Research ArticleClinical Studies

Clinical Significance of 18F-fluorodeoxyglucose and Glucose Transporter 1 mRNA in Clear Cell Renal Cell Carcinoma

HIRONORI BETSUNOH, SETSU SAKAMOTO, YASUSHI KAJI, AKINORI NUKUI, MINORU KOBAYASHI, MASAHIRO YASHI, KEITARO HAYASHI, NAOHIKO ANZAI and TAKAO KAMAI
Anticancer Research October 2021, 41 (10) 5179-5188; DOI: https://doi.org/10.21873/anticanres.15336

Abstract

Background/Aim: 18F-fluorodeoxyglucose (FDG) uptake measurement on positron emission tomography/computed tomography (PET/CT) is difficult in renal tumors because of the nearby renal parenchyma and urinary tract, which excrete FDG. We carefully examined the maximum standardized uptake value (SUVmax) on FDG-PET/CT and investigated the relationship between major glucose transporters in the kidney and clear cell renal cell carcinoma (ccRCC) progression. Patients and Methods: Forty-five patients with ccRCC underwent FDG-PET/CT for staging and nephrectomy. Glucose transporter mRNA expression was examined in the removed kidney. Results: SUVmax was increased in high-stage and high-grade tumors. Glucose transporter 1 (GLUT1) mRNA expression was higher in tumor tissues, in contrast to other glucose transporters. SUVmax was not correlated with GLUT1 mRNA expression. Kaplan-Meier analysis showed reduced overall and recurrence-free survival in the high SUVmax group. Conclusion: Primary ccRCC lesions show a high SUVmax and GLUT1 mRNA over-expression. SUVmax increases with tumor upstaging and upgrading.

Key Words:

The glucose transport system is located at the cell membrane and found throughout the body but particularly in the kidney and intestine. There are two glucose transporters: the glucose transporter (GLUTs) with 14 members (1) and the sodium-glucose transporter (SGLTs) with 5 members (2). GLUTs and SGLTs act as facilitative and secondary active transport systems, respectively. In this process, glucose is initially transported from the renal tubular lumen to tubular cells by SGLT1 and SGLT2 at the apical membrane, followed by transport to the intravascular lumen by GLUT1 and GLUT2 at the basolateral membrane. Because SGLT2 is a key molecular factor for glucose reabsorption in the kidney, it has recently attracted attention for the development of antidiabetic agents. Several studies have measured SGLT1, GLUT1, or GLUT2 in many malignancies (3-6). Nakajo et al. (5) reported that the staining scores of GLUT1 were higher in a high-risk thymic epithelial tumor group than in a low-risk group and identified a significant correlation between 18F-fluorodeoxyglucose (FDG) uptake and GLUT1 staining score. For renal cell carcinomas (RCCs), Chan et al. (3) reported that, of GLUT1, GLUT2, GLUT3, and GLUT4, GLUT1 mRNAs were over-expressed. Kobayashi et al. (6) investigated GLUT1 and -2 and SGLT1 and -2 expression by immunostaining and determined that they had no significant correlation with pathological variables. FDG-positron emission tomography (PET) is useful for evaluating malignancies and monitoring treatment effect because PET detects the altered glycometabolism of malignancies (3, 5, 7-10). Although some studies have focused on the use of FDG-PET for detecting metastatic RCCs (7, 8), there are few reports on its use in primary RCC (9, 10). One reason for this scant evidence is the close proximity between primary RCC and the urinary tract, which is the site of FDG excretion. Accordingly, care must be taken to not mistake the excreted FDG as a primary RCC lesion.

In another study, Saito et al. (11) analyzed C-reactive protein (CRP) kinetics and overall survival in metastatic RCC and revealed that CRP could be used as a biomarker. However, there was no consideration of whether the prognosis of primary RCC was associated with glycometabolism and CRP. Thus, examination of all factors together could be more important for the prognosis of RCC. In relation to this, glucose transporters (6) and FDG uptake (9) have been studied independently in ccRCC. Accordingly, here, we carefully measured the SUVmax of FDG and the mRNA levels of glucose transporters in primary ccRCC lesions to determine whether a high SUVmax and over-expression of these mRNAs correlate with tumor progression as the primary endpoint. The secondary endpoint was the relationship of the SUVmax, GLUT1 mRNA, and CRP with prognosis.

