Cancer Protein Biomarkers Research Articles

Primer Exchange Reaction-Synthesized DNAzyme for the Sensitive Determination of an Oral Cancer Protein Biomarker

A novel biosensing method is reported for the fluorescence determination of an oral cancer protein biomarker using primer exchange reaction (PER)-synthesized DNAzyme. Specifically, the target protein is captured by antibody-functionalized magnetic beads and recruits antibody-nucleic acid probes through immunoreactions to form sandwich-like complexes. After magnetic separation, the nucleic acid part of the antibody-nucleic acid probe participates in the PER as a catalytic hairpin, mediating the extension of primers. The extended primer forms the complete sequence of RNA-cleaving DNAzyme to effectively catalyze the cleavage of molecular beacons and produce a significantly amplified fluorescence signal. Taking interleukin 6 as a model biomarker, the method allows quantitative determination of the target in a wide linear range from 5 fg/mL to 500 pg/mL with a detection limit of 2.3 fg/mL and shows desirable specificity and usability in biological samples. More importantly, the complete DNAzyme is synthesized by the target-powered PER, which not only ensures the detection specificity, but also enables the decrease of background signals, thus greatly improving the sensitivity. Therefore, the method may provide a valuable tool for the determination of oral cancer protein biomarkers and may expand applications of DNAzyme in biosensing.

Research on Clinical Effectiveness of Aspirin for Treating Breast Cancer and Cell Protein Biomarkers on Aspirin Treatment in Drug-Resistant Estrogen Receptor-Positive Breast Cancer Cells

Background: Aspirin (ASA) has been reported to have an antitumor effect but the role of ASA in the prevention and treatment of breast cancer (BC) is still controversial. This study aimed to identify clinical effectiveness of ASA in the treatment of BC and explore the antitumor target proteins of ASA that may be involved in overcoming tamoxifen resistance in estrogen receptor (ER)-positive BC cells. Materials and Methods: Randomized controlled trials (RCTs) of ASA in the treatment of BC were queried from the databases, including PubMed, Web of Science, Cochrane Library, WanFang, and Chinese National Knowledge Infrastructure. According to the quality standard recommended in the Newcastle-Ottawa Scale (NOS), the outcome indexes were analyzed by RevMan 5.3 and Stata 12.0 software. Cell culture experiments were performed to explore the effect of tamoxifen combined with ASA on the proliferation of ER-positive BC cell lines MCF-7 and MCF-7/TAM. Cell cytotoxicity was determined by the 3-(4, 5-di-2-yl)-2, 5-ditetrazolium bromide (MTT) assay. A quantitative proteomic analysis was conducted between the control and experimental groups to identify differentially expressed proteins (DEPs). Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used for bioinformatic analysis of DEPs. The protein expression in patients of ER-positive BC was analyzed by immunochemistry (IHC). Results: Nine RCTs including 162,381 patients were selected for this study. The meta-analysis revealed that daily ASA use, as compared with its non-use, was associated with a decreased risk of BC death: relative risk (RR) = 0.83%, 95% CI [0.73, 0.94], Z = 2.89, P = 0.004 (P

Electrochemical studies of biofunctionalized MoS2 matrix for highly stable immobilization of antibodies and detection of lung cancer protein biomarker

The CS/MoS2 matrix (CS = chitosan) is explored for the stable immobilization of anti-NSE antibodies and detection of the lung cancer protein biomarker neuron-specific enolase (NSE) for the first time.

CRISPR/Cas12a-based biosensor for colorimetric detection of serum prostate-specific antigen by taking nonenzymatic and isothermal amplification

