Diagnostic value of CEA and CYFRA 21-1 tumor markers in primary lung cancer

Five years of advances in electrochemical analysis of protein biomarkers in lung cancer: a systematic review

Lung cancer is the leading cause of cancer death in both men and women. It represents a public health problem that must be addressed through the early detection of specific biomarkers and effective treatment. To address this critical issue, it is imperative to implement effective methodologies for specific biomarker detection of lung cancer in real clinical samples. Electrochemical methods, including microfluidic devices and biosensors, can obtain robust results that reduce time, cost, and assay complexity. This comprehensive review will explore specific studies, methodologies, and detection limits and contribute to the depth of the discussion, making it a valuable resource for researchers and clinicians interested in lung cancer diagnosis.

Clinical practice guidelines for molecular tumor marker, 2nd edition review part 2

In recent years, rapid advancement in gene/protein analysis technology has resulted in target molecule identification that may be useful in cancer treatment. Therefore, "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" was published in Japan in September 2021. These guidelines were established to align the clinical usefulness of external diagnostic products with the evaluation criteria of the Pharmaceuticals and Medical Devices Agency. The guidelines were scoped for each tumor, and a clinical questionnaire was developed based on a serious clinical problem. This guideline was based on a careful review of the evidence obtained through a literature search, and recommendations were identified following the recommended grades of the Medical Information Network Distribution Services (Minds). Therefore, this guideline can be a tool for cancer treatment in clinical practice. We have already reported the review portion of "Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition" as Part 1. Here, we present the English version of each part of the Clinical Practice Guidelines for Molecular Tumor Marker, Second Edition.

High-Throughput Microfluidic Extraction of Platelet-free Plasma for MicroRNA and Extracellular Vesicle Analysis

Cell-free RNAs and extracellular vesicles (EVs) are valuable biomarkers in liquid biopsies, but they are prone to preanalytical variabilities such as nonstandardized centrifugation or ex vivo blood degradation. Herein, we report a high-throughput and label-free inertial microfluidic device (ExoArc) for isolation of platelet-free plasma from blood for RNA and EV analysis. Unlike conventional inertial microfluidic devices widely used for cell sorting, a submicrometer size cutoff (500 nm) was achieved which completely removed all leukocytes, RBCs, platelets, and cellular debris based on differential lateral migration induced by Dean vortices. The single-step operation also reduced platelet-associated miRNAs (∼2-fold) compared to centrifugation. We clinically validated ExoArc for plasma miRNA profiling (39 samples) and identified a 7-miRNA panel that detects non-small cell lung cancer with ∼90% sensitivity. ExoArc was also coupled with size exclusion chromatography (SEC) to isolate EVs within 50 min with ∼10-fold higher yield than ultracentrifugation. As a proof-of-concept for EV-based transcriptomics analysis, we performed miRNA analysis in healthy and type 2 diabetes mellitus (T2DM) subjects (n = 3 per group) by coupling ExoArc and ExoArc+SEC with quantitative polymerase chain reaction (RT-qPCR) assay. Among 293 miRNAs detected, plasmas and EVs showed distinct differentially expressed miRNAs in T2DM subjects. We further demonstrated automated in-line EV sorting from low volume culture media for continuous EV monitoring. Overall, the developed ExoArc offers a convenient centrifugation-free workflow to automate plasma and EV isolation for point-of-care diagnostics and quality control in EV manufacturing.

Prediction of lung cancer using novel biomarkers based on microbiome profiling of bronchoalveolar lavage fluid

There is an unmet need for biomarkers for the diagnosis of lung cancer and decision criteria for lung biopsy. We comparatively investigated the lung microbiomes of patients with lung cancer and benign lung diseases. Patients who underwent bronchoscopy at Chungnam National University Hospital between June 2021 and June 2022 were enrolled. Bronchoalveolar lavage fluid (BALF) was collected from 24 patients each with lung cancer and benign lung diseases. The samples were analyzed using 16S rRNA-based metagenomic sequencing. We found that alpha diversity and the beta diversity distribution (P = 0.001) differed significantly between patients with benign lung diseases and those with lung cancer. Firmicutes was the most abundant phylum in patients with lung cancer (33.39% ± 17.439), whereas Bacteroidota was the most abundant phylum in patients with benign lung disease (31.132% ± 22.505), respectively. In differential abundance analysis, the most differentially abundant microbiota taxon was unclassified_SAR202_clade, belonging to the phylum Chloroflexi. The established prediction model distinguished patients with benign lung disease from those with lung cancer with a high accuracy (micro area under the curve [AUC] = 0.98 and macro AUC = 0.99). The BALF microbiome may be a novel biomarker for the detection of lung cancer.

Evaluating the predictive significance of systemic immune-inflammatory index and tumor markers in lung cancer patients with bone metastases

Objective

This study aims to develop a predictive model for identifying lung cancer patients at elevated risk for bone metastases, utilizing the Unified Immunoinflammatory Index and various tumor markers. This model is expected to facilitate timely and effective therapeutic interventions, especially in the context of the growing significance of immunotherapy for lung cancer treatment.

Methods

A retrospective analysis was conducted on 324 lung cancer patients treated between January 2019 and January 2021. After meeting the inclusion criteria, 241 patients were selected, with 56 exhibiting bone metastases. The cohort was divided into a training group (169 patients) and a validation group (72 patients) at a 7:3 ratio. Lasso regression was employed to identify critical variables, followed by logistic regression to construct a Nomogram model for predicting bone metastases. The model's validity was ascertained through internal and external evaluations using the Concordance Index (C-index) and Receiver Operating Characteristic (ROC) curve.

Results

The study identified several factors influencing bone metastasis in lung cancer, such as the Systemic Immune-Inflammatory Index (SII), Carcinoembryonic Antigen (CEA), Neuron Specific Enolase (NSE), Cyfra21-1, and Neutrophil-to-Lymphocyte Ratio (NLR). These factors were incorporated into the Nomogram model, demonstrating high validation accuracy with C-index scores of 0.936 for internal and 0.924 for external validation.

Conclusion

The research successfully developed an intuitive and accurate Nomogram prediction model utilizing clinical indicators to predict the risk of bone metastases in lung cancer patients. This tool can be instrumental in aiding clinicians in developing personalized treatment plans, thereby optimizing patient outcomes in lung cancer care.

Clinical role of serum tumor markers SCC, NSE, CA 125, CA 19-9, and CYFRA 21-1 in patients with lung cancer

OBJECTIVE

The aim of the study was to assess the diagnostic value of tumor markers in discriminating between lung cancer and benign chest diseases (BCDs).

METHODS

There were 322 patients enrolled in this investigation including 180 cases of lung cancer and 142 cases of BCD. Serum neuron-specific enolase (NSE), cancer antigen 125, cancer antigen 19-9, squamous cell carcinoma-related antigen, and cytokeratin fragment 19 (CYFRA 21-1) were compared between different populations, cancer stages, and before and after treatment. Logistic regression and receiver operating characteristic curves were used to evaluate the diagnostic markers.

RESULTS

Both NSE and CYFRA 21-1 were significantly associated with lung cancer. The CYFRA 21-1 showed the best performance, as well as its combinations, for lung cancer diagnosis. It also showed significant change 6 months after radical surgery in lung cancer patients.

CONCLUSION

The marker CYFRA 21-1 could be developed as an adjuvant marker for the early diagnosis of lung cancer and as a prognostic marker for lung cancer treatment.

Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules

Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.

Biosensors for the detection of lung cancer biomarkers: A review on biomarkers, transducing techniques and recent graphene-based implementations

Lung cancer remains the leading cause of cancer-related death. In addition to chest X-rays and computerised tomography, the detection of cancer biomarkers serves as an emerging diagnostic tool for lung cancer. This review explores biomarkers including the rat sarcoma gene, the tumour protein 53 gene, the epidermal growth factor receptor, the neuron-specific enolase, the cytokeratin-19 fragment 21-1 and carcinoembryonic antigen as potential indicators of lung cancer. Biosensors, which utilise various transduction techniques, present a promising solution for the detection of lung cancer biomarkers. Therefore, this review also explores the working principles and recent implementations of transducers in the detection of lung cancer biomarkers. The transducing techniques explored include optical techniques, electrochemical techniques and mass-based techniques for detecting biomarkers and cancer-related volatile organic compounds. Graphene has outstanding properties in terms of charge transfer, surface area, thermal conductivity and optical characteristics, on top of allowing easy incorporation of other nanomaterials. Exploiting the collective merits of both graphene and biosensor is an emerging trend, as evidenced by the growing number of studies on graphene-based biosensors for the detection of lung cancer biomarkers. This work provides a comprehensive review of these studies, including information on modification schemes, nanomaterials, amplification strategies, real sample applications, and sensor performance. The paper concludes with a discussion of the challenges and future outlook of lung cancer biosensors, including scalable graphene synthesis, multi-biomarker detection, portability, miniaturisation, financial support, and commercialisation.