Patients and Methods

Patients. We retrospectively studied 45 consecutive Japanese patients with ccRCC diagnosed by nephrectomy from 2012 to 2015 (median age: 68 years), but patients receiving therapy before surgery were excluded. Patient characteristics are summarized in Table I. Although we performed nephrectomy only in 10 stage IV patients with metastasis, this is the standard medical treatment wherever possible. Accordingly, the overall survival (n=45) and recurrence-free survival (n=35) populations differ. In addition, patients underwent FDG-PET/computed tomography (CT) for preoperative staging prior to nephrectomy; SUVmax was measured on FDG-PET; and CRP was measured within three weeks before surgery. Several tumor tissue specimens and normal renal parenchymal tissue specimens were harvested from all patients and stored at −80°C as soon as possible after nephrectomy, as described previously (9, 12). Normal renal parenchymal tissue specimens were obtained from parts of the resected kidneys as far away from the tumor as possible. If the tumor was centrally located, normal parenchymal tissue was attained from the upper or lower pole. The tumor grade and clinical stage were determined by the Fuhrman system and TNM classification, respectively (13, 14). Histopathological examinations of the resected kidneys were performed independently by two pathologists. Patients with abnormalities in putative normal tissue samples through microscopic examination were excluded. This study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics review board of our hospital. Additionally, each patient provided written informed consent.

View this table:
Table I.

Patient and tumor characteristics.

We typically performed postoperative adjuvant therapy with interferon (IFN)-alpha (3, 5, or 6 million units of natural human IFN-alpha two or three times a week), sorafenib (400 to 800 mg/day), sunitinib (25 to 50 mg/day for 4 weeks, followed by 2 weeks off therapy), or temsirolimus (25 mg/week) if patients had metastatic lesions.

FDG-PET and contrast-enhanced CT. Patients generally received an intravenous injection of FDG (222-333 MBq) at 4.5 MBq/kg after fasting for at least 6 h. Whole-body imaging using a combined FDG-PET/CT scanner (Biograph Sensation 16; Siemens, Erlangen, Germany) and image analysis were performed as described previously (15, 16). The PET and CT scanners covered a region ranging from the brain to the mid-thigh. At 1 h after 18F-FDG injection, CT scanning was conducted and whole-body PET scanning was performed with acquisition for 3 min per bed position using the three-dimensional acquisition mode. Patients underwent contrast-enhanced CT at the same time as PET or within 3 weeks. To acquire the PET/contrast-enhanced CT images, the scans were conducted after CT and PET and subsequent intravenous administration of contrast agent. Additional scans covering only the upper abdomen were performed 40, 75, and 180 s after contrast agent injection, regardless of whether PET/contrast-enhanced CT or contrast-enhanced CT was performed.

Image analysis. SUVmax was determined according to the following formula using Syngo.via software (Siemens Healthcare, Forchheim, Germany):Embedded Image

At the time of the contrast-enhanced CT (2.2 FDG-PET and contrast-enhanced CT), we obtained the enhanced CT images (corticomedullary, nephrographic, and excretory). Thus, the SUVmax was measured in reference to these phases. Accordingly, it was not difficult to identify the volume of interest (VOI), even if the lesion had faint FDG (Figure 1A–C). Alternatively, a manual region of interest was drawn in the case of urinary excretion of FDG near the lesion or the presence of an FDG-avid lesion on a spherical VOI (Figure 1D–F) to avoid FDG contamination, for instance in the case of a higher-stage tumor. The PET/CT images were independently reviewed by two physicians: by a certified physician of PET nuclear medicine (HB) as part of a pilot study and by a board-certified nuclear medicine physician (SS) as supervisor.

Figure 1.
Figure 1.

18F-FDG/CT images of two patients with ccRCC. Axial CT, nephrographic phase (A), fused PET/CT (B), and PET (C) images of a 55-year-old man with ccRCC, G2, pT3aNxM0; SUVmax was 3.2 in a spherical VOI. Axial CT, nephrographic phase (D), fused PET/CT (E), and PET (F) images of a 76-year-old man with ccRCC, G3, pT3bNxM0; SUVmax was 7.0 in a spherical VOI. A manual region of interest was drawn to avoid urinary excretion of FDG (dashed circle). ccRCC: Clear cell renal cell carcinoma; CT: computed tomography; FDG: 18F-fluorodeoxyglucose; PET: positron emission tomography; SUV: standardized uptake value; VOI: volume-of-interest.

