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ABSTRACT The 5-year survival rate of patients with metastatic renal cell carcinoma (mRCC) is <12% due to treatment failure. Therapeutic strategies that overcome resistance to modestly
effective drugs for mRCC, such as sorafenib (SF), could improve outcome in mRCC patients. SF is terminally biotransformed by UDP-glucuronosyltransferase-1A9 (A9) mediated glucuronidation,
which inactivates SF. In a clinical-cohort and the TCGA-dataset, A9 transcript and/or protein levels were highly elevated in RCC specimens and predicted metastasis and overall-survival. This
suggested that elevated A9 levels even in primary tumors of patients who eventually develop mRCC could be a mechanism for SF failure. 4-methylumbelliferone (MU), a choleretic and
antispasmodic drug, downregulated A9 and inhibited SF-glucuronidation in RCC cells. Low-dose SF and MU combinations inhibited growth, motility, invasion and downregulated an invasive
signature in RCC cells, patient-derived tumor explants and/or endothelial-RCC cell co-cultures; however, both agents individually were ineffective. A9 overexpression made RCC cells resistant
to the combination, while its downregulation sensitized them to SF treatment alone. The combination inhibited kidney tumor growth, angiogenesis and distant metastasis, with no detectable
toxicity; A9-overexpressing tumors were resistant to treatment. With effective primary tumor control and abrogation of metastasis in preclinical models, the low-dose SF and MU combinations
could be an effective treatment option for mRCC patients. Broadly, our study highlights how targeting specific mechanisms that cause the failure of “old” modestly effective FDA-approved
drugs could improve treatment response with minimal alteration in toxicity profile. SIMILAR CONTENT BEING VIEWED BY OTHERS RESISTANCE TO TYROSINE KINASE INHIBITORS PROMOTES RENAL CANCER
PROGRESSION THROUGH MCPIP1 TUMOR-SUPPRESSOR DOWNREGULATION AND C-MET ACTIVATION Article Open access 22 September 2022 ENHANCED YB1/EPHA2 AXIS SIGNALING PROMOTES ACQUIRED RESISTANCE TO
SUNITINIB AND METASTATIC POTENTIAL IN RENAL CELL CARCINOMA Article Open access 19 August 2020 PDZK1 CONFERS SENSITIVITY TO SUNITINIB IN CLEAR CELL RENAL CELL CARCINOMA BY SUPPRESSING THE
PDGFR-Β PATHWAY Article 31 May 2024 INTRODUCTION The 5-year survival rate of patients with metastatic renal cell carcinoma (mRCC) is <12%1,2,3. Approximately 30% of patients have
metastasis at initial diagnosis and another ~30% develop metastasis, even after surgical intervention. Tyrosine kinase and mTOR inhibitors are approved as first- or second-line treatments
for mRCC4,5. Recently, immune checkpoint inhibitors were approved as a first-line treatment for treatment-naïve patients with intermediate or high-risk advanced RCC6,7. However, the majority
of patients experience tumor progression due to treatment resistance8,9,10. Sorafenib (SF) is a multi-kinase inhibitor with anti-angiogenic and anti-proliferative properties that was
FDA-approved for the treatment of mRCC3,11. However, due to its modest efficacy and treatment resistance, it is generally used only if other therapies have failed12,13,14. Studies have
implicated EGFR, c-Jun, PI3K/AKT, and Ras/Raf/MEK/ERK pathways, as well as, autophagy and/or epithelial-mesenchymal transition (EMT) in SF failure in the clinic15,16. However, no studies
have identified mechanisms directly relating to SF activity, nor inter-patient differences accounting for variable response to SF. 4-methylumbelliferone (MU; 7-hydroxy-4-methylcoumerin or
Hymecromone) has choleretic and antispasmodic properties, but it lacks the anti-sperminogenic and anti-aromatase activities of coumarin, as well as, the anticoagulant activity of
coumadin17,18,19,20,21,22. The maximum tolerated dose of MU in mice is 2.8–7.3 g/kg (NIOS registry). We and others have shown that inhibition of HA synthesis is the major mechanism of the
anticancer properties of MU as a single agent (IC50 = 0.4 mM)20,22,23,24,25. However, in RCC models, we showed that at plasma achievable levels (~5 µM) SF synergized with MU, and this
combination (SF + MU) had potent antitumor efficacy at doses where both agents individually were ineffective26,27,28,29. In the synergistic combination, MU doses were also 2–4-fold less than