CRISPR/Cas12a-based biosensors have received intensive attention in the detection of nucleic acids, but their application for the detection of protein cancer biomarkers remains challenging. Here, we report an enzyme-free hybridization chain reaction (HCR)-powered CRISPR/Cas12a-based biosensor for colorimetric detection of serum prostate-specific antigen (PSA). The nonenzymatic and isothermal characteristics of HCR were utilized to transduce serum PSA into nucleic acids product, which was specifically recognized by the CRISPR/Cas12a system along with the activation of the trans-cleavage activity of Cas12a. Activated Cas12a cleaved the linker ssDNA between the gold nanoparticles (AuNPs)-DNA probes pair for inducing the dispersion of AuNPs with color change. The results showed that this assay was capable of the sensitive and selective detection of PSA in spiked samples and clinical samples in visual and quantitative modes, exhibiting a limit of detection (LOD) of 0.1 ng mL−1 (3δ/slope). This assay well integrates enzyme-free and isothermal amplification power of HCR, specific recognition and trans-cleavage activity of CRISPR/Cas12a system and distance-dependent optical properties of AuNPs into a single sensing system, serving as a solid basis for the development of nonenzymatic and isothermal amplified CRISPR/Cas system-based biosensor for the detection of protein cancer biomarkers.

A Prostate Cancer Proteomics Database for SWATH-MS Based Protein Quantification.

Simple SummaryProstate cancer is the third most frequent cancer in men worldwide, with a notable increase in prevalence over the past two decades. The PSA is the only well-established protein biomarker for prostate cancer diagnosis, staging, and surveillance. It frequently leads to inaccurate diagnosis and overtreatment since it is an organ-specific biomarker rather than a tumour-specific biomarker. As a result, one of the primary goals of prostate cancer proteome research is to identify novel biomarkers that can be used with or instead of PSA, particularly in non-invasive blood samples. Thousands of peptides or assays were detected in blood samples from patients with low- to high-grade prostate cancer and healthy individuals, allowing data processing of sequential window acquisition of all theoretical mass spectra (SWATH-MS). By assisting in the detection of prostate cancer biomarkers in blood samples, this useful resource will improve our understanding of the role of proteomics in prostate cancer diagnosis and risk assessment.Prostate cancer is the most frequent form of cancer in men, accounting for more than one-third of all cases. Current screening techniques, such as PSA testing used in conjunction with routine procedures, lead to unnecessary biopsies and the discovery of low-risk tumours, resulting in overdiagnosis. SWATH-MS is a well-established data-independent (DI) method requiring prior knowledge of targeted peptides to obtain valuable information from SWATH maps. In response to the growing need to identify and characterise protein biomarkers for prostate cancer, this study explored a spectrum source for targeted proteome analysis of blood samples. We created a comprehensive prostate cancer serum spectral library by combining data-dependent acquisition (DDA) MS raw files from 504 patients with low, intermediate, or high-grade prostate cancer and healthy controls, as well as 304 prostate cancer-related protein in silico assays. The spectral library contains 114,684 transitions, which equates to 18,479 peptides translated into 1227 proteins. The robustness and accuracy of the spectral library were assessed to boost confidence in the identification and quantification of prostate cancer-related proteins across an independent cohort, resulting in the identification of 404 proteins. This unique database can facilitate researchers to investigate prostate cancer protein biomarkers in blood samples. In the real-world use of the spectrum library for biomarker detection, using a signature of 17 proteins, a clear distinction between the validation cohort’s pre- and post-treatment groups was observed. Data are available via ProteomeXchange with identifier PXD028651.