Real-time reverse transcription-polymerase chain reaction. Total cellular RNA was purified from all 45 sets of tumor and normal renal parenchymal tissue samples with an RNA preparation kit (High Pure RNA Kit; Roche Diagnostic Ltd., Mannheim, Germany) and was used as a template for the synthesis of cDNA. The reaction mixture (100 μl) contained 1 μg of random hexamers and 100 units of MMLV-reverse transcriptase and was incubated at 25°C for 10 min, 42°C for 30 min, and then at 99°C for 5 min. The following primers were used to amplify the indicated genes in tumor tissues after confirmation of their specificity (Takara Bio Ltd., Shiga, Japan): GLUT1, sense, 5’-CTTCCTGCTC ATCAACCGCA-3’, antisense, 5’-TGACGATACC GGAGCCAATG-3’; GLUT2, sense, 5’-AGGACTTCTG TGGACCTTAT GTG-3’, antisense, 5’-TTCATGTCA AAAAGCAGGG-3’; SGLT1, sense, 5’-CTCTT CGCC ATTTCTTTCATC-3’, antisense, 5’-ATGCACATCC GGAA TGGGT-3’; SGLT2, sense, 5’-AGTGCCTGCT CTGGTTTTGT-3’, antisense, 5’-GAGGCTGTGGC TTATGGTGT-3’. Quantitative real-time RT-PCR was performed in a 25-μl reaction mixture containing 20 ng sample cDNA, 100 nM sense primer, 100 nM antisense primer, and 12.5 μl of SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA, USA). The PCR program included: 45 cycles at 95°C for 15 s and 60°C for 1 min using a TP960 Thermal Cycler Dice (Takara Bio Ltd.). A standard curve was generated for each mRNA by five-fold dilution of a control RNA sample, and the expression of each target mRNA was calculated as a ratio to that of 103 copies of β-actin (Takara Bio Ltd.) to determine the relative expression level (17, 18). The mean value obtained by the analysis of three samples of resected tissue was calculated as described previously.

Statistical analysis. To analyze the mRNA expression pattern of glucose transporters (GLUT1, GLUT2, SGLT1, SGLT2) and the SUVmax of the primary tumors, the 45 patients were classified according to stage I (n=19), II (n=2), III (n=14), and IV (n=10)–and grade G1 (n=4), G2 (n=30), G3 (n=9), and G4 (n=2). Although we wanted to clarify whether mRNA expression of glucose transporters and SUVmax would change with upstaging or upgrading, the numbers of patients for each stage and grade were unbalanced. Therefore, we used the following two sets of categories: I–II (n=21) and III–IV (n=24), and G1–2 (n=34) and G3–4 (n=11). We analyzed the mRNA expression of glucose transporters (GLUT1, GLUT2, SGLT1, SGLT2) and SUVmax by stage and grade using Student’s t-test or the Mann-Whitney U-test. Kaplan-Meier curves and the log-rank test were used to estimate overall survival and relapse-free survival for groups distributed according to the cutoff values. These curves were based on cutoff points identified using a receiver operating characteristic (ROC) curve and then the patients were divided into two groups. For example, the cutoff point for GLUT1 mRNA was set as 12.3 (copies relative to 103 copies of β-actin mRNA) for overall survival. We analyzed several variables (age, sex, stage, grade, metastasis, GLUT1 mRNA, SUVmax, and CRP) for overall survival and relapse-free survival by Cox proportional-hazards regression analysis and Kaplan-Meier curves. Spearman’s rank correlation coefficient analysis was used to determine the relationship between the expression of GLUT1 mRNA and SUVmax values and between CRP values and SUVmax values. In all analyses, a p-value less than 0.05 was considered statistically significant. Data were analyzed with Microsoft Excel and StatFlex Ver. 6.0 (Artech Ltd., Osaka, Japan).

Results

mRNA expression of glucose transporters. The expression of GLUT1 mRNA was significantly increased in tumor tissue (T) (median, 12.7 copies relative to 103 copies of β-actin mRNA) compared with normal renal parenchymal tissue (N) (median, 0.5) (Figure 2). However, there was no difference in the expression of other types of glucose transporter mRNA between the tumor tissue and the normal renal parenchymal tissue (Figure 2).

