A pathology atlas of the human cancer transcriptome

Abstract

Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.

Novel MXD4–NUTM1 fusion transcript identified in primary ovarian undifferentiated small round cell sarcoma

“…NUTM1 (NUT midline carcinoma family member 1, also known as C15orf55 or NUT ), which maps to chromosome15q14, is typically expressed in a normal testis but not expressed in many other normal and malignant tissues 35, 3637, 38.…”

Activation of the Farnesoid X-receptor in breast cancer cell lines results in cytotoxicity but not increased migration potential

“…As such, they may represent important targets to instigate metabolic reprogramming of tumour cells, leading to a reduction in supply of the components required for cell growth [10]. Nuclear receptor expression is widespread throughout the body [11], with a number being (over)expressed in breast tumours [12]. Indeed, two of the three major classifiers for breast cancer, the estrogen receptor (ER; NR3A1) and the progesterone receptor (PR; NR3C3), are nuclear receptors, and disruption of their regulatory action is a successful treatment in receptor positive tumours [13,14].…”

Microdevices for Non-Invasive Detection of Bladder Cancer

“…More broadly, application of single-cell transcriptomics to exfoliated bladder cancer cells from a large population of patients would provide a reference transcriptomic dataset of bladder cancer variants, useful for placing patients within a broader context of prior knowledge and for predicting efficacy of potential treatment paths based on historical data [139]. Likewise, techniques for investigating DNA methylation and changes in chromatin accessibility could provide mechanistic insight into the genomic changes that drive alterations in gene expression, cellular physiology, and progression to a cancerous state [140,141].…”