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      PTEN and Other PtdIns(3,4,5)P 3 Lipid Phosphatases in Breast Cancer

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          Abstract

          The phosphoinositide 3-kinase (PI3K)/AKT signalling pathway is hyperactivated in ~70% of breast cancers. Class I PI3K generates PtdIns(3,4,5)P 3 at the plasma membrane in response to growth factor stimulation, leading to AKT activation to drive cell proliferation, survival and migration. PTEN negatively regulates PI3K/AKT signalling by dephosphorylating PtdIns(3,4,5)P 3 to form PtdIns(4,5)P 2. PtdIns(3,4,5)P 3 can also be hydrolysed by the inositol polyphosphate 5-phosphatases (5-phosphatases) to produce PtdIns(3,4)P 2. Interestingly, while PTEN is a bona fide tumour suppressor and is frequently mutated/lost in breast cancer, 5-phosphatases such as PIPP, SHIP2 and SYNJ2, have demonstrated more diverse roles in regulating mammary tumourigenesis. Reduced PIPP expression is associated with triple negative breast cancers and reduced relapse-free and overall survival. Although PIPP depletion enhances AKT phosphorylation and supports tumour growth, this also inhibits cell migration and metastasis in vivo, in a breast cancer oncogene-driven murine model. Paradoxically, SHIP2 and SYNJ2 are increased in primary breast tumours, which correlates with invasive disease and reduced survival. SHIP2 or SYNJ2 overexpression promotes breast tumourigenesis via AKT-dependent and independent mechanisms. This review will discuss how PTEN, PIPP, SHIP2 and SYNJ2 distinctly regulate multiple functional targets, and the mechanisms by which dysregulation of these distinct phosphoinositide phosphatases differentially affect breast cancer progression.

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          Cancer statistics, 2020

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
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            COSMIC: the Catalogue Of Somatic Mutations In Cancer

            Abstract COSMIC, the Catalogue Of Somatic Mutations In Cancer (https://cancer.sanger.ac.uk) is the most detailed and comprehensive resource for exploring the effect of somatic mutations in human cancer. The latest release, COSMIC v86 (August 2018), includes almost 6 million coding mutations across 1.4 million tumour samples, curated from over 26 000 publications. In addition to coding mutations, COSMIC covers all the genetic mechanisms by which somatic mutations promote cancer, including non-coding mutations, gene fusions, copy-number variants and drug-resistance mutations. COSMIC is primarily hand-curated, ensuring quality, accuracy and descriptive data capture. Building on our manual curation processes, we are introducing new initiatives that allow us to prioritize key genes and diseases, and to react more quickly and comprehensively to new findings in the literature. Alongside improvements to the public website and data-download systems, new functionality in COSMIC-3D allows exploration of mutations within three-dimensional protein structures, their protein structural and functional impacts, and implications for druggability. In parallel with COSMIC’s deep and broad variant coverage, the Cancer Gene Census (CGC) describes a curated catalogue of genes driving every form of human cancer. Currently describing 719 genes, the CGC has recently introduced functional descriptions of how each gene drives disease, summarized into the 10 cancer Hallmarks.
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              Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications.

              The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                02 December 2020
                December 2020
                : 21
                : 23
                : 9189
                Affiliations
                Cancer Program, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia; mariah.csolle@ 123456monash.edu (M.P.C.); lisa.ooms@ 123456monash.edu (L.M.O.); antonella.papa@ 123456monash.edu (A.P.)
                Author notes
                [* ]Correspondence: christina.mitchell@ 123456monash.edu ; Tel.: +61-3-9905-4318
                Author information
                https://orcid.org/0000-0001-8653-7121
                Article
                ijms-21-09189
                10.3390/ijms21239189
                7730566
                33276499
                d9f63a85-1866-45ca-a3cd-2815ac86b0ec
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 04 November 2020
                : 01 December 2020
                Categories
                Review

                Molecular biology
                phosphoinositide 3-kinase (pi3k),akt,inositol polyphosphate phosphatases,phosphatase tensin homolog deleted on chromosome 10 (pten),proline rich inositol polyphosphate 5-phosphatase (pipp),src homology 2-containing inositol phosphatase 2 (ship2),synaptojanin 2 (synj2),breast cancer

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