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  • Research article
  • Open Access
  • Open Peer Review

Comparison of clinicopathologic characteristics, epigenetic biomarkers and prognosis between renal pelvic and ureteral tumors in upper tract urothelial carcinoma

Contributed equally
BMC UrologyBMC series – open, inclusive and trusted201818:22

https://doi.org/10.1186/s12894-018-0334-7

  • Received: 12 September 2017
  • Accepted: 12 March 2018
  • Published:
Open Peer Review reports

Abstract

Background

There's no consensus about the difference between renal pelvic and ureteral tumors in terms of clinical features, pathological outcomes, epigenetic biomarkers and prognosis.

Methods

The data of 341 patients with renal pelvic tumors and 271 patients with ureteral tumors who underwent radical nephroureterectomy between 1999 and 2011 were retrospectively reviewed. The clinicopathologic features, gene promoters methylation status and oncologic outcomes were compared. Regression analysis was performed to identify oncologic prognosticators.

Results

Patients with ureteral tumors were relatively older (p = 0.002), and had higher likelihood of pre-operative renal insufficiency (p < 0.001), hypertension (p = 0.038) and hydronephrosis (P < 0.001), while in patients with renal pelvic tumors gross hematuria was more prevalent (p < 0.001). Renal pelvic tumors tended to exhibit non-organ-confined disease (p = 0.004) and larger tumor diameter (p = 0.001), while ureteral tumors had a higher likelihood of exhibiting high grade (p < 0.001) and sessile architecture (p = 0.023). Hypermethylated gene promoters were significantly more prevalent in renal pelvic tumors (p < 0.001), specifically for TMEFF2, GDF15, RASSF1A, SALL3 and ABCC6 (all p < 0.05). Tumor location failed to independently predict cancer-specific survival, overall survival, intravesical or contralateral recurrence (all p > 0.05), while gene methylation status was demonstrated to be an independent prognostic factor.

Conclusion

Renal pelvic tumors and ureteral tumors exhibited significant differences in clinicopathologic characteristics and epigenetic biomarkers. Gene promoter methylation might be an important mechanism in explaining distinct tumor patterns and behaviors in UTUC.

Keywords

  • Methylation
  • Prognosis
  • Radical nephroureterectomy (RNU)
  • Renal pelvis
  • Upper tract urothelial carcinomas (UTUC)
  • Ureter

Background

Urothelial carcinomas could be located anywhere throughout the whole urinary tract, e.g. renal pelvis, ureter, bladder and urethra [1]. Upper tract urothelial carcinoma refers to renal pelvic and ureteral tumors [2], with radical nephroureterectomy (RNU) and excision of the bladder cuff as the standard treatment [3].

Since both ureteral tumors and renal pelvic tumors originate from the urothelium, they have been traditionally classified as a single entity (UTUC) and managed in a relatively similar fashion, barring nephron-sparing approaches for more distally located tumors. In recent years there have been studies focusing on the impact of tumor location on prognosis [47], though evidence concerning clinical, pathological and genetic differences between renal pelvic and ureteral tumors remains scarce [8].

Microsatellite instability and hypermethylation have been proposed as key genetic differences between bladder cancer and UTUC [911], and we recently found gene promoter methylation status to hold biologic and prognostic significance in UTUC [12]. In the present study based on a large cohort of Chinese UTUC patients, we investigated the difference between renal pelvic and ureteral tumors in terms of clinical features, pathological outcomes, epigenetic biomarkers and prognosis.

Methods

Patient selection

Review board approve from Peking University First Hospital was acquired and all patients signed the informed consent to participate into the study. We evaluated consecutive Chinese UTUC patients who underwent RNU from 1999 to 2011 at Peking University First Hospital. We excluded patients with synchronous bilateral UTUC, distant metastasis prior to surgery or without complete follow-up data. Patients without available DNA from the surgical specimen for analysis of gene promoter methylation status were also excluded. Six hundred and-twelve patients were finally enrolled for analysis.

RNU including an extravesical excision of distal ureter by open Gibson incision was performed in all patients. No patients received neoadjuvant chemotherapy or prophylactic post-operative intravesical instillation (MMC or THP), while adjuvant chemotherapy for high-risk patients was administered at the treating physician’s discretion.

Patient evaluation

Computed tomography (CT) or magnetic resonance imaging (MRI), urological ultrasound, and cystoscopy were performed in all patients before surgery. Urinary cytology and ureteroscopy were used to help diagnosis. Renal function was assessed by estimated glomerular filtration rate (eGFR) calculated by Chinese population-specific equation: eGFR(ml/min/1.73m2) = 175 × Scr-1.234 × age-0.179 (× 0.79 if female) [13]. Ipsilateral hydronephrosis was determined pre-operatively.

Patients were categorized into 2 groups (renal pelvis versus ureter) in the current analysis based on the location of the main lesion on pathological specimen (e.g. the highest tumor stage). Pathological examination was performed according to standard procedures by a dedicated pathologist. Tumors were staged per the 2002 Union for International Cancer Control (UICC) TNM classification, and grading was evaluated per the World Health Organization (WHO) classification of 1973.

DNA extraction and methylation analysis

The procedure of DNA extraction and methylation analysis has been reported in a previous publication by our research group [12]. Based on the formalin-fixed paraffin-embedded tumor samples stored in our center, DNA samples were obtained and were treated for bisulfite transformation. Methylation-sensitive polymerase chain reaction (MSP) was used to analyze the gene promoters methylation status [14]. We used methylated human genomic DNA (Qiagen, Hilden, Germany) as positive control and water blanks with polymerase chain reaction mixtures as negative control. Based on previous literatures we did not detect the methylation status of the gene promoters in matched paracarcinoma tissues due to the limited methylation rates [1520].

Follow-up schedule

Follow-up consisted of cystoscopy, chest X-ray, urine cytology, and serum creatinine every 3 months for the first 3 years and then once per year thereafter. Abdominal ultrasound or CT/MRI was performed to examine the contralateral upper urinary tract. Overall survival (OS), cancer specific survival (CSS), bladder recurrence and contralateral recurrence were documented and compared by tumor location. Bladder recurrence was defined as subsequent bladder tumor detected by cystoscopy and confirmed by pathologic examination, and contralateral recurrence was defined as urothelial carcinoma found in the contralateral upper urinary tract. Cause of death was determined by death certificates, by medical notes or by the patients’ responsible physicians.

Statistical analysis

Statistical analysis was carried by using R software i386 2.15.3 (R Foundation for Statistical Computing, http://www.r-project.org) and SPSS 20.0 (IBM Corp, Armonk, NY, USA). Categorical variables were tested by the Pearson’s test and Chi-square test, while variables with a continuous distribution were evaluated by the Mann-Whitney U test. Cox regression model was used for survival analysis, and Kaplan-Meier curves including log-rank test was employed. A single-sided p value of lower than 0.05 was regarded as statistical significance.

