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Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

ABSTRACT: Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

SUBMITTER: Zhou JY

PROVIDER: S-EPMC5850958 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Zhou Jian-Ying JY Chen Lijun L Zhang Bai B Tian Yuan Y Liu Tao T Thomas Stefani N SN Chen Li L Schnaubelt Michael M Boja Emily E Hiltke Tara T Kinsinger Christopher R CR Rodriguez Henry H Davies Sherri R SR Li Shunqiang S Snider Jacqueline E JE Erdmann-Gilmore Petra P Tabb David L DL Townsend R Reid RR Ellis Matthew J MJ Rodland Karin D KD Smith Richard D RD Carr Steven A SA Zhang Zhen Z Chan Daniel W DW Zhang Hui H

Journal of proteome research 20171116 12

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cance ...[more]

PMID: 29124938

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Project description:BACKGROUND: Attempts to reduce morbidity and mortality in breast cancer is based on efforts to identify novel biomarkers to support prognosis and therapeutic choices. The present study has focussed on S100 proteins as a potentially promising group of markers in cancer development and progression. One reason of interest in this family of proteins is because the majority of the S100 genes are clustered on a region of human chromosome 1q21 that is prone to genomic rearrangements. Moreover, there is increasing evidence that S100 proteins are often up-regulated in many cancers, including breast, and this is frequently associated with tumour progression. METHODS: Samples of breast cancer tissues were obtained during surgical intervention, according to the bioethical recommendations, and cryo-preserved until used. Tissue extracts were submitted to proteomic preparations for 2D-IPG. Protein identification was performed by N-terminal sequencing and/or peptide mass finger printing. RESULTS: The majority of the detected S100 proteins were absent, or present at very low levels, in the non-tumoral tissues adjacent to the primary tumor. This finding strengthens the role of S100 proteins as putative biomarkers. The proteomic screening of 100 cryo-preserved breast cancer tissues showed that some proteins were ubiquitously expressed in almost all patients while others appeared more sporadic. Most, if not all, of the detected S100 members appeared reciprocally correlated. Finally, from the perspective of biomarkers establishment, a promising finding was the observation that patients which developed distant metastases after a three year follow-up showed a general tendency of higher S100 protein expression, compared to the disease-free group. CONCLUSIONS: This article reports for the first time the comparative proteomic screening of several S100 protein members among a large group of breast cancer patients. The results obtained strongly support the hypothesis that a significant deregulation of multiple S100 protein members is associated with breast cancer progression, and suggest that these proteins might act as potential prognostic factors for patient stratification. We propose that this may offer a significant contribution to the knowledge and clinical applications of the S100 protein family to breast cancer.

Project description:ImportanceTreatment options for early breast cancer include breast-conserving surgery with radiation therapy (RT) or mastectomy and breast reconstruction without RT. Despite marked differences in these treatment strategies, little is known with regard to their association with long-term quality of life (QOL).ObjectiveTo evaluate the association of treatment with breast-conserving surgery with RT vs mastectomy and reconstruction without RT with long-term QOL.Design, setting, and participantsThis comparative effectiveness research study used data from the Texas Cancer Registry for women diagnosed with stage 0-II breast cancer and treated with breast-conserving surgery or mastectomy and reconstruction between 2006 and 2008. The study sample was mailed a survey between March 2017 and April 2018. Data were analyzed from August 1, 2018 to October 15, 2021.ExposuresBreast-conserving surgery with RT or mastectomy and reconstruction without RT.Main outcomes and measuresThe primary outcome was satisfaction with breasts, measured with the BREAST-Q patient-reported outcome measure. Secondary outcomes included BREAST-Q physical well-being, psychosocial well-being, and sexual well-being; health utility, measured using the EuroQol Health-Related Quality of Life 5-Dimension, 3-Level questionnaire; and local therapy decisional regret. Multivariable linear regression models with weights for treatment, age, and race and ethnicity tested associations of the exposure with outcomes.ResultsOf 647 patients who responded to the survey (40.0%; 356 had undergone breast-conserving surgery, and 291 had undergone mastectomy and reconstruction), 551 (85.2%) confirmed treatment with breast-conserving surgery with RT (n = 315) or mastectomy and reconstruction without RT (n = 236). Among the 647 respondents, the median age was 53 years (range, 23-85 years) and the median time from diagnosis to survey was 10.3 years (range, 8.4-12.5 years). Multivariable analysis showed no significant difference between breast-conserving surgery with RT (referent) and mastectomy and reconstruction without RT in satisfaction with breasts (effect size, 2.71; 95% CI, -2.45 to 7.88; P = .30) or physical well-being (effect size, -1.80; 95% CI, -5.65 to 2.05; P = .36). In contrast, psychosocial well-being (effect size, -8.61; 95% CI, -13.26 to -3.95; P < .001) and sexual well-being (effect size, -10.68; 95% CI, -16.60 to -4.76; P < .001) were significantly worse with mastectomy and reconstruction without RT. Health utility (effect size, -0.003; 95% CI, -0.03 to 0.03; P = .83) and decisional regret (effect size, 1.32; 95% CI, -3.77 to 6.40; P = .61) did not differ by treatment group.Conclusions and relevanceThe findings support equivalence of breast-conserving surgery with RT and mastectomy and reconstruction without RT with regard to breast satisfaction and physical well-being. However, breast-conserving surgery with RT was associated with clinically meaningful improvements in psychosocial and sexual well-being. These findings may help inform preference-sensitive decision-making for women with early-stage breast cancer.

Dataset Information

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

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Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

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