








































This is an open access article under the terms of a license that permits non-commercial use, provided the original work is properly cited.  
© 2023 The Authors. Société Internationale d'Urologie Journal, published by the Société Internationale d'Urologie, Canada.

SIUJ.ORG SIUJ  •  Volume 4, Number 4  •  July 2023

Key Words Competing Interests Article Information

Bladder cancer, minimal residual disease, 
next generation sequencing, cell-free DNA, 
circulating tumor DNA, urinary tumor DNA

None declared. Received on May 11, 2023 
Accepted on July 1, 2023

This article has been peer reviewed. 
Soc Int Urol J. 2023;4(4):247–256

DOI: 10.48083/ WJMB7232

247

ORIGINAL RESEARCH — LIQUID BIOPSY

Utilizing Cell-Free Urinary and Plasma Tumor DNA  
to Predict Pathologic Stage at Radical Cystectomy

Prithvi B. Murthy,1 Billie Gould,2 Facundo Davaro,1 Pan Du,2 Lucia Camperlengo,1 Shreyas Naidu,1  
Kyle Rose,1 Scott M. Gilbert,1 Philippe E. Spiess,1 Wade Sexton,1 G. Daniel Grass,3 Rohit Jain,1  
Xuefeng Wang,4 Joshua J. Meeks,5 Andrea Necchi,6,7 Liang Cheng,8 Shidong Jia,2 Roger Li1

1 Department of Genitourinary Oncology, Moffitt Cancer Center, Tampa, United States 2 Predicine, Hayward, United States 3 Department of Radiation Oncology, 
Moffitt Cancer Center, Tampa, United States 4 Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, United States 5 Department of Urology, 
Northwestern University, Feinberg School of Medicine, Chicago, United States 6 IRCCS San Raffaele Hospital and Scientific Institute, Milan, Italy  
7 Vita-Salute San Raffaele University, Milan, Italy 8 Department of Pathology and Laboratory Medicine, Brown University, Providence, United States

Abstract

Objective To assess the ability of cell-free urinary and plasma tumor DNA (cfDNA) to predict pathologic stage at 
radical cystectomy for patients with clinical muscle-invasive bladder cancer.

Methods A total of 25 patients with clinical muscle-invasive bladder cancer were enrolled before undergoing radical 
cystectomy. Blood and urine were collected before surgery. The 600-gene PredicineATLAS panel was used to sequence 
blood buffy-coat germline DNA, plasma cfDNA, and urine cfDNA samples. Low-pass whole genome sequencing was 
performed on plasma- and urine-derived cfDNA. CfDNA tumor fraction (TF), genome-wide copy number burden 
(CNB), and estimated tumor mutational burden (TMB) were measured in both plasma and urine samples and their 
correlation with pathologic T-stage was examined.

Results Three of 25 plasma samples had insufficient cfDNA. In 22 of 22 plasma samples and 24 of 25 urine samples, 
at least one nonsynonymous somatic variant was detected. Across the cohort, 44% of plasma variants were concordant 
with paired urine variants. The mean number of variants did not differ between noninvasive (< pT1/pN0) and invasive 
disease (≥ pT1 or N+) for both plasma (8 vs. 9.5 variants; P = 0.85) and urine (33.7 vs. 30 variants; P = 0.45). A strong 
correlation was observed between urine TF and urine CNB score within patients (rv = 0.92). Plasma TF (r  = 0.38), 
urine TF (r  =  0.21), and urine CNB score (r  =  0.16) exhibited positive correlations with pT stage. Patients with 
carcinoma in situ (CIS) had higher mean urine TF and CNB scores ( P = 0.07 and P = 0.05, respectively). Plasma TF 
and CNB score did not correlate with the presence of CIS.

Conclusions Combining plasma- and urine-based cfDNA analysis may help identify patients with residual disease 
at radical, although we were unable to predict pathologic T-stage based on these metrics.The presence of CIS may 
contribute to greater urinary CNB and TF levels. Considering CIS in the analysis may improve the ability to correlate 
tumor metrics with pathologic stage. Low-pass whole genome sequencing–derived urinary CNB correlates strongly 
with urinary TF and may provide a less resource-intensive method for future longitudinal disease monitoring.

