Abstract
Targeted protein degradation has become a notable drug development strategy, but its application has been limited by the dependence on protein-based chimeras with restricted genetic manipulation capabilities. The use of long non-coding RNAs (lncRNAs) has emerged as a viable alternative, offering interactions with cellular proteins to modulate pathways and enhance degradation capabilities. Here we introduce a strategy employing artificial lncRNAs (alncRNAs) for precise targeted protein degradation. By integrating RNA aptamers and sequences from the lncRNA HOTAIR, our alncRNAs specifically target and facilitate the ubiquitination and degradation of oncogenic transcription factors and tumor-related proteins, such as c-MYC, NF-κB, ETS-1, KRAS and EGFR. These alncRNAs show potential in reducing malignant phenotypes in cells, both in vitro and in vivo, offering advantages in efficiency, adaptability and versatility. This research enhances knowledge of lncRNA-driven protein degradation and presents an effective method for targeted therapies.
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Data availability
The data supporting the findings of this study are available within the paper and its Supplementary Information. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD052457. Additional information is available from the authors upon reasonable request. Source data are provided with this paper.
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Acknowledgements
This work was supported by grants from the National Key R&D Program of China (2021YFA0911600) to Y.L.; the National Natural Science Foundation of China (82273135) to L.Y.; the National Natural Science Foundation of China (82303113) to A.L.; the Shenzhen Science and Technology Program (RCJC20221008092723011 and JCYJ20220818102001002) to Y.L.; the Beijing Municipal Science & Technology Commission (Z221100007422073) to L.Y.; the Guangdong Basic and Applied Basic Research Foundation (2023A1515111041) to C.C.; and the research fund of the Synthetic Biology Research Center of Shenzhen University to Y.L.
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C.C. performed data analysis and contributed to paper preparation. A.L. assisted with the design of cell experiments and provided technical support. C.X. conducted statistical analysis and helped with the interpretation of results. B.W. was involved in the design and execution of mouse experiments. L.Y. was responsible for securing funding and overseeing the process, while Y.L. provided the conceptual framework, designed the experiments and also secured funding.
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Extended data
Extended Data Fig. 1 The protein quantification results from main figures.
Figures A-H correspond to the quantitative statistical results of Figs. 1a, e, g, h, i, 2c, d in the main text, respectively. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test.
Extended Data Fig. 2 The specificity of alncRNA.
(A) RIP analysis of the interaction of alncRNA with a panel of RBPs in cell lysates. Antibodies recognizing the RBPs shown were used for IP in each case; control IP reactions were carried out using a corresponding IgG. AlncRNA levels were measured by RT-qPCR and normalized to the levels of GAPDH mRNA levels in the same IP samples measured by RT-qPCR analysis. Data were quantified as enrichment of alncRNA in the RBP IP relative to the IgG IP. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (B-C) The protein levels of RBPs were analyzed in alncRNA-expressing cells by WB. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (D) Proteomics analysis ensures the specificity of alncRNA. The data were analyzed using a two-tailed unpaired Student’s t-test. Adjustments were made for multiple comparisons using the Bonferroni correction method. (E-F) RIP assays show that alncRNA is pulled down by Dzip3 and GFP antibody in cells. Immunoprecipitation with control IgG served as the negative control. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (G) RNA pull-down assays showed that Dzip3 and GFP was pulled down by alncRNA. Antisense of alncRNA was used as negative control. (H-I) The effect of reporter gene activation was determined by dual-luciferase reporter assay. CRISPR plasmids were transfected into cells stably expressing a dual-luciferase reporter vector. Relative luciferase activities were determined as the ratios between Rluc and Fluc values. Data represent mean ± s.d. from four independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (J-K) Fold change in abundance of whole-cell proteins detected using quantitative proteomics analysis after c-Myc (J) and NF-κB (K) degradation. The data were analyzed using a two-tailed unpaired Student’s t-test. Adjustments were made for multiple comparisons using the Bonferroni correction method.
Extended Data Fig. 3 The dependence of the protein degradation function of alncRNA on Dzip3.
(A) Forty-eight hours after transfecting the shRNAs shown and alncRNA, the levels of GFP, Dzip3 and loading control GAPDH were assessed by WB analysis. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (B) Forty-eight hours after overexpressing plasmids Dzip3 mutant or Dzip3 WT in cells, the levels of GFP, Dzip3 (WT and mutant) and loading control GAPDH were assessed by WB analysis. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (C) Forty-eight hours after transfecting plasmids GFP WT or GFP mutant, the levels of GFP (WT and mutant) and loading control GAPDH were assessed by WB analysis. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (D) Following transfection of cells with plasmids GFP WT or GFP mutant, RIP analysis was performed to quantify the interaction of WT GFP and mutant GFP with alncRNA; binding was normalized to GAPDH mRNA levels in the IP samples. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (E) The half-lives (t1/2) of alncRNA and GAPDH mRNA were quantified by measuring the rate of decline in transcript levels by RT-qPCR. Data represent the means and s.d. from three independent experiments.
