The efficacy of second-line nivolumab versus tyrosine kinase inhibitors for renal cell carcinoma with bone metastases: A multi-institutional retrospective study

The efficacy of second-line nivolumab versus tyrosine kinase inhibitors for renal cell carcinoma with bone metastases: A multi-institutional retrospective study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The efficacy of second-line nivolumab versus tyrosine kinase inhibitors for renal cell carcinoma with bone metastases: A multi-institutional retrospective study Gaku Yamamichi, Taigo Kato, Akihiro Yoshimura, Masaru Tani, Yuki Horibe, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4962940/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Immune checkpoint inhibitor combination therapy has been standardized for first-line treatment for metastatic renal cell carcinoma (mRCC), leading to the changes in second-line treatment options such as nivolumab or tyrosine kinase inhibitors (TKIs). However, there have been few reports comparing the efficacy of these drugs in mRCC patients, especially with bone metastases (BM), which are associated with a poor prognosis. Therefore, we aimed to compare the efficacy of nivolumab and TKIs as second-line treatments for 87 mRCC patients with BM and the microenvironments of the primary tumor and BM lesions. Multivariate analysis revealed poor risk according to the IMDC classification (p < 0.01) and high serum ALP value (p = 0.031) as worse prognostic factors, while there was no significant difference of overall survival between patients with nivolumab and TKIs. However, the objective response rate at BM lesions was significantly higher with TKIs than with nivolumab (p = 0.014). Immunohistochemistry analysis also revealed that VEGFR2 expression was significantly higher at BM lesions compared to that in primary tumors, showing the potential benefit of TKIs over nivolumab in mRCC patients with BM. In conclusion, TKIs could be the promising second-line treatment for mRCC with metastasis limited to the bone. Biological sciences/Cancer/Cancer microenvironment Biological sciences/Cancer/Cancer therapy Biological sciences/Cancer/Metastases Biological sciences/Cancer/Urological cancer Renal cell carcinoma bone metastasis second-line treatment nivolumab tyrosine kinase inhibitor overall survival Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Renal cell carcinoma (RCC) ranks as the fourteenth most frequently diagnosed cancer globally [ 1 ]. In 2020, an estimated 431,288 new cases of RCC and associated 179,368 deaths were reported. With the advances in imaging and inspection technology, the incidence of RCC has been increasing at an annual rate of 1–2% [ 2 ]. Immune checkpoint inhibitor (ICI) combination therapy, such as ICI plus ICI or ICI plus tyrosine kinase inhibitor (TKI), has become commonly used as the first-line systemic treatment for metastatic RCC (mRCC). After the refractoriness to ICI combination therapy, a majority of patients developed progressive disease requiring subsequent TKIs or nivolumab [ 3 ]. So far, although comparable efficacies of axitinib and nivolumab as secondary treatments for mRCC have been reported [ 4 ], There are limited real-world clinical reports on second-line treatments for RCC. Among various types of metastases, RCC is especially susceptible to bone metastasis (BM), which occurs in approximately 30% of patients with mRCC [ 5 ]. BM may lead to severe complications, including skeletal-related events, and is a poor prognostic factor for patients with mRCC [ 6 ]. Negishi et al. reported that the effectiveness of ICI against BM site in mRCC is limited with only 5% [ 7 ]. On the other hand, the METEOR trial reported that cabozantinib, a well-known TKI, led to a better prognosis of mRCC with BM than everolimus after at least one previous TKI [ 8 ]. However, the efficacy of cabozantinib in treating bone metastatic lesion remains unclear. Therefore, this study aimed to compare the treatment efficacies of second-line TKIs and nivolumab in patients with RCC and BM. Additionally, we evaluated the expression of receptors targeted by cabozantinib, the immune microenvironment, and hypoxic conditions using immunohistochemistry to compare primary tumors and BM lesions. Results Patient characteristics The clinicopathological characteristics and outcomes of the 87 patients with mRCC and BM included in the study are summarized in Table 1 . The median age of the patients in the nivolumab and TKI groups was 66 years (range, 29–87 years) and 69 years (range, 33–84 years), respectively. The most prevalent histological type was clear cell carcinoma, observed in 25 (86%) and 47 (81%) patients treated with nivolumab and TKI, respectively. The nivolumab group predominantly comprised patients with poor International Metastatic Renal Cell Carcinoma Database (IMDC) risk (52.0%), whereas 76.0% of patients treated with a TKI were classified as having favorable and intermediate risk. The most commonly prescribed TKI was axitinib (n = 35, 60%), followed by cabozantinib (n = 14, 24%). Table 1 Patient characteristics. Nivolumab (n = 29) TKI (n = 58) P -value Age (years) 66 (29–87) 69 (33–84) 0.76 Sex, Male: Female 24 (83%): 5 (17%) 43 (74%): 15 (26%) 0.43 Histopathology Clear cell RCC Papillary RCC Others/unknown 25 (86%) 1 (3%) 3 (10%) 47 (81%) 3 (5%) 8 (14%) 0.76 1.0 0.75 IMDC risk Favorable / Intermediate Poor 14 (48%) 15 (52%) 44 (76%) 14 (24%) 0.015 Previous partial or total nephrectomy 24 (83%) 43 (74%) 0.43 Local therapy for BM radiation therapy surgery 17 (59%) 4 (14%) 34 (59%) 4 (7%) 1.0 0.43 Patients with metastasis other than bone 26 (90%) 47 (81%) 0.37 Location of metastatic sites Bone Lung Lymph node Liver Brain Others 29 (100%) 16 (55%) 11 (38%) 6 (21%) 3 (10%) 9 (31%) 58 (100%) 39 (67%) 12 (21%) 11 (19%) 7 (12%) 13 (22%) 1.0 0.35 0.12 1.0 1.0 0.44 Number of BM Single Multiple 4 (14%) 25 (86%) 12 (21%) 46 (79%) 0.56 Prior 1st line treatment TKI ICI + TKI ICI + ICI Interferon-α Others 25 (86%) 4 (14%) 0 0 0 26 (45%) 14 (24%) 4 (7%) 8 (14%) 7 (12%) < 0.01 0.40 0.30 0.048 0.090 Type of second-line TKI treatment Axitinib Cabozantinib Sorafenib Sunitinib - 35 (60%) 14 (24%) 5 (9%) 4 (7%) - Bone modifying agents 20 (69%) 45 (76%) 0.44 ALP (U/L) 287 (153–1632) 288 (135–3406) 0.31 LDH (U/L) 218 (125–703) 213 (97–2154) 0.60 NLR 3.2 (1.4–32.5) 3.5 (1.3–16.1) 0.85 Observation period from the Second-line therapy (months) 7.0 (1–73) 11.5 (1–93) 0.81 TKI , tyrosine kinase inhibitor; RCC , renal cell carcinoma; IMDC , International Metastatic Database Consortium; BM , bone metastasis; ICI , immune checkpoint inhibitor; ALP , alkaline phosphatase; LDH , lactate dehydrogenase; NLR , neutrophil-to-lymphocyte ratio. Clinical outcomes of patients treated with second-line nivolumab or tyrosine kinase inhibitors Overall, the median follow-up durations of patients treated with nivolumab and TKI groups were 7.0 (range, 1–73) and 11.5 (range, 1–93) months, respectively. There were no significant differences between the cancer-specific survival (CSS) and overall survival (OS) of the patients treated with nivolumab and a TKI (p = 0.76 and p = 0.55, respectively (Fig. 1 , Supplementary Table S1 , Table 2 ). Multivariate analyses revealed that poor risk based on the IMDC classification and high serum alkaline phosphatase (ALP) concentration (≥ 288 U/L) were significantly associated with reduced OS (hazard ratio [HR] = 3.24, 95% CI; 1.84–5.71, p < 0.01; HR = 1.78, 95% CI; 1.05–3.01, p < 0.01, Table 2 ). Accordingly, OS was significantly shorter for patients with poor risk based on the IMDC classification and high serum ALP concentration (≥ 288 U/L) (HR = 3.58, 95% CI; 2.08–6.17, p < 0.01; HR = 2.01, 95% CI; 1.21–3.35, p < 0.01, Fig. 2 ). Table 2 Univariate and multivariate analyses of OS after the introduction of second-line therapy. Univariate