Is CDX2 immunostaining useful for delineating anorectal from penile/vulvar squamous cancer in the setting of squamous cell carcinoma with clinically unknown primary site presenting with histologically confirmed inguinal lymph node metastasis?

Gunia, Sven; Koch, Stefan; May, Matthias

doi:10.1136/jclinpath-2012-201138

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…34,35 However, no hegemonic panel of IHC markers has been established, and instead multiple panels are used to address this challenge. [35][36][37][38][39][40] Unfortunately, there is not a single specific marker which by itself can provide a conclusive diagnosis. Low reproducibility is another intrinsic limitation of this technique, in part due to the need to interpret IHC preparations, which, by their nature, involve subjective observation.…”

Section: Diagnostic Tools In Cupsmentioning

confidence: 99%

Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary

et al. 2017

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Epigenetic alterations are a common hallmark of human cancer. Single epigenetic markers are starting to be incorporated into clinical practice; however, the translational use of these biomarkers has not been validated at the 'omics' level. The identification of the tissue of origin in patients with cancer of unknown primary (CUP) is an example of how epigenomics can be incorporated in clinical settings, addressing an unmet need in the diagnostic and clinical management of these patients. Despite the great diagnostic advances made in the past decade, the use of traditional diagnostic procedures only enables the tissue of origin to be determined in ∼30% of patients with CUP. Thus, development of molecularly guided diagnostic strategies has emerged to complement traditional procedures, thereby improving the clinical management of patients with CUP. In this Review, we present the latest data on strategies using epigenetics and other molecular biomarkers to guide therapeutic decisions involving patients with CUP, and we highlight areas warranting further research to engage the medical community in this unmet need.

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Section: Diagnostic Tools In Cupsmentioning

confidence: 99%

Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary

et al. 2017

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“…For these patients in routine clinical practice, the main strategy for identifying the primary tumor was tissue-of-origin (TOO) studies using histochemistry and immunohistochemistry (IHC), which were considered as standard tests to suggest the origin of the lesion. Tissue-specific protein markers such as cytokeratins (CKs) including CK7 (KRT7) and CK20 (KRT20), homeobox protein Nkx-2.1 (TTF1), mammaglobin-A, and homeobox protein CDX-2 have been widely applied to predict primary sites ( 2 , 24 - 29 ). These markers were mainly used as a panel, the choice of which greatly affected subsequent diagnosis ( 27 , 30 - 33 ).…”

Section: Introductionmentioning

confidence: 99%

Data independent acquisition-mass spectrometry (DIA-MS)-based comprehensive profiling of bone metastatic cancers revealed molecular fingerprints to assist clinical classifications for bone metastasis of unknown primary (BMUP)

Ku¹,

Cai²,

Xu³

et al. 2020

Transl Cancer Res TCR

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Background Bone metastasis is the third most common metastatic cancers worldwide. It is a group of highly heterogeneous diseases with various potential cancer primaries. Among them, one third was diagnosed as bone metastasis of unknown primary (BMUP) due to lack of indication for the primary tumor even after comprehensive examinations. Thus, the prognosis of BMUP is often very poor since the treatment was largely empirical and untargeted. To assist identification of the primary tumor, a series of molecular markers including traditional tissue-specific histochemistry as well as gene and mRNA markers were developed with moderate to good sensitivity and specificity. Methods In this paper, we carried out a comprehensive expression profiling for fresh-frozen tissue samples of bone metastasis from lung, prostate and liver cancers using high resolution, data-independent-acquisition mass spectrometry (DIA-MS). The proteome variation was analyzed and protein classifiers were prioritized. Results Over 6,000 proteins were quantified from 18 samples, which, to the best of our knowledge, was never achieved before. Further statistical analysis and bioinformatics data mining revealed 4 significant proteins (RFIP1, CK15, ESYT2, and MAL2) with excellent discriminating capabilities with AUCs higher than 0.8. Conclusions The comprehensive proteome map of bone metastases will complement available genomic and transcriptomic data. Newly discovered protein classifiers will expand current diagnostic arsenal for tissue of origin studies in BMUP. Furthermore, the proteome map generated in this study by DIA-MS allows future data re-mining as our knowledge advances to assist investigation of bone metastasis and progression of tumors as well as the development of diagnostic tools and prognosis management for BMUPs.

