Lncrna TINCR Favors Tumorigenesis Via STAT3–TINCR–EGFR-Feedback

Wang et al. Cell Death and Disease (2021) 12:83 https://doi.org/10.1038/s41419-020-03188-0 Cell Death & Disease

ARTICLE Open Access LncRNA TINCR favors tumorigenesis via STAT3–TINCR–EGFR-feedback loop by recruiting DNMT1 and acting as a competing endogenous RNA in human breast cancer Qin Wang1,JienaLiu1, Zilong You1, Yanling Yin1,LeiLiu1,YujuanKang1,SiweiLi1, Shipeng Ning1,HuiLi1, Yajie Gong1, Shouping Xu1 and Da Pang 1,2

Abstract The long noncoding RNA (lncRNA) TINCR has recently been found to be associated with the progression of human malignancies, but the molecular mechanism of TINCR action remains elusive, particularly in breast cancer. The oncogenic role of TINCR was examined in vitro and in vivo in breast cancer. Next, the interaction between TINCR, DNMT1, and miR-503-5p methylation was explored. Moreover, the mechanism by which TINCR enhances EGFR expression and downstream signaling via an RNA–RNA interaction was comprehensively investigated. Furthermore, upstream transcriptional regulation of TINCR expression by STAT3 was examined by performing chromatin immunoprecipitation. Finally, feedback signaling in the STAT3–TINCR–EGFR downstream cascade was also investigated. TINCR is upregulated in human breast cancer tissues, and TINCR knockdown suppresses tumorigenesis in vitro and in vivo. Mechanistically, TINCR recruits DNMT1 to the miR-503-5p locus promoter, which increases the

1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; methylation and suppresses the transcriptional expression of miR-503-5p. Furthermore, TINCR also functions as a competing endogenous RNA to upregulate EGFR expression by sponging miR-503-5p. In addition, TINCR stimulates JAK2–STAT3 signaling downstream from EGFR, and STAT3 reciprocally enhances the transcriptional expression of TINCR. Our ﬁndings broaden the current understanding of the diverse manners in which TINCR functions in cancer biology. The newly identiﬁed STAT3–TINCR–EGFR-feedback loop could serve as a potential therapeutic target for human cancer.

Introduction diagnostic biomarkers and potential targets for cancer – Long noncoding RNAs (lncRNAs) are >200-nt-long therapeutics3 5, and recent examination of increasing RNA transcripts encoded by the genome that are mostly numbers of cancer transcriptomes by using next- not translated into proteins, but play key roles in reg- generation sequencing has identiﬁed thousands of ulating gene expression, chromatin dynamics, differ- lncRNAs whose aberrant expression is associated with entiation, growth, and development1,2. Several lncRNAs different cancer types, including breast, pancreatic, lung, – are also aberrantly expressed in cancers and can serve as liver, gastric, head and neck, and colon cancers6 12. Although lncRNAs have now been recognized as funda- mental regulators of gene expression, most lncRNAs Correspondence: Shouping Xu ([email protected])or remain functionally uncharacterized in cancer. Da Pang ([email protected]) Breast cancer (BC) is the most common female malig- 1 Department of Breast Surgery, Harbin Medical University Cancer Hospital, nant tumor worldwide. A major feature is its challenging Harbin, China 13 2Heilongjiang Academy of Medical Sciences, Harbin, China heterogeneity at the clinical and molecular level . Over Edited by B. Rotblat

© The Author(s) 2021 Open Access This 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 linktotheCreativeCommons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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the past few decades, BC has revealed that it is quite (Fig. 1f). Next, GO and KEGG pathway analyses were complex and has no longer been considered a single performed to identify the potential functions of TINCR disease, but rather a set of distinct subtypes14. BC sub- (Fig. 1g, h and Supplementary Table S2). The results types have been classified according to immunohisto- indicated TINCR involvement in the biological processes chemical markers, clinicopathologic features, genomic of mitotic nuclear division, cell division, regulation of the alterations, and gene-expression profiling15,16. Aberrant cell cycle, DNA-replication initiation, DNA methylation, expression of EGFR, a receptor tyrosine kinase of the chromosome segregation, cell proliferation, and ERBB family17, can result in unregulated growth stimu- microtubule-based movement (Fig. 1g and Supplementary – lation and tumorigenesis in various types of cancer18 22. Table S2). Moreover, our results suggested potential Moreover, inappropriate EGFR activation can occur TINCR participation in cell- cycle pathway, oocyte through a range of complex mechanisms, including gene meiosis pathway, salivary-secretion pathway, p53 signal- amplification, autocrine ligand–receptor stimulation, and ing pathway, progesterone-mediated oocyte-maturation – epigenetic modulation23 25. However, to determine how pathway, aldosterone synthesis, and secretion pathway, intrinsic and acquired resistance to EGFR inhibitors in and other pathways related to tumorigenesis (Fig. 1h and cancer treatments can be avoided, it is essential to com- Supplementary Table S2). The association of TINCR prehensively elucidate the regulatory landscape of the overexpression with patient survival was analyzed in 125 ERBB family and the interaction and crosstalk between patients with breast cancer in the HMUCC cohort. lncRNAs and ERBB-family members. Patients harboring tumors with upregulated TINCR Here, we uncovered the diverse manners in which the expression were associated with poor overall survival (OS) lncRNA TINCR functions in breast cancer biology. (Supplementary Fig. S1). TINCR was found to be upregulated and positively cor- Besides breast cancer, multiple other cancers exhibited related with EGFR expression in human breast cancer. TINCR upregulation, including adrenocortical carcinoma Mechanistic analyses revealed that TINCR recruits (ACC), bladder urothelial carcinoma (BLCA), cervical DNMT1 to the miR-503-5p locus promoter and thereby and endocervical cancers (CESC), lymphoid neoplasm- increases miR-503-5p methylation and suppresses its diffuse large B-cell lymphoma (DLBC), acute myeloid transcriptional expression, and further that TINCR also leukemia (LAML), lung squamous-cell carcinoma functions as a competing endogenous RNA (ceRNA) to (LUSC), pancreatic adenocarcinoma (PAAD), testicular upregulate EGFR expression by sponging miR-503-5p. germ-cell tumors (TGCT), thyroid carcinoma (THCA), Moreover, TINCR stimulates JAK2–STAT3 signaling and thymoma (THYM), according to an analysis of the downstream from EGFR, and STAT3, in turn, increases GEPIA database (Fig. 2a). To investigate the relationship the transcriptional expression of TINCR. Our findings between TINCR expression and the prognosis of cancer enhance the current understanding of the diverse roles of patients, Kaplan–Meier survival analysis and log-rank test TINCR in cancer biology, and the newly identified were performed to assess the effects of TINCR expression STAT3–TINCR–EGFR-feedback loop might represent a and clinical outcomes on the survival of patients with potential therapeutic target for human cancer. breast cancer in the GEO database (two TINCR probes were used here, 244374-at/229385-at) (Supplementary Results Table S3) and other cancers in TCGA database. High TINCR expression is upregulated and correlated with poor TINCR expression indicated markedly poorer prognosis prognosis in breast cancer than low TINCR expression did in BRCA patients (Fig. By using the large-scale cancer-genome RNA-seq 2b–g) and BLCA, kidney renal papillary-cell carcinoma expression data from TCGA database, we examined the (KIRP), ovarian serous cystadenocarcinoma (OV), uterine potential association of carcinogenesis with the lncRNAs corpus endometrial carcinoma (UCEC), esophageal car- differentially expressed between breast-cancer and adja- cinoma (ESCA), THCA, kidney renal clear-cell carcinoma cent normal tissues (Fig. 1a, b). Here, we focused on (KIRC), and stomach adenocarcinoma (STAD) patients TINCR, which was found to be expressed at higher levels (Fig. 2h–s). EGFR showed higher expression in the 4T1, in human breast-cancer than in normal tissues (Fig. 1c, d). MDA-MB-231, and UACC-812 cell lines than the other To validate the result, we analyzed 250 tissue specimens— tested cell lines (Supplementary Fig. S2). Thus, the fol- 125 breast-cancer and 125 adjacent normal tissues—from lowing experiments were performed with these three cell Harbin Medical University Cancer Center (HMUCC), and lines to examine the regulatory effects on EGFR we found that TINCR was upregulated in breast-cancer expression. tissues relative to the expression in normal tissues (Fig. 1e and Supplementary Table S1). Moreover, TINCR TINCR promotes tumor growth in vivo and in vitro expression was higher in advanced tumor-node metastasis We next investigated the potential biological functions (TNM) stages III and IV than in TNM stages I and II of TINCR: we used shRNAs specifically designed to target

