Serum proteomics analysis of candidate predictive biomarker panel for the diagnosis of trastuzumab-based therapy resistant breast cancer

Human Blood Serum Counteracts EGFR/HER2-Targeted Drug Lapatinib Impact on Squamous Carcinoma SK-BR-3 Cell Growth and Gene Expression

Lapatinib is a targeted therapeutic inhibiting HER2 and EGFR proteins. It is used for the therapy of HER2-positive breast cancer, although not all the patients respond to it. Using human blood serum samples from 14 female donors (separately taken or combined), we found that human blood serum dramatically abolishes the lapatinib-mediated inhibition of growth of the human breast squamous carcinoma SK-BR-3 cell line. This antagonism between lapatinib and human serum was associated with cancelation of the drug induced G1/S cell cycle transition arrest. RNA sequencing revealed 308 differentially expressed genes in the presence of lapatinib. Remarkably, when combined with lapatinib, human blood serum showed the capacity of restoring both the rate of cell growth, and the expression of 96.1% of the genes expression of which were altered by the lapatinib treatment alone. Co-administration of EGF with lapatinib also restores the cell growth and cancels alteration of expression of 95.8% of the genes specific to lapatinib treatment of SK-BR-3 cells. Differential gene expression analysis also showed that in the presence of human serum or EGF, lapatinib was unable to inhibit the Toll-Like Receptor signaling pathway and alter expression of genes linked to the Gene Ontology term of Focal adhesion.

Proteomic analysis of plasma proteins from patients with cardiac rupture after acute myocardial infarction using TMT-based quantitative proteomics approach

BACKGROUND

Cardiac rupture (CR) is a rare but catastrophic mechanical complication of acute myocardial infarction (AMI) that seriously threatens human health. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of CR has yet to be elucidated.

METHODS

In the present study, a quantitative approach with tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry was used to characterize the differential protein expression profiles of patients with CR. Plasma samples were collected from patients with CR (n = 37), patients with AMI (n = 47), and healthy controls (n = 47). Candidate proteins were selected for validation by multiple reaction monitoring (MRM) and enzyme-linked immunosorbent assay (ELISA).

RESULTS

In total, 1208 proteins were quantified and 958 differentially expressed proteins (DEPs) were identified. The difference in the expression levels of the DEPs was more noticeable between the CR and Con groups than between the AMI and Con groups. Bioinformatics analysis showed most of the DEPs to be involved in numerous crucial biological processes and signaling pathways, such as RNA transport, ribosome, proteasome, and protein processing in the endoplasmic reticulum, as well as necroptosis and leukocyte transendothelial migration, which might play essential roles in the complex pathological processes associated with CR. MRM analysis confirmed the accuracy of the proteomic analysis results. Four proteins i.e., C-reactive protein (CRP), heat shock protein beta-1 (HSPB1), vinculin (VINC) and growth/differentiation factor 15 (GDF15), were further validated via ELISA. By receiver operating characteristic (ROC) analysis, combinations of these four proteins distinguished CR patients from AMI patients with a high area under the curve (AUC) value (0.895, 95% CI, 0.802-0.988, p < 0.001).

CONCLUSIONS

Our study highlights the value of comprehensive proteomic characterization for identifying plasma proteome changes in patients with CR. This pilot study could serve as a valid foundation and initiation point for elucidation of the mechanisms of CR, which might aid in identifying effective diagnostic biomarkers in the future.

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

Breast cancer (BC) is one of the most heterogeneous groups of cancer. As every biotype of BC is unique and presents a particular "omic" signature, they are increasingly characterized nowadays with novel mass spectrometry (MS) strategies. BC therapeutic approaches are primarily based on the two features of human epidermal growth factor receptor 2 (HER2) and estrogen receptor (ER) positivity. Various strategic MS implementations are reported in studies of BC also involving data independent acquisitions (DIAs) of MS which report novel differential proteomic, lipidomic, proteogenomic, phosphoproteomic, and metabolomic characterizations associated with the disease and its therapeutics. Recently many "omic" studies have aimed to identify distinct subsidiary biotypes for diagnosis, prognosis, and targets of treatment. Along with these, drug-induced-resistance phenotypes are characterized by "omic" changes. These identifying aspects of the disease may influence treatment outcomes in the near future. Drug quantifications and characterizations are also done regularly and have implications in therapeutic monitoring and in drug efficacy assessments. We report these studies, mentioning their implications toward the understanding of BC. We briefly provide the MS instrumentation principles that are adopted in such studies as an overview with a brief outlook on DIA-MS strategies. In all of these, we have chosen a model cancer for its revelations through MS-based "omics".

