Biomarkers For Detection Of Cancer Research Articles

Abstract 2409: Circulating differential methylation allele fraction (DMAF) strongly correlates with circulating tumor DNA (ctDNA) variant allele fraction (VAF)

Abstract Measurement of ctDNA has been established as a prognostic biomarker of cancer disease burden. Emerging evidence has demonstrated that differential methylation patterns can serve as an accurate biomarker both for cancer detection and for predicting the tissue of origin. While it is important to distinguish cancer-positive from cancer-negative patients, clinical decision making increasingly depends on the exact level of the measured biomarker. To that end, we report on the correlation between ctDNA VAF and DMAF across patients with colorectal cancer (CRC). Pre-surgical plasma samples from patients with CRC (N=70) were sourced from the prospective GALAXY, observational arm of ongoing CIRCULATE-Japan study trial (UMIN000039205). Samples classified as ctDNA-positive by a tumor-informed ctDNA assay (SignateraTM) were included in this analysis and ctDNA VAF (%) was calculated. We performed deep methylation sequencing (Illumina Novaseq) across multiple target regions using two independent target sets. DMAF was calculated computationally, which estimates the fraction of differential methylation alleles for circulating cell-free DNA across target regions. Among 70 CRC patients, 68 had positive ctDNA results. Median age at testing was 64.0 years and male individuals represented 55.9% (n=38) of the cohort. Among them, 9 (13.2%) were stage I, 24 (35.3%) were stage II, 22 (32.3%) were stage III, 8 (11.7%) were stage IV, and 5 (7.3%) had unknown staging. The correlation of DMAF with ctDNA VAF was 0.894 (Spearman’s Rank Correlation Coefficient) and was independent of disease stage, histology, age, and sex. Among MSS (micro-satellite stable; n=58) and MSI-H (micro-satellite unstable n=10) patients, the DMAF correlation was 0.9 and 0.915, respectively. The correlation between two target sets evaluating DMAF with differing numbers of targeted regions was high (0.89). These data demonstrate that abundance of differential methylation in CRC patients correlates with VAF regardless of clinicopathologic features of patients with CRC. Methylation-based assays are a promising tool for cancer detection and quantifying the disease burden. Citation Format: Preethi Srinivasan, Tzu-Chun Chen, Ehsan Haghshenas, Misagh Kordi, Ilker Tunc, Wenching Chan, Omid Shams Solari, Joshua Babiarz, Yoshiaki Nakamura, Takayuki Yoshino, Alexey Aleshin, Trupti Kawli, Johannes G. Reiter. Circulating differential methylation allele fraction (DMAF) strongly correlates with circulating tumor DNA (ctDNA) variant allele fraction (VAF) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2409.

Abstract 3670: Reducing the patient burden for ctDNA biomarkers: Advancing small volume home-based collection technologies

