# Association ofβ-Catenin, APC, SMAD3/4, Tp53, and Cyclin D1 Genes in Colorectal Cancer: A Systematic Review and Meta-Analysis

Authors: Hongfeng Yan; Fuquan Jiang; Jianwu Yang
Journal: Genetics Research
 (2022)

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## Abstract

Objectives. Accumulating evidence indicates that the expression and/or variants of several genes play an essential role in the progress of colorectal cancer (CRC). The current study is a meta-analysis undertaken to estimate the prognosis and survival associated with CTNNB1/β-catenin, APC, Wnt, SMAD3/4, TP53, and Cyclin D1 genes among CRC patients. Methods. The authors searched PubMed, EMBASE, and Science Direct for relevant reports published between 2000 and 2020 and analyzed them to determine any relationship between the (immunohistochemically/sequencing-detected) gene expression and variants of the selected genes and the survival of CRC patients. Results. The analysis included 34,074 patients from 64 studies. To evaluate association, hazard ratios (HRs) were estimated for overall survival (OS) or disease-free survival (DFS), with a 95% confidence interval (CIs). Pooled results showed that β-catenin overexpression, APC mutation, SMAD-3 or 4 loss of expression, TP53 mutations, and Cyclin D1 expression were associated with shorter OS. β-Catenin overexpression (HR: 0.137 (95% CI: 0.131–0.406)), loss of expression of SMAD3 or 4 (HR: 0.449 (95% CI: 0.146–0.753)), the mutations of TP53 (HR: 0.179 (95% CI: 0.126–0.485)), and Cyclin D1 expression (HR: 0.485 (95% CI: 0.772–0.198)) also presented risk for shorter DFS. Conclusions. The present meta-analysis indicates that overexpression or underexpression and variants of CTNNB1/β-catenin, APC, SMAD3/4, TP53, and Cyclin D1 genes potentially acted as unfavorable biomarkers for the prognosis of CRC. The Wnt gene was not associated with prognosis.


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## Body

## 1. Introduction

Globally, cancer is the second leading cause of death after heart disease, and it is a prominent health issue. More specifically, colorectal cancer (CRC) is the third leading cause of death among men and women [1]. Unlike many other types of cancer, the survival rate for CRC has not changed a great deal. Recent studies showed that the prognostication of CRC depends upon the clinicopathological factors and the stages of tumor characteristics and reported the association with survival times and clinical outcomes [2–4]. Several susceptibility studies on the association of a genetic variant and CRC have been reported [5]. The solid tumors of CRC have served as genetic and biological paradigms and instigated to conduct studies on early detection [6], prevention [7], risk stratification [8], and treatments [9]. However, a greater understanding and identification of genetic biomarkers involving molecular and genetic pathways with improved sensitivity and specificity could improve screening for and expedite the diagnosis of CRC, yielding better outcomes. Currently, the prediction of outcomes in CRC relies heavily on traditional cancer characterization methods, including clinicopathological characteristics, such as staging, tumor size, invasion, tumor sidedness, and metastasis. It contributes to CRC’s high mortality rate and tendency for poor prognosis with disappointing survival rates [10].The uses of molecular prognostic biomarkers to forecast the progression of the condition and likely survival have interested scholars for some time [11]. However, CRC is a very diverse disease, and it is associated with complex interactions between genetic biomarkers and environmental risk factors. In addition, transduction pathways, namely transforming growth factor β-suppressor of mothers against decapentaplegic (TGFβ-SMADs), wingless/integrated (Wnt), and tumor suppressor protein (p53), play an essential role in the initiation and development of CRC [4]. The tumor protein p53 gene (Tp53) located at chromosome 17p13 consists of 90% of missense mutations. Furthermore, studies have reported that genetic variations, particularly at codon 72 Pro/Arg gene polymorphism of the Tp53 gene, could affect the prognosis and treatment of CRC [12]. The Wnt signaling pathway is of particular interest because of its vital function in embryogenesis and tissue homeostasis. Many studies have identified the excessive activation of Wnt signaling as playing a major role in CRC [13]. A genome-scale analysis has recognized that 90% of patients with CRC carried genetic variations in the Wnt signaling pathway, particularly the loss-of-functional variations of adenomatous polyposis coli (APC) and variations that activate the mutations of β-catenin [14].The membranous expression ofβ-catenin applies a restrictive impact on the movements of tumor cells and their growth. The increases in cell motility, growth, and transformation promote tumorigenesis because of the loss of β-catenin expression on the cell surface [12]. Pre-existing intracellular β-catenin can cause abnormality in Wnt/β-catenin-TCF signaling, leading to the progression of CRC. The hyperactivation of Wnt/β-catenin signaling enhances the invasive and metastatic possibility of CRC cells, while the knockdown of β-catenin in CRC cells reduces cell proliferation and further invasion [15]. Studies have reported the detection of nuclear β-catenin expression using immunohistochemical methods, and they have reported an association with a high burden of tumor and poor CRC survival [15].Somatic mutations at theAPC gene are found in approximately 75% of CRC cases. Several studies have suggested worse outcomes for CRC patients with wild-type APC (APC-WT) in comparison to mutant-type APC (APC-MT) [16]. However, the prognostic implication of this genomic alteration is not well-defined, especially in metastatic CRCs. SMAD4/DPC4 is a tumor suppressor gene that regulates cell growth and a common intracellular mediator that could alter the TGFβ signaling to promote tumor progression. Studies have reported an association of SMAD4 genetic variation with tumor invasion, metastasis, and prognosis in various cancers [17].In light of inconsistent results in the literature, the authors perceived a need for a meta-analysis that would explore the prognostic value of selected genes in CRC. The objectives were to estimate the pooled risk (hazard ratio, HR) identified (between the years 2000 and 2020) for each of these genes for overall survival (OS) and disease-free survival (DFS) in CRC patients. Thus, this meta-analysis comprehensively explores the prognostic role of selected genes in theβ-catenin and related pathway implicated in the development and progression of CRC.


## 2. Methods

### 2.1. Publication Search and Inclusion Criteria

The authors searched the databases of PubMed, EMBASE and Science Direct for relevant published articles. Search terms included medical phrases related toSMAD 3, SMAD 4, β-catenin, Catenin beta 1(CTNNB1), APC, Wnt, Cyclin D1, Tp53, or p53 genes and their variants/polymorphisms, in combination with words related to CRC (tumor, neoplasms, carcinoma, CRC, colon cancer, or rectal cancer). In addition, terms related to prognosis (outcome or survival) were used to retrieve eligible studies from 2000 through to the end of 2020. Furthermore, the references in the selected published articles were searched to identify potentially relevant studies.Eligible studies were selected based on the following criteria: (a) pathologically confirmed (i.e., via tissue samples) patients with CRC, (b) immunohistochemical/sequencing detection methods for the selected genes and OS, DFS, cancer-specific survival (CSS), or recurrence-free survival (RFS), (c) English language, and (d) full-text articles. Editorial letters, reviews, case reports, studies with duplicated/repeated data, and studies lacking essential information and animal studies were excluded.


### 2.2. Data Extraction

In accordance with the meta-analysis of observational studies in epidemiology (MOOSE) guidelines [18] and in compliance with PRISMA guidelines, the data were evaluated and extracted by two independent researchers, who entered them all onto the data extraction form. For data extraction, the details recorded were as follows: the first author, publication year, country, total number of cases, type of cancer, stages, reported genes, gene detection method, cut-off values used, hazard ratios (HRs) with their 95% confidence intervals (CIs), and P values. For inconsistencies, a consensus was reached on each item among the authors. The Newcastle–Ottawa scale (NOS) was used to evaluate the quality of the eligible studies.


### 2.3. Statistical Analysis

The meta-analysis was executed based on HRs calculated by the log‐rank test for OS and RFS differences with different gene expression levels. Calculations were based on HRs from the original publications, including 95% CI, and subsequent back-calculation to log (HR) and standard error (SE) for overall estimates. Wherever available, HRs based on a multivariate analysis were used. Log (HR) and SE were entered in statistical software NCSS (NCSS, LLC, Kaysville, UT,https://www.ncss.com/), and meta-analyses were validated in the software Comprehensive Meta‐Analysis (CMA; Biostat, Inc., Englewood, NJ, https://www.meta-analysis.com/). The heterogeneity of pooled results was analyzed using Cochran’s Q test and the Higgins I-squared statistic. The absence of heterogeneity is based on the Q test revealed P heterogeneity>0.1 and I2 < 50%. To estimate the summary HRs/ORs, a fixed-effects model (the Mantel–Haenszel method) was used [19]. Elsewhere, the arandom-effects model (the DerSimonian and Laird method) [20] was used. To examine the publication bias, Begg’s funnel plot and Egger’s linear regression test were used, and P<0.05 was considered statistically significant (i.e., an asymmetrical distribution). All of the results were presented with HRs, upper and lower limits, and P values and were illustrated in forest plots for the individual studies with the weighted and pooled effects.


## 2.1. Publication Search and Inclusion Criteria

The authors searched the databases of PubMed, EMBASE and Science Direct for relevant published articles. Search terms included medical phrases related toSMAD 3, SMAD 4, β-catenin, Catenin beta 1(CTNNB1), APC, Wnt, Cyclin D1, Tp53, or p53 genes and their variants/polymorphisms, in combination with words related to CRC (tumor, neoplasms, carcinoma, CRC, colon cancer, or rectal cancer). In addition, terms related to prognosis (outcome or survival) were used to retrieve eligible studies from 2000 through to the end of 2020. Furthermore, the references in the selected published articles were searched to identify potentially relevant studies.Eligible studies were selected based on the following criteria: (a) pathologically confirmed (i.e., via tissue samples) patients with CRC, (b) immunohistochemical/sequencing detection methods for the selected genes and OS, DFS, cancer-specific survival (CSS), or recurrence-free survival (RFS), (c) English language, and (d) full-text articles. Editorial letters, reviews, case reports, studies with duplicated/repeated data, and studies lacking essential information and animal studies were excluded.


