Gene expression profiling separates chromophobe renal cell carcinoma from oncocytoma and identifies vesicular transport and cell junction proteins as differentially expressed genes

The MAL Family of Proteins: Normal Function, Expression in Cancer, and Potential Use as Cancer Biomarkers

The MAL family of integral membrane proteins consists of MAL, MAL2, MALL, PLLP, CMTM8, MYADM, and MYADML2. The best characterized members are elements of the machinery that controls specialized pathways of membrane traffic and cell signaling. This review aims to help answer the following questions about the MAL-family genes: (i) is their expression regulated in cancer and, if so, how? (ii) What role do they play in cancer? (iii) Might they have biomedical applications? Analysis of large-scale gene expression datasets indicated altered levels of MAL-family transcripts in specific cancer types. A comprehensive literature search provides evidence of MAL-family gene dysregulation and protein function repurposing in cancer. For MAL, and probably for other genes of the family, dysregulation is primarily a consequence of gene methylation, although copy number alterations also contribute to varying degrees. The scrutiny of the two sources of information, datasets and published studies, reveals potential prognostic applications of MAL-family members as cancer biomarkers-for instance, MAL2 in breast cancer, MAL2 and MALL in pancreatic cancer, and MAL and MYADM in lung cancer-and other biomedical uses. The availability of validated antibodies to some MAL-family proteins sanctions their use as cancer biomarkers in routine clinical practice.

Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics

Malignant chromophobe renal cancer (chRCC) and benign oncocytoma (RO) are two renal tumor types difficult to differentiate using histology and immunohistochemistry-based methods because of their similarity in appearance. We previously developed a transcriptomics-based classification pipeline with "Chromophobe-Oncocytoma Gene Signature" (COGS) on a single-molecule counting platform. Renal cancer patients (n = 32, chRCC = 17, RO = 15) were recruited from Augusta University Medical Center (AUMC). Formalin-fixed paraffin-embedded (FFPE) blocks from their excised tumors were collected. We created a custom single-molecule counting code set for COGS to assay RNA from FFPE blocks. Utilizing hematoxylin-eosin stain, pathologists were able to correctly classify these tumor types (91.8%). Our unsupervised learning with UMAP (Uniform manifold approximation and projection, accuracy = 0.97) and hierarchical clustering (accuracy = 1.0) identified two clusters congruent with their histology. We next developed and compared four supervised models (random forest, support vector machine, generalized linear model with L2 regularization, and supervised UMAP). Supervised UMAP has shown to classify all the cases correctly (sensitivity = 1, specificity = 1, accuracy = 1) followed by random forest models (sensitivity = 0.84, specificity = 1, accuracy = 1). This pipeline can be used as a clinical tool by pathologists to differentiate chRCC from RO.

Identification of co-expression hub genes for ferroptosis in kidney renal clear cell carcinoma based on weighted gene co-expression network analysis and The Cancer Genome Atlas clinical data

Renal clear cell carcinoma (KIRC) is one of the most common tumors worldwide and has a high mortality rate. Ferroptosis is a major mechanism of tumor occurrence and development, as well as important for prognosis and treatment of KIRC. Here, we conducted bioinformatics analysis to identify KIRC hub genes that target ferroptosis. By Weighted gene co-expression network analysis (WGCNA), 11 co-expression-related genes were screened out. According to Kaplan Meier's survival analysis of the data from the gene expression profile interactive analysis database, it was identified that the expression levels of two genes, PROM2 and PLIN2, are respectively related to prognosis. In conclusion, our findings indicate that PROM2 and PLIN2 may be effective new targets for the treatment and prognosis of KIRC.

Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning

Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discovery dataset. The transcriptomic differences were identified with unsupervised learning in the discovery dataset (97.8% accuracy) with density based UMAP (DBU). The top 30 genes were identified by univariate gene expression analysis and ROC analysis, to create a gene signature called COGS. COGS, combined with DBU, was able to differentiate chRCC from RO in the discovery dataset with an accuracy of 97.8%. The classification accuracy of COGS was validated in an independent meta-dataset consisting of TCGA-KICH and GSE12090, where COGS could differentiate chRCC from RO with 100% accuracy. The differentially expressed genes were involved in carbohydrate metabolism, transcriptomic regulation by TP53, beta-catenin-dependent Wnt signaling, and cytokine (IL-4 and IL-13) signaling highly active in cancer cells. Using multiple datasets and machine learning, we constructed and validated COGS as a tool that can differentiate chRCC from RO and complement histology in routine clinical practice to distinguish these two tumors.

Immune MAL2-practice: breast cancer immunoevasion via MHC class I degradation

The success of tumor immunotherapy, while partial, confirms the existence and importance of tumor immunosurveillance. CD8+ T cell recognition of tumor-specific peptides bound to MHC class I (MHC-I) molecules is central to this process. In this issue of the JCI, Fang, Wang, et al. describe a unique tumor immunoevasion strategy based on endocytosis and degradation of MHC-I complexes mediated by the trafficking factor MAL2. Notably, MAL2 expression was associated with poor prognosis of breast cancer, and its downregulation enhanced CD8+ T cell recognition of breast cancer in various experimental models. This work demonstrates that a deeper understanding of tumor interference with MHC-I stability and trafficking has considerable potential for enhancing immunotherapies.

A Novel Prognostic Model of Endometrial Carcinoma Based on Clinical Variables and Oncogenomic Gene Signature

Due to the difficulty in predicting the prognosis of endometrial carcinoma (EC) patients by clinical variables alone, this study aims to build a new EC prognosis model integrating clinical and molecular information, so as to improve the accuracy of predicting the prognosis of EC. The clinical and gene expression data of 496 EC patients in the TCGA database were used to establish and validate this model. General Cox regression was applied to analyze clinical variables and RNAs. Elastic net-penalized Cox proportional hazard regression was employed to select the best EC prognosis-related RNAs, and ridge regression was used to construct the EC prognostic model. The predictive ability of the prognostic model was evaluated by the Kaplan-Meier curve and the area under the receiver operating characteristic curve (AUC-ROC). A clinical-RNA prognostic model integrating two clinical variables and 28 RNAs was established. The 5-year AUC of the clinical-RNA prognostic model was 0.932, which is higher than that of the clinical-alone (0.897) or RNA-alone prognostic model (0.836). This clinical-RNA prognostic model can better classify the prognosis risk of EC patients. In the training group (396 patients), the overall survival of EC patients was lower in the high-risk group than in the low-risk group [HR = 32.263, (95% CI, 7.707-135.058), P = 8e-14]. The same comparison result was also observed for the validation group. A novel EC prognosis model integrating clinical variables and RNAs was established, which can better predict the prognosis and help to improve the clinical management of EC patients.

PROM1 and PROM2 expression differentially modulates clinical prognosis of cancer: a multiomics analysis

Prominin 1 (PROM1) is considered a biomarker for cancer stem cells, although its biological role is unclear. Prominin 2 (PROM2) has also been associated with certain cancers. However, the prognostic value of PROM1 and PROM2 in cancer is controversial. Here, we performed a systematic data analysis to examine whether prominins can function as prognostic markers in human cancers. The expression of prominins was assessed and their prognostic value in human cancers was determined using univariate and multivariate survival analyses, via various online platforms. We selected a group of prominent functional protein partners of prominins by protein-protein interaction analysis. Subsequently, we investigated the relationship between mutations and copy number alterations in prominin genes and various types of cancers. Furthermore, we identified genes that correlated with PROM1 and PROM2 in certain cancers, based on their levels of expression. Gene ontology and pathway analyses were performed to assess the effect of these correlated genes on various cancers. We observed that PROM1 was frequently overexpressed in esophageal, liver, and ovarian cancers and its expression was negatively associated with prognosis, whereas PROM2 overexpression was associated with poor overall survival in lung and ovarian cancers. Based on the varying characteristics of prominins, we conclude that PROM1 and PROM2 expression differentially modulates the clinical outcomes of cancers.