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250 ng of gDNA, 5–30 ng of plasma cfDNA, and up to  
30 ng urinary cf DNA from urine supernatant were 
used for next-generation sequencing (NGS) library 
preparation, panel-based hybridization, and enrichment 
prior to 150-bp paired-end sequencing on the Illumina 
NovaSeq 6000 platform (Illumina, San Diego, California, 
US). The plasma samples were sequenced using the 600-
gene CLIA-validated PredicineATLAS panel assay. The 
urine samples were sequenced using the PredicineWES+ 
whole-exome panel, which includes approximately 
20 000 genes and encompasses all regions present in the 
ATLAS panel genes. In this study, we compared variants 
in ATLAS panel genes only. In parallel, both plasma and 
urine samples were sequenced using low-pass (1–3X) 
whole genome sequencing (WGS). 

Analyses of NGS data
The data was analyzed using the Predicine DeepSea 
analysis pipeline, which begins with the raw sequencing 
data (BCL files) and produces the final variant calls. 
Brief ly, the pipeline first performs adapter trimming, 
barcode checking, and correction, followed by paired 
FASTQ read alignment to the human reference genome 
build hg19 using the BWA software package. Candidate 
variants, consisting of point mutations, small insertions, 
and deletions, are identified across the targeted regions 
covered in the panel. 

Variant calling and annotation
Candidate variants with low base quality, mapping 
scores, and other quality metrics are filtered as part of 
the DeepSea pipeline. Sequencing and polymerase chain 
reaction (PCR) errors are also corrected using a previously 
described algorithm[11]. White-list variant annotations 
are applied to genomic regions that are found to be 
mutated at high frequency in cancer datasets from the 
Catalogue Of Somatic Mutations In Cancer (COSMIC), 
The Cancer Genome Atlas (TCGA), and internal 
Predicine samples. In general, a variant identified in 
cfDNA is considered a somatic mutation only if (1) at least 
three distinct fragments—at least one of the fragments 
with double-strand support; i.e. the mutation is observed 
on both DNA strands—contain the mutation; and (2) 
the mutant allele frequency is higher than 0.25%, or 0.1% 
for white-list mutations—ie, mutations are observed at 
high frequency across different cancer types in public 
cancer databases; and (3) the ctDNA variant–containing 
fragments are significantly over-represented compared 
to the matched PBMC sample, as determined by a Fisher 
exact test (P value < 0.01 and odds ratio > 3). Non-white–
list variants with high variant frequency (> 30%) are 
considered suspicious germline variants. Gene-level copy 
number variants are reported for both urine and plasma at 
CLIA-validated thresholds: copy number ≥ 2.18 (gain) or  
≤ 1.85 (loss)[12,13]. 

Candidate somatic mutations were annotated for their 
effect on protein-coding genes as well as probable patho-
genicity using the ClinVar database and annotation tool 
Varsome[14]. Intronic and silent changes were excluded 
from our analyses, while missense mutations, nonsense 
mutations, frameshifts, or splice site alterations were 
retained. We also excluded common germline variants 
annotated in the 1000 Genomes, ExAC, gnomAD, and 
KAVIAR databases with a population allele frequency > 
0.5%. Finally, CHIP variants were identified by compar-
ing them with matched PBMC samples. Variants in 
common CHIP genes (DNMT3A, TET2, ASXL1, JAK2, 
and PPM1D) were called CHIP mutations if there were 
supporting mutated fragments in matched PBMC 
samples. Likely CHIP mutations were called for variants 
in genes such as TP53, ATM, CHEK2, SF3B1, etc., which 
often share mutations in both CHIP and solid tumors, 
if there were supporting mutated fragments in matched 
PBMC samples and the Fisher exact test was not statisti-
cally significant.