Accurate detection of early-stage lung cancer using a panel of circulating cell-free DNA methylation biomarkers

BACKGROUND

Lung cancer remains the leading cause of cancer mortality worldwide. Early detection of lung cancer helps improve treatment and survival. Numerous aberrant DNA methylations have been reported in early-stage lung cancer. Here, we sought to identify novel DNA methylation biomarkers that could potentially be used for noninvasive early diagnosis of lung cancers.

METHODS

This prospective-specimen collection and retrospective-blinded-evaluation trial enrolled a total of 317 participants (198 tissues and 119 plasmas) comprising healthy controls, patients with lung cancer and benign disease between January 2020 and December 2021. Tissue and plasma samples were subjected to targeted bisulfite sequencing with a lung cancer specific panel targeting 9,307 differential methylation regions (DMRs). DMRs associated with lung cancer were identified by comparing the methylation profiles of tissue samples from patients with lung cancer and benign disease. Markers were selected with minimum redundancy and maximum relevance algorithm. A prediction model for lung cancer diagnosis was built through logistic regression algorithm and validated independently in tissue samples. Furthermore, the performance of this developed model was evaluated in a set of plasma cell-free DNA (cfDNA) samples.

RESULTS

We identified 7 DMRs corresponding to 7 differentially methylated genes (DMGs) including HOXB4, HOXA7, HOXD8, ITGA4, ZNF808, PTGER4, and B3GNTL1 that were highly associated with lung cancer by comparing the methylation profiles of lung cancer and benign nodule tissue. Based on the 7-DMR biomarker panel, we developed a new diagnostic model in tissue samples, termed "7-DMR model", to distinguish lung cancers from benign diseases, achieving AUCs of 0.97 (95%CI: 0.93-1.00)/0.96 (0.92-1.00), sensitivities of 0.89 (0.82-0.95)/0.92 (0.86-0.98), specificities of 0.94 (0.89-0.99)/1.00 (1.00-1.00), and accuracies of 0.90 (0.84-0.96)/0.94 (0.89-0.99) in the discovery cohort (n = 96) and the independent validation cohort (n = 81), respectively. Furthermore, the 7-DMR model was applied to noninvasive discrimination of lung cancers and non-lung cancers including benign lung diseases and healthy controls in an independent validation cohort of plasma samples (n = 106), yielding an AUC of 0.94 (0.86-1.00), sensitivity of 0.81 (0.73-0.88), specificity of 0.98 (0.95-1.00), and accuracy of 0.93 (0.89-0.98).

CONCLUSION

The 7 novel DMRs could be promising methylation biomarkers that merits further development as a noninvasive test for early detection of lung cancer.

Programmable DNA Circuit-Facilitated Determination of Circulating Extracellular Vesicle PD-L1 for Lung Cancer Diagnosis and Immunotherapy Response Prediction

Circulating extracellular vesicle (EV) PD-L1 is correlated with the occurrence and progression of lung cancer and has great potential as a valuable diagnostic and immunotherapy predictive biomarker. In this work, we propose a fluorescent biosensing method for the sensitive and accurate determination of circulating EV PD-L1. Specifically, after the phosphatidylserine-targeting peptide-assisted magnetic enrichment, a programmable DNA circuit is designed to translate the presence of PD-L1 to the appearance of numerous duplex DNA probes on the circulating EV surface. Upon fructose treatment, these newly formed duplex DNA probes are released from the EV surface to activate the trans-cleavage activity of CRISPR/Cas12a system, which finally produces a significant fluorescence signal. Experimental results reveal that the method not only enables sensitive determination of EV PD-L1 with a detection limit of 67 particles/mL but also demonstrates the potential use in the diagnosis and immunotherapy response prediction of lung cancer in a principle-of-proof study. Therefore, the method may provide a useful tool for EV PD-L1 determination, which may provide valuable information for the precise diagnosis and personalized treatment of lung cancer patients.

Diagnostic and Prognostic Significance of Serum Biomarkers - Serum Amyloid A and CYFRA 21-1 in Lung Cancer

Introduction

Bronchogenic carcinoma is a leading cause of cancer-related death in men and women. Early diagnosis and treatment in these cases are essential for a better prognosis. Serum biomarkers such as serum amyloid A (SAA) and CYFRA 21-1 have generated encouraging results regarding their use in the diagnosis of these cases but data on their role in the Indian scenario are still lacking.

Aim

The study aims to measure the levels of SAA and CYFRA 21-1 in various types of lung cancer and compare them with patients without lung cancer. It also aims to compare the values of these biomarkers before and after chemotherapy and correlate them with response to treatment.

Materials and Methods

It was a prospective, case-control study conducted in the Department of Pulmonary Medicine, Government Medical College, Chandigarh. All histologically and/or cytologically proven lung cancer cases were included in the study group while patients with diseases other than lung cancer formed the control group. All patients were evaluated through a complete history and thorough clinical examination. Measurement of SAA and CYFRA 21-1 in blood was done by sandwich ELISA method. The patients in the study group were followed up regularly and the biomarkers were measured again after four cycles of chemotherapy. The response of tumors to chemotherapy was evaluated as per modified Response Evaluation Criteria in Solid Tumors criteria. The statistical analysis was carried out using SPSS version 19.0.

Results

The study group and control group included 20 patients each. Hoarseness of voice and hemoptysis were significantly associated with lung cancer patients (P = 0.001 and P = 0.025, respectively). Serum levels above 8745 ng/ml for SAA and 2.55 ng/ml for serum CYFRA 21-1 were used as diagnostic biomarker in lung cancer. The serum levels of CYFRA 21-1 were found to be significantly raised in nonsmall cell carcinoma (NSCLC) in comparison to SCLC of lung. There was a statistically significant decrease in the serum levels of CYFRA 21-1 in lung cancer patients on C4 cycle of chemotherapy in comparison to C1 cycle (P = 0.014).

Conclusion

SAA and CYFRA 21-1 could be valuable diagnostic biomarkers in lung cancer. CYFRA 21-1, in addition, could also be used as prognostic biomarker in lung cancer patients undergoing chemotherapy as it showed significant decrease after C4-cycle of chemotherapy. It can also be a potential biomarker to differentiate small cell and NSCLC.

A combined preoperative red cell distribution width and carcinoembryonic antigen score contribute to prognosis prediction in stage I lung adenocarcinoma

AIMS

Hematological markers that can be used for prognosis prediction for stage I lung adenocarcinoma (LUAD) are still lacking. Here, we examined the prognostic value of a combination of the red cell distribution width (RDW) and carcinoembryonic antigen (CEA), namely, the RDW-CEA score (RCS), in stage I LUAD.

MATERIALS AND METHODS

A retrospective study with 154 patients with stage I LUAD was conducted. Patients were divided into RCS 1 (decreased RDW and CEA), RCS 2 (decreased RDW and increased CEA, increased RDW and decreased CEA), and RCS 3 (increased RDW and CEA) subgroups based on the best optimal cutoff points of RDW and CEA for overall survival (OS). The differences in other clinicopathological parameters among RCS subgroups were calculated. Disease-free survival (DFS) and OS among these groups were determined by Kaplan-Meier analysis, and risk factors for outcome were calculated by a Cox proportional hazards model.

RESULTS

Seventy, 65, and 19 patients were assigned to the RCS 1, 2, and 3 subgroups, respectively. Patients ≥ 60 years (P < 0.001), male sex (P = 0.004), T₂ stage (P = 0.004), and IB stage (P = 0.006) were more significant in the RCS 2 or 3 subgroups. The RCS had a good area under the curve (AUC) for predicting DFS (AUC = 0.81, P < 0.001) and OS (AUC = 0.93, P < 0.001). The DFS (log-rank = 33.26, P < 0.001) and OS (log-rank = 42.05, P < 0.001) were significantly different among RCS subgroups, with RCS 3 patients displaying the worst survival compared to RCS 1 or 2 patients. RCS 3 was also an independent risk factor for both DFS and OS.

