Elucidating the earliest pathogenic steps in cancer development is fundamental to improving its early detection and prevention. Ovarian high-grade serous carcinoma (HGSC), a highly aggressive cancer, mostly originates from the fallopian tube epithelium through a precursor stage, serous tubal intraepithelial carcinoma (STIC). In this study, we performed spatial transcriptomic analysis to compare STICs, carcinoma, and their matched normal fallopian tube epithelium. Several differentially expressed genes in STICs and carcinomas were involved in cancer metabolism and detected in a larger independent transcriptomic dataset of ovarian HGSCs. Among these, insulin-like growth factor binding protein-2 (IGFBP2) was found to undergo DNA hypomethylation and to be increased at the protein level in STICs. Pyrosequencing revealed an association of IGFBP2 expression with the methylation state of its proximal enhancer, and 5-azacytidine treatment increased IGFBP2 expression. In postmenopausal fallopian tubes, where most STICs are detected, IGFBP2 immunoreactivity was detected in all 38 proliferatively active STICs but was undetectable in morphologically normal tubal epithelia, including those with TP53 mutations. In premenopausal fallopian tubes, IGFBP2 expression was limited to the secretory epithelium at the proliferative phase, and estradiol treatment increased IGFBP2 expression levels. IGFBP2 knockdown suppressed the growth of IGFBP2-expressing tubal epithelial cells via inactivation of the AKT pathway. Taken together, demethylation of the proximal enhancer of IGFBP2 drives tumor development by maintaining the increased IGFBP2 required for proliferation in an otherwise estrogen-deprived, proliferation-quiescent, and postmenopausal tubal microenvironment.

Significance:

Molecular studies of the earliest precursor lesions of ovarian cancer reveal a role of IGFBP2 in propelling tumor initiation, providing new insights into ovarian cancer development.

Elucidating pathogenic steps in early cancer development is fundamental to identifying biomarkers for early detection and to exploring effective strategies for cancer prevention. Both tasks represent an unmet need in those cancers that are usually not amenable to routine screening and primary prevention. Ovarian cancer is one such example—the malignancy is located deep in the pelvis, not readily detected clinically until late-stage disease. Currently, there are few effective approaches for intercepting its progression from a noninvasive precursor stage to an advanced incurable stage.

Ovarian cancer is unique among human cancers because it is unlikely to develop de novo. As supported by a wealth of epidemiologic, clinical, pathologic, and molecular studies, the emerging paradigm in the genesis of high-grade serous carcinoma (HGSC), the most common ovarian cancer, is that HGSC initially arises in fallopian tubes through precursor lesions that then progress to disseminated disease involving adjacent ovaries, peritoneal soft tissues, and lymph nodes (1, 2). TP53 mutation is the earliest known molecular genetic change, and its missense or nonsense mutations occur in almost all precursor lesions and HGSCs (3–5). TP53 mutation is apparently insufficient to drive malignant transformation as evidenced by the presence of a TP53 mutated lesion in the fallopian tube, termed “p53 signature,” containing a minute stretch of clonally derived, morphologically normal-appearing tubal epithelium (about 12 to 50 cells) histologically indistinguishable from the background of TP53 wild-type epithelium. Most of those p53 signature lesions are not proliferative and may remain clinically indolent, most likely representing an evolutionary dead end.

However, some TP53 mutated clones may continue proliferating and accumulate chromosomal alterations and additional sequence mutations, leading to genetic heterogeneity that provides a platform for selection and evolution to HGSC. Those lesions are collectively known as serous tubal intraepithelial carcinoma (STIC) and are histologically characterized by highly atypical cells with enlarged nuclei, mitosis, and apoptosis manifesting as an in situ lesion of HGSC. Because STIC and p53 signatures are minuscule and not grossly visible, these lesions can only be microscopically diagnosed in formalin-fixed, paraffin-embedded (FFPE) tissue sections.

On the basis of a mathematical model and a clinical correlation study, a STIC may take an extended time, often decades, to develop after the first hit, TP53 mutation, but a shorter time to progress (approximately 6–7 years) to HGSC (5, 6). Genetic predisposition including mutations in BRCA1 and BRCA2 accelerates HGSC development. In a multicenter study after extensively examining surgically removed fallopian tubes, STIC and p53 signatures were detected, respectively, in 10% and 27% of fallopian tubes from BRCA1/2 carriers undergoing prophylactic salpingo-oophorectomy (7).

To better understand the mechanisms contributing to tumor initiation in HGSC, researchers have compared molecular alterations among STICs, p53 signatures, and matched normal-appearing fallopian tube epithelium to depict the genetic and epigenetic landscape in tumor initiation (5, 8, 9). Moreover, STIC also expressed several HGSC protein biomarkers (10–16). Despite this progress, the genome-wide transcriptomic alterations in STICs remain elusive, mainly due to challenges in performing transcriptomic assays in such miniscule lesions in FFPE tissues. Here, we report spatial profiles of transcriptomes in STICs, corresponding normal fallopian tube epithelium (NFTE) and stroma, and associated HGSCs. The data reveal the earliest changes in gene expression during the development of HGSC and identify a novel role of insulin-like growth factor binding protein-2 (IGFBP2) in initiating HGSC.

Tissue acquisition and preparation

All FFPE tissues were retrieved from the pathology archival files and the gynecologic tissue repository at the Johns Hopkins Medical Institutions and the Inova Fairfax Hospital, Fairfax, Virginia. This study was conducted in accordance with the ethical guidelines (e.g., Declaration of Helsinki, CIOMS, Belmont Report, U.S. Common Rule) and was approved by the local institutional review board. Informed consent was waived because the archived formalin-fixed and paraffin-embedded tissue sections from paraffin tissue blocks stored in the pathology archive were all anonymous and not associated with personal health information. We used morphologic criteria assisted by IHC to diagnose STICs and p53 signatures as previously reported (3). A total of 76 precursor lesions including 15 p53 signatures and 61 STICs were available for this study. Among them, 59 (77.63%) were incidental findings without concurrent ovarian HGSC. For each lesion, normal-appearing tubal epithelium was available for study. After serial sectioning, 13 STICs with sufficient STIC cells remained and were available for transcriptomic profiling, while the remaining cases were used for IHC. We also included three HGSC tissues (from 2 patients) with concurrent STIC where the HGSC involvement of fallopian tubes was minimal.

Small segments of fallopian tubes from premenopausal women undergoing salpingo-oophorectomy for benign indications were analyzed and the segments were the remaining tissue following routine sampling for pathologic diagnosis. Portions of the tubes were sectioned, opened, and incubated with MEBM (Lonza, CC3153) with/without 50 nmol/L estradiol (E2) overnight. After incubation, the tissue segments were fixed in 10% neutral buffered formalin and embedded in paraffin for IHC. The rest of the fallopian tube was opened and incubated with trypsin at 37°C for 15 minutes followed by neutralization with RPMI1640, 10% FBS. The epithelium was harvested by gently scraping mucosal surface using a cell scraper. The cells were passed through 100-μm cell strainers to remove tissue debris then were suspended in soft gel with or without 50 nmol/L E2 to grow spheroids.

Spatial transcriptomic profiling

The GeoMx Human Whole Transcriptome assay (NanoString, Inc., RRID: SCR_021660) was employed to measure mRNA expression levels on FFPE tissues. This assay was based on using a DNA barcoding technology for mRNA detection via a UV photocleavable linker. Unstained slides (5 μm thick) from 13 STIC lesions, 3 HGSCs, and their matched normal-appearing tubal tissues were used. Individual tissue sections were labeled with a cocktail of probes and 3 fluorescently labeled morphology markers: a pan-cytokeratin antibody with a green fluorescent dye, a p53 antibody with a red fluorescent dye, and DAPI to detect nuclei. Areas of interest (AOI) were selected on the basis of fluorescence imaging. In addition to epithelium, we also selected stroma immediately underlying the lesions for transcriptomic analysis. UV light illuminated each AOI to release the barcodes from that region for subsequent counting, and the barcodes were then mapped back to distinct regions of interest.

