Abstract
Background:
Infigratinib (BGJ398) is a potent, selective fibroblast growth factor receptor (FGFR) 1–3 inhibitor with significant activity in metastatic urothelial carcinoma (mUC) bearing FGFR3 alterations. It can cause hyperphosphatemia due to the “on-target” class effect of FGFR1 inhibition.
Objective:
To investigate the relationship between hyperphosphatemia and treatment response in patients with mUC.
Intervention:
Oral infigratinib 125 mg/d for 21 d every 28 d.
Design, setting, and participants:
Data from patients treated with infigratinib in a phase I trial with platinum-refractory mUC and activating FGFR3 alterations were retrospectively analyzed for clinical efficacy in relation to serum hyperphosphatemia. The relationship between plasma infigratinib concentration and phosphorous levels was also assessed.
Outcome measurements and statistical analysis:
Clinical outcomes were compared in groups with/without hyperphosphatemia.
Results and limitations:
Of the 67 patients enrolled, 48 (71.6%) had hyperphosphatemia on one or more laboratory tests. Findings in patients with versus without hyperphosphatemia were the following: overall response rate 33.3% (95% confidence interval [CI] 20.4–48.4) versus 5.3% (95% CI 0.1–26.0); disease control rate 75.0% (95% CI 60.4–86.4) versus 36.8% (95% CI 16.3–61.6). This trend was maintained in a 1-mo landmark analysis. Pharmacokinetic/pharmacodynamic analysis showed that serum phosphorus levels and physiologic infigratinib concentrations were correlated positively. Key limitations include retrospective design, lack of comparator, and limited sample size.
Conclusions:
This is the first published study to suggest that hyperphosphatemia caused by FGFR inhibitors, such as infigratinib, can be a surrogate biomarker for treatment response. These findings are consistent with other reported observations and will need to be validated further in a larger prospective trial.
Patient summary:
Targeted therapy is a new paradigm in treating bladder cancer. In a study using infigratinib, a drug that targets mutations in a gene called fibroblast growth factor receptor 3 (FGFR3), we found that elevated levels of phosphorous were associated with greater clinical benefit. In the future, these data may help inform treatment strategies.
Keywords: Biomarker, Infigratinib, Fibroblast growth factor receptor, Hyperphosphatemia, Pharmacodynamics, Pharmacokinetics, Response rate, Urothelial carcinoma
1. Introduction
Metastatic urothelial cancer (UC) remains an incurable disease with significant morbidity and healthcare utilization. Platinum-based chemotherapy remains a cornerstone of therapy, but more recently, several immune checkpoint inhibitors (ICIs) have been introduced to provide additional treatment options. Unfortunately, only a minority of patients (13‒29%) will respond to checkpoint inhibition [1–3]. As an alternative to chemotherapy and immunotherapy, The Cancer Genome Atlas (TCGA) and several other datasets have characterized multiple potentially “druggable” targets in UC. Among these are activating mutations or fusions of fibroblast growth factor receptor 3 (FGFR3), which is altered in approximately 20% of patients with lower tract UC in between 40‒75% of patients with upper tract UC [4–6]. Interestingly, it has been observed that patients with this particular subtype of UC might have lower response rates to ICIs, such as atezolizumab and nivolumab [1,2].
Several potent and selective FGFR3 tyrosine kinase inhibitors have been assessed in metastatic UC, including infigratinib (BGJ398) and erdafitinib [7,8]. Erdafitinib recently garnered accelerated Food and Drug Administration (FDA) approval for FGFR3-altered advanced UC on the basis of a phase II single-arm study [7]. Infigratinib has been examined in a phase Ib expansion cohort and demonstrated an overall response rate (ORR) of 25.4% and disease control rate (DCR) of 64.2%, with a favorable side-effect profile [8]. The most common side effect with these two drugs was hyperphosphatemia, which occurred in approximately 40‒60% of the study population [7,8]. The resulting hyperphosphatemia from FGFR inhibitors is thought to be an “on-target” mechanism-based toxicity (MBT) associated with inhibition of FGFR1 activity. Overall, these drugs have been reported to be well tolerated, with only a minority of patients developing grade 3/4 hyperphosphatemia (2% [two of 99 patients] with erdafitinib and 1.5% [one of 67 patients] with infigratinib) [7,8].
