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Keywords:

  • kidney neoplasms;
  • carcinoma;
  • renal cell;
  • tumor biomarkers;
  • BAP1;
  • survival

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

BACKGROUND

The majority of patients diagnosed with clear cell renal cell carcinoma (ccRCC) have low-risk disease with a < 10% chance of ccRCC-specific death. DNA sequencing revealed that mutations in BAP1 (BRCA1 associated protein-1) occur in 5% to 15% of ccRCC cases and are associated with poor outcomes. The vast majority of BAP1 mutations abolish protein expression. In this study, we used a highly sensitive and specific immunohistochemistry (IHC) assay to test whether BAP1 expression is an independent marker of ccRCC-specific survival, particularly in patients with low-risk disease.

METHODS

BAP1 expression was assessed, using IHC, in 1479 patients who underwent nephrectomy to treat clinically localized ccRCC. A centralized pathologist dichotomized patients as either BAP1-positive or BAP1-negative. The authors employed Kaplan-Meier and Cox regression models to associate BAP1 expression with cancer-specific survival.

RESULTS

A total of 10.5% of tumors were BAP1-negative, 84.8% of tumors were BAP1-positive, and 4.6% of tumors had ambiguous staining for BAP1. Patients with BAP1-negative tumors have an increased risk of ccRCC-related death (hazard ratio [HR] = 3.06; 95% confidence interval [CI] = 2.28-4.10; P = 6.77 × 10−14). BAP1 expression remained an independent marker of prognosis after adjusting for the UCLA integrated staging system (UISS) (HR = 1.67; 95% CI = 1.24-2.25; P < .001). Finally, BAP1 was an independent prognostic marker in low-risk patients with a Mayo Clinic stage, size, grade, and necrosis (SSIGN) score of ≤ 3 (HR = 3.24; 95% CI = 1.26-8.33; P = .015).

CONCLUSIONS

This study used a large patient cohort to demonstrate that BAP1 expression is an independent marker of prognosis in patients with low-risk (SSIGN≤ 3) ccRCC. Cancer 2014;1059–1067. © 2014 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Approximately 40,000 patients are diagnosed with clear cell renal cell carcinoma (ccRCC) annually in the United States.[1] Due in part to the widespread use of abdominal imaging, ∼60% of patients with ccRCC are diagnosed at an early stage and have a low risk (< 10%) of cancer-related death. Although the majority of patients in this category have good outcomes, there is a subset (∼5%) that dies from metastatic renal cancer. However, no markers exist to identify this group. Recent discoveries about the molecular genetics of renal cancer offer the opportunity to further stratify these patients and have the potential to change clinical practice by providing patients with a more personalized prognosis and possibly a potential therapeutic target.[2-5]

Historically, studies involving the molecular pathogenesis of ccRCC focused on the loss of the von Hippel-Lindau (VHL) gene located on chromosome 3p, an area frequently deleted in ccRCC.[6, 7] More recently, multiple groups have identified recurrent mutations of additional genes located on chromosome 3p including BAP1, PBRM1, and SETD2.[8-10] Mutations in BAP1 (BRCA1 associated protein-1) occur in 5% to 15% of sporadic ccRCC tumors, and germline BAP1 mutations occur in some familial cases of ccRCC.[11, 12] BAP1 functions as a de-ubiquinating enzyme that regulates multiple cellular pathways related to tumorigenesis.[4, 13] ccRCC tumors with BAP1 mutations have distinct RNA profiles compared to BAP1 wild-type tumors, suggesting that BAP1 mutant tumors could represent their own unique ccRCC phenotype.[4] Finally, we and others have demonstrated an association between BAP1 mutations and increased risk of death among patients undergoing surgery for ccRCC.[3, 4] Taken together, there is considerable evidence to support a key role for BAP1 mutations in the pathogenesis and prognosis of ccRCC.

