A plasma SNORD33 signature predicts platinum benefit in metastatic triple-negative breast cancer patients

Biyun Wang, Yannan Zhao, Yi Li, Yingying Xu, Yun Chen, Qiuyu Jiang, Dingjin Yao, Li Zhang, Xichun Hu, Chaowei Fu, Si Zhang, She Chen, Biyun Wang, Yannan Zhao, Yi Li, Yingying Xu, Yun Chen, Qiuyu Jiang, Dingjin Yao, Li Zhang, Xichun Hu, Chaowei Fu, Si Zhang, She Chen

No abstract available

Keywords: Breast cancer; Chemoresistance; MeCP2; Platinum; Prognostic biomarker; SNORD33.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Reduced SNORD33 level predicts cisplatin (DDP) resistance in mTNBC. a 231/DDP cells are resistant to cisplatin. 231 and 231/DDP cells were incubated with indicated concentration of DDP for 48 h. CCK8 assays were performed to detect cell viability. n = 3; *** represents P < 0.001; two-tailed t-test. b Heat map analysis displays the differential expression of snoRNAs including SNORD33 in 231 and 231/DDP cells. c Volcano map analysis shows that SNORD33 expression is most significantly reduced in 231/DDP cells. d SNORD33 is down-regulated in 231/DDP cells. SNORD33 levels in normal 231 cells and cisplatin-resistant 231/DDP cells were assessed by qRT-PCR and normalized against U6. n = 3; ** represents P < 0.01; two-tailed t test. e SNORD33 knockdown increases cell viability of cisplatin treated TNBC cells. SNORD33 was knocked down in MDA-MB-231, MDA-MB-468 and SUM149PT cells. Cells were then treated with cisplatin at indicated concentrations for 48 h and cell viability was determined by CCK8 assay. n = 3; ** represents P < 0.01, *** represents P < 0.001; two-tailed t test. f Patients selection and study design: plasma from patients (n = 209) who received platinum-based regimens in NCT01287624, NCT02341911 and NCT02546934 trials were included in platinum-regimen cohort and those (n = 45) who received non-platinum regimen were included in non-platinum-regimen cohort. Peripheral blood mononuclear cells from patients (n = 114) in platinum-regimen cohort were randomly tested for gBRCA mutation. g, h Kaplan–Meier survival curves for median progression-free survival (PFS) in mTNBC patients receiving first-line platinum-based regimen based on the expression of SNORD33. Training cohort (n = 81), P = 0.005 (g); validation cohort (n = 128), P < 0.001 (h). Cut-off threshold was median value in these cohort; log-rank test. i Kaplan-Meier survival curves for median PFS in mTNBC patients received first-line non-platinum-based regimen. Cut-off threshold was median value in this cohort, P = 0.053; log-rank test. j Plasma SNORD33 level was significantly higher in patients reaching clinical benefit (CB, CR + PR + SD>6 months). Training cohort (11.88 versus 10.98, P = 0.012), validation group (11.72 versus 11.23, P = 0.006), combined cohorts (11.88 versus 10.98, P = 0.038); two-tailed t test. k, l BRCA mutation neither correlates with plasma SNORD33 level (1.27 versus 1.22, P = 0.949) (k), nor relates to PFS (l) in patients with platinum-based chemotherapy. Kaplan-Meier survival curves for median PFS in mTNBC patients received first-line non-platinum-based regimen based on gBRCA mutation (l). Cut-off threshold was median value in this cohort (n = 114). P = 0.961; log-rank test. m The prognostic accuracy for platinum response by the SNORD33 signature, liver metastasis and number of metastatic sites. n Prognostic nomogram to assign the probability of PFS for TNBC patients after first-line platinum treatment initiation. The probability of PFS at 2, 4, 6, 10, 12 and 18 