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<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="research-article" xml:lang="en"><processing-meta tagset-family="jats" base-tagset="archiving" mathml-version="3.0" table-model="xhtml"><custom-meta-group><custom-meta assigning-authority="highwire" xlink:type="simple"><meta-name>recast-jats-build</meta-name><meta-value>a5a9521409</meta-value></custom-meta></custom-meta-group></processing-meta><front><journal-meta><journal-id journal-id-type="hwp">jitc</journal-id><journal-id journal-id-type="nlm-ta">J Immunother Cancer</journal-id><journal-id journal-id-type="publisher-id">jitc</journal-id><journal-title-group><journal-title>Journal for ImmunoTherapy of Cancer</journal-title><abbrev-journal-title abbrev-type="publisher">J Immunother Cancer</abbrev-journal-title><abbrev-journal-title>J Immunother Cancer</abbrev-journal-title></journal-title-group><issn pub-type="epub">2051-1426</issn><publisher><publisher-name>BMJ Publishing Group Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">jitc-2020-002127</article-id><article-id pub-id-type="doi">10.1136/jitc-2020-002127</article-id><article-id pub-id-type="pmid">33980590</article-id><article-id pub-id-type="apath" assigning-authority="highwire">/jitc/9/5/e002127.atom</article-id><article-categories><subj-group subj-group-type="heading"><subject>Immunotherapy biomarkers</subject></subj-group><subj-group subj-group-type="collection" assigning-authority="publisher"><subject>Open access</subject></subj-group><subj-group subj-group-type="collection" assigning-authority="publisher"><subject>Immunotherapy Biomarkers</subject></subj-group><subj-group subj-group-type="collection" assigning-authority="highwire"><subject>Special collections</subject><subj-group><subject>JITC</subject><subj-group><subject>Immunotherapy Biomarkers</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="collection" assigning-authority="highwire"><subject>Special collections</subject><subj-group><subject>Open access</subject></subj-group></subj-group><series-title>Original research</series-title></article-categories><title-group><article-title><italic toggle="yes">TERT</italic> promoter mutations and other prognostic factors in patients with advanced urothelial carcinoma treated with an immune checkpoint inhibitor</article-title></title-group><contrib-group><contrib contrib-type="author" id="author-82353896" xlink:type="simple"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0002-3092-3565</contrib-id><name name-style="western"><surname>de Kouchkovsky</surname><given-names>Ivan</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74364135" xlink:type="simple"><name name-style="western"><surname>Zhang</surname><given-names>Li</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354316" xlink:type="simple"><name name-style="western"><surname>Philip</surname><given-names>Errol J</given-names></name><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author" id="author-82354441" xlink:type="simple"><name name-style="western"><surname>Wright</surname><given-names>Francis</given-names></name><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author" id="author-82354500" xlink:type="simple"><name name-style="western"><surname>Kim</surname><given-names>Daniel M</given-names></name><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author" id="author-82354407" xlink:type="simple"><name name-style="western"><surname>Natesan</surname><given-names>Divya</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354161" xlink:type="simple"><name name-style="western"><surname>Kwon</surname><given-names>Daniel</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354304" xlink:type="simple"><name name-style="western"><surname>Ho</surname><given-names>Hansen</given-names></name><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author" id="author-82354394" xlink:type="simple"><name name-style="western"><surname>Ho</surname><given-names>Son</given-names></name><xref ref-type="aff" rid="aff3">3</xref></contrib><contrib contrib-type="author" id="author-82354378" xlink:type="simple"><name name-style="western"><surname>Chan</surname><given-names>Emily</given-names></name><xref ref-type="aff" rid="aff4">4</xref></contrib><contrib contrib-type="author" id="author-82354365" xlink:type="simple"><name name-style="western"><surname>Porten</surname><given-names>Sima P</given-names></name><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author" id="author-82354361" xlink:type="simple"><name name-style="western"><surname>Wong</surname><given-names>Anthony C</given-names></name><xref ref-type="aff" rid="aff6">6</xref></contrib><contrib contrib-type="author" id="author-79344858" xlink:type="simple"><name name-style="western"><surname>Desai</surname><given-names>Arpita</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-83466437" xlink:type="simple"><name name-style="western"><surname>Huang</surname><given-names>Franklin W</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354250" xlink:type="simple"><name name-style="western"><surname>Chou</surname><given-names>Jonathan</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74364188" xlink:type="simple"><name name-style="western"><surname>Oh</surname><given-names>David Y</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354343" xlink:type="simple"><name name-style="western"><surname>Pruthi</surname><given-names>Raj S</given-names></name><xref ref-type="aff" rid="aff5">5</xref></contrib><contrib contrib-type="author" id="author-74364131" xlink:type="simple"><name name-style="western"><surname>Fong</surname><given-names>Lawrence</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354204" xlink:type="simple"><name name-style="western"><surname>Small</surname><given-names>Eric J</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-82354186" xlink:type="simple"><name name-style="western"><surname>Friedlander</surname><given-names>Terence W</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" corresp="yes" id="author-79344600" xlink:type="simple"><name name-style="western"><surname>Koshkin</surname><given-names>Vadim S</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib></contrib-group><aff id="aff1"><label>1</label><institution content-type="department" xlink:type="simple">Medicine</institution>, <institution xlink:type="simple">University of California San Francisco</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><aff id="aff2"><label>2</label><institution xlink:type="simple">University of California San Francisco School of Medicine</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><aff id="aff3"><label>3</label><institution xlink:type="simple">University of California San Francisco School of Pharmacy</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><aff id="aff4"><label>4</label><institution content-type="department" xlink:type="simple">Pathology</institution>, <institution xlink:type="simple">University of California San Francisco</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><aff id="aff5"><label>5</label><institution content-type="department" xlink:type="simple">Urology</institution>, <institution xlink:type="simple">University of California San Francisco</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><aff id="aff6"><label>6</label><institution content-type="department" xlink:type="simple">Radiation Oncology</institution>, <institution xlink:type="simple">University of California San Francisco</institution>, <addr-line content-type="city">San Francisco</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country></aff><author-notes><corresp><label>Correspondence to</label> Dr Vadim S Koshkin; <email xlink:type="simple">Vadim.Koshkin@ucsf.edu</email></corresp></author-notes><pub-date date-type="pub" iso-8601-date="2021-05" pub-type="ppub" publication-format="print"><month>5</month><year>2021</year></pub-date><pub-date date-type="pub" iso-8601-date="2021-05-11" pub-type="epub-original" publication-format="electronic"><day>11</day><month>5</month><year>2021</year></pub-date><pub-date iso-8601-date="2021-05-03T06:45:20-07:00" pub-type="hwp-received"><day>3</day><month>5</month><year>2021</year></pub-date><pub-date iso-8601-date="2021-05-03T06:45:20-07:00" pub-type="hwp-created"><day>3</day><month>5</month><year>2021</year></pub-date><pub-date iso-8601-date="2021-05-12T08:46:18-07:00" pub-type="epub"><day>12</day><month>5</month><year>2021</year></pub-date><volume>9</volume><issue>5</issue><elocation-id>e002127</elocation-id><history><date date-type="accepted" iso-8601-date="2021-04-07"><day>07</day><month>04</month><year>2021</year></date></history><permissions><copyright-statement>© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</copyright-statement><copyright-year>2021</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/" xlink:type="simple"><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/" start_date="2021-05-11">http://creativecommons.org/licenses/by-nc/4.0/</ali:license_ref><license-p>This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/" xlink:type="simple">http://creativecommons.org/licenses/by-nc/4.0/</ext-link>.