| Literature DB >> 29228656 |
Stefanie Avril1,2, Yasemin Dincer1, Katharina Malinowsky1, Claudia Wolff1, Sibylle Gündisch1, Alexander Hapfelmeier3, Melanie Boxberg1, Holger Bronger4, Karl-Friedrich Becker1, Barbara Schmalfeldt4,5.
Abstract
Despite frequent initial response rates of epithelial ovarian cancer to platinum-based chemotherapy the majority of patients develop drug resistance. Our aim was to evaluate differential expression of signaling-pathway proteins in platinum-sensitive versus platinum-resistant primary epithelial ovarian cancer specimens to identify predictive biomarkers for treatment response. 192 patients were studied comprising of independent training (n = 89) and validation (n = 103) cohorts. Full-length proteins were extracted from paraffin-embedded samples including multiple regions per tumor to account for intratumoral heterogeneity. Quantitative reverse-phase-protein-arrays were used to analyze protein and phospho-protein levels of 41 signaling molecules including growth-factor receptors, AKT and MAPK signaling pathways as well as angiogenesis and cell-adhesion. Platinum-resistant ovarian cancers (56/192) demonstrated significantly higher intratumoral levels of the angiogenesis-associated growth-factor receptors PDGFR-beta and VEGFR2 compared to platinum-sensitive tumors. In addition, patients with high PDGFR-beta expression had significantly shorter overall and progression-free survival (HR 3.6 and 2.4; p < 0.001). The prognostic value of PDGFR-beta and VEGFR2 was confirmed in publicly available microarray-datasets. High intratumoral levels of the angiogenesis-related growth-factor receptors PDGFR-beta and VEGFR2 might serve as novel predictive biomarkers to identify primary resistance to platinum-based chemotherapy. Those ovarian cancer patients might particularly benefit from additional anti-vascular therapy including anti-VEGF antibody or receptor tyrosine-kinase-inhibitor therapy.Entities:
Keywords: ovarian cancer; phosphoproteomics; platinum chemotherapy resistance; response prediction; reverse phase protein array (RPPA)
Year: 2017 PMID: 29228656 PMCID: PMC5716696 DOI: 10.18632/oncotarget.18415
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Patient characteristics
| Total ( | Training set ( | Validation set ( | ||||
|---|---|---|---|---|---|---|
| (%) | (%) | (%) | ||||
| 61 (23; 88) | 58 (23; 84) | 61 (25; 88) | ||||
| Histologic subtype | ||||||
| High-grade serous | 144 | (75%) | 63 | (71%) | 81 | (78%) |
| High-grade endometrioid | 22 | (11%) | 15 | (17%) | 7 | (7%) |
| Low-grade serous | 3 | (2%) | 2 | (2%) | 1 | (1%) |
| Mucinous | 16 | (8%) | 8 | (9%) | 8 | (8%) |
| Clear cell | 7 | (4%) | 1 | (1%) | 6 | (6%) |
| I | 23 | (12%) | 12 | (13%) | 11 | (10%) |
| II | 7 | (4%) | 4 | (5%) | 3 | (3%) |
| III | 147 | (76%) | 68 | (76%) | 79 | (77%) |
| IV | 15 | (8%) | 5 | (6%) | 10 | (10%) |
| None | 86 | (45%) | 41 | (46%) | 45 | (44%) |
| Present | 106 | (55%) | 48 | (54%) | 58 | (56%) |
| Sensitive | 136 | (71%) | 69 | (78%) | 67 | (65%) |
| Resistant | 56 | (29%) | 20 | (22%) | 36 | (35%) |
| Carboplatin plus paclitaxel | 144 | (75%) | 67 | (75%) | 77 | (75%) |
| Carboplatin plus paclitaxel plus third agent* | 20 | (10%) | 6 | (7%) | 14 | (13%) |
| Carboplatin monotherapy | 24 | (13%) | 13 | (15%) | 11 | (11%) |
| Carboplatin plus cyclophosphamide | 4 | (2%) | 3 | (3%) | 1 | (1%) |
| 42 (1; 195) | 41 (3; 167) | 42 (1; 195) | ||||
| Median (95% CI) [months] | 23 (18; 30) | 27 (21; 46) | 19 (14; 30) | |||
| Median (95% CI) [months] | 58 (48; 75) | 65 (44; NA) | 50 (42; 75) | |||
| 140 | (73%) | 63 | (71%) | 77 | (75%) | |
| 106 | (55%) | 46 | (52%) | 60 | (58%) | |
Platinum sensitivity/ resistance, defined by a progression-free interval of ≥ / < 6 months after completion of chemotherapy
Progression-free and overall survival were calculated by Kaplan Meier method
*cyclophosphamide, epirubicine, gemcitabine, or topotecane; CI, confidence interval; NA, upper bound of 95% confidence interval not reached within follow-up period.
