Serum Biomarker For Cancer Research Articles

Tissue factor pathway inhibitor 2 as a serum biomarker for endometrial cancer: a single-center retrospective study

BackgroundEndometrial cancer is the most common gynecological malignancy; however, there is no useful blood diagnostic biomarker. This study aimed to determine the utility of tissue factor pathway inhibitor 2 (TFPI2), a biomarker of ovarian cancer, as a diagnostic marker for endometrial cancer.MethodsWe examined serum TFPI2 levels in patients with endometrial cancer (n = 328) compared to those in healthy controls (n = 65) and evaluated the performance of serum TFPI2 levels as a diagnostic marker. We investigated the clinicopathological characteristics of patients with TFPI2-negative and TFPI2-positive endometrial cancer. Using immunohistochemistry (IHC), we examined TFPI2 expression in tumor tissues of 105 patients with type II endometrial carcinoma and evaluated the correlation between serum and tissue TFPI2 positivity.ResultsPatients with endometrial cancer had significantly higher serum TFPI2 levels than controls (196.7 pg/mL vs. 83.3 pg/mL; p < 0.001). The sensitivity and specificity were 54.3% and 95.4%, respectively (cutoff value, 191 pg/mL). Serum TFPI2 levels were significantly elevated along with the stage progression (stage I, 189.6 pg/mL; stage III, 230.9 pg/mL; stage IV, 312.5 pg/mL; p < 0.001). Patients with high-risk histology showed significantly elevated serum TFPI2 levels than those with low-risk histology (220.8 pg/mL vs. 187.7 pg/mL; p < 0.001). The positivity rate for TFPI2 was the highest among tumor markers, including CA125, CA19-9, and CEA. Serum TFPI2 and CA125 levels were almost independent (r = 0.203, p < 0.001), and the combined sensitivity increased to 58.8%. The 5-year survival rate was significantly worse in TFPI2-positive patients (≥ 191 pg/mL, n = 178) than in TFPI2-negative patients (< 191 pg/mL, n = 150) (hazard ratio, 8.22; 95% confidence interval, 2.49–27.1; p < 0.001). TFPI2 immunostaining revealed that 37.1% (39/105) of the samples were positive for TFPI2, with an IHC score of > 0. There was no significant difference in the immunostaining score according to histological type. Serum TFPI2 levels and immunostaining score showed poor agreement (kappa coefficient, -0.039).ConclusionsThe serum TFPI2 level is a promising marker for diagnosing and predicting the prognosis of endometrial cancer. No correlation exists between serum and tissue TFPI2 levels. Further multicenter clinical trials are needed to test the utility of TFPI2 as a diagnostic marker.

Evaluation of Serum Cytokeratines, Thymidine Kinase, and Growth Factors as Cancer Biomarkers in Colorectal Cancer.

Classical serum cancer biomarkers, such as carcinoembryonic antigen (CEA) and cancer antigen 19-9 (CA 19-9), remain important tools in colorectal cancer (CRC) management for disease follow up. However, their sensitivity and specificity are low for diagnostic and prognostic evaluation. The aim of this study was to evaluate the potential of biomarkers reflecting biological activity of tumors - tissue polypeptide specific antigen (TPS), cytokeratin fragment 19 (CYFRA 21-1), thymidine kinase (TK), insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein 3 (IGF-BP3) - together with the CEA and CA 19-9 in CRC diagnosis and prognosis. This is a retrospective study including 148 CRC patients and 68 age-matched healthy subjects. Serum biomarkers were measured in pre-operative serum samples using immunoanalytical methods. The end-point for the diagnostic evaluation was the area under the receiving operating characteristic curve (AUC ROC) of the biomarkers. The end-point for the prognostic evaluation was overall survival. Serum levels of CEA, CA 19-9, TPS, and TK were significantly increased in CRC early-stage patients compared with healthy controls. Each of the studied biomarkers had AUC between 0.6 and 0.7. Analysis of survival demonstrated that the patients with CEA, CA 19-9, cytokeratin, and TK above optimal cut offs had significantly shorter survival. A multivariate analysis performed on all the study biomarkers resulted in the selection of CYFRA 21-1 as the best performing biomarker with hazard ratio 10.413. The combination of cytokeratins and thymidine kinase with classical cancer biomarkers enables the prediction of tumor aggressiveness and long-term prognosis.

