Single- imaging reveals unexpected heterogeneity of telomerase expression across human cell lines

Teisha J. Rowlanda,b,c,1, Gabrijela Dumbovica,b,1, Evan P. Hassa,b, John L. Rinna,b,c, and Thomas R. Cecha,b,c,2

aDepartment of Biochemistry, University of Colorado Boulder, Boulder, CO 80303; bBioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303; and cHoward Hughes Medical Institute, University of Colorado Boulder, Boulder, CO 80303

Contributed by Thomas R. Cech, July 19, 2019 (sent for review May 16, 2019; reviewed by Steven Artandi and Karen L. Beemon) Telomerase is pathologically reactivated in most human , and related pathological conditions (i.e., telomeropathies such where it maintains chromosomal and allows immortal- as , , and pulmonary ization. Because telomerase reverse transcriptase (TERT) is usually fibrosis) (14). the limiting component for telomerase activation, numerous While many TERT expression studies have been published, studies have measured TERT mRNA levels in populations of cells these studies have been complicated by difficulties in detecting or in tissues. In comparison, little is known about TERT expression low levels of endogenously expressed TERT mRNA (15) and at the single-cell and single-molecule level. To address this, we have typically used methods that look at bulk expression levels analyzed TERT expression across 10 human cancer lines using within a cell population or tissue sample. Traditional cell pop- single-molecule RNA fluorescent in situ hybridization (FISH) and ulation studies provide little insight into cell-to-cell heteroge- made several unexpected findings. First, there was substantial cell- neity and spatial aspects of mRNA expression (16), which has to-cell variation in number of sites and ratio of left unanswered—or provided only unclear answers to—many transcription sites to gene copies. Second, previous classification of lines as having monoallelic or biallelic TERT expression was intriguing questions about TERT expression. For example, while found to be inadequate for capturing the TERT gene expression population averages can be a good starting point for under- patterns. Finally, spliced TERT mRNA had primarily nuclear locali- standing overall expression levels of a given mRNA, these data zation in cancer cells and induced pluripotent stem cells (iPSCs), in cannot answer questions related to expression at the single-cell stark contrast to the expectation that spliced mRNA should be level, such as how many gene copies are active per cell and predominantly cytoplasmic. These data reveal unappreciated het- whether there is significant heterogeneity between cancer types erogeneity, complexity, and unconventionality in TERT expression or among cells in a given cell line, and can even be misleading across human cancer cells. when such heterogeneity is involved. Additionally, while cell fractionation can be done on a population of cells, studies of cancer | single-molecule imaging | telomerase | TERT | transcription population averages cannot provide insight into where molecules of TERT pre-mRNA and spliced (i.e., mature) mRNA reside elomeres, protective structures found at the ends of eukary- within single cells; an important consideration as subcellular Totic , contain a highly repetitive DNA sequence and associated ; they are important for maintaining Significance chromosomal and genomic stability (1). In early human devel- opment, chromosomal shortening that occurs due to Telomerase, which extends DNA at ends, is “ ” the end-replication problem during cell proliferation can be composed of an RNA template and a catalytic subunit, compensated by telomerase. Telomerase, first discovered in 1985 telomerase reverse transcriptase (TERT). TERT gene expression in the ciliate (2), is a ribonucleoprotein that has been of great interest because it is required for pro- lengthens and maintains the telomeres. After development, liferation of most cancers, but expression investigations have telomerase is inactivated in most cells, leading to pro- been limited due to low endogenous mRNA levels. Here, we gressive telomere shortening until a critical length halts cell di- employ single-molecule RNA fluorescent in situ hybridization vision and triggers cell (the ). However, (FISH) in 10 human lines and make findings that are ∼ telomerase is pathologically active in 80 to 90% of malignant unanticipated based upon bulk TERT mRNA measurements. For human cancers, which is considered an early cancer progression example, there is great cell-to-cell variation in the number of – event (3 5). transcription sites, and spliced TERT mRNA has greater nuclear Expression of the catalytic subunit of telomerase, telomerase localization than cytoplasmic. Overall, our findings provide in- reverse transcriptase (TERT) (6, 7), is required for telomerase sights regarding TERT expression, localization patterns, and activity. Introduction of TERT expression into normal human variability in cancer on a single-cell level. somatic cells leads to telomere elongation and cellular immor- talization, making its expression necessary, but not sufficient, for Author contributions: T.J.R., G.D., J.L.R., and T.R.C. designed research; T.J.R., G.D., and driving oncogenesis in most cancers (8, 9). Increased TERT ex- E.P.H. performed research; T.J.R., G.D., E.P.H., J.L.R., and T.R.C. analyzed data; and T.J.R., pression levels have also been found to be associated with poorer G.D., E.P.H., J.L.R., and T.R.C. wrote the paper. patient prognoses for several cancer types, including breast cancer, Reviewers: S.A., Stanford University; and K.L.B., Johns Hopkins University. urothelial bladder carcinomas, non–small-cell lung carcinomas, Conflict of interest statement: T.R.C. is on the board of directors of Merck, Inc., and a melanoma, and thyroid tumors (10–13), highlighting the impor- consultant for Storm Therapeutics, neither of which provided funding for this study. tance of understanding the role of TERT expression in cancer Published under the PNAS license. and its progression. 1T.J.R. and G.D. contributed equally to this work. It is thought that TERT expression, which is relatively low, 2To whom correspondence may be addressed. Email: [email protected]. must be tightly regulated to ensure normal telomere mainte- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. nance. Even a small decrease in TERT activity, such as by 10 to 1073/pnas.1908275116/-/DCSupplemental. 20%, may potentially result in abnormal telomere maintenance Published online August 26, 2019.

