Literature DB >> 26743277

Correlations between intratumoral interstitial fibrillary network and vascular network in Srigley patterns of prostate adenocarcinoma.

George Mitroi1, Răzvan Mihail Pleşea, Oltin Tiberiu Pop, Dragoş Viorel Ciovică, Mircea Sebastian Şerbănescu, Dragoş Ovidiu Alexandru, Adrian Stoiculescu, Iancu Emil Pleşea.   

Abstract

OBJECTIVE: The study aims to assess the both individual behavior and correlations of stromal fibrillary component (SFC) and vascular density (VD) in relation with Srigley architectural patterns of prostate carcinoma.
MATERIALS AND METHODS: Digital images of prostate adenocarcinoma labeled following both Gleason and Srigley systems were acquired with ×20 objective from two serial sections, 340 from the section stained using Gömöri technique for SFC assessment and another corresponding 340 from the section immunomarked with anti-CD34 antibody for assessment of VD. The SFC amount and VD were determined and compared. Srigley patterns were divided in two redefined behavioral groups: "solid" group (Srigley I, Srigley III, Srigley IV) and "necrotizing" group (Srigley II with subdivisions: Gleason 3A, 3C and 5A).
RESULTS: SFC mean values had an ascending trend in both "solid" and "necrotizing" groups. VD mean values had an ascending trend in "solid" group but a descending trend in "necrotizing" group towards Gleason 5A pattern. SFC and VD values had a direct, ascending correlation for all determinations (p=0.0006), but also for "solid" (p=0.005) and "necrotizing" (p=0.026) groups. The two stromal elements had different behaviors both individually and in their correlation that seem to be related with their interaction with different tumor cellular populations.
CONCLUSIONS: Our results could plead for the hypothesis that the different subtypes of tumor architecture represent steps of a continuous process from well-differentiated status to poorly or undifferentiated status but who is accomplished by two different tumor cells populations with different distinct behavior in their relationship with the stromal microenvironment.

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Year:  2015        PMID: 26743277

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


  1 in total

1.  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

  1 in total

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