Grade-dependent Proteomics Characterization of Kidney Cancer

Kidney cancer is frequently metastatic on presentation at which point the disease is associated with a 95% mortality. Assessment of tumor grade on pathological examination is the most powerful means for prognostication as well as for stratification of patients into those who might respond to conventional or targeted therapy. Although there exist several grading systems in common use, all suffer from significant disparity among observers. In an attempt to objectify this process as well as to acquire grade-specific mechanistic information, we performed LC-MS/MS-based proteomics analysis on 50 clear cell kidney cancers equally distributed among normal tissues and Fuhrman grades 1–4. Initial experiments confirmed the utility of using archived formalin-fixed paraffin-embedded samples for LC-MS/MS-based proteomics analysis, and the LC-MS/MS findings were validated by extensive immunoblotting. We now show that changes among many biochemical processes and pathways are strongly grade-dependent with the glycolytic and amino acid synthetic pathways highly represented. In addition, proteins relating to acute phase and xenobiotic metabolism signaling are highly represented. Self-organized mapping of proteins with similar patterns of expression led to the creation of a heat map that will be useful in grade characterization as well as in future research relating to oncogenic mechanisms and targeted therapies for kidney cancer.Kidney cancer (or renal cell carcinoma (RCC)¹) is the seventh most common malignancy, the 10th most common cause of cancer death in men, and the ninth most common cancer in women. In 2009, an estimated 13,000 deaths (8,100 men and 4,900 women) will occur in the United States. The disease is frequently asymptomatic; a third of cases are diagnosed when the disease is already metastatic at which time it has 95% mortality (1).Assessment of tumor grade is the most powerful available means to date of determining tumor prognosis; thus objective criteria for assessing grade are essential such that prognostication is unambiguous. In addition, grade criteria are useful in stratifying patients into those most likely to respond to conventional as well as new targeted therapies. There exist several systems for assigning tumor grade in RCC, although most pathologists utilize the Fuhrman grading system. As is evidenced by the abundance of extant grading systems (2), there appears to be a general lack of consensus and thus considerable variability in assigning tumor grades. Objective criteria for grade assignment utilizing specific protein markers will be useful in objectifying this process and thereby allowing for more accurate prognostication. Furthermore assessment of the biological basis of the differences among grades, as evidenced by diverse biochemical pathways altered in a grade-specific fashion, will lead to the development of novel diagnostic assays as well as therapeutic interventions.Once objective grading criteria are put forth, molecular mechanisms by which tumors transition among grades can be identified and further investigated. Using this information, it might be possible to recapitulate the grade transition in vitro to discover novel mechanisms of oncogenesis or at least of transition from a relatively benign to a highly malignant phenotype. Moreover utilizing a systems biology approach to glean grade-specific network and pathway data has the capability to further the understanding of RCC oncogenesis. This approach can be used to identify novel mechanisms of tumor progression within grades and thereby can yield druggable targets.We now show that validated grade-specific, highly sensitive proteomics analysis of RCC resulted in the identification of proteins that vary in expression in a grade-specific fashion. From these data, we identified pathways and networks that are relevant, and likely critical, to grade transitions, and we discovered markers that, either separately or in combination, are able to assist in differentiation among grades. Furthermore our analysis yielded pathways altered in RCC that can ultimately be used both to stratify patients to grade-specific treatments and to identify new therapeutic targets.