Biomarkers For Detection Of Cancer Research Articles

Unveiling potential: urinary exosomal mRNAs as non-invasive biomarkers for early prostate cancer diagnosis

BackgroundThis study investigated the use of urinary exosomal mRNA as a potential biomarker for the early detection of prostate cancer (PCa).MethodsNext-generation sequencing was utilized to analyze exosomal RNA from 10 individuals with confirmed PCa and 10 individuals without cancer. Subsequent validation through qRT-PCR in a larger sample of 43 PCa patients and 92 healthy controls revealed distinct mRNA signatures associated with PCa.ResultsNotably, mRNAs for RAB5B, WWP1, HIST2H2BF, ZFY, MARK2, PASK, RBM10, and NRSN2 showed promise as diagnostic markers, with AUC values between 0.799 and 0.906 and significance p values. Combining RAB5B and WWP1 in an exoRNA diagnostic model outperformed traditional PSA tests, achieving an AUC of 0.923, 81.4% sensitivity, and 89.1% specificity.ConclusionsThese findings highlight the potential of urinary exosomal mRNA profiling, particularly focusing on RAB5B and WWP1, as a valuable strategy for improving the early detection of PCa.

Aptamer-enabled electrochemical bioplatform utilizing surface-modified g-C3N4/MoS2/PANI nanocomposite for detection of CA125 biomarker

Detecting ovarian cancer at an early stage is crucial for enhancing patient outcomes, underscoring the demand for an efficient and non-invasive detection method. Cancer antigen 125 (CA125) is a vital biomarker in ovarian cancer detection, and there is a pressing demand to develop a quick, sensitive, and simple detection method. Nanobiosensors are increasingly being used by scientists due to their high selectivity and sensitivity, allowing for the swift and precise detection of a wide range of biomarkers. This study aimed to design and fabricate an electrochemical nanobiosensor that could accurately and selectively detect CA125. The nanobiosensor employed graphitic carbon nitrides, molybdenum disulfide, and polyaniline (g-C3N4/MoS2/PANI) to stabilize aptamer strands on a modified glassy carbon electrode. The aptasensor was used to perform electrochemical detection of labeled CA125, utilizing methylene blue and label-free ferrocyanide methods. Ferrocyanide and methylene blue detection limits were determined to be 0.196 U.mL−1 for ferrocyanide and 0.196 U.mL−1 for methylene blue, with a linear detection range of 2–10 U.mL−1 for linear detection. The study results showed that the modified electrode exhibited high selectivity towards CA125 and superior stability compared to other biomolecules. The electrochemical aptasensor also displayed impressive performance when analyzing the serum of patients and healthy people. These findings hold significant promise for future investigation in ovarian cancer diagnosis. This novel electrochemical nanobiosensor may aid in the early detection and management of ovarian cancer, ultimately leading to better patient outcomes.

Analysis of cancer detection methods based on nanomaterials

This research discusses the application of nanomaterials in cancer detection and the comparison between various application methods, highlighting their high sensitivity and specificity in the detection of cancer biomarkers. Nanomaterials have the ability to selectively target and bind specific molecules, resulting in improved detection accuracy. They also facilitate the simultaneous detection of multiple biomarkers and enable non-invasive tumor visualization by various imaging methods. Despite the many advantages, there are still many challenges related to safety considerations and optimization of detection techniques that need to be addressed urgently. Nonetheless, the nanomaterials-based approach holds significant promise for improving cancer detection technology and improving early diagnosis. Further research is essential in order to fully exploit the power of nanomaterials in accurate and efficient cancer detection. By addressing these challenges, difficulties, and conducting additional research, nanomaterials have the potential to revolutionize cancer detection, resulting in improved results accuracy, earlier detection of disease, and better treatment for the benefit of humanity.