It has previously been reported that other molecularly targeted agents can cause “on-target” MBTs, such as skin rash and hypertension, when using epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF) inhibitors, respectively [9–11]. Furthermore, it has also been observed that these MBTs may serve as surrogate biomarkers associated with treatment efficacy across several malignancies, such as head and neck, lung, and colorectal cancer [9–11]. Recently, an association between treatment response and hyperphosphatemia with erdafitinib has been suggested [12]. We sought to confirm this observation by exploring whether hyperphosphatemia could serve as a surrogate biomarker for infigratinib response in patients with metastatic UC in our previously reported dataset [8]. This is the first study to suggest that MBT-based hyperphosphatemia caused by FGFR inhibitors can be a surrogate biomarker for treatment response.
2. Patients and methods
2.1. Patient selection
As it has previously been reported, patients with metastatic UC who were refractory, intolerant, or ineligible for platinum-based chemotherapy were prescreened for FGFR3 alterations using a commercially available comprehensive genomics profiling (CGP) platform (Foundation Medicine; Cambridge, MA, USA) in the expansion cohort of a phase Ib clinical trial (ClinicalTrials.gov Identifier: NCT01004224) [8]. Patients were determined to be eligible for the study if they possessed somatic alterations in FGFR3 with suspected functional significance, World Health Organization performance status of 0‒2, adequate bone marrow function, normal calcium and phosphate levels, and adequate hepatic and renal function. Those who had received prior therapy with FGFR or MEK inhibitors were excluded from the study. The protocol and consent for this international multicenter study were approved by the institutional review board at each center. All patients enrolled in this study provided separate consents to screen for FGFR3 alterations (unless genomic testing was done as per standard of care) and for therapy with infigratinib.
2.2. Treatment and assessments
Patients received oral infigratinib for 21 d in a 28-d cycle at a starting dose of 125 mg/d. Dose reductions to 100 mg/d followed by 75 mg/d were permitted, with further dose reductions allowed on an individual basis. Infigratinib was continued until disease progression or intolerable toxicity. Hyperphosphatemia prophylaxis with the oral phosphate binder sevelamer hydrochloride was administered as part of the protocol, and a low-phosphate diet was recommended at the start of therapy. We defined hyperphosphatemia as serum phosphorous levels exceeding 5.5 mg/dl, which was consistent with the threshold for dose reduction or interruption in this study protocol.
Patients received baseline imaging, which included computed tomography (CT) of the chest, abdomen, and pelvis; brain magnetic resonance imaging (MRI) or CT; and technetium bone scan. Follow-up serial imaging included CT of the chest, abdomen, and pelvis (along with bone scan if indicated) at 8-wk intervals thereafter.
2.3. Genomic assessment of tissue and blood specimens
Methods for CGP used in this study have been published previously [5]. The patients submitted available formalin-fixed paraffin-embedded tissue derived from primary or metastatic site biopsy, transurethral resection of bladder tumor, cystectomy, or nephroureterectomy. Functional significance of mutations in FGFR3 was determined through interrogation of the Catalogue of Somatic Mutations in Cancer (COSMIC) database and review of published literature. Ultimately, these included mutations in exon 7 (R248C, S249C), exon 10 (G372C, A393E, Y375C), exon 15 (K652M/T, K652E/Q), or FGFR3 fusions including, but not limited to, the FGFR3-TACC fusion.
Plasma was collected at baseline and multiple prespecified time points during treatment. Cell-free DNA was extracted from plasma specimens using the QIAmp Circulating Nucleic Acid kit (QIAGEN, Hilden, Germany), and the TruSeq Nano DNA Library Prep kit (Illumina Inc., San Diego, CA, USA) was used for construction of libraries. A 600-gene PanCancer panel was used; sequencing was performed on an Illumina HiSeq 2500 sequencer (Illumina Inc.) with a median coverage of 775×. Detailed methods have been published previously.