## 2.2. Data Extraction

In accordance with the meta-analysis of observational studies in epidemiology (MOOSE) guidelines [18] and in compliance with PRISMA guidelines, the data were evaluated and extracted by two independent researchers, who entered them all onto the data extraction form. For data extraction, the details recorded were as follows: the first author, publication year, country, total number of cases, type of cancer, stages, reported genes, gene detection method, cut-off values used, hazard ratios (HRs) with their 95% confidence intervals (CIs), and P values. For inconsistencies, a consensus was reached on each item among the authors. The Newcastle–Ottawa scale (NOS) was used to evaluate the quality of the eligible studies.


## 2.3. Statistical Analysis

The meta-analysis was executed based on HRs calculated by the log‐rank test for OS and RFS differences with different gene expression levels. Calculations were based on HRs from the original publications, including 95% CI, and subsequent back-calculation to log (HR) and standard error (SE) for overall estimates. Wherever available, HRs based on a multivariate analysis were used. Log (HR) and SE were entered in statistical software NCSS (NCSS, LLC, Kaysville, UT,https://www.ncss.com/), and meta-analyses were validated in the software Comprehensive Meta‐Analysis (CMA; Biostat, Inc., Englewood, NJ, https://www.meta-analysis.com/). The heterogeneity of pooled results was analyzed using Cochran’s Q test and the Higgins I-squared statistic. The absence of heterogeneity is based on the Q test revealed P heterogeneity>0.1 and I2 < 50%. To estimate the summary HRs/ORs, a fixed-effects model (the Mantel–Haenszel method) was used [19]. Elsewhere, the arandom-effects model (the DerSimonian and Laird method) [20] was used. To examine the publication bias, Begg’s funnel plot and Egger’s linear regression test were used, and P<0.05 was considered statistically significant (i.e., an asymmetrical distribution). All of the results were presented with HRs, upper and lower limits, and P values and were illustrated in forest plots for the individual studies with the weighted and pooled effects.


## 3. Results

### 3.1. Study Characteristics

Figure1 shows the comprehensive process used to select articles in this study, which was based on PRISMA guidelines. After the removal of duplicates, the database search yielded 4,112 articles. Based on the inclusion criteria and after screening the titles, abstracts, figures, and key data, 82 articles were finalized for literature studies [21–40], [41–60], [61–80], [81–102]. However, only 64 articles [21–31, 33–36, 38–40, 42–56, 59–61, 64, 66, 68–70, 72, 73, 75, 76, 78, 81–86, 88, 90, 91, 93, 95, 97–102] were retrieved for meta-analysis with 105 data points of the selected genes. Of these, four studies had evaluated the prognostic value for RFS [47, 81, 88, 101]. Six studies included cancer-specific survival [26, 46, 48, 65, 98, 103], whereas three reported progression-free survival (PFS) [32, 76, 84]. All others reported either OS and/or DFS. Since the number of studies for the first three indicators was small, the data for CSS, PFS, and RFS were combined with DFS. Thus, 64 studies involving 34,074 patients evaluating OS and DFS were analyzed in the current meta-analysis.Figure 1
PRISMA flow chart of the selected studies.