Results

Clinical characteristics

Overall, 612 patients with either renal pelvic tumor (n = 341; 55.7%) or ureteral tumor (n = 271; 44.3%) were included. The median age of the entire cohort of patients was 68 (interquartile range, IQR: 60–74) years, and 272 (44.4%) were female, with a male:female ratio of 1.25:1. Previous or concomitant bladder cancer was present in 67 patients (10.9%).

The clinical features are exhibited in Table 1, grouped by tumor location. Patients with ureteral tumors were relatively older (p = 0.002), and suffered from high likelihood of pre-operative renal insufficiency (p < 0.001), hypertension (p = 0.038) and hydronephrosis (P < 0.001), while in patients with renal pelvic tumors gross hematuria was more prevalent (p < 0.001).
Table 1

Clinical and pathological characteristics of all UTUC patients stratified by tumor location

  

Tumor location

Univariate analysis

All

Renal pelvis

Ureter

Chi-square or Z

p value

Patients, no. (%)

612 (100)

341 (55.7)

271 (44.3)

  

Pre-operative characteristic

 Gender, no. (%)

   

0.160

0.743

  Male

340 (55.6)

187 (54.8)

153 (56.5)

  

  Female

272 (44.4)

154 (45.2)

118 (43.5)

  

 Age, no. (%)

   

4.929

0.027*

  <70

340 (55.6)

203 (59.5)

137 (50.6)

  

   ≥ 70

272 (44.4)

138 (40.5)

134 (49.4)

  

 Age, mean ± SD

 

65.29 ± 11.11

68.07 ± 10.20

−3.173

0.002*

 Previous or concomitant bladder cancer, no. (%)

   

1.931

0.193

  Absent

545 (89.1)

309 (90.6)

236 (87.1)

  

  Present

67 (10.9)

32 (9.4)

35 (12.9)

  

 Initial complaint, no. (%)

   

24.205

< 0.001*

  Absent

84 (13.7)

26 (7.6)

58 (21.4)

  

  Present

528 (86.3)

315 (92.4)

213 (78.6)

  

 Gross hematuria, no. (%)

   

65.132

< 0.001*

  Absent

148 (24.2)

40 (11.7)

108 (39.9)

  

  Present

464 (75.8)

301 (88.3)

163 (60.1)

  

 Preoperative renal function, no. (%)

   

23.703

< 0.001*

  End-stage CKD (eGFR<15)

34 (5.6)

24 (7.0)

10 (3.7)

  

  Moderate CKD (60>eGFR≥15)

198 (32.4)

83 (24.3)

115 (42.4)

  

  Early CKD (eGFR≥60)

378 (61.8)

233 (68.3)

145 (53.5)

  

 eGFR, mean ± SD

 

69.69 ± 30.11

62.43 ± 22.32

−4.329

< 0.001*

 Side, no. (%)

   

1.115

0.329

  Left

315 (51.5)

182 (53.4)

133 (49.1)

  

  Right

297 (48.5)

159 (46.6)

138 (50.9)

  

 Hydronephrosis, no. (%)

   

134.680

< 0.001*

  Absent

273 (44.6)

223 (65.4)

50 (18.5)

  

  Present

339 (55.4)

118 (34.6)

221 (81.5)

  

 Multifocality, no. (%)

   

0.339

0.563

  Single

472 (77.1)

266 (78.0)

206 (76.0)

  

  Multiple

140 (22.9)

75 (22.0)

65 (24.0)

  

 Smoking, no. (%)

   

0.050

0.836

  No

497 (81.2)

278 (81.5)

219 (80.8)

  

  Yes

115 (18.8)

63 (18.5)

52 (19.2)

  

 Alcohol, no. (%)

   

0.697

0.452

  No

539 (88.1)

297 (87.1)

242 (89.3)

  

  Yes

73 (11.9)

44 (12.9)

29 (10.7)

  

 Diabetes, no. (%)

   

0.249

0.661

  No

511 (83.5)

287 (84.2)

224 (82.7)

  

  Yes

101 (16.5)

54 (15.8)

47 (17.3)

  

 Hypertension, no. (%)

   

4.454

0.038*

  No

363 (59.3)

215 (63.0)

148 (54.6)

  

  Yes

249 (40.7)

126 (37.0)

123 (45.4)

  

 Pre-RNU ureteroscopy, no. (%)

   

20.495

< 0.001*

  No

536 (87.6)

317 (93.0)

219 (80.8)

  

  Yes

76 (12.4)

24 (7.0)

52 (19.2)

  

Pathological outcomes

 Architecture, no. (%)

   

40.135

< 0.001*

  Papillary

479 (78.3)

299 (87.7)

180 (66.4)

  

  Sessile

133 (21.7)

42 (12.3)

91 (33.6)

  

 Tumor stage, no. (%)

   

0.094

0.796

  Ta-T1

206 (33.7)

113 (33.1)

93 (34.3)

  

  T2–4

406 (66.3)

228 (66.9)

178 (65.7)

  

 Tumor grade, no. (%)

   

31.628

< 0.001*

  G1

19 (3.1)

4 (1.2)

15 (5.5)

  

  G2

334 (54.6)

218 (63.9)

116 (42.8)

  

  G3

259 (42.3)

119 (34.9)

140 (51.7)

  

 Lymph node status, no. (%)

   

4.014

0.051

  N0 or Nx

571 (93.3)

312 (91.5)

259 (95.6)

  

  N+

41 (6.7)

29 (8.5)

12 (4.4)

  

 Non-organ-confined disease, no. (%)

   

8.257

0.004*

  No

412 (67.3)

213 (62.5)

199 (73.4)

  

  Yes

200 (32.7)

128 (37.5)

72 (26.6)

  

 Tumor size, mean ± SD

 

3.58 ± 2.15

3.27 ± 2.41

−3.342

0.001*

Histologic Subtype

 Tumor necrosis, no. (%)

   

0.038

0.901

  No

537 (87.7)

300 (88.0)

237 (87.5)

  

  Yes

75 (12.3)

41 (12.0)

34 (12.5)

  

 Squamous metaplasia, no. (%)

   

0.038

0.878

  No

566 (92.5)

316 (92.7)

250 (92.3)

  

  Yes

46 (7.5)

25 (7.3)

21 (7.7)

  

 Sarcomatoid metaplasia, no. (%)

   

0.039

0.843

  No

586 (95.8)

327 (95.9)

259 (95.6)

  

  Yes

26 (4.2)

14 (4.1)

12 (4.4)

  

 Gland-like differentiation, no. (%)

   

2.738

0.119

  No

591 (96.6)