its IC50 for inhibiting HA synthesis26. Therefore, the mechanism by which low doses of MU improve the efficacy of SF is independent of the inhibition of HA signaling that occurs at higher
doses20,22,23,24,25. SF is metabolized primarily in the liver; oxidative metabolism by Cytochrome P450 3A4 (CYP3A4) is the major pathway yielding SF N-oxide metabolites. CYP3A4 is also
expressed in the normal kidney in proximal tubular epithelial cells and in tumor cells in RCC30,31. As a minor pathway, in the liver SF also directly undergoes terminal biotransformation by
UDP-glucuronosyltransferase -1A9 (UGT1A9 or A9); A9 is also the major isoform in the kidney32,33,34,35. Glucuronidation is usually the terminal biotransformation and 15–19% of the SF dose is
excreted in urine as a glucuronide metabolite32,35. We evaluated if MU alters SF metabolism and improves its efficacy. Efficacy of SF + MU combination were evaluated in preclinical models
of RCC and endothelial cells, including a SF-resistant spontaneously metastatic model. Our study shows that A9 is overexpressed in RCC cells. MU alone and the combination downregulate A9
expression and inhibit SF glucuronidation. Tumors from patients who develop mRCC overexpress A9 transcript and protein. A9 expression correlates with clinical outcomes. Patient-derived
tumorspheroids and tumor models reveal that by downregulating A9, MU improves the antitumor and antimetastatic activities of SF. Therefore, SF + MU combination could be a potential treatment
for mRCC. RESULTS IDENTIFICATION OF A9 AS A POSSIBLE TARGET FOR SF + MU COMBINATION We previously demonstrated that the combination of SF with MU had synergistic efficacy against RCC cells
both in vitro and in a subcutaneous xenograft26. Optimal synergy between SF and MU was observed at concentrations (5 µM SF; 0.1–0.2 mM MU) where both agents individually were ineffective26.
The combinations (SF + MU: 5/0.1, 5/0.2) were equally effective in both VHL+ and VHL− RCC cell lines; VHL is a tumor suppressor that is frequently mutated or deleted in RCC36. Since both
CYP3A4 and A9 metabolize SF and are expressed in the kidney31,32,33,35,37,38, we investigated if their expression, and consequently, SF metabolism are altered in RCC cells treated with the
SF and MU combination (SF + MU). While A9 transcript and protein levels were about 15-fold elevated in RCC cell lines, CYP3A4 expression was similar in the normal kidney epithelial line
(HK-2) and RCC cells (Fig. 1a; Supplementary data: Fig. 1A, Table 1). Moreover, MU treatment alone downregulated A9 transcript and protein expression by 3 to 4-fold in 786-O and Caki-1 cells
(Fig. 1b, c). These cell lines were chosen as, Caki-1 is VHL+ and 786-O cell line is VHL−39. The SF + MU combination was similarly effective in downregulating A9 transcript expression (Fig.
1b). However, CYP3A4 expression was not affected by either MU or SF + MU treatments (Supplementary Fig. 1B). To study if downregulation of A9 by SF + MU treatment contributed to the
observed antitumor effects of the treatment, we stably expressed FLAG-tagged A9 protein in 786-O and Caki-1 cells (Fig. 1d). As shown in Fig. 1e, SF + MU treatment downregulated A9 protein
levels in the EV-transfectants. However, in A9-transfectants, which express A9 under a viral promoter, A9 levels remained largely unaffected by SF + MU treatment. A9 expression in the A9
transfectants was comparable to that found in RCC tissues (described below). Reverse HPLC analysis of SF or SF + MU treated 786-O EV cells showed inhibition of SF glucuronidation by the
treatment, whereas SF glucuronidation was only partially inhibited by the treatment in A9 transfectants (Supplementary Fig. 1C). A9-EXPRESSION IS INCREASED IN RCC SPECIMENS AND ASSOCIATES
WITH CLINICAL OUTCOME AND SF-RESISTANCE Since RCC cells showed increased A9 levels when compared to HK-2 cells, we measured A9 expression in tumor and NK tissues from RCC patients
(clinical-cohort; Supplementary Table 2). The majority of tumor specimens in the cohort were of clear cell (cc) RCC (58/83). Compared to NK specimens, A9 mRNA levels were about 6-fold
upregulated in ccRCC tumors; the increase in non-ccRCC tumors (papillary, chromophobe, collecting duct, and sarcomatoid), was ~3-fold (Fig. 2a). The increase in A9 levels in both ccRCC and
non-ccRCC tumors was also significantly higher when compared to oncocytoma (Fig. 2a). A9 levels were ~16-fold higher in small RCC tumors (<4 cm) compared to oncocytoma (Fig. 2b).