Essence - A New Electrochemical Platform

There is a great demand for a fast, on-site screening test, especially during the COVID-19 pandemic. However, most point-of-care (POC) sensors usually suffer from insufficient sensitivity and selectivity. Often these devices have a very high rate of false positives and false negatives. The incorrect data could result in low customer usage (both the patient and the doctor) due to decreased confidence in the results. Portable ELISA-based kits can have low rates of false-positive and false negatives. However, ELISA is inherently complicated and often requires a specialist on-site to ensure the success of each sample's high costs and time.Here we show a new electrochemical platform called ESSENCE. ESSENCE is an Electrochemical Sensor that uses a Shear-Enhanced, flow-through Nanoporous Capacitive Electrode. ESSENCE can overcome current electrochemical sensors' selectivity and sensitivity limitations. The ESSENCE sensor architecture is a microfluidic channel sandwiched between two gold micro-electrode glass slides, formed a non-planar interdigitated porous electrode that improved electric field penetration compared with the traditional planar interdigitated electrode. The porous electrode structure used in this research has a high Zeta potential compared to the bare glass surface. This results in a significantly smaller Debye double-layer (EDL) length than in a clear channel. Due to a smaller EDL length, the relaxation frequency increases, which shifts the EIS signal to a higher frequency range (1kHz to 100MHz) and results in a fast response with a higher signal-to-noise ratio in Electrochemical Impedance Spectroscopy(EIS) measurements.Further, the modular fabrication of the ESSENCE chip allows ESSENCE to target different biomolecules from DNAs to protein cancer biomarkers by simply changing the packed transducer material. However, the packing material’s conductivity represents a significant challenge to the electrochemical response of ESSENCE. The high conductivity of the transducer material shorts the system leading to a pure resistive response. Impedance spectroscopy (EIS) response of ESSENCE cannot be distinguished enough to determine if the sensor is working. ESSENCE has a switchable electrode system for usage in multiple configurations like a material electrode, clear electrode, and working electrode to overcome these limitations. For carbon nanotube (CNT) transducers with functionalized oligos on the CNT, a 20-fold jump in the signal is noticed from the working electrode configuration compared to the other configurations. It is worthwhile to note that depending on the biomolecule (DNA or Protein), the surface charge transfer resistance (Rct) in the EIS signal of ESSENCE can either show a decrease (DNA) or increase (protein) on the binding of the target bio-molecule (target DNA to DNA or target protein to protein). The change in the Rct depends on the charge of the molecule. It has been seen that on the binding of a target protein, the active area of the electrode surface decreased, leading to a reduction in current and a concomitant increase in Rct. On binding of the target DNA, the capture-target DNA pair essentially becomes a part of the electrode due to its charge. This increase in charge is more significant than any reduction in the surface area due to the DNA's binding. This leads to an increase in current to the packed electrode, leading to a concomitant decrease in Rct.The fluid flow through the porous electrode increases mixing, minimizes diffusion, and generates a significantly enhanced fluidic shear force. This force e can unbind most of the false-positive signals generated by non-specific binding, such as physical adhesive or biofouling. The porous electrode also provides a high surface area to volume ratio to capture the target analyte leading to increased sensitivity. We have an automatic fluidic control system in ESSENCE that minimized any errors in the operation of ESSENCE. Our system has high selectivity and sensitivity for DNA (fM sensitivity, selective against non-target DNA), breast cancer biomarker proteins (p53, pg/L sensitivity, selective against non-target HER2). Figure 1

Detection of Circulating Serum Protein Biomarkers of Non-Muscle Invasive Bladder Cancer after Protein Corona-Silver Nanoparticles Analysis by SWATH-MS

Because cystoscopy is expensive and invasive, a new method of detecting non-invasive muscular bladder cancer (NMIBC) is needed. This study aims to identify potential serum protein markers for NMIBC to improve diagnosis and to find treatment approaches that avoid disease progression to a life-threatening phenotype (muscle-invasive bladder cancer, MIBC). Here, silver nanoparticles (AgNPs, 9.73 ± 1.70 nm) as a scavenging device together with sequential window acquisition of all theoretical mass spectra (SWATH-MS) were used to quantitatively analyze the blood serum protein alterations in two NMIBC subtypes, T1 and Ta, and they were compared to normal samples (HC). NMIBC’s analysis of serum samples identified three major groups of proteins, the relative content of which is different from the HC content: proteins implicated in the complement and coagulation cascade pathways and apolipoproteins. In conclusion, many biomarker proteins were identified that merit further examination to validate their useful significance and utility within the clinical management of NMIBC patients.

Porous Silicon-Based Aptasensors: Toward Cancer Protein Biomarker Detection.