333(97.7)

258 (95.2)

  

  Yes

21 (3.4)

8(2.3)

13 (4.8)

  

 Presence of CIS, no. (%)

   

3.987

0.071

  No

596 (97.4)

336 (98.5)

260 (95.9)

  

  Yes

16 (2.6)

5 (1.5)

11 (4.1)

  

UTUC upper tract urothelial carcinoma, CKD chronic kidney disease, eGFR estimated glomerular filtration rate, RNU radical nephroureterectomy, CIS carcinoma in situ, SD standard deviation, HR Hazard Ratio, CI confidence interval

*Statistically significant

Pathological outcomes

The frequencies of muscle-invasive disease (≥pT2) and lymph node metastasis were comparable between groups; however, non-organ-confined tumors (≥pT3) were more prevalent in patients with renal pelvic tumors versus the ureteral tumor counterparts (p = 0.004). In concordance with this observation, sessile architecture and larger tumor size were more prevalent in patients with renal pelvic tumors as well (p < 0.001). G3 tumor grade, however, was present more often in ureteral tumors (p < 0.001). There were no differences in terms of squamous and glandular differentiation.

Molecular biomarkers

In 542 patients (88.6%) at least one methylated gene promoter was found, with a mean methylated genes number of 3.33 ± 2.31. Methylation was present significantly more frequently in renal pelvic tumors (Table 2), particularly with a higher rate of methylated TMEFF2, GDF15, RASSF1A, SALL3 and ABCC6 (all p < 0.05) (Fig. 1a). The mean number methylated genes in renal pelvic tumors was 3.71 ± 2.33, while in ureteral tumors was only 2.85 ± 2.19 (p < 0.001). Besides many patients with ureteral tumors presented with only very few methylated genes. (Fig. 1b).
Table 2

Molecular biomarkers

 

All

Renal pelvis

Ureter

Chi-square or Z

p value

Patients, no. (%)

612 (100)

341 (55.7)

271 (44.3)

  

 TMEFF2, no. (%)

   

6.717

0.011*

  Unmethylated

346 (56.5)

177 (51.9)

169 (62.4)

  

  Methylated

266 (43.5)

164 (48.1)

102 (37.6)

  

 HSPA2, no. (%)

   

3.172

0.083

  Unmethylated

355 (58.0)

187 (54.8)

168 (62.0)

  

  Methylated

257 (42.0)

154 (45.2)

103 (38.0)

  

 GDF15, no. (%)

   

57.000

< 0.001*

  Unmethylated

304 (49.7)

123 (36.1)

181 (66.8)

  

  Methylated

308 (50.3)

218 (63.9)

90 (33.2)

  

 RASSF1A, no. (%)

   

20.465

< 0.001*

  Unmethylated

448 (73.2)

225 (66.0)

223 (82.3)

  

  Methylated

164 (26.8)

116 (34.0)

48 (17.7)

  

 SALL3, no. (%)

   

7.119

0.008*

  Unmethylated

403 (65.8)

209 (61.3)

194 (71.6)

  

  Methylated

209 (34.2)

132 (38.7)

77 (28.4)

  

 VIM, no. (%)

   

2.347

0.128

  Unmethylated

219 (35.8)

113 (33.1)

106 (39.1)

  

  Methylated

393 (64.2)

228 (66.9)

165 (60.9)

  

 ABCC6, no. (%)

   

4.719

0.037*

  Unmethylated

523 (85.5)

282 (82.7)

241 (88.9)

  

  Methylated

89 (14.5)

59 (17.3)

30 (11.1)

  

 CDH1, no. (%)

   

0.208

0.728

  Unmethylated

524 (85.6)

290 (85.0)

234 (86.3)

  

  Methylated

88 (14.4)

51 (15.0)

37 (13.7)

  

 THBS1, no. (%)

   

0.005

1.000

  Unmethylated

457 (74.7)

255 (74.8)

202 (74.5)

  

  Methylated

155 (25.3)

86 (25.2)

69 (25.5)

  

 BRCA1, no. (%)

   

0.460

0.523

  Unmethylated

504 (82.4)

284 (83.3)

220 (81.2)

  

  Methylated

108 (17.6)

57 (16.7)

51 (18.8)

  

 Presence of hypermethylation in any gene, no. (%)

   

9.420

0.003*

  Unmethylated

70 (11.4)

27 (7.9)

43 (15.9)

  

  Methylated

542 (88.6)

314 (92.1)

228 (84.1)

  

 Mean methylated genes

 

3.71 ± 2.33

2.85 ± 2.19

−4.503

< 0.001*

 Number of methylated genes, no. (%)

   

17.202

< 0.001*

  0–2

254 (41.5)

118 (34.6)

136 (50.2)

  

  3–5

243 (39.7)

145 (42.5)

98 (36.2)

  

  6–10

115 (18.8)

78 (22.9)

37 (13.7)

  

 Number of methylated genes, no. (%) in Ta-1

   

11.251

0.004*

  All

206 (100)

113 (54.9)

93 (45.1)

  

  0–2

95 (46.1)

41 (36.3)

54 (58.1)

  

  3–5

80 (38.8)

49 (43.4)

31 (33.3)

  

  6–10

31 (15.0)

23 (20.4)

8 (8.6)

  

 Number of methylated genes, no. (%) in T2–4

   

7.318

0.026*

  All

406 (100)

228 (56.2)

178 (43.8)

  

  0–2

159 (39.2)

77 (33.8)

82 (46.1)

  

  3–5

163 (40.1)

96 (42.1)

67 (37.6)

  

  6–10

84 (20.7)

55 (24.1)

29 (16.3)

  

 Number of methylated genes, no. (%) in G1–2

   

18.433

< 0.001*

  All

353 (100)

222 (62.9)

131 (37.1)

  

  0–2

156 (44.2)

80 (36.0)

76 (58.0)

  

  3–5

141 (39.9)

97 (43.7)

44 (33.6)

  

  6–10

56 (15.9)

45 (20.3)

11 (8.4)

  

 Number of methylated genes, no. (%) in G3

   

4.449

0.108

  All

259 (100)

119 (45.9)

140 (54.1)

  

  0–2

98 (37.8)

38 (31.9)

60 (42.9)

  

  3–5

102 (39.4)

48 (40.3)

54 (38.6)

  

  6–10

59 (22.8)

33 (27.7)

26 (18.6)

  

*Statistically significant

UTUC upper tract urothelial carcinoma

Fig. 1
Fig. 1

Distribution of aberrant methylated genes in renal pelvic and ureteral tumors (a) and the cumulative numbers of aberrant methylated genes (b)

In subgroup analysis based on tumor stage, renal pelvic tumors exhibited more methylated genes both in non-muscle-invasive and muscle-invasive diseases, while in subgroup analysis based on tumor grade, the difference was significant only in lower tumor stages (G1–2).