Moreover, A9 mRNA levels were 2.6-fold higher in tumors from patients who either had or developed metastasis during follow-up, than in tumors from patients who did not (Fig. 2c). In both
univariate and multivariate analyses, A9 levels were significant predictors of metastasis (Supplementary Tables 3, 4). Furthermore, Kaplan–Meier plots showed that high A9 levels
significantly stratified patients into higher risk for metastasis (Fig. 2d). In renal cells, A9 is localized within the endoplasmic reticulum34. Therefore, we analyzed A9 protein levels in
microsome preparations from NK, and kidney tumors from patients in the clinical cohort. A9 levels were 5–10-fold elevated in tumor microsomes and the increase was higher in tumors from
patients who developed metastasis (Fig. 2e). We next analyzed whether A9 expression correlated with clinical outcome in a ccRCC TCGA-cohort of 542 patients (Supplementary Table 2). Although
clinical outcome in terms of OS but not metastasis are available. Nevertheless, A9 levels significantly correlated with M-stage (_P_ = 0.0015; odds ratio = 2.08; 95% CI: 1.3–3.3). In
univariate analysis, A9 levels associated with OS and in multivariate analysis age, M-stage, and A9 levels were independent predictors of metastasis (Supplementary Tables 3, 4). Kaplan–Meier
plots showed that A9 levels significantly stratified patients for risk for death (Fig. 2f). A9-OVEREXPRESSION ATTENUATES CYTOTOXICITY OF SF + MU Since A9 expression was elevated in RCC
cells and tumors and downregulated by MU, we examined the sensitivity of EV and A9 transfectants to SF in combination with different doses of MU. In a dose-dependent manner, SF alone
inhibited proliferation of 786-O and Caki-1 EV transfectants with an IC50 of ~7.8 µM (Fig. 3a, b; Supplementary Table 5). Combination of SF with MU at 0.1 or 0.2 mM dose lowered the IC50 by
1.9- to 3.9-fold in 786-O and 1.6- to 3.5-fold in Caki-1 EV cells, respectively. A9 transfectants were slightly resistant to SF and the SF + MU combinations could lower the IC50 by only 24%
to 40% at 0.2 mM dose (Fig. 3a, b; Supplementary Table 5). To examine whether downregulation of A9 would sensitize the RCC cells to SF treatment, we generated A9 shRNA transfectants of both
786-O and Caki-1 cells using two different shRNA constructs. In these transfectants, A9 expression was downregulated by ≥80% (Supplementary Fig. 2A, Supplementary Table 1). When compared to
the control shRNA transfectants, IC50 for growth inhibition by SF alone was 2.5–3.1-fold lower in the A9 shRNA transfectants (Supplementary Fig. 2B, C; Supplementary Table 5). At the 400
b.i.d oral dose, the plasma level of SF is ~5 µM26,27,28,29. To determine if MU at 0.1 and 0.2 mM doses can improve the response to SF at the pharmacologically achievable dose of 5 µM, we
performed subsequent experiments using 5 µM SF + 0.1 mM MU (5/0.1) and 5 µM SF + 0.2 mM MU (5/0.2) combinations. At these doses, SF + MU inhibited clonogenic survival by 86–98.8% in
EV-transfectants, but A9-transfectants were resistant (Fig. 3c, d). In A9-shRNA transfectants, SF alone inhibited clonogenic survival by >90% (Supplementary Fig. 2D). RCC is known for its
pro-angiogenic environment in which tumor cells stimulate growth and motility of endothelial cells39. Therefore, we assessed the effect of SF + MU on the viability of HMEC-1 and HULEC-5a
microvessel endothelial cells, co-cultured with EV- and A9-transfectants of both 786-O and Caki-1 cells. When co-cultured with EV-transfectants, both HMEC-1 and HULEC-5a remained sensitive
to SF + MU; 84.8% reduction in viable cells at 5/0.2 dose. However, endothelial cells were resistant to treatment when co-cultured with A9-transfectants (Fig. 3e, Supplementary Fig. 2E). We
also evaluated the therapeutic potential of the SF + MU combination on two patient-derived RCC tumorspheres (TS1; TS2). SF + MU (5/0.2) inhibited the anchorage independent growth
(3D-culture) of TS1 and TS2 by 69–81%, while SF and MU alone were ineffective (Fig. 3f, g). Similarly, SF + MU caused >60% inhibition of TS2 growth in 2D-cultures (Fig. 3f, g). A9
EXPRESSION ATTENUATES CELL CYCLE ARREST AND APOPTOSIS INDUCTION BY SF + MU To further evaluate the mechanism of SF + MU-mediated inhibition of cell growth, we conducted cell cycle analysis
on SF + MU treated EV- and A9-transfectants. Within 24-h of treatment, SF + MU mainly caused G2-M arrest in 786-O EV-transfectants. At 5/0.2 SF + MU dose, 1.74-fold more cells were in the
G2-M phase. In Caki-1 EV-transfectants, SF + MU mainly induced cell cycle arrest in the G0-G1 phase, with a corresponding 1.6-fold decrease in the S-phase (Fig. 4a). However, SF + MU failed
to induce cell cycle arrest in A9-transfectants in both cell types. G2-M-arrest in 786-O EV-transfectants was validated by decreased p-Rb and cyclin E1 levels, and increased Cyclin B1 and
p-CDK1 levels (Fig. 4c). Similarly, decreased levels of p-Rb, Cyclin E1, Cyclin D1, and p-CDK2, and increased p21 levels, validated G0-G1 arrest in Caki-1 EV-transfectants by SF + MU (Fig.