2.4. Pharmacokinetic/pharmacodynamic assessments
Serial blood samples were collected following the method previously described by Nogova et al [13]. Briefly, serum blood samples were collected at various time points, including up to 24 h prior to initiation and then on treatment days 1, 15, and 28 of the first cycle. Plasma from these samples was then collected and frozen at ≤–60°C until they could be analyzed together as a batch. Infigratinib plasma concentrations were measured using a validated liquid chromatography–tandem mass spectrometry method with a 1.0 ng/ml lower limit of quantification [13]. Pharmacokinetic (PK) parameters were calculated using noncompartmental methods with the Phoenix WinNonlin (Pharsight, Mountain View, CA, USA) software suite [13]. Serum phosphorus levels were measured as part of the standard clinical chemistry panel for safety monitoring, which was assessed at baseline, cycle 1 on days 1, 2, 8, 15 and 22, and subsequent cycles on days 1 and 15.
Infigratinib PK and pharmacodynamics (PD) in relation to hyperphosphatemia were examined by selecting patients with at least one evaluable PK parameter (area under the time-concentration curve [AUC] or maximum plasma concentrations [Cmax]) and serum phosphorus level at the same visit. The PK parameters AUCint (dosing interval, 0–24 h after the dose) and Cmax were dose normalized to their corresponding dose for patients in the dose-escalation cohorts. Patients were categorized as those having hyperphosphatemia or not at the visit where a PK parameter was available, and box plots were generated to compare PK parameters by serum phosphorus category. Plasma infigratinib concentration and serum phosphorus levels across various time points were calculated by selecting patients with at least both these values from the same visit. Scatter plots of infigratinib concentrations versus serum phosphorus levels were plotted with linear regression analysis, which were then used to generate R2 values.
2.5. Statistical analysis
ORR (partial response [PR] plus complete response [CR]), DCR (CR and PR plus stable disease [SD]), and best overall response (BOR) were characterized in all patients using Response Evaluation Criteria in Solid Tumors (RECIST v1.0). ORR, DCR, and BOR with 95% confidence intervals (CIs) based on the exact binomial method were calculated by comparing patients with hyperphosphatemia (defined as serum phosphorus levels >5.5 mg/dl after the dose) versus non-hyperphosphatemia (defined as serum phosphorus levels ≤5.5 mg/dl after the dose). Median and range of duration of response for patients with confirmed responses (confirmed CR or PR) were also summarized by hyperphosphatemia status. Progression-free survival (PFS) and overall survival (OS) in the subgroups of patients with hyperphosphatemia and non-hyperphosphatemia, respectively, and in the overall population were described using the Kaplan-Meier methods. Owing to the small sample size, statistical comparisons were not feasible and thus not performed for PFS and OS analysis.
Fisher’s exact test was used to test the association between hyperphosphatemia and whether or not a patient is able to complete 30 d of infigratinib. Then landmark analyses (using a 30-d threshold) were also performed for efficacy endpoints (ORR, PFS, and OS) by comparing patients with hyperphosphatemia versus non-hyperphosphatemia. The landmark analyses entailed using the same abovementioned statistical analysis methods after excluding patients who discontinued infigratinib in <30 d.
In addition, the correlation between the patient’s measured serum phosphorus and infigratinib plasma levels were explored by plotting pairs of serum phosphorus level and infigratinib plasma concentration at selected visits, and testing the slope of the fitted regression line.
3. Results
3.1. Patient characteristics
A total of 67 patients with activating FGFR3 mutations or fusions were enrolled for this study. Based on serum phosphorous levels exceeding 5.5 mg/dl, we found that 48 patients had hyperphosphatemia during study therapy and 19 did not (Table 1). The median age for the whole study population was 67 yr (range, 39‒85); 35 (72.9%) and 11 (57.9%) patients were men in the hyperphosphatemia and non-hyperphosphatemia groups, respectively. A total of 24 (50%) and six (31.6%) patients had received more than two lines of prior antineoplastic therapies in the hyperphosphatemia and non-hyperphosphatemia groups, respectively (Supplementary Table 1).