Oncologic outcomes

The median follow-up duration was 64 months. In all 210 (34.3%) patients died and 187 (30.6%) died secondary to urothelial cancer. The cumulative 5-year OS and CSS rates were 69.1% and 71.4%, respectively. Bladder recurrence was found in 174 (28.4%) patients, and 32 (5.2%) patients experienced contralateral recurrence.

By univariate analysis, there’s no relationship between tumor location (renal pelvis versus ureter) OS (p = 0.104), CSS (p = 0.071), bladder recurrence (p = 0.294) or contralateral recurrence (p = 0.871). (Fig. 2).
Fig. 2
Fig. 2

Estimated Kaplan-Meier overall survival (a) (p = 0.104), cancer specific survival (b) (p = 0.071), bladder recurrence-free survival (c) (p = 0.294) and contralateral carcinoma-free survival (d) (p = 0.871) curves stratified by tumor location

Other factors, including tumor stage, presence of hydronephrosis, and the methylation status of several genes were proved to be important predictive factors for survival. (Table 3). On Kaplan-Meier analysis, less cumulative number of methylated genes was correlated with better CSS, with mean CSS time of 101 months, 79 months and 77 months for patients with 0–2, 3–5 and 6–10 methylated genes, respectively (Fig. 3a). Though not statistically significant, a trend to higher risk for bladder recurrence in patients with less number of methylated genes (p = 0.081, Fig. 3b) was found. Besides the number of methylated genes (as continuous) was found to affect CSS (HR = 1.348, p = 0.003) and bladder recurrence (HR = 0.787, p = 0.026) in univariate analysis (Table 3 and 4).
Table 3

Prognostic factors for cancer-specific survival in the entire cohort of UTUC patients and stratified by tumor location

Variables

All patients (n = 612)

Renal pelvis (n = 341)

Ureter (n = 271)

UVA

MVA

UVA

MVA

UVA

MVA

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

Location (ureter vs renal pelvis)

1.302

0.976–1.738

0.073

               

Gender (men vs women)

1.611

1.206–2.152

0.001*

1.45

1.07–1.96

0.016*

1.680

1.117–2.527

0.013*

1.46

0.94–2.27

0.091

1.574

1.039–2.383

0.032*

1.43

0.93–2.21

0.103

Age (continuous)

1.020

1.005–1.035

0.009*

1.32

1.07–1.64

0.010*

1.008

0.988–1.028

0.422

   

1.032

1.008–1.056

0.008*

1.09

0.78–1.52

0.628

Preoperative hydronephosis

1.595

1.183–2.151

0.002*

1.77

1.28–2.45

0.001*

1.766

1.168–2.671

0.007*

1.89

1.20–2.98

0.006*

1.191

0.691–2.053

0.529

   

Multifocality (presence of multiple foci vs absence)

1.414

1.028–1.943

0.033*

1.57

1.10–2.24

0.014*

1.675

1.088–2.578

0.019*

1.70

1.03–2.82

0.040*

1.145

0.711–1.845

0.577

   

Preoperative renal function(eGFR, continuous)

0.996

0.991–1.001

0.119

   

1.000

0.993–1.007

0.993

   

0.989

0.979–0.998

0.021*

0.77

0.55–1.06

0.106

Previous or concomitant BT (presence vs absence)

1.544

1.019–2.339

0.041*

1.53

0.97–2.41

0.070

1.980

1.099–3.568

0.023*

2.03

1.04–3.94

0.037*

1.183

0.657–2.132

0.575

   

Gross hematuria (presence vs absence)

0.913

0.650–1.282

0.599

   

0.625

0.353–1.104

0.105

   

1.329

0.845–2.090

0.218

   

Smoke (presence vs absence)

1.102

0.765–1.588

0.601

   

1.242

0.757–2.037

0.391

   

0.985

0.572–1.698

0.958

   

Alcohol (presence vs absence)

1.108

0.726–1.690

0.634

   

1.546

0.912–2.619

0.105

   

0.713

0.344–1.477

0.363

   

Diabetes (presence vs absence)

0.891

0.592–1.340

0.579

   

0.994

0.563–1.756

0.984

   

0.797

0.442–1.437

0.451

   

Hypertension (presence vs absence)

1.180

0.879–1.584

0.270

   

1.056

0.689–1.618

0.802

   

1.230

0.810–1.868

0.332

   

Preoperative ureteroscopy

0.616

0.383–0.992

0.046*

0.72

0.44–1.18

0.194

0.234

0.058–0.951

0.042*

0.24

0.06–1.03

0.055

0.663

0.387–1.137

0.135

   

Tumor stage^ (T4 vs T3 vs T2 vs T1 vs Ta)

1.725

1.443–2.061

< 0.001*

2.42

1.56–3.76

< 0.001*

1.514

1.197–1.915

0.001*

1.83

1.04–3.21

0.035*

2.288

1.716–3.050

< 0.001*

2.53

1.46–4.38

0.001*

Tumor grade^ (G3 vs G2 vs G1)

1.593

1.222–2.075

0.001*

0.69

0.36–1.34

0.274

1.284

0.868–1.900

0.211

   

1.856

1.271–2.710

0.001*

1.30

0.47–3.61

0.611

Lymph node status (N+ vs Nx vs N-)

2.524

1.583–4.023

< 0.001*

1.82

1.08–3.07

0.024*

2.863

1.615–5.074

< 0.001*

2.49

1.26–4.92

0.009*

2.356

1.024–5.417

0.044*

1.18

0.49–2.84

0.713

Architecture (presence of sessile vs absence)

1.974

1.437–2.713

< 0.001*

1.38

0.92–2.07

0.125

2.105

1.242–3.566

0.006*

1.20

0.63–2.28

0.584

1.811

1.186–2.766

0.006*

0.98

0.55–1.75

0.951

CIS (presence of sessile vs absence)

1.027

0.480–2.202

0.994

   

1.386

0.424–4.535

0.590

   

0.808

0.296–2.210

0.678

   

Necrosis(presence vs absence)

1.925

1.302–2.846

0.001*

1.36

0.84–2.18

0.207

1.606

0.905–2.850

0.105

   

2.352

1.375–4.025

0.002*

1.36

0.69–2.70

0.376

Squamous metaplasia (presence vs absence)

1.783

1.081–2.943

0.024*

1.45

0.85–2.48

0.171

2.123

1.063–4.241

0.033*

2.31

1.06–5.02

0.034*

1.485

0.716–3.079

0.288

   

Sarcomatoid metaplasia (presence vs absence)

