| Literature DB >> 34217244 |
Wei Shang1, Chuanwang Yan2, Ran Liu1, Lili Chen3, Dongdong Cheng4, Liang Hao5, Wenguang Yuan1, Jingbo Chen6, Hui Yang7.
Abstract
BACKGROUND: Various studies investigating the clinical significance of FBXW7 mutation and/or expression have yielded inconclusive results in colorectal cancer (CRC) patients. Therefore, the present meta-analysis summarizes previous evidence and evaluates the clinical significance, including the prognostic role, of FBXW7 status in CRCs.Entities:
Keywords: Cancer; Expression; FBXW7; Mutation; Survival
Year: 2021 PMID: 34217244 PMCID: PMC8254329 DOI: 10.1186/s12885-021-08535-8
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.430
Fig. 1A flow chart of this study
Characteristics of studies included in the present meta-analysis
| Detection of FBXW7 mutation/expression | Study | Study Region | Recruitment time | No. of patients | Clinical Stage | FBXW7 status method | Cut off | Antibody source | Dilution | Case: Low/High (MT/WT) | Median follow-up months | Analysis method | OS HR(95%CI) | DFS HR(95%CI) | Quality score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mutation | Chang, 2015 [ | Taiwan | 2000-2009 | 1519 | TNM I-IV | MassArray | NA | NA | NA | 114/1405 | NA | Univariate | 1.00 (0.98–1.02) | NA | 8 |
| Mouradov, 2013 [ | Australia | 2002-2004 | 822 | TNM II-III | Sanger sequencing | NA | NA | NA | 41/781 | 32.2 | Univariate | 0.96 (0.45–2.06) | NA | 7 | |
| Korphaisarn, 2017 [ | USA | 2009-2015 | 527 | TNM IV | NGS | NA | NA | NA | 43/484 | 30.4 | Multivariate | 2.00 (1.27–3.16) | NA | 8 | |
| Iwatsuki, 2010 [ | Japan | 1993-1999 | 93 | Duke A-D | qRT-PCR | Median | NA | NA | 46/47 | 36 | Multivariate | 1.98 (1.26–3.27) | NA | 7 | |
| Gao, 2019 [ | China | 2015-2016 | 207 | TNM I-IV | MiSeq | NA | NA | NA | 33/174 | 23 | Univariate | 0.59 (0.21–1.68) | 0.75 (0.32–1.79) | 7 | |
| Expression | He, 2019 [ | China | 2009-2011 | 140 | TNM I-IV | IHC | NA | Abcam, USA | 1:500 | 84/56 | NA | Univariate | 2.30 (0.92–5.76) | 2.45 (1.22–4.92) | 6 |
| Liu, 2018 [ | China | 2010-2015 | 509 | TNM I-IV | IHC | Score 4 | Abcam, USA | 1:200 | 359/150 | NA | Univariate | 2.22 (1.40–3.45) | NA | 6 | |
| Li, 2018 [ | China | 2007-2009 | 276 | TNM I-IV | IHC | Score 1 | Bethyl, USA | NA | 60/216 | NA | Multivariate | 3.57 (2.23–5.71) | 4.63 (2.65–8.13) | 7 | |
| Tang, 2016 [ | China | 2011-2011 | 50 | Duke A-D | IHC | score 3 | Santa Cruz, USA | 1:60 | 23/27 | NA | Univariate | 1.04 (0.12–9.42) | NA | 7 | |
| Kawashita, 2017 [ | Japan | 2001-2009 | 56 | NA | IHC | Score 3 | Abcam, USA | 1:100 | 24/32 | 55 | Univariate | 1.98 (0.42–9.26) | 1.50 (0.79–2.85) | 7 |
a Low/High indicates low expression of FBXW7 versus high expression of FBXW7 in studies investigating the RNA or protein level of FBXW7, and the MT/WT implies the mutation of FBXW7 versus wild type of FBXW7 in studies investigating the mutation rate of FBXW7
Meta-analysis of FXBW7 status and clinicopathological features in CRC
| Parameters Characteristics | Number of studies | OR (95%CI) | I2 (%) | Z | ||
|---|---|---|---|---|---|---|
| Age(≥ 60 year vs. < 60 year) | 3 | 1.00 (0.93–1.36) | 0 | 0.71 | 0.00 | 1.00 |
| Gender (Male vs. Female) | 7 | 1.03 (0.83–1.28) | 6 | 0.38 | 0.28 | 0.78 |