Copy number alterations and copy  
number burden
Copy number variation was first estimated at the gene 
level using the NGS panel data. The in-house pipeline 
calculates the on-target unique fragment coverage based 
on consensus BAM files, which are first corrected for GC 
bias and then adjusted for probe-level bias (estimated 
from a pooled reference). Each adjusted coverage profile 
is self-normalized (assuming diploid status of each 
sample) and then compared against correspondingly 
adjusted coverages from a group of normal reference 
samples to estimate the significance of each copy number 
variant. To call an amplification or deletion of a gene, we 
required the absolute z-score and copy number change to 
pass minimum thresholds. 

We measured genome-wide copy number burden 
with PredicineCNB[15]. This score represents a compre-
hensive genome-wide measure of copy number varia-
tion adapted from the previously developed ichorCNA 
method. To calculate the CNB score, the ichorCNA algo-
rithm was applied to GC and mappability-normalized 
reads to estimate plasma and urine copy number varia-
tions using a hidden Markov model (HMM)[16]. First, 
we measured segment level (1 MB) copy number devi-
ation as the log2 ratio of the normalized reads between 
a sample and normal plasma background (or used a 
normal gDNA background for urine CNB). Then, we 
quantified arm-level CNV deviation as the average of 
segment CNVs across each chromosome arm. Our 
method also accounts for local cfDNA fragment-size 
distributions. Finally, we calculated sample-level copy 
number burden (CNB score) as the sum of absolute 
z-score of arm-level CNV deviation, where a higher 
CNB score indicates a greater absolute CNV abnormality 
compared to the normal background. 

Introduction

Survival following radical cystectomy (RC) for urothelial 
carcinoma of the bladder is strongly influenced by the 
pathologic T-stage and the presence of lymph node 
metastasis[1,2]. Patients with non–organ-confined 
disease or lymph node involvement have nearly 50% 
lower survival rates at 5 years. The ability to predict 
minimal residual disease has profound implications for 
patient management, especially considering that more 
than 60% of patients who are pT0 on transurethral 
resection before radical cystectomy harbor residual 
disease[3]. Individuals with complete response or 
minima l residua l disease following neoadjuvant 
chemotherapy may opt for bladder-sparing therapies, 
while those with more aggressive disease may be 
counseled to receive additional cycles of chemotherapy 
or undergo prompt surgical resection. 

Cell-free circulating tumor DNA in the plasma 
(ctDNA) and urine (utDNA) are emerging as promis-
ing biomarkers for identifying the presence of bladder 
cancer, predicting pathologic complete response (pCR), 
detecting disease recurrence following RC, and assess-
ing response to adjuvant immunotherapy[4–9]. Though 
significant inroads have been made to maximize clini-
cal utility, neither ctDNA nor utDNA has been shown to 
predict pathologic T-stage following RC. Instead, binary 
outcomes related to the presence or absence of ct/utDNA 
have been associated with survival following radical 
cystectomy[6,8]. In this study, we employed ultra-low-
pass whole genome sequencing and ultra-deep–targeted 
sequencing of both utDNA and ctDNA to investigate the 
potential of these biomarkers for predicting pathologic 
stage prior to RC.

Materials and Methods
After obtaining institutional review board (IRB) 
approval (MCC 21616), we prospectively enrolled  
25 patients diagnosed with muscle-invasive bladder 
cancer (MIBC) at H. Lee Moffitt Cancer Center between 
November 2021 and August 2022, prior to their radical 
cystectomy. Patients with prior history of upper tract 
urothelial carcinoma or non-urothelial bladder cancer 
were not eligible for enrollment. A previous history of 
nonmuscle-invasive bladder cancer, with or without 
history of intravesical treatment, was not an exclusion 
criterion. All patients provided written informed 
consent and the study was approved by the institutional 
review board. Treatment and surveillance followed 
accepted national guidelines. The multidisciplinary 
treatment team made recommendations regarding 
the omission of neoadjuvant chemotherapy, the 
performance of template-based lymphadenectomy, 
and the administration of adjuvant treatment. Board-
certified genitourinary pathology specialists reviewed 
the pathologic specimens. Postsurgical surveillance 
consisted of cross-sectional imaging, urine cytology, and 
laboratory assessment every 3 to 6 months. Peripheral 
blood (10 mL) was collected in EDTA-containing tubes 
(Streck cell-free DNA BCT, La Vista, Nebraska, US) 1 to 
2 hours prior to surgery. Within 2 hours of collection, 
whole blood underwent a 2-step centrifugation at 
1600g for 10 minutes, followed by 320g for 10 minutes 
at 10 °C. Plasma, buffy coat, and cell pellets were stored 
at –80 °C. Urine was collected in a sterile container, 
with a minimum of 25 mL and a maximum of 45 mL 
immediately transferred into a 50-mL conical tube. 
Within 15 minutes of collection, 5 mL of Streck Urine 
Preserve was added. The capped specimen was gently 
inverted 10 times, followed by centrifugation at 3200g 
for 10 minutes at 25 °C. The supernatant was transferred 
without disturbing the cell pellet and frozen at –80 °C. 