### 3.2. Review of Eligible Studies

The 82 studies identified as having presented data on baseline genes and prognosis in CRC are listed in Table1 [21–40], [41–60], [61–80], [81–102]. Most of these studies were from the USA (n = 18), followed by China (n = 11), Korea (n = 7), Sweden (n = 6), Japan and Greece (n = 5), Australia and Austria (n = 4), Norway (n = 3), Taiwan, Egypt, Germany, Hungary, Italy, Netherlands and Turkey (n = 2), and one each from Brazil, France, Hungary, Iran, Poland, Romania, Scotland, Spain, and Switzerland. Two studies were multicentric [45, 52]. The number of patients ranged from 39 [93] to 3,583 [45]. Patients were diagnosed with CRC (n = 59), rectal cancer (n = 7), and colon cancer (n = 12). The data presented in these studies were on the Wnt gene (n = 6), β-catenin or CTNNB1 (n = 28), Tp53 or p53 (n = 33), APC (n = 11), SMAD (19), and Cyclin-D1 (n = 8), with some studies including data on multiple genes (Figure 1). The extraction procedure in all studies was carried out using IHC on tissue samples. The tumors were most commonly graded according to TNM or Dukes’ classification, which is 14.9% [71] to 69.4% [59] of the right-sided tumors.Table 1
Characteristics of included studies.
No.AuthorYearRegionSample sizeMale %Sample typeTumor typeClinical stage of tumorTumor side (right %)GeneMethod of gene expressionElevated levels/abnormalityCut-off valueOutcomeNOS rating1Rafael et al. [21]2014Spain34553.3TissueCRCDuke A-DNAWntSSCPMutationsNAβ-Catenin mutation not associated with OS52Yoshida et al. [22]2015Japan20159.7TissueCRCStage 1,2,3NAWntIHCHigh, low>50%Nuclearβ-catenin associated with poor OS and DFS63Ting et al. [23]2013Taiwan28252.4TissueCRCAJCCNAWntGenomic DNA sequencing, tagger algorithmPolymorphismNAWnt polymorphism associated with high risk in OS64Veloudis et al. [24]2017Greece57NATissueColon and rectal adenocarcinomaTNM 1–433.3WntIHCNegative, weak, intermediate, strongMedianNuclearβ-catenin associated with poor OS55Kim et al. [25]2018Korea19465.5TissueCRCNA22.2Wnt 5AGenomic DNA extractionMethylated/nonmethylatedNAMethylation observed in 32%, not associated with OS76Wangefjord et al. [26]2011Austria52747.6TissueCRCTNM 1–4NACyclin D1IHCweak, moderate, strong>0–>75%High Cyclin D1 expression associated with poor survival in men77Bazan et al. [27]2005Italy16047.5TissueCRCDuke A-DNATP53PCR-SSCPMutationNAAssociated with poor OS68Khan et al. [28]2018USA182556.7TissueCRCNA37.2TP53Genomic sequencingMutation5–10%Associated with poor OS5CTNNB1SMAD-4APC9Brandstedt et al. [29]2014Sweden3040TissueCRCTNM 1–4NAp53IHC staining and gene sequencingPositive/negativep53: >50%;β-catenin: 0–2;Cyclin D1: 0->75%Associated with poor OS610Huemer et al. [30]2018Austria16139.7TissueCRCGrade 1–324TP53Genomic DNA sequencingMutationNATP53 mutation not associated with shorter OS compared with TP53 wild type tumor. TP53 mutation not associated with shorter OS in right-sided tumors511Sun et al. [31]2014China19764.4TissueCRCTNM 0–4NATP53IHCHigh/low150Associated with poor OS512Theodoropoulos et al. [32]2008Greece16567.8TissueColorectal adeno cancerTNM stage 1–4NATP53Nuclear immunostaining of positive cellsOverexpression>10%p53+: 63.5% tumors. Advanced T stage associated with p53 expression413Warren et al. [33]2013USA60755.5TissueColon cancerStage 3NATP53Direct sequencing and hybridizationMutationNATP53 mutations- 45%414Netter et al. [34]2014France6875TissueColon ca., metastaticNA67.6TP53FASAY and sanger sequencingNA10–15%Associated with poor OS515Kandioler et al. [35]2015Austria38951.1TissueColon cancerStage 3NATP53Sanger sequencingMutations<75%Associated with poor OS416Chen et al. [36]2013China20342.3TissueCRCAJCCNATP53IHCNegative, positive>10%Associated with poor OS517Russo et al. [37]2014USA22226.12TissueCRCStage 1–4NATP53,APCClinical tumor genotypingMutationsNATP53 mutations: 21%APC mutations: 8%518Oh et al. [38]2019Korea62159.9TissueCRCAJCC 2 and 3NATP53IHC and next generation sequencingWeak, moderate, strong0%Weak expression associated with poor OS619Wang et al. [39]2017China12450.8TissueCRCTNM 1–4NATP53IHCExpression>10%P53 positive: 58.8%720Zhang et al. [40]2014China18542.7TissueCRCAJCC 1–440TP53IHCNegative/positive<10% cells with +ve nuclei: Negative; >10% cells with +ve nuclei: PositiveAssociated with poor OS721Godai et al. [41]2009Japan21157.8TissueCRCDuke stage A-DNATP53Genomic DNA SequencingMutationsNATP53 mutations: 70%622Chun et al. [42]2019USA40155.6TissueCRCAJCC24.6TP53APCSMAD-4Next gen sequencingLow or high risk (EAp53 score)NATP53 mutations: 65.6%APC mutations: 47.4%SMAD-4 mutations: 11.4%823Tiong et al. [43]2014China and taiwanNANATissueCRCNANATP53,CTNNB1,Wnt 5AIHCOverexpressionNAAssociated with poor survival424Li et al. [44]2018China31557.1TissueCRCTNMNATP53Next gen mutational analysisMutationNADouble mutated P53 with PIK3CA associated with poor survival625Iacopetta et al. [45]2006Multinational358352.3TissueCRCDukes stage A-DNATP53PCRMutationNATP53 mutation associated with distal colon cancer626Morikawa et al. [46]2012USA106039TissueColon and rectal cancerStages 1–4NATP53IHCModerate and strongNAAssociated with poor OS827Kawaguchi et al. [47]2019USA49058.3TissueCRCAJCC Cat. TNATP53SMAD-4Nextgen sequencingExpression>10%Associated with poor OS728Samowitz et al. [48]2002USA146450.2TissueColon cancerAJCCNATP53NANANAAssociated with poor survival729Soong et al. [49]2000Australia995NATissueCRCDuke stage B&C34TP53NAMutationNA39% mutations530Jurach et al. [50]2006Brazil8356.6TissueRectalAstler Coller B&CNATP53IHCMutation>20%Associated with poor OS531Loes et al. [51]2016Norway15160.2TissueCRCNANATP53Sanger sequencingMutationsNATP53 mutations- 60.4%432Iacopetta et al. [52]2006Multinational358352.3TissueCRCDukes stage A-DNATP53PCRMutationNATP53 mutation associated with distal colon cancer633Salim et al. [53]2013Sweden85NATissueColon cancerNANAβ-CateninIHCLess expression<50%Associated with poor OS434Kamposioras et al. [54]2013Greece10661.3TissueCRCNA40% (CRC)β-CateninIHCOverexpressionModerateAssociated with poor OS735Gao et al. [55]2014China18158TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpression>50%Associated with poor OS636Jang et al. [56]2012Korea21861.4TissueColon cancerNA23.3β-Catenin,Cyclin D1IHCOverexpression>30%Associated with poor survival537Lee et al. [57]2013Korea30561.9TissueCRCAJCC stages 1–4NAβ-CateninIHCOverexpression>30%Associated with poor OS638Wong et al. [58]2003China6065TissueCRCNANAβ-CateninIHCOverexpression>300Associated with poor survival439Chung et al. [59]2001USA543NATissueCRCNANAβ-CateninIHCOverexpressionModerateAssociated with poor survival440Fernebro et al. [60]2004Sweden25767.3TissueRectal cancerNANAβ-Catenin, p53IHCAbnormal expressionWeakAssociated with poor survival541Bondi et al. [61]2004Norway16245.6Tissuecolon cancerNANAβ-CateninIHCoverexpression>1%Associated with poor survival442Kim et al. [62]2005Korea124NATissueCRCDuke A-DNAβ-CateninIHCAbnormal expression>5%Associated with poor survival643Filiz et al. [63]2010Turkey13860.1TissueCRCNANAβ-CateninIHCExpression levelsWeakAssociated with poor survival544Jung et al. [64]2013Korea34959.5TissueCRCNA21.7β-Catenin, p53IHCOverexpression>0%Associated with poor survival745Wangefjord et al. [65]2013Sweden52747.4TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpressionModerateAssociated with poor survival546Balzi et al. [66]2015Italy32153.2TissueCRCNANAβ-CateninIHCOverexpressionModerateAssociated with poor survival547Youssef et al. [67]2015Egypt7248.1TissueCRCTNM stages 1–4 and dukes A-C69.4β-CateninIHCOverexpression>10%Associated with poor survival648Togo et al. [68]2008USA18362.8TissueCRCTNM stages 1–433.3β-Catenin, p53IHCOverexpressionModerate/strong expressionAssociated with poor survival549Matsuoka et al. [69]2011Japan15663.4TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpression>20%Associated with poor survival750Morikawa et al. [70]2011USA95539.9TissueCRCNANAβ-CateninIHCOverexpressionModerate/strong expressionAssociated with poor survival851Ozguven et al. [71]2011Turkey6033.3TissueCRCNANAβ-CateninIHCoverexpression>0%Associated with poor survival552Stanczak et al. [72]2011Poland6666.66TissueCRCNANAβ-CateninIHCOverexpression>10%Associated with poor survival653Toth et al. [73]2012Hungary7950.6TissueCRCNANAβ-CateninIHCOverexpression>10%Associated with poor survival754Sun et al. [74]2011China6764.2TissueColon cancerNANAβ-CateninIHCDecreased expression>10%Downregulation associated with increased expression of E-Cadherin855Wang et al. [75]2020USA341 (COH)56.3TissueCOADNA30.7APC TP53 CTNNB1DNA sequencingMutationsNAAPC mutations- 74.8%8934 (MSKCC)52.9TissueNA26.1APC TP53 CTNNB1DNA sequencingMutationsNAAPC mutations- 74.8%56Mondaca et al. [76]2020USA471TissueCRCNA32%APC CTNNB1Tumor genomic profilingExpressionNAAPC associated with poor survival757Schell et al. [77]2016USA407NATissueCRCNA41APCTGSMutationNAAssociated with poor survival458Gerami et al. [78]2020Iran5777.2Frozen tissueCRCTNM stage 1 to 436.8APCDNA sequencingAG vs. AA genotypeNAAG genotype associated with poor survival559Conlin et al. [79]2005Scotland10760.7TissueCRCDuke stage A-D14.9APC p53Genomic DNA extraction and sequencingMutationsNAAPC mutations: 56%; p53 mutations: 61%; not associated460Wang et al. [80]2020USA331NAMicrosatellite stable, tissueCRC4NAAPCNext-gen genomic analysisAPC –WT or APC-MTNAAPC-WT associated with poor survival761Jorissen et al. [81]2015Australia74655.4CRC MSI (unstable) and MSS (stable); validation cohort, tissueCRCStage 1 to 442.2APC TP53DNA sequencingAPC-WT or APC-MTNATP53: 55.4%; APC-WT associated with poor survival662Voorneveld et al. [82]2012Netherlands209NATissueCRCNANASMAD-4IHCExpressionNAAssociated with poor survival563Li et al. [83]2011China147NATissueCRCNANASMAD-4IHCExpressionNAAssociated with poor survival564Yoo et al. [84]2019Korea1370NATissueCRCNANASMAD-4NASMAD-4 high vs. lowNAAssociated with poor survival565Su et al. [85]2016China25157.37TissueCRCStages 1–4NASMAD-4NASMAD-4 positiveNANo association566Isaksson et al. [86]2006Sweden8642TissueCRCDuke A-C35SMAD-4IHCNegative – 3+NAAssociated with poor OS667Fleming et al. [87]2013Australia74455.6Sporadic CRCs, tissueCRCAJCC stages 1–442.07SMAD-4IHCStroma high, stroma lowNAAssociated with poor survival468Roth et al. [88]2012Switzerland1404NATissueCRCStage 2 (18%) and 3 (23%)NASMAD-4IHC detectionLoss of expressionNAAssociated with poor survival669Lampropoulos et al. [89]2012Greece195NATissueCRCStage 1 to 4NASMAD-4NANANAAssociated with poor survival470Isaksson et al. [90]2011Sweden441NATissueCRCStage 1 to 4NASMAD-4IHCLoss, moderate, high0–5%Loss of SMAD—24%; associated with poor OS571Jia et al. [91]2017US20951.7TissueCRCStages 1–4NASMAD-4Genomic DNA sequencingHigh, lowNAHigh cytoplasm and low nuclear SMAD-4 not associated with OS772Oyanagi et al. [92]2019Japan201117TissueCRCTNM 1–456SMAD-4IHCWeak, strong>95%SMAD-4 alterations: 28%, associated with poor OS and RFS673Ionescu et al. [93]2014Romania3966.6TissueCRCDuke A-D25.6SMAD-3q-RT-PCROverexpression, under-expressionNANo association with OS674Fukushima et al. [94]2003Japan100NASporadic CRC and normal tissueSporadic CRCNANASMAD3/SMAD4PCR-SSCPAbnormalNASMAD-3: no abnormality; SMAD-4: abnormal 5 cases475Chun et al. [95]2014Korea20165.7TissueRectal cancer3NASMAD4PCRNuclear or cytoplasmic SMAD-4NANo association676Bacman et al. [96]2007Germany31061TissueColon cancerStage 2 (57.4%) and 3 (42.6%)NASMAD3/SMAD4PCRSMAD-3 and SMAD-4 in tumor high or lowNASMAD-3 and SMAD-4 in tumor, effects on TGFβ R2 pathway downregulation577Meskar et al. [97]2009Netherlands13554.4TissueCRCStage 1 (17.8%), 2 (77.8%) and 3 (4.4%)53.3SMAD4NAStroma high vs. stroma lowNAStroma high SMAD-4 associated with poor prognosis778Horst et al. [98]2009Germany14250TissueCRCUICC stage 2ANAβ-CateninIHC stainingNuclearβ-cateninNAAssociated with poor survival679Bondi et al. [99]2005Norway21947.9TissueColon cancerDuke A-DNACyclin D1Real time q-PCR and IHCLow, highGrade +2Cyclin not associated with survival.680Bahnassy et al. [100]2004Egypt6060.0TissueCRCTNM 1–4NACyclin D1DNA extraction and gene amplification, IHCamplification>75%Associated with poor survival781Saridaki et al. [101]2010Greece14456.94TissueCRCStages 1–4NACyclin D1DNA extraction and IHCWeak, strong≥50% with weak and ≥20% with strong stainingOverexpression is not associated with poor outcomes682Ogino et al. [102]2009USA60243TissueColon cancerAJCC stages 1–4NACyclin D1IHCNo, weak, moderate, strongStrong staining in any fractionOverexpression not associated with poor survival8NA: not applicable; CRC: colon rectal cancer; COAD: colon adenocarcinoma; IHC: immunohistochemical; OS: overall survival.


