Combining multiple serum biomarkers in tumor diagnosis: A clinical assessment

Advanced detection of cervical cancer biomarkers using engineered filamentous phage nanofibers

Cervical cancer is a major global health concern, characterized by its high incidence and mortality rates. The detection of tumor markers is crucial for managing cancer, making treatment decisions, and monitoring disease progression. Vascular endothelial growth factor (VEGF) and programmed death-ligand 1 (PDL-1) are key targets in cervical cancer therapy and valuable biomarkers in predicting treatment response and prognosis. In this study, we found that combining the measurement of VEGF and soluble PDL-1 can be used for diagnosing and evaluating the progression of cervical cancer. To explore a more convenient approach for detecting and assessing cervical cancer, we designed and prepared an engineered fd bacteriophage, a human-safe viral nanofiber, equipped with two peptides targeting VEGF and PD-L1. The dual-display phage nanofiber specifically recognizes and binds to both proteins. Utilizing this nanofiber as a novel capture agent, we developed a new enzyme-linked immunosorbent assay (ELISA) method. This method shows significantly enhanced detection sensitivity compared to conventional ELISA methods, which use either anti-VEGF or anti-PD-L1 antibodies as capture agents. Therefore, the phage dual-display nanofiber presents significant potential in detecting cancer markers, evaluating medication efficacy, and advancing immunotherapy drug development. KEY POINTS: • The combined measurement of VEGF and soluble Programmed Death-Ligand 1(sPD-L1) demonstrates an additive effect in the diagnosis of cervical cancer. Fd phage nanofibers have been ingeniously engineered to display peptides that bind to VEGF and PD-L1, enabling the simultaneous detection of both proteins within a single assay • Genetically engineered phage nanofibers, adorned with two distinct peptides, can be utilized for the diagnosis and prognosis of cancer and can be mass-produced cost-effectively through bacterial infections • Employing dual-display fd phage nanofibers as capture probes, the phage ELISA method exhibited significantly enhanced detection sensitivity compared to traditional sandwich ELISA. Furthermore, phage ELISA facilitates the detection of a single protein or the simultaneous detection of multiple proteins, rendering them powerful tools for protein analysis and diagnosis across various fields, including cancer research.

Diagnostic Accuracy of Biomarkers and International Ovarian Tumor Analysis Simple Rules in Diagnosis of Ovarian Cancer

This study investigated whether combining International Ovarian Tumor Analysis (IOTA) Simple Rules with tumor biomarkers would improve the diagnostic accuracy for early detection of adnexal malignancies. Receiver operating characteristic curve analysis of suspected adnexal tumors was performed in 226 women admitted for surgery at the University Clinical Center of Kosovo. Primary outcome was the diagnostic accuracy of the combination of adnexal mass biomarkers and IOTA Simple Rules. IOTA Simple Rules combined with biomarker indications increased the diagnostic accuracy of classifying adnexal masses. Data analysis of individual measures showed that ferritin had the lowest rate of sensitivity.

Clinical Utility of Circulating Tumor Cells in the Early Detection of Lung Cancer in Patients with a Solitary Pulmonary Nodule

Objective: Lung cancer is the most common cancer and can appear as a solitary pulmonary nodule. Early detection of lung cancer in this patient population would be beneficial for the disease management. In this study, the potential application of circulating tumor cells (CTCs) on early detection of lung cancer in this population was investigated. Methods: The number of CTCs in bronchoalveolar lavage fluid and serum levels of tumor-related markers, cancer antigen 125 (CA125), carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) were measured in patients with a solitary pulmonary nodule. The association between CTCs and lung cancer was examined. The diagnosis performances of CTCs and selected tumor-related markers were compared. Results: The CTC positivity was significantly associated with lung cancer (P = .009). The sensitivity of CTCs and CA125, CEA, NSE, and CA125/CEA/NSE was 75%, 5.6%, 0%, 25%, and 33%, respectively. The sensitivity of CTCs was improved from 75% to 83% by the combination with CA125 or NSE. Conclusion: CTCs may be helpful for the early detection of lung cancer in patients with a solitary pulmonary nodule.

