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IGF-IR: a new prognostic biomarker for human glioblastoma

View Article: PubMed Central - PubMed

ABSTRACT

Background:: Glioblastomas (GBMs) are the most common malignant primary brain tumours in adults and are refractory to conventional therapy, including surgical resection, radiotherapy and chemotherapy. The insulin-like growth factor (IGF) system is a complex network that includes ligands (IGFI and IGFII), receptors (IGF-IR and IGF-IIR) and high-affinity binding proteins (IGFBP-1 to IGFBP-6). Many studies have reported a role for the IGF system in the regulation of tumour cell biology. However, the role of this system remains unclear in GBMs.

Methods:: We investigate the prognostic value of both the IGF ligands' and receptors' expression in a cohort of human GBMs. Tissue microarray and image analysis were conducted to quantitatively analyse the immunohistochemical expression of these proteins in 218 human GBMs.

Results:: Both IGF-IR and IGF-IIR were overexpressed in GBMs compared with normal brain (P<10−4 and P=0.002, respectively). Moreover, with regard to standard clinical factors, IGF-IR positivity was identified as an independent prognostic factor associated with shorter survival (P=0.016) and was associated with a less favourable response to temozolomide.

Conclusions:: This study suggests that IGF-IR could be an interesting target for GBM therapy.

No MeSH data available.


Related in: MedlinePlus

Kaplan–Meier survival curves of GBM patients according to the IGF-IR expression categorised as (A) negative (i.e., LI<1%) or positive (i.e., LI⩾1%); (B) negative (i.e., LI<1%), weakly positive (i.e., 1%⩽LI<30%) or strongly positive (i.e., LI⩾30%), and Kaplan–Meier survival curves of GBM patients according to the adjuvant treatment in IGF-IR-negative (i.e., LI<1%) (C) or IGF-IR-positive (i.e., LI⩾1%) (D) cases. Each dot symbolises a death due to cancer and each cross indicates a survivor or a death not related to cancer (censured data).
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fig3: Kaplan–Meier survival curves of GBM patients according to the IGF-IR expression categorised as (A) negative (i.e., LI<1%) or positive (i.e., LI⩾1%); (B) negative (i.e., LI<1%), weakly positive (i.e., 1%⩽LI<30%) or strongly positive (i.e., LI⩾30%), and Kaplan–Meier survival curves of GBM patients according to the adjuvant treatment in IGF-IR-negative (i.e., LI<1%) (C) or IGF-IR-positive (i.e., LI⩾1%) (D) cases. Each dot symbolises a death due to cancer and each cross indicates a survivor or a death not related to cancer (censured data).

Mentions: First, we analysed the impact of the clinical factors (listed in Table 1) on the cancer-specific survival by means of univariate analyses (Table 2). As expected, older age was associated with a reduced median survival (P=0.0004); macroscopically complete resection (based on radiology reports of first postoperative imaging) significantly improved the median survival of the patients (from 8.4 to 13.1 months; P=0.002), as did the addition of TMZ to radiotherapy (from 10.6 to 14.9 months; P=10−5). No association was found between the quantitative immunostaining evaluation of the expression of IGFI, IGFII or IGF-IIR and the patient outcomes. In contrast, IGF-IR LI was negatively associated with cancer-specific survival (P=0.046). We also evaluated the prognostic impact of these four markers after binarising the data (negative/positive, as described in Materials and Methods). Similar to the results of the quantitative immunostaining evaluation, only positive expression of IGF-IR was associated with significantly reduced survival, as shown in Figure 3A (P=0.02). Interestingly, when the IGF-IR expression was categorised into three groups (i.e., negative, weakly positive and strongly positive), the median survival of patients with strong expression of IGF-IR was observed to be dramatically reduced (4.5 months) compared with that of the GBM IGF-IR-negative patients (11.6 months) (three-group comparison P=0.01; negative vs strongly positive P=0.007; Figure 3B). A multivariate Cox regression analysis was then performed to test the prognostic contribution of IGF-IR expression in the presence of the prognostic clinical factors, that is, those for which the univariate results were significant (see Table 2). This model was established using 167 cases (excluding cases with missing values and the non-standard treatment category, see Table 1). We previously verified that the univariate results shown in Table 2 remain valid with this reduced series (except that the quantitative IGF-IR LI variable slightly lost in significance with P=0.057), without impacting the selection of variables introduced in the Cox model. As detailed in Table 3, IGF-IR-positive staining (P=0.016) as well as older age (P=0.003), macroscopically partial resection (P=0.039) and radiotherapy alone (P=0.003) were independent prognostic factors associated with shorter survival.