PROM2 promotes gemcitabine chemoresistance via activating the Akt signaling pathway in pancreatic cancer

In recent years, the deoxycytidine analogue gemcitabine (2′,2′,-difluorodeoxycytidine) has become the first-line chemotherapeutic agent for patients with pancreatic cancer. However, due to the intrinsic resistance of pancreatic cancer cells, gemcitabine-based chemotherapy yields limited disease control, with >85% disease progression at 6 months from diagnosis. Therefore, elucidating the mechanisms of chemoresistance is a critical step in improving cancer therapy, especially for the treatment of pancreatic cancer. We show PROM2, a transmembrane glycoprotein, is ubiquitously upregulated in pancreatic cancer cell. We also found higher PROM2 expression is associated with shortened overall and disease-free survival times in patients diagnosed with pancreatic cancer. We provide evidence that PROM2 promotes chemoresistance to gemcitabine both in vivo and in vitro. Mechanistically, we demonstrate that PROM2 could directly interacted with Akt and activates the Akt signaling pathway, which thus inhibiting gemcitabine-induced apoptosis. As further evidence, we show PROM2 expression and Akt phosphorylation both promote gemcitabine chemoresistance, and cause poorer survival in clinical samples with pancreatic cancer. Combining gemcitabine with the Akt inhibitor MK-2206 facilitated significant tumor shrinkage and dramatically elevated the survival status in mice xenografted with pancreatic cancer cells. Our findings not only establish PROM2 as a novel positive regulator of the Akt signaling pathway and a candidate prognostic indicator of gemcitabine response, but also provide a neo-therapeutic approach for patients resistant to gemcitabine treatment.

A cell membrane protein called PROM2 promotes the resistance of pancreatic cancer to the anti-cancer drug gemcitabine, suggesting PROM2 and the molecular signaling pathway it stimulates could be targeted by new treatments. Researchers in China led by Jian Sun at Sun Yat-Sen University, Guangzhou, investigated the role of PROM2 in cultured human pancreatic cancer cells and in a mouse model of pancreatic cancer. Production and activity of PROM2 were increased in cancer cells, leading to increased resistance to gemcitabine. The researchers found that PROM2’s promotion of gemcitabine resistance was linked to its ability to bind to another protein called Akt. This interaction stimulates the Akt signaling pathway, sustaining cancer cells. Combining gemcitabine therapy with an Akt pathway inhibitor restored cancer cell sensitivity to gemcitabine, revealing a potential approach to developing drugs to overcome gemcitabine resistance.

Identification of Key Genes and Prognostic Analysis between Chromophobe Renal Cell Carcinoma and Renal Oncocytoma by Bioinformatic Analysis

The present techniques of clinical and histopathological diagnosis hardly distinguish chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). To identify differentially expressed genes (DEGs) as effective biomarkers for diagnosis and prognosis of ChRCC and RO, three mRNA microarray datasets (GSE12090, GSE19982, and GSE8271) were downloaded from the GEO database. Functional enrichment analysis of DEGs was performed by DAVID. STRING and Cytoscape were applied to construct the protein-protein interaction (PPI) network and key modules of DEGs. Visualized plots were conducted by the R language. We downloaded clinical data from the TCGA database and the influence of key genes on the overall survival of ChRCC was performed by Kaplan–Meier and Cox analyses. Gene set enrichment analysis (GSEA) was utilized in exploring the function of key genes. A total of 79 DEGs were identified. Enrichment analyses revealed that the DEGs are closely related to tissue invasion and metastasis of cancer. Subsequently, 14 hub genes including ESRP1, AP1M2, CLDN4, and CLDN7 were detected. Kaplan–Meier analysis indicated that the low expression of CLDN7 and GNAS was related to the worse overall survival in patients with ChRCC. Univariate Cox analysis showed that CLDN7 might be a helpful biomarker for ChRCC prognosis. Subgroup analysis revealed that the expression of CLDN7 showed a downtrend with the development of the clinical stage, topography, and distant metastasis of ChRCC. GSEA analysis identified that cell adhesion molecules cams, B cell receptor signaling pathway, T cell receptor signaling pathway, RIG-I like receptor signaling pathway, Toll-like receptor signaling pathway, and apoptosis pathway were associated with the expression of CLDN7. In conclusion, ESRP1, AP1M2, CLDN4, PRSS8, and CLDN7 were found to distinguish ChRCC from RO. Besides, the low expression of CLDN7 was closely related to ChRCC progression and could serve as an independent risk factor for the overall survival in patients with ChRCC.

Hybrid oncocytic/chromophobe renal tumors are molecularly distinct from oncocytoma and chromophobe renal cell carcinoma

Hybrid oncocytic/chromophobe tumor (HOCT) of the kidney represents a poorly understood clinicopathologic entity with pathologic features that overlap between benign renal oncocytoma (RO) and malignant chromophobe renal cell carcinoma (ChRCC). Consequently, characterization of HOCT and its separation from the foregoing entities are clinically important. The aim of this study was to describe the pathologic and molecular features of HOCT and to compare them with those of RO and ChRCC. We retrospectively identified a cohort of 73 cases with renal oncocytic tumors (19 RO, 27 HOCT, and 27 ChRCC) for whom clinical follow-up data were available by 2 tertiary care hospitals. All cases were sporadic except for 2 HOCTs that were associated with Birt-Hogg-Dubé syndrome. Lesional tissues were retrieved for molecular analysis. We performed targeted gene sequencing of all exons of 261 cancer related genes on a subset of HOCT samples (n = 16). Gene expression profiling of a customized codeset was conducted on 19 RO, 24 HOCT, and 27 ChRCC samples. Clinicopathologic characteristics as well as DNA copy number alterations, mutational and transcriptional features of HOCT derived from sequencing and expression profiling data are described and compared to those in RO and ChRCC. HOCTs were more frequently multifocal and did not exhibit mutations in genes that are recurrently mutated in RO or ChRCC but showed copy number alterations primarily involving losses in chromosomes 1 and X/Y. The mRNA transcript data show that HOCT can be separated from RO and ChRCC. Hence, HOCT appears to represent a distinct renal tumor entity with genomic features that are intermediate between those of RO and ChRCC.

Computational identification of vesicular transport proteins from sequences using deep gated recurrent units architecture

Protein function prediction is one of the most well-studied topics, attracting attention from countless researchers in the field of computational biology. Implementing deep neural networks that help improve the prediction of protein function, however, is still a major challenge. In this research, we suggested a new strategy that includes gated recurrent units and position-specific scoring matrix profiles to predict vesicular transportation proteins, a biological function of great importance. Although it is difficult to discover its function, our model is able to achieve accuracies of 82.3% and 85.8% in the cross-validation and independent dataset, respectively. We also solve the problem of imbalance in the dataset via tuning class weight in the deep learning model. The results generated showed sensitivity, specificity, MCC, and AUC to have values of 79.2%, 82.9%, 0.52, and 0.861, respectively. Our strategy shows superiority in results on the same dataset against all other state-of-the-art algorithms. In our suggested research, we have suggested a technique for the discovery of more proteins, particularly proteins connected with vesicular transport. In addition, our accomplishment could encourage the use of gated recurrent units architecture in protein function prediction.