Although previous studies used DNA sequencing to identify and associate BAP1 loss with adverse clinical outcomes in ccRCC, these studies were limited by 1) the expense associating with sequencing BAP1 and limited clinical applicability, and 2) relatively small sample sizes that were insufficiently powered to explore unique subgroups (ie, those patients with “low-risk” disease). We developed an immunohistochemistry (IHC) assay to assess expression of BAP1 protein with positive and negative predictive values of > 98%.[8] Using this IHC assay, we sought to determine if BAP1 protein expression is an independent marker of ccRCC-related prognosis, especially in those patients with low-risk disease as defined by individual pathologic indices (ie, stage and grade) and our own institution's multivariable prognostic algorithms that account for tumor stage, size, grade, and necrosis (SSIGN score[14, 15]). Finally, in an exploratory analysis, we assessed whether BAP1 expression remained an independent marker of prognosis after adjusting for other biomarkers that are associated with ccRCC prognosis (ie, PDL1, Ki-67, survivin).

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Patient Selection

After Institutional Review Board approval, we identified 1479 patients treated with radical nephrectomy or nephron-sparing surgery for unilateral, sporadic, noncystic ccRCC between 1990 and 2006 from the Mayo Clinic Rochester Nephrectomy Registry with representative paraffin-embedded tissue blocks available for IHC staining and data on RCC-specific death. Of these 1479 patients, we successfully stained 1454 (98.3%) for BAP1, and 25 slides were defective or did not stain.

Data Collection

Follow-up data (ie, date of RCC death, date of last follow-up) and clinicopathologic covariates were abstracted from the Registry at Mayo Clinic. Briefly, these data are routinely updated and maintained through a combination of active (mail-out questionnaires) and passive (medical record, linkage to national databases) surveillance by experienced clinical coordinators. Pathologic features were analyzed in a standardized fashion by one urologic pathologist (J.C.C.) who centrally reviewed the microscopic hematoxylin and eosin–stained slides from all specimens without knowledge of patient outcome.

BAP1 Protein Expression by IHC

IHC assay for BAP1 was performed as described.[8] Positive staining in the background stromal cells and intratumoral lymphocytes served as internal positive control. A pathologist (P.K.), who was blinded to the clinicopathological variables, reviewed all immunostained slides, and a second pathologist (D.R.) reviewed all cases that lacked diffuse strong nuclear staining. Pathologists did not agree on a total of 6 (0.4%) samples. Tumors were categorized as BAP1-negative when tumor cells showed diffuse absence of nuclear BAP1 staining (previously shown to correlate with BAP1 mutation),[8] and BAP1-positive when tumor cells demonstrated diffuse nuclear staining with intensity equal to or stronger than the surrounding stromal cells and lymphocytes. In a small subset of tumors, BAP1 expression was unclear. Within this unclear group, some tumors were “BAP1 heterogeneous” with some cells staining positive for BAP1 and some cells negative (range of 1%-99% cells staining negative for BAP1). Also within the group that was unclear for BAP1 staining, there were tumors expressing BAP1 uniformly but weakly. Because of the uncertainty of BAP1 expression, we excluded both the “BAP1 heterogenous” and “diffusely weak” cohorts from our primary analysis.

Previous Published ccRCC Nomograms and Assessment of PDL1, Ki-67, and Survivin

We compared the impact of BAP1 expression on several previously published and validated ccRCC nomograms including the 2002 American Joint Committee on Cancer (AJCC) TNM stage groupings,[16] the UCLA Integrated Scoring System (UISS),[17] nomograms from Memorial Sloan-Kettering Cancer Center,[18, 19] and the Mayo Clinic SSIGN Score.[14, 15] In a subset of patients and as previously described, we assessed the expression by IHC of programmed death ligand 1 (PDL1), Ki-67, and survivin.[20]

Statistical Methods

Clinical and pathologic data were compared between patients with BAP1-positive and BAP1-negative tumors using t tests, Fisher's exact tests, and Chi-square tests, as appropriate. Unless noted otherwise, SSIGN and UISS scores were modeled as continuous variables. Cox models were used to assess the association of BAP1 expression, dichotomized as negative versus positive expression, with RCC-specific death after adjusting for age. In addition, the Kaplan-Meier method was used to estimate RCC-specific death, adjusting for the competing risk of death due to other causes. Subsequently, BAP1 was further evaluated in multivariable models adjusting for other known prognostic variables of ccRCC outcome, one at a time, in addition to age. We calculated concordance (c) index values to assess predictive ability. All reported c indexes were generated using the bootstrap methodology proposed by Harrell et al and represent optimism-corrected estimates of concordance.[21] Statistical analyses were performed using the R programming language, version 2.15. All tests were 2-sided and P values < .05 were considered statistically significant.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Association of BAP1 With Clinical and Pathologic Characteristics

