Evaluation of serum epidermal growth factor receptor (EGFR) in correlation to circulating tumor cells in patients with metastatic breast cancer

Nanoproteomics deciphers the prognostic value of EGFR family proteins-based liquid biopsy

Monitoring tumor-associated protein status in serum can effectively track tumors and avoid time-consuming, costly, and invasive tissue biopsy. Epidermal growth factor receptor (EGFR) family proteins are often recommended in the clinical management of multiple solid tumors. However, the low-abundance of serum EGFR (sEGFR) family proteins hinders the depth-understanding of their function and tumor management. Herein, a nanoproteomics approach coupling with aptamer-modified MOFs (NMOFs-Apt) with mass spectrometry was developed for the enrichment and quantitative analysis of sEGFR family proteins. This nanoproteomics approach exhibited high sensitivity and specificity for sEGFR family protein quantification, with the limit of quantification as low as 1.00 nM. After detecting 626 patients' sEGFR family proteins with various malignant tumors, we concluded that the levels of serum proteins had a moderate concordance with tissue counterparts. Metastatic breast cancer patients with a high level of serum human epidermal growth factor receptor 2 (sHER2) and a low level of sEGFR had a poor prognosis, and patients with a sHER2 decrease of more than 20% had longer disease-free time after receiving chemotherapy. This nanoproteomics method provided a simple and effective approach for low-abundant serum protein detection and our results clarified the potential of sHER2 and sEGFR as cancer markers.

A generalizable nanopore sensor for highly specific protein detection at single-molecule precision

Protein detection has wide-ranging implications in molecular diagnostics. Substantial progress has been made in protein analytics using nanopores and the resistive-pulse technique. Yet, a long-standing challenge is implementing specific interfaces for detecting proteins without the steric hindrance of the pore interior. Here, we formulate a class of sensing elements made of a programmable antibody-mimetic binder fused to a monomeric protein nanopore. This way, such a modular design significantly expands the utility of nanopore sensors to numerous proteins while preserving their architecture, specificity, and sensitivity. We prove the power of this approach by developing and validating nanopore sensors for protein analytes that drastically vary in size, charge, and structural complexity. These analytes produce unique electrical signatures that depend on their identity and quantity and the binder-analyte assembly at the nanopore tip. The outcomes of this work could impact biomedical diagnostics by providing a fundamental basis for biomarker detection in biofluids.

Investigation of the Anticancer Potential of 2-alkoxycarbonylallyl Esters Against Metastatic Murine Breast Cancer Line 4T1 Targeting the EGFR: A Combined Molecular Docking, QSAR, and Machine Learning Approach

Background:

The search for novel and potent anticancer drugs is imperative. This present study aims to unravel the mechanisms of action of 2-alkoxyecarbonyl esters using robust model(s) that can accurately predict the bioactivity of novel compounds. Twenty-four potential anticancer 2- alkoxycarbonylallyl ester compounds obtained from the literature were employed in building a 3D-QSAR model.

Objectives:

The objective of this study is to determine the predictive ability of the GFA-based QSAR models and extreme machine learning models and compare them. The lead compounds and newly designed compounds were docked at the active site of a human epidermal growth factor receptor (EGFR) kinase domain to determine their binding modes and affinity.

Methods:

QikProp program and Spartan packages were employed for screening compounds for druglikeness and toxicity. QSAR models were equally used to predict the bioactivities of these molecules using the Material Studio package. Molecular docking of the molecules at the active site of an EGFR receptor, 1M17, was done using Auto dock tools.

Results:

The model of choice, with r2pred (0.857), satisfied the recommended standard for a stable and reliable model. The low value of r2, Q2 for several trials and cRp2 (0.779 ≥ 0.5) and the high value of correlation coefficient r2 for the training set (0.918) and test set (0.849) provide credence to the predictability of the model. The superior inhibition of EGFR displayed by the lead compounds (20 and 21) with binding energies of 6.70 and 7.00 kcalmol-1, respectively, is likely due to the presence of double bonds and α-ester groups. ADMET screening showed that these compounds are highly druggable. The designed compounds (A and B) displayed better inhibition of EGFR.

