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Are primary renal cell carcinoma and metastases of renal cell carcinoma the same cancer?
Urologic Oncology: Seminars and Original Investigations 34 (2016) 215–220
Review article
Are primary renal cell carcinoma and metastases of renal cell carcinoma the same cancer? Aleksandra Semeniuk-Wojtaś, M.D.*, Rafał Stec, M.D., Ph.D., Cezary Szczylik Department of Oncology, Military Institute of Medicine in Warsaw, Warsaw, Poland Received 14 April 2015; received in revised form 30 November 2015; accepted 21 December 2015
Abstract Metastasis is a process consisting of cells spreading from the primary site of the cancer to distant parts of the body. Our understanding of this spread is limited and molecular mechanisms causing particular characteristics of metastasis are still unknown. There is some evidence that primary renal cell carcinoma (RCC) and metastases of RCC exhibit molecular differences that may effect on the biological characteristics of the tumor. Some authors have detected differences in clear cell and nonclear cell component between these 2 groups of tumors. Investigators have also determined that primary RCC and metastases of RCC diverge in their range of renal-specific markers and other protein expression, gene expression pattern, and microRNA expression. There are also certain proteins that are variously expressed in primary RCCs and their metastases and have effect on clinical outcome, e.g., endothelin receptor type B, phos-S6, and CD44. However, further studies are needed on large cohorts of patients to identify differences representing promising targets for prognostic purposes predicting disease-free survival and the metastatic burden of a patient as well as their suitability as potential therapeutic targets. To sum up, in this review we have attempted to summarize studies connected with differences between primary RCC and its metastases and their influence on the biological characteristics of renal cancer. r 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Renal cancer; Metastases; Differences; Heterogenity; Biomarkers
1. Introduction Kidney cancer is not a single disease because it comprises a number of different cancers that occur in the kidney, each with a different histology, which respond differently to therapy and are caused by mutations in different genes. Renal cell carcinoma (RCC) is the most common kidney malignancy and the development of macroscopic metastases of RCC is the major cause of tumorassociated deaths. The morbidity of RCC has consistently increased by approximately 1.5% to 5.9% annually until RCC is now the 10th most common in men and 14th most common in women [1]. Pathologic stage, based on the size of the tumor and the extent of invasion, grade, the histological cell type as well as clinical parameters are Corresponding author. Tel. þ48-22-681-7110; fax: +48-261-818-437. E-mail address: [email protected] (A. Semeniuk-Wojtaś). *
widely used in clinical practice for the prognosis of RCC. Despite this, none of these algorithms are 100% accurate. Identification of alterations that contribute to the variation in tumor behavior and clinical outcome within organ-confined or metastatic RCC is needed for improved management of RCC. Recent advances in understanding cancer as a genetic disease have allowed the development of targeted molecular therapies; however, resistance to these drugs remains a significant problem. Perhaps the key to understand the different clinical outcome and resistance to treatment as well as developing more effective treatments is an in depth study of the metastatic tumors. Little is known about the molecular mechanisms enabling metastatic spread of the primary tumor; however, there is some evidence that primary RCC and metastases of RCC exhibit molecular differences. This article provides an overview of the most important publications on genetic and molecular variations between primary tumors and metastases of RCC.
http://dx.doi.org/10.1016/j.urolonc.2015.12.013 1078-1439/r 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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2. Results and discussion 2.1. Histopathological analyses The diagnosis of a metastasis of clear cell RCC (ccRCC) is based almost entirely on the presence of classic morphologic features along with a prior clinical history of ccRCC, but sometimes it still can be challenging. This may be owing to it presenting many years after the initial diagnosis of a primary renal neoplasm or due to diverse histological variations in RCC. Several immunohistochemistry panels have proven useful in identifying primary or metastatic RCC but some investigators showed variation in renal marker expression in metastatic and primary tumors. Pan et al. detected that metastatic lesions had significantly higher paired box gene (PAX2 and PAX8) H-scores than matched primary tumors. In addition, they found complete loss of marker expression in 6 metastases compared with primary tumors, and this occurred significantly more frequently with RCC antigen [2]. Also, Barr et al. [3] detected that intensity of PAX8 expression was higher in metastases than in primary sites. PAX proteins are involved in cell proliferation, apoptosis inhibitory, differentiation and migration, and constitute, therefore, putative targets of disruption during tumorigenesis. Besides, PAX2 expression is promoted by the loss of von Hippel-Lindau (VHL) and hypoxia in ccRCC. Lee et al. [4] performed immunohistochemical staining for renal-specific markers, but it failed to find any significant changes between these 2 groups of tumors. In addition, they observed that 52.9% of metastatic lesions contained a nonclear cell component such as eosinophilic cytoplasm, rhabdoid features, and sarcomatoid differentiation. Of the metastatic tumors, 24.4% lesions with a nonclear cell component were composed of a nonclear cell component alone without a typical clear cell area. In 81% of metastatic lesions with a nonclear cell component, the corresponding primary tumors showed the same histologic type. Sarcomatoid and rhabdoid components of ccRCC may represent a subclone of the primary tumor that has undergone dedifferentiation. Molecular studies have shown concordant loss of chromosome 3p and a VHL gene mutation in rhabdoid and clear cells from the same case, suggesting divergent differentiation from the same clone [5]. A few authors have compared also vascularization in primary RCCs and in metastatic RCC (mRCCs). Aziz et al. [6] determined that the microvessel area, defined as the total area of microvessels in a given sample area, were higher in primary tissues compared with their metastatic equivalents, but Zhang et al. did not find differences in the expression of chitinase 3-like 1 and microvessel density, defined as measurable vessels in a sample area between primary and metastatic sites [7]. Remark et al. analyzed the immune environment of primary tumors and matched metastatic lesions and found that each metastasis has different immune infiltrates density that correlated with patient survival. They
