Expression of MUC1 (EMA) and E-cadherin in renal cell carcinoma: a systematic immunohistochemical analysis of 188 cases

Langner, Cord; Ratschek, Manfred; Rehak, Peter; Schips, Luigi; Zigeuner, Richard

doi:10.1038/sj.modpathol.3800032

Cited by 26 publications

(39 citation statements)

References 22 publications

(37 reference statements)

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“…Loss of cell surface localization of E-Cadherin was seen for 13 of 15 (87%) cases; however, the significance of this finding is uncertain as both papillary and clear cell renal cell carcinoma have low reported rates of E-Cadherin expression. 49 As a DEK-ARMC12 fusion has not been previously reported, and was identified in just a single case, both its prevalence and functional significance in contributing to renal cell carcinoma oncogenesis is uncertain. It is entirely possible that it represents a nonspecific structural abnormality secondary to amplification-related events in the region.…”

Section: Discussionmentioning

confidence: 99%

TFEB-VEGFA (6p21.1) co-amplified renal cell carcinoma: a distinct entity with potential implications for clinical management

et al. 2017

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A subset of renal cell carcinomas shows TFEB overexpression secondary to MALAT1-TFEB gene fusion. As alternate mechanisms of TFEB overexpression are likely to have the same effect, we sought to determine the frequency of amplification of TFEB and the adjacent VEGFA gene at 6p21.1. As patients with metastatic renal cell carcinomas are managed with anti-VEGF therapies, we retrospectively assessed therapeutic response in patients with amplified tumors. Amplification status was analyzed for 875 renal cell carcinomas from our institution, a consultative case and 794 cases from The Cancer Genome Atlas. Cases were classified as having low level (5-10 copies), and high-level amplification (>10 copies), and were further analyzed for adjacent oncogene copy number status (n=6; 3 single-nucleotide polymorphism genomic microarray, 3 The Cancer Genome Atlas) and structural rearrangements (n=1; mate-pair sequencing). These were then reviewed for histopathology, immunophenotype, and response to VEGF-targeted therapy on follow-up. In all, 10/875 (1.1%) institutional cases, 1 consultative case, and 3/794 (0.4%) of The Cancer Genome Atlas cases showed TFEB high-level amplification, while 14/875 (1.6%) cases showed TFEB low-level amplification. All cases had associated VEGFA amplification. This was confirmed with evaluation for copy number changes (n=6). The 6p21.1 high and low-level amplified tumors occurred in adults (mean age: 66), with over half being ≥pT3 (13/25, 52%), and most showed oncocytic, tubulopapillary features and high grade (≥grade 3: 20/22, 91%). These were aggressive tumors with metastasis and death from renal cell carcinoma in 11 (of 24, 46%) cases. Four patients received targeted therapy and had a mean survival of 31 months (range: 17-50) post nephrectomy. In summary, a group of aggressive renal cell carcinomas show genomic amplification of the 6p21.1 region including TFEB and VEGFA genes and share morphologic features. Additional studies are warranted to determine whether these patients respond to anti-VEGF therapy.

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Section: Discussionmentioning

confidence: 99%

TFEB-VEGFA (6p21.1) co-amplified renal cell carcinoma: a distinct entity with potential implications for clinical management

et al. 2017

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“…However, all of these studies analyze less than four markers. [6][7][8][9][10][11] In this study, we examined a total of eight tumor markers which were reported previously to be involved in the natural history and progression of renal cell carcinoma. To the best of our knowledge, this is the first cluster analysis of renal cell carcinoma patients based on tissue microarray data.…”

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confidence: 99%

Tumor classification by tissue microarray profiling: random forest clustering applied to renal cell carcinoma