analysis Multivariate analysis HR 95% CI P- value HR 95% CI P- value Age (years) < 66 ≥ 66 Reference 1.27 0.77–2.10 0.35 - - - Sex Female Male Reference 0.66 0.37–1.18 0.16 Reference 0.62 0.35–1.12 0.11 IMDC risk Favorable / Intermediate Poor Reference 3.58 2.08–6.17 < 0.01 Reference 3.24 1.84–5.71 < 0.01 Local therapy for BM 1.25 0.73–2.14 0.42 - - - Metastasis other than bone No Yes Reference 1.29 0.64–2.63 0.48 - - - Number of BM Single Multiple Reference 1.34 0.72–2.48 0.36 - - - 2nd line therapy ICI TKI Reference 1.19 0.68–2.07 0.55 - - - Bone modifying agents 1.18 0.65–2.15 0.58 - - - ALP (U/L) Low (< 288) High (≥ 288) Reference 2.01 1.21–3.35 < 0.01 Reference 1.78 1.05–3.01 0.031 LDH (U/L) Low (< 215) High (≥ 215) Reference 1.59 0.96–2.61 0.070 Reference 1.29 0.77–2.16 0.33 NLR Low (< 3.5) High (≥ 3.5) Reference 1.31 0.79–2.16 0.29 - - - OS , overall survival; HR , hazard ratio; TKI , tyrosine kinase inhibitor; IMDC , International Metastatic Database Consortium, BM , bone metastasis, ICI , immune checkpoint inhibitor; ALP , alkaline phosphatase; LDH , lactate dehydrogenase; NLR , neutrophil-to-lymphocyte ratio. To exclude the influence of radiation therapy on BM site, we examined 72 patients with untreated BM site (Supplementary Table S2). Comparison of the outcomes of second-line treatment for BM according to the MD Anderson (MDA) criteria showed that the overall response rate (ORR) was significantly higher for the TKI group (29.2%) than for the nivolumab group (4.2%) (p = 0.014) (Table 3 ). This indicated that TKIs may be more effective than nivolumab for treatment-naïve BM. Table 3 Overall response rate of second-line treatment to locally untreated BM according to the MDA criteria and RECIST 1.1. TKI (n = 48) Nivolumab (n = 24) P -value MDA criteria CR 0 0 PR 14 1 SD 27 16 PD 7 7 ORR 14/48 (29.2%) 1/24 (4.2%) 0.014 RECIST 1.1 CR 0 0 PR 7 1 SD 34 16 PD 7 7 ORR 7/48 (14.6%) 1/24 (4.2%) 0.25 CR , complete response; PR , partial response; SD , stable disease; PD , progressive disease; ORR , overall response rate. Significant difference between the tumor microenvironments of primary tumors and bone metastasis Next, we investigated the presence of tumor-infiltrated immune cells and several molecules targeted by TKIs in tumor microenvironment in primary tumors and BM sites. Representative immunohistochemistry results are shown in Figs. 3 and 4 . As a result, we found a significant increase of the VEGFR2-positive cells in the BM lesions (p = 0.048). In addition, we confirmed that the CD8 + T-cells and CD20 + B-cell counts were higher in primary tumors (p = 0.075 and p = 0.10, respectively; Fig. 5 ). Collectively, these results indicate that primary tumors and BM have different tumor microenvironments, affecting the efficacy of TKIs and nivolumab therapies. Discussion The guidelines of the European Association of Urology recommend ICI combination therapy as the first-line treatment for mRCC [ 9 ]. There is no established drug selection for the second-line treatment of mRCC, but several studies suggest that second-line treatment consists of nivolumab monotherapy or TKI [ 9 ]. On the other hand, the effectiveness of TKI and ICI greatly depends on the tumor microenvironment, but it varies in RCC due to several patient factors including tumor heterogeneity [ 10 ]. For RCC, the characteristics of metastatic tumor cells and the surrounding microenvironment may not always match those of primary tumors [ 11 ]. Therefore, a comparative analysis of the molecular biomarker expression profiles of primary and metastatic specimens, such as bone, should be performed [ 12 ]. The bone matrix is inherently rich in growth factors, making it a favorable and fertile environment for metastatic tumors, irrespective of the primary tumor type. BM is considered a poor prognostic factor for patients with mRCC [ 13 ]. In the microenvironment of BM lesions, regulatory T-cells and myeloid-derived suppressor cells are abundant, which suppresses tumor immunity [ 14 , 15 ], which may lead to poor prognosis for mRCC patients with BM. Moreover, in RCC, inactivation of the von Hippel-Lindau tumor suppressor gene is common and leads to an increase in hypoxia-inducible factor-alpha, resulting in the overexpression of vascular endothelial growth factor (VEGF) [ 16 ]. This growth factor promotes tumor angiogenesis and plays a crucial role in the invasion and metastasis of RCC. On the other hand, tyrosine kinase is an important enzyme in intracellular signal transduction, and binding of VEGF to the VEGF receptor (VEGFR) increases receptor tyrosine kinase activity and initiates intracellular signal transduction. Considering above, we aimed to compare the efficacies of nivolumab and TKIs as second-line treatments for patients with mRCC with BM, elucidating the differences between the tumor microenvironments of primary and BM lesions. In this study, we present two novel findings. First, we found that TKIs were more effective as second-line treatments for BM lesions in RCC than nivolumab monotherapy, as evidenced by the higher ORR at the BM sites (Table 3 ). Previous studies have shown a significant difference in the treatment efficacy of ICI across metastatic lesions [ 17 ]. In a large-scale tumor-agnostic study, BM lesions were associated with resistance to ICI [ 18 ]. In patients with mRCC treated with second-line nivolumab, treatment efficacy varies significantly with the metastatic site [ 19 ], with bone exhibiting a particularly low ORR of 5%, compared to 36% for lung and 50% for liver metastases [ 7 ]. In patients with mRCC treated with nivolumab as second-line therapy or beyond, BM, rather than lung or lymph node metastases, was associated with poor progression-free survival (PFS) and OS [ 20 ]. In the present study, an elevated serum ALP concentration, which reflects the overall deterioration of systemic conditions such as BM volume, was an independent poor prognostic factor for second-line treatment of mRCC with BM (Table 2 ). Considering above, TKIs are considered a promising option for patients with mRCC with BM and without other visceral metastases. Second, VEGFR2 expression was higher in BM lesions than in primary tumors, and BM lesions showed a trend of decreased CD8 + tumor-infiltrating T-lymphocytes and tumor-infiltrating CD20 + B-cells (Fig. 5 ), which may contribute to the lower ORR of nivolumab than of TKI for BM lesions. Tao et al. reported that tumor-infiltrating B-lymphocytes in mRCC have been shown to recruit and activate CD8 + tumor-infiltrating T-lymphocytes, thereby enhancing anti-tumor effects [ 21 ], and this process is involved in the formation of tertiary lymphoid structures [ 22 ]. TKIs are also considered more likely to be effective for cases of RCC with high expression of VEGFR2 [ 23 ]. In this study, we described a significant increase of VEGFR2- positive cells in BM sites, demonstrating the potential benefits of TKI in patients with mRCC with BM. Especially, considering that cabozantinib displayed the strongest inhibition toward VEGFR2 among several types of TKIs, cabozantinib may likely contributes to the enhanced antitumor activity in BM [ 24 ]. This study had several limitations. First, this was a retrospective study with a few cases. While it was a multicenter study including five hospitals, the number of patients with mRCC with BM receiving second-line treatment was limited, and even fewer underwent surgery for BM lesions. Therefore, future studies with larger sample sizes and more extensive designs are warranted. Second, we used the MDA criteria and Response Evaluation Criteria in Solid Tumors to evaluate the treatment efficacy for BM lesions, but there is currently no consensus on the best response evaluation system for them [ 25 ]. Notwithstanding, several studies have used the MDA criteria to evaluate BM lesions [ 26 ]. In this