Long non-coding RNA AGAP2-AS1 is up regulated in colorectal cancer

Accumulating evidence has indicated that, aberrant lncRNA expression plays essential roles in the colorectal cancer (CRC) tumorigenesis. AGAP2-AS1 is upregulated in some cancers, however, its involvement in the CRC tumorigenesis in the population of North-West of Iran has remained unknown. In this study, we evaluated its deregulation in CRC microarray datasets, colon cell lines, CRC tumor, adenomatous colorectal polyps and their paired normal tissues. The results showed that AGAP2-AS1 is upregulated in CRC and might be considered as a potential biomarker for CRC development. Moreover, our results suggest AGAP2-AS1 promoted CRC progression by sponging the hsa-miR-15/16 family and upregulation of their targets.

The function of LncRNAs and their role in the prediction, diagnosis, and prognosis of lung cancer

Lung cancer remains a major threat to human health. Low dose CT scan (LDCT) has become the main method of early screening for lung cancer due to the low sensitivity of chest X-ray. However, LDCT not only has a high false positive rate, but also entails risks of overdiagnosis and cumulative radiation exposure. In addition, cumulative radiation by LDCT screening and subsequent follow-up can increase the risk of lung cancer. Many studies have shown that long noncoding RNAs (lncRNAs) remain stable in blood, and profiling of blood has the advantages of being noninvasive, readily accessible and inexpensive. Serum or plasma assay of lncRNAs in blood can be used as a novel detection method to assist LDCT while improving the accuracy of early lung cancer screening. LncRNAs can participate in the regulation of various biological processes. A large number of researches have reported that lncRNAs are key regulators involved in the progression of human cancers through multiple action models. Especially, some lncRNAs can affect various hallmarks of lung cancer. In addition to their diagnostic value, lncRNAs also possess promising potential in other clinical applications toward lung cancer. LncRNAs can be used as predictive markers for chemosensitivity, radiosensitivity, and sensitivity to epidermal growth factor receptor (EGFR)-targeted therapy, and as well markers of prognosis. Different lncRNAs have been implicated to regulate chemosensitivity, radiosensitivity, and sensitivity to EGFR-targeted therapy through diverse mechanisms. Although many challenges need to be addressed in the future, lncRNAs have bright prospects as an adjunct to radiographic methods in the clinical management of lung cancer.

Application of Lectin Microarrays for Biomarker Discovery

Many proteins in living organisms are glycosylated. As their glycan patterns exhibit protein-, cell-, and tissue-specific heterogeneity, changes in the glycosylation levels could serve as useful indicators of various pathological and physiological states. Thus, the identification of glycoprotein biomarkers from specific changes in the glycan profiles of glycoproteins is a trending field. Lectin microarrays provide a new glycan analysis platform, which enables rapid and sensitive analysis of complex glycans without requiring the release of glycans from the protein. Recent developments in lectin microarray technology enable high-throughput analysis of glycans in complex biological samples. In this review, we will discuss the basic concepts and recent progress in lectin microarray technology, the application of lectin microarrays in biomarker discovery, and the challenges and future development of this technology. Given the tremendous technical advancements that have been made, lectin microarrays will become an indispensable tool for the discovery of glycoprotein biomarkers.

Porcine seminal protein-I and II mRNA expression in boar spermatozoa is significantly correlated with fertility