Predictive value of serum proteomic biomarkers for noise-induced hearing loss

Early detection of noise-induced hearing loss (NIHL) in patients with long-term noise exposure is vital for improving public health and reducing social burden. However, at present, the diagnosis of NIHL mainly depends on audiometric testing, and the primary test is pure-tone audiometry. Moreover, testing requires professional operators and complex equipment; thus, NIHL is often diagnosed at a later disease stage. Using a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic approach, we identified 9 differentially expressed proteins (DEPs), namely, 6 upregulated serum proteins and 3 downregulated serum proteins, in samples from 50 ground crew personnel working at an air force station. Then, according to the results, we predicted that caldesmon (CALD1), myocilin (MYOC), zyxin (ZYX), creatine kinase M-type (CKM), insulin-like growth factor-binding protein 2 (IGFBP2), complement factor H-related protein 4 (CFHR4), prenylcysteine oxidase 1 (PCYOX1), heat shock cognate 71 kDa protein (HSPA8), and immunoglobulin lambda variable 3-21 (IGLV3-21) were associated with NIHL. We selected these DEPs as variables to perform logistic regression. Finally, a logistic regression model was constructed based on IGFBP2, ZYX, CKM, and CFHR4. The area under the curve was 0.894 (95% CI = 0.812 to 0.977). These findings suggested that IGFBP2, ZYX, CKM, and CFHR4 in serum are differentially expressed in NIHL patients and have the potential to be biomarkers for predicting the risk for NIHL. Further experiments in mice showed that ZYX and IGFBP2 in the cochlear were increased after noise exposure. ZYX and IGFBP2 may be involved in the occurrence and development of NIHL.

Microcystin-LR-Induced Interaction between M2 Tumor-Associated Macrophage and Colorectal Cancer Cell Promotes Colorectal Cancer Cell Migration through Regulating the Expression of TGF-β1 and CST3

Microcystin-LR (MC-LR) is a toxic secondary metabolite produced by cyanobacteria that has been demonstrated to promote colorectal cancer (CRC). However, the mechanism by which MC-LR enhances CRC in the tumor microenvironment (TME) is poorly understood. To elucidate its role in TME, a co-culture system was established using CRC cells and M2 macrophages in a Transwell chamber. The study found that MC-LR promotes CRC cell migration by upregulating TGF-β1 expression and secretion in M2 macrophages and downregulating CST3 in CRC cells. Neutralizing TGF-β1 increased CST3 expression in CRC cells, while overexpressing CST3 in CRC cells suppressed TGF-β1 expression in M2 macrophages, both of which weakened MC-LR-induced cellular motility in the co-culture system. In vivo, the mice in the MC-LR/AOM/DSS group had more tumor nodules, deeper tumor invasion, and higher M2 macrophage infiltration compared to the AOM/DSS group, and the expression of TGF-β1 and CST3 in tumors was consistent with the cellular level. Overall, this study provides insights into the regulatory mechanism of MC-LR on TME, revealing that MC-LR upregulates the expression and secretion of TGF-β1 in M2 macrophages, which in turn inhibits the expression of CST3 in CRC cells to promote migration.

Association between genome-wide epigenetic and genetic alterations in breast cancer tissue and response to HER2-targeted therapies in HER2-positive breast cancer patients: new findings and a systematic review

Recent evidence suggests that genetic and epigenetic mechanisms might be associated with acquired resistance to cancer therapies. The aim of this study was to assess the association of genome-wide genetic and epigenetic alterations with the response to anti-HER2 agents in HER2-positive breast cancer patients. PubMed was screened for articles published until March 2021 on observational studies investigating the association of genome-wide genetic and epigenetic alterations, measured in breast cancer tissues or blood, with the response to targeted treatment in HER2-positive breast cancer patients. Sixteen studies were included in the review along with ours, in which we compared the genome-wide DNA methylation pattern in breast tumor tissues of patients who acquired resistance to treatment (case group, n = 6) to that of patients who did not develop resistance (control group, n = 6). Among genes identified as differentially methylated between the breast cancer tissue of cases and controls, one of them, PRKACA, was also reported as differentially expressed in two studies included in the review. Although included studies were heterogeneous in terms of methodology and study population, our review suggests that genes of the PI3K pathway may play an important role in developing resistance to anti-HER2 agents in breast cancer patients. Genome-wide genetic and epigenetic alterations measured in breast cancer tissue or blood might be promising markers of resistance to anti-HER2 agents in HER2-positive breast cancer patients. Further studies are needed to confirm these data.