18488–18497 | PNAS | September 10, 2019 | vol. 116 | no. 37 www.pnas.org/cgi/doi/10.1073/pnas.1908275116 Downloaded by guest on September 25, 2021 localization can have profound effects on the function of RNA occurrence of TERT protein (visualized using an anti-FLAG an- molecules. tibody to the 3×FLAG-tagged TERT protein) and TERT mRNA Recent advancements in RNA imaging (15, 17) allow visuali- (visualized by TERT exon smFISH). TERT OE cells that were zation of mRNAs and actively transcribing alleles at the single- positive for anti-FLAG staining (i.e., expressing TERT protein) cell level even at low abundance. In the current study, we de- also showed clear TERT exon probe hybridization (Fig. 1 C, Top), termined single-cell TERT expression levels in several cancer while nontransfected cells had much lower levels of TERT mRNA cell lines that had been previously classified as having either and showed no anti-FLAG staining (Fig. 1 C, Bottom). These monoallelic or biallelic expression (MAE or BAE, respectively) experiments gave considerable confidence that the oligonucleo- of TERT by Huang et al. (18). They determined the MAE or tide probes specifically recognized TERT pre-mRNA and BAE status of these lines by quantifying allelic imbalances of spliced mRNA. heterozygous single- polymorphisms (SNPs) in TERT As additional controls, we performed GAPDH exon and in- exons using whole-genome sequencing and RNA-sequencing tron smFISH on TERT OE and nontransfected cells (SI Ap- (RNA-seq) data from the Broad Institute’s Cancer Cell Line pendix, Fig. S1). GAPDH exon probes showed characteristic Encyclopedia (18). For reasons that remain unknown, MAE or signal in the cytoplasm, and nuclear exon signals colocalizing BAE of TERT was found to consistently associate with certain with intron signals marked active GAPDH transcription sites (SI cancer types; for example, melanoma and pancreatic cancer cell Appendix, Fig. S1B). Both nontransfected and TERT OE trans- lines had MAE of TERT, while breast and prostate lines had fected cells typically had 0 to 2 exon–intron colocalized nuclear BAE of TERT. Other cancer types were found to be composed “spots,” or signals. Some HEK293T cells had 3 exon–intron of a mixture of MAE and BAE lines. Overall, 44% (39/88) of cell colocalized spots per nucleus, which is not unexpected due to the lines investigated had MAE of TERT, while the other lines had abnormal karyotype of HEK293T cells (27). Altogether, these BAE of TERT. Nearly one-half (19/39) of MAE lines contained data are supportive of our TERT smFISH probes being specific a TERT promoter known to reactivate TERT expres- for detecting and visualizing TERT RNA and TERT active sion via transcription factor recruitment (19–22), while all other transcription sites. MAE lines contained no known TERT (i.e., appar- ently “wild-type” lines). It remains unclear how these wild-type Unexpected Variation of TERT Expression across Different Cancer Cell lines reactivated TERT, or potentially failed to inactivate the Lines. After confirming the specificity of our TERT smFISH TERT

gene (23). Interestingly, Huang et al. reported no significant probes, we used these probes to visualize active genes on a GENETICS difference in TERT expression levels between mutant and wild- single-cell level across different cancer cell lines. We selected a type MAE lines, nor between MAE and BAE lines, although total of 9 cell lines that varied in cancer type and allelic TERT other studies have reported some cancer types that frequently expression classification (Table 1). Three of these cancer lines contain TERT promoter mutations (e.g., bladder, glioblastoma, are known to contain a common activating TERT promoter and melanoma) to have increased TERT expression (13, 24, 25). mutation (chr5:1,295,228 C>T; hg19), located 124 bp upstream In the current study, we utilized the powerful technique of of the TERT start site (ATG) (18), referred to here single-molecule RNA fluorescent in situ hybridization (smFISH) as −124 mutants. We also included induced pluripotent stem to image and analyze individual TERT mRNA molecules and cells (iPSCs) (line WTC-11), which express TERT, and an os- active TERT transcription sites (17). We found unexpected teosarcoma cancer cell line (U-2 OS) known to use the alter- variance in the number of active transcription sites, both among native lengthening of telomeres (ALT) mechanism and therefore cells within a given cancer cell line and between different lines, be telomerase-negative (28). The number of active transcription which increased as the mean number of transcription sites in cell sites per cell was determined for each cell line based on the lines increased (R2 = 0.92), supportive of transcriptional bursting colocalization of intron and exon probe signals (Fig. 2A and SI (26). TERT DNA FISH showed that the number of transcription Appendix, Table S1). As expected, in WTC-11 cells, the mode sites correlated with the number of gene copies (R2 = 0.42), as number of TERT transcription sites was 2 (38% of cells) and the one might expect. However, we unexpectedly found the MAE mean was 1.87 (±0.12), while in U-2 OS cells the mode was and BAE classification of these cancer cell lines to hide much 0 (97% of cells) and the mean was 0.03 (±0.02). Also, as complexity, as the ratio of transcription sites to gene copies expected, linear regression analysis across all 11 cell lines tested generated from our smFISH and DNA FISH data often did not revealed a strong positive correlation between both the mean support the cell line’s allelic classification. These data add to our number of transcription sites (Fig. 2B) and the TERT RNA understanding of variance in TERT expression across human levels as measured via quantitative real-time PCR (qRT-PCR) cancers, which could help guide future cancer modeling and (Fig. 2C) with the mean number of TERT mRNA exon spots per cancer therapeutic efforts. cell (R2 = 0.64 and 0.63, respectively). GAPDH control smFISH on 3 cell lines (iPSC line WTC-11 and TERT-expressing cancer Results cell lines SNU-475 and DB) showed expected hybridization Validation of TERT smFISH. To analyze TERT active transcription patterns with the GAPDH exon and intron probes (SI Appendix, sites at the single-cell level, we employed dual-color smFISH. Fig. S3 A and B), further supporting the specificity of our We designed probe sets to independently target smFISH assays. TERT intron and GAPDH intron probes were TERT intron 2 and multiple exons, thus marking the site of also used to colabel these cells and gave results similar to those transcription (Fig. 1A). To confirm the specificity of the probes, seen when TERT and GAPDH probes were used separately (SI we analyzed their hybridization in HEK293T cells transfected to Appendix, Fig. S3C). overexpress (OE) exon-only full-length 3×FLAG-tagged TERT The number of active TERT transcription sites per cell de- as well as in nontransfected cells. In nontransfected cells, TERT tected by smFISH varied substantially across the cancer cell lines intron signals appeared in the nuclei as punctate dots that colo- (see Fig. 2A and SI Appendix, Table S1 for mode and mean calized with the TERT exon signals, indicating active transcription values, respectively). The mode number of transcription sites for sites (Fig. 1 B, Top). HEK293T cells transfected with TERT OE most telomerase-positive cell lines (6/9 lines) was 0, with only a vector showed markedly increased levels of exon probe hybridiza- minority of cells showing 1 or a few transcription sites. Given that tion (Fig. 1 B, Middle). RNase A treatment eliminated all detect- these cancer cells are telomerase-positive and TERT is essential able signal in TERT smFISH (Fig. 1 B, Bottom), confirming that for telomerase activity, this was an unexpected finding (Discus- our probes specifically recognize an RNA target. Because trans- sion). In sharp contrast, other lines had mode values of 2 (LN-18 fection of the HEK293T cells was incomplete, we analyzed the co- and HuTu 80) or 5 (NCI-H196), with only a small fraction of the