Enzymatic response of heparin-protamine complex: Spectroscopic investigation and application for lung adenocarcinoma cells detection

Though the heparin-protamine complex (HP complex) is a crucial system utilized in clinical settings, the metabolic pathways of this complex remain inadequately understood. Herein, the enzymatic degradation of the heparin-protamine complex by trypsin and its broader implications were investigated. By utilizing fluorescent gold nanoclusters liganded with the HP complex (AuNCs-HP complex), we observed significant morphological and spectral changes during enzymatic degradation. Experiments showed that AuNCs-HP complex could be degraded and cleaved into small fragments by trypsin. Moreover, the AuNCs-HP complex demonstrated its potential as a highly sensitive spectral sensing platform, enabling precise measurement of trypsin activity with an outstanding detection limit (0.34 ng mL−1). Additionally, we explored its utility for specific tumor cell detection, focusing on lung adenocarcinoma cells, and successfully identified their presence through distinctive fluorescence changes. These remarkable findings not only contribute valuable insights into targeted degradation systems but also offer promising opportunities for cancer biomarker detection. The AuNCs-HP complex serves as an innovative tool for real-time trypsin activity monitoring, paving the way for advanced biomedical applications.

Large-scale proteomics reveals precise biomarkers for detection of ovarian cancer in symptomatic women

Ovarian cancer is the 8th most common cancer among women and has a 5-year survival of only 30–50%. While the survival is close to 90% for stage I tumours it is only 20% for stage IV. Current biomarkers are not sensitive nor specific enough, and novel biomarkers are urgently needed. We used the Explore PEA technology for large-scale analysis of 2943 plasma proteins to search for new biomarkers using two independent clinical cohorts. The discovery analysis using the first cohort identified 296 proteins that had significantly different levels in malign tumours as compared to benign and for 269 (91%) of these, the association was replicated in the second cohort. Multivariate modelling, including all proteins independent of their association in the univariate analysis, identified a model for separating benign conditions from malign tumours (stage I–IV) consisting of three proteins; WFDC2, KRT19 and RBFOX3. This model achieved an AUC of 0.92 in the replication cohort and a sensitivity and specificity of 0.93 and 0.77 at a cut-off developed in the discovery cohort. There was no statistical difference of the performance in the replication cohort compared to the discovery cohort. WFDC2 and KRT19 have previously been associated with ovarian cancer but RBFOX3 has not previously been identified as a potential biomarker. Our results demonstrate the ability of using high-throughput precision proteomics for identification of novel plasma protein biomarker for ovarian cancer detection.

Visual detection of microRNAs using gold nanorod-based lateral flow nucleic acid biosensor and exonuclease III-assisted signal amplification.

An ultrasensitive method for the visual detection of microRNAs (miRNAs) in cell lysates using a gold nanorod-based lateral flow nucleic acid biosensor (GN-LFNAB) and exonuclease III (Exo III)-assisted signal amplification. The Exo III-catalyzed target recycling strategy is employed to generate a large number of single-strand DNA products, which can be detected by GN-LFNAB visually. With the implementation of a unique recycling strategy, we have demonstrated that the miRNA in the concentration as low as 0.5pM can be detected without the need for instrumentation, providing a detection limit that surpasses previous reports. The new biosensor is ultrasensitive and can be applied to the reliable monitoring of miRNAs in cell lysates with high accuracy. The approach offers a simple and rapid tool for cancer diagnosis and clinical biomedicine, thanks to its flexibility, simplicity, cost-effectiveness, and convenience. This new method has the potential to significantly improve the detection and monitoring of cancer biomarkers, ultimately contributing to more effective cancer diagnosis and treatment.

Super-resolution Multispectral Imaging Nanoimmunosensor for Simultaneous Detection of Diverse Early Cancer Biomarkers.