Tandem mass tagging combined with liquid chromatography-tandem mass spectrometry technique to detect protein markers in gastroesophageal junction adenocarcinoma

BACKGROUND

Gastroesophageal junction adenocarcinoma (GEJA) is a malignant tumor located at the junction of the esophagus and stomach, the incidence of which is increasing year by year, while screening for early biomarkers is limited. Tandem mass tagging (TMT) coupled with liquid chromatography-tandem mass spectrometry (LC/MS/MS) has been used to screen for differential proteins in various cancers.

METHODS

Differential proteins in GEJA and precancerous lesions were screened using TMT-LC/MS/MS, and then proteins that met expectations were selected for trend clustering analysis, combined with GO and KEGG analysis for functional annotation of differential proteins in GEJA. Then, parallel reaction monitoring and immunohistochemistry techniques were used to validate the accuracy of the proteomics data.

RESULTS

Our group screened the differential proteins during GEJA progression using proteomics technology, analyzed the expression trends and functional regions involved in the differential proteins during carcinogenesis, and validated the accuracy of the experimental results.

CONCLUSIONS

The screening of differential proteins in GEJA carcinogenesis based on TMT-LC/MS/MS technology provides detailed information for the elucidation of GEJA progression process, pathogenesis, early screening and screening of candidate markers.

Relationship between metabolic reprogramming and drug resistance in breast cancer

Breast cancer is the leading cause of cancer death in women. At present, chemotherapy is the main method to treat breast cancer in addition to surgery and radiotherapy, but the process of chemotherapy is often accompanied by the development of drug resistance, which leads to a reduction in drug efficacy. Furthermore, mounting evidence indicates that drug resistance is caused by dysregulated cellular metabolism, and metabolic reprogramming, including enhanced glucose metabolism, fatty acid synthesis and glutamine metabolic rates, is one of the hallmarks of cancer. Changes in metabolism have been considered one of the most important causes of resistance to treatment, and knowledge of the mechanisms involved will help in identifying potential treatment deficiencies. To improve women’s survival outcomes, it is vital to elucidate the relationship between metabolic reprogramming and drug resistance in breast cancer. This review analyzes and investigates the reprogramming of metabolism and resistance to breast cancer therapy, and the results offer promise for novel targeted and cell-based therapies.

Circulating Proteins Associated with Response and Resistance to Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Simple Summary

The goal of this study was to find circulating proteins that can be easily sampled and incorporated into a clinical setting to improve predictive treatment response in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy. We looked for potential biomarkers in serum, which we identified using two proteomics techniques: qualitative LC-MS/MS and a quantitative assay that assessed protein expression between responders and non-responders HER2-positive breast cancer patients to neoadjuvant chemotherapy.

Abstract

Despite the increasing use of neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer (BC) patients, the clinical problem of predicting individual treatment response remains unanswered. Furthermore, the use of ineffective chemotherapeutic regimens should be avoided. Serum biomarker levels are being studied more and more for their ability to predict therapy response and aid in the development of personalized treatment regimens. This study aims to identify effective protein networks and biomarkers to predict response to NAC in HER2-positive BC patients through an exhaustive large-scale LC-MS/MS-based qualitative and quantitative proteomic profiling of serum samples from responders and non-responders. Serum samples from HER2-positive BC patients were collected before NAC and were processed by three methods (with and without nanoparticles). The qualitative analysis revealed differences in the proteomic profiles between responders and non-responders, mainly in proteins implicated in the complement and coagulation cascades and apolipoproteins. Qualitative analysis confirmed that three proteins (AFM, SERPINA1, APOD) were correlated with NAC resistance. In this study, we show that serum biomarker profiles can predict treatment response and outcome in the neoadjuvant setting. If these findings are further developed, they will be of significant clinical utility in the design of treatment regimens for individual BC patients.

Circulating metabolites serve as diagnostic biomarkers for HER2-positive breast cancer and have predictive value for trastuzumab therapy outcomes

Human epidermal growth factor receptor 2 (HER2)‐positive is a particularly aggressive type of the breast cancer. Trastuzumab‐based therapy is a standard treatment for HER2‐positive breast cancer, but some patients are resistance to the therapy. There are no known diagnostic biomarkers to improve the early diagnosis of HER2‐positive breast cancer and the clinical utility of trastuzumab therapy. Using ultrahigh‐performance liquid time of flight mass spectrometry (UPLC‐TOF‐MS)‐based serum metabolomics and multivariate statistical analysis, we investigated and identified the circulating metabolites L‐arginine and arachidonic acid were elevated in trastuzumab‐responsive and trastuzumab‐resistant HER2‐positive breast cancer patients, and increased until reaching their peaks in trastuzumab‐resistant HER2‐positive breast cancer patients. Moreover, an equation for assessing the risk scores based on linear logistic regression models involving L‐arginine and arachidonic acid was created, which was beneficial for revealing metabolic changes in HER2‐positive breast cancer and enhancing current trastuzumab‐based therapy. In summary, we develop serum‐based metabolic biomarkers for diagnosis of HER2‐positive breast cancers and predicts the therapeutic effects of trastuzumab therapy.