We used 3rd quadrant (Q3; NanoString, Inc.) normalization of all raw data because it consistently outperformed other methods, including Negative Probe, which over normalizes small regions, and Housekeeper Normalization, which was susceptible to inconsistency in experiments investigating disparate sample types that often had different expression levels. All data analyses were performed using R software. For each comparison, we first selected genes with at least a 2-fold change in mean expression levels. We performed two-sample t test on log2-transformed gene expression data to select the top genes with the smallest P values. In volcano plots, only genes with P < 0.05 were included. The top upregulated and downregulated genes were indicated by different colors. The heatmap was constructed using log2 transformation of the top 70 genes with the smallest P values.

IHC

IHC was performed using monoclonal antibodies against IGFBP2, p53, and Ki-67 (Supplementary Table S1). Antigen retrieval and immunostaining followed previous reports (17). The staining patterns in both normal-appearing fallopian tube epithelium and precursor lesions including STICs and p53 signatures were recorded. H-score was used to semiquantitatively measure IGFPB2 immunoreactivity in epithelial cells using the formula: H-score = ∑ (intensity score) × (% of lesion cells at a given intensity level) × 100. Intensity was scored as 0, 1, 2, or 3 by two investigators. Rare discrepancies were resolved by review and discussion for a consensus. The p53 staining pattern was interpreted (i) as a missense mutation pattern when intense and diffuse immunoreactivity in epithelial cells was present; (ii) as a null mutation pattern when the signal was virtually undetectable (with a positive internal control); and (iii) as a wild-type pattern when weak focal staining was present. The percentage of Ki-67–positive nuclei was determined among lesions and control epithelium.

Cell culture, drug treatment, and lentivirus transduction

Cell lines were cultured with RPMI1640 (Gibco, 11875093), 10% heat-inactivated FBS (Sigma, F4135), and 1% penicillin–streptomycin (Gibco). All the cell lines were confirmed to be Mycoplasma negative by the universal Mycoplasma Detection Kit (ATCC, 30–1012K). To determine the effect of DNA demethylation on the expression of IGFBP2, we treated fallopian tube epithelial (FTE) cell lines expressing a low level of IGFBP2, including FT194 (RRID: CVCL_A4AW), FT241, and FT2821A (18, 19), with 0.5 μmol/L 5-Azacytidine (5-AZA, Sigma, A2385) for 24 hours. Control cells were left untreated. Both floating and attached cells were collected for RNA and protein expression analysis. To perform immunocytochemistry of IGFBP2 on cell blocks, we harvested cells treated with 0.5 μmol/L 5-AZA for 24 hours. Those cells were fixed with 10% neutral buffered formalin, and the cell pallets were then embedded in paraffin and sectioned onto unstained plus slides for IGFBP2 staining. To assess the effect of E2 on the regulation of IGFBP2 expression, FT194 and FT241 cells were cultured in RPMI1640 medium supplemented with 1% penicillin–streptomycin and 50 nmol/L E2 (Sigma, E2758) for 48 hours.

We knocked down IGFBP2 using Mission Lentiviral Transduction Particles targeting the IGFBP2 coding sequence or Nontarget shRNA lentiviral particles as controls (Sigma). Two sets of IGFBP2 shRNA with target sequences CCAGTTCTGACACACGTATTT and ACAGTGCAAGATGTCTCTGAA were used in this study. Cells with high IGFBP2 expression, including FT2821J (18, 19), OVCAR3 (RRID: CVCL_0465), and PEA2 (RRID: CVCL_2683), were incubated with viral stock supplemented with 8 μg/mL Polybrene (Sigma, H9268) for 24 to 72 hours. For organoid culture, the primary FTE cells were transduced without polybrene supplement for 72 hours. After transduction, cells were harvested using TrypLE Express Enzyme (Gibco, 1264–013) and cultured in VitroGel ORGANOID-1 (TheWell, VHM04–1, see below).

Pyrosequencing

A total of 7 samples including 4 normal fallopian tube tissues, one STIC, and two HGSCs were analyzed by pyrosequencing. After laser capture microdissection, DNA was extracted using QIAamp FFPE DNA Tissue Kit (Qiagen, 56404) followed by bisulfite-conversion using the EZ DNA Methylation-Lightning Kit (Zymo, D5031) according to the manufacturer's instructions. DNA sequence upstream (Chr2: 216631996–216633220, hg38) from the IGFBP2 coding region was obtained from the UCSC genome browser (20). The average methylation of the CpG sites was quantified by pyrosequencing using the PyroMark PCR Kit (Qiagen, 978703) and PyroMark Q96 MD (Qiagen). In brief, PCR products were denatured, washed, and annealed to a sequencing primer. The pyrosequencing reaction started at the 3′-end of the sequencing primer. Each sample well received nucleotides (A, T, G, and C) one at a time. If the added base was complementary to the base in the PCR product, light emission occurred through an enzymatic cascade. The light intensity was recorded and presented graphically in a pyrogram. The performance of each pyrosequencing assay was evaluated using standards consisting of 0% to 100% bisulfite-converted CpG-Methylated HeLa Genomic DNA (New England BioLabs) mixed with bisulfite-converted unmethylated Human Male Genomic DNA (Promega). The same assays were also performed on cell lines to confirm demethylation after 5-AZA treatment. Supplementary Table S2 listed the primers used for pyrosequencing.

Subcutaneous xenograft tumor model

All animal-related procedures were approved by the Johns Hopkins University Animal Care and Use Committee. OVCAR3 and PEA2 cells transduced with lentivirus with shRNA against IGFBP2 or control shRNA (107 cells) were mixed 1:1 with Matrigel (Corning, 356234) and subcutaneously injected into the flank subcutaneous tissues in each of 4- to 6-week-old nu/nu female mice (n = 10, Jackson lab, RRID: IMSR_JAX:002019). The tumor size was measured periodically using calipers. Tumor volume was calculated using the formula: TV = 4/3 π (length/2) (width/2)2.

Statistical analysis

To validate our findings, we compared the current NanoString data with results from previously published data (GSE114493; ref. 21). Post-alignment normalization of the RNA sequencing (RNA-seq) data and differential expression analysis was performed, as previously described (21) using Voom in the limma package from Bioconductor (22, 23). For biological assays, data were presented as mean ± one SE. Unpaired two-tailed Student t test was used to evaluate the statistical significance of the difference between two groups unless otherwise stated. Differences were considered significant for P value < 0.05. Figures and tables were prepared using standard R functions or Prism software.

Data availability

The data generated in this study are available within the article and its Supplementary Data files. The raw data of the spatial transcriptomics were provided by the NanoString bioinformatic team through a service agreement and are available in Supplementary Table S3.

