Identification of fatty acid binding proteins as markers associated with the initiation and/or progression of renal cell carcinoma

Renal cell carcinoma (RCC) representing the most common neoplasia of the kidney in Western countries is a histologic diverse disease with an often unpredictable course. The prognosis of RCC is worsened with the onset of metastasis, and the therapies currently available are of limited success for the treatment of metastatic RCC. Although gene expression analyses and other methods are promising tools clarifying and standardizing the pathological classification of RCC, novel innovative molecular markers for the diagnosis, prognosis, and for the monitoring of this disease during therapy as well as potential therapeutic targets are urgently needed. Using proteome-based strategies, a number of RCC-associated markers either over-expressed or down-regulated in tumor lesions in comparison to the normal epithelium have been identified which have been implicated in tumorigenesis, but never linked to the initiation and/or progression of RCC. These include members of the fatty acid binding protein family, which have the potential to serve as diagnostic or prognostic markers for the screening of RCC patients.     

左右半结肠癌多组学分子特征差异的研究进展

结肠癌(colon cancer,CC)是一种常见的恶性肿瘤,其发病率和死亡率均占癌症前列.根据解剖学位置,CC可分为左半结肠癌(left-sided colon cancer,LCC)和右半结肠癌(right-sided colon cancer,RCC),两者在临床特征上表现出较大的差异.近些年来,随着生物学技术和...     

N-cadherin is differentially expressed in histological subtypes of papillary renal cell carcinoma

ABSTRACT: BACKGROUND: Papillary renal cell carcinoma (RCC) represents a rare tumor, which is divided, based on histological criteria, into two subtypes. In contrast to type I papillary RCC type II papillary RCC shows a worse prognosis. So far, reliable immunohistochemical markers for the distinction of these subtypes are not available. METHODS: In the present study the expression of N(neural)-, E(epithelial)-, P(placental)-, und KSP(kidney specific)-cadherin was examined in 22 papillary RCC of histological type I and 18 papillary RCC of histological type II (n = 40). RESULTS: All papillary RCC type II displayed a membranous expression for N-cadherin, whereas type I did not show any membranous positivity for N-cadherin. E-cadherin exhibited a stronger, but not significant, membranous as well as cytoplasmic expression in type II than in type I papillary RCC. A diagnostic relevant expression of P- and KSP-cadherin could not be demonstrated in both tumor entities. CONCLUSION: Thus N-cadherin represents the first immunhistochemical marker for a clear cut differentiation between papillary RCC type I and type II and could be a target for therapy and diagnostic in the future. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2011556982761733.     

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30 % of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20 % or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL.     

Identification of a universal 6-lncRNA prognostic signature for three pathologic subtypes of renal cell carcinoma

Renal cell carcinoma (RCC) is the most common adult renal epithelial cancer susceptible to metastasis and patients with irresectable RCC always have a poor prognosis. Long noncoding RNAs (lncRNAs) have recently been documented as having critical roles in the etiology of RCC. Nevertheless, the prognostic significance of lncRNA-based signature for outcome prediction in patients with RCC has not been well investigated. Therefore, it is essential to identify a lncRNA-based signature for predicting RCC prognosis. In the current study, we comprehensively analyzed the RNA sequencing data of the three main pathological subtypes of RCC (kidney renal clear cell carcinoma [KIRC], kidney renal papillary cell carcinoma [KIRP], and kidney chromophobe carcinoma [KICH]) from The Cancer Genome Atlas (TCGA) database, and identified a 6-lncRNA prognostic signature with the help of a step-wise multivariate Cox regression model. The 6-lncRNA signature stratified the patients into low- and high-risk groups with significantly different prognosis. Multivariate Cox regression analysis showed that predictive value of the 6-lncRNA signature was independent of other clinical or pathological factors in the entire cohort and in each cohort of RCC subtypes. In addition, the three independent prognostic clinical factors (including age, pathologic stage III, and stage IV) was also stratified into low- and high-risk groups basis on the risk score, and the stratification analyses demonstrated that the high-risk score was a poor prognostic factor. In conclusion, these findings indicate that the 6-lncRNA signature is a novel prognostic biomarker for all three subtypes of RCC, and can increase the accuracy of predicting overall survival.     