The anterior gradient homologue-2 (AGR2) protein is an attractive biomarker for various types of cancer. In pancreatic cancer, it is secreted to the pancreatic juice by premalignant lesions, which would be an ideal stage for diagnosis. Thus, designing assays for the sensitive detection of AGR2 would be highly valuable for the potential early diagnosis of pancreatic and other types of cancer. Herein, we present a biosensor for label-free AGR2 detection and investigate approaches for enhancing the aptasensor sensitivity by accelerating the target mass transfer rate and reducing the system noise. The biosensor is based on a nanostructured porous silicon thin film that is decorated with anti-AGR2 aptamers, where real-time monitoring of the reflectance changes enables the detection and quantification of AGR2, as well as the study of the diffusion and target-aptamer binding kinetics. The aptasensor is highly selective for AGR2 and can detect the protein in simulated pancreatic juice, where its concentration is outnumbered by orders of magnitude by numerous proteins. The aptasensor’s analytical performance is characterized with a linear detection range of 0.05–2 mg mL–1, an apparent dissociation constant of 21 ± 1 μM, and a limit of detection of 9.2 μg mL–1 (0.2 μM), which is attributed to mass transfer limitations. To improve the latter, we applied different strategies to increase the diffusion flux to and within the nanostructure, such as the application of isotachophoresis for the preconcentration of AGR2 on the aptasensor, mixing, or integration with microchannels. By combining these approaches with a new signal processing technique that employs Morlet wavelet filtering and phase analysis, we achieve a limit of detection of 15 nM without compromising the biosensor’s selectivity and specificity.

SecProCT: In Silico Prediction of Human Secretory Proteins Based on Capsule Network and Transformer.

Identifying secretory proteins from blood, saliva or other body fluids has become an effective method of diagnosing diseases. Existing secretory protein prediction methods are mainly based on conventional machine learning algorithms and are highly dependent on the feature set from the protein. In this article, we propose a deep learning model based on the capsule network and transformer architecture, SecProCT, to predict secretory proteins using only amino acid sequences. The proposed model was validated using cross-validation and achieved 0.921 and 0.892 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively. Meanwhile, the proposed model was validated on an independent test set and achieved 0.917 and 0.905 accuracy for predicting blood-secretory proteins and saliva-secretory proteins, respectively, which are better than conventional machine learning methods and other deep learning methods for biological sequence analysis. The main contributions of this article are as follows: (1) a deep learning model based on a capsule network and transformer architecture is proposed for predicting secretory proteins. The results of this model are better than the those of existing conventional machine learning methods and deep learning methods for biological sequence analysis; (2) only amino acid sequences are used in the proposed model, which overcomes the high dependence of existing methods on the annotated protein features; (3) the proposed model can accurately predict most experimentally verified secretory proteins and cancer protein biomarkers in blood and saliva.

Comprehensive Library Generation for Identification and Quantification of Endometrial Cancer Protein Biomarkers in Cervico-Vaginal Fluid.

Simple SummaryEndometrial cancer is the most common cancer of the female reproductive tract, and its incidence is rising. Early diagnosis has the potential to improve survival as women can receive care at the earliest possible stage when curative treatment is likely. Current tests for endometrial cancer diagnosis are sequentially invasive with low patient acceptability. A detection tool based on minimally invasive samples such as cervico-vaginal fluid would be a major advance in the field. This study focuses on the potential of detecting endometrial cancer based on the proteins and peptides expressed in cervico-vaginal fluid. Using Sequential window acquisition of all theoretical mass spectra (SWATH-MS), we present a spectral library of thousands of proteins in the cervico-vaginal fluid of women with or at risk of endometrial cancer. This important resource will enable the identification of endometrial cancer biomarkers in cervico-vaginal fluid and advances our knowledge of the role of proteomics in endometrial cancer detection.Endometrial cancer is the most common gynaecological malignancy in high-income countries and its incidence is rising. Early detection, aided by highly sensitive and specific biomarkers, has the potential to improve outcomes as treatment can be provided when it is most likely to effect a cure. Sequential window acquisition of all theoretical mass spectra (SWATH-MS), an accurate and reproducible platform for analysing biological samples, offers a technological advance for biomarker discovery due to its reproducibility, sensitivity and potential for data re-interrogation. SWATH-MS requires a spectral library in order to identify and quantify peptides from multiplexed mass spectrometry data. Here we present a bespoke spectral library of 154,206 transitions identifying 19,394 peptides and 2425 proteins in the cervico-vaginal fluid of postmenopausal women with, or at risk of, endometrial cancer. We have combined these data with a library of over 6000 proteins generated based on mass spectrometric analysis of two endometrial cancer cell lines. This unique resource enables the study of protein biomarkers for endometrial cancer detection in cervico-vaginal fluid. Data are available via ProteomeXchange with unique identifier PXD025925.