DNA extraction
Germline DNA (gDNA), and plasma cfDNA derived 
from peripheral blood mononuclear cells (PBMCs) 
were extracted using a combination of established 
proprietary kits and in-house column-based methods, 
as previously described[10]. Plasma and urinary 
cfDNAs were extracted using a bead-based extraction 
protocol. Twenty-three of 25 patients had adequate 
preoperative plasma samples for cfDNA extraction.  
The quantity and quality of purified cfDNA were 
assessed using a Qubit fluorimeter (ThermoFisher 
Scientific, Waltham, Massachusetts, US) and Bioanalyzer 
2100 (Agilent Technologies, California, US). For cfDNA 
samples with significant genomic contamination from 
peripheral blood cells, a bead-based size selection 
was performed to remove large genomic fragments 
(AMPure XP beads, Beckman Coulter, California, 
US). After quality assessment and quantification, up to  

Abbreviations 
CNVs copy number variants
cfDNA cell-free DNA 
ctDNA circulating tumor DNA
gDNA germline DNA
MAF mutant allele fraction 
MIBC muscle-invasive bladder cancer
NAC neoadjuvant chemotherapy
NGS next-generation sequencing
PBMCs peripheral blood mononuclear cells
RC radical cystectomy
SNVs single nucleotide variants
TF tumor fraction
TMB tumor mutational burden
utDNA urinary tumor DNA
WGS whole genome sequencing

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Variations in cfDNA metrics based on tumor 
stage and presence of CIS
We assessed the cfDNA tumor fraction (TF), genome-
wide CNB score, and estimated TMB using both plasma 
and urine samples. TF, determined based on observed 
MAFs in the panel, had a mean of 3.5% (range, 0.66%–
11.5%) in plasma and a mean of 14.2% (range, 0%–
71.0%) in urine. Genome-wide CNB score, determined 
based on copy number variation across the genome 
using low-pass sequencing, was also higher in the urine 
(mean, 7.6; range, 5.3–11.4), versus plasma (mean, 4.8; 
range, 3.6–7.3). There was a positive correlation between 
tumor fraction and CNB score calculated from plasma 
and urine (Online Supplementary Figure 1). A strong 
correlation was also observed between urine tumor 
fraction and urine CNB score within patients (r = 0.92). 

Using these metrics, we assessed the correlation 
between preoperative ut/ctDNA burden and pathologic 
T-stage identified in the RC specimen. Plasma and urine 
TF showed weak correlations with T-stage (Figure 3A, 
r = 0.38 and 0.21, respectively). Urine CNB score also 
showed a positive correlation with T-stage (Figure 3B, 
r  =  0.16). The number of variants observed in plasma 
and subsequently the estimated plasma TMB showed 
the greatest difference between the group of 3 patients 
with noninvasive disease and the 22 patients with 
invasive disease, although the difference did not reach  
statistical significance (pTMB, 0.7 vs. 3.4, P  =  0.12, 

FIGURE 1.