4d). Contrarily, SF + MU had little to no effect on the expression of cell cycle markers in A9-transfectants. Since SF + MU treatment caused cell cycle arrest in EV-, but not
A9-transfectants, we further determined whether the combination could induce apoptosis in these transfectants. After 48-h of treatment SF + MU induced apoptosis by ≥8-fold in
EV-transfectants, compared to untreated control (Fig. 4b). However, SF + MU failed to induce apoptosis in A9-transfectants. Decreased levels of pro-survival marker Mcl-1, and increased
levels of pro-apoptotic markers cleaved PARP and cleaved caspase-3 validated induction of apoptosis by SF + MU in EV-transfectants; no changes in these markers were observed in
A9-transfectants (Fig. 4c, d). INHIBITION OF MOTILITY AND INVASION BY SF + MU IS ATTENUATED IN A9-TRANSFECTANTS In our previous study, we demonstrated that SF + MU effectively inhibited RCC
cell motility and invasion26. Therefore, we evaluated the effect of SF + MU treatment on chemotactic motility and invasive activity of EV- and A9-transfectants. Consistent with previous
results, SF + MU inhibited chemotactic motility by 3-fold and invasion by 4-fold in EV-transfectants, compared to untreated control (Fig. 5a, b). However, in A9-transfectants, SF + MU
inhibited chemotactic motility only by 1.2-fold, with no inhibition of invasive activity (Fig. 5a, b). Additionally, when compared to Ctrl-shRNA transfectants, SF alone inhibited wound
closure and invasive activity of A9-shRNA transfectants (Supplementary Fig. 3A–D). We have previously shown that HA receptors CD44 and RHAMM are elevated in RCC specimens and that their
expression correlates with metastasis40. CD44 and RHAMM have been shown to complex with MET, and promote an invasive phenotype including up-regulation of MMP-9 and Caveolin-1
expression22,23,41,42. Consistently, in EV-transfectants SF + MU downregulated CD44, RHAMM, phospho-MET, MMP-9, and Caveolin-1 levels by 2–10-fold (Fig. 5c, Supplementary Table 1). However,
SF + MU did not significantly downregulate their levels in A9-transfectants of both cell lines (Fig. 5c). A9 EXPRESSING CAKI-1 TUMORS ARE RESISTANT TO SF + MU: SUBCUTANEOUS MODEL Caki-1
tumors are resistant to SF treatment at 60-mg/kg, which is close to the maximum tolerated dose43. Previously, we showed that SF + MU combination inhibited Caki-1 tumor growth in a
subcutaneous xenograft, without serum or tissue toxicity26. Treatment of Caki-1 EV tumors with SF (30 mg/kg) and MU (100 or 200 mg/kg), starting when tumors reached ~ 100 mm3, inhibited
tumor growth. When compared to the vehicle group, tumor weight decreased by ~ 80% in SF + MU treatment groups, however, A9 tumors were resistant to the treatment (Fig. 5d, e). SF + MU
treatment did not affect animal weight (Supplementary Fig. 3E). EV and A9 tumors in both the vehicle and treatment groups were angiogenic and invaded skeletal muscle, microvessels, and
subcutaneous fat. However, EV tumors in the treatment group displayed pyknotic nuclei (Fig. 6a). As expected A9 was downregulated in the SF + MU treated EV tumors but the treatment did not
affect the expression in A9 tumors (Fig. 6a). SF + MU treated EV tumors were devoid of microvessels and Ki67 staining (proliferation index), but were positive for active (cleaved) caspase-3
staining. Vehicle-treated EV tumors and vehicle or SF + MU treated A9 tumors showed high microvessel density and Ki67 staining but low cleaved caspase-3 expression (Fig. 6a, Supplementary
Fig. 3F, G). Further analysis of tumor tissues, confirmed the in vitro results that when compared to the vehicle-treated group, SF + MU treatment downregulated phospho-MET, and CD44 levels
in EV tumors, but not in A9 tumors (Fig. 6b). SF is known to potently inhibit the kinase activity of c-Raf; IC50 of 6 nmol/L44. In SF + MU treated EV tumors, phospho-c-Raf (S338) levels were
downregulated by 2.5-fold, whereas, the levels were not consistently affected in A9 tumors (Fig. 6b). A9 EXPRESSION ATTENUATES ANTITUMOR AND ANTIMETASTATIC EFFICACY OF SF + MU: ORTHOTOPIC
MODEL For the orthotopic model, we used luciferase-expressing Caki-1 cells (Caki-1-luc). In the vehicle treatment group, Caki-1-luc EV tumors developed within 4–5 weeks post-surgery and
metastasis was visible at 5–6 weeks (end point; Fig. 6c). In the SF + MU group, 80% of mice developed tumors by 5–6 weeks but tumor growth was significantly slower and 80% of the mice did
not show visible metastasis in organ histology (Fig. 6c, e). The bioluminescence intensity of the EV tumors in the treatment group was 32-fold lower than in the vehicle group at 5–6 weeks
