Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 59,633 bioRxiv papers from 265,294 authors.
The mammalian circadian clock is a critical regulator of metabolism and cell division. Although multiple lines of evidence indicate that systemic disruption of the circadian clock can promote cancer, whether the clock is disrupted in primary human tumors is unknown. Here we used transcriptome data from mice to define a signature of the mammalian circadian clock based on the co-expression of 12 genes that form the core clock or are directly controlled by the clock. Our approach can be applied to samples that are not labeled with time of day and were not acquired over the entire circadian (24-h) cycle. We validated the clock signature in transcriptome data from healthy human tissues, then developed a metric we call the delta clock correlation distance (ΔCCD) to describe the extent to which the signature is perturbed in samples from one condition relative to another. We calculated the ΔCCD comparing human tumor and non-tumor samples from The Cancer Genome Atlas and eight independent datasets, discovering widespread dysregulation of clock gene co-expression in tumor samples. Subsequent analysis of data from clock gene knockouts in mice suggested that clock dysregulation in human cancer is not caused solely by loss of activity of clock genes. Furthermore, by analyzing a large set of genes previously inferred to be rhythmic in healthy human lung, we found that dysregulation of the clock in human lung cancer is accompanied by dysregulation of broader patterns of circadian co-expression. Our findings suggest that clock dysregulation is a common means by which human cancers achieve unrestrained growth and division, and that restoring clock function could be a viable therapeutic strategy in multiple cancer types. In addition, our approach opens the door to using publicly available transcriptome data to quantify clock disruption in a multitude of human phenotypes. Our method is available as a web application at https://hugheylab.shinyapps.io/deltaccd.
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