Conclusion:

The QSAR model used here performed better than the Random Forest Regression model for predicting the bioactivity of these anticancer compounds, while the designed compounds (A and B) performed better with higher binding affinity than the lead compounds. Implementing the developed model would be helpful in the search for novel anticancer agents.

Non-Coding Variants in Cancer: Mechanistic Insights and Clinical Potential for Personalized Medicine

The cancer genome is characterized by extensive variability, in the form of Single Nucleotide Polymorphisms (SNPs) or structural variations such as Copy Number Alterations (CNAs) across wider genomic areas. At the molecular level, most SNPs and/or CNAs reside in non-coding sequences, ultimately affecting the regulation of oncogenes and/or tumor-suppressors in a cancer-specific manner. Notably, inherited non-coding variants can predispose for cancer decades prior to disease onset. Furthermore, accumulation of additional non-coding driver mutations during progression of the disease, gives rise to genomic instability, acting as the driving force of neoplastic development and malignant evolution. Therefore, detection and characterization of such mutations can improve risk assessment for healthy carriers and expand the diagnostic and therapeutic toolbox for the patient. This review focuses on functional variants that reside in transcribed or not transcribed non-coding regions of the cancer genome and presents a collection of appropriate state-of-the-art methodologies to study them.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Correlations between serum cetuximab and EGFR-related markers, and skin disorders in head and neck cancer patients

PURPOSE

Cetuximab inhibits epidermal growth factor receptor (EGFR) signaling in cancer and skin cells, thereby inducing anti-cancer effects and skin disorders. The present study aimed to evaluate the relationships between serum cetuximab and EGFR-related markers, and adverse effects in head and neck cancer patients.

METHODS

Thirty-four head and neck cancer patients receiving weekly intravenous cetuximab were enrolled. Serum cetuximab levels were determined just before dosing. Blood samples for determination of serum EGFR-related markers including soluble epidermal growth factor receptor (sEGFR) and interleukin-6 (IL-6) were obtained. The severities of skin disorders, their medications, and hypomagnesemia treatment were also assessed.

RESULTS

Serum levels of cetuximab and sEGFR were negatively and positively correlated with that of IL-6, respectively. The serum cetuximab level was twofold higher in the patients with a grade 2-3 skin rash than with a grade 0-1 rash. The serum cetuximab cutoff value related to severe skin rash was 71 μg/mL (sensitivity, 59%; and specificity, 94%). The use of a strong topical corticosteroid for skin rash was also associated with a higher serum cetuximab level. Serum levels of sEGFR and IL-6 had no correlations with the skin disorder severities or their medications. Hypomagnesemia treatment using intravenous magnesium sulfate was not related to serum cetuximab and EGFR-related markers.

CONCLUSIONS

Head and neck cancer patients with a higher serum IL-6 level tended to have a lower serum cetuximab level. Serum cetuximab had positive correlations to skin rash severity and its medication in the study population.

Prognostic impact of serum levels of EGFR and EGFR ligands in early-stage breast cancer

Epidermal growth factor receptor (EGFR) and its ligands are involved in cancer pathogenesis. The emerging role of treatments co-targeting the EGFR system in breast cancer has increased the need to identify companion biomarkers. The aim of this study is to investigate whether pretreatment serum levels of EGFR and EGFR ligands in early-stage breast cancer patients might provide prognostic information as a stepping stone for further investigation. The study, which included 311 early-stage breast cancer patients, investigated associations between preoperative serum levels of EGFR and EGFR ligands (epidermal growth factor, heparin-binding epidermal growth factor (HBEGF), amphiregulin, transforming growth factor-α and betacellulin) and survival. Cutoffs were determined using Youden’s method, and overall survival (OS) and invasive disease-free survival (IDFS) were evaluated using Cox regression. Preoperative S-EGFR < 60.3 ng/mL was associated with shorter OS and IDFS in both univariate analyses and when adjusting for standard prognostic factors (p < 0.05). Preoperative S-HBEGF < 21.4 pg/mL was associated with shorter OS in both univariate and multivariate analyses, whereas association with shorter IDFS could only be demonstrated in the univariate analysis. In conclusion, our study demonstrated shorter survival in early-stage breast cancer patients who had low pretreatment levels of either S-EGFR or S-HBEGF.