Stoichiogenomics reveal oxygen usage bias, key proteins and pathways associated with stomach cancer

Stomach cancer involves hypoxia-specific microenvironments. Stoichiogenomics explores environmental resource limitation on biological macromolecules in terms of element usages. However, the patterns of oxygen usage by proteins and the ways that proteins adapt to a cancer hypoxia microenvironment are still unknown. Here we compared the oxygen and carbon contents ([C]) between proteomes of stomach cancer (hypoxia) and two stomach glandular cells (normal). Key proteins, genome locations, pathways, and functional dissection associated with stomach cancer were also studied. An association of oxygen content ([O]) and protein expression level was revealed in stomach cancer and stomach glandular cells. For differentially expressed proteins (DEPs), oxygen contents in the up regulated proteins were3.2%higherthan that in the down regulated proteins in stomach cancer. A total of 1,062 DEPs were identified; interestingly none of these proteins were coded on Y chromosome. The up regulated proteins were significantly enriched in pathways including regulation of actin cytoskeleton, cardiac muscle contraction, pathway of progesterone-mediated oocyte maturation, etc. Functional dissection of the up regulated proteins with high oxygen contents showed that most of them were cytoskeleton, cytoskeleton associated proteins, cyclins and signaling proteins in cell cycle progression. Element signature of resource limitation could not be detected in stomach cancer for oxygen, just as what happened in plants and microbes. Unsaved use of oxygen by the highly expressed proteins was adapted to the rapid growth and fast division of the stomach cancer cells. In addition, oxygen usage bias, key proteins and pathways identified in this paper laid a foundation for application of stoichiogenomics in precision medicine.

Proteomic distinction of renal oncocytomas and chromophobe renal cell carcinomas

BACKGROUND

Renal oncocytomas (ROs) are benign epithelial tumors of the kidney whereas chromophobe renal cell carcinoma (chRCCs) are malignant renal tumors. The latter constitute 5-7% of renal neoplasias. ROs and chRCCs show pronounced molecular and histological similarities, which renders their differentiation demanding. We aimed for the differential proteome profiling of ROs and early-stage chRCCs in order to better understand distinguishing protein patterns.

METHODS

We employed formalin-fixed, paraffin-embedded samples (six RO cases, six chRCC cases) together with isotopic triplex dimethylation and a pooled reference standard to enable cohort-wide quantitative comparison. For lysosomal-associated membrane protein 1 (LAMP1) and integrin alpha-V (ITGAV) we performed corroborative immunohistochemistry (IHC) in an extended cohort of 42 RO cases and 31 chRCC cases.

RESULTS

At 1% false discovery rate, we identified > 3900 proteins, of which > 2400 proteins were consistently quantified in at least four RO and four chRCC cases. The proteomic expression profiling discriminated ROs and chRCCs and highlighted established features such as accumulation of mitochondrial proteins in ROs together with emphasizing the accumulation of endo-lysosomal proteins in chRCCs. In line with the proteomic data, IHC showed enrichment of LAMP1 in chRCC and of ITGAV in RO.

CONCLUSION

We present one of the first differential proteome profiling studies on ROs and chRCCs and highlight differential abundance of LAMP1 and ITGAV in these renal tumors.

Identification and Validation of Radiographic Enhancement for Reliable Differentiation of CD117(+) Benign Renal Oncocytoma and Chromophobe Renal Cell Carcinoma

Purpose: The diagnostic differential for CD117/KIT(+) oncocytic renal tumor biopsies is limited to benign renal oncocytoma versus chromophobe renal cell carcinoma (ChRCC); however, further differentiation is often challenging and requires surgical resection. We investigated clinical variables that might improve preoperative differentiation of CD117(+) renal oncocytoma versus ChRCC to avoid the need for benign tumor resection.Experimental Design: A total of 124 nephrectomy patients from a single institute with 133 renal oncocytoma or ChRCC tumors were studied. Patients from 2003 to 2012 comprised a retrospective cohort to identify clinical/radiographic variables associated with renal oncocytoma versus ChRCC. Prospective validation was performed among consecutive renal oncocytoma/ChRCC tumors resected from 2013 to 2017.Results: Tumor size and younger age were associated with ChRCC, and multifocality with renal oncocytoma; however, the most reliable variable for ChRCC versus renal oncocytoma differentiation was the tumor:cortex peak early-phase enhancement ratio (PEER) using multiphase CT. Among 54 PEER-evaluable tumors in the retrospective cohort [19 CD117(+), 13 CD117(-), 22 CD117-untested], PEER classified each correctly as renal oncocytoma (PEER >0.50) or ChRCC (PEER ≤0.50), except for four misclassified CD117(-) ChRCC variants. Prospective study of PEER confirmed 100% accuracy of renal oncocytoma/ChRCC classification among 22/22 additional CD117(+) tumors. Prospective interobserver reproducibility was excellent for PEER scoring (intraclass correlation coefficient, ICC = 0.97) and perfect for renal oncocytoma/ChRCC assignment (ICC = 1.0).Conclusions: In the largest clinical comparison of renal oncocytoma versus ChRCC to our knowledge, we identified and prospectively validated a reproducible radiographic measure that differentiates CD117(+) renal oncocytoma from ChRCC with potentially 100% accuracy. PEER may allow reliable biopsy-based diagnosis of CD117(+) renal oncocytoma, avoiding the need for diagnostic nephrectomy. Clin Cancer Res; 24(16); 3898-907. ©2018 AACR.

CLDN8, an androgen-regulated gene, promotes prostate cancer cell proliferation and migration

The proliferation of prostate cancer cells is controlled by the androgen receptor (AR) signaling pathway. However, the function of AR target genes has not been fully elucidated. In previous studies, we have identified global AR binding sites and AR target genes in prostate cancer cells. Here, we focused on Claudin 8 (CLDN8), a protein constituting tight junctions in cell membranes. We found one AR binding site in the promoter region and two functional androgen‐responsive elements in the sequence. Reporter assay revealed that transcriptional activation of the CLDN8 promoter by androgen is dependent on these androgen‐responsive elements. Furthermore, CLDN8 mRNA is induced by androgen time‐dependently and the induction is blocked by AR inhibitor, suggesting that AR is involved in the transcriptional activation. In addition, our functional analyses by overexpression and knockdown of CLDN8 mRNA indicate that CLDN8 promotes prostate cancer cell proliferation and migration. Claudin 8 was overexpressed in prostate cancer clinical samples compared to benign tissues. Furthermore, we found that CLDN8 regulates intracellular signal transduction and stabilizes the cytoskeleton. Taken together, these results indicate that CLDN8 functions as an AR downstream signal to facilitate the progression of prostate cancer. Claudin 8 may be a novel molecular target for prostate cancer therapy.