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

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.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Single-cell RNA sequencing reveals cell heterogeneity and transcriptome profile of breast cancer lymph node metastasis

Molecular mechanisms underlying breast cancer lymph node metastasis remain unclear. Using single-cell sequencing, we investigated the transcriptome profile of 96,796 single cells from 15 paired samples of primary tumors and axillary lymph nodes. We identified nine cancer cell subclusters including CD44 + / ALDH2 + /ALDH6A1 + breast cancer stem cells (BCSCs), which had a copy-number variants profile similar to that of normal breast tissue. Importantly, BCSCs existed only in primary tumors and evolved into metastatic clusters infiltrating into lymph nodes. Furthermore, transcriptome data suggested that NECTIN2-TIGIT-mediated interactions between metastatic breast cancer cells and tumor microenvironment (TME) cells, which promoted immune escape and lymph node metastasis. This study is the first to delineate the transcriptome profile of breast cancer lymph node metastasis using single-cell RNA sequencing. Our findings offer novel insights into the mechanisms underlying breast cancer metastasis and have implications in developing novel therapies to inhibit the initiation of breast cancer metastasis.

Next generation proteomics with drug sensitivity screening identifies sub-clones informing therapeutic and drug development strategies for multiple myeloma patients

With the introduction of novel therapeutic agents, survival in Multiple Myeloma (MM) has increased in recent years. However, drug-resistant clones inevitably arise and lead to disease progression and death. The current International Myeloma Working Group response criteria are broad and make it difficult to clearly designate resistant and responsive patients thereby hampering proteo-genomic analysis for informative biomarkers for sensitivity. In this proof-of-concept study we addressed these challenges by combining an ex-vivo drug sensitivity testing platform with state-of-the-art proteomics analysis. 35 CD138-purified MM samples were taken from patients with newly diagnosed or relapsed MM and exposed to therapeutic agents from five therapeutic drug classes including Bortezomib, Quizinostat, Lenalidomide, Navitoclax and PF-04691502. Comparative proteomic analysis using liquid chromatography-mass spectrometry objectively determined the most and least sensitive patient groups. Using this approach several proteins of biological significance were identified in each drug class. In three of the five classes focal adhesion-related proteins predicted low sensitivity, suggesting that targeting this pathway could modulate cell adhesion mediated drug resistance. Using Receiver Operating Characteristic curve analysis, strong predictive power for the specificity and sensitivity of these potential biomarkers was identified. This approach has the potential to yield predictive theranostic protein panels that can inform therapeutic decision making.

Serum proteomic analysis of novel predictive serum proteins for neurological prognosis following cardiac arrest

Early prognostication of neurological outcome in comatose patients after cardiac arrest (CA) is vital for clinicians when assessing the survival time of sufferers and formulating appropriate treatment strategies to avoid the withdrawal of life‐sustaining treatment (WLST) from patients. However, there is still a lack of sensitive and specific serum biomarkers for early and accurate identification of these patients. Using an isobaric tag for relative and absolute quantitation (iTRAQ)‐based proteomic approach, we discovered 55 differentially expressed proteins, with 39 up‐regulated secreted serum proteins and 16 down‐regulated secreted serum proteins between three comatose CA survivors with good versus poor neurological recovery. Then, four proteins were selected and were validated via an enzyme‐linked immunosorbent assay (ELISA) approach in a larger‐scale sample containing 32 good neurological outcome patients and 46 poor neurological outcome patients, and it was confirmed that serum angiotensinogen (AGT) and alpha‐1‐antitrypsin (SERPINA1) were associated with neurological function and prognosis in CA survivors. A prognostic risk score was developed and calculated using a linear and logistic regression model based on a combination of AGT, SERPINA1 and neuron‐specific enolase (NSE) with an area under the curve of 0.865 (P < .001), and the prognostic risk score was positively correlated with the CPC value (R = 0.708, P < .001). We propose that the results of the risk score assessment not only reveal changes in biomarkers during neurological recovery but also assist in enhancing current therapeutic strategies for comatose CA survivors.