Dysregulated EGFR pathway in serum in early-stage breast cancer patients: A case control study

The epidermal growth factor receptor (EGFR) and its ligands are involved in cancer pathogenesis and they might serve as circulating biomarkers. The current study aims to investigate if abnormal pre-treatment serum levels of EGFR and EGFR ligands are present in women with early-stage breast cancer and if up- or downregulation of EGFR and EGFR ligands occur in defined patient subgroups. Pre-treatment serum samples were obtained from 311 women with newly diagnosed early-stage breast cancer and from 419 healthy women and analysed for EGFR and the ligands: Epidermal growth factor (EGF), heparin-binding epidermal growth factor (HBEGF), betacellulin (BTC), amphiregulin (AREG), and transforming growth factor α (TGF-α). Previously, age-dependent 95% reference intervals for EGFR and the EGFR ligands have been established based on the healthy women population. S-EGFR, S-EGF, S-HBEGF, S-AREG, and S-TGFα were all significantly different in women with breast cancer compared to healthy women (p < 0.05). Elevated S-EGFR, according to the reference intervals, was present in 11.3% of breast cancer patients, whereas decreased S-EGF was found in 11.6%. Elevated S-EGFR was associated with estrogen receptor positivity of tumor (ER+) and a subgroup of ER + breast cancer patients showed markedly elevated S-EGFR (>120 ng/mL).

The prognostic relevance of urokinase-type plasminogen activator (uPA) in the blood of patients with metastatic breast cancer

In breast cancer (BC), elevated levels of urokinase-type plasminogen activator (uPA) in tumor tissue have been confirmed as a strong prognostic factor in level-of-evidence-1 studies. The aim of the present study was to evaluate the clinical relevance of uPA levels in serum of metastatic BC patients and to compare uPA with other blood-based biomarkers. 252 patients were enrolled in this prospective, multicentre study. Blood samples were collected before begin of first-line or later-line systemic treatment. Serum uPA was quantified by a commercially available ELISA. Circulating tumor cells (CTCs) were detected using CellSearch; other biomarkers (EGFR, VEGF, HER2, RAS p21, TIMP1, CAIX) by ELISA. Using the ROC analysis, the optimal cut-off value (determined by the Youden index) of serum uPA was 2.52 ng/ml. Using this value, 26% of patients had elevated uPA levels. Patients with visceral metastasis and more than one metastatic site were significantly more likely to present with elevated uPA levels. CTC status, serum HER2, RAS p21, CAIX, TIMP1 and VEGF correlated significantly with uPA levels. Elevated uPA levels predicted shorter overall and progression-free survival in univariate analysis (median OS: 7.5 months [95%-CI 4.5–10.5 months] vs. not reached, p < 0.001; PFS: 4.8 [95%-CI: 3.1–6.5] vs. 9.1 [7.4–10.8] months, p < 0.001). In multivariate analysis, elevated uPA, presence of ≥5 CTCs, elevated RAS p21, higher grading and higher line of therapy were independent predictors of shorter OS, while elevated CTC counts, higher line of therapy and negative estrogen receptor status were independent predictors of shorter PFS. In conclusion, elevated uPA levels independently predict reduced overall survival and improved prognostication in patients with known CTC status. Whether high serum uPA might identify patients most likely to benefit from therapies targeting uPA, remains to be evaluated in future trials.

Epidermal growth factor receptor and podocin predict nephropathy progression in type 2 diabetic patients through interaction with the autophagy influencer ULK-1

AIMS

Diabetic nephropathy (DN) that progress to end stage renal failure is a serious health problem. Autophagy is involved in DN pathogenesis. Finding renal prognostic biomarkers can help in the future renal status prevision. Therefore, the aim of current study was to evaluate and correlate circulating levels of autophagy regulator protein Unc-51-like kinase 1 (ULK-1) with the widely expressed receptor in mammalian kidney; epidermal growth factor receptor (EGFR); and the key functional podocyte protein podocin (PDCN).

