Cancer. TERT promoter mutations and telomerase reactivation in urothelial cancer

Abstract

Reactivation of telomerase, the chromosome end-replicating enzyme, drives human cell immortality and cancer. Point mutations in the telomerase reverse transcriptase (TERT) gene promoter occur at high frequency in multiple cancers, including urothelial cancer (UC), but their effect on telomerase function has been unclear. In a study of 23 human UC cell lines, we show that these promoter mutations correlate with higher levels of TERT messenger RNA (mRNA), TERT protein, telomerase enzymatic activity, and telomere length. Although previous studies found no relation between TERT promoter mutations and UC patient outcome, we find that elevated TERT mRNA expression strongly correlates with reduced disease-specific survival in two independent UC patient cohorts (n = 35; n = 87). These results suggest that high telomerase activity may be a better marker of aggressive UC tumors than TERT promoter mutations alone.

Fig. 1. TERT gene copy number and promoter mutations in UC cell lines

(A) Map of the proximal TERT promoter. Relevant mutations, the major annotated TSS and the translational start codon (+1) are indicated. (B) TERT CNV (top) and TERT promoter genotype (bottom) in the UC23 and in reference cell lines (Ctrls). The genes TATA Binding Protein (TBP), Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) or Metastasis Associated Lung Adenocarcinoma Transcript 1 (MALAT1) were used for normalization.

Fig. 2. TERT promoter mutations are associated with increased TERT mRNA and protein and telomerase activity

(A) Quantification of TERT mRNA in cell lines with wild-type versus mutant TERT promoters by qRT-PCR amplification of exon 14 normalized to 18S rRNA or GAPDH mRNA. (Throughout this work, “mRNA” refers to transcripts containing TERT exon 14 or exon 3, which will include alternatively spliced variants that do not yield a functional RT.) Two cell lines that are wild-type at −124/−146 have the −57 A>C mutation (gray dots). T24T is a more tumorigenic variant of T24, and SLT4 and FL3 were derived from tumors that had metastasized in mice injected with T24T cells (these cell lines are indicated with magenta dots; also see tables S1–S3). (B) Quantification of TERT protein by IP followed by immunoblot. (C) Representative immunoblots showing TERT protein levels in several of the UC23. IP ctrl, see Supplemental Methods. The efficiency of IP was found to be similar from lysates prepared from each cell line (fig. S4). (D) Quantification of telomerase activities in UC23 cell extracts, measured by extension of a telomeric oligonucleotide in the presence of [α-³²P]dGTP. (E) Representative autoradiogram of telomeric oligonucleotides extended by telomerase following TERT IP. LC, DNA loading control. (F) Log₂(telomerase activity) versus log₂(TERT mRNA) for each of the UC23. Cell lines are color-coded as in panel A. (G) Log₂(telomerase activity) versus log₂(TERT protein). (H) Log₂(telomerase activity) versus log₂(TR RNA). In G and H, molecules/cell calculated as in (25).

Fig. 3. TERT promoter mutations are associated with long telomeres in the UC23, as determined by telomeric restriction fragment (TRF) analysis

(A) Southern blot with a telomeric DNA probe was performed as in (34). Standards, TRFs from HeLa cell lines previously characterized as having long, intermediate, or short telomeres (34). (B) Quantification of TRFs in wild-type versus promoter-mutant cell lines; dots colored as in Fig. 2.

Fig. 4. Tumor expression level of TERT mRNA is inversely associated with disease-specific survival of patients with UC

The prognostic value of TERT mRNA expression for DSS in patients who underwent radical cystectomy and who did not receive chemotherapy or additional treatments before or after cystectomy in the (A) CNUH and (B) MSKCC cohorts. Kaplan-Meier curves for patients with low and high expression levels of TERT mRNA were generated (Supplementary Materials) and the corresponding log-rank p-values and hazard ratios (HR) are as indicated. CNUH data include only patients with muscle-invasive tumors, while MSKCC data include patients both with muscle-invasive tumors and non-invasive tumors. A similar analysis could not be performed using the The Cancer Genome Atlas since this dataset is not limited to DSS.