Abstract:Lethal progression of prostate cancer metastasis can be improved by developing animal models that recapitulate the clinical conditions. We report here that cytokeratin 13 (KRT13), an intermediate filament protein, plays a directive role in prostate cancer bone, brain, and soft tissue metastases. KRT13 expression was elevated in bone, brain, and soft tissue metastatic prostate cancer cell lines and in primary and metastatic clinical prostate, lung, and breast cancer specimens. When KRT13 expression was determin… Show more
Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.
Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.
“…A recent study similarly identified KRT13 as enriched in human fetal prostate epithelial cells and confirmed it as a marker for the stem/progenitor population in adult prostate tissue (Liu et al, 2016). Of note, KRT13 plays a directive role in prostate cancer metastasis and its expression in primary prostate tumors is predictive of metastasis and lower survival (Li et al, 2016). Little is known about PRAC1 , which encodes a small nuclear protein in human prostate and bladder cancer with prognostic capability (Kim et al, 2015; Lenka et al, 2013).…”
Using primary cultures of normal human prostate epithelial cells, we developed a novel prostasphere-based, label-retention assay that permits identification and isolation of stem cells at a single cell level. Their bona fide stem cell nature was corroborated using in vitro and in vivo regenerative assays and documentation of symmetric/asymmetric division. Robust WNT10B and KRT13 levels without E-cadherin or KRT14 staining distinguished individual stem cells from daughter progenitors in spheroids. Following FACS to isolate label-retaining stem cells from label-free progenitors, RNA-seq identified unique gene signatures for the separate populations which may serve as useful biomarkers. Knockdown of KRT13 or PRAC1 reduced sphere formation and symmetric self-renewal highlighting their role in stem cell maintenance. Pathways enrichment identified ribosome biogenesis and membrane estrogen-receptor signaling in stem cells with NF-κB signaling enriched in progenitors; activities that were biologically confirmed. Further, bioassays identified heightened autophagy flux and reduced metabolism in stem cells relative to progenitors. These approaches similarly identified stem-like cells from prostate cancer specimens and prostate, breast and colon cancer cell lines suggesting wide applicability. Together, the present studies isolate and identify unique characteristics of normal human prostate stem cells and uncover processes that maintain stem cell homeostasis in the prostate gland.
“…For example, FK866, a non-competitive highly specific inhibitor of NAMPT, shows potent anti-tumor activity both in vitro and in vivo [ 61 ] on pancreatic cancer samples overexpressing NAMPT mRNA. Among the other genes of our signature upregulated in STS samples are C16orf74 and KRT13 , which are associated with poor OS in pancreatic [ 62 ] and prostate [ 63 ] cancers.…”
BackgroundPancreatic carcinoma is one of the most lethal human cancers. In patients with resectable tumors, surgery followed by adjuvant chemotherapy is the only curative treatment. However, the 5-year survival is 20%. Because of a strong metastatic propensity, neoadjuvant chemotherapy is being tested in randomized clinical trials. In this context, improving the selection of patients for immediate surgery or neoadjuvant chemotherapy is crucial, and high-throughput molecular analyses may help; the present study aims to address this.MethodsClinicopathological and gene expression data of 695 pancreatic carcinoma samples were collected from nine datasets and supervised analysis was applied to search for a gene expression signature predictive for overall survival (OS) in the 601 informative operated patients. The signature was identified in a learning set of patients and tested for its robustness in a large independent validation set.ResultsSupervised analysis identified 1400 genes differentially expressed between two selected patient groups in the learning set, namely 17 long-term survivors (LTS; ≥ 36 months after surgery) and 22 short-term survivors (STS; dead of disease between 2 and 6 months after surgery). From these, a 25-gene prognostic classifier was developed, which identified two classes (“STS-like” and “LTS-like”) in the independent validation set (n = 562), with a 25% (95% CI 18–33) and 48% (95% CI 42–54) 2-year OS (P = 4.33 × 10–9), respectively. Importantly, the prognostic value of this classifier was independent from both clinicopathological prognostic features and molecular subtypes in multivariate analysis, and existed in each of the nine datasets separately. The generation of 100,000 random gene signatures by a resampling scheme showed the non-random nature of our prognostic classifier.ConclusionThis study, the largest prognostic study of gene expression profiles in pancreatic carcinoma, reports a 25-gene signature associated with post-operative OS independently of classical factors and molecular subtypes. This classifier may help select patients with resectable disease for either immediate surgery (the LTS-like class) or neoadjuvant chemotherapy (the STS-like class). Its assessment in the current prospective trials of adjuvant and neoadjuvant chemotherapy trials is warranted, as well as the functional analysis of the classifier genes, which may provide new therapeutic targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0936-z) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
