Plasma Proteome Signature to Predict the Outcome of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Abstract

The plasma proteome of 51 non-metastatic breast cancer patients receiving neoadjuvant chemotherapy (NCT) was prospectively analyzed by high-resolution mass spectrometry coupled with nano-flow liquid chromatography using blood drawn at the time of diagnosis. Plasma proteins were identified as potential biomarkers, and their correlation with clinicopathological variables and survival outcomes was analyzed. Of 51 patients, 20 (39.2%) were HR+/HER2-, five (9.8%) were HR+/HER2+, five (9.8%) were HER2+, and 21 (41.2%) were triple-negative subtype. During a median follow-up of 52.0 months, there were 15 relapses (29.4%) and eight deaths (15.7%). Four potential biomarkers were identified among differentially expressed proteins: APOC3 had higher plasma concentrations in the pathological complete response (pCR) group, whereas MBL2, ENG, and P4HB were higher in the non-pCR group. Proteins statistically significantly associated with survival and capable of differentiating low- and high-risk groups were MBL2 and P4HB for disease-free survival, P4HB for overall survival, and MBL2 for distant metastasis-free survival (DMFS). In the multivariate analysis, only MBL2 was a consistent risk factor for DMFS (HR: 9.65, 95% CI 2.10–44.31). The results demonstrate that the proteomes from non-invasive sampling correlate with pCR and survival in breast cancer patients receiving NCT. Further investigation may clarify the role of these proteins in predicting prognosis and thus their therapeutic potential for the prevention of recurrence.

Quantitative Plasma Proteomics to Identify Candidate Biomarkers of Relapse in Pediatric/Adolescent Hodgkin Lymphoma

“…To date LC-MS-based quantitative proteomics analytical workflow allowed to discover several novel potential cancer biomarkers in serum/plasma for clinical application (reviewed by [ 15 ]): for instance, recently, altered protein abundances were found in non-Hodgkin lymphoma, infected or not by human immunodeficiency virus, (i.e., C1Q and B2M) [ 34 ]; predicted the outcome of breast cancer patients receiving neodiuvant chemotherapy (APOC3, MBL2, ENG and P4HB) [ 35 ] or associated with high risk of ovarian cancer in BRCA1/2 carriers (SPARC and THBS1) [ 20 ].…”

Endoplasmic Reticulum Stress-Regulated Chaperones as a Serum Biomarker Panel for Parkinson’s Disease

“…We searched through the list of proteins to identify chaperones. From the list of proteins with KDEL-like motif [ 29 , 30 ], we selected chaperones PDIA1, PDIA3, GRP78, calreticulin, MANF, and CDNF, because they were previously reported to (1) be upregulated in brain tissues of PD patients [ 7 , 9 , 11 , 23 – 28 ], (2) exhibit altered secretion from cells upon ER stress [ 13 , 57 – 59 ], and (3) have been detected in blood/CSF [ 33 – 36 , 60 , 61 ]. From the list of secreted chaperones, only the localization of clusterin and ERdj3 have been reported to be altered upon ER stress [ 32 , 44 ].…”

Recent Contributions of Mass Spectrometry-Based “Omics” in the Studies of Breast Cancer

“…DDA in BC proteomic and metabolomic research is used for identifying and characterizing specific molecular targets. DDA approaches have been used to analyze breast cancer cell lines or tumor tissues to identify differentially expressed proteins associated with tumor development, progression, or response to treatment. ,, DDA has also been utilized to discover potential biomarkers for breast cancer diagnosis , or prognosis by comparing proteomic profiles between cancerous and noncancerous tissues. , …”

“…Levels of these proteins were related to survival and capable of differentiating between the low-and high-risk groups. 43 Recent studies suggest the presence of immune-related long noncoding RNAs (lncRNAs) in BRCA patients. Fonseca-Montanõ identified LINC00426 in PAM50 BRCA subtypes from two clinically independent cohorts (BRCA-TCGA and GEO-GSE96058 data sets).…”

“…Numerous studies that attempted to derive various biomarkers are integrated under different sections of the review. Such publications of biomarkers are discussed which include proteome markers of drug resistance, identifiers of radiotherapy response, metabolic tissue markers for disease for screening and diagnosis, phosphoproteome-based signaling cascade identifiers for an aggressive disease type, biomarkers from archival samples for prediction of overall survival, protein markers of benign mammogram findings, androgen receptors as diagnosis markers, serum metabolomic fingerprinting, novel volatile organic compounds (VOCs) in urine as biomarkers for diagnosis, , overall survival predictors and immune phenotype related biomarkers, lymph node markers to flag metastasis, interactive marginal tissue biomarkers regulating neoplasm, markers for diagnosis through rapid lipid profiling, endocrine therapy resistance identifiers like aromatase inhibitor resistance (promoted by a RNA DIO3OS), glycan-profile-based markers, specific progression markers, plasma proteome-based prognostic markers, epithelial-mesenchymal transition (EMT) markers, extracellular matrix (ECM) markers like cytokeratin-19, E-cadherin gene expression as metastasis indicators, predictive biomarkers for immunotherapy, retrospective investigation panels based on drug responses and metastasis, tumor microenvironment related target markers implicated in evasion of immunity and drug evasion strategies, extracellular vesicle-based biomarkers for expansion of liquid biopsies, drug resistance linked to tissue environment like hypoxia in BC tumors, proteome signatures of drug resistance in BC cells, biomarkers of invasive ductal carcinoma as novel phenotypes and better classifiers of disease, heterogeneity panel identifiers in subtypes, additional markers for disease subtype conforming to conventional subtypes, glycan biomarkers, and progression identifiers through the salivary proteome . Cell lines are probed for drug-resistant proteomes, and potential drug responsive proteins are identified .…”