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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2022.1012173</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The role of YAP1 in survival prediction, immune modulation, and drug response: A pan-cancer perspective</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Hu</surname>
<given-names>Xueqing</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1952955"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Yingru</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1081778"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yu</surname>
<given-names>Hao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Yiyang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1395726"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Sun</surname>
<given-names>Xiaoting</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/846076"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Qi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/834969"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Yan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1007190"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine</institution>, <addr-line>Shanghai</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Jongdae Lee, Guangzhou Medical University, China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Hong Sook Kim, Sungkyunkwan University, South Korea; Nor Hazwani Ahmad, Universiti Sains Malaysia (USM), Malaysia</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Yan Wang, <email xlink:href="mailto:yanwang@shutcm.edu.cn">yanwang@shutcm.edu.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>21</day>
<month>11</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>13</volume>
<elocation-id>1012173</elocation-id>
<history>
<date date-type="received">
<day>05</day>
<month>08</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>31</day>
<month>10</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Hu, Zhang, Yu, Zhao, Sun, Li and Wang</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Hu, Zhang, Yu, Zhao, Sun, Li and Wang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>Dysregulation of the Hippo signaling pathway has been implicated in multiple pathologies, including cancer, and <italic>YAP1</italic> is the major effector of the pathway. In this study, we assessed the role of <italic>YAP1</italic> in prognostic value, immunomodulation, and drug response from a pan-cancer perspective.</p>
</sec>
<sec>
<title>Methods</title>
<p>We compared <italic>YAP1</italic> expression between normal and cancerous tissues and among different pathologic stages survival analysis and gene set enrichment analysis were performed. Additionally, we performed correlation analyses of <italic>YAP1</italic> expression with RNA modification-related gene expression, tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint regulator expression, and infiltration of immune cells. Correlations between <italic>YAP1</italic> expression and IC<sub>50</sub>s (half-maximal inhibitory concentrations) of drugs in the CellMiner database were calculated.</p>
</sec>
<sec>
<title>Results</title>
<p>We found that <italic>YAP1</italic> was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications, particularly m6A methylation. High expression of <italic>YAP1</italic> was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. <italic>YAP1</italic> expression was negatively correlated with the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, and positively correlated with the infiltration of myeloid-derived suppressor cells (MDSCs) and cancer-associated fibroblasts (CAFs) in pan-cancer. Higher <italic>YAP1</italic> expression showed upregulation of TGF-&#x3b2; signaling, Hedgehog signaling, and KRAS signaling. IC<sub>50</sub>s of FDA-approved chemotherapeutic drugs capable of inhibiting DNA synthesis, including teniposide, dacarbazine, and doxorubicin, as well as inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials were negatively correlated with <italic>YAP1</italic> expression.</p>
</sec>
<sec>
<title>Discussion</title>
<p>In conclusion, <italic>YAP1</italic> is aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of <italic>YAP1</italic> is associated with poor survival outcomes in certain cancer types. YAP1 may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The tumor-promoting activity of <italic>YAP1</italic> is attributed to the activation of TGF-&#x3b2;, Hedgehog, and KRAS signaling pathways. AZD2858 and varlitinib might be effective in cancer patients with high <italic>YAP1</italic> expression.</p>
</sec>
</abstract>
<kwd-group>
<kwd>
<italic>YAP1</italic>
</kwd>
<kwd>pan-cancer</kwd>
<kwd>immune</kwd>
<kwd>survival</kwd>
<kwd>drug response</kwd>
</kwd-group>
<counts>
<fig-count count="8"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="119"/>
<page-count count="19"/>
<word-count count="7158"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>The Hippo signaling pathway is an evolutionarily conserved pathway with a biological role in cell fate determination, organ size control, and tissue regeneration in most tissues and organs (<xref ref-type="bibr" rid="B1">1</xref>&#x2013;<xref ref-type="bibr" rid="B4">4</xref>). Dysregulation of this pathway has been implicated in a variety of pathologies and has received extensive attention over the past two decades (<xref ref-type="bibr" rid="B5">5</xref>). In cancer research, the activated Hippo pathway is considered a tumor suppressor pathway due to its role in inhibiting cell proliferation and promoting apoptosis (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>).</p>
<p>Growth factors, glucose, hypoxia, cell polarity, and mechanical cues from cell&#x2013;cell or cell&#x2013;extracellular matrix attachment regulate the Hippo pathway (<xref ref-type="bibr" rid="B9">9</xref>). The core components of the Hippo pathway in mammals consist of a kinase cascade, MST1/2 and LATS1/2, and the main effector YAP1/TAZ, a transcriptional coactivator without DNA-binding domains. The major binding partners of YAP1/TAZ are TEAD1&#x2013;4. Other transcriptional factors, including AP1, PITX2, ZEB1, MYC, E2F, and SMADs, have also been reported to cooperate with the YAP1/TAZ&#x2013;TEAD complex (<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B15">15</xref>). In addition, RUNX2, TP73, and FOXO1 also directly bind to YAP1/TAZ (<xref ref-type="bibr" rid="B16">16</xref>). <italic>YAP1</italic> overexpression has been reported to be oncogenic in bile duct, breast, colon, lung, and liver cancers (<xref ref-type="bibr" rid="B17">17</xref>&#x2013;<xref ref-type="bibr" rid="B23">23</xref>). Inhibition of the Hippo pathway or overexpression of <italic>YAP1</italic> may lead to the nuclear translocation of <italic>YAP1</italic>, which then binds to transcription factors to promote the expression of tumor-promoting genes. Of note, YAP1 also functions as a tumor corepressor to repress the expression of downstream genes, including the cell-cycle kinase inhibitor p27, by recruiting the NuRD (nucleosome remodeling deacetylase) complex, YY1, or EZH2, a polycomb repressive complex member (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Thus, the role of transcriptional cofactor or transcriptional corepressor of YAP1 is largely context-dependent. Therefore, better defining the role of <italic>YAP1</italic> in each cancer type will be a key challenge for future studies about target identification and cancer therapy. We investigated the potential role of <italic>YAP1</italic> in survival predication from a pan-cancer perspective.</p>
<p>Tumor-infiltrating immune cells are a major component of the ecosystem in tumor microenvironment (TME) and regulate tumor progression (<xref ref-type="bibr" rid="B26">26</xref>). Recently, the Hippo signaling pathway is emerging as an important pathway to affect immune function in cancer (<xref ref-type="bibr" rid="B27">27</xref>). <italic>YAP1</italic> has been reported to affect the activity of B cells, Tregs, macrophages, and myeloid-derived suppressor cells (MDSCs) in several cancer types (<xref ref-type="bibr" rid="B28">28</xref>). However, the role of <italic>YAP1</italic> in different cancer types and its mechanisms in immune regulation remain to be investigated. In this study, we analyzed the correlation between <italic>YAP1</italic> expression and infiltration of various immune cells in 33 cancer types.</p>