Inhibition of miR146b-5p suppresses CT-guided renal cell carcinoma by targeting TRAF6

Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system. Due to the lack of early symptoms, diagnosis of RCC usually occurs at late stages or after cancer metastasis leading to poor prognosis. Therefore, it is crucial to study early molecular mechanisms and biomarkers. Previous studies have suggested that microRNAs are involved in RCC initiation and development, making them a good candidate for early diagnosis and therapy. MiR146b-5P plays important roles in the progression of multiple cancers including thyroid cancer, pancreatic cancer, cervical cancer. However, it is not clear whether and how miR146b-5P is involved in RCC. In this study, we aimed to investigate the function of miR146b-5P in RCC. We examined the expression levels of miR146b-5p in renal cancer tissue and cell lines. We also explored the effects of blocking miR146b-5p in renal tumor growth and inflammatory signaling. Finally, we determined if miR146b-5p regulates tumorigenesis through TRAF6. We found that miR146b-5p levels were significantly increased in renal cancer tissue and renal cancer cells. Blocking miR146b-5p suppressed renal tumor growth and enhanced inflammatory response through increased TRAF6 expression. These effects were eliminated in TRAF6 knockout mice. Our results suggest that enhanced miR146b-5p expression may be a biomarker for RCC and modulating miR146b-5p and TRAF6 levels represent a potential therapeutic strategy for RCC.     

Genetic analysis to complement histopathological diagnosis of brain tumors

Gliomas, the most frequent tumors originating in the human nervous system, are divided into various subtypes. Currently, microscopic examination alone is insufficient for classification and grading so that genetic profiles are increasingly being emphasized in recognition of the emerging role of molecular diagnostic approaches to glioma classification. Glioblastomas (WHO grade IV) may develop de novo (primary glioblastomas) or through progression from lower-grade astrocytomas (secondary glioblastomas), while both glioblastomas show similar histological features. In contrast, they do constitute distinct disease entities that evolve through different genetic pathways, and are likely to differ in prognosis and response to therapy. Oligodendrogliomas (WHO grade II) account for 2.7% of brain tumors and 5-18% of all gliomas. Since this tumor is recognized as a particular subtype of glioma that shows remarkable responses to chemotherapy, a correct diagnosis is of prime importance. The difficulty is that histological differentiation of oligodendrogliomas from diffuse astrocytomas is highly subjective in cases without typical morphological features and there is a lack of reliable immunohistochemical markers. While histological distinction of low-grade gliomas from reactive astrocytes is also often difficult, reactive astrocytes usually lack genetic alterations. More biological and molecular approaches to glioma classification thus appear warranted to provide improved means to achieve correct diagnoses.     

Glutamate (mGluR-5) gene expression in brain regions of streptozotocin induced diabetic rats as a function of age: role in regulation of calcium release from the pancreatic islets in vitro

Metastatic renal cell carcinoma (RCC) is highly resistant to conventional systemic treatments, including chemotherapy, radiotherapy and hormonal therapies. Previous studies have shown over-expression of EGFR is associated with high grade tumors and a worse prognosis. Recent studies suggest anticancer therapies targeting the EGFR pathway have shown promising results in clinical trials of RCC patients. Therefore, characterization of the level and localization of EGFR expression in RCC is important for target-dependent therapy. In this study, we investigated the clinical significance of cellular localization of EGFR in human normal renal cortex and RCC. RCC and adjacent normal kidney tissues of 63 patients were obtained for characterization of EGFR expression. EGFR protein expression was assessed by immunohistochemistry on a scale from 0 to 300 (percentage of positive cells × staining intensity) and Western blotting. EGFR membranous staining was significantly stronger in RCC tumors than in normal tissues (P < 0.001). In contrast, EGFR cytoplasmic staining was significantly higher in normal than in tumor tissues (P < 0.001). The levels of membranous or cytoplasmic EGFR expression in RCC tissues were not correlated with sex, tumor grade, TNM stage or overall survival (P > 0.05). These results showed abundant expression of membranous EGFR in RCC, and abundant expression of cytoplasmic EGFR in normal tissues. EGFR expression in RCC was mostly located in the cell membrane, whereas the EGFR expression in normal renal tissues was chiefly seen in cytoplasm. Our results suggest different locations of EGFR expression may be associated with human renal tumorigenesis.     

