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      Homing in on a Moving Target: Androgen Receptor Cistromic Plasticity in Prostate Cancer

      , ,
      Endocrinology
      The Endocrine Society

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          Abstract

          The androgen receptor (AR) is the critical driver in prostate cancer and exerts its function mainly through transcriptional control. Recent advances in clinical studies and cell line models have illustrated that AR chromatin binding features are not static; rather they are highly variable yet reproducibly altered between clinical stages. Extensive genomic analyses of AR chromatin binding features in different disease stages have revealed a high degree of plasticity of AR chromatin interactions in clinical samples. Mechanistically, AR chromatin binding patterns are associated with specific somatic mutations on AR and other permutations, including mutations of AR-interacting proteins. Here we summarize the most recent studies on how the AR cistrome is dynamically altered in prostate cancer models and patient samples, and what implications this has for the identification of therapeutic targets to avoid the emergence of treatment resistance.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation

            Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.
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              Organoid cultures derived from patients with advanced prostate cancer.

              The lack of in vitro prostate cancer models that recapitulate the diversity of human prostate cancer has hampered progress in understanding disease pathogenesis and therapy response. Using a 3D organoid system, we report success in long-term culture of prostate cancer from biopsy specimens and circulating tumor cells. The first seven fully characterized organoid lines recapitulate the molecular diversity of prostate cancer subtypes, including TMPRSS2-ERG fusion, SPOP mutation, SPINK1 overexpression, and CHD1 loss. Whole-exome sequencing shows a low mutational burden, consistent with genomics studies, but with mutations in FOXA1 and PIK3R1, as well as in DNA repair and chromatin modifier pathways that have been reported in advanced disease. Loss of p53 and RB tumor suppressor pathway function are the most common feature shared across the organoid lines. The methodology described here should enable the generation of a large repertoire of patient-derived prostate cancer lines amenable to genetic and pharmacologic studies. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Endocrinology
                The Endocrine Society
                1945-7170
                November 01 2022
                October 11 2022
                November 01 2022
                October 11 2022
                September 20 2022
                : 163
                : 11
                Article
                10.1210/endocr/bqac153
                36125208
                cf86abaa-6c73-490d-8137-d5e209102e50
                © 2022

                https://academic.oup.com/pages/standard-publication-reuse-rights

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