Abstract There is broad consensus from regulatory agencies, clinicians and patients for the need to move to decentralized trials while focusing on patient-centric approaches with the COVID-19 pandemic being the catalyst. This requires the development of new sample collection capabilities and workflows to ensure that the necessary biomarkers can be measured. Circulating tumor DNA (ctDNA) has become an increasingly important biomarker for cancer detection and genetics, and monitoring patients during treatment. Typical measurements of ctDNA involve venous draws of >10mls of whole blood that require patients to be in clinic. Here, we test the feasibility of using a new collection device, Tasso+, to collect capillary blood for ctDNA analysis using the Guardant360 panel. A pilot of whole blood microsamples (< 1 mL) with a cfDNA yield of 0.7-1.4 ng/ml spiked to 0.5% MAF with Seraseq ctDNA reference material. This resulted in detection of ~20% of the total expected variants across variant classes showing the feasibility of using the G360 panel to detect low volume/low MAF samples. Initial testing of Tasso+ collected samples revealed a 5-10x increase in high MW gDNA compared to traditional venipuncture. SPRI bead-based size selection was used in the extraction protocol to remove >95% of the high MW DNA, resulting in a 35% loss of target cfDNA fraction. Traditional venipuncture samples and Tasso+ samples were collected from 5 cancer patients and run using the G360 platform. Microsamples detected 75% of the variants across all variant classes found in venipuncture samples. Tasso+ lost sensitivity of variants when the MAF was <0.5%. To expand usage of Tasso+ to at-home collection of blood for ctDNA analysis, we sought to determine if lyophilization of the Streck DNA BCT RUO tube reagent could still provide stability to samples and a potential framework for at-home collections. Venipuncture and Tasso+ samples were collected from control patients, pooled and spiked with Seraseq cfDNA reference material. Samples were aliquoted into standard liquid Streck tubes or tubes with lyophilized reagent at the concentration per manufacturer’s directions and evaluated for stability over time. The Tasso+ samples with a target MAF between 0.5%-2.0% detected ~26% of all variants compared to the standard samples with a similar MAF. Lyophilization of the Streck reagent had minimal effect (<20% reduction in variants detected) on the reagent’s performance as there were approximately an equal number of total variants detected when comparing liquid and lyophilized samples for both the standard tubes and Tasso+ samples. Overall, these results provide support and a framework for using a home-based patient-centric sampling approach for monitoring ctDNA from cancer patients in clinical development. Citation Format: Brad R. Evans, Robert J. Foley, Steven M. Townson, Emily J. Welch, Kevin P. Bateman. Reducing the patient burden for ctDNA biomarkers: Advancing small volume home-based collection technologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3670.

Abstract 5025: Extracellular vesicle DNA as a potential biomarker for cancer detection: A comparative analysis with ctDNA

Abstract Background: Liquid biopsy testing has been implemented in clinical practice because of recent advancements in detecting and characterizing circulating tumor DNA (ctDNA). The Food and Drug Administration (FDA) has approved three ctDNA liquid biopsy tests that detect mutations in cancers, which can aid clinicians in choosing the most effective treatments. While ctDNA has been validated for clinical applications, the same is not true for extracellular vesicle (EV)-associated DNA, which is another promising biomarker. Previously, our laboratory developed the Extracellular Vesicle-Associated DNA Database (EV-ADD) to provide validated experimental details and data extracted from peer-reviewed published literature on EV-DNA. The aim of our study was to investigate the potential clinical utility of EV-DNA in liquid biopsy for tumor detection by surveying studies on EV-ADD that compared ctDNA and EV-DNA. Methods: We searched the entire EV-ADD to selectively identify studies that compared cell-free DNA (cfDNA) or ctDNA and EV-DNA in cancer patients (inclusion criteria). The sensitivity and specificity of cancer detection, the concentrations of DNA, and the methods of detection were compared between ct/cfDNA and EV-DNA. We define sensitivity as the ability to detect mutations in ctDNA/EV-DNA from patient blood when the mutations are known. Specificity is defined as the proportion of true negatives from the sum of true negatives and false positives. A true negative case occurs when no driver mutation is detected in ctDNA/EV-DNA of a patient whose tumor does not have the mutation either. A false positive case occurs when a driver mutation is detected in ctDNA/EV-DNA of a patient whose tumor does not have the mutation. Results: Of 97 studies in the database, 20 met our inclusion criteria. From 12 studies that matched our definition of sensitivity, the sensitivity of EV-DNA and ctDNA ranged from 19% to 95% and 14% to 97%, respectively. From the same 12 studies, the specificity of EV-DNA and ctDNA ranged from 89% to 100% and 80% to 100%, respectively. Other studies that met our inclusion criteria but did not match our definition of sensitivity either calculated sensitivity differently (2 studies), calculated sensitivity the same way in pleural effusions (2 studies), in bronchoalveolar lavage fluid (2 studies), analyzed mitochondrial DNA (1 study), or did not calculate sensitivity (1 study). The concentrations of EV-DNA and ctDNA in blood ranged from 0.8 - 118.4 ng/ml and 4.0 - 236.5 ng/ml, respectively. Digital droplet PCR (ddPCR) and sequencing were the most common methods (45% and 35%, respectively) for detecting cancer mutations. Conclusions: Since EV-DNA performed comparably to ctDNA in detecting cancer DNA in the blood of patients, EV-DNA should be seriously considered as a potential biomarker and complementary tool for detecting and monitoring cancer tumors. Citation Format: Tad Wu, Thupten Tsering, Yunxi Chen, Amélie Nadeau, Julia V. Burnier. Extracellular vesicle DNA as a potential biomarker for cancer detection: A comparative analysis with ctDNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5025.

