Supervised clustering of immunohistochemical markers to distinguish atypical endometrial hyperplasia from grade 1 endometrial cancer

Laas, Enora; Ballester, Marcos; Cortez, Annie; Gonin, Julie; Daraı̈, Émile; Graesslin, Olivier

doi:10.1016/j.ygyno.2014.02.018

Cited by 10 publications

(3 citation statements)

References 36 publications

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“…and p53 were the most predictive, confirming their crucial role in endometrial carcinogenesis. These results are in agreement with those of previous studies focusing on the transition between simple hyperplasia and atypical endometrial hyperplasia [12] on one hand and between atypical endometrial hyperplasia and type I G1 EC on the other, with similar proteins involved in the processes [13]. Several retrospective studies have shown that ER and PR status in EC are independent prognostic markers [14][15][16].…”

Section: Discussionsupporting

confidence: 92%

Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer

Laas

Ballester

Cortez

et al. 2017

Pathol. Oncol. Res.

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Considerable heterogeneity exists in outcomes of early endometrial cancer (EC) according to the type but also the histological grading. Our goal was to describe the immunohistochemical profiles of type I EC according to grades and type II EC, to identify groups of interacting proteins using principal component analysis (PCA) and unsupervised clustering. We studied 13 immunohistochemical markers (steroid receptors, pro/anti-apoptotic proteins, metalloproteinases (MMP) and tissue inhibitor of metalloproteinase (TIMP), and CD44 isoforms known for their role in endometrial pathology. Co-expressed proteins associated with the type, grade and outcome of EC were determined by PCA and unsupervised clustering. PCA identified three functional groups of proteins from 43 tissue samples (38 type I and 5 type II EC): the first was characterized by p53 expression; the second by MMPs, bcl-2, PR B and CD44v6; and the third by ER alpha, PR A, TIMP-2 and CD44v3. Unsupervised clustering found two main clusters of proteins, with both type I grade 3 and type II EC exhibiting the same cluster profile. PCA and unsupervised clustering of immunohistochemical markers in EC contribute to a better comprehension and classification of the disease.

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Section: Discussionsupporting

confidence: 92%

Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer

Laas

Ballester

Cortez

et al. 2017

Pathol. Oncol. Res.

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“…This statistical method has been used to distinguish atypical hyperplasia and grade 1 endometrioid endometrial cancer [37] or atypical and non-atypical endometrial hyperplasia [38] based on immunohistochemical markers of endometrial tissue samples.…”

Section: Methodsmentioning

confidence: 99%

Supervised Clustering of Adipokines and Hormonal Receptors Predict Prognosis in a Population of Obese Women with Type 1 Endometrial Cancer

Uzan

Laas

Alsamad

et al. 2017

IJMS

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Obesity is a major risk factor for endometrial cancer (EC). Yet, its impact on prognosis is controversial. Obesity is associated with metabolic and hormonal dysregulation as well as adipokines increase. The aim of this study was to characterize the expression of biological factors related to obesity within the tumor and evaluate their impact on prognosis. One hundred and thirty-six patients, including 55 obese patients, with endometrioid type I EC operated by total hysterectomy were included in this retrospective study conducted in a Tertiary teaching hospital between 2000 and 2013. Immunohistochemistry (IHC) study was performed on type I EC tumor samples using five adipokines (SPARC, RBP4 (Retinol Binding Protein 4), adiponectin, TNF α, IL-6) and hormonal receptors (estrogen receptor and progesterone receptor). Supervised clustering of immunohistochemical markers was performed to identify clusters that could be associated with prognostic groups. The prognosis of the obese population was not different from the prognosis of the general population. Adipokine expression within tumors was not different in these two populations. In obese population, we found three clusters where co-expression was associated with a recurrence group in comparison with a non-recurrence group and four clusters where co-expression was associated with the high risk FIGO (International Federation of Gynecology and Obstetrics) stage I group in comparison of low risk FIGO stage I group. While obesity does not appear as a prognostic factor in endometrioid type I EC, the co-expression of biological factors in IHC on hysterectomy specimens allowed to distinguish two prognostic groups in obese population.

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“…Sohn et al identified a five-protein signature in patients with triple negative breast cancer that was a predictor of recurrence-free survival [ 51 ]. In ovarian cancer, researchers were able to validate a protein panel that was able to stratify patients to long- and short-term survival using an in-depth proteomics analysis of archived patient blood samples [ 52 ]. The presence of platelet-C4d has been shown to correlate with vascular embolic events in lupus patients [ 53 ], and free C4d has been identified in saliva from patients with oral squamous cell cancers [ 54 ].…”

Section: Circulating Proteinsmentioning

confidence: 99%

Optimizing the Detection of Circulating Markers to Aid in Early Lung Cancer Detection

Murlidhar

Ramnath

Nagrath

et al. 2016

Cancers

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Improving early detection of lung cancer is critical to improving lung cancer survival. Studies have shown that computerized tomography (CT) screening can reduce mortality from lung cancer, but this involves risks of radiation exposure and can identify non-cancer lung nodules that lead to unnecessary interventions for some. There is a critical need to develop alternative, less invasive methods to identify patients who have early-stage lung cancer. The detection of circulating tumor cells (CTCs) are a promising area of research, but current technology is limited by a low yield of CTCs. Alternate studies are investigating circulating nucleic acids and proteins as possible tumor markers. It is critical to develop innovative methods for early lung cancer detection that may include CTCs or other markers that are low-risk and low-cost, yet specific and sensitive, to facilitate improved survival by diagnosing the disease when it is surgically curable.

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Supervised clustering of immunohistochemical markers to distinguish atypical endometrial hyperplasia from grade 1 endometrial cancer

Cited by 10 publications

References 36 publications

Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer

Unsupervised Clustering of Immunohistochemical Markers to Define High-Risk Endometrial Cancer

Supervised Clustering of Adipokines and Hormonal Receptors Predict Prognosis in a Population of Obese Women with Type 1 Endometrial Cancer

Optimizing the Detection of Circulating Markers to Aid in Early Lung Cancer Detection

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