Rowland et al. PNAS | September 10, 2019 | vol. 116 | no. 37 | 18489 Downloaded by guest on September 25, 2021 Fig. 1. TERT exon and intron single-molecule RNA FISH (smFISH) probe design and specificity. (A) The University of California, Santa Cruz, Genome Browser view showing the localization of TERT intron (magenta) and exon (gray) oligonucleotide probes. (B) Maximum-intensity projections of TERT exon and intron smFISH of HEK293T cells that were (Top) nontransfected, (Middle) transfected with TERT-3×FLAG overexpression (OE) plasmid, and (Bottom) transfected with TERT OE plasmid treated with RNase A prior to hybridization. The arrowheads indicate representative colocalization of exon and intron signals consistent with active transcription sites. (C) Maximum-intensity projections of HEK293T cells that were (Top) transfected with TERT-3×FLAG OE plasmid and (Bottom) nontransfected. TERT mRNA was monitored with TERT exon smFISH and TERT protein with immunostaining against the FLAG tag. TERT exon probes are shown in gray, intron probes in magenta, anti-FLAG immunostaining in green, and DAPI in blue. (Scale bars, 5 μm.)

18490 | www.pnas.org/cgi/doi/10.1073/pnas.1908275116 Rowland et al. Downloaded by guest on September 25, 2021 Table 1. Monoallelic or biallelic TERT expression classification and promoter mutation status of TERT-expressing cancer cell lines Cell line Cancer type Promoter mutation status Expression classification Exon 2 SNP?

NCI-H196 Lung cancer Wild type Monoallelic Yes Panc 10.05 Pancreas Wild type Monoallelic Yes LN-18 Glioblastoma Wild type Monoallelic Yes U-87 MG Glioblastoma −124 heterozygous mutant Monoallelic Yes SNU-475 Liver −124 heterozygous mutant Monoallelic Yes HT-1376 Bladder −124 heterozygous mutant Monoallelic* Yes DB Leukemia Wild type Biallelic Yes HuTu 80 Stomach Wild type Biallelic Yes SK HEP-1 Liver Wild type Biallelic Yes

*Our data show the HT-1376 line to be more biallelic.

cells showing no transcription sites. Due to variation within the cell transcription sites. Overall, these data suggest that the cells are lines, while the mean number of transcription sites for most usually not utilizing all copies of the TERT gene present. cell lines was less than 1.00 (4/9 lines), mean values for the other To better understand the genotypic abnormalities observed in cell lines ranged from 1.90 (±0.26) to 6.78 (±0.53). Using linear re- the TERT DNA FISH, a representative telomerase-expressing gression analysis, variance within the 11 cell lines was found to have cancer cell line (LN-18) was further characterized using TERT a strong positive correlation with the number of active transcription DNA FISH of metaphase cells and karyotype analysis. The sites (R2 = 0.92) (Fig. 2D). A similar but weaker correlation was metaphase DNA FISH agreed with the interphase TERT DNA found between variance within the cell lines and the number of FISH performed on this cell line, both showing most cells to have TERT mRNA exon spots (R2 = 0.57) (SI Appendix,Fig.S2). It was 3 copies of the TERT gene (Fig. 3C). The metaphase analysis also surprising to find that while TERT exon probe spots were additionally showed TERT triploidy to be due to amplified full- abundant in the cytoplasm of HEK293T cells overexpressing TERT length and partial copies of chromosome 5, where the TERT GENETICS (Fig. 1 B and C), in both iPSCs and cancer cells endogenously gene resides. This finding was supported by in-depth karyotype expressing TERT, significantly more exon spots were localized analysis (Fig. 3D), which showed this cell line to have an overall within the nucleus than the cytoplasm. Specifically, for each cell, near-triploid (3n), unbalanced karyotype with complex abnor- the number of colocalized intron–exon spots was subtracted from malities. Specifically, most cells were XY or XXY and found to the total number of nuclear exon spots, and this was compared to the contain 2 to 3 copies of most chromosomes (with some cells total number of cytoplasmic exon spots, revealing predominantly containing 4 copies of some chromosomes). Regarding chro- nuclear localization of spliced mRNA (Fig. 2E; P ≤ 0.004). We mosome 5, 3 full or partial copies, sometimes containing un- further validated that the TERT mRNA signal is within the nucleus identifiable material possibly due to chromosomal duplications by analyzing images in orthogonal projections and 3D (SI Appendix, or deletions, were typically observed in the karyotype analysis. Fig. S4). Because only cytoplasmic TERT mRNA could be trans- These data indicate that abnormal numbers of the TERT gene lated into protein, this observation correlates with the low copy observed in our cancer lines via TERT DNA FISH (i.e., >2 number of TERT protein in cancer cells (29). Overall, our TERT copies per cell) are not limited to the TERT gene, and instead smFISH data indicate that substantial unexpected variation and are part of a complex, aneuploid karyotype present in the patterns in TERT expression exists within and across different cancer cells. cancer cell lines. Classification of Cancer Cell Lines as Monoallelic or Biallelic Is Insufficient Variation in TERT Gene Copy Number across Different Cancer Cell to Capture TERT Expression Patterns. As mentioned earlier, the 9 Lines. To determine whether the variation in TERT expression TERT-expressing cancer cell lines used in the present study had across different cancer cell lines is due to differences in TERT been previously classified based on allelic TERT expression and gene copy numbers, TERT DNA FISH was performed (Fig. 3A). TERT promoter mutation status (Table 1). To confirm the expec- As a positive control, the TERT DNA FISH showed the diploid ted allelic classifications, we used genomic DNA (gDNA) se- WTC-11 cells to have a mode number of 2 spots per nucleus quencing combined with RT-PCR sequencing of a known SNP in (94% of cells) and a mean number of 2.01 (±0.04) (see SI Ap- TERT exon 2 (rs2736098) (SI Appendix,Fig.S5A). The classifica- pendix, Table S1 and Fig. S3A, for mean and mode values, re- tion of having either monoallelic or biallelic expression (MAE or spectively). Of the 10 cancer cell lines tested, most lines (8/10) BAE, respectively) of TERT was confirmed for all 9 cell lines, ex- had a mode value of 2 to 4 spots per nucleus, with 3 lines having cept for the HT-1376 cell line, which was reported to have MAE a mode value of 2 spots (85 to 98% of cells in these lines), 4 with but appeared to have more BAE (SI Appendix,Fig.S5B and Table 3 spots (70 to 90% of cells), and 1 with 4 spots (86%). In sharp 1). While many lines showed similar levels of both alleles based on contrast to the smFISH data, the number of genes per cell had gDNA sequencing (NCI-H196, Panc 10.05, DB, HuTu 80, and SK low variance within each of these 8 cell lines. The remaining 2 HEP-1), several lines had gDNA with relatively greater levels of cancer cell lines had a mode value of 10 spots per nucleus (24 to the inactive allele (LN-18, SNU-475, HT-1376) or active allele 35% of cells) and relatively higher variance within each line. The (U-87 MG). mean number of active transcription sites (as determined via Some of the cancer cell lines with apparent MAE of TERT TERT smFISH) was found to have a positive correlation with had, as expected, roughly one-half of their TERT gene copies the number of DNA FISH spots across the 9 TERT-expressing active based on our TERT smFISH and DNA FISH data, but cancer cell lines (R2 = 0.42), a correlation that was dominated by this did not necessarily mean there were simply 2 gene copies the 2 high-DNA copy lines that also had among the highest with 1 being active. For example, while Panc 10.05 cells did have number of transcription sites (Fig. 3B). The mean difference on average 2 (2.25 ± 0.05) TERT gene copies and 1 (0.75 ± 0.20) between the number of active sites and DNA FISH spots in the active transcription site, NCI-H196 cells, surprisingly, had on 10 cancer cell lines was 2.1 (±0.9) more DNA FISH spots than average 11 (10.98 ± 0.28) gene copies and 7 (6.78 ± 0.54)