(_P_ = 0.008; Fig. 6d). All mice implanted with A9-transfectant developed tumors within 3 weeks and distant metastasis by 4–5 weeks. A9 tumors were resistant to treatment (Fig. 6c).
Histology confirmed primary kidney tumor and metastasis to lungs, liver and pancreas in the EV-vehicle and in A9-vehicle and treatment groups (Fig. 6e). In the EV-treatment group, histology
confirmed a small kidney tumor but metastasis was abrogated (Fig. 6e). These results demonstrate that the expression of A9 in RCC cells is responsible for SF resistance. However,
downregulation of A9 by MU sensitizes cells to SF treatment. Furthermore, SF + MU combination has potent antitumor and antimetastatic efficacy without toxicity. DISCUSSION Despite several
new classes of targeted agents being approved for therapy, treatment resistance is a major challenge that continues to drive the dismal five-year survival of mRCC patients1,2,3. In addition
to discovering new therapeutic agents, understanding why a drug fails may lead to strategies to overcome drug resistance. While pathways/targets such as, ERK, EGFR, PI3K/Akt, hypoxia,
autophagy, and EMT have been implicated in SF failure, none are targets of SF, nor do they target SF for metabolism/inactivation. These pathways also do not reveal why some patients respond
to SF treatment while others do not15,16,45. Our study demonstrates, for the first time, that upregulation of A9 in tumor tissues, may at least be one of the mechanisms contributing to SF
failure in the clinic. This is because glucuronidation of SF by A9 is the terminal inactivating SF biotransformation32,33,35. By downregulating A9, MU synergizes with SF to effectively
abrogate RCC growth and metastasis. The salient points of our study are as follows: 1. A9 levels are elevated in RCC tissues/cells and potentially predict metastasis in RCC patients. 2. RCC
cells are able to glucuronidate SF. 3. By downregulating A9, MU blocks inactivation of SF, and consequently, improves its antitumor and antimetastatic efficacy. 4. Since the combination is
effective at low doses, where both drugs individually are ineffective, it should minimize off-target effects and toxicity. Our results demonstrate that SF would have modest efficacy when
used as a treatment for mRCC. This is because A9 levels are significantly elevated in tumors from patients who either have or will develop metastasis and SF is used for treating mRCC. Data
on RCC cell lines show that A9 levels are highly upregulated in RCC cells when compared to NK epithelial cells. Upregulation of A9 in RCC cells was rather unexpected, since A9 is the major
UGT enzyme in the kidney and a study on 26 kidney specimens reported downregulation of A9 in kidney tumors when compared to NK tissues38. However, in a clinical cohort of 134 specimens our
study demonstrates that A9 levels are highly elevated in different types of RCC, as compared to NK and oncocytoma. Distinguishing between small renal tumors (<4 cm) and oncocytoma is
clinically significant46. Since A9 levels in small renal tumors are ~16-fold higher than in oncocytoma, increased A9 levels may be of value in percutaneous biopsy tissue. At present, it is
unclear why A9 is upregulated in invasive tumors. It is possible that detoxification of metabolic byproducts by terminal A9-mediated glucuronidation enhances tumor cell survival. Since mRCC
is rarely biopsied, we could not analyze A9 expression in metastatic tissues. Nevertheless, increased A9 expression in RCC tumors that metastasize implies that mRCC may be inherently less
sensitive to SF treatment. This is further corroborated by the ccRCC TCGA cohort in which A9 expression correlates with M-stage and is a predictor of OS. Although MU is known to inhibit HA
synthesis20,22,23,24,25, downregulation of A9 by MU at doses where MU does not inhibit HA synthesis reveals that A9 is the target of MU at low doses. A9 expression under a viral promoter
attenuates the inhibitory effects of SF + MU against RCC cells in both _in vitro_ and xenograft models. This further establishes that A9 downregulation by MU is a key reason for the observed
anti-RCC efficacy of the SF + MU combination. Re-sensitization of RCC cells to SF alone by shRNA-mediated downregulation of A9 is again supportive of A9-overexpression plausibly
contributing to SF unresponsiveness in RCC cells and mRCC. SF + MU combination inhibited the growth and invasive activities of RCC cells and of endothelial cells co-cultured with RCC cells.