Targeting of tumor associated antigens in renal cell carcinoma using proteome-based analysis and their clinical significance

The suitability of proteome-based strategies for the targeting of tumor-associated markers along with further analysis regarding their clinical significance were investigated in human renal cell carcinoma (RCC). The immunogenic protein expression profile of normal kidney and RCC cell lines was studied by proteome analysis combined with immunoblotting using sera from healthy donors and RCC patients, also termed PROTEOMEX. Employing this approach, a series of proteins reactive with either RCC patient sera and/or reactive with control sera were identified by microanalysis of tryptic peptides. Some of these candidate antigens represent members of the cytoskeletal family, such as cytokeratins, in particular cytokeratin 8, cytoskeletal tropomyosin, F-actin capping protein, gamma-actin, stathmin, tubulin-alpha, tubulin-beta and vimentin. The expression pattern and clinical significance of three of these antigens, namely cytokeratin 8, stathmin and vimentin, were further analyzed in a large series of surgically removed RCC lesions of distinct subtypes. A heterogeneous expression pattern of cytokeratin 8, stathmin and vimentin was demonstrated in the different RCC subtypes. All epithelial cells of the autologous normal kidney showed a strong cytokeratin 8 staining pattern, whereas they totally lack vimentin expression. Stathmin was expressed in 10% of tubule cells. In conclusion, PROTEOMEX could be employed for the identification of tumor-associated antigens of the cytoskeleton which are differentially expressed in RCC of distinct subtypes as well as in normal renal epithelium.     

Semi-supervised methods to predict patient survival from gene expression data

An important goal of DNA microarray research is to develop tools to diagnose cancer more accurately based on the genetic profile of a tumor. There are several existing techniques in the literature for performing this type of diagnosis. Unfortunately, most of these techniques assume that different subtypes of cancer are already known to exist. Their utility is limited when such subtypes have not been previously identified. Although methods for identifying such subtypes exist, these methods do not work well for all datasets. It would be desirable to develop a procedure to find such subtypes that is applicable in a wide variety of circumstances. Even if no information is known about possible subtypes of a certain form of cancer, clinical information about the patients, such as their survival time, is often available. In this study, we develop some procedures that utilize both the gene expression data and the clinical data to identify subtypes of cancer and use this knowledge to diagnose future patients. These procedures were successfully applied to several publicly available datasets. We present diagnostic procedures that accurately predict the survival of future patients based on the gene expression profile and survival times of previous patients. This has the potential to be a powerful tool for diagnosing and treating cancer.     

Role of gene expression profiling for diagnosing acute leukemias

Cytomorphology and cytochemistry in combination with multiparameter immunophenotyping today are the standard methods for establishing the diagnosis of acute leukemias. In addition, cytogenetics, fluorescence in situ hybridization, and polymerase chain reaction based assays provide important information regarding biologically defined and prognostically relevant subgroups and allow a comprehensive diagnosis of well defined subentities. With regard to the clinical setting a better understanding of the clinical course of distinct biologically defined disease subtypes is needed to select disease-specific therapeutic approaches. Paralleling the increase in knowledge on deregulated pathways in leukemia the development of new therapeutics is accelerated and therefore requires a detailed and comprehensive diagnostic tool. Revealing and quantifying the expression status of many ten thousands of genes in a single analysis the microarray technology holds this potential to become an essential tool for the molecular classification of leukemias. It may therefore be used as a routine method for diagnostic purposes in the near future. Furthermore, it is anticipated that new biologically defined and clinically relevant subtypes of leukemia will be identified based on gene expression profiling. This method may therefore guide therapeutic decisions.     

Human breast cancer associated fibroblasts exhibit subtype specific gene expression profiles

ABSTRACT: BACKGROUND: Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. METHODS: To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. RESULTS: We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER + cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs likely contribute to the enhanced migration of breast cancer cells in transwell assays and may contribute to the unfavorable prognosis of Her2+ breast cancer. CONCLUSIONS: These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer.     