Gut Microbiota Signatures with Potential Clinical Usefulness in Colorectal and Non-Small Cell Lung Cancers.

The application of bacterial metagenomic analysis as a biomarker for cancer detection is emerging. Our aim was to discover gut microbiota signatures with potential utility in the diagnosis of colorectal cancer (CRC) and non-small cell lung cancer (NSCLC). A prospective study was performed on a total of 77 fecal samples from CRC and NSCLC patients and controls. DNA from stool was analyzed for bacterial genomic sequencing using the Ion Torrent™ technology. Bioinformatic analysis was performed using the QIIME2 pipeline. We applied logistic regression to adjust for differences attributable to sex, age, and body mass index, and the diagnostic accuracy of our gut signatures was compared with other previously published results. The feces of patients affected by different tumor types, such as CRC and NSCLC, showed a differential intestinal microbiota profile. After adjusting for confounders, Parvimonas (OR = 53.3), Gemella (OR = 6.01), Eisenbergiella (OR = 5.35), Peptostreptococcus (OR = 9.42), Lactobacillus (OR = 6.72), Salmonella (OR = 5.44), and Fusobacterium (OR = 78.9) remained significantly associated with the risk of CRC. Two genera from the Ruminococcaceae family, DTU089 (OR = 20.1) and an uncharacterized genus (OR = 160.1), were associated with the risk of NSCLC. Our two panels had better diagnostic capacity for CRC (AUC = 0.840) and NSLC (AUC = 0.747) compared to the application of two other published panels to our population. Thus, we propose a gut bacteria panel for each cancer type and show its potential application in cancer diagnosis.

Enhancing breast cancer screening with urinary biomarkers and Random Forest supervised classification: A comprehensive investigation

ObjectivesUrinary sex hormones are investigated as potential biomarkers for the early detection of breast cancer, aiming to evaluate their relevance and applicability, in combination with supervised machine-learning data analysis, toward the ultimate goal of extensive screening. MethodsSex hormones were determined on urine samples collected from 250 post-menopausal women (65 healthy - 185 with breast cancer, recruited among the clinical patients of Candiolo Cancer Institute FPO-IRCCS (Torino, Italy). Two analytical procedures based on UHPLC-MS/HRMS were developed and comprehensively validated to quantify 20 free and conjugated sex hormones from urine samples. The quantitative data were processed by seven machine learning algorithms. The efficiency of the resulting models was compared. ResultsAmong the tested models aimed to relate urinary estrogen and androgen levels and the occurrence of breast cancer, Random Forest (RF) proved to underscore all the other supervised classification approaches, including Partial Least Squares – Discriminant Analysis (PLS-DA), in terms of effectiveness and robustness. The final optimized model built on only five biomarkers (testosterone-sulphate, alpha-estradiol, 4-methoxyestradiol, DHEA-sulphate, and epitestosterone-sulphate) achieved an approximate 98% diagnostic accuracy on replicated validation sets. To balance the less-represented population of healthy women, a Synthetic Minority Oversampling TEchnique (SMOTE) data oversampling approach was applied. ConclusionsBy means of tunable hyperparameters optimization, the RF algorithm showed great potential for early breast cancer detection, as it provides clear biomarkers ranking and their relative efficiency, allowing to ground the final diagnostic model on a restricted selection five steroid biomarkers only, as desirable for noninvasive tests with wide screening purposes.

Functions of Differentially Regulated miRNAs in Breast Cancer Progression: Potential Markers for Early Detection and Candidates for Therapy.