### 3.3. Quality of Eligible Studies

The Newcastle–Ottawa Scale (NOS) was used to examine the methodological quality of the included studies. As previously described, a score of 9 implied the highest quality, while a score of ≥5 was considered to be high quality. Seventy-two studies included in our meta-analysis were of high quality, i.e., they had scores of 5 or more after quality assessment.


### 3.4. Prognostic Value of Gene Expression and Mutations in Colorectal Cancer

Sixty-five studies, with 105 data points on genes where HR data was available, were included in the meta-analysis. These are shown in Table2. Twenty-eight enrolled studies provided the HRs, and 95% CI directly or indirectly reported the correlation between β-catenin overexpression and OS. The pooled HR of β-catenin overexpression in the nucleus, cytoplasm, or membranous with OS was 0.257 (95% CI: 0.003–0.511; Q = 53.978; P=0.000) (Figure 2(a)), however, heterogeneity existed. The association of β-catenin overexpression with shorter DFS was analyzed. The pooled HR was 0.137 (95% CI: 0.131–0.406; Q = 48.832; P=0.000) (Figure 2(b)). The above results suggested that β-catenin overexpression in the nucleus, membrane, or cytoplasm was associated with lower OS and DFS.Table 2
Hazard ratios of studies included in meta-analysis.
No.AuthorYearGeneOutcomeHR95% CILowerUpper1Wang et al. (COH/UCD) [75]2020APCOS0.620.440.86Wang et al. (MSKCC) [75]APCOS0.630.490.81Wang et al. (COH/UCD) [75]CTNNB1OS0.950.352.55Wang et al. (MSKCC) [75]CTNNB1OS1.670.863.26Wang et al. (COH/UCD) [75]TP53OS1.330.931.88Wang et al. (MSKCC) [75]TP53OS1.000.771.302Mondaca et al. [76]2020APCProgression-free survival0.680.540.86OS0.560.420.75CTNNB1Progression-free survival1.630.972.74OS1.180.642.193Gerami et al. [78]2020APCOS3.241.218.684Jorissen et al. (MSI) [81]2015APCOS0.900.272.96RFS1.260.256.50Jorissen et al. (MSS) [81]2015APCOS2.011.173.43RFS2.711.395.28Jorissen et al. (Validation cohort, MSS) [81]2015APCOS3.021.675.47RFS2.141.104.185Voorneveld et al. [82]2012SMAD-4OS2.471.024.156Li et al. [83]2011SMAD-4OS7.043.8812.827Yoo et al. [84]2019SMAD-4Progression-free survival1.271.011.60Cancer-free survival1.451.061.998Su et al. [85]2016SMAD-4DFS0.920.691.222OS0.870.641.1879Roth et al. [88]2012SMAD-4OS1.581.232.01RFS1.471.191.8110Isaksson et al. [90]2011SMAD-4OS1.811.093.0011Chun et al. [95]2014SMAD-4 (nuclear)OS1.710.833.511SMAD-4 (cytoplasmic)OS1.150.572.3012Meskar et al. [97]2009SMAD4OS7.984.1215.44DFS6.573.4312.5613Salim et al. [53]2013β catenin (membrane β-catenin absent + nuclear GSK3 β)OS1.981.013.8914Kamposioras et al. [54]2013β-Catenin (membrane)DFS0.330.140.7715Gao et al. [55]2014β-Catenin (membrane)OS1.130.622.05β-Catenin (nucleus)OS0.710.381.7016Jang et al. [56]2012β-CateninOS0.410.190.85DFS1.160.472.85Jang et al. [56]2012Cyclin D1OS0.2050.090.46DFS0.450.210.9617Chung et al. [59]2001β-Catenin, nuclearOS1.020.731.31β-Catenin, phosphonuclearOS2.181.303.6818Fernebro et al. [60]2004β-Catenin (cytoplasm)OS0.320.120.83β-Catenin (membrane)OS1.71.003.0Fernebro et al. [60]2004β-Catenin (nucleus)OS1.10.622.0p53OS1.10.502.519Bondi et al. [61]2004β-Catenin (nuclear, combined with C-Myc)OS5.261.9314.3620Jung et al. [64]2013β-CateninOS0.680.391.19p53OS1.390.822.2821Wangefjord et al. [65]2013β-CateninCancer-specific survival0.700.510.9722Balzi et al. [66]2015β-Catenin (nucleus)OS1.990.755.32DFS1.260.622.5623Togo et al. [68]2008β-CateninDFS1.940.864.38p53DFS1.700.833.4824Matsuoka et al. [69]2011β-CateninOS2.661.544.6025Morikawa et al. [70]2011β-Catenin (cytoplasm)Cancer-specific mortality0.820.641.06β-Catenin (nucleus)Cancer-specific mortality0.800.621.0326Stanzak et al. [72]2011β-CateninOS2.481.304.7427Toth et al. [73]2012β-Catenin (membrane)OS0.580.142.28β-Catenin (nucleus)OS2.250.618.3228Horst et al. [98]2009β-CateninDFS2.921.306.53Cancer-specific survival7.462.0826.7229Bazan et al. [27]2005TP53OS2.261.214.21DFS2.141.064.3230Khan et al. [28]2018TP53OS0.880.781.00CTNNB1OS0.790.441.44SMAD-4OS1.311.091.57APCOS0.890.791.0131Brandstedt et al. [29]2014p53CRC Risk0.190.040.96β-CateninCRC risk0.970.661.41Cyclin D1CRC risk0.070.010.8832Huemer et al. [30]2018TP53OS1.220.841.7833Sun et al. [31]2014TP53OS2.051.263.3434Warren et al. [33]2013TP53OS0.710.650.76DFS0.600.540.6635Netter et al. [34]2014TP53OS0.990.531.55Progression-free survival1.040.601.7936Loes et al. [51]2016TP53Disease-specific survival0.780.471.2837Kandioler et al. [35]2015TP53OS1.881.173.04CFS1.731.042.8638Chen et al. [36]2013TP53OS1.580.972.56DFS1.711.032.8639Oh et al. [38]2019TP535-year survival2.711.604.6040Wang et al. [39]2017TP53OS0.470.270.83DFS0.420.240.7341Zhang et al. [40]2014TP53OS1.660.883.14DFS1.650.813.3842Chun et al. [42]2019TP53OS2.621.414.8743Tiong et al. [43]2014TP53 (and CTNNB1)OS1.501.052.14Wnt 5AOS1.931.173.1944Li et al. [44]2018TP53 (double mutation with PIK3CA)OS2.021.043.91TP53OS1.680.982.8745Morikawa et al. [46]2012TP53Cancer-specific survival1.301.021.6546Kawaguchi et al. [47]2019TP53OS2.211.493.28RFS1.401.111.78SMAD-4OS1.821.172.83RFS1.621.202.2047Samowitz et al. [48]2002TP53OS1.341.071.63Cancer-specific survival1.100.911.3448Soong et al. [49]2000TP53OS1.400.892.2149Jurach et al. [50]2006TP53OS2.321.344.03Recurrence2.641.195.8350Iacopetta et al. [45]2006TP53OS2.521.284.9351Iacopetta et al. [52]2006TP53OS0.610.500.7352Wangefjord et al. [26]2011Cyclin D1Cancer-specific survival0.690.490.9653Isaksson et al. [86]2006SMAD-4OS4.571.1717.854Tonescu et al. [93]2014SMAD-3OS1.090.303.9955Jia et al. [91]2017SMAD-4 (nuclear)OS1.700.963.00SMAD-4 (cytoplasm)OS1.390.762.5656Kim et al. [25]2018WntOS1.250.871.7857Veloudis et al. [24]2017Wnt/β-cateninOS3.861.2411.958Ting et al. [23]2013WntOS4.571.7312.159Yoshida et al. [22]2015WntDFS1.500.802.8β-CateninDFS2.101.103.9OS1.901.003.460Rafael et al. [21]2014WntOS0.360.052.6361Bondi et al. [99]2005Cyclin D1OS0.570.330.9862Bahnassy et al. [100]2004Cyclin D1OS10.861.0586.263Saridaki et al. [101]2010Cyclin D1OS1.10.61.8RFS0.80.51.464Ogino et al. [102]2009Cyclin D1OS0.740.570.98CSS0.570.390.84The table represents 105 data points on genes where HR data were available. OS: overall survival, RFS: relapse-free survival, CFS: cancer-free survival, DFS: disease-free survival, PFS: progression-free survival, CRC risk: colorectal cancer risk.Figure 2
Forest plot ofβ-catenin gene and overall survival in CRC (a). Forest plot of β-catenin gene and disease-free survival in CRC (b).
(a)(b)For theAPC gene, the pooled HR for OS based on 8 studies was 0.035 (95% CI: 0.308–0.377; Q = 51.76; P=0.000) (Figure 3(a)). This value suggested the association of the mutant variant with a lower OS compared with the wild type but not for DFS, where pooled HR = 0.387 (95% CI: 0.483–1.256; Q = 22.624; P=0.000) (Figure 3(b)). For the SMAD3/4 genes, 13 studies were included. The pooled HR was 0.688 (95% CI: 0.403–0.974; Q = 47.689; P=0.000) (Figure 4(a)). Their pooled HR for DFS was 0.449 (95% CI: 0.146–0.753; Q = 32.012; P=0.000) (Figure 4(b)). These results implied a worse prognosis of CRC in the event of the loss of expression of SMAD-3 or SMAD-4.Figure 3
Forest plot ofAPC gene and overall survival in CRC (a). Forest plot of APC gene and disease-free survival in CRC (b).
(a)(b)Figure 4
Forest plot ofSMAD3/4 gene and overall survival in CRC (a). Forest plot of SMAD3/4 gene and disease-free survival in CRC (b).
(a)(b)Studies reporting the mutations of theTp53 gene (n = 24) had a pooled HR of 0.319 (95% CI: 0.133–0.504; Q = 201.339; P=0.000) (Figure 5(a)) for OS and 0.179 (95% CI: 0.126–0.485; Q = 143.796; P=0.000) (Figure 5(b)) for DFS (n = 14). The results were widely heterogenous but implied significantly poor prognosis overall, as well as DFS, in CRC cases. Five studies showed a pooled HR of 0.671 (95% CI: 0.116–1.458; Q = 10.746; P=0.030) (Figure 6) for the Wnt gene with OS, thereby showing no association of Wnt gene expression/mutation with survival in CRC. Since only one study [14] reported the hazard ratio for DFS, meta-analysis was not performed for the Wnt gene with shorter DFS. Five studies on Cyclin D1 were included in the meta-analysis. The pooled HR for OS was 0.362 (95% CI: 0.944–0.221; Q = 5.421; P=0.253) (Figure 7(a)) and that for DFS was 0.485 (95% CI: 0.772–0.198; Q = 5.810; P=0.214) (Figure 7(b)). High Cyclin D1, therefore, produced a worse prognosis in CRC, both in terms of OS and DFS.Figure 5
Forest plot ofTP53 gene and overall survival in CRC (a). Forest plot of TP53 gene and disease-free survival in CRC (b).
(a)(b)Figure 6
Forest plot ofWNT gene and overall survival in CRC.Figure 7
Forest plot ofCyclin D1 gene and overall survival in CRC (a). Forest plot of cyclin D1 gene and disease-free survival in CRC (b).
(a)(b)