In recent years, genomic and proteomic biomarkers have been identified for the diagnosis of male fertility to overcome the limitations of conventional semen analysis. Owing to the limited genes available so far, the single gene approach is commonly adopted for analyzing the phenotype of interest. However, the single-gene approach is less effective than multiple-gene strategies for diagnosing a desirable phenotype. Herein, we investigate the ability of two fertility-related genomic markers (porcine seminal protein (PSP)-I and PSP-II) in spermatozoa to predict boar litter size in addition to conventional semen parameters. First, we examined different semen parameters (motility, motion kinematics, and capacitation status) and gene expression in high- and low-litter size boar spermatozoa. Then, we evaluated the correlation of these parameters with the fertility of 21 Yorkshire boars. Finally, we investigated the efficacy of single/combined markers to predict male fertility using a comprehensive statistical model. Our result showed that there were no significant differences in sperm motility, motion kinematics, or capacitation status, however, the mRNA expression of PSP-I and PSP-II in spermatozoa was significantly different in high- and low-litter size boars. In the individual screening test, the expression of both genes was negatively correlated with boar fertility (r = 0-0.578 and -0.456, respectively), whereas only hyperactivation (HYP) showed a positive correlation (r = 0.444) among the tested semen parameters. As single markers, PSP-I and PSP-II have a better diagnostic power to predict boar fertility, regardless of HYP, in quality assessment analyses. In addition, when these markers were combined, the positive predictive value, negative predictive value, and overall test effectiveness for fertility detection were improved. Surprisingly, when PSP-I and PSP-II were considered together, the deviation of the predicted average litter size between high- and low-litter size boars was 1.77. Based on the findings, we suggest that the use of genomic markers in spermatozoa rather than commonly analyzed semen parameters may be more accurate for evaluating male fertility. Moreover, using a combination of markers could increase the overall accuracy of (in)fertility predictions, and thus, could be considered for field application.

Diagnostic value of CA-153 and CYFRA 21-1 in predicting intraocular metastasis in patients with metastatic lung cancer

Lung cancer is prone to metastasis to various organs. Although intraocular metastasis (IOM) occurs at a later stage than metastasis to other organs, it often adversely affects the quality of life and suggests a poor prognosis. In this study, we selected 1608 patients with lung cancer who had metastasis to at least one site and explored clinical differences between those with IOM and non‐IOM (NIOM). An independent t test and chi‐squared test were used to analyze the clinical features of the patients. The statistically significant parameters were analyzed by binary logistic regression to determine the risk factors for IOM. A receiver operating characteristic curve was constructed to assess their diagnostic value in IOM. The results showed that no significant differences were noted in age, gender, and pathological type between the IOM and NIOM groups. However, the IOM group had higher levels of alpha‐fetoprotein, carcinoembryonic antigen, cancer antigen (CA)‐125, CA‐153, cytokeratin fragment 19 (CYFRA 21‐1), and total prostate‐specific antigen, compared with the NIOM group. Binary logistic regression indicated that CA‐153 and CYFRA 21‐1 were risk factors for IOM in patients with MLC (P < 0.05). Area under the curve of CA‐153, CYFRA 21‐1 and their combination were 0.791, 0.860, and 0.872 respectively. The cutoff values for CA‐153 and CYFRA 21‐1 were 22.2 U/mL and 6.785 ng/mL. In conclusion, both CA‐153 and CYFRA 21‐1 were independent risk factors for IOM in patients with metastatic lung cancer (MLC), whereas the combination of CA‐153 and CYFRA 21‐1 assessment yields the most value in the detection of IOM in patients with MLC.

Identifying the Best Marker Combination in CEA, CA125, CY211, NSE, and SCC for Lung Cancer Screening by Combining ROC Curve and Logistic Regression Analyses: Is It Feasible?

The detection of serum biomarkers can aid in the diagnosis of lung cancer. In recent years, an increasing number of lung cancer markers have been identified, and these markers have been reported to have varying diagnostic values. A method to compare the diagnostic value of different combinations of biomarkers needs to be established to identify the best combination. In this study, automatic chemiluminescence analyzers were employed to detect the serum concentrations of carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), cytokeratin 19 fragment (CY211), neuron-specific enolase (NSE), and squamous cell carcinoma antigen (SCC) in 780 healthy subjects, 650 patients with pneumonia, and 633 patients with lung cancer. Receiver operating characteristic (ROC) curve and logistic regression analyses were also used to evaluate the diagnostic value of single and multiple markers of lung cancer. The sensitivities of the five markers alone were lower than 65% for lung cancer screening in healthy subjects and pneumonia patients. SCC was of little value in screening lung cancer. After combining two or more markers, the areas under the curves (AUCs) did not increase with the increase in the number of markers. For healthy subjects, the best marker for lung cancer screening was the combination CEA + CA125, and the positive cutoff range was 0.577 CEA + 0.035 CA125 > 2.084. Additionally, for patients with pneumonia, the best screening markers displayed differences in terms of sex but not age. The best screening marker for male patients with pneumonia was the combination CEA + CY211 with a positive cutoff range of 0.008 CEA + 0.068 CY211 > 0.237, while that for female patients with pneumonia was CEA > 2.73 ng/mL, which could be regarded as positive. These results showed that a two-marker combination is more suitable than a multimarker combination for the serological screening of tumors. Combined ROC curve and logistic regression analyses are effective for identifying the best markers for lung cancer screening.