also found a correlation between the density of infiltrating DC-LAMPþ, CD8þ, and NKp46þ cells in the primary tumor and in the corresponding lung metastasis. Similarity of the immune pattern of the primary tumor and metastasis could reflect, either a potential “imprinting” of the immune microenvironment by the tumor cells or the possibility that the immune contexture in the primary tumor, results in “educated” immune cells that are recalled in the metastatic sites [8]. 2.2. Genomic and proteomic changes Several authors have attempted to identify the genetic changes underlying metastatic progression of human RCC. Bissig et al. revealed that primary tumors and their corresponding metastases were never identical. Genomic changes that frequently occurred in metastases but not in the corresponding primary tumors included 8p, 9p, 17qþ, 21qþ, and Xqþ [9]. The number of genetic aberrations detected in metastases was higher than the number found in primary ccRCC. This is consistent with the theory that RCC progression from nonmetastatic primary tumors to metastasis is driven by an accumulation of genetic changes. The absence of shared genetic changes also includes the possibility that a clonal relationship was missed because of genetic heterogeneity within the primary tumor. Gerlinger et al. [10] found differences in mutations in primary tumors compared with metastatic tumors and provided evidence of intratumor heterogeneity. A single tumorbiopsy specimen reveals a minority of genetic aberrations (including mutations, allelic imbalance, and ploidy) that are present in an entire tumor. Cell clones with metastasisspecific genetic changes may represent minor cell populations in the primary tumor. Besides, growth conditions may differ at varying metastatic sites, giving growth advantage to different cell clones in primary tumors and metastases. Collating between ccRCC metastases and G1 primary tumors identified 43 gene sets with significant upregulation in metastases and 96 gene sets with significant down-regulation, respectively. When comparing ccRCC metastases with G3 primary tumors, there were 20 gene sets with significant up-regulation in metastases and 149 gene sets with significant down-regulation, respectively. Pathways involved in intercellular adhesion, cell-matrix adhesion, and apoptosis were significantly down-regulated in metastases and gene sets with significant up-regulation in metastases are involved in cell cycle control, energy metabolism, and cellular migration. Metastatic cells reflect increased resistance against signals that could induce cellular death and these changes might contribute to a high resistance against various cytotoxic therapies. Up-regulated expression of genes that contribute to cellular motility in the metastatic cells suggests that metastases have higher potential to migration than primary tumors [11]. Wuttig et al. compared the expression profiles of a cohort of pulmonary metastases of ccRCC with profiles of primary RCC and
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Table 1 Differences in expression of miRNAs in metastases compared with primary RCC tumors Study
Up-regulated miRNAs
Down-regulated miRNAs
White et al. [17, 21] Wotschofsky et al. [18] Heinzelmann et al. [19] Butz et al. [20]
miR-638, miR-1915, miR-149 miR-21, miR-155, miR-210, miR-223, miR-224, miR-296 miR-199b-5p, miR-33b-3p and miR-34c-5p
MiR-10b, miR-196a, miR-27b miR-127, miR-370 miR-204, miR-10b and miR-139-5p miR-30a-5p
detected 810 differentially expressed genes. Among the identified genes were the matrix metallopeptidases MMP7 and MMP9, chemokine receptor 3 (CXCR3), differentiation marker membrane metallo-endopeptidase (CD10), apoptosis inhibitor bcl2 and the cell-surface protein CD44. Most of the genes that are dysregulated in metastases promote metastasis-associated processes, like angiogenesis, cell migration, cell motility, and cell adhesion [12]. Authors also detected 167 genes that showed differential expression in synchronously vs. metachronously metastasized tumors [12]. Vaziri et al. sequenced the VHL tumor suppressor gene that is associated with hereditary and sporadic forms of ccRCC in paired tumor specimens and determined that in 40% of patients the VHL status differed between the matched lesions. Also, sometimes, although the primary tumor was wild-type, a mutant VHL gene was identified in the metastatic lesion [13]. Abbas et al. [14] analyzed a set of 45 angiogenesis-associated genes and determined that most genes showed similar expression profiles in primary tumors and metastases. Other authors have focused on microRNAs (miRNAs), i.e., short non–protein-coding RNAs that silencing the expression of genes involved in the control of cell development, proliferation, and apoptosis [15]. miRNAs that have prometastatic or antimetastatic effects have been called
