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      Urine tumor DNA detection of minimal residual disease in muscle-invasive bladder cancer treated with curative-intent radical cystectomy: A cohort study

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          Abstract

          Background

          The standard of care treatment for muscle-invasive bladder cancer (MIBC) is radical cystectomy, which is typically preceded by neoadjuvant chemotherapy. However, the inability to assess minimal residual disease (MRD) noninvasively limits our ability to offer bladder-sparing treatment. Here, we sought to develop a liquid biopsy solution via urine tumor DNA (utDNA) analysis.

          Methods and findings

          We applied urine Cancer Personalized Profiling by Deep Sequencing (uCAPP-Seq), a targeted next-generation sequencing (NGS) method for detecting utDNA, to urine cell-free DNA (cfDNA) samples acquired between April 2019 and November 2020 on the day of curative-intent radical cystectomy from 42 patients with localized bladder cancer. The average age of patients was 69 years (range: 50 to 86), of whom 76% (32/42) were male, 64% (27/42) were smokers, and 76% (32/42) had a confirmed diagnosis of MIBC. Among MIBC patients, 59% (19/32) received neoadjuvant chemotherapy. utDNA variant calling was performed noninvasively without prior sequencing of tumor tissue. The overall utDNA level for each patient was represented by the non-silent mutation with the highest variant allele fraction after removing germline variants. Urine was similarly analyzed from 15 healthy adults. utDNA analysis revealed a median utDNA level of 0% in healthy adults and 2.4% in bladder cancer patients. When patients were classified as those who had residual disease detected in their surgical sample ( n = 16) compared to those who achieved a pathologic complete response (pCR; n = 26), median utDNA levels were 4.3% vs. 0%, respectively ( p = 0.002). Using an optimal utDNA threshold to define MRD detection, positive utDNA MRD detection was highly correlated with the absence of pCR ( p < 0.001) with a sensitivity of 81% and specificity of 81%. Leave-one-out cross-validation applied to the prediction of pathologic response based on utDNA MRD detection in our cohort yielded a highly significant accuracy of 81% ( p = 0.007). Moreover, utDNA MRD–positive patients exhibited significantly worse progression-free survival (PFS; HR = 7.4; 95% CI: 1.4–38.9; p = 0.02) compared to utDNA MRD–negative patients. Concordance between urine- and tumor-derived mutations, determined in 5 MIBC patients, was 85%. Tumor mutational burden (TMB) in utDNA MRD–positive patients was inferred from the number of non-silent mutations detected in urine cfDNA by applying a linear relationship derived from The Cancer Genome Atlas (TCGA) whole exome sequencing of 409 MIBC tumors. We suggest that about 58% of these patients with high inferred TMB might have been candidates for treatment with early immune checkpoint blockade. Study limitations included an analysis restricted only to single-nucleotide variants (SNVs), survival differences diminished by surgery, and a low number of DNA damage response (DRR) mutations detected after neoadjuvant chemotherapy at the MRD time point.

          Conclusions

          utDNA MRD detection prior to curative-intent radical cystectomy for bladder cancer correlated significantly with pathologic response, which may help select patients for bladder-sparing treatment. utDNA MRD detection also correlated significantly with PFS. Furthermore, utDNA can be used to noninvasively infer TMB, which could facilitate personalized immunotherapy for bladder cancer in the future.

          Abstract

          Pradeep S. Chauhan and colleagues, investigate a liquid biopsy solution via urine tumor DNA (utDNA) analysis to assess minimal residual disease in patients with muscle-invasive bladder cancer.

          Author summary

          Why was this study done?
          • The standard of care for muscle-invasive bladder cancer (MIBC) is neoadjuvant chemotherapy followed by radical cystectomy, which significantly impacts quality of life.

          • The inability to assess minimal residual disease (MRD) noninvasively limits our ability to offer bladder-sparing treatment.

          • We determine if urine tumor DNA (utDNA) detection just prior to radical cystectomy can predict pathologic complete response (pCR) and differences in survival outcomes.

          • We determine if utDNA analysis can identify patients who are candidates for early immune checkpoint blockade.

          What did the researchers do and find?
          • We applied urine Cancer Personalized Profiling by Deep Sequencing (uCAPP-Seq) to urine cell-free DNA (cfDNA) samples acquired on the day of curative-intent radical cystectomy from 42 patients with localized bladder cancer.

          • Positive utDNA MRD detection was highly correlated with the absence of pCR ( p < 0.001) with a sensitivity of 81% and specificity of 81%.

          • utDNA MRD–positive patients exhibited significantly worse progression-free survival (PFS) compared to utDNA MRD–negative patients (HR = 7.4; 95% CI: 1.4–38.9; p = 0.02).

          • Patients with high TMB inferred from urine might have been candidates for early treatment with immune checkpoint blockade.

          What do these findings mean?
          • utDNA MRD detection prior to curative-intent radical cystectomy for bladder cancer correlated significantly with pathologic response, which may help select patients for bladder-sparing treatment.

          • utDNA can be used to noninvasively infer TMB, which could facilitate personalized immunotherapy for bladder cancer patients in the future.