The four-transmembrane protein MAL2 and tumor protein D52 (TPD52) are highly expressed in colorectal cancer and correlated with poor prognosis

The four-transmembrane protein MAL2 and tumor protein D52 (TPD52) have been shown to be involved in tumorigenesis of various cancers. However, their roles in colorectal cancer (CRC) remain unclear. In this study, we explored the expressions of MAL2 and TPD52 in tumor specimens resected from 123 CRC patients and the prognostic values of the two proteins in CRC. Immunohistochemical analyses showed that MAL2 (P<0.001) and TPD52 (P<0.001) were significantly highly expressed in primary carcinoma tissues compared with adjacent non-cancerous mucosa tissues. And TPD52 exhibited frequent overexpression in liver metastasis tissues relative to primary carcinoma tissues (P = 0.042), while MAL2 in lymphnode and liver metastasis tissues showed no significant elevation. Real-time quantitative PCR (RT-qPCR) showed the identical results. Correlation analyses by Pearson's chi-square test demonstrated that MAL2 in tumors was positively correlated with tumor status (pathological assessment of regional lymph nodes (pN, P = 0.024)), and clinic stage (P = 0.017). Additionally, the expression of TPD52 was detected under the same condition and was shown to be positively correlated withtumor status (pathological assessment of the primary tumor (pT, P = 0.035), distant metastasis (pM, P = 0.001)) and CRC clinicopathology(P = 0.024). Kaplan-Meier survival curves indicated that positive MAL2 (P<0.001) and TPD52 (P<0.001) expressions were associated with poor overall survival (OS) in CRC patients. Multivariate analysis showed that MAL2 and TPD52 expression was an independent prognostic factor for reduced OS of CRC patients. Moreover, overexpression of TPD52 in CRC SW480 cells showed an increased cell migration (P = 0.023) and invasion (P = 0.012) through inducing occurrence of epithelial-mesenchymal transition (EMT) and activating focal adhesion kinase (FAK)-mediated integrin signalling and PI3K⁄Akt signalling.Whereas TPD52-depleted cells showed the reverse effect. These data suggested that MAL2 and TPD52 might be potential biomarkers for clinical prognosis and might be a promising therapeutic target for CRC.

Comparative study of CT appearances in renal oncocytoma and chromophobe renal cell carcinoma

BACKGROUND

Renal oncocytoma (RO) and chromophobe renal cell carcinoma (ChRCC) share histologic and some imaging features.

PURPOSE

To investigate the multidetector computed tomography (MDCT) characteristics of these two tumor types.

MATERIAL AND METHODS

Fifty-six patients with RO and 54 patients with ChRCC were studied retrospectively. MDCT was undertaken to investigate differences in tumor characteristics.

RESULTS

Calcifications were visible in 24 (42.8%) patients with RO and in 11 (20.4%) patients with ChRCC (P = 0.011). 26 patients with RO had stellate scars as did 14 patients with ChRCC (P = 0.025). Spoken-wheel-like enhancement was visible in 41 patients with RO and in 11 with ChRCC (P < 0.001). Thirty-nine (69.6%) patients with RO and nine (16.7%) patients with ChRCC showed segmental inversion (P < 0.001). Two patients with RO had retroperitoneal lymph node enlargement as did 13 patients with ChRCC (P = 0.002). Combined evaluation of stellate scar, spoken-wheel-like enhancement, and segmental enhancement inversion features were found to have a sensitivity of 99.1% (106 of 107), a specificity of 100% (3 of 3), a positive predictive value of 100% (106 of 106), and a negative predictive value of 75% (3 of 4). The attenuation of RO tumors was greater than that of ChRCC tumors, normal renal parenchyma on unenhanced CT (P = 0.031). Enhancement was higher with RO than with ChRCC tumors in all phases (P = 0.021, < 0.001, and 0.007, respectively).

CONCLUSION

CT imaging features such as stellate scar, spoken-wheel-like enhancement, and segmental enhancement inversion were more common in RO and they may help in differentiating RO from ChRCC.

Tumour and patient factors in renal cell carcinoma-towards personalized therapy

Renal cell carcinoma (RCC) comprises a heterogeneous group of histologically and molecularly distinct tumour subtypes. Current targeted therapies have improved survival in patients with advanced disease but complete response occurs rarely, if at all. The genomic characterization of RCC is central to the development of novel targeted therapies. Large-scale studies employing multiple 'omics' platforms have led to the identification of key driver genes and commonly altered pathways. Specific molecular alterations and signatures that correlate with tumour phenotype and clinical outcome have been identified and can be harnessed for patient management and counselling. RCC seems to be a remarkably diverse malignancy with significant intratumour and intertumour genetic heterogeneity. The tumour microenvironment is increasingly recognized as a vital regulator of RCC tumour biology. Patient factors, including immune response and drug metabolism, vary widely, which can lead to widely divergent responses to drug therapy. Intratumour heterogeneity poses a significant challenge to the development of personalized therapies in RCC as a single biopsy might not accurately represent the clonal population ultimately responsible for aggressive biologic behaviour. On the other hand, the diversity of genomic alterations in RCC could also afford opportunities for targeting unique pathways based on analysis of an individual tumour's molecular composition.

Expression of histone methyltransferases as novel biomarkers for renal cell tumor diagnosis and prognostication

Renal cell tumors (RCTs) are the most lethal of the common urological cancers. The widespread use of imaging entailed an increased detection of small renal masses, emphasizing the need for accurate distinction between benign and malignant RCTs, which is critical for adequate therapeutic management. Histone methylation has been implicated in renal tumorigenesis, but its potential clinical value as RCT biomarker remains mostly unexplored. Hence, the main goal of this study was to identify differentially expressed histone methyltransferases (HMTs) and histone demethylases (HDMs) that might prove useful for RCT diagnosis and prognostication, emphasizing the discrimination between oncocytoma (a benign tumor) and renal cell carcinoma (RCC), especially the chromophobe subtype (chRCC). We found that the expression levels of 3 genes--SMYD2, SETD3, and NO66--was significantly altered in a set of RCTs, which was further validated in a large independent cohort. Higher expression levels were found in RCTs compared to normal renal tissues (RNTs) and in chRCCs comparatively to oncocytomas. SMYD2 and SETD3 mRNA levels correlated with protein expression assessed by immunohistochemistry. SMYD2 transcript levels discriminated RCTs from RNT, with 82.1% sensitivity and 100% specificity [area under curve (AUC) = 0.959], and distinguished chRCCs from oncocytomas, with 71.0% sensitivity and 73.3% specificity (AUC = 0.784). Low expression levels of SMYD2, SETD3, and NO66 were significantly associated with shorter disease-specific and disease-free survival, especially in patients with non-organ confined tumors. We conclude that expression of selected HMTs and HDMs might constitute novel biomarkers to assist in RCT diagnosis and assessment of tumor aggressiveness.

Spectrum of diverse genomic alterations define non-clear cell renal carcinoma subtypes

To further understand the molecular distinctions between kidney cancer subtypes, we analyzed exome, transcriptome and copy number alteration data from 167 primary human tumors that included renal oncocytomas and non-clear cell renal cell carcinomas (nccRCCs), consisting of papillary (pRCC), chromophobe (chRCC) and translocation (tRCC) subtypes. We identified ten significantly mutated genes in pRCC, including MET, NF2, SLC5A3, PNKD and CPQ. MET mutations occurred in 15% (10/65) of pRCC samples and included previously unreported recurrent activating mutations. In chRCC, we found TP53, PTEN, FAAH2, PDHB, PDXDC1 and ZNF765 to be significantly mutated. Gene expression analysis identified a five-gene set that enabled the molecular classification of chRCC, renal oncocytoma and pRCC. Using RNA sequencing, we identified previously unreported gene fusions, including ACTG1-MITF fusion. Ectopic expression of the ACTG1-MITF fusion led to cellular transformation and induced the expression of downstream target genes. Finally, we observed upregulation of the anti-apoptotic factor BIRC7 in MiTF-high RCC tumors, suggesting a potential therapeutic role for BIRC7 inhibitors.