<p>Strategies to inhibit YAP1 activity include the following (<xref ref-type="bibr" rid="B1">1</xref>): Disrupting the YAP1&#x2013;TEAD binding or blocking the transcriptional activity of the YAP1&#x2013;TEAD complex. Carbonic anhydrase 3 (CA3) and verteporfin act by disrupting the YAP1&#x2013;TEAD binding (<xref ref-type="bibr" rid="B29">29</xref>&#x2013;<xref ref-type="bibr" rid="B31">31</xref>). The TDU domain of vestigial like family member 4 (VGLL4), a natural antagonist of YAP1, competes with YAP1 to bind TEADs (<xref ref-type="bibr" rid="B32">32</xref>). Narciclasine and peptide17 competes with TEAD4 for binding to YAP1 (<xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B34">34</xref>). In addition, K-975, a TEAD inhibitor, inhibits YAP1/TAZ&#x2013;TEAD interaction (<xref ref-type="bibr" rid="B35">35</xref>) (<xref ref-type="bibr" rid="B2">2</xref>). Targeting downstream targets of YAP1/TAZ (BCL-xL, FOXM1, and TG2). A37, celecoxib, TP-0903, cyclic peptide RA-V (deoxybouvardin), navitoclax, thiostrepton, and NC-9 fall into this category (<xref ref-type="bibr" rid="B36">36</xref>&#x2013;<xref ref-type="bibr" rid="B43">43</xref>). Of these drugs, only verteporfin has been approved by Food and Drug Administration (FDA). However, <italic>YAP1</italic> may act in a TEAD-independent manner (<xref ref-type="bibr" rid="B44">44</xref>). The efficacy and selectivity of other drugs are not satisfactory. New drugs are needed to inhibit <italic>YAP1</italic> activity. In this study, we calculated the correlation between <italic>YAP1</italic> expression and IC<sub>50</sub>s of drugs with FDA approval or in clinical trials, which is a simple way to roughly assess the drug sensitivity.</p>
<p>In this study, we analyzed <italic>YAP1</italic> expression in 33 cancer types to reveal its role in predicating prognosis, modulating TME, and drug response to chemotherapeutic and targeted drugs that were FDA-approved or are in clinical trials.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Methods and materials</title>
<sec id="s2_1">
<title>Data collection</title>
<p>Transcriptional RNA-sequence data [cohort: TCGA Pan-Cancer (PANCAN), batch effects normalized mRNA data], genome-wide DNA methylation levels (DNA Methylation 450K), and clinical characteristics (curated clinical data) of samples related to 33 cancer types were downloaded from UCSC Xena (<uri xlink:href="https://xenabrowser.net/datapages/">https://xenabrowser.net/datapages/</uri>), which is derived from TCGA resources (<xref ref-type="bibr" rid="B45">45</xref>).</p>
</sec>
<sec id="s2_2">
<title>Survival analysis</title>
<p>Survival information, including overall survival (OS), progression-free interval (PFI), disease-free interval (DFI), and disease-specific survival (DSS), was also downloaded from the UCSC Xena database. The Kaplan&#x2013;Meier model and univariate Cox regression were then used to assess the prognostic value of <italic>YAP1</italic>. Bivariate <italic>YAP1</italic> expression levels were used to perform Kaplan&#x2013;Meier curves analysis using the optimal cut point from the survminer R package (0.4.9) and survival R package (version 3.3.1). <italic>p</italic>-values of the Kaplan&#x2013;Meier method and hazard ratio (HR) with a 95% confidence interval (95% CI) were calculated for each cancer type and presented as forest plots using the forestplot R package (version 2.0.1).</p>
</sec>
<sec id="s2_3">
<title>Infiltration of immune cells</title>
<p>The proportions of 22 immune cell types and immune scores of all samples of 33 cancer types were downloaded from the supplementary data of the published paper (<xref ref-type="bibr" rid="B46">46</xref>). Infiltration of immune cells was performed with the CIBERSORT program, a method that uses gene expression profiles of complex tissues to calculate cell composition (<xref ref-type="bibr" rid="B47">47</xref>). The Xcell, TIMER, EPIC, quanTIseq, and MCP-counter programs were also used. TIMER provides the coefficients of six immune infiltrating cells indicating the relative abundance of immune cells (<xref ref-type="bibr" rid="B48">48</xref>). The EPIC program estimates the proportions of immune and cancer cells by separating the reference gene expression profiles of major non-malignant cell types (<xref ref-type="bibr" rid="B49">49</xref>). The ESTIMATE program was performed to infer tumor purity and immune cell admixture (immune score) from expression data (<xref ref-type="bibr" rid="B50">50</xref>). Pearson correlation coefficients between <italic>YAP1</italic> expression and infiltration of immune cells or immune score were calculated using the ggpubr R package (version 0.4.0), and scatter plots were visualized using ggplot2 (version 3.3.6).</p>
</sec>
<sec id="s2_4">
<title>Gene set enrichment analysis</title>
<p>For each cancer type, samples with <italic>YAP1</italic> expression above the median level were grouped as high <italic>YAP1</italic> expression, and the others were grouped as low <italic>YAP1</italic> expression to compare the difference in their hallmark gene sets. Fifty hallmark gene sets were downloaded from the Molecular Signatures Database (MSigDB, <uri xlink:href="https://www.gsea-msigdb.org/gsea/index.jsp">https://www.gsea-msigdb.org/gsea/index.jsp</uri>), and gene set enrichment analysis (GSEA) was performed using GSEA software (version 4.2.3). One thousand times was set as the number of permutations and phenotypes was set as permutation type. Normalized enrichment score (NES) and nominal <italic>p</italic> value for each biological process were calculated for each cancer type. Hallmark gene sets with nominal <italic>p</italic> value &lt; 0.05 were presented as a bubble plot using the ggplot2 R package.</p>
</sec>
<sec id="s2_5">
<title>Correlation of <italic>YAP1</italic> expression with tumor mutation burden and microsatellite instability</title>
<p>Tumor mutation burden (TMB) andmicrosatellite instability (MSI) levels for each sample in pan-cancer were downloaded from the supplementary data of the published paper (<xref ref-type="bibr" rid="B46">46</xref>). Pearson correlation coefficients between <italic>YAP1</italic> expression and TMB or MSI levels for each cancer type were calculated using ggpubr R package and displayed as radar charts using fmsb R package (version 0.7.3).</p>
</sec>
<sec id="s2_6">
<title>Azoxymethane/dextran sulfate sodium-induced colorectal cancer model and immunohistochemical staining of YAP1</title>
<p>CRC was induced in C57BL/6J mice by azoxymethane (AOM)/dextran sulfate sodium (DSS) as previously described (<xref ref-type="bibr" rid="B51">51</xref>). Colon sections of each mouse were collected for IHC staining and YAP1 was stained as previously described (<xref ref-type="bibr" rid="B51">51</xref>).</p>
</sec>
<sec id="s2_7">
<title>Assessment of drug sensitivity</title>
<p>IC<sub>50</sub>s (half-maximal inhibitory concentrations) of drugs and gene expression of cancer cell lines were downloaded from the CellMiner database (<uri xlink:href="https://discover.nci.nih.gov/cellminer/home.do">https://discover.nci.nih.gov/cellminer/home.do</uri>). Only drugs with FDA approval or in clinical trials were included in further analyses. Pearson correlation coefficients between <italic>YAP1</italic> expression and the IC<sub>50</sub> <italic>z</italic> score of each drug were calculated using the ggpubr R package and represented as bubble plots or scatter plots using the ggplot2 R package.</p>
</sec>
<sec id="s2_8">
<title>Cell viability assay</title>
<p>Cells were seeded at a density of 1&#xa0;&#xd7;&#xa0;10<sup>4</sup> cells/well in 96-well plates. When cells reached 60% confluence, drugs were added into the wells and incubated for 24&#xa0;h or 48&#xa0;h. Medium containing 10% Cell Counting Kit-8 (CCK-8) reagent (Dojindo, Japan) was then added into the cells and incubated for another 1.5&#xa0;h at 37&#xb0;C. The light absorbance was measured at 450 nm on the microplate reader (Bio-Rad, USA). Each group was performed in sextuplicate. Verteporfin, AZD-2858 were purchased from TargetMol, USA, and varlitinib was purchased from MCE, USA</p>
</sec>
<sec id="s2_9">
<title>Western blot assay</title>
<p>Cellular proteins were extracted with protein extraction reagent (Beyotime Biotechnology) and quantified by BCA protein assay (Beyotime Biotechnology). A total of 12 &#x3bc;g of protein per sample was added to SDS-PAGE gels for electrophoresis (100&#xa0;V, 2&#xa0;h), followed by constant flow membrane transfer (ice bath, 210 mA, 2&#xa0;h). The transferred polyvinylidene fluoride (PVDF) membranes were blocked with 5% BSA-containing Tris-buffered saline with Tween (TBST) for 2&#xa0;h at room temperature, and incubated with primary antibodies overnight at 4&#xb0;C. Then, membranes were washed three times with TBST and incubated with secondary antibody at room temperature for 2&#xa0;h. Membranes were examined with a gel imager (ECL, Millipore, USA). Antibodies of Vimentin, E-Cadherin, smad2, ERK, p-ERK, CREB, and GAPDH were purchased from Cell Signaling Technology (CST); YAP1, p-YAP1, and PD-L1 were purchased from Proteintech. All primary antibodies were used at 1:1,000 dilution. Secondary antibodies were purchased from Beyotime Biotechnology (1:2,000 dilution).</p>