metastamirs [16]. Investigators detected differences in expression of miRNAs in metastases compared with primary tumors and found that miRNA expression was dependent on the metastatic site, i.e., miR-199b showed strongly increased expression in metastases from the lung but was only weakly increased in distant metastases from the brain. Wotschofsky et al. confirmed the general downregulation of miRNAs in metastatic samples [17–19]. Table 1 summarizes findings noted by the cited authors. White et al. evaluated molecular pathways and proteinprotein interactions to characterize mechanisms that drive mRCC and identified 198 proteins that were dysregulated in any of the mRCC samples. The top up-regulated proteins were as follows: Ig lambda chain C regions (9IGLC1), thymosin β4 (TMSB4X), and the ferritin light chain, whereas the most down-regulated proteins were as follows: agmatinase (AGMAT), aminobutyrate aminotransferase (ABAT) and fatty acid-binding protein (FABP1). The most common molecular functions identified included protein binding, oxidoreductase ability, and nucleotide binding. The authors also performed pathway analysis and detected that the most significant dysregulated pathways were glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle. These data show that cancer cells reprogram their metabolism and shift from aerobic to anaerobic
Table 2 Differences in proteins expression in metastases compared with primary RCC tumors Symbol
Name
Function
Authors
Expression in metastases compared to primary RCC
MEK 1 ALDH1 bcl2 14–3-3ζ Ki67 SNAIL
Mitogen activated protein kinase-1 Aldehyde dehydrogenase enzyme
Proliferation Cellular differentiation Inhibiting apoptosis Cellular migration Proliferation marker Takes part in epithelial to mesenchymal transition Take part in epithelial to mesenchymal transition Promotes cell proliferation
Aziz et al. [30] Abourbih et al. [31] Lee et al. [32] Masui et al. [33] Laird et al. [34] Laird et al. [34]
Higher Lower Higher Higher Higher Higher
Laird et al. [34]
Higher
Schultz et al. [35]
Higher
Regulates cell growth Promotes cell proliferation
Schultz et al. [35] Schultz et al. [35]
Higher Higher
Transmembrane serine protease, cellular activator of growth factor
Mukai et al. [36]
Higher
14–3-3 zeta/delta Snail family zinc finger 1
SLUG
Snail family zinc finger 2
phos-AKT
Phosphorylated v-akt murine thymoma viral oncogene homolog 1 4E-binding protein-1 v-myc avian myelocytomatosis viral oncogene homolog
4EBP1 c-MYC Matriptase
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Table 3 Association between differences in expression of examined proteins in metastases compared with primary RCC and clinical outcomes (prognostic) Symbol
Name
Function
Study
Expression in metastases compared to primary RCC
Clinical outcomes
CD31 [38]
Platelet/endothelial cell adhesion molecule Endothelin Receptor type B
Adhesion molecule
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.096)
Member of the Endothelin axis, take part in tumor progression Expressed by endothelial cells, take part in tumor progression Regulates cell growth
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.006) longer DFS (P ¼ 0.016)
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.012) longer DFS (P ¼ 0.086)
Schultz et al. [35]
Higher
Longer DSS (P ¼ 0.006)
Cellular migration Transcription factor
Masui et al. [33] Buchner et al. [37]
Higher Lower
Shorter DFS Shorter TSS (P ¼ 0.04)
Silenced genes that regulate e.g. tumor proliferation, invasion, and angiogenesis Promotes inactivation and apoptosis of activated anti-tumor T cells Induces apoptosis Transmembrane glycoproteins, receptor for hyaluronate Growth factor receptor Growth factor receptor, take part in angiogenesis Growth factor, take part in angiogenesis
Lee and Cho [28]
No difference
Xu et al. [29]
Higher
Shorter DFS (P ¼ 0.019) shorter OS (P ¼ 0.066) Shorter DSS (P ¼ 0.03)
Jilaveanu et al. [24] Thompson et al. [39]
Higher Not assessed
Not assessed Shorter DSS (P ¼ 0.002)
Zigeuner et al. [40] Lim et al. [41]
Higher Higher
Shorter DFS (P ¼ 0.01) Shorter OS (P ¼ 0.011)
Mukai et al. [36]
Higher
Shorter OS (P ¼ 0.02)
Laird et al. [34]
Higher
Lower CSS (P ¼ 0.011)
Laird et al. [34]
No difference
lower CSS (P ¼ 0.003)
EDNRB
TSPAN7
Tetraspanin 7
phos-S6
Phosphorylated S6 protein Profilin- 1 Hepatocyte nuclear factor 1 beta Enhancer of zeste homolog 2
Pfn1 HNF-1β EZH2
PD-L1 [39]
Programmed death ligand 1
p53 CD44
Tumor protein p53 CD44 molecule
MET
Receptor tyrosine kinase Vascular endothelial growth factor receptor 1 Vascular endothelial growth factor ligand D
VEGFR1
VEGFD
CSS ¼ cancer-specific survival; DFS ¼ disease-free survival; DSS ¼ disease-specific survival; OS ¼ overall survival; TSS ¼ tumor-specific survival.
respiration. It is hypothesized that the glycolytic phenotype arises in metastasis because of transient hypoxic episodes. Cancer cells are also able to perform glycolysis and are resistant to hypoxia, so will be selectively favored for survival and growth [21]. Stickel et al. [22] determined that metastases were similar to the primary tumors, both at the level of HLA ligand presentation and mRNA but distant metastases showed higher amounts of HLA class I molecules compared to local lymph node metastases [23]. Jilaveanu et al. [24] detected that metastases demonstrated higher expression of programmed death ligand 1 (PD-L1) that connects with the costimulatory receptor on T cells and promotes inactivation and apoptosis of activated anti-tumor T cells [25] but in another study tumor cell PD-L1 levels were not different in primary tumors and metastases [26]. Lee and Choe examined the expression of enhancer of zeste homolog 2 (EZH2) that silenced genes that regulate, e.g.,
tumor proliferation, invasion, and angiogenesis [27] and showed that almost all metastases exhibited similar EZH2 expression as their primary tumors [28] but Xu et al. determined that metastatic ccRCCs expressed the marker more commonly than primary ccRCCs. In addition, tumors in the liver and brain had the strongest EZH2 expression, while lung metastases exhibited the lowest expression [29]. Table 2 shows differences in protein expression between primary RCC and metastatic tumors. 2.3. Biomarkers Differences in biology between primary tumors and metastases give rise to searching a biomarker that predicts aggressive clinical behavior of metastatic tumor. Buchner et al. [37] identified that hepatocyte nuclear factor 1 beta (HNF-1β), Na-dependent glucose transporter 1 (KIAA1919)
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and synapse defective 1 (SYDE1) discriminated patient groups with significantly different prognoses. Other authors also analyzed influence of expression of examined proteins on clinical outcomes and detected that some of them have prognostic value. Table 3 summarizes the findings noted by the authors.