Of the total cohort of 1479 slides, we successfully stained BAP1 in 1454 (98.3%). An additional 44 samples were excluded from the analysis secondary to inadequate follow up or duplicate ID leaving a total of 1410 (95.3%) for analysis. Of the 1410 successfully stained slides with adequate clinical follow up, 1344 were classified as either BAP1 negative (n = 148, 10.5%) or BAP1 positive (n = 1196, 84.8%), and the rest were BAP1 unclear (n = 66, 4.7%). Of the 66 BAP1 unclear, 33 (50%) had BAP1 heterogenous staining with some cells staining positive and others staining negative, and 33 (50%) were diffusely weak for BAP1. The 66 BAP1 unclear were removed from the primary analysis. The list of clinical characteristics of the BAP1 negative and positive (n = 1344) are listed in Table 1. Representative examples of BAP1 staining are demonstrated in Figure 1. A total of 1092 patients were alive at last follow-up, with a mean duration of follow-up of 8.3 years (median, 7.7 years; range, 0.003 = 22.1 years). Only 20 (1.4%) patients had fewer than 2 years of follow-up. There was no difference in age, sex, history of smoking, or history of alcohol use between patients with BAP1 negative and positive tumors. Tumors that were BAP1-negative by IHC possessed a larger tumor size, TNM stage, nuclear grade, and presence of coagulative tumor necrosis (all with P < .0001).[3, 4, 8] BAP1-negative tumors also had significantly higher SSIGN and UISS scores. Notably, all BAP1-negative tumors had a nuclear grade of 2 or higher and in fact, 90% of the BAP1-mutant tumors were of high (grade 3-4) Fuhrman grade.

Table 1. Clinical and Pathological Information for Patients in the BAP1 Analyses
 BAP1-Negative N = 148 (11%)BAP1-Positive N = 1196 (89%)Total (N = 1344)P
Sex   .6468
Female48 (32.4%)415 (34.7%)463 (34.4%) 
Male100 (67.6%)781 (65.3%)881 (65.6%) 
Age at surgery   .3008
Mean64.262.963.1 
Median65.464.064.2 
Range(35.9-90.0)(19.8-90.2)(19.8-90.2) 
BMI   .0313
Mean28.929.929.8 
Median27.829.028.7 
Range(17.9-61.3)(15.9-60.8)(15.9-61.3) 
Cigarette use   .2708
Missing137790 
Never57 (42.2%)507 (45.3%)564 (45.0%) 
Current25 (18.5%)150 (13.4%)175 (14.0%) 
Past53 (39.3%)462 (41.3%)515 (41.1%) 
Alcohol use   .5306
Missing12104116 
Never70 (51.5%)510 (46.7%)580 (47.2%) 
Current56 (41.2%)477 (43.7%)533 (43.4%) 
Past10 (7.4%)105 (9.6%)115 (9.4%) 
Tumor size   <.0001
Mean8.35.76.0 
Median8.05.05.0 
Range(1.4-29.0)(0.5-24.0)(0.5-29.0) 
Time to last follow-up   <.0001
Mean6.07.67.5 
Median5.37.17.0 
Range(0.0-20.9)(0.0-22.1)(0.0-22.1) 
Death   .0001
No64 (43.2%)718 (60.0%)782 (58.2%) 
Yes84 (56.8%)478 (40.0%)562 (41.8%) 
Death from RCC   <.0001
No89 (60.1%)1003 (83.9%)1092 (81.3%) 
Yes59 (39.9%)193 (16.1%)252 (18.8%) 
TNM stage   <.0001
Missing044 
150 (33.8%)780 (65.4%)830 (61.9%) 
228 (18.9%)158 (13.3%)186 (13.9%) 
367 (45.3%)247 (20.7%)314 (23.4%) 
43 (2.0%)7 (0.6%)10 (0.7%) 
Nuclear grade   <.0001
10 (0.0%)107 (8.9%)107 (8.0%) 
211 (7.4%)607 (50.8%)618 (46.0%) 
3109 (73.6%)433 (36.2%)542 (40.3%) 
428 (18.9%)49 (4.1%)77 (5.7%) 
Coagulative tumor necrosis   <.0001
No71 (48.0%)985 (82.4%)1056 (78.6%) 
Yes77 (52.0%)211 (17.6%)288 (21.4%) 
SSIGN category   <.0001
Missing32169201 
0-344 (37.9%)769 (74.9%)813 (71.1%) 
4-745 (38.8%)215 (20.9%)260 (22.7%) 
8+27 (23.3%)43 (4.2%)70 (6.1%) 
UISS score   <.0001
Missing145 
14 (2.7%)519 (43.5%)523 (39.1%) 
2128 (87.1%)632 (53.0%)760 (56.8%) 
312 (8.2%)34 (2.9%)46 (3.4%) 
42 (1.4%)6 (0.5%)8 (0.6%) 
51 (0.7%)1 (0.1%)2 (0.1%) 
PDL1 expression   .0003
Missing102848950 
Negative33 (71.7%)319 (91.7%)352 (89.3%) 
Positive13 (28.3%)29 (8.3%)42 (10.7%) 
Survivin expression   .0002
Missing102848950 
<1523 (50.0%)269 (77.3%)292 (74.1%) 
≥1523 (50.0%)79 (22.7%)102 (25.9%) 
Ki-67 Expression   .0007
Missing102848950 
< 5020 (43.5%)244 (70.1%)264 (67.0%) 
≥ 5026 (56.5%)104 (29.9%)130 (33.0%) 
image