Constitutive patterns of gene expression regulated by RNA-binding proteins

Background

RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but the partners of many RNA-binding proteins are still uncharacterized.

Results

We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively and negatively correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein–RNA interactions, with positively correlated patterns related to cell cycle control and negatively correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein–RNA interactions and expression networks, we developed the catRAPID express web server.

Conclusions

Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid future experimental studies.

Epithelial splicing regulator protein 1 and alternative splicing in somatotroph adenomas

Somatotroph adenomas secrete supraphysiological amounts of GH, causing acromegaly. We have previously hypothesized that epithelial mesenchymal transition (EMT) may play a central role in the progression of these adenomas and that epithelial splicing regulator 1 (ESRP1) may function prominently as a master regulator of the EMT process in pituitary adenomas causing acromegaly. To further elucidate the role of ESRP1 in somatotroph adenomas and in EMT progression, we used RNA sequencing (RNAseq) to sequence somatotroph adenomas characterized by high and low ESRP1 levels. Transcripts identified by RNAseq were analyzed in 65 somatotroph adenomas and in GH-producing pituitary rat cells with a specific knockdown of Esrp1. The clinical importance of the transcripts was further investigated by correlating mRNA expression levels with clinical indices of disease activity and treatment response. Many of the transcripts and isoforms identified by RNAseq and verified by quantitative PCR were involved in vesicle transport and calcium signaling and were associated with clinical outcomes. Silencing Esrp1 in GH3 cells resulted in changes of gene expression overlapping the data observed in human somatotroph adenomas and revealed a decreased granulation pattern and attenuated GH release. We observed an alternative splicing pattern for F-box and leucine-rich repeat protein 20, depending on the ESPR1 levels and on changes in circulating IGF-I levels after somatostatin analog treatment. Our study indicates that ESRP1 in somatotroph adenomas regulates transcripts that may be essential in the EMT progression and in the response to somatostatin analog treatment.

Expression of the Na+/K+-transporting ATPase gamma subunit FXYD2 in renal tumors

Chromophobe renal cell carcinoma (RCC) is a form of renal cancer that may be confused with other eosinophilic renal tumors, including oncocytoma, type 2 papillary RCC, and clear-cell RCC with eosinophilic features. There are currently no robust markers to distinguish these neoplasms. Chromophobe RCC and renal oncocytoma are presumably derived from the distal nephron. FXYD2 is a distal tubule regulator of the trimeric Na(+/)K(+)-transporting ATPase that is enriched in kidney tissue. In this study, we investigated the expression of FXYD2 in normal human kidney, 27 chromophobe RCCs, 30 oncocytomas, 15 clear-cell RCCs, and 11 papillary RCCs. Immunohistochemical staining for FXYD2 showed diffuse, strong immunoreactivity in the basolateral membrane of distal tubules of normal human kidney. Ninety-six percent (26/27) of chromophobe RCCs were immunoreactive for FXYD2 in a distinctly membranous pattern. Twenty-five of these tumors showed at least focal 2+ staining. In contrast, only 17% (5/30) of renal oncocytomas, 11% (2/15) of clear-cell RCCs, and 0% (0/11) of papillary RCCs displayed FXYD2 immunoreactivity. None of these cases showed ≥2+ FXYD2 staining. A subset of cases was confirmed as oncocytoma or chromophobe RCC using cytokeratin 7, colloidal iron, and interphase fluorescence in situ hybridization analysis of chromosomes 1, 2, 6, 10, and 17. Among this subset, 100% (7/7) of chromophobe RCCs were FXYD2 positive, whereas 17% (2/12) of oncocytomas were stained with FXYD2. The oncocytomas that stained with FXYD2 did so in a weak (1+), patchy manner. In contrast, chromophobe RCCs showed ≥2+ staining in 86% (6/7) of these tumors. For comparison, this subset was also stained for kidney-specific cadherin (Ksp-cadherin). Ksp-cadherin showed positive staining in 100% (7/7) of chromophobe RCCs and 33% (4/12) of oncocytomas. This is the first report demonstrating the potential utility of FXYD2 immunohistochemistry in the diagnosis of chromophobe RCC.

Prominin-2 and Other Relatives of CD133

Several molecules related to prominin-1/CD133, which was first characterized as a marker of mouse neuroepithelial stem cells and human hematopoietic stem cells, have been identified in various species. In mammals, a second prominin gene, prominin-2, has been identified and characterized, whereas in nonmammalian species, up to three prominin genes are potentially expressed. The structural similarities between prominin-1 and prominin-2 are, to some extent, reflected by their biochemical properties; both proteins are selectively concentrated in specific plasma membrane subdomains that protrude into the extracellular space and are released in small extracellular membrane vesicles. In contrast to the apically confined prominin-1, prominin-2 is distributed in a nonpolarized apico-basolateral fashion in polarized epithelial cells and appears to be expressed in separate epithelial cells. Their distinctive localization in plasma membrane protrusions is a hallmark of prominins, validating the naming of the family after its first identified member. Insights into the distinctive and/or complementary roles of the two prominins may be obtained by analyzing the evolutionary history of these proteins and the characteristics of orthologs and paralogs in more distantly related species. In addition, the characterization of prominins may shed light on the still elusive function of CD133.

Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression

Lung cancer is the leading cause of cancer death worldwide, and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung pairs, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent down-regulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways, and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and down-regulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell–cell and cell–matrix interactions, was recently shown to be a tumor suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by identifying novel epigenetically deregulated genes potentially involved in lung adenocarcinoma development/progression, and by describing an epigenetic subgroup of lung adenocarcinoma associated with characteristic molecular alterations.

Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays

PURPOSE

To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.

EXPERIMENTAL DESIGN

A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.

RESULTS

We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%). The correct classification by subtype was 19/20 (95%) for clear cell, 14/14 (100%) for papillary, 17/19 (89%) for chromophobe, 18/19 (95%) for oncocytomas.

CONCLUSIONS

Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

Birt-Hogg-Dubé renal tumors are genetically distinct from other renal neoplasias and are associated with up-regulation of mitochondrial gene expression

Background

Germline mutations in the folliculin (FLCN) gene are associated with the development of Birt-Hogg-Dubé syndrome (BHDS), a disease characterized by papular skin lesions, a high occurrence of spontaneous pneumothorax, and the development of renal neoplasias. The majority of renal tumors that arise in BHDS-affected individuals are histologically similar to sporadic chromophobe renal cell carcinoma (RCC) and sporadic renal oncocytoma. However, most sporadic tumors lack FLCN mutations and the extent to which the BHDS-derived renal tumors share genetic defects associated with the sporadic tumors has not been well studied.

