Identification of a beta-casein-like peptide in breast nipple aspirate fluid that is associated with breast cancer

Nipple Aspirate Fluid at a Glance

Simple Summary

Nipple aspirate fluid (NAF) is a promising source of markers for detection of breast cancer. NAF can be acquired via the nipple by aspiration using a suction device, which is well tolerated by women. Future possible applications of biomarkers for breast cancer derived from NAF could be (1) as a detection tool to identify the initiation of the cancer development process, (2) as an additional tool next to imaging (mammography and breast magnetic resonance imaging) or (3) as a replacement tool for when imaging is not advisable for women, such as during pregnancy and breastfeeding. With this paper, we present a narrative review and perspectives of NAF research at a glance.

Abstract

Nipple aspirate fluid (NAF) is an intraductal mammary fluid that, because of its close proximity to and origin from the tissue from which breast cancer originates, is a promising source of biomarkers for early breast cancer detection. NAF can be non-invasively acquired via the nipple by aspiration using a suction device; using oxytocin nasal spray helps increase yield and tolerability. The aspiration procedure is generally experienced as more tolerable than the currently used breast imaging techniques mammography and breast magnetic resonance imaging. Future applications of NAF-derived biomarkers include their use as a tool in the detection of breast carcinogenesis at its earliest stage (before a tumor mass can be seen by imaging), or as a supporting diagnostic tool for imaging, such as when imaging is less reliable (to rule out false positives from imaging) or when imaging is not advisable (such as during pregnancy and breastfeeding). Ongoing clinical studies using NAF samples will likely shed light on NAF’s content and clinical potential. Here, we present a narrative review and perspectives of NAF research at a glance.

Proteomics and its applications in breast cancer

Breast cancer is an individually unique, multi-faceted and chameleonic disease, an eternal challenge for the new era of high-integrated precision diagnostic and personalized oncomedicine. Besides traditional single-omics fields (such as genomics, epigenomics, transcriptomics and metabolomics) and multi-omics contributions (proteogenomics, proteotranscriptomics or reproductomics), several new "-omics" approaches and exciting proteomics subfields are contributing to basic and advanced understanding of these "multiple diseases termed breast cancer": phenomics/cellomics, connectomics and interactomics, secretomics, matrisomics, exosomics, angiomics, chaperomics and epichaperomics, phosphoproteomics, ubiquitinomics, metalloproteomics, terminomics, degradomics and metadegradomics, adhesomics, stressomics, microbiomics, immunomics, salivaomics, materiomics and other biomics. Throughout the extremely complex neoplastic process, a Breast Cancer Cell Continuum Concept (BCCCC) has been modeled in this review as a spatio-temporal and holistic approach, as long as the breast cancer represents a complex cascade comprising successively integrated populations of heterogeneous tumor and cancer-associated cells, that reflect the carcinoma's progression from a "driving mutation" and formation of the breast primary tumor, toward the distant secondary tumors in different tissues and organs, via circulating tumor cell populations. This BCCCC is widely sustained by a Breast Cancer Proteomic Continuum Concept (BCPCC), where each phenotype of neoplastic and tumor-associated cells is characterized by a changing and adaptive proteomic profile detected in solid and liquid minimal invasive biopsies by complex proteomics approaches. Such a profile is created, beginning with the proteomic landscape of different neoplastic cell populations and cancer-associated cells, followed by subsequent analysis of protein biomarkers involved in epithelial-mesenchymal transition and intravasation, circulating tumor cell proteomics, and, finally, by protein biomarkers that highlight the extravasation and distant metastatic invasion. Proteomics technologies are producing important data in breast cancer diagnostic, prognostic, and predictive biomarkers discovery and validation, are detecting genetic aberrations at the proteome level, describing functional and regulatory pathways and emphasizing specific protein and peptide profiles in human tissues, biological fluids, cell lines and animal models. Also, proteomics can identify different breast cancer subtypes and specific protein and proteoform expression, can assess the efficacy of cancer therapies at cellular and tissular level and can even identify new therapeutic target proteins in clinical studies.