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A Normal Cancer B Volcano Plot

60 RP11−1100L3.8 FGF14−AS2 MIR497HG AC016995.3 AC005682.5 48 RP11−161M6.2 AC074289.1 RP11−295M3.4 AC097724.3 RP4−575N6.4 36 RP13−1016M1.2 RP11−70D24.2 MIR99AHG AP000473.5 WDR86−AS1 24 RP11−394O4.5 ACTA2−AS1 -log2(P-value) RP11−474O21.5 LINC00961 RP11−536O18.1 12 RP11−104L21.2 RP11−855A2.5 AC093110.3 RP11−968O1.5 RP1−302G2.5 0 RP11−736K20.5 MAGI2−AS3 -3.07 -1.93 -0.78 0.36 1.51 2.65 3.8 RP11−1024P17.1 RP11−158M2.3 log2(FoldChange) RP11−182J1.17 PP14571 C RP11−459E5.1 LINC01605 20 LINC01614 RP11−417E7.2 TONSL−AS1 AC068580.5 HOTAIR **** RP11−465B22.8 RP11−510N19.5 16 RP1−86C11.7 10 TINCR CTD−2510F5.4 CTA−384D8.35 RP11−353N14.2 TFAP2A−AS1 5 FAM83H−AS1 12 RP11−429J17.7

U47924.27 TINCR expression RP11−22C11.2 0 RP11−1136G4.2 RP6−65G23.3 AC104667.3 RP11−92K15.3 8 C6orf99 −5 AC009005.2 Tumor Normal RP3−395M20.12 BRCA RP5−963E22.6 ATP2A1−AS1 −10 (Num(T)=1104;Num(N)=113) TYMSOS

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a a l l e e 1 R R 0 0 8 Tumor Normal Tumor Normal Stage Stage BRCA (N=125) I&II III&IV (Num(T)=1085; Num(N)=291) GH GO:0007067~mitotic nuclear division hsa04110:Cell cycle GO:0051301~cell division hsa04114:Oocyte meiosis GO:0051726~regulation of cell cycle hsa04970:Salivary secretion GO:0007062~sister chromatid cohesion hsa04530:Tight junction GO:0000281~mitotic cytokinesis hsa04115:p53 signaling pathway GO:0000082~G1/S transition of mitotic cell cycle hsa04670:Leukocyte transendothelial migration GO:0007052~mitotic spindle organization hsa04914:Progesterone-mediated oocyte maturation GO:0042267~natural killer cell mediated cytotoxicity hsa04540:Gap junction GO:0006270~DNA replication initiation hsa03460:Fanconi anemia pathway GO:0007059~chromosome segregation hsa04925:Aldosterone synthesis and secretion GO:0007018~microtubule-based movement hsa00750:Vitamin B6 metabolism GO:0000086~G2/M transition of mitotic cell cycle GO:0051256~mitotic spindle midzone assembly hsa04520:Adherens junction GO:0030855~epithelial cell differentiation hsa01230:Biosynthesis of amino acids hsa04911:Insulin secretion GO:0006306~DNA methylation GO:0007017~microtubule-based process hsa00601:Glycosphingolipid biosynthesis GO:0008283~cell proliferation hsa05130:Pathogenic Escherichia coli infection GO:0016055~Wnt signaling pathway hsa00310:Lysine degradation GO:0007049~cell cycle hsa04261:Adrenergic signaling in cardiomyocytes GO:1902749~regulation of cell cycle G2/M phase transition hsa04710:Circadian rhythm 0 12345678910 06712345 -lg(P value) -lg(P value)

Fig. 1 (See legend on next page.)

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(see ﬁgure on previous page) Fig. 1 TINCR is highly expressed in human breast cancer. a Hierarchical-clustering heatmap of differentially expressed lncRNAs in breast-cancer

and adjacent normal tissues, generated from RNA-seq data from TCGA. Colors: expression levels indicated by log2-transformed scale bar below the matrix; red and blue: max and min expression levels, respectively. b Volcano plot of lncRNAs differentially expressed between breast-cancer tissues normal tissues. P < 0.001, fold change >1.2 or fold change < –1.2. c–e TINCR expression in cancer and normal tissues from 1104 breast cancer patients in TCGA cohort (c), 1,085 breast-cancer patients in GEPIA cohort (d), and 125 breast-cancer patients in HMUCC cohort (e). f TINCR expression in breast cancers of different TNM stages in TCGA database. (g, h) GO and KEGG analyses of TINCR. P < 0.05 indicated statistical signiﬁcance. Vertical axis:

biological process or pathway category; horizontal axis: −log10 (P value) of significant biological process or pathway. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. the mouse homolog of the gene, Tincr, and injected Balb/ Considering the aforementioned results, we sought to c mice with 4T1 cells in vivo. Tumor growth was mark- ascertain whether TINCR knockdown and EGFR- edly inhibited in mice injected with TINCR-knockdown inhibitor treatment used together would produce a cells as compared with the growth in mice injected with synergistic anticancer effect. When TINCR knockdown control cells (Fig. 3a, b), and the median tumor weight was combined with treatment with the EGFR inhibitor was also lower in the knockdown than in the control gefitinib, cell-inhibition activity was higher than in the group (Fig. 3c). Furthermore, the results of in vitro assays gefitinib group (IC50 = 13.29 and 10.02 μmol/L vs. showed that proliferation and colony formation were 26.3 μmol/L) (Fig. 4g). Furthermore, this combination lower in TINCR-knockdown cells relative to control (Fig. treatment more effectively inhibited tumor growth than 3d–g), and TINCR knockdown also decreased the inva- the single treatments in vivo (Fig. 4h, i), and the median siveness of these cells (Fig. 3h, i). tumor weight was lower in the combination- treatment group than in the gefitinib or control group (Fig. 4j). TINCR upregulates EGFR expression and downstream signaling in human breast cancer TINCR upregulates EGFR expression by acting as a ceRNA The aforementioned guilt-by-association analysis and our to sponge miR-503-5p previous study26 suggested that TINCR could perform its Next, we investigated the potential mechanism by which potential oncogenic function through EGFR and the EGFR TINCR regulates EGFR expression. First, the subcellular downstream signaling pathway. Here, TINCR knockdown localization of TINCR was examined, which revealed decreased EGFR mRNA and protein expression relative to TINCR localization in both the cytoplasm and the nucleus control in UACC-812 and MDA-MB-231 cells (Fig. 4a, b). in breast-cancer cells (Fig. 5a and Supplementary Fig. S6). We also examined the relationship between TINCR and LncRNAs localized in the cytoplasm typically act as EGFR protein expression in 120 breast-cancer samples from ceRNAs to influence the expression of their target HMUCC,andtheresultsshowedthattheEGFRlevelwas genes27. To identify miRNA candidates that might be higher in TINCR high-expression tissues than in TINCR affected in TINCR-knockdown and scrambled-control low-expression tissues (Fig. 4c, Supplementary Fig.S3, and groups, transcriptome miRNA sequencing was performed Supplementary Table S4). Next, we tested how TINCR to identify microRNAs that potentially bind TINCR knockdown affects EGFR downstream signaling. As per our transcript on the HMUCC cohort samples. We identified expectation, TINCR knockdown led to a decrease in p- 138 potential microRNA candidates in TINCR- JAK2, STAT3, and p-STAT3 relative to their levels in knockdown compared to the control groups (Supple- control cells (Fig. 4d). To gain insights into the role of mentary Table S5). Furthermore, the public databases TINCR in EGFR downstream signaling in a clinical context, TargetScan, RNA22, and StarBase were used to predict we performed immunohistochemical analysis on samples potential miRNAs that bind to EGFR 3ʹ-UTR (Supple- from the HMUCC cohort, which revealed that JAK2 and mentary Table S5), and overlapping miRNAs were STAT3 were more abundant in TINCR high-expression examined among the transcriptome-sequencing data from tissues than TINCR low-expression tissues (Fig. 4e, Sup- the HMUCC cohort and the TargetScan, RNA22, and plementary Fig. S4, and Supplementary Table S4). Fur- StarBase databases (Fig. 5b and Supplementary Table S5). thermore, in Balb/c mice injected with 4T1 cells in vivo, Ultimately, miR-503-5p was selected for the following EGFR and its downstream-signaling molecules were experiments. The knockdown of TINCR increased the downregulated in the TINCR-knockdown group relative to expression of miR-503-5p (Fig. 5c). Moreover, the levels the control group (Fig. 4f). To further validate the result, we of TINCR, EGFR mRNA, and EGFR protein were analyzed tissue specimens from HMUCC, and we found decreased and increased, respectively, after transfection of that EGFR, JAK2, and STAT3 were upregulated in breast- miR-503-5p mimic and its corresponding inhibitor (Fig. cancer tissues relative to the expression in normal tissues 5d, e). Notably, combining TINCR knockdown with miR- (Supplementary Fig. S5). 503-5p-inhibitor treatment attenuated the decrease in

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ABC TINCR 244374_at TINCR 244374_at ACC BLCA BRCA CESC DLBC LAML LUSC PAAD TGCT THCA THYM 90 80 70 60 50 60 80 100 40 TINCR High (n=588) 40 30 TINCR Low (n=698) 40 60TINCR 80 100 High (n=1503) 20 Log-rank p=0.008 TINCR Low (n=1663) Log-rank p=0.048 Overall survival(%) HR=1.52 10 HR=1.17 Disease free survival(%) Transcripts Per Million (TPM) 0 020 020 0 50 100 150 0 50 100 150 200 250 T (n=77) T (n=47) T (n=404)N (n=28) T (n=306)N (n=13) T (n=173)N (n=70)T (n=486) T (n=179) T (n=137) T (n=512) T (n=118) N (n=128) T (n=1085)N (n=291) N (n=337) N (n=338) N (n=171) N (n=165) N (n=337) N (n=339) Time (months) Time (months) DEFG TINCR 244374_at TINCR 229385_s_at TINCR 229385_s_at TINCR 229385_s_at 100 100 80 80 100 80 60 TINCR High (n=615) 60 TINCR High (n=613) TINCR Low (n=671) TINCR High (n=618) TINCR Low (n=697)

40 Log-rank p=0.049 Log-rank p=0.047 TINCR High (n=1535) TINCR Low (n=692) HR=1.35 Log-rank p=0.014 HR=1.25 TINCR Low (n=1631) HR=1.5 Overall survival(%)

20 40 Log-rank p=0.024 HR=1.23 Disease free survival(%) 0 020 0204060 020406080100 Distant metastasis free survival(%) Distant metastasis free survival(%) 050100150 050100150 0 50 100 150 200 250 0 50 100 150 Time (months) Time (months) Time (months) Time (months) HI JK BLCA BLCA KIRP KIRP 100 TINCR High (n=122) 100 TINCR Low (n=363) 80 Log-rank p=0.048 80 HR=1.32 60 40 60 80 100 40 60 TINCR High (n=133) TINCR High (n=125) TINCR Low (n=105) TINCR High (n=103) TINCR Low (n=280) Overall survival(%) Overall survival(%) 20 40 Log-rank p=0.047 20 TINCR Low (n=270) Log-rank p=0.004

Disease free survival(%) HR=2.09 Log-rank p=9.7e-06 Disease free survival(%) HR=2.97 HR=3.55 0 0 020406080100 020 050100150 0 50 100 150 0 50 100 150 200 0 20 40 60 80 100 120 Time (months) Time (months) Time (months) Time (months) LMNO OV OV UCEC UCEC 100 100 TINCR High (n=193) 100 TINCR Low (n=310) TINCR High (n=149) 80 80 Log-rank p=0.028 TINCR Low (n=62) 80 HR=1.34 Log-rank p=0.049 60

HR=1.43 60 TINCR High (n=351) 40 40 60 80 100 TINCR Low (n=205) TINCR High (n=517) Log-rank p=0.045 HR=1.79 Overall survival(%) Overall survival(%) 20 20

TINCR Low (n=196) 20 40

Disease free survival(%) Log-rank p=0.001 Disease free survival(%) HR=2.8 0 0204060 0 0 050100150 050100150 0 50 100 150 200 0 50 100 150 200 Time (months) Time (months) Time (months) Time (months) PQRSESCA THCA KIRC STAD

TINCR High (n=284) 100 TINCR High (n=30) TINCR Low (n=493) TINCR Low (n=96) Log-rank p=7.5e-12 Log-rank p=0.019 80 HR=2.79 HR=2.78

TINCR High (n=279) 60 80 100 TINCR Low (n=192)

40 60 80 100 TINCR High (n=146) Log-rank p=0.045 40 60 80 100 40 HR=2.36 TINCR Low (n=201) Log-rank p=0.001 Overall survival(%) Overall survival(%) HR=2.96 Disease free survival(%) Disease free survival(%) 020 020 0 204060 020 0 20406080 050100150 0 50 100 150 0 20 40 60 80 100 120 Time (months) Time (months) Time (months) Time (months)