Figure 1. Representative photomicrographs show BAP1 IHC staining. (A) BAP1-negative tumors. All tumor nuclei uniformly stained negative for BAP1 whereas lymphocytes and stromal cells serve as positive control. (B) BAP1-positive tumors. All tumor nuclei uniformly and strongly stained positive for BAP1. (C) BAP1 heterogenous. The tumor has a focus of BAP1-negative tumor cells with surrounding positively staining tumor of lower nuclear grade. (D) Diffusely weak BAP1 tumors. BAP1 staining was present in a majority of the tumor cells; however, the intensity was very weak and significantly less than the BAP1-positive tumors. This pattern could represent either a problem with the staining or decreased expression of BAP1. Tumors with BAP1 focal negativity (n = 33) or weak BAP1 staining (n = 33) were removed from the primary analysis. All images are 200× magnification.

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Univariate Analysis BAP1 Expression With ccRCC-Specific Death

At last follow-up, a total of 562 (42%) deaths and 252 (19%) ccRCC-specific deaths occurred. Patients with BAP1-negative tumors were 3 times more likely to experience RCC specific death compared with patients with BAP1-positive tumors (HR = 3.06; 95% CI = 2.28-4.10; P = 6.77 × 10−14) (Fig. 2).

image

Figure 2. Kaplan-Meier estimate of renal cell carcinoma (RCC)-specific death in patients with BAP1-negative and -positive tumors. In a univariate analysis, patients with BAP1-negative tumors had a significantly increased risk of clear cell RCC–specific death when compared to BAP1-positive tumors (hazard ratio = 3.06; 95% confidence interval = 2.28-4.10; P = 6.77 × 10−14).

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In secondary analyses, we interrogated the 66 patients who had unclear BAP1 tumor staining, and of these 66, 62 had adequate follow-up. We were unable to detect a difference in ccRCC-specific death between the 30 patients with heterogeneous BAP1 expression and patients with BAP1-positive tumors (HR = 1.25; 95% CI = 0.55-2.81; P = .59). However, the 32 patients with “diffusely weak” BAP1 expression had an increased risk of ccRCC death (HR = 2.00; 95% CI = 1.09-3.67; P = .025) when compared to patients with BAP1-positive tumors (Supporting Fig. 1; see online supporting information).