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="jitc-2020-002127.pdf" xlink:type="simple"/><abstract><sec><title>Background</title><p>Immune checkpoint inhibitors (ICI) can achieve durable responses in a subset of patients with locally advanced or metastatic urothelial carcinoma (aUC). The use of tumor genomic profiling in clinical practice may help suggest biomarkers to identify patients most likely to benefit from ICI.</p></sec><sec><title>Methods</title><p>We undertook a retrospective analysis of patients treated with an ICI for aUC at a large academic medical center. Patient clinical and histopathological variables were collected. Responses to treatment were assessed for all patients with at least one post-baseline scan or clear evidence of clinical progression following treatment start. Genomic profiling information was also collected for patients when available. Associations between patient clinical/genomic characteristics and objective response were assessed by logistic regression; associations between the characteristics and progression-free survival (PFS) and overall survival (OS) were examined by Cox regression. Multivariable analyses were performed to identify independent prognostic factors.</p></sec><sec><title>Results</title><p>We identified 119 aUC patients treated with an ICI from December 2014 to January 2020. Genomic profiling was available for 78 patients. Overall response rate to ICI was 29%, and median OS (mOS) was 13.4 months. Favorable performance status at the start of therapy was associated with improved OS (HR 0.46, p=0.025) after accounting for other covariates. Similarly, the presence of a <italic toggle="yes">TERT</italic> promoter mutation was an independent predictor of improved PFS (HR 0.38, p=0.012) and OS (HR 0.32, p=0.037) among patients who had genomic profiling available. Patients with both a favorable performance status and a <italic toggle="yes">TERT</italic> promoter mutation had a particularly good prognosis with mOS of 21.1 months as compared with 7.5 months in all other patients (p=0.03).</p></sec><sec><title>Conclusions</title><p>The presence of a <italic toggle="yes">TERT</italic> promoter mutation was an independent predictor of improved OS in a cohort of aUC patients treated with an ICI who had genomic data available. Most of the clinical and laboratory variables previously shown to be prognostic in aUC patients treated with chemotherapy did not have prognostic value among patients treated with an ICI. Genomic profiling may provide important prognostic information and affect clinical decision making in this patient population. Validation of these findings in prospective patient cohorts is needed.</p></sec></abstract><kwd-group><kwd>urinary bladder neoplasms</kwd><kwd>immunotherapy</kwd><kwd>tumor biomarkers</kwd><kwd>genetic markers</kwd></kwd-group><custom-meta-group><custom-meta xlink:type="simple"><meta-name>special-feature</meta-name><meta-value>unlocked</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1"><title>Background</title><p>Immune checkpoint inhibitors (ICI) have revolutionized the management of metastatic and locally advanced urothelial carcinoma of the bladder and urinary tract (aUC). Starting with atezolizumab in May of 2016, five ICIs are now approved for the treatment of aUC after progression on a platinum-based chemotherapy regimen.<xref ref-type="bibr" rid="R1 R2 R3 R4 R5">1–5</xref> Cisplatin-ineligible patients may also receive pembrolizumab or atezolizumab in the front-line setting,<xref ref-type="bibr" rid="R6 R7 R8">6–8</xref> while avelumab was recently granted Food and Drug Administration (FDA) approval as switch maintenance therapy following first-line platinum-based chemotherapy.<xref ref-type="bibr" rid="R9">9</xref> Yet while ICIs can achieve durable responses in a subset of patients, only 20%–25% of patients respond to immunotherapy<xref ref-type="bibr" rid="R1 R2 R3 R4 R5 R6 R7 R8">1–8</xref> and reliable predictors of response to ICI are lacking. As alternative targeted therapies emerge for patients with aUC,<xref ref-type="bibr" rid="R10 R11">10 11</xref> there is an urgent need for novel biomarkers to help identify patients most likely to benefit from ICI treatment.</p><p>Existing data on the predictive value of programmed death-ligand 1 (PD-L1) expression in aUC are mixed: high PD-L1 expression was associated with response to post-platinum atezolizumab in the initial phase 2 IMvigor 210 study and to front-ine pembrolizumab in the KEYNOTE-052 study,<xref ref-type="bibr" rid="R7 R12">7 12</xref> however, durable responses can still be seen in patients with low PD-L1 expression.<xref ref-type="bibr" rid="R13">13</xref> Conversely, low PD-L1 expression may predict inferior outcomes in patients receiving front-line ICI.<xref ref-type="bibr" rid="R8 R14">8 14</xref> Tumor mutation burden (TMB) is thought to contribute to tumor immunogenicity through increased neoantigen expression, and in June 2020 pembrolizumab was granted accelerated FDA approval for the treatment of advanced solid tumors with a high TMB that have progressed on prior therapy.<xref ref-type="bibr" rid="R15">15</xref> Retrospective evidence in aUC suggests that a high TMB may indeed predict clinical benefit to ICI,<xref ref-type="bibr" rid="R16 R17">16 17</xref> and a multivariable analysis of clinical and genomic factors in aUC showed that high TMB—along with low neutrophil to lymphocyte ratio (NLR) and lack of visceral metastases—was associated with response to immunotherapy.<xref ref-type="bibr" rid="R18">18</xref> A prespecified subgroup analysis of IMvigor130 failed to demonstrate a survival benefit of front-line atezolizumab (alone or in combination with chemotherapy) over platinum-based chemotherapy in patients with a high TMB, although a smaller subset of patients who had both high PD-L1 expression and high TMB did seem to derive more benefit from atezolizumab relative to platinum-based chemotherapy.<xref ref-type="bibr" rid="R19">19</xref> Prospective validation of TMB as a biomarker of response to ICI in aUC is still needed.</p><p>Genomic profiling using next-generation sequencing (NGS) is increasingly used in the management of cancer patients and patients with aUC. We hypothesized that the use of this real-world genomic data—in combination with baseline clinical and laboratory features—may help to identify novel independent predictive markers of response to immunotherapy. Here, we present the results of a single-center retrospective analysis of the clinical and genomic factors associated with clinical outcomes among aUC patients treated with an ICI.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Patient and data collection</title><p>Patients treated with ICI monotherapy for aUC at the University of California, San Francisco from December 2014 to January 2020 were included in this retrospective analysis. Patient data were collected from electronic medical record review in compliance with institutional review board guidelines. Patient eligibility criteria included: histologically confirmed UC, presence of locally advanced or metastatic disease, at least one dose of an ICI administered (including atezolizumab, pembrolizumab, nivolumab, durvalumab or avelumab), and available clinical, pathologic and imaging data prior to initiation of treatment. To be considered eligible for response assessment, a patient needed to have at least one scan following initiation of an ICI or clear evidence of clinical progression as assessed by the treating physician. Patients who received an ICI for an indication other than aUC were excluded from this analysis.</p><p>Baseline clinical and laboratory characteristics were collected for each patient. Results of testing for PD-L1 expression via the PD-L1 IHC 22C3 pharmDx assay (NeoGenomics Laboratories) were also collected when performed at the discretion of the treating clinician. Tumor genomic profiling was performed using Clinical Laboratory Improvement Amendments (CLIA) certified commercially available (FoundationOne and StrataNGS) NGS platforms, or a CLIA certified institutional NGS assay (UCSF 500 Cancer Gene Panel Test, which uses hybrid capture enrichment of target DNA to interrogate 479 common cancer genes). For some patients, pathogenic germline mutations were also identified on commercially available CLIA-certified NGS platforms (Ambry Genetics, Myriad Genetics and Invitae), and thus were also included in this analysis.