Fig. 2 High expression of TINCR is correlated with poor prognosis in human cancer. a Scatter diagram depicting TINCR expression in multiple cancer and adjacent normal tissues, generated from GEPIA database. b–g Kaplan–Meier analysis of OS (b, e), DFS (c, f), and DMFS (d, g) of breast- cancer patients according to TINCR expression, generated from GEO database. h–s Kaplan–Meier analysis of OS and DFS in BLCA (h, i), KIRP (j, k), OV (l, m), UCEC (n, o), ESCA (p), THCA (q), KIRC (r), and STAD (s) patients according to TINCR expression, generated from TCGA database. Data are shown as means ± standard deviation (SD); Student’s t test, *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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A B C Balb/C 2000 * Scramble 1.0

) Sh Tincr #1 3 1500 Scramble *** *** 0.8 1000 *** 0.6

* 0.4 Sh Tincr#1 500 *

Tumor volume(mm Tumor * of tumor(g) Weight 0.2

0 0.0 6 8 10 12 14 16 18 20 (days) Scramble Sh Tincr #1 DE F 4T1 UACC812 4T1 0.8 0.6 **** Scramble NC 250 *** Sh Tincr #1 SiTINCR #1 Scramble Sh Tincr #1 Sh Tincr #2 0.6 * 0.5 200 Sh Tincr #2 * * SiTINCR #2 * * 150 0.4 0.4 * * 100 50 Number of colonies 0.2 0.3 0 Cell viability(OD450) Cell viability(OD450)

incr #2 0.0 0.2 Scramble 24h 48h 72h 24h 48h 72h 96h Sh Tincr #1Sh T

G UACC812 I 4T1 UACC 812 MDA-MB-231 ** NC Si TINCR #1 Si TINCR #2 300 ** 0h 0h 200

100 NC

Scramble Number of colonies 0

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SiTINCR #1 SiTINCR #2 H 4T1 UACC 812 MDA-MB-231

0h 0h NC Scramble

Sh Tincr #1 Sh Tincr Si TINCR #1 24h 24h #1 #1 NC

Si TINCR

0h 0h #2 #2 Sh Tincr #1 #2 Sh Tincr #2 Si TINCR

Si TINCR Si TINCR Sh Tincr #2 Sh Tincr Si TINCR #2 Sh Tincr

24h 24h

*** 800 ** *** 200 400 *** *** ** 600 150 300 400 100 ** *** 200 **** 150 80 ** 100 200 100 50 ** 80 *** 60 0 0 0 100 Cell numbers/well Cell numbers/well Cell numbers/well 60 40 NC NC 40 50 20 20 Scramble Sh Tincr #1Sh Tincr #2 SiTINCR SiTINCR#1 #2 SiTINCR #1SiTINCR #2 0 0 0 Wound healing Wound healing Wound healing Wound percentage%(24h/0h) percentage%(24h/0h) NC percentage%(24h/0h) NC incr #1 incr #2 T Scramble Sh Sh T SiTINCR #1SiTINCR #2 SiTINCR #1SiTINCR #2

Fig. 3 TINCR promotes tumor growth in vivo and in vitro. a Tumorigenesis and tumor tissue of each group of Balb/c mice (n = 6/group). b, c Tumor volume and weight measured in Balb/c mice after injection of 4T1 cells transfected with Tincr-speciﬁc or scrambled-control shRNA. Tumor tissues were measured at the indicated time points and dissected at the endpoint. d–i Knockdown of Tincr/TINCR expression inhibits proliferation (d, e), colony formation (f, g), and migration (h, i) of 4T1, UACC 812, and MDA-MB-231 cells. Scale bar, 100 μm. Data are presented as means from three independent experiments ± S.D. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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Fig. 4 TINCR regulates EGFR expression and downstream signaling in human cancer. a, b TINCR knockdown decreases expression of EGFR mRNA (a) and protein (b) in UACC 812 and MBA-MB-231 cells. c EGFR protein expression is higher in TINCR-high breast-cancer tissues than in TINCR-low tissues and vice versa in 122 patients in the HMUCC cohort. Scale bar, 400 μm. d TINCR knockdown decreases the levels of p-JAK2, STAT3, and p- STAT3 in UACC 812 cells. e JAK2 and STAT3 protein expression is higher in TINCR-high breast-cancer tissues than in TINCR-low tissues and vice versa in 125 patients in the HMUCC cohort. Scale bar, 400 μm. f TINCR knockdown decreases the levels of EGFR, JAK2, p-JAK2, STAT3, and p-STAT3 in vivo

(n = 6/group). g Geﬁtinib IC50 analysis after Tincr knockdown. h Tumorigenesis and tumor tissue of each group of Balb/c mice (n = 6/group). i, j Tumor growth and weight measured in Balb/c mice in each group. Tumors were measured at the indicated time points and dissected at the endpoint. Data are presented as means from three independent experiments ± S.D. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

Ofﬁcial journal of the Cell Death Differentiation Association age al. et Wang Of i.5 Fig. ﬁ iljunlo h elDahDfeetainAssociation Differentiation Death Cell the of journal cial Selgn nnx page.) next on legend (See miR-503-5p mimic miR-503-5p inhibitor Relative EGFR expression 0 1 2 3 4 elDahadDisease and Death Cell DE AB G F

hsa-miR-503-5p NC MDA-MB-231 hsa-miR-503-5p *** Relative GAPDH expression Relative U1 expression Relative TINCR expression TINCR mut *** 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 TINCR WT EGFR mut EGFR WT miR-503-5p mimic UACC812 **** **** miR-503-5p inhibitor ****

NC UACC812 ’3’ 5’ 3’ 5’ 3’ 5’ ’3’ 5’ 3’ 5’ 3’ 5’ ****** **** T47D **** GACGUCUUGACAAGGGCGACGAU * CGGACGAGG UUGACAAGG CGGACGAGG Position chr7:55274319-55274324 AGACUACAAAAAUGAA AGACUACAAAAAUGAAGCUGCUC Position chr19:5567847-5567864 * *** miR-503-5p mimic MCF7 ****

MDA-MB-468 ** miR-503-5p inhibitor Relative TINCR expression (2021)12:83 0.0 0.5 1.0 1.5 2.0 2.5

NC MDA-MB-231 ..... **** *** *** GCGACGA AT AGTAG CGCUGCU ..... MDA-MB-231 ** .....

..... ** ...... miR-503-5p mimic **** ..... miR-503-5p inhibitor MDA-MB-453 **** Cytoplasm Nucleus ..... ** ..... GCTACCGC GCTACCGC GCTACCGC UACC812

T AGTAG ..... NC

..... *** **** ..... **** ..... *** C ** miR-503-5p inhibitor C miR-503-5p mimic

miR-125b-1-3p Relative expression MDA-MB-231 UACC812

Relative luciferase activity 0 2 4 6 0.0 0.5 1.0 1.5 GAPDH EGFR p-EGFR GAPDH EGFR p-EGFR Si TINCR MiR-503-5pMiR mimic NC miR-129-2-3p RNA22 H 630 TINCR pmirGLO NC

miR-149-5p NC SiTINCR#1#2 traeTargetScan StarBase + _ _ _ 1.0 1.0 1.0 1.0 *** 22 684 miR-212-3p MiR-503-5pMiR mimic NC 27 TINCR-mut pmirGLO 59 0.3 0.4 0.3 0.5 + _ _ _ * miR-34b-3p * 52

miR-34c-5p * 29 23 102 UACC812 1.0 1.0 1.0 1.0 + _ _ _ * * miR-424-5p 5 0 Relative luciferase activity * 591 * * 3.0 2.9 2.8 2.3 0.0 0.5 1.0 1.5 miR-503-3p + _ _ _

