Ex Vivo Microtumor Testing to Predict Chemotherapy Responses in Patients with Bladder Cancer

Take Home Message

Ex vivo three-dimensional microtumor testing shows promise in predicting chemotherapy response in patients with bladder cancer within clinical timelines, highlighting its potential to serve as a clinical biomarker to guide treatment decision-making.

Abstract

Background

Patients with bladder cancer (BC) may receive intravesical or systemic chemotherapy, but predictive biomarkers to guide treatment selection are lacking. Consequently, some patients receive ineffective treatment, resulting in unnecessary toxicity and an increased risk of tumor progression.

Objective

To evaluate the feasibility of ex vivo micro-tumor testing for predicting chemotherapy response in patients with BC.

Design, setting, and participants

In this prospective study, 65 patients with BC were enrolled (Institutional Review Board no. MEC-2022-0233). Tumor samples were collected during transurethral resection or radical cystectomy. BC was confirmed by uropathological review, supported by the detection of BC-associated mutations in hTERT, FGFR3, and PIK3CA. Patient-derived micro-tumors were exposed ex vivo to anticancer drugs, and responses were assessed using image-based measurements of viability and morphology.

Outcome measurements and statistical analysis

The primary outcome was successful completion of ex vivo drug testing within 14 days of tissue collection. The secondary outcome was concordance between ex vivo sensitivity and clinical response to platinum-based chemotherapy. Clinical response data were available for nine patients.

Results and limitations

Ex vivo drug testing was successful for 48 of 65 patients (74%), with all successful results generated within 14 days of tissue collection. Among the nine patients with evaluable clinical outcomes following platinum-based chemotherapy, ex vivo responses corresponded with observed treatment responses. The main limitations were the small clinical correlation cohort and the limited number of drugs evaluated.

Conclusions

Ex vivo micro-tumor drug testing is feasible for BC within a clinically relevant timeframe. The observed correspondence between ex vivo and clinical responses to platinum-based chemotherapy supports further investigation of this approach for personalized treatment selection in BC.

ADVANCING PRACTICE.

What does this study add?

To our knowledge, there is currently no method to predict chemotherapy treatment responses for patients with bladder cancer (BC) within clinical timelines. This study demonstrates the development and feasibility of ex vivo microtumor drug sensitivity testing to predict responses to chemotherapy in patients with BC within 14 d, thereby supporting clinical treatment decision-making.

Clinical Relevance

This study demonstrates that ex vivo microtumor drug sensitivity testing can be successfully performed using routine bladder cancer specimens within a clinically actionable timeframe. Although requiring prospective validation in larger cohorts, the observed concordance between ex vivo chemosensitivity and patient response to platinum-based chemotherapy suggests that this functional assay could complement existing biomarkers to personalize treatment selection, potentially avoiding ineffective therapy and supporting decision-making for neoadjuvant chemotherapy in muscle-invasive bladder cancer and intravesical chemotherapy in non–muscle-invasive disease.

Patient Summary

We evaluated a novel approach to support treatment decision-making for patients with bladder cancer by assessing laboratory responses of patient-derived tumor cells. Drug testing within 2 wk of diagnosis was feasible for most patients. Among patients receiving platinum-based chemotherapy, laboratory test responses were concordant with clinical outcomes, suggesting the potential utility of the test in guiding treatment decision-making.

1. Introduction

Bladder cancer (BC) is classified into non–muscle-invasive BC (NMIBC) and muscle-invasive BC (MIBC). NMIBC accounts for ∼70% of newly diagnosed cases and is primarily treated with transurethral resection of the bladder tumor (TURBT), followed by adjuvant intravesical therapy. Based on clinicopathological risk factors, patients with intermediate-risk (IR) disease typically receive intravesical chemotherapy (IVC), whereas patients with high-risk (HR) disease receive Bacillus Calmette-Guérin (BCG) [1]. However, no standard IVC regimen is recommended for patients with IR disease, and agents such as gemcitabine, mitomycin C, and epirubicin are commonly used [1], [2]. Radical cystectomy (RC) is recommended for patients with BCG-unresponsive NMIBC, but many patients are unfit for or decline surgery, supporting the development of bladder-sparing salvage therapies [1], [3], [4], [5], [6]. Despite these advances, treatment efficacy is often limited, and durable responses remain uncommon [5]. Current European Association of Urology guidelines do not specify treatment regimens for IR or BCG-unresponsive HR-NMIBC, resulting in management strategies that frequently rely on physicians’ preferences [1].