Multivariable Analysis of BAP1 With ccRCC-Specific Death

We performed a multivariable analysis to assess if BAP1 expression was independently associated with ccRCC-specific death after adjustment for known prognostic variables (Table 2). BAP1 was no longer statistically significant after adjusting for nuclear grade and SSIGN score, but retained its statistical significance after adjusting for TNM (HR = 1.69; 95% CI = 1.25-2.27; P = .0006), presence of necrosis (HR = 1.57; 95% CI = 1.16-2.12; P = .0036), tumor size (HR = 1.90; 95% CI = 1.40-2.57; P < .0001) and UISS (HR = 1.67; 95% CI = 1.24-2.67; P = .0008). In these multivariable models, we also noted improvements in the c index when the BAP1 variable was added to a model containing known predictors of ccRCC outcome.

Table 2. Hazard Rates and P Values for BAP1 Expression After Adjust for Age as Well as After Additionally Adjusting for Known Prognostic Variablesa
 HR (95% CI)PC-IndexN (No. of Events)
  1. a

    Age was included as a covariate in all of the Cox models.

  2. Abbreviations: CI, confidence interval; HR, hazard ratio; SSIGN, tumor stage, size, grade, and necrosis; UISS, UCLA Integrated Scoring System.

BAP13.059 (2.283-4.099)6.77E-140.6371344 (252)
Adjusted for nuclear grade1.151 (0.845-1.567).37210.8011344 (252)
Adjusted for TNM stage1.685 (1.251-2.268).00058840.8201340 (252)
Adjusted for necrosis1.566 (1.158-2.118).0035820.8131344 (252)
Adjusted for tumor size1.897 (1.402-2.567)3.34E-050.8021338 (251)
Adjusted for SSIGN score0.89 (0.624-1.271).5220.8791143 (197)
Adjusted for UISS score1.668 (1.237-2.25).00080580.6701339 (251)
Adjusted for B7H12.677 (1.654-4.333).00006160.618394 (100)
Adjusted for Survivin1.821 (1.122-2.953).01520.752394 (100)
Adjusted for Ki672.144 (1.327-3.466).001840.719394 (100)
Adjusted for B7H1, Survivin, Ki671.808 (1.118-2.923).01570.751394 (100)

Impact of BAP1 Expression on ccRCC-Specific Death in Low-, Intermediate-, and High-Risk Groups

As noted above, BAP1 was not an independent prognostic variable after adjusting for SSIGN score. Next, we evaluated whether there was a statistically significant interaction between BAP1 expression and SSIGN score and determined that in fact there was a significant interaction (P = .02). The statistically significant interaction implies that the association between BAP1 expression and ccRCC-specific death depends on SSIGN score. Stated another way, the association between BAP1 expression and ccRCC-specific death is not the same across all SSIGN score values. Therefore, we divided patients into low, intermediate, and high-risk based on the Mayo SSIGN score: SSIGN ≤ 3 (n = 813, 41 events), SSIGN 4-7 (n = 260, 108 events), and SSIGN ≥ 7 (n = 70, 48 events). We then compared the outcomes between patients with BAP1-negative and BAP1-positive tumors within these categories (Table 3). In the SSIGN ≤ 3 category, which encompassed 84% of patients, patients with BAP1-negative tumors had an increased rate of RCC-specific death (HR = 3.24; 95% CI = 1.26-8.33; P = .014) (Fig. 3). BAP1 expression did not affect RCC-specific death in the SSIGN 4-7 or SSIGN ≥ 7 cohorts, but these categories included only 16% of patients. BAP1 expression did not impact death from causes other than RCC in any SSIGN categories.

Table 3. BAP1-Positive/BAP1-Negative (All Nonhighlighted Samples, no Focal Negatives or Weak Positives)
RCC-Specific SurvivalSSIGN ≤ 3SSIGN 4–7SSIGN ≥ 8
(n = 813, 41 Events)(n = 260, 108 Events)(n = 70, 48 Events)
HR (95% CI)PC-IndexHR (95% CI)PC-IndexHR (95% CI)PC-Index
  1. Abbreviations: CI, confidence interval; HR, hazard ratio; NA, not applicable; RCC, renal cell carcinoma; SSIGN, tumor stage, size, grade, and necrosis.

