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Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer.

Pietrowska M, Polanska J, Marczak L, Behrendt K, Nowicka E, Stobiecki M, Polanski A, Tarnawski R, Widlak P - J Transl Med (2010)

Bottom Line: On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances).Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery.On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

View Article: PubMed Central - HTML - PubMed

Affiliation: Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.

ABSTRACT

Background: The proteomics approach termed proteome pattern analysis has been shown previously to have potential in the detection and classification of breast cancer. Here we aimed to identify changes in serum proteome patterns related to therapy of breast cancer patients.

Methods: Blood samples were collected before the start of therapy, after the surgical resection of tumors and one year after the end of therapy in a group of 70 patients diagnosed at early stages of the disease. Patients were treated with surgery either independently (26) or in combination with neoadjuvant chemotherapy (5) or adjuvant radio/chemotherapy (39). The low-molecular-weight fraction of serum proteome was examined using MALDI-ToF mass spectrometry, and then changes in intensities of peptide ions registered in a mass range between 2,000 and 14,000 Da were identified and correlated with clinical data.

Results: We found that surgical resection of tumors did not have an immediate effect on the mass profiles of the serum proteome. On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances). Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery. This suggests that the observed changes reflect overall responses of the patients to the toxic effects of adjuvant radio/chemotherapy. In line with this hypothesis we detected two serum peptides (registered m/z values 2,184 and 5,403 Da) whose changes correlated significantly with the type of treatment employed (their abundances decreased after adjuvant therapy, but increased in patients treated only with surgery). On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

Conclusions: The study establishes a high potential of MALDI-ToF-based analyses for the detection of dynamic changes in the serum proteome related to therapy of breast cancer patients, which revealed the potential applicability of serum proteome patterns analyses in monitoring the toxicity of therapy.

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Related in: MedlinePlus

Assessment of differences of proteome patterns specific for serum samples collected at different time points. A - The q-values were plotted against the p-values of differences between compared samples A. B and C; each dot represents one spectral component, the red horizontal line represents a q-value cut-off equal to 0.05. B - Average differential spectra computed for each pair-wise comparison; blue arrowheads marked positions of spectral components that differentiated samples at high levels of significance (q-value < 0.05).
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Figure 1: Assessment of differences of proteome patterns specific for serum samples collected at different time points. A - The q-values were plotted against the p-values of differences between compared samples A. B and C; each dot represents one spectral component, the red horizontal line represents a q-value cut-off equal to 0.05. B - Average differential spectra computed for each pair-wise comparison; blue arrowheads marked positions of spectral components that differentiated samples at high levels of significance (q-value < 0.05).

Mentions: In the first step of analysis three pair-wise comparisons of mass spectra registered with MALDI-ToF system for samples collected before the start of therapy (sample A), after the surgical removal of tumor (samples B), and one year after the end of basic therapy (samples C) were performed for each patient to obtain individual differential spectra, and then the average differential spectra that described analyzed group of 70 patients were computed. For each of all spectral components (i.e. registered peptide ions) the significance of a difference in abundance between compared time points was characterized by its p-value and q-value; the latter one reflected significance of differences adjusted for multiple testing using the False Discovery Rate (FDR) approach. Figure 1A shows q-values plotted against p-values of such differences for each spectral component in three pair-wise analyses; a q-value equal to 0.05 was chosen here as the rigid significance cut-off level. We did not find significant differences between serum samples collected before the start of therapy and after surgery (A vs. B). In marked contrast, several spectral components showed significant changes in their abundance when we compared samples collected before the start of therapy and one year after the end of therapy (A vs. C), as well as samples collected after the surgery and one year after the end of therapy (B vs. C). Figure 1B shows location of such differentiating components marked along corresponding average differential spectra. Fourteen spectral components changed their abundance significantly between samples A and C, while 24 spectral components changed their abundance significantly between samples B and C. Importantly, the same 8 spectral components differentiated samples C from both samples A and samples B (approximate registered m/z values = 2742, 3992, 5877, 6489, 8888, 8931, 8942 and 8973 Da). When a less rigid significance cut-off level q-value equal 0.1 was considered 69 spectral components appeared to differentiate samples B and C, while only 6 spectral components differentiated samples A and B (Figure 1A). The m/z values of registered spectral components were annotated at the knowledge base EPO-KB (Empirical Proteomic Ontology Knowledge Base) [38] aiming at hypothetical identification of serum peptides (assuming their mono-protonation and allowing for a 0.5% mass accuracy limit). Such analysis allowed hypothetical annotation of 22 out of 69 components that differentiated samples B and C. Table 1 shows examples of spectral components that differentiated samples B and C. We conclude that serum proteome patterns were similar when samples collected before the start of therapy and after the surgery were compared. In marked contrast, proteome patterns of serum samples collected one year after the end of basic therapy changed when compared to both types of samples collected at earlier time points.


Mass spectrometry-based analysis of therapy-related changes in serum proteome patterns of patients with early-stage breast cancer.

