Prostate tumors downregulate microseminoprotein‐beta (MSMB) in the surrounding benign prostate epithelium and this response is associated with tumor aggressiveness

Bergström, Sofia Halin; Järemo, Helena; Nilsson, Maria; Adamo, Hanibal Hani; Bergh, Anders

doi:10.1002/pros.23466

Cited by 20 publications

(14 citation statements)

References 26 publications

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“…Microseminoprotein‐β (MSMB)/Prostate secretory protein of 94 amino acids (PSP94), primarily found in the prostatic secretion, was originally isolated and purified from human seminal plasma. Recent studies have suggested that loss of its expression was associated with PCa aggressiveness 36,37 …”

Section: Discussionmentioning

confidence: 99%

Proteomic and transcriptomic profiling of Pten gene‐knockout mouse model of prostate cancer

Zhang

Kim

et al. 2020

The Prostate

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Background The prostate‐specific phosphatase and tensin homolog deleted on chromosome 10 (Pten) gene‐conditional knockout (KO) mouse carcinogenesis model is highly desirable for studies of prostate cancer biology and chemoprevention due to its close resemblance of primary molecular defect and many histopathological features of human prostate cancer including androgen response and disease progression from prostatic intraepithelial neoplasia to invasive adenocarcinoma. Here, we profiled the proteome and transcriptome of the Pten‐KO mouse prostate tumors for global macromolecular expression alterations for signaling changes and biomarker signatures. Methods For proteomics, four pairs of whole prostates from tissue‐specific conditional knockout Pten‐KO mice (12‐15 weeks of age) and their respective wild‐type littermates housed in the same cages were analyzed by 8‐plex isobaric tags for relative and absolute quantitation iTRAQ. For microarray transcriptomic analysis, three additional matched pairs of prostate/tumor specimens from respective mice at 20 to 22 weeks of age were used. Real‐time quantitative reverse transcription‐polymerase chain reaction was used to verify the trends of protein and RNA expression changes. Gene Set Enrichment Analysis and Ingenuity Pathway Analysis were carried out for bioinformatic characterizations of pathways and networks. Results At the macromolecular level, proteomic and transcriptomic analyses complement and cross‐validate to reveal overexpression signatures including inflammation and immune alterations, in particular, neutrophil/myeloid lineage suppressor cell features, chromatin/histones, ion and nutrient transporters, and select glutathione peroxidases and transferases in Pten‐KO prostate tumors. Suppressed expression patterns in the Pten‐KO prostate tumors included glandular differentiation such as secretory proteins and androgen receptor targets, smooth muscle features, and endoplasmic reticulum stress proteins. Bioinformatic analyses identified immune and inflammation responses as the most profound macromolecular landscape changes, and the predicted key nodal activities through Akt, nuclear factor‐kappaB, and P53 in the Pten‐KO prostate tumor. Comparison with other genetically modified mouse prostate carcinogenesis models revealed notable molecular distinctions, especially the dominance of immune and inflammation features in the Pten‐KO prostate tumors. Conclusions Our work identified prominent macromolecular signatures and key nodal molecules that help to illuminate the patho‐ and immunobiology of Pten‐loss driven prostate cancer and can facilitate the choice of biomarkers for chemoprevention and interception studies in this clinically relevant mouse prostate cancer model.

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Section: Discussionmentioning

confidence: 99%

Proteomic and transcriptomic profiling of Pten gene‐knockout mouse model of prostate cancer

Zhang

Kim

et al. 2020

The Prostate

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“…The association with increased pEGF-R [13], ErbB2 [28], and pAkt [29] signaling in the tumor epithelium, and with multiple signs of a particularly active tumor stroma response [18, 19], such as decreased stroma androgen receptors [30] and caveolin-1 [31], increased angiogenesis [15], high stroma hyaluronic acid [32] and a M2-macrophage (CD163+) [33] and mast cell- [34] associated inflammation suggest several potential targets that deserve future attention. This subgroup of tumors was apparently also associated with expression of the TRMPSS2-ERG fusion gene [35] and with changes in the so called tumor instructed normal tissue, see [8–11], although of moderate magnitude, separating it from prostates with less aggressive tumors.…”

Section: Discussionmentioning

confidence: 99%

“…Using different cut-offs for high and low immunoreactivity, the PSA/Ki67-defined groups were related to outcome in patients managed by watchful waiting and to previously collected data related to biological characteristics of these tumors. As previous studies in animal models and in tissue samples from patients have suggested that prostate tumors influence the surrounding non-malignant parts of the prostate in ways related to tumor aggressiveness, we also examined how the surrounding parts of the prostate were affected/colored/tinted (TINT = tumor instructed/indicating normal tissue), for additional description and references see [8–11].…”