BAP1-Positive1.0 (reference)NA 1.0 (reference)NA 1.0 (reference)NA 
BAP1-Negative3.24 (1.26-8.33).0150.6871.19 (0.73-1.94).4810.5120.87 (0.48-1.56).6400.523
image

Figure 3. Kaplan-Meier estimate of renal cell carcinoma (RCC)-specific death in patients with BAP1-negative and -positive tumors by SSIGN ≤ 3, SSIGN 4-7, and SSIGN ≥ 7 scores. (A) In the SSIGN ≤ 3 category (n = 813 with 41 deaths), BAP1-negative tumors continued to be independently associated with an increased rate of RCC-specific death (hazard ratio = 3.24; 95% confidence interval = 1.26-8.33; P = .015). (B, C) BAP1 expression did not impact RCC-specific death in the cohort of patients whose tumor were SSIGN 4-7 and SSIGN ≥ 7.

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Association of BAP1 With Other Validated Prognostic Biomarkers and Impact Prognostic Utility of BAP1 Expression

From a previous study, we demonstrated that PDL1, survivin, and Ki-67 are negative prognostic biomarkers in ccRCC.[20] Of the 1344 total tumors analyzed in this study for BAP1 expression, expression data for PDL1, survivin, and Ki-67 was available for 394 tumors. As an exploratory analysis, we compared the expression of these markers in BAP1 negative and positive patients (Table 1). Interestingly, BAP1-negative tumors were more likely to be PDL1 positive (28.3% versus 8.3%, P = .0003), survivin high (50% versus 22.7%, P = .0002), and Ki-67 high (56.5% versus 29.9%, P = .0007). In addition, we found that BAP1 remained an independent prognostic marker after adjustment for PDL1, survivin, and Ki-67 (Table 2).

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Although the majority of patients diagnosed with ccRCC present with small, organ-confined tumors with a “low-risk” of ccRCC-specific death, there is a significant subset of these patients (∼5%-10%) who develop metastatic disease and die from ccRCC. A key need is to develop reliable and inexpensive tests that identify the patients with low-risk ccRCC who will ultimately progress and succumb to their disease. The use of molecular genetics to identify patients with low-risk ccRCC who are actually at risk of ccRCC death following surgery has the ability to change the field by not only providing a useful prognostic marker but also a potential therapeutic target in the adjuvant setting. In this study, we are the first to use our own cost-effective, highly sensitive and specific, and Clinical Laboratory Improvement Amendments (CLIA)-certified IHC assay to test whether BAP1 expression is associated with risk of ccRCC death in a large cohort of patients (> 1400) undergoing surgery for clinically localized ccRCC. Of particular interest, we find that BAP1 expression is an independent marker of prognosis for patients with low-risk ccRCC (ie, Mayo SSIGN score ≤ 3) (HR = 3.24; 95% CI = 1.26-8.33; P = .015). That is, even among this group of low-risk patients where deaths from ccRCC are rare, BAP1 expression helps identify patients wrongly classified as having low-risk disease. In summary, our data suggest that BAP1 identifies the most aggressive forms of ccRCC (even among those with low-risk tumors) and as such, we advocate for the use of BAP1 staining to better inform postsurgical management for patients with clinically localized ccRCC.

We have previously shown that there is a good correlation between BAP1 mutations and loss of BAP1 protein.[8] Here, we use a more cost-effective and potentially more sensitive test to assess BAP1 status in tumors,[8] and we demonstrate that patients with BAP1-negative tumors have an increased risk of ccRCC-specific death. In total, we found that ∼11% of ccRCC tumors were BAP1-negative by IHC staining, which is consistent with previous studies reporting the prevalence of BAP1 mutations in 5% to 15% of ccRCC tumors.[3, 4, 8] However, because this does not take into account patients with weak staining who seemingly behave like BAP1-negative patients (and may be such), this figure may be an underestimate. Given the relatively low cost and reproducibility of this IHC assay, this test has the potential to offer a straightforward, affordable screening tool to identify ccRCC tumors with a more aggressive behavior. In addition, this assay has the ability to identify tumors that lack a BAP1 mutation but do not express BAP1, due to epigenetic silencing, and therefore IHC may be superior to sequencing as a screening test. Because ccRCC is a highly molecularly heterogeneous tumor,[22] IHC has the ability to identify tumors with focal areas of BAP1 loss, which may behave differently.