3. Conclusion The present review describes differences between primary renal tumors and their metastases at various levels of cellular functionality associated with tumor biology and clinical outcome. Disease progression in RCC is associated with significant changes in the expression of genes and proteins, which probably makes metastatic cancer cells that are more aggressive. These changes may partially explain the difficulties connected with different clinical outcomes within organ-confined and metastatic RCC but at present, no RCC biomarker is an appropriate candidate for use in clinical practice. However, Wuttig et al. provided evidence that “late metastases” diagnosed Z5 years after nephrectomy and “early metastases” occurred r9 months after nephrectomy showed differential expression of genes involved in metastasis-associated processes and have greater metastatic potential [12] despite clinical analyses showing a better outcome of patients with a longer period from nephrectomy to recurrence of the disease. This may indicate that differential expression of genes and proteins in a primary tumor and matched metastases is only one of the causes of the various clinical behaviors of these tumors. Greater analysis of the differences between primary tumors and metastases, also on immunological level, is required to gain a full assessment of the pathway changes, as these differences may have implications for future work understanding the cancer biology. Further prospective studies on large cohort patients are needed to identify differences representing promising targets for prognostic purposes, predicting the disease-free survival and metastatic burden of a patient as well as their suitability as potential therapeutic targets. References [1] Bielecka ZF, Czarnecka AM, Szczylik C. Genomic analysis as the first step toward personalized treatment in renal cell carcinoma. Front Oncol 2014;4:194. [2] Pan Z, Grizzle W, Hameed O. Significant variation of immunohistochemical marker expression in paired primary and metastatic clear cell renal cell carcinomas. Am J Clin Pathol 2013;140:410–8. [3] Barr ML, Jilaveanu LB, Camp RL, et al. PAX-8 expression in renal tumours and distant sites: A useful marker of primary and metastatic renal cell carcinoma. J Clin Pathol 2015;68:12–7. [4] Lee C, Park J, Moon K, et al. Histologic variations and immunohistochemical features of metastatic clear cell renal cell carcinoma. Korean J Pathol 2013;47:426–32. [5] Humphrey PA. Renal cell carcinoma with rhabdoid features. J Urol 2011;186:675–6.
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[6] Aziz S, Sznol J, Adeniran A, et al. Vascularity of primary and metastatic renal cell carcinoma specimens. J Transl Med 2013;11:15. [7] Zhang JP, Yuan HX, Kong WT, et al. Increased expression of Chitinase 3-like 1 and microvessel density predicts metastasis and poor prognosis in clear cell renal cell carcinoma. Tumour Biol 2014;35:12131–7. [8] Remark R, Alifano M, Cremer I, et al. Characteristics and clinical impacts of the immune environments in colorectal and renal cell carcinoma lung metastases: influence of tumor origin. Clin Cancer Res 2013;19:4079–91. [9] Bissig H, Richter J, Desper R, et al. Evaluation of the clonal relationship between primary and metastatic renal cell carcinoma by comparative genomic hybridization. Am J Pathol 1999;155:267–74. [10] Gerlinger M, Rowan A, Horswell S, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 2012;366:883–92. [11] Maruschke M, Hakenberg O, Koczan D, et al. Expression profiling of metastatic renal cell carcinoma using gene set enrichment analysis. Int J Urol 2014;21:46–51. [12] Wuttig D, Baier B, Fuessel S, et al. Gene signatures of pulmonary metastases of renal cell carcinoma reflect the disease-free interval and the number of metastases per patient. Int J Cancer 2009;125:474–82. [13] Vaziri S, Tavares E, Golshayan A, et al. Differing von Hippel Lindau genotype in paired primary and metastatic tumors in patients with clear cell renal cell carcinoma. Front Oncol 2012;2:51. [14] Abbas M, Salem J, Stucki-Koch A, et al. Expression of angiogenic factors is increased in metastasized renal cell carcinoma. Virchows Arch 2014;464:197–202. [15] Zhang B, Wang Q, Pan X. MicroRNAs and their regulatory roles in animals and plants. J Cell Physiol 2007;210:279–89. [16] Hurst DR, Edmonds MD, Welch DR. Metastamir: the field of metastasis-regulatory microRNA is spreading. Cancer Res 2009;69: 7495–8. [17] White NM, Khella HW, Grigull J, et al. miRNA profiling in metastatic renal cell carcinoma reveals a tumour-suppressor effect for miR-215. Br J Cancer 2011;105:1741–9. [18] Wotschofsky Z, Liep J, Meyer HA, et al. Identification of metastamirs as metastasis-associated microRNAs in clear cell renal cell carcinomas. Int J Biol Sci 2012;8:1363–74. [19] Heinzelmann J, Unrein A, Wickmann U, et al. MicroRNAs with prognostic potential for metastasis in clear cell renal cell carcinoma: a comparison of primary tumors and distant metastases. Ann Surg Oncol 2014;21:1046–54. [20] Butz H, Szabó PM, Khella H, et al. miRNA-target network reveals miR-124as a key miRNA contributing to clear cell renal cell carcinoma aggressive behaviour by targeting CAV1 and FLOT1. Oncotarget 2015;6(14):12543–57. [21] White N, Newsted D, Masui O, et al. Identification and validation of dysregulated metabolic pathways in metastatic renal cell carcinoma. Tumor Biol 2014;35:1833–46. [22] Stickel J, Weinzierl A, Hillen N, et al. HLA ligand profiles of primary renal cell carcinoma maintained in metastases. Cancer Immunol Immunother 2009;58:1407–17. [23] Stickel J, Stickel N, Hennenlotter J, et al. Quantification of HLA class I molecules on renal cell carcinoma using Edman degradation. BMC Urol 2011;11:1. [24] Jilaveanu LB, Shuch B, Zito CR, et al. PD-L1 expression in clear cell renal cell carcinoma: an analysis of nephrectomy and sites of metastases. J Cancer 2014;24:166–72. [25] Dong H, Strome SE, Salomao DR, et al. Tumor-associated B7-H1 promotes T-cell apoptosis: a potential mechanism of immune evasion. Nat Med 2002;8:793–800. [26] Callea M, Albiges L, Gupta M, et al. Differential expression of PD-L1 between primary and metastatic sites in clear cell renal cell carcinoma. Cancer Immunol Res 2015:[pii: canimm.0043.2015. Epub ahead of print]. [27] Simon JA, Lange CA. Roles of the EZH2 histone methyltransferase in cancer epigenetics. Mutat Res 2008;647:21–9.