Section: Introductionmentioning

confidence: 99%

Immunoreactivity for prostate specific antigen and Ki67 differentiates subgroups of prostate cancer related to outcome

et al. 2019

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Based on gene-expression profiles, prostate tumors can be subdivided into subtypes with different aggressiveness and response to treatment. We investigated if similar clinically relevant subgroups can be identified simply by the combination of two immunohistochemistry markers: one for tumor cell differentiation (prostate specific antigen, PSA) and one for proliferation (Ki67). This was analyzed in men with prostate cancer diagnosed at transurethral resection of the prostate 1975–1991 (n = 331) where the majority was managed by watchful waiting. Ki67 and PSA immunoreactivity was related to outcome and to tumor characteristics previously associated with prognosis. Increased Ki67 and decreased PSA were associated with poor outcome, and they provided independent prognostic information from Gleason score. A combinatory score for PSA and Ki67 immunoreactivity was produced using the median PSA and Ki67 levels as cut-off (for Ki67 the upper quartile was also evaluated) for differentiation into subgroups. Patients with PSA low/Ki67 high tumors showed higher Gleason score, more advanced tumor stage, and higher risk of prostate cancer death compared to other patients. Their tumor epithelial cells were often ERG positive and expressed higher levels of ErbB2, phosphorylated epidermal growth factor receptor (pEGF-R) and protein kinase B (pAkt), and their tumor stroma showed a reactive response with type 2 macrophage infiltration, high density of blood vessels and hyaluronic acid, and with reduced levels of caveolin-1, androgen receptors, and mast cells. In contrast, men with PSA high/Ki67 low tumors were characterized by low Gleason score, and the most favorable outcome amongst PSA/Ki67-defined subgroups. Men with PSA low/Ki67 low tumors showed clinical and tumor characteristics intermediate of the two groups above. A combinatory PSA/Ki67 immunoreactivity score identifies subgroups of prostate cancers with different epithelial and stroma phenotypes and highly different outcome but the clinical usefulness of this approach needs to be validated in other cohorts.

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“…Further, human MSMB protein is expressed in the prostate, while fly CG34177 protein is expressed in the accessory gland, the fly analog of the mammalian prostate, with both proteins being secreted into seminal fluid in flies and mammals (Mbikay et al 1987; Sitnik et al 2016). Lower levels of expression and allelic variants of the MSMB gene have been associated with prostate cancer (Harries et al 2010; Waters et al 2010; Lou et al 2012; Peng et al 2017; Bergström et al 2018). MSMB and CG34177 are expressed in tissues other than the prostate and accessory gland, including larval imaginal discs, consistent with its knockdown reducing growth of the wing, but the functions of the human and fly proteins have not been defined (Ulvsbäck et al 1989; Graveley et al 2011).…”

Section: Resultsmentioning

confidence: 99%

An RNAi Screen for Genes Required for Growth ofDrosophilaWing Tissue

Rotelli

Bolling

Killion

et al. 2019

G3 Genes|Genomes|Genetics

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Cell division and tissue growth must be coordinated with development. Defects in these processes are the basis for a number of diseases, including developmental malformations and cancer. We have conducted an unbiased RNAi screen for genes that are required for growth in the Drosophila wing, using GAL4-inducible short hairpin RNA (shRNA) fly strains made by the Drosophila RNAi Screening Center. shRNA expression down the center of the larval wing disc using dpp-GAL4, and the central region of the adult wing was then scored for tissue growth and wing hair morphology. Out of 4,753 shRNA crosses that survived to adulthood, 18 had impaired wing growth. FlyBase and the new Alliance of Genome Resources knowledgebases were used to determine the known or predicted functions of these genes and the association of their human orthologs with disease. The function of eight of the genes identified has not been previously defined in Drosophila. The genes identified included those with known or predicted functions in cell cycle, chromosome segregation, morphogenesis, metabolism, steroid processing, transcription, and translation. All but one of the genes are similar to those in humans, and many are associated with disease. Knockdown of lin-52, a subunit of the Myb-MuvB transcription factor, or βNACtes6, a gene involved in protein folding and trafficking, resulted in a switch from cell proliferation to an endoreplication growth program through which wing tissue grew by an increase in cell size (hypertrophy). It is anticipated that further analysis of the genes that we have identified will reveal new mechanisms that regulate tissue growth during development.

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Prostate tumors downregulate microseminoprotein‐beta (MSMB) in the surrounding benign prostate epithelium and this response is associated with tumor aggressiveness

Cited by 20 publications

References 26 publications

Proteomic and transcriptomic profiling of Pten gene‐knockout mouse model of prostate cancer

Proteomic and transcriptomic profiling of Pten gene‐knockout mouse model of prostate cancer

Immunoreactivity for prostate specific antigen and Ki67 differentiates subgroups of prostate cancer related to outcome

An RNAi Screen for Genes Required for Growth ofDrosophilaWing Tissue

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