Overexpression of Periostin in Tumor Biopsy Samples Is Associated With Prostate Cancer Phenotype and Clinical Outcome

Cattrini, Carlo; Rubagotti, Alessandra; Nuzzo, Pier Vitale; Zinoli, Linda; Salvi, Sandra; Boccardo, Simona; Perachino, Marta; Cerbone, Luigi; Vallome, Giacomo; Latocca, Maria Maddalena; Zanardi, Elisa; Boccardo, Francesco

doi:10.1016/j.clgc.2018.07.019

Cited by 10 publications

(9 citation statements)

References 22 publications

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“…Then, we identified a total of 23 ARGs that significantly correlated with PCa patients' survival. In concordance with previous studies which investigate the ARG solely in prostate cancer, genes including NRP1 (Tse et al 2017), JAG2 (Kwon et al 2016), COL5A2 (Ren et al 2021), POSTN (Cattrini et al 2018), FSTL1 (Zhao et al 2019), PF4 (Baselga et al 2008), JAG1 (Terada et al 2014), COL3A1 (Angel et al 2020), VCAN (Asano et al 2017), VEGFA (Zhan et al 2013), SPP1 (Pang et al 2019), VTN (Niu et al 2016), and S100A4 (Ganaie et al 2020) were identified as unfavorable prognosis-related biomarkers in prostate cancer. Meanwhile, the prognosis roles of APP (Takayama et al 2009) and FGFR1 (Yang et al 2013b) were controversial with previous studies, which needed further validation and study.…”

Section: Discussionsupporting

confidence: 88%

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

Dai

Zhu

et al. 2022

Mol Med

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Angiogenesis plays the critical roles in promoting tumor progression, aggressiveness, and metastasis. Although few studies have revealed some angiogenesis-related genes (ARGs) could serve as prognosis-related biomarkers for the prostate cancer (PCa), the integrated role of ARGs has not been systematically studied. The RNA-sequencing data and clinical information of prostate adenocarcinoma (PRAD) were downloaded from The Cancer Genome Atlas (TCGA) as discovery dataset. Twenty-three ARGs in total were identified to be correlated with prognosis of PRAD by the univariate Cox regression analysis, and a 19-ARG signature was further developed with significant correlation with the disease-free survival (DFS) of PRAD by the least absolute shrinkage and selection operator (LASSO) Cox regression with tenfold cross-validation. The signature stratified PRAD patients into high- and low-ARGs signature score groups, and those with high ARGs signature score were associated with significantly poorer outcomes (median DFS: 62.71 months vs unreached, p < 0.0001). The predicting ability of ARGs signature was subsequently validated in two independent cohorts of GSE40272 & PRAD_MSKCC. Notably, the 19-ARG signature outperformed the typical clinical features or each involved ARG in predicting the DFS of PRAD. Furthermore, a prognostic nomogram was constructed with three independent prognostic factors, including the ARGs signature, T stage and Gleason score. The predicted results from the nomogram (C-index = 0.799, 95%CI = 0.744–0.854) matched well with the observed outcomes, which was verified by the calibration curves. The values of area under receiver operating characteristic curve (AUC) for DFS at 1-, 3-, 5-year for the nomogram were 0.82, 0.83, and 0.83, respectively, indicating the performance of nomogram model is of reasonably high accuracy and robustness. Moreover, functional enrichment analysis demonstrated the potential targets of E2F targets, G2M checkpoint pathways, and cell cycle pathways to suppress the PRAD progression. Of note, the high-risk PRAD patients were more sensitive to immune therapies, but Treg might hinder benefits from immunotherapies. Additionally, this established tool also could predict response to neoadjuvant androgen deprivation therapy (ADT) and some chemotherapy drugs, such as cisplatin, paclitaxel, and docetaxel, etc. The novel ARGs signature, with prognostic significance, can further promote the application of targeted therapies in different stratifications of PCa patients.

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Section: Discussionsupporting

confidence: 88%

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

Dai

Zhu

et al. 2022

Mol Med

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“…The overexpression of these proteins in osteoblastic prostate cancer has been reported to be related to an increase in tumorigenicity in vivo 59 . Additional proteins of interest that were observed with significant increased levels in recurrent versus nonrecurrent patients in our data set include POSTN a secreted protein that has been associated with prostate cancer development and progression, 60 EPCAM a protein with expression levels correlated with Gleason score and bone metastasis in prostate cancer patients, 61 and RPSA a protein significantly associated with invasion and metastasis in pancreatic cancer 62 . Protein‐binding activity modulator (PC00095) and protein‐modifying enzymes (PC00260) such a DPP4, a protein that has been identified as a tumor suppressor gene during progression to castration‐resistant prostate cancer, 63 was observed to have decreased levels in recurrent prostate cancer.…”