Online Supplementary Table 3). Similarly, neither 
urine- or plasma-derived CNB score nor tumor fraction 
could distinguish between noninvasive and invasive 
disease in this small group. Despite the study lacking 
statistical power to evaluate the accuracy of combin-
ing metrics for predicting the presence of invasive vs. 
noninvasive disease in this cohort of patients, we noted 
that several patients with fewer than 5 variants detected 
in plasma still had a high urinary CNB score (Online 
Supplementary Figure 2). Thus, a combined approach 
using both plasma variant detection and urinary 
low-pass sequencing to determine CNB score might be 
useful for early detection of MIBC. 

It is important to note that utDNA metrics were 
strongly influenced by the presence of CIS. Both urine 
mean TF and CNB score were higher in patients with 
pure or concomitant CIS (Figures 4 A and B, P = 0.07 
and P = 0.05, respectively). The correlations remained 
statistically significant or marginally significant while 
controlling for pathologic T-stage within CIS/non-CIS 
groups (multivariate regression coef = 0.63, P = 0.047 
and coef  =  4.8, P  =  0.08, respectively). In contrast, 
plasma TF and CNB score did not exhibit significant 
correlations with the presence of CIS.  

Discussion
Deep sequencing of utDNA and ctDNA is increasingly 
used to help determine minimal residual disease in 

Gene fusions
DNA rearrangement was detected by identifying the 
alignment break points based on the BAM files before 
consensus filtering. Suspicious alignments were filtered 
based on repeat regions, local entropy calculation, and 
similarity between reference and alternative alignments. 
To report a DNA fusion, larger than 3 unique alignments 
(at least one of them double stranded) were required.

Tumor fraction
The ctDNA fraction was estimated based on the 
mutant allele fraction of autosomal somatic mutations, 
as described prev iously[17]. Brief ly, under t he 
conservative assumption that each SNV may have loss 
of heterozygosity, the mutant allele fraction (MAF) and 
ctDNA fraction are related as MAF  =  (ctDNA * 1) / 
[(1 – ctDNA) * 2 + ctDNA *1], and so ctDNA = 2 / ((1 / 
MAF) + 1). Somatic mutations in genes with a detectable 
copy number gain were omitted from ctDNA fraction 
estimation, thus only a subset of samples could have the 
ctDNA fraction accurately estimated from mutation data.

TMB score estimation
Blood- and urine-based tumor mutational burden 
(TMB) was defined as the number of somatic coding 
SNVs, including synonymous and nonsynonymous 
va ria nts, w it hin pa nel ta rget reg ions. Because 
TMB estimation considers all variants (including 
synonymous), higher variant call specificity is required. 
More stringent cutoffs were used for variant calls, and 
only variants with allele frequency ≥ 0.35% were used 
in score calculation. The TMB score was normalized by 
the total effective targeted panel size within the coding 
region. Samples with the maximum somatic allelic 
frequency (MSAF) < 0.7% were excluded from TMB 
estimation.

Outcomes and statistical analyses
The primary objective was to investigate the ability of 
preoperative plasma and urine to predict pathologic 
disease stage at cystectomy. All differences between 
patient group means were tested using a Wilcoxon 
test. Correlations between tumor burden metrics and 
pathologic T-stage rank were measured using the 
Spearman correlation coefficient. Multivariate models 
to predict CIS were fitted to the entire dataset using 
binomial logistic regression with pathologic tumor stage 
as a covariate. All tests were conducted in R version 4.3.0.

Results
Cohort clinicopathologic features and 
specimen analysis
A total of 25 patients with clinically muscle-invasive 
bladder cancer underwent RC with curative intent 
(Online Supplementary Table 1). All but 2 patients 
were diagnosed with MIBC based on transurethral 