Methods

BHDS individuals were identified symptomatically and FLCN mutations were confirmed by DNA sequencing. Comparative gene expression profiling analyses were carried out on renal tumors isolated from individuals afflicted with BHDS and a panel of sporadic renal tumors of different subtypes using discriminate and clustering approaches. qRT-PCR was used to confirm selected results of the gene expression analyses. We further analyzed differentially expressed genes using gene set enrichment analysis and pathway analysis approaches. Pathway analysis results were confirmed by generation of independent pathway signatures and application to additional datasets.

Results

Renal tumors isolated from individuals with BHDS showed distinct gene expression and cytogenetic characteristics from sporadic renal oncocytoma and chromophobe RCC. The most prominent molecular feature of BHDS-derived kidney tumors was high expression of mitochondria-and oxidative phosphorylation (OXPHOS)-associated genes. This mitochondria expression phenotype was associated with deregulation of the PGC-1α-TFAM signaling axis. Loss of FLCN expression across various tumor types is also associated with increased nuclear mitochondrial gene expression.

Conclusions

Our results support a genetic distinction between BHDS-associated tumors and other renal neoplasias. In addition, deregulation of the PGC-1α-TFAM signaling axis is most pronounced in renal tumors that harbor FLCN mutations and in tumors from other organs that have relatively low expression of FLCN. These results are consistent with the recently discovered interaction between FLCN and AMPK and support a model in which FLCN is a regulator of mitochondrial function.

Molecular pathology of chromophobe renal cell carcinoma: a review

The recognition of chromophobe renal cell carcinoma (RCC) among other distinct types of renal cell tumors (RCT) based on light-microscopic features, such as cytoplasmic and nuclear characteristics, might pose a dilemma in some cases because of morphological pattern overlapping with renal oncocytoma or conventional RCC. The present article reviews chromophobe RCC with focus on aspects of its molecular pathology, which was shown using ancillary modern microarray-based technology that can distinguish it from its mimics and therefore be helpful for its correct diagnosis. Although the high resolution DNA-microarray analyses excluded with all certainty the occurrence of small specific alterations, the loss of entire chromosomes 2, 10, 13, 17 and 21 occurs exclusively in chromophobe RCC and therefore probes localized at these chromosomes might be used to establish the diagnosis of chromophobe RCC in cases with uncertain histology. The usefulness of proposed candidate genes selected by the global gene expression analyses in the diagnostic pathology is far below expectations. The conflicting staining patterns, together with the poor specificity of used antibodies, leads us to believe that these candidate immunomarkers might not help in the separation of chromophobe RCC, with the exception of CD82, which has recently been suggested to be used for routine histological diagnosis.

Molecular pathology of renal oncocytoma: a review

Differentiating renal oncocytoma from its renal cell carcinoma (RCC) mimics, particularly chromophobe RCC, can be difficult, especially when limited tissue is available for evaluation and requires sophisticated microscopic, ultrastructural and immunohistochemical evaluation. In this review, the relevant literature has been reviewed, and supporting data obtained by applying modern microarray-based technologies are discussed with a focus on molecular pathology of renal oncocytoma. The high resolution whole-genome DNA-microarray based analyses excluded with all certainty the occurrence of small specific alterations. Renal oncocytomas are characterized by variable chromosomal patterns. The number of genes selected by global gene expression analyses and their usefulness in the diagnostic pathology based on immunohistochemical evaluation is far below the expectations. The conflicting staining patterns, together with the poor specificity of proposed antibodies, leads us to believe that these candidate immunomarkers might not help in the separation of these tumors. Applying DNA based tools might help in the diagnosis of renal oncocytoma with uncertain histology. However, only the combination of all available techniques could give reliable information.

MAL2 and tumor protein D52 (TPD52) are frequently overexpressed in ovarian carcinoma, but differentially associated with histological subtype and patient outcome

BACKGROUND

The four-transmembrane MAL2 protein is frequently overexpressed in breast carcinoma, and MAL2 overexpression is associated with gain of the corresponding locus at chromosome 8q24.12. Independent expression microarray studies predict MAL2 overexpression in ovarian carcinoma, but these had remained unconfirmed. MAL2 binds tumor protein D52 (TPD52), which is frequently overexpressed in ovarian carcinoma, but the clinical significance of MAL2 and TPD52 overexpression was unknown.

METHODS

Immunohistochemical analyses of MAL2 and TPD52 expression were performed using tissue microarray sections including benign, borderline and malignant epithelial ovarian tumours. Inmmunohistochemical staining intensity and distribution was assessed both visually and digitally.

RESULTS

MAL2 and TPD52 were significantly overexpressed in high-grade serous carcinomas compared with serous borderline tumours. MAL2 expression was highest in serous carcinomas relative to other histological subtypes, whereas TPD52 expression was highest in clear cell carcinomas. MAL2 expression was not related to patient survival, however high-level TPD52 staining was significantly associated with improved overall survival in patients with stage III serous ovarian carcinoma (log-rank test, p < 0.001; n = 124) and was an independent predictor of survival in the overall carcinoma cohort (hazard ratio (HR), 0.498; 95% confidence interval (CI), 0.34-0.728; p < 0.001; n = 221), and in serous carcinomas (HR, 0.440; 95% CI, 0.294-0.658; p < 0.001; n = 182).

CONCLUSIONS

MAL2 is frequently overexpressed in ovarian carcinoma, and TPD52 overexpression is a favourable independent prognostic marker of potential value in the management of ovarian carcinoma patients.

Genomic expression and single-nucleotide polymorphism profiling discriminates chromophobe renal cell carcinoma and oncocytoma

Background

Chromophobe renal cell carcinoma (chRCC) and renal oncocytoma are two distinct but closely related entities with strong morphologic and genetic similarities. While chRCC is a malignant tumor, oncocytoma is usually regarded as a benign entity. The overlapping characteristics are best explained by a common cellular origin, and the biologic differences between chRCC and oncocytoma are therefore of considerable interest in terms of carcinogenesis, diagnosis and clinical management. Previous studies have been relatively limited in terms of examining the differences between oncocytoma and chromophobe RCC.

Methods

Gene expression profiling using the Affymetrix HGU133Plus2 platform was applied on chRCC (n = 15) and oncocytoma specimens (n = 15). Supervised analysis was applied to identify a discriminatory gene signature, as well as differentially expressed genes. High throughput single-nucleotide polymorphism (SNP) genotyping was performed on independent samples (n = 14) using Affymetrix GeneChip Mapping 100 K arrays to assess correlation between expression and gene copy number. Immunohistochemical validation was performed in an independent set of tumors.

Results

A novel 14 probe-set signature was developed to classify the tumors internally with 93% accuracy, and this was successfully validated on an external data-set with 94% accuracy. Pathway analysis highlighted clinically relevant dysregulated pathways of c-erbB2 and mammalian target of rapamycin (mTOR) signaling in chRCC, but no significant differences in p-AKT or extracellular HER2 expression was identified on immunohistochemistry. Loss of chromosome 1p, reflected in both cytogenetic and expression analysis, is common to both entities, implying this may be an early event in histogenesis. Multiple regional areas of cytogenetic alterations and corresponding expression biases differentiating the two entities were identified. Parafibromin, aquaporin 6, and synaptogyrin 3 were novel immunohistochemical markers effectively discriminating the two pathologic entities.