CONCLUSIONS

RCS is a useful prognostic indicator in stage I LUAD patients, and RCS 3 patients have poorer survival. However, randomized controlled trials are needed to validate our findings in the future.

Combination of serum ACSL4 levels and low-dose 256-slice spiral CT exhibits the potential in the early screening of lung cancer

BACKGROUND

The prognosis of lung cancer is related to the stage of the disease at the time of detection, and early diagnosis can prolong survival time. In this prospective observational cohort research, we aimed to analyze the diagnostic performance of the combined application of ACSL4 and low-dose 256-slice spiral computed tomography (CT) to lung cancer.

METHODS

This prospective observational cohort research enrolled a total of 512 patients with pulmonary nodules (PN) who were found with PN by CT. All patients were divided into 2 groups through biopsy operation, including 449 patients with benign PN and 63 patients with malignant PN. Both groups were scanned with a Philips Brilliance 256iCT machine. Imaging features of PN were recorded. All images of the nodules were used for data measurement and image analysis by the Lung Nodule Assessment analysis software. The serum ACSL4, carcinoembryonic antigen (CEA), cytokeratin 19 fragment 21-1 (CYFRA21-1), neuron-specific enolase, carbohydrate antigen 199 (CA199) and carbohydrate antigen 125 (CA125) levels were measured by enzyme-linked immunosorbent assay method. The demographic data and clinical data, including age, sex, body mass index, smoke condition, TNM stage, lymph node metastasis and distant metastasis were collected. All the patients were followed for 5 years. Statistical analysis was conducted using SPSS software with P  < .05 as statistically different.

RESULTS

The diameter of nodules, the proportion of burr signs and smoking status, and the serum levels of CEA, CYFRA21-1, CA199, CA125 were significantly higher in malignant nodules group compared with the benign nodules group. Serum ACSL4 levels of malignant nodules group (19.33 ± 6.92 ng/mL) were remarkably lower than the benign nodules group (25.34 ± 3.78 ng/mL). ACSL4 was negatively correlated with CEA, CYFRA21-1, CA199, and CA125. ACSL4 was associated with the clinical outcomes in malignant PN patients and lower ACSL4 predicted poor clinic outcomes and prognosis. In addition, ACSL4 combined with low-dose 256-slice spiral CT had satisfactory diagnostic value for lung cancer.

CONCLUSION

In summary, our results showed that combination application of ACSL4 and low-dose 256-slice spiral CT might be a potential method for the early screening of lung cancer.

Development and validation of reassigned CEA, CYFRA21-1 and NSE-based models for lung cancer diagnosis and prognosis prediction

BACKGROUND

The majority of lung cancer(LC) patients are diagnosed at advanced stage with a poor prognosis. However, there is still no ideal diagnostic and prognostic prediction model for lung cancer.

METHODS

Data of CEA, CYFRA21-1 and NSE test of patients with LC and benign lung diseases (BLDs) or healthy people from Physical Examination Center was collected. Samples were divided into three data sets as needed. Reassign three kinds of tumor markers (TMs) according to their distribution characteristics in different populations. Diagnostic and prognostic models were thus established, and independent validation was conducted with other data sets.

RESULTS

The diagnostic prediction model showed good discrimination ability: the area under the receiver operating characteristic curve (AUC) differentiated LC from healthy people and BLDs (diagnosed within 2 months), being 0.88 and 0.84 respectively. Meanwhile, the prognostic prediction model did great in prediction: AUC in training data set and test data set were 0.85 and 0.8 respectively.

CONCLUSION

Reassigned CEA, CYFRA21-1 and NSE can effectively predict the diagnosis and prognosis of LC. Compared with the same TMs that were considered individually, this diagnostic prediction model can identify high-risk population for LC screening more accurately. The prognostic prediction model could be helpful in making more scientific treatment and follow-up plans for patients.

Predicting EGFR mutation, ALK rearrangement, and uncommon EGFR mutation in NSCLC patients by driverless artificial intelligence: a cohort study

Background

Timely identification of epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement status in patients with non-small cell lung cancer (NSCLC) is essential for tyrosine kinase inhibitors (TKIs) administration. We aimed to use artificial intelligence (AI) models to predict EGFR mutations and ALK rearrangement status using common demographic features, pathology and serum tumor markers (STMs).

Methods

In this single-center study, demographic features, pathology, EGFR mutation status, ALK rearrangement, and levels of STMs were collected from Wuhan Union Hospital. One retrospective set (N = 1089) was used to train diagnostic performance using one deep learning model and five machine learning models, as well as the stacked ensemble model for predicting EGFR mutations, uncommon EGFR mutations, and ALK rearrangement status. A consecutive testing cohort (n = 1464) was used to validate the predictive models.

Results

The final AI model using the stacked ensemble yielded optimal diagnostic performance with areas under the curve (AUC) of 0.897 and 0.883 for predicting EGFR mutation status and 0.995 and 0.921 for predicting ALK rearrangement in the training and testing cohorts, respectively. Furthermore, an overall accuracy of 0.93 and 0.83 in the training and testing cohorts, respectively, were achieved in distinguishing common and uncommon EGFR mutations, which were key evidence in guiding TKI selection.

Conclusions

In this study, driverless AI based on robust variables could help clinicians identify EGFR mutations and ALK rearrangement status and provide vital guidance in TKI selection for targeted therapy in NSCLC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02053-2.

Integration of bioinformatics analysis and experimental validation identifies plasma exosomal miR-103b/877-5p/29c-5p as diagnostic biomarkers for early lung adenocarcinoma

The aim of this study was to identify miRNAs in plasma exosomes as noninvasive biomarkers for the early diagnosis of lung adenocarcinoma (LUAD). First, exosomal miRNA profiling of three patients with early LUAD and three patients with benign lung disease were screened by next-generation sequencing (NGS) method. Sequencing results showed that 154 exosomal miRNAs were differentially expressed in the plasma of LUAD patients, among which 68 miRNAs were up-regulated and 86 miRNAs were down-regulated. GSE137140 is a GEO database containing serum miRNAs sequencing data from 1566 lung cancer patients and 1774 non-cancer patients controls. When comparing the sequencing data, it was found that most miRNAs (37/68) up-regulated in our LUAD group were also significantly up-regulated in GSE137140, suggesting that circulating miRNAs in lung cancer patients may be enriched in plasma exosomes. In GSE137140, the AUC of the combination of hsa-miR-103b, hsa-miR-29c-5p and hsa-miR-877-5p was 0.873, showing great potential as new tumor markers. To our knowledge, these three exosomal miRNAs have not been reported in lung cancer research. Furthermore, bioinformatics tools were used to analyze the target genes of three candidate miRNAs, which were indeed closely related to the occurrence and development of lung cancer. Bioinformatics algorithms deduced a highly conserved sequence in the 3'-UTR of SFRP4, FOXM1 and TMEM98 that could be bound with miR-103b/877-5p/29c-5p. A luciferase assay indicated that miR-103b/877-5p/29c-5p directly targeted the 3'-UTR of SFRP4, FOXM1 and TMEM98, respectively. Finally, three candidate miRNAs were validated by qRT-PCR in 17 early LUAD samples and 17 control plasma samples. Integration of bioinformatics analysis and experimental validation identifies, this study provides novel insights into miRNA-related networks in LUAD. Hsa-miR-103b, hsa-miR-29c-5p, and hsa-miR-877-5p may be used as diagnostic biomarkers for early LUAD.