study, we revealed that TKIs may have higher efficacy than nivolumab against BM lesion and poor IMDC risk classification and elevated serum ALP concentrations are associated with worse prognosis in patients with mRCC and BM receiving second-line therapy. In patients with mRCC with metastases limited to the bone, TKIs may be more effective than nivolumab. Methods Patient selection We retrospectively reviewed the clinical data of 721 patients with RCC and analyzed the clinicopathological data of 87 patients with mRCC with BM who initiated second-line treatment with nivolumab (n = 29) or TKI (n = 58) at Osaka University Hospital, Osaka Police Hospital, Osaka General Medical Center, Osaka Rosai Hospital, and Osaka National Hospital between January 2008 and December 2023. BM was diagnosed using computed tomography with MRI or bone scintigraphy, which was performed as needed [ 27 ]. The TKIs included sunitinib, axitinib, cabozantinib, sorafenib, and pazopanib. The dosage and administration intervals followed standard treatment protocols. The following patient data were collected from the hospital records of the patients: age, sex, histopathology of RCC, IMDC classification for first-line therapy, previous nephrectomy, local therapy for BM site, location of metastatic sites, number of BMs, first-line therapy regimen, type of second-line regimen, bone modifying agent, serum concentration of ALP, serum concentration of lactate dehydrogenase, neutrophil-lymphocyte ratio, best ORR for the second line therapy, second-line therapy CSS, and OS. The therapeutic efficacy of second-line treatment was assessed every 2–3 months using computed tomography according to the Response Evaluation Criteria in Solid Tumors version 1.1 and MDA criteria [ 28 ]. The best response of each patient during treatment was determined and classified as complete response, partial response, stable disease, or progressive disease. This study was approved by the Institutional Review Board of the Osaka University Hospital (# 018 − 0003). All procedures were conducted in accordance with the Declaration of Helsinki, and informed consent was obtained from all participants. Immunohistochemical staining and quantification The primary RCC tissue resected after total nephrectomy was stored as formalin-fixed paraffin-embedded tissue blocks. The resected RCC tissue from the BM site in the same patients was subjected to tris-ethylenediaminetetraacetic acid until tissue softening was observed. This was followed by paraffin fixation. Immunohistochemical staining was performed using 4 µm-thick paraffin-embedded tissue samples of primary RCC samples and BM tissues. The tissue samples were deparaffinized using xylene and a graded series of ethanol solutions and stained with eosin. Other sections were treated with EDTA buffer (pH 9.0) and activated by warming at 125°C for 30 seconds using a Pascal pressure chamber (S2800, Dako) for antigen activation treatment. Endogenous peroxidase activity was blocked by incubating the sections with 0.3% hydrogen peroxide for 5 min, followed by overnight incubation with primary antibodies against CD8 (1:100; ab17147, Abcam) as a marker for cytotoxic T-lymphocytes, CD20 (1:800; ab9475, Abcam) as a marker for B-cells, PD-L1 (clone 28 − 8, 1:200; ab205921, Abcam), HIF2α (1:200; ab243861, Abcam), c-MET (1:100; ab51067, Abcam), VEGFR2 (1:100; ab115805, Abcam), and AXL (1:2000; ab219651, Abcam) at 4°C. The EnVision + system horseradish peroxidase-labeled polyclonal anti-rabbit and anti-mouse antibody (DAKO) was used, and staining was performed using DAB substrate (MK210, TaKaRa) according to the manufacturer’s instructions. Finally, the sections were counterstained with hematoxylin, dehydrated using a graded series of ethanol concentrations, and cleared with xylene. The CD8 + and CD20 + cell counts within the tumor were counted separately. Three distinct random regions featuring the highest abundance of positive cells were identified using an x40 objective lens, and the average count was used for statistical analysis [ 28 ]. The membranous PD-L1 expression in the tumor cells was assessed at three random locations using an x40 objective lens, and the average count was used for statistical analysis [ 29 , 30 ]. HIF2α was assessed for positivity exclusively within the nuclei of tumor cells [ 31 ]. The ratios of c-MET, VEGFR2, and AXL expressions in the membrane and cytoplasm of tumor cells were determined [ 32 , 33 ]. HIF2α, c-MET, VEGFR2, and AXL were evaluated and analyzed in three random fields of view using an x40 objective lens. The number of positive cells and their levels of expression were automatically determined using a microscope (BZ-X710; KEYENCE). Statistical analysis Clinical characteristics were compared using the Mann-Whitney U test. Fisher's exact test was used to analyze the therapeutic effects of the ICIs and TKIs. Univariate and multivariate logistic regression analyses were performed to assess the relative contributions to CSS and OS. CSS and OS were estimated using the Kaplan-Meier method and Cox proportional hazard regression. All p-values were two-sided, and differences were considered statistically significant at p < 0.05. Data were analyzed using JMP Pro (v.17.0.0; SAS Institute, Cary, NC, USA). Declarations Competing interests The authors declare no competing interests. Author Contribution G.Y. contributed to data collection and analysis, table and figure preparation, reference collection, and manuscript writing. G.Y. and T.K. contributed to the data collection and analysis and supervised all activities. A.Y., M.T., Y.H., L.Y., S.N., Y.O., T.O., T.U., A.Y., Y.I., T.H., Y.Y., K.H., A.K., T.T., K.N., S.T., M.T., and N.N. supervised all the activities. The first draft of the manuscript was prepared by G. 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Kim, M. et al . Prognostic value of vascular endothelial growth factor (VEGF), VEGF receptor 2, platelet-derived growth factor-β (PDGF-β), and PDGF-β receptor expression in papillary renal cell carcinoma. Hum. Pathol. 61 , 78-89 (2017). Zucca, L. E. et al . Expression of tyrosine kinase receptor AXL is associated with worse outcome of metastatic renal cell carcinomas treated with sunitinib. Urol. Oncol. 36 , 11.e13–11.e21 (2018). Additional Declarations No competing interests reported. Supplementary Files SciRepSupplementaryInformation20240823.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4962940","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":357650994,"identity":"66def558-696f-4b6e-9e17-70a660fb8886","order_by":0,"name":"Gaku Yamamichi","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Gaku","middleName":"","lastName":"Yamamichi","suffix":""},{"id":357650995,"identity":"3c3c6d01-fed4-4fce-b771-c9d176402d43","order_by":1,"name":"Taigo Kato","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYBACCRDxAZkjAZNibMClhZmBcQbJWph5sGrBBSTbzx98bNt2T45B7PDBGwwVdfKS7QfYJBhq7BiYZ2O3Rponmdk4t63YmEE6LdmC4cxhw9k8CUAtx5IZGOccwKpFjiGZTTq3LSGxQTrHTIKx7QDjPIb8bxIMbAeAXkzAroX/MZu0JVgLUCVjW539PP4HQFv+4dYiLQG0hRFiCxtQC3PibIkEEAO3FskZj40Ne84lGLNJpxlbJJw5nDxzxgNmi8S+ZB5cfpE4n/jwwY+yBDl+6eSHNz5U1NnOOJ/AeOPDNzs5QxwhBgdsIALuEiCDx3AGLrU4gTzBSB0Fo2AUjIIRAgDIBFBS4VuAogAAAABJRU5ErkJggg==","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Taigo","middleName":"","lastName":"Kato","suffix":""},{"id":357650996,"identity":"9ab2be91-2682-4147-bad5-4d3f956bb989","order_by":2,"name":"Akihiro Yoshimura","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Akihiro","middleName":"","lastName":"Yoshimura","suffix":""},{"id":357650998,"identity":"6c376394-5209-4bce-9562-fd585f9fa990","order_by":3,"name":"Masaru Tani","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Masaru","middleName":"","lastName":"Tani","suffix":""},{"id":357651000,"identity":"fa8fdd1a-d3a4-46fc-9b7f-0d0ced53363c","order_by":4,"name":"Yuki