2.595

1.526–4.413

< 0.001*

0.79

0.40–1.56

0.493

2.541

1.171–5.513

0.018*

1.03

0.40–2.62

0.955

2.629

1.266–5.459

0.010*

1.00

0.41–2.45

0.993

Gland-like differentiation (presence vs absence)

1.963

0.965–3.995

0.063

   

3.394

1.239–9.296

0.017*

2.08

0.68–6.34

0.197

1.229

0.449–3.362

0.688

   

Tumor size (continuous)

1.172

1.112–1.236

< 0.001*

1.17

1.04–1.32

0.010*

1.163

1.070–1.264

< 0.001*

1.16

0.93–1.44

0.188

1.184

1.110–1.264

< 0.001*

1.26

1.06–1.49

0.008*

TMEFF2 (methylated vs unmethylated)

1.812

1.353–2.427

< 0.001*

1.67

1.12–2.50

0.012*

1.634

1.085–2.459

0.019*

1.16

0.70–1.92

0.562

2.189

1.434–3.340

< 0.001*

1.84

0.97–3.50

0.061

HSPA2 (methylated vs unmethylated)

1.815

1.349–2.442

< 0.001*

1.52

1.03–2.24

0.036*

2.064

1.365–3.119

0.001*

1.40

0.86–2.28

0.180

1.698

1.097–2.626

0.017*

1.08

0.60–1.97

0.793

GDF15 (methylated vs unmethylated)

1.242

0.930–1.660

0.142

   

1.575

1.025–2.421

0.038*

1.24

0.73–2.12

0.426

1.152

0.741–1.793

0.530

   

RASSF1A (methylated vs unmethylated)

1.383

1.002–1.908

0.049*

1.15

0.78–1.70

0.477

1.271

0.824–1.961

0.279

   

1.796

1.102–2.929

0.019*

1.57

0.87–2.82

0.135

SALL3 (methylated vs unmethylated)

1.214

0.887–1.662

0.226

   

0.887

0.565–1.392

0.602

   

1.853

1.190–2.885

0.006*

1.58

0.93–2.68

0.094

VIM (methylated vs unmethylated)

1.360

1.002–1.847

0.049*

0.99

0.68–1.44

0.941

1.630

1.041–2.550

0.033*

1.37

0.81–2.32

0.243

1.208

0.786–1.857

0.388

   

ABCC6 (methylated vs unmethylated)

1.430

0.928–2.203

0.105

   

1.206

0.682–2.134

0.519

   

2.283

1.165–4.476

0.016*

1.51

0.67–3.38

0.317

CDH1 (methylated vs unmethylated)

1.178

0.766–1.812

0.456

   

1.112

0.618–2.001

0.724

   

1.401

0.741–2.649

0.300

   

THBS1 (methylated vs unmethylated)

1.131

0.811–1.577

0.468

   

0.877

0.534–1.439

0.603

   

1.415

0.899–2.227

0.133

   

BRCA1 (methylated vs unmethylated)

0.851

0.565–1.280

0.438

   

0.678

0.361–1.272

0.226

   

1.026

0.596–1.765

0.927

   

No. methylated genes (continuous)

1.348

1.107–1.641

0.003*

0.62

0.30–1.28

0.193

1.225

0.930–1.613

0.149

   

1.646

1.234–2.196

0.001*

0.58

0.18–1.82

0.351

UVA univariate analysis, MVA multivariate analysis, eGFR estimated glomerular filtration rate, UTUC upper tract urothelial carcinoma, BT bladder tumor, CIS carcinoma in situ, HR Hazard Ratio, CI confidence interval

*Statistically significant

Fig. 3
Fig. 3

Estimated Kaplan-Meier cancer specific survival (a) (p = 0.001) and bladder recurrence-free survival (b) (p = 0.081) curves stratified by numbers of methylated genes (0–2 versus 3–5 versus 6–10)

Table 4

Prognostic factors for bladder recurrence in the entire cohort of UTUC patients and stratified by tumor location

Variables

All patients (n = 612)

Renal pelvis (n = 341)

Ureter (n = 271)

UVA

MVA

UVA

MVA

UVA

MVA

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

HR

95%CI

p value

Location (ureter vs renal pelvis)

1.172

0.870–1.579

0.297

               

Gender (men vs women)

1.150

0.854–1.550

0.357

   

1.279

0.850–1.924

0.239

   

1.035

0.668–1.606

0.876

   

Age (continuous)

0.987

0.974–1.000

0.050

   

0.983

0.966–1.000

0.055

   

0.989

0.970–1.010

0.989

   

Preoperative hydronephosis

1.173

0.868–1.585

0.298

   

1.141

0.745–1.748

0.545

   

1.050

0.608–1.815

0.861

   

Multifocality (presence of multiple foci vs absence)

1.732

1.260–2.381

0.001*

1.42

1.01–2.01

0.045*

1.833

1.185–2.835

0.006*

1.75

1.13–2.72

0.012*

1.610

1.011–2.566

0.045*

1.44

0.86–2.43

0.167

Preoperative renal function(eGFR, continuous)

0.999

0.993–1.004

0.671

   

0.999

0.993–1.006

0.876

   

0.999

0.989–1.009

0.887

   

Previous or concomitant BT (presence vs absence)

1.900

1.267–2.850

0.002*

1.47

0.95–2.28

0.081

1.710

0.931–3.138

0.084

   

2.034

1.176–3.517

0.011*

1.39

0.75–2.58

0.293

Gross hematuria (presence vs absence)

1.108

0.773–1.588

0.577

   

1.102

0.572–2.125

0.772

   

1.268

0.802–2.005

0.310

   

Smoke (presence vs absence)

0.946

0.644–1.388

0.775

   

1.097

0.655–1.836

0.726

   

0.784

0.441–1.394

0.407

   

Alcohol (presence vs absence)

0.771

0.473–1.257

0.297

   

0.901

0.480–1.692

0.746

   

0.622

0.286–1.351

0.230

   

Diabetes (presence vs absence)

1.086

0.736–1.601

0.679

   

0.842

0.469–1.515

0.567

   

1.414

0.837–2.388

0.196

   

Hypertension (presence vs absence)

0.774

0.566–1.059

0.109

   

0.916

0.595–1.412

0.692

   

0.614

0.391–0.967

0.035*

0.71

0.44–1.15

0.163

Preoperative ureteroscopy

1.631

1.111–2.395

0.012*

1.25

0.83–1.87

0.285

2.087

1.137–3.829

0.018*

1.62

0.87–3.02

0.126

1.319

0.794–2.189

0.285

   

Tumor stage^ (T4 vs T3 vs T2 vs T1 vs Ta)

0.861

0.731–1.014

0.074

   

0.956

0.772–1.185

0.683

   

0.744

0.574–0.965

0.026*

0.81

0.54–1.20

0.292

Tumor grade^ (G3 vs G2 vs G1)