Rowland et al. PNAS | September 10, 2019 | vol. 116 | no. 37 | 18491 Downloaded by guest on September 25, 2021 Fig. 2. TERT smFISH reveals variation of TERT expression across cancer cell lines. (A) Representative single-cell maximum-intensity projections of TERT exon and intron smFISH and histograms quantifying cell-to-cell variation in number of transcription sites (number of colocalized exon–intron signals per nucleus) across different cancer cell lines. The arrowheads indicate colocalization of exon and intron signal consistent with active transcription sites. TERT-expressing cancer lines are arranged from least to greatest mean number of active transcription sites (from Top to Bottom). TERT exon probes are shown in gray, intron probes in magenta, and DAPI in blue. (Scale bars, 5 μm.) (B) Number of active transcription sites (colocalized exon–intron spots per nucleus measured via smFISH) increases with number of TERT mRNA exon spots (per cell measured via smFISH). The linear regression line is forced through the 0,0 intersect. (C) Number of TERT mRNA exon spots (per cell measured via smFISH) correlates with RNA expression levels (measured via qRT-PCR). The linear regression lineis forced through the 0,0 intersect. (D) Variance of active transcription sites (colocalized exon–intron spots per nucleus measured via smFISH) within a cell line increases with number of transcription sites. (E) Spliced TERT mRNA (exon spots minus colocalized exon–intron spots per nucleus, or total exon spots per cytoplasm, as measured via smFISH) primarily has nuclear localization in all lines investigated. Data point values for all cell lines shown in B–D are provided in SI Appendix, Table S1. Error bars represent SEM; n = 55 to 204 cells, depending on the cell line, as shown in A. Data points (B–E) represent mean values, and error bars represent SEM. For smFISH, n = 55 to 204 cells, depending on the cell line, as shown in A. For qRT-PCR, n = 3 independent measurements.

18492 | www.pnas.org/cgi/doi/10.1073/pnas.1908275116 Rowland et al. Downloaded by guest on September 25, 2021 GENETICS

Fig. 3. TERT DNA FISH reveals more TERT genes than active transcription sites in most cancer cell lines. (A) Representative TERT DNA FISH single-cell images, with arrowheads indicating probe spots within each nucleus, and histograms quantifying TERT DNA FISH, showing variation in TERT gene copy number among different cell lines but usually little variation within a given cell line (n = 200 cells for each cell line). TERT-expressing cancer lines are arranged from least to greatest mean number of active transcription sites (from Top to Bottom). (Scale bars, 5 μm.) (B) Number of TERT gene copies (measured via DNA FISH) increases with the number of active transcription sites (number of colocalized exon–intron spots per nucleus measured via smFISH). Error bars represent SEM. For smFISH, n = 55 to 204 cells, depending on the cell line, as shown in Fig. 2A. For DNA FISH, n = 200 cells for each cell line. (C) TERT DNA FISH of repre- sentative metaphase cells from 1 cancer cell line (LN-18) shows TERT triploidy, with arrowheads indicating probe spots, similar to the TERT smFISH and DNA FISH findings for this line. (D) Karyotype analysis of 1 cancer cell line (LN-18) shows triploidy karyotype, similar to the TERT smFISH and DNA FISH findings for this line. In the karyotype analysis, the red arrows indicate sites of chromosomal breaks for each abnormality observed, except for the red arrows above the “M” (the M designates the area of the karyogram where the marker chromosomes [mar] were placed; the red arrows here label each marker chromosome with what it is called [e.g., “mar1”]). DNA FISH probes are shown in red, and DAPI is shown in blue for A and C.