Table 1 ‒
Patient characteristics in patients with hyperphosphatemia versus non-hyperphosphatemia
| Characteristic | Hyperphosphatemia (n = 48) | Non-hyperphosphatemia (n = 19) |
|---|---|---|
| Age (yr), n (%) | ||
| <65 | 18 (37.5) | 11 (57.9) |
| ≥65 yr | 30 (62.5) | 8 (42.1) |
| Gender, n (%) | ||
| Male | 35 (72.9) | 11 (57.9) |
| Female | 13 (27.1) | 8 (42.1) |
| WHO PS, n (%) | ||
| 0 | 13 (27.1) | 8 (42.1) |
| 1 | 30 (62.5) | 6 (31.6) |
| 2 | 5 (10.4) | 5 (26.3) |
| Bellmunt criteria—risk group, n (%) a | ||
| 0 | 7 (14.6) | 5 (26.3) |
| 1 | 21 (43.8) | 6 (31.6) |
| 2 | 18 (37.5) | 7 (36.8) |
| 3 | 2 (4.2) | 1 (5.3) |
| Visceral disease, n (%) | ||
| Lung | 30 (62.5) | 11 (57.9) |
| Liver | 17 (35.4) | 8 (42.1) |
| Lymph node metastases, n (%) | ||
| Yes | 20 (41.7) | 8 (42.1) |
| No | 28 (58.3) | 11 (57.9) |
| Bony metastases, n (%) | ||
| Yes | 16 (33.3) | 10 (52.6) |
| No | 32 (66.7) | 9 (47.4) |
| Any prior immunotherapy, n (%) | ||
| Yes | 8 (16.7) | 5 (26.3) |
| No | 40 (83.3) | 14 (73.7) |
ECOG = Eastern Cooperative Oncology Group; WHO PS = World Health Organization performance status.
Hyperphosphatemia and non-hyperphosphatemia were defined as serum phosphorus levels >5.5 and ≤5.5 mg/dl after the dose, respectively.
Bellmunt Criteria include ECOG >0, liver metastases, and hemoglobin <10 g/dl at baseline.
3.2. Efficacy
Among the 67 treated patients, one in the hyperphosphatemia group had a confirmed CR, whereas none was noted in the non-hyperphosphatemia group (Table 2). ORR for the former group was noted to be 33.3% (95% CI 20.4–48.4). Among those who had hyperphosphatemia, 15 patients (31.1%) had a PR and 20 patients (41.7%) had SD. This group had a DCR of 75.0% (95% CI 60.4–86.4%). It was also noted that the median PFS was 4.93 mo (95% CI 3.65‒5.98) and median OS was 8.74 mo (95% CI 5.72‒13.67) in these patients.
Table 2 ‒
Efficacy of results for the treatment of patients with hyperphosphatemia versus non-hyperphosphatemia
| Hyperphosphatemia(n = 48) | Non-hyperphosphatemia (n = 19) | |
|---|---|---|
| Response assessment, n (%) | ||
| CR, confirmed | 1 (2.1) | 0 |
| PR, confirmed | 15 (31.3) | 1 (5.3) |
| CR or PR, unconfirmed | 8 (16.7) | 3 (15.8) |
| SD | 20 (41.7) | 6 (31.6) |
| Progressive disease | 11 (22.9) | 7 (36.8) |
| Unknown/not done | 1 (2.1) | 5 (26.3) |
| Confirmed objective response (CR or PR), n (%) | 16 (33.3) | 1 (5.3) |
| 95% CI | 20.4, 48.4 | 0.1, 26.0 |
| Best overall response (CR or PR, confirmed/unconfirmed), n (%) | 24 (50.0) | 4 (21.1) |
| 95% CI | 35.2, 64.8 | 6.1, 45.6 |
| Disease control rate (CR, PR, or SD), n (%) | 36 (75.0) | 7 (36.8) |
| 95% CI | 60.4, 86.4 | 16.3, 61.6 |
CI = confidence interval; CR = complete response; PR = partial response; SD = stable disease.
Hyperphosphatemia and non-hyperphosphatemia were defined as serum phosphorus levels >5.5 and ≤5.5 mg/dl after the dose, respectively.
In the non-hyperphosphatemia group, one PR was observed (ORR 5.3%) and six patients had a best response of SD (DCR 36.8%). The median PFS was 1.84 mo (95% CI 1.28‒3.48) and the median OS was 7.62 mo (95% CI 2.53‒15.57) in non-hyperphosphatemia patients.
In summary, patients who were found to have hyperphosphatemia had significantly higher ORRs than those with non-hyperphosphatemia (33.3% vs 5.3%); the same was also true for DCR (75.0% vs 36.8%).