Section: Discussionmentioning

confidence: 83%

Protein signatures to distinguish aggressive from indolent prostate cancer

et al. 2022

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Background Distinguishing men with aggressive from indolent prostate cancer is critical to decisions in the management of clinically localized prostate cancer. Molecular signatures of aggressive disease could help men overcome this major clinical challenge by reducing unnecessary treatment and allowing more appropriate treatment of aggressive disease. Methods We performed a mass spectrometry‐based proteomic analysis of normal and malignant prostate tissues from 22 men who underwent surgery for prostate cancer. Prostate cancer samples included Grade Groups (3–5), with 8 patients experiencing recurrence and 14 without evidence of recurrence with a mean of 6.8 years of follow‐up. To better understand the biological pathways underlying prostate cancer aggressiveness, we performed a systems biology analysis and gene enrichment analysis. Proteins that distinguished recurrent from nonrecurrent cancer were chosen for validation by immunohistochemical analysis on tissue microarrays containing samples from a larger cohort of patients with recurrent and nonrecurrent prostate cancer. Results In all, 24,037 unique peptides (false discovery rate < 1%) corresponding to 3,313 distinct proteins were identified with absolute abundance ranges spanning seven orders of magnitude. Of these proteins, 115 showed significantly (p < 0.01) different levels in tissues from recurrent versus nonrecurrent cancers. Analysis of all differentially expressed proteins in recurrent and nonrecurrent cases identified several protein networks, most prominently one in which approximately 24% of the proteins in the network were regulated by the YY1 transcription factor (adjusted p < 0.001). Strong immunohistochemical staining levels of three differentially expressed proteins, POSTN, CALR, and CTSD, on a tissue microarray validated their association with shorter patient survival. Conclusions The protein signatures identified could improve understanding of the molecular drivers of aggressive prostate cancer and be used as candidate prognostic biomarkers.

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“…Several reports have demonstrated that high periostin expression correlates with higher GG of prostate cancer 19,25,26 and worse patient prognosis. 26,27 We revealed that high GG and low periostin expression were associated with pEPE. This discrepancy possibly arises from cutoff differences of GG among studies.…”

Section: Discussionmentioning

confidence: 99%

Histological parameters and stromal desmoplastic status affecting accurate diagnosis of extraprostatic extension of prostate cancer using multi‐parametric magnetic resonance imaging

Okano,

Miyai,

Mikoshi

et al. 2024

Int J of Urology

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ObjectiveTo investigate the clinicopathological factors affecting discrepancies between multi‐parametric magnetic resonance imaging (mpMRI) and histopathological evaluation for diagnosis of extraprostatic extension (EPE) of prostate cancer.MethodsOne hundred‐and‐three lesions from 96 cases with suspected EPE on preoperative mpMRI, of which 60 and 43 showed bulging and frank capsular breach, respectively, were grouped according to pathological (p)EPE in radical prostatectomy specimens. Additionally, clinicopathological/immunohistochemical findings for periostin reflecting a desmoplastic stromal reaction were compared between these groups.ResultspEPE was detected in 49 (48%) of the 103 lesions. Of these, 25 (42%) showed bulging and 24 (56%) showed frank capsular breach on MRI. In the total cohort, the absence of pEPE was significantly associated with a lower Gleason Grade Group (GG) (p < 0.0001), anterior location (p = 0.003), absence of intraductal carcinoma of the prostate (IDC‐P) (p = 0.026), and high stromal periostin expression (p < 0.0001). These trends were preserved in subgroups defined by MRI findings, except for anterior location/IDC‐P in the bulging subgroup.ConclusionsGG, anterior location, and periostin expression may cause mpMRI–pathological discrepancies regarding EPE. Periostin expression was a significant pEPE‐negative factor in all subgroup analyses. Our results indicate that patients with suspected EPE on MRI, regardless of their pEPE results, should be followed as carefully as those with definite pEPE.

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Overexpression of Periostin in Tumor Biopsy Samples Is Associated With Prostate Cancer Phenotype and Clinical Outcome

Cited by 10 publications

References 22 publications

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

The novel transcriptomic signature of angiogenesis predicts clinical outcome, tumor microenvironment and treatment response for prostate adenocarcinoma

Protein signatures to distinguish aggressive from indolent prostate cancer

Histological parameters and stromal desmoplastic status affecting accurate diagnosis of extraprostatic extension of prostate cancer using multi‐parametric magnetic resonance imaging

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