Comprehensive aptamer-based screen of 1317 proteins uncovers improved stool protein markers of colorectal cancer.

To screen and validate novel stool protein biomarkers of colorectal cancer (CRC). A novel aptamer-based screen of 1317 proteins was used to uncover elevated proteins in the stool of patients with CRC, as compared to healthy controls (HCs) in a discovery cohort. Selected biomarker candidates from the discovery cohort were ELISA validated in three independent cross-sectional cohorts comprises 76 CRC patients, 15 adenoma patients, and 63 healthy controls, from two different ethnicities. The expression of the potential stool biomarkers within CRC tissue was evaluated using single-cell RNA-seq datasets. A total of 92 proteins were significantly elevated in CRC samples as compared to HCs in the discovery cohort. Among Caucasians, the 5 most discriminatory proteins among the 16 selected proteins, ordered by their ability to distinguish CRC from adenoma and healthy controls, were MMP9, haptoglobin, myeloperoxidase, fibrinogen, and adiponectin. Except myeloperoxidase, the others were significantly associated with depth of tumor invasion. The 8 stool proteins with the highest AUC values were also discriminatory in a second cohort of Indian CRC patients. Several of the stool biomarkers elevated in CRC were also expressed within CRC tissue, based on the single-cell RNA-seq analysis. Stool MMP9, fibrinogen, myeloperoxidase, and haptoglobin emerged as promising CRC stool biomarkers, outperforming stool Hemoglobin. Longitudinal studies are warranted to assess the clinical utility of these novel biomarkers in early diagnosis of CRC.

A Noninvasive Multianalytical Approach for Lung Cancer Diagnosis of Patients with Pulmonary Nodules.

Addressing the high false‐positive rate of conventional low‐dose computed tomography (LDCT) for lung cancer diagnosis, the efficacy of incorporating blood‐based noninvasive testing for assisting practicing clinician's decision making in diagnosis of pulmonary nodules (PNs) is investigated. In this prospective observative study, next generation sequencing‐ (NGS‐) based cell‐free DNA (cfDNA) mutation profiling, NGS‐based cfDNA methylation profiling, and blood‐based protein cancer biomarker testing are performed for patients with PNs, who are diagnosed as high‐risk patients through LDCT and subsequently undergo surgical resections, with tissue sections pathologically examined and classified. Using pathological classification as the gold standard, statistical and machine learning methods are used to select molecular markers associated with tissue's malignant classification based on a 98‐patient discovery cohort (28 benign and 70 malignant), and to construct an integrative multianalytical model for tissue malignancy prediction. Predictive models based on individual testing platforms have shown varying levels of performance, while their final integrative model produces an area under the receiver operating characteristic curve (AUC) of 0.85. The model's performance is further confirmed on a 29‐patient independent validation cohort (14 benign and 15 malignant, with power > 0.90), reproducing AUC of 0.86, which translates to an overall sensitivity of 80% and specificity of 85.7%.

Proteomics study of colorectal cancer and adenomatous polyps identifies TFR1, SAHH, and HV307 as potential biomarkers for screening