Furthermore, ectopic expression of A9 not only attenuated the inhibitory effects of the combination in RCC cells, but also protected endothelial cells from these effects. This suggests that
by overexpressing A9, RCC cells ensure an angiogenic microenvironment that is resistant to SF treatment. Furthermore, the increased efficacy of SF due to A9 downregulation is the basis for
the high efficacy of SF + MU in preclinical models of RCC. Indeed, tumors in the SF + MU treatment groups grew only about 100–200 mm3, the size beyond which tumors require angiogenesis for
growth and dissemination. SF + MU also inhibited the growth of patient-derived tumorspheres. This demonstrates that assessment of the efficacy of SF + MU in patient-derived tumorspheres
together with the evaluation of A9 protein expression in tumor microsomes, could be exploited for clinical translation of the combination. Effective treatments that directly target drug
resistance could improve the outcome of mRCC patients. The orthotopic Caki-1-luc model has 100% tumor-take and with distant organ metastasis developing within 5–6 weeks. RCC primarily
metastasizes via venous circulation, with frequent sites of metastases being lung, bone, lymph node, and liver; atypical sites include adrenal glands, brain, and pancreas47. In the
Caki-1-luc model, tumors metastasized to lungs, liver, and pancreas. In this model bone metastasis was not visible, probably because the experimental end point (5–6 weeks) due to large
kidney mass, was reached prior to frank bone metastasis. In this aggressive model, SF + MU oral treatment slowed tumor growth and abrogated metastasis in the majority of animals. This
demonstrates that SF + MU may be effective as an antimetastatic treatment. The unresponsiveness of A9 tumors to the combination further demonstrates that A9 downregulation is a key reason
for the high efficacy of SF + MU in RCC models. Downregulation of A9 by MU raises the possibility that the combination may be associated with increased SF-related toxicity. However, SF is
primarily metabolized by the CYP3A4 pathway in the liver32,33,35. Toxicity may also be less of a concern since due to synergy, lower doses of SF and MU are needed to achieve therapeutic
response. Moreover, in both the present and our published studies, SF + MU did not cause serum or tissue toxicity and mice did not lose weight26. Since SF is FDA-approved and MU is available
as OTC-supplement, their combination is potentially a targeted, minimally toxic, and effective treatment against mRCC. Broadly, our study highlights how targeting specific mechanisms that
cause the failure of “old” modestly effective FDA-approved drugs, could improve treatment responsiveness in cancer patients with minimal alteration in toxicity profile. MATERIALS AND METHODS
CELL LINES AND REAGENTS Human RCC cell lines (786-O, Caki-1, and 769-P), immortalized normal kidney cell line (HK-2) and human dermal (HMEC-1) and lung (HULEC-5a) microvessel endothelial
cells were obtained from American Type Culture Collection® and cultured as per ATCC recommendations. Cell lines were authenticated and tested for mycoplasma contamination by Genetica DNA
Laboratories Inc., Cincinnati, OH. All experiments were conducted within ten passages. Reagents, primers, constructs and antibodies are described in Supplementary Table 6. CLINICAL SPECIMENS
AND TUMORSPHERES: CLINICAL-COHORT Eighty-three RCC and 51 normal kidney (NK) specimens were obtained from patients undergoing nephrectomy for RCC (Supplementary Table 2). Specimens were
obtained at University of Miami, Miller School of Medicine under an approved institutional review board protocol and after obtaining informed patient consent. De-identified specimens and
de-linked data were transferred to Augusta University under an approved protocol. All clinical specimens are consecutively numbered such that investigators performing the assays were blinded
from clinical information. Analysis was performed after all samples were tested. Tumorspheres were established from fresh clinical specimens collected at Augusta University under an
approved protocol. Tumorspheres were established under ultra-low attachment conditions in MammoCultTM Medium. For proliferation assays primary cultures were either plated in 2D adherent or