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[28] Lee H, Choe M. Expression of EZH2 in renal cell carcinoma as a novel prognostic marker. Pathol Int 2012;62:735–41. [29] Xu B, Abourbih S, Sircar K, et al. Enhancer of zeste homolog 2 expression is associated with metastasis and adverse clinical outcome in clear cell renal cell carcinoma: a comparative study and review of the literature. Arch Pathol Lab Med 2013;137:10. [30] Aziz S, Sznol J, Adeniran A, et al. Expression of drug targets in primary and matched metastatic renal cell carcinoma tumors. BMC Clin Pathol 2013;13:3. [31] Abourbih S, Sircar K, Tanguay S, et al. Aldehyde dehydrogenase 1 expression in primary and metastatic renal cell carcinoma: an immunohistochemistry study. World J Surg Oncol 2013;11: 298. [32] Lee C, Genega E, Hutchinson B, et al. Conventional (clear cell) renal carcinoma metastases have greater bcl-2 expression than high-risk primary tumors. Urol Oncol 2003;21:179–84. [33] Masui O, White NM, DeSouza LV, et al. Quantitative proteomic analysis in metastatic renal cell carcinoma reveals a unique set of proteins with potential prognostic significance [Other authors also analyzed influence of expression of examined proteins on clinical outcomes and detected that some of them have prognostic value]. Mol Cell Proteomics 2013;12:132–44. [34] Laird A, O'Mahony FC, Nanda J, et al. Differential expression of prognostic proteomic markers in primary tumour, venous tumour thrombus and metastatic renal cell cancer tissue and correlation with patient outcome. PLoS One 2013;8:4.
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Review article
Are primary renal cell carcinoma and metastases of renal cell carcinoma the same cancer? Aleksandra Semeniuk-Wojtaś, M.D.*, Rafał Stec, M.D., Ph.D., Cezary Szczylik Department of Oncology, Military Institute of Medicine in Warsaw, Warsaw, Poland Received 14 April 2015; received in revised form 30 November 2015; accepted 21 December 2015
Abstract Metastasis is a process consisting of cells spreading from the primary site of the cancer to distant parts of the body. Our understanding of this spread is limited and molecular mechanisms causing particular characteristics of metastasis are still unknown. There is some evidence that primary renal cell carcinoma (RCC) and metastases of RCC exhibit molecular differences that may effect on the biological characteristics of the tumor. Some authors have detected differences in clear cell and nonclear cell component between these 2 groups of tumors. Investigators have also determined that primary RCC and metastases of RCC diverge in their range of renal-specific markers and other protein expression, gene expression pattern, and microRNA expression. There are also certain proteins that are variously expressed in primary RCCs and their metastases and have effect on clinical outcome, e.g., endothelin receptor type B, phos-S6, and CD44. However, further studies are needed on large cohorts of patients to identify differences representing promising targets for prognostic purposes predicting disease-free survival and the metastatic burden of a patient as well as their suitability as potential therapeutic targets. To sum up, in this review we have attempted to summarize studies connected with differences between primary RCC and its metastases and their influence on the biological characteristics of renal cancer. r 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Renal cancer; Metastases; Differences; Heterogenity; Biomarkers
1. Introduction Kidney cancer is not a single disease because it comprises a number of different cancers that occur in the kidney, each with a different histology, which respond differently to therapy and are caused by mutations in different genes. Renal cell carcinoma (RCC) is the most common kidney malignancy and the development of macroscopic metastases of RCC is the major cause of tumorassociated deaths. The morbidity of RCC has consistently increased by approximately 1.5% to 5.9% annually until RCC is now the 10th most common in men and 14th most common in women [1]. Pathologic stage, based on the size of the tumor and the extent of invasion, grade, the histological cell type as well as clinical parameters are Corresponding author. Tel. þ48-22-681-7110; fax: +48-261-818-437. E-mail address: [email protected] (A. Semeniuk-Wojtaś). *
widely used in clinical practice for the prognosis of RCC. Despite this, none of these algorithms are 100% accurate. Identification of alterations that contribute to the variation in tumor behavior and clinical outcome within organ-confined or metastatic RCC is needed for improved management of RCC. Recent advances in understanding cancer as a genetic disease have allowed the development of targeted molecular therapies; however, resistance to these drugs remains a significant problem. Perhaps the key to understand the different clinical outcome and resistance to treatment as well as developing more effective treatments is an in depth study of the metastatic tumors. Little is known about the molecular mechanisms enabling metastatic spread of the primary tumor; however, there is some evidence that primary RCC and metastases of RCC exhibit molecular differences. This article provides an overview of the most important publications on genetic and molecular variations between primary tumors and metastases of RCC.