Breast cancer remains a major global health concern, emphasizing the need for reliable biomarkers to enhance early detection and therapeutic interventions. MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNA (~22 nt in length) molecules, which are aberrantly expressed in cancer and seem to influence tumor behavior and progression. Specific miRNA dysregulation has been associated with breast cancer initiation, proliferation, invasion, and metastasis. Understanding the functional roles of these miRNAs provides valuable insights into the intricate molecular mechanisms underlying breast cancer progression. The diagnostic potential of miRNAs as non-invasive biomarkers for early breast cancer detection is a burgeoning area of research. This review aims to elucidate the functions of differentially regulated miRNAs in breast cancer progression and assess their potential as markers for early detection, stage-specific biomarkers, and therapeutic targets. Furthermore, the ability of specific miRNAs to serve as prognostic indicators and predictors of treatment response highlights their potential clinical utility in guiding personalized therapeutic interventions.

Lipidomics reveals new lipid-based lung adenocarcinoma early diagnosis model.

Lung adenocarcinoma (LUAD) continues to pose a significant mortality risk with a lack of dependable biomarkers for early noninvasive cancer detection. Here, we find that aberrant lipid metabolism is significantly enriched in lung cancer cells. Further, we identified four signature lipids highly associated with LUAD and developed a lipid signature-based scoring model (LSRscore). Evaluation of LSRscore in a discovery cohort reveals a robust predictive capability for LUAD (AUC: 0.972), a result further validated in an independent cohort (AUC: 0.92). We highlight one lipid signature biomarker, PE(18:0/18:1), consistently exhibiting altered levels both in cancer tissue and in plasma of LUAD patients, demonstrating significant predictive power for early-stage LUAD. Transcriptome analysis reveals an association between increased PE(18:0/18:1) levels and dysregulated glycerophospholipid metabolism, which consistently displays strong prognostic value across two LUAD cohorts. The combined utility of LSRscore and PE(18:0/18:1) holds promise for early-stage diagnosis and prognosis of LUAD.

Roles of Histone H2A Variants in Cancer Development, Prognosis, and Treatment.

Histones are nuclear proteins essential for packaging genomic DNA and epigenetic gene regulation. Paralogs that can substitute core histones (H2A, H2B, H3, and H4), named histone variants, are constitutively expressed in a replication-independent manner throughout the cell cycle. With specific chaperones, they can be incorporated to chromatin to modify nucleosome stability by modulating interactions with nucleosomal DNA. This allows the regulation of essential fundamental cellular processes for instance, DNA damage repair, chromosomal segregation, and transcriptional regulation. Among all the histone families, histone H2A family has the largest number of histone variants reported to date. Each H2A variant has multiple functions apart from their primary role and some, even be further specialized to perform additional tasks in distinct lineages, such as testis specific shortH2A (sH2A). In the past decades, the discoveries of genetic alterations and mutations in genes encoding H2A variants in cancer had revealed variants' potentiality in driving carcinogenesis. In addition, there is growing evidence that H2A variants may act as novel prognostic indicators or biomarkers for both early cancer detection and therapeutic treatments. Nevertheless, no studies have ever concluded all identified variants in a single report. Here, in this review, we summarize the respective functions for all the 19 mammalian H2A variants and their roles in cancer biology whilst potentiality being used in clinical setting.

Recent Advances in Fluorescent Probes for Cancer Biomarker Detection.

Many important biological species have been identified as cancer biomarkers and are gradually becoming reliable targets for early diagnosis and late therapeutic evaluation of cancer. However, accurate quantitative detection of cancer biomarkers remains challenging due to the complexity of biological systems and the diversity of cancer development. Fluorescent probes have been extensively utilized for identifying biological substances due to their notable benefits of being non-invasive, quickly responsive, highly sensitive and selective, allowing real-time visualization, and easily modifiable. This review critiques fluorescent probes used for detecting and imaging cancer biomarkers over the last five years. Focuses are made on the design strategies of small-molecule and nano-sized fluorescent probes, the construction methods of fluorescence sensing and imaging platforms, and their further applications in detection of multiple biomarkers, including enzymes, reactive oxygen species, reactive sulfur species, and microenvironments. This review aims to guide the design and development of excellent cancer diagnostic fluorescent probes, and promote the broad application of fluorescence analysis in early cancer diagnosis.