Pietrowska M, Polanska J, Marczak L, Behrendt K, Nowicka E, Stobiecki M, Polanski A, Tarnawski R, Widlak P - J Transl Med (2010)

Assessment of differences of proteome patterns specific for serum samples collected at different time points. A - The q-values were plotted against the p-values of differences between compared samples A. B and C; each dot represents one spectral component, the red horizontal line represents a q-value cut-off equal to 0.05. B - Average differential spectra computed for each pair-wise comparison; blue arrowheads marked positions of spectral components that differentiated samples at high levels of significance (q-value < 0.05).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2908576&req=5

Figure 1: Assessment of differences of proteome patterns specific for serum samples collected at different time points. A - The q-values were plotted against the p-values of differences between compared samples A. B and C; each dot represents one spectral component, the red horizontal line represents a q-value cut-off equal to 0.05. B - Average differential spectra computed for each pair-wise comparison; blue arrowheads marked positions of spectral components that differentiated samples at high levels of significance (q-value < 0.05).
Mentions: In the first step of analysis three pair-wise comparisons of mass spectra registered with MALDI-ToF system for samples collected before the start of therapy (sample A), after the surgical removal of tumor (samples B), and one year after the end of basic therapy (samples C) were performed for each patient to obtain individual differential spectra, and then the average differential spectra that described analyzed group of 70 patients were computed. For each of all spectral components (i.e. registered peptide ions) the significance of a difference in abundance between compared time points was characterized by its p-value and q-value; the latter one reflected significance of differences adjusted for multiple testing using the False Discovery Rate (FDR) approach. Figure 1A shows q-values plotted against p-values of such differences for each spectral component in three pair-wise analyses; a q-value equal to 0.05 was chosen here as the rigid significance cut-off level. We did not find significant differences between serum samples collected before the start of therapy and after surgery (A vs. B). In marked contrast, several spectral components showed significant changes in their abundance when we compared samples collected before the start of therapy and one year after the end of therapy (A vs. C), as well as samples collected after the surgery and one year after the end of therapy (B vs. C). Figure 1B shows location of such differentiating components marked along corresponding average differential spectra. Fourteen spectral components changed their abundance significantly between samples A and C, while 24 spectral components changed their abundance significantly between samples B and C. Importantly, the same 8 spectral components differentiated samples C from both samples A and samples B (approximate registered m/z values = 2742, 3992, 5877, 6489, 8888, 8931, 8942 and 8973 Da). When a less rigid significance cut-off level q-value equal 0.1 was considered 69 spectral components appeared to differentiate samples B and C, while only 6 spectral components differentiated samples A and B (Figure 1A). The m/z values of registered spectral components were annotated at the knowledge base EPO-KB (Empirical Proteomic Ontology Knowledge Base) [38] aiming at hypothetical identification of serum peptides (assuming their mono-protonation and allowing for a 0.5% mass accuracy limit). Such analysis allowed hypothetical annotation of 22 out of 69 components that differentiated samples B and C. Table 1 shows examples of spectral components that differentiated samples B and C. We conclude that serum proteome patterns were similar when samples collected before the start of therapy and after the surgery were compared. In marked contrast, proteome patterns of serum samples collected one year after the end of basic therapy changed when compared to both types of samples collected at earlier time points.

Bottom Line: On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances).Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery.On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

View Article: PubMed Central - HTML - PubMed

Affiliation: Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland.

ABSTRACT

Background: The proteomics approach termed proteome pattern analysis has been shown previously to have potential in the detection and classification of breast cancer. Here we aimed to identify changes in serum proteome patterns related to therapy of breast cancer patients.

Methods: Blood samples were collected before the start of therapy, after the surgical resection of tumors and one year after the end of therapy in a group of 70 patients diagnosed at early stages of the disease. Patients were treated with surgery either independently (26) or in combination with neoadjuvant chemotherapy (5) or adjuvant radio/chemotherapy (39). The low-molecular-weight fraction of serum proteome was examined using MALDI-ToF mass spectrometry, and then changes in intensities of peptide ions registered in a mass range between 2,000 and 14,000 Da were identified and correlated with clinical data.

Results: We found that surgical resection of tumors did not have an immediate effect on the mass profiles of the serum proteome. On the other hand, significant long-term effects were observed in serum proteome patterns one year after the end of basic treatment (we found that about 20 peptides exhibited significant changes in their abundances). Moreover, the significant differences were found primarily in the subgroup of patients treated with adjuvant therapy, but not in the subgroup subjected only to surgery. This suggests that the observed changes reflect overall responses of the patients to the toxic effects of adjuvant radio/chemotherapy. In line with this hypothesis we detected two serum peptides (registered m/z values 2,184 and 5,403 Da) whose changes correlated significantly with the type of treatment employed (their abundances decreased after adjuvant therapy, but increased in patients treated only with surgery). On the other hand, no significant correlation was found between changes in the abundance of any spectral component or clinical features of patients, including staging and grading of tumors.

Conclusions: The study establishes a high potential of MALDI-ToF-based analyses for the detection of dynamic changes in the serum proteome related to therapy of breast cancer patients, which revealed the potential applicability of serum proteome patterns analyses in monitoring the toxicity of therapy.

Show MeSH
Related in: MedlinePlus