The translational landscape of mTOR signalling steers cancer initiation and metastasis.

The mammalian target of rapamycin (mTOR) kinase is a master regulator of protein synthesis that couples nutrient sensing to cell growth and cancer. However, the downstream translationally regulated nodes of gene expression that may direct cancer development are poorly characterized. Using ribosome profiling, we uncover specialized translation of the prostate cancer genome by oncogenic mTOR signalling, revealing a remarkably specific repertoire of genes involved in cell proliferation, metabolism and invasion. We extend these findings by functionally characterizing a class of translationally controlled pro-invasion messenger RNAs that we show direct prostate cancer invasion and metastasis downstream of oncogenic mTOR signalling. Furthermore, we develop a clinically relevant ATP site inhibitor of mTOR, INK128, which reprograms this gene expression signature with therapeutic benefit for prostate cancer metastasis, for which there is presently no cure. Together, these findings extend our understanding of how the 'cancerous' translation machinery steers specific cancer cell behaviours, including metastasis, and may be therapeutically targeted.

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system's use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications.

Effects of the herbal extract PC-SPES on microtubule dynamics and paclitaxel-mediated prostate tumor growth inhibition.

BACKGROUND: PC-SPES is a botanical preparation shown to have efficacy in patients with androgen-dependent and androgen-independent prostate carcinoma. Several herbal constituents in PC-SPES inhibit tumor growth through cell cycle arrest and apoptosis, although the mechanisms of these activities are poorly defined. We sought to identify PC-SPES-induced changes in gene expression, specifically in those genes encoding cytoskeletal proteins that could be associated with PC-SPES-induced cytoxicity. METHODS: LNCaP prostate carcinoma cells were treated with PC-SPES, and changes in gene expression were determined by complementary DNA (cDNA) microarray hybridization and northern blot analyses. PC-SPES and paclitaxel, a microtubule-stabilizing drug, effects on microtubules were assessed by immunofluorescence of treated cells and by in vitro tubulin polymerization assays. In vivo effects of PC-SPES and paclitaxel were assessed using CWR22R androgen-independent prostate cancer xenografts. All statistical tests were two-sided. RESULTS: PC-SPES treatment of LNCaP cells for 24 hours altered the expression of 17 cytoskeletal genes. mRNA levels of alpha-tubulin decreased sevenfold. Although paclitaxel stabilized and PC-SPES treatment disrupted microtubule architecture in LNCaP cells, the combination of both agents had an intermediate effect. PC-SPES inhibited tubulin polymerization in vitro, even in the presence of paclitaxel. Compared with tumors in control mice (mean tumor volume = 2983 mm(3), 95% confidence interval [CI] = 2380 to 3586 mm(3)), tumors were statistically significantly smaller in mice that received PC-SPES (mean tumor volume = 2018 mm(3), 95% CI = 1450 to 2568 mm(3); P =.028), paclitaxel (mean tumor volume = 1340 mm(3), 95% CI = 697 to 1983 mm(3); P<.001), or the combination of PC-SPES and paclitaxel (mean tumor volume = 1955 mm(3), 95% CI = 1260 to 2650 mm(3); P =.034). CONCLUSION: PC-SPES may interfere with microtubule polymerization. This activity has implications for the clinical management of patients with advanced prostate cancer who may be taking PC-SPES concurrently with microtubule-modulating chemotherapeutic agents, such as paclitaxel.

The androgen receptor represses transforming growth factor-beta signaling through interaction with Smad3.

In the prostate, androgens negatively regulate the expression of transforming growth factor-beta (TGF-beta) ligands and receptors and Smad activation through unknown mechanisms. We show that androgens (dihydrotestosterone and R1881) down-regulate TGF-beta1-induced expression of TGF-beta1, c-Fos, and Egr-1 in the human prostate adenocarcinoma cell line, LNCaP. Moreover, 5alpha-dihydrotestosterone (DHT) inhibits TGF-beta1 activation of three TGF-beta1-responsive promoter constructs, 3TP-luciferase, AP-1-luciferase, and SBE4(BV)-luciferase, in LNCaP cells either with or without enforced expression of TGF-beta receptors (TbetaRI and TbetaRII). Similarly, DHT inhibits the activation of Smad-binding element (SBE)4(BV)-luciferase by either constitutively activated TbetaRI (T204D) or constitutively activated Smad3 (S3*). Activation of SBE4(BV)-luciferase by S3* in the NRP-154 prostatic cell line, which is androgen receptor (AR)-negative but highly responsive to TGF-beta1, is blocked by co-transfection with either full-length AR or AR missing the DNA binding domain. Immunoprecipitation and GST pull-down assays show that AR directly associates with Smad3 but not Smad2 or Smad4. Electrophoretic mobility shift assays indicate that the AR ligand binding domain directly inhibits the association of Smad3 to the Smad-binding element. In conclusion, our data demonstrate for the first time that ligand-bound AR inhibits TGF-beta transcriptional responses through selectively repressing the binding of Smad3 to SBE.