</sec>
<sec id="s2_10">
<title>Reverse transcription-quantitative polymerase chain reaction</title>
<p>Primers were designed using the Primer-Blast tool at NCBI (<uri xlink:href="https://www.ncbi.nlm.nih.gov/tools/primer-blast/">https://www.ncbi.nlm.nih.gov/tools/primer-blast/</uri>) and synthesized by Sangon Biological Engineering Co., Ltd. (Shanghai, China). The sequences of the primers are listed in <xref ref-type="supplementary-material" rid="SM2">
<bold>Supplementary Table S1</bold>
</xref>. Total cellular RNA was extracted with RNA Trizol (Beyotime Biotechnology). Reverse transcription of RNA was performed using HiScript III RT SuperMix (Vazyme). The SYBR qPCR Mix (Vazyme) was used in a 10-&#xb5;l reaction mixture that included 1 &#xb5;l of cDNA template, 0.4 &#xb5;l of each 0.5 &#xb5;M primer, 3.6 &#xb5;l of ddH<sub>2</sub>O, and 5 &#xb5;l of 2&#xd7; SYBR buffer. The reaction was performed with 1 cycle of 30 s at 95&#xb0;C and 50 cycles of 10 s at 95&#xb0;C, 30 s at 60&#xb0;C, and 15 s at 60&#xb0;C. Actin was used as the reference mRNA. The qPCR reaction was performed in triplicate.</p>
</sec>
<sec id="s2_11">
<title>Statistical analysis</title>
<p>Differences in <italic>YAP1</italic> mRNA expression between normal and cancer tissues or between the two pathological stages of each cancer type were tested by Wilcox test. The differences in the proportions of the four pathological stages between groups with high or low <italic>YAP1</italic> expression were compared by chi-squared test. Differences in OS, PFI, DFI, and DSS between those two subgroups were compared using the Kaplan&#x2013;Meier method and log-rank rest. The HRs were calculated by univariate Cox regression. All <italic>p</italic> values were two-sided, and <italic>p</italic> &lt; 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>
<italic>YAP1</italic> is aberrantly expressed in various cancer tissues</title>
<p>We compared <italic>YAP1</italic> mRNA expression between normal and primary cancer tissues in 23 cancer types. For the other 10 cancer types, RNA-sequence data from paired normal tissues were not available. <italic>YAP1</italic> was differently expressed in 14 of the 23 cancer types with statistical significance. Among them, <italic>YAP1</italic> expression was upregulated in cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), and thyroid carcinoma (THCA), and was downregulated in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), and uterine corpus endometrial carcinoma (UCEC) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). IHC staining also identified that <italic>YAP1</italic> was upregulated in colon cancer tissues versus normal colonic mucosa tissues (<xref ref-type="bibr" rid="B52">52</xref>). <italic>YAP1</italic> has been reported to be upregulated in CHOL and THCA (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). <italic>YAP1</italic> does not contain DNA-binding sequences; thus, the binding partners are important for its function. <italic>YAP1</italic> binds to TEADs to facilitate the expression of tumor-promoting genes, and YAP1 may switch to bind to TP73 to promote apoptosis of cancer cells (<xref ref-type="bibr" rid="B19">19</xref>). Therefore, we also analyzed the expression of <italic>TEADs</italic> and <italic>TP73</italic> in pan-cancer. Consistent with <italic>YAP1</italic> expression, <italic>TEAD2</italic> was upregulated not only in CHOL, COAD, and THCA, but also in BRCA, HNSC, liver hepatocellular carcinoma (LIHC), LUAD, LUSC, and UCEC (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). Expression of <italic>TEAD1/2/4</italic> is shown in <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Figure S1</bold>
</xref>. TP73 was also upregulated in most cancer types, including CHOL, COAD, and THCA (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>). Xia et&#xa0;al. reported that high levels of <italic>YAP1</italic> expression were positively correlated with <italic>TEAD4</italic> gene expression, and their co-expression was a prognostic marker for poor ovarian cancer survival (<xref ref-type="bibr" rid="B53">53</xref>). High expressions of <italic>YAP1</italic> and <italic>TEADs</italic> and their target genes were associated with low OS in patients with non-metastatic human gastric carcinomas (<xref ref-type="bibr" rid="B54">54</xref>). Strano et&#xa0;al. reported that physical interaction with YAP1 protein enhanced transcriptional activity of TP73 (<xref ref-type="bibr" rid="B55">55</xref>). High expression of <italic>YAP1, TEAD4</italic>, and <italic>TP73</italic> was significantly associated with high grade, advanced stage, supraglottic location of tumors, nodal metastases, and recurrence of human laryngeal cancer. In addition, high expression of all proteins was significantly associated with poor overall and disease-free survival (<xref ref-type="bibr" rid="B56">56</xref>). The tumor-promoting or tumor-suppressing role of the YAP1&#x2013;TP73 complex, as well as the binding preference mechanism of YAP1 remains to be revealed.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Transcriptional level of YAP1, TEAD2, and TP53 in normal and cancer tissues according to RNA-sequence data from TCGA. ****p &lt; 0.0001, ***p &lt; 0.001, **p &lt; 0.01, *p &lt; 0.05, and ns p &gt; 0.05.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g001.tif"/>
</fig>
</sec>
<sec id="s3_2">
<title>
<italic>YAP1</italic> expression correlates with its DNA methylation and RNA modification</title>
<p>To seek the potential regulation of <italic>YAP1</italic> expression by DNA methylation and post-transcriptional RNA modifications, we performed correlation analyses. DNA methylation levels of eight CpG sites in the 5&#x2019;UTR of <italic>YAP1</italic> were included. In general, <italic>YAP1</italic> expression was negatively correlated with its DNA methylation level in most cancer types, suggesting that DNA demethylation in the 5&#x2019;UTR of <italic>YAP1</italic> may promote its expression (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). RNA modifications play pivotal roles in RNA stability and translation efficiency. We found that a wide range of RNA modification-related genes were positively correlated with <italic>YAP1</italic> expression. Genes responsible for reading, writing, and erasing the modifications on m1A, m5C, and m6A were broadly associated with <italic>YAP1</italic> expression in all cancer types, particularly in lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), rectum adenocarcinoma (READ), skin cutaneous melanoma (SKCM), uveal melanoma (UVM), and testicular germ cell tumors (TGCT) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>). Among the 37 regulators, RNA m6A methylation readers and writers, including <italic>ZC3H13, LRPPPRC, YTHDC2, YTHDF3</italic>, and <italic>KIAA1429</italic>, were positively correlated with <italic>YAP1</italic> expression in more than 20 of the 33 cancer types with statistical significance, suggesting the potential role of RNA m6A methylation in facilitating <italic>YAP1</italic> mRNA stability.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>YAP1 expression correlates with its DNA methylation and RNA modification. <bold>(A)</bold> Pearson correlation between YAP1 expression and its DNA methylation in 33 cancer types. <bold>(B)</bold> Pearson correlation between YAP1 expression and RNA modification regulators. *p &lt; 0.05.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g002.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>Clinical prognostic value of <italic>YAP1</italic> in pan-cancer</title>
<p>To assess the role of <italic>YAP1</italic> in predicating clinical outcomes of patients in 33 cancer types, we analyzed OS, DSS, DFI, and PFI using the Kaplan&#x2013;Meier method (log-rank test) and univariate Cox regression. High <italic>YAP1</italic> expression was a risk factor for the OS in seven cancer types, PFI in eight cancer types, DFI in six cancer types, and DSS in eight cancer types. In general, high <italic>YAP1</italic> expression was risky in adrenocortical carcinoma (ACC), BLCA, COAD, brain lower grade glioma (LGG), LUAD, and pancreatic adenocarcinoma (PAAD), but it is a protective factor in esophageal carcinoma (ESCA), KIRC, PRAD, and mesothelioma (MESO) (<xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3A, B</bold>