MiR-503-5pMiR mimic NC 2 1

EGFR pmirGLO miR-503-5p 1.0 1.0 1.0 1.0 * * * * HMUCC + _ _ _ * * * * miR-10b-3p 26 *

miR-125b-2-3p MiR-503-5pMiR mimic NC 0.5 0.7 0.5 0.5 + __ _ _ I EGFR-mut pmirGLO

miR-199a-5p 1.2 1.1 1.3 1.3 * * * + + * _ * * * * 38kDa 170kDa 170kDa 38kDa 170kDa 170kDa ae8o 16 of 8 Page Wang et al. Cell Death and Disease (2021) 12:83 Page 9 of 16

(see ﬁgure on previous page) Fig. 5 TINCR promotes EGFR expression by acting as a ceRNA. a Subcellular localization of TINCR in breast-cancer cell lines, assessed using nuclear/cytoplasmic extract isolation assay. b Overlapping miRNAs in transcriptome miRNA sequencing data from HMUCC cohort and TargetScan, RNA22, and starBase databases. Venn diagrams were generated using Venny online software (http://bioinfogp.cnb.csic.es/tools/ venny/). c qRT-PCR examination of the expression of miRNAs in UACC 812 cells transfected with a TINCR-speciﬁc siRNA or scrambled siRNA. d, e Expression of TINCR, EGFR mRNA (d), and EGFR protein (e) in UACC 812 and MDA-MB-231 cells treated with miR-503-5p mimic or inhibitor. f, g Complementarity between miR-503-5p seed sequence and 3ʹ-UTRs of TINCR (f) and EGFR (g) predicted through a computational and bioinformatics-based approach by using TargetScan and StarBase online databases. Watson–Crick complementarity is connected by “|.” Nucleotide-replacement mutations made to the genes are underlined. h, i Luciferase-reporter assay for assessing interactions between miR-503-5p and its binding sites or mutated binding sites in 3ʹ-UTRs of TINCR (h) and EGFR (i) in HEK293T cells. Data are presented as means from three independent experiments ± S.D. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

EGFR protein levels (Fig. 5e). Last, the results of 503-5p was upregulated when DNMT1 expression was luciferase-reporter assays to investigate physical interac- knocked down (Fig. 6e), and the results of ChIP-PCR tions showed that both EGFR and TINCR with their wild- assays indicated DNMT1 enrichment at the miR-503-5p type 3ʹ-UTRs were regulated by miR-503-5p, and that this promoter (Fig. 6f). Notably, RIP-assay results indicated effect could be abolished by mutating their miRNA- markedly higher TINCR enrichment in the DNMT1 binding sites (Fig. 5f–i). These results indicate that EGFR group than the IgG group (Fig. 6g), and DNMT1 and TINCR are bona fide direct targets of miR-503-5p. enrichment at the miR-503-5p promoter was decreased relative to control after knockdown of TINCR (Fig. 6h). TINCR recruits DNMT1 to miR-503-5p locus and suppresses its expression via DNA methylation Identification of positive-feedback loop in As mentioned in the preceding section, TINCR was also STAT3–TINCR–EGFR axis localized in the nucleus (Fig. 5a and Supplementary Fig. To investigate the transcriptional regulation upstream S6), which suggested that TINCR could exert its reg- of TINCR, we used the online database JASPAR (http:// ulatory effect through epigenetic modification of target jaspar.genereg.net/) to search for transcription factors genes, and knockdown of TINCR expression was found to that might potentially be enriched at the promoter of the upregulate miR-503-5p (Fig. 5c). First, TINCR knock- TINCR locus. The analysis yielded putative STAT3- down increased pri-mir-503-5p and pre-mir-503-5p level binding sites in the region upstream of the TSS of relative to control in UACC 812 cells (Fig. 6a). Because TINCR (Fig. 7a). Moreover, there were obvious enrich- DNA methylation is a major epigenetic-modification ment peaks of STAT3 in the promotor region (chr19- mechanism that results in the downregulation of gene 5572112–5573399) of TINCR in HCC70 cells in expression11, we tested whether methylation of the miR- ENCODE database (Fig. 7b). Next, from the CCLE data- 503 locus was regulated through TINCR. Next, we base, TINCR expression was found to be positively cor- obtained information on the region around the tran- related with STAT3 expression in human cancer cells scriptional start site (TSS, −2000 to +200 bases; “−”: (Fig. 7c). Last, STAT3 knockdown decreased the expres- upstream of TSS; “+”: downstream of TSS) by using the sion of TINCR (Fig. 7d), and the results of ChIP-PCR University of California at Santa Cruz (UCSC) database assays indicated that STAT3 was highly enriched at the (http://genome.ucsc.edu/cgi-bin/hgGateway), and we TINCR promoter relative to mock control (Fig. 7e). Col- then located a CpG island in the promoter region of miR- lectively, our results indicate that TINCR stimulates the 503 locus from the public data of the Li Lab (http://www. activation of EGFR and its key downstream-signaling urogene.org/methprimer/index.html) (Fig. 6b). Bisulfite effectors, including STAT3, which, reciprocally, promotes sequencing was performed to investigate the role of the transcriptional expression of TINCR. TINCR in CpG-island methylation in the miR-503 locus. As expected, TINCR knockdown led to a decrease in miR- Discussion 503-5p CpG-island methylation at positions LncRNAs have been found to be associated with ChrX.133680280 and ChrX.133680391 (Supplementary tumorigenesis and drug resistance in various types of – Table S6), and pri-miR-503-5p, pre-miR-503-5p, and cancer29 33. Identification of novel onco-lncRNAs and miR-503-5p expression was increased following treatment their regulatory mechanisms, and development of novel with the DNA methyltransferase inhibitor decitabine lncRNA-based targeted strategies for combating cancer, (1 μM) (Fig. 6c, d). Because DNMT1 is a maintenance appears promising and may introduce a new paradigm in methyltransferase that preserves the methylation state cancer research. Moreover, EGFR activity has been across mitotic divisions28, we tested whether miR-503-5p reported to be modulated by diverse signaling path- – expression is regulated by DNMT1. Accordingly, miR- ways34 40. However, the comprehensive regulation of

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ABmiR-503-5p C UACC812 MDA-MB-231 UACC812 (TSS,+1) ** 4 6 chrX: CTL **** NC **** **** (-310,+92) **** Decitabine **** Si TINCR #1 CpG island 3 *** level

level 4 Si TINCR #2

gene 2

gene **

2 1 Relative Relative

0 0 Pri-miR-503-5p Pre-miR-503-5p

UACC812 MDA-MB-231 Pri-miR-503-5p Pri-miR-503-5p DE F Pre-miR-503-5p Pre-miR-503-5p ** * ** 4 2.0 **** ** InputIgG DNMT1 3 1.5 miR-503-5p 247bp UACC812 expression ** expression 2 1.0 miR-503-5p 247bp MDA-MB-231 miR-503-5p 1 miR-503-5p 0.5

0 0.0 Relative CTL Decitabine CTL Decitabine Relative NC NC UACC812 MDA-MB-231 G H Si DNMT1Si #1 DNMT1 #2 Si DNMT1Si #1 DNMT1 #2 0.020 ** 15 0.015 *** # # # 10 0.010 % Input % Input 5 0.005

0.000 0

DNMT1 DNMT1 DNMT1 DNMT1 Mock(IgG) Mock(IgG) Mock(IgG) Mock(IgG)