Figure 2.
Figure 2.

mRNA expression of the glucose transporters. Statistical significance was evaluated using the Mann-Whitney U-test. N: Normal renal parenchymal tissue; T: tumor tissue. Box plots show median, 10%-90%, 25%, and 75% quartiles.

mRNA expression of glucose transporters and SUVmax on FDG-PET by stage and grade. Overall median values of the mRNA expression of glucose transporters (GLUT1, GLUT2, SGLT1, SGLT2) and SUVmax were (12.7, 3.2, 1.2, 3.2) copies relative to 103 copies of β-actin mRNA and 3.9, respectively. Median values of mRNA expression of the glucose transporters GLUT1, GLUT2, SGLT1, and SGLT2 by stage and grade were as follows: Stage I–II, 12.7, 2.1, 0.9, and 2.1, respectively; Stage III–IV, 12.9, 3.6, 1.3, and 3.5, respectively; G1–2, 13.7, 3.0, 1.2, and 3.2, respectively; and G3–4, 8.8, 3.9, 1.2, and 4.6, respectively (Figure 3A-D). Median SUVmax values by stage and grade were as follows: Stage I–II, 2.9; Stage III–IV, 4.7; G1–2, 3.6; and G3–4, 4.8 (Figure 3E). Although the mRNA levels of glucose transporters did not correlate with stage or grade (Figure 3A-D), the SUVmax of ccRCC positively correlated with both stage and grade (stage: p<0.01, Student’s t-test; grade: p<0.05, Mann-Whitney U-test; Figure 3E).

Figure 3.
Figure 3.

Correlation of the mRNA expression levels of glucose transporters (GLUT1, GLUT2, SGLT1, SGLT2) (A-D) and SUVmax values (E) with both staging and grading. A Kruskal-Wallis test was used for staging, and a Mann-Whitney U-test was used for grading. In (E), the two-sample t-test was used to compare groups I-II vs. III-IV. The Mann-Whitney test was used to compare groups G1-2 vs. G3-4. GLUT: Glucose transporter; SUV: standardized uptake value.

Correlation between survival rate and clinicopathological factors. CRP is also indicated as a clinical factor related to tumor progression. Thus, its correlation with overall survival was analyzed (n=45). GLUT1 mRNA, SUVmax, and CRP were categorized into two groups using the binary variable as a check of clinical validity by ROC analysis and a sensitivity–specificity curve because the results of Cox proportional-hazards regression analyses using continuous variable and binary variable showed no great difference. When CRP of 0.51 (mg/dl), SUVmax of 4.6, and a GLUT1 mRNA expression of 12.3 (copies relative to 103 copies of β-actin mRNA) were used as cutoff points, the sensitivity, specificity, area under the curve (AUC), and minimum distances from the left upper point (0,1) of the ROC curves were respectively 75.0%, 77.8%, 0.830, and 0.11; 75.0%, 77.8%, 0.830, and 0.11; and 52.8%, 55.6%, 0.556, and 0.42. We also analyzed the correlation with recurrence-free survival in patients who underwent radical nephrectomy (n=35), excluding the 10 patients with metastasis who had a nephrectomy, using the following cutoff points: CRP of 0.35 (mg/dl), SUVmax of 4.5, and a GLUT1 mRNA expression of 20.5 (copies relative to 103 copies of β-actin mRNA). In this case, the sensitivity, specificity, AUC, and minimum distance from the left upper point (0,1) of the ROC curves were respectively 76.7%, 80.0%, 0.900, and 0.06; 90.0%, 90.0%, 0.937, and 0.02; and 70.0%, 66.7%, 0.753, and 0.20.

Kaplan-Meier analysis of overall and recurrence-free survival was performed using the CRP, SUVmax and GLUT1 mRNA cutoff points. High CRP and a high SUVmax were significantly associated with a poor overall survival and recurrence-free survival rate after surgery (p<0.01, Figure 4A, C, and D; p<0.05, Figure 4B), unlike GLUT1 mRNA expression (p=0.30, Figure 4E; p=0.05, Figure 4F). We examined the statistical association of overall survival with age, sex, stage, grade, metastasis, CRP, GLUT1 mRNA, and SUVmax. Metastasis, CRP, and SUVmax were individually confirmed to be significant factors in univariate regression analyses (Table II). These factors were correlated with each other according to Fisher’s exact test and the χ2-test (Table III).