Transcriptomic analysis in the development of HGSCs

This study intended to discover differentially expressed genes in STIC as compared with NFTE. We focused on studying incidental STICs; therefore only a few concurrent HGSCs were available for comparison. GeoMx human whole transcriptome assays were performed on 13 STICs, 3 HGSCs, and 12 samples of adjacent NFTE derived from 7 patients. Stromal components obtained 100 μm directly underneath each epithelial segment of STIC and NFTE were also analyzed. In total, we analyzed 49 AOIs (Fig. 1AE). All AOIs showed a sequencing saturation above the 50% cutoff, which approximated a read depth of 100 reads/μm2, as recommended by the manufacturer (Fig. 1F). To adjust counts among different samples for meaningful comparison, we used Q3 to normalize the raw data (Fig. 1G). In total, we assayed 18,676 genes across the entire set of AOIs with 11,941 genes expressed in 10% of the AOIs and 3,645 genes expressed in 50% of the AOIs (Fig. 1H). In three of those STICs, of which the lesion cells were abundant, we selected two AOIs from different regions in each STIC. Using log2 transformation of gene expression, we computed the ratio of variable (Rvar) for individual genes between the intra-STIC gene expression variance to that of inter-STIC gene expression across all lesions. A ratio Rvar < 1 implies gene expressions across AOIs within the same STIC was closer to each than expressions across different STICs. We have observed Rvar < 1 in 95% (17745/18677), 79% (14827/18677), and 70% (13100/18677) of genes from the three STICs, respectively (Fig.1I). We noted that one STIC lesion had a remarkably high expression level in genes expressing CD45 and CD4 in the STIC-associated stroma. Indeed, review on the hematoxylin and eosin section showed an intense lymphocytic infiltrate underneath the STIC lesion but not in adjacent NFTE from the same patient or in STIC lesions from the remaining cases that had a background level of CD45 expression by NanoString (Fig. 1J). This finding supports the robustness of the transcriptomic profiling technique and analysis.

Figure 1.

Spatial transcriptomic analysis in ovarian cancer precursors. A, A representative image of human fallopian tube stained with p53, pan-cytokeratin, and DAPI. The specimen contains a STIC, which is labeled by red immunofluorescence with an anti-p53 antibody while all epithelial cells are labeled by green immunofluorescence with a pan-cytokeratin antibody. B, The corresponding hematoxylin and eosin staining at the same magnification. C, Image from B of NFTE with hematoxylin and eosin staining under a higher magnification. D, Image from B of STIC with hematoxylin and eosin staining under a higher magnification. E, Examples of STIC and NFTE from cases analyzed. F, Sequencing saturation by AOI. Each dot in the plot represents one sample. Samples were grouped for transcriptomic profiling. G, Data from F normalized to the third quartile (Q3) to account for differences in cellularity, AOI size, etc. H, Percentage of genes detected across 49 AOIs. A total of 18,676 genes were assayed. I, Comparison of intra-STIC and inter-STIC gene expression variances. The x-axis is the number of genes analyzed by NanoString. The y-axis indicates the ratio of the intra-STIC gene expression variance from two different AOIs with the same lesion to the gene expression variance across all lesions (inter-STIC) for individual genes. The horizontal (gray) line indicates the ratio of one. J, Relative CD45 expression in STIC stroma (left). STIC Case 4 shows a high expression level and histologically it contains an increased lymphocyte density in the stroma (top right). In contrast, another STIC, has a very low CD45 level and a background lymphocyte density in stroma (bottom right). Both STICs are associated with concurrent HGSCs.

Figure 1.

Spatial transcriptomic analysis in ovarian cancer precursors. A, A representative image of human fallopian tube stained with p53, pan-cytokeratin, and DAPI. The specimen contains a STIC, which is labeled by red immunofluorescence with an anti-p53 antibody while all epithelial cells are labeled by green immunofluorescence with a pan-cytokeratin antibody. B, The corresponding hematoxylin and eosin staining at the same magnification. C, Image from B of NFTE with hematoxylin and eosin staining under a higher magnification. D, Image from B of STIC with hematoxylin and eosin staining under a higher magnification. E, Examples of STIC and NFTE from cases analyzed. F, Sequencing saturation by AOI. Each dot in the plot represents one sample. Samples were grouped for transcriptomic profiling. G, Data from F normalized to the third quartile (Q3) to account for differences in cellularity, AOI size, etc. H, Percentage of genes detected across 49 AOIs. A total of 18,676 genes were assayed. I, Comparison of intra-STIC and inter-STIC gene expression variances. The x-axis is the number of genes analyzed by NanoString. The y-axis indicates the ratio of the intra-STIC gene expression variance from two different AOIs with the same lesion to the gene expression variance across all lesions (inter-STIC) for individual genes. The horizontal (gray) line indicates the ratio of one. J, Relative CD45 expression in STIC stroma (left). STIC Case 4 shows a high expression level and histologically it contains an increased lymphocyte density in the stroma (top right). In contrast, another STIC, has a very low CD45 level and a background lymphocyte density in stroma (bottom right). Both STICs are associated with concurrent HGSCs.

Close modal

Analyses of the transcriptomic data between STIC and NFTE from the same specimens identified 82 genes showing greater than 2-fold changes in expression levels. Among them, changes in expression of 39 genes were significant (P < 0.01; Fig. 2A and B; Supplementary Table S4). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in the STIC specific genes (as compared with NFTE) shows gene enrichment in several pathways, most notably the PI3K–Akt signaling pathway (Supplementary Fig. S1 and Supplementary Table S5). In comparing stromal components of STIC and NFTE, we identified 60 genes showing greater than 2-fold changes in expression levels. Among these, only 3 genes were significant (P < 0.01; Fig. 2C and D). We also compared STICs with HGSCs and found 1,526 genes with greater than 2-fold changes in expression levels, 1,068 genes with greater than 3-fold changes, and among them 128 genes showed significant changes (P < 0.01; Fig. 2E and F).

Figure 2.

The most differentially expressed genes between tissue groups. Volcano plots and heatmaps showing genes that are either upregulated or downregulated between two groups. A and B, Differentially expressed genes between STICs and NFTE. C and D, Differentially expressed genes in associated stroma between STIC and NFTE samples. E and F, Differentially expressed genes between STICs and HGSC. G and H, Differentially expressed genes between HGSC and NFTE.

Figure 2.

The most differentially expressed genes between tissue groups. Volcano plots and heatmaps showing genes that are either upregulated or downregulated between two groups. A and B, Differentially expressed genes between STICs and NFTE. C and D, Differentially expressed genes in associated stroma between STIC and NFTE samples. E and F, Differentially expressed genes between STICs and HGSC. G and H, Differentially expressed genes between HGSC and NFTE.

Close modal

Because only three concurrent HGSCs were available for NanoString, we used our preexisting RNA-seq data from 96 HGSCs and NFTEs to determine if we could detect differentially expressed genes in STICs and HGSCs from this current study in HGSCs but not in NFTEs from that previous study (21). We found that most (57/76) top candidate genes (Fig. 2G and H) identified here were differentially expressed in the previous dataset along the same trend in HGSC as compared with NFTE (adjusted P < 0.05; Supplementary Fig. S2; ref. 21). On the basis of the lowest P value and availability of antibodies that were suitable for staining FFPE tissues, we chose 4 genes including two upregulated genes (IGFBP2 and PRAME) and two downregulated genes (FGF2 and CRISP3) for IHC validation. Alongside the HGSCs, we intended to determine if changes in expression also occurred in STICs. As expected, our results showed prominent IGFBP2 and PRAME immunoreactivity in representative STICs but not in adjacent NFTE. We also observed FGF2 and CRISP3 staining in NFTE but not in STICs or HGSCs (Supplementary Fig. S3).