0.655

0.504–0.851

0.002*

0.54

0.31–0.93

0.027*

0.515

0.336–0.789

0.002*

0.30

0.13–0.71

0.006*

0.777

0.555–1.089

0.143

   

Lymph node status (N+ vs Nx vs N-)

0.326

0.121–0.879

0.027*

0.45

0.17–1.23

0.120

0.491

0.180–1.338

0.164

   

0.046

0.000–5.017

0.199

   

Architecture (presence of sessile vs absence)

0.718

0.479–1.075

0.108

   

0.721

0.349–1.490

0.377

   

0.644

0.389–1.067

0.087

   

CIS (presence of sessile vs absence)

1.604

0.789–3.262

0.192

   

1.498

0.369–6.086

0.572

   

1.555

0.676–3.573

0.299

   

Necrosis(presence vs absence)

1.164

0.750–1.806

0.498

   

1.532

0.881–2.664

0.131

   

0.810

0.390–1.682

0.572

   

Squamous metaplasia(presence vs absence)

0.626

0.308–1.274

0.196

   

0.630

0.231–1.720

0.367

   

0.609

0.223–1.665

0.334

   

Sarcomatoid metaplasia (presence vs absence)

0.490

0.182–1.321

0.159

   

0.465

0.114–1.887

0.284

   

0.541

0.133–2.204

0.392

   

Gland-like differentiation (presence vs absence)

0.576

0.184–1.806

0.344

   

0.619

0.086–4.452

0.634

   

0.509

0.125–2.073

0.346

   

Tumor size (continuous)

0.920

0.850–0.996

0.039*

0.91

0.78–1.06

0.213

0.967

0.872–1.072

0.520

   

0.875

0.771–0.991

0.036*

0.83

0.64–1.08

0.170

TMEFF2 (methylated vs unmethylated)

0.714

0.521–0.978

0.036*

0.91

0.60–1.38

0.657

0.839

0.554–1.268

0.404

   

0.593

0.358–0.984

0.043*

1.00

0.50–2.00

0.999

HSPA2 (methylated vs unmethylated)

0.704

0.511–0.968

0.031*

0.82

0.55–1.24

0.348

0.792

0.519–1.207

0.278

   

0.626

0.380–1.033

0.067

   

GDF15 (methylated vs unmethylated)

0.823

0.611–1.110

0.203

   

0.936

0.616–1.421

0.755

   

0.738

0.456–1.196

0.217

   

RASSF1A (methylated vs unmethylated)

0.598

0.407–0.878

0.009*

0.69

0.45–1.07

0.095

0.786

0.499–1.237

0.298

   

0.318

0.138–0.731

0.007*

0.41

0.17–0.97

0.042*

SALL3 (methylated vs unmethylated)

0.725

0.519–1.013

0.059

   

0.669

0.427–1.048

0.079

   

0.837

0.505–1.386

0.489

   

VIM (methylated vs unmethylated)

0.862

0.636–1.167

0.336

   

1.302

0.831–2.041

0.249

   

0.567

0.367–0.875

0.010*

0.64

0.38–1.06

0.081

ABCC6 (methylated vs unmethylated)

0.805

0.499–1.297

0.373

   

1.007

0.578–1.752

0.981

   

0.508

0.185–1.392

0.188

   

CDH1 (methylated vs unmethylated)

0.681

0.413–1.124

0.133

   

0.870

0.474–1.597

0.654

   

0.466

0.188–1.155

0.099

   

THBS1 (methylated vs unmethylated)

0.960

0.678–1.359

0.818

   

1.044

0.651–1.675

0.858

   

0.872

0.522–1.457

0.601

   

BRCA1 (methylated vs unmethylated)

0.977

0.659–1.448

0.908

   

0.858

0.485–1.515

0.597

   

1.131

0.655–1.955

0.659

   

No. methylated genes(continuous)

0.787

0.637–0.972

0.026*

1.14

0.56–2.34

0.718

0.906

0.688–1.193

0.483

   

0.656

0.460–0.935

0.020*

0.96

0.34–2.72

0.934

*Statistically significant

UVA univariate analysis, MVA multivariate analysis, eGFR estimated glomerular filtration rate, UTUC upper tract urothelial carcinoma, BT bladder tumor, CIS carcinoma in situ, HR Hazard Ratio, CI confidence interval

Sub-group analysis demonstrated differences in oncologic prognosticators for CSS and bladder recurrence based on tumor location (Table 3 and 4). Rerunning the dataset by dividing patients into renal pelvic tumors only (n = 304), ureteral tumors only (n = 267) and both renal pelvic and ureteral tumors (n = 41) did not change the results (Table 5).
Table 5

Comparison in patients with renal pelvis tumor only and with ureteral tumor only

 

Location

Comparison between three groups

Comparison after excluding cases in both locations

All

Renal pelvis only

Ureter only

Both locations

Chi-square or Z

p value

Chi-square or Z

p value

Patients, no. (%)

612 (100)

304 (49.7)

267 (43.6)

41 (6.7)

    

Pre-operative characteristic

 Gender, no. (%)

    

1.595

0.450

0.495

0.501

  Male

340 (55.6)

163 (53.6)

151 (56.6)

26 (63.4)

    

  Female

272 (44.4)

141 (46.4)

116 (43.4)

15 (36.6)

    

 Age, no. (%)

    

5.554

0.062

5.391

0.023*

  <70

340 (55.6)

182 (59.9)

134 (50.2)

24 (58.5)

    

   ≥ 70

272 (44.4)

122 (40.1)

133 (49.8)

17 (41.5)

    

 Age, mean ± SD

 

65.09 ± 11.32

68.12 ± 10.22

66.52 ± 10.79

11.059

0.004*

−3.298

0.001*

 Previous or concomitant bladder cancer, no. (%)

    

31.791

< 0.001*

8.721

0.004*

  Absent

545 (89.1)

286 (94.1)

232 (86.9)

27 (65.9)

    

  Present

67 (10.9)

18 (5.9)

35 (13.1)

14 (34.1)

    

 Initial complaint, no. (%)

    

23.992

< 0.001*

23.745

< 0.001*

  Absent

84 (13.7)

22 (7.2)

57 (21.3)

5 (12.2)

    

  Present

528 (86.3)

282 (92.8)

210 (78.7)

36 (87.8)

    

 Gross hematuria, no. (%)

    

66.717

< 0.001*

65.579

< 0.001*

  Absent

148 (24.2)

33 (10.9)

107 (40.1)

8 (19.5)

    

  Present

464 (75.8)

271 (89.1)

160 (59.9)

33 (80.5)

    

 Preoperative renal function, no. (%)

    

39.081

< 0.001*

29.841

< 0.001*

  End-stage CKD (eGFR<15)