Figure 4.
Figure 4.

Overall survival curves (n=45) and recurrence-free survival curves (n=35). (A) CRP: lower group <0.51 (mg/dl), higher group ≥0.51 (mg/dl), (B) CRP: lower group <0.35, higher group ≥0.35 [same as (A)], (C) SUVmax: lower uptake group <4.6, higher uptake group ≥4.6. (D) SUVmax: lower uptake group <4.5 [same as (C)]. (E) GLUT1 mRNA: higher expression group ≥12.3, lower expression group <12.3, higher uptake group ≥12.3. (F) GLUT1 mRNA: higher expression group ≥20.5 [same as (E)]. CRP: C-reactive protein; GLUT: glucose transporter; SUV: standardized uptake value.

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Table II.

Univariate and multivariate regression analyses using the Cox proportional-hazards model for prediction of overall survival (n=45).

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Table III.

Factor correlation analysis (metastasis, CRP and SUVmax).

Correlation of SUVmax with GLUT1 mRNA and CRP. There was no correlation between SUVmax and GLUT1 mRNA expression (Figure 5A), but there was a correlation between SUVmax and CRP (Spearman’s rank correlation r=0.457, p<0.01; Figure 5B). Furthermore, by considering the result shown in Figure 5B, it was confirmed that there was multicollinearity between SUVmax and CRP. Thus, multivariate regression analysis of metastasis, SUVmax, and GLUT1 mRNA was performed (Table II). However, no factors were independently associated with prognosis. According to the analysis of recurrence-free survival, CRP was confirmed to be a significant factor in univariate regression analysis, and SUVmax could not be analyzed due to the close relationship between the higher SUVmax uptake group and the recurrence group (Table IV).

Figure 5.
Figure 5.

Spearman’s rank correlation of SUVmax values with GLUT1mRNA levels (A) and CRP values (B). GLUT: Glucose transporter; SUV: standardized uptake value; CRP: C-reactive protein.

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Table IV.

Univariate regression analysis of recurrence-free survival using the Cox proportional-hazards model (n=35).

Discussion

By comparing primary ccRCC with normal renal parenchymal tissues, we aimed to examine how the mRNA expression of glucose transporters (GLUT1, GLUT2, SGLT1, and SGLT2) changed and whether these glucose transporters related to FDG accumulation and prognosis. We showed that GLUT1 mRNA was over-expressed, although no significant change was found for GLUT2, SGLT1, and SGLT2. These findings resemble those of a study by Chan et al. (3) and the results of staining with GLUT1 for malignant thymic epithelial tumors (5). The lesion expression patterns from the above analyses would probably result in an upregulated glycometabolism due to GLUT1 mRNA over-expression and tumor progression. However, there was no relationship between GLUT1 mRNA and stage, grade, or survival in our study. Thus, specific glycometabolism-related glucose transporters could not be linked to ccRCC.

Based on the analysis of FDG accumulation, FDG uptake increased with both upstaging and upgrading. Thus, it can be suggested that an increased FDG uptake in primary ccRCC is related to poor prognosis.

In the kidney, GLUT1, GLUT2, SGLT1, and SGLT2, which belong to distinct glucose transporter families, play roles in facilitative and secondary active transport at renal proximal tubular epithelial cells. Most ccRCCs arise from these cells. In ccRCCs, von Hippel-Lindau (VHL) tumor suppressor protein becomes inactivated by mutation (>50%) or methylation (5%-10%) (19-21). This leads to upregulation of hypoxia-inducible factor (HIF)-1, which is normally induced under hypoxic conditions, followed by enhanced transcription of several targets, such as GLUT1 and vascular endothelial growth factor (22).

