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<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="brief-report" 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>1d2b230b09</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-2019-000438</article-id><article-id pub-id-type="doi">10.1136/jitc-2019-000438</article-id><article-id pub-id-type="pmid">32111729</article-id><article-id pub-id-type="apath" assigning-authority="highwire">/jitc/8/1/e000438.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>Short report</series-title></article-categories><title-group><article-title>
<italic toggle="yes">ARID1A</italic> alterations function as a biomarker for longer progression-free survival after anti-PD-1/PD-L1 immunotherapy</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" id="author-74834921" xlink:type="simple"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0001-7352-8621</contrib-id><name name-style="western"><surname>Okamura</surname><given-names>Ryosuke</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74835343" xlink:type="simple"><name name-style="western"><surname>Kato</surname><given-names>Shumei</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74835282" xlink:type="simple"><name name-style="western"><surname>Lee</surname><given-names>Suzanna</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74835290" xlink:type="simple"><name name-style="western"><surname>Jimenez</surname><given-names>Rebecca E</given-names></name><xref ref-type="aff" rid="aff1">1</xref></contrib><contrib contrib-type="author" id="author-74835312" xlink:type="simple"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0003-4403-0271</contrib-id><name name-style="western"><surname>Sicklick</surname><given-names>Jason K</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref></contrib><contrib contrib-type="author" id="author-74835329" xlink:type="simple"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0003-4110-1214</contrib-id><name name-style="western"><surname>Kurzrock</surname><given-names>Razelle</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">Center for Personalized Cancer Therapy</institution>, <institution xlink:type="simple">UC San Diego Moores Cancer Center</institution>, <addr-line content-type="city">La Jolla</addr-line>, <addr-line content-type="state">California</addr-line>, <country>USA</country>
</aff><aff id="aff2">
<label>2</label>
<institution content-type="department" xlink:type="simple">Division of Surgical Oncology, Department of Surgery</institution>, <institution xlink:type="simple">UC San Diego Moores Cancer Center</institution>, <addr-line content-type="city">La Jolla</addr-line>, <addr-line content-type="state">California</addr-line>, <country>United States</country>
</aff><author-notes><corresp>
<label>Correspondence to</label> Dr Ryosuke Okamura; <email xlink:type="simple">ryokamura@health.ucsd.edu</email>
</corresp></author-notes><pub-date date-type="pub" iso-8601-date="2020-02" pub-type="ppub" publication-format="print"><month>2</month><year>2020</year></pub-date><pub-date date-type="pub" iso-8601-date="2020-02-27" pub-type="epub-original" publication-format="electronic"><day>27</day><month>2</month><year>2020</year></pub-date><pub-date iso-8601-date="2019-12-20T04:54:25-08:00" pub-type="hwp-received"><day>20</day><month>12</month><year>2019</year></pub-date><pub-date iso-8601-date="2019-12-20T04:54:25-08:00" pub-type="hwp-created"><day>20</day><month>12</month><year>2019</year></pub-date><pub-date iso-8601-date="2020-02-27T19:56:21-08:00" pub-type="epub"><day>27</day><month>2</month><year>2020</year></pub-date><volume>8</volume><issue>1</issue><elocation-id>e000438</elocation-id><history><date date-type="accepted" iso-8601-date="2020-02-11"><day>11</day><month>02</month><year>2020</year></date></history><permissions><copyright-statement>© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.</copyright-statement><copyright-year>2020</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/" xlink:type="simple"><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/" start_date="2020-02-27">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-2019-000438.pdf" xlink:type="simple"/><abstract><sec><title>Background</title><p>Several cancer types harbor alterations in the gene encoding AT-Rich Interactive Domain-containing protein 1A (ARID1A), but there are no approved therapies to address these alterations. Recent studies have shown that <italic toggle="yes">ARID1A</italic> deficiency compromises mismatch repair proteins. Herein, we analyzed 3403 patients who had tumor tissue next-generation sequencing.</p></sec><sec><title>Findings</title><p>Among nine cancer subtypes with &gt;5% prevalence of <italic toggle="yes">ARID1A</italic> alterations, microsatellite instability-high as well as high tumor mutational burden was significantly more frequent in <italic toggle="yes">ARID1A</italic>-altered versus <italic toggle="yes">ARID1A</italic> wild-type tumors (20% vs 0.9%, p&lt;0.001; and 26% vs 8.4%, p&lt;0.001, respectively). Median progression-free survival (PFS) after checkpoint blockade immunotherapy was significantly longer in the patients with <italic toggle="yes">ARID1A</italic>-altered tumors (n=46) than in those with <italic toggle="yes">ARID1A</italic> wild-type tumors (n=329) (11 months vs 4 months, p=0.006). Also, multivariate analysis showed that <italic toggle="yes">ARID1A</italic> alterations predicted longer PFS after checkpoint blockade (HR (95% CI), 0.61 (0.39 to 0.94), p=0.02) and this result was independent of microsatellite instability or mutational burden; median overall survival time was also longer in <italic toggle="yes">ARID1A-</italic>altered versus wild-type tumors (31 months vs 20 months), but did not reach statistical significance (p=0.13).