</xref>). Of note, high <italic>YAP1</italic> expression was a risk factor for all four prognostic survival indicators of ACC and BLCA (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). Therefore, the role of <italic>YAP1</italic> is largely context-dependent. In ACC, COAD, and TGCT, <italic>YAP1</italic> expression was higher in the late pathologic stage (AJCC pathologic stages III and IV) than that in the early stage (AJCC pathologic stages I and II) (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). In BLCA, PAAD, and TGCT, a higher frequency of patients with more severe stages was observed in patients with higher <italic>YAP1</italic> expression compared with those with lower <italic>YAP1</italic> expression (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3D</bold>
</xref>). Those results demonstrate that <italic>YAP1</italic> may promote cancer progression in ACC, COAD, PAAD, and TGCT. Among them, the tumor-promoting role of <italic>YAP1</italic> in COAD and PAAD has been determined experimentally (<xref ref-type="bibr" rid="B57">57</xref>, <xref ref-type="bibr" rid="B58">58</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Prognostic value of YAP1 expression in pan-cancer. <bold>(A)</bold> Survival outcomes of cancer patients with high or low YAP1 expression. Bold lines: p &lt; 0.05. <bold>(B)</bold> Survival curves of PFI in ACC, BLCA, COAD, and PAAD. <bold>(C)</bold>YAP1 expression between patients with the early or late pathologic stages of cancer. <bold>(D)</bold> Distribution of pathologic stages in BLCA, PAAD, and TGCT. ***p &lt; 0.001, **p &lt; 0.01, and *p &lt; 0.05.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g003.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>
<italic>YAP1</italic> induces immunosuppressive TME</title>
<p>TME contains tumor cells, immune cells, and stromal cells, which play pivotal roles in cancer initiation, progression, and drug response. We analyzed the correlation between <italic>YAP1</italic> expression and infiltration of 19 cell types in tumor tissues using CIBERSORT, Xcell, TIMER, EPIC, quanTIseq, and MCP-counter programs. We found that <italic>YAP1</italic> expression was associated with infiltration of cells in both innate and adaptive immune system in pan-cancer. In general, <italic>YAP1</italic> expression was negatively correlated with the infiltration of CD8+ T cells, T follicular helper cells, &#x3b3;&#x3b4; T cells, activated natural killer (NK) T cells, CD4+ Th1 cells, and myeloid dendritic cells in most cancer types, but positively correlated with the infiltration of MDSCs, cancer-associated fibroblasts (CAFs), and neutrophil cells (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>). These results were consistent using different tools, except for the filtration of CD8+ T cells calculated by TIMER and other programs. EPIC and TIMER programs showed an opposite correlation between <italic>YAP1</italic> expression and infiltration of CD4+ T cells in a few cancer types. The correlation of <italic>YAP1</italic> expression with infiltration of regulatory T cells (Tregs), plasma B cells, NK cells, and macrophage was contradictory when using different programs (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>). Thus, experiments are needed to confirm the results. Notably, CD8+ T cells are a key subset of MHC class I-restricted T cells and are one of the major mediators of adaptive immunity. High expression of <italic>YAP1</italic> may inhibit the infiltration of CD8+ T cells in 21 of the 33 cancer types (BLCA, BRCA, COAD, HNSC, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, OV, MESO, PCPG, PRAD, SARC, SKCM, TGCT, THCA, THYM, UCEC, and UCS), indicating its immunosuppressive role in TME (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). Immune score predicts the level of infiltrating immune cells. <italic>YAP1</italic> expression was negatively with the immune score in 12 cancer types (HNSC, KIRC, KIRP, LIHC, MESO, OV, SARC, SKCM, TGCT, THCA, THYM, and UCEC). However, it was positively correlated with the immune score in BRCA, DLBC, GBM, LGG, PAAD, PCPG and PRAD (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4C</bold>
</xref>). <italic>IL-6, CSF-1, CSF-2, CSF-3</italic>, and <italic>CXCL5</italic>, which are capable of recruiting MDSCs, were downregulated in CRC cells when YAP1 was inhibited by verteporfin (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8C</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Correlation of <italic>YAP1</italic> expression with immune cell infiltration. <bold>(A)</bold> Pearson correlation between <italic>YAP1</italic> expression and infiltration of 22 immune cell types using different programs. Positive correlation is in red and negative correlation is in blue. *<italic>p</italic> &lt; 0.05. <bold>(B)</bold> Pearson correlation between <italic>YAP1</italic> expression and infiltration of CD8+ T cells in pan-cancer. Only statistically significant cancer types were shown. <bold>(C)</bold> Pearson correlation between <italic>YAP1</italic> expression and immune score. Only statistically significant cancer types were shown. Tfh, T follicular helper cells. Treg, regulatory T cells; NKT, natural killer T cells; NK, natural killer cells; CAF, cancer-associated fibroblast; MDSC, myeloid-derived suppressor cell; Endo, endothelial cell; Eos, eosinophil; HSC, hematopoietic stem cell. &#x3b3;&#x3b4; T cells, gamma-delta T cells.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g004.tif"/>
</fig>
</sec>
<sec id="s3_5">
<title>Correlations between <italic>YAP1</italic> and immune checkpoints, TMB, and MSI</title>
<p>Immune checkpoints are regulators of the immune system. They consist of a group of programmed death receptors and their ligands expressed on immune cells. Tumor cells can evade immune destruction by upregulating immune checkpoints (<xref ref-type="bibr" rid="B59">59</xref>). Therefore, we performed the Pearson correlation analyses to reveal the relationship between <italic>YAP1</italic> expression and 46 immune checkpoint regulators. We found that <italic>YAP1</italic> expression was positively correlated with most immune checkpoint genes and immune cell marker genes in all 33 cancer types. <italic>CTLA-4, TIM-3 (HAVCR2)</italic>, and <italic>PD-1 (PDCD1)</italic> are key checkpoint regulators that suppress immune response. They all positively correlated with <italic>YAP1</italic> expression in LGG, PAAD, and PRAD, but negatively correlated with <italic>YAP1</italic> expression in MESO, SARC, TGCT, and UCEC (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). We confirmed that YAP1 inhibitor verteporfin greatly reduced PD-L1 expression in CRC cell lines (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8B</bold>
</xref>). In most cancer types, <italic>CD274 (PD-L1), NRP1</italic>, and <italic>TNFSF15</italic> were positively correlated with <italic>YAP1</italic> expression. In PAAD, PRAD and PCPG, <italic>YAP1</italic> expression was highly correlated with the expression of most immune checkpoint genes, suggesting that YAP1 may help cancer cells to evade immune destruction (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). TMB refers to the total number of mutations per million bases (<xref ref-type="bibr" rid="B60">60</xref>). It is considered a promising biomarker of immune response, as tumors with high mutations are associated with high tumor neo-antigen burden, making them immunogenic, and therefore being more responsive to immunotherapy (<xref ref-type="bibr" rid="B61">61</xref>&#x2013;<xref ref-type="bibr" rid="B64">64</xref>). MSI is a condition of genetic susceptibility to mutation due to impaired DNA mismatch repair (<xref ref-type="bibr" rid="B65">65</xref>). It is also used as a major predictive marker for the efficacy of immune checkpoint blockade therapies (<xref ref-type="bibr" rid="B66">66</xref>). We found that <italic>YAP1</italic> expression was positively correlated with TMB in TGCT and was negatively correlated in PCPG, KIRP, and COAD (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). In addition, <italic>YAP1</italic> expression was positively correlated with MSI in GBM, HNSC, and TGCT and was negatively correlated with MSI in DLBC, PRAD, THCA, and UCS (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>). Our results suggest that <italic>YAP1</italic> may predict the efficacy of immune checkpoint inhibitors in TGCT, GBM, and HNSC.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Correlation between expression of <italic>YAP1</italic> and immune checkpoints, TMB, and MSI. <bold>(A)</bold> Heat map of correlation between <italic>YAP1</italic> expression and 46 immune checkpoint regulators. *<italic>p</italic> &lt; 0.05. <bold>(B, C)</bold> Correlation between <italic>YAP1</italic> expression, TMB, and MSI. ***<italic>p</italic> &lt; 0.001, **<italic>p</italic> &lt; 0.01, and *<italic>p</italic> &lt; 0.05.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g005.tif"/>