Conclusions

Gene expression profiles, high-throughput SNP genotyping, and pathway analysis effectively distinguish chRCC from oncocytoma. We have generated a novel transcript predictor that is able to discriminate between the two entities accurately, and which has been validated both in an internal and an independent data-set, implying generalizability. A cytogenetic alteration, loss of chromosome 1p, common to renal oncocytoma and chRCC has been identified, providing the opportunities for identifying novel tumor suppressor genes and we have identified a series of immunohistochemical markers that are clinically useful in discriminating chRCC and oncocytoma.

JISTIC: identification of significant targets in cancer

BACKGROUND

Cancer is caused through a multistep process, in which a succession of genetic changes, each conferring a competitive advantage for growth and proliferation, leads to the progressive conversion of normal human cells into malignant cancer cells. Interrogation of cancer genomes holds the promise of understanding this process, thus revolutionizing cancer research and treatment. As datasets measuring copy number aberrations in tumors accumulate, a major challenge has become to distinguish between those mutations that drive the cancer versus those passenger mutations that have no effect.

RESULTS

We present JISTIC, a tool for analyzing datasets of genome-wide copy number variation to identify driver aberrations in cancer. JISTIC is an improvement over the widely used GISTIC algorithm. We compared the performance of JISTIC versus GISTIC on a dataset of glioblastoma copy number variation, JISTIC finds 173 significant regions, whereas GISTIC only finds 103 significant regions. Importantly, the additional regions detected by JISTIC are enriched for oncogenes and genes involved in cell-cycle and proliferation.

CONCLUSIONS

JISTIC is an easy-to-install platform independent implementation of GISTIC that outperforms the original algorithm detecting more relevant candidate genes and regions. The software and documentation are freely available and can be found at: http://www.c2b2.columbia.edu/danapeerlab/html/software.html.

Comparison of gene expression profiles in tubulocystic carcinoma and collecting duct carcinoma of the kidney

The relationship between tubulocystic carcinoma and collecting duct carcinoma of the kidney remains controversial. Some experts are of the opinion that the tumors are related, considering tubulocystic carcinoma to be synonymous with low-grade collecting duct carcinoma. However, others maintain that the 2 are distinct, unrelated entities on the basis of morphologic features and clinical outcome. To explore the relationship between tubulocystic carcinoma and collecting duct carcinoma, we compared the expression of several gene products at the mRNA level in cohorts of each tumor subtype. Seven cases of tubulocystic carcinoma and 8 cases of collecting duct carcinoma were identified. Total RNA was isolated from formalin-fixed paraffin-embedded tissue from each case. Relative expression levels of vimentin, alpha methylacyl CoA racemase, E-cadherin, p53, CD10 antigen, parvalbumin, cytokeratin 7, and cytokeratin 19 were assessed by quantitative reverse transcription polymerase chain reaction. Tubulocystic carcinoma was characterized by relative overexpression of vimentin, p53, and alpha methylacyl CoA racemase, compared with collecting duct carcinoma (P<0.05 for each gene, t test). In general, tubulocystic carcinoma expressed higher levels of E-cadherin and CD10, whereas collecting duct carcinoma expressed higher levels of cytokeratin 19; however, these trends did not reach statistical significance in this study cohort. Tubulocystic carcinoma and collecting duct carcinoma did not express cytokeratin 7 differentially. Case-to-case variability of gene expression limited the effectiveness of any one marker to distinguish the tumor types. Our study demonstrates that tubulocystic carcinoma and collecting duct carcinoma have different expression profiles of selected genes, including vimentin, p53, and alpha methylacyl CoA racemase. Further analysis of additional cases, using quantitative reverse transcription polymerase chain reaction and immunohistochemistry, will be useful to test the reproducibility of these findings. In addition, larger studies may establish statistical differences in expression of other genes analyzed in this study. Overall, these findings support the view that tubulocystic carcinoma and collecting duct carcinoma should be considered as 2 distinct entities at the molecular level.

Renal cell carcinoma

Renal Cell Carcinoma (RCC) has the highest mortality rate of the genitourinary cancers and the incidence of RCC has risen steadily. If detected early, RCC is curable by surgery although a minority are at risk of recurrence. Increasing incidental detection and an ageing population has led to active surveillance as an option for patients with small renal masses. RCC is heterogeneous and comprises several histological cell types with different genetics, biology and behavior. The identification of the genes predisposing to inherited syndromes with RCC has provided much of our knowledge of the molecular basis of early sporadic RCC. Many of the oncogenes and tumor suppressor genes that are mutated leading to pathway dysregulation in RCC remain to be elucidated. Global studies of copy number, gene sequencing, gene expression, miRNA expression and gene methylation in primary RCC will lead towards this goal. The natural history of RCC indicated by candidate precursor lesions, multifocal or bilateral disease, growth rate of small renal masses under surveillance, and high risk populations provide insight into the behavior of this disease. The use of molecular markers for early detection and prognosis merits more attention with ongoing advances in omics technologies. This review focuses on early RCC, that is disease confined within the renal capsule.

Renal tubulocystic carcinoma is closely related to papillary renal cell carcinoma: implications for pathologic classification

Tubulocystic carcinoma of the kidney (TC-RCC) is a rare renal tumor with unique gross and microscopic features unlike other types of renal cell carcinoma (RCC). Several recent studies recommend that it should be classified as a distinct RCC subtype. In this study, we provide pathologic and cytogenetic evidence supporting that TC-RCC is closely related to papillary RCC (PRCC). This study included 20 cases of renal tumors that partially or exclusively comprised a TC-RCC component. Pathologic examination documented the gross and microscopic features of TC-RCC, including multicentricity and the presence of concomitant PRCC and papillary adenoma. Formalin-fixed, paraffin-embedded sections from 12 TC-RCC and 20 PRCC were subjected to a multicolor fluorescence in situ hybridization assay containing probes for chromosomes 7, 17, and Y. One hundred nuclei were examined to enumerate the copy numbers of chromosomes in each tumor and its corresponding normal kidney tissue. A tumor with a percentage of cells harboring a chromosomal change > or = mean+3 SD of normal tissue was considered to harbor that chromosomal change, and a tumor with a percentage of cells with null Y chromosome count (loss of Y chromosome) > or = mean+3 SD of normal tissue was considered to harbor Y chromosome loss. Four of the 20 TC-RCCs were multicentric. Ten had associated PRCC or papillary adenoma within the same kidney as the TC-RCC. In 4 cases, the tubulocystic and papillary components were admixed together within the same lesion. The tumor cells lining both the tubulocystic and papillary components had similar cytologic features. Ten of 12 TC-RCCs had a chromosome 7 gain, 8 of 12 cases had a chromosome 17 gain, and 8 of 9 cases had a loss of Y chromosome. Six of 9 cases with all 3 chromosomes studied had a gain of chromosomes 7 and 17 and a loss of Y chromosome. Our study shows that TC-RCCs and PRCCs are closely related entities. With its distinctive gross and microscopic features, TC-RCC may be considered a unique "morphologic entity." However, before it is accepted as a distinct renal cell carcinoma subtype, further studies are needed to document a characteristic molecular signature associated with this tumor.