In medical diagnosis, relying on only one type of biomarker is insufficient to accurately identify cancer. Blood-based multicancer early detection can help identify more than one type of cancer from a single blood sample. In this study, a super-resolution multispectral imaging nanoimmunosensor (srMINI) based on three quantum dots (QDs) of different color conjugated with streptavidin was developed for the simultaneous screening of various cancer biomarkers in blood at the single-molecule level. In the experiment, the srMINI chip was used to simultaneously detect three key cancer biomarkers: carcinoembryonic antigen (CEA), C-reactive protein (CRP), and alpha-fetoprotein (AFP). The srMINI chip exhibited 108 times higher detection sensitivity of 0.18-0.5 ag/mL (1.1-2.6 zM) for these cancer biomarkers than commercial enzyme-linked immunosorbent assay kits because of the absence of interfering signals from the substrate, establishing considerable potential for multiplex detection of cancer biomarkers in blood. Therefore, the simultaneous detection of various cancer biomarkers using the developed srMINI chip with high diagnostic precision and accuracy is expected to play a decisive role in early diagnosis or community screening as a single-molecule biosensor.

DNA origami-templated gold nanorod dimer nanoantennas: enabling addressable optical hotspots for single cancer biomarker SERS detection.

The convergence of DNA origami and surface-enhanced Raman spectroscopy (SERS) has opened a new avenue in bioanalytical sciences, particularly in the detection of single-molecule proteins. This breakthrough has enabled the development of advanced sensor technologies for diagnostics. DNA origami offers a highly controllable framework for the precise positioning of nanostructures, resulting in superior SERS signal amplification. In our investigation, we have successfully designed and synthesized DNA origami-based gold nanorod monomer and dimer assemblies. Moreover, we have evaluated the potential of dimer assemblies for label-free detection of a single biomolecule, namely epidermal growth factor receptor (EGFR), a crucial biomarker in cancer research. Our findings have revealed that the significant Raman amplification generated by DNA origami-assembled gold nanorod dimer nanoantennas facilitates the label-free identification of Raman peaks of single proteins, which is a prime aim in biomedical diagnostics. The present work represents a significant advancement in leveraging plasmonic nanoantennas to realize single protein SERS for the detection of various cancer biomarkers with single-molecule sensitivity.

An electrochemical/SERS dual-mode immunosensor using TMB/Au nanotag and Au@2D-MoS2 modified screen-printed electrode for sensitive detection of prostate cancer biomarker

This study describes a novel dual-mode immunosensor that combines electrochemical (EC) and surface-enhanced Raman scattering (SERS) techniques for the detection of prostate-specific antigen (PSA), a biomarker associated with prostate cancer. The sensor consists of a nanocomposite of gold nanoparticles (AuNPs) deposited on two-dimensional (2D) molybdenum disulfide (Au@MoS2) modified on a working carbon electrode of a screen-printed electrode (SPE). Subsequently, the primary antibody (Ab1) is immobilized on the modified electrode, creating Ab1/Au@MoS2/SPE for specific recognition of the target PSA. In parallel, AuNPs are conjugated with a secondary antibody (Ab2) and a probe molecule, 3,3′,5,5′-tetramethylbenzidine (TMB), leading nanotags (TMB/Ab2/AuNPs) formation exhibiting strong SERS and EC responses. Upon the presence of the target, sandwich immunocomplexes can be formed through antigen-antibody interactions (Ab1-PSA-Ab2). The differential pulse voltammetry (DPV) technique is employed for EC detection mode, while a handheld Raman spectrometer with a 785nm excitation laser is utilized to collect SERS signals. The developed system demonstrates excellent selectivity and sensitivity, with low limits of detection (LODs) of 3.58pgmL−1 and 4.83pgmL−1 for EC and SERS sensing, respectively. Importantly, the dual-mode immunosensor proves effective quantifying PSA protein in human serum samples with good recovery. Given its high sensitivity and proficiency in analyzing biological samples, this proposed immunosensor holds promise as an alternative tool for the early diagnosis of cancers.

Nanozyme Catalytic Performance Enhancement through Defect and Electronic Structure Regulation of Metal-Doped NiCo2O4@Pd.