Extended Data Fig. 4 The target proteins degraded by alncRNA in different tumor cell lines.
(A-B) The alncRNA facilitates the degradation of c-MYC (A) and NF-κB (B) in different tumor cell lines. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (C-D) The target genes of c-MYC (C) and NF-κB (D) were downregulated by alncRNA. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (E) The alncRNA promotes degradation of KRAS in pancreatic cancer cell lines. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test.
Extended Data Fig. 5 The gradual decrease in the protein levels of c-MYC and NF-κB after treated with alncRNA.
(A-B) The results illustrate the time-dependent degradation of c-MYC (A) and NF-κB (B) proteins mediated by alncRNA. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (C-D) Flow cytometry analysis revealed the apoptosis rate of bladder cancer cells transfected with alncRNA targeting c-MYC (C) and NF-κB (D) protein degradation at 24 h. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test.
Extended Data Fig. 6 The tumor-suppressive effects of AAV-Dzip3-c-Myc after Dzip3 knockdown.
(A-B) The quantification results of Edu positive cells in Fig. 3c, d (A) and Fig. 3g, h (B). Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (C) Measurement of 3 pairs of metastatic model’s bioluminescence imaging. (D) The survival curve of mice showed that tail vein injection of AAV-Dzip3-c-MYC did not significantly shorten the survival time of the mice. (E) ELISA results showing the levels of IL-6, TNF-α and IL-1β in the serum of BALB/c nude mice. (F-G) Forty-eight hours after transfecting the shRNAs shown and alncRNA, the levels of c-MYC, Dzip3 and loading control GAPDH were assessed by WB analysis. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (H-I) Tumor growth assays demonstrate that when Dzip3 is knocked down in cells, AAV-Dzip3-c-Myc does not exhibit a significant tumor-suppressive effect compared to the control Dzip3-NC. The number of mice for each group was 6 (n = 6 mice / group). Data represent mean ± s.d. The P value was determined by a two-tailed unpaired Student’s t test.
Extended Data Fig. 7 The alncRNA promotes degradation of ETS-1 in bladder cancer cell lines.
(A) The interaction between ETS-1 and Dzip3 was tested by immunoprecipitation. (B-C) The protein levels of ETS-1 were analyzed in alncRNA-expressing BCa cells by WB. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (D-E) After alncRNA degraded ETS-1 protein expression, wound healing assays were utilized to assess the migratory abilities of two bladder cancer cells. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (F) After alncRNA degraded ETS-1 protein expression, transwell assays were utilized to assess the cell motility of two bladder cancer cells. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (G) Measurement of a metastatic model’s bioluminescence imaging. The signal intensities for luminescence are displayed. The number of metastatic nodules formed in the lungs of mice for each group was 6 (n = 6 mice / group). Data represent mean ± s.d. The P value was determined by a two-tailed unpaired Student’s t test.
Extended Data Fig. 8 The alncRNA promotes degradation of EGFR in bladder cancer cell lines.
(A-B) The protein levels of EGFR were analyzed in alncRNA-expressing BCa cells by WB. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (C) The mRNA levels of EGFR were analyzed in alncRNA-expressing BCa cells by RT-qPCR. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (D-E) The CCK-8 assay demonstrated the effect of alncRNA-degraded EGFR protein expression on the proliferation of bladder cancer cells (T24 and 5637). Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-way ANOVA. (F-H) After alncRNA degraded EGFR protein expression, wound healing assays were utilized to assess the migratory abilities of two bladder cancer cells. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (I) The caspase-3/ELISA assay demonstrates the impact of alncRNA targeting EGFR protein degradation on cell apoptosis (T24 and 5637). Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test. (J) The target genes of EGFR were downregulated by alncRNA. Data represent mean ± s.d. from three independent experiments. The P values were determined by a two-tailed unpaired Student’s t test.
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Cao, C., Li, A., Xu, C. et al. Engineering artificial non-coding RNAs for targeted protein degradation. Nat Chem Biol (2024). https://doi.org/10.1038/s41589-024-01719-w
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DOI: https://doi.org/10.1038/s41589-024-01719-w