Horibe","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Horibe","suffix":""},{"id":357651002,"identity":"4f80c29c-12d7-4aa7-b149-43268381bff5","order_by":5,"name":"Yutong Liu","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yutong","middleName":"","lastName":"Liu","suffix":""},{"id":357651003,"identity":"110100b0-2a17-4274-b937-8716a6382902","order_by":6,"name":"Nesrine Sassi","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nesrine","middleName":"","lastName":"Sassi","suffix":""},{"id":357651004,"identity":"6334a916-af77-428c-ab54-b13a006b59ca","order_by":7,"name":"Yohei Okuda","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yohei","middleName":"","lastName":"Okuda","suffix":""},{"id":357651005,"identity":"9abe1879-b349-41ee-be59-ccc49f6d5ea8","order_by":8,"name":"Toshiki Oka","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Toshiki","middleName":"","lastName":"Oka","suffix":""},{"id":357651006,"identity":"2eea7387-b0fd-46d9-b77b-b4307a7cb907","order_by":9,"name":"Toshihiro Uemura","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Toshihiro","middleName":"","lastName":"Uemura","suffix":""},{"id":357651009,"identity":"24a97202-becd-47e3-a860-455528f0f134","order_by":10,"name":"Akinaru Yamamoto","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Akinaru","middleName":"","lastName":"Yamamoto","suffix":""},{"id":357651010,"identity":"4ae76479-4a14-4220-8fd4-65bd803068d5","order_by":11,"name":"Yu Ishizuya","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ishizuya","suffix":""},{"id":357651011,"identity":"b526b998-41ba-44c5-bffd-79969958f05d","order_by":12,"name":"Takuji Hayashi","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Takuji","middleName":"","lastName":"Hayashi","suffix":""},{"id":357651012,"identity":"f6da5c4f-157b-4139-9e07-6243bdbdb0e5","order_by":13,"name":"Yoshiyuki Yamamoto","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yoshiyuki","middleName":"","lastName":"Yamamoto","suffix":""},{"id":357651014,"identity":"e42ada76-129c-4229-952e-26dc3c66dd9d","order_by":14,"name":"Koji Hatano","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Koji","middleName":"","lastName":"Hatano","suffix":""},{"id":357651016,"identity":"59a1ea3f-e72b-49d1-b99b-f11433b897ff","order_by":15,"name":"Atsunari Kawashima","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Atsunari","middleName":"","lastName":"Kawashima","suffix":""},{"id":357651017,"identity":"c80a76aa-5bc1-4d12-bef3-6649e268cfc8","order_by":16,"name":"Tetsuya Takao","email":"","orcid":"","institution":"Osaka General Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Tetsuya","middleName":"","lastName":"Takao","suffix":""},{"id":357651018,"identity":"aa7a1982-b0bc-4430-9157-0c6506035272","order_by":17,"name":"Kensaku Nishimura","email":"","orcid":"","institution":"National Hospital Organization Osaka National Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kensaku","middleName":"","lastName":"Nishimura","suffix":""},{"id":357651020,"identity":"53f4436c-94a4-4ef2-a102-961c1de95695","order_by":18,"name":"Shingo Takada","email":"","orcid":"","institution":"Osaka Police Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shingo","middleName":"","lastName":"Takada","suffix":""},{"id":357651021,"identity":"b9b4f22c-ed61-4547-8f34-cd1f9d1e7e72","order_by":19,"name":"Masao Tsujihata","email":"","orcid":"","institution":"Osaka Rosai Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masao","middleName":"","lastName":"Tsujihata","suffix":""},{"id":357651022,"identity":"db5e1c08-7d45-439d-aee8-262f7ed6bb9a","order_by":20,"name":"Norio Nonomura","email":"","orcid":"","institution":"Osaka University Graduate School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Norio","middleName":"","lastName":"Nonomura","suffix":""}],"badges":[],"createdAt":"2024-08-23 09:01:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4962940/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4962940/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66762820,"identity":"60499eb8-1fe6-45b3-833f-d655f619f87a","added_by":"auto","created_at":"2024-10-16 09:00:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31853,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves of cancer-specific survival (a) and overall survival (b) for patients with metastatic renal cell carcinoma after second-line treatment with ICIs and TKIs.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/6b6eace4edbdffd233cbcd84.png"},{"id":66762821,"identity":"e9ae670d-c356-47a6-b55f-6a2fcf84ea27","added_by":"auto","created_at":"2024-10-16 09:00:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60878,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves of cancer-specific survival and overall survival for patients with metastatic renal cell carcinoma stratified by IMDC risk classification (a, c) and ALP concentration (b, d).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/8fcc67f5f43383a4ebee31fd.png"},{"id":66762825,"identity":"1f6e2854-e7fa-44a6-90ca-80d98f6b7bc1","added_by":"auto","created_at":"2024-10-16 09:00:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1103279,"visible":true,"origin":"","legend":"\u003cp\u003eImmunohistochemical staining results for the primary site of clear cell renal cell carcinoma. Scale bar represents 200 μm.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/563fea9556a09b88011a8977.png"},{"id":66762822,"identity":"527f037b-9a00-455b-b94a-f140818a8d95","added_by":"auto","created_at":"2024-10-16 09:00:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1029198,"visible":true,"origin":"","legend":"\u003cp\u003eImmunohistochemical staining results for the bone metastatic lesion of clear cell renal cell carcinoma. Scale bar represents 200 μm.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/3642488a4a598578c48dc3e7.png"},{"id":66762824,"identity":"689cf0f3-2a7d-4072-b70c-941947507c86","added_by":"auto","created_at":"2024-10-16 09:00:48","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":92963,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of expression levels of CD8, CD20, PD-L1, HIF2α, c-MET, VEGFR2, and AXL in the primary tumor and bone metastatic lesions of clear cell renal cell carcinoma.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/0bfdefd09042d6ca3dfd2076.png"},{"id":68212915,"identity":"99aa67c7-05ab-46a9-96bc-be513680653b","added_by":"auto","created_at":"2024-11-04 18:16:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3203713,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/c8be4130-9695-4478-bcec-149ce4c5aa03.pdf"},{"id":66763723,"identity":"cca4ecf6-3a97-41e2-9e1d-7c1468941dc1","added_by":"auto","created_at":"2024-10-16 09:08:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21242,"visible":true,"origin":"","legend":"","description":"","filename":"SciRepSupplementaryInformation20240823.docx","url":"https://assets-eu.researchsquare.com/files/rs-4962940/v1/db9a262ae7c7b0f8bab78553.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The efficacy of second-line nivolumab versus tyrosine kinase inhibitors for renal cell carcinoma with bone metastases: A multi-institutional retrospective study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) ranks as the fourteenth most frequently diagnosed cancer globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In 2020, an estimated 431,288 new cases of RCC and associated 179,368 deaths were reported. With the advances in imaging and inspection technology, the incidence of RCC has been increasing at an annual rate of 1\u0026ndash;2% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Immune checkpoint inhibitor (ICI) combination therapy, such as ICI plus ICI or ICI plus tyrosine kinase inhibitor (TKI), has become commonly used as the first-line systemic treatment for metastatic RCC (mRCC). After the refractoriness to ICI combination therapy, a majority of patients developed progressive disease requiring subsequent TKIs or nivolumab [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. So far, although comparable efficacies of axitinib and nivolumab as secondary treatments for mRCC have been reported [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], There are limited real-world clinical reports on second-line treatments for RCC.