Cervicovaginal Metabolome and Tumor Characteristics for Endometrial Cancer Detection and Risk Stratification.

Endometrial cancer is highly prevalent and lacking noninvasive diagnostic techniques. Diagnosis depends on histological investigation of biopsy samples. Serum biomarkers for endometrial cancer have lacked sensitivity and specificity. The objective of this study was to investigate the cervicovaginal environment to improve the understanding of metabolic reprogramming related to endometrial cancer and identify potential biomarker candidates for noninvasive diagnostic and prognostic tests. Cervicovaginal lavages were collected from 192 participants with endometrial cancer (n = 66) and non-malignant conditions (n = 108), and global untargeted metabolomics was performed. Using the metabolite data (n = 920), we completed a multivariate biomarker discovery analysis. We analyzed grade 1/2 endometrioid carcinoma (n = 53) and other endometrial cancer subtypes (n = 13) to identify shared and unique metabolic signatures between the subtypes. When compared to non-malignant conditions, downregulation of proline (P < 0.0001), tryptophan (P < 0.0001), and glutamate (P < 0.0001) was found among both endometrial cancer groups, relating to key hallmarks of cancer including immune suppression and redox balance. Upregulation (q < 0.05) of sphingolipids, fatty acids, and glycerophospholipids was observed in endometrial cancer in a type-specific manner. Furthermore, cervicovaginal metabolites related to tumor characteristics, including tumor size and myometrial invasion. Our findings provide insights into understanding the endometrial cancer metabolic landscape and improvement in diagnosis. The metabolic dysregulation described in this article linked specific metabolites and pathophysiological mechanisms including cellular proliferation, energy supply, and invasion of neighboring tissues. Furthermore, cervicovaginal metabolite levels related to tumor characteristics, which are used for risk stratification. Overall, development of noninvasive diagnostics can improve both the acceptability and accessibility of diagnosis.

Screening of lung cancer serum biomarkers based on Boruta-shap and RFC-RFECV algorithms

ObjectiveThis study aimed to identify a set of serum miRNAs as potential biomarkers for lung cancer diagnosis using algorithmic approaches. MethodsSerum miRNA expression data from lung cancer patients and non-tumor controls were obtained. The top six miRNAs were selected using Boruta-shap and RFC-RFECV algorithms. A Gaussian Naive Bayes (NB) classifier was trained and evaluated using cross-validation, ROC curve analysis, and evaluation metrics. ResultsSix miRNAs (hsa-miRNA-144, hsa-miRNA-107, hsa-miRNA-484, hsa-miRNA-103, hsa-miRNA-26b, and hsa-miRNA-641) were identified as feature genes. The NB classifier achieved an area under curve (AUC) of 0.8966 and a mean AUC of 0.88 in cross-validation. Accuracy, recall, and F1 scores exhibited promising results, with an accuracy of 82%. In the validation set, the AUC values for the NB and SVC classifiers were 0.9345 and 0.9423, respectively, with a mean AUC of 0.95 in cross-validation. The classifiers demonstrated an accuracy of 89% in diagnosing lung cancer. ConclusionThis study identified a panel of six serum miRNAs with potential as non-invasive biomarkers for lung cancer diagnosis. These miRNAs show promise in providing sensitive and specific tools for detecting lung cancer. SignificanceLung cancer is one of the top cancers worldwide, threatening the health and lives of tens of thousands of people. miRNA is a biomarker, which can be used as a potential clinical tool for diagnosis and prognosis of cancer patients. Therefore, the use of multiple miRNAs to construct diagnostic models may be one of the future methods of accurate diagnosis of lung cancer. In this study, we used the Boruta-shap and RFC-RFECV algorithms to automatically identify and extract characteristic miRNAs highly associated with lung cancer, thereby establishing an accurate classifier for the diagnosis of lung cancer with characteristic miRNAs.