et al. 2005

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A random forest (RF) predictor (Breiman 2001) is an ensemble of individual tree predictors. As part of their construction, RF predictors naturally lead to a dissimilarity measure between the observations. One can also define an RF dissimilarity measure between unlabelled data: the idea is to construct an RF predictor that distinguishes the 'observed' data from suitably generated synthetic data (Breiman 2003). The observed data are the original unlabelled data while the synthetic data are drawn from a reference distribution. Recently, RF dissimilarities have been used successfully in several unsupervised learning tasks involving genomic data.Unlike standard dissimilarities, the relationship between the RF dissimilarity and the variables can be difficult to disentangle. Here we describe the properties of the RF dissimilarity and make recommendations on how to use it in practice.An RF dissimilarity can be attractive because it handles mixed variable types well, is invariant to monotonic transformations of the input variables, is robust to outlying observations, and accommodates several strategies for dealing with missing data. The RF dissimilarity easily deals with large number of variables due to its intrinsic variable selection, e.g. the Addcl1RF dissimilarity weighs the contribution of each variable on the dissimilarity according to how dependent it is on other variables.We find that the RF dissimilarity is useful for detecting tumor sample clusters on the basis of tumor marker expressions. In this application, biologically meaningful clusters can often be described with simple thresholding rules.

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“…14 The characteristic morphologic features are enough to classify them in most cases, however, immunohistochemical, ultrastructural, or cytogenetic studies should be used for correct classification because of morphologic similarities among the histologic subtypes. [4][5][6][8][9][10] The genetic changes of VHL (3p25), c-MET (7q31) and BHD (17p11.2) are well documented in familial cases of cRCC, pRCC and chRCC, respectively. 14 Specific chromosome changes have been described in association with the histologic subtypes of sporadic RCC; the deletion of chromosome 3p in more than 90% of cRCCs, the characteristic trisomy of chromosomes 7 and 17 in pRCC, and multiple chromosomal loss in chRCC.…”

Section: Discussionmentioning

confidence: 99%

“…1,[5][6][7][8] Immunohistochemically, the tumor cells are strongly positive for E-cadherin and CK7, but negative for CD10 and vimentin. 9,10 However, it is sometimes difficult to differentiate this tumor from benign renal oncocytoma or more aggressive clear cell RCC.…”

Section: Introductionmentioning

confidence: 99%

Chromogenic in situ hybridization detection of chromosome 7 and 17 abnormalities in renal cell carcinomas and comparison to flow cytometric DNA ploidy patterns

Choi

Shin

et al. 2008

Basic and Applied Pathology

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Background and aim: The chromogenic in situ hybridization (CISH) is a new method in which chromosome aberration is determined by using a chromogenic reaction. We report the aberrations of chromosome 7 and 17 in three major subtypes of renal cell carcinomas (RCC), and compared these chromosomal changes with the flow cytometric DNA ploidy patterns. Methods: Aberrations of chromosomes 7 and 17 in 21 clear cell (c), 6 papillary (p) and 15 chromophobe (ch) RCCs were studied and compared with flow cytometric DNA ploidy. Results: Two of 14 chRCCs (14.3%) were monosomic for chromosome 7, but none of the cRCCs or pRCCs were monosomic. Twelve (85.7%) chRCCs showed monosomy for chromosome 17, but none of the pRCCs were monosomic. Three pRCCs (50%), 5 of 14 (35.7%) chRCCs and 2 (9.5%) cRCCs were polysomic for chromosome 7, whereas only one pRCC was polysomic. DNA aneuploidy was found in 2 pRCCs (33.3%), 2 cRCCs (9.5%), and 6 chRCCs (46.2%). Hypodiploidy was seen in one chRCC, and triploidy was seen in all types of RCCs. DNA aneuploidy was more frequent in cases with both chromosome 7 and 17 abnormalities (80%) than in cases with abnormality of one (38.5%) or neither (4.5%). Conclusion: The CISH method is useful in detecting chromosomal change in RCC, and the identification of chromosome 17 monosomy is helpful in diagnosis of chRCC.

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Expression of MUC1 (EMA) and E-cadherin in renal cell carcinoma: a systematic immunohistochemical analysis of 188 cases

Cited by 26 publications

References 22 publications

TFEB-VEGFA (6p21.1) co-amplified renal cell carcinoma: a distinct entity with potential implications for clinical management

TFEB-VEGFA (6p21.1) co-amplified renal cell carcinoma: a distinct entity with potential implications for clinical management

Tumor classification by tissue microarray profiling: random forest clustering applied to renal cell carcinoma

Chromogenic in situ hybridization detection of chromosome 7 and 17 abnormalities in renal cell carcinomas and comparison to flow cytometric DNA ploidy patterns

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