3D ultra-low attachment conditions and treated 24 h later. TCGA COHORT TCGA data on 542 clear cell RCC specimens was accessed through UCSC-Xena Browser and included demographic/pathologic
parameters, overall survival (OS) and RNA-Seq data. Since the UGT1A 8–10 isoforms have 96% nucleotide sequence identity, A9 probes should recognize other isoforms. Therefore, data of all
three isoforms was utilized for reporting the association of A9 clinical outcome. GLUCURONIDATION ASSAY In all, 786-O cells cultured in growth medium were incubated with MU (0.2 mM) for 8.5
h followed by incubation with SF for 12 h. The cells and media were extracted in equal volume of acetonitrile, followed by extraction in ethylacetate. Sorafenib control was extracted 5 min
after adding on the cells. SF was also incubated with UGT1A9 supersomes at 37 °C for 25 min in an UGT assay buffer (BD Biosciences). Ethylacetate extracts of all samples were dried,
resuspended in acetonitrile, and subjected to reverse phase HPLC on a C18 column; gradient: acetonitrile and 20 mM ammonium acetate/0.1% formic acid29,33. MICROSOME PREPARATION Microsomes
were prepared as described by Mohr et al.48. Microsomes were characterized by immunoblot analysis of microsome marker, cytochrome p450 oxidoreductase (POR). A9-OVEREXPRESSION AND KNOCKDOWN
Full length human A9 cDNA (Genbank: NM_021027) was cloned into the pQCXIH retroviral expression vector with a 3×-FLAG tag at the C-terminus; EV: empty vector with no insert. 786-O and Caki-1
cells were stably transfected with EV or A9 construct by retroviral infection. For A9 knockdown, RCC cells were transfected with A9-shRNA (Supplementary Table 6) or a non-targeting shRNA.
PHENOTYPIC READOUT ASSAYS FOR EV AND A9 TRANSFECTANTS Proliferation: transfectants (5×104 cells/well) cultured in growth medium were treated with SF (0–15 µM) and MU (0–0.2 mM) combination;
viable cells were counted at 72-hours. Colony assay: transfectants (500 cells/well) were treated with SF + MU for 10 days. Colonies containing ≥50 cells were stained with crystal violet and
counted. Co-culture studies: in a 2D-assay, transfectants (bottom chamber) were co-cultured with HMEC-1 or HULEC-5a (top chamber; 3 µm insert). 24-h later co-cultures were treated with SF +
MU for 48-hours. Cell viability was assessed by MTT (3-(4, 5-dimethylthiazolyl-2)-2,5 diphenyltetra-zolium bromide) assay. Motility and invasion: transfectants were treated with SF + MU, and
motility and invasion were assessed after 18- and 48-h incubation, respectively26. In a scratch wound assay, 786-O cell transfectants were cultured in 0.1% FBS containing medium. Wound
closure was calculated as described before23. Cell cycle analysis and apoptosis: transfectants were treated with SF + MU for 24- (cell-cycle) or 48-h (apoptosis). Cell cycle was analyzed by
flow cytometry following propidium iodide staining and using ModFit LT v4 software. Apoptosis was measured using a Cell Death Detection ELISAPLUS Kit. RT-QPCR AND IMMUNOBLOT ASSAYS 786-O and
Caki-1 transfectants treated with SF + MU for 48–60 h. Total RNA or cell lysates were subjected to reverse-transcription quantitative Polymerase Chain Reaction (RT-qPCR) or immunoblotting,
respectively, (Supplementary Table 6). XENOGRAFT STUDIES All studies on mice were conducted using a protocol approved by the Institutional Animal Care and Use Committee. Animals were
randomized into vehicle or treatment groups based on the order of retrieval from cages. Cages were housed in random order on shelves. Investigators preparing drug combinations did not
administer the drugs. SUBCUTANEOUS XENOGRAFT Dorsal flanks of 5–6 week old athymic nude mice were subcutaneously injected with 2 × 106 Caki-1 cells mixed 1:1 with MatrigelTM. Treatment was
started when tumors reached ~100 mm3 (day 14, ref. 2). SF was dissolved in Koliphor EL and ethanol solution (1:1); MU was dissolved in filter-sterilized 2% sucrose. SF and MU solutions (1:4
proportion; final ethanol concentration 12.5%) were mixed and mice were gavaged daily with 0.1 ml volume of SF + MU Tumor volume was measured weekly (end point: 49 days; tumor volume ~1000