34 (5.6)

21 (6.9)

10 (3.7)

3 (7.3)

    

  Moderate CKD (60>eGFR≥15)

198 (32.4)

64 (21.1)

112 (41.9)

22 (53.7)

    

  Early CKD (eGFR≥60)

378 (61.8)

218 (71.7)

144 (53.9)

16 (39.0)

    

 eGFR, mean ± SD

 

71.30 ± 29.38

62.63 ± 22.32

55.80 ± 31.99

34.160

< 0.001*

−5.108

< 0.001*

 Hydronephrosis, no. (%)

    

156.085

< 0.001*

151.247

< 0.001*

  Absent

273 (44.6)

212 (69.7)

49 (18.4)

12 (29.3)

    

  Present

339 (55.4)

92 (30.3)

218 (81.6)

29 (70.7)

    

 Multifocality, no. (%)

    

156.779

< 0.001*

10.618

< 0.001*

  Single

472 (77.1)

266 (87.5)

206 (77.2)

0

    

  Multiple

140 (22.9)

38 (12.5)

61 (22.8)

41 (100)

    

Pathological outcomes

 Architecture, no. (%)

    

39.792

< 0.001*

39.811

< 0.001*

  Papillary

479 (78.3)

269 (88.5)

178 (66.7)

32 (78.0)

    

  Sessile

133 (21.7)

35 (12.5)

89 (33.3)

9 (22.0)

    

 Tumor stage, no. (%)

    

0.160

0.923

0.155

0.723

  Ta-T1

206 (33.7)

100 (32.9)

92 (34.5)

14 (34.1)

    

  T2–4

406 (66.3)

204 (67.1)

175 (65.5)

27 (65.9)

    

 Tumor grade, no. (%)

    

30.572

< 0.001*

28.242

< 0.001*

  G1

19 (3.1)

4 (1.3)

15 (5.6)

0

    

  G2

334 (54.6)

214 (70.4)

115 (43.1)

25 (61.0)

    

  G3

259 (42.3)

106 (34.9)

137 (51.3)

16 (39.0)

    

 Lymph node status, no. (%)

    

3.772

0.152

3.769

0.064

  N0 or Nx

571 (93.3)

278 (91.4)

255 (95.5)

38 (92.7)

    

  N+

41 (6.7)

26 (8.6)

12 (4.5)

3 (7.3)

    

 Non-organ-confined disease, no. (%)

    

10.339

0.006*

9.592

0.002*

  No

412 (67.3)

186 (61.2)

196 (73.4)

30 (73.2)

    

  Yes

200 (32.7)

118 (38.8)

71 (26.6)

11 (26.8)

    

 Tumor size, mean ± SD

 

3.56 ± 1.94

3.25 ± 2.40

3.89 ± 3.39

13.014

0.001*

−3.695

< 0.001*

 Methylation status

        

 TMEFF2, no. (%)

    

6.972

0.031*

6.481

0.011*

  Unmethylated

346 (56.5)

158 (52.0)

167 (62.5)

21 (51.2)

    

  Methylated

266 (43.5)

146 (48.0)

100 (37.5)

20 (48.8)

    

 HSPA2, no. (%)

    

3.398

0.183

3.064

0.089

  Unmethylated

355 (58.0)

167 (54.9)

166 (62.2)

22 (53.7)

    

  Methylated

257 (42.0)

137 (45.1)

101 (37.8)

19 (46.3)

    

 GDF15, no. (%)

    

56.507

< 0.001*

56.310

< 0.001*

  Unmethylated

304 (49.7)

107 (35.2)

178 (66.7)

19 (46.3)

    

  Methylated

308 (50.3)

197 (64.8)

89 (33.3)

22 (53.7)

    

 RASSF1A, no. (%)

    

22.562

< 0.001*

22.341

< 0.001*

  Unmethylated

448 (73.2)

197 (64.8)

220 (82.4)

31 (75.6)

    

  Methylated

164 (26.8)

107 (35.2)

47 (17.6)

10 (24.4)

    

 SALL3, no. (%)

    

9.797

0.007*

6.982

0.010*

  Unmethylated

403 (65.8)

188 (61.8)

193 (72.3)

22 (53.7)

    

  Methylated

209 (34.2)

116 (38.2)

74 (27.7)

19 (46.3)

    

 VIM, no. (%)

    

3.367

0.186

1.819

0.192

  Unmethylated

219 (35.8)

103 (33.9)

105 (39.3)

11 (26.8)

    

  Methylated

393 (64.2)

201 (66.1)

162 (60.7)

30 (73.2)

    

 ABCC6, no. (%)

    

6.282

0.043*

6.119

0.016*

  Unmethylated

523 (85.5)

250 (82.2)

239 (89.5)

34 (82.9)

    

  Methylated

89 (14.5)

54 (17.8)

28 (10.5)

7 (17.1)

    

 CDH1, no. (%)

    

1.054

0.590

0.116

0.809

  Unmethylated

524 (85.6)

260 (85.5)

231 (86.5)

33 (80.5)

    

  Methylated

88 (14.4)

44 (14.5)

36 (13.5)

8 (19.5)

    

 THBS1, no. (%)

    

1.041

0.594

0.096

0.772

  Unmethylated

457 (74.7)

230 (75.7)

199 (74.5)

28 (68.3)

    

  Methylated

155 (25.3)

74 (24.3)

68 (25.5)

13 (31.7)

    

 BRCA1, no. (%)

    

2.219

0.330

0.863

0.375

  Unmethylated

504 (82.4)

256 (84.2)

217 (81.3)

31 (75.6)

    

  Methylated

108 (17.6)

48 (15.8)

50 (18.7)

10 (24.4)

    

 Presence of hypermethylation in any gene, no. (%)

    

8.739

0.013*

8.537

0.004*

  Unmethylated

70 (11.4)

24 (7.9)

42 (15.7)

4 (9.8)

    

  Methylated

542 (88.6)

28 (92.1)

225 (84.3)

37 (90.2)

    

 Mean methylated genes

 

3.70 ± 2.33

2.83 ± 2.18

3.85 ± 2.35

21.900

< 0.001*

−4.431

< 0.001*

 Number of methylated genes, no. (%)

    

20.046

< 0.001*

16.108

< 0.001*

  0–2

254 (41.5)

108 (35.5)

135 (50.6)

11 (26.8)

    

  3–5

243 (39.7)

126 (41.4)

97 (36.3)

20 (48.8)

    

  6–10

115 (18.8)

70 (23.0)

35 (13.1)

10 (24.4)

    

Prognostic outcomes

aOverall mortality, no. (%)

    

0.059

0.011*

4.547

0.033*

  Survive

379 (66.4)

210 (69.1)

169 (63.3)

23 (56.1)

    