http://dx.doi.org/10.1016/j.urolonc.2015.12.013 1078-1439/r 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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2. Results and discussion 2.1. Histopathological analyses The diagnosis of a metastasis of clear cell RCC (ccRCC) is based almost entirely on the presence of classic morphologic features along with a prior clinical history of ccRCC, but sometimes it still can be challenging. This may be owing to it presenting many years after the initial diagnosis of a primary renal neoplasm or due to diverse histological variations in RCC. Several immunohistochemistry panels have proven useful in identifying primary or metastatic RCC but some investigators showed variation in renal marker expression in metastatic and primary tumors. Pan et al. detected that metastatic lesions had significantly higher paired box gene (PAX2 and PAX8) H-scores than matched primary tumors. In addition, they found complete loss of marker expression in 6 metastases compared with primary tumors, and this occurred significantly more frequently with RCC antigen [2]. Also, Barr et al. [3] detected that intensity of PAX8 expression was higher in metastases than in primary sites. PAX proteins are involved in cell proliferation, apoptosis inhibitory, differentiation and migration, and constitute, therefore, putative targets of disruption during tumorigenesis. Besides, PAX2 expression is promoted by the loss of von Hippel-Lindau (VHL) and hypoxia in ccRCC. Lee et al. [4] performed immunohistochemical staining for renal-specific markers, but it failed to find any significant changes between these 2 groups of tumors. In addition, they observed that 52.9% of metastatic lesions contained a nonclear cell component such as eosinophilic cytoplasm, rhabdoid features, and sarcomatoid differentiation. Of the metastatic tumors, 24.4% lesions with a nonclear cell component were composed of a nonclear cell component alone without a typical clear cell area. In 81% of metastatic lesions with a nonclear cell component, the corresponding primary tumors showed the same histologic type. Sarcomatoid and rhabdoid components of ccRCC may represent a subclone of the primary tumor that has undergone dedifferentiation. Molecular studies have shown concordant loss of chromosome 3p and a VHL gene mutation in rhabdoid and clear cells from the same case, suggesting divergent differentiation from the same clone [5]. A few authors have compared also vascularization in primary RCCs and in metastatic RCC (mRCCs). Aziz et al. [6] determined that the microvessel area, defined as the total area of microvessels in a given sample area, were higher in primary tissues compared with their metastatic equivalents, but Zhang et al. did not find differences in the expression of chitinase 3-like 1 and microvessel density, defined as measurable vessels in a sample area between primary and metastatic sites [7]. Remark et al. analyzed the immune environment of primary tumors and matched metastatic lesions and found that each metastasis has different immune infiltrates density that correlated with patient survival. They
also found a correlation between the density of infiltrating DC-LAMPþ, CD8þ, and NKp46þ cells in the primary tumor and in the corresponding lung metastasis. Similarity of the immune pattern of the primary tumor and metastasis could reflect, either a potential “imprinting” of the immune microenvironment by the tumor cells or the possibility that the immune contexture in the primary tumor, results in “educated” immune cells that are recalled in the metastatic sites [8]. 2.2. Genomic and proteomic changes Several authors have attempted to identify the genetic changes underlying metastatic progression of human RCC. Bissig et al. revealed that primary tumors and their corresponding metastases were never identical. Genomic changes that frequently occurred in metastases but not in the corresponding primary tumors included 8p, 9p, 17qþ, 21qþ, and Xqþ [9]. The number of genetic aberrations detected in metastases was higher than the number found in primary ccRCC. This is consistent with the theory that RCC progression from nonmetastatic primary tumors to metastasis is driven by an accumulation of genetic changes. The absence of shared genetic changes also includes the possibility that a clonal relationship was missed because of genetic heterogeneity within the primary tumor. Gerlinger et al. [10] found differences in mutations in primary tumors compared with metastatic tumors and provided evidence of intratumor heterogeneity. A single tumorbiopsy specimen reveals a minority of genetic aberrations (including mutations, allelic imbalance, and ploidy) that are present in an entire tumor. Cell clones with metastasisspecific genetic changes may represent minor cell populations in the primary tumor. Besides, growth conditions may differ at varying metastatic sites, giving growth advantage to different cell clones in primary tumors and metastases. Collating between ccRCC metastases and G1 primary tumors identified 43 gene sets with significant upregulation in metastases and 96 gene sets with significant down-regulation, respectively. When comparing ccRCC metastases with G3 primary tumors, there were 20 gene sets with significant up-regulation in metastases and 149 gene sets with significant down-regulation, respectively. Pathways involved in intercellular adhesion, cell-matrix adhesion, and apoptosis were significantly down-regulated in metastases and gene sets with significant up-regulation in metastases are involved in cell cycle control, energy metabolism, and cellular migration. Metastatic cells reflect increased resistance against signals that could induce cellular death and these changes might contribute to a high resistance against various cytotoxic therapies. Up-regulated expression of genes that contribute to cellular motility in the metastatic cells suggests that metastases have higher potential to migration than primary tumors [11]. Wuttig et al. compared the expression profiles of a cohort of pulmonary metastases of ccRCC with profiles of primary RCC and
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Table 1 Differences in expression of miRNAs in metastases compared with primary RCC tumors Study
Up-regulated miRNAs
Down-regulated miRNAs
