Biomarkers For Detection Of Cancer Research Articles

Advancements in Early Detection and Screening Strategies for Pancreatic Cancer: From Genetic Susceptibility to Novel Biomarkers.

Pancreatic cancer is a rare but lethal cancer due to its biologically aggressive nature, advanced stage at the time of diagnosis, and poor response to oncologic therapies. The risk of pancreatic cancer is significantly higher to 5% in certain high-risk individuals with inherited genetic susceptibility. Screening for pancreatic cancer in these individuals from high-risk groups can help with the early detection of pancreatic cancer as well as the detection of precursor lesions leading to early surgical resection and improved overall outcomes. The advancements in radiological imaging as well as advanced endoscopic procedures has made a significant impact on the early diagnosis, surveillance, and staging of pancreatic cancer. There is also a significant advancement in the development of biomarkers for the early detection of pancreatic cancer, which has also led to the development of liquid biopsy, allowing for microRNA detection in serum and circulating tumor cells. Various societies and organizations have provided guidelines for pancreatic cancer screening and surveillance in high-risk individuals. In this review, we aim to discuss the hereditary risk factors for developing pancreatic cancer, summarize the screening recommendations by different societies, and discuss the development of novel biomarkers and areas for future research in pancreatic cancer screening for high-risk individuals.

Ultrasensitive Detection of Cancer Biomarkers Using Photonic-Crystal-Enhanced Single-Molecule Imaging.

The rapid and sensitive quantification of low-abundance protein markers holds immense significance in early disease diagnosis and treatment. Single-molecule fluorescence imaging exhibits very high detection sensitivity and thus has great application potential in this area. The single-molecule signal, however, is often susceptible to interference from background noise due to its inherently weak intensity. A variety of signal amplification techniques based on cascading reactions have been developed to improve the signal-to-noise ratio of single-molecule imaging. Nevertheless, the operation of these methods is typically complicated and time-consuming, which limits the clinical application. Herein, we introduce an enzyme-free, photonic-crystal-based single-molecule (PC-SM) biochip for cost-effective, time-efficient, and ultrasensitive detection of disease markers. The PC-SM biochip can enhance the signal-to-noise ratio of single molecules by nearly 3-fold compared with unamplified samples, through coupling of the single-molecule photon energy with the optical band gap of the photonic crystal. We used the PC-SM biochip to detect the low-abundance leukemia inhibitory factor in the blood of pancreatic cancer patients and healthy people and achieved a detection limit of 2.0 pg/L and an AUC of 0.9067. The method exhibits exceptional sensitivity and specificity, showing great application potential in various clinical settings.

Next-Generation Electrochemical Biosensing Based on Ternary Nanocomposites of nMoS2@Rgo@MWCNT for Label-Free Cancer Biomarker Detection in Undiluted Human Serum

Sperm protein-17 (Sp17) is a cancer-testicular antigen that is expressed in various types of cancers and has been proposed as a potential biomarker for cancer. However, the detection of Sp17 in human serum is challenging due to its low concentration and the lack of specific and sensitive methods. Hence, there is an urgent need to develop fast, accurate, reliable, and cost-effective disposable biosensors for Sp17 detection. Herein, we report sensing of Sp17 with a disposable carbon cloth-based electrode (CC) modified with a ternary nanocomposite comprising molybdenum disulphide (MoS2), reduced graphene oxide (rGO), and multi-walled carbon nanotube (MWCNT). The nanocomposite was synthesized by a facile hydrothermal method and was well-characterized in terms of structural, morphological, and chemical attributes using X-ray diffraction, transmission electron microscopy, scanning electron microscopy, Raman spectroscopy spectral techniques, and electrochemical studies to prove the robust formation of the electroactive ternary nanocomposite and its suitability for Sp17 detection. The nanocomposite exhibited excellent electrocatalytic activity, biocompatibility, and stability. We immobilized a Sp17-specific antibody on the surface of the nanocomposite-modified electrode and used it as a biosensor for Sp17 detection. The biosensor showed a linear response range from 0.01 to 11 ng mL-1 and a limit of detection (LOD) and limit of quantification (LOQ) of 0.23 ng mL-1 and 0.79 ng mL-1, respectively having sensitivity of 9.97 mA ng mL-1 cm-2. The biosensor was successfully applied to detect Sp17 in human serum samples and showed good accuracy, reproducibility, and selectivity, making it helpful for use in translational medicine research and clinical applications. The biosensor also demonstrated a high correlation with a commercial enzyme-linked immunosorbent assay (ELISA) kit. Our results suggest that the proposed biosensor is a promising tool for Sp17 detection in human serum and could be useful for the diagnosis and prognosis of ovarian cancer and other Sp17-related cancers. Keywords: Carbon cloth; Biosensor; Electrochemistry; Sperm protein 17; Cancer biomarker; Nanocomposite

Multi-omic analysis identifies metabolic biomarkers for the early detection of breast cancer and therapeutic response prediction

Reliable blood-based tests for identifying early-stage breast cancer remain elusive. Employing single-cell transcriptomic sequencing analysis, we illustrate a close correlation between nucleotide metabolism in the breast cancer and activation of regulatory Tcells (Tregs) in the tumor microenvironment, which shows distinctions between subtypes of patients with triple-negative breast cancer (TNBC) and non-TNBC, and is likely to impact cancer prognosis through the A2AR-Treg pathway. Combining machine learning with absolute quantitative metabolomics, we have established an effective approach to the early detection of breast cancer, utilizing a four-metabolite panel including inosine and uridine. This metabolomics study, involving 1111 participants, demonstrates high accuracy across the training, test, and independent validation cohorts. Inosine and uridine prove predictive of the response to neoadjuvant chemotherapy (NAC) in patients with TNBC. This study deepens our understanding of nucleotide metabolism in breast cancer development and introduces a promising non-invasive method for early breast cancer detection and predicting NAC response in patients with TNBC.

