Overexpression of Malat1 drives metastasis through inflammatory reprogramming of the tumor microenvironment

Abstract

Expression of the long noncoding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) correlates with tumor progression and metastasis in many tumor types. However, the impact and mechanism of action by which MALAT1 promotes metastatic disease remain elusive. Here, we used CRISPR activation (CRISPRa) to overexpress MALAT1/Malat1 in patient-derived lung adenocarcinoma (LUAD) cell lines and in the autochthonous K-ras/p53 LUAD mouse model. Malat1 overexpression was sufficient to promote the progression of LUAD to metastatic disease in mice. Overexpression of MALAT1/Malat1 enhanced cell mobility and promoted the recruitment of protumorigenic macrophages to the tumor microenvironment through paracrine secretion of CCL2/Ccl2. Ccl2 up-regulation was the result of increased global chromatin accessibility upon Malat1 overexpression. Macrophage depletion and Ccl2 blockade counteracted the effects of Malat1 overexpression. These data demonstrate that a single lncRNA can drive LUAD metastasis through reprogramming of the tumor microenvironment.

Figure 1.. High MALAT1 levels predict poor patient prognosis and increase cell mobility.

(A) RNAScope images of MALAT1 RNA in normal and tumor tissue from lung cancer patients TMA; arrowheads, alveoli; arrow bronchiole; T, tumor; (B) MALAT1 RNA levels in normal (N=156) and tumor tissue (N=161) (unpaired t-test,); (C) Kaplan–Meier survival curves. Patients were stratified in two groups according to MALAT1 signal (Low MALAT1, bottom tertile, N=56, High MALAT1, top two tertiles, N=105; log-rank test, P=0.0206); (D) in vitro CRISPRa construct; (E) MALAT1 RNA levels relative to GAPDH in H23C and H2122C cells expressing Con, hA1, and hA2 MALAT1-specific CRISPRa; (F) Growth analysis of cells in (E); (G) Boyden chamber transwell migration assay images of H23C cells in (E); (H) Quantification of images in (G); (I) in vitro CRISPRi construct; (J) MALAT1 RNA levels relative to GAPDH in H2009C cells expressing Con, hI1, and hI2 MALAT1-specific CRISPRi; (K) Growth analysis of cells in (J); (L) Quantification of migrated cells in Boyden chamber transwell migration assay; (M) MALAT1 ENE domain indicating the PAM site for CRISPR mutagenesis (orange) and non-degrading ASO (green); (N, O) MALAT1 levels relative to GAPDH in indicated gRNA- or ASO-treated cells; (P, Q) Images and quantification of migrated cells in Boyden chamber transwell migration assay of cells in (N, O). (D-Q) Graphs show individual data points and mean±SD of N≥3 independent experiments; ratio paired t-test (E, J, N, O) and unpaired t-test (F, H, K, L, P, Q) comparing experimental (hA1 and hA2) to control (Con) samples.

Figure 2.. Malat1 overexpression in KP LUAD model cooperates with p53 loss to promote tumor progression.

(A) KP LUAD model; (B) RNAScope images of Malat1 levels in KP tumors at indicated time-points pti; (C) Quantification of images in (B) (8 weeks pti, N=15; 12 weeks pti, N=33; 16 weeks pti, N=52; 19 weeks pti, N=47 tumors), unpaired t-tests compare late (12, 16, and 19 wks pti) to early (8wks pti) timepoint; (D) Tumor-specific Malat1 CRISPRa in KPC/KC LUAD models; (E, F) RNAScope images (E) and quantification (F) of Malat1 RNA levels in tumors from indicated KPC (top) and KC (bottom) mice (N≥50 tumors per group); (G) H&E and Mason Trichrome staining of consecutive lung sections of indicated KPC mice analyzed at 16 weeks pti; (H) Quantification of relative tumor burden of mice in (G) (KPC: Con, N=8; mA1, N=9; mA2, N=8 mice); (I) Quantification of tumor grade of mice in (G) (KPC; Con, N=151; mA1, N=227; mA2, N=189 tumors); (J, K) Quantification of pHH3- and Ki67-positive cells from immunostaining in tumors from indicated mice (pHH3: Con, N=18; mA1, N=17; mA2, N=16 tumors; Ki67: Con, N=27; mA1, N=119; mA2, N=74 tumors); (L) H&E staining of lung sections of indicated KC mice analyzed at 16 weeks pti ; (M) Quantification of relative tumor burden of mice in (L) (KC: Con, N=10; mA1, N=12; mA2, N=8 mice); (N) Quantification of tumor grade of mice in (L) (KC: Con, N=715; mA1, N=451; mA2, N=401 tumors); (B, E, G, L) Scale bar as indicated; (F, H, J, K, M) Graphs show individual data points and mean±SD of indicated numbers of biological replicates; unpaired t-tests compare experimental (mA1 and mA2) to control (Con) group.

Figure 3.. Malat1 overexpression enables LUAD metastasis.

(A) Representative H&E and GFP immunostaining images of consecutive sections of liver and lymph node (LN) metastasis (Met) in mA1 KPC animals; (B) Fraction of cohort with no metastases, local only, or local and distal metastases (N=8–10 mice per group); (C) Survival curves (N=10 mice per group, log-rank test); (D) Hmga2 immunostaining in indicated KPC/KC mice; (E) Quantification of the fraction of Hmga2-positive tumors in indicated KPC/KC mice (KPC: Con, N=17, mA1, N=32, mA2, N=20 tumors; KC: Con, N=50, mA1, N=50, mA2, N=57 tumors). (A, D) Scale bars as indicated.