Dynamic monitoring serum tumor markers to predict molecular features of EGFR-mutated lung cancer during targeted therapy

To reveal the correlation of dynamic serum tumor markers (STMs) and molecular features of epidermal growth factor receptor‐mutated (EGFR‐mutated) lung cancer during targeted therapy, we retrospectively reviewed 303 lung cancer patients who underwent dynamic STM tests [neuron‐specific enolase (NSE), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), the soluble fragment of cytokeratin 19 (CYFRA21‐1), and squamous cell carcinoma antigen (SCC)] and circulating tumor DNA (ctDNA) testing with a panel covering 168 genes. At baseline, patients with EGFR mutation trended to have abnormal CEA, abnormal CA153, and normal SCC levels. Additionally, patients with Thr790Met (T790M) mutation were more likely to have abnormal CEA levels than patients without T790M mutation. Among patients with secondary resistance to EGFR tyrosine kinase inhibitors (TKI), the dynamic STMs showed a descending trend in the responsive stage and a rising trend in the resistant stage. However, the changing slopes differed between T790M subgroup and the non‐T790M subgroup in individual STMs. Our study demonstrated that the combination of baseline levels and variations of STMs (including the responsive stage and resistant stage) can be suggestive of secondary EGFR‐T790M mutation [area under the curve (AUC) = 0.897] and that changing trends of STMs (within 8 weeks after initiating the TKI therapy) can be potential predictors for the clearance of EGFR ctDNA [AUC = 0.871]. In conclusion, dynamic monitoring STMs can help to predict the molecular features of EGFR‐mutated lung cancer during targeted therapy.

Serum tumor markers level and their predictive values for solid and micropapillary components in lung adenocarcinoma

Background

This study aims to reveal the serum tumor marker (STM) levels in lung adenocarcinoma (LUAD) histological subtypes and evaluate their values in predicting the solid and micropapillary components (SMC).

Methods

We retrospectively analyzed 3100 invasive LUAD patients between January 2017 and December 2020. Associations between preoperative STMs (CEA, CYFRA21‐1, CA199, CA724, NSE, AFP) and LUAD subtypes were evaluated. Multivariate regression analyses were used to determine the independent predictors. Predictive models for SMC were constructed and AUC (area under the curve) was calculated.

Results

CEA and CYFRA21‐1 levels differed across the LUAD histological subtypes, with the SPA (solid‐predominant adenocarcinoma) having the highest level and the LPA (lepidic‐predominant adenocarcinoma) harboring the lowest level (p <0.001). Tumors with SMC also had higher CEA and CYFRA21‐1 levels than those absence of SMC. Gender, tumor size, CEA, Ki‐67, EGFR mutation (solid components only), and tumor differentiation were significantly independently associated with the containing of SMC. Patients were split into two data sets (training set: 2017–2019 and validation set: 2020). The model with gender and tumor size yielded an AUC of 0.723 (training set) and 0.704 (validation set) for the solid component. Combination of CEA, gender, and tumor size led to a significant increase in the predictive accuracy (training set: 0.771, p = 0.009; validation set: 0.747, p = 0.034). The AUC of the model for micropapillary component with only gender and tumor size was 0.699 and 0.711 in the training set and validation set, respectively. Integration of CEA with gender and tumor size significantly improved the predictive performance with an AUC of 0.746 (training set, p = 0.045) and 0.753 (validation set, p <0.001).

Conclusion

Serum CEA and CYFRA21‐1 varied considerably according to LUAD histological subtypes. The combination of serum CEA and other factors showed prominent values in predicting the SMC.

Development and Validation of a Preoperative CT-Based Nomogram to Differentiate Invasive from Non-Invasive Pulmonary Adenocarcinoma in Solitary Pulmonary Nodules

Purpose

Patients and Methods

Results

Conclusion

Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

Evaluation of Analytical Performances of Magnetic Force-Assisted Electrochemical Sandwich Immunoassay for the Quantification of Carcinoembryonic Antigen

Carcinoembryonic antigen (CEA) is a biomarker indicated in different cancers, targeted for quantitative analysis via immunoassay. Here we introduce a new technique called magnetic force-assisted electrochemical sandwich immunoassay (MESIA) for determination of CEA level in a drop of human serum using a fully automated point-of-care testing (POCT) device. The analytical performances of the assay are assessed based on precision, accuracy, limit of blank (LoB), limit of detection (LoD) and limit of quantitation (LoQ), linearity, Hook effect, interference, cross-reactivity, and method comparison following the guidelines of the Clinical Laboratory Standards Institute (CLSI). The LoD is 0.50 ng/ml. A linear relationship is shown in the range of 0.5–200 ng/ml. A high dose effect is not seen up to approximately 500,000 ng/ml. The recovery range is from 94.7 to 108.9%. The %CV of run-to-run and within-lab variations are less than 2.04 and 4.41% across the CEA concentrations, respectively, whereas reproducibility is 4.45–6.24%. Method comparison shows that the assay correlates well with the reference device (R² = 0.9884). The assay demonstrates acceptable precision, accuracy, LoB, LoD and LoQ, hook effect, linearity, interference, cross-reactivity, and high correlation with its reference device. Thus, the system is suitable for the quantification of CEA in clinical practices with a POCT manner.

A sandwiched photoelectrochemical biosensing platform for detecting Cytokeratin-19 fragments based on Ag2S-sensitized BiOI/Bi2S3 heterostructure amplified by sulfur and nitrogen co-doped carbon quantum dots

A sandwiched photoelectrochemical (PEC) immunosensor based on BiOI/Bi₂S₃/Ag₂S was designed for the quantitative detection of cytokeratin-19 fragments (CYFRA21-1) in serum. In this work, due to the intervention of the narrow band gap Bi₂S₃, the absorption of the light source by the BiOI/Bi₂S₃ heterostructure has been significantly enhanced. Meanwhile, the matched band structure of BiOI, Bi₂S₃ and Ag₂S promoted the rapid transfer of electrons between the conduction bands and effectively inhibited the recombination of electron-hole pairs, thus enhanced the photoelectric signals. Sulfur and nitrogen co-doped carbon quantum dots (S,N-CQDs) with up-conversion luminescence properties provided more light energy for the base materials. On the other hand, S,N-CQDs were combined with Ab₂ through polydopamine (PDA), as secondary antibody labels, further enhanced the sensitivity of the sensor. Herein, the linear range of the sensor was from 0.001 to 100 ng mL^-1 and the detection limit was 1.72 pg mL^-1. In addition, the sensor provides a feasible way for the detection of tumor markers due to its excellent selectivity, repeatability and good stability.

Biosensors and nanotechnology for cancer diagnosis (lung and bronchus, breast, prostate, and colon): a systematic review

The second cause of death in the world has been reported to be cancer, and it has been on the rise in recent years. As a result of the difficulties of cancer detection and its treatment, the survival rate of patients is unclear. The early detection of cancer is an important issue for its therapy. Cancer detection based on biomarkers may effectively enhance the early detection and subsequent treatment. Nanomaterial-based nanobiosensors for cancer biomarkers are excellent tools for the molecular detection and diagnosis of disease. This review reports the latest advancement and attainment in applying nanoparticles to the detection of cancer biomarkers. In this paper, the recent advances in the application of common nanomaterials like graphene, carbon nanotubes, Au, Ag, Pt, and Fe₃O₄together with newly emerged nanoparticles such as quantum dots, upconversion nanoparticles, inorganics (ZnO, MoS₂), and metal-organic frameworks for the diagnosis of biomarkers related to lung, prostate, breast, and colon cancer are highlighted. Finally, the challenges, outlook, and closing remarks are given.

Clinicopathological characteristics of IgG4-related lung disease

Background

Immunoglobulin G4-related lung disease (IgG4-RLD) is a rare entity. We retrospectively analyzed the clinical and histopathological characteristics of patients with pathologically confirmed IgG4-RLD to improve the diagnosis rate and reduce the risk of misdiagnosis.

Methods

We screened the pathological reports of 4838 patients with pulmonary surgery and/or biopsy specimens from April 2017 to April 2021 at Sun Yat-Sen Memorial Hospital affiliated with Sun Yat-Sen University, and specimens from 65 patients with suspected IgG4-RLD were subjected to immunohistochemical staining for IgG4 and IgG. Finally, 10 patients with definite IgG4-RLD that was pathologically confirmed were enrolled and analyzed.