</p></sec><sec><title>Conclusions</title><p>Our findings suggest that <italic toggle="yes">ARID1A</italic> alterations merit further exploration as a novel biomarker correlating with better outcomes after checkpoint blockade immunotherapy.</p></sec></abstract><kwd-group><kwd>
<italic toggle="yes">ARID1A</italic>
</kwd><kwd>PD-L1</kwd><kwd>immune checkpoint inhibitor</kwd><kwd>immunotherapy</kwd><kwd>tumor mutation burden</kwd><kwd>microsatellite instability</kwd><kwd>biomarker</kwd></kwd-group><funding-group specific-use="FundRef"><award-group id="funding-1" xlink:type="simple"><funding-source xlink:type="simple">
<institution-wrap><institution xlink:type="simple">The Joan and Irwin Jacobs Fund</institution></institution-wrap>
</funding-source></award-group><award-group id="funding-2" xlink:type="simple"><funding-source xlink:type="simple">
<institution-wrap><institution xlink:type="simple">NIH</institution></institution-wrap>
</funding-source><award-id xlink:type="simple">P30 CA023100</award-id></award-group></funding-group><custom-meta-group><custom-meta xlink:type="simple"><meta-name>special-feature</meta-name><meta-value>unlocked</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>special-property</meta-name><meta-value>contains-inline-supplementary-material</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>The <italic toggle="yes">ARID1A</italic> gene encoding AT-Rich Interactive Domain-containing protein 1A is known as a member of the switching/sucrose non-fermentable (SWI/SNF) complex involved in chromatin remodeling.<xref ref-type="bibr" rid="R1">1</xref> Mutations in and loss of the <italic toggle="yes">ARID1A</italic> gene mostly lead to its inactivation and ARID1A protein loss.<xref ref-type="bibr" rid="R2">2</xref> Certain types of cancer, including clear cell ovarian carcinoma (46%–50%), gastric adenocarcinoma (10%–35%), and cholangiocarcinoma (15%–27%), frequently harbor <italic toggle="yes">ARID1A</italic> alterations.<xref ref-type="bibr" rid="R2 R3 R4">2–4</xref> To date, clinical and preclinical data indicate that <italic toggle="yes">ARID1A</italic> alterations may sensitize tumors to drugs targeting the ataxia telangiectasia and Rad3-related (ATR) protein, the enhancer of zeste 2 (EZH2), or the phosphatidylinositol-3-kinase (PI3K) pathway,<xref ref-type="bibr" rid="R5 R6 R7 R8 R9 R10">5–10</xref> but no therapies targeting <italic toggle="yes">ARID1A</italic> alterations have been approved. Importantly, Shen <italic toggle="yes">et al</italic> demonstrated that <italic toggle="yes">ARID1A</italic> alterations interact with the mismatch repair (MMR) protein MSH2 and, hence, compromise MMR.<xref ref-type="bibr" rid="R3">3</xref> Tumors formed by an <italic toggle="yes">ARID1A</italic>-deficient ovarian cancer cell line in syngeneic mice exhibited higher mutation load, as well as increased numbers of tumor-infiltrating lymphocytes and elevated programmed cell death-ligand 1 (PD-L1) expression. Furthermore, administration of anti-PD-L1 antibody decreased cancer burden and extended survival of mice bearing <italic toggle="yes">ARID1A</italic>-deficient but not <italic toggle="yes">ARID1A</italic> wild-type ovarian tumors.<xref ref-type="bibr" rid="R3">3</xref> Interestingly, alterations in the polybromo-1 (<italic toggle="yes">PBRM1</italic>) gene, which is another member of the SWI/SNF complex, have been reported to correlate with salutary effects in cancer patients receiving checkpoint blockade inhibitors, though the clinical evidence remains controversial.<xref ref-type="bibr" rid="R11 R12">11 12</xref> In gastric cancers, <italic toggle="yes">ARID1A</italic> alterations are associated with Epstein-Barr virus infection, which is in turn associated with checkpoint blockade response.<xref ref-type="bibr" rid="R13">13</xref> Herein, for the first time to our knowledge, we investigated the clinical correlation between <italic toggle="yes">ARID1A</italic> alterations and treatment benefit after anti-programmed cell death-1 (PD-1)/PD-L1 immunotherapy in the human pan-cancer setting.