\u003c/p\u003e \u003cp\u003eAmong various types of metastases, RCC is especially susceptible to bone metastasis (BM), which occurs in approximately 30% of patients with mRCC [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. BM may lead to severe complications, including skeletal-related events, and is a poor prognostic factor for patients with mRCC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Negishi et al. reported that the effectiveness of ICI against BM site in mRCC is limited with only 5% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. On the other hand, the METEOR trial reported that cabozantinib, a well-known TKI, led to a better prognosis of mRCC with BM than everolimus after at least one previous TKI [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the efficacy of cabozantinib in treating bone metastatic lesion remains unclear. Therefore, this study aimed to compare the treatment efficacies of second-line TKIs and nivolumab in patients with RCC and BM. Additionally, we evaluated the expression of receptors targeted by cabozantinib, the immune microenvironment, and hypoxic conditions using immunohistochemistry to compare primary tumors and BM lesions.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eThe clinicopathological characteristics and outcomes of the 87 patients with mRCC and BM included in the study are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The median age of the patients in the nivolumab and TKI groups was 66 years (range, 29\u0026ndash;87 years) and 69 years (range, 33\u0026ndash;84 years), respectively. The most prevalent histological type was clear cell carcinoma, observed in 25 (86%) and 47 (81%) patients treated with nivolumab and TKI, respectively. The nivolumab group predominantly comprised patients with poor International Metastatic Renal Cell Carcinoma Database (IMDC) risk (52.0%), whereas 76.0% of patients treated with a TKI were classified as having favorable and intermediate risk. The most commonly prescribed TKI was axitinib (n\u0026thinsp;=\u0026thinsp;35, 60%), followed by cabozantinib (n\u0026thinsp;=\u0026thinsp;14, 24%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient characteristics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNivolumab\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTKI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;58)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003cem\u003e-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (29\u0026ndash;87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (33\u0026ndash;84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, Male: Female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (83%): 5 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (74%): 15 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistopathology\u003c/p\u003e \u003cp\u003eClear cell RCC\u003c/p\u003e \u003cp\u003ePapillary RCC\u003c/p\u003e \u003cp\u003eOthers/unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (86%)\u003c/p\u003e \u003cp\u003e1 (3%)\u003c/p\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (81%)\u003c/p\u003e \u003cp\u003e3 (5%)\u003c/p\u003e \u003cp\u003e8 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003cp\u003e1.0\u003c/p\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMDC risk\u003c/p\u003e \u003cp\u003eFavorable / Intermediate\u003c/p\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (48%)\u003c/p\u003e \u003cp\u003e15 (52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (76%)\u003c/p\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious partial or total nephrectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal therapy for BM\u003c/p\u003e \u003cp\u003eradiation therapy\u003c/p\u003e \u003cp\u003esurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (59%)\u003c/p\u003e \u003cp\u003e4 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (59%)\u003c/p\u003e \u003cp\u003e4 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients with metastasis other than bone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation of metastatic sites\u003c/p\u003e \u003cp\u003eBone\u003c/p\u003e \u003cp\u003eLung\u003c/p\u003e \u003cp\u003eLymph node\u003c/p\u003e \u003cp\u003eLiver\u003c/p\u003e \u003cp\u003eBrain\u003c/p\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (100%)\u003c/p\u003e \u003cp\u003e16 (55%)\u003c/p\u003e \u003cp\u003e11 (38%)\u003c/p\u003e \u003cp\u003e6 (21%)\u003c/p\u003e \u003cp\u003e3 (10%)\u003c/p\u003e \u003cp\u003e9 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (100%)\u003c/p\u003e \u003cp\u003e39 (67%)\u003c/p\u003e \u003cp\u003e12 (21%)\u003c/p\u003e \u003cp\u003e11 (19%)\u003c/p\u003e \u003cp\u003e7 (12%)\u003c/p\u003e \u003cp\u003e13 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003cp\u003e0.35\u003c/p\u003e \u003cp\u003e0.12\u003c/p\u003e \u003cp\u003e1.0\u003c/p\u003e \u003cp\u003e1.0\u003c/p\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of BM\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMultiple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (14%)\u003c/p\u003e \u003cp\u003e25 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (21%)\u003c/p\u003e \u003cp\u003e46 (79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior 1st line treatment\u003c/p\u003e \u003cp\u003eTKI\u003c/p\u003e \u003cp\u003eICI\u0026thinsp;+\u0026thinsp;TKI\u003c/p\u003e \u003cp\u003eICI\u0026thinsp;+\u0026thinsp;ICI\u003c/p\u003e \u003cp\u003eInterferon-α\u003c/p\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (86%)\u003c/p\u003e \u003cp\u003e4 (14%)\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (45%)\u003c/p\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003cp\u003e4 (7%)\u003c/p\u003e \u003cp\u003e8 (14%)\u003c/p\u003e \u003cp\u003e7 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e0.40\u003c/p\u003e \u003cp\u003e0.30\u003c/p\u003e \u003cp\u003e0.048\u003c/p\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of second-line TKI treatment\u003c/p\u003e \u003cp\u003eAxitinib\u003c/p\u003e \u003cp\u003eCabozantinib\u003c/p\u003e \u003cp\u003eSorafenib\u003c/p\u003e \u003cp\u003eSunitinib\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (60%)\u003c/p\u003e \u003cp\u003e14 (24%)\u003c/p\u003e \u003cp\u003e5 (9%)\u003c/p\u003e \u003cp\u003e4 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone modifying agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (69%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e287 (153\u0026ndash;1632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288 (135\u0026ndash;3406)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e218 (125\u0026ndash;703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (97\u0026ndash;2154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2 (1.4\u0026ndash;32.