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          Most cited references71

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          Cancer statistics, 2020

          Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
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            The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data.

            The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. © 2012 AACR.
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              The mutational constraint spectrum quantified from variation in 141,456 humans

              Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: SoftwareRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: InvestigationRole: ResourcesRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Journal
                PLoS Med
                PLoS Med
                plos
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                31 August 2021
                August 2021
                : 18
                : 8
                : e1003732
                Affiliations
                [1 ] Division of Cancer Biology, Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [2 ] Division of Medical Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [3 ] Siteman Cancer Center, Barnes Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri, United States of America
                [4 ] Department of Genetics, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [5 ] McDonnell Genome Institute, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [6 ] Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [7 ] Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [8 ] Division of Urology, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [9 ] Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, Missouri, United States of America
                [10 ] Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, United States of America
                Author notes

                I have read the journal’s policy and the authors of this manuscript have the following competing interests: A.A.C. has patent filings related to cancer biomarkers, and has served as a consultant/advisor to Roche, Tempus, Geneoscopy, NuProbe, Daiichi Sankyo, AstraZeneca, Fenix Group International and Guidepoint; A.A.C. has stock options in Geneoscopy, research support from Roche, and ownership interests in Droplet Biosciences. V.K.A. has received research funding from ORIC Pharmaceuticals and currently serves as an employee of Bristol Myers Squibb; V.K.A. has stock options in both companies. Z.L.S. serves as a consultant/advisor for Photocure, outside of the submitted work. B.C.B. discloses honoraria from Mevion Medical Systems and consulting work for Regeneron/Sanofi, outside of the submitted work. R.K.B. is employed as a hospital medicine physician for SSM Health St. Louis. F.Q. has stock options in Centene, Gilead, and Horizon Therapeutics. No potential conflicts of interest were disclosed by the other authors.

                Author information
                https://orcid.org/0000-0003-4304-011X
                https://orcid.org/0000-0002-6244-5107
                https://orcid.org/0000-0002-6320-3927
                https://orcid.org/0000-0003-4582-3353
                https://orcid.org/0000-0002-6718-5439
                https://orcid.org/0000-0002-8005-701X
                https://orcid.org/0000-0002-7482-1413
                https://orcid.org/0000-0002-5167-3630
                https://orcid.org/0000-0002-5945-3288
                https://orcid.org/0000-0003-1694-9109
                https://orcid.org/0000-0003-3115-3061
                Article
                PMEDICINE-D-21-00202
                10.1371/journal.pmed.1003732
                8407541
                34464379
                b0d2fdc8-b9cd-4eb8-babd-8be42bc28f26
                © 2021 Chauhan et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 January 2021
                : 12 July 2021
                Page count
                Figures: 5, Tables: 1, Pages: 30
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: TL1TR002344
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100006098, Radiological Society of North America;
                Award Recipient :
                Funded by: Midwest Stone Institute
                Award Recipient :
                Funded by: Rabushka Bladder Cancer Research Fund
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100001021, Damon Runyon Cancer Research Foundation;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100014571, Alvin J. Siteman Cancer Center;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100006108, National Center for Advancing Translational Sciences;
                Award ID: UL1TR002345
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: K08CA238711
                Award Recipient :
                Funded by: Cancer Research Foundation
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100001368, V Foundation for Cancer Research;
                Award Recipient :
                This work was supported by the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) under award number TL1TR002344 (Principal Investigator, Jay F. Piccirillo; K.C.), the Radiological Society of North America (RSNA) Medical Student Research Grant (K.C.), the Midwest Stone Institute (Z.L.S.), the Rabushka Bladder Cancer Research Fund (Z.L.S., V.K.A.), the Damon Runyon Clinical Investigator Award (V.K.A), the Alvin J. Siteman Cancer Research Fund (A.A.C.), the National Institutes of Health (NIH) National Center for Advancing Translational Sciences (NCATS) under award number UL1TR002345 (Principal Investigator, Bradley Evanoff; A.A.C.), the National Cancer Institute (NCI) under award number K08CA238711 (A.A.C.), the Cancer Research Foundation Young Investigator Award (A.A.C.), and the V Foundation V Scholar Award (A.A.C.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Urology
                Genitourinary Cancers
                Bladder Cancer
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Genitourinary Tract Tumors
                Bladder Cancer
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Urine
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Urine
                Biology and Life Sciences
                Physiology
                Body Fluids
                Urine
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Biology and Life Sciences
                Genetics
                Gene Identification and Analysis
                Mutation Detection
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Surgical Excision
                Cystectomy
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Urinary System Procedures
                Cystectomy
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Chemotherapy
                Medicine and Health Sciences
                Oncology
                Cancer Treatment
                Cancer Chemotherapy
                Medicine and Health Sciences
                Pharmaceutics
                Drug Therapy
                Chemotherapy
                Cancer Chemotherapy
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Oncology
                Cancer Chemotherapy
                Medicine and Health Sciences
                Oncology
                Clinical Oncology
                Cancer Chemotherapy
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Malignant Tumors
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                Medicine
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