### 3.5. Publication Bias

We assessed the publication bias forAPC, SMAD, β-catenin, and Tp53 gene studies by constructing funnel plots (Figure 8(a)–8(f)) as more than ten studies were included in the meta-analysis. Egger’s test indicated that publication bias existed for the evaluation of the impact of β-catenin, APC, and Tp53 with OS, however, Begg’s test showed no significant publication bias (β-catenin and OS: I2 = 65.83%, tau (τ) = 0.047 (P=0.76), β-catenin and DFS: I2 = 71.33%, τ = 0.21 (P=0.25), TP53 and OS: I2 = 88.82%, τ = 0.153 (P=0.28), TP53 and DFS: I2 = 89.12%, τ = 0.25 (P=0.13), APC and OS: I2 = 86.48%; τ = 0.28 (P=0.32), SMAD and OS: I2 = 83.17%, and τ = 0.23 (P=0.27)). It is notable that with Egger’s test, there is insufficient power of testing when the number of selected studies is below 20. It was, therefore, not attempted for the remaining genes.Figure 8
The funnel plot of studies included forAPC gene and OS in CRC (a). The funnel plot of studies included for SMAD gene and OS in CRC (b). The funnel plot of studies included for β-catenin gene and OS in CRC (c). The funnel plot of studies included for β-catenin gene and DFS in CRC (d). The funnel plot of studies included for TP53 gene and OS in CRC (e). The funnel plot of studies included for TP53 gene and DFS in CRC (f).
(a)(b)(c)(d)(e)(f)


## 3.1. Study Characteristics

Figure1 shows the comprehensive process used to select articles in this study, which was based on PRISMA guidelines. After the removal of duplicates, the database search yielded 4,112 articles. Based on the inclusion criteria and after screening the titles, abstracts, figures, and key data, 82 articles were finalized for literature studies [21–40], [41–60], [61–80], [81–102]. However, only 64 articles [21–31, 33–36, 38–40, 42–56, 59–61, 64, 66, 68–70, 72, 73, 75, 76, 78, 81–86, 88, 90, 91, 93, 95, 97–102] were retrieved for meta-analysis with 105 data points of the selected genes. Of these, four studies had evaluated the prognostic value for RFS [47, 81, 88, 101]. Six studies included cancer-specific survival [26, 46, 48, 65, 98, 103], whereas three reported progression-free survival (PFS) [32, 76, 84]. All others reported either OS and/or DFS. Since the number of studies for the first three indicators was small, the data for CSS, PFS, and RFS were combined with DFS. Thus, 64 studies involving 34,074 patients evaluating OS and DFS were analyzed in the current meta-analysis.Figure 1
PRISMA flow chart of the selected studies.