</p><p>Assessment of objective response (defined as a complete response (CR) or partial response (PR)) or progression was determined based on the judgment of the investigator assessing the patient’s chart using the available information from radiographic reports or clinical notes. Response assessment in patients who received &gt;1 ICI in sequence was performed only during the first course of ICI therapy. Duration of response was defined as the time from the first documented clinical or radiographic response to progression, death or time of last follow-up for patients who had not yet progressed on ICI. Progression-free survival (PFS) was defined as the time from ICI start to progression or death; patients alive without disease progression at last follow-up were censored at the date of last follow-up. Overall survival (OS) was defined as the time from ICI start until death; those alive at last follow-up were censored at the date of last follow-up. PFS and OS in patients who received &gt;1 ICI in sequence were defined from the start of the first course of ICI therapy and objective response rate (ORR) was assessed only with the first ICI therapy.</p></sec><sec id="s2-2"><title>Statistical analysis</title><p>Summary statistics were used to describe baseline patient and treatment characteristics, as well as PD-L1 expression status, TMB and genomic alterations identified by NGS when available. Wilcoxon rank-sum test was used to compare TMB between patients with or without specific genomic alterations. Univariable analysis was performed to assess for correlations between clinical outcomes (response, PFS and OS) and<xref ref-type="bibr" rid="R1">1</xref> the top 20 most commonly altered genes,<xref ref-type="bibr" rid="R2">2</xref> relevant baseline demographic and clinical characteristics (age, location of primary tumor, histology, Eastern Cooperative Oncology Group (ECOG) performance status score, front-line versus postplatinum treatment setting, presence of visceral metastases, body mass index and<xref ref-type="bibr" rid="R3">3</xref> laboratory variables (albumin, hemoglobin, creatinine levels and NLR). Logistic model was used for binary response outcome and Cox proportional hazard (cph) model was used for time-to-event outcomes (ie, PFS and OS). To account for possible confounders and assess the independent effect of specific variables on treatment outcomes, multivariable logistic regression and Cox proportional hazard models were applied.</p><p>Four prespecified prognostic variables (albumin and hemoglobin levels, ECOG score, and the presence of visceral metastases) were selected a priori for the multivariable analyses, based on the existing literature.<xref ref-type="bibr" rid="R20 R21 R22">20–22</xref> Additional variables with p&lt;0.1 in the corresponding univariable analysis were included in the multivariable analyses. Two separate analyses for ORR, PFS and OS were performed<xref ref-type="bibr" rid="R1">1</xref>: using only clinical variables in the entire patient cohort and<xref ref-type="bibr" rid="R2">2</xref> using combined clinical and genomic variables in the subset of patients who had undergone genomic profiling. Statistical significance was set at a p&lt;0.05. Adjustment for multiple testing was not performed. All analyses were conducted using the R statistical computing software (<ext-link ext-link-type="uri" xlink:href="http://www.r-project.org" xlink:type="simple">http://www.r-project.org</ext-link>).</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><sec id="s3-1"><title>Baseline patient characteristics</title><p>We identified 119 patients treated with an ICI for aUC from December 2014 to January 2020. Primary site of disease was bladder for 90 patients (75.6%), or upper genitourinary tract for 29 (24.4%) of patients. Sixty-three of 119 patients (52.9%) had undergone prior definitive surgery, and 50 (79.4%) of those patients had received neoadjuvant chemotherapy. The most common histological pattern was pure UC in 77 (64.7%) patients, while 14 (11.8%) patients had pure variant histology or variant-predominant histology (squamous cell carcinoma in 7, neuroendocrine in 2, adenocarcinoma in 2, other histology in 3). The remaining 28 patients (23.5%) had mixed histology that was urothelial predominant (with a component of squamous cell, plasmacytoid or micropapillary histology in 17, 4 and 4 cases, respectively; other histology in the remaining 3 cases). With regards to ICI treatment, the majority of patients received pembrolizumab (68.1%) or atezolizumab (29.4%), with the remainder receiving nivolumab (1.7%) and durvalumab (0.8%). Roughly half of all ICIs were administered in the postplatinum metastatic setting (61 out of 119 patients, 51.3%), with the remaining 58 patients (48.7%) receiving ICI in the front-line or treatment-naive metastatic setting; six patients received more than one ICI in sequence. A total of 78 of the 119 (65.6%) patients had genomic profiling data available. Other baseline characteristics at the start of ICI therapy are summarized in <xref ref-type="table" rid="T1">table 1</xref>.</p><table-wrap position="float" id="T1" orientation="portrait"><object-id pub-id-type="publisher-id">T1</object-id><label>Table 1</label><caption><p>Baseline characteristics at the start of immune checkpoint inhibitor therapy</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Characteristics</td><td align="left" valign="bottom" rowspan="1" colspan="1">Entire cohort (n=119)</td><td align="left" valign="bottom" rowspan="1" colspan="1">Patients with available genomic data (n=78)</td></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Age, years—median (IQR)</td><td align="left" valign="top" rowspan="1" colspan="1">71 (65, 77)</td><td align="left" valign="top" rowspan="1" colspan="1">71 (66, 76)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Male—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">77 (64.7)</td><td align="left" valign="top" rowspan="1" colspan="1">49 (62.8)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Female—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">42 (35.3)</td><td align="left" valign="top" rowspan="1" colspan="1">29 (37.2)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Smoking history (present or former)—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">71 (59.7)</td><td align="left" valign="top" rowspan="1" colspan="1">46 (59.0)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Ethnicity—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> White</td><td align="left" valign="top" rowspan="1" colspan="1">81 (68.1)</td><td align="left" valign="top" rowspan="1" colspan="1">54 (69.2)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Asian</td><td align="left" valign="top" rowspan="1" colspan="1">19 (16.0)</td><td align="left" valign="top" rowspan="1" colspan="1">12 (15.4)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> African American</td><td align="left" valign="top" rowspan="1" colspan="1">6 (5.0)</td><td align="left" valign="top" rowspan="1" colspan="1">5 (6.4)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Hispanic</td><td align="left" valign="top" rowspan="1" colspan="1">4 (3.4)</td><td align="left" valign="top" rowspan="1" colspan="1">2 (2.6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Other</td><td align="left" valign="top" rowspan="1" colspan="1">7 (5.9)</td><td align="left" valign="top" rowspan="1" colspan="1">4 (5.1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Primary bladder tumor—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">90 (75.6)</td><td align="left" valign="top" rowspan="1" colspan="1">57 (73.1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Upper tract disease—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">29 (24.4)</td><td align="left" valign="top" rowspan="1" colspan="1">21 (26.9)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Cystectomy or nephroureterectomy—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">63 (52.9)</td><td align="left" valign="top" rowspan="1" colspan="1">47 (60.3)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Histology—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Pure urothelial histology</td><td align="left" valign="top" rowspan="1" colspan="1">77 (64.7)</td><td align="left" valign="top" rowspan="1" colspan="1">47 (60.3)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Mixed variant histology</td><td align="left" valign="top" rowspan="1" colspan="1">36 (30.3)</td><td align="left" valign="top" rowspan="1" colspan="1">27 (34.6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Pure variant histology</td><td align="left" valign="top" rowspan="1" colspan="1">6 (5.0)</td><td align="left" valign="top" rowspan="1" colspan="1">4 (5.1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Immunotherapy