</fig>
</sec>
<sec id="s3_6">
<title>
<italic>YAP1</italic>-associated cancer hallmarks</title>
<p>Hallmark gene sets summarize and represent specific well-defined biological states or processes and display coherent expression. We subdivided patients into two groups for each cancer type based on <italic>YAP1</italic> expression above or below the median level, and analyzed the differences in 50 hallmark gene sets across 33 cancer types. More than 23 hallmarks were aberrantly upregulated in LAML, LGG, and PCPG patients with high <italic>YAP1</italic> expression versus those with low <italic>YAP1</italic> expression. Various hallmark gene sets were upregulated in pan-cancer. TGF-&#x3b2; signaling pathway was upregulated in 23 cancer types, mitotic spindle process in 16 cancer types, Hedgehog signaling pathway in 15 cancer types, KRAS signaling in 8 cancer types, epithelial mesenchymal transition (EMT) in 10 cancer types, and angiogenesis in 7 cancer types, indicating that <italic>YAP1</italic> is involved in promoting cell proliferation, cancer cell stemness, invasiveness, and migration processes (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). We then confirmed these results on CRC cell lines (Lovo and SW620). As expected, YAP1 was upregulated in AOM/DSS-induced colitis-associated cancer in C57BL/6J mice (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8A</bold>
</xref>). The YAP1 inhibitor verteporfin significantly reduced their cell viability (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8B</bold>
</xref>). Verteporfin also reduced expression of p-ERK (KRAS signaling pathway) and smad2 (TGF-&#x3b2; signaling pathway), and downregulated Wnt target genes <italic>AXIN2</italic>, <italic>BIRC5, CCND1</italic>, and <italic>CD44</italic> (<xref ref-type="fig" rid="f8">
<bold>Figures&#xa0;8C, D</bold>
</xref>). In addition, upregulation of E-cadherin (epithelial maker) and downregulation of vimentin (mesenchymal marker) were observed in verteporfin treatment, suggesting a role of YAP1 in promoting EMT (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8D</bold>
</xref>). Of note, those results were based on enrolled cancerous samples. The hallmark difference between samples with higher and lower <italic>YAP1</italic> expression is less than that between the samples with or without <italic>YAP1</italic> function. Thus, the YAP1-associated hallmarks included but were not limited to those mentioned above</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>GSEA of hallmarks in cancer patients with high <italic>YAP1</italic> expression versus those with low YAP1 expression. Only statistically significant hallmarks (p &lt; 0.05) were shown.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g006.tif"/>
</fig>
</sec>
<sec id="s3_7">
<title>Potential drugs for <italic>YAP1</italic>
</title>
<p>We further screened potential drugs that may be effective in cancer patients with high <italic>YAP1</italic> expression. We downloaded the <italic>z</italic> scores of IC<sub>50</sub>s of 24,360 drugs in 60 cancer cell lines. Only 218 FDA-approved drugs and 574 drugs in clinical trials were included for correlation analysis. Of the 218 FDA-approved drugs, chemotherapeutic agents that inhibit DNA synthesis (teniposide, dacarbazine, doxorubicin, triethylenemelamine, nitrogen mustard, etoposide, and thiotepa) topped the list, which might be effective in treating cancer patients with high <italic>YAP1</italic> expression. Interestingly, an antipsychotic medication, fluphenazine, may also have an effect. Inhibitors of hypoxia-inducible factor (IDF-11774), MCL-1 (S63845, AZD-5991, pyridoclax, and S-64315), ribonucleotide reductase (imexon), FASN (JNJ-54302833), WNT signaling (CCT251545), STAT/STAT3 (CPD-401), and CHK (rabusertib) were among the top 10 drugs in clinical trial that may work in patients with high <italic>YAP1</italic> expression, whereas inhibitors of EGFR (TAS6417), Bruton&#x2019;s agammaglobulinemia tyrosine kinase (BTK) (spebrutinib), SYK (entospletinib), RET (Blu667), VEGFR2 (ENMD-2076, P-529), and &#x3b1;v&#x3b2;3 integrin (MK-0429, cilengitide) may not work (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). We then treated Lovo and SW620 cell lines with AZD2858 and varlitinib alone or in combination with verteporfin. These results showed that the inhibitory rate of combined treatment <italic>versus</italic> verteporfin is smaller than that of AZD2858 or varlitinib alone <italic>versus</italic> control, indicating that the role of AZD2858 and varlitinib in cytotoxicity was partially dependent on YAP1 activity (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8E</bold>
</xref>). In addition, the combination of varlitinib and verteporfin was more effective than either single agent. KRAS is an effector molecule responsible for signal transduction from ligand-bound EGFR to the nucleus. Varlitinib is a targeted drug against EGFR. Dual inhibition of EGFR and YAP1 obtained better therapeutic outcomes, suggesting that the KRAS pathway was involved in YAP1 activity, as we analyzed <italic>in silico</italic> (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>).</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Potential drugs for <italic>YAP1</italic>. <bold>(A)</bold> Correlation of <italic>YAP1</italic> expression with and IC<sub>50</sub> <italic>z</italic> score of FDA-approved drugs (top 25). <bold>(B)</bold> Correlation of <italic>YAP1</italic> expression and IC<sub>50</sub> of drugs in clinical trial.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g007.tif"/>
</fig>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Experiments to confirm the activities of <italic>YAP1</italic>. <bold>(A)</bold> IHC staining of YAP1 in normal colon tissue and AOM/DSS-induced colitis-associated CRC in C57BL/6J mice. <bold>(B)</bold> Effect of YAP1 inhibitor verteporfin (VP) on the viability of CRC cells (24&#xa0;h). <bold>(C)</bold> Regulation of YAP1 inhibitor on Wnt target genes and chemokines that recruit MDSCs&#x2019; infiltration in LoVo cell line. <bold>(D)</bold> YAP1 is involved in KRAS and TGF-&#x3b2; signaling pathways as well as EMT processes in Lovo cell line. <bold>(E)</bold> Effect of AZD2858 and varlitinib in combination with YAP1 inhibitor on the viability of CRC cells. &#x3b4;: versus control group, &#x3d5; versus verteporfin group. VP: 1 &#x3bc;M; AZD2858: 1 &#x3bc;M; varlitinib: 5 mM. ns (no significance), *p &lt; 0.05, **<italic>p</italic> &lt; 0.01, and ***<italic>p</italic> &lt; 0.001.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-13-1012173-g008.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>
<italic>YAP1</italic> is a transcriptional co-activator and a major effector of the Hippo signaling pathway. Emerging work indicates that <italic>YAP1</italic> is widely activated in human malignancies and is essential for cancer initiation, progression, and drug resistance in most solid tumors. High expression of <italic>YAP1</italic> has been reported to promote the excessive cell proliferation in multiple tissues, including liver, gastrointestinal tissue, skin, and heart (<xref ref-type="bibr" rid="B67">67</xref>&#x2013;<xref ref-type="bibr" rid="B70">70</xref>). TEAD-dependent <italic>YAP1</italic> function has also been linked to invasive and metastatic behavior of tumor cells (<xref ref-type="bibr" rid="B71">71</xref>). Compelling evidence also showed that <italic>YAP1</italic> can alter the TME by recruiting immunosuppressive cell types, suppressing cytotoxic T-cell function or promoting the polarization of tumor-associated macrophages towards the pro-tumor M2 phenotype (<xref ref-type="bibr" rid="B72">72</xref>&#x2013;<xref ref-type="bibr" rid="B74">74</xref>). In this study, we analyzed <italic>YAP1</italic> expression in pan-cancer and evaluated its role in prognostic value, immunomodulation, and drug response.</p>