IGF-IR: a new prognostic biomarker for human glioblastoma
Kaplan–Meier survival curves of GBM patients according to the IGF-IR expression categorised as (A) negative (i.e., LI<1%) or positive (i.e., LI⩾1%); (B) negative (i.e., LI<1%), weakly positive (i.e., 1%⩽LI<30%) or strongly positive (i.e., LI⩾30%), and Kaplan–Meier survival curves of GBM patients according to the adjuvant treatment in IGF-IR-negative (i.e., LI<1%) (C) or IGF-IR-positive (i.e., LI⩾1%) (D) cases. Each dot symbolises a death due to cancer and each cross indicates a survivor or a death not related to cancer (censured data).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4559821&req=5

fig3: Kaplan–Meier survival curves of GBM patients according to the IGF-IR expression categorised as (A) negative (i.e., LI<1%) or positive (i.e., LI⩾1%); (B) negative (i.e., LI<1%), weakly positive (i.e., 1%⩽LI<30%) or strongly positive (i.e., LI⩾30%), and Kaplan–Meier survival curves of GBM patients according to the adjuvant treatment in IGF-IR-negative (i.e., LI<1%) (C) or IGF-IR-positive (i.e., LI⩾1%) (D) cases. Each dot symbolises a death due to cancer and each cross indicates a survivor or a death not related to cancer (censured data).
Mentions: First, we analysed the impact of the clinical factors (listed in Table 1) on the cancer-specific survival by means of univariate analyses (Table 2). As expected, older age was associated with a reduced median survival (P=0.0004); macroscopically complete resection (based on radiology reports of first postoperative imaging) significantly improved the median survival of the patients (from 8.4 to 13.1 months; P=0.002), as did the addition of TMZ to radiotherapy (from 10.6 to 14.9 months; P=10−5). No association was found between the quantitative immunostaining evaluation of the expression of IGFI, IGFII or IGF-IIR and the patient outcomes. In contrast, IGF-IR LI was negatively associated with cancer-specific survival (P=0.046). We also evaluated the prognostic impact of these four markers after binarising the data (negative/positive, as described in Materials and Methods). Similar to the results of the quantitative immunostaining evaluation, only positive expression of IGF-IR was associated with significantly reduced survival, as shown in Figure 3A (P=0.02). Interestingly, when the IGF-IR expression was categorised into three groups (i.e., negative, weakly positive and strongly positive), the median survival of patients with strong expression of IGF-IR was observed to be dramatically reduced (4.5 months) compared with that of the GBM IGF-IR-negative patients (11.6 months) (three-group comparison P=0.01; negative vs strongly positive P=0.007; Figure 3B). A multivariate Cox regression analysis was then performed to test the prognostic contribution of IGF-IR expression in the presence of the prognostic clinical factors, that is, those for which the univariate results were significant (see Table 2). This model was established using 167 cases (excluding cases with missing values and the non-standard treatment category, see Table 1). We previously verified that the univariate results shown in Table 2 remain valid with this reduced series (except that the quantitative IGF-IR LI variable slightly lost in significance with P=0.057), without impacting the selection of variables introduced in the Cox model. As detailed in Table 3, IGF-IR-positive staining (P=0.016) as well as older age (P=0.003), macroscopically partial resection (P=0.039) and radiotherapy alone (P=0.003) were independent prognostic factors associated with shorter survival.

View Article: PubMed Central - PubMed

ABSTRACT

Background:: Glioblastomas (GBMs) are the most common malignant primary brain tumours in adults and are refractory to conventional therapy, including surgical resection, radiotherapy and chemotherapy. The insulin-like growth factor (IGF) system is a complex network that includes ligands (IGFI and IGFII), receptors (IGF-IR and IGF-IIR) and high-affinity binding proteins (IGFBP-1 to IGFBP-6). Many studies have reported a role for the IGF system in the regulation of tumour cell biology. However, the role of this system remains unclear in GBMs.

Methods:: We investigate the prognostic value of both the IGF ligands' and receptors' expression in a cohort of human GBMs. Tissue microarray and image analysis were conducted to quantitatively analyse the immunohistochemical expression of these proteins in 218 human GBMs.

Results:: Both IGF-IR and IGF-IIR were overexpressed in GBMs compared with normal brain (P&lt;10&minus;4 and P=0.002, respectively). Moreover, with regard to standard clinical factors, IGF-IR positivity was identified as an independent prognostic factor associated with shorter survival (P=0.016) and was associated with a less favourable response to temozolomide.

Conclusions:: This study suggests that IGF-IR could be an interesting target for GBM therapy.

No MeSH data available.


Related in: MedlinePlus