Results

The incidence of pathologically confirmed IgG4-RLD was 0.2% (10/4838). The ten patients had an average age of 59.7 years at diagnosis, and the male-to-female ratio was 9:1. The initial clinical manifestations were nonspecific, and cough was the most common symptom (4/10). More than one organ was involved in most patients (8/10), and mediastinal/hilar lymph node involvement was often observed (7/10). Serum IgG4 was analyzed in 6 patients and found to be elevated. Serum tumor marker levels were within the normal range or were slightly elevated. Computed tomography (CT) of the chest and/or ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET-CT) imaging revealed that 5 patients had a mixed type, 3 patients had the solid nodular type, and 2 patients had the bronchovascular type. All pulmonary masses and large nodules with solid patterns had spiculated margins and inhomogeneous enhancement with or without pleural indentation and a lobulated appearance. Abundant lymphoplasmacytic cell infiltration and fibrosis were observed in all patients. The expression of IgG4 and IgG was upregulated in the pulmonary sections. Seven patients were treated with glucocorticoids with or without additional immunosuppressants and responded well.

Conclusions

The results of our study suggest that multiple imaging findings, an elevated serum IgG4 concentration, and no significant increase in serum tumor biomarkers could provide diagnostic support for IgG4-RLD, especially for isolated IgG4-RLD or IgG4-RLD that includes other organ involvement that does not aid in establishing the diagnosis.

Bimodal Multiplexed Detection of Tumor Markers in Non-Small Cell Lung Cancer with Polymer Dot-Based Immunoassay

Semiconducting polymer nanoparticles (Pdots) have been demonstrated to be a promising class of probes for use in fluorometric immunochromatographic test strips (ICTS). The advantages of Pdots in ICTSs include ultrahigh brightness, minimal nonspecific adsorption, and multicolor availability, which together contribute to the high sensitivity, good specificity, and multiplexing ability. These unique properties can therefore circumvent several significant challenges of commercial ICTSs, including insufficient specificity/sensitivity and difficulty in quantitative and multiplexed detection. Here, we developed a colorimetric and fluorescent bimodal readout ICTS based on gold-Pdot nanohybrids for the determination of carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA 21-1) expressed abnormally in human blood of non-small-cell lung cancer (NSCLS). The vivid color from Au nanomaterials can be used for rapid qualitative screening (colorimetry) in 15 min, while the bright fluorescence of Pdots is ideal for the advanced quantitative measurements of CEA and CYFRA21-1 concentrations in whole blood samples. This bimodal ICTS platform possesses phenomenal detection sensitivity of 0.07 and 0.12 ng/mL for CYFRA21-1 and CEA, respectively. The accuracy and reliability of this ICTS platform were further evaluated with clinical serum samples from NSCLS patients at different stages, showing good consistency with the results from electrochemiluminescence immunoassay.

Biocompatible graphene-zirconia nanocomposite as a cyto-safe immunosensor for the rapid detection of carcinoembryonic antigen

Graphene-based materials have gained remarkable attention in numerous disciplines owing to their unique electrochemical properties. Out of various hybridized nanocomposites, graphene-zirconia nanocomposite (GZ) was distinctive due to its biocompatibility. Zirconia nanoparticles serve as spacers that reduce the stacking of graphene and improve the electrochemical performance of the material. Considering that lungs and skin suffer the greatest exposure to nanoparticles, this study aimed to evaluate the cytotoxicity of the as-synthesized GZ nanocomposites on MRC5 (lung cells) and HaCaT (skin cells) via morphological observation and cell viability assay using 3-(4,5 dimethylthiazol-2-yl)-(2,5-diphenyltetrazolium bromide) tetrazolium (MTT). GZ-treated cells showed a comparable proliferation rate and morphology with untreated cells under microscopic evaluation. Based on MTT results, the IC₅₀ values of GZ were > 500 µg/ml for MRC5 and HaCaT cells. The excellent biocompatibility was the supremacy of GZ over other nanocomposites applied as electrode materials in biosensors. GZ was functionalized with biolinker for the detection of carcinoembryonic antigen (CEA). The proposed immunosensor exhibited good responses towards CEA detection, with a 4.25 pg/ml LOD and correlation coefficient of R² = 0.99 within a linear working range from 0.01 to 10 ng/ml. The performance of the immunosensor to detect CEA present in human serum was also evaluated. Good recovery of CEA was found, suggesting that the proposed immunosensor possess a high affinity to CEA even in a complex biological matrix, rendering it a promising sensing platform for real sample analysis and open a new way for the detection of cancer-associated proteins.

The diagnostic value of the combination of carcinoembryonic antigen, squamous cell carcinoma-related antigen, CYFRA 21-1, neuron-specific enolase, tissue polypeptide antigen, and progastrin-releasing peptide in small cell lung cancer discrimination

BACKGROUND

The diagnostic value of six tumor markers was investigated and the appropriate combinations of those tumor markers to discriminate small cell lung cancer was explored.

METHODS

Patients suspected with lung cancer (1938) were retrospectively analyzed. Candidate tumor markers from carcinoembryonic antigen (CEA), squamous cell carcinoma-related antigen (SCC), cytokeratin 19 fragment 21-1 (CYFRA 21-1), neuron-specific enolase (NSE), tissue polypeptide antigen (TPA), and progastrin releasing peptide (ProGRP) were selected to construct a logistic regression model. The receiver operating characteristic curve was used for evaluating the diagnostic value of the tumor markers and the predictive model.

RESULTS

ProGRP had the highest positive rate (72.3%) in diagnosed small cell lung cancer, followed by neuron-specific enolase (68.3%), CYFRA21-1 (50.5%), carcinoembryonic antigen (45.5%), tissue polypeptide antigen (30.7%), and squamous cell carcinoma-related antigen (5.9%). The predictive model for small cell lung cancer discrimination was established, which yielded the highest area under the curve (0.888; 95% confidence interval: 0.846-0.929), with a sensitivity of 71.3%, a specificity of 95.0%, a positive predictive value of 49.0%, and a negative predictive value of 98.0%.

CONCLUSIONS

Combining tumor markers can improve the efficacy for small cell lung cancer discrimination. A predictive model has been established in small cell lung cancer differential diagnosis with preferable efficacy.

Diagnostic, Predictive, and Prognostic Biomarkers in Non-Small Cell Lung Cancer (NSCLC) Management

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite growing efforts for its early detection by screening populations at risk, the majority of lung cancer patients are still diagnosed in an advanced stage. The management of lung cancer has dramatically improved in the last decade and is no longer based on the "one-fits-all" paradigm or the general histological classification of non-small cell versus small cell lung cancer. Emerging options of targeted therapies and immunotherapies have shifted the management of lung cancer to a more personalized treatment approach, significantly influencing the clinical course and outcome of the disease. Molecular biomarkers have emerged as valuable tools in the prognosis and prediction of therapy response. In this review, we discuss the relevant biomarkers used in the clinical management of lung tumors, from diagnosis to prognosis. We also discuss promising new biomarkers, focusing on non-small cell lung cancer as the most abundant type of lung cancer.

Four plasma miRNAs act as biomarkers for diagnosis and prognosis of non-small cell lung cancer

Previous studies have reported that the aberrant expression of circulating microRNAs (miRNAs/miRs) can be used as diagnostic and prognostic markers in non-small cell lung cancer (NSCLC). The present study aimed to assess the diagnostic and prognostic predictive values of four plasma miRNAs for NSCLC. A total of 12 candidate miRNAs were selected that have previously been reported to be aberrantly expressed in NSCLC, and their plasma levels in the training set were detected via reverse transcription-quantitative PCR analysis. The screened out miRNAs were further validated in the testing set. The area under the curve (AUC) of the receiver operating characteristic curve was constructed to evaluate diagnostic performance. Kaplan-Meier survival analysis was performed to assess the association between the plasma miRNA levels and disease-free survival (DFS) time. The results demonstrated that 4/12 plasma miRNAs (miR-210, miR-1290, miR-150 and miR-21-5p) were highly expressed in patients with NSCLC compared with their expression levels in patients with benign lung disease (BLD) and healthy controls in the training and testing sets, respectively. The AUC values of the four-miRNA panel were 0.96 and 0.93 in the training and testing sets, respectively, for distinguishing patients with NSCLC from healthy controls, which were similar to the AUC values for distinguishing patients with NSCLC from patients with BLD (0.96 and 0.94). The AUC values of the four-miRNA panel in patients with stage I NSCLC were comparable to that of patients with stage II-III NSCLC (0.942 and 0.965). Patients with high plasma levels of miR-210 and miR-150 had worse DFS than those with low plasma levels of these miRNAs. In addition, patients whose plasma levels of the four miRNAs decreased by >50% after surgery exhibited a good DFS. Taken together, the results of the present study suggest that these four miRNAs (miR-210, miR-1290, miR-150 and miR-21-5p) act as useful biomarkers for early diagnosis and prognosis of NSCLC.