months can be obtained as function of total points calculated as the sum points of each specific variable. Points are assigned for each risk factor by drawing a line upward from the corresponding values to the ‘point’ line. The total sum of points for three risk factors is plotted on the ‘total points’ line. A vertical line is drawn for reading the corresponding predictions of 2, 4, 6, 10, 12 and 18 months PFS probability. o A calibration curve of the nomogram. The calibration of the prediction model was performed by a visual calibration plot comparing the predicted and actual probability of PFS. The 1000 bootstrap resamples for internal validation was used to assess the predictive accuracies of nomogram
Fig. 2
Fig. 2
MeCP2 contributes to SNORD33 mediated cisplatin resistance in mTNBC. aRPL13A, DICER enzyme, or SNORD32a were knocked down in MDA-MB-231 cells. bRPL13A, DICER enzyme, or SNORD32a knockdown do not change the cell viability in response to platinum. These results indicated that platinum resistance arising from loss of SNORD33 may be not caused by alterations of host gene, forming functional miRNA or rRNA modification. c The silver-stained bands showed the bands of the sense and antisense strands. The different bands were concentrated in the range of 50–80 kDa and 30–40 kDa. Mass spectrometry show that MeCP2 is a candidate protein for SNORD33 interaction. d MeCP2 immunoprecipitates were enriched by SNORD33. RNA pull-down (upper panel) and RIP (RNA immunoprecipitation) assays (lower panel) were performed in MDA-MB-231 cells. Anti-IgG was used as a negative control. n = 3; *** represents P < 0.001; two-tailed t test. e SNORD33 knockdown in MDA-MB-231 cells doesn’t alter MeCP2 mRNA and protein levels. f mRNA levels of MeCP2 target genes are decreased in MDA-MB-231 cells knocking down of SNORD33. The mRNA levels of GADD45α, MYOD1, FOXF1, CDKL5, CLDN6 in MDA-MB-231 cells were determined by qRT-PCR. n = 3; * represents P < 0.05, ** represents P < 0.01, *** represents P < 0.001; two-tailed t test. g SNORD33 knockdown promotes MeCP2 binding to downstream target gene promoter. SNORD33 was knocked down in MDA-MB-231 cells and chromatin immunoprecipitation (ChIP) assay was performed. qRT-PCR quantification of the immunoprecipitated DNA were measured. Normal rabbit IgG were used as a negative control. Values represented enrichment relative to input DNA. Data are presented as mean ± SD; ** represents P < 0.01, *** represents P<0.001; one-way ANOVA. h, i SNORD33 knockdown does not change the binding of co-repressor mSIN3A and HDAC1 to MeCP2. SNORD33 was knocked down in MDA-MB-231 cells and co-immunoprecipitation was performed by MeCP2 antibody. MeCP2, mSIN3A and HDAC1 proteins were detected with western blot (h). The binding affinity between MeCP2/mSIN3A and MeCP2/HDAC1 was quantified (i). n = 3; n.s. represents not significant; two-tailed t test. j Down-regulation of MeCP2 rescues SNORD33 knockdown induced cell death. The proliferation of cisplatin treated MDA-MB-231, MDA-MB-468, SUM149PT cells was determined by CCK8 assay. n = 3; *** represents P < 0.001; two-tailed t test. k, l Down-regulation of MeCP2 rescues SNORD33 knockdown decreased cell apoptosis (k) and induced alteration of apoptotic markers (l). Apoptosis of cisplatin treated cells was determined by flow cytometric analysis. Western blot was used to detect the indicated apoptotic markers in cisplatin treated cells. 10 μM cisplatin for MDA-MB-231, 8 μM cisplatin for MDA-MB-468 and 3 μM cisplatin for SUM149PT cells

