Detection of breast cancer biomarkers in nipple aspirate fluid by SELDI-TOF and their identification by combined liquid chromatography-tandem mass spectrometry

He, Jianbo; Gornbein, Jeffrey; Shen, Dejun; Lu, Ming; Rovai, Leonor E.; Shau, Hungyi; Katz, John; Whitelegge, Julian P.; Faull, Kym F.; Chang, Helena R.

doi:10.3892/ijo.30.1.145

Cited by 22 publications

(22 citation statements)

References 20 publications

(36 reference statements)

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“…He et al analyzed NAF samples from healthy individuals and women with breast cancer by using SELDI-TOF-MS (14 ). These investigators identified 16 proteins that differed between samples from cancer patients and individuals.…”

Section: Comparison Of the Identified Proteins With Other Reported Prmentioning

confidence: 99%

Nipple Aspirate Fluid Proteome of Healthy Females and Patients with Breast Cancer

et al. 2010

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Section: Comparison Of the Identified Proteins With Other Reported Prmentioning

confidence: 99%

Nipple Aspirate Fluid Proteome of Healthy Females and Patients with Breast Cancer

et al. 2010

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“…Standardized protocols were used for tissue collection, storage and sample preparation to minimize variability between samples. We have also previously demonstrated that the SELDI spectra of the same specimens are relatively stable and reproducible, with virtually identical spectra produced from the same sample upon re-analysis several days later (36). Since the SELDI-TOF technology enables a straightforward analysis of protein biomarkers, it provides a means to rapidly evaluate intact protein patterns in a large number of specimens.…”

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confidence: 99%

Tumor proteomic profiling predicts the susceptibility of breast cancer to chemotherapy

Shen²,

Chung³

et al. 2009

Int J Oncol

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Abstract. Chemotherapy is often used for breast cancer treatment, but individual outcome varies widely. We hypothesized that tumor proteomic profiles obtained prior to chemotherapy may predict the individual tumor response to treatment. The goal of our study was to explore feasibility of using proteomic profiling to preselect patients for an effective chemotherapeutic regimen. Tumors from 52 patients with T2-T4 breast cancer were prospectively collected before neoadjuvant chemotherapy, and were analyzed using surface-enhanced laser desorption ionization/time of flight (SELDI) mass spectrometry. Mass spectral profiles were obtained from tumors with various sensitivities to chemotherapy. Both nonsupervised hierarchical clustering and supervised neural network-based classification approaches were employed to compare the profiles. The first two thirds of the enrolled cases (35) were allocated to a training set to select peaks characteristic of resistant tumors. The candidate peaks were used to develop a predicting rule to evaluate the remaining 17 specimens in the validation set. In the training set, the most prominent differences were found between drug resistant and drug susceptible tumors by non-supervised hierarchical clustering. In the validation set, the supervised classification with the K nearest neighbor (KNN) model correctly classified most tumor responses with an accuracy rate of 92.3% [100% of resistant tumors (4/4), and 84.6% of the tumors with favorable response (11/13)]. In the entire group, a single peak at m/z 16,906 correctly separated 88.9% of the tumors with pathologically complete response, and 91.7% of the resistant tumors. The data suggest that breast cancer protein biomarkers may be used to pre-select patients for optimal chemotherapeutic treatment. IntroductionPreoperative chemotherapy (neoadjuvant chemotherapy) has gained wide acceptance for treating patients with locally advanced breast cancer. In these patients the most acknowledged benefit is the reduction in tumor size allowing either a complete resection of an otherwise unresectable tumor or breast conservation surgery in some patients with large tumors. Furthermore, tumor response to neoadjuvant treatment has been shown to be prognostically significant. Other less proven benefits of neoadjuvant chemotherapy include eradication of microscopic metastases and improved survivals (1-3). Postoperative adjuvant chemotherapy has been used successfully to improve survival rates in patients with early stage breast cancer (4). Although many patients benefit from chemotherapy, some fail to respond. However, the success of chemotherapy, whether pre-or post-operative, in any given individual cannot be predicted. The uncertain benefit for a particular individual, as well as significant toxicity of chemotherapy in all patients, calls for development of methods to select the right patients for treatment and spare those who will not benefit. ); PAM, prediction analysis with microarrays; pCR, pathological complete response, no residual cancer found at ...