Upstream DNA hypomethylation of IGFBP2 in STIC and ovarian cancer

In addition to molecular genetic changes, DNA hypomethylation is another common attribute of developing cancer as tumor cells alter transcriptional activities in several cancer-related genes such as programmed death-ligand 1 (24, 25). Thus, we studied whether the overexpressed genes in STICs and HGSCs were associated with DNA hypomethylation in the upstream regulatory regions of the corresponding genes. On the basis of the MethylationEPIC dataset of methylation profiles in NFTE, STICs, and HGSCs (26), we assessed correlations between DNA methylation and gene expression levels. We used the following criteria to define differentially methylated regions: (i) presence of CpG sites within 1,500 b.p. from the transcription start site; (ii) adjusted P value < 0.05; (iii) NFTE β value > 0.7 or < 0.3; (iv) at least 2 CpG sites fulfilling the above criteria. In total, 10 of the 111 differentially expressed genes identified by transcriptomic analysis fulfilled the criteria, including MEST, PRR9, FGF2, LUC7L3, IGFBP2, PRAME, SEPHS2, PENK, SIGLEC15, and SLC2A7. Figure 3A and B and Supplementary Fig. S4 show the DNA methylation status in the regulatory elements of representative IGFBP2, FGF2, and PRAME. Among these genes, IGFBP2 and PRAME were of particular interest as upregulation of their protein levels were validated in STICs. Because IGFBP2 has been reported to be associated with ovarian cancer metastasis and invasion (27), we further characterized it in this study.

Figure 3.

Hypomethylation of CpG sites upstream of IGFBP2 in precursor lesions is associated with IGFBP2 overexpression. A and B, DNA methylation status of the two CpG sites upstream of IGFBP2 identified by MethylationEPIC array in microdissected NFTE, precursor lesions, and HGSC. Each dot represents one sample. N1, NFTE immediately proximal to STIC; N2, NFTE distal to STIC; N3, NFTE from the contralateral fallopian tube; p53, p53 signature. C, Pyrosequencing analysis showing DNA methylation status upstream of IGFBP2. TSS, transcription starting site. D, Methylation of 40% in total CpG sites is used as a cutoff. White circles, unmethylated cytosines; black circles, methylated cytosines within CpG sites. E, Immunoblots showing IGFBP2 expression levels in cellular extracts of FT194, FT241, and FT2821A cells after treatment with 5-AZA for 24 hours. GAPDH was used as a loading control. F, qRT-PCR of IGFBP2 in FT194 after treatment with 0.5 μmol/L or 1 μmol/L 5-AZA for 24 hours. G, Immunostaining of IGFBP2 in FT194 cells after treatment with 0.5 μmol/L 5-AZA for 24 hours.

Figure 3.

Hypomethylation of CpG sites upstream of IGFBP2 in precursor lesions is associated with IGFBP2 overexpression. A and B, DNA methylation status of the two CpG sites upstream of IGFBP2 identified by MethylationEPIC array in microdissected NFTE, precursor lesions, and HGSC. Each dot represents one sample. N1, NFTE immediately proximal to STIC; N2, NFTE distal to STIC; N3, NFTE from the contralateral fallopian tube; p53, p53 signature. C, Pyrosequencing analysis showing DNA methylation status upstream of IGFBP2. TSS, transcription starting site. D, Methylation of 40% in total CpG sites is used as a cutoff. White circles, unmethylated cytosines; black circles, methylated cytosines within CpG sites. E, Immunoblots showing IGFBP2 expression levels in cellular extracts of FT194, FT241, and FT2821A cells after treatment with 5-AZA for 24 hours. GAPDH was used as a loading control. F, qRT-PCR of IGFBP2 in FT194 after treatment with 0.5 μmol/L or 1 μmol/L 5-AZA for 24 hours. G, Immunostaining of IGFBP2 in FT194 cells after treatment with 0.5 μmol/L 5-AZA for 24 hours.

Close modal

We sought to determine the extent of DNA hypomethylation upstream of IGFBP2 in detail. Laser-microdissection was performed to enrich epithelial cells from one STIC, two HGSCs, and 4 NFTE specimens. IGFBP2 immunostaining was used to specifically locate the areas with high IGFBP2 expression for microdissection. We performed pyrosequencing on the 7 samples following bisulfite conversion and sequenced 11 CpG sites within 679 b.p. upstream of the transcription start site (Chr2: 216632150–216632827, hg38), which overlaps the region identified as proximal enhancers by ENCODE. In accordance with the results of MethylationEPIC array data, the CpG sites within this proximal enhancer region showed significant hypomethylation in STICs and HGSCs compared with NFTE. We also sequenced 19 CpG sites downstream of the transcription start site (including 14 CpG sites within a CpG island, Chr2: 216632828–216633181, hg38, total length 354 base pairs) and these CpG sites resided in regions of promoter-like signature, to rule out the possibility that upregulation of IGFBP2 expression was caused by promoter hypomethylation (28). None of these CpG sites showed significant methylation changes in STICs and HGSCs compared with NFTE (Fig. 3C and D).

To further support that DNA hypomethylation was responsible for transcriptional upregulation, we treated NFTE cell lines (FT194, FT241, FT2821A) having low or undetectable levels of intrinsic IGFBP2 expression with 0.5 μmol/L 5-AZA, and confirmed DNA demethylation by pyrosequencing (Supplementary Fig. S5). Twenty-four hours after the treatment, we conducted semiquantitative RT-PCR, Western blotting, and immunostaining, which showed a significant increase in both mRNA and protein levels of IGFBP2 (Fig. 3EG). These data suggest that DNA hypomethylation in the proximal enhancer was associated with IGFBP2 overexpression.

IGFBP2 expression in fallopian tube tissues, precursors, and HGSCs

To determine the prevalence of IGFBP2 overexpression in tubal lesions and HGSCs, we applied IHC on FFPE tissue sections. A total of 61 STICs, 15 p53 signatures, 30 HGSCs, and 55 normal fallopian tubes were evaluated using the same protocol. The levels of IGFBP2 expression in the lesional tissues were compared with NFTE on the same sections if present. We also stained sections with p53 and Ki-67 antibodies to help locate tubal lesions and assess their proliferative activity. Proliferatively active STICs (hereinafter “active STIC”) were those with a Ki-67 labeling index at least 5 times greater than that in surrounding normal epithelium. Those STICs showing proliferative activity that was similar to the surrounding normal epithelial level of Ki-67 labeling index were termed proliferatively dormant STICs (hereinafter “dormant STIC”) or serous tubal intraepithelial lesions. We found intense and diffuse immunoreactivity of IGFBP2 in 36 (94.74%) of 38 proliferatively active STICs, 2 (7.41%) of 27 dormant STICs, and none of 15 p53 signatures. Staining results together with clinicopathologic features and representative photomicrographs are summarized in Table 1 and shown in Fig. 4AC. Figure 4D shows H-scores of IGFBP2 staining on different types of tissues. The great majority of proliferatively active STICs and HGSCs have significantly higher H-scores than NFTE. There were 4 cases showing STICs containing both proliferatively active and dormant areas. In those cases, we found a higher staining intensity of IGFBP2 in the regions with a higher Ki-67 labeling index compared with the adjacent dormant counterpart with a low Ki-67 index (Fig. 4E). IGFBP2 immunoreactivity was undetectable in tubal epithelium associated with concurrent STICs or HGSCs in postmenopausal women, and we extended this finding to normal appearing fallopian tubes without any lesions in younger premenopausal women. Interestingly, we observed positive IGFBP2 staining in secretory epithelial cells in most premenopausal fallopian tube samples. This result raises the possibility that IGFBP2 expression in normal premenopausal fallopian tubes is estrogen dependent.

Table 1.

The expression of IGFBP2 in ovarian cancer precursor lesions and associated patient characteristics.