UACC812 MDA-MB-231 NC Si TINCR

Fig. 6 TINCR recruits DNMT1 to miR-503-5p promoter to regulate miR-503-5p gene methylation. a TINCR knockdown increases Pri-MiR-503- 5p and Pre-MiR-503-5p expression in UACC 812 cells. b Schematic representation of predicted CpG island in miR-503-5p locus. CpG island located in the promoter region of miR-503-5p locus around the transcriptional start site (TSS, −310 to +92 bases; “−”: upstream of TSS; “+”: downstream of TSS). c Pri-MiR-503-5p and Pre-MiR-503-5p expression is upregulated in UACC 812 and MDA-MB-231 cells treated with decitabine (1 μM) for 10 h. d MiR- 503-5p expression is upregulated in UACC-812 and MDA-MB-231 cells treated with decitabine (1 μM) for 10 h. e miR-503-5p expression is upregulated in UACC 812 and MDA-MB-231 cells following DNMT1 knockdown. f ChIP assay results indicating that DNMT1 is enriched at miR-503-5p locus CpG islands in UACC 812 and MDA-MB-231 cells. g RIP-assay results showing higher enrichment of TINCR in DNMT1 group than IgG group in UACC 812 and MDA-MB-231 cells. IgG: negative control. h ChIP assay results indicating diminished enrichment of DNMT1 at the promoter of miR- 503-5p locus after TINCR knockdown. Data are presented as means from three independent experiments ± S.D. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001, ###P < 0.001.

EGFR by lncRNAs remains poorly understood. Our study model of the molecular mechanism underlying the dual revealed that TINCR upregulated EGFR expression regulation by TINCR of EGFR and its downstream genes through a ceRNA interaction to trigger enhanced through miR-503-5p. JAK2–STAT3 downstream signaling, and that STAT3, in Generally, lncRNAs interact with chromatin DNA, turn, increased TINCR transcriptional expression. Our RNA, or protein, thereby regulating chromatin accessi- study uncovers a distinctive facet of tumorigenesis by bility, RNA stability, and protein activity or stability in cis- identifying a previously unknown positive-feedback loop or trans-manner41,42. Unlike the classical theory, the in the STAT3–TINCR–EGFR signaling pathway; this identiﬁcation of TINCR ceRNA and RNA–protein- suggests that the feedback loop could represent a new mediated dual regulation in this study reﬂects the therapeutic target in pharmacological strategies developed lncRNA-mediated complex regulation of its target genes. for human cancers. In Fig. 7f, we present a schematic In terms of their regulatory mechanism, lncRNAs

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AC 10 R=0.1067 P=0.0006 5 N=1019 0

Matrix ID Name Score Relative score Start End Predicted sequence -5 MA0144.2 STAT3 7.56 0.89 297 307 CCTCTGGGAAA -10 MA0144.2 STAT3 5.28 0.86 52 62 ATGCCTGTAAT -15 Relative STAT3 expression Relative STAT3 MA0144.2 STAT3 4.33 0.85 2259 2269 GCTCCTGGAAG -5 0 5 10 MA0144.2 STAT3 4.12 0.85 404 414 GTACCTAGAAG Relative TINCR expression MA0144.2 STAT3 4.01 0.85 1431 1441 GTGCTGGGATT D MA0144.2 STAT3 2.91 0.83 1749 1759 GTCCTTAAAAA **** 1.4 MA0144.2 STAT3 2.36 0.83 363 373 GTCATGAGAAA 1.2 **** MA0144.2 STAT3 2.06 0.82 1439 1449 ATTCCAGGCAT 1.0 MA0144.2 STAT3 1.89 0.82 13 23 CTACTAAAAAT 0.8 0.05 MA0144.2 STAT3 0.92 0.81 69 79 TACTCGGGAAG 0.04 0.03 0.02 0.01 0.00 Relative TINCR expression B refGene TINCR NC Si STAT3 #1 Si STAT3 #2 Ruler p13.3 chr19 5570K 5580K E 8 * * Primer #1 0.7 * chr19:5572112-5573399 Primer #2 6 * Primer #3 84620_HCC70_STAT3 * * * * * Primer #4 4

0.0 % Input 0.27 2 NS NS NS 84621_HCC70_STAT3 NS 0

0.00 STAT3 STAT3 STAT3 STAT3 STAT3 STAT3 STAT3 STAT3 Mock(IgG) Mock(IgG)

NC Si STAT3 #1 F

P P Cytoplasm P P

JAK2 EGFR mRNA P miR-503-5p

STAT3 P TINCR

1 Activation Inhibition

P Phosphorylation STAT3 TINCR DNMT1 P TINCR EGFR TINCR 2 miR-503

Pri-miRNA Pre-miRNA Nucleus

Fig. 7 (See legend on next page.)

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(see figure on previous page) Fig. 7 Identification of the positive-feedback loop in STAT3–TINCR–EGFR signaling axis. a Upper corner of picture: STAT3-binding motif; lower table: prediction of STAT3-binding sites within TINCR promoter region, from JASPAR database. b Enrichment peak of STAT3 in the promoter of TINCR in ChIP-seq of HCC70 cells in ENCODE database. c TINCR expression is positively correlated with STAT3 mRNA expression in 1019 cancer cell lines in CCLE cohort. d STAT3 knockdown decreases TINCR expression in MBA-MB-231 cells. e ChIP assay results indicating STAT3 enrichment at TINCR promoter and diminished STAT3 enrichment at the promoter after STAT3 knockdown. f Molecular mechanism of dual regulation by TINCR of EGFR and its downstream genes. Data are presented as means from three independent experiments ± S.D. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. localized in the cytoplasm have been widely reported to broadinstitute.org/ccle/about), and Gene Expression potentially compete for miRNA-response elements Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). All (MREs) with target genes closely related to cancer transcripts were normalized by the log2 method. Wil- occurrence and development by acting as ceRNAs; this coxon rank-sum statistical analysis was used to detect would weaken the inhibitory effect of miRNAs on target significant differences among tumors or between tumor genes and indirectly regulate the expression levels of the and normal samples. The correlations between genes were – target genes43 46. Our study suggests that TINCR func- assessed by Spearman’s correlation coefficients. To cal- tions as a ceRNA to upregulate EGFR expression by acting culate Spearman’s correlation coefficient, we rank and as a sponge for miR-503-5p. Conversely, lncRNAs loca- compare data sets to find Σd2, then plug the value into the lized in the nucleus can regulate gene expression by acting standard version of Spearman’s rank- correlation coeffi- as epigenetic modulators47,48. However, no previous study cient formula according to previous study49 Guilt-by- has reported lncRNA regulation of miRNAs through the association analysis was performed to identify coding modification of methylation. We have shown here for the genes that were positively or negatively correlated with first time that TINCR can recruit DNMT1 to the miR- TINCR expression. JASPAR (http://jaspar.genereg.net/) 503-5p promoter to regulate miR-503-5p locus methyla- was used to examine the transcription factors that might tion and thus transcription. Thus, this study fills in the potentially be enriched at the TINCR locus promoter. theoretical gap in the lncRNA- regulation model and Correlations between TINCR and EGFR/JAK2 mRNA provides a comprehensive understanding regarding the levels were assessed using Pearson correlation coeffi- above-mentioned dual-regulatory network in human cients. Unpaired Student’s t tests were used to detect breast cancer. significant differences among tumors or between tumor In conclusion, this study has revealed that TINCR and normal samples. Survival was calculated by the promotes tumorigenesis through a STAT3–TINCR– Kaplan–Meier method, with the log-rank test applied for EGFR-feedback loop by recruiting DNMT1 and acting as comparison. Overall survival (OS) was calculated as the a ceRNA in human breast cancer. We have demonstrated time from surgery until death; disease-free survival (DFS) for the first time that TINCR upregulates EGFR expres- was measured as the time for which patients were disease- sion by means of a dual molecular mechanism through free, and distant metastasis-free survival (DMFS) was the aforementioned RNA–protein and RNA–RNA inter- calculated as the survival time specifically free of distant actions to suppress miR-503-5p expression. These find- metastasis. The log-rank test was used to examine the ings broaden the ceRNA landscape of TINCR and survival difference between distinct patient groups. All enhance our understanding of the complex regulatory statistical tests were two-sided, and P < 0.05 was con- network through which lncRNAs influence their target sidered statistically significant. Gene ontology (GO)-term genes. Moreover, the study has uncovered a previously enrichment and Kyoto Encyclopedia of Genes and Gen- unrecognized positive-feedback loop in the STAT3– omes (KEGG) pathway analyses of these genes were TINCR–EGFR signaling axis in tumorigenesis, and this performed using DAVID as previously described50,51 feedback loop could thus represent a new target in pharmacological strategies for treating human breast Breast-tissue specimens and clinical assessments cancer. Eligible patients with a histological diagnosis of breast cancer who had received neither chemotherapy nor Materials and methods radiotherapy before surgical resection were recruited to Public data access and analysis this study. Informed consent was obtained from all Genome-wide expression profiles of TINCR and clinical patients. In total, 125 breast-cancer tissues and 125 nor- pathology information were downloaded from the data- mal tissues were obtained from Harbin Medical Uni- bases of The Cancer Genome Atlas (TCGA) (https://tcga- versity Cancer Center (HMUCC). For RNA extraction, data.nci.nih.gov/), Gene Expression Profiling Interactive fresh tissue was collected from patients with breast cancer Analysis (GEPIA) (http://gepia.cancer-pku.cn/), Cancer and normal controls and stored at −80 °C immediately Cell Line Encyclopedia (CCLE) (https://portals. after resection. Two independent senior pathologists