</p></sec><sec id="s2" sec-type="materials"><title>Materials and methods</title><sec id="s2-1"><title>Study population and next-generation sequence</title><p>In a cohort of 3403 eligible patients at the Center for Personalized Cancer Therapy (University of California San Diego Moores Cancer Center), whose tissue DNA was analyzed by next-generation sequencing (NGS) by Foundation Medicine, Inc. (CLIA-licensed and CAP-accredited laboratory. Cambridge, Massachusetts, USA <ext-link ext-link-type="uri" xlink:href="https://www.foundationmedicine.com" xlink:type="simple">https://www.foundationmedicine.com</ext-link>), we reviewed the clinicopathological and genomic information of patients whose tumors were pathologically diagnosed as one of nine types of cancer that frequently harbored <italic toggle="yes">ARID1A</italic> alterations (&gt;5% of prevalence in this cohort): non-small cell lung cancer, colorectal adenocarcinoma, breast cancer, melanoma, pancreatic ductal adenocarcinoma, cholangiocarcinoma/hepatocellular carcinoma, gastric/esophageal adenocarcinoma, uterine/ovary endometrial (endometrioid) carcinoma (including clear-cell carcinoma), and urothelial bladder carcinoma. Tissue DNA sequencing at the laboratory was approved by the US Food and Drug Administration in November 2017 and designed to include all genes somatically altered in human solid malignancies that were validated as targets for therapy, either approved or in clinical trials, and/or that were unambiguous drivers of oncogenesis based on available knowledge.<xref ref-type="bibr" rid="R14 R15">14 15</xref> Although the gene panel expanded with time (236–324 genes), the interrogation of the <italic toggle="yes">ARID1A</italic> gene was considered consistent. Only characterized <italic toggle="yes">ARID1A</italic> alterations were considered in this study (variants of unknown significant were excluded). In terms of microsatellite instability (MSI) status, 114 intron homo-polymer repeat loci with adequate coverage are analyzed for length variability and compiled into an overall score via principal components analysis.<xref ref-type="bibr" rid="R16 R17">16 17</xref> Measuring genes interrogated on the tissue DNA NGS and extrapolating to the genome as a whole as previously validated determined tumor mutational burden (TMB).<xref ref-type="bibr" rid="R18">18</xref> TMB was classified to three categories: high (≥20 mutations/mb), intermediate (6–19 mutations/mb), and low (&lt;6 mutations/mb).</p></sec><sec id="s2-2"><title>Statistics</title><p>Using the Mann-Whitney U test and Fisher’s exact test, respectively, we compared categorical and continuous data. Progression-free survival (PFS) and overall survival (OS) data were measured from date of the initiation of anti-PD-1/PD-L1 immunotherapy and plotted by the Kaplan-Meier method. Data were censored if patient was progression free or alive (for PFS and OS, respectively) at last follow-up. The curves were compared by using the log-rank test. In multivariate analysis to investigate independent predictive factors for the PFS after anti-PD-1/PD-L1 immunotherapy, we used Cox’s proportional hazard model for estimating HR and its 95% CI (variables with p&lt;0.1 in the univariate analyses were entered into the multivariate analysis). RO performed and verified statistical analysis using SPSS V.24 software.</p></sec></sec><sec id="s3" sec-type="results"><title>Results and discussion</title><p>Starting with 3403 eligible patients who underwent tissue DNA NGS, we found 1540 patients with nine types of cancer diagnoses that had &gt;5% prevalence of characterized <italic toggle="yes">ARID1A</italic> alterations in tissue DNA NGS (<xref ref-type="fig" rid="F1">figure 1A</xref> and <xref ref-type="supplementary-material" rid="SP1">online supplementary figure 1</xref>). Of 161 patients with ≥1 characterized <italic toggle="yes">ARID1A</italic> alteration in diverse types of cancer, 142 had <italic toggle="yes">ARID1A</italic> substitution or frameshift alterations, while the remaining 19 had insertions, deletions, allelic loss, rearrangement, or truncation. Endometrial and gastroesophageal cancers were the tumor types in which <italic toggle="yes">ARID1A</italic> alterations were most frequent—49% and 20% of cases, respectively (<xref ref-type="fig" rid="F1">figure 1A</xref>). The median number of genomic coalterations among tumors with <italic toggle="yes">ARID1A</italic> alterations was 6 (range, 1–72) (not including <italic toggle="yes">ARID1A</italic> alterations), which was significantly higher than the median of 4 alterations (range, 0–61) among those cancers with wild-type <italic toggle="yes">ARID1A</italic> (p&lt;0.001). The rate of MSI-high was significantly higher in tumors with <italic toggle="yes">ARID1A</italic> alterations than in those with wild-type <italic toggle="yes">ARID1A</italic> (20% vs 0.9%; p&lt;0.001) and in multiple individual tumor types as well (eg, MSI-high in <italic toggle="yes">ARID1A</italic>-altered vs wild-type endometrial cancer, 41% vs 0%, p=0.001) (<xref ref-type="fig" rid="F1">figure 1B</xref>). Similarly, TMB-high (≥20 mutations/mb) was more often observed in tumors with <italic toggle="yes">ARID1A</italic> alterations than in those with wild-type <italic toggle="yes">ARID1A</italic> (26% vs 8.4%; p&lt;0.001) and in individual tumor types (eg, endometrial cancer, 35% vs 0%, p=0.001) (<xref ref-type="fig" rid="F1">figure 1C</xref>).</p><supplementary-material id="SP1" position="float" orientation="portrait" xlink:type="simple"><object-id pub-id-type="publisher-id">SP1</object-id><object-id pub-id-type="doi">10.1136/jitc-2019-000438.supp1</object-id><label>Supplementary data</label><p>
<inline-supplementary-material id="SS1" xlink:href="jitc-2019-000438supp001.pdf" mime-subtype="pdf" mimetype="application" xlink:type="simple"/>