<p>According to the TCGA database, <italic>YAP1</italic> expression was elevated in CHOL, COAD, and THCA, but decreased in 11 of the 23 cancer types, namely, BLCA, BRCA, HNSC, KICH, KIRC, KIRP, LUAD, LUSC, PCPG, PRAD, and UCEC (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). However, <italic>YAP1</italic> has been reported to be oncogenic in BLCA (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>), BRCA (<xref ref-type="bibr" rid="B77">77</xref>), HNSC (<xref ref-type="bibr" rid="B78">78</xref>), KICH (<xref ref-type="bibr" rid="B79">79</xref>), KIRC (<xref ref-type="bibr" rid="B80">80</xref>), KIRP (<xref ref-type="bibr" rid="B81">81</xref>), LUAD (<xref ref-type="bibr" rid="B82">82</xref>), LUSC (<xref ref-type="bibr" rid="B83">83</xref>), PRAD (<xref ref-type="bibr" rid="B84">84</xref>), and UCEC (<xref ref-type="bibr" rid="B85">85</xref>). PCPG is a rare adrenal tumor. The role of <italic>YAP1</italic> in PCPG remains to be investigated. The downregulation of <italic>YAP1</italic> in those caners might be due to case number limitation, and in addition to <italic>YAP1</italic> expression level, <italic>YAP1</italic> activity also depends on its cellular location. High <italic>YAP1</italic> expression is a risk factor for survival outcomes in ACC, BLCA, LGG, LUAD, PAAD, and COAD (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Moreover, in ACC, BLCA, COAD, and TGCT, <italic>YAP1</italic> was associated with more severe pathologic stages (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Among them, the prognostic value of <italic>YAP1</italic> on BLCA (<xref ref-type="bibr" rid="B84">84</xref>), LUAD (<xref ref-type="bibr" rid="B86">86</xref>), PAAD (<xref ref-type="bibr" rid="B87">87</xref>) and COAD (<xref ref-type="bibr" rid="B88">88</xref>) has been reported.</p>
<p>According to our result, high expression of <italic>YAP1</italic> predicted poor survival outcomes in patients with LUAD, COAD, and PAAD, and was associated with more severe pathologic stages in patients with COAD, PAAD, and TGCT (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). PAAD has been reported to be characterized by immunosuppressive TME. In this study, <italic>YAP1</italic> in PAAD was positively correlated with a wide range of immune checkpoint regulators. <italic>YAP1</italic> expression was positively correlated with levels of TMB and MSI in TGCT. In addition, important immune cells, including activated CD4+ memory T cells and T follicular helper cells, were positively correlated with <italic>YAP1</italic> expression in LUAD. Therefore, we would like to discuss in more detail the role of <italic>YAP1</italic> in these cancer types.</p>
<p>Elevated expression of the gene signature for <italic>YAP1/TAZ</italic> activity is associated with poor prognosis in patients with non-small-cell lung cancer (NSCLC) (<xref ref-type="bibr" rid="B89">89</xref>, <xref ref-type="bibr" rid="B90">90</xref>), which is consistent with the results of LUAD in our study (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Our GSEA results suggested that high <italic>YAP1</italic> expression was associated with reduced activities of DNA repair processes (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>), and defective DNA repair contributes to individual susceptibility to lung cancer development (<xref ref-type="bibr" rid="B91">91</xref>). We also showed that TGF-&#x3b2; signaling was upregulated in LUAD with high <italic>YAP1</italic> expression (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). TGF-&#x3b2; is the most potent inducer of EMT in NSCLC and is pivotal to the development of tumor-promoting microenvironment in the lung cancer tissues (<xref ref-type="bibr" rid="B92">92</xref>). In our findings, <italic>YAP1</italic> may inhibit infiltration of CD8+ T cells, CD4+ Th1 cells, T follicular helper cells, and NKT cells, but increase infiltration of CAFs, which promote the development of LUAD. Zhang et&#xa0;al. have reported that <italic>YAP1</italic> activation was not sufficient to trigger NSCLC formation, but promoted its progression to higher grades (<xref ref-type="bibr" rid="B89">89</xref>, <xref ref-type="bibr" rid="B93">93</xref>). The role of <italic>YAP1</italic> in immune cell infiltration in LUAD will be further experimentally confirmed in our future studies.</p>
<p>High level of <italic>YAP</italic> activity has been found to be prognostic for poor outcome in four datasets of CRC patients (<xref ref-type="bibr" rid="B94">94</xref>). In our study, <italic>YAP1</italic> expression was associated with severe pathologic stage and poor survival outcome in COAD (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). <italic>YAP1/TAZ</italic> is required for the formation and growth of intestinal tumors (<xref ref-type="bibr" rid="B95">95</xref>). Among the enriched hallmarks, higher <italic>YAP1</italic> expression was associated with upregulated Wnt &#x3b2;-catenin signaling, TGF-&#x3b2; signaling <italic>via</italic> NFKB, and Hedgehog signaling (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). Overactivation of the Wnt signaling pathway is the most oncogenic pathway in CRC. In addition, &#x3b2;-catenin-driven cancers require the <italic>YAP1</italic> transcriptional complex for tumorigenesis (<xref ref-type="bibr" rid="B96">96</xref>), suggesting the network between the two signaling pathways. Barry et&#xa0;al. reported that forced <italic>YAP1</italic> overexpression in the gut epithelium was not sufficient to form tumor (<xref ref-type="bibr" rid="B95">95</xref>). The lack of Wnt signaling pathway might be the reason. In COAD, <italic>YAP1</italic> expression was positively correlated with the infiltration of MDSCs and CAFs, and was negatively correlated with the infiltration of CD8+ T cells, CD4+ Th1 cells, activated NK cells, and NKT cells (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). Mechanically, <italic>YAP1</italic> promotes MDSC induction by inhibiting <italic>PTEN</italic> expression, resulting in upregulation of <italic>COX-2, p-AKT</italic>, and <italic>p-p65</italic> in CRC-derived cells, which leads to secretion of the cytokine granulocyte-macrophage colony-stimulating factor (<xref ref-type="bibr" rid="B97">97</xref>). <italic>YAP1</italic>-dependent matrix remodeling is required for the generation and maintenance of CAFs (<xref ref-type="bibr" rid="B98">98</xref>). Mechanisms of <italic>YAP1</italic> in recruiting CAFs and suppressing CD4+ Th1 cells, T follicular helper cells, activated NK cells, and NKT cells are yet to be unraveled.</p>
<p>PAAD is a very aggressive neoplasia that seems to arise from pancreatic exocrine cells. Pancreas-specific <italic>YAP1</italic> knockout halted tumor progression (<xref ref-type="bibr" rid="B99">99</xref>). Activation of <italic>YAP1</italic> in acinar cells upregulated JAK-STAT3 signaling and promoted the development of pancreatic cancer (<xref ref-type="bibr" rid="B100">100</xref>). In this study, <italic>YAP1</italic> expression was higher in PAAD patients with more severe pathological stages (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Mechanically, <italic>YAP1</italic> and the ZEB1 complex activates <italic>ITGA3</italic> to promote its metastasis (<xref ref-type="bibr" rid="B101">101</xref>). PAAD is characterized by immunosuppressive TME. In our results, <italic>YAP1</italic> expression was positively correlated with MDSC infiltration and negatively correlated with NKT cells. Mielgo et&#xa0;al. reported that <italic>YAP1</italic> recruited MDSCs to suppress T-cell function and generate an immunosuppressive microenvironment (<xref ref-type="bibr" rid="B102">102</xref>). The mechanism remains to be clarified.</p>
<p>Testicular cancer is a very common malignancy in young men. Although testicular cancer has a high cure rate, patients have a high long-term risk of secondary malignant tumors. Ji et&#xa0;al. have reported that different immune status in TME may be responsible for the different survival outcomes of TGCT patients (<xref ref-type="bibr" rid="B103">103</xref>). Moreover, YAP1 inhibition enhanced the chemosensitivity of cisplatin in TGCT (<xref ref-type="bibr" rid="B104">104</xref>). Studies about the YAP1 in immunomodulation in TGCT remain absent.</p>
