Tissue Array-Based Predictions of Pathobiology, Prognosis, and Response to Treatment for Renal Cell Carcinoma Therapy

Abstract

Renal cell carcinoma is the most lethal of the common urologic malignancies, with ϳ40% of patients eventually dying of cancer progression. Approximately one third of patients present with metastatic disease, and up to 40% treated for localized disease have a recurrence. Historically, clinical factors have been used as prognostic markers for patients with renal cell carcinoma. Recent advances in the understanding of the pathogenesis, behavior, and molecular biology of renal cell carcinoma have paved the way for developments that may enhance early diagnosis, better predict tumor prognosis, and improve survival for renal cell carcinoma patients. Furthermore, reliable predictive factors are essential for the stratification of patients into clinically meaningful categories, which can be used to provide patients with counseling regarding prognosis, select treatment modalities, and determine eligibility for clinical trials. This has led to the creation of integrated staging systems that predict outcome by combining pathological and clinical variables. Although staging has been improved with the development of integrated systems, molecular tumor markers are expected to revolutionize the staging of renal cell carcinoma in the future. The development of methods based on gene and tissue arrays has created a powerful tool for evaluating hundreds to thousands of tumors simultaneously with histologic, immunohistochemical, and chromosomal analyses. Gene array analysis permits rapid molecular profiling, and tissue arrays enable the analysis of protein expression profiles on specimens to determine their potential clinical significance and role in renal cell carcinoma biology. This article reviews the tissue array-based predictors of pathobiology, prognosis, response to treatment, and potential molecular targets for therapy of renal cell carcinoma.

Increasing expression of serine protease matriptase in ovarian tumors: tissue microarray analysis of immunostaining score with clinicopathological parameters

“…[17][18][19][20][21][22][23][24][25][26][27][28] Previous studies of individual cases limited the value of stain intensity-based immunohistochemical quantitation because of the instability of the signal generated by chemical reaction under different environmental conditions. 17,[26][27][28] However, immunohistochemistry studies using tissue microarray technique are more reliable than studies involving individual tissues because all tissues are processed under the same immunostaining conditions and analyzed simultaneously in a tissue microarray slide. 17,[26][27][28] Thus, the immunostaining scores used in our study are a better reflection of the relative level of matriptase protein expression in tumors.…”

“…17,[26][27][28] However, immunohistochemistry studies using tissue microarray technique are more reliable than studies involving individual tissues because all tissues are processed under the same immunostaining conditions and analyzed simultaneously in a tissue microarray slide. 17,[26][27][28] Thus, the immunostaining scores used in our study are a better reflection of the relative level of matriptase protein expression in tumors.…”

“…Immunohistochemistry studies in tissue microarray slides are more reliable than studies in individual slides because all tissues in each array slide are prepared and stained under the same conditions and are analyzed simultaneously. 17 In a series of patients with ovarian tumors, we compared immunostaining scores for matriptase among different histological types of ovarian tumors. Our findings demonstrate for the first time that matriptase is overexpressed in many malignant ovarian tumors.…”

VHLinactivation in renal cell carcinoma: implications for diagnosis, prognosis and treatment

“…The antigen carbonic anhydrase IX (CAIX, also called G250) was identified through a massive tissue microarray screen investigating prognostic factors for RCC. CAIX is a transcriptional target of the HIFmediated transcriptional response to hypoxia or VHL loss [63][64][65]. CAIX is an immediate target of HIF activation and provides a convenient marker for clear cell histology tumors and has been associated with a favorable prognosis [66].…”

Genomics of renal cell cancer — Does it provide breakthrough?

“…19 In a similar analysis CAIX, vimentin and p53 were statistically significant predictors of survival independent of the clinical variables. 22 A model using comparative genomic hybridization (CGH), a molecular screening method permitting the detection of all DNA losses and gains in a tumor, suggested that there may be at least two subclasses of clear cell RCC: one marked by the events -6q, +17q, +17p, and the other by -9p, -13q, -18q. In papillary RCC the gains of 7p and 17p are significantly higher in type 1 than in type 2 tumors.…”