MiRNA as a Biomarker for the Early Detection of Colorectal Cancer.

MicroRNAs (miRNAs) are short, non-coding RNA segments that can be detected in a variety of clinical samples, including serum, stool, and urine. While miRNAs were initially known for their effect on post-translational gene expression, the last decade of research has shown them to be promising biomarkers for the detection of many types of cancer. This paper explores the use of miRNA detection as a tool for colorectal cancer (CRC) screening. We discuss the current state of miRNA detection, compare it to the existing CRC screening tools, and highlight the advantages and drawbacks of this approach from a clinical and logistical perspective. Our research finds that miRNA-based tests for CRC show great potential, but that widespread clinical adoption will be conditional on future research overcoming key hurdles.

Abstract B048: Evaluating the impact of pulmonary diseases on the use of microRNAs as biomarkers for early detection of ovarian cancer

Abstract B048: Evaluating the impact of pulmonary diseases on the use of microRNAs as biomarkers for early detection of ovarian cancer

Reticular Heterojunction for Organic Photoelectrochemical Transistor Detection of Neuron-Specific Enolase.

Reticular heterojunctions on the basis of metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have sparked considerable interest in recent research endeavors, which nevertheless have seldom been studied in optoelectronic biosensing. In this work, its utilization for organic photoelectrochemical transistor (OPECT) detection of the important cancer biomarker of neuron-specific enolase (NSE) is reported. A MOF@COF@CdS quantum dots (QDs) heterojunction is rationally designed to serve as the photogating module against the polymeric channel. Linking with a sandwich complexing event, target-dependent alternation of the photogate is achieved, leading to the changed photoelectric conversion efficiency as indicated by the amplified OPECT signals. The proposed assay demonstrates good analytical performance in detecting NSE, featuring a linear detection range from 0.1pgmL-1 to 100ngmL-1 , with a detection limit of 0.033pgmL-1 .

Extracellular vesicles as a promising source of lipid biomarkers for breast cancer detection in blood plasma.

Extracellular vesicles (EVs), including exosomes and microvesicles, mediate intercellular communication in cancer, from development to metastasis. EV-based liquid biopsy is a promising strategy for cancer diagnosis as EVs can be found in cancer patients' body fluids. In this study, the lipid composition of breast cancer-derived EVs was studied as well as the potential of blood plasma EVs for the identification of lipid biomarkers for breast cancer detection. Initially, an untargeted lipidomic analysis was carried out for a panel of cancerous and non-cancerous mammary epithelial cells and their secreted EVs. We found that breast cancer-derived EVs are enriched in sphingolipids and glycerophospholipids compared to their parental cells. The initial in vitro study showed that EVs and their parental cells can be correctly classified (100% accuracy) between cancerous and non-cancerous, as well as into their respective breast cancer subtypes, based on their lipid composition. Subsequently, an untargeted lipidomic analysis was carried out for blood plasma EVs from women diagnosed with breast cancer (primary or progressive metastatic breast cancer) as well as healthy women. Correspondingly, when blood plasma EVs were analysed, breast cancer patients and healthy women were correctly classified with an overall accuracy of 93.1%, based on the EVs' lipid composition. Similarly, the analysis of patients with primary breast cancer and healthy women showed an overall accuracy of 95% for their correct classification. Furthermore, primary and metastatic breast cancers were correctly classified with an overall accuracy of 89.5%. This reveals that the blood plasma EVs' lipids may be a promising source of biomarkers for detection of breast cancer. Additionally, this study demonstrates the usefulness of untargeted lipidomics in the study of EV lipid composition and EV-associated biomarker discovery studies. This is a proof-of-concept study and a starting point for further analysis on the identification of EV-based biomarkers for breast cancer.

