13 research outputs found
Diagnostic markers for the detection of ovarian cancer in <i>BRCA1</i> mutation carriers
<div><p>Background</p><p>Screening for ovarian cancer (OC) in women at high risk consists of a combination of carbohydrate antigen 125 (CA125) and transvaginal ultrasound, despite their low sensitivity and specificity. This could be improved by the combination of several biomarkers, which has been shown in average risk patients but has not been investigated until now in female <i>BRCA</i> mutation carriers.</p><p>Methods</p><p>Using a multiplex, bead-based, immunoassay system, we analyzed the concentrations of leptin, prolactin, osteopontin, insulin-like growth factor II, macrophage inhibitory factor, CA125 and human epididymis antigen 4 in 26 healthy wild type women, 26 healthy <i>BRCA1</i> mutation carriers, 28 wildtype OC patients and 26 OC patients with <i>BRCA1</i> mutation.</p><p>Results</p><p>Using the ROC analysis, we found a high overall sensitivity of 94.3% in differentiating healthy controls from OC patients with comparable results in the wildtype subgroup (sensitivity 92.8%, AUC = 0.988; p = 5.2e-14) as well as in <i>BRCA1</i> mutation carriers (sensitivity 95.2%, AUC = 0.978; p = 1.7e-15) at an overall specificity of 92.3%.</p><p>The used algorithm also allowed to identify healthy <i>BRCA1</i> mutation carriers when compared to healthy wildtype women (sensitivity 88.4%, specificity 80.7%, AUC = 0.895; p = 6e-08), while this was less pronounced in patients with OC (sensitivity 66.7%, specificity 67.8%, AUC = 0.724; p = 0.00065).</p><p>Conclusion</p><p>We have developed an algorithm, which can differentiate between healthy women and OC patients and have for the first time shown, that such an algorithm can also be used in <i>BRCA</i> mutation carriers. To clarify a suggested benefit to the existing early detection program, large prospective trials with mainly early stage OC cases are warranted.</p></div
Sensitivity and specificity.
<p>Sensitivity and specificity of the combination of five biomarkers (CA125, MIF, Leptin, HE4, OPN) in differentiating between healthy women and OC patients (A), healthy wildtype women and wildtype OC patients (B), healthy <i>BRCA1</i> mutation carriers and <i>BRCA1</i> mutation carriers with OC (C), healthy wildtype women and healthy <i>BRCA1</i> mutation carriers (D) and wildtype OC patients and <i>BRCA1</i> mutation carriers with OC (E).</p
Serum levels of the six biomarkers.
<p>Different serum levels of CA125 (A), MIF (B), Leptin (C), HE4 (D), IGF2 (E), OPN (F) in the four groups (Co WT = healthy wildtype, Co BRCA = healthy <i>BRCA1</i> mutation carriers, CaWT = wildtype ovarian cancer patients, CaBRCA = <i>BRCA1</i> mutation carriers with ovarian cancer).</p
Patients characteristics of the healthy control group (wildtype and <i>BRCA1</i>) and patients tumor characteristics of the group of ovarian cancer patients (wildtype and <i>BRCA1</i>).
<p>Patients characteristics of the healthy control group (wildtype and <i>BRCA1</i>) and patients tumor characteristics of the group of ovarian cancer patients (wildtype and <i>BRCA1</i>).</p
Correlations of the levels of the investigated biomarkers with age in the four study groups.
<p>Correlations of the levels of the investigated biomarkers with age in the four study groups.</p
Table_1_Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.DOCX
<p>Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuestâ„¢ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.</p
Table_6_Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.XLSX
<p>Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuestâ„¢ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.</p
Table_4_Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.XLSX
<p>Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuestâ„¢ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.</p
Table_5_Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.XLSX
<p>Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuestâ„¢ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.</p
Table_2_Proteomic and Bioinformatic Studies for the Characterization of Response to Pemetrexed in Platinum Drug Resistant Ovarian Cancer.XLSX
<p>Proteomics and bioinformatics are a useful combined technology for the characterization of protein expression level and modulation associated with the response to a drug and with its mechanism of action. The folate pathway represents an important target in the anticancer drugs therapy. In the present study, a discovery proteomics approach was applied to tissue samples collected from ovarian cancer patients who relapsed after the first-line carboplatin-based chemotherapy and were treated with pemetrexed (PMX), a known folate pathway targeting drug. The aim of the work is to identify the proteomic profile that can be associated to the response to the PMX treatment in pre-treatement tissue. Statistical metrics of the experimental Mass Spectrometry (MS) data were combined with a knowledge-based approach that included bioinformatics and a literature review through ProteinQuestâ„¢ tool, to design a protein set of reference (PSR). The PSR provides feedback for the consistency of MS proteomic data because it includes known validated proteins. A panel of 24 proteins with levels that were significantly different in pre-treatment samples of patients who responded to the therapy vs. the non-responder ones, was identified. The differences of the identified proteins were explained for the patients with different outcomes and the known PMX targets were further validated. The protein panel herein identified is ready for further validation in retrospective clinical trials using a targeted proteomic approach. This study may have a general relevant impact on biomarker application for cancer patients therapy selection.</p