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Using Urine to Detect Bladder Cancer Biomarkers: A Multi-Omics Approach

Biomarker detection is a fundamental requirement for early cancer detection. The rapidly developing field of multi-omics has the potential to assist in early-stage diagnosis, whilst also providing a greater level of information about the underlying molecular biology of cancer. Although still in its infancy, multi-omics is already beginning to prove itself as a powerful tool for both researchers and clinicians alike.

Pradeep Singh Chauha, Staff Scientist in the Aadel Chaudhuri lab at Washington University at St. Louis, spoke at a recent Front Line Genomics webinar series on using a multi-omics based approach for urine biomarker detection to monitor bladder cancer. To hear Pradeep’s presentation in full, as well as other talks on the use of multi-omics for cancer biomarker detection and analysis, please check out the on-demand webinar here.

The burden of bladder cancer

Bladder cancer is a major concern for American populations (see Figure 1). In the US, bladder cancer is the sixth most commonly diagnosed cancer, with its incidence being four times higher in men compared to women. Importantly, bladder cancer is also the most expensive malignancy due to significant costs associated with its diagnosis, management and surveillance. Surgical treatment options are guided by the stage of bladder cancer – i.e., whether or not the cancer has invaded muscle tissue.

Figure 1. Burden of bladder cancer on US population. This figure is a screenshot from Pradeep’s presentation at the Front Line Genomics webinar.

In non-muscle invasive bladder cancer (NMIBC), patients are treated with transurethral resection of bladder tumours alone, or in conjunction with intravesical therapy. Generally, the five-year survival rates for NMIBC are favourable, but there is still a risk of recurrence and progression to more advanced stages of the disease. For muscle invasive bladder cancer (MIBC), the standard treatment is radical cystectomy with urinary diversion – a complex surgery that significantly affects the quality of life for patients. For this cancer, the 5-year survival rate is only 50% and patients carry a substantial risk of disease recurrence.

However, there is another promising treatment option. It’s thought that 25% to 30% of bladder cancer patients will achieve pathological complete response to neoadjuvant chemotherapy treatment. Identifying patients that will respond to this therapy would be hugely effective in treating patients without requiring radical cystectomy surgery. Despite the benefits, there’s currently no primary method for identifying which patients would respond to neoadjuvant chemotherapy.

A new method for MRD detection

Identifying patients for neoadjuvant chemotherapy requires an assessment of minimal residual disease (MRD), which usually requires invasive medical procedures. In light of this, Pradeep and colleagues created a solution to this problem with the development of a non-invasive liquid biopsy technique for MRD analysis. The novel technique – urine Cancer Personalized Profiling by Deep Sequencing (uCAPP-Seq), works by detecting circulating free DNA (cfDNA) from urine samples to identify patients that are therapy candidates and predict survival outcomes.

A study using this technique was published in 20211involving 42 localised bladder cancer patients, using blood and urine samples collected just before radical cystectomy surgery. uCAPP-Seq uses a focused MRD gene panel, consisting of 49 genes reported to be frequently mutated in bladder cancer. The performance of the panel was first tested in sillico using MIBC tumour data from The Cancer Genome Atlas (TGCA) and DFCI/MSKCC (see Figure 2, left). Using this panel, 96% of tumours were found to have detectable mutations, with a median of 5 mutations detected per patient.

Figure 2. Performance of uCAPP-Seq MRD gene panel. This figure is a screenshot from Pradeep’s presentation at the Front Line Genomics webinar.

Additionally, the MRD panel was also applied to patient urine samples where it detected 52 non-silent and 17 silent cfDNA mutations (see Figure 2, right). Silent mutations are neutral mutations that do not affect protein function, whereas non-silent mutations create a change in the amino acid sequence of a protein. Only mutations detected in urine cfDNA with duplex support and with no read support in matched peripheral blood germline samples were considered.

Overall, non-silent mutations were detected at a sensitivity and specificity of 81%, making them a helpful tool to accurately classify pathologic response. This MRD panel was then used to classify pathologic complete response patients (pCR) from non-pathologic complete response patients (non-pCR). Patients with non-pCR had a higher quantity of urine cfDNA mutations, and patients with more than 2.3% urine tumour DNA were classified as having MRD positively detected.