Fabrication of and characterization of directional antibody-conjugated gold nanourchin colloid and effect of laser polarization on SERS detection of breast cancer biomarker in serum

We describe the results of citrate-stabilized 100 nm gold nanourchins (GNU) functionalized and conjugated with monoclonal antibody (mAb) in directional orientation to investigate the interaction with breast cancer serum (BCS) overexpressed with CA 15–3 biomarker. UV-Vis, fluorescence, FT-NIR spectroscopy, and SERS with 637 nm Raman probe were employed for non-destructive analysis. UV-Vis spectroscopy exhibited two distinct peaks at 230 and 280 nm related to tyrosine (Tyr) and tryptophan (Trp) with the corresponding fluorescence peaks at 285 and 315 nm respectively. FT-NIR showed some new lines after the interaction such as CH2 combination in carbohydrates, and NH2 amino acids. Directional orientation indicated a higher SERS intensity than random due to higher parallel dipole moments of asymmetric molecules and the polarization sensitivity of GNU. The SERS signals increased significantly after the interaction and the intensity of the Raman lines varied nonlinearly with the laser power. The data were filtered using the filtfilt filter from scipy.signals, baseline corrected using the Improved Asymmetric Least Squares (isals) function from the pybaselines.Whittaker library, and normalized using the minmax_scale function from sklearn.preprocessing. The scikit-learn Principal Component Analysis (PCA) function was used to analyze the dataset by identifying the directions of maximum variability in the data.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

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.

Correlation Analysis Between Serum Cancer Biomarkers and Nutrition Index Score in Lung Cancer Patients

This study investigates the correlation between serum cancer biomarkers and nutrition index scores in a retrospective analysis of 200 hospitalized lung cancer patients from March 2018 to March 2022. Benign pulmonary nodule patients (n = 50) and healthy subjects (n = 32) were randomly selected. The serum levels of carcinoembryonic antigen (CEA), nerve-specific enolase (NSE), cytokeratin 19 fragment (CYFRA21-1), squamous cell carcinoma antigen (SCCA), and cancer antigen 125 (CA125) were measured using a nano-magnetic particle chemiluminescence method. The serum levels of alkaline phosphatase (ALP), albumin (ALB), total cholesterol, and peripheral blood lymphocyte count were analyzed using an automatic biochemical analyzer. Differential expression analysis was conducted to identify significant serum indexes in lung cancer patients. Based on the serum nutritional index level, controlling nutritional status (CONUT) scores were calculated for each patient and used to categorize them into high-score or low-score groups. The results demonstrated a significant increase in the expression levels of CEA, NSE, CYFRA21-1, SCCA, CA125, ALB, and ALP in patients diagnosed with lung cancer. Patients with higher CONUT scores were more susceptible to pulmonary infection and cancer pain and had higher CEA, NSE, CYFRA21-1, and ALP levels than those with lower scores. Regression analysis revealed a positive correlation between the CONUT score and the levels of CEA, NSE, and CYFRA21-1. Therefore, the increase in cancer biomarkers is related to the nutritional status of lung cancer patients, and a declining nutritional score can predict disease progression and assess lung cancer.

Nomogram predicts risk of perineural invasion based on serum biomarkers for pancreatic cancer

BackgroundPancreatic cancer is a fatal tumor, and the status of perineural invasion (PNI) of pancreatic cancer was positively related to poor prognosis including overall survival and recurrence-free survival. This study aims to develop and validate a predictive model based on serum biomarkers to accurately predict the perineural invasion.Materials and methodsThe patients from No.924 Hospital of PLA Joint Logistic Support Force were included. The predictive model was developed in the training cohort using logistic regression analysis, and then tested in the validation cohort. The area under curve (AUC), calibration curves and decision curve analysis were used to validate the predictive accuracy and clinical benefits of nomogram.ResultsA nomogram was developed using preoperative total bilirubin, preoperative blood glucose, preoperative CA19-9. It achieved good AUC values of 0.753 and 0.737 in predicting PNI in training and validation cohorts, respectively. Calibration curves showed nomogram had good uniformity of the practical probability of PNI. Decision curve analyses revealed that the nomogram provided higher diagnostic accuracy and superior net benefit compared to single indicators.ConclusionThe present study constructed and validate a novel nomogram predicted the PNI of resectable PHAC patients with high stability and accuracy. Besides, it could better screen high-risk probability of PNI in these patients, and optimize treatment decision-making.

