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Prognostic Role of TIGIT Expression in Patients with Solid Tumors: A Meta-Analysis

Kunmin Xiao, Kunlin Xiao, Kexin Li, Peng Xue, Shijie Zhu

2021Journal of Immunology Research41 citationsDOIOpen Access PDF

Abstract

Background. T cell immunoglobulin and ITIM domain (TIGIT) is a recently identified immunosuppressive receptor. The expression levels of TIGIT affect the prognosis of patients with solid tumors. To fully comprehend the role of TIGIT on the prognosis of patients with solid tumors, we conducted a meta-analysis. Methods. We performed an online search of PubMed, Embase, Web of Science (WOS), and MEDLINE databases for literature published till March 31, 2021. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the literature, and Stata 16.0 and Engauge Digitizer 4.1 software were used for data analysis. Results. Our literature search identified eight papers comprising 1426 patients with solid tumors. Increased expression of TIGIT was associated with poor prognosis. High expression of TIGIT was a risk factor for overall survival (OS) { <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mtext>hazard</a:mtext> <a:mtext> </a:mtext> <a:mtext>ratio</a:mtext> <a:mtext> </a:mtext> <a:mfenced open="(" close=")"> <a:mrow> <a:mtext>HR</a:mtext> </a:mrow> </a:mfenced> <a:mo>=</a:mo> <a:mn>1.66</a:mn> </a:math> , 95% confidence interval (CI) [1.26, 2.20], <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M2"> <e:mi>P</e:mi> <e:mo>&lt;</e:mo> <e:mn>0.001</e:mn> </e:math> } and progression-free survival (PFS) ( <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M3"> <g:mtext>HR</g:mtext> <g:mo>=</g:mo> <g:mn>1.44</g:mn> </g:math> , 95% CI [1.15, 1.81], <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M4"> <i:mi>P</i:mi> <i:mo>=</i:mo> <i:mn>0.01</i:mn> </i:math> ). We performed subgroup analysis to explore the source of heterogeneity, colorectal cancer ( <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M5"> <k:mtext>HR</k:mtext> <k:mo>=</k:mo> <k:mn>2.07</k:mn> </k:math> , 95% CI [0.23, 18.82], <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M6"> <m:mi>P</m:mi> <m:mo>=</m:mo> <m:mn>0.518</m:mn> </m:math> ), lung cancer ( <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M7"> <o:mtext>HR</o:mtext> <o:mo>=</o:mo> <o:mn>1.29</o:mn> </o:math> , 95% CI [0.96, 1.72], <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" id="M8"> <q:mi>P</q:mi> <q:mo>=</q:mo> <q:mn>0.094</q:mn> </q:math> ), esophageal cancer ( <s:math xmlns:s="http://www.w3.org/1998/Math/MathML" id="M9"> <s:mtext>HR</s:mtext> <s:mo>=</s:mo> <s:mn>1.70</s:mn> </s:math> , 95% CI [1.20, 2.40], <u:math xmlns:u="http://www.w3.org/1998/Math/MathML" id="M10"> <u:mi>P</u:mi> <u:mo>=</u:mo> <u:mn>0.003</u:mn> </u:math> ), and other cancers ( <w:math xmlns:w="http://www.w3.org/1998/Math/MathML" id="M11"> <w:mtext>HR</w:mtext> <w:mo>=</w:mo> <w:mn>1.83</w:mn> </w:math> , 95% CI [1.25, 2.68], <y:math xmlns:y="http://www.w3.org/1998/Math/MathML" id="M12"> <y:mi>P</y:mi> <y:mo>=</y:mo> <y:mn>0.002</y:mn> </y:math> ). In addition to cancer type, expression location, sample size, and different statistical analysis methods are also considered the possible causes of heterogeneity between studies. Funnel plots suggested no publication bias for OS ( <ab:math xmlns:ab="http://www.w3.org/1998/Math/MathML" id="M13"> <ab:mi>P</ab:mi> <ab:mo>=</ab:mo> <ab:mn>0.902</ab:mn> </ab:math> ), and Egger’s test supported this conclusion ( <cb:math xmlns:cb="http://www.w3.org/1998/Math/MathML" id="M14"> <cb:mi>P</cb:mi> <cb:mo>=</cb:mo> <cb:mn>0.537</cb:mn> </cb:math> ). Conclusion. TIGIT expression was associated with OS and PFS in patients with solid tumors. Patients with elevated TIGIT expression have a shorter OS and PFS, and TIGIT expression could be a novel biomarker for prognosis prediction and a valuable therapeutic target for solid tumors.

Topics & Concepts

TIGITMeta-analysisCancer researchOncologyInternal medicineExpression (computer science)MedicineComputer scienceImmunotherapyCancerProgramming languageCancer Immunotherapy and BiomarkersImmune Cell Function and InteractionT-cell and B-cell Immunology