Colorectal cancer (CRC) is a malignant tumour with high morbidity and mortality worldwide. Efficient screening strategies for CRC and pre-cancerous lesions can promote early medical intervention and treatment, thereby reducing morbidity and mortality. Proteins are generally considered key biomarkers of cancer. Herein, we performed a quantitative, original-tissue proteomics study in a cohort of ninety patients from pre-cancerous to cancerous conditions via liquid chromatography-tandem mass spectrometry. In total, 134,812 peptides, 8697 proteins, 2355 union differentially expressed proteins (DEPs), and 409 shared DEPs (compared with adjacent tissues) were identified. The number of DEPs indicated a positive correlation with increasing severity of illness. The union and shared DEPs were both enriched in the KEGG pathway of focal adhesion, metabolism of xenobiotics by cytochrome P450, and drug metabolism by cytochrome P450. Among the 2355 union DEPs, 32 were selected for identification and validation by multiple reaction monitoring from twenty plasma specimens. Of these, three proteins, transferrin receptor protein 1 (TFR1), adenosylhomocysteinase (SAHH), and immunoglobulin heavy variable 3–7 (HV307), were significantly differentially expressed and displayed the same expression pattern in plasma as observed in the tissue data. In conclusion, TFR1, SAHH, and HV307 may be considered as potential biomarkers for CRC screening. SignificanceAlthough CRC is a malignant tumour with high morbidity and mortality worldwide, efficient screening strategies for CRC and pre-cancerous lesions can play an important role in addressing these issues. Screening of molecular biomarkers provide a non-invasive, cost-effective, and efficient approach. Proteins are generally considered key molecular biomarkers of cancer. Our study reports a quantitative proteomics analysis of protein biomarkers for colorectal cancer (CRC) and adenomatous polyps, and identifies TFR1, SAHH, and HV307 as potential biomarkers for screening. This research makes a significant contribution to the literature as although mass spectrometry-based proteomics research has been widely used for clinical research, its application to clinical translation as parallel specimens ranging from pre-cancerous to cancerous tissues—according to the degree of disease progression—has not been readily assessed.

Urine protein biomarkers of bladder cancer arising from 16-plex antibody-based screens.

Purpose: The purpose of this study is to identify novel urine protein biomarkers of bladder cancer using a Luminex based screening platform.Materials and Methods: The current study examines urine samples from 66 subjects, comprised of 31 Urology clinic controls and 35 bladder cancer patients, using a Luminex based screening platform. ELISA validation was carried out for the top 4 prospective urine biomarkers using an independent cohort of 20 Urology clinic controls and 60 bladder cancer (BC) subjects.Results: Of the 16 proteins screened by Luminex, 10 showed significant elevation in BC compared to the controls. Eight of these urine proteins were able to differentiate BC from control urine with ROC AUC values exceeding 0.70 at p < 0.0001, with specificity values exceeding 0.9. Upon ELISA validation, urine IL-1α, IL-1ra, and IL-8 were able to distinguish control urine from urine drawn from various bladder cancer stages, with IL-8 being the best discriminator. Compared to members of the IL-1 cytokine family, urine IL-8 was also best at discriminating T1 and/or T2–T4 from Ta BC (ROC AUC ≥ 0.83), as well as high grade from low grade BC (ROC AUC ≥ 0.82).Conclusions: These findings suggest that urine IL-1α, IL-1ra and IL-8 are useful indicators of bladder cancer. Urine IL-8 not only distinguishes bladder cancer from controls, it also discriminates high grade from low grade disease, and the successive clinical stages of bladder cancer. While supportive of previous reports, these findings warrant further analysis in prospective cohorts.

ESSENCE – A rapid, shear-enhanced, flow-through, capacitive electrochemical platform for rapid detection of biomolecules

The rapid, sensitive, and selective detection of target analytes using electrochemical sensors is challenging. ESSENCE, a new Electrochemical Sensor that uses a Shear-Enhanced, flow-through Nanoporous Capacitive Electrode, overcomes current electrochemical sensors' response limitations, selectivity, and sensitivity limitations. ESSENCE is a microfluidic channel packed with transducer material sandwiched by a top and bottom microelectrode. The room-temperature instrument less integration process allows the switch of the transducer materials to make up the porous electrode without modifying the electrode architecture or device protocol. ESSENCE can be used to detect both biomolecules and small molecules by simply changing the packed transducer material. Electron microscopy results confirm the high porosity. In conjunction with the non-planar interdigitated electrode, the packed transducer material results in a flow-through porous electrode. Electron microscopy results confirm the high porosity. The enhanced shear forces and increased convective fluxes disrupt the electric double layer's (EDL) diffusive process in ESSENCE. This disruption migrates the EDL to high MHz frequency allowing the capture signal to be measured at around 100 kHz, significantly improving device timing (rapid detection) with a low signal-to-noise ratio. The device's unique architecture allows us multiple configuration modes for measuring the impedance signal. This allows us to use highly conductive materials like carbon nanotubes. We show that by combining single-walled carbon nanotubes as transducer material with appropriate capture probes, NP-μIDE has high selectivity and sensitivity for DNA (fM sensitivity, selective against non-target DNA), breast cancer biomarker proteins (p53, pg/L sensitivity, selective against non-target HER2).

