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bioRxiv2016

Cancer cells with alternative lengthening of telomeres do not display a general hypersensitivity to ATR inhibition

Telomere maintenance is a hallmark of cancer as it provides cancer cells with cellular immortality. A significant fraction of tumors uses the alternative lengthening of telomeres (ALT) pathway to elongate their telomeres and to gain an unlimited proliferation potential. Since the ALT pathway is unique to cancer cells, it represents a potentially valuable, currently unexploited target for anticancer therapies. Recently, it was proposed that ALT renders cells hypersensitive to ataxia telangiectasia-and RAD3-related (ATR) protein inhibitors (Flynn et al., Science 347, 273). Here, we measured the response of various ALT or telomerase positive cell lines to the ATR inhibitor VE-821. In addition, we compared the effect of the inhibitor on cell viability in an isogenic cell line, in which ALT was active or suppressed. In these experiments a general ATR inhibitor sensitivity of cells with ALT could not be confirmed. We rather propose that the observed variations in sensitivity reflect differences between cell lines that are unrelated to ALT.

Cancer Biology↗

bioRxiv2016

Quantification of telomere features in tumor tissue sections by an automated 3D imaging-based workflow

The microscopic analysis of telomere features provides a wealth of information on the mechanism by which tumor cells maintain their unlimited proliferative potential. Accordingly, the analysis of telomeres in tissue sections of patient tumor samples provides can be exploited to obtain diagnostic information and to define tumor subgroups. In many instances, however, analysis of the image data is conducted by manual inspection of 2D images at relatively low resolution for only a small part of the sample. As the telomere feature signal distribution is frequently heterogeneous, this approach is prone to a biased selection of the information present in the image and lacks subcellular details. Here we address these issues by using an automated high-resolution imaging and analysis workflow that quantifies individual telomere features on tissue sections for a large number of cells. The approach is particularly suited to assess telomere heterogeneity and low abundant cellular sub-populations with distinct telomere characteristics in a reproducible manner. It comprises the integration of multi-color fluorescence in situ hybridization, immunofluorescence and DNA staining with targeted automated 3D fluorescence microscopy and image analysis. We apply our method to telomeres in glioblastoma and prostate cancer samples, and describe how the imaging data can be used to derive statistically reliable information on telomere length distribution or colocalization with PML nuclear bodies. We anticipate that relating this approach to clinical outcome data will prove to be valuable for pretherapeutic patient stratification.\n\nAbbreviations

Cancer Biology↗