Prediction Model for Lung Cancer in High-Risk Nodules Being Considered for Resection: Development and Validation in a Chinese Population

Background

Determining benign and malignant nodules before surgery is very difficult when managing patients with pulmonary nodules, which further makes it difficult to choose an appropriate treatment. This study aimed to develop a lung cancer risk prediction model for predicting the nature of the nodule in patients’ lungs and deciding whether to perform a surgical intervention.

Methods

This retrospective study included patients with pulmonary nodules who underwent lobectomy or sublobectomy at Tianjin Medical University General Hospital between 2017 and 2020. All subjects were further divided into training and validation sets. Multivariable logistic regression models with backward selection based on the Akaike information criterion were used to identify independent predictors and develop prediction models.

Results

To build and validate the model, 503 and 260 malignant and benign nodules were used. Covariates predicting lung cancer in the current model included female sex, age, smoking history, nodule type (pure ground-glass and part-solid), nodule diameter, lobulation, margin (smooth, or spiculated), calcification, intranodular vascularity, pleural indentation, and carcinoembryonic antigen. The final model of this study showed excellent discrimination and calibration with a concordance index (C-index) of 0.914 (0.890–0.939). In an independent sample used for validation, the C-index for the current model was 0.876 (0.825–0.927) compared with 0.644 (0.559–0.728) and 0.681 (0.605–0.757) for the Mayo and Brock models. The decision curve analysis showed that the current model had higher discriminatory power for malignancy than the Mayo and the Brock models.

Conclusions

The current model can be used in estimating the probability of lung cancer in nodules requiring surgical intervention. It may reduce unnecessary procedures for benign nodules and prompt diagnosis and treatment of malignant nodules.

Diagnostic value of oncofetal miRNAs in cancers: A comprehensive analysis of circulating miRNAs in pan-cancers and UCB

BACKGROUND

Circulating miRNAs are promising biomarkers for detection of various cancers. As a "developmental" disorder, cancer showed great similarities with embryos.

OBJECTIVE

A comprehensive analysis of circulating miRNAs in umbilical cord blood (UCB) and pan-cancers was conducted to identify circulating miRNAs with potential for cancer detection.

METHODS

A total of 3831 cancer samples (2050 serum samples from 15 types of cancers and 1781 plasma samples from 13 types of cancers) and 248 UCB samples (120 serum and 128 plasma samples) with corresponding NCs from Chinese populations were analyzed via consistent experiment workflow with Exiqon panel followed by multiple-stage validation with qRT-PCR.

RESULTS

Thirty-four serum and 32 plasma miRNAs were dysregulated in at least one type of cancer. Eighteen serum and 16 plasma miRNAs were related with embryos. Among them, 9 serum and 8 plasma miRNAs with consistent expression patterns between pan-cancers and UCB were identified as circulating oncofetal miRNAs. Retrospective analysis confirmed the diagnostic ability of circulating oncofetal miRNAs for specific cancers. And the oncofetal miRNAs were mainly up-regulated in tissues of pan-cancers.

CONCLUSIONS

Our study might serve as bases for the potential application of the non-invasive biomarkers in the future clinical.

Current and Future Development in Lung Cancer Diagnosis

Lung cancer is the leading cause of cancer-related deaths in North America and other developed countries. One of the reasons lung cancer is at the top of the list is that it is often not diagnosed until the cancer is at an advanced stage. Thus, the earliest diagnosis of lung cancer is crucial, especially in screening high-risk populations, such as smokers, exposure to fumes, oil fields, toxic occupational places, etc. Based on the current knowledge, it looks that there is an urgent need to identify novel biomarkers. The current diagnosis of lung cancer includes different types of imaging complemented with pathological assessment of biopsies, but these techniques can still not detect early lung cancer developments. In this review, we described the advantages and disadvantages of current methods used in diagnosing lung cancer, and we provide an analysis of the potential use of body fluids as carriers of biomarkers as predictors of cancer development and progression.

The Past, Present, and Future (Liquid Biopsy) of Serum Tumor Markers in Lung Cancer: A Primer for the Radiologist

ABSTRACT

Lung cancer continues to be a major cause of death throughout the world. The ability to both accurately diagnose lung cancer in its early stages and monitor response to treatment is essential to reducing the morbidity and mortality associated with the disease. Serum tumor markers have been identified as potential biomarkers that may aid in lung cancer diagnosis and surveillance. These markers, when combined with cross-sectional imaging, may result in more robust screening and surveillance protocols. The future role of serum tumor markers in lung cancer includes the advancement of "liquid biopsies," in which peripheral blood samples are analyzed for tumor components without the need for a tissue biopsy.

Usefulness of protein-based salivary markers in the diagnosis of oral potentially malignant disorders: A systematic review and meta-analysis

By using a meta-analytical approach, this study aimed to analyse the diagnostic capacity of protein-based biomarkers in saliva for the differential diagnosis of oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) from healthy individuals as control group (HCG).Articles on protein-based biomarkers in saliva, which provided quantitative expression in individuals with clinical and histopathological diagnosis of OPMD or oral leukoplakia (OL) were considered eligible. Searches were conducted in eight electronic databases. The methodological quality was assessed using the Quality Assessment of Diagnostic Studies tool (QUADAS-2). Functional analysis was also performed. Meta-analyses were performed using the OpenMeta tool (Analyst).Meta-analysis was possible for 4 of the 11 biomarkers studied. Only the carcinoembryonic antigen (CEA) and the soluble fragment of cytokeratin 19 (CYFRA21) were significant for the OSCC/OPMD subgroup, both with a very low heterogeneity. CEA had an OE = 25.854 (CI95%: 13.215-38.492, p< 0.001, I2 = 0) and CYFRA21 had an OE = 9.317 (CI95%: 9.014-9.619, p< 0.001, I2 = 0). For the OPMD/HCG subgroup, only CYFRA21 was significant, with an OE = 3.679 (CI95%: 0.663-6.696, p= 0.017) although with high heterogeneity (I2 = 91.24).The CEA and CYFRA21 markers proved very useful when differentiating OSCC from OPMD. The CYFRA21 was the only protein that was capable of distinguishing between OPMD and healthy controls.

Interspace-controlled biosensing interface with enhanced charge transfer based on tripod DNA probes

Binding of a target by a probe for selective detection depends on the state of the probes on the sensing interface. Here, the hanging strand length of triple-helix DNA was used to form tripod probes immobilized via π-π interactions on a reduced graphene-oxide substrate. The spacing between the probes was adjusted by controlling the lengths of the tripod "feet" on the substrate; that is, increased probe spacing occurred when foot size increased over the range of 6-12 bases. The surface coverages and electron-transfer rates mediated the tripod DNA probes were characterized by electrochemical methods and atomic force microscopy. The electron-transfer mediated by the tripod DNA probes was higher than that mediated by doubled-stranded DNA. Then different sizes tripod DNA probes were developed for protein-CEA detection. The DNA probes with 10 bases feet showed the best detection limit of detection of 10^-6 ng/mL in the detection linear range (10^-6 - 25 ng/mL). The result demonstrated the tripod DNA probes with different sizes could obtain excellent sensitivity when it applied to the target with appropriate size. This interspace-controlled biosensing interface of tripod DNA probes with enhanced charge transfer should find widespread applications in clinical, medical, biological, and environmental areas for precise detection of differently sized targets.

High Diagnostic and Prognostic Value of miRNAs Compared with the Carcinoembryonic Antigen as a Traditional Tumor Marker

A significant challenge in cancer detection and treatment is early diagnosis and accurate prognosis of the disease that enables effective therapies and interventions to improve the patient's condition. Up to now, many parts of research have tended to focus on the carcinoembryonic antigen (CEA) to detect cancers and estimate the survival rates of patients with multiple cancer types, including colorectal, breast, non-small cell lung, and pancreas cancer. Limited sensitivity and specificity of this traditional tumor marker make it an inappropriate biomarker to diagnose cancer, especially in the early stages, while several lines of research have introduced miRNAs as reliable indicators of tumor initiation, development, and therapy response. Indeed, miRNAs have unique properties that provide considerable benefits, such as discriminating benign diseases from malignancies, prediction of cancer possibility and progress, checking sensitivity to treatment, and initial detection of tumors. This review summarizes the relationships between miRNAs and CEA, the diagnostic significance of CEA in combination with miRNAs, and the distinct advantages of miRNAs over CEA as tumor biomarkers. Advancement in our current understanding of miRNAs is essential to discover new and effective biomarkers for diagnostic, prognostic, and therapeutic goals of cancer patients.