Ultrasensitive electrochemical determination of the cancer biomarker protein sPD-L1 based on a BMS-8-modified gold electrode

This work describes the modification of a gold electrode with the BMS-8 compound that interacts with the Programmed Death-Ligand 1 (PD-L1), an immune checkpoint protein. The results show that we can confirm the presence of the sPD-L1 in the concentration range of 10−18 to 10−8 M using electrochemical impedance spectroscopy (EIS) with a limit of detection (LOD) of 1.87 × 10−14 M for PD-L1 (S/N = 3.3) and at a concentration of 10−14 M via cyclic voltammetry (CV). Additionally, high-resolution X-ray photoelectron spectroscopy (XPS), contact angle, and surface free energy measurements were applied to confirm the functionalization of the electrode. We investigated the selectivity of the electrode for other proteins: Programmed Death-1 (PD-1), cluster of differentiation 160 (CD160), and B- and T-lymphocyte attenuator (BTLA) at concentrations of 10−8 M. Differentiation between PD-L1 and PD-1 was achieved based on the analysis of the capacitance effect frequency dispersion at the surface of the modified Au electrode with BMS-8 after incubation at various concentrations of PD-L1 and PD-1 proteins in the range of 10−18 to 10−8 M. Significant differences were observed in the heterogeneity of PD-L1 and PD-1. The results of the quasi-capacitance studies demonstrate that BMS-8 strongly and specifically interacts with the PD-L1 protein.

Hierarchical gold nanostructures based sensor for sensitive and fast detection of cancer biomarker

Importance of precision diagnostics in healthcare has been ignited by the idea that early detection of cancer would immensely benefit patients in terms of more effective and timely treatment modality. Clinical samples in the form of biopsy specimen/serum/urine/saliva contains an ocean of diagnostic information to generate conclusive information for more precise and evidence-based options to manage cancer. However, to achieve this, there is a need detect biomarkers, that can provide significantly increased diagnostic accuracy. Nanobiosensors have undoubtedly boomed to claim ultrasensitive detection of DNA cancer biomarkers in attomolar and femtomolar range. However, ultrasensitive and accurate detection of protein biomarker is rare. This work describes fabrication of a hierarchical gold nano-biosensor (HAu) for ultra-sensitive detection of cancer protein biomarkers in pg/mL range. Unique chemical modification during electrochemical synthesis has rendered highly uniformed and dense nanostructures of gold on a solid platform. Factors affecting homogeneity and sensitivity of the sensing platform have been optimized in detail. Voltammetric sensing based on antibody-antigen interaction on the given sensing platform has demonstrated a wide linear range of detection for EGFR varying from 10 pg/mL to 1 ng/mL concentration.

A label-free multiplex electrochemical biosensor for the detection of three breast cancer biomarker proteins employing dye/metal ion-loaded and antibody-conjugated polyethyleneimine-gold nanoparticles.

A new electrochemical immunosensor is developed for the label-free simultaneous detection of mucin1 (MUC1), cancer antigen 15-3 (CA15-3), and human epidermal growth factor receptor 2 (HER2) early breast cancer biomarkers. The biosensor is simply designed using the deposition of three different systems of redox species-antibody-conjugated polyethylenimine coated-gold nanoparticles (PEI-AuNPs), for the first time. The screen-printed carbon electrode (SPCE) comprising a three-working electrode array is modified with the conjugated PEI-AuNPs. Multiplex sensing is performed by utilizing the distinguishable electrochemical responses of the redox-active species; anthraquinone-2-carboxylic acid (AQ), thionine chloride (TH), and AgNO3 (Ag+) on the PEI-AuNPs conjugates for the detection of MUC1, CA15-3, and HER2, respectively. The single-run determination of the biomarkers by the proposed immunosensor is carried out by measuring the decrease (%) in the oxidation peak currents due to the formation of three kinds of antibody-antigen complexes. The decreased currents are logarithmically proportional to the antigen concentrations in the ranges of 0.10-100 U mL-1 CA15-3 and 0.10-100 ng mL-1 MUC1 and HER2 with detection limits of 0.21 U mL-1, 0.53 ng mL-1 and 0.50 ng mL-1, respectively, which are significantly lower than the clinically relevant cut-off levels. The sensor reveals high selectivity and satisfactory reproducibility. After storing for two weeks, the sensor retains the responses with ca. 90% of the initial currents. The immunosensor is successfully applied to detect three tumor markers in human serum and can provide a new technological platform for the development of low-cost, highly stable, sensitive, selective, and point-of-care (POC) diagnosis.