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“…Currently, immunohistochemistry (IHC) utilizing antibodies targeted to certain tumor-specific antigens is the main method for primary tumor identification in patients with CUP [2, 10]. However, there is not a single, specific marker that can be used to conclusively diagnose the primary tumor, leading to the use of multiple different IHC markers, and generating the possibility that different clinicians will arrive at different diagnoses of the primary tumor type [2, 11-14]. Recent advances in genomics has led to the development of potential new means fordiagnosing these tumors; multiple studies have utilized gene expression profiles and other molecular markers to diagnose CUP [2].…”

Section: Introductionmentioning

confidence: 99%

Pan-cancer machine learning predictors of primary site of origin and molecular subtype

Flynn

Namburi

Paisie

et al. 2018

Preprint

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15Background: It is estimated by the American Cancer Society that approximately 5% of all 16 metastatic tumors have no defined primary site (tissue) of origin and are classified as cancers of 17 unknown primary (CUPs). The current standard of care for CUP patients depends on 18 immunohistochemistry (IHC) based approaches to identify the primary site. The addition of post-19 mortem evaluation to IHC based tests helps to reveal the identity of the primary site for only 20 25% of the CUPs, emphasizing the acute need for better methods of determination of the site of 21 origin. CUP patients are therefore given generic chemotherapeutic agents resulting in poor 22 prognosis. When the tissue of origin is known, patients can be given site specific therapy with 23 significant improvement in clinical outcome. Similarly, identifying the primary site of origin of 24 metastatic cancer is of great importance for designing treatment. 26Identification of the primary site of origin is an import first step but may not be sufficient 27 information for optimal treatment of the patient. Recent studies, primarily from The Cancer 28Genome Atlas (TCGA) project, and others, have revealed molecular subtypes in several cancer 29 types with distinct clinical outcome. The molecular subtype captures the fundamental 30 mechanisms driving the cancer and provides information that is essential for the optimal 31 treatment of a cancer. Thus, along with primary site of origin, molecular subtype of a tumor is 32 emerging as a criterion for personalized medicine and patient entry into clinical trials. 34However, there is no comprehensive toolset available for precise identification of tissue of origin 35 or molecular subtype for precision medicine and translational research. 37Methods and Findings: We posited that metastatic tumors will harbor the gene expression 38 profiles of the primary site of origin of the cancer. Therefore, we decided to learn the molecular 39 characteristics of the primary tumors using the large number of cancer genome profiles 40 available from the TCGA project. Our predictors were trained for 33 cancer types and for the 11 41 cancers where there are established molecular subtypes. We estimated the accuracy of several 42 machine learning models using cross-validation methods. The extensive testing using 43 independent test sets revealed that the predictors had a median sensitivity and specificity of 44 97.2% and 99.9% respectively without losing classification of any tumor. Subtype classifiers 45 achieved median sensitivity of 87.7% and specificity of 94.5% via cross validation and 46 presented median sensitivity of 79.6% and specificity of 94.6% in two external datasets of 1,999 47 total samples. Importantly, these external data shows that our classifiers can robustly predict the 48 primary site of origin from external microarray data, metastatic cancer data, and patient-derived 49 xenograft (PDX) data. 50 51 Conclusion: We have demonstrated the utility of gene expression profiles to solve the 52 important clinical challenge...

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Is CDX2 immunostaining useful for delineating anorectal from penile/vulvar squamous cancer in the setting of squamous cell carcinoma with clinically unknown primary site presenting with histologically confirmed inguinal lymph node metastasis?

Cited by 5 publications

References 8 publications

Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary

Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary

Data independent acquisition-mass spectrometry (DIA-MS)-based comprehensive profiling of bone metastatic cancers revealed molecular fingerprints to assist clinical classifications for bone metastasis of unknown primary (BMUP)

Pan-cancer machine learning predictors of primary site of origin and molecular subtype

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