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5 (1.3\u0026ndash;16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservation period from the Second-line therapy (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.0 (1\u0026ndash;73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5 (1\u0026ndash;93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eTKI\u003c/em\u003e, tyrosine kinase inhibitor; \u003cem\u003eRCC\u003c/em\u003e, renal cell carcinoma; \u003cem\u003eIMDC\u003c/em\u003e, International Metastatic Database Consortium; \u003cem\u003eBM\u003c/em\u003e, bone metastasis; \u003cem\u003eICI\u003c/em\u003e, immune checkpoint inhibitor; \u003cem\u003eALP\u003c/em\u003e, alkaline phosphatase; \u003cem\u003eLDH\u003c/em\u003e, lactate dehydrogenase; \u003cem\u003eNLR\u003c/em\u003e, neutrophil-to-lymphocyte ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinical outcomes of patients treated with second-line nivolumab or tyrosine kinase inhibitors\u003c/h2\u003e \u003cp\u003eOverall, the median follow-up durations of patients treated with nivolumab and TKI groups were 7.0 (range, 1\u0026ndash;73) and 11.5 (range, 1\u0026ndash;93) months, respectively. There were no significant differences between the cancer-specific survival (CSS) and overall survival (OS) of the patients treated with nivolumab and a TKI (p\u0026thinsp;=\u0026thinsp;0.76 and p\u0026thinsp;=\u0026thinsp;0.55, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Multivariate analyses revealed that poor risk based on the IMDC classification and high serum alkaline phosphatase (ALP) concentration (\u0026ge;\u0026thinsp;288 U/L) were significantly associated with reduced OS (hazard ratio [HR]\u0026thinsp;=\u0026thinsp;3.24, 95% CI; 1.84\u0026ndash;5.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; HR\u0026thinsp;=\u0026thinsp;1.78, 95% CI; 1.05\u0026ndash;3.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Accordingly, OS was significantly shorter for patients with poor risk based on the IMDC classification and high serum ALP concentration (\u0026ge;\u0026thinsp;288 U/L) (HR\u0026thinsp;=\u0026thinsp;3.58, 95% CI; 2.08\u0026ndash;6.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; HR\u0026thinsp;=\u0026thinsp;2.01, 95% CI; 1.21\u0026ndash;3.35, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of OS after the introduction of second-line therapy.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;66\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026ndash;2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u0026ndash;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u0026ndash;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIMDC risk\u003c/p\u003e \u003cp\u003eFavorable / Intermediate\u003c/p\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e3.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.08\u0026ndash;6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.84\u0026ndash;5.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal therapy for BM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.73\u0026ndash;2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetastasis other than bone\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u0026ndash;2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of BM\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMultiple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72\u0026ndash;2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2nd line therapy\u003c/p\u003e \u003cp\u003eICI\u003c/p\u003e \u003cp\u003eTKI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u0026ndash;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone modifying agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.65\u0026ndash;2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (U/L)\u003c/p\u003e \u003cp\u003eLow (\u0026lt;\u0026thinsp;288)\u003c/p\u003e \u003cp\u003eHigh (\u0026ge;\u0026thinsp;288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21\u0026ndash;3.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05\u0026ndash;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH (U/L)\u003c/p\u003e \u003cp\u003eLow (\u0026lt;\u0026thinsp;215)\u003c/p\u003e \u003cp\u003eHigh (\u0026ge;\u0026thinsp;215)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026ndash;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u0026ndash;2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR\u003c/p\u003e \u003cp\u003eLow (\u0026lt;\u0026thinsp;3.5)\u003c/p\u003e \u003cp\u003eHigh (\u0026ge;\u0026thinsp;3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003cp\u003e1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u0026ndash;2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eOS\u003c/em\u003e, overall survival; \u003cem\u003eHR\u003c/em\u003e, hazard ratio; \u003cem\u003eTKI\u003c/em\u003e, tyrosine kinase inhibitor; \u003cem\u003eIMDC\u003c/em\u003e, International Metastatic Database Consortium, \u003cem\u003eBM\u003c/em\u003e, bone metastasis, \u003cem\u003eICI\u003c/em\u003e, immune checkpoint inhibitor; \u003cem\u003eALP\u003c/em\u003e, alkaline phosphatase; \u003cem\u003eLDH\u003c/em\u003e, lactate dehydrogenase; \u003cem\u003eNLR\u003c/em\u003e, neutrophil-to-lymphocyte ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo exclude the influence of radiation therapy on BM site, we examined 72 patients with untreated BM site (Supplementary Table S2). Comparison of the outcomes of second-line treatment for BM according to the MD Anderson (MDA) criteria showed that the overall response rate (ORR) was significantly higher for the TKI group (29.2%) than for the nivolumab group (4.2%) (p\u0026thinsp;=\u0026thinsp;0.014) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This indicated that TKIs may be more effective than nivolumab for treatment-na\u0026iuml;ve BM.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall response rate of second-line treatment to locally untreated BM according to the MDA criteria and RECIST 1.1.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTKI (n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNivolumab (n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDA criteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eORR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14/48 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/24 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRECIST 1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eORR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7/48 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/24 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eCR\u003c/em\u003e, complete response; \u003cem\u003ePR\u003c/em\u003e, partial response; \u003cem\u003eSD\u003c/em\u003e, stable disease; \u003cem\u003ePD\u003c/em\u003e, progressive disease; \u003cem\u003eORR\u003c/em\u003e, overall response rate.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSignificant difference between the tumor microenvironments of primary tumors and bone metastasis\u003c/h2\u003e \u003cp\u003eNext, we investigated the presence of tumor-infiltrated immune cells and several molecules targeted by TKIs in tumor microenvironment in primary tumors and BM sites. Representative immunohistochemistry results are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. As a result, we found a significant increase of the VEGFR2-positive cells in the BM lesions (p\u0026thinsp;=\u0026thinsp;0.048). In addition, we confirmed that the CD8\u003csup\u003e+\u003c/sup\u003e T-cells and CD20\u003csup\u003e+\u003c/sup\u003e B-cell counts were higher in primary tumors (p\u0026thinsp;=\u0026thinsp;0.075 and p\u0026thinsp;=\u0026thinsp;0.10, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Collectively, these results indicate that primary tumors and BM have different tumor microenvironments, affecting the efficacy of TKIs and nivolumab therapies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe guidelines of the European Association of Urology recommend ICI combination therapy as the first-line treatment for mRCC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. There is no established drug selection for the second-line treatment of mRCC, but several studies suggest that second-line treatment consists of nivolumab monotherapy or TKI [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. On the other hand, the effectiveness of TKI and ICI greatly depends on the tumor microenvironment, but it varies in RCC due to