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.

Evaluation of the Plasma Expression Levels of miR-21 and miR-145 as Potential Non-Invasive Biomarkers for Early Detection of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in the world. Early detection would be greatly enhanced if accurate and cost-effective diagnostic biomarkers for CRC were accessible. The development of blood tests would evidently lower the screening cost of CRC detection. The aim of the present study was to examine the prospective of plasma miRNAs as non-invasive biomarkers for CRC screening. The expressions of miR-21 and miR-145 in the plasma of colorectal adenocarcinomas and normal healthy controls were quantified by using TaqMan miRNA assays. MiRNA expression levels were also correlated with commonly used clinicopathological features of CRC. Out of 30 CRC patients, 19 were male and 11 were female. The Mean age of patients was 51.3 ±14.6 years. A statistically significant increase in expression of miR-21 was observed in CRC patients' as compared to healthy controls (p<0.001). A significant association between miR-21 expression and age group (p=0.002) was noticed. Also, a statistically significant difference (p=0.015) between miR-21 expression and tumor location in the proximal and distal sites of the colon was observed in CRC patients. Further, a statistically significant downregulation of miR-145 expression was observed in the plasma of CRC patients as compared to healthy controls (p<0.05). This is the first study to report a significant association between miR-21 expression, age group, and tumor location in CRC patients. The present study thus emphasises that the appraisal of miR-21 and miR-145 plasma levels may serve as a promising non-invasive screening tool for the early detection of colorectal cancer.

Circulating tumour DNA analysis for early detection of lung cancer: a systematic review.

Circulating tumor DNA (ctDNA) analysis has been applied in cancer diagnostics including lung cancer. Specifically for the early detection purpose, various modalities of ctDNA analysis have demonstrated their potentials. Such analyses have showed diverse performance across different studies. We performed a systematic review of original studies published before 1 January 2023. Studies that evaluated ctDNA alone and in combination with other biomarkers for early detection of lung cancer were included. The systematic review analysis included 56 original studies that were aimed for early detection of lung cancer. There were 39 studies for lung cancer only and 17 for pan-cancer early detection. Cancer and control cases included were heterogenous across studies. Different molecular features of ctDNA have been evaluated, including 7 studies on cell-free DNA concentration, 17 on mutation, 29 on methylation, 5 on hydroxymethylation and 8 on fragmentation patterns. Among these 56 studies, 17 have utilised different combinations of the above-mentioned ctDNA features and/or circulation protein markers. For all the modalities, lower sensitivities were reported for the detection of early-stage cancer. The systematic review suggested the clinical utility of ctDNA analysis for early detection of lung cancer, alone or in combination with other biomarkers. Future validation with standardised testing protocols would help integration into clinical care.

Unraveling the Connection: Extracellular Vesicles and Non-Small Cell Lung Cancer.

Extracellular vesicles (EVs) are nanoscale lipid bilayer vesicles released during cell activation, cellular damage, or apoptosis. They carry nucleic acids, proteins, and lipids facilitating intercellular communication and activate signaling pathways in target cells. In non-small cell lung cancer (NSCLC), EVs may contribute to tumor growth and metastasis by modulating immune responses, facilitating epithelial-mesenchymal transition, and promoting angiogenesis, while potentially contributing to resistance to chemotherapy drugs. EVs in liquid biopsies serve as non-invasive biomarkers for early cancer detection and diagnosis. Due to their small size, inherent molecular transport properties, and excellent biocompatibility, EVs also act as natural drug delivery vehicles in NSCLC therapy.

Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.

Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs). In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database. Cuproptosis-related lncRNAs were identified and used to develop a prognostic model, which helped categorize patients into high- and low-risk groups. The model was validated through survival analysis, risk curves, independent prognostic analysis, receiver operating characteristic curve analysis, decision curves, and nomograms. In addition, we performed various immune-related analyses. LncRNA expression levels were examined in normal human colorectal epithelial cells (FHC) and CRC cells (HCT-116) using quantitative polymerase chain reaction (qPCR). Six cuproptosis-related lncRNAs were identified: ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2, AL137782.1, and AC099850.3. The prognostic model distinguished between high-/low-risk populations, demonstrating excellent predictive ability for survival outcomes. Immunocorrelation analysis showed significant differences in immune cell infiltration and functions, immune checkpoint expression, and m6A methylation-related genes. The qPCR results showed significant upregulation of ZKSCAN2-DT, AL161729.4, AC016394.1, AC007128.2 in HCT-116 cells, while AL137782.1 and AC099850.3 expression patterns were significantly downregulated. Cuproptosis-related lncRNAs can potentially serve as reliable diagnostic and prognostic biomarkers for CRC.

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.

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 785 nm excitation laser is utilized to collect SERS signals. The developed system demonstrates excellent selectivity and sensitivity, with low limits of detection (LODs) of 3.58 pg mL−1 and 4.83 pg mL−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.

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.