Fisher’s exact test was used to evaluate any association between hyperphosphatemia status and whether or not patients had received <30 d of treatment, and the test found a correlation between hyperphosphatemia and patients with <30 d of infigratinib (p < 0.0001). This analysis indicated that more patients experienced hyperphosphatemia if they received ≥30 d of treatment than those who received <30 d of treatment (81% vs 11%). Therefore, the landmark analysis (which excluded patients with <30 d of infigratinib treatment) was applied, and similar trends were also observed for the same endpoints: ORR was 37.5% (95% CI 22.7‒54.2%) and 11.1% (95% CI 1.4‒34.7%) for the hyperphosphatemia and non-hyperphosphatemia groups, respectively. The median PFS was 5.42 mo (95% CI 3.52‒6.37) and 3.68 mo (95% CI 1.84‒4.93), respectively. The median OS was 9.66 mo (95% CI 6.90‒15.28) and 6.24 mo (95% CI 3.94‒16.82), respectively.
3.3. Safety
Grade 3/4 adverse effects occurred at similar levels in both groups: at 70.8% (n = 34) and 63.2% (n = 12) in the hyperphosphatemia and non-hyperphosphatemia groups, respectively (Table 3). The hyperphosphatemia group, compared with the non-hyperphosphatemia group, had a higher rate of dose interruptions and adjustments at 89.6% (n = 43) and 52.6% (n = 10), respectively. Interestingly, the hyperphosphatemia group had a lower discontinuation rate than the non-hyperphosphatemia group due to treatment-related adverse events: 6.3% (n = 3) and 36.8% (n = 7), respectively.
Table 3 ‒
Summary of treatment-emergent adverse events (TEAEs) in patients with hyperphosphatemia versus non-hyperphosphatemia
| Parameter, n (%) | Hyperphosphatemia (n = 48) | Non-hyperphosphatemia (n = 19) |
|---|---|---|
| Any TEAE | 48 (100.0) | 18 (94.7) |
| Grade 3 or 4 TEAE | 34 (70.8) | 12 (63.2) |
| Serious TEAE | 17 (35.4) | 7 (36.8) |
| Treatment-related TEAE | 47 (97.9) | 17 (89.5) |
| Serious treatment-related TEAE | 3 (6.3) | 1 (5.3) |
| TEAE leading to treatment discontinuation | 3 (6.3) | 7 (36.8) |
| TEAE leading to dose interruption/dose adjustment | 43 (89.6) | 10 (52.6) |
Hyperphosphatemia and non-hyperphosphatemia were defined as serum phosphorus levels >5.5 and ≤5.5 mg/dl after the dose, respectively.
3.4. Relationship between hyperphosphatemia and drug exposure
We then asked the question whether patients who had developed hyperphosphatemia may also have higher plasma exposure of infigratinib. In order to answer this question, we performed PK and PD analyses of hyperphosphatemia and non-hyperphosphatemia patients. The PK/PD analysis showed a similar median AUCint and Cmax value for infigratinib on day 1 of cycle 1, as was expected, but on day 15 of cycle 1, when the patients were expected to reach a steady state of infigratinib, patients with hyperphosphatemia had a higher median dose-normalized exposure, with an AUCint of 26.1 ng/ml/mg and a Cmax of 1.75 ng/ml, than those with non-hyperphosphatemia, who showed an AUCint of 5.2 ng/ml/mg and a Cmax of 0.7 ng/ml (Fig. 1A and 1B). To further validate these findings, we then investigated whether there was a correlation between the patient’s measured serum phosphorus and infigratinib plasma levels across various time points. We observed that the predose (trough) concentration of infigratinib showed a positive relationship with serum phosphorus levels (p < 0.0001; Fig. 2). At steady state of infigratinib, trough concentration (cycle 1, day 15), and subsequent visits analyzed (cycle 1, day 22), a higher concentration of infigratinib corresponded to a higher phosphorus level. Overall, these findings suggested that patients who developed hyperphosphatemia also had a higher measured plasma concentration of infigratinib.