METHODS

Serum levels were assessed by ELISA in 72 type 2 diabetic patients classified according to their urinary albumin/creatinine ratio; 19 normoalbuminuric, 37 microalbuminuric and 16 macroalbuminuric patients; age and sex matched with 18 healthy controls.

RESULTS

Microalbuminuria and macroalbuminuria patients exhibited decreased ULK-1, EGFR and PDCN levels. Only EGFR showed lower levels in normoalbuminuria compared with controls. ULK-1 and EGFR were significantly higher in normoalbuminuria compared with microalbuminuria and macroalbuminuria patients. ULK-1, EGFR and PDCN were correlated with each other and with some metabolic parameters.

CONCLUSIONS

ULK-1 with EGFR can predict early impairment in DN while PDCN can highlight progressive DN risk EGFR and PDCN may interact synergistically with ULK-1 in autophagy dysregulation as a pathogenic mechanism of DN induction and progression.

EGFR detection in extracellular vesicles of breast cancer patients through immunosensor based on silica-chitosan nanoplatform

In the present work, we designed a microfluidic electrochemical immunosensor with enough sensibility and precision to quantify epithermal growth factor receptor (EGFR) in plasma extracellular vesicles (EVs) of plasma from breast cancer patients. The sensor employs SiNPs coated with chitosan (SiNPs-CH) as reaction's platform, based on the covalently immobilization of monoclonal anti-EGFR on SiNPs-CH retained in the central channel (CC) of the microfluidic device. The synthetized SiNPs-CH were characterized by UV-visible spectroscopy (UV-visible), energy dispersive spectrometry (EDS), Nanoparticle Tracking Analysis (NTA) and transmission electron microscopy (TEM). EGFR was quantified by a direct sandwich immunoassay measuring through a horseradish peroxidase (HRP)-conjugated anti-EGFR. The enzymatic product (benzoquinone) was detected by reduction at - 100 mV on a sputtering gold electrode. The measured current was directly proportional to the level of EGFR in human serum samples. The linear range was from 0 ng mL^-1 to 50 ng mL^-1. The detection limit was 1.37 pg mL^-1, and the within- and between-assay coefficients of variation were below 6.25%. Finally, plasma samples from 30 early breast cancer patients and 20 healthy donor were analyzed by the novel method. EGFR levels in EVs (EVs-EGFR) were significantly higher than in the healthy control group (p = 0.002) and also, more sensitivity and specificity than normal serum markers like CEA and CA15.3 has been observed. EVs-EGFR concentration correlates with EGFR tumor status (p = 0.0003) as well as it correlate with the tumor size and pathological grade. To conclude, plasma EVs are suitable for proteomic characterization of cancer disease, as long as the employed method has sufficient sensitivity, like the case of immune-electrochemical nanosensors with incremented reaction surface.

Rapid screening of multi-target antitumor drugs by nonimmobilized tumor cells/tissues capillary electrophoresis

As there are more target categories on tumor cells/tissues than on receptor-overexpressing cells, and tumor tissues can better simulate TME, we established a new method of screening multi-target antitumor drugs by nonimmobilized tumor cells/tissues capillary electrophoresis under approximately tumor physiological environment. In this method, the natural structure and active conformation of the target proteins on tumor cells/tissues can be well maintained without separation and purification. Therefore, we successfully used this method to study the interactions between the Aidi injection (ADI)/its main components and tumor cells/tissues by optimizing a series of experimental conditions, discovered seven components with binding activity to A549 cells, five of them with specific interaction to tumor tissues, and calculated the binding kinetic parameters (K, k_a, k_d, and k'). Then, antitumor activity assays in vitro and in vivo were carried out to discover a new drug combination with higher targeting, better pharmaceutical efficacy, and lower toxic side effects. Finally, molecular docking studies were performed to investigate the potential target groups of the interactions between the effective drug combination and A549 cells/tissues. In summary, the method was verified to be valid and feasible, and can be easily transferred to a capillary array electrophoresis for high-throughput drug screening.