<p>In this study, from a pan-cancer perspective, high expression of <italic>YAP1</italic> was associated with upregulation of TGF-&#x3b2; signaling, KRAS signaling, Hedgehog signaling, EMT, and androgen response in most cancer types (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>). There was a close interplay between YAP1 and TGF-&#x3b2; signaling. <italic>YAP1</italic> activation promoted TGF-&#x3b2; expression, which was involved in the biological processes of endothelial-to-mesenchymal transition (EMT) and fibrosis (<xref ref-type="bibr" rid="B105">105</xref>&#x2013;<xref ref-type="bibr" rid="B107">107</xref>) in the liver, lung, and kidney. Their interactions in other organ tissues need to be investigated. We confirmed that YAP1 was able to upregulate smad2 in TGF-&#x3b2; signaling in CRC cell lines (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). KRAS and YAP1 converged on the transcription factor FOS and activated a transcriptional program involved in regulating EMT (<xref ref-type="bibr" rid="B108">108</xref>). However, another study found limited overlap of gene expression between KRAS G12V and YAP1 S127A-driven tumors (<xref ref-type="bibr" rid="B109">109</xref>). The interplay between YAP1 and KRAS signaling remains largely unknown. In this study, YAP1 inhibitor reduced the KRAS pathway activity in CRC (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). Hedgehog signaling activation could upregulate <italic>YAP1</italic> expression and induce osteosarcoma development (<xref ref-type="bibr" rid="B110">110</xref>), or aid in generation of liver (<xref ref-type="bibr" rid="B111">111</xref>). The cooperation between Hedgehog and YAP1 signaling in tumor formation and progression remains to be uncovered<italic>. YAP1</italic> mRNA was upregulated in androgen-insensitive prostate cancer cells (<xref ref-type="bibr" rid="B112">112</xref>), but the mechanism of their interaction is largely unknown. Furthermore, in our findings, the YAP1 inhibitor did reduce EMT markers in CRC.</p>
<p>Emerging evidence demonstrated the role of <italic>YAP1</italic> in modulating TME. In this study, we found that <italic>YAP1</italic> may suppress the infiltration of CD8+ T lymphocytes, &#x3b3;&#x3b4; T cells, T follicular helper cells, NKT cells, and activated NK cells. Moreover, <italic>YAP1</italic> may recruit the CAFs and MDSCs to tumor site to suppress the immune response. Among them, the relationship between <italic>YAP1</italic> and infiltration of CD8+ T lymphocytes, MDSCs, and CAFs has been reported in several cancer types. However, the mechanisms are incomplete. The role of <italic>YAP1</italic> in the infiltration and activities of T follicular helper cells, NKT cells, and activated NK cells remains to be investigated. Stampouloglou et&#xa0;al. reported that <italic>YAP1</italic> overexpression in T cells reduced their activation, differentiation, and function, which translated <italic>in vivo</italic> into an impairment of T-cell infiltration and tumor repression (<xref ref-type="bibr" rid="B113">113</xref>). Another study confirmed that <italic>YAP1</italic> attenuated CD8+ T cell-mediated anti-tumor response (<xref ref-type="bibr" rid="B114">114</xref>). Mechanically, <italic>YAP1</italic> overexpression in cancer cells could upregulate <italic>PD-L1</italic> expression and impede the activities of CD8+ T cells in melanoma (<xref ref-type="bibr" rid="B115">115</xref>). Another mechanism is that YAP1/TEAD directly upregulates <italic>CXCL5</italic> in cancer cells to recruit CXCR2-expressing MDSCs, leading to decreased infiltration of CD8+ T cells (<xref ref-type="bibr" rid="B74">74</xref>). In addition, <italic>IL-6</italic> and <italic>CSF1-3</italic> induced by <italic>YAP1</italic> in PAAD stimulated the accumulation of MDSCs (<xref ref-type="bibr" rid="B116">116</xref>), and upregulation of <italic>COX2</italic> by <italic>YAP1</italic> in human granulosa cells promoted the recruitment of MDSCs (<xref ref-type="bibr" rid="B117">117</xref>). The role of <italic>YAP1</italic> in CD8+ T cells and MDSCs in other cancer types remains to be unraveled. In this study, we confirmed the results by experiments on CRC cells and found that the YAP1 inhibitor verteporfin decreased the expression of <italic>PD-L1, CXCL5, COX-2, IL-6</italic>, and <italic>CSF1-3</italic> (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). Mechanotransduction-mediated <italic>YAP1</italic> activation establishes a feed-forward self-reinforcing loop that contributes to maintenance of the CAF phenotype and promotes breast cancer invasion (<xref ref-type="bibr" rid="B98">98</xref>). Mechanistically, active <italic>YAP1</italic> promotes the expression of <italic>ANLN</italic> and <italic>DIAPH3</italic> and stabilizes actomyosin proteins, which is required for the generation and maintenance of CAFs (<xref ref-type="bibr" rid="B98">98</xref>). Another mechanism is that high expression of <italic>YAP1</italic> in the tumor stromal cells converts normal fibroblasts into CAFs in the TME of prostate cancer (<xref ref-type="bibr" rid="B118">118</xref>). The function of <italic>YAP1</italic> in CAFs of other cancer types remains largely unknown. In this study, high expression of <italic>YAP1</italic> was associated with TGF-&#x3b2; signaling in pan-cancer. TGF-&#x3b2;-associated extracellular matrix genes link CAFs to immune evasion and immunotherapy failure (<xref ref-type="bibr" rid="B57">57</xref>). Therefore, <italic>YAP1</italic> may be involved in the function of CAF through TGF-&#x3b2; signaling. We found that YAP1 inhibitor verteporfin reduced smad2 expression in CRC cell lines, suggesting a downregulation of TGF-&#x3b2; signaling (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref>). The role of <italic>YAP1</italic> in the infiltration and activity of T follicular helper cells, NKT cells, and activated NK cells remains to be investigated. Another interesting result in this study is that <italic>YAP1</italic> expression was negatively correlated with infiltration of CD8+ T cells, but positively correlated with infiltration of resting CD4+ memory T cells in most cancer types. This might not be due to the direct relationship between these two cells. <italic>YAP1</italic> expression was also negatively correlated with infiltration of activated CD4+ memory T cells, suggesting that <italic>YAP1</italic> may impede the activation of memory CD4+ T cells. CD4+ T cells are required for survival of CD8+ T cells during both primary and memory recall responses (<xref ref-type="bibr" rid="B119">119</xref>). Therefore, the possible relationship is that <italic>YAP1</italic> may impair the activation of memory CD4+ T cells, and impede the survival of CD8 T cells. Further experimental studies on CD4+ T cells will be conducted in the near future to verify the role of <italic>YAP1</italic> in memory CD4+ T-cell activation.</p>
<p>Further analyses showed that <italic>YAP1</italic> expression was positively correlated to a wide range of immune checkpoints, especially in PAAD, PCPG, and PRAD, suggesting that <italic>YAP1</italic> is a potential new drug target for anti-cancer immunotherapy in these cancer types. In PAAD, PRAD, and LGG, <italic>YAP1</italic> expression was positively correlated with the expression of <italic>CTLA-4, TIM-3 (HAVCR2)</italic>, and <italic>PD-1 (PDCD1)</italic>, which are key checkpoint regulators that suppress immune reaction. In most cancer types, <italic>CD274 (PD-L1), NRP1</italic>, and <italic>TNFSF15</italic> were positively correlated with <italic>YAP1</italic> expression. <italic>YAP1</italic> has been reported to induce <italic>PD-L1</italic> expression (<xref ref-type="bibr" rid="B115">115</xref>). Apart from <italic>PD-L1</italic>, <italic>YAP1</italic> might also regulate the expression of other immune checkpoints. The relationship between these immune checkpoints and <italic>YAP1</italic> and the role of their interactions in TME regulation remain to be investigated. These checkpoint regulators may play key roles in <italic>YAP1</italic>-induced immunosuppressive TME. In PAAD, PRAD, and PCPG, <italic>YAP1</italic> expression was highly correlated with the expression of most immune checkpoint genes in our result. Among them, PAAD has been reported to be characterized by the immunosuppressive microenvironment, suggesting a role for <italic>YAP1</italic> in PAAD development (<xref ref-type="bibr" rid="B102">102</xref>).</p>
<p>Methylation of DNA cytosine bases leads to the inaccessibility of DNA regulatory elements to their transcription factors through a number of mechanisms, leading to the gene transcription shutdown. We found that <italic>YAP1</italic> expression was negatively regulated by its DNA methylation in the 5&#x2019;UTR. Cellular RNAs are naturally decorated with a variety of chemical modifications, which affect the mRNA stability and translation. In our study, extensive modification &#x201c;effectors,&#x201d; including enzymes of &#x201c;writers&#x201d; and &#x201c;erasers&#x201d; that alter the modification level and binding proteins of &#x201c;readers&#x201d; that recognize the chemical marks, were positively correlated with <italic>YAP1</italic> mRNA level. Further research should be conducted to study whether aberrant DNA methylation and RNA modifications of <italic>YAP1</italic> are involved in cancer development and how they work.</p>
<p>FDA-approved chemotherapeutic drugs that are capable of inhibiting DNA synthesis, including teniposide, dacarbazine, doxorubicin, and triethylenemelamine, and inhibitors of hypoxia-inducible factor, MCL-1, ribonucleotide reductase, and FASN in clinical trials are potential drugs to treat cancer patients with high <italic>YAP1</italic> expression. Among them, the cytotoxicity effect of AZD2858 and varlitinib was partially attributed to YAP1 activity.</p>
