Literature DB >> 31567190

Cervical Adenocarcinoma: Histopathologic Features From Biopsies to Predict Tumor Behavior.

Glorimar Rivera-Colon1, Hao Chen1, Shuang Niu1, Elena Lucas1, Steven Holloway2, Kelley Carrick1, Katja Gwin1, Jayanthi Lea2,3, Wenxin Zheng1,2,3.   

Abstract

The pattern-based classification system of endocervical adenocarcinoma correlates with nodal metastasis and clinical outcomes, but its application in biopsies is challenging. The aim of this study was the correlation of additional histologic features with patterns of invasion as well as prognosis. A total of 103 specimens from 71 cervical adenocarcinoma cases were studied. Among the 71 cases, all had resection specimens including hysterectomy, cold knife cone excision or loop electrosurgical excision procedure excision, and 32 of these had prior cervical biopsies. We applied the pattern-based classification system to all the specimens and evaluated histopathologic features microscopically. Findings in biopsies were compared with their corresponding resections and correlated with nodal status and disease stage. In 71 resection specimens, pattern A was present in 10 (14.1%), pattern B in 12 (16.9%), and pattern C in 49 (69%) cases. Of the 32 cervical biopsies, pattern of invasion could be classified in only 16 (50%) cases, including 1 (6%) with pattern A, 4 (25%) with pattern B, and 11 (69%) with pattern C. Of the 32 cervical biopsies, 30 could be evaluated for intraluminal necrotic/tumor debris and/or grade 3 nuclei, which correlated with pattern C as well as with lymph node metastasis in the subsequent staging specimens. No tumor with patterns A or B had intraluminal necrotic/tumor debris or grade 3 nuclei in either biopsy or resection specimens. Therefore, intraluminal necrotic/tumor debris and grade 3 nuclei are highly predictive histologic features for cervical adenocarcinomas with pattern C invasion and nodal metastasis.

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Year:  2020        PMID: 31567190     DOI: 10.1097/PAS.0000000000001379

Source DB:  PubMed          Journal:  Am J Surg Pathol        ISSN: 0147-5185            Impact factor:   6.394


  6 in total

1.  Screening of prognostic immune genes and establishment of prognostic model of cervical adenocarcinoma based on bioinformatics analysis.

Authors:  Yunhua Yi; Jiangxin Sheng; Jichan Nie
Journal:  Ann Transl Med       Date:  2022-05

2.  mTOR Pathway Activation Assessed by Immunohistochemistry in Cervical Biopsies of HPV-associated Endocervical Adenocarcinomas (HPVA): Correlation With Silva Invasion Patterns.

Authors:  Sheila Segura; Simona Stolnicu; Monica Boros; Kay Park; Pedro Ramirez; Gloria Salvo; Denise Frosina; Achim Jungbluth; Robert A Soslow
Journal:  Appl Immunohistochem Mol Morphol       Date:  2021-08-01

3.  Combined Evaluation of Preoperative Serum CEA and CA125 as an Independent Prognostic Biomarker in Patients with Early-Stage Cervical Adenocarcinoma.

Authors:  Genping Huang; Ruizhe Chen; Nanjia Lu; Qin Chen; Weiguo Lv; Baohua Li
Journal:  Onco Targets Ther       Date:  2020-06-08       Impact factor: 4.147

Review 4.  Grading of Endocervical Adenocarcinomas: Review of the Literature and Recommendations From the International Society of Gynecological Pathologists.

Authors:  Karen L Talia; Esther Oliva; Joseph T Rabban; Naveena Singh; Simona Stolnicu; W Glenn McCluggage
Journal:  Int J Gynecol Pathol       Date:  2021-03-01       Impact factor: 3.326

5.  The Silva Pattern-based Classification for HPV-associated Invasive Endocervical Adenocarcinoma and the Distinction Between In Situ and Invasive Adenocarcinoma: Relevant Issues and Recommendations From the International Society of Gynecological Pathologists.

Authors:  Isabel Alvarado-Cabrero; Carlos Parra-Herran; Simona Stolnicu; Andres Roma; Esther Oliva; Anais Malpica
Journal:  Int J Gynecol Pathol       Date:  2021-03-01       Impact factor: 3.326

6.  OXTRHigh stroma fibroblasts control the invasion pattern of oral squamous cell carcinoma via ERK5 signaling.

Authors:  Liang Ding; Yong Fu; Nisha Zhu; Mengxiang Zhao; Zhuang Ding; Xiaoxin Zhang; Yuxian Song; Yue Jing; Qian Zhang; Sheng Chen; Xiaofeng Huang; Lorraine A O'Reilly; John Silke; Qingang Hu; Yanhong Ni
Journal:  Nat Commun       Date:  2022-08-31       Impact factor: 17.694

  6 in total

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