several patient factors including tumor heterogeneity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. For RCC, the characteristics of metastatic tumor cells and the surrounding microenvironment may not always match those of primary tumors [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, a comparative analysis of the molecular biomarker expression profiles of primary and metastatic specimens, such as bone, should be performed [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe bone matrix is inherently rich in growth factors, making it a favorable and fertile environment for metastatic tumors, irrespective of the primary tumor type. BM is considered a poor prognostic factor for patients with mRCC [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In the microenvironment of BM lesions, regulatory T-cells and myeloid-derived suppressor cells are abundant, which suppresses tumor immunity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which may lead to poor prognosis for mRCC patients with BM. Moreover, in RCC, inactivation of the von Hippel-Lindau tumor suppressor gene is common and leads to an increase in hypoxia-inducible factor-alpha, resulting in the overexpression of vascular endothelial growth factor (VEGF) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This growth factor promotes tumor angiogenesis and plays a crucial role in the invasion and metastasis of RCC. On the other hand, tyrosine kinase is an important enzyme in intracellular signal transduction, and binding of VEGF to the VEGF receptor (VEGFR) increases receptor tyrosine kinase activity and initiates intracellular signal transduction. Considering above, we aimed to compare the efficacies of nivolumab and TKIs as second-line treatments for patients with mRCC with BM, elucidating the differences between the tumor microenvironments of primary and BM lesions.\u003c/p\u003e \u003cp\u003eIn this study, we present two novel findings. First, we found that TKIs were more effective as second-line treatments for BM lesions in RCC than nivolumab monotherapy, as evidenced by the higher ORR at the BM sites (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Previous studies have shown a significant difference in the treatment efficacy of ICI across metastatic lesions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In a large-scale tumor-agnostic study, BM lesions were associated with resistance to ICI [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In patients with mRCC treated with second-line nivolumab, treatment efficacy varies significantly with the metastatic site [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], with bone exhibiting a particularly low ORR of 5%, compared to 36% for lung and 50% for liver metastases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In patients with mRCC treated with nivolumab as second-line therapy or beyond, BM, rather than lung or lymph node metastases, was associated with poor progression-free survival (PFS) and OS [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In the present study, an elevated serum ALP concentration, which reflects the overall deterioration of systemic conditions such as BM volume, was an independent poor prognostic factor for second-line treatment of mRCC with BM (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Considering above, TKIs are considered a promising option for patients with mRCC with BM and without other visceral metastases.\u003c/p\u003e \u003cp\u003eSecond, VEGFR2 expression was higher in BM lesions than in primary tumors, and BM lesions showed a trend of decreased CD8\u003csup\u003e+\u003c/sup\u003e tumor-infiltrating T-lymphocytes and tumor-infiltrating CD20\u003csup\u003e+\u003c/sup\u003e B-cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which may contribute to the lower ORR of nivolumab than of TKI for BM lesions. Tao et al. reported that tumor-infiltrating B-lymphocytes in mRCC have been shown to recruit and activate CD8\u003csup\u003e+\u003c/sup\u003e tumor-infiltrating T-lymphocytes, thereby enhancing anti-tumor effects [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and this process is involved in the formation of tertiary lymphoid structures [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. TKIs are also considered more likely to be effective for cases of RCC with high expression of VEGFR2 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In this study, we described a significant increase of VEGFR2- positive cells in BM sites, demonstrating the potential benefits of TKI in patients with mRCC with BM. Especially, considering that cabozantinib displayed the strongest inhibition toward VEGFR2 among several types of TKIs, cabozantinib may likely contributes to the enhanced antitumor activity in BM [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study had several limitations. First, this was a retrospective study with a few cases. While it was a multicenter study including five hospitals, the number of patients with mRCC with BM receiving second-line treatment was limited, and even fewer underwent surgery for BM lesions. Therefore, future studies with larger sample sizes and more extensive designs are warranted. Second, we used the MDA criteria and Response Evaluation Criteria in Solid Tumors to evaluate the treatment efficacy for BM lesions, but there is currently no consensus on the best response evaluation system for them [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Notwithstanding, several studies have used the MDA criteria to evaluate BM lesions [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we revealed that TKIs may have higher efficacy than nivolumab against BM lesion and poor IMDC risk classification and elevated serum ALP concentrations are associated with worse prognosis in patients with mRCC and BM receiving second-line therapy. In patients with mRCC with metastases limited to the bone, TKIs may be more effective than nivolumab.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003e We retrospectively reviewed the clinical data of 721 patients with RCC and analyzed the clinicopathological data of 87 patients with mRCC with BM who initiated second-line treatment with nivolumab (n\u0026thinsp;=\u0026thinsp;29) or TKI (n\u0026thinsp;=\u0026thinsp;58) at Osaka University Hospital, Osaka Police Hospital, Osaka General Medical Center, Osaka Rosai Hospital, and Osaka National Hospital between January 2008 and December 2023. BM was diagnosed using computed tomography with MRI or bone scintigraphy, which was performed as needed [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The TKIs included sunitinib, axitinib, cabozantinib, sorafenib, and pazopanib. The dosage and administration intervals followed standard treatment protocols.\u003c/p\u003e \u003cp\u003e The following patient data were collected from the hospital records of the patients: age, sex, histopathology of RCC, IMDC classification for first-line therapy, previous nephrectomy, local therapy for BM site, location of metastatic sites, number of BMs, first-line therapy regimen, type of second-line regimen, bone modifying agent, serum concentration of ALP, serum concentration of lactate dehydrogenase, neutrophil-lymphocyte ratio, best ORR for the second line therapy, second-line therapy CSS, and OS.\u003c/p\u003e \u003cp\u003eThe therapeutic efficacy of second-line treatment was assessed every 2\u0026ndash;3 months using computed tomography according to the Response Evaluation Criteria in Solid Tumors version 1.1 and MDA criteria [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The best response of each patient during treatment was determined and classified as complete response, partial response, stable disease, or progressive disease.