Antibody-modified integrated microfluidic terahertz biosensor for detection of breast cancer biomarkers

Antibody-modified integrated microfluidic terahertz biosensor for detection of breast cancer biomarkers

Bio-functionalized carbon dots for signaling immuno-reaction of carcinoembryonic antigen in an electrochemical biosensor for cancer biomarker detection

Early diagnosis of cancer demands sensitive and accurate detection of cancer biomarkers in blood. Carbon dots (CDs) bio-functionalization with antibodies, peptides or aptamers have played significant role in cancer diagnosis and targeted cancer therapy. Herein, a biosensor for detection of cancer biomarker carcinoembryonic antigen (CEA) in blood serum has been designed using CDs bio-functionalized with HRP-conjugated CEA antibody (CUCDs@CEAAb2) as detection probe. CDs were synthesized by upscaling of cow urine, a nitrogen rich biomass waste, by hydrothermal method. Detection probe based on CDs resulted in 3.5 times higher sensitivity as compared to conventional electrochemical sandwich immunoassay. To further improve the sensor performance, hyper-branched polyethylenimine grafted poly amino aniline (PEI-g-PAANI) was used as the sensing interface, which enabled immobilization of higher amount of capture antibody. Detection of CEA in human blood serum coupled with wide linear range (0.5–50 ng/ml), good specificity, stability, reproducibility and low detection limit (10 pg/ml) signified the excellence of CUCDs based CEA immunosensor. CUCDs exhibited excitation wavelength dependent fluorescence property and showed strong blue emission under UV irradiation. MTT assay indicated that the material is not toxic towards human dental pulp stem cells (hDPSCs) and MG63 osteosarcoma cells (cell viability > 90%). The present study demonstrates a methodology for valorization of animal waste to a cost-effective carbon based functional nanomaterial for clinical detection of cancer biomarkers.

Salivary metabolomic biomarkers for non-invasive lung cancer detection.

Identifying novel biomarkers for early detection of lung cancer is crucial. Non-invasively available saliva is an ideal biofluid for biomarker exploration; however, the rationale underlying biomarker detection from organs distal to the oral cavity in saliva requires clarification. Therefore, we analyzed metabolomic profiles of cancer tissues compared with those of adjacent non-cancerous tissues, as well as plasma and saliva samples collected from patients with lung cancer (n = 109 pairs). Additionally, we analyzed plasma and saliva samples collected from control participants (n = 83 and 71, respectively). Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were performed to comprehensively quantify hydrophilic metabolites. Paired tissues were compared, revealing 53 significantly different metabolites. Plasma and saliva showed 44 and 40 significantly different metabolites, respectively, between patients and controls. Of these, 12 metabolites exhibited significant differences in all three comparisons and primarily belonged to the polyamine and amino acid pathways; N1-acetylspermidine exhibited the highest discrimination ability. A combination of 12 salivary metabolites was evaluated using a machine learning method to differentiate patients with lung cancer from controls. Salivary data were randomly split into training and validation datasets. Areas under the receiver operating characteristic curve were 0.744 for cross-validation using training data and 0.792 for validation data. This model exhibited a higher discrimination ability for N1-acetylspermidine than that for other metabolites. The probability of lung cancer calculated using this model was independent of most patient characteristics. These results suggest that consistently different salivary biomarkers in both plasma and lung tissues might facilitate non-invasive lung cancer screening.

CIRCULATING PROTEINS AS DIAGNOSTIC BIOMARKERS IN BREAST CANCER

Purpose: Summary of tumor-produced circulating proteins as biomarkers in breast cancer (BC) detection. Subjects and method: A meta-analysis of 50 researches on protein biomarkers in BC diagnosis. Results: Many studies have shown that tumors continuously release components such as protein, RNA, and DNA into the bloodstream during apotosis. There are different protein markers, as tissue markers and serum markers involved assisting diagnosis, but none of them can independently establish the final diagnotic BC at an early stage. Therefore, scientific communities have been putting lots of effort to discover biomarkers for better identifying this malignant disease at earlier stages.