</p></supplementary-material><fig position="float" id="F1" orientation="portrait"><object-id pub-id-type="publisher-id">F1</object-id><label>Figure 1</label><caption><p>(A) Prevalence of characterized <italic toggle="yes">ARID1A</italic> alterations in tissue DNA NGS according to cancer types (n=1540). (B) Frequency of MSI-high according to <italic toggle="yes">ARID1A</italic> status (microsatellite status was available in 1093 patients (71.0%)). (C) Frequency of TMB-high according to <italic toggle="yes">ARID1A</italic> status (TMB-status was available in 1411 patients (91.6%); p values are for TMB-high rates): TMB-high (≥20 mutations/mb); TMB-intermediate (6–19 mutations/mb); TMB-low (&lt;6 mutations/mb). <italic toggle="yes">ARID1A</italic>, AT-Rich Interactive Domain-containingprotein 1A; bladder, urothelial bladder carcinoma; breast, breast cancer; cholangio/HCC, cholangiocarcinoma and hepatocellular carcinoma; colorectal, colorectal adenocarcinoma; endometrial, uterine/ovary endometrial (endometrioid) carcinoma; gastroesophageal, gastric/esophageal adenocarcinoma; MSI, microsatellite instability; NGS, next-generation sequencing; NSCLC, non-small cell lung cancer; pancreatic, pancreatic ductal adenocarcinoma; TMB, tumor mutational burden.</p></caption><graphic xlink:href="jitc-2019-000438f01" position="float" orientation="portrait" xlink:type="simple"/></fig><p>Overall, 375 patients (24%) among the 1540 patients with the nine types of cancer with &gt;5% <italic toggle="yes">ARID1A</italic> alterations received anti-PD-1/PD-L1 immunotherapy in the advanced/metastatic disease setting (see <xref ref-type="supplementary-material" rid="SP1">online supplementary figure 1</xref>). MSI-high and TMB-high were seen in 4.3% (n=16) and 17% (n=65) of these 375 patients, respectively. As shown in <xref ref-type="fig" rid="F2">figure 2A</xref>, patients with <italic toggle="yes">ARID1A</italic>-altered tumors showed a significantly longer PFS than those with the wild-type tumors (10.9 months vs 3.9 months, p=0.006) from the start of anti-PD-1/PD-L1 immunotherapy. When PFS was analyzed according to cancer diagnosis (only tumor types with ≥5 patients with <italic toggle="yes">ARID1A</italic> alterations), similar sensitivity was observed in individual tumor types (eg, colorectal cancer (5.2 months vs 2.1 months, p=0.005); endometrial cancer (4.6 months vs 3.0 months, p=0.02)) (see <xref ref-type="supplementary-material" rid="SP1">online supplementary figure 2</xref>). Importantly, even when only patients without MSI-high were included to the analysis, <italic toggle="yes">ARID1A</italic>-altered tumors showed a significantly longer PFS than those with wild-type tumors: HR (95% CI), 0.62 (0.40 to 0.97); p=0.03 (<xref ref-type="fig" rid="F2">figure 2B</xref>). In the same way, when only patients without TMB-high were included to the analysis, patients with <italic toggle="yes">ARID1A</italic>-altered tumors (vs <italic toggle="yes">ARID1A</italic> wild-type) showed a trend towards longer PFS: HR (95% CI), 0.69 (0.43 to 1.08) although not statistically significant (p=0.10) (see <xref ref-type="supplementary-material" rid="SP1">online supplementary figure 3</xref>) (small numbers of patients precluded analysis of patients with MSI-high or TMB-high who had <italic toggle="yes">ARID1A</italic> alterations vs not). When examining OS in <italic toggle="yes">ARID1A</italic>-altered versus the wild-type patients, median OS time was longer in the <italic toggle="yes">ARID1A</italic>-altered group (30.8 months vs 20 months), but this did not reach statistical significance (p=0.13) (see <xref ref-type="supplementary-material" rid="SP1">online supplementary figure 4</xref>). In order to better determine if the correlation between <italic toggle="yes">ARID1A</italic> alterations and longer PFS was independent of specific confounding variables, we performed a multivariate analysis (patient characteristics of <italic toggle="yes">ARID1A</italic>-altered vs wild-type patients are shown in <xref ref-type="table" rid="T1">table 1</xref>). Our Cox-regression model demonstrated that <italic toggle="yes">ARID1A</italic> alterations were selected as an independent predictor of better outcome (PFS) after anti-PD-1/PD-L1 immunotherapy (HR (95% CI), 0.61 (0.40 to 0.94); p=0.03) (<xref ref-type="table" rid="T2">table 2</xref>).</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 curve of PFS according to <italic toggle="yes">ARID1A</italic> status. (A) Among patients who received anti-programmed cell death-1 (PD-1)/programmed cell death-ligand 1 (PD-L1) immunotherapy (n=375). (B) Among patients without microsatellite instability-high who received anti-PD-1/PD-L1 immunotherapy (n=359). Similar results were seen even if the MS-unknown (n=60) were excluded (p=0.02). <italic toggle="yes">ARID1A</italic>, AT-Rich Interactive Domain-containingprotein 1A; MS, microsatellite status; PFS, progression-free survival.</p></caption><graphic xlink:href="jitc-2019-000438f02" position="float" orientation="portrait" xlink:type="simple"/></fig><table-wrap position="float" id="T1" orientation="portrait"><object-id pub-id-type="publisher-id">T1</object-id><label>Table 1</label><caption><p>Characteristics of patients who underwent anti-PD-1/PD-L1 immunotherapy (n=375)</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Variables</td><td align="left" valign="bottom" rowspan="1" colspan="1">