Rowland et al. PNAS | September 10, 2019 | vol. 116 | no. 37 | 18493 Downloaded by guest on September 25, 2021 transcription sites (SI Appendix, Table S1). These findings also align with our gDNA sequencing results showing both cell lines to have similar levels of both alleles. Other cell lines with ap- parent MAE had a greater number of TERT gene copies than an expected 2:1 gene copy/transcription site ratio would cause. For example, U-87 MG cells had ∼2 (2.17 ± 0.04) gene copies and nearly zero (0.19 ± 0.03) transcription sites and SNU-475 cells had ∼3 (3.05 ± 0.04) gene copies and nearly 1 (0.76 ± 0.14) transcription site. For SNU-475 cells, these findings align with our gDNA and RT-PCR sequencing results showing these cells to have relatively greater levels of gDNA of the inactive allele. While U-87 MG cells had relatively greater levels of gDNA of the active allele, our FISH data suggest that only a fraction of these copies are actually active. Another cell line with apparent MAE, LN-18, had ∼3 (3.07 ± 0.06) gene copies and 3 (3.26 ± 0.36) transcription sites per cell, a 1:1 ratio. These findings are surprising because we also found these cells to have relatively greater levels of gDNA of the inactive allele. Overall, it is noteworthy that while all apparently MAE cell lines only express gene copies with one version of a SNP, there is much underlying complexity, with a ratio of inactive to active gene copies not typically being simply 1:1. For the cell lines with apparent BAE of TERT, both allelic versions of the TERT gene would be expected to be active based on our RT-PCR sequencing results. However, our FISH data suggest that 3 of these 4 lines have many TERT gene copies that are inactive at a given time, because there are many more gene copies than active transcription sites. Specifically, SK HEP-1 cells had ∼3 (3.09 ± 0.05) gene copies and nearly 2 (1.90 ± 0.26) transcription sites, DB cells had ∼4 (3.88 ± 0.03) gene copies and 1 (0.83 ± 0.13) transcription site, and HT-1376 cells had ∼10 (10.11 ± 0.24) gene copies and nearly 3 (2.78 ± 0.27) transcription sites. For DB cells, there was a slight preference for 1 allele type to have more active copies than the other, based on our RT-PCR sequencing. This was also seen in HT-1376 cells, although in these cells the active allele was much less common than the inactive allele, based on gDNA sequencing, which aligns with our FISH data showing many more gene copies than tran- scription sites in these cells. HuTu 80, the other apparently BAE cell line, had ∼2 (2.02 ± 0.01) gene copies and 4 (4.07 ± 0.32) apparent “transcription sites,” which is not possible (Discussion). For lines HuTu 80 and SK HEP-1, the active copies appeared to be composed of similar levels of both allele types, based on our RT- PCR sequencing. Overall, for the apparently BAE cell lines, it is interesting that these cells contain many inactive copies of the TERT gene (making up most gene copies for one-half of these cell lines), with the active copies comprising similar levels of both allele versions or a slight preference for one over another.

Telomere Length Has Little Correlation with TERT RNA Levels. To Fig. 4. Telomere restriction fragment (TRF) assay of different cell lines, with determine whether there is a correlation between the number of sizes shown in base pairs and red dots indicating the mean telomere size for TERT TERT each lane. TERT-expressing cancer lines are arranged from least to greatest active transcription sites, TERT RNA levels, or mean number of active transcription sites (from Left to Right). AG02603 and gene copies and the telomere lengths of these cells, we per- AG02261 are both apparently healthy human adult fibroblast cell lines formed telomere restriction fragment (TRF) analysis (Fig. 4). (untransformed) taken from lung and abdomen tissue, respectively. The iPSCs, ALT cells, and several telomerase-positive cancer cell lines (e.g., DB and HuTu 80) had relatively long telomeres, while other cancer lines (e.g., U-87 MG, Panc 10.05, SK HEP-1, cancer lines is ultimately determined by factors beyond TERT HT-1376, NCI-H196) had relatively short telomeres. Densitom- expression alone. etric quantification of the TRF size distributions showed the telomere lengths of the telomerase-positive cancer cell lines and Discussion iPSCs (see SI Appendix, Table S1, for cell line mean values) to Utilizing smFISH, we observed great heterogeneity in the have little correlation with TERT RNA levels, as measured via number of active TERT transcription sites across several differ- qRT-PCR (R2 = 0.35; P = 0.07) (SI Appendix,Fig.S6), and no ent human cancer cell lines and among different cells of a given correlation with the number of active TERT transcription sites line. Comparing these data with TERT DNA FISH assays, we (measured via TERT RNA smFISH; R2 = 0.01) or TERT gene conclude that previous classifications of cancer cell lines as copies (measured via TERT DNA FISH; R2 = 0.15). These ob- having monoallelic or biallelic TERT expression hide much servations suggest that steady-state telomere length in these complexity; the ratios of transcription sites to gene copies in