\u003c/p\u003e \u003cp\u003e This study was approved by the Institutional Review Board of the Osaka University Hospital (# 018\u0026thinsp;\u0026minus;\u0026thinsp;0003). All procedures were conducted in accordance with the Declaration of Helsinki, and informed consent was obtained from all participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemical staining and quantification\u003c/h2\u003e \u003cp\u003eThe primary RCC tissue resected after total nephrectomy was stored as formalin-fixed paraffin-embedded tissue blocks. The resected RCC tissue from the BM site in the same patients was subjected to tris-ethylenediaminetetraacetic acid until tissue softening was observed. This was followed by paraffin fixation. Immunohistochemical staining was performed using 4 \u0026micro;m-thick paraffin-embedded tissue samples of primary RCC samples and BM tissues. The tissue samples were deparaffinized using xylene and a graded series of ethanol solutions and stained with eosin. Other sections were treated with EDTA buffer (pH 9.0) and activated by warming at 125\u0026deg;C for 30 seconds using a Pascal pressure chamber (S2800, Dako) for antigen activation treatment. Endogenous peroxidase activity was blocked by incubating the sections with 0.3% hydrogen peroxide for 5 min, followed by overnight incubation with primary antibodies against CD8 (1:100; ab17147, Abcam) as a marker for cytotoxic T-lymphocytes, CD20 (1:800; ab9475, Abcam) as a marker for B-cells, PD-L1 (clone 28\u0026thinsp;\u0026minus;\u0026thinsp;8, 1:200; ab205921, Abcam), HIF2α (1:200; ab243861, Abcam), c-MET (1:100; ab51067, Abcam), VEGFR2 (1:100; ab115805, Abcam), and AXL (1:2000; ab219651, Abcam) at 4\u0026deg;C. The EnVision\u0026thinsp;+\u0026thinsp;system horseradish peroxidase-labeled polyclonal anti-rabbit and anti-mouse antibody (DAKO) was used, and staining was performed using DAB substrate (MK210, TaKaRa) according to the manufacturer\u0026rsquo;s instructions. Finally, the sections were counterstained with hematoxylin, dehydrated using a graded series of ethanol concentrations, and cleared with xylene.\u003c/p\u003e \u003cp\u003eThe CD8\u003csup\u003e+\u003c/sup\u003e and CD20\u003csup\u003e+\u003c/sup\u003e cell counts within the tumor were counted separately. Three distinct random regions featuring the highest abundance of positive cells were identified using an x40 objective lens, and the average count was used for statistical analysis [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The membranous PD-L1 expression in the tumor cells was assessed at three random locations using an x40 objective lens, and the average count was used for statistical analysis [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. HIF2α was assessed for positivity exclusively within the nuclei of tumor cells [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The ratios of c-MET, VEGFR2, and AXL expressions in the membrane and cytoplasm of tumor cells were determined [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. HIF2α, c-MET, VEGFR2, and AXL were evaluated and analyzed in three random fields of view using an x40 objective lens. The number of positive cells and their levels of expression were automatically determined using a microscope (BZ-X710; KEYENCE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eClinical characteristics were compared using the Mann-Whitney U test. Fisher's exact test was used to analyze the therapeutic effects of the ICIs and TKIs. Univariate and multivariate logistic regression analyses were performed to assess the relative contributions to CSS and OS. CSS and OS were estimated using the Kaplan-Meier method and Cox proportional hazard regression. All p-values were two-sided, and differences were considered statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Data were analyzed using JMP Pro (v.17.0.0; SAS Institute, Cary, NC, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eG.Y. contributed to data collection and analysis, table and figure preparation, reference collection, and manuscript writing. G.Y. and T.K. contributed to the data collection and analysis and supervised all activities. A.Y., M.T., Y.H., L.Y., S.N., Y.O., T.O., T.U., A.Y., Y.I., T.H., Y.Y., K.H., A.K., T.T., K.N., S.T., M.T., and N.N. supervised all the activities. The first draft of the manuscript was prepared by G. Y. and T. K. All authors have read and approved the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003eThis study was supported by JSPS KAKENHI (grant number: 21K09396).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data presented in this study are available on request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBukavina, L. \u003cem\u003eet al\u003c/em\u003e. Epidemiology of renal cell carcinoma: 2022 update. \u003cem\u003eEur. Urol.\u003c/em\u003e \u003cstrong\u003e82\u003c/strong\u003e, 529\u0026ndash;542 (2022).\u003c/li\u003e\n \u003cli\u003eParosanu, A. I., Baston, C., Stanciu, I. M., Parlog, C. F.\u0026nbsp;＆\u0026nbsp;Nitipir, C. 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Oncol.\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 11.e13\u0026ndash;11.e21 (2018).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Renal cell carcinoma, bone metastasis, second-line treatment, nivolumab, tyrosine kinase inhibitor, overall survival","lastPublishedDoi":"10.21203/rs.3.rs-4962940/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4962940/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eImmune checkpoint inhibitor combination therapy has been standardized for first-line treatment for metastatic renal cell carcinoma (mRCC), leading to the changes in second-line treatment options such as nivolumab or tyrosine kinase inhibitors (TKIs). However, there have been few reports comparing the efficacy of these drugs in mRCC patients, especially with bone metastases (BM), which are associated with a poor prognosis. Therefore, we aimed to compare the efficacy of nivolumab and TKIs as second-line treatments for 87 mRCC patients with BM and the microenvironments of the primary tumor and BM lesions. Multivariate analysis revealed poor risk according to the IMDC classification (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and high serum ALP value (p\u0026thinsp;=\u0026thinsp;0.031) as worse prognostic factors, while there was no significant difference of overall survival between patients with nivolumab and TKIs. However, the objective response rate at BM lesions was significantly higher with TKIs than with nivolumab (p\u0026thinsp;=\u0026thinsp;0.014). Immunohistochemistry analysis also revealed that VEGFR2 expression was significantly higher at BM lesions compared to that in primary tumors, showing the potential benefit of TKIs over nivolumab in mRCC patients with BM. In conclusion, TKIs could be the promising second-line treatment for mRCC with metastasis limited to the bone.\u003c/p\u003e","manuscriptTitle":"The efficacy of second-line nivolumab versus tyrosine kinase inhibitors for renal cell carcinoma with bone metastases: A multi-institutional retrospective study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-16 09:00:43","doi":"10.21203/rs.3.rs-4962940/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eeda1661-6e43-436c-af63-1aeea25adfc8","owner":[],"postedDate":"October 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38044139,"name":"Biological sciences/Cancer/Cancer microenvironment"},{"id":38044140,"name":"Biological sciences/Cancer/Cancer therapy"},{"id":38044141,"name":"Biological sciences/Cancer/Metastases"},{"id":38044142,"name":"Biological sciences/Cancer/Urological cancer"}],"tags":[],"updatedAt":"2024-11-04T18:08:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-16 09:00:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4962940","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4962940","identity":"rs-4962940","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}