Blood vs urine: A battle of sensitivity

Generally, it is thought that testing biofluids that are more proximal to the tumour increases the sensitivity of MRD detection. Therefore, Pradeep and colleagues then tested to see whether urine or blood samples were optimal for MRD detection using their technique. In a 2023 study2, uCAPP-Seq was conducted using paired urine and plasma samples from 40 bladder cancer patients. They showed that non-pCR patients had higher variant allele frequency detected compared to their respective pCR samples, in urine or plasma (see Figure 3, left). However, urine was also found to be more sensitive than plasma in predicting pCR (see Figure 3, right).

Figure 3. Urine outperforms plasma for bladder cancer MRD detection. This figure is a screenshot from Pradeep’s presentation at the Front Line Genomics webinar.

TMB as a biomarker for immunotherapy response

Tumour mutational burden, or TMB, has been shown to be a predictive biomarker of immunotherapy response dating as far back as 20143. High TMB is known to predict response to immune-checkpoint inhibitors. In their 2021 study, Pradeep and colleagues wanted to investigate whether they could infer TMB in urine with their custom TMB panel, using a process known as hybrid-capture cfDNA analysis.

The researchers classified their patients into two categories: those with high TMB detected (>170 non-silent mutations detected) and low TMB detected (<170 mutations). Using this threshold, it was determined that 58% of the MRD-positive patients (from urine tumour DNA) with high TMB could be candidates for neoadjuvant immunotherapy treatment. In contrast, the other 42% of patients with no active driver mutations could be offered adjuvant chemotherapy or radiotherapy.

The team explored this approach further in their 2023 study, this time combining uCAPP-Seq with ultra-low pass whole genome sequencing (see Figure 4). The study cohort included 74 bladder cancer patients, again collecting urine and plasma samples for analysis. Urine cfDNA was sequenced by uCAPP-Seq to detect single nucleotide variants, whilst ultra-low pass whole genome sequencing was used to identify genome-wide copy number alterations. These two approaches were then integrated into a machine learning algorithm to identify MRD and predict survival.

Figure 4: Applying Integrating approach to predict MRD in patients with MIBC. This figure is a screenshot from Pradeep’s presentation at the Front Line Genomics webinar.

Overall, this approach was successful in identifying copy number alterations in urine cfDNA in non-pCR patients. Conversely, no copy number alterations were detected in the cfDNA of the healthy control group. In addition, the variant allele frequency and inferred TMB were significantly higher in the non-pCR patients than in the pCR patients. Therefore, these features of urine cfDNA (alongside, other factors such as age and gender) were used to create a predictive model for pCR that outperforms plasma ctDNA analysis.

Finally, this model was applied to the 74 bladder cancer patients to predict survival outcomes. The patients, for whom MRD was detected, showed significantly worse progression-free survival. Therefore, this multi-omics approach to urine cfDNA analysis appears to be a powerful yet sensitive method to detect MRD in bladder cancer patients and predict outcomes. In the future, this type of integrative analysis may become a popular approach to facilitate personalised clinical decision making for cancer patients.

To find out more about the liquid biopsy research the Chaudhuri lab are doing, further information and recent publications can be found on their lab website.

Webinar Q&A (Direct quotes, edited for brevity)

Q: “Are there any future plans to continue this work?”

A: “Yes. This work was done using urine, and the advantage of collecting urine is that it’s ultra non-invasive. You can collect larger amounts compared to peripheral blood. So, we are expanding this research to other genitourinary cancers – like prostate and kidney cancers – where we could use urine to analyse the tumour.”


1.      Chauhan, P. S. et al. Urine tumor DNA detection of minimal residual disease in muscle-invasive bladder cancer treated with curative-intent radical cystectomy: A cohort study. PLoS Med. 18, e1003732 (2021).

2.      Chauhan, P. S. et al. Urine cell-free DNA multi-omics to detect MRD and predict survival in bladder cancer patients. NPJ Precis Oncol 7, 6 (2023).

3.      Snyder, A. et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N. Engl. J. Med. 371, 2189–2199 (2014).