## 3.2. Review of Eligible Studies

The 82 studies identified as having presented data on baseline genes and prognosis in CRC are listed in Table1 [21–40], [41–60], [61–80], [81–102]. Most of these studies were from the USA (n = 18), followed by China (n = 11), Korea (n = 7), Sweden (n = 6), Japan and Greece (n = 5), Australia and Austria (n = 4), Norway (n = 3), Taiwan, Egypt, Germany, Hungary, Italy, Netherlands and Turkey (n = 2), and one each from Brazil, France, Hungary, Iran, Poland, Romania, Scotland, Spain, and Switzerland. Two studies were multicentric [45, 52]. The number of patients ranged from 39 [93] to 3,583 [45]. Patients were diagnosed with CRC (n = 59), rectal cancer (n = 7), and colon cancer (n = 12). The data presented in these studies were on the Wnt gene (n = 6), β-catenin or CTNNB1 (n = 28), Tp53 or p53 (n = 33), APC (n = 11), SMAD (19), and Cyclin-D1 (n = 8), with some studies including data on multiple genes (Figure 1). The extraction procedure in all studies was carried out using IHC on tissue samples. The tumors were most commonly graded according to TNM or Dukes’ classification, which is 14.9% [71] to 69.4% [59] of the right-sided tumors.Table 1
Characteristics of included studies.
No.AuthorYearRegionSample sizeMale %Sample typeTumor typeClinical stage of tumorTumor side (right %)GeneMethod of gene expressionElevated levels/abnormalityCut-off valueOutcomeNOS rating1Rafael et al. [21]2014Spain34553.3TissueCRCDuke A-DNAWntSSCPMutationsNAβ-Catenin mutation not associated with OS52Yoshida et al. [22]2015Japan20159.7TissueCRCStage 1,2,3NAWntIHCHigh, low>50%Nuclearβ-catenin associated with poor OS and DFS63Ting et al. [23]2013Taiwan28252.4TissueCRCAJCCNAWntGenomic DNA sequencing, tagger algorithmPolymorphismNAWnt polymorphism associated with high risk in OS64Veloudis et al. [24]2017Greece57NATissueColon and rectal adenocarcinomaTNM 1–433.3WntIHCNegative, weak, intermediate, strongMedianNuclearβ-catenin associated with poor OS55Kim et al. [25]2018Korea19465.5TissueCRCNA22.2Wnt 5AGenomic DNA extractionMethylated/nonmethylatedNAMethylation observed in 32%, not associated with OS76Wangefjord et al. [26]2011Austria52747.6TissueCRCTNM 1–4NACyclin D1IHCweak, moderate, strong>0–>75%High Cyclin D1 expression associated with poor survival in men77Bazan et al. [27]2005Italy16047.5TissueCRCDuke A-DNATP53PCR-SSCPMutationNAAssociated with poor OS68Khan et al. [28]2018USA182556.7TissueCRCNA37.2TP53Genomic sequencingMutation5–10%Associated with poor OS5CTNNB1SMAD-4APC9Brandstedt et al. [29]2014Sweden3040TissueCRCTNM 1–4NAp53IHC staining and gene sequencingPositive/negativep53: >50%;β-catenin: 0–2;Cyclin D1: 0->75%Associated with poor OS610Huemer et al. [30]2018Austria16139.7TissueCRCGrade 1–324TP53Genomic DNA sequencingMutationNATP53 mutation not associated with shorter OS compared with TP53 wild type tumor. TP53 mutation not associated with shorter OS in right-sided tumors511Sun et al. [31]2014China19764.4TissueCRCTNM 0–4NATP53IHCHigh/low150Associated with poor OS512Theodoropoulos et al. [32]2008Greece16567.8TissueColorectal adeno cancerTNM stage 1–4NATP53Nuclear immunostaining of positive cellsOverexpression>10%p53+: 63.5% tumors. Advanced T stage associated with p53 expression413Warren et al. [33]2013USA60755.5TissueColon cancerStage 3NATP53Direct sequencing and hybridizationMutationNATP53 mutations- 45%414Netter et al. [34]2014France6875TissueColon ca., metastaticNA67.6TP53FASAY and sanger sequencingNA10–15%Associated with poor OS515Kandioler et al. [35]2015Austria38951.1TissueColon cancerStage 3NATP53Sanger sequencingMutations<75%Associated with poor OS416Chen et al. [36]2013China20342.3TissueCRCAJCCNATP53IHCNegative, positive>10%Associated with poor OS517Russo et al. [37]2014USA22226.12TissueCRCStage 1–4NATP53,APCClinical tumor genotypingMutationsNATP53 mutations: 21%APC mutations: 8%518Oh et al. [38]2019Korea62159.9TissueCRCAJCC 2 and 3NATP53IHC and next generation sequencingWeak, moderate, strong0%Weak expression associated with poor OS619Wang et al. [39]2017China12450.8TissueCRCTNM 1–4NATP53IHCExpression>10%P53 positive: 58.8%720Zhang et al. [40]2014China18542.7TissueCRCAJCC 1–440TP53IHCNegative/positive<10% cells with +ve nuclei: Negative; >10% cells with +ve nuclei: PositiveAssociated with poor OS721Godai et al. [41]2009Japan21157.8TissueCRCDuke stage A-DNATP53Genomic DNA SequencingMutationsNATP53 mutations: 70%622Chun et al. [42]2019USA40155.6TissueCRCAJCC24.6TP53APCSMAD-4Next gen sequencingLow or high risk (EAp53 score)NATP53 mutations: 65.6%APC mutations: 47.4%SMAD-4 mutations: 11.4%823Tiong et al. [43]2014China and taiwanNANATissueCRCNANATP53,CTNNB1,Wnt 5AIHCOverexpressionNAAssociated with poor survival424Li et al. [44]2018China31557.1TissueCRCTNMNATP53Next gen mutational analysisMutationNADouble mutated P53 with PIK3CA associated with poor survival625Iacopetta et al. [45]2006Multinational358352.3TissueCRCDukes stage A-DNATP53PCRMutationNATP53 mutation associated with distal colon cancer626Morikawa et al. [46]2012USA106039TissueColon and rectal cancerStages 1–4NATP53IHCModerate and strongNAAssociated with poor OS827Kawaguchi et al. [47]2019USA49058.3TissueCRCAJCC Cat. TNATP53SMAD-4Nextgen sequencingExpression>10%Associated with poor OS728Samowitz et al. [48]2002USA146450.2TissueColon cancerAJCCNATP53NANANAAssociated with poor survival729Soong et al. [49]2000Australia995NATissueCRCDuke stage B&C34TP53NAMutationNA39% mutations530Jurach et al. [50]2006Brazil8356.6TissueRectalAstler Coller B&CNATP53IHCMutation>20%Associated with poor OS531Loes et al. [51]2016Norway15160.2TissueCRCNANATP53Sanger sequencingMutationsNATP53 mutations- 60.4%432Iacopetta et al. [52]2006Multinational358352.3TissueCRCDukes stage A-DNATP53PCRMutationNATP53 mutation associated with distal colon cancer633Salim et al. [53]2013Sweden85NATissueColon cancerNANAβ-CateninIHCLess expression<50%Associated with poor OS434Kamposioras et al. [54]2013Greece10661.3TissueCRCNA40% (CRC)β-CateninIHCOverexpressionModerateAssociated with poor OS735Gao et al. [55]2014China18158TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpression>50%Associated with poor OS636Jang et al. [56]2012Korea21861.4TissueColon cancerNA23.3β-Catenin,Cyclin D1IHCOverexpression>30%Associated with poor survival537Lee et al. [57]2013Korea30561.9TissueCRCAJCC stages 1–4NAβ-CateninIHCOverexpression>30%Associated with poor OS638Wong et al. [58]2003China6065TissueCRCNANAβ-CateninIHCOverexpression>300Associated with poor survival439Chung et al. [59]2001USA543NATissueCRCNANAβ-CateninIHCOverexpressionModerateAssociated with poor survival440Fernebro et al. [60]2004Sweden25767.3TissueRectal cancerNANAβ-Catenin, p53IHCAbnormal expressionWeakAssociated with poor survival541Bondi et al. [61]2004Norway16245.6Tissuecolon cancerNANAβ-CateninIHCoverexpression>1%Associated with poor survival442Kim et al. [62]2005Korea124NATissueCRCDuke A-DNAβ-CateninIHCAbnormal expression>5%Associated with poor survival643Filiz et al. [63]2010Turkey13860.1TissueCRCNANAβ-CateninIHCExpression levelsWeakAssociated with poor survival544Jung et al. [64]2013Korea34959.5TissueCRCNA21.7β-Catenin, p53IHCOverexpression>0%Associated with poor survival745Wangefjord et al. [65]2013Sweden52747.4TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpressionModerateAssociated with poor survival546Balzi et al. [66]2015Italy32153.2TissueCRCNANAβ-CateninIHCOverexpressionModerateAssociated with poor survival547Youssef et al. [67]2015Egypt7248.1TissueCRCTNM stages 1–4 and dukes A-C69.4β-CateninIHCOverexpression>10%Associated with poor survival648Togo et al. [68]2008USA18362.8TissueCRCTNM stages 1–433.3β-Catenin, p53IHCOverexpressionModerate/strong expressionAssociated with poor survival549Matsuoka et al. [69]2011Japan15663.4TissueCRCTNM stages 1–4NAβ-CateninIHCOverexpression>20%Associated with poor survival750Morikawa et al. [70]2011USA95539.9TissueCRCNANAβ-CateninIHCOverexpressionModerate/strong expressionAssociated with poor survival851Ozguven et al. [71]2011Turkey6033.3TissueCRCNANAβ-CateninIHCoverexpression>0%Associated with poor survival552Stanczak et al. [72]2011Poland6666.66TissueCRCNANAβ-CateninIHCOverexpression>10%Associated with poor survival653Toth et al. [73]2012Hungary7950.6TissueCRCNANAβ-CateninIHCOverexpression>10%Associated with poor survival754Sun et al. [74]2011China6764.2TissueColon cancerNANAβ-CateninIHCDecreased expression>10%Downregulation associated with increased expression of E-Cadherin855Wang et al. [75]2020USA341 (COH)56.3TissueCOADNA30.7APC TP53 CTNNB1DNA sequencingMutationsNAAPC mutations- 74.8%8934 (MSKCC)52.9TissueNA26.1APC TP53 CTNNB1DNA sequencingMutationsNAAPC mutations- 74.8%56Mondaca et al. [76]2020USA471TissueCRCNA32%APC CTNNB1Tumor genomic profilingExpressionNAAPC associated with poor survival757Schell et al. [77]2016USA407NATissueCRCNA41APCTGSMutationNAAssociated with poor survival458Gerami et al. [78]2020Iran5777.2Frozen tissueCRCTNM stage 1 to 436.8APCDNA sequencingAG vs. AA genotypeNAAG genotype associated with poor survival559Conlin et al. [79]2005Scotland10760.7TissueCRCDuke stage A-D14.9APC p53Genomic DNA extraction and sequencingMutationsNAAPC mutations: 56%; p53 mutations: 61%; not associated460Wang et al. [80]2020USA331NAMicrosatellite stable, tissueCRC4NAAPCNext-gen genomic analysisAPC –WT or APC-MTNAAPC-WT associated with poor survival761Jorissen et al. [81]2015Australia74655.4CRC MSI (unstable) and MSS (stable); validation cohort, tissueCRCStage 1 to 442.2APC TP53DNA sequencingAPC-WT or APC-MTNATP53: 55.4%; APC-WT associated with poor survival662Voorneveld et al. [82]2012Netherlands209NATissueCRCNANASMAD-4IHCExpressionNAAssociated with poor survival563Li et al. [83]2011China147NATissueCRCNANASMAD-4IHCExpressionNAAssociated with poor survival564Yoo et al. [84]2019Korea1370NATissueCRCNANASMAD-4NASMAD-4 high vs. lowNAAssociated with poor survival565Su et al. [85]2016China25157.37TissueCRCStages 1–4NASMAD-4NASMAD-4 positiveNANo association566Isaksson et al. [86]2006Sweden8642TissueCRCDuke A-C35SMAD-4IHCNegative – 3+NAAssociated with poor OS667Fleming et al. [87]2013Australia74455.6Sporadic CRCs, tissueCRCAJCC stages 1–442.07SMAD-4IHCStroma high, stroma lowNAAssociated with poor survival468Roth et al. [88]2012Switzerland1404NATissueCRCStage 2 (18%) and 3 (23%)NASMAD-4IHC detectionLoss of expressionNAAssociated with poor survival669Lampropoulos et al. [89]2012Greece195NATissueCRCStage 1 to 4NASMAD-4NANANAAssociated with poor survival470Isaksson et al. [90]2011Sweden441NATissueCRCStage 1 to 4NASMAD-4IHCLoss, moderate, high0–5%Loss of SMAD—24%; associated with poor OS571Jia et al. [91]2017US20951.7TissueCRCStages 1–4NASMAD-4Genomic DNA sequencingHigh, lowNAHigh cytoplasm and low nuclear SMAD-4 not associated with OS772Oyanagi et al. [92]2019Japan201117TissueCRCTNM 1–456SMAD-4IHCWeak, strong>95%SMAD-4 alterations: 28%, associated with poor OS and RFS673Ionescu et al. [93]2014Romania3966.6TissueCRCDuke A-D25.6SMAD-3q-RT-PCROverexpression, under-expressionNANo association with OS674Fukushima et al. [94]2003Japan100NASporadic CRC and normal tissueSporadic CRCNANASMAD3/SMAD4PCR-SSCPAbnormalNASMAD-3: no abnormality; SMAD-4: abnormal 5 cases475Chun et al. [95]2014Korea20165.7TissueRectal cancer3NASMAD4PCRNuclear or cytoplasmic SMAD-4NANo association676Bacman et al. [96]2007Germany31061TissueColon cancerStage 2 (57.4%) and 3 (42.6%)NASMAD3/SMAD4PCRSMAD-3 and SMAD-4 in tumor high or lowNASMAD-3 and SMAD-4 in tumor, effects on TGFβ R2 pathway downregulation577Meskar et al. [97]2009Netherlands13554.4TissueCRCStage 1 (17.8%), 2 (77.8%) and 3 (4.4%)53.3SMAD4NAStroma high vs. stroma lowNAStroma high SMAD-4 associated with poor prognosis778Horst et al. [98]2009Germany14250TissueCRCUICC stage 2ANAβ-CateninIHC stainingNuclearβ-cateninNAAssociated with poor survival679Bondi et al. [99]2005Norway21947.9TissueColon cancerDuke A-DNACyclin D1Real time q-PCR and IHCLow, highGrade +2Cyclin not associated with survival.680Bahnassy et al. [100]2004Egypt6060.0TissueCRCTNM 1–4NACyclin D1DNA extraction and gene amplification, IHCamplification>75%Associated with poor survival781Saridaki et al. [101]2010Greece14456.94TissueCRCStages 1–4NACyclin D1DNA extraction and IHCWeak, strong≥50% with weak and ≥20% with strong stainingOverexpression is not associated with poor outcomes682Ogino et al. [102]2009USA60243TissueColon cancerAJCC stages 1–4NACyclin D1IHCNo, weak, moderate, strongStrong staining in any fractionOverexpression not associated with poor survival8NA: not applicable; CRC: colon rectal cancer; COAD: colon adenocarcinoma; IHC: immunohistochemical; OS: overall survival.