Spinel oxides have emerged as a promising candidate in the realm of nanozymes with variable oxidation states, while their limited active sites and low conductivity hinder further application. In this work, we synthesize a series of metal-doped NiCo2O4 nanospheres decorated with Pd, which are deployed as highly efficient nanozymes for the detection of cancer biomarkers. Through meticulous modulation of the molar ratio between NiCo2O4 and Pd, we orchestrated precise control over the oxygen vacancies and electronic structure within the nanozymes, a key factor in amplifying the catalytic prowess. Leveraging the superior H2O2 reduction catalytic properties of Fe-NiCo2O4@Pd, we have successfully implemented its application in the electrochemical detection of biomarkers, achieving unparalleled analytical performance, much higher than that of Pd/C and other reported nanozymes. This research paves the way for innovative electron modification strategies in the design of high-performance nanozymes, presenting a formidable tool for clinical diagnostic analyses.

Nanochannels-based self-correction electrochemical detection of mucin 1 with in-situ generated phosphomolybdic acid

Accurate detection of cancer biomarkers like mucin 1 (MUC-1) is significantly important for diagnosis and prognosis of tumor. Herein, a self-correction electrochemical immunoassay for MUC-1 detection was developed based on bioinspired nanochannels and electrochemistry of molybdophosphate. MUC-1 can be captured in the bioinspired polymer nanochannels via the formation of immunocomplex. Then, diffusion of MoO42− in the nanochannels would be sterically hindered and the in-situ generation of phosphomolybdic acid onto the electrode surface which was modified with phosphate chitosan hydrogel, would be influenced. Therefore, the two well-defined redox peaks of phosphomolybdic acid can be applied to the detection of the antigen. To improve detection sensitivity, the phosphate chitosan was incorporated with carbon nanotubes. Moreover, the occurrence in nanochannels was amplified by hybridization chain reaction, which enhanced the hindrance for transport of MoO42− by increasing steric effect, electrostatic repulsion as well as anchoring sites. Under optimized conditions, currents of the both anodic peaks on square wave voltametric voltammograms decreased linearly with the logarithm of the concentration of MUC-1 ranging from 10 fg∙mL−1 to 100 ng∙mL−1 with a detection limit of 6.0 fg∙mL−1. And thus, the detection results can be self-corrected by the results acquired from the two peaks, which had valuable implications for the reliable MUC-1 detection in disease diagnosis and therapy application.

FOXP3 serum concentration; a likely predictor of CIN and cervical cancer: Secondary analysis from a case control study at a clinic in South western Uganda

Biomarkers including Forkhead/winged-helix transcription factor box P3 have been proposed in immunohistochemical techniques to diagnose cervical lesions, but can be objectively quantified and measured in blood using methods that can be standardised. In this study we quantified the serum FOXP3 concentrations and assessed their association with cervical lesions at the cervical cancer clinic of Mbarara Regional Hospital (MRRH) Southwestern Uganda.We performed secondary analysis on archived serum samples from a previous unmatched case control study in which we recruited 90 cervical cancer (CC) cases, 90 cervical intraepithelial neoplasia (CIN) cases before any form of treatment and 90 controls. Clinical and demographic data were recorded. We measured FOXP3 concentrations using quantitative ELISA. We performed descriptive statistics and logistic regression in STATA 17 and took P-values of < 0.05 as statistically significant.The mean concentration of FOXP3 was higher in serum samples from CC cases compared with CIN cases and controls, and this difference was statistically significant (P value < 0.001). More than half (52/90,58 %) of serum samples from CC cases had FOXP3 concentrations greater than 0.0545 ng/ml (P value < 0.001). Increase serum FOXP3 expression was not associated with CIN. Increase in serum FOXP3 concentrations were observed to increase the chances of CC by 2 times (OR: 2.094, P value 0.038, 95 % CI: 1.042–––4.209).Serum FOXP3 is likely associated with cervical lesions especially CC in our study population. Serum FOXP3 testing may be useful in resource limited settings to aid detection of such lesions given the challenges associated with cytology and VIA. We recommend diagnostic utility studies for circulating FOXP3 as a biomarker for detection of cervical cancer.