References

    1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–249. doi: 10.3322/caac.21660.
    1. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–752. doi: 10.1038/35021093.
    1. Berrada N, Delaloge S, Andre F. Treatment of triple-negative metastatic breast cancer: toward individualized targeted treatments or chemosensitization? Ann Oncol. 2010;21(Suppl 7):vii30–vii35. doi: 10.1093/annonc/mdq279.
    1. Denkert C, Liedtke C, Tutt A, von Minckwitz G. Molecular alterations in triple-negative breast cancer-the road to new treatment strategies. Lancet. 2017;389(10087):2430–2442. doi: 10.1016/S0140-6736(16)32454-0.
    1. Bachellerie JP, Cavaille J, Huttenhofer A. The expanding snoRNA world. Biochimie. 2002;84(8):775–790. doi: 10.1016/S0300-9084(02)01402-5.
    1. Cui L, Nakano K, Obchoei S, Setoguchi K, Matsumoto M, Yamamoto T, et al. Small nucleolar noncoding RNA SNORA23, up-regulated in human pancreatic ductal adenocarcinoma, regulates expression of Spectrin repeat-containing nuclear envelope 2 to promote growth and metastasis of xenograft tumors in mice. Gastroenterology. 2017;153(1):292–306 e2. doi: 10.1053/j.gastro.2017.03.050.
    1. Liao J, Yu L, Mei Y, Guarnera M, Shen J, Li R, et al. Small nucleolar RNA signatures as biomarkers for non-small-cell lung cancer. Mol Cancer. 2010;9:198. doi: 10.1186/1476-4598-9-198.
    1. Mei YP, Liao JP, Shen J, Yu L, Liu BL, Liu L, et al. Small nucleolar RNA 42 acts as an oncogene in lung tumorigenesis. Oncogene. 2012;31(22):2794–2804. doi: 10.1038/onc.2011.449.
    1. Okugawa Y, Toiyama Y, Toden S, Mitoma H, Nagasaka T, Tanaka K, et al. Clinical significance of SNORA42 as an oncogene and a prognostic biomarker in colorectal cancer. Gut. 2017;66(1):107–117. doi: 10.1136/gutjnl-2015-309359.
    1. Appaiah HN, Goswami CP, Mina LA, Badve S, Sledge GW, Jr, Liu Y, et al. Persistent upregulation of U6:SNORD44 small RNA ratio in the serum of breast cancer patients. Breast Cancer Res. 2011;13(5):R86. doi: 10.1186/bcr2943.
    1. Baraniskin A, Nopel-Dunnebacke S, Ahrens M, Jensen SG, Zollner H, Maghnouj A, et al. Circulating U2 small nuclear RNA fragments as a novel diagnostic biomarker for pancreatic and colorectal adenocarcinoma. Int J Cancer. 2013;132(2):E48–E57. doi: 10.1002/ijc.27791.
    1. Crea F, Quagliata L, Michael A, Liu HH, Frumento P, Azad AA, et al. Integrated analysis of the prostate cancer small-nucleolar transcriptome reveals SNORA55 as a driver of prostate cancer progression. Mol Oncol. 2016;10(5):693–703. doi: 10.1016/j.molonc.2015.12.010.
    1. Tosar JP, Garcia-Silva MR, Cayota A. Circulating SNORD57 rather than piR-54265 is a promising biomarker for colorectal cancer: common pitfalls in the study of somatic piRNAs in cancer. RNA. 2021;27(4):403–410. doi: 10.1261/rna.078444.120.
    1. Rimer JM, Lee J, Holley CL, Crowder RJ, Chen DL, Hanson PI, et al. Long-range function of secreted small nucleolar RNAs that direct 2′-O-methylation. J Biol Chem. 2018;293(34):13284–13296. doi: 10.1074/jbc.RA118.003410.
    1. Vieira JP, Lopes F, Silva-Fernandes A, Sousa MV, Moura S, Sousa S, et al. Variant Rett syndrome in a girl with a pericentric X-chromosome inversion leading to epigenetic changes and overexpression of the MECP2 gene. Int J Dev Neurosci. 2015;46:82–87. doi: 10.1016/j.ijdevneu.2015.07.010.
    1. Pandey S, Pruitt K. Functional assessment of MeCP2 in Rett syndrome and cancers of breast, colon, and prostate. Biochem Cell Biol. 2017;95(3):368–378. doi: 10.1139/bcb-2016-0154.

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