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confirmed the pathological diagnosis and molecular sub- FBS for 14 days. Colonies were fixed with 4% methanol for type of each cancer tissue. This study conformed to the 30 min, and 500 μL of 0.5% crystal violet (Catalog #: 332488, clinical research guidelines and was approved by the Sigma-Aldrich,St.Louis,MO,USA)wasaddedtoeachwell research ethics committee of Harbin Medical University for 30 min to visualize the colonies for counting. Cancer Hospital. We obtained written informed consent from all patients. Invasion assays Cells in serum-free RPMI-1640 or DMEM medium were ® Cell culture, plasmid construction, and transfection placed in the BRAND Insert with Matrigel (Catalog #: Breast-cancer cell lines (UACC-812, MDA-MB-231, and BR782806, Sigma-Aldrich, USA). RPMI-1640 or DMEM 4T1) were obtained from the Chinese Academy of Sciences medium containing 10% FBS was added to the lower Cell Bank and Cellbio (China) and cultured and stored chamber. After incubating at 37 °C for 24 h, the noninvad- according to their instructions. Mycoplasma testing was ing cells that remained in the top chamber were removed performed before the experiments. For transfection, cells with a cotton swab, and the cells that had migrated to the were seeded in six-well dishes the night before to obtain underside of the membrane were fixed with 100% methanol 60–70% confluence for plasmid transfection and 80% con- for 30 min, air-dried, stained with 0.5% crystal violet, fluence for microRNA (miRNA) or siRNA transfection; on imaged, and counted under a light microscope. the following day, cells were transfected using Lipofecta- mine 2000 (Invitrogen), according to the manufacturer’s Wound-healing assay instructions. At 48 h post transfection, cells were harvested Cells were plated in six-well culture plates and culti- for quantitative reverse-transcription-PCR (qRT-PCR) vated to achieve over 90% confluence in RPMI-1640 or analysis. For lentiviral transduction, lentiviruses were used DMEM medium containing 5% FBS. A vertical wound per to infect 5 × 105 cells seeded in six-well plates by using well was created using a 10-µL pipette tip. After two 4–6 μg/mL polybrene (107689, Sigma-Aldrich), after which washes with PBS to eliminate cell debris, the cells were the infected cells were selected using 1 μg/mL puromycin reincubated in RPMI-1640 or DMEM medium containing (Catalog Number 540411, Calbiochem, USA). Stable 0.1% FBS. Images were captured at the indicated time to knockdown cell lines were identified using qRT-PCR. measure the size of the remaining wound. qRT-PCR Western blotting The total RNA was isolated from cells and tissue sam- Cells were lysed in lysis buffer containing 150 mmol/L ples by using Trizol reagent (Invitrogen) according to the NaCl, 1% Triton X-100, 5 mmol/L EDTA, 5000 U/mL manufacturer’s protocols, and 0.5 μg of the RNA was aprotinin, 20 mg/mL leupeptin, 1 mmol/L phe- reverse-transcribed into cDNA by using a High-Capacity nylmethylsulfonylfluoride, 2 mmol/L sodium orthovana- cDNA Reverse Transcription Kit (Applied Biosystems, date, 50 mmol/L NaF, 5% glycerol, 10 mmol/L Tris-HCl USA). The SYBR Green PCR Master Mix Kit (Applied (pH 7.4), and 2% SDS. Next, protein concentrations were Biosystems) was used to quantify RNA levels, with measured using a protein assay kit (Catalog #: 5000001, GAPDH or U6 serving as an internal control. qRT-PCR Bio-Rad, Richmond, CA), and then equal amounts of was performed on a 7500 FAST Real-Time PCR System protein were separated using SDS-PAGE and electro- (Applied Biosystems). blotted onto nitrocellulose membranes, which were blocked (overnight at 4 °C) with 5% nonfat milk in 0.1% Cell-viability assays Tween-20/TBST. The membranes were immunoblotted The viability of treated cells was quantified using the with primary antibodies from Cell Signaling Technology Cell Counting Kit-8 (CCK-8, Dojindo Laboratories, (CST) against EGFR (#2085), p-EGFR (#11862), JAK2 Kumamoto, Japan) assay, according to the manufacturer’s (Catalog #: 3230), p-JAK2 (Catalog #: 3771), STAT3 instructions. Briefly, cells were seeded in 96-well micro- (Catalog #: 9139), and p-STAT3 (Catalog #: 9145), washed titer plates at a density of 3–5×103 cells/well with 100 μL with Tween-20/PBS, and incubated with horseradish of the medium, CCK-8 solution was added to each well, peroxidase-conjugated secondary antibodies for 1 h. After and the plates were incubated at 37 °C for 60 min. Next, washing with Tween-20/PBS, protein bands on the the 450-nm absorbance of each cell suspension was membranes were visualized using an enhanced chemilu- measured using a microplate reader, with a medium minescence detection system (Western Lightning, Perkin- containing 10% CCK-8 serving as a control. Elmer, Norwalk, CT, USA).