The upregulation of POLR3G correlates with increased malignancy of bladder urothelium

Bladder cancer remains a significant health challenge due to its high recurrence and progression rates. This study aims to evaluate the role of POLR3G in the development and progression of bladder cancer and the potential of POLR3G to serve as a novel therapeutic target. We constructed a bladder cancer model in Wistar rats by administering N-butyl-N-(4-hydroxybutyl) nitrosamine (BBN), which successfully induced a transition from normal mucosa to hyperplasia and ultimately to urothelial carcinoma. We observed a progressive upregulation of POLR3G expression during the bladder cancer development and progression. To investigate the functional role of POLR3G, we performed functional experiments in bladder cancer cell lines. The results demonstrated that knocking down POLR3G significantly inhibited cell proliferation, migration, and invasion. We further conducted RNA sequencing on POLR3G-knockdown bladder cancer cells, and Metascape was employed to perform the functional enrichment analysis of the differentially expressed genes (DEGs). Enrichment analysis revealed the enrichment of DEGs in the RNA polymerase and apoptotic cleavage of cellular proteins pathways, as well as their involvement in the Wnt and MAPK signaling pathways. The downregulation of Wnt pathway-related proteins such as Wnt5a/b, DVL2, LRP-6, and phosphorylated LRP-6 upon POLR3G knockdown was further confirmed by Western blotting, indicating that POLR3G might influence bladder cancer behavior through the Wnt signaling pathway. Our findings suggest that POLR3G plays a crucial role in bladder cancer progression and could serve as a potential therapeutic target. Future studies should focus on the detailed mechanisms by which POLR3G regulates these signaling pathways and its potential as a biomarker for early detection and prognosis of bladder cancer.

Plasma cell-free DNA methylome-based liquid biopsy for accurate gastric cancer detection.

Early detection plays a critical role in mitigating mortality rates linked to gastric cancer. However, current clinical screening methods exhibit suboptimal efficacy. Methylation alterations identified from cell-free DNA (cfDNA) present a promising biomarker for early cancer detection. Our study focused on identifying gastric cancer-specific markers from cfDNA methylation to facilitate early detection. We enrolled 150 gastric cancer patients and 100 healthy controls in this study, and undertook genome-wide methylation profiling of cfDNA using cell-free methylated DNA immunoprecipitation and high-throughput sequencing. We identified 21 differentially methylated regions (DMRs) between the gastric tumor and nontumor groups using multiple algorithms. Subsequently, using the 21 DMRs, we developed a gastric cancer detection model by random forest algorithm in the discovery set, and validated the model in an independent set. The model was able to accurately discriminate gastric cancer with a sensitivity and specificity of 93.90% and 95.15% in the discovery set, respectively, and 88.38% and 94.23% in the validation set, respectively. These results underscore the efficacy and accuracy of cfDNA-derived methylation markers in distinguishing early stage gastric cancer. This study highlighted the significance of cfDNA methylation alterations in early gastric cancer detection.

Promising microRNAs in pre-diagnostic serum associated with lung cancer up to eight years before diagnosis: a HUNT study