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“…Although several discriminating protein peaks were detected when comparing equal volumes of NAF or DLF from breast cancer patients and healthy controls by SELDI-TOF MS [62][63][64][65], large variations in the spectra between different samples within one diagnostic group were observed [63][64][65]. Likely originating from the wide protein content range of NAF (1-90 mg/ml [62]), further studies have normalised the protein content prior to analysis.…”

Section: Protein Profiling Of Serum and Plasmamentioning

confidence: 99%

“…Likely originating from the wide protein content range of NAF (1-90 mg/ml [62]), further studies have normalised the protein content prior to analysis. Nonetheless, despite normalisation, Sauter et al [66,67] could not confirm the initially observed diagnostic potential of three SELDI-TOF MS peaks (identified as hemoglobin beta chain isoforms) in a second, larger, study population.…”

Section: Protein Profiling Of Serum and Plasmamentioning

confidence: 99%

“…While this fluid exits each breast through six to nine orifices at the nipple, it can be collected by either of two noninvasive methods; aspiration or ductal lavage. Both nipple aspirate fluid (NAF) and ductal lavage fluid (DLF) are traditionally used for cytological assessment [62,63], but their vicinity to the breast epithelium renders them valuable matrices for diagnostic protein profiling studies as well.…”

Section: Protein Profiling Of Serum and Plasmamentioning

confidence: 99%

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Clinical proteomics in breast cancer: a review

Gast

Schellens

Beijnen

2008

Breast Cancer Res Treat

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Breast cancer imposes a significant healthcare burden on women worldwide. Early detection is of paramount importance in reducing mortality, yet the diagnosis of breast cancer is hampered by the lack of an adequate detection method. In addition, better breast cancer prognostication may improve selection of patients eligible for adjuvant therapy. Hence, new markers for early diagnosis, accurate prognosis and prediction of response to treatment are warranted to improve breast cancer care. Since proteomics can bridge the gap between the genetic alterations underlying cancer and cellular physiology, much is expected from proteome analyses for the detection of better protein biomarkers. Recent technical advances in mass spectrometry, such as matrix-assisted laser desorption/ ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and its variant surface-enhanced laser desorption/ ionisation (SELDI-) TOF MS, have enabled highthroughput proteome analysis. In the current review, we give a comprehensive overview of the results of expression proteomics (i.e. protein profiling) research performed in breast cancer using these two platforms. Many protein peaks have been reported to bear significant diagnostic, prognostic or predictive value, however, only few candidate markers have been structurally identified yet. In addition, although of pivotal importance in preventing overfitting of data and systematic bias by pre-analytical parameters, validation of biomarker candidates by other, quantitative, methods and/or in new populations is very limited. Moreover, none of the identified candidate biomarkers has been investigated for their utility as breast cancer markers in large, prospective, clinical settings. As such, the candidate biomarkers discussed in this overview have not been validated sufficiently to be used for clinical patient care. Nonetheless, regarding the promising results up to now, MALDI-and SELDI-TOF MS protein profiling studies could eventually fulfil the great promise that protein biomarkers have for improving cancer patient outcome, provided that these studies are performed with adequate statistical power and analytical rigour.

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Detection of breast cancer biomarkers in nipple aspirate fluid by SELDI-TOF and their identification by combined liquid chromatography-tandem mass spectrometry

Cited by 22 publications

References 20 publications

Nipple Aspirate Fluid Proteome of Healthy Females and Patients with Breast Cancer

Nipple Aspirate Fluid Proteome of Healthy Females and Patients with Breast Cancer

Tumor proteomic profiling predicts the susceptibility of breast cancer to chemotherapy

Clinical proteomics in breast cancer: a review

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