Hybrid Paper-Plastic Microchip for Flexible and High-Performance Point-of-Care Diagnostics

A low-cost and easy-to-fabricate microchip remains a key challenge for the development of true point-of-care (POC) diagnostics. Cellulose paper and plastic are thin, light, flexible, and abundant raw materials, which make them excellent substrates for mass production of POC devices. Herein, a hybrid paper-plastic microchip (PPMC) is developed, which can be used for both single and multiplexed detection of different targets, providing flexibility in the design and fabrication of the microchip. The developed PPMC with printed electronics is evaluated for sensitive and reliable detection of a broad range of targets, such as liver and colon cancer protein biomarkers, intact Zika virus, and human papillomavirus nucleic acid amplicons. The presented approach allows a highly specific detection of the tested targets with detection limits as low as 10² ng mL^-1 for protein biomarkers, 10³ particle per milliliter for virus particles, and 10² copies per microliter for a target nucleic acid. This approach can potentially be considered for the development of inexpensive and stable POC microchip diagnostics and is suitable for the detection of a wide range of microbial infections and cancer biomarkers.

Clean Colorectum at Diagnostic Colonoscopy: Subsequent Detection of Extracolonic Malignancies by Plasma Protein Biomarkers?

Introduction

Most of the subjects undergoing diagnostic colonoscopy do not have neoplastic bowel lesions. Potentially, some of the symptoms may therefore be caused by extracolonic malignancy, and subjects with persisting symptoms may need subsequent examinations. Blood-based, cancer-associated biomarkers may aid in directing the examinations for other specific malignant diseases.

Methods

EDTA plasma samples available from a previous prospective study of subjects undergoing diagnostic colonoscopy were used for analysis of 18 protein biomarkers. The study population of 3732 subjects included 400 patients with colorectal cancer (CRC) and 177 patients with extracolonic malignancies. Univariable analysis of the association of specific biomarkers and extracolonic cancers included those with 10 or more cases. Subsequently, reduced models of 4 or 6 biomarkers, respectively, were established by choosing those with the highest likelihood; age and sex were included as well.

Results

Univariable analyses showed that CyFra21-1 had an area under curve (AUC) of 0.87 for lung cancers (n = 33), CA19-9 had an AUC of 0.85 for pancreatic cancer (n = 22), CA125 had an AUC of 0.95 for ovary cancer (n = 16), B2M had an AUC of 0.81 for non-Hodgkin lymphoma (n = 12), and total prostate-specific antigen had an AUC of 0.99 for prostate cancer (n = 10). The multivariable analysis of 4 or 6 biomarkers plus age and sex as explanatory variables showed AUCs of 0.82 to 0.85 both for extracolonic cancers and CRC. The 4 biomarkers included in the model for detection of extracolonic cancers were CA125, hsCRP, CA19-9, and CyFra21-1; the 2 additional for the 6 biomarkers model were CEA and Galectin-3. Similarly, the 4 biomarkers included in the model for detection of CRC were CEA, CyFra21-1, Ferritin, and HE4; the two additional for the 6 biomarkers model were hsCRP and Pepsinogen 2.

Conclusions

Results of this study indicate that it may be possible to detect subjects that have an increased risk of extracolonic cancer following a colonoscopy without findings of neoplastic lesions. Combinations of various protein biomarkers may direct subsequent examination after colonoscopy with clean colorectum. The results, although preliminary, may form the basis for additional research directed both for primary examinations of subjects with symptoms of malignancy and subsequent examinations after colonoscopy.

