CircRIC8B regulates the lipid metabolism of chronic lymphocytic leukemia through miR199b-5p/LPL axis

Author(s): Zijuan Wu ¹ ^, ² ^, ³ , Danling Gu ¹ ^, ² ^, ³ , Ruixin Wang ¹ ^, ² ^, ³ , Xiaoling Zuo ¹ ^, ² ^, ³ , Huayuan Zhu ¹ ^, ² ^, ³ , Luqiao Wang ¹ ^, ² ^, ³ , Xueying Lu ¹ ^, ² ^, ³ , Yi Xia ¹ ^, ² ^, ³ , Shuchao Qin ¹ ^, ² ^, ³ , Wei Zhang ¹ ^, ² ^, ³ , Wei Xu ¹ ^, ² ^, ³ , Lei Fan ¹ ^, ² ^, ³ ^, , Jianyong Li ¹ ^, ² ^, ³ ^, ⁴ ^, , Hui Jin ¹ ^, ² ^, ³ ^,

Publication date (Electronic): 5 September 2022

Journal: Experimental Hematology & Oncology

Publisher: BioMed Central

Keywords: Chronic lymphocytic leukemia, Lipid metabolism, circRIC8B, LPL, Ezetimibe

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Abstract

Objective

Circular RNAs (circRNAs) play a critical role in the modulation of tumor metabolism. However, the expression patterns and metabolic function of circRNAs in chronic lymphocytic leukemia (CLL) remain largely unknown. This study aimed to elucidate the role of circRNAs in the lipid metabolism of CLL.

Methods

The expression and metabolic patterns of circRNAs in a cohort of 53 patients with CLL were investigated using whole transcriptome sequencing. Cell viability, liquid chromatography with tandem mass spectrometry (LC–MS/MS) analysis, lipid analysis, Nile red staining as well as triglyceride (TG) assay were used to evaluate the biological function of circRIC8B in CLL. The regulatory mechanisms of circRIC8B/miR-199b-5p/lipoprotein lipase (LPL) axis were explored by luciferase assay, RNA immunoprecipitation (RIP), qRT-PCR, and fluorescence in situ hybridization (FISH). CCK-8 and flow cytometry were used to verify the inhibition role of cholesterol absorption inhibitor, ezetimibe, in CLL cells.

Results

Increased circRIC8B expression was positively correlated with advanced progression and poor prognosis. Knockdown of circRIC8B significantly suppressed the proliferation and lipid accumulation of CLL cells. In contrast, the upregulation of circRIC8B exerted opposite effects. Mechanistically, circRIC8B acted as a sponge of miR-199b-5p and prevented it from decreasing the level of LPL mRNA, and this promotes lipid metabolism alteration and facilitates the progression of CLL. What’s more, ezetimibe suppressed the expression of LPL mRNA and inhibited the growth of CLL cells.

Conclusions

In this study, the expressional and metabolic patterns of circRNAs in CLL was illustrated for the 1st time. Our findings revealed that circRIC8B regulates the lipid metabolism abnormalities in and development of CLL through the miR-199b-5p/LPL axis. CircRIC8B may serve as a promising prognostic marker and therapeutic target, which enhances the sensitivity to ezetimibe in CLL.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40164-022-00302-0.

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Most cited references 37

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Cancer statistics, 2020

Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2020)

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.

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GSVA: gene set variation analysis for microarray and RNA-Seq data

Sonja Hänzelmann, Robert Castelo, Justin Guinney (2013)

Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

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Fundamentals of cancer metabolism

Ralph DeBerardinis, Navdeep Chandel (2016)

Researchers provide a conceptual framework to understand current knowledge of the fundamentals of cancer metabolism.

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Author and article information

Contributors

Lei Fan: fanlei3014@126.com

Jianyong Li: lijianyonglm@126.com

Hui Jin: jinzi817@live.cn

Journal

Journal ID (nlm-ta): Exp Hematol Oncol

Journal ID (iso-abbrev): Exp Hematol Oncol

Title: Experimental Hematology & Oncology

Publisher: BioMed Central (London )

ISSN (Electronic): 2162-3619

Publication date (Electronic): 5 September 2022

Publication date PMC-release: 5 September 2022

Publication date Collection: 2022

Volume: 11

Electronic Location Identifier: 51

Affiliations

[1 ]GRID grid.412676.0, ISNI 0000 0004 1799 0784, Department of Hematology, , Pukou CLL Center, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, ; Nanjing, 210029 China

[2 ]GRID grid.89957.3a, ISNI 0000 0000 9255 8984, Key Laboratory of Hematology of Nanjing Medical University, ; Nanjing, 210029 China

[3 ]GRID grid.89957.3a, ISNI 0000 0000 9255 8984, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, , Nanjing Medical University, ; Nanjing, 210029 China

[4 ]GRID grid.429222.d, ISNI 0000 0004 1798 0228, National Clinical Research Center for Hematologic Diseases, the First Affiliated Hospital of Soochow University, ; Suzhou, 215000 China

Article

Publisher ID: 302

DOI: 10.1186/s40164-022-00302-0

PMC ID: 9442988

PubMed ID: 36064433

SO-VID: 66c83272-b65c-40f4-a46a-81fcfc33ccd9

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 31 May 2022

Date accepted : 20 August 2022

Funding

Funded by: Young Scholars Fostering Fund of the First Affiliated Hospital of Nanjing Medical University

Award ID: PY2021036

Award Recipient : Zijuan Wu

Funded by: National Natural Science Foundation of China

Award ID: 81770166

Award ID: 81720108002

Award ID: 82170185

Award Recipient : Wei Xu Jianyong Li Hui Jin

Funded by: CSCO Research Foundation

Award ID: Y-Roche2019/2-0090

Award Recipient : Lei Fan

Funded by: Translational research grant of NCRCH

Award ID: 2020ZKZB01

Award Recipient : Jianyong Li

Funded by: FundRef http://dx.doi.org/10.13039/501100004608, Natural Science Foundation of Jiangsu Province;

Award ID: BK20211376

Award Recipient : Hui Jin

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: chronic lymphocytic leukemia,lipid metabolism,circric8b,lpl,ezetimibe

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ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: chronic lymphocytic leukemia, lipid metabolism, circric8b, lpl, ezetimibe

CircRIC8B regulates the lipid metabolism of chronic lymphocytic leukemia through miR199b-5p/LPL axis

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Abstract

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Conclusions

Supplementary Information

Related collections

Journal of Circulating Biomarkers

Most cited references 37

Cancer statistics, 2020

GSVA: gene set variation analysis for microarray and RNA-Seq data

Fundamentals of cancer metabolism

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