  Death

192

94 (30.9)

98 (36.7)

18 (43.9)

    

aCancer-specific mortality, no. (%)

    

0.059

0.011*

4.547

0.033*

  Survive

425 (69.4)

223 (73.4)

178 (66.7)

34 (58.5)

    

  Death

187 (30.6)

81 (26.6)

89 (33.3)

17 (41.5)

    

aIntravesical recurrence, no. (%)

    

6.131

0.047*

2.879

0.090

  No recurrence

438 (71.6)

228 (75.0)

185 (69.3)

25 (61.0)

    

  Recurrence

174 (28.4)

76 (25.0)

82 (30.7)

16 (39.0)

    

aContralateral recurrence, no. (%)

    

6.668

0.036*

0.610

0.435

  No recurrence

580 (94.8)

291 (95.7)

253 (94.8)

41 (87.8)

    

  Recurrence

32 (5.2)

13 (4.3)

14 (5.2)

5 (12.2)

    

CKD chronic kidney disease, eGFR estimated glomerular filtration rate, SD standard deviation

*Statistically significant

aLog-rank test was used

Discussions

In a meta-analysis which included 17 studies with 12,094 patients, Wu et al. demonstrated that ureteral tumors exhibited worse CSS and recurrence-free survival than renal pelvic tumors based on adjusted HRs; however, no such results were noticed in subgroup analysis of pT3/4 and pN1 tumors, though the authors observed significant heterogeneity among reported articles [4]. The only corresponding study that additionally included molecular work was published in 2013, in which Krabbe et al. found no difference in the expression of p21, p27, p53, cyclin E, and Ki-67 [8].

Regarding the relatively higher stages of renal pelvic tumors, Raman et al. suggested that ureteral tumors tend to be diagnosed earlier due to ureteric obstruction, and thus were likely to be detected at a lower stage [5]. In the current cohort of patients, more patients with renal pelvic tumors were diagnosed due to gross hematuria, while the prevalent presence of hydronephrosis could help the detection of ureteral tumors by ultrasound in annual regular physical examination in many patients.

It’s interesting that the presence of sessile architecture and higher tumor grade was more common in ureteral tumors, which indicated the higher aggressiveness of ureteral tumors, as demonstrated in prior studies [4]. The change of DNA methylation status is regarded to be a key event in transcriptionally repressed regions of the genome [12]. Hypermethylation is a mechanism for repression of gene transcription in cancer [9]. Prior studies on bladder cancer demonstrated aberrant methylation status of some specific gene promoter as a sign of higher aggressiveness and worse prognosis [11, 1519]. We similarly found that increased number of methylated genes appeared to correlate with worse CSS.

Our results demonstrate that renal pelvic and ureteral tumors, though both belong to UTUC, are not totally biologically homogenous and might behave differently. It’s interesting that the rate of hypermethylation was much more higher in renal pelvis tumors than in the ureter, but the ureteral tumors exhibited higher aggressiveness and relatively worse prognosis. What’s more, it’s notable that on sub-analysis, the number of methylated genes was a stronger driver for oncologic outcomes in ureteral tumors. This being said, however, each gene must also be viewed separately, as the prognostic effect of gene hypermethylation appeared to differ by location, further implicating differences in underlying biology between the two groups.

In a published Meta-analysis ureteral location was related to higher risk of bladder recurrence [21]. Although no statistical difference was found in our study, a more distally located tumor within the ureter could conceivably affect bladder recurrence as seen in our previous publication [22].The analysis with gene methylation status didn’t seem to be very informative for this phenomenon. In a Japanese multi-institutional study, Tanaka et al. found that the patterns of tumor spread was related to primary location of the urothelial carcinoma: patients with ureteral tumors (especially at middle and lower part) tended to suffer from local recurrence in the pelvic cavity, while renal pelvic tumors were associated with higher risk of lung metastasis [7]. The underlying biological mechanisms about the differences in the patterns of tumor metastasis corresponding to tumor location remain to be elucidated in the future.

Our study has several limitations related to the retrospective design, and there might be some selection and recall bias, especially considering some patients were excluded due to the unavailable extracted DNA for test. The exact rate and site of distant metastasis and local recurrence were also incompletely available, which precluded further analysis concerning difference patterns of disease recurrence.

Despite these limitations, our study was the first comparative study that integrated epigenetic information with UTUC tumor location, and to our knowledge, the first study that demonstrated the higher prevalence of gene promoter hyper-methylation in renal pelvic tumors. Indeed, future research is warranted to further elucidate the role that gene methylation plays in the development and biology of renal pelvic and ureteral tumors.

Conclusion

Renal pelvic tumors and ureteral tumors exhibited significant differences in clinicopathologic characteristics and epigenetic biomarkers. Gene promoter methylation might be an important mechanism in explaining distinct tumor patterns and behaviors in UTUC.

Abbreviations

CSS: 

Cancer specific survival

CT: 

Computed tomography

eGFR: 

Estimated glomerular filtration rate

HR: 

Hazard ratio

MRI: 

Magnetic resonance imaging

MSP: 

Methylation-sensitive polymerase chain reaction

OS: 

Overall survival

RNU: 

Radical nephroureterectomy

UICC: 

Union for International Cancer Control

UTUC: 

Upper tract urothelial carcinoma

WHO: 

World Health Organization

Declarations

Acknowledgements

The author thank the entire staff of Department of Urology, Peking University First Hospital Structured data processing occurred partially using Medbanks’ approach [Medbanks (Beijing) Network Technology CO, Ltd].

Funding

This study was funded by Collaborative Research Foundation of Peking University Health Science Center and National Taiwan University, the College of Medicine (BMU20120318), the Natural Science Foundation of Beijing (7152146), the Clinical Features Research of Capital (No. Z151100004015173), the Capital Health Research and Development of Special (2016–1-4077) and Fund for Fostering Young Scholars of Peking University Health Science Center (BMU2017PY009).

Availability of data and materials

The datasets of the current study are available from the corresponding author on reasonable request.

Authors’ contributions

DF, SH, XL, LZ (Zhou): Protocol/project development; DF, SH, ZC, GX, LZ (Zhang), XL: Data collection or management; DF, SH GX: Data analysis; DF, SH, NS: Manuscript writing/editing; XL, LZ (Zhou): Critical revision of the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The study received the ethics approval by the Ethic Committee of Peking University First Hospital (No. 2016–1253).

All procedures performed in studies involving human participants were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

All patients agreed and signed the informed consent to participate into the study, and they agreed that their information (including clinical information, surgical related data, pathological data and surveillance) would be collected for scientific study and by published in professional medical journals.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Centre, No. 8 Xishiku St, Xicheng District, Beijing, 100034, China
(2)
Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA

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Copyright

© The Author(s). 2018

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