MIBC, representing ∼30% of BC cases, is treated with neoadjuvant platinum-based chemotherapy (NAC), followed by RC or chemoradiation [7]. Only 30% of the patients treated with NAC show a pathological complete response (pCR) at RC (stage ypT0N0), and these patients have a 90% 5-yr overall survival rate [8], [9]. Nonresponders (ypT1N0 or higher) to NAC seem to have worse outcomes than those treated with RC alone [10], indicating that delayed cystectomy might compromise outcomes [11], [12].

There are currently no reliable biomarkers to predict chemotherapy response in BC, whereas ineffective treatment places patients at risk of tumor progression, delayed cystectomy, increased toxicity, and increased health care costs. To improve BC outcomes, it is crucial to provide the most effective therapy for each patient in a timely manner. Here, we developed an ex vivo microtumor testing platform and evaluated its potential for personalized therapy in BC.

2. Patients and methods

2.1. Patients

Adult patients aged ≥18 yr with suspected HR-NMIBC or MIBC who had sufficient tumor material to meet diagnostic requirements and donate tissue samples for research were eligible for inclusion. Patients were included at five hospitals (Erasmus MC, Amphia, Haga, Franciscus Gasthuis en Vlietland, and Medisch Spectrum Twente).

2.2. Clinical response assessment

For patients treated with NAC, response classification was based on histopathological evaluation of posttreatment cystectomy specimens by dedicated genitourinary pathologists, which represents the current clinical standard in this setting. A pCR was defined as the absence of residual viable tumor (ypT0N0), whereas a pathological partial response (pPR) was defined as noninvasive downstaging (ypTis-TaN0). Pathological nonresponse (pNR) was defined as residual invasive disease (ypT1Nany or higher). For analysis, patients with pCR or pPR (ypT2 or lower) were classified as responders, whereas patients with residual invasive disease (ypT1Nany or higher, pNR) were classified as nonresponders.

For patients treated in the palliative or metastatic setting, response was assessed radiographically according to the Response Evaluation Criteria in Solid Tumors (RECIST), version 1.1. Baseline and follow-up computed tomography scans were evaluated by the treating physicians, and the best overall response during treatment was categorized as clinical complete response (cCR), clinical partial response (cPR), clinical stable disease (cSD), or clinical progressive disease (cPD). Patients with cCR or cPR were classified as responders, whereas patients with cSD or cPD were classified as nonresponders.

2.3. Ethical considerations

Patients scheduled for TURBT or RC were approached for inclusion in the preoperative phase. Patients received detailed information forms, were verbally informed about the study, and were given the opportunity to ask questions before providing written consent. All enrolled patients provided written consent for this study, which was authorized by the ethics committee at Erasmus MC (MEC-2018-1096) and was conducted in accordance with the Declaration of Helsinki.

2.4. End point analyses

The primary end point was the successful completion of ex vivo microtumor testing. Successful ex vivo microtumor testing was defined by at least one dose-response curve meeting the quality control standards outlined in the Patients and methods section. The secondary end point was the association between ex vivo and clinical responses to platinum-based chemotherapy.

2.5. Sample acquisition and characterization

Fresh BC tissue was collected during TURBT or following RC. TURBT samples were obtained through two cold cup biopsies (∼2–3 mm³) from the luminal tumor area. RC samples (∼5 mm³) were collected from the bladder specimen following macroscopic evaluation and selection of tumor tissue by an experienced pathologist. The tissue was submerged immediately in Belzer UW Cold Storage Solution (Bridge To Life Ltd., Columbia, SC, USA), maintained at 4°C, and transported to the research facilities within 24 h. Upon arrival, the tissue was divided for sample characterization and microtumor testing. Tissue processing and hematoxylin and eosin (H&E) staining were performed, followed by evaluation by a uropathologist to confirm the presence of BC cells. DNA was extracted from confirmed tumor tissue using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s protocol. BC-specific hot spot mutations in the TERT promoter sequence chr5:1,295,228C>T, chr5:1,295,248G>A and chr5:1,295,250C>T [GRCh37/hg19], FGFR3 (R248Q/E, S249C, G372C, Y375C, A393E, K652E/M) and PIK3CA (E542K, E545G/K and H1047R) were detected via SNaPshot analysis, as previously described [13], [14], [15].

2.6. Ex vivo microtumor drug sensitivity testing

Ex vivo microtumor testing was performed as previously described [16]. Additional details can be found in Supplementary Material.

