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

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p

Ratio of proliferation markers and HSP90 gene expression as a predictor of pathological complete response in breast cancer neoadjuvant chemotherapy

Introduction. Prediction of response to preoperative breast cancer chemotherapy may offer a substantial optimization of medical management of this disease. The most efficient prediction would be done a priori, before the start of chemotherapy and based on the biological features of patient and tumor. Numerous markers have been proposed but none of them has been applied as a routine. The role of MKI67 and HSP90 expression has been recently suggested to predict treatment sensitivity in HER2-positive breast cancer. The aim of this study was to validate the utility of proliferation based markers (MKI67 and CDK1) and heat shock proteins (namely HSP90) to predict response to chemotherapy in cohort of breast cancer patients treated preoperatively. Material and methods. Ninety-three patients with breast cancer, all females, mean age 42.2 years, among them 32% T1-T2 patients, 49% T3 patients and 13% with T4 tumor stage, 27% N0, 42% N1, 16% N2, 15% N3 were subjected to initial chemotherapy. The majority of patients (86%) received anthracycline and taxane chemotherapy. Among the patients there were 9 individuals with metastatic disease (M1) at initial presentation, and 11 patients were not treated surgically after initial chemotherapy (no sufficient disease response). From 82 patients operated on, 20 patients (24%) showed pathological complete response (pCR), while in 62 patients there was no pCR. 42% of patients were hormone-sensitive HER2-negative, 20% hormone-sensitive HER2-positive, 9% only HER-positive and 29% with triple negative breast cancer. Four gene transcripts (MKI67, cyclin-dependent kinase 1 [CDK1], heat shock proteins HSP90AA1 and HSP- 90AB1) were analyzed in total RNA isolated from single core obtained during preoperative core needle biopsy by quantitative real-time PCR with fluorescent probes (Universal Probe Library, Roche). Results were normalized to the panel of reference genes. Results. There were no statistically significant differences in MKI67 and CDK1 expression between pCR and no pCR groups (p = 0.099 and 0.35, respectively), although the median expression of both genes was slightly higher in pCR group. In contrast, both HSP90AA1 and HSP90AB1 transcripts showed decreased expression in pCR group (medians 0.77 and 0.55) when compared to no p CR group (median 0.86 and 0.73), statistically significant for HSP90AA1 (p = 0.031) and of borderline significance for HSP90AB1 (p = 0.054). The most significant predictor of pCR was the ratio of CDK1 transcript to HSP90AA transcript. This ratio was significantly higher in CR group (median 0.99) than in no CR group (median 0.68, p = 0.0023), and showed a potential diagnostic utility (area under receiver operating characteristic [ROC] curve 0.72). Conclusions. HSP90AA1 and AB1 genes exhibit low expression in breast cancers highly sensitive to chemotherapy and may indicate the patients with higher probability of pathological complete response. The ratio of HSP90AA1 to proliferation-related markers (CDK1 or MKI67) may be even better predictor of pCR chance, with higher expression of proliferation genes and lower stress response in patients sensitive to chemotherapy

Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer

<p>Abstract</p> <p>Background</p> <p>Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry.</p> <p>Methods</p> <p>Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women). Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other high-molecular-weight serum proteins. Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves.</p> <p>Results</p> <p>We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients. The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity. Spectral components (i.e., protein ions) that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity). Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression. In addition, we observed a significantly (p = 0.0003) increased level of osteopontin in blood of the group of cancer patients studied (however, the plasma level of osteopontin classified cancer samples with 88% sensitivity but only 28% specificity).</p> <p>Conclusion</p> <p>MALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls. Importantly, a classifier built on MS-based serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays.</p