Figure 4.. Malat1 overexpression downregulates epithelial gene expression programs in LUAD.

(A) PCA of RNA sequencing data (KPC: Con, N=3; mA1, N=3); (B) GSEA in PC1 genes; -log10(padj); (C, D) Scatter plot of DEGs determined from exonic (C) and intronic (D) read coverage (purple, upregulated, blue, downregulated, |log2FC|>1, adjusted p<0.05); (E, F) Enrichment of GO genesets in downregulated genes from (C, D); (G) Cumulative frequency distribution plots of indicated genesets relative to matched controls; (H) GSEA of indicated geneset; (I) Quantification of Cdh1 immunostaining (KPC: Con, N=31, mA1, N=64, mA2, N=85 tumors). Graph show individual data points and mean±SD of indicated number of biological replicates, unpaired t-tests compare experimental (mA1 and mA2) to control (Con) group.

Figure 5.. Malat1 overexpression promotes the recruitment of pro-tumor M2 macrophages.

(A) Immunostaining for Cd68 (total), Cd206 (M2-specific), and iNos (M1-specific) macrophage markers in consecutive lung sections from indicated KPC mice at 16 weeks pti; (B) Quantification of Cd68-positive cells from images in (A) (KPC: Con, N=36, mA1, N=60, mA2, N=35 tumors, unpaired t-tests compare experimental (mA1 and mA2) to control (Con) group); (C) Quantification of Cd68-negative and -positive tumors at early (8–12 weeks) and late (16–20 weeks) pti in indicated mice (KC: N=16–27 tumors, KPC: N=60–136 tumors from 3–4 mice per condition); (D) Timeline of macrophage depletion experiment; (E) Cd68 immunostaining, H&E and Trichrome staining of consecutive lung sections of mice treated in (D) (KPC mA1: Control; N=2; Depletion: N=2 mice); (F) Validation of macrophage depletion by quantification of the fraction of Cd68-negative (Cd68-) and -positive (Cd68+) tumors from images in (E) (KPC mA1: Control: N=94; Depletion: N=52 tumors)); (G, H) Quantification of tumor burden of mice in (E) and tumor grade of tumors in (F).

Figure 6.. MALAT1 overexpression promotes cell mobility through a CCL2-dependent paracrine mechanism.

(A, B) Quantification of migrated cells (A) and wound healing (B) of H23 and cancer-associated fibroblasts (CAFs) treated with CM collected from indicated H23C cells; (C) CCL2 protein levels by proteome profiling of CM; (D) CCL2 RNA levels relative to GAPDH in indicated H23C cells; (E, F) Boyden chamber transwell migration assay images of H23 cells (E) and CAFs (F) incubated with CM from indicated H23C cells in the absence (IgG) or presence of CCL-neutralizing antibody (αCCL2); (G, H) Quantification of migrated cells from images in (E, F); (I, J) Quantification of wound healing of cells and treatments in (E, F); (K) Growth analysis of cells in (E). (A-K) Graphs show individual data points and mean±SD of N=3 independent experiments; (A, B, G, H, I, J, K) Unpaired t-tests and (D) ratio paired t-test compare experimental (hA1 and hA2) to control (Con) samples.

Figure 7.. Ccl2 signaling mediates macrophages recruitment and tumor progression in Malat1-overexpressing tumors.

(A) Left Ccl2 RNA levels relative to Gapdh, Right Ccl2 protein levels detected by ELISA in CM from indicated KPC cells. Graphs show individual data points and mean±SD of N=3 biological replicates, ratio paired t-test; (B) Read coverage of Ccl2 gene from RNA-seq data; (C) Timeline of Ccl2 blockade experiment; (D) RH&E and Cd68 immunostaining images of consecutive lung sections (KPC: Con+IgG, N=5, mA1+IgG, N=5, Con+α-Ccl2, N=8, mA1+α-Ccl2, N=5 mice); (E-G) Quantification of Cd68-positive cells (E), tumor burden (F), and tumor grade (G) from images in (D) (KPC: Con+IgG, N=50, mA1+IgG, N=60, Con+ α-Ccl2, N=70, mA1+ α-Ccl2, N=50 tumors); (E, F) Graphs show individual data points and mean±SD of biological replicates, unpaired t-tests compare α-Ccl2- to IgG-treated groups.

Figure 8.. Malat1 overexpression increases chromatin accessibility of PRC2 target genes, including Ccl2.

(A) Malat1 smRNA-FISH in indicated KPC cells, red, DAPI, blue; (B) Butterfly plot of peaks with differential chromatin accessibility (log2FC) in ATAC-seq analysis, pink, significant peaks (FDR<0.05) (KPC: Con, N=2, mA1, N=2); (C) GSEA of genes ranked based on differential accessibility in analysis in (B); (D) ATAC-seq read coverage of indicated loci; (E) Fold change of normalized total counts from data in (B) within promoter and gene body of genes depicted in (D); (F) Ezh2 and Ccl2 levels relative to Gapdh in indicated KP cells; Graphs show individual data points and mean±SD of N=3 independent experiments; Ratio paired t-test; (G) Enrichment of PRC2 targets geneset in analysis in (C); (H, I) GSEA of genes ranked based on strength of Spearman correlation between CCL2 expression and gene expression in TCGA Firehose Legacy LUAD RNAseq dataset (N=230 samples).