IntroductionBlood biomarkers for early detection of lung cancer (LC) are in demand. There are few studies of the full microRNome in serum of asymptomatic subjects that later develop LC. Here we searched for novel microRNA biomarkers in blood from non-cancer, ever-smokers populations up to eight years before diagnosis.MethodsSerum samples from 98,737 subjects from two prospective population studies, HUNT2 and HUNT3, were considered initially. Inclusion criteria for cases were: ever-smokers; no known cancer at study entrance; 0–8 years from blood sampling to LC diagnosis. Each future LC case had one control matched to sex, age at study entrance, pack-years, smoking cessation time, and similar HUNT Lung Cancer Model risk score. A total of 240 and 72 serum samples were included in the discovery (HUNT2) and validation (HUNT3) datasets, respectively, and analysed by next-generation sequencing. The validated serum microRNAs were also tested in two pre-diagnostic plasma datasets from the prospective population studies NOWAC (n = 266) and NSHDS (n = 258). A new model adding clinical variables was also developed and validated.ResultsFifteen unique microRNAs were discovered and validated in the pre-diagnostic serum datasets when all cases were contrasted against all controls, all with AUC > 0.60. In combination as a 15-microRNAs signature, the AUC reached 0.708 (discovery) and 0.703 (validation). A non-small cell lung cancer signature of six microRNAs showed AUC 0.777 (discovery) and 0.806 (validation). Combined with clinical variables of the HUNT Lung Cancer Model (age, gender, pack-years, daily cough parts of the year, hours of indoor smoke exposure, quit time in years, number of cigarettes daily, body mass index (BMI)) the AUC reached 0.790 (discovery) and 0.833 (validation). These results could not be validated in the plasma samples.ConclusionThere were a few significantly differential expressed microRNAs in serum up to eight years before diagnosis. These promising microRNAs alone, in concert, or combined with clinical variables have the potential to serve as early diagnostic LC biomarkers. Plasma is not suitable for this analysis. Further validation in larger prospective serum datasets is needed.

A Clinically Feasible Diagnostic Electrochemical Micronano Motors Biosensor Built on Miniature Swimmer for Multiplex Detection and Grading of Breast Cancer Biomarkers.

Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), and Ki67 are four crucial biomarkers used in the clinical diagnosis of breast cancer. Accurate detection of these biomarkers is essential for an effective diagnosis and treatment. MOF-based micronano motors (MOFtors) are promising for various applications, including environmental remediation, targeted nanosurgery, and biomarker detection. This paper presents a clinically feasible diagnostic electrochemical micronano motor biosensor, built on a miniature swimmer, for the multiplex detection and grading of breast cancer biomarkers. We designed a biosensor, named MOFtor-MSEM, incorporating aptamers and antibodies functionalized on SiO2@Co-Fe-MOF, which acts as a miniature swimmer in solution. The SiO2@Co-Fe-MOF serves as the body, while complementary double-chain-linked antibodies function as paddles. In a homogeneous solution, when a positive voltage is applied to the working electrode, the electrostatic interaction between the neutral SiO2@Co-Fe-MOF and the negatively charged complementary double-linked antibody causes the antibody to move toward the electrode and then regress due to water resistance. This back-and-forth motion propels the miniature swimmer, enabling it to move the target analyte through the solution. The sensor features an automatic "sample-amplifying signal-output" process, achieving simultaneous signal amplification and output of four electrochemical signals on a single nanomaterial, a significant challenge in electrochemical sensing. The biosensor boasts a short detection time of 40 min, compared to approximately 1 week for current clinical tissue testing. Additionally, the bioplatform selectively detects HER2, ER, Ki67, and PR in the range of 0-1500 pg/mL, with detection limits of 0.01420, 0.03201, 0.01430, and 0.01229 pg/mL, respectively.

Recent progress in Nanomaterial based biosensors for the detection of cancer biomarkers in human fluids

Recent progress in Nanomaterial based biosensors for the detection of cancer biomarkers in human fluids

Targeted proteomics of plasma extracellular vesicles uncovers MUC1 as combinatorial biomarker for the early detection of high-grade serous ovarian cancer

