Literature DB >> 23303017

Correlations between intratumoral interstitial fibrillary network and tumoral architecture in prostatic adenocarcinoma.

A Stoiculescu1, I E Pleşea, O T Pop, D O Alexandru, M Man, M Serbănescu, R M Pleşea.   

Abstract

The authors made a preliminary assessment of possible correlations between the amount of intratumoral stromal fibrillary components (ISFC) and the architectural tumoral patterns described by Gleason. The studied material consisted of samples obtained by transurethral resection from 34 patients diagnosed with prostatic adenocarcinoma. Ten fields, five for dominant and five for secondary identified patterns of each case, with no necrosis were selected randomly from Gömöri stained sections using ×20 objective. ISFC-ratio increased with Gleason pattern both for the entire group but also for "Necrotizing" phenotype patterns and "Solid" phenotype patterns, excepting the subtype "4A" where the stromal compartment was reduced by the expansion of tumoral ducts enlarged by growing tumoral intraductal cribriform masses. These preliminary data showed that stromal microenvironment try to adapt to the loss of tumoral differentiation by increasing the amount of fibrillary components of intratumoral stromal compartment.

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Year:  2012        PMID: 23303017

Source DB:  PubMed          Journal:  Rom J Morphol Embryol        ISSN: 1220-0522            Impact factor:   1.033


  3 in total

1.  Correlations Between Intratumoral Interstitial Fibrillary Network and Vascular Network in Gleason Patterns of Prostate Adenocarcinoma.

Authors:  R M Pleșea; M S Șerbănescu; D O Alexandru; V Ciovică; A Stoiculescu; O T Pop; C Simionescu; I E Pleșea
Journal:  Curr Health Sci J       Date:  2015-12-22

2.  High-frequency ultrasound: an essential non-invasive tool for the pre-therapeutic assessment of basal cell carcinoma.

Authors:  Raluca Maria Bungărdean; Mircea Sebastian Şerbănescu; Horaţiu Alexandru Colosi; Maria Crişan
Journal:  Rom J Morphol Embryol       Date:  2021 Apr-Jun       Impact factor: 1.033

3.  Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.

Authors:  Mircea Sebastian Şerbănescu; Nicolae Cătălin Manea; Liliana Streba; Smaranda Belciug; Iancu Emil Pleşea; Ionica Pirici; Raluca Maria Bungărdean; Răzvan Mihail Pleşea
Journal:  Rom J Morphol Embryol       Date:  2020       Impact factor: 1.033

  3 in total

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