2.7. Chemosensitivity score and clinical reporting

Exclusion criteria were the absence of BC after pathological evaluation and the acquisition of insufficient or damaged tumor tissue. Chemosensitivity of patients was assessed by comparing the area under the curves (AUCs) of the dose-response curves in this study with those in a larger in-house ex vivo drug testing database. A multilevel Bayesian linear regression model was fit to the data and, after correcting for tumor type (BC) and compound (carboplatin, cisplatin, and gemcitabine) effects, yielded a probability distribution of each patient’s chemosensitivity corrected for compound-specific and disease-specific factors. A Bayesian framework was chosen because the primary quantity of interest is an unobserved patient-level chemosensitivity effect inferred from sparse, unbalanced compound-response data, allowing uncertainty in this latent effect to be propagated directly to the cohort-relative score. The general chemosensitivity score of each patient is the transformed mean of this distribution, expressed as an inverse quantile of the full patient cohort (0 = most resistant; 1 = most sensitive). No thresholding was applied to classify patients as sensitive or resistant, as the analysis relied exclusively on continuous scoring.

2.8. Statistical analyses

Continuous data were summarized using the median (interquartile range [IQR]), mean, and standard error of the mean (SEM). Categorical data were summarized as frequencies and percentages. The Mann-Whitney U test was used to analyze continuous nonnormally distributed data. Linear associations between drug responses were assessed using the Pearson correlation coefficient (r), and associations between chronological sample order and successful microtumor generation were assessed using logistic regression, with sample order modeled as a continuous variable. Corresponding p values were calculated. Distributional asymmetry of chemotherapy responses was assessed using the D’Agostino–Pearson K² test for normality. A p value <0.05 was considered statistically significant.

3. Results

3.1. Patients and sample characteristics

Between June 2020 and January 2024, 82 patients were screened for eligibility. A total of 17 patients (20.7%) were excluded for the following reasons: two patients were diagnosed with benign lesions (2.4%), one patient declined to undergo diagnostic TURBT (1.2%), and no tissue was acquired during diagnostic TURBT in six patients (7.3%) because the surgeons were unaware of the study procedures (n = 3), were unable to reach the tumor tissue with cold cup biopsy forceps (n = 2), or did not suspect the lesion to be high-grade BC during surgery (n = 1). In 6 patients (7.3%), tissue was insufficient (fewer than two cold-cup biopsies; n = 3), cauterized (n = 2), or accidentally frozen during transport (n = 1). Two patients (2.4%) were not diagnosed with BC but with ovarian carcinoma or diffuse large B-cell lymphoma. The remaining 65 patients met the eligibility criteria and were included in the study (Fig. 1A). An overview of patient characteristics is provided in Table 1.

Fig. 1.

Study procedures and subcohorts for primary and secondary end point analyses. (A) Patient cohort stratified by diagnosis. (B) Schematic depiction of study procedures. (C) Subcohorts for primary end point analysis: successful completion of ex vivo three-dimensional microtumor testing within 14 d after tissue collection and secondary end point analyses: association between ex vivo and patient response to platinum-based chemotherapy. MIBC = muscle-invasive bladder cancer; NMIBC = non–muscle invasive bladder cancer; 3D = three dimensional.

Table 1.

Characteristics of participants by cohort^a

	NMIBC (n = 29; 45%)	MIBC (n = 36; 55%)	p valueb
Hospital, n (%)			0.22
Amphia	8 (12.3)	16 (24.6)
Haga	11 (16.9)	5 (7.7)
Erasmus MC	6 (9.2)	7 (10.8)
Franciscus Gasthuis en Vlietland	2 (3.1)	5 (7.7)
Medisch spectrum Twente	2 (3.1)	3 (4.6)
Age (yr), median (range)	72 (46–82)	72 (42–96)	0.78
Sex, n (%)			1.00
Male	21 (32.3)	26 (40.0)
Female	8 (12.3)	10 (15.4)
Clinical tumor stage, n (%)			<0.0001
Ta	11 (16.9)	–
T1	18 (27.7)	–
T2	–	18 (27.7)
T3	–	17 (26.2)
T4	–	1 (1.5)
Clinical nodal stage, n (%)			0.04
N0	29 (44.6)	28 (43.1)
N1	–	3 (4.6)
N2	–	4 (6.2)
N3	–	1 (1.5)
Clinical metastatic stage, n (%)			0.01
M0	29 (44.6)	29 (44.6)
M1	–	7 (10.8)
NMIBC EAU risk group, n (%)			NA
Intermediate	8 (12.3)	–
High	18 (27.7)	–
Very high	3 (4.6)	–

NMIBC = non–muscle invasive bladder cancer; MIBC = muscle-invasive bladder cancer; EAU = European Association of Urology; NA = not applicable.