treatment setting—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Front-line metastatic</td><td align="left" valign="top" rowspan="1" colspan="1">58 (48.7)</td><td align="left" valign="top" rowspan="1" colspan="1">37 (47.4)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Postplatinum</td><td align="left" valign="top" rowspan="1" colspan="1">61 (51.3)</td><td align="left" valign="top" rowspan="1" colspan="1">41 (52.6)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ECOG PS—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> 0–1</td><td align="left" valign="top" rowspan="1" colspan="1">66 (55.5)</td><td align="left" valign="top" rowspan="1" colspan="1">49 (62.8)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> ≥2</td><td align="left" valign="top" rowspan="1" colspan="1">25 (21.0)</td><td align="left" valign="top" rowspan="1" colspan="1">11 (14.1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Unknown</td><td align="left" valign="top" rowspan="1" colspan="1">28 (23.5)</td><td align="left" valign="top" rowspan="1" colspan="1">18 (23.1)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Visceral metastases—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">90 (75.6)</td><td align="left" valign="top" rowspan="1" colspan="1">55 (70.5)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">BMI, kg/m<sup>2</sup>—median (IQR)</td><td align="left" valign="top" rowspan="1" colspan="1">24.9 (22.0, 28.6)</td><td align="left" valign="top" rowspan="1" colspan="1">25.2 (22.0, 28.8)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hemoglobin &lt;100 g/L—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">37 (31.1)</td><td align="left" valign="top" rowspan="1" colspan="1">26 (33.3)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Creatinine, mg/dL—median (IQR)</td><td align="left" valign="top" rowspan="1" colspan="1">1.35 (1.03, 1.75)</td><td align="left" valign="top" rowspan="1" colspan="1">1.41 (1.09, 1.78)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Albumin, g/dL—median (IQR)</td><td align="left" valign="top" rowspan="1" colspan="1">3.4 (3.0, 3.8)</td><td align="left" valign="top" rowspan="1" colspan="1">3.6 (3.0, 3.8)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NLR &lt;5—n (%)</td><td align="left" valign="top" rowspan="1" colspan="1">65 (54.6)</td><td align="left" valign="top" rowspan="1" colspan="1">46 (59.0)</td></tr></tbody></table><table-wrap-foot><fn id="T1_FN1"><p>BMI, body mass index; NLR, neutrophil to lymphocyte ratio; ECOG PS, Eastern Cooperative Oncology Group performance status.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3-2"><title>Treatment outcomes</title><p>Among all 119 patients treated with ICI, ORR was 29%, including 13% (n=16) CR and 15% (n=18) PR. An additional 16 patients (13%) achieved stable disease (SD) as their best response, for a disease control rate (DCR) of 42%. With a median follow-up of 6.3 months in this study, median PFS was 2.6 months (95% CI 2.01 to 4.34 months) and median OS was 13.4 months (95% CI 11.3 to 20.7). Among patients who achieved CR or PR, the median duration of response was 13.4 months (IQR 4.7–22.5). Relative to patients with mixed or pure variant histology (n=42), patients with pure urothelial histology (n=77) had more favorable PFS (median PFS 3.36 vs 1.88 months, p=0.04) and a trend towards more favorable OS (median OS 15.5 vs 12.3 months, p=0.07). There were no statistically significant differences in clinical outcomes among patients with primary bladder and primary upper tract tumors or between patients receiving ICI in the front-line versus postplatinum setting.</p></sec><sec id="s3-3"><title>Clinical prognostic factors</title><p>Favorable baseline performance status (ECOG ≤1) was associated with a longer OS (HR 0.40, 95% CI 0.22 to 0.74, p=0.003) and a trend toward a longer PFS (HR 0.59, 95% CI 0.59 to 1.00, p=0.05) on univariable analysis (<xref ref-type="table" rid="T2">table 2</xref>). It remained an independent predictor of OS after adjusting for other pretreatment clinical and laboratory variables (HR 0.46, 95% CI 0.23 to 0.90, p=0.03; <xref ref-type="table" rid="T3">table 3</xref>). On the other hand, the presence of visceral metastases was associated with shorter PFS (HR 2.24, 95% CI 1.32 to 3.79, p=0.003) and OS (HR 2.53, 95% CI 1.29 to 4.98, p=0.007) on univariable analysis, as well as a lower likelihood of response to ICI (OR 0.74, 95% CI 0.62 to 0.89, p=0.002; <xref ref-type="table" rid="T2">table 2</xref>). The presence of visceral metastases was not associated with ORR or OS on multivariable analysis, although we did observe a trend toward shorter PFS in this patient population (HR 1.97, 95% CI 0.99 to 3.92, p=0.06; <xref ref-type="table" rid="T3">table 3</xref>). Pretreatment albumin level, NLR &lt;5 and the presence of pure UC histology in a biopsy sample were associated with favorable outcomes on univariable analysis only. No significant associations with treatment outcomes were seen with location of primary tumor or with receiving ICI in the front-line versus postplatinum setting.</p><table-wrap position="float" id="T2" orientation="portrait"><object-id pub-id-type="publisher-id">T2</object-id><label>Table 2</label><caption><p>Univariable analysis of objective response, progression-free survival and overall survival with relevant clinical and genomic characteristics</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="2" colspan="1">Characteristics</td><td align="left" valign="bottom" rowspan="1" colspan="2">Objective response</td><td align="left" valign="bottom" rowspan="1" colspan="2">Progression free Survival</td><td align="left" valign="bottom" rowspan="1" colspan="2">Overall survival</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">OR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Age</td><td align="left" valign="top" rowspan="1" colspan="1">1.00 (1.00 to 1.01)</td><td align="left" valign="top" rowspan="1" colspan="1">0.28</td><td align="left" valign="top" rowspan="1" colspan="1">0.99 (0.97 to 1.01)</td><td align="left" valign="top" rowspan="1" colspan="1">0.20</td><td align="left" valign="top" rowspan="1" colspan="1">1.00 (0.98 to 1.03)</td><td align="left" valign="top" rowspan="1" colspan="1">0.90</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Bladder versus upper tract UC</td><td align="left" valign="top" rowspan="1" colspan="1">0.89 (0.73 to 1.08)</td><td align="left" valign="top" rowspan="1" colspan="1">0.23</td><td align="left" valign="top" rowspan="1" colspan="1">1.03 (0.64 to 1.66)</td><td align="left" valign="top" rowspan="1" colspan="1">0.91</td><td align="left" valign="top" rowspan="1" colspan="1">1.47 (0.80 to 2.70)</td><td align="left" valign="top" rowspan="1" colspan="1">0.22</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Histology (pure UC vs mixed or pure variant histology)</td><td align="left" valign="top" rowspan="1" colspan="1">1.17 (0.99 to 1.39)</td><td align="left" valign="top" rowspan="1" colspan="1">0.08</td><td align="left" valign="top" rowspan="1" colspan="1">0.64 (0.42 to 0.99)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.04</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.63 (0.37 to 1.05)</td><td align="left" valign="top" rowspan="1" colspan="1">0.08</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Front line versus postplatinum</td><td align="left" valign="top" rowspan="1" colspan="1">1.09 (0.92 to 1.28)</td><td align="left" valign="top" rowspan="1" colspan="1">0.33</td><td align="left" valign="top" rowspan="1" colspan="1">0.84 (0.55 to 1.27)</td><td align="left" valign="top" rowspan="1" colspan="1">0.40</td><td align="left" valign="top" rowspan="1" colspan="1">1.12 (0.68 to 1.83)</td><td align="left" valign="top" rowspan="1" colspan="1">0.66</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ECOG PS≤1</td><td align="left" valign="top" rowspan="1" colspan="1">1.13 (0.92 to 1.39)</td><td align="left" valign="top" rowspan="1" colspan="1">0.25</td><td align="left" valign="top" rowspan="1" colspan="1">0.59 (0.35 to 1.00)</td><td align="left" valign="top" rowspan="1" colspan="1">0.05</td><td align="left" valign="top" rowspan="1" colspan="1">0.40 (0.22 to 0.74)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.003</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Visceral metastases</td><td align="left" valign="top" rowspan="1" colspan="1">0.74 (0.62 to 0.89)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.002</bold></td><td align="left" valign="top" rowspan="1" colspan="1">2.23 (1.32 to 3.79)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.003</bold></td><td align="left" valign="top" rowspan="1" colspan="1">2.53 (1.29 to 4.98)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.007</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">BMI</td><td