Colony-formation assays Animal experiments In total, 1000× cells were plated in a six-well plate and Animal experiments were approved by the Medical cultured in RPMI-1640 or DMEM medium containing 10% Experimental Animal Care Commission of Harbin

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Medical University. Six-to-eight-week female Balb/c mice Bisulfite-sequencing PCR (BSP) were obtained from Beijing Vital River Laboratory Animal To measure the methylation levels on the miR-503 Technology Company. Approximately 5 × 104 cells locus promoter, BSP was conducted as described in our transfected with 4T1-Scramble or 4T1-Sh Tincr shRNA previous study53. Briefly, online tools were used to analyze were suspended in 200 μL of serum-free medium and the CpG islands in the miR-503 locus promoter, and CpG injected directly into the right mammary fat pad. Gefitinib sites at the 5ʹ end of the promoter, within the sequence (Catalog #: S1025, Selleck) was administered orally for ranging from nucleotide −310 to 92, were selected for 7 days at a dose of 50 mg/kg52. Tumor growth was mea- BSP analysis. Genomic DNA was isolated and modified sured using calipers once every 3 days, and tumor volume with bisulfite, and the bisulfite-treated DNA was PCR- was calculated as tumor volume = 1/2 (length × width2). amplified. Subsequently, the PCR products were separated After the mice were euthanized at the endpoint, the on gels, and the bands of the correct size were excised, tumors induced by the injections were dissected out and and the PCR products were purified and subcloned into weighed. pTG19-T vector; positive clones were obtained through ampicillin antibiotic selection, and ten positive clones Immunohistochemistry were subject to DNA sequencing at Generay Biotech Co., Paraffin-embedded tissue sections of 100 breast-cancer Ltd. (Shanghai, China). tissues were deparaffinized in xylene, rehydrated in a graded series of ethanol solutions, and incubated for Chromatin-immunoprecipitation (ChIP) assay 20 min in 3% H2O2 to block endogenous peroxidase ChIP assays were performed using a ChIP Assay Kit activity. Next, the sections were heated in target-retrieval (Catalog #: P2078, Beyotime, Shanghai, China), according solution (Dako) for 15 min in a microwave oven (Oriental to the manufacturer’s protocol with slight modifications. Rotor) for antigen retrieval. After blocking nonspecific Cells were cross-linked for 10 min with 1% formaldehyde, binding by incubating sections with 10% goat serum for and after terminating the reaction by adding 0.125 mol/L 2 h at room temperature, the sections were incubated glycine (final concentration), sonicated cell lysates were overnight at 4 °C with anti-EGFR, anti-JAK2, or anti- prepared, and DNA was immunoprecipitated using an STAT3 primary antibody. Subsequently, sections were anti-STAT3 antibody (Catalog #: 9139, CST) or anti- incubated with an appropriate secondary antibody for DNMT1 antibody (Catalog #: GTX116011, GeneTex); 20 min at 37 °C, and binding was visualized using 3,3’- IgG (BD Biosciences, San Diego, CA, USA) served as the diaminobenzidine tetrahydrochloride. After each treat- negative control. PCR was performed on the immuno- ment, sections were washed thrice with TBST for 5 min. precipitated DNA to amplify the binding sites, and the amplified fragments were analyzed on agarose gels. RNA-FISH assay Chromatin (10%) from before the immunoprecipitation ® ViewRNA Probe (Catalogue Number VA1-3016120, was used as the input control. Santa Clara) was purchased to perform FISH assay according to the manufacturer’s protocol. TINCR hybri- Dual-luciferase-reporter assay dization was carried out in a moist chamber. After The full-length 3ʹ-untranslated regions (UTRs) of digestion with a working protease solution, slides were human TINCR and EGFR were PCR-amplified and the incubated with RNase III (AM2290, Life Technologies, fragments were cloned separately into the multiple- USA) or RNase A (AM2272, Life Technologies) for 2 h. cloning sites in psi-CHECK-2 luciferase miRNA- Standard immunofluorescence and imaging was per- expression reporter vector. HEK293T cells (plated at formed by confocal microscopy. ~40–50% confluence) were used for the dual-luciferase- reporter assays, and Lipofectamine 2000 (Catalog #: RNA-immunoprecipitation (RIP) assay 11668500, Invitrogen) was used to transfect the cells with RIP was performed using a Magna RNA-binding pro- 20 μmol/L hsa-miR-503-5p mimic or negative-control tein immunoprecipitation kit (Catalog #: 17-700 Milli- (NC) mimic and 0.5 mg of the plasmid. Luciferase activ- pore, Bedford, MA, USA), according to the ities were measured at 48 h post transfection by using a manufacturer’s instructions. Briefly, cell lysates were dual-luciferase-reporter assay kit (Catalog #: E1910, Pro- incubated with RIP buffer containing magnetic beads mega, USA) and a luminometer (GloMaxTM 20/20, conjugated with negative-control normal mouse IgG or Promega, USA). human anti-DNMT1 antibody. The samples were then incubated with Proteinase K to isolate the immunopre- Statistical analyses cipitated RNA. Last, the purified RNAs were extracted The expression of each lncRNA was dichotomized by and analyzed using real-time PCR to confirm the presence using the median expression as the cutoff to define high of the binding targets. values (at or above the median) versus low values (below

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the median). The differences in the results of the in vitro 12. Shao, Y. et al. Low expression of lncRNA-HMlincRNA717 in human gastric and in vivo experiments between groups were analyzed cancer and its clinical significances. Tumour Biol. 35, 9591–9595 (2014). ’ t ’ fi 13. Zoi, I., Karamouzis, M. V., Adamopoulos, C. & Papavassiliou, A. G. RANKL sig- using Student s test. Spearman s correlation coef cients naling and ErbB receptors in breast carcinogenesis. Trends Mol. Med. 22, were calculated for correlation analyses. All experiments 839–850 (2016). were performed independently in triplicate. All statistical 14. Nicolini, A., Ferrari, P. & Duffy, M. J. Prognostic and predictive biomarkers in P breast cancer: past, present and future. Semin Cancer Biol. 52,56–73 (2018). tests were two-sided, and < 0.05 was considered statis- 15. Salgado, R., Aftimos, P., Sotiriou, C. & Desmedt, C. Evolving paradigms in tically significant. multifocal breast cancer. Semin Cancer Biol. 31,111–118 (2015). 16. Hwang, K. T. et al. Impact of breast cancer subtypes on prognosis of women Acknowledgements with operable invasive breast cancer: a population-based study using SEER This work was supported by funding from the National Natural Science database. Clin. Cancer Res. 25, 1970–1979 (2019). Foundation of China (Grant numbers 81972706, 81602323, and 81872149), 17. Hynes,N.E.ErbB2:fromanEGFRrelative to a central target for cancer therapy. Project Nn10 of Harbin Medical University Cancer Hospital (Grant number Cancer Res. 76, 3659–3662 (2016). Nn102017-02), Outstanding Youth Project of Heilongjiang Provincial Natural 18. Wang,Y.,Chen,W.,Chen,J.,Pan,Q.&Pan,J.LncRNAexpressionprofiles of Science Foundation (Grant number YQ2019H027), Wu Lien-teh Science EGFR exon 19 deletions in lung adenocarcinoma ascertained by using Foundation of Harbin Medical University (Grant number WLD-QN1706), microarray analysis. Med. Oncol. 31, 137 (2014). 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