18494 | www.pnas.org/cgi/doi/10.1073/pnas.1908275116 Rowland et al. Downloaded by guest on September 25, 2021 these lines were often unexpected based on their allelic TERT gene is located, making the DNA FISH and karyotype classification. findings here not so unexpected (11). Here we go on to correlate The variability in single-cell TERT expression levels may re- numbers of TERT genes with numbers of active transcription flect the irregular nature of transcription. The correlation we sites using smFISH. While we found a general positive correla- observed between the number of active transcription sites in- tion (Fig. 3B), we also found that most gene copies are not being creasing with variance within the cell lines (Fig. 2D) supports actively expressed, or are expressed at an undetectably low rate, transcriptional bursting, or long periods of inactivity interspersed at any given time. with short periods of strong activity. Specifically, the observed Because many factors are thought to be involved in deter- variance is nearly equal to the mean (R2 = 0.92), indicative of a mining whether a TERT gene is transcribed into RNA, it is not Poisson distribution, which is supportive of transcriptional surprising that our observed correlation (R2 = 0.42) was not bursting (26). We found that nearly all MAE and BAE lines stronger. For example, genomic rearrangements upstream of, as contained many inactive copies of the TERT gene, which could well as proximal to, TERT have been found to cause increased also be due to transcriptional bursting and the “snapshot pic- TERT expression in some glioblastomas and neuroblastomas ture” that smFISH allows. We were particularly intrigued to find (33, 34). Detecting such subtle rearrangements is beyond the that 6 out of 9 telomerase-positive cancer cell lines had a modal scope of the current study. Cell line-specific variations in the number of transcription sites of zero. The cell lines were not levels of transcription factors that activate or repress TERT ex- synchronized; thus, some cells might be in phases of the cell cycle pression (35) are likely to further complicate correlations between when TERT is not actively transcribed. As described above, gene copy numbers and transcription levels. extremely “bursty” transcription is another possibility; at the We and others have previously classified cancer cell lines as extreme, TERT expression might skip an entire cell cycle and having MAE or BAE of TERT (18, 22, 36), but our current work then compensate in subsequent cycles. Consistent with our reveals that this simple classification is insufficient to capture the findings, a recent study dedicated to development of TERT complexity of TERT gene expression in many cell lines (Table 1 RNAscope as a sensitive assay for visualizing TERT mRNA and SI Appendix, Fig. S5 and Table S1). While 2 apparently observed a similar heterogeneous pattern of TERT expression MAE lines did roughly have the expected 2:1 ratio of TERT gene among HeLa cells (15). (It is worth noting that RNAscope is copies to active transcription start sites (based on our FISH different from smFISH in that it uses an additional amplification data), only 1 of these (Panc 10.05) had ∼2 gene copies and 1

step post probe hybridization, which results in a more intense transcription site, while the other (NCI-H196) had a surprising GENETICS signal compared to the smFISH used here.) Both of these ap- average 11 gene copies and 7 transcription sites (11:7). The 3 proaches support the conclusion that many telomerase-positive remaining apparently MAE lines (U-87 MG, SNU-475, and cancer cell lines display heterogeneity in TERT expression, LN-18) had unexpected ratios (roughly 2:0, 3:1, and 3:3, making it likely that similar heterogeneity in TERT expression is respectively). So, while all apparently MAE lines only express gene present in primary tumors as well. copies with one version of a SNP, there is much underlying Our smFISH experiments also revealed an unexpected sub- complexity, with a ratio of total gene copies to transcription sites cellular distribution for TERT mRNA. Given that spliced mRNAs not typically being simply 2:1. Such unexpected ratios could affect are exported from the nucleus for translation, one would expect studies on TERT that attempt to group these cells primarily most spliced mRNA to be cytoplasmic, although substantial ex- based on allelic status and/or promoter mutation status. For the ceptions have been reported (30). Indeed, for GAPDH mRNA and apparently BAE cancer cell lines, both allelic versions of the for overexpressed TERT mRNA, we observed exonic signal to be TERT gene are active based on our RT-PCR sequencing results, mostly cytoplasmic (Fig. 1 and SI Appendix,Fig.S1). These control and thus the active gene copies must be made up of both allele experiments demonstrate that cytoplasmic RNA is not more diffi- versions. However, our FISH data suggest that these lines rarely cult to detect than nuclear mRNA using smFISH. However, for all have a 2:2 ratio of gene copies to transcription sites, with actual 9 telomerase-positive cancer cell lines and iPSCs, the spliced TERT ratios being roughly 3:2, 4:1, and 10:3 for SK HEP-1, DB, and mRNA (assessed by signal from exon probes only and not intron 2) HT-1376 cell lines, respectively. was mostly nuclear (Fig. 2E and SI Appendix,Fig.S4). This result is HuTu80 was the only cell line that showed fewer TERT genes in line with a report by Malhotra et al. (31), who performed sub- than “transcription sites”; its 2:4 ratio should not be possible. cellular fractionation of GM12878 and HEK-293 cells and found a Many nuclei contained 2 large signals of intron–exon probe substantial fraction of TERT mRNA to be surprisingly nuclear, as colocalization, which may be the transcription sites, and multiple measured by RNA-seq and qRT-PCR. It is possible that these smaller ones, which may be unspliced TERT pre-mRNA re- nuclear transcripts are not fully spliced (our intron probes hybrid- leased from the site of transcription. The hypothesis of decreased ized to the second intron), which could potentially lead to nuclear TERT pre-mRNA splicing efficiency in this particular cell line is retention. Other factors that could give rise to such a noncanonical testable in the future. Alternatively, we cannot rule out hybridiza- distribution of an mRNA include slow export from the nucleus, tion to RNA from a reactivated pseudogene unique to this cell line, low cytoplasmic stability, or possibly some nuclear function of although there have not been reports of a TERT pseudogene. TERT mRNA. In any case, the surprising nuclear localization of Telomere lengths were found to have an unconvincing corre- much TERT mRNA suggests that translatable TERT mRNA lation with TERT RNA levels via qRT-PCR (Fig. 4 and SI Ap- copy numbers are even lower than implied by bulk mRNA pendix, Fig. S6; R2 = 0.35; P = 0.07) and did not correlate with measurements. TERT active transcription site data via smFISH or TERT gene TERT DNA FISH showed several lines to have amplified copy numbers via DNA FISH. Previous studies have also not numbers of the TERT gene, which was independently supported shown a consistent correlation between telomerase activity and by karyotype analysis (Fig. 3D). TERT gene copy amplifications TERT gene copy number (13, 32). Such lack of correlation is not are well known, including at least a subset of the following types surprising, because numerous events separate TERT gene copy of cancer cell lines: bladder, epidermal, neuroblastomas, hepatic, number from telomerase extension of telomeres. These events lung, cervical, breast, colorectal, head and neck, gastrointestinal, include pre-mRNA transcription, splicing, nuclear export, mRNA osteosarcoma, melanoma, and leukemia carcinomas (11, 24, 32). stability, translation, assembly of the telomerase holoenzyme, and Up to 60 copies have been detected in some individual leukemia its recruitment to telomeres, each of which may be subject to cells (32). Of note, a large study examining 2,210 solid tumors regulation. For example, our group has previously found that a spanning 27 tumor tissue types found the eighth most frequent subpopulation of TERT protein subunits is not assembled into the chromosomal gain (13.2% of tumors) to occur in 5p, where the active telomerase ribonucleoprotein (RNP) enzyme, complicating