SpecimenAgeHistologyp53 mutation patternIGFBP2 stainingKi67%Concurrent HGSOCGermline mutations
FTE-1 67 p53 signature Missense Negative No  
FTE-2 56 p53 signature Missense Negative NA No  
FTE-3 46 p53 signature Missense Negative No  
FTE-4 46 p53 signature Missense Negative No  
FTE-5 46 p53 signature Missense Negative No  
FTE-6 46 p53 signature Missense Negative No  
FTE-7 73 p53 signature Missense Negative 1.2 No  
FTE-8 73 p53 signature Missense Negative No  
FTE-9 73 p53 signature Missense Negative No  
FTE-10 58 p53 signature Missense Negative 5.3 No Lynch syndrome 
FTE-11 70 p53 signature Missense Negative No  
FTE-12 70 p53 signature Missense Negative No  
FTE-13 72 p53 signature Missense Negative 4.3 Yes  
FTE-14 60 p53 signature Missense Negative NA No  
FTE-15 52 p53 signature Missense Negative No  
FTE-16 71 Dormant/Active STICa Missense Positive/positive 7/35 No  
FTE-17 50 Dormant/Active STICa Missense Negative/positive 1/43 No  
FTE-18 44 Dormant/Active STICa Missense Negative/positive (weak) 5.2/40 No VUS, ATM(p.V455M), RAD50(p.R1260H) 
FTE-19 65 Dormant/Active STICa Nonsense Negative/positive (weak) NA No  
FTE-20 46 Dormant STIC Missense Negative No  
FTE-21 47 Dormant STIC Missense Negative No  
FTE-22 46 Dormant STIC Missense Negative Yes  
FTE-23 72 Dormant STIC Missense Negative No  
FTE-24 73 Dormant STIC Missense Negative No  
FTE-25 73 Dormant STIC Missense Negative No  
FTE-26 58 Dormant STIC Missense Negative No Lynch syndrome 
FTE-27 58 Dormant STIC Missense Negative No Lynch syndrome 
FTE-28 51 Dormant STIC Missense Negative No  
FTE-29 72 Dormant STIC Missense Negative Yes  
FTE-30 55 Dormant STIC Missense Negative No BRCA, type? 
FTE-31 60 Dormant STIC Missense Positive No  
FTE-32 68 Dormant STIC Missense Negative No  
FTE-33 66 Dormant STIC Missense Negative No  
FTE-34 69 Dormant STIC Missense Negative Yes  
FTE-35 69 Dormant STIC Missense Negative Yes  
FTE-36 58 Dormant STIC Missense Negative No  
FTE-37 58 Dormant STIC Missense Negative No  
FTE-38 58 Dormant STIC Missense Negative No  
FTE-39 58 Dormant STIC Missense Negative No  
FTE-40 73 Dormant STIC Missense Negative No  
FTE-41 73 Dormant STIC Missense Negative No  
FTE-42 73 Dormant STIC Missense Negative No  
FTE-43 46 Active STIC Missense Positive 74 No  
FTE-44 65 Active STIC Missense Positive 95 No BRCA2 
FTE-45 65 Active STIC Missense Positive 96 No BRCA2 
FTE-46 66 Active STIC Missense Positive NA Yes  
FTE-47 76 Active STIC Missense Positive NA No  
FTE-48 58 Active STIC Nonsense Positive (weak) 84 No  
FTE-49 71 Active STIC Missense Positive 12 No  
FTE-50 71 Active STIC Nonsense Positive 53 No  
FTE-51 71 Active STIC Nonsense Positive 55 No  
FTE-52 56 Active STIC Missense Positive (weak) NA No  
FTE-53 75 Active STIC Missense Positive 62 No  
FTE-54 75 Active STIC Missense Positive 69 No  
FTE-55 71 Active STIC Missense Positive (weak) 17 No BRCA1 
FTE-56 71 Active STIC Missense Positive 29 No  
FTE-57 71 Active STIC Missense Positive 23 No  
FTE-58 57 Active STIC Missense Positive NA Yes  
FTE-59 63 Active STIC Missense Positive NA Yes  
FTE-60 57 Active STIC Missense Positive 44 Yes  
FTE-61 57 Active STIC Missense Positive 52 Yes  
FTE-62 57 Active STIC Missense Positive 47 Yes  
FTE-63 79 Active STIC Missense Positive 20 No  
FTE-64 46 Active STIC Nonsense Positive (weak) 62 No BRCA1 
FTE-65 46 Active STIC Nonsense Positive (weak) 78 No BRCA1 
FTE-66 44 Active STIC Missense Positive 25 No VUS, ATM(p.V455M), RAD50(p.R1260H) 
FTE-67 41 Active STIC Missense Positive 81 No BRCA2 
FTE-68 51 Active STIC Nonsense Negative 23 No  
FTE-69 72 Active STIC Missense Positive 42 Yes  
FTE-70 72 Active STIC Missense Positive 31 Yes  
FTE-71 62 Active STIC Missense Positive 40 Yes BRCA1 
FTE-72 85 Active STIC Nonsense Positive 70 Yes  
FTE-73 85 Active STIC Nonsense Positive 78 Yes  
FTE-74 67 Active STIC Nonsense Positive 33 No  
FTE-75 65 Active STIC Missense Negative 21 No  
FTE-76 59 Active STIC Missense Positive 52 Yes  
SpecimenAgeHistologyp53 mutation patternIGFBP2 stainingKi67%Concurrent HGSOCGermline mutations
FTE-1 67 p53 signature Missense Negative No  
FTE-2 56 p53 signature Missense Negative NA No  
FTE-3 46 p53 signature Missense Negative No  
FTE-4 46 p53 signature Missense Negative No  
FTE-5 46 p53 signature Missense Negative No  
FTE-6 46 p53 signature Missense Negative No  
FTE-7 73 p53 signature Missense Negative 1.2 No  
FTE-8 73 p53 signature Missense Negative No  
FTE-9 73 p53 signature Missense Negative No  
FTE-10 58 p53 signature Missense Negative 5.3 No Lynch syndrome 
FTE-11 70 p53 signature Missense Negative No  
FTE-12 70 p53 signature Missense Negative No  
FTE-13 72 p53 signature Missense Negative 4.3 Yes  
FTE-14 60 p53 signature Missense Negative NA No  
FTE-15 52 p53 signature Missense Negative No  
FTE-16 71 Dormant/Active STICa Missense Positive/positive 7/35 No  
FTE-17 50 Dormant/Active STICa Missense Negative/positive 1/43 No  
FTE-18 44 Dormant/Active STICa Missense Negative/positive (weak) 5.2/40 No VUS, ATM(p.V455M), RAD50(p.R1260H) 
FTE-19 65 Dormant/Active STICa Nonsense Negative/positive (weak) NA No  
FTE-20 46 Dormant STIC Missense Negative No  
FTE-21 47 Dormant STIC Missense Negative No  
FTE-22 46 Dormant STIC Missense Negative Yes  
FTE-23 72 Dormant STIC Missense Negative No  
FTE-24 73 Dormant STIC Missense Negative No  
FTE-25 73 Dormant STIC Missense Negative No  
FTE-26 58 Dormant STIC Missense Negative No Lynch syndrome 
FTE-27 58 Dormant STIC Missense Negative No Lynch syndrome 
FTE-28 51 Dormant STIC Missense Negative No  
FTE-29 72 Dormant STIC Missense Negative Yes  
FTE-30 55 Dormant STIC Missense Negative No BRCA, type? 
FTE-31 60 Dormant STIC Missense Positive No  
FTE-32 68 Dormant STIC Missense Negative No  
FTE-33 66 Dormant STIC Missense Negative No  
FTE-34 69 Dormant STIC Missense Negative Yes  
FTE-35 69 Dormant STIC Missense Negative Yes  
FTE-36 58 Dormant STIC Missense Negative No  
FTE-37 58 Dormant STIC Missense Negative No  
FTE-38 58 Dormant STIC Missense Negative No  
FTE-39 58 Dormant STIC Missense Negative No  
FTE-40 73 Dormant STIC Missense Negative No  
FTE-41 73 Dormant STIC Missense Negative No  
FTE-42 73 Dormant STIC Missense Negative No  
FTE-43 46 Active STIC Missense Positive 74 No  
FTE-44 65 Active STIC Missense Positive 95 No BRCA2 
FTE-45 65 Active STIC Missense Positive 96 No BRCA2 
FTE-46 66 Active STIC Missense Positive NA Yes  
FTE-47 76 Active STIC Missense Positive NA No  
FTE-48 58 Active STIC Nonsense Positive (weak) 84 No  
FTE-49 71 Active STIC Missense Positive 12 No  
FTE-50 71 Active STIC Nonsense Positive 53 No  
FTE-51 71 Active STIC Nonsense Positive 55 No  
FTE-52 56 Active STIC Missense Positive (weak) NA No  
FTE-53 75 Active STIC Missense Positive 62 No  
FTE-54 75 Active STIC Missense Positive 69 No  
FTE-55 71 Active STIC Missense Positive (weak) 17 No BRCA1 
FTE-56 71 Active STIC Missense Positive 29 No  
FTE-57 71 Active STIC Missense Positive 23 No  
FTE-58 57 Active STIC Missense Positive NA Yes  
FTE-59 63 Active STIC Missense Positive NA Yes  
FTE-60 57 Active STIC Missense Positive 44 Yes  
FTE-61 57 Active STIC Missense Positive 52 Yes  
FTE-62 57 Active STIC Missense Positive 47 Yes  
FTE-63 79 Active STIC Missense Positive 20 No  
FTE-64 46 Active STIC Nonsense Positive (weak) 62 No BRCA1 
FTE-65 46 Active STIC Nonsense Positive (weak) 78 No BRCA1 
FTE-66 44 Active STIC Missense Positive 25 No VUS, ATM(p.V455M), RAD50(p.R1260H) 
FTE-67 41 Active STIC Missense Positive 81 No BRCA2 
FTE-68 51 Active STIC Nonsense Negative 23 No  
FTE-69 72 Active STIC Missense Positive 42 Yes  
FTE-70 72 Active STIC Missense Positive 31 Yes  
FTE-71 62 Active STIC Missense Positive 40 Yes BRCA1 
FTE-72 85 Active STIC Nonsense Positive 70 Yes  
FTE-73 85 Active STIC Nonsense Positive 78 Yes  
FTE-74 67 Active STIC Nonsense Positive 33 No  
FTE-75 65 Active STIC Missense Negative 21 No  
FTE-76 59 Active STIC Missense Positive 52 Yes  