Circulating and tumor-associated caspase-4: a novel diagnostic and prognostic biomarker for non-small cell lung cancer

Late diagnosis limits therapeutic options and survival rate of non-small cell lung cancer (NSCLC) patients. Therefore the identification of biomarkers represents an emerging medical need.

A highly sensitive and specific test was developed to identify/quantify a novel/selective diagnostic biomarker for NSCLC patients, caspase-4. This test was validated by using i) plasma from 125 NSCLC patients and 79 healthy (non-pathological) subjects, ii) plasma from 139 smokers and iii) from 70 chronic-obstructive pulmonary disease (COPD) patients. Caspase-4 quantification was also assessed in the lung tumor mass of 98 paired NSCLC patients compared to 10 non-tumor lung tissues (i.e. tuberculosis).

Circulating caspase-4 was detected in both healthy and NSCLC patients; however at different range values: 2.603–3.372 ng/ml for NSCLC patients (95% CI) compared to 0.3994-0.6219 ng/ml for healthy subjects (95% CI). The sensitivity of the test ranged from 97.07% to 100%; the specificity was 88.1% with a positive predictive value of 92.54%, accuracy of 95.19% and AUC of 0.971. Smokers (95% CI, 0.3947–0.6197 ng/ml) and COPD patients (95% CI, 1.703–2.995 ng/ml) showed intermediate values of circulating caspase-4. Tissue levels of caspase-4 in the tumor mass showed that 72 (72.7%) out of 99 patients were positive. More importantly, higher levels (cut-off value = 0.307 ng/ml) of caspase-4 in the tumor mass were associated to reduced overall survival (median 0.92 years) compared to NSCLC patients with lower levels (median 3.02 years).

We report for the first time caspase-4 as a novel diagnostic and prognostic biomarker, opening new therapeutic perspectives for NSCLC patients.

Identification of serum proteins and multivariate models for diagnosis and therapeutic monitoring of lung cancer

Lung cancer is one of the most prevalent cancers and has very poor treatment outcome. Biomarkers useful for screening and assessing early therapeutic response may significantly improve the therapeutic outcome but are still lacking. In this study, serum samples from 218 non-small cell lung cancer (NSCLC) patients, 34 small cell lung cancer (SCLC) patients and 171 matched healthy controls from China were analyzed for 11 proteins using the Luminex multiplex assay. Eight of the 11 proteins (OPN, SAA, CRP, CYFRA21.1, CEA, NSE, AGP and HGF) are significantly elevated in NSCLC and SCLC (p = 10⁻⁵−10⁻⁵⁹). At the individual protein level, OPN has the best diagnostic value for NSCLC (AUC = 0.92), two acute phase proteins (SAA and CRP) have AUC near 0.83, while CEA and CYFRA21.1 also possess good AUC (0.81 and 0.77, respectively). More importantly, several three-protein combinations that contain OPN and CEA plus one of four proteins (CRP, SAA, CYFRA21.1 or NSE) have excellent diagnostic potential for NSCLC (AUC = 0.96). Four proteins (CYFRA21.1, CRP, SAA and NSE) are severely reduced and three proteins (OPN, MIF and NSE) are moderately decreased after platinum-based chemotherapy. Therapeutic response index (TRI) computed with 3–5 proteins suggests that approximately 25% of the NSCLC patients respond well to the therapy and TRI is significantly correlated with pre-treatment protein levels. Our data suggest that therapeutic response in NSCLC patients can be effectively measured but personalized biomarkers may be needed to monitor different subsets of patients.

Clinical evaluation and therapeutic monitoring value of serum tumor markers in lung cancer

BACKGROUND

Tumor markers CYFRA21-1, CEA, NSE, CA125, pro-GRP and SCC are routinely used for lung cancer. However, there has been no systematic evaluation of these markers in the same cohort. The aim of this study was to evaluate the diagnostic and therapeutic monitoring value of these markers.

METHODS

The levels of 6 serum tumor markers were measured in 392 patients, including 308 patients with non-small cell lung cancer (NSCLC) and 84 with small cell lung cancer (SCLC), and 116 patients with benign lung diseases and 144 healthy controls. 34 patients were followed up after operation and chemotherapy. Multiple logistic models and receiver operating characteristic (ROC) curves were used to evaluate their diagnostic value.