<italic toggle="yes">ARID1A</italic>-altered<break/>(n=46)</td><td align="left" valign="bottom" rowspan="1" colspan="1">
<italic toggle="yes">ARID1A</italic>-wild type<break/>(n=329)</td><td align="left" valign="bottom" rowspan="1" colspan="1">P value</td></tr></thead><tbody><tr><td align="left" valign="top" colspan="4" rowspan="1">
<bold>Basic characteristics and tissue DNA next-generation sequencing</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Age at tissue DNA analysis, years</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Median (range)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">65.1 (34.0–89.4)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">63.0 (22.3–93.7)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.49</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Gender</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Female</td><td align="char" char="." valign="top" rowspan="1" colspan="1">25 (54.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">142 (43.2%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.16</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Male</td><td align="char" char="." valign="top" rowspan="1" colspan="1">21 (45.7%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">187 (56.8%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> –</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Diagnosis</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Lung cancer, non-small cell</td><td align="char" char="." valign="top" rowspan="1" colspan="1">7 (15.2%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">104 (31.6%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.02</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Colorectal adenocarcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">12 (26.1%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">37 (11.2%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.009</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Breast cancer</td><td align="char" char="." valign="top" rowspan="1" colspan="1">1 (2.2%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">24 (7.3%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.34</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Melanoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">6 (13.0%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">91 (27.7%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.046</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Pancreatic ductal adenocarcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">1 (2.2%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">7 (2.1%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &gt;0.99</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Cholangiocarcinoma/hepatocellular carcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (4.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">13 (4.0%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.71</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Gastric/esophageal adenocarcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">5 (10.9%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">16 (4.9%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.16</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Endometrial carcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">10 (21.7%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">13 (4.0%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Urothelial bladder carcinoma</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (4.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">24 (7.3%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.76</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Characterized alterations</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Median (range)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">8 (2–57)*</td><td align="char" char="." valign="top" rowspan="1" colspan="1">5 (1–24)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Microsatellite status</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> MSI-high</td><td align="char" char="." valign="top" rowspan="1" colspan="1">13 (28.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">3 (0.9%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Stable</td><td align="char" char="." valign="top" rowspan="1" colspan="1">31 (67.4%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">268 (81.5%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.03</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Unknown</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (4.