Rowland et al. PNAS | September 10, 2019 | vol. 116 | no. 37 | 18495 Downloaded by guest on September 25, 2021 correlations between TERT expression and telomere length washing 2 times with PBS. Coverslips were immersed in 70% EtOH and in- measurements (29). Finally, telomere length is a balance between cubated at 4 °C for a minimum of 1 h. Coverslips were then washed with extension and shrinkage, so even if TERT RNA levels correlated 2 mL of wash buffer A (LGC Biosearch Technologies) at RT for 5 min. RNase A-treated controls were incubated in 2 mL of RNase A (200 μg/mL in PBS) for with extension, they would not necessarily always correlate with μ steady-state telomere length. Considering these and other com- 1 h at 37 °C prior washing with wash buffer A. Cells were hybridized with 80 L of hybridization buffer (LGC Biosearch Technologies) containing properly plicating factors, it is not surprising that we did not see a stronger diluted smRNA FISH probes (1:100) overnight at 37 °C in a humid chamber. correlation between telomere length and metrics of TERT ex- The next day, cells were washed with 1 mL of wash buffer A for 30 min at pression or with TERT gene copy number. 37 °C, followed by another wash with wash buffer A containing Hoechst Overall, the data presented here reveal substantial heteroge- DNA stain (1:1,000; Thermo Fisher Scientific) for 30 min at 37 °C. Coverslips neity in TERT expression across human cancers. We show that were washed with 1 mL of wash buffer B (LGC Biosearch Technologies) for 5 TERT expression can be highly variable, both between cancer min at RT, mounted with ProlongGold (Life Technologies) on a glass slide, cell lines and within a given line itself. Being aware of hetero- and left to curate overnight at 4 °C before proceeding to image acquisition geneity within a cell line may be important for designing effective (see below). All smFISH graphs were prepared using GraphPad Prism 8 cancer therapeutics, as subpopulations of cells in a tumor (37) software (version 8.1.0). with higher or lower TERT levels may need to be targeted dif- ferently to avoid drug tolerance. Our finding that classifying smFISH/Anti-FLAG Immunofluorescence. Coverslips intended for anti-FLAG immunofluorescence and smFISH were processed in the same way as de- cancer cell lines as simply monoallelic or biallelic does not scribed above, with the following changes: 1) hybridization buffer contained capture the complexity of their gene expression patterns will also 1:100 dilution of TERT exon and intron probes and 1:800 dilution of primary be important when trying to categorize cancers based on dif- antibody (mouse M2 monoclonal anti-FLAG; F1804; Sigma), and 2) the first ferences in TERT expression. Clearly such allelic classifications wash with wash buffer A after overnight hybridization contained 1:800 di- need to be elaborated upon to properly describe the complex luted anti-mouse secondary antibody labeled with Alexa Fluor 488 (Abcam; regulation processes at play. Single-cell techniques, such as ab150113). smFISH and DNA FISH, are clearly powerful tools that may be necessary for complete classification of allelic behaviors, partic- Microscopy and Image Analysis. Z stacks (200-nm z step) capturing entire cell ularly in cancer cells where heterogeneity occurs, as well as for volume were acquired with a GE wide-field DeltaVision Elite microscope revealing surprising subcellular localizations, such as seen here with an Olympus UPlanSApo 100×/1.40-numerical aperture oil objective lens by the predominantly nuclear localization of spliced TERT and a PCO Edge sCMOS camera using corresponding filters. Three- dimensional stacks were deconvolved using the built-in DeltaVision Soft- mRNA. WoRx Imaging software. Maximum intensity projections of each image were Materials and Methods subjected for quantification using Fiji. Analysis of z-stacked images used to generate the maximum intensity projections was additionally performed in Cell Lines, Culture, and Transfection. Lines SNU-475, DB, NCI-H196 (American 3D to confirm that nuclear intron and exon spots were within the nucleus, Type Culture Collection [ATCC]), and Panc 10.05 (University of Colorado rather than above or below the nucleus. Cancer Center, Protein Production/MoAB/Tissue Culture Shared Resource [PPSR]) were maintained in RPMI-1640 medium (Gibco Thermo Fisher Sci- DNA Isolation, PCR, and Sequencing. gDNA was isolated from cells using Quick- entific). Lines SK HEP-1, HT-13376, HuTu80 (ATCC), AG02603, and AG02261 DNA Miniprep Kit (11-317AC; Zymo Research). Twenty-microliter PCRs were (Coriell Institute) were maintained in Eagle’s minimum essential medium performed using 50 ng of gDNA and Phusion High-Fidelity DNA (EMEM) (Gibco Thermo Fisher Scientific). Lines U-87 MG (PPSR), LN-18 (F-530; Thermo Fisher Scientific) supplemented with 7-deaza-2′-deoxy-guanosine- (ATCC), and U-2 OS [kind gift of David Spector, Cold Spring Harbor Labo- 5′-triphosphate (7-Deaza-dGTP) (10988537001; Sigma-Aldrich) to aid in amplify- ratory, Cold Spring Harbor, NY (38)] were maintained in Dulbecco’s modified ing GC-rich regions. Sequences for primers (Integrated DNA Technologies) are Eagle medium (DMEM) (Gibco Thermo Fisher Scientific). All media were listed in SI Appendix,TableS2. PCR products were purified using E.Z.N.A. Cycle supplemented with 100 μg/mL penicillin and 100 μg/mL streptomycin (Gibco Pure Kit (D6492; Omega Bio-Tek) and underwent Sanger sequencing (GENEWIZ). Thermo Fisher Scientific) and 10% (Sigma-Aldrich), 5% (only line LN-18), or 15% FBS (AG02603 and AG02261). iPSC line WTC-11 (Coriell Institute) was maintained on recombinant human vitronectin (39, 40) (Thermo Fisher Scientific), RNA Extraction, cDNA Synthesis, and qRT-PCR. Total RNA was isolated from coating 6-well tissue culture plastic plates (Thermo Fisher Scientific), with cells using the E.Z.N.A. Total RNA Kit I (R6834; Omega Bio-Tek) and the RNase- Essential 8 Flex Medium (Thermo Fisher Scientific) and passaged using EDTA free DNase Set I (E1091-02; Omega Bio-Tek) to eliminate potentially con- (Thermo Fisher Scientific). All lines were cultured according to recommended taminating DNA. One microgram of RNA was used to synthesize cDNA, using protocols. the SuperScript IV First-Strand Synthesis System (Invitrogen Thermo Fisher For TERT overexpression, 17.5 μg of a plasmid expressing hTERT [kind gift Scientific; 18091050) with random hexamers and RNase H treatment. qRT-PCR of , École polytechnique fédérale de Lausanne (EPFL), Lausanne, was performed with SYBR Select Master Mix (4472908; Thermo Fisher Sci- Switzerland (41)] was transiently transfected into 1 T-150 flask HEK293T cells entific) supplemented with 7-Deaza-dGTP using the LightCycler 480 software using 175 μL of Lipofectamine 2000 solution (52887; Invitrogen) diluted in (Roche). Primers used were previously described (13, 43), except for TERT OptiMem medium for 4 h at 37 °C. Following the 4-h incubation, medium exon 2 primers (primer sequences are listed in SI Appendix, Table S2). Using was changed to DMEM supplemented with 6 mM L-glutamine, 10% FBS, primers to amplify exon 2 omits a significant amount of TERT RNA with a 100 μg/mL penicillin, and 100 μg/mL streptomycin. Following overnight deletion of this exon (44). Primer specificity was confirmed using gel elec- culture at 37 °C, cells were passaged onto cover glasses prepared for smFISH trophoresis, melting temperature analysis, and Sanger sequencing. Ten- at a density of 1.7 × 105 cells/well in 12-well tissue culture plastic plates. microliter qRT-PCRs were run in triplicate on a 96-well plate, and data Following 48 h culture at 37 °C on the cover glasses, cells were fixed were normalized to the geometric mean of 3 “housekeeping” genes (glyc- for smFISH. eraldehyde phosphate dehydrogenase [GPI], glucose phosphate [PPIA], and hydroxymethylbilane synthase [HMBS]). PCR products to be se- smFISH. smFISH was performed as previously described (17, 42). Tiled oligo- quenced were purified using E.Z.N.A. Cycle Pure Kit (D6492; Omega Bio-Tek) targeting TERT intron and TERT exons labeled with Quasar 570 and underwent Sanger sequencing (GENEWIZ). (TERT intron) and Quasar 670 (TERT exon) were designed with LGC Biosearch Technologies’ Stellaris online RNA FISH probe designer (Stellaris Probe De- DNA FISH and Karyotype Analysis. DNA FISH (Empire Genomics; TERT-20-OR) signer, version 4.2) and produced by LGC Biosearch Technologies. As controls of all cell lines and karyotyping of LN-18 cells were performed by the WiCell for active transcription detection and proper hybridization to nuclear and Research Institute Characterization Laboratory. cytoplasmic , we additionally custom-designed targeting GAPDH intron labeled with Quasar 670. GAPDH exon predesigned probe set Telomere Length by Southern Blotting. TRF length analysis was carried out as (42) labeled with Quasar 670 was purchased from LGC Biosearch Technologies. previously described (45–48). Briefly, gDNA was isolated from cells using Cells were seeded on glass coverslips coated with poly-L-lysine (10 μg/mL in Quick-DNA Miniprep Kit (11-317AC; Zymo Research). A total of 1.5 to 4.5 μg PBS). Before hybridization, coverslips were washed 2 times with PBS, fixed in of gDNA from each cell line was digested with RsaI and HinfI. Digested 3.7% formaldehyde in PBS for 10 min at room temperature (RT), followed by gDNA samples were resolved on a 0.8% agarose gel. The DNA was then