Fig. 1 ‒
PK/PD analysis of infigratinib treatment based on serum phosphorus levels. (A) Dose-adjusted Cmax in relation to serum phosphorus levels. At steady state (C1D15 and C1D28), patients with hyperphosphatemia were found to have a higher steady-state maximum concentration (Cmax) than those with non-hyperphosphatemia. (B) Patients with hyperphosphatemia were found to have a higher AUCint at steady state than those with non-hyperphosphatemia. Note: Hyperphosphatemia and non-hyperphosphatemia were defined as serum phosphorus levels >5.5 and ≤5.5 mg/dl after the dose, respectively. AUCint = area under the time-concentration curve over a dose interval; C = cycle; Cmax = maximum plasma concentration; D = dose.
Fig. 2 ‒
Patient serum phosphorus levels in relation to plasma infigratinib concentration. Patients who had higher serum phosphorus levels (mmol/l) were found to have higher plasma concentrations of infigratinib (ng/ml). The green dots represent each patient’s measurement across various time points of the study. The blue line represents the best fit linear regression trend. The slope for C1D8 before the dose is significant with p < 0.0001. C = cycle; D = dose.
4. Discussion
Building on previous observations in the field, this is the first published study to systematically investigate the hypothesis that hyperphosphatemia as an “on-target” adverse effect may serve as a surrogate biomarker of FGFR3 inhibitor treatment response in metastatic UC [12]. Our data suggest that hyperphosphatemia secondary to infigratinib may be associated with a higher ORR (33.3% vs 5.3%, p = 0.026). This was further validated by controlling to only include those patients who had at least 1-mo duration of infigratinib treatment. These landmark analyses still showed similar trends in differences between the hyperphosphatemia and non-hyperphosphatemia groups across ORR, PFS, and OS. In addition, PK/PD analysis (Fig. 1 and 2) found that patients with higher plasma concentrations of infigratinib also achieved higher serum phosphorus levels. Altogether, these results suggest that hyperphosphatemia may be a surrogate biomarker for increased on-target FGFR engagement by infigratinib.
MBTs from other molecular targeted agents, such as skin rash (EGFR) and hypertension (VEGF), have been reported previously in multiple studies to serve as surrogate biomarkers of treatment response to EGFR and VEGF inhibitors in the treatment of several tumor types, such as non–small-cell lung [9,14], head and neck [10], colorectal [11,15], and pancreatic [16] cancer. It has also been suggested that the greater the associated MBT, the greater the drug exposure and antitumor activity [17].
Our study is limited in that it was retrospective and exploratory in nature without a preplanned statistical design, and did not have a randomized comparator. The true effect of a biomarker can be proved only in a larger randomized controlled trial, a strategy that can mitigate the effect of confounding variables. Moreover, it had a relatively small sample size, which made it impossible to assess significant comparisons and use multivariate analysis to control for potential selection and confounding factors, such as patient demographics, baseline phosphorus levels, and heterogeneity in PK among the individuals. Another confounding factor may be that patients with non-hyperphosphatemia may possibly have had more aggressive disease, making them more refractory to all treatments. Therefore, this association warrants further investigation in a larger prospective randomized clinical trial to test the validity of this correlation and to assess whether hyperphosphatemia can serve specifically as a predictive biomarker for treatment response and outcomes on infigratinib. This phenomenon will be explored in a randomized phase III trial comparing infigratinib with placebo in patients with FGFR3-altered UC following surgical resection (NCT04197986).
5. Conclusions
Hyperphosphatemia is a well-described class effect of FGFR inhibitors, including infigratinib, and is generally reversible and easily managed. Mechanistically, it is a consequence of FGFR1 inhibition, which is inhibited by infigratinib at single nanomolar potency. Our data support previous observations with FGFR inhibitors, suggesting that patients with metastatic UC receiving infigratinib who develop hyperphosphatemia are more likely to have a treatment response. Importantly, the correlative relationship between hyperphosphatemia and efficacy showed similar trends in the overall and landmark analyses. Larger cohorts and prospective trials are required to validate our findings and assess the potential clinical utility of hyperphosphatemia as a biomarker.
Supplementary Material
Acknowledgments
Funding/Support and role of the sponsor: This work was supported by QED Therapeutics Inc.