In this study, we showed increased FDG uptake and GLUT1 mRNA over-expression in ccRCCs. Our results appear to be concordant with those of studies examining glucose metabolism in RCC (3, 23). Although many studies of FDG uptake in other malignancies have been published (5, 24, 25), none have examined the relationship between FDG uptake, GLUT1, and RCC. The following are possible reasons for this gap. One is the rather faint FDG uptake in many RCCs, which is especially common in early stages. As described above, our data showed that the median SUVmax value in ccRCC stage I– II was just 2.9. These results could indicate a technical limitation to the accurate measurement of the accumulation because of a lower contrast between the RCCs and the surrounding renal tissue/adjacent urinary tract; these regions have faint-to-strong FDG uptake physiologically. Miyakita et al. (26) calculated the SUV of kidney tumors in 10 patients, obtaining a value of 2.42±1.40, and Bachor et al. (27) reported that RCC was overlooked preoperatively in 6 of 26 patients with histologically proven RCC because of a false negative diagnosis on PET. Miyakita et al. (26) also suggested that RCC cells themselves have a low potential for glucose metabolism and that FDG accumulation is decreased, even though GLUT1 is over-expressed in many RCCs. However, Steinberg et al. (28) and Schmoll et al. (29) showed that glucose 6-phosphatase was strongly reduced in RCCs compared with control kidney tissue of the same patient. In addition, hexokinase (HK) 2, which is an HK isozyme and a key molecule for glycolysis in cancer cells (30), is over-expressed in RCC tissues (23). Considering the abovementioned reports of increased glucose metabolism in RCCs (23, 28, 29), we calculated the SUVmax of lesions carefully, even if they only showed faint FDG accumulation. Accordingly, we were able to determine the relationship between FDG accumulation in the lesions and parameters such as stage, histological grade, and prognosis. Thus, we hypothesize that these are the reasons for the paucity of reports regarding FDG accumulation and metabolism in RCCs.

Here, we also examined FDG accumulation and glucose transporter mRNA. We initially hypothesized that the abnormal FDG uptake would arise from GLUT1 mRNA over-expression. However, there was no correlation between FDG and GLUT1 mRNA. Thus, we postulate that the abnormal FDG uptake might be caused by other catalyzing substances besides GLUT1, but we did not explore alternative molecular pathways of FDG uptake, for example, glucose 6-phosphatase and HK.

We also showed that SUVmax on PET-CT was related to metastasis and CRP by the chi-square test. Kaplan-Meier curves showed that SUVmax and CRP were significantly associated with overall and recurrence-free survival rates. In particular, the higher SUVmax group was strongly associated with the recurrence group, meaning that multivariate regression analysis could not be performed due to the close relationship between these two groups. Spearman’s correlation between SUVmax and CRP showed a strong correlation. Thus, both SUVmax and CRP could be prognostic factors.

Thus, we propose the following: in many ccRCCs, the VHL pathway is inactivated and HIF is upregulated, followed by over-expression of GLUT1 and HK2 (3, 23). This mechanism, which results in an increase in the glycolytic system, could be reflected in SUVmax. Accordingly, we predict that high SUVmax and CRP are related to poor prognosis, even though SUVmax is generally low in ccRCC.

Because our findings were limited to a portion of the glycolytic system, the exploration of other enzymes involved in the glycolytic system and FDG accumulation is required. In future work, we hope to clarify the mechanisms underlying the progression of ccRCC. A high SUVmax and GLUT1 mRNA over-expression were observed in primary ccRCC. SUVmax increased with upstaging and upgrading, unlike GLUT1 mRNA. Moreover, there was no correlation between SUVmax and GLUT1 mRNA, indicating the possible involvement of other metabolic mechanisms in ccRCC.

Acknowledgements

The Authors thank Hitomi Sakuraoka, Mai Takahashi, Kyoko Arai, Masaya Seki and Kazumi Akimoto for their skillful technical assistance. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Footnotes

  • Authors’ Contributions

    Concept development and manuscript preparation (HB, SS, YK, NA, TK), Data generation (HB, SS, YK, AN, MY, TK), Experimental design (HB, SS, MK, KH), Data analysis (HB, SS). All Authors cooperated in the internal review of the manuscript prior to submission.

  • Conflicts of Interest

    The Authors have no conflicts of interest directly relevant to the content of this article.

  • Received July 8, 2021.
  • Revision received August 10, 2021.
  • Accepted August 11, 2021.

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Clinical Significance of 18F-fluorodeoxyglucose and Glucose Transporter 1 mRNA in Clear Cell Renal Cell Carcinoma
HIRONORI BETSUNOH, SETSU SAKAMOTO, YASUSHI KAJI, AKINORI NUKUI, MINORU KOBAYASHI, MASAHIRO YASHI, KEITARO HAYASHI, NAOHIKO ANZAI, TAKAO KAMAI
Anticancer Research Oct 2021, 41 (10) 5179-5188; DOI: 10.21873/anticanres.15336
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