resection of bladder tumor. Two patients with T1 disease 
on transurethral resection had cross-sectional imaging 
concerning for muscle invasion and were considered 
to have clinical MIBC. Nine received neoadjuvant 
chemotherapy (NAC) followed by RC, and 16 underwent 
upfront RC. All surgical procedures were performed at a 
single institution. Prior to surgery, both urine and plasma 
were collected from each patient on the day of RC. All 25 
urine samples underwent quality control, and all of them 
passed urinary cell-free DNA extraction quality control. 
However, 3 plasma samples failed the quality control test. 
Of these, 2 plasma samples had low sample collection 
volume (< 2 mL), resulting in low cfDNA extraction yields 
and the third sample had low sequencing depth, likely due 
to sample degradation. The plasma samples that passed 
the quality checks were subjected to sequencing across 
regions in the PredicineATLAS 600 gene targeted cancer 
panel using 150 bp paired end reads. Plasma samples 
were sequenced at an average target depth of 31 000X and 
an average unique fragment coverage of 3454 fragments 
(n  =  22 patients). Urine samples were sequenced at an 
average depth of 14 000X and an average unique fragment 
coverage of 3077 fragments (n = 25 patients). Overall, we 
detected at least one nonsynonymous somatic variant in 
all plasma samples and 24 of 25 urine samples. 

Across the cohort, we detected 656 non-synonymous 
single nucleotide variants (SNVs) and indels, 377 gene-
level copy number variants (CNVs), and 5 fusion muta-
tions (Online Supplementary Table 2). Plasma samples 
exhibited a median of 5 SNVs/indels (range, 1–36) and 
1 CNV (range, 0–7). In contrast, patient urine samples 
showed a median of 17 SNVs/indels (range, 0–77) and 
a median of < 1 CNV (range, 0–54). For concordant 
variants, the mutant allele frequency (MAF) was almost 
always higher in urine than in plasma (Figure 1A). 
Overall, 44% of plasma variants were concordant with 
paired urinary variants (Figure 1B). Seven nonconcor-
dant plasma variants and 44 nonconcordant urine muta-
tions occurred within white-list genes (ie, genes mutated 
at high frequency across cancer types). Concordance 
between plasma- and urine-derived variants ranged 
between 0% to 70% within patients (Figure 1C). 

We observed somatic alterations in several genes 
previously associated with bladder cancer (Figure 2)[18]. 
The most common mutations occurred in TERT 
promoter (59%), KMT2D (59%), TP53 (55%), ARID1A 
(45%), and KDM6A (41%). We also observed frequent 
mutations in genes associated with MIBC, such as 
EGFR (28%), RB1 (27%), ERBB2 (27%), ATM (20%), 
and FGFR3 (12%) (Online Supplementary Table 2). 
Overall, there was no significant difference in the mean 
number of variants between patients with noninvasive 
(< pT1/pN0) and invasive (≥ pT1 or N+) disease for both 
plasma (8 vs. 9.5 variants; P = 0.85) and urine (33.7 vs  
30 variants; P = 0.45).

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NAC followed by RC[8]. The researchers employed a 
tumor-informed approach to select 50 somatic variants 
per patient from transurethral resection specimens to 
create a custom sequencing panel. cfDNA positivity was 
established by comparing patient-specific variants to 
all nonpatient-specific variants, and cfDNA levels were 
monitored throughout the NAC course using mean vari-
ant allele frequency. While the investigators were able 
to predict treatment response to NAC based on utDNA 
and ctDNA clearance, they did not identify a significant 

FIGURE 3.

correlation between mean variant allele frequency of the 
samples collected after NAC but prior to RC and patho-
logic stage at RC. In our study, 6 of 9 patients treated 
with NAC showed a decrease in urinary tumor fraction 
post-treatment (median change in TF, –1.3%, data not 
shown). Yet, neither urinary tumor fraction nor CNB 
levels could distinguish between noninvasive and inva-
sive disease. Future studies should focus on the specific 
alterations more frequently found in noninvasive versus 
invasive bladder cancer to improve disease staging.

various bladder cancer settings[5,6,8,9,19]. Significant 
advances in next-generation sequencing technologies 
and the integration of genome-wide tumor DNA metrics 
have improved the ability to predict pathologic complete 
response to neoadjuvant chemotherapy and estimate 
survival after RC[6]. However, the accurate prediction 
of pathologic T-stage using quantitative cfDNA metrics 
has not yet been demonstrated. 