Abbreviation: NA, not available.

aDormant SITC continuous with active STIC.

Figure 4.

IHC of IGFBP2 and correlation with lesion subtypes. A and B, Examples showing IGFBP2 immunostaining in STIC (A) and HGSC (B) but not adjacent NFTE. Solid arrow, STIC; open arrow, NFTE; stars, HGSCs in three different cases. C, Summary of IGFBP2 staining in p53 signature, dormant STIC, and active STIC. Red, percentage of positive cases. D, Scatter plot of IGFBP2 immunostaining H-scores of various lesions. Each symbol represents an individual lesion. E, An example of STIC containing both proliferatively active and dormant areas. IGFBP2 immunostaining is positive in proliferatively active STIC (Ki-67 positive). H&E, hematoxylin and eosin.

Figure 4.

IHC of IGFBP2 and correlation with lesion subtypes. A and B, Examples showing IGFBP2 immunostaining in STIC (A) and HGSC (B) but not adjacent NFTE. Solid arrow, STIC; open arrow, NFTE; stars, HGSCs in three different cases. C, Summary of IGFBP2 staining in p53 signature, dormant STIC, and active STIC. Red, percentage of positive cases. D, Scatter plot of IGFBP2 immunostaining H-scores of various lesions. Each symbol represents an individual lesion. E, An example of STIC containing both proliferatively active and dormant areas. IGFBP2 immunostaining is positive in proliferatively active STIC (Ki-67 positive). H&E, hematoxylin and eosin.

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Estrogen enhances IGFBP2 expression in NFTE

To test the hypothesis that estrogen enhances IGFBP2 expression, we first correlated IGFBP2 staining intensity in tubal epithelial cells with menstrual cycle and with the postmenopausal state. In premenopausal fallopian tubes, we found that IGFBP2 expression in secretory tubal epithelial cells was more prominent in the proliferative phase than in the secretory phase, while in postmenopausal fallopian tubes immunoreactivity was undetectable. However, the signal intensity of IGFBP2 in proliferative phase was much weaker than active STIC (Figs. 4D, 5A and B). As E2 plays a key role in the cyclic changes in female reproductive organs, we next examined if the expression of IGFBP2 was regulated by E2. After treating FT194 and FT241 tubal epithelial cells with E2 for 24 hours, we observed an increased expression of ERα, the predominant isoform of estrogen receptor (ER) in endometrium and fallopian tubes. Strikingly, the expression of IGFBP2 was also increased following E2 treatment (Fig. 5C). We obtained fresh normal fallopian tube tissue fragments from salpingo-oophorectomy (with or without hysterectomy) specimens performed for benign reasons including leiomyoma in premenopausal women. After treating the fallopian tube tissues ex vivo with E2, secretory epithelium became positive for IGFBP2 whereas the vehicle-treated tissues did not (Fig. 5D).

Figure 5.

Estrogen regulates IGFBP2 expression in normal premenopausal fallopian tube epithelium. A, IGFBP2 immunoreactivity in fallopian tubes from women at different menstrual phases (secretory/proliferative/postmenopausal) and in STIC. B, H-score of IGFBP2 expression levels at different menstrual phases. n.s., nonsignificant. C, Immunoblots for ERα and IGFBP2 in cellular extracts of FT194 and FT241 cell lines after treatment with 50 nmol/L E2 for 48 hours. GAPDH was used as a loading control. D, IGFBP2 expression increases in freshly harvested human fallopian tube tissue after E2 treatment. E, ChIP-seq data for ERα on T47D and Ishikawa cell lines showing ESR1 peaks (red squares) located within 1 kb downstream of the transcription starting site of IGFBP2. The data were obtained from the ENCODE database.

Figure 5.

Estrogen regulates IGFBP2 expression in normal premenopausal fallopian tube epithelium. A, IGFBP2 immunoreactivity in fallopian tubes from women at different menstrual phases (secretory/proliferative/postmenopausal) and in STIC. B, H-score of IGFBP2 expression levels at different menstrual phases. n.s., nonsignificant. C, Immunoblots for ERα and IGFBP2 in cellular extracts of FT194 and FT241 cell lines after treatment with 50 nmol/L E2 for 48 hours. GAPDH was used as a loading control. D, IGFBP2 expression increases in freshly harvested human fallopian tube tissue after E2 treatment. E, ChIP-seq data for ERα on T47D and Ishikawa cell lines showing ESR1 peaks (red squares) located within 1 kb downstream of the transcription starting site of IGFBP2. The data were obtained from the ENCODE database.

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We then retrieved data from ENCODE pertaining to chromatin immunoprecipitation sequencing (ChIP-seq) using an anti-ESR1 antibody on Ishikawa and T47D cell lines to assess the potential transcriptional regulation of IGFBP2 by ESR1. The ENCODE data showed that ESR1 peaks were located 1 k.b. downstream of the transcription start site within the presumed promoter region of IGFBP2 (Fig. 5E). These data suggest E2 regulates the expression of IGFBP2 in premenopausal NFTE.