| Differentiation(Well vs. Moderate + Poor) | 2 | 0.81 (0.40–1.64) | 0 | 0.63 | 0.89 | 0.37 |
| Differentiation(Well+ Moderate vs. Poor) | 4 | 0.72 (0.35–1.48) | 69 | 0.02 | 0.59 | 0.55 |
| Size(≥ 5 cm vs. < 5 cm) | 3 | 0.93 (0.64–1.35) | 0 | 0.45 | 0.37 | 0.71 |
| Tumor location(Colon vs. Rectum) | 5 | 0.85 (0.64–1.12) | 30 | 0.22 | 1.17 | 0.24 |
| Venous invasion(Present vs. Absent) | 3 | 1.63 (1.01–2.64) | 14 | 0.31 | 1.99 | 0.05 |
| Peritoneal metastasis (Present vs. Absent) | 2 | 0.82 (0.38–1.80) | 0 | 0.40 | 0.49 | 0.63 |
| Depth of invasion (T1 + T2 vs. T3 + T4) | 3 | 0.44 (0.27–0.74) | 0 | 0.99 | 3.12 | < 0.01 |
| Lymph node metastasis (Positive vs. Negative) | 5 | 1.88 (1.40–2.53) | 0 | 0.45 | 4.18 | < 0.01 |
| Distant metastasis (Present vs. Absent) | 3 | 1.85 (0.34–10.24) | 92 | < 0.01 | 0.71 | 0.48 |
| TNM stage(I + II vs. III + IV) | 3 | 0.53 (0.15–1.84) | 95 | < 0.01 | 1.00 | 0.32 |
| Duke’s stage(A + B vs. C + D) | 2 | 0.45 (0.04–5.20) | 90 | < 0.01 | 0.64 | 0.52 |
Fig. 2Forest plots: Summary hazard ratios (HRs) and 95% confidence intervals (CIs) of colorectal cancer OS (a) and DFS (b) for FBXW7 status
Subgroup analyses for overall survival
| Outcome | Characteristics | Number of studies | HR(95%CI) | I2 (%) | Ph | Z | |
|---|---|---|---|---|---|---|---|
| Recruitment time | Before 2009 | 5 | 1.24 (0.93–1.65) | 88 | < 0.01 | 1.46 | 0.14 |
| After 2009 | 5 | 1.32 (1.17–1.50) | 32 | 0.21 | 4.43 | < 0.01 | |
| Region | Eastern asia | 8 | 1.27 (1.04–1.55) | 77 | < 0.01 | 2.31 | 0.02 |
| Other regions | 2 | 1.18 (0.87–1.61) | 62 | 0.10 | 1.08 | 0.28 | |
| FBXW7 detection method | IHC/qRT-PCR | 6 | 1.39 (1.22–1.59) | 46 | 0.10 | 4.95 | < 0.01 |
| Sequencing | 4 | 1.17 (0.94–1.47) | 73 | 0.01 | 1.40 | 0.16 | |
| Sample Size | ≥ 100 | 7 | 1.23 (1.01–1.51) | 81 | < 0.01 | 2.06 | 0.04 |
| < 100 | 3 | 1.33 (1.09–1.63) | 0 | 0.85 | 2.81 | < 0.01 | |
| Data types | Univariate | 7 | 1.13 (0.94–1.35) | 56 | 0.03 | 1.28 | 0.20 |
| Multivariate | 3 | 1.47 (1.25–1.74) | 50 | 0.13 | 4.56 | < 0.01 |
Fig. 3Begg’s funnel plots of the natural logarithm of the hazard ratios (HRs) and the SE of the natural logarithm of the HRs for the included studies reported with OS (a) and PFS (b)
The influence of individual study on the pooled estimate for outcomes
| Outcome | Study omitted | HR(95%CI) | I2 (%) | Z | ||
|---|---|---|---|---|---|---|
| OS | Chang, 2015 [ | 1.32 (1.15–1.52) | 49 | 0.05 | 3.93 | < 0.01 |
| He, 2019 [ | 1.23 (1.04–1.47) | 76 | < 0.01 | 2.38 | 0.02 | |
| Mouradov, 2013 [ | 1.28 (1.08–1.52) | 75 | < 0.01 | 2.83 | < 0.01 | |
| Liu, 2018 [ | 1.22 (1.02–1.47) | 74 | < 0.01 | 2.18 | 0.03 | |
| Korphaisarn, 2017 [ | 1.23 (1.02–1.48) | 75 | < 0.01 | 2.21 | 0.03 | |
| Iwatsuki, 2010 [ | 1.19 (1.03–1.38) | 59 | 0.01 | 2.39 | 0.02 | |
| Li, 2018 [ | 1.23 (1.03–1.48) | 75 | < 0.01 | 2.24 | 0.03 | |
| Tang, 2016 [ | 1.26 (1.06–1.48) | 76 | < 0.01 | 2.69 | < 0.01 | |
| Gao, 2019 [ | 1.29 (1.10–1.52) | 73 | < 0.01 | 3.10 | < 0.01 | |
| Kawashita, 2017 [ | 1.24 (1.05–1.47) | 76 | < 0.01 | 2.55 | 0.01 | |
| DFS | He, 2019 [ | 1.01 (0.56–1.80) | 0 | 0.80 | 0.03 | 0.97 |
| Li, 2018 [ | 1.02 (0.58–1.79) | 0 | 0.82 | 0.06 | 0.95 | |
| Gao, 2018 [ | 1.31 (0.56–3.11) | 0 | 0.94 | 0.62 | 0.53 | |
| Kawashita, 2017 [ | 0.99 (0.51–1.91) | 0 | 0.78 | 0.03 | 0.98 |