Telomerase RNA component lncRNA as potential diagnostic biomarker promotes CRC cellular migration and apoptosis evasion via modulation of β-catenin protein level.

Long non-coding RNA (LncRNA) telomerase RNA component (TERC) has telomerase-dependent and independent activity in numerous cancer types. The present study purposes to demonstrate the role of lncRNA TERC as a diagnostic serum biomarker in colorectal cancer (CRC) patients and the molecular mechanism of lncRNA TERC in inducing tumor in CRC cell lines. PCR array was performed to examine lncRNAs dysregulated in CRC. LncRNA TERC expression level was evaluated in 70 CRC patients and 35 control subjects using RT-qPCR. Then transfection was performed to build down-expression models of lncRNA TERC. ROC curve analysis was applied to assess the diagnostic value of serum LncRNA CRC. In addition, RT-qPCR was used to detect expression level of lncRNA TERC and β-catenin mRNA. Moreover, ELISA and Western blot were used to detect the level of β-catenin protein in sera of CRC patients and cell lines. The biological functions such as cell growth and migration of CRC cells were assessed using a wound healing assay. Cell cycle analysis and apoptosis analysis were performed using flow cytometry. The lncRNA TERC is overexpressed in the sera of CRC patients with high diagnostic and stage discrimination accuracy. Furthermore, lncRNA TERC expression was upregulated in CRC cell lines and lncRNA TERC silencing induced cell arrest and apoptosis and inhibited cell migration. Furthermore, inhibition of lncRNA TERC reduces β-catenin protein levels. The lncRNA TERC could be considered as an early stages CRC diagnostic biomarker with a good ability to discriminate between CRC stages. lncRNA TERC induces CRC by promoting cell migration and evading apoptosis by elevating the level of β-catenin protein.

Cell-free circulating ALU repeats in serum have a prognostic value for colorectal cancer patients.

Carcinoembryonic antigen (CEA) is the only established serum biomarker for colorectal cancer (CRC). To facilitate therapy decisions and improve the overall survival of CRC patients, prognostic biomarkers are required. We studied the prognostic value of five different cell free circulating DNA (fcDNA) fragments. The potential markers were ALU115, ALU247, LINE1-79, LINE1-300 and ND1-mt. The copy numbers of the DNA fragments were measured in the peripheral blood serum of 268 CRC patients using qPCR, the results were compared to common and previously described markers. We found that ALU115 and ALU247 fcDNA levels correlate significantly with several clinicopathological parameters. An increased amount of ALU115 and ALU247 fcDNA fragments coincides with methylation of HPP1 (P< 0.001; P< 0.01), which proved to be a prognostic marker itself in former studies and also with increased CEA level (P< 0.001). ALU115 and ALU247 can define patients with poor survival in UICC stage IV (Alu115: HR = 2.9; 95% Cl 1.8-4.8, P< 0.001; Alu247: HR = 2.2; 95% Cl 1.3-3.6; P= 0.001). Combining ALU115 and HPP1, the prognostic value in UICC stage IV is highly significant (P< 0.001). This study shows that an increased level of ALU fcDNA is an independent prognostic biomarker for advanced colorectal cancer disease.

Glass-Based Nanobiosensor Immobilized with Oriented Antibody-Conjugated Gold Nanourchin for Targeted Detection of Breast Cancer Biomarker in Serum Using FT-NIR and SERS

Glass-Based Nanobiosensor Immobilized with Oriented Antibody-Conjugated Gold Nanourchin for Targeted Detection of Breast Cancer Biomarker in Serum Using FT-NIR and SERS

Capitalizing glycomic changes for improved biomarker-based cancer diagnostics.

Cancer serum biomarkers are valuable or even indispensable for cancer diagnostics and/or monitoring and, currently, many cancer serum markers are routinely used in the clinic. Most of those markers are glycoproteins, carrying cancer-specific glycan structures that can provide extra-information for cancer monitoring. Nonetheless, in the majority of cases, this differential feature is not exploited and the corresponding analytical assays detect only the protein amount, disregarding the analysis of the aberrant glycoform. Two exceptions to this trend are the biomarkers α-fetoprotein (AFP) and cancer antigen 19-9 (CA19-9), which are clinically monitored for their cancer-related glycan changes, and only the AFP assay includes quantification of both the protein amount and the altered glycoform. This narrative review demonstrates, through several examples, the advantages of the combined quantification of protein cancer biomarkers and the respective glycoform analysis, which enable to yield the maximum information and overcome the weaknesses of each individual analysis. This strategy allows to achieve higher sensitivity and specificity in the detection of cancer, enhancing the diagnostic power of biomarker-based cancer detection tests.