Knockdown of IGFBP2 suppresses proliferation and spheroid formation by NFTE

To determine whether IGFBP2 expression was essential for cell survival and growth, we knocked down IGFBP2 in one FTE cell line (FT2821J) and two HGSC (OVCAR3 and PEA2) cell lines that expressed IGFBP2. Using immunoblot analysis, we confirmed that shRNA knockdown of IGFBP2 suppressed IGFBP2 expression (Fig. 6A). In all three cell groups, IGFBP2 knockdown led to lower proliferative activity in 2D cell culture systems (Fig. 6B and C).

Figure 6.

Knockdown of IGFBP2 decreases Akt phosphorylation and suppresses the proliferation and spheroid formation of NFTE. A, Immunoblots of IGFBP2 from FT2821J, PEA2, and OVCAR3 cell lines after IGFBP2 shRNA lentivirus knockdown. B, Left, colony formation assays in FT2821J, PEA2, and OVCAR3 cells after IGFBP2 knockdown. Right, quantification of data from left panel. C, Cell proliferation assays after IGFBP2 knockdown in FT2821J, PEA2, and OVCAR3 cells. D and E, Representative images of FT2821J and primary NFTE cell spheroids. Left, vehicle control. Middle, IGFBP2 knockdown. Right, GFP fluorescence image of the spheroid shown in the middle panel. Scale bar units, μm. F and G, Scatter plots showing the number (F) and diameter (G) of spheroids after knockdown of IGFBP2 in FT2821J and primary FTE cells. H, Immunoblots showing expression of cleaved-PARP, PCNA, IGFBP2, and α-tubulin (loading control) in extracts from FT2821J cells and primary cultures of fallopian tube epithelium after treatment with IGFBP2 shRNA lentivirus for 3 days. I, Knockdown of IGFBP2 in IGFBP2-high cell lines reduces Akt phosphorylation but less PTEN expression. J, Overexpression of IGFBP2 induces Akt phosphorylation in IGFBP2-low FTE cell lines (FT194 and FT241). **, P < 0.01.

Figure 6.

Knockdown of IGFBP2 decreases Akt phosphorylation and suppresses the proliferation and spheroid formation of NFTE. A, Immunoblots of IGFBP2 from FT2821J, PEA2, and OVCAR3 cell lines after IGFBP2 shRNA lentivirus knockdown. B, Left, colony formation assays in FT2821J, PEA2, and OVCAR3 cells after IGFBP2 knockdown. Right, quantification of data from left panel. C, Cell proliferation assays after IGFBP2 knockdown in FT2821J, PEA2, and OVCAR3 cells. D and E, Representative images of FT2821J and primary NFTE cell spheroids. Left, vehicle control. Middle, IGFBP2 knockdown. Right, GFP fluorescence image of the spheroid shown in the middle panel. Scale bar units, μm. F and G, Scatter plots showing the number (F) and diameter (G) of spheroids after knockdown of IGFBP2 in FT2821J and primary FTE cells. H, Immunoblots showing expression of cleaved-PARP, PCNA, IGFBP2, and α-tubulin (loading control) in extracts from FT2821J cells and primary cultures of fallopian tube epithelium after treatment with IGFBP2 shRNA lentivirus for 3 days. I, Knockdown of IGFBP2 in IGFBP2-high cell lines reduces Akt phosphorylation but less PTEN expression. J, Overexpression of IGFBP2 induces Akt phosphorylation in IGFBP2-low FTE cell lines (FT194 and FT241). **, P < 0.01.

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To better simulate the in vivo condition, we performed 3D culture and mouse xenograft tumor model. On the basis of 3D spheroid cultures generated from freshly harvested human FTE cells or FT2821J cells, we also observed smaller sizes and numbers of spheroids in knockdown groups compared with controls (Fig. 6DG). Western blot analysis also showed reduced proliferating cell nuclear antigen (PCNA) and increased cleaved PARP expression after IGFBP2 knockdown (Fig. 6H). Silencing of IGFBP2 significantly inhibited OVCAR3 tumor growth in mice as compared with control cells, which were transduced with lentivirus carrying nontarget shRNA (Supplementary Fig. S6A). The growth inhibitory effect rendered by IGFBP2 inactivation was consistent with that in previous reports (29, 30). Western blot was performed to confirm the knockdown of IGFBP2 before the xenograft injection (Supplementary Fig. S6B). We next sought to determine which pathways downstream of IGFBP2 contribute to cell proliferation and stemness. Western blot analysis confirmed decreased Akt phosphorylation after knockdown of IGFBP2 (Fig. 6I) and increased Akt phosphorylation after overexpression of IGFBP2 (Fig. 6J), while p-p38/p-ERK/p-JUNK remained unchanged (data not shown). Western blot on PTEN was also performed as IGFBP2 has been reported to negatively regulate PTEN (31, 32). Interestingly, PTEN expression did not increase upon IGFBP2 knockdown. This result suggests that expression of IGFBP2 activates the Akt pathway and contributes to cell proliferation through a mechanism other than downregulating PTEN in our model.

The emerging paradigm of HGSC genesis from fallopian tube epithelium has provided investigators an opportunity to study the earliest molecular changes in fallopian tube precursor lesions. Unlike other common neoplastic diseases, very few recurrent somatic mutations in cancer-driver genes have been detected and functionally validated in the development of STIC, with the exception of mutations in TP53 and in genes involved in homologous recombination-mediated DNA double-strand break repair including BRCA1 and BRCA2 (5, 8, 9). This finding indicates that mechanisms other than somatic mutation play a critical role in HGSC initiation. For example, epigenetic changes such as DNA methylation and chromatin modification can also contribute to aberrantly expressed driver genes that activate the signaling pathways that may transform tubal epithelial cells (33, 34). In this study, we first performed spatial transcriptomic analysis in STIC epithelium and underlying stroma and HGSC to identify aberrantly expressed cancer-related genes in comparison to normal tubal epithelium (NFTE), and we determined whether epigenetic regulation of their expression took place. We then focused on one aberrantly expressed gene, IGFBP2, to explore its roles in HGSC development.

NanoString digital spatial profiling analysis in STICs and HGSCs demonstrates the difference of global mRNA profiles as compared with NFTE. As expected, we observe that the two different regions within a STIC more resemble each other than with other STICs. We also identified several cancer-related genes that were either upregulated or downregulated in transformed epithelial cells compared with normal-appearing epithelium. The majority of the differentially expressed genes in STIC and HGSC can be verified in RNA-seq data from an independent set of HGSCs and normal fallopian tube cases (21). We were able to validate representative genes including FGF2, CRISP3, PRAME, and IGFBP2 using an orthogonal approach, IHC, on selected STIC and HGSC samples. Loss of FGF2 has been reported during malignant transformation of mammary duct epithelium (35) and has also been shown to have a causal role in branching morphogenesis in breast cancer cell lines (35, 36). In normal tissues, CRISP3 was expressed in neutrophils and exocrine tissues including salivary glands, pancreas, and prostate (37). It is likely that downregulation of FGF2 and CRISP3 expression in STICs is related to their loss of secretory differentiation or cell lineage. On the other hand, PRAME is a cancer-related gene expressed in testis that has been reported to be expressed in many cancers (38), likely due to promoter hypomethylation (39–41). Activation of PRAME has been reported to be oncogenic through binding to retinoid acid receptor, preventing target gene transcription (42). In contrast to epithelial cells, we only identify few genes of interest in the stroma underlying STIC lesions, raising the possibility that stromal microenvironment is mostly similar between STIC and NFTE. Our results may help generate experimentally testable hypotheses regarding initiation of ovarian HGSC.