Exploring Volatile Organic Compounds in Breath for High-Accuracy Prediction of Lung Cancer

(1) Background: Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods: The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results: The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.89, 0.82, 0.94, and 0.95, respectively. When we further adjusted the confounding effect of environmental VOCs on the relationship between participants' exhaled VOCs and lung cancer occurrence, our model was improved to reach 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 AUC. (4) Conclusion: A quantitative VOCs databank integrated with the application of an XGBoost classifier provides a persuasive platform for lung cancer prediction.

Serum macrophage inhibitory cytokine-1 as a clinical marker for non-small cell lung cancer

The aim of this study was to investigate the value of serum macrophage inhibitory factor‐1 (MIC‐1) level in patients with non–small cell lung cancer (NSCLC). Serum samples from 296 patients with NSCLC and 240 healthy controls were collected. The levels of serum MIC‐1 were determined by ELISA. The serum MIC‐1 levels in NSCLC patients were higher than that of the controls (P <.001). Univariate and multivariate Cox regression analysis showed that serum MIC‐1 was an independent prognostic indicator of OS and PFS. Serum MIC‐1 is a valuable biomarker for the diagnosis and prognosis of NSCLC.

Site-Specific N-Linked Glycosylation Analysis of Human Carcinoembryonic Antigen by Sheathless Capillary Electrophoresis-Tandem Mass Spectrometry

With 28 potential N-glycosylation sites, human carcinoembryonic antigen (CEA) bears an extreme amount of N-linked glycosylation, and approximately 60% of its molecular mass can be attributed to its carbohydrates. CEA is often overexpressed and released by many solid tumors, including colorectal carcinomas. CEA displays an impressive heterogeneity and variability in sugar content; however, site-specific distribution of carbohydrate structures has not been reported so far. The present study investigated CEA samples purified from human colon carcinoma and human liver metastases and enabled the characterization of 21 out of 28 potential N-glycosylation sites with respect to their occupancy. The coverage was achieved by a multienzymatic digestion approach with specific enzymes, such as trypsin, endoproteinase Glu-C, and the nonspecific enzyme, Pronase, followed by analysis using sheathless CE-MS/MS. In total, 893 different N-glycopeptides and 128 unique N-glycan compositions were identified. Overall, a great heterogeneity was found both within (micro) and in between (macro) individual N-glycosylation sites. Moreover, notable differences were found on certain N-glycosylation sites between primary adenocarcinoma and metastatic tumor in regard to branching, bisection, sialylation, and fucosylation. Those features, if further investigated in a targeted manner, may pave the way toward improved diagnostics and monitoring of colorectal cancer progression and recurrence. Raw mass spectrometric data and Skyline processed data files that support the findings of this study are available in the MassIVE repository with the identifier MSV000086774 [DOI: 10.25345/C5Z50X].

CYFRA 21-1 in patients with suspected cancer: evaluation of an optimal cutoff to assess the diagnostic efficacy and prognostic value

Objectives

Chosen cutoff for cytokeratin 19 fragment antigen (CYFRA 21-1) as a tumor biomarker considerably influences its diagnostic and prognostic usefulness. The aim of the present study is to determine an optimal cutoff value for diagnostic validity of CYFRA 21-1 by Lumipulse ^® technology in patients with suspected cancer and also to determine if CYFRA 21-1 levels provide prognostic value.

Methods

A consecutive 284 patients suggestive of malignant disease from six hospitals of Madrid were enrolled in a retrospective design. Optimal CYFRA 21-1 cutoff value was obtained by receiver operating characteristic curve and Youden test. The diagnostic validity was evaluated according to sensitivity, specificity, predictive values and likelihood ratios. The prognostic value of CYFRA 21-1 was checked using multiple logistic regression. Thirty-two diagnostic cancers were confirmed.

Results

The most optimal cutoff was 3.15 ng/mL. This cutoff showed a better specificity 93.63% (95% confidence interval [CI], 89.66-96.16), positive predictive value 60.98% (95% CI, 44.54-75.38) and positive likelihood ratio 12.65 (95% CI, 7.64-20.95) than the cutoff recommended by Fujirebio^® (1.8 ng/mL) (specificity: 73.71% [95% CI, 67.72-78.95], positive predictive value: 29.79% [95% CI, 21.02-40.23] and positive likelihood ratio 3.43 [95% CI, 2.71-4.35]), improving the current diagnostic accuracy. In multivariate analysis, elevated levels of CYFRA 21-1 (>3.15 ng/mL) was confirmed as an unfavorable prognostic factor.

Conclusions

The best cutoff for CYFRA 21-1 obtained was 3.15 ng/mL in patients with suspected cancer. This new cutoff decreases the false positive rate and improves the diagnostic efficacy of CYFRA 21-1 as a tumor marker as well as its association with death events.

9G TestTM Cancer/Lung: A Desirable Companion to LDCT for Lung Cancer Screening

Simple Summary

Lung cancer is the most common cause of cancer-related deaths globally. Patients diagnosed at early-stage (0–I) have a higher survival rate than the metastasized stages (III–IV). Thus, there is great potential to reduce mortality by diagnosing lung cancer at stage 0~I through community screening. LDCT is a promising method, but it has a high false-positive rate. Therefore, a biomarker test that can be used in combination with LDCT for lung cancer screening to reduce false-positive rates is highly awaited. The present study evaluated the applicability of 9G test^TM Cancer/Lung test to detect stage 0~IV lung cancer. 9G test^TM Cancer/Lung test detects stage I, stage II, stage III, and stage IV cancers with the sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3%. These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer.

Abstract

A complimentary biomarker test that can be used in combination with LDCT for lung cancer screening is highly desirable to improve the diagnostic capacity of LDCT and reduce the false-positive rates. Most importantly, the stage I lung cancer detection rate can be dramatically increased by the simultaneous use of a biomarker test with LDCT. The present study was conducted to evaluate 9G test^TM Cancer/Lung’s sensitivity and specificity in detecting Stage 0~IV lung cancer. The obtained results indicate that the 9G test^TM Cancer/Lung can detect lung cancer with overall sensitivity and specificity of 75.0% (69.1~80.3) and 97.3% (95.0~98.8), respectively. The detection of stage I, stage II, stage III, and stage IV cancers with sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3% have never been reported before. The receiver operating characteristic curve analysis allowed us to determine the population-weighted AUC of 0.93 (95% CI, 0.91–0.95). These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer. Furthermore, obtained results indicate that the use of 9G test^TM Cancer/Lung with LDCT for lung cancer screening can increase stage I cancer detection, which is crucial to improve the currently low 5-year survival rates.

Auxiliary diagnostic value of tumor biomarkers in pleural fluid for lung cancer-associated malignant pleural effusion

Background

Pleural effusion (PE) can be divided into benign pleural effusion (BPE) and malignant pleural effusion (MPE). There is no consensus on the identification of lung cancer-associated MPE using the optimal cut-off levels from five common tumor biomarkers (CEA, CYFRA 21-1, CA125, SCC-Ag, and NSE). Therefore, we aimed to find indicators for the auxiliary diagnosis of lung cancer-associated MPE by analyzing and then validating the optimal threshold levels of these biomarkers in pleural fluid (PF) and serum, as well as the PF/serum ratio.

Patients and method

The study has two sets of patients, i.e. the training set and the test set. In the training set, 348 patients with PE, between January 1, 2016 and December 31, 2017, were divided into BPE and MPE based on the cytological diagnosis. Subsequently, the optimal cut-off levels of tumor biomarkers were analyzed. In the test set, the diagnostic compliance rate was verified with 271 patients with PE from January 1, 2018 to July 31, 2019 to evaluate the auxiliary diagnostic value of the aforementioned indicators.