^aPercentages may not total 100 because of rounding.

^bThe p values were calculated using the Wilcoxon rank-sum test for continuous and Fisher exact test for categorical variables.

We confirmed the presence of tumor in the tissue used for ex vivo microtumor establishment through pathological evaluation (H&E staining) and detection of BC-specific mutations (SNaPshot analysis; Fig. 1B). H&E staining showed urothelial cancer in all 65 samples. Additionally, frequent BC hot spot mutations were detected in the promoter of hTERT (78% mutated) and the coding regions of FGFR3 (20% mutated) and PIK3CA (13% mutated). A detailed overview of patient and sample characteristics is provided in Supplementary Table 1.

3.2. Establishment of an ex vivo microtumor testing platform for both NMIBC and MIBC

Completion of ex vivo microtumor testing within 14 d was successful in 82.8% (95% confidence interval [CI] = 66.5–92.4) of patients with NMIBC and 66.7% (95% CI = 50.3–79.8) of patients with MIBC (Fig. 1C). Logistic regression did not identify a statistically significant association between chronological sample order and successful microtumor testing (Fig. 2A). Nevertheless, the data suggest a sustained increase in success rates for MIBC samples beginning in the second half of 2023. Potential increases in success rates were achieved through optimization of the mechanical dissociation process. For successful samples, the median percent coefficient of variation (%CV) was 12.5% ± 6.4% (well below the 20% threshold indicating a precise assay), and the median Z′-factor was 0.60 ± 0.24 (exceeding the 0.5 benchmark for a robust assay).

Fig. 2.

Feasibility of ex vivo drug sensitivity testing in bladder cancer. (A) Sample success rates for NMIBC and MIBC over time. Logistic regression did not identify a statistically significant association between chronological sample order and successful microtumor testing (p = 0.82 for NMIBC and p = 0.55 for MIBC). (B) Heat map summarizing patient-specific ex vivo drug responses and tumor stage group. Ex vivo response was normalized within treatment, and the number depicts the percentile relative to the cohort. Samples with resistant (blue), sensitive (green), or drug-specific (black) ex vivo drug response profiles are highlighted. MIBC = muscle-invasive bladder cancer; NMIBC = non–muscle invasive bladder cancer.

Overall, a median of two different drugs was successfully tested per patient (IQR = 1–3). Some patients were uniformly sensitive (eg, MST-4 and EMC-6) or resistant (eg, SFG9 and Haga-7) to all tested drugs, whereas others showed drug-specific sensitivity (eg, EMC-8 and EMC-11; Fig. 2B). Responses to enfortumab vedotin (EV) were observed in 50% (3/6) of the patients (Supplementary Fig. 1A). No significant differences in drug responses were observed between samples that were treated on the same day and those treated on the next day (Mann-Whitney U test; Supplementary Fig. 1B). As expected, cisplatin and carboplatin responses were significantly correlated (r = 0.662, p = 0.001; Supplementary Fig. 1C), whereas no correlation was observed between cisplatin and gemcitabine (r = 0.024, p = 0.905) or between gemcitabine and carboplatin (r = 0.21, p = 0.212; Supplementary Fig. 1C). No significant differences in single-agent drug responses were observed when comparing ex vivo drug responses between NMIBC and MIBC samples (Supplementary Fig. 1D). Interestingly, gemcitabine responses showed an asymmetric distribution among patients with NMIBC (D’Agostino–Pearson K² = 5.997, p < 0.05), highlighting a subgroup of patients with NMIBC who had a favorable ex vivo response to gemcitabine (Supplementary Fig. 1D).

Together, these results confirm the successful establishment of a robust, high-quality ex vivo microtumor platform for both NMIBC and MIBC.