## 3.3. Quality of Eligible Studies

The Newcastle–Ottawa Scale (NOS) was used to examine the methodological quality of the included studies. As previously described, a score of 9 implied the highest quality, while a score of ≥5 was considered to be high quality. Seventy-two studies included in our meta-analysis were of high quality, i.e., they had scores of 5 or more after quality assessment.


## 3.4. Prognostic Value of Gene Expression and Mutations in Colorectal Cancer

Sixty-five studies, with 105 data points on genes where HR data was available, were included in the meta-analysis. These are shown in Table2. Twenty-eight enrolled studies provided the HRs, and 95% CI directly or indirectly reported the correlation between β-catenin overexpression and OS. The pooled HR of β-catenin overexpression in the nucleus, cytoplasm, or membranous with OS was 0.257 (95% CI: 0.003–0.511; Q = 53.978; P=0.000) (Figure 2(a)), however, heterogeneity existed. The association of β-catenin overexpression with shorter DFS was analyzed. The pooled HR was 0.137 (95% CI: 0.131–0.406; Q = 48.832; P=0.000) (Figure 2(b)). The above results suggested that β-catenin overexpression in the nucleus, membrane, or cytoplasm was associated with lower OS and DFS.Table 2
Hazard ratios of studies included in meta-analysis.
No.AuthorYearGeneOutcomeHR95% CILowerUpper1Wang et al. (COH/UCD) [75]2020APCOS0.620.440.86Wang et al. (MSKCC) [75]APCOS0.630.490.81Wang et al. (COH/UCD) [75]CTNNB1OS0.950.352.55Wang et al. (MSKCC) [75]CTNNB1OS1.670.863.26Wang et al. (COH/UCD) [75]TP53OS1.330.931.88Wang et al. (MSKCC) [75]TP53OS1.000.771.302Mondaca et al. [76]2020APCProgression-free survival0.680.540.86OS0.560.420.75CTNNB1Progression-free survival1.630.972.74OS1.180.642.193Gerami et al. [78]2020APCOS3.241.218.684Jorissen et al. (MSI) [81]2015APCOS0.900.272.96RFS1.260.256.50Jorissen et al. (MSS) [81]2015APCOS2.011.173.43RFS2.711.395.28Jorissen et al. (Validation cohort, MSS) [81]2015APCOS3.021.675.47RFS2.141.104.185Voorneveld et al. [82]2012SMAD-4OS2.471.024.156Li et al. [83]2011SMAD-4OS7.043.8812.827Yoo et al. [84]2019SMAD-4Progression-free survival1.271.011.60Cancer-free survival1.451.061.998Su et al. [85]2016SMAD-4DFS0.920.691.222OS0.870.641.1879Roth et al. [88]2012SMAD-4OS1.581.232.01RFS1.471.191.8110Isaksson et al. [90]2011SMAD-4OS1.811.093.0011Chun et al. [95]2014SMAD-4 (nuclear)OS1.710.833.511SMAD-4 (cytoplasmic)OS1.150.572.3012Meskar et al. [97]2009SMAD4OS7.984.1215.44DFS6.573.4312.5613Salim et al. [53]2013β catenin (membrane β-catenin absent + nuclear GSK3 β)OS1.981.013.8914Kamposioras et al. [54]2013β-Catenin (membrane)DFS0.330.140.7715Gao et al. [55]2014β-Catenin (membrane)OS1.130.622.05β-Catenin (nucleus)OS0.710.381.7016Jang et al. [56]2012β-CateninOS0.410.190.85DFS1.160.472.85Jang et al. [56]2012Cyclin D1OS0.2050.090.46DFS0.450.210.9617Chung et al. [59]2001β-Catenin, nuclearOS1.020.731.31β-Catenin, phosphonuclearOS2.181.303.6818Fernebro et al. [60]2004β-Catenin (cytoplasm)OS0.320.120.83β-Catenin (membrane)OS1.71.003.0Fernebro et al. [60]2004β-Catenin (nucleus)OS1.10.622.0p53OS1.10.502.519Bondi et al. [61]2004β-Catenin (nuclear, combined with C-Myc)OS5.261.9314.3620Jung et al. [64]2013β-CateninOS0.680.391.19p53OS1.390.822.2821Wangefjord et al. [65]2013β-CateninCancer-specific survival0.700.510.9722Balzi et al. [66]2015β-Catenin (nucleus)OS1.990.755.32DFS1.260.622.5623Togo et al. [68]2008β-CateninDFS1.940.864.38p53DFS1.700.833.4824Matsuoka et al. [69]2011β-CateninOS2.661.544.6025Morikawa et al. [70]2011β-Catenin (cytoplasm)Cancer-specific mortality0.820.641.06β-Catenin (nucleus)Cancer-specific mortality0.800.621.0326Stanzak et al. [72]2011β-CateninOS2.481.304.7427Toth et al. [73]2012β-Catenin (membrane)OS0.580.142.28β-Catenin (nucleus)OS2.250.618.3228Horst et al. [98]2009β-CateninDFS2.921.306.53Cancer-specific survival7.462.0826.7229Bazan et al. [27]2005TP53OS2.261.214.21DFS2.141.064.3230Khan et al. [28]2018TP53OS0.880.781.00CTNNB1OS0.790.441.44SMAD-4OS1.311.091.57APCOS0.890.791.0131Brandstedt et al. [29]2014p53CRC Risk0.190.040.96β-CateninCRC risk0.970.661.41Cyclin D1CRC risk0.070.010.8832Huemer et al. [30]2018TP53OS1.220.841.7833Sun et al. [31]2014TP53OS2.051.263.3434Warren et al. [33]2013TP53OS0.710.650.76DFS0.600.540.6635Netter et al. [34]2014TP53OS0.990.531.55Progression-free survival1.040.601.7936Loes et al. [51]2016TP53Disease-specific survival0.780.471.2837Kandioler et al. [35]2015TP53OS1.881.173.04CFS1.731.042.8638Chen et al. [36]2013TP53OS1.580.972.56DFS1.711.032.8639Oh et al. [38]2019TP535-year survival2.711.604.6040Wang et al. [39]2017TP53OS0.470.270.83DFS0.420.240.7341Zhang et al. [40]2014TP53OS1.660.883.14DFS1.650.813.3842Chun et al. [42]2019TP53OS2.621.414.8743Tiong et al. [43]2014TP53 (and CTNNB1)OS1.501.052.14Wnt 5AOS1.931.173.1944Li et al. [44]2018TP53 (double mutation with PIK3CA)OS2.021.043.91TP53OS1.680.982.8745Morikawa et al. [46]2012TP53Cancer-specific survival1.301.021.6546Kawaguchi et al. [47]2019TP53OS2.211.493.28RFS1.401.111.78SMAD-4OS1.821.172.83RFS1.621.202.2047Samowitz et al. [48]2002TP53OS1.341.071.63Cancer-specific survival1.100.911.3448Soong et al. [49]2000TP53OS1.400.892.2149Jurach et al. [50]2006TP53OS2.321.344.03Recurrence2.641.195.8350Iacopetta et al. [45]2006TP53OS2.521.284.9351Iacopetta et al. [52]2006TP53OS0.610.500.7352Wangefjord et al. [26]2011Cyclin D1Cancer-specific survival0.690.490.9653Isaksson et al. [86]2006SMAD-4OS4.571.1717.854Tonescu et al. [93]2014SMAD-3OS1.090.303.9955Jia et al. [91]2017SMAD-4 (nuclear)OS1.700.963.00SMAD-4 (cytoplasm)OS1.390.762.5656Kim et al. [25]2018WntOS1.250.871.7857Veloudis et al. [24]2017Wnt/β-cateninOS3.861.2411.958Ting et al. [23]2013WntOS4.571.7312.159Yoshida et al. [22]2015WntDFS1.500.802.8β-CateninDFS2.101.103.9OS1.901.003.460Rafael et al. [21]2014WntOS0.360.052.6361Bondi et al. [99]2005Cyclin D1OS0.570.330.9862Bahnassy et al. [100]2004Cyclin D1OS10.861.0586.263Saridaki et al. [101]2010Cyclin D1OS1.10.61.8RFS0.80.51.464Ogino et al. [102]2009Cyclin D1OS0.740.570.98CSS0.570.390.84The table represents 105 data points on genes where HR data were available. OS: overall survival, RFS: relapse-free survival, CFS: cancer-free survival, DFS: disease-free survival, PFS: progression-free survival, CRC risk: colorectal cancer risk.Figure 2
Forest plot ofβ-catenin gene and overall survival in CRC (a). Forest plot of β-catenin gene and disease-free survival in CRC (b).
(a)(b)For theAPC gene, the pooled HR for OS based on 8 studies was 0.035 (95% CI: 0.308–0.377; Q = 51.76; P=0.000) (Figure 3(a)). This value suggested the association of the mutant variant with a lower OS compared with the wild type but not for DFS, where pooled HR = 0.387 (95% CI: 0.483–1.256; Q = 22.624; P=0.000) (Figure 3(b)). For the SMAD3/4 genes, 13 studies were included. The pooled HR was 0.688 (95% CI: 0.403–0.974; Q = 47.689; P=0.000) (Figure 4(a)). Their pooled HR for DFS was 0.449 (95% CI: 0.146–0.753; Q = 32.012; P=0.000) (Figure 4(b)). These results implied a worse prognosis of CRC in the event of the loss of expression of SMAD-3 or SMAD-4.Figure 3
Forest plot ofAPC gene and overall survival in CRC (a). Forest plot of APC gene and disease-free survival in CRC (b).
(a)(b)Figure 4
Forest plot ofSMAD3/4 gene and overall survival in CRC (a). Forest plot of SMAD3/4 gene and disease-free survival in CRC (b).
(a)(b)Studies reporting the mutations of theTp53 gene (n = 24) had a pooled HR of 0.319 (95% CI: 0.133–0.504; Q = 201.339; P=0.000) (Figure 5(a)) for OS and 0.179 (95% CI: 0.126–0.485; Q = 143.796; P=0.000) (Figure 5(b)) for DFS (n = 14). The results were widely heterogenous but implied significantly poor prognosis overall, as well as DFS, in CRC cases. Five studies showed a pooled HR of 0.671 (95% CI: 0.116–1.458; Q = 10.746; P=0.030) (Figure 6) for the Wnt gene with OS, thereby showing no association of Wnt gene expression/mutation with survival in CRC. Since only one study [14] reported the hazard ratio for DFS, meta-analysis was not performed for the Wnt gene with shorter DFS. Five studies on Cyclin D1 were included in the meta-analysis. The pooled HR for OS was 0.362 (95% CI: 0.944–0.221; Q = 5.421; P=0.253) (Figure 7(a)) and that for DFS was 0.485 (95% CI: 0.772–0.198; Q = 5.810; P=0.214) (Figure 7(b)). High Cyclin D1, therefore, produced a worse prognosis in CRC, both in terms of OS and DFS.Figure 5
Forest plot ofTP53 gene and overall survival in CRC (a). Forest plot of TP53 gene and disease-free survival in CRC (b).
(a)(b)Figure 6
Forest plot ofWNT gene and overall survival in CRC.Figure 7
Forest plot ofCyclin D1 gene and overall survival in CRC (a). Forest plot of cyclin D1 gene and disease-free survival in CRC (b).
(a)(b)