mm3). ORTHOTOPIC MODEL Luciferase-expressing Caki-1 transfectants (EV, A9) were implanted underneath the renal capsule of 8-week-old athymic mice. From day 9, mice were treated with SF + MU
or the vehicle and imaged weekly using Ami-X imaging system (Spectral Instruments Imaging). Images were analyzed using AMIView Software. HISTOLOGY AND IMMUNOHISTOCHEMISTRY Tumors and organs
were analyzed by histology. Tumor specimens were stained for microvessels (anti-CD31), A9 and Ki67 (proliferation index) as described before49. SAMPLE SIZE CALCULATION A9 levels were
measured on 134 available clinical specimens. The mean difference in A9 levels between normal (0.97 ± 1.8) and tumor (4.9 ± 7.1) specimen was 3.93. To detect this difference with 80% power
we only needed a total of 54 specimens With 134 specimens, our study was sufficiently powered. In the xenograft studies, the mean difference in tumor weights between the vehicle (774.5 ±
274.6) and the treatment group (218.5 ± 261.5) was 556. To detect this difference with 80% power we only needed a total of 8 animals (or 4 animals per group). With a total of 10 or 12
animals in xenograft models, our study was sufficiently powered. STATISTICAL ANALYSES JMP Pro 14 and GraphPad Prism 8.0.0 software were used for analyses. No samples were excluded from the
analysis. In the clinical-cohort, the significance of differences in the expression of A9 between groups were evaluated by one-way ANOVA followed by Mann-Whitney U test because data were
determined to be non-normally distributed as per the Shapiro Wilks’ test; _P_-values are two-tailed. Association of A9 expression with clinical and outcome parameters was determined by
logistic regression and Cox proportional hazard models. Kaplan–Meier plots with log-rank statistics were prepared to determine if A9 expression categorized RCC patients into risk categories
for predicting metastasis. For TCGA data, combined A9 marker was generated as described before50,51. Experiments were repeated in two different cell line models or primary tumor spheroids or
two xenograft models as indicated. Mean ± SD (or SEM) was computed for quantifiable parameters (e.g., cell number, percentage motility, percentage invasion, and tumor volume). Differences
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Download references ACKNOWLEDGEMENTS This study was partly supported by 5R01CA176691-05 (V.B.L.); 1F31 CA210612-01 to A.R.J.; 1F31 CA236437-01 to D.S.M. The content of this article is solely
the responsibility of the authors and does not necessarily represent the official views of the NIH. AUTHOR INFORMATION Author notes * Travis J. Yates Present address: Travis Yates: QualTek
Molecular Laboratories, King of Prussia, PA, USA * These authors contributed equally: Andre R. Jordan, Jiaojiao Wang AUTHORS AND AFFILIATIONS * Department of Biochemistry and Molecular
Biology, Medical College of Georgia, Augusta University, 1410 Laney Walker Blvd., Augusta, GA, 30912, USA Andre R. Jordan, Jiaojiao Wang, Sarrah L. Hasanali, Daley S. Morera, Charles S. Li,
Muthusamy Thangaraju & Vinata B. Lokeshwar * Sheila and David Fuente Graduate Program in Cancer Biology, University of Miami-Miller School of Medicine, Miami, 1600 NW 10th Avenue, Miami,
FL, 33136, USA Andre R. Jordan & Travis J. Yates * Honors Program in Medical Education, University of Miami-Miller School of Medicine, Miami, 1600 NW 10th Avenue, Miami, FL, 33136, USA
Soum D. Lokeshwar * GeneChem Diagnostics Laboratory, Miami, FL, 33157, USA Nagarajarao Shamaladevi * Department of Surgery, Division of Urology, Medical College of Georgia, Augusta
University, 1410 Laney Walker Blvd., Augusta, GA, 30912, USA Zachary Klaassen & Martha K. Terris * Department of Biochemistry and Molecular Biology, University of Nebraska Medical
Center, Omaha, NE, USA Amar B. Singh * Memorial Healthcare System, Aventura, FL, 33180, USA Mark S. Soloway Authors * Andre R. Jordan View author publications You can also search for this
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_et al._ Molecular targeting of renal cell carcinoma by an oral combination. _Oncogenesis_ 9, 52 (2020). https://doi.org/10.1038/s41389-020-0233-0 Download citation * Received: 28 January
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