3.3. Ex vivo drug response profiles correlate with patient response to platinum-based chemotherapy

The correlation between ex vivo drug responses and patient response to therapy was evaluated in patients with MIBC treated with platinum-based chemotherapy (n = 16). Nine of the 16 patients treated with NAC (n = 4) or palliative platinum-based chemotherapy (n = 5) had successful ex vivo drug testing results and were included for analysis (Figs. 1C and 3A–B; Supplementary Fig. 2A–B). Patient-specific chemosensitivity scores were correlated with the pathological response in patients receiving NAC or with the clinical response (RECIST 1.1) in patients receiving palliative treatment. General chemosensitivity scores significantly separated patients who responded (mean ± SEM = 0.650 ± 0.107) from nonresponders (mean ± SEM = 0.252 ± 0.081; Mann–Whitney U test, p < 0.02; Fig. 3B–C). To support clinical application, an easy-to-use reporting system that makes ex vivo drug testing accessible to clinicians was developed (Fig. 3D).

Fig. 3.

Ex vivo response to platinum-based chemotherapy correlates with patient response. (A) Clinical course of patients with MIBC treated with platinum-based chemotherapy. (B) Summary of general chemosensitivity score as determined through ex vivo 3D micro tumor testing and matched clinical response to platinum-based chemotherapy according to pathological response group or RECIST 1.1 (mean ± SEM; Mann-Whitney U, * p < 0.05). (C) Clinical chemotherapy response according to RECIST 1.1 as illustrated by pre- and posttreatment computerized tomography scans from patients treated with platinum-based chemotherapy (EMC-2; gemcitabine/carboplatin, EMC-13 gemcitabine/cisplatin). Red arrows indicate metastatic lesions. (D) General chemosensitivity reporting, as illustrated for EMC-13 (sensitive) and EMC-2 (resistant). CTx = chemotherapy; cCR = clinical complete response; cPR = clinical partial response; cSD = clinical stable disease; cPD = clinical progressive disease; pCR = pathological complete response; pPR = pathological partial response; pNR = pathological non-response; TURBT = transurethral resection of the bladder tumor.

4. Discussion

The search for reliable biomarkers to personalize BC treatment has long been hampered by the absence of robust predictors, leaving many patients exposed to unnecessary toxicity, disease progression, and increased health care costs. In this study, a successful (>80% for both NMIBC and MIBC) and high-quality (good %CV and Z-prime) ex vivo microtumor platform using fresh tumor tissue collected during routine procedures (TURBT and RC) was established, with results generated within clinically relevant timelines (<14 d). Ex vivo microtumor responses significantly correlated with patient responses to platinum-based chemotherapy, providing initial evidence that this approach may guide clinical decision-making in BC.

For patients with NMIBC, current European guidelines still largely rely on a one-size-fits-all approach with IVC or BCG [1]. Gemcitabine has shown efficacy comparable to that of mitomycin C in reducing recurrence [17], and new delivery methods are being developed [18]. Because gemcitabine is not routinely administered in our region, direct clinical correlation could not be evaluated. Nevertheless, the observed patient-specific ex vivo sensitivity supports further investigation of microtumor testing for NMIBC stratification.

In MIBC, sequencing approaches have shown promise for predicting responses to NAC but lack prospective validation [19], [20], [21], [22], [23], [24]. Unlike static biomarkers, functional drug testing integrates multiple factors involved in treatment response (eg, mutations, protein expression, and stromal components) into a single prediction score. Consistent with findings in other malignancies [25], [26], [27], [28], [29], [30], ex vivo microtumor testing effectively predicted patient responses to platinum-based chemotherapy despite the limited cohort size. Future studies should expand patient numbers, define optimal chemosensitivity thresholds, and validate performance prospectively.

Antibody-drug conjugates (ADCs), such as EV, and immunotherapies such as pembrolizumab, have recently entered MIBC treatment guidelines, particularly in metastatic disease. Although immunotherapies were not evaluated and EV was tested in only a limited number of patients, the successful implementation of this approach in other indications supports the feasibility of extending it to BC [16]. Importantly, chemotherapy remains a cornerstone of nonmetastatic MIBC treatment, underscoring the relevance of the current findings.

Several limitations warrant consideration. The need for fresh tissue forces drug testing before a definitive diagnosis (NMIBC or MIBC), risking the assessment of patients who will not receive therapy. Second, BC is heterogeneous and intratumoral heterogeneity presents a significant challenge for predicting therapy response using only a small tumor fragment. Furthermore, pathological response after NAC reflects the combined effects of chemotherapy and surgery and should therefore be interpreted as a surrogate end point rather than a direct measure of chemotherapy efficacy. Irrespective, ex vivo microtumor testing demonstrated predictive value (Fig. 3B), supporting further evaluation in larger cohorts.

