| Literature DB >> 34540691 |
Mahdi Abdoli Shadbad1,2, Negar Hosseinkhani2, Zahra Asadzadeh2, Oronzo Brunetti3, Nicola Silvestris3,4, Behzad Baradaran2,5,6.
Abstract
BACKGROUND: Cancer stem cells have been implicated in tumor relapse, tumor invasion, and cancer therapy resistance in high-grade gliomas; thus, characterizing cancer stem cell-related markers can help determine the prognosis of affected patients. Preclinical studies have reported that CD133 is implicated in tumor recurrence and cancer therapy resistance in high-grade gliomas; however, clinical studies have reported inconclusive results regarding its prognostic value in patients with high-grade gliomas.Entities:
Keywords: CD133; high-grade gliomas; high-grade gliomas recurrence pattern; high-grade gliomas relapse; magnetic resonance imaging; progression-free survival; time to distant recurrence; time to local recurrence
Year: 2021 PMID: 34540691 PMCID: PMC8445366 DOI: 10.3389/fonc.2021.722833
Source DB: PubMed Journal: Front Oncol ISSN: 2234-943X Impact factor: 6.244
Figure 1The flowchart of literature identification, inclusion, and exclusion in the current systematic review.
The characteristics of the twelve included studies.
| No. | First author, year | Country | Sample size | Glioma grade | Endpoint | Detection method | Cut-off |
|---|---|---|---|---|---|---|---|
| 1 | Tetsu Yamaki, 2020 ( | Japan | 167 | IV | TTD and TTL | The integration of IHC with Western blot | Ratio>1 |
| 2 | Yasuo Iwadate, 2017 ( | Japan | 70 | IV | PFS | IHC | 10% |
| 3 | Yasuo Iwadate, 2016 ( | Japan | 80 | IV | PFS | IHC | 10% |
| 4 | Ichiyo Shibahara, 2015 ( | Japan | 86 | III | TTD and TTL | The integration of IHC with Western blot | Ratio > 1 |
| 5 | Rikke H Dahlrot, 2014 ( | Denmark | 211 | III and IV | PFS | Immunofluorescence | 2% |
| 6 | Jung Ha Shin, 2013 ( | South Korea | 67 | IV | PFS | IHC | 50% |
| 7 | Ichiyo Shibahara, 2013 ( | Japan | 112 | IV | TTD and TTL | The integration of IHC with Western blot | Ratio > 1 |
| 8 | Consolación Melguizo, 2012 ( | Spain and Italy | 78 | IV | PFS | IHC | 25% |
| 9 | Kyung-Jung Kim, 2011 ( | South Korea | 88 | IV | PFS | IHC | 50% |
| 10 | JIE HE, 2011 ( | China | 59 | III and IV | PFS | IHC | 10% |
| 11 | Roberto Pallini, 2008 ( | Italy | 44 | IV | PFS | Immunofluorescence | 2% |
| 12 | Felix Zeppernick, 2008 ( | Germany | 24 | III | PFS | IHC | 1% |
TTD, time to distant recurrence; TTL, time to local recurrence; PFS, progression-free survival, and IHC, immunohistochemistry.
Figure 2The forest plot of studies evaluating the prognostic value of CD133 overexpression in determining the PFS of patients with high-grade gliomas; Rikke H Dahlrot (IV) pertains to the Dahlrot et al.’s study on patients with grade IV gliomas, and Rikke H Dahlrot pertains to the Dahlrot et al.’s study on patients with grade III gliomas.
Figure 3The forest plot of studies evaluating the prognostic value of CD133 overexpression in determining the PFS of patients with high-grade gliomas (with 2% cut-off); Rikke H Dahlrot (IV) pertains to the Dahlrot et al.’s study on patients with grade IV gliomas, and Rikke H Dahlrot pertains to the Dahlrot et al.’s study on patients with grade III gliomas.
Figure 4The forest plot of studies evaluating the prognostic value of CD133 overexpression in determining the PFS of patients with high-grade gliomas (with 10% cut-off).
Figure 5The forest plot of studies evaluating the prognostic value of CD133 overexpression in determining the PFS of patients with high-grade gliomas (with 50% cut-off).
Figure 6The forest plot of studies evaluating the prognostic value of CD133 in determining the TTD of glioblastoma patients.
Figure 7The forest plot of studies evaluating the prognostic value of CD133 in determining the TTD of patients with high-grade gliomas.
Figure 8The forest plot of studies evaluating the prognostic value of CD133 in determining the TTL of glioblastoma patients.
Figure 9The forest plot of studies evaluating the prognostic value of CD133 in determining the TTL of patients with high-grade gliomas.
The quality assessment of included studies based on the Hayden et al. checklists.
| First author and the year of publication | Study participation | Study attrition | Prognostic factor measurement | Outcome measurement | Confounding measurement and account | Analysis |
|---|---|---|---|---|---|---|
| Tetsu Yamaki, 2020 ( | *** | *** | *** | *** | *** | *** |
| Yasuo Iwadate, 2017 ( | *** | *** | *** | *** | *** | *** |
| Yasuo Iwadate, 2016 ( | *** | *** | *** | *** | *** | *** |
| Ichiyo Shibahara, 2015 ( | *** | *** | ** | *** | *** | *** |
| Rikke H Dahlrot, 2014 ( | *** | *** | *** | *** | * | ** |
| Jung Ha Shin, 2013 ( | *** | *** | *** | *** | *** | *** |
| Ichiyo Shibahara, 2013 ( | *** | *** | *** | *** | *** | *** |
| Consolación Melguizo 2012 ( | *** | *** | *** | *** | * | ** |
| Kyung-Jung Kim, 2011 ( | *** | *** | *** | *** | *** | *** |
| JIE HE, 2011 ( | *** | *** | *** | * | * | *** |
| Roberto Pallini, 2008 ( | *** | *** | *** | *** | *** | *** |
| Felix Zeppernick, 2008 ( | *** | ** | *** | *** | *** | *** |
***Bias might not present; **Bias might be partly present; *Bias might be present.