align="left" valign="top" rowspan="1" colspan="1">1.02 (1.00 to 1.03)</td><td align="left" valign="top" rowspan="1" colspan="1">0.05</td><td align="left" valign="top" rowspan="1" colspan="1">0.97 (0.93 to 1.01)</td><td align="left" valign="top" rowspan="1" colspan="1">0.14</td><td align="left" valign="top" rowspan="1" colspan="1">0.91 (0.86 to 0.96)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.001</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Albumin</td><td align="left" valign="top" rowspan="1" colspan="1">1.20 (1.05 to 1.37)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.009</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.57 (0.43 to 0.75)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>&lt;0.001</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.49 (0.36 to 0.67)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>&lt;0.001</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hemoglobin &lt;100 vs ≥100 g/L</td><td align="left" valign="top" rowspan="1" colspan="1">0.835 (0.70 to 1.00)</td><td align="left" valign="top" rowspan="1" colspan="1">0.05</td><td align="left" valign="top" rowspan="1" colspan="1">1.71 (1.11 to 2.65)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.02</bold></td><td align="left" valign="top" rowspan="1" colspan="1">1.45 (0.85 to 2.47)</td><td align="left" valign="top" rowspan="1" colspan="1">0.18</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Creatinine</td><td align="left" valign="top" rowspan="1" colspan="1">1.01 (0.92 to 1.11)</td><td align="left" valign="top" rowspan="1" colspan="1">0.91</td><td align="left" valign="top" rowspan="1" colspan="1">0.83 (0.63 to 1.08)</td><td align="left" valign="top" rowspan="1" colspan="1">0.16</td><td align="left" valign="top" rowspan="1" colspan="1">0.86 (0.64 to 1.16)</td><td align="left" valign="top" rowspan="1" colspan="1">0.32</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NLR &lt;5 vs NLR ≥5</td><td align="left" valign="top" rowspan="1" colspan="1">1.18 (1.00 to 1.40)</td><td align="left" valign="top" rowspan="1" colspan="1">0.06</td><td align="left" valign="top" rowspan="1" colspan="1">0.61 (0.40 to 0.94)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.03</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.45 (0.26 to 0.75)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.002</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">TMB ≥10 mut/Mb vs TMB &lt;10 mut/Mb</td><td align="left" valign="top" rowspan="1" colspan="1">3.45 (1.04 to 11.11)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.04</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.42 (0.22 to 0.81)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.009</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.69 (0.03 to 1.43)</td><td align="left" valign="top" rowspan="1" colspan="1">0.32</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">TERT</italic> promoter mutation</td><td align="left" valign="top" rowspan="1" colspan="1">1.33 (1.08 to 1.65)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.01</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.41 (0.24 to 0.72)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.002</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.53 (0.27 to 1.06)</td><td align="left" valign="top" rowspan="1" colspan="1">0.07</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">MDM2</italic> mutation</td><td align="left" valign="top" rowspan="1" colspan="1">1.41 (1.01 to 1.96)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>&lt;0.05</bold></td><td align="left" valign="top" rowspan="1" colspan="1">0.98 (0.46 to 2.08)</td><td align="left" valign="top" rowspan="1" colspan="1">0.95</td><td align="left" valign="top" rowspan="1" colspan="1">0.72 (0.28 to 1.88)</td><td align="left" valign="top" rowspan="1" colspan="1">0.51</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">CDKN2B</italic> mutation</td><td align="left" valign="top" rowspan="1" colspan="1">0.94 (0.74 to 1.20)</td><td align="left" valign="top" rowspan="1" colspan="1">0.61</td><td align="left" valign="top" rowspan="1" colspan="1">1.36 (0.77 to 2.40)</td><td align="left" valign="top" rowspan="1" colspan="1">0.29</td><td align="left" valign="top" rowspan="1" colspan="1">1.91 (0.98 to 3.73)</td><td align="left" valign="top" rowspan="1" colspan="1">0.06</td></tr></tbody></table><table-wrap-foot><fn id="T2_FN1"><p>Bold values denote statistical significance at the p &lt; 0.05 level.</p></fn><fn id="T2_FN2"><p>BMI, body mass index; NLR, neutrophil to lymphocyte ratio; ECOG PS, Eastern Cooperative Oncology Group Performance Status; TMB, tumor mutation burden; UC, urothelial carcinoma.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T3" orientation="portrait"><object-id pub-id-type="publisher-id">T3</object-id><label>Table 3</label><caption><p>Multivariable analysis of overall survival with prespecified clinical variables and clinical and genomic characteristics with significant findings on univariable analysis (p&lt;0.1)</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="2" colspan="1">Characteristics</td><td align="left" valign="bottom" rowspan="1" colspan="2">Multivariable analysis (clinical and genomic data; n=78)</td><td align="left" valign="bottom" rowspan="1" colspan="2">Multivariable analysis (entire cohort, clinical data only; n=119)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Histology (pure UC vs mixed or pure variant histology)</td><td align="left" valign="top" rowspan="1" colspan="1">1.09 (0.32 to 3.74)</td><td align="left" valign="top" rowspan="1" colspan="1">0.89</td><td align="left" valign="top" rowspan="1" colspan="1">0.91 (0.41 to 2.02)</td><td align="left" valign="top" rowspan="1" colspan="1">0.81</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ECOG PS ≤1</td><td align="left" valign="top" rowspan="1" colspan="1">0.38 (0.11 to 1.32)</td><td align="left" valign="top" rowspan="1" colspan="1">0.13</td><td align="left" valign="top" rowspan="1" colspan="1">0.46 (0.23 to 0.90)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.03</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Visceral metastases</td><td align="left" valign="top" rowspan="1" colspan="1">2.47 (0.73 to 8.33)</td><td align="left" valign="top" rowspan="1" colspan="1">0.14</td><td align="left" valign="top" rowspan="1" colspan="1">1.89 (0.75 to 4.79)</td><td align="left" valign="top" rowspan="1" colspan="1">0.18</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">BMI</td><td align="left" valign="top" rowspan="1" colspan="1">0.93 (0.84 to 1.02)</td><td align="left" valign="top" rowspan="1" colspan="1">0.14</td><td align="left" valign="top" rowspan="1" colspan="1">0.98 (0.89 to 1.03)</td><td align="left" valign="top" rowspan="1" colspan="1">0.27</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Albumin</td><td align="left" valign="top" rowspan="1" colspan="1">0.49 (0.18 to 1.32)</td><td align="left" valign="top" rowspan="1" colspan="1">0.16</td><td align="left" valign="top" rowspan="1" colspan="1">0.55 (0.30 to 1.01)</td><td align="left" valign="top" rowspan="1" colspan="1">0.05</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hemoglobin &lt;100 vs ≥100 g/L</td><td align="left" valign="top" rowspan="1" colspan="1">0.41 (0.1 to 1.75)</td><td align="left" valign="top" rowspan="1" colspan="1">0.23</td><td align="left" valign="top" rowspan="1" colspan="1">0.82 (0.31 to 2.14)</td><td align="left" valign="top" rowspan="1" colspan="1">0.68</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NLR &lt;5 vs ≥5</td><td align="left" valign="top" rowspan="1" colspan="1">1.83 (0.50 to 6.74)</td><td align="left" valign="top" rowspan="1" colspan="1">0.36</td><td align="left" valign="top" rowspan="1" colspan="1">1.05 (0.51 to 2.15)</td><td align="left" valign="top" rowspan="1" colspan="1">0.90</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">TERT</italic> promoter mutation</td><td align="left" valign="top" rowspan="1" colspan="1">0.30 (0.10 to 0.93)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.04</bold></td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">CDKN2B</italic> mutation</td><td align="left" valign="top" rowspan="1" colspan="1">1.86 (0.55 to 6.26)</td><td align="left" valign="top" rowspan="1" colspan="1">0.32</td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td></tr></tbody></table><table-wrap-foot><fn id="T3_FN1"><p>Bold values denote statistical significance at the p &lt; 0.05 level.</p></fn><fn id="T3_FN2"><p>BMI, body mass index; ECOG, Eastern Cooperative Oncology Group Performance Status; N/A, not available; NLR, neutrophil to lymphocyte ratio; UC, urothelial carcinoma.