Limited biopsy material remains a practical challenge, restricting both microtumor yield and the number of drugs tested per patient. Although initial MIBC success rates were modest (50%), optimization increased success rates to >80% and >90% for MIBC and NMIBC, respectively. Future studies should explore platinum-gemcitabine combination testing, reduce tissue requirements, expand drug panels to include immunotherapies and ADCs, and identify factors affecting assay success to further increase translational relevance. Cryopreserved BC tissue may provide an opportunity for repeat testing and will be evaluated in future studies [31].

Other functional approaches under investigation for predicting responses in patients with BC include tumor tissue slices and patient-derived organoids (PDOs) [31], [32], [33], [34]. Tumor tissue slices retain the stromal component but remain viable for only a few days because of limited nutrient and oxygen diffusion, thereby hampering drug profiling [32]. PDOs enable medium-throughput drug screening but often lose stromal compartments and heterogeneity during passaging and typically do not meet clinical timelines [33]. Short-term PDOs more closely resemble our approach but are dissociated into single cells before seeding. Short-term PDOs have been demonstrated to reflect the phenotypic and genetic heterogeneity of primary tumors, and molecular markers have been related to ex vivo drug responses [31], [34]. Their ability to stratify patients with IR NMIBC for various IVC regimens is currently under investigation [35].

5. Conclusions

In this study, a successful (>80% for both NMIBC and MIBC), robust, and high-quality ex vivo microtumor platform was established using fresh tumor tissue collected during routine procedures (TURBT and RC), with a turnaround time within clinical timelines (<14 d). Ex vivo microtumor responses significantly correlated with patient responses to platinum-based chemotherapy, thereby providing the first evidence that ex vivo microtumor testing may serve as a predictive biomarker to guide clinical decision-making. If further validated, our approach may help guide the choice between platinum-based NAC and direct cystectomy for patients with MIBC and prioritize IVC regimens for patients with NMIBC.



Author contributions: Esmee Koedoot and Tahlita C.M. Zuiverloon had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.



Study concept and design: Scholtes, Ceton, Koedoot, van der Meer, Vader, Boormans, Zuiverloon.

Acquisition of data: Scholtes, Ceton, Koedoot, Sijsenaar, Montero, Roeland, van der Meer.

Analysis and interpretation of data: Scholtes, Ceton, Koedoot, Sijsenaar, Montero, Roeland, van der Meer, van Leenders.

Drafting of the manuscript: Scholtes, Ceton, Koedoot.

Critical revision of the manuscript for important intellectual content: Koedoot, van der Meer, van Soest, van Leenders, Vader, Boormans, Zuiverloon.

Statistical analysis: Scholtes, Ceton, Koedoot, van der Meer.

Obtaining funding: Vader, Boormans, Zuiverloon.

Administrative, technical, or material support: van Soest, Leijte, Roshani, Korthorst, Vader, Boormans, Zuiverloon.

Supervision: Koedoot, van der Meer, Vader, Zuiverloon.

Other: None.



Financial disclosures: Esmee Koedoot and Tahlita C.M. Zuiverloon certify 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: Esmee Koedoot, Timothy J.P. Sijsenaar, Dieudonné J. van der Meer, and Willemijn Vader report employment with VitroScan.



Funding/Support and role of the sponsor: The name of the organization or organizations that had a role in sponsoring the data and material in the study include the following: Erasmus MC, Health∼Holland PPP, VitroScan. All funding or other financial support, and material support for this research and/or work are clearly identified hereunder. The specific role of the funding organization or sponsor includes design and conduct of the study, collection of the data, management of the data, analysis, interpretation of the data, preparation, review, and approval of the manuscript.



Acknowledgements: The authors thank the patients for participating in the study. The study was supported by the following grants: Erasmus MC mRACE grant (#111296, T. Zuiverloon), Health∼Holland PPP Allowance (EVITA, #EMCLSH21006, VitroScan, J. Boormans and T. Zuiverloon), Health∼Holland PPP Allowance (MIBC-Org # LSHM23065, T. Zuiverloon), Erasmus MC Foundation grant (#20926, T. Zuiverloon), MKB Innovatiestimulering Topsectoren Zuid-Holland (MIT ZH – R&D, #DOS-202200005490, VitroScan).

Associate Editor: Maria Carmen Mir

Statistical Editor: Melissa Assel

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Supplementary Data 1

Detailed methods on ex vivo microtumor drug sensitivity testing.

Supplementary Data 2

Detailed overview of patient and sample characteristics.

Supplementary Data 3

Overview of all supplementary figures.