How BAP1 loss is associated with a more aggressive biology and poorer outcomes is not well understood. Interestingly, there is a correlation between BAP1 inactivation and activation of mammalian target of rapamycin complex 1 (mTORC1).[4, 8] However, whether BAP1 loss correlates with sensitivity with mTORC1 inhibitors remains to be established. In addition, not all high-grade tumors are BAP1-negative, and therefore there are likely other genetic events capable of inducing high-grade features. However, once high-grade features are present, regardless of the genetic etiology, the prognosis remains poor.

Over the past decade several investigators (including members of our group) have reported on the association of tumor-based biomarkers with risk of cancer-specific death among patients undergoing surgery for localized ccRCC. As such, key questions for our current efforts center on 1) the association of loss of BAP1 with expression of these previously reported biomarkers of ccRCC aggressiveness, and 2) the ability of loss of BAP1 to predict ccRCC survival after adjustment for these other biomarkers. The first question provides valuable insight (ie, hypothesis generation) into the possible biological links between BAP1 loss and molecular events within ccRCC tissues that are directly targetable (which BAP1, as a tumor suppressor protein lost in tumors, is not). The second question addresses the ability of BAP1 to independently predict ccRCC outcomes and therefore informs the ability of BAP1 to be combined with other known biomarkers to create more robust, multibiomarker panels for predicting ccRCC outcome. Here, our goal was to evaluate BAP1 specifically and not to develop a multivariable prognostic model that can be used clinically. In our exploratory analyses, we observed that BAP1-negative tumors are more likely to be PDL1-positive and have higher expression of survivin and Ki-67 (all markers we have previously reported and validated to be associated with greater risk of RCC-specific death). The association with BAP1 loss and PDL1 expression may have therapeutic implications. Moreover, we observed that the association of BAP1 expression with increased risk of RCC death remains apparent (albeit attenuated) after adjusting for all 3 of these established biomarkers of ccRCC aggressiveness. From a biological standpoint, it remains unclear if BAP1 mutations are directly linked to expression of PDL1, survivin, and Ki-67.

There are several limitations of our study that warrant further discussion. First, although the number of patients is quite large, further validation may be necessary to confirm that BAP1 loss is an independent marker of prognosis in the SSIGN low-risk cohort. Second, our subjects represent the practice of a tertiary referral center and exhibit limited racial/ethnic diversity (> 95% Caucasian). Third, although the prevalence of BAP1 mutations in ccRCC is 5% to 15% in primary tumors, more work is necessary to determine the prevalence of BAP1 mutations in metastatic lesions, because it is highly possible that BAP1 wild-type primary tumors gain BAP1 mutations during the metastatic process.

In summary, we are the first to demonstrate that BAP1 expression is an independent marker of prognosis in ccRCC, particularly in patients who are considered low-risk by conventional algorithms. In addition, this is largest study to assess the prognostic impact of BAP1 on RCC-specific survival. We underscore that the ultimate clinical potential for BAP1 will be realized with the identification and application of targeted therapies and with individualized approaches in the adjuvant and/or metastatic setting.

CONFLICT OF INTEREST DISCLOSURES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Dr. Joseph is supported by a grants from the American Association of Cancer Research and the Mayo Clinic Center for Individualized Medicine established through a gift of the Lou Gerstner Family. Dr. Ho is supported by grants from the National Institutes of Health (NIH) (K12 CA090628). Dr. Parker is supported by grants from NIH (R01CA134466). Dr. Brugarolas is supported by grants from CPRIT (RP101075-RP130603) and NIH (R01CA129387 and 1P30CA142543). All other authors made no disclosures.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURES
  9. REFERENCES
  10. Supporting Information

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