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T4" orientation="portrait"><object-id pub-id-type="publisher-id">T4</object-id><label>Table 4</label><caption><p>Multivariable analyses of progression-free survival with prespecified clinical variables and clinical and genomic characteristics with significant findings on univariable analysis (p&lt;0.1)</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="2" colspan="1">Characteristics</td><td align="left" valign="bottom" rowspan="1" colspan="2">Multivariable analysis (clinical and genomic data; n=78)</td><td align="left" valign="bottom" rowspan="1" colspan="2">Multivariable analysis (entire cohort, clinical data only; n=119)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td><td align="left" valign="bottom" rowspan="1" colspan="1">HR (95% CI)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Histology (pure UC vs mixed or pure variant histology)</td><td align="left" valign="top" rowspan="1" colspan="1">0.92 (0.39 to 2.16)</td><td align="left" valign="top" rowspan="1" colspan="1">0.84</td><td align="left" valign="top" rowspan="1" colspan="1">1.10 (0.59 to 2.04)</td><td align="left" valign="top" rowspan="1" colspan="1">0.77</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ECOG PS ≤1</td><td align="left" valign="top" rowspan="1" colspan="1">0.83 (0.33 to 2.13)</td><td align="left" valign="top" rowspan="1" colspan="1">0.69</td><td align="left" valign="top" rowspan="1" colspan="1">0.68 (0.38 to 1.20)</td><td align="left" valign="top" rowspan="1" colspan="1">0.19</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Visceral metastases</td><td align="left" valign="top" rowspan="1" colspan="1">1.87 (0.79 to 4.43)</td><td align="left" valign="top" rowspan="1" colspan="1">0.16</td><td align="left" valign="top" rowspan="1" colspan="1">1.97 (0.99 to 3.92)</td><td align="left" valign="top" rowspan="1" colspan="1">0.06</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Albumin</td><td align="left" valign="top" rowspan="1" colspan="1">0.65 (0.35 to 1.20)</td><td align="left" valign="top" rowspan="1" colspan="1">0.17</td><td align="left" valign="top" rowspan="1" colspan="1">0.66 (0.42 to 1.05)</td><td align="left" valign="top" rowspan="1" colspan="1">0.08</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hemoglobin &lt;100 vs ≥100 g/L</td><td align="left" valign="top" rowspan="1" colspan="1">1.01 (0.40 to 2.54)</td><td align="left" valign="top" rowspan="1" colspan="1">0.98</td><td align="left" valign="top" rowspan="1" colspan="1">1.22 (0.60 to 2.45)</td><td align="left" valign="top" rowspan="1" colspan="1">0.58</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">NLR &lt;5 vs ≥5</td><td align="left" valign="top" rowspan="1" colspan="1">1.12 (0.45 to 2.79)</td><td align="left" valign="top" rowspan="1" colspan="1">0.81</td><td align="left" valign="top" rowspan="1" colspan="1">0.85 (0.47 to 1.52)</td><td align="left" valign="top" rowspan="1" colspan="1">0.57</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"><italic toggle="yes">TERT</italic> promoter mutation</td><td align="left" valign="top" rowspan="1" colspan="1">0.38 (0.18 to 0.81)</td><td align="left" valign="top" rowspan="1" colspan="1"><bold>0.01</bold></td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td><td align="left" valign="top" rowspan="1" colspan="1">N/A</td></tr></tbody></table><table-wrap-foot><fn id="T4_FN1"><p>Bold values denote statistical significance at the p &lt; 0.05 level.</p></fn><fn id="T4_FN2"><p>N/A, not available; NLR, neutrophil to lymphocyte ratio; ECOG PS, Eastern Cooperative Oncology Group performance status; UC, urothelial carcinoma.</p></fn></table-wrap-foot></table-wrap></sec><sec id="s3-4"><title>Genomic prognostic factors</title><p>Genomic profiling results were available for 78 patients (<xref ref-type="table" rid="T1">table 1</xref>). Patients with available genomic profiling were more likely to have an ECOG performance status score ≤1 relative to patients without genomic profiling; other baseline characteristics were balanced between the two groups. Most assays were performed through FoundationOne or the CLIA-certified institutional UCSF500 platform (n=44 and n=30, respectively). The most commonly altered genes were the <italic toggle="yes">TERT</italic> promoter (61.0%), <italic toggle="yes">TP53</italic> (51.9%), <italic toggle="yes">RB1</italic> (31.2%), <italic toggle="yes">CKDN2A</italic> (28.6%), <italic toggle="yes">CDKN2B</italic> (27.3%), <italic toggle="yes">ARID1A</italic> (23.4%), <italic toggle="yes">ERBB2</italic> (18.2%), <italic toggle="yes">KDM6A</italic> (19.5%), <italic toggle="yes">PIK3CA</italic> (16,9%), <italic toggle="yes">FGFR3</italic> and <italic toggle="yes">MLL2</italic> (13.0% each). Mutations in the <italic toggle="yes">TERT</italic> promoter and <italic toggle="yes">MDM2</italic> genes were associated with clinical outcomes on univariable analysis: specifically, the presence of a <italic toggle="yes">TERT</italic> promoter mutation was associated with increased response rate (OR 1.33, p=0.010) and longer PFS (HR 0.41, p=0.002), while the presence of an <italic toggle="yes">MDM2</italic> mutation was associated with lower response rate (OR 1.41, p=0.045). There was a non-statistically significant trend towards shorter OS in patients with <italic toggle="yes">CDKN2B</italic> mutations (<xref ref-type="table" rid="T2">table 2</xref>). Other genomic alterations were not associated with clinical outcomes. On multivariable analysis performed in patients with available genomic profiling results, the presence of a <italic toggle="yes">TERT</italic> promoter mutation was the only variable predictive of improved PFS (HR 0.38, 95% CI 0.18 to 0.81, p=0.01) and OS (HR 0.32, 95% CI 0.10 to 0.93, p=0.04) (<xref ref-type="table" rid="T3 T4">tables 3 and 4</xref>). In an exploratory analysis, survival in patients with both favorable genomic (ie, TERT promoter mutation) and clinical (ie, baseline ECOG score ≤1) prognostic factors was compared with that of patients with only one or no favorable prognostic factor (<xref ref-type="fig" rid="F1">figure 1</xref>). Patients with both a <italic toggle="yes">TERT</italic> promoter mutation and baseline ECOG performance status ≤1 (n=31) had a significantly longer median OS compared with the remaining patients (n=29) (21.2 vs 7.5 months, p=0.03).</p><fig position="float" id="F1" orientation="portrait"><object-id pub-id-type="publisher-id">F1</object-id><label>Figure 1</label><caption><p>Kaplan-Meier curves of OS (A) in patients with (n=47) vs without (n=31) a <italic toggle="yes">TERT</italic> promoter mutation and (B) in patients with both a <italic toggle="yes">TERT</italic> promoter mutation and favorable pretreatment performance status (ECOG score ≤1; n=31) versus patients with no <italic toggle="yes">TERT</italic> promoter mutation or unfavorable performance status (ECOG score &gt;1; n=29). Log-rank test was used to compare survival between each group. ECOG, eastern cooperative Oncology group; OS, overall survival; TERTp, <italic toggle="yes">TERT</italic> promoter.</p></caption><graphic xlink:href="jitc-2020-002127f01" position="float" orientation="portrait" xlink:type="simple"/></fig></sec><sec id="s3-5"><title>Tumor mutation burden</title><p>TMB assessment was included in some NGS platforms and available in 62 patients. The median TMB among patients with available data was 11 mutations/megabase (mut/Mb; range 1–55). Median PFS was significantly longer in TMB-high (TMB ≥10 mut/Mb, n=38) compared with TMB-low (TMB &lt;10 m/mb, n=24) patients (15.0 vs 3.1 months, p=0.005; <xref ref-type="fig" rid="F2">figure 2</xref>). Median OS was also numerically longer in TMB-high patients (28.2 vs 16.5 months) though this difference was not statistically significant (p=0.20). Compared with TMB-low status, TMB-high status was associated with a higher ORR(OR 3.45, 95% CI 1.04 to 11.11, p=0.043) and longer PFS (HR 0.42, 95% CI 0.22 to 0.81, p=0.009), but not OS (<xref ref-type="table" rid="T1">table 1</xref>, <xref ref-type="fig" rid="F2">figure 2</xref>). As TMB was only available in a subset of patients, it was not included in our multivariable analysis.</p><fig position="float" id="F2" orientation="portrait"><object-id pub-id-type="publisher-id">F2</object-id><label>Figure 2</label><caption><p>Kaplan-Meier curves of PFS and OS in patients with high (n=38) vs low (n=24) TMB (A, B, respectively) and positive (n=11) vs negative (n=10) PD-L1 expression status (C, D, respectively). Log-rank test was used to compare survival between each group. OS, overall survival; PFS, progression free survival; TMB, tumor mutation burden.