RESULTS

CEA, NSE, CA125 and pro-GRP in SCLC, and CYFRA21-1 as well as CEA in NSCLC, were higher than those in control groups. The level of CEA and CA125 were related to the clinical stages of NSCLC. Pro-GRP was significantly increased in extensive disease (ED) compared with limited disease (LD) in SCLC. CYFRA21-1 was reduced after the third and fifth treatment cycle respectively in patients who undergoing operation and without operation. NSE and pro-GRP were reduced significantly after the second and third treatment cycles, respectively.

CONCLUSIONS

CEA, NSE, CA125 and pro-GRP could serve as biomarkers for SCLC, and CEA and CYFRA21-1 could serve as biomarkers for NSCLC. Pro-GRP, CA125 and CEA were related to the clinical stages of lung cancer. CYFRA21-1, NSE and pro-GRP could be used for monitoring the effect of chemotherapy.

Diagnostic significance of S100A2 and S100A6 levels in sera of patients with non-small cell lung cancer

Biochemical markers play a significant role in the diagnosis of lung cancer. Recent studies have demonstrated a link involving S100 Calcium Binding Proteins (S100A2, S100A6) and non-small cell lung cancer (NSCLC), but the expediency of their serum levels in NSCLC has not been established. In this study, we evaluate the potential of serum S100A2 and S100A6 levels as diagnostic markers for NSCLC. Enzyme-linked immunosorbent assay (ELISA) was performed to detect the levels of S100A2 and S100A6 in 141 NSCLC patients and 150 healthy subjects. Serum levels of the two proteins in patients with NSCLC were higher compared to healthy controls (P = 0.0002 for S100A2 and P < 0.0001 for S100A6). Moreover, the levels of S100A2 and S100A6 were higher in the sera of stage I/II NSCLC patients compared to healthy controls with P = 0.01 and <0.0001, respectively. Receiver operating characteristic (ROC) analysis showed that S100A2 could distinguish NSCLC patients from healthy controls (AUC = 0.646), and S100A6 could also identify NSCLC (AUC = 0.668). Meanwhile, these two proteins showed notable capabilities for distinguishing stage I/II NSCLC from healthy controls (AUC = 0.708 for S100A2 and AUC = 0.702 for S100A6). Our results indicate that serum levels of S100A2 and S100A6 are significantly elevated in early stage NSCLC and may have the potential for NSCLC biomarker. Further studies with large sample population would help validate our findings.

Differentially expressed glycosylated patterns of α-1-antitrypsin as serum biomarkers for the diagnosis of lung cancer

Lung cancer is the most common malignancy worldwide. Thus, there is a critical need for diagnostic biomarkers with adequate sensitivity and specificity for lung cancer detection. Glycans in glycoproteins are significantly altered in cancer, and may serve as a tool for identifying potential diagnostic biomarkers. Recent studies have reported changes in α-1-antitrypsin (A1AT) glycosylation in lung cancer serum, tissue and cell lines. In this study, a lectin microarray was used to detect glycosylation changes in serum A1AT from patients with lung adenocarcinoma (ADC), squamous cell lung cancer, small-cell lung cancer (SCLC) and benign pulmonary diseases. Differentially expressed glycosylated patterns of A1AT were identified by lectin arrays and were confirmed by lectin-based enzyme-linked immunosorbent assay (ELISA). We found that galactosylated A1AT could distinguish non-small-cell lung cancer (NSCLC) from benign pulmonary diseases (AUC = 0.834); fucosylated A1AT showed exceptional capability in distinguishing ADC from benign diseases (AUC = 0.919) or other lung cancer subtypes (AUC = 0.844), and A1AT containing poly-LacNAc could detect SCLC from benign diseases (AUC = 0.905) or NSCLC (AUC = 0.707). The present study indicates that glycosylated patterns of A1AT may serve as potential biomarkers for detection of lung cancer. Further studies in larger sample sizes are necessary to validate the clinical utility of these markers.