## 3.5. Publication Bias

We assessed the publication bias forAPC, SMAD, β-catenin, and Tp53 gene studies by constructing funnel plots (Figure 8(a)–8(f)) as more than ten studies were included in the meta-analysis. Egger’s test indicated that publication bias existed for the evaluation of the impact of β-catenin, APC, and Tp53 with OS, however, Begg’s test showed no significant publication bias (β-catenin and OS: I2 = 65.83%, tau (τ) = 0.047 (P=0.76), β-catenin and DFS: I2 = 71.33%, τ = 0.21 (P=0.25), TP53 and OS: I2 = 88.82%, τ = 0.153 (P=0.28), TP53 and DFS: I2 = 89.12%, τ = 0.25 (P=0.13), APC and OS: I2 = 86.48%; τ = 0.28 (P=0.32), SMAD and OS: I2 = 83.17%, and τ = 0.23 (P=0.27)). It is notable that with Egger’s test, there is insufficient power of testing when the number of selected studies is below 20. It was, therefore, not attempted for the remaining genes.Figure 8
The funnel plot of studies included forAPC gene and OS in CRC (a). The funnel plot of studies included for SMAD gene and OS in CRC (b). The funnel plot of studies included for β-catenin gene and OS in CRC (c). The funnel plot of studies included for β-catenin gene and DFS in CRC (d). The funnel plot of studies included for TP53 gene and OS in CRC (e). The funnel plot of studies included for TP53 gene and DFS in CRC (f).
(a)(b)(c)(d)(e)(f)


## 4. Discussion

Colorectal carcinogenesis is a complex multistage process that involves multiple genetic variations. The aberrant activation of theWnt/β-catenin pathway has been identified as being involved in the progression of CRC [104] and early colorectal tumorigenesis [103]. In several studies, the β-catenin accumulation in the nucleus or cytoplasm was identified as a marker for poor prognosis. The variations of the APC or CTNNB1 genes are the main causes of the accumulation of nuclear β-catenin [105]. In contrast, β-catenin expression in the nucleus was associated with noninvasive tumors and more favorable outcomes [106] but remains controversial.The current meta-analysis has explored the cumulative prognostic significance of the different subcellular localizations ofβ-catenin expression among CRC subjects. The results indicated that the nuclear expression or decreased expression of β-catenin in the membrane was associated with lower OS, which is consistent with the published articles. Pooled data from a study [107] found that the reduced expression of β-catenin in the membrane to be significantly associated with poor survival among CRC patients, thus the majority of the selected studies are from nuclear β-catenin overexpression.Wnt2 is an oncogene with the potential to activate canonical Wnt signaling during CRC tumorigenesis [21, 22]. The role of Wnt5 in the progression of CRC is quite complex and appears to be inconsistent in findings. Several studies [21–25] proved that Wnt5a was silenced in most CRC cell-lines because of recurrent methylation in the promoter region. Wnt5a acts as a tumor suppressor by interfering with the canonical β-catenin signaling. However, it activates the noncanonical signaling pathways [100]. In this study, there was no significant association of Wnt (2 and 5) to OS or DFS found among CRC patients, and it is well in accordance with the contradictory studies reported [23–25].In our meta-analysis pertaining toSMAD genes, we found that the loss of SMAD 3 or SMAD4 staining was strongly associated with a worse prognosis for OS and DFS (including CSS/RFS). Several other individual reports are in alignment with our findings [87, 92, 93]. These studies reported SMAD-4 to have a stronger association compared with SMAD-3 or other SMAD genes.Most studies have shown the predictive value ofTp53 for overall survival in CRC to be poor. Dong et al. [108] reported 53% of Tp53 gene variation as the susceptibility for the development of CRC. Another study reported that, in mouse models, a high rate of spontaneous tumors was noted because of p53-deficiency [109]. Moreover, the deletion of p53 and the Tp53 gene variation led to tumor progression and tumor cell death.A meta-analysis of Asian patients indicates that an association betweenTp53 Arg72Pro polymorphism CC genotype might contribute to an increased risk of CRC [110]. The current meta-analysis included diverse populations, and the results pertaining to the association of Tp53 with shorter overall and DFS in CRCs may, therefore, be considered more generalizable.In an independent study of 331 patients, the prognostic value ofAPC was evaluated, and the findings were validated on a public database of stage IV colon cancer from Memorial Sloan Kettering Cancer Center (MSKCC) [75]. The study found that APC-WT was present in 26% of metastatic CRC patients, and it was more prevalent in patients of younger age and those with right-sided tumors. APC-WT tumors have been shown to be associated with other Wnt-activating alterations, including CTNNB1, FBXW7, RNF43, ARID1A, and SOX9. APC-WT patients in a study were found to have a worse overall survival (OS) than APC-MT pts (HR = 1.809, 95% CI: 1.260–2.596) [75]. Overall, in most studies, APC-WT is associated with poor OS. Additionally, APC-WT tumors were associated with other activating alterations of the Wnt pathway, including RNF43 and CTNNB1.Cyclin D1 overexpression has been reported to occur in 40–70% of colorectal tumors [111]. Despite the well-established role of Cyclin D1 in cell cycle progression, previous data on Cyclin D1 and clinical outcomes in CRC have been conflicting. Cyclin D1 overexpression has also been significantly related to poor OS in Asian and non-Asian CRC patients [112]. Two mechanisms have been implicated, namely nuclear expression and cytoplasmic expression, wherein most studies found an association of the nuclear expression of Cyclin D1 with OS and DFS. Moreover, Cyclin D1 also has been shown as a poor prognosis marker when co-expressed with other genes, notably p53 [113]. These results are consistent with the present meta-analysis’s findings that shortened overall survival and DFS are associated with Cyclin D1 among CRC patients.We acknowledge that this study has several limitations. Firstly, the element of bias cannot be ruled out because of the inclusion of retrospective studies. Secondly, all of the selected studies measured gene expression by immunohistochemistry and sequencing methods. Moreover, the cut-offs used in various studies differed between and across the genes studied. However, there was no subgroup analysis performed to investigate the potential effect of the technique on the combined results. Thirdly, some heterogeneity has been found because of location and the types of cancer. To eliminate variations across studies, a random-effects model was performed accordingly. Limited databases were used for article search, and only freely available full-text articles in the English language were used, which might affect the persuasive power of the pooled estimate, although to a limited extent. In addition, publication bias existed because only studies generating positive results or significant outcomes were suitable for publication. Future research might helpfully contribute further relevant analyses and well-designed extensive prospective studies, since they will address the limitations of the current meta-analysis.


## 5. Conclusion

The present meta-analysis has found that the genes associated with worst OS in CRC wereβ-catenin (cytoplasmic, membranous, and nuclear overexpression), APC (mutant type), Tp53 (mutated), SMAD-3 and SMAD-4 (loss of expression), and Cyclin D1 (high). The gene associated with shorter DFS in CRC patients was APC (mutant type). In contrast, Wnt (2 and 5) genes were not associated with prognosis in CRC in this meta-analysis.



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*Source: 5338956-2022-08-17.xml*