Screening of novel serum biomarkers for gastric cancer in coastal populations using a protein microarray.

Gastric cancer (GC) has high rates of morbidity and mortality, and this phenomenon is particularly evident in coastal regions where local dietary habits favor the consumption of pickled foods such as salted fish and vegetables. In addition, the diagnosis rate of GC remains low due to the lack of diagnostic serum biomarkers. Therefore, in this study, we aimed to identify potential serum GC biomarkers for use in clinical practice. To identify candidate biomarkers of GC, 88 serum samples were first screened using a high-throughput protein microarray to measure the levels of 640 proteins. Then, 333 samples were used to validate the potential biomarkers using a custom antibody chip. ELISA, western blot, and immunohistochemistry were then used to verify the expression of the target proteins. Finally, logistic regression was performed to select serum proteins for the diagnostic model. As a result, five specific differentially expressed proteins, TGFβ RIII, LAG-3, carboxypeptidase A2, Decorin and ANGPTL3, were found to have the ability to distinguish GC. Logistic regression analysis showed that the combination of carboxypeptidase A2 and TGFβ RIII had superior potential for diagnosing GC (area under the ROC curve [AUC] = 0.801). The results suggested that these five proteins alone and the combination of carboxypeptidase A2 and TGFβ RIII may be used as serum markers for the diagnosis of GC.

Tailored pretreatment of serum samples and biomarker extraction afforded by ionic liquids as constituents of aqueous biphasic systems

Prostate cancer serum biomarkers, such as the U.S. Food and Drug Administration (FDA)-approved prostate specific antigen (PSA), are valuable markers of diagnosis, response to treatment and disease progression. Despite the expected benefits of using PSA to better manage the mortality and morbidity associated to prostate cancer, sample complexity and interference within analysis make its quantification in serum a high-cost and strenuous assignment. Here, we make use of the simple preparation, water-rich environment, and selectivity of aqueous biphasic systems (ABS) to develop alternative serum pretreatment strategies. A set of ammonium- and phosphonium-based ionic liquids (ILs) were used as either main phase-forming agents in IL-salt ABS or as adjuvants in polymer-salt ABS, allowing to explore the IL designer solvent nature and versatile role in ABS formation and performance. Serum pretreatment efficiency was evaluated by the capacity of each ABS to simultaneously deplete high abundance serum proteins (immunoglobulin G, IgG, and human serum albumin, HSA) at the systems’ interphase (thus, generating a three-phase partitioning system – ABS-TPP) and extract PSA to a single ABS phase. Regardless of the ABS typology under appraisal (IL-salt or polymer-salt-IL), the proper design of the IL structure is critical for both the ability to deplete high abundance serum proteins and extract PSA. The results demonstrate that, in addition to the proper choice of the ABS typology, a careful adjustment of the IL hydrophobicity is key to achieve the simultaneous depletion of high-abundance proteins and complete PSA extraction in a single step, creating new approaches for PSA analysis and its application in diagnosis/prognosis.

A highly sensitive sensor for carcinoembryonic antigen based on AlGaN/GaN high-electron-mobility transistors

Carcinoembryonic antigen (CEA) is a well-known biomarker and validated serum biomarker for lung cancer. We introduce a simple label-free method for CEA detection. Specific recognition of CEA was made possible by immobilizing CEA antibodies in the sensing region of AlGaN/GaN high-electron-mobility transistors. The biosensors have a detection limit of 1 fg ml−1 in phosphate buffer solution. This approach has advantages of integration, miniaturization, low cost, and rapid detection compared to other testing methods for lung cancer and could be used in future medical diagnostics.