</p></caption><graphic xlink:href="jitc-2020-002127f02" position="float" orientation="portrait" xlink:type="simple"/></fig><p>We observed a significant interaction between <italic toggle="yes">CKDN2A</italic> and <italic toggle="yes">CDKN2B</italic> alterations and TMB. Specifically, patients with CDKN2A alterations had a significantly lower TMB than patients without (median TMB 7 vs 12 mut/Mb, p=0.04); similarly, patients with <italic toggle="yes">CDKN2B</italic> alterations had a significantly lower TMB compared with wild type counterparts (median TMB 7 vs 12.5 mut/Mb, p=0.02). On the other hand, there was no significant difference in median TMB (11.8 mut/Mb vs 11 mut/Mb) or the incidence of TMB-high status (57.5% vs 66.7%) across patients with or without <italic toggle="yes">TERT</italic> promoter mutations.</p></sec><sec id="s3-6"><title>PD-L1 expression status</title><p>Testing for PD-L1 expression status was performed in 21 patients; PD-L1 was considered positive (Combined Positive Score ≥10) in 11 out of 21 tested cases (52.4%). Compared with PD-L1 negative cases, patients with PD-L1 expression had a significantly longer median PFS (not reached vs 3.36 months, p=0.02) and prolonged median OS (17.5 vs 12.6 months), though the latter did not meet statistical significance (p=0.12; <xref ref-type="fig" rid="F2">figure 2</xref>). Among the subset of patients with positive PD-L1 expression and high TMB (n=7), clinical benefit to ICI treatment was seen for all patients including a CR in three, PR in two, and SD in two patients (ORR 71.4%); median OS was not reached. Given our limited sample size, PD-L1 expression was excluded from our univariable and multivariable analyses, however, 8 of the 11 patients (72.7%) with a positive PD-L1 expression status achieved an objective response to ICI (including 4 CR), while only 2 out of the 10 patients with negative PD-L1 status had PR as best response to ICI, with no observed CRs.</p></sec></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><p>In this single-center retrospective cohort of 119 patients with advanced urothelial cancer treated with an ICI, ORR was 29% and median OS was 13.4 months. These results are comparable to the outcomes reported in clinical trials of ICI in aUC published to date.<xref ref-type="bibr" rid="R1 R2 R3 R4 R5 R6 R7 R8 R9">1–9</xref> With genomic profiling results available in 78 out of 119 patients, this study constitutes one of the larger exploratory analyses of combined genomic, laboratory and clinical characteristics in aUC patients treated with an ICI. The results show that the presence of a <italic toggle="yes">TERT</italic> promoter mutation is associated with improved long-term clinical outcomes, including a significantly longer PFS and OS, even after adjusting for other baseline characteristics. On the other hand, aside from ECOG performance status, pretreatment clinical and laboratory characteristics were not independently associated with response to ICI or with clinical outcomes. Altogether, these findings suggest that the presence of a <italic toggle="yes">TERT</italic> promoter mutation may represent an important genomic predictive marker of response to ICI treatment in patients with aUC.</p><p><italic toggle="yes">TERT</italic> promoter mutations increase expression of the <italic toggle="yes">TERT</italic> gene—which encodes the catalytic subunit of the telomerase enzyme.<xref ref-type="bibr" rid="R23">23</xref> Telomerase activity is suppressed in normal human urothelial cells, and reactivation is thought to constitute an early driver of urothelial carcinogenesis.<xref ref-type="bibr" rid="R24">24</xref> In line with this, <italic toggle="yes">TERT</italic> promoter mutations are the most common genomic alteration in UC,<xref ref-type="bibr" rid="R25">25</xref> and were observed in 61% of patients in this cohort. Increased telomerase activity contributes to tumorigenesis by preventing telomere shortening in replicating cancer cells.<xref ref-type="bibr" rid="R24">24</xref> Telomere length-independent mechanisms of oncogenicity have also been described, including suppression of oncogene-induced and aneuploidy-induced senescence<xref ref-type="bibr" rid="R26">26</xref> and induction of epithelial-to-mesenchymal transition (EMT).<xref ref-type="bibr" rid="R27">27</xref> Interestingly, among patients with non-muscle invasive bladder cancer, the presence of a <italic toggle="yes">TERT</italic> promoter mutation was shown to be an independent predictor of nonrecurrence following BCG therapy.<xref ref-type="bibr" rid="R28">28</xref> However, the prognostic and predictive significance of <italic toggle="yes">TERT</italic> promoter mutations in patients with aUC is not well established. Although an initial study of over 400 bladder cancer samples failed to detect any significant association between <italic toggle="yes">TERT</italic> promoter mutations and clinical outcomes,<xref ref-type="bibr" rid="R29">29</xref> subsequent analyses have suggested an increased risk of recurrence,<xref ref-type="bibr" rid="R30">30</xref> distant metastases<xref ref-type="bibr" rid="R31">31</xref> and decreased survival<xref ref-type="bibr" rid="R32 R33">32 33</xref> in patients with <italic toggle="yes">TERT</italic> promoter mutations. Importantly, the patients included in these studies were treated with platinum-based chemotherapy regimens. A more recent analysis by Nassar and colleagues evaluated clinical and genomic predictors of response to ICI in a cohort of 62 patients with aUC. However, genomic profiling was performed by exon capture and therefore did not sequence the <italic toggle="yes">TERT</italic> promoter region.<xref ref-type="bibr" rid="R18">18</xref> Thus, to our knowledge, the impact of <italic toggle="yes">TERT</italic> promoter mutations has not been previously studied in patients with aUC treated with ICIs.<xref ref-type="bibr" rid="R32 R33">32 33</xref></p><p>In the current analysis, we observed a strong association between <italic toggle="yes">TERT</italic> promoter mutations and superior PFS and OS, even after adjusting for other clinical, laboratory, and genomic variables. Although the prevalence of <italic toggle="yes">TERT</italic> promoter mutations is higher in bladder UC than in upper tract UC, we did not find any significant association between primary tumor location and outcomes in our cohort. Instead, we hypothesize that the presence of a <italic toggle="yes">TERT</italic> promoter mutation may be associated with increased tumor immunogenicity through several potential mechanisms. <italic toggle="yes">TERT</italic> promoter mutations have been shown to promote EMT in various cancer cell lines,<xref ref-type="bibr" rid="R27">27</xref> which has in turn been associated with increased PD-L1 expression.<xref ref-type="bibr" rid="R34">34</xref> PD-L1 expression status is associated with increased responses to ICI therapy, but was not assessed in enough patients within this cohort to be included in our multivariable analysis or to assess its relationship with <italic toggle="yes">TERT</italic> promoter mutations. Separately, a study of 398 patients with UC showed that tumors with <italic toggle="yes">TERT</italic> promoter alterations had a significantly higher mutational burden compared with those without <italic toggle="yes">TERT</italic> promoter mutation (median TMB 8 vs 4 mut/Mb; p&lt;0.001), as well as a significantly higher copy number alteration burden.<xref ref-type="bibr" rid="R33">33</xref> A similar association between <italic toggle="yes">TERT</italic> promoter mutations and higher TMB was recently described in a pan-cancer analysis.<xref ref-type="bibr" rid="R35">35</xref> The same study also described a longer median OS in a subset of patients with <italic toggle="yes">TERT</italic> promoter mutations treated with anti-CTLA4 agents. Other genomic biomarkers associated with increased TMB (eg, DNA damage repair gene alterations or the presence of an apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) enzyme mutational signature) have been found to predict response to ICI therapy.<xref ref-type="bibr" rid="R18 R36">18 36</xref> Median TMB in our cohort was numerically slightly higher among patients with a <italic toggle="yes">TERT</italic> promoter mutation compared with wild type patients (11.8 vs 11 m/mb), though this difference was not statistically significant. Interestingly, a recent study of 32 patients with metastatic renal cell carcinoma (RCC) treated with an ICI showed that the presence of a <italic toggle="yes">TERT</italic> promoter mutation was a negative predictor of outcome.<xref ref-type="bibr" rid="R37">37</xref> In part, these discordant findings underscore cross-cancer differences in mechanisms of antitumor immune response as well as differences in tumor biology. Other biomarkers in aUC, such as PD-L1 expression, have shown similarly conflicting results in predicting response to immunotherapy in RCC<xref ref-type="bibr" rid="R38 R39 R40">38–40</xref>—while TMB high status in RCC has somewhat surprisingly been associated with inferior outcomes and decreased immune cell infiltration.