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">58 (17.6%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.02</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Tumor mutational burden, mutations/mb</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Median (range)†</td><td align="char" char="." valign="top" rowspan="1" colspan="1">16.0 (1.0–321.0)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">6.1 (0.0–222.0)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> ≥20 (high)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">18 (39.1%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">47 (14.3%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> 6–19 (intermediate)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">16 (34.8%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">129 (39.2%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.63</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> &lt;6 (low)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">8 (17.4%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">133 (40.4%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.002</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Unknown</td><td align="char" char="." valign="top" rowspan="1" colspan="1">4 (8.7%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">20 (6.1%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.52</td></tr><tr><td align="left" valign="top" colspan="4" rowspan="1">
<bold>Anti-PD-1/PD-L1 immunotherapy</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Administered as</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> 1st line</td><td align="char" char="." valign="top" rowspan="1" colspan="1">8 (17.4%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">113 (34.3%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> <bold>0.03</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> ≥2nd line</td><td align="char" char="." valign="top" rowspan="1" colspan="1">38 (82.6%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">216 (65.7%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> –</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Regimen of anti-PD-1/PD-L1 immunotherapy</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"> </td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Anti-PD-1/PD-L1 monotherapy</td><td align="char" char="." valign="top" rowspan="1" colspan="1">25 (54.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">170 (51.7%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.76</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> With molecular targeting drug</td><td align="char" char="." valign="top" rowspan="1" colspan="1">7 (15.2%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">36 (10.9%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.46</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> With CTLA4 inhibitor</td><td align="char" char="." valign="top" rowspan="1" colspan="1">6 (13.0%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">56 (17.0%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.67</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> With cytotoxic chemotherapy</td><td align="char" char="." valign="top" rowspan="1" colspan="1">4 (8.7%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">33 (10.0%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> &gt;0.99</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> With molecular targeting and cytotoxic drugs</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (4.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (0.6%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.08</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Others‡</td><td align="char" char="." valign="top" rowspan="1" colspan="1">2 (4.3%)</td><td align="char" char="." valign="top" rowspan="1" colspan="1">32 (9.7%)</td><td valign="top" align="char" char="." rowspan="1" colspan="1"> 0.41</td></tr></tbody></table><table-wrap-foot><fn id="T1_FN1"><p>All p-values &lt;0.05 are listed in bold.</p></fn><fn id="T1_FN2"><p>*Excluded <italic toggle="yes">ARID1A</italic> alterations.</p></fn><fn id="T1_FN3"><p>†Among 1411 patients whose TMB data were available.</p></fn><fn id="T1_FN4"><p>‡With NKG2A inhibitor (n=9); with CD73 inhibitor (n=8); with IDO1 inhibitor (n=6); with CD122-preferential IL-2 pathway agonist (n=5); with CTLA4 inhibitor and molecular targeting drug (n=2); with OX40 agonist (n=2); with CEA/BiTE inhibitor (n=1); with 4-1BB inhibitor (n=1).</p></fn><fn id="T1_FN5"><p>
<italic toggle="yes">ARID1A</italic>, AT-Rich Interactive Domain-containing protein 1A gene; bladder, urothelial bladder carcinoma; breast, breast cancer; cholangio/HCC, cholangiocarcinoma and hepatocellular carcinoma; colorectal, colorectal adenocarcinoma; CTLA4, cytotoxic T lymphocyte antigen 4; endometrial, uterine/ovary endometrial (endometrioid) carcinoma; gastroesophageal, gastric/esophageal adenocarcinoma; MSI, microsatellite instability; NSCLC, non-small cell lung cancer; pancreatic, pancreatic ductal adenocarcinoma; PD-1/PD-L1, programmed cell death-1 and its ligand.