Consistent with previous studies, urine-derived 
cfDNA exhibited a larger spectrum of unique tumor-de-
rived alterations and higher mean mutant allele 

FIGURE 2.

frequency compared to plasma-derived cf DNA[19]. 
Furthermore, we obser ved a positive correlation 
between tumor fraction and CNB score derived from 
both utDNA and ctDNA with increasing pathologic 
T-stage. However, in this pilot study, we were unable to 
accurately predict the presence of invasive versus nonin-
vasive residual disease before cystectomy. 

To examine the role of cfDNA in predicting response 
to NAC, Christensen et al. used a custom next-genera-
tion sequencing panel to longitudinally assess urine and 
plasma samples on a cohort of 92 patients undergoing 

A

B

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cohort received neoadjuvant chemotherapy, which may 
have an unknown impact on sample variant makeup. 
In this study, we lacked the power to test multivariate 
models, but we did find several non-concordant muta-
tions between plasma and urine in white-list cancer-as-
sociated genes, highlighting the utility of mutational 
profiling using both urine and plasma. Future work 
incorporating larger datasets is needed to reassess the 
value of combining cf DNA and clinical features to 
predict the presence of invasive versus noninvasive 
disease. Additionally, further studies should explore 
incorporating the sequencing of personalized markers 
derived from initial tumor tissue biopsy with the panel 
genes used in this study. 

Conclusions
We observed a positive correlation between both utDNA 
and ctDNA metrics with increasing pathologic T-stage in 
patients who underwent radical cystectomy. Specifically, 
patients with CIS on final pathology exhibited higher 
urinary copy number burden and tumor fraction. 
Future assessments that control for the presence of CIS 
may improve the ability to correlate cfDNA metrics with 
pathologic staging. The observed changes in urinary 
tumor burden in response to treatment, along with 
optimized plasma- and urine-based cf DNA metrics, 
may help to identify patients who are candidates for 
bladder preservation. The use of combined plasma- and 
urine-based liquid biopsy techniques holds promise in 
the early detection of MIBC and the measurement of 
minimal residual disease during treatment. 

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prognosis. J Natl Compr Canc Netw.2009;7(1):48–57. doi: 10.6004/
jnccn.2009.0004. PMID: 19176205.

Moreover, we found a strong, direct association 
between CNB score calculated from low-pass WGS and 
panel-derived tumor fraction within the urine. CNB has 
been used as an alternative strategy for ctDNA analysis 
because of its low cost and high sensitivity, even when 
plasma tumor fraction is low[20,21]. In a study aiming 
to predict minimal residual disease using utDNA, 
Chauhan and colleagues developed a random forest 
model incorporating copy number burden–derived 
tumor fraction from ultra-low-pass WGS, whole-ex-
ome–derived estimates of variant allele frequency, and 
inferred tumor mutational burden from all non-si-
lent mutations[6]. Survival estimates derived from this 
model aligned with progression-free and overall survival 
estimates stratified by pathologic complete response, 
helping to establish the utility of CNB-based analyses of 
liquid biopsy data. 

Importantly, we observed that the presence of CIS 
was associated with higher urine CNB scores and TF 
levels. CIS is a well-described high-grade urothelial 
lesion characterized by cellular discohesion among other 
features[10]. Due to the propensity of CIS for exfoliation 
and shedding, the sensitivity of detecting CIS compared 

to other noninvasive high-grade urothelial tumors is 
higher using both urine-based conventional cytology 
and f luorescence in situ hybridization assays[22–24]. 
Our results support these findings and demonstrate 
higher concentrations of tumor-derived cf DNA in the 
urine supernatant in the context of CIS. As the disease 
burden of CIS cannot be reliably estimated due to diffi-
culty with cystoscopic identification, utDNA may serve 
as an indirect measure of disease burden and treatment 
response. In addition, utDNA may serve as a more reli-
able source for genomic studies of CIS, as tissue-based 
studies have been notoriously difficult because of sample 
size limitations and the inability to comprehensively 
capture tumor heterogeneity. As CIS has become an 
important component in therapeutic trials for nonmus-
cle-invasive bladder cancer, a reliable utDNA test that 
correlates with tumor burden and treatment response 
may also serve as a molecular endpoint for future clini-
cal trials[25]. Further investigations of the utDNA profile 
associated with CIS are urgently needed.