Diatomite-Based, Flexible SERS Immunosensor Platform for Rapid, Specific, and Sensitive Detection of Circulating Cancer-Specific Protein Biomarkers in Serum Using Raman Probes.

Cancer is one of the most actively researched diseases having a high mortality rate when not detected at an early stage. Thus, rapid, simultaneous, and sensitive quantification of cancer biomarkers plays an important role in early diagnosis, with patient impact to disability adjusted life years. Herein, a diatomite-based SERS flexible platform for the rapid and sensitive detection of circulating cancer-specific protein biomarkers in serum is presented. In this approach, diatomite/AgNPs strips with maximum SERS activity prepared using the layer-by-layer (LbL) technique were modified with specific antibodies, and specific antigens (HER2, CA15-3, PSA, and MUC4) were captured and detected. By using Raman probes specific to the captured antigens in serum, a SERS limit of detection (LOD) of 0.1 ng/mL was measured (calculated LOD < 0.1 ng/mL). This value is lower than the cutoff amount of cancer antigens in the person's blood. The specificity for the antigens of each antibody was calculated to be higher than 95%. As a result, an immunosensor for rapid detection of cancer biomarkers in serum with good specificity, high sensitivity, good reproducibility, and low cost has been demonstrated. Overall, we show that the prepared diatomite-based SERS substrate with a high surface-to-volume ratio is a useable platform for immunoassay tests.

Development of Shark Single Domain Antibodies Specific for Human α-Fetoprotein and the Multimerization Strategy in Serum Detection.

Sensitive detection of cancer biomarkers can contribute to the timely diagnosis and treatment of diseases. In this study, the whitespotted bamboo sharks were immunized with human α-fetoprotein (AFP), and a phage-displayed variable new antigen receptor (VNAR) single domain antibody library was constructed. Then four unique VNARs (VNAR1, VNAR11, VNAR21, and VNAR25) against AFP were isolated from the library by biopanning for the first time. All of the sequences belong to type II of VNAR, and the VNAR11 was much different from the rest of the three sequences. Then VNAR1 and VNAR11 were selected to fuse with the C4-binding protein α chain (C4bpα) sequence and efficiently expressed in the Escherichia coli system. Furthermore, a VNAR-C4bpα-mediated sandwich chemiluminescence immunoassay (VSCLIA) was developed for the detection of AFP in human serum samples. After optimization, the VSCLIA showed a limit of detection of 0.74 ng/mL with good selectivity and accuracy. Moreover, the results of clinical serum samples detected by the VSCLIA were confirmed by an automatic immunoanalyzer in the hospital, indicating its practical application in actual samples. In conclusion, the novel antibody element VNAR exhibits great potential for immunodiagnosis, and this study also provides a new direction and experimental basis for AFP detection.

Salivary Biomarkers for Oral Cancer Detection: An Exploratory Systematic Review.

Different efforts have been made to find better and less invasive methods for the diagnosis and prediction of oral cancer, such as the study of saliva as a source of biomarkers. The aim of this study was to perform a scoping review about salivary molecules that have been assessed as possible biomarkers for the diagnosis of oral squamous cell carcinoma (OSCC). A search was conducted using EBSCO, PubMed (MEDLINE), Scopus, and Web of Science. The research question was as follows: which molecules present in saliva have utility to be used as biomarkers for the early detection of oral cancer? Sixty-two studies were included. Over 100 molecules were assessed. Most of the markers were oriented towards the early diagnosis of OSCC and were classified based on their ability for detecting OSCC and oral potentially malignant disorders (OPMDs), OSCC outcome prediction, and the prediction of the malignant transformation of OPMDs. TNF-α, IL-1β, IL-6 IL-8, LDH, and MMP-9 were the most studied, with almost all studies reporting high sensitivity and specificity values. TNF-α, IL-1β, IL-6 IL-8, LDH, and MMP-9 are the most promising salivary biomarkers. However, more studies with larger cohorts are needed before translating the use of these biomarkers to clinical settings.