Gene expression profiling of chromophobe renal cell carcinomas and renal oncocytomas by Affymetrix GeneChip using pooled and individual tumours

Due to overlapping morphology, malignant chromophobe renal cell carcinomas (RCC) and benign renal oncocytomas (RO) may pose a diagnostic problem. In the present study, we have applied different algorithms to evaluate the data sets obtained by hybridisation of pooled and also individual samples of renal cell tumours (RCT) onto two different gene expression platforms. The two approaches revealed high similarities in the gene expression profiles of chromophobe RCCs and ROs but also some differences. After identifying the differentially expressed genes by statistic analyses, the candidate genes were further selected by a real time and normal RT-PCR and their products were analysed by immunohistochemistry. We have identified CD82 and S100A1 as valuable markers for chromophobe RCC as well as AQP6 for ROs. However, these genes are expressed at the protein level in other types of RCTs as well albeit at a low frequency and low intensity. As none of the selected genes marks exclusively one type of RCTs, for the differential diagnosis of chromophobe RCCs and ROs, a set of markers such as CD82, S100A1 and AQP6 as well as some others would be an option in routine histological laboratories.

Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

Recent advances in biomarker discovery, biocomputing and nanotechnology have raised new opportunities in the emerging fields of personalized medicine (in which disease detection, diagnosis and therapy are tailored to each individual's molecular profile) and predictive medicine (in which genetic and molecular information is used to predict disease development, progression and clinical outcome). Here, we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, in addition to the prospects for and challenges involved in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases.

High-resolution DNA copy number and gene expression analyses distinguish chromophobe renal cell carcinomas and renal oncocytomas

Background

The diagnosis of benign renal oncocytomas (RO) and chromophobe renal cell carcinomas (RCC) based on their morphology remains uncertain in several cases.

Methods

We have applied Affymetrix GeneChip Mapping 250 K NspI high-density oligoarrays to identify small genomic alterations, which may occur beyond the specific losses of entire chromosomes, and also Affymetrix GeneChip HG-U133 Plus2.0 oligoarrays for gene expression profiling.

Results

By analysing of DNA extracted from 30 chRCCs and 42 ROs, we have confirmed the high specificity of monosomies of chromosomes 1, 2, 6, 10, 13, 17 and 21 in 70–93% of the chRCCs, while ROs displayed loss of chromosome 1 and 14 in 24% and 5% of the cases, respectively. We demonstrated that chromosomal gene expression biases might correlate with chromosomal abnormalities found in chromophobe RCCs and ROs. The vast majority genes downregulated in chromophobe RCC were mapped to chromosomes 2, 6, 10, 13 and 17. However, most of the genes overexpressed in chromophobe RCCs were located to chromosomes without any copy number changes indicating a transcriptional regulation as a main event.

Conclusion

The SNP-array analysis failed to detect recurrent small deletions, which may mark loci of genes involved in the tumor development. However, we have identified loss of chromosome 2, 10, 13, 17 and 21 as discriminating alteration between chromophobe RCCs and ROs. Therefore, detection of these chromosomal changes can be used for the accurate diagnosis in routine histology.

Differential expression of KAI1 metastasis suppressor protein in renal cell tumor histological subtypes

PURPOSE

The similar appearance of renal tumor histological subtypes can complicate differential diagnoses. This problem is most notable for the chromophobe subtype of renal cell carcinoma, which can be histologically indistinguishable from oncocytoma with investigational molecular markers failing to provide reliable differentiation. KAI1 is a metastasis suppressor gene whose expression correlates inversely with the metastatic potential of most solid tumor cancer types. We tested the hypothesis that KAI1 is differentially expressed among renal tumor histological subtypes.

MATERIALS AND METHODS

Immunohistochemical staining for KAI1 protein was performed in 152 nephrectomy specimens, including 48 clear cell, 35 papillary and 31 chromophobe renal cell carcinoma samples, 28 oncocytomas and 10 tumor-free kidneys. Staining was scored as none/minimal, low, moderate or high. KAI1 mRNA levels were compared by quantitative reverse transcriptase-polymerase chain reaction in an additional 22 chromophobe renal cell carcinoma and oncocytoma samples.

RESULTS

In all 10 tumor-free kidneys KAI1 protein was detected exclusively in distal tubule cell membranes. Of the tumor specimens KAI1 protein was absent in all papillary renal cell carcinoma specimens. It was present in only 1 of 48 clear cell renal cell carcinomas (2%) and 2 of 28 oncocytomas (7%) but only at low levels. In contrast, 27 of 31 chromophobe renal cell carcinoma specimens (87%) expressed KAI1 protein, most at moderate or high levels. The diagnostic accuracy of KAI1 immunostaining for discerning chromophobe renal cell carcinoma from oncocytoma was 90% with similar results observed at the RNA level.

CONCLUSIONS

KAI1 is an accurate biomarker for chromophobe renal cell carcinoma that may aid in the diagnostic differentiation of chromophobe renal cell carcinoma from oncocytoma. It remains to be determined whether KAI1 expression contributes to the low metastatic potential of chromophobe renal cell carcinoma.

Molecular Pathology of the Genitourinary Tract: Molecular Pathology of Kidney and Testes

With the advent of newer molecular technologies, our knowledge of cellular mechanisms with tumors of the kidney and testis has grown exponentially. Molecular technologies have led to better understanding of interplay between the von Hippel-Lindau gene and angiogenic cytokines in renal cancer and isochromosome 12p in testicular neoplasms. The result has been development of antiangiogenic-targeted therapy within recent years that has become the mainstay treatment for metastatic renal cell cancer. In the near future, classification and diagnosis of renal and testicular tumors through morphologic analysis will be supplemented by molecular information correlating to prognosis and targeted therapy. This article outlines tumor molecular pathology of the kidney and testis encompassing current genomic, epigenomic, and proteonomic findings.

Mucin 1 (MUC1) is a novel partner for MAL2 in breast carcinoma cells

BACKGROUND

The MAL2 gene, encoding a four-transmembrane protein of the MAL family, is amplified and overexpressed in breast and other cancers, yet the significance of this is unknown. MAL-like proteins have trafficking functions, but their molecular roles are largely obscure, partly due to a lack of known binding partners.

METHODS

Yeast two-hybrid screening of a breast carcinoma cDNA expression library was performed using a full-length MAL2 bait, and subsequent deletion mapping experiments were performed. MAL2 interactions were confirmed by co-immunoprecipitation analyses and confocal microscopy was employed to compare protein sub-cellular distributions. Sucrose density gradient centrifugation of membranes extracted in cold Triton X-100 was employed to compare protein distributions between Triton X-100-soluble and -insoluble fractions.

RESULTS

The tumor-associated protein mucin 1 (MUC1) was identified as a potential MAL2 partner, with MAL2/MUC1 interactions being confirmed in myc-tagged MAL2-expressing MCF-10A cells using co-immunoprecipitation assays. Deletion mapping experiments demonstrated a requirement for the first MAL2 transmembrane domain for MUC1 binding, whereas the MAL2 N-terminal domain was required to bind D52-like proteins. Confocal microscopy identified cytoplasmic co-localisation of MUC1 and MAL2 in breast cell lines, and centrifugation of cell lysates to equilibrium in sucrose density gradients demonstrated that MAL2 and MUC1 proteins were co-distributed between Triton X-100-soluble and -insoluble fractions. However co-immunoprecipitation analyses detected MAL2/MUC1 interactions in Triton X-100-soluble fractions only. Myc-MAL2 expression in MCF-10A cells was associated with both increased MUC1 detection within Triton X-100-soluble and -insoluble fractions, and increased MUC1 detection at the cell surface.

CONCLUSION

These results identify MUC1 as a novel MAL2 partner, and suggest a role for MAL2 in regulating MUC1 expression and/or localisation.