White et al. [17, 21] Wotschofsky et al. [18] Heinzelmann et al. [19] Butz et al. [20]
miR-638, miR-1915, miR-149 miR-21, miR-155, miR-210, miR-223, miR-224, miR-296 miR-199b-5p, miR-33b-3p and miR-34c-5p
MiR-10b, miR-196a, miR-27b miR-127, miR-370 miR-204, miR-10b and miR-139-5p miR-30a-5p
detected 810 differentially expressed genes. Among the identified genes were the matrix metallopeptidases MMP7 and MMP9, chemokine receptor 3 (CXCR3), differentiation marker membrane metallo-endopeptidase (CD10), apoptosis inhibitor bcl2 and the cell-surface protein CD44. Most of the genes that are dysregulated in metastases promote metastasis-associated processes, like angiogenesis, cell migration, cell motility, and cell adhesion [12]. Authors also detected 167 genes that showed differential expression in synchronously vs. metachronously metastasized tumors [12]. Vaziri et al. sequenced the VHL tumor suppressor gene that is associated with hereditary and sporadic forms of ccRCC in paired tumor specimens and determined that in 40% of patients the VHL status differed between the matched lesions. Also, sometimes, although the primary tumor was wild-type, a mutant VHL gene was identified in the metastatic lesion [13]. Abbas et al. [14] analyzed a set of 45 angiogenesis-associated genes and determined that most genes showed similar expression profiles in primary tumors and metastases. Other authors have focused on microRNAs (miRNAs), i.e., short non–protein-coding RNAs that silencing the expression of genes involved in the control of cell development, proliferation, and apoptosis [15]. miRNAs that have prometastatic or antimetastatic effects have been called
metastamirs [16]. Investigators detected differences in expression of miRNAs in metastases compared with primary tumors and found that miRNA expression was dependent on the metastatic site, i.e., miR-199b showed strongly increased expression in metastases from the lung but was only weakly increased in distant metastases from the brain. Wotschofsky et al. confirmed the general downregulation of miRNAs in metastatic samples [17–19]. Table 1 summarizes findings noted by the cited authors. White et al. evaluated molecular pathways and proteinprotein interactions to characterize mechanisms that drive mRCC and identified 198 proteins that were dysregulated in any of the mRCC samples. The top up-regulated proteins were as follows: Ig lambda chain C regions (9IGLC1), thymosin β4 (TMSB4X), and the ferritin light chain, whereas the most down-regulated proteins were as follows: agmatinase (AGMAT), aminobutyrate aminotransferase (ABAT) and fatty acid-binding protein (FABP1). The most common molecular functions identified included protein binding, oxidoreductase ability, and nucleotide binding. The authors also performed pathway analysis and detected that the most significant dysregulated pathways were glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle. These data show that cancer cells reprogram their metabolism and shift from aerobic to anaerobic
Table 2 Differences in proteins expression in metastases compared with primary RCC tumors Symbol
Name
Function
Authors
Expression in metastases compared to primary RCC
MEK 1 ALDH1 bcl2 14–3-3ζ Ki67 SNAIL
Mitogen activated protein kinase-1 Aldehyde dehydrogenase enzyme
Proliferation Cellular differentiation Inhibiting apoptosis Cellular migration Proliferation marker Takes part in epithelial to mesenchymal transition Take part in epithelial to mesenchymal transition Promotes cell proliferation
Aziz et al. [30] Abourbih et al. [31] Lee et al. [32] Masui et al. [33] Laird et al. [34] Laird et al. [34]
Higher Lower Higher Higher Higher Higher
Laird et al. [34]
Higher
Schultz et al. [35]
Higher
Regulates cell growth Promotes cell proliferation
Schultz et al. [35] Schultz et al. [35]
Higher Higher
Transmembrane serine protease, cellular activator of growth factor
Mukai et al. [36]
Higher
14–3-3 zeta/delta Snail family zinc finger 1
SLUG
Snail family zinc finger 2
phos-AKT
Phosphorylated v-akt murine thymoma viral oncogene homolog 1 4E-binding protein-1 v-myc avian myelocytomatosis viral oncogene homolog
4EBP1 c-MYC Matriptase
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Table 3 Association between differences in expression of examined proteins in metastases compared with primary RCC and clinical outcomes (prognostic) Symbol
Name
Function
Study
Expression in metastases compared to primary RCC
Clinical outcomes
CD31 [38]
Platelet/endothelial cell adhesion molecule Endothelin Receptor type B
Adhesion molecule
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.096)
Member of the Endothelin axis, take part in tumor progression Expressed by endothelial cells, take part in tumor progression Regulates cell growth
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.006) longer DFS (P ¼ 0.016)
Wuttig et al. [12]
Lower
Longer TSS (P ¼ 0.012) longer DFS (P ¼ 0.086)
Schultz et al. [35]
Higher
Longer DSS (P ¼ 0.006)
Cellular migration Transcription factor
Masui et al. [33] Buchner et al. [37]
Higher Lower
Shorter DFS Shorter TSS (P ¼ 0.04)
Silenced genes that regulate e.g. tumor proliferation, invasion, and angiogenesis Promotes inactivation and apoptosis of activated anti-tumor T cells Induces apoptosis Transmembrane glycoproteins, receptor for hyaluronate Growth factor receptor Growth factor receptor, take part in angiogenesis Growth factor, take part in angiogenesis
Lee and Cho [28]
No difference
Xu et al. [29]
Higher
Shorter DFS (P ¼ 0.019) shorter OS (P ¼ 0.066) Shorter DSS (P ¼ 0.03)
Jilaveanu et al. [24] Thompson et al. [39]
Higher Not assessed
Not assessed Shorter DSS (P ¼ 0.002)
Zigeuner et al. [40] Lim et al. [41]
Higher Higher
Shorter DFS (P ¼ 0.01) Shorter OS (P ¼ 0.011)
Mukai et al. [36]
Higher
Shorter OS (P ¼ 0.02)
Laird et al. [34]
Higher
Lower CSS (P ¼ 0.011)
Laird et al. [34]
No difference
lower CSS (P ¼ 0.003)
EDNRB
TSPAN7
Tetraspanin 7
phos-S6
Phosphorylated S6 protein Profilin- 1 Hepatocyte nuclear factor 1 beta Enhancer of zeste homolog 2
Pfn1 HNF-1β EZH2
PD-L1 [39]
Programmed death ligand 1
p53 CD44
Tumor protein p53 CD44 molecule
MET
Receptor tyrosine kinase Vascular endothelial growth factor receptor 1 Vascular endothelial growth factor ligand D
VEGFR1
VEGFD
CSS ¼ cancer-specific survival; DFS ¼ disease-free survival; DSS ¼ disease-specific survival; OS ¼ overall survival; TSS ¼ tumor-specific survival.