<xref ref-type="bibr" rid="R41">41</xref> Ultimately, while our study reports important hypothesis-generating findings, further prospective validation will be needed to confirm the prognostic significance of <italic toggle="yes">TERT</italic> promoter mutation in patients with aUC treated with an ICI and to investigate potential mechanisms that explain this finding.</p><p>PD-L1 expression in the tumor and tumor microenvironment has been extensively studied as a biomarker of response and survival in aUC patients receiving ICI. Unfortunately, PD-L1 expression status was not available for most of the patients in our cohort—reflecting standard of care clinical practice prior to mid 2018—and could not be included in our univariable and multivariable analyses. Patients with a PD-L1 CPS ≥10 did in fact have a higher ORR, median PFS and OS compared with patients with a PD-L1 CPS&lt;10. However, ICI treatment still achieved a PR in 2 and SD in 3 out of 10 patients with a CPS &lt;10. Similarly, a higher TMB was associated with improved outcomes in our univariable analysis, yet 6 out of 25 (24%) patients with TMB &lt;10 had an objective response, including 1 CR. Thus, while TMB-high or positive PD-L1 expression status may predict clinical benefit to ICI, there is not currently enough evidence to justify withholding ICI therapy for aUC patients whose tumors have low TMB or low PD-L1 expression. Interestingly, a recent interim analysis of IMvigor 130 clinical trial suggests that the cooccurrence of high TMB and PD-L1 expression in the tumor may be particularly predictive of a survival benefit with front-line ICI over platinum-based chemotherapy.<xref ref-type="bibr" rid="R19">19</xref> Consistent with this finding, we observed an ORR of 71.4% (CR 42.9%), among this subset of patients our cohort (n=7), and all of these patients had at least SD as best response to ICI treatment.</p><p>Several of the clinical and laboratory markers associated with OS (ECOG performance status, albumin and the presence of visceral metastases) in our univariable analysis have previously been shown to predict survival in patients receiving cytotoxic chemotherapy for aUC.<xref ref-type="bibr" rid="R20 R21">20 21</xref> Baseline performance status remained predictive of OS on multivariable analysis, and we observed a non-statistical trend toward improved OS in patients with higher albumin. We did not see any independent association between survival and hemoglobin levels or survival and the presence of visceral metastases after adjusting for other clinical variables. While this may in part reflect differences in the underlying mechanism of action of ICI compared with cytotoxic chemotherapy, these results should be interpreted with caution given our smaller sample size. Indeed in another cohort of 62 patients with metastatic UC treated with ICI, the lack of visceral metastases did in fact predict clinical benefit to immunotherapy.<xref ref-type="bibr" rid="R18">18</xref></p><p>The main limitations of this study are the retrospective nature of our analysis and the relatively small sample size of our cohort—which may have limited the statistical power of our univariable and multivariable analyses. No centralized radiology or pathology review were done as part of this analysis, reflecting the real-world context of this study. We also studied a fairly heterogeneous patient population, including a mix of histological subtypes and patients treated with ICI both in the front-line and treatment-refractory metastatic settings. Tumor mutational profiling was performed on biopsies of primary tumors and distant metastases alike, using several different NGS platforms, yet this experience also reflects real-world clinical practice in most centers. Finally given the lack of a comparison group, it is more challenging to determine whether the variables associated with response and favorable outcome in our cohort were prognostic biomarkers in urothelial cancer patients, or specifically predictive of a clinical benefit to ICI in this patient population. Nonetheless, this study constitutes one of the largest retrospective analyses of combined clinical and genomic factors in aUC patients treated with ICI. Our findings confirm some of the previously reported associations between pre-treatment variables and clinical outcomes, and identify presence of a <italic toggle="yes">TERT</italic> mutation as a novel putative genomic biomarker in this patient population. As for all retrospective analyses, further prospective validation is needed.</p></sec><sec id="s5" sec-type="conclusions"><title>Conclusion</title><p>Consistent with the published literature, this study indicates that only 25%–30% of unselected patients with aUC will respond to checkpoint blockade inhibition in the front-line or platinum-refractory metastatic setting. With the exception of ECOG performance status, established prognostics factors for patients receiving chemotherapy were not associated with OS in this cohort of aUC patients treated with ICIs. On the other hand, the presence of a <italic toggle="yes">TERT</italic> promoter mutation was found to be a novel and independent predictor of improved PFS and OS for aUC patients treated with ICI. The co-occurrence of a <italic toggle="yes">TERT</italic> promoter mutation and favorable pretreatment performance status (ECOG score ≤1) was associated with a particularly good prognosis (median OS of 21.2 months). Whether the presence of a <italic toggle="yes">TERT</italic> promoter mutation is a predictive rather than purely prognostic biomarker in this patient population remains to be determined. Overall, these findings indicate that genomic profiling done through NGS platforms as part of standard clinical practice can provide independent prognostic information among aUC patients treated with ICI and consequently can significantly influence clinical decision making and consideration of patients for clinical trials.</p></sec></body><back><fn-group><fn fn-type="other"><label>Correction notice</label><p>This paper has been updated since first published to amend author name 'Vadim S Koshkin'.</p></fn><fn fn-type="other"><label>Contributors</label><p>VK, IdK and LZ conceived and designed the project. VK, IdK, EJP, FW, DMK, DN, DMK, SH, HH and EC contributed to data collection, preparation, analysis and interpretation. LZ contributed to data analysis. VK, IdK drafted the manuscript. IdK, LZ, EJP, FW, DMK, DN, DMK, HH, SH, EC, SPP, ACW, AD, FWH, JC, DYO, RSP, LF, EJS, TWF and VK revised the manuscript. All authors have read and approved the submitted version.</p></fn><fn fn-type="other"><label>Funding</label><p>The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.</p></fn><fn fn-type="conflict"><label>Competing interests</label><p>AD reports personal fees from Dendreon. JC reports funding from Bristol-Meyers Squibb. FWH reports funding from GlaxoSmithKline DYO reports research support from Roche/Genentech, Merck and PACT Pharma, as well as consulting fees from Maze Therapeutics. LF reports grants from Abbvie, Bavarian Nordic, BMS, Dendreon, Janssen, Merck ansd Roche-Genentech. EJS reports personal fees and funding from Fortis Therapeutics, personal fees and funding from Harpoon Therapeutics, as well as personal fees from Janssen, Johnson and Johnson, Teon Therapeutics, Ultragenyx, Beigene and Tolero. TWF reports personal fees from EMD Serono, Astra Zeneca, grants from Roche/Genentech, as well as grants and personal fees from Seattle Genetics. VK reports grants and personal fees from Clovis, personal fees from Pfizer, AstraZeneca, Dendreon and Seattle Genetics, as well as grants from Nektar and Endocyte. The other authors have declared no relevant competing interests related to this manuscript.</p></fn><fn fn-type="other"><label>Provenance and peer review</label><p>Not commissioned; externally peer reviewed.</p></fn></fn-group><sec sec-type="data-availability"><title>Data availability statement</title><p>Deidentified patient data are available from the corresponding author, VK, on reasonable request sent to the following address: Vadim.Koshkin@ucsf.edu.</p></sec><sec sec-type="ethics-statement"><title>Ethics statements</title><sec sec-type="ethics-consent-to-publish"><title>Patient consent for publication</title><p>Not required.</p></sec><sec sec-type="ethics-approval"><title>Ethics approval</title><p>Retrospective deidentified patient data were collected in compliance with the IRB guidelines of the participating institution and did not require specific approval from an ethics committee.</p></sec></sec><ref-list><title>References</title><ref id="R1"><label>1</label><mixed-citation 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