EpCAM is a new potential serum biomarker for early gastric cancer

EpCAM is a new potential serum biomarker for early gastric cancer

Nanodot zirconium trisulfide based highly efficient biosensor for early diagnosis of lung cancer

In present work, we report results of the studies related to the synthesis of nanodot metal chalcogenide (zirconium trisulfide, ∼5.7 nm in size) based biosensing platform for early detection of lung cancer serum biomarker (CKAP4). The nanodot zirconium trisulfide (nZrS3) was synthesized through low temperature hydrothermal method (200 °C for 72 h) and functionalized with 3-aminopropyl triethoxysilane (APTES) molecules via chemical process. To fabricate thin and uniform film onto the pre-hydrolyzed indium tin oxide (ITO) coated glass electrode of functionalized nanomaterials (APTES/nZrS3), an optimized electrophoretic condition (25 V for 60 s) was applied. Further, for covalent immobilization of anti-CKAP4 onto the APTES/nZrS3/ITO electrode, EDC-NHS chemistry was used and for blocking of non-specific binding sites, bovine serum albumin (BSA) was non-covalently immobilized via drop-cast method. The synthesized as well as functionalized nanomaterial and fabricated electrodes were characterized through X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), cyclic voltammetry (CV) and differential pulse voltammetry (DPV) techniques. Further, the electrochemical response studies of developed biosensing platform i.e., BSA/anti-CKAP4/APTES/nZrS3/ITO were carried out through DPV technique. The biosensing platform has ability to detect CKAP4 biomarker in the range of 100 pg mL−1-800 pg mL−1 with ultra-sensitivity of 68.76 µA [log (pg mL−1)]−1cm−2, notable lower detection limit of 86 pg mL−1 and shelf life upto 36 days. Moreover, the electrochemical data obtained, exhibit a good correlation with the concentrations of the cancer biomarker CKAP4 found in lung cancer patients as determined by the enzyme-linked immunosorbent assay (ELISA) technique.

HNRNPA2B1-Mediated MicroRNA-92a Upregulation and Section Acts as a Promising Noninvasive Diagnostic Biomarker in Colorectal Cancer

MicroRNA-92a (miR-92a) may serve as a novel promising biomarker in multiple cancers, including colorectal cancer (CRC); however, the diagnostic accuracy and the underlying molecular mechanism of miR-92a in CRC is poorly understood. We first carried out meta-analysis and found that serum/plasma miR-92a yield better diagnostic efficacy when compared to stool samples and CRC tissues, and this finding was validated by our independent study through stool sample. Multiple bioinformatics assay indicated that miR-92a expression was positively correlated with heterogeneous nuclear ribonucleoproteins A2/B1 (HNRNPA2B1) expression and closely related with the clinical characteristics of CRC. Experimental evidence showed that knockdown of HNRNPA2B1 could significantly decrease miR-92a expression and secretion in RKO cells. HNRNPA2B1 mediated miR-92a via m6A RNA modification. These findings indicate that HNRNPA2B1-m6A RNA modification-derived MicroRNA-92a upregulation and section from the local CRC acts a candidate noninvasive serum biomarker in colorectal cancer. Our study provides a novel insight into miR-92a mechanisms in relation to both expression and secretion for CRC diagnosis.

Response Evaluation in Patients with Peritoneal Metastasis Treated with Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC).

Pressurized intraperitoneal aerosol chemotherapy (PIPAC) directed therapy emerged as a treatment of peritoneal metastasis (PM) a decade ago. The response assessment of PIPAC is not uniform. This narrative review describes non-invasive and invasive methods for response evaluation of PIPAC and summarizes their current status. PubMed and clinicaltrials.gov were searched for eligible publications, and data were reported on an intention-to-treat basis. The peritoneal regression grading score (PRGS) showed a response in 18-58% of patients after two PIPACs. Five studies showed a cytological response in ascites or peritoneal lavage fluid in 6-15% of the patients. The proportion of patients with malignant cytology decreased between the first and third PIPAC. A computed tomography showed stable or regressive disease following PIPAC in 15-78% of patients. The peritoneal cancer index was mainly used as a demographic variable, but prospective studies reported a response to treatment in 57-72% of patients. The role of serum biomarkers of cancer or inflammation in the selection of candidates for and responders to PIPAC is not fully evaluated. In conclusion, response evaluation after PIPAC in patients with PM remains difficult, but PRGS seems to be the most promising response evaluation modality.