementary file1 TableS1: A list of differentially regulated mRNAs in PXA versus control brain,obtained by applying log2 fold change cut-off. (XLSX 1154 KB)

12035_2022_2893_MOESM2_ESM.xlsx

Supplementary file2 TableS2: A list of differentially regulated lncRNAs in PXA versus control brain,obtained by applying log2 fold change cut-off. (XLSX 157 KB)

12035_2022_2893_MOESM3_ESM.ps

Supplementary file3 Fig.1: A depiction of non-redundant GO BP and GO MF terms of the top 100 most differentially expressed mRNAs in PXA using http://revigo.irb.hr/ online tool. a GO BP of upregulated mRNAs. b GO BPof downregulated mRNAs. c GO MF of upregulated mRNAs. d GO MF of downregulatedmRNAs (PS 575 KB)

12035_2022_2893_MOESM4_ESM.xlsx

Supplementary file4 TableS3: A list of the 100 most deregulated lncRNAs’ predicted transcripts obtainedby arranging as per ‘Sum of energy’ values using ‘LncRRiSearch’ webtoolhttp://rtools.cbrc.jp/LncRRIsearch/. (XLSX 174 KB)

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Supplementary file5 Fig.2: A depiction of non-redundant GO BP and GO MF terms of the top 100 most differentially expressed lncRNAs in PXA using http://revigo.irb.hr/ onlinetool. a GO MF of upregulated lncRNAs. b GO MF of downregulated lncRNAs. c GO BPof upregulated lncRNAs. d GO BP of downregulated lncRNAs. (PS 514 KB)

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Supplementary file6 TableS4: A list of pathway terms reported from the lncRNA target PPI network using‘g:Profiler’ online tool https://biit.cs.ut.ee/gprofiler/. (XLSX 21 KB)

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Supplementary file7 Table S5: Differentially expressed mRNAs in PXA as predicted targets of the differentially expressed lncRNAs using‘LncRRiSearch’ webtool http://rtools.cbrc.jp/LncRRIsearch/. List made byintersecting the predicted targets of lncRNAs with the list of differentially regulated genes in PXA. (XLSX 22 KB)

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Supplementary file8 TableS6: Expression correlation output file as obtained from the ‘Expression correlation’ plugin of Cytoscape by choosing >0.85 as the Pearson’scorrelation cut-off (r). (XLSX 778 KB)

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Supplementary file9 TableS7: A list of pathways for the top 30 co-expressed and differentially regulated lncRNA-mRNA pairs obtained using ‘g:Profiler’ online toolhttps://biit.cs.ut.ee/gprofiler/. (XLSX 10 KB)

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Supplementary file10 TableS8: Progression free survival data input file for the 20 most differentially regulated lncRNAs in PXA. Median expression threshold set for dividing thepatients in low and high expression groups. (XLSX 41 KB)

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Supplementary file11 TableS9: Progression free survival data input file for the 20 most differentially regulated mRNAs in PXA. Median expression threshold set for dividing thepatients in low and high expression groups. (XLSX 199 KB)

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Dandapath, I., Gupta, R., Singh, J. et al. Long Non-coding RNA and mRNA Co-expression Network Reveals Novel Players in Pleomorphic Xanthoastrocytoma. Mol Neurobiol 59, 5149–5167 (2022). https://doi.org/10.1007/s12035-022-02893-5

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