Footnotes
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Financial disclosures: Sumanta K. Pal certifies that all conflicts of interest, including specific financial interests and relationships and affiliations relevant to the subject matter or materials discussed in the manuscript (eg, employment/affiliation, grants or funding, consultancies, honoraria, stock ownership or options, expert testimony, royalties, or patents filed, received, or pending), are the following: Yung Lyou: none. Petros Grivas: consulting or advisory role (author)—Merck, Bristol-Myers Squibb, AstraZeneca, Clovis Oncology, EMD Serono, Seattle Genetics, Foundation Medicine, Driver, Inc., Pfizer, QED Therapeutics, HERON, Janssen, Bayer, Genzyme, Mirati Therapeutics, Exelixis, Roche, and GlaxoSmithKline; research funding (institution)—Pfizer, Clovis Oncology, Bavarian Nordic, Immunomedics, Bristol-Myers Squibb, and Debiopharm Group. Jonathan E. Rosenberg: honoraria (author)—UpToDate, Bristol-Myers Squibb, AstraZeneca, Medscape, Vindico, Peerview, Chugai Pharma, Research To Practice, Intellisphere, Clinical Care Options, and Clinical Mind; consulting or advisory role (author)—Merck, Agensys, Genentech, Sanofi, AstraZeneca, Bristol-Myers Squibb, EMD Serono, Seattle Genetics, Bayer, Inovio Pharmaceuticals, BioClin Therapeutics, QED Therapeutics, Adicet Bio, Sensei Biotherapeutics, Fortress Biotech, Pharmacyclics, Western Oncolytics, GlaxoSmithKline, Janssen Oncology, Astellas Pharma, Boehringer Ingelheim, and Mirati Therapeutics; research funding (institution)—Oncogenex, Agensys, Mirati Therapeutics, Novartis, Viralytics, Genentech, Incyte, Seattle Genetics, Bayer, AstraZeneca, QED Therapeutics, Astellas Pharma, and Jounce Therapeutics); patents, royalties, and other intellectual property (institution)—predictor of platinum sensitivity; travel, accommodations, and expenses (author)—Genentech; Bristol-Myers Squibb). Jean Hoffman-Censits: consulting or advisory role (author)—Roche/Genentech, Foundation Medicine, and AstraZeneca; travel, accommodations, expenses (author)—Roche/Genentech; honoraria (author)—Roche/Genentech and Clovis Oncology; research funding (institution)—Sanofi. David I. Quinn: consulting or advisory role (author)—Astellas Pharma, Pfizer, Bristol-Myers Squibb, Genentech/Roche, Merck Sharp & Dohme, Bayer, Exelixis, AstraZeneca, Sanofi, Dendreon, EMD Serono, Janssen Oncology, Amgen, Eisai, Novartis, US Biotest, and Clovis Oncology; honoraria (author)—Bayer, Astellas Pharma, Pfizer, Genentech/Roche, Merck Sharp & Dohme, Bristol-Myers Squibb, AstraZeneca, Dendreon, Exelixis, Sanofi, Janssen Oncology, Novartis, Mundipharma, Pharmacyclics, and Clovis Oncology; research funding (institution)—Millennium, Genentech/Roche, Sanofi, and GlaxoSmithKline. Daniel Petrylak: consulting or advisory role (author)—Bayer, Bellicum Pharmaceuticals, Dendreon, Johnson & Johnson, Exelixis, Ferring, Millennium, Medivation, Pfizer, Roche, Sanofi, Tyme, Astellas Pharma, AstraZeneca, and Lilly; expert testimony (author)—Celgene and Sanofi; stock and other ownership interests (author)—Bellicum Pharmaceuticals and Tyme; research funding (institution)—Progenics, Johnson & Johnson, Dendreon, Sanofi, Endocyte, Genentech, Merck, Astellas Medivation, Novartis, Agensys, AstraZeneca, Bayer, Lilly, Innocrin Pharma, MedImmune, Millennium, Pfizer, Roche, Sotio, Seattle Genetics, and Clovis Oncology. Matthew Galsky: consulting or advisory role (author)—BioMotiv, Janssen, Dendreon, Merck, GlaxoSmithKline, Lilly, Astellas Pharma, Genentech, Bristol-Myers Squibb, Novartis, Pfizer, EMD Serono, AstraZeneca, Seattle Genetics, Incyte, Aileron Therapeutics, Dracen, Inovio