Our preexisting RNA-seq transcriptomic data in HGSC and NFTE as well as our methylomic data in STIC, HGSC, and NFTE allowed us to further identify a focused set of genes that are upregulated in STIC and HGSC due to gene hypomethylation and which are functionally associated with pathogenesis of ovarian cancer. As a result, we selected an upregulated gene, IGFBP2, for functional characterization in STIC development. Our results showed that the proximal enhancer of IGFBP2 regulated IGFBP2 gene expression in STIC and HGSC. Thus, IGFBP2, like human cancer antigens, can result from reexpression of genes due to epigenetic relaxation (43–45). Along this line, autoantibodies against IGFBP2 were detected in serum from patients with lung, breast, and colorectal cancers (46–48), and a DNA vaccine targeting the N-terminus of IGFBP2 has been recently proposed (49), indicating that IGFBP2 is a tumor antigen.

Our findings have biological implications in tumor initiation of HGSC. In premenopausal women, FTE cells are repeatedly exposed to follicular fluid during ovulation. The insulin-like growth factor (IGF) axis has been proposed to play an important role in mediating the effects of follicular fluid on tubal epithelium. This is evidenced by a previous study showing that binding of IGF2 from follicular fluid to IGF1R receptor on FTE cell lines promotes stemness through activation of the downstream AKT/mTOR/NANOG pathway (50, 51). In addition, IGFBP2 in the follicular fluid binds to IGF2, prolonging its half-life and thus its biological effects (50, 52, 53).

In the current study, we report that IGFBP2 is also expressed in fallopian tube secretory epithelial cells from premenopausal but not postmenopausal women, and such local effect may further enhance the IGF activity in tubal epithelium. Because of its well-established proliferation-promoting role, IGF-related signaling helps tubal epithelial cells regenerate and substitute for those that are severely damaged by follicular fluid-derived genotoxic factors, mainly reactive oxygen species (50, 54, 55) However, the tubal epithelium that survives can accumulate molecular genetic alterations including somatic mutations like TP53 mutation and DNA copy number gain/loss if cellular proliferation resumes. It has been estimated that tumor initiation from the first hit, mostly likely a TP53 mutation to form a STIC, takes decades of slow progression from that initial lesion at a young age to the patient's early 50s when cyclic ovulations cease, and serum estrogen levels sharply decrease.

As ER expression continues even after menopause in gynecologic tissues including fallopian tube epithelium (56, 57), loss of IGFBP2 expression in the fallopian tube epithelium of postmenopausal women is likely due to decreased serum estrogen levels. Indeed, our in vitro and ex vivo studies showing that IGFBP2 expression in tubal secretory epithelial cells depends on E2 is consistent with our observation that, in all specimens analyzed, postmenopausal fallopian tubes lose IGFBP2 expression. A similar finding has also been reported in endometrial stromal cells in which E2 increases IGFBP2 expression (58, 59). While estrogen contributes to the proliferative activity in tubal epithelium in premenopausal women, the greatly reduced estrogen level in postmenopausal women does not support the proliferative activity in those extant precursor lesions, acting as a natural barrier for tumor progression. Therefore, in order for those STIC cells to progress to HGSC, STIC cells need to acquire new molecular rewiring that stimulates their proliferation and clonal expansion. From this perspective, we identified a new pathogenic mechanism in HGSC in which epigenetic alterations reactivate IGFBP2 expression, which in turn locally promotes cellular proliferation for tumor progression. This mechanism allows STIC and HGSC cells to exhibit estrogen-independent growth in postmenopausal women.

IGFBP2 has been suggested to participate in cancer-driving signaling in a number of cancer types in addition to ovarian cancer (27, 60, 61). Targeting IGFBP2 and its pathway has emerged as a new avenue for cancer therapy. Pharmacologic targeting of the HIF1α–IGFBP2 axis impairs IGF1-AKT signaling and suppresses the growth and metastasis of relapsed anaplastic Wilms tumor (29). OGX-225, an antisense oligonucleotide that targets IGFBP2 mRNA, decreases the proliferation of breast cancer cells (62). Moreover, a human single chain recombinant monoclonal antibody that targets the C-terminus of IGFBP2 and interferes with its binding to integrin inhibits migration and invasion of glioma cells (63), and neutralizing antibodies against IGFBP2 lead to decreased activation of downstream oncogenic signaling pathways and decreased tumor growth (64).

A number of limitations in this study should be pointed out. The technical platform we used for transcriptomic profiling is not ideal for studying very small lesions (less than 100 lesional cells) including minute STICs and p53 signatures. Neither is it suitable for addressing possible intra-STIC heterogeneity, which will require methods with single cell resolution. On the basis of the current data, we are not able to correlate molecular changes and clinical outcomes in those women with incidental STICs. A large consortium-type study involving collection of tissue materials accompanied by long-term follow-up information would be required. Second, the effects of 5-AZA used in this study were global and not specific to the proximal enhancer of IGFBP2. Our results shown here cannot rule out the possibility of 5-AZA having an indirect (or nonspecific) impact on IGFBP2 through global demethylation. Third, it should not be construed that IGFBP2 overexpression is sufficient to sustain the growth and expansion of STICs. For that, it will be necessary to perform functional validation and characterization of other STIC-upregulated genes and to determine how they collaborate to contribute to tumor initiation. Finally, it should be noted that we only focused on STIC as the origin of HGSC in this study; we did not explore the transcriptomic alterations in other unusual non-STIC precursors such as ovarian surface or cortical inclusion cysts showing dysplasia (1).

In summary, we report that the STIC transcriptomic landscape is populated with several differentially expressed cancer-associated genes that distinguish STICs from normal tubal epithelium. This data set may help, in conjunction with The Cancer Genome Atlas ovarian cancer data, various research projects aimed at elucidating the pathophysiology of ovarian cancer and identification of biomarkers for early detection and chemoprevention. In particular, we demonstrate that IGFBP2 upregulation likely plays a pivotal role in propelling tumor progression in ovarian cancer precursor lesions, and we explain how epigenetic regulation of the IGFBP2 during ovarian cancer initiation accounts for estrogen-independent growth of STIC cells.

B.G. Wang reports personal fees from Genetron Health USA outside the submitted work. No disclosures were reported by the other authors.

Y. Wang: Conceptualization, formal analysis, validation, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. P. Huang: Data curation, software, formal analysis, visualization, methodology, writing–original draft, writing–review and editing. B.G. Wang: Resources, writing–review and editing. T. Murdock: Resources, writing–review and editing. L. Cope: Data curation, software, formal analysis, validation, visualization, writing–original draft. F.-C. Hsu: Software, formal analysis, visualization, writing–original draft. T.-L. Wang: Conceptualization, resources, supervision, funding acquisition, methodology, writing–review and editing. l.-M. Shih: Conceptualization, resources, supervision, funding acquisition, methodology, writing–original draft, project administration, writing–review and editing.

The authors gratefully acknowledge Dr. Ronny Drapkin from University of Pennsylvania and Dr. Wei Zhang from Wake Forest University School of Medicine for providing FTE cell lines and IGFBP2 plasmid, respectively. The authors thank Dr. Thomas R. Pisanic II for advice in methylation study and Dr. Zheng-Cheng Yu at Johns Hopkins for assisting with the mice xenograft experiment. This study was supported by grants Break Through Cancer, US Department of Defense Ovarian Cancer Research Program (OC210403), NIH/NCI (P50CA228991, R01CA260628, R01CA215483, U2C CA271891), The Honorable Tina Brozman Foundation, and Richard W. TeLinde Endowment from the Johns Hopkins University.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

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