Overexpression of signaling pathway proteins in platinum-resistant versus platinum-sensitive epithelial ovarian cancer
| Protein | ||
|---|---|---|
| Training set ( | Validation set ( | |
| Growth factors/receptors | ||
| pEGFR (Tyr1086) | 0.03* | 0.98 |
| HER2 (extracellular) | 0.01* | 0.59 |
| HER3 | 0.03* | 0.31 |
| PDGFbb | 0.03* | 0.72 |
| | ||
| | ||
| pVEGFR2 | 0.03* | 0.56 |
| AKT-pathway | ||
| mTOR | 0.02* | 0.41 |
| PI3K | 0.05* | 0.40 |
| MAPK-pathway | ||
| JNK/SAPK | 0.03* | 0.47 |
| ERK | 0.008** | 0.56 |
The table summarizes all signaling proteins showing statistically significant overexpression in platinum- resistant versus platinum-sensitive ovarian cancer in the training cohort. Proteins also showing statistically significant overexpression in the validation cohort are indicated in bold.
* ≤ 0.05, ** < 0.01.
The percentage of platinum-resistant patients was 22% (20/89) in the training set and 35% (36/103) in the validation set.
Figure 1Increased PDGFRβ and VEGFR2 protein levels are associated with platinum resistance
Higher intratumoral protein levels of PDGFRβ (A) and VEGFR2 (B) were demonstrated in platinum-resistant (defined as < 6 months progression-free interval following chemotherapy) vs. platinum-sensitive ovarian cancer patients in an independent training (n = 89) and validation cohort (n = 103).
Association between signaling pathway proteins and patient outcome
| Protein | Training set ( | Validation set ( | ||||||
|---|---|---|---|---|---|---|---|---|
| OS | PFS | OS | PFS | |||||
| [ | HR | [ | HR | [ | HR | [ | HR | |
| Growth factors/ receptors | ||||||||
| | ||||||||
| pEGFR (Tyr1086) | 0.07 | 2.4 | 0.36 | 1.5 | 0.97 | 1.0 | 0.84 | 1.0 |
| pVEGFR2 | 0.09 | 2.2 | 0.35 | 1.5 | 0.13 | 1.8 | 0.36 | 1.3 |
| AKT-pathway | ||||||||
| PTEN | 0.08 | 1.5 | 0.19 | 1.3 | 0.26 | 1.1 | 0.22 | 1.1 |
| MAPK-pathway | ||||||||
| ERK | 0.004** | 1.8 | 0.004** | 1.8 | 0.34 | 1.1 | 0.62 | 1.1 |
The table summarizes all proteins showing an association with shorter overall or progression-free survival with a hazard ratio ≥ 1.3 (and p-value < 0.1) in the training cohort. Proteins also showing a significant association with survival in the validation cohort are indicated in bold.
* ≤ 0.05, ** < 0.01, *** < 0.001.
HR, hazard ratio calculated for every increase in protein expression by 100 units.
OS, overall survival; PFS, progression-free survival.
Figure 2Higher PDGFRβ protein is associated with reduced survival of ovarian cancer patients
Patients with higher intratumoral PDGFRβ (above 1.5* median) demonstrated significantly shorter progression-free and overall survival (p < 0.01) compared to patients with low PDGFRβ (below 1.5* median) in both training (A, B) and validation cohort (C, D).
Increasing intratumoral levels of signaling pathway proteins associated with incomplete tumor resection
| Protein | Training set ( | Validation set ( | ||
|---|---|---|---|---|
| [ | OR | [ | OR | |
| Growth factors/ receptors | ||||
| VEGF | 0.09 | 3.0 | 0.56 | 1.2 |
| HER2 (extracellular) | 0.02* | 3.3 | 0.67 | 0.9 |
| HER2 | 0.05* | 2.2 | 0.73 | 1.1 |
| HER3 | 0.04* | 1.5 | 0.60 | 1.2 |
| AKT-pathway | ||||
| PI3K | 0.08 | 2.2 | 0.64 | 1.1 |
| PTEN | 0.08 | 1.8 | 0.28 | 1.2 |
| MAPK-pathway | ||||
| ERK | 0.002** | 4.4 | 0.23 | 1.3 |
The table summarizes all proteins showing an association with incomplete tumor resection with an odds ratio ≥ 1.3 (and p-value < 0.1) in the training cohort.
* ≤ 0.05, ** < 0.01.
OR, odds ratio for incomplete tumor resection calculated for every increase in protein expression by 100 units.
Figure 3Higher PDGFRβ and VEGFR2 gene expression is associated with shorter overall survival in publicly available microarray datasets of ovarian cancer
Patients with high PDGFRβ or VEGFR2 gene expression (red) showed significantly shorter overall survival compared to those with low PDGFRβ or VEGFR2 gene expression (blue) (p < 0.05). This Kaplan-Meier analysis was based on the PrognoScan database (http://www.prognoscan.org/) using three independent cohorts including 278 (A), 185 (B), and 85 (C) ovarian cancer patients, respectively, from the publicly available Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) accession numbers GSE 9891 (A), GSE 26712 (B), and GSE 8841 (C) [20–22].