Pharmaceuticals, and NuMab; patents, royalties, and other intellectual property (author)—methods and composition for treating cancer and related methods (Mount Sinai School of Medicine, July 2020; application number: 20120322792); stock and other ownership interests (author)—Rappta Therapeutics; research funding (institution)—Janssen Oncology, Dendreon, Novartis, Bristol-Myers Squibb, Merck, AstraZeneca, and Genentech/Roche. Ulka Vaishampayan: consulting or advisory role (author)—Pfizer, Astellas Pharma, Bristol-Myers Squibb, Exelixis, Genentech/Roche, and Bayer; speakers’ bureau (author)—Pfizer, Bayer, Bristol-Myers Squibb, Exelixis, Genentech/Roche, and Sanofi; honoraria (author)—Pfizer, Janssen, Novartis, Bayer, Sanofi, Bristol-Myers Squibb, Genentech, and Exelixis; research funding (institution)—Astellas Pharma, Exelixis, Pfizer, Bristol-Myers Squibb, and Novartis. Ugo De Giorgi: consulting or advisory role (author)—Pfizer, Janssen, Astellas Pharma, Sanofi, Bristol-Myers Squibb, Bayer, Ipsen, and Merck; research funding (institution)—Sanofi, AstraZeneca, and Roche; travel, accommodations, and expenses (author)—Bristol-Myers Squibb, Ipsen, Janssen, and Pfizer. Sumati Gupta: research funding (institution)—Mirati Therapeutics, Novartis, Pfizer, Viralytics, Hoosier Cancer Research Network, Rexahn Pharmaceuticals, Five Prime Therapeutics, Incyte, MedImmune, Merck, Bristol-Myers Squibb, Clovis Oncology, and LSK. Howard Burris: consulting or advisory role (institution)—Mersana, AstraZeneca, FORMA Therapeutics, Janssen, Novartis, Roche/Genentech, TG Therapeutics, MedImmune, Bristol-Myers and Squibb; leadership (author)—HCA Healthcare/Sarah Cannon; expert testimony (author)—Novartis; stock and other ownership interests—HCA Healthcare/Sarah Cannon; research funding (institution)—Roche/Genentech, Bristol-Myers Squibb, Incyte, Tarveda Therapeutics, Mersana, AstraZeneca, MedImmune, Macrogenics, Novartis, Boehringer Ingelheim, Lilly, Seattle Genetics, Abbvie, Bayer, Celldex, Merck, Celgene, Agios, Jounce Therapeutics, Moderna Therapeutics, CytomX Therapeutics, GlaxoSmithKline, Verastem, Tesaro, Immunocore, Takeda, Millennium, BioMed Valley Discoveries, Pfizer, PTC Therapeutics, TG Therapeutics, Loxo, Vertex, eFFECTOR Therapeutics, Janssen, Gilead Sciences, Valent Technologies, BioAtla, CicloMed, Harpoon Therapeutics, Jiangsu Hengrui Medicine, Revolution Medicines, Daiichi Sankyo, H3 Biomedicine, Neon Therapeutics, OncoMed, Regeneron, and Sanofi. Recipient: your Institution. Jessica Rearden: employment—QED Therapeutics Inc. Yining Ye: employment—QED Therapeutics Inc. Hao Wang: employment—QED Therapeutics Inc. Maribel Reyes: employment—QED Therapeutics Inc. Susan Moran: employment—QED Therapeutics Inc. Siamak Daneshmand: consulting or advisory role—QED Therapeutics Inc. Dean Bajorin: consulting or advisory role (author)—Bristol-Myers Squibb, Novartis, Roche/Genentech, Merck, Genentech, Roche, Lilly, Fidia Farmaceutici S. p. A., Eisai, Urogen Pharma, Pfizer, and EMD Serono); travel, accommodations, and expenses (author)—Roche/Genentech, Merck, Bristol-Myers Squibb, Lilly, and Urogen Pharma; honoraria (author)—Merck Sharp & Dohme; research funding (institution)—Dendreon, Novartis, Amgen, Genentech/Roche, Merck, Bristol-Myers Squibb, AstraZeneca, Astellas Pharma, and Seattle Genetics/Astellas. Sumanta K. Pal: consulting or advisory role (author)—Pfizer, Novartis, Aveo, Myriad Pharmaceuticals, Genentech, Exelixis, Bristol-Myers Squibb, Astellas Pharma, Ipsen, and Eisai; honoraria (author)—Novartis, Medivation, and Astellas Pharma; research funding (author)—Medivation.
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