respiration. It is hypothesized that the glycolytic phenotype arises in metastasis because of transient hypoxic episodes. Cancer cells are also able to perform glycolysis and are resistant to hypoxia, so will be selectively favored for survival and growth [21]. Stickel et al. [22] determined that metastases were similar to the primary tumors, both at the level of HLA ligand presentation and mRNA but distant metastases showed higher amounts of HLA class I molecules compared to local lymph node metastases [23]. Jilaveanu et al. [24] detected that metastases demonstrated higher expression of programmed death ligand 1 (PD-L1) that connects with the costimulatory receptor on T cells and promotes inactivation and apoptosis of activated anti-tumor T cells [25] but in another study tumor cell PD-L1 levels were not different in primary tumors and metastases [26]. Lee and Choe examined the expression of enhancer of zeste homolog 2 (EZH2) that silenced genes that regulate, e.g.,
tumor proliferation, invasion, and angiogenesis [27] and showed that almost all metastases exhibited similar EZH2 expression as their primary tumors [28] but Xu et al. determined that metastatic ccRCCs expressed the marker more commonly than primary ccRCCs. In addition, tumors in the liver and brain had the strongest EZH2 expression, while lung metastases exhibited the lowest expression [29]. Table 2 shows differences in protein expression between primary RCC and metastatic tumors. 2.3. Biomarkers Differences in biology between primary tumors and metastases give rise to searching a biomarker that predicts aggressive clinical behavior of metastatic tumor. Buchner et al. [37] identified that hepatocyte nuclear factor 1 beta (HNF-1β), Na-dependent glucose transporter 1 (KIAA1919)
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and synapse defective 1 (SYDE1) discriminated patient groups with significantly different prognoses. Other authors also analyzed influence of expression of examined proteins on clinical outcomes and detected that some of them have prognostic value. Table 3 summarizes the findings noted by the authors.
3. Conclusion The present review describes differences between primary renal tumors and their metastases at various levels of cellular functionality associated with tumor biology and clinical outcome. Disease progression in RCC is associated with significant changes in the expression of genes and proteins, which probably makes metastatic cancer cells that are more aggressive. These changes may partially explain the difficulties connected with different clinical outcomes within organ-confined and metastatic RCC but at present, no RCC biomarker is an appropriate candidate for use in clinical practice. However, Wuttig et al. provided evidence that “late metastases” diagnosed Z5 years after nephrectomy and “early metastases” occurred r9 months after nephrectomy showed differential expression of genes involved in metastasis-associated processes and have greater metastatic potential [12] despite clinical analyses showing a better outcome of patients with a longer period from nephrectomy to recurrence of the disease. This may indicate that differential expression of genes and proteins in a primary tumor and matched metastases is only one of the causes of the various clinical behaviors of these tumors. Greater analysis of the differences between primary tumors and metastases, also on immunological level, is required to gain a full assessment of the pathway changes, as these differences may have implications for future work understanding the cancer biology. Further prospective studies on large cohort patients are needed to identify differences representing promising targets for prognostic purposes, predicting the disease-free survival and metastatic burden of a patient as well as their suitability as potential therapeutic targets. References [1] Bielecka ZF, Czarnecka AM, Szczylik C. Genomic analysis as the first step toward personalized treatment in renal cell carcinoma. Front Oncol 2014;4:194. [2] Pan Z, Grizzle W, Hameed O. Significant variation of immunohistochemical marker expression in paired primary and metastatic clear cell renal cell carcinomas. Am J Clin Pathol 2013;140:410–8. [3] Barr ML, Jilaveanu LB, Camp RL, et al. PAX-8 expression in renal tumours and distant sites: A useful marker of primary and metastatic renal cell carcinoma. J Clin Pathol 2015;68:12–7. [4] Lee C, Park J, Moon K, et al. Histologic variations and immunohistochemical features of metastatic clear cell renal cell carcinoma. Korean J Pathol 2013;47:426–32. [5] Humphrey PA. Renal cell carcinoma with rhabdoid features. J Urol 2011;186:675–6.
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