[Preliminary study of MALDI-TOF mass spectrometry-based screening of patients with the NSCLC serum-specific peptides]

背景与目的

早期诊断是提高肺癌生存率的关键，传统的肺癌诊断技术仍存在一定局限性。鉴于近年来以质谱为核心技术的肿瘤蛋白组学在癌症诊断方面的初步研究，本研究探索性应用基质辅助激光解析电离飞行时间质谱（matrix assisted laser desorption ionization-time of flight-mass spectrometry, MALDI-TOF-MS）分析非小细胞肺癌（non-small cell lung cancer, NSCLC）患者和健康人群的血清差异多肽，以建立NSCLC的血清分类模型。

方法

将年龄和性别匹配的133例NSCLC患者和132例健康者血清标本按照3:1的比例随机分为两组：训练组由100例NSCLC患者和100例健康者血清标本组成，用以建立分类模型；测试组由33例NSCLC患者和32例健康者血清标本组成，用以验证模型。采用铜离子鳌合纳米磁珠提取血清多肽、MALDI-TOF-MS技术检测得到质谱图。ClinProTools^TM统计软件分析训练组NSCLC患者与健康者之间的多肽图谱，从中筛选出一组差异多肽并建立分类模型，最后用测试组对模型进行盲样验证。

结果

在训练组中观察到血清质荷比（m/z）在1, 000 Da-10, 000 Da范围内有131个差异多肽信号峰，在此范围内共得到14个有统计学意义的差异多肽峰（P < 0.000, 001; AUC≥0.9），其中NSCLC患者与健康者相比，表达上调的多肽有2个，表达下调的有12个，由统计软件筛选出3个多肽峰（7, 478.59 Da、2, 271.44 Da、4, 468.38 Da）建立分类模型，然后对测试组进行验证，其盲样验证敏感性100%，特异性96.9%，准确率98.5%。

结论

本组研究显示NSCLC患者与健康人群的血清多肽存在差异，应用MALDI-TOF-MS技术可建立NSCLC的血清多肽分类模型且小规模验证具有较好的敏感性和特异性，希望大规模验证模型，并与传统诊断方法对照或结合，进而尝试建立一种新的NSCLC早期诊断模式。

Diagnosis of gallbladder cancer using matrix-assisted laser desorption/ionization time-of-flight profiling

Proteomic fingerprint technology combining magnetic beads with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was used to profile and compare the serum proteins from 45 patients with gallbladder cancer and 50 healthy blood donors. The proteomic patterns were identified; the tree model of biomarkers was constructed and evaluated using the Biomarker Patterns Software. The model tree was constructed based on the 3 biomarkers (5913 Da, 6181 Da and 13,752 Da), which generated excellent separation between the gallbladder cancer and control groups. The sensitivity was 86.7% and the specificity was 93.3%. The blind test data showed a sensitivity of 80% and a specificity of 90%. Taken together, our studies suggested that biomarkers for gallbladder cancer could be discovered in serum by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with the use of magnetic beads. The pattern of combined markers would provide a powerful and reliable diagnostic method for gallbladder cancer with high sensitivity and specificity.

Protein biomarkers for the early detection of breast cancer

Advances in breast cancer control will be greatly aided by early detection so as to diagnose and treat breast cancer in its preinvasive state prior to metastasis. For breast cancer, the second leading cause of cancer-related death among women in the United States, early detection does allow for increased treatment options, including surgical resection, with a corresponding better patient response. Unfortunately, however, many patients' tumors are diagnosed following metastasis, thus making it more difficult to successfully treat the malignancy. There are, at present, no existing validated plasma/serum biomarkers for breast cancer. Only a few biomarkers (such as HER-2/neu, estrogen receptor, and progesterone receptor) have utility for diagnosis and prognosis. Thus, there is a great need for new biomarkers for breast cancer. This paper will focus on the identification of new serum protein biomarkers with utility for the early detection of breast cancer.

Advances in proximal fluid proteomics for disease biomarker discovery

Although serum/plasma has been the preferred source for identification of disease biomarkers, these efforts have been met with little success, in large part due the relatively small number of highly abundant proteins that render the reliable detection of low abundant disease-related proteins challenging due to the expansive dynamic range of concentration of proteins in this sample. Proximal fluid, the fluid derived from the extracellular milieu of tissues, contains a large repertoire of shed and secreted proteins that are likely to be present at higher concentrations relative to plasma/serum. It is hypothesized that many, if not all, proximal fluid proteins exchange with peripheral circulation, which has provided significant motivation for utilizing proximal fluids as a primary sample source for protein biomarker discovery. The present review highlights recent advances in proximal fluid proteomics, including the various protocols utilized to harvest proximal fluids along with detailing the results from mass spectrometry- and antibody-based analyses.