Nonspecific nuclear uptake of anti-MUC1 aptamers by dead cells: the role of cell viability monitoring in aptamer targeting of membrane-bound protein cancer biomarkers.

Most aptamers targeting cell-expressed antigens are intended for in vivo application, however, these sequences are commonly generated in vitro against synthetic oligopeptide epitopes or recombinant proteins. As these in vitro analogues frequently do not mimic the in vivo target within an endogenous environment, the evolved aptamers are often prone to nonspecific binding. The presence of dead cells and cellular debris further complicate aptamer targeting, due to their high nonspecific affinities to single-stranded DNA. Despite these known limitations, assessment of cell viability and/or the removal of dead cells is rarely applied as part of the methodology during in vivo testing of aptamer binding. Furthermore, the extent and route(s) by which dead cells uptake existing aptamers remains to be determined in the literature. For this purpose, the previously reported aptamer sequences 5TR1, 5TR4, 5TRG2 and S22 - enriched against the MUC1 tumour marker of the mucin glycoprotein family - were used as model sequences to evaluate the influence of cell viability and the presence of nontarget cell-expressed protein on aptamer binding to the MUC1 expressing human cancer cell lines MCF-7, Hs578T, SW480, and SW620. From fluorescence microscopy analysis, all tested aptamers demonstrated extensive nonspecific uptake within the nuclei of dead cells with compromised membrane integrities. Using fluorescent-activated cell sorting (FACS), the inclusion of excess double-stranded DNA as a blocking agent showed no effect on nonspecific aptamer uptake by dead cells. Further nonspecific binding to cell-membrane bound and intracellular protein was evident for each aptamer sequence, as assessed by southwestern blotting and FACS. These factors likely contributed to the ∼120-fold greater binding response of the 5TR1 aptamer to dead MCF-7 cells over equivalent live cell populations. The identification of dead cells and cellular debris using viability stains and the subsequent exclusion of these cells from FACS analysis was identified as an essential requirement for the evaluation of aptamer binding specificity to live cell populations of the cancer cell lines MCF-7, Hs578T and SW480. The research findings stress the importance of dead cell uptake and more comprehensive cell viability screening to validate novel aptamer sequences for diagnostic and therapeutic application.

Matrix-Assisted Ionization and Tandem Mass Spectrometry Capabilities in Protein Biomarker Characterization-An Initial Study Using the Small Cell Lung Cancer Biomarker Progastrin Releasing Peptide as a Model Compound.

This initial study evaluates vacuum matrix-assisted ionization (vMAI) mass spectrometry (MS) for identification and determination of tryptic peptides from the biomarker protein progastrin releasing peptide (ProGRP). Similar peptides and charge states were observed as in liquid chromatography (LC) electrospray ionization (ESI) MS. The prolonged ion duration in vMAI with similar charge states as in ESI was advantageous for determining the MS/MS fragmentation conditions compared to MAI. It is assumed that the vacuum ionization conditions lower the detection limits of the experiment. This may be the reason vMAI combined with high resolution MS enabled detection of tryptic peptides from more digested proteins than MAI selected reaction monitoring MS. Additionally, MAI ion mobility spectrometry MS (MAI-IMS-MS) was evaluated for differentiation of intact protein isoforms, successfully enabling differentiation of the isoforms by drift time selection. Examples are both shown for model proteins bovine serum albumin, cytochrome C, and lysozyme and the clinically relevant small cell lung cancer protein biomarker ProGRP, which exists in three isoforms. Coupling with the vacuum ionization conditions using a dedicated vacuum-probe source MAI enables information to be extracted readily as with conventional approaches, just faster.