18496 | www.pnas.org/cgi/doi/10.1073/pnas.1908275116 Rowland et al. Downloaded by guest on September 25, 2021 transferred to Hybond N+ Nylon membrane (GE), which was probed for useful discussions. We thank Arthur Zaug (T.R.C. laboratory) for assistance

telomeric sequence using a radiolabeled (TTAGGG)4 probe. The membrane with the TERT overexpression and TRF experiments. We thank Roy Parker was imaged using phosphor screens and a Typhoon FLA 9500 Variable Mode and Carolyn Decker (University of Colorado Boulder) for access to, and Imager (GE) (49). To calculate mean telomere length, lane intensity profiles training on, the DeltaVision Elite microscope. We thank the BioFrontiers were extracted and their centers were found using ImageQuant TL, and Advanced Light Microscopy Core and Joe Dragavon (University of Colorado Boulder) for access to image analysis software. We thank Theresa Nahreini lengths of these center points were calculated using a λ-HindIII molecular and Nicole Kethley for use of the Facility (University of Colorado weight marker (NEB). Graphs were prepared using GraphPad Prism 8 soft- Boulder). We thank the WiCell Research Institute Characterization Labora- ware (version 8.1.0). tory, specifically Kim Leonhard and Erik McIntire, for DNA FISH and karyotype analysis and thoughtful discussions. This work was funded by ACKNOWLEDGMENTS. We thank Andrew J. Bonham (Metropolitan State National Institutes of Health Grant R01 GM099705 to T.R.C. T.R.C. is an University of Denver) and Taeyoung Hwang (University of Colorado Boulder) investigator and J.L.R. is a faculty scholar of the Howard Hughes Medical for thoughtful discussions on this work. We thank T.R.C. laboratory members Institute. J.L.R. is the Leslie Orgel Professor in RNA Science and holds a Marvin H. Dan Youmans, Yicheng Long, Josh Stern, Ci Ji Lim, and Anne Gooding for Caruthers Endowed Chair for Early Career Faculty in the BioFrontiers Institute.

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