</p></fn></table-wrap-foot></table-wrap><table-wrap position="float" id="T2" orientation="portrait"><object-id pub-id-type="publisher-id">T2</object-id><label>Table 2</label><caption><p>Univariate and multivariate analyses for progression-free survival after anti-PD-1/PD-L1 immunotherapy (n=375). Variables with p&lt;0.10 in the univariate analyses were entered into the multivariate analysis</p></caption><table frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom" rowspan="3" colspan="1">Characteristics</td><td align="left" valign="bottom" rowspan="1" colspan="4">Progression-free survival</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="2">Univariate analysis</td><td align="left" valign="bottom" rowspan="1" colspan="2">Multivariate analysis</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Median, months</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, years*</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> ≥63 (n=195) vs &lt;63 (n=180)</td><td align="left" valign="top" rowspan="1" colspan="1">4.6 vs 4.0</td><td align="char" char="." rowspan="1" valign="top" colspan="1">0.57</td><td align="left" valign="top" rowspan="1" colspan="1">–</td><td rowspan="1" valign="top" align="char" char="." colspan="1">–</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Gender</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Female (n=167) vs male (n=208)</td><td align="left" valign="top" rowspan="1" colspan="1">3.8 vs 5.1</td><td align="char" char="." rowspan="1" valign="top" colspan="1">0.08</td><td align="left" valign="top" rowspan="1" colspan="1">1.16 (0.91 to 1.47)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">0.23</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Diagnosis</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td rowspan="1" valign="top" align="char" char="." colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> NSCLC (n=111) vs not (n=264)</td><td align="left" valign="top" rowspan="1" colspan="1">4.9 vs 4.1</td><td align="char" char="." rowspan="1" valign="top" colspan="1">0.99</td><td align="left" valign="top" rowspan="1" colspan="1">–</td><td rowspan="1" valign="top" align="char" char="." colspan="1">–</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Colorectal (n=49) vs not (n=326)</td><td align="left" valign="top" rowspan="1" colspan="1">2.9 vs 4.6</td><td align="char" char="." rowspan="1" valign="top" colspan="1">
<bold>0.02</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">1.38 (0.98 to 1.97)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">0.07</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Melanoma (n=97) vs not (n=278)</td><td align="left" valign="top" rowspan="1" colspan="1">7.8 vs 3.7</td><td align="char" char="." rowspan="1" valign="top" colspan="1">&lt;<bold>0.001</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">0.69 (0.50 to 0.95)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">
<bold>0.02</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Endometrial (n=23) vs not (n=352)</td><td align="left" valign="top" rowspan="1" colspan="1">3.7 vs 4.2</td><td align="char" char="." rowspan="1" valign="top" colspan="1">0.64</td><td align="left" valign="top" rowspan="1" colspan="1">–</td><td rowspan="1" valign="top" align="char" char="." colspan="1">–</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Number of characterized alteration in tissue DNA†</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> ≥6 (n=195) vs &lt;6 (n=180)</td><td align="left" valign="top" rowspan="1" colspan="1">4.2 vs 4.2</td><td align="char" char="." rowspan="1" valign="top" colspan="1">
<bold>0.03</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">1.09 (0.84 to 1.41)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">0.51</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">MSI-status</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> MSI-high (n=16) vs not‡ (n=359)</td><td align="left" valign="top" rowspan="1" colspan="1">12.3 vs 4.0</td><td align="char" char="." rowspan="1" valign="top" colspan="1">
<bold>0.01</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">0.74 (0.33 to 1.64)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">0.46</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">TMB, mutations/mb</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> TMB-high (≥20) (n=65) vs not‡ (n=310)</td><td align="left" valign="top" rowspan="1" colspan="1">13.6 vs 3.7</td><td align="char" char="." rowspan="1" valign="top" colspan="1">&lt;<bold>0.001</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">0.47 (0.31 to 0.71)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">&lt;<bold>0.001</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">ARID1A status</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> <italic toggle="yes">ARID1A</italic>-altered (n=46) vs wild type (n=329)</td><td align="left" valign="top" rowspan="1" colspan="1">10.9 vs 3.9</td><td align="char" char="." rowspan="1" valign="top" colspan="1">
<bold>0.006</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">0.61 (0.39 to 0.94)§</td><td rowspan="1" valign="top" align="char" char="." colspan="1">
<bold>0.02</bold>
</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Regimen of anti-PD-1/PD-L1 immunotherapy</td><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td align="left" valign="top" rowspan="1" colspan="1"/><td valign="top" align="char" char="." rowspan="1" colspan="1"/></tr><tr><td align="left" valign="top" rowspan="1" colspan="1"> Administered as 1st line (n=121) vs ≥2nd line (n=254)</td><td align="left" valign="top" rowspan="1" colspan="1">7.4 vs 3.7</td><td align="char" char="." rowspan="1" valign="top" colspan="1">
<bold>0.001</bold>