Our assessment is limited by small sample size and 
the use of a single preoperative time point for urine and 
plasma sampling. In addition, a subset of our patient 

FIGURE 4.

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11. Newman AM, Lovejoy AF, Klass DM, Kurtz DM, Chabon JJ, Scherer 
F, et al. Integrated digital error suppression for improved detection 
of circulating tumor DNA. Nat Biotechnol.2016;34(5):547–555. doi: 
10.1038/nbt.3520. PMID: 27018799; PMCID: PMC4907374.

12. Yu L, Lopez G, Rassa J, Wang Y, Basavanhally T, Browne A, et al. Direct 
comparison of circulating tumor DNA sequencing assays with targeted 
large gene panels. PLoS One.2022;17(4):e0266889. doi: 10.1371/
journal.pone.0266889. PMID: 35482763; PMCID: PMC9049497.

13. Predicine | Advancing Precision Cancer Therapies. PredicineATLASTM. 
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14. Kopanos C, Tsiolkas V, Kouris A, Chapple CE, Albarca Aguilera M, 
Meyer R, et al. VarSome: the human genomic variant search engine. 
Bioinformatics.2019;35(11):1978–1980. doi: 10.1093/bioinformatics/
bty897. PMID: 30376034; PMCID: PMC6546127.

15. Davis AA, Luo J, Zheng T, et al. Genomic complexity predicts resistance 
to endocrine therapy and CDK4/6 inhibition in hormone receptor–
positive (HR+)/HER2-negative metastatic breast cancer. Clin Cancer 
Res.2023;29(9):1719–1729. doi: 10.1158/1078-0432.CCR-22-2177. 
PMID: 36693175; PMCID: PMC10150240.

16. Adalsteinsson VA, Ha G, Freeman SS, Choudhury AD, Stover DG, 
Parsons HA, et al. Scalable whole-exome sequencing of cell-free 
DNA reveals high concordance with metastatic tumors. Nat 
Commun.2017;8(1):1324. doi: 10.1038/s41467-017-00965-y. PMID: 
29109393; PMCID: PMC5673918.

17. Newman AM, Bratman SV, To J, Wynne JF, Eclov NC, Modlin LA, et al. 
An ultrasensitive method for quantitating circulating tumor DNA with 
broad patient coverage. Nat Med.2014;20(5):548–554. doi: 10.1038/
nm.3519. PMID: 24705333; PMCID: PMC4016134.

18. Rober tson AG, Kim J, Al-A hmadie H, Bellmunt J, Guo G, 
Cherniack AD, et al.; TCGA Research Network. Comprehensive 
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Cell.2017;171(3):540–556.e25. doi: 10.1016/j.cell.2017.09.007. PMID: 
28988769; PMCID: PMC5687509.

19. Zhang R, Zang J, Xie F, Zhang Y, Wang Y, Jing Y, et al. Urinary molecular 
pathology for patients with newly diagnosed urothelial bladder cancer. 
J Urol.2021;206(4):873–884. doi: 10.1097/JU.0000000000001878. 
PMID: 34061567.

20. Lee DH, Yoon H, Park S, Kim JS, Ahn YH, Kwon K, et al. Urinary 
exosomal and cell-free DNA detects somatic mutation and 
copy number alteration in urothelial carcinoma of bladder. Sci 
Rep.2018;8(1):14707. doi: 10.1038/s41598-018-32900-6. PMID: 
30279572; PMCID: PMC6168539.

21. Molparia B, Nichani E, Torkamani A. Assessment of circulating 
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28686671; PMCID: PMC5501586.

22. Halling KC, King W, Sokolova IA, Meyer RG, Burkhardt HM, Halling AC, 
et al. A comparison of cytology and fluorescence in situ hybridization 
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1775. PMID: 11025767.

23. Owens CL, Epstein JI. Significance of denuded urothelium in papillary 
urothelial lesions. Am J Surg Pathol.2007;31(2):298 –303. doi: 
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