BackgroundThe five-year prognosis for patients with late-stage high-grade serous carcinoma (HGSC) remains dismal, underscoring the critical need for identifying early-stage biomarkers. This study explores the potential of extracellular vesicles (EVs) circulating in blood, which are believed to harbor proteomic cargo reflective of the HGSC microenvironment, as a source for biomarker discovery.ResultsWe conducted a comprehensive proteomic profiling of EVs isolated from blood plasma, ascites, and cell lines of patients, employing both data-dependent (DDA) and data-independent acquisition (DIA) methods to construct a spectral library tailored for targeted proteomics. Our investigation aimed at uncovering novel biomarkers for the early detection of HGSC by comparing the proteomic signatures of EVs from women with HGSC to those with benign gynecological conditions. The initial cohort, comprising 19 donors, utilized DDA proteomics for spectral library development. The subsequent cohort, involving 30 HGSC patients and 30 control subjects, employed DIA proteomics for a similar purpose. Support vector machine (SVM) classification was applied in both cohorts to identify combinatorial biomarkers with high specificity and sensitivity (ROC-AUC > 0.90). Notably, MUC1 emerged as a significant biomarker in both cohorts when used in combination with additional biomarkers. Validation through an ELISA assay on a subset of benign (n = 18), Stage I (n = 9), and stage II (n = 9) plasma samples corroborated the diagnostic utility of MUC1 in the early-stage detection of HGSC.ConclusionsThis study highlights the value of EV-based proteomic analysis in the discovery of combinatorial biomarkers for early ovarian cancer detection.

Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma.

This review comprehensively explores the complex interplay between extracellular vesicles (ECVs)/exosomes and circadian rhythms, with a focus on the role of this interaction in hepatocellular carcinoma (HCC). Exosomes are nanovesicles derived from cells that facilitate intercellular communication by transporting bioactive molecules such as proteins, lipids, and RNA/DNA species. ECVs are implicated in a range of diseases, where they play crucial roles in signaling between cells and their surrounding environment. In the setting of cancer, ECVs are known to influence cancer initiation and progression. The scope of this review extends to all cancer types, synthesizing existing knowledge on the various roles of ECVs. A unique aspect of this review is the emphasis on the circadian-controlled release and composition of exosomes, highlighting their potential as biomarkers for early cancer detection and monitoring metastasis. We also discuss how circadian rhythms affect multiple cancer-related pathways, proposing that disruptions in the circadian clock can alter tumor development and treatment response. Additionally, this review delves into the influence of circadian clock components on ECV biogenesis and their impact on reshaping the tumor microenvironment, a key component driving HCC progression. Finally, we address the potential clinical applications of ECVs, particularly their use as diagnostic tools and drug delivery vehicles, while considering the challenges associated with clinical implementation.

Comprehensive serum proteomics profiles and potential protein biomarkers for the early detection of advanced adenoma and colorectal cancer.

The majority of colorectal cancer (CRC) cases develop from precursor advanced adenoma (AA). With the development of proteomics technologies, blood protein biomarkers have potential applications in the early screening of AA and CRC in the general population. To identify serum protein biomarkers for the early screening of AA and CRC. We collected 43 serum samples from 8 normal controls (NCs), 19 AA patients and 16 CRC patients at China-Japan Friendship Hospital. Quantitative proteomic analysis was performed using liquid chromatography-mass spectrometry/mass spectrometry and data independent acquisition, and differentially expressed proteins (DEPs) with P-values < 0.05 and absolute fold changes > 1.5 were screened out, followed by bioinformatics analysis. Prognosis was further analyzed based on public databases, and proteins expression in tissues were validated by immunohistochemistry. A total of 2132 proteins and 17365 peptides were identified in the serum samples. There were 459 upregulated proteins and 118 downregulated proteins in the NC vs AA group, 289 and 180 in the NC vs CRC group, and 52 and 248 in the AA vs CRC group, respectively. Bioinformatic analysis revealed that these DEPs had different functions and participated in extensive signaling pathways. We also identified DIAPH1, VASP, RAB11B, LBP, SAR1A, TUBGCP5, and DOK3 as important proteins for the progression of AA and CRC. Furthermore, VASP (P < 0.01), LBP (P = 0.01), TUBGCP5 (P < 0.01), and DOK3 (P < 0.01) were associated with a poor prognosis. In addition, we propose that LBP and VASP may be more promising protein biomarkers for the early screening of colorectal tumors. Our study elucidated the serum proteomic profiles of AA and CRC patients, and the identified proteins, such as LBP and VASP, may contribute to the early detection of AA and CRC.