</td><td align="left" valign="top" rowspan="1" colspan="1">0.80 (0.60 to 1.07)</td><td rowspan="1" valign="top" align="char" char="." colspan="1">0.13</td></tr></tbody></table><table-wrap-foot><fn id="T2_FN1"><p>All p-values &lt;0.05 are listed in bold.</p></fn><fn id="T2_FN2"><p>*Age at tissue DNA analysis. Dichotomized by the median.</p></fn><fn id="T2_FN3"><p>†Dichotomized by the median.</p></fn><fn id="T2_FN4"><p>‡Including patients whose data were not reported.</p></fn><fn id="T2_FN5"><p>§The HR (95% CI) was similar (0.55 (0.34 to 0.88), p=0.01) even if patients with MS-unknown or TMB-unknown (n=70) were excluded.</p></fn><fn id="T2_FN6"><p>
<italic toggle="yes">ARID1A</italic>, AT-Rich Interactive Domain-containing protein 1A gene; CI, confidence interval; HR, hazard ratio; MSI, microsatellite instability; NSCLC, non-small cell lung cancer; PD-1/PD-L1, programmed cell death-1 and its ligand; TMB, tumor mutational burden.</p></fn></table-wrap-foot></table-wrap><p>In conclusion, 28% of <italic toggle="yes">ARID1A</italic>-altered tumors (n=32 of 114 patients whose microsatellite and TMB status were both available) had either MSI-high or TMB-high (or both), and the rate of MSI-high and TMB-high was significantly higher in <italic toggle="yes">ARID1A</italic>-altered versus wild-type tumors. These findings are consistent with previous reports that <italic toggle="yes">ARID1A</italic> deficiency is correlated with MMR deficiency.<xref ref-type="bibr" rid="R3 R19">3 19</xref>
<italic toggle="yes">ARID1A</italic> alterations were independently and significantly associated with longer PFS after anti-PD-1/PD-L1 immunotherapy (regardless of microsatellite and TMB status). This study has several limitations such as the small number of patients with each cancer type, which restricted our ability to analyze individual tumor histologies. Nevertheless, the results suggest generalizability across tumor types. Another limitation was that improvement in OS in <italic toggle="yes">ARID1A</italic>-altered patients (vs wild-type) did not reach statistical significance; larger numbers of patients are needed to validate this endpoint. Therefore, <italic toggle="yes">ARID1A</italic> alterations may be a genomic marker of checkpoint blockade sensitivity, in addition to other putative markers such as MSI-high and TMB-high.<xref ref-type="bibr" rid="R20 R21 R22">20–22</xref> Our observations indicate that <italic toggle="yes">ARID1A</italic> alterations warrant further studies with longer follow-up and larger numbers of patients in order to confirm if they can be added to the armamentarium of genomic markers that are exploitable for matching patients to immunotherapy in the pan-cancer setting.<xref ref-type="bibr" rid="R23 R24">23 24</xref>
</p></sec></body><back><fn-group><fn fn-type="other"><label>Contributors</label><p>Study conception and design: RO, SK, JKS, and RK; data acquisition: RO, SL, and REJ; statistical analysis: RO and SK; data interpretation: RO, SK, JKS, and RK; drafting the manuscript or revising it critically: all authors; final approval of the manuscript: all authors.</p></fn><fn fn-type="other"><label>Funding</label><p>This work was funded in part by the Joan and Irwin Jacobs Fund and NIH P30 CA023100 (RK). We appreciate funding support from Hope for a Cure Foundation, Jon Strong, NIH R01 CA226803, and FDA R01 FD006334 (JKS).</p></fn><fn fn-type="conflict"><label>Competing interests</label><p>SK serves as a consultant fee (Foundation Medicine) and speaker’s fee (Roche). JKS has the following disclosure information: Research funding (Novartis Pharmaceuticals, Amgen Pharmaceuticals, and Foundation Medicine); Consultant fee (Grand Rounds (2015–2019), Loxo Oncology (2017–2018), Deciphera (2019), and Roche (2019)). RK has the following disclosure information: Stock and Other Equity Interests (IDbyDNA, CureMatch, and Soluventis); Consulting or Advisory role (Gaido, LOXO, X-Biotech, Actuate Therapeutics, Roche, NeoMed, Soluventis, and Pfizer); Speaker’s fee (Roche); Research Funding (Incyte, Genentech, Merck Serono, Pfizer, Sequenom, Foundation Medicine, Guardant Health, Grifols, Konica Minolta, DeBiopharm, Boerhringer Ingelheim, and OmniSeq (All institutional)); Board Member (CureMatch).</p></fn><fn fn-type="other"><label>Patient consent for publication</label><p>Not required.</p></fn><fn fn-type="other"><label>Ethics approval</label><p>This study was approved by the Internal Review Board at UC San Diego Moores Cancer Center. All investigations followed the guidelines of the <italic toggle="yes">Profile-Related Evidence Determining Individualized Cancer Therapy</italic> study (UCSDPREDICT study: <ext-link ext-link-type="clintrialgov" xlink:href="NCT02478931" xlink:type="simple">NCT02478931</ext-link>) for data collection and any investigational therapies for which the patient gave consent.</p></fn><fn fn-type="other"><label>Provenance and peer review</label><p>Not commissioned; externally peer reviewed.</p></fn><fn fn-type="other"><label>Data availability statement</label><p>Data are available upon reasonable request. The data that support the findings of our study are available upon request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.</p></fn></fn-group><ref-list><title>References</title><ref id="R1"><label>1</label><mixed-citation publication-type="journal" xlink:type="simple">
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