</sec>
<sec id="s5">
<title>Conclusion</title>
<p>
<italic>YAP1</italic> was aberrantly expressed in various cancer types and regulated by its DNA methylation and post-transcriptional modifications. High expression of <italic>YAP1</italic> was associated with poor survival outcomes in ACC, BLCA, LGG, LUAD, and PAAD. <italic>YAP1</italic> may promote tumor progression through immunosuppression, particularly by suppressing the infiltration of CD8+ T lymphocytes, CD4+ Th1 cells, T follicular helper cells, NKT cells, and activated NK cells, as well as recruiting MDSCs and CAFs in pan-cancer. The <italic>YAP1</italic>-promoting tumor activity is probably attributed to the activation of TGF-&#x3b2;, Hedgehog, or KRAS signaling pathways. AZD2858 and varlitinib in clinical trials might be effective in cancer patients with high <italic>YAP1</italic> expression.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>XH contributed to designing the article structure, writing&#x2014;original draft, editing the figures and funding acquisition. YRZ contributed to performing experiments, editing the figures, and writing&#x2014;review. HY contributed to performing experiments. YYZ and XS contributed to formal analysis. QL contributed to funding acquisition. YW contributed to supervision, funding acquisition, and project administration. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by the National Natural Science Foundation of China (81904130, 82122075, and 82074232), the Project of Shanghai Science and Technology Committee (19YF1449900), the Shanghai Frontier Research Base of Disease and Syndrome Biology of Inflammatory Cancer Transformation (2021KJ03&#x2013;12), the &#x201c;Shu Gguang&#x201d; project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (21SG43), the Clinical Research Plan of SHDC (SHDC2020CR4043), and the Shanghai Youth Talent Support Program.</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2022.1012173/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2022.1012173/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Image_1.jpeg" id="SM1" mimetype="image/jpeg">
<label>Supplementary Figure&#xa0;1</label>
<caption>
<p>Transcriptional level of <italic>TEAD1</italic>, <italic>TEAD3</italic> and <italic>TEAD4</italic> in normal and cancer tissues according to RNA-sequence data from TCGA. ****<italic>p</italic> &lt; 0.0001, ***<italic>p</italic> &lt; 0.001, **<italic>p</italic> &lt; 0.01, *<italic>p</italic> &lt; 0.05, ns <italic>p</italic> &gt; 0.05.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Table_1.xlsx" id="SM2" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
</sec>
<glossary>
<title>Glossary</title>
<table-wrap position="anchor">
<table>
<tbody>
<tr>
<td valign="top" align="left">ACC</td>
<td valign="top" align="left">adrenocortical carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">BLCA</td>
<td valign="top" align="left">bladder urothelial carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">BRCA</td>
<td valign="top" align="left">breast invasive carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">CESC</td>
<td valign="top" align="left">cervical squamous cell carcinoma and endocervical adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">CHOL</td>
<td valign="top" align="left">cholangiocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">CI</td>
<td valign="top" align="left">confidence interval</td>
</tr>
<tr>
<td valign="top" align="left">CNTL</td>
<td valign="top" align="left">controls</td>
</tr>
<tr>
<td valign="top" align="left">COAD</td>
<td valign="top" align="left">colon adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">DFI</td>
<td valign="top" align="left">disease-free interval</td>
</tr>
<tr>
<td valign="top" align="left">DLBC</td>
<td valign="top" align="left">lymphoid neoplasm diffuse large B-cell lymphoma</td>
</tr>
<tr>
<td valign="top" align="left">DSS</td>
<td valign="top" align="left">disease-specific survival</td>
</tr>
<tr>
<td valign="top" align="left">ESCA</td>
<td valign="top" align="left">esophageal carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">GBM</td>
<td valign="top" align="left">glioblastoma multiforme</td>
</tr>
<tr>
<td valign="top" align="left">GSEA</td>
<td valign="top" align="left">gene set enrichment analysis</td>
</tr>
<tr>
<td valign="top" align="left">HNSC</td>
<td valign="top" align="left">head and neck squamous cell carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">HR</td>
<td valign="top" align="left">hazard ratio</td>
</tr>
<tr>
<td valign="top" align="left">IC50</td>
<td valign="top" align="left">half-maximal inhibitory concentration</td>
</tr>
<tr>
<td valign="top" align="left">KICH</td>
<td valign="top" align="left">kidney chromophobe</td>
</tr>
<tr>
<td valign="top" align="left">KIRC</td>
<td valign="top" align="left">kidney renal clear cell carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">KIRP</td>
<td valign="top" align="left">kidney renal papillary cell carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">LAML</td>
<td valign="top" align="left">acute myeloid leukemia</td>
</tr>
<tr>
<td valign="top" align="left">LCML</td>
<td valign="top" align="left">chronic myelogenous leukemia</td>
</tr>
<tr>
<td valign="top" align="left">LGG</td>
<td valign="top" align="left">brain lower-grade glioma</td>
</tr>
<tr>
<td valign="top" align="left">LIHC</td>
<td valign="top" align="left">liver hepatocellular carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">LUAD</td>
<td valign="top" align="left">lung adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">LUSC</td>
<td valign="top" align="left">lung squamous cell carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">MDSC</td>
<td valign="top" align="left">myeloid-derived suppressor cells</td>
</tr>
<tr>
<td valign="top" align="left">MESO</td>
<td valign="top" align="left">mesothelioma</td>
</tr>
<tr>
<td valign="top" align="left">MISC</td>
<td valign="top" align="left">miscellaneous</td>
</tr>
<tr>
<td valign="top" align="left">MSI</td>
<td valign="top" align="left">microsatellite instability</td>
</tr>
<tr>
<td valign="top" align="left">NES</td>
<td valign="top" align="left">normalized enrichment score</td>
</tr>
<tr>
<td valign="top" align="left">NK</td>
<td valign="top" align="left">natural killer</td>
</tr>
<tr>
<td valign="top" align="left">OS</td>
<td valign="top" align="left">overall survival</td>
</tr>
<tr>
<td valign="top" align="left">OV</td>
<td valign="top" align="left">ovarian serous cystadenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">PAAD</td>
<td valign="top" align="left">pancreatic adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">PCPG</td>
<td valign="top" align="left">pheochromocytoma and paraganglioma</td>
</tr>
<tr>
<td valign="top" align="left">PFI</td>
<td valign="top" align="left">progression-free interval</td>
</tr>
<tr>
<td valign="top" align="left">PRAD</td>
<td valign="top" align="left">prostate adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">PVDF</td>
<td valign="top" align="left">polyvinylidene fluoride</td>
</tr>
<tr>
<td valign="top" align="left">READ</td>
<td valign="top" align="left">rectum adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">SARC</td>
<td valign="top" align="left">sarcoma</td>
</tr>
<tr>
<td valign="top" align="left">SKCM</td>
<td valign="top" align="left">skin cutaneous melanoma</td>
</tr>
<tr>
<td valign="top" align="left">STAD</td>
<td valign="top" align="left">stomach adenocarcinoma</td>
</tr>
<tr>
<td valign="top" align="left">TBST</td>
<td valign="top" align="left">Tris-buffered saline with Tween</td>
</tr>
<tr>
<td valign="top" align="left">TGCA</td>
<td valign="top" align="left">The Cancer Genome Atlas</td>
</tr>
<tr>
<td valign="top" align="left">TGCT</td>
<td valign="top" align="left">testicular germ cell tumor</td>
</tr>
<tr>
<td valign="top" align="left">THCA</td>
<td valign="top" align="left">thyroid carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">THYM</td>
<td valign="top" align="left">thymoma</td>
</tr>
<tr>
<td valign="top" align="left">TMB</td>
<td valign="top" align="left">tumor gene mutation burden</td>
</tr>
<tr>
<td valign="top" align="left">UCEC</td>
<td valign="top" align="left">uterine corpus endometrial carcinoma</td>
</tr>
<tr>
<td valign="top" align="left">UCS</td>
<td valign="top" align="left">uterine carcinosarcoma</td>
</tr>
<tr>
<td valign="top" align="left">UVM</td>
<td valign="top" align="left">uveal melanoma</td>
</tr>
</tbody>
</table>
</table-wrap>
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