Review of chromophobe renal cell carcinoma with focus on clinical and pathobiological aspects

In recent years, the concept of chromophobe renal cell carcinoma (RCC) has been established. Chromophobe RCCs account for about 4-6% of all renal tumors. Macroscopically, the cut surface of the tumor is generally grey-beige in color. Histologically, there are two variants (typical and eosinophilic). In the typical variant, large tumor cells with architecture of a compact tubulo-cystic pattern proliferate. The cytoplasm is abundant and shows a fine reticular translucent pattern. The cell border is thick, prominent and eosinophilic. In the eosinophilic variant, tumor cells are smaller and markedly eosinophilic, and a perinuclear halo is often seen. Histochemically, the tumor cells generally show a diffuse and strong reaction for Hale's colloidal iron staining. Ultrastructurally, tumor cells contain many cytoplasmic microvesicles (150-300 nm). In chromosomal analysis, a low chromosome number is characteristic of chromophobe RCCs, due to the frequent occurrence of a combined loss of chromosomes 1, 2, 6, 10, 13, 17, and 21. In differential diagnosis, histological distinction from oncocytomas, which share a common phenotype (intercalated cells of the collecting duct system), is most important. In this diagnostic setting, recent studies have given rise to several problems. Firstly, some cases of coexistent chromophobe RCC and oncocytoma (so-called renal oncocytosis) or cases of oncocytoma with metastasis have recently been reported. Secondly, the existence of chromophobe adenoma, which is the benign counterpart of chromophobe RCC, and an oncocytic variant of chromophobe RCC has recently been suggested. Therefore, further studies are needed to elucidate the relationship between chromophobe RCCs and oncocytomas, to confirm whether chromophobe adenoma actually exists or not, and to identify the key gene that causes chromophobe RCCs.     

Multiclass microarray data classification based on confidence evaluation

Microarray technology is becoming a powerful tool for clinical diagnosis, as it has potential to discover gene expression patterns that are characteristic for a particular disease. To date, this possibility has received much attention in the context of cancer research, especially in tumor classification. However, most published articles have concentrated on the development of binary classification methods while neglected ubiquitous multiclass problems. Unfortunately, only a few multiclass classification approaches have had poor predictive accuracy. In an effort to improve classification accuracy, we developed a novel multiclass microarray data classification method. First, we applied a "one versus rest-support vector machine" to classify the samples. Then the classification confidence of each testing sample was evaluated according to its distribution in feature space and some with poor confidence were extracted. Next, a novel strategy, which we named as "class priority estimation method based on centroid distance", was used to make decisions about categories for those poor confidence samples. This approach was tested on seven benchmark multiclass microarray datasets, with encouraging results, demonstrating effectiveness and feasibility.     

Similarities of ordered gene lists

MOTIVATION: Many applications of microarray technology in clinical cancer studies aim at detecting molecular features for refined diagnosis. In this paper, we follow an opposite rationale: we try to identify common molecular features shared by phenotypically distinct types of cancer using a meta-analysis of several microarray studies. We present a novel algorithm to uncover that two lists of differentially expressed genes are similar, even if these similarities are not apparent to the eye. The method is based on the ordering in the lists. RESULTS: In a meta-analysis of five clinical microarray studies we were able to detect significant similarities in five of the ten possible comparisons of ordered gene lists. We included studies, where not a single gene can be significantly associated to outcome. The detection of significant similarities of gene lists from different microarray studies is a novel and promising approach. It has the potential to improve upon specialized cancer studies by exploring the power of several studies in one single analysis. Our method is complementary to previous methods in that it does not rely on strong effects of differential gene expression in a single study but on consistent ones across multiple studies.     

Cutaneous melanoma: fishing with chips

DNA microarray technology is a versatile platform that allows rapid genetic analysis to take place on a genome-wide scale and has revolutionized the way cancers are studied. This platform has enabled researchers to characterize mechanisms central to tumorigenesis and understand important molecular events in the multi-step tumor progression model of cutaneous melanoma and other cancers. In melanoma, multiple global gene expression profiling studies using various DNA microarray platforms and various experimental designs have been performed. Each study has been able to capture and characterize either the involvement of a novel pathway or a novel cause-effect-relationship. The use of microarrays to define subclasses, to identify differentially regulated genes within a mutational context to analyze epigenetically regulated genes has resulted in an unprecedented understanding of the biology of cutaneous melanoma that may lead to more accurate diagnosis, more comprehensive prognosis, prediction and more effective therapeutic interventions. Related DNA microarray platforms like array-comparative genomic hybridization (CGH) have also been instrumental to identify many non-random chromosomal alterations; however, studies identifying validated targets as a result of CGH are limited. Thus, there exists significant opportunity to discover novel melanoma genes and translate such discoveries into meaningful clinical endpoints. In this review, we focus on various DNA microarray-based studies performed in cutaneous melanoma and summarize our current understanding of the genetics and biology of melanoma progression derived from accumulating genomic information.