Result

In the training set, PF CEA at the cut-off value of 5.23 ng/ml was the most effective indicator for MPE compared with other tumor biomarkers (all p < 0.001). In the test set, PF CEA at the cut-off value of 5.23 ng/ml showed the highest sensitivity, specificity and accuracy, positive and negative predictive value among other tumor biomarkers, which were 99.0%, 69.1%, 91.6%, 90.7%, and 95.9%, respectively.

Conclusion

PF CEA at the cut-off level of 5.23 ng/ml was the most effective indicator for identifying lung cancer-associated MPE among the five common tumor biomarkers.

Circulating serum exosomal miR-20b-5p and miR-3187-5p as efficient diagnostic biomarkers for early-stage non-small cell lung cancer

IMPACT STATEMENT

The high mortality of non-small cell lung cancer (NSCLC) is mainly because the cancer has progressed to a more advanced stage before diagnosis. If NSCLC can be diagnosed at early stages, especially stage 0 or I, the overall survival rate will be largely improved by definitive treatment such as lobectomy. We herein validated two novel circulating serum ExmiRs as diagnostic biomarkers for early-stage NSCLC to fulfill the unmet medical need. Considering the number of specimens in this study, circulating serum exosomal miR-20b-5p and miR-3187-5p are putative NSCLC biomarkers, which need to be further investigated in a larger randomized controlled clinical trial.

Expression of Cripto-1 predicts poor prognosis in stage I non-small cell lung cancer

Cripto-1 (CR-1) is related to the biological behaviour and prognosis of carcinomas. The purpose of this study was to investigate the significance of CR-1 expression in surgically resected stage I non-small cell lung cancer (NSCLC). One hundred and forty-eight patients with completely resected stage I NSCLC and available clinical follow-up data were assessed. The protein expression of CR-1 in the tumours was detected by immunohistochemistry. CR-1 was highly expressed in 64 of 148 tumours. Among patients with high CR-1 expression, progression-free survival and overall survival rate were significantly lower than those of patients with low CR-1 levels (P = .013 and P = .019, respectively). The incidence of distant metastasis in patients with high CR-1 expression was significantly higher than that of in patients with low CR-1 expression (57.13% vs 21.43%, P = .001). The results of the multivariate analysis confirmed that a high CR-1 was a significant factor for poor prognosis. In conclusion, CR-1 could be a useful prognostic factor in patients with stage I NSCLC, likely as an indicator of the metastatic propensity of the tumour.

A combination of four serum miRNAs for screening of lung adenocarcinoma

Serum microRNAs (miRNAs), with their noticeable stability and unique expression pattern in patients with various diseases, are robust novel non-invasive biomarkers for cancer detection. The objective of this study was to identify specific serum miRNAs as potential biomarkers for screening lung adenocarcinoma. The study was divided into a screening phase, training phase, and validation phase. The expression of 46 serum miRNAs from lung adenocarcinoma (LUAD) patients and healthy controls (HCs) were examined in the screening phase. The expression of the most dysregulated miRNAs was further verified in training (30 LUAD vs. 30 HCs) and validation (82 LUAD vs. 90 HCs) phases. Seven serum miRNAs (miR-142-5p, miR-203a-5p, miR-409-3p, miR-223-3p, miR-150-5p, miR-486-5p and miR-146a-5p) in LUAD patients were significantly dysregulated compared to those in HCs. Their ability to diagnose lung cancer was also significant, with miR-142-5p (AUC = 0.743), miR-409-3p (AUC = 0.755), miR-223-3p (AUC = 0.828) and miR-146a-5p (AUC = 0.745) being more prominent. The combined use of these four could enhance diagnostic value (AUC = 0.933). Our findings define a distinct miRNA expression profile in the serum of LUAD patients. The four-miRNA panel (miR-142-5p, miR-409-3p, miR-223-3p and 146a-5p) may be considered as a novel, non-invasive biomarker for LUAD early detection.

Development of a prediction model with serum tumor markers to assess tumor metastasis in lung cancer

BACKGROUND

This study aimed to explore the possibility of serum tumor markers (TMs) combinations in assessing tumor metastasis in patients with lung cancer.

METHODS

We performed a retrospective analysis of 541 patients diagnosed with lung cancer between January 2016 and December 2017 at the Pneumology Department of Dazhou Central Hospital. Serum carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125, CA153, CA199, CA724, cytokeratin 19 fragment (CYFRA), and neuron-specific enolase (NSE) levels were quantified in each patient at the time of lung cancer diagnosis. Metastasis was confirmed by computed tomography, and/or positron emission tomography, and/or surgery or other necessary methods. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the performance of the model.

RESULTS

Of the 541 patients eligible for final analysis, 253 were detected with metastasis and 288 were detected without metastasis. Compared with those in nonmetastatic patients, the serum CEA, CA125, CA199, CA153, CYFRA, and NSE levels were notably higher in metastatic patients (P < .05). The ROC curve demonstrated that the CEA-CA125-CA199-CA153-CYFRA-NSE-CA724 combination based on the cut-off value had an optimal area under the curve and specificity in assessing tumor metastasis. The decision tree model is a convenient and valuable tool for guiding the appropriate application of our model to assess metastasis in lung cancer patients.

CONCLUSIONS

Our study suggested that the nomogram of the regression model is valuable for assessing tumor metastasis in newly diagnosed lung cancer patients before traditional standard methods are used. These findings could aid in the evaluation of metastasis in the clinic.

Transcriptomic Analysis in Liquid Biopsy Identifies Circulating PCTAIRE-1 mRNA as a Biomarker in NSCLC

BACKGROUND/AIM

Circulating mRNA can be a useful source of cancer biomarkers. We took advantage of direct transcriptomic analysis in plasma RNA to identify novel mRNA markers for non-small cell lung cancer (NSCLC).

PATIENTS AND METHODS

Plasma RNA from NSCLC patients and healthy individuals was profiled with cDNA-mediated annealing, selection, extension and ligation (DASL) microarrays. The microarray results were further validated in plasma RNA.

RESULTS

Through RNA profiling and online database mining, four gene transcripts were filtered as candidate markers of NSCLC. After validation, the PCTAIRE-1 transcript was identified as a circulating mRNA marker. The diagnostic potential of PCTAIRE-1 was evaluated by receiver operating characteristic curve analysis, which gave a sensitivity and specificity of 60% and 85%, respectively. In addition, high plasma PCTK1 levels were also correlated with poor progression-free survival (p=0.008).

CONCLUSION

Circulating mRNA can be profiled with the DASL assay. From the profile, PCTAIRE-1 RNA in the plasma we discovered as a novel diagnostic/prognostic biomarker and an indicator of poor survival in NSCLC patients.

Noninvasive biomarkers for lung cancer diagnosis, where do we stand?

The 2010's saw demonstration of the power of lung cancer screening to reduce mortality. However, with implementation of lung cancer screening comes the challenge of diagnosing millions of lung nodules every year. When compared to other cancers with widespread screening strategies (breast, colorectal, cervical, prostate, and skin), obtaining a lung nodule tissue biopsy to confirm a positive screening test remains associated with higher morbidity and cost. Therefore, non-invasive diagnostic biomarkers may have a unique opportunity in lung cancer to greatly improve the management of patients at risk. This review covers recent advances in the field of liquid biomarkers and computed tomographic imaging features, with special attention to new methods for combination of biomarkers as well as the use of artificial intelligence for the discrimination of benign from malignant nodules.

Applications and strategies in nanodiagnosis and nanotherapy in lung cancer

Lung cancer is the second most common cancer and the leading cause of death in both men and women in the world. Lung cancer is heterogeneous in nature and diagnosis is often at an advanced stage as it develops silently in the lung and is frequently associated with high mortality rates. Despite the advances made in understanding the biology of lung cancer, progress in early diagnosis, cancer therapy modalities and considering the mechanisms of drug resistance, the prognosis and outcome still remains low for many patients. Nanotechnology is one of the fastest growing areas of research that can solve many biological problems such as cancer. A growing number of therapies based on using nanoparticles (NPs) have successfully entered the clinic to treat pain, cancer, and infectious diseases. Recent progress in nanotechnology has been encouraging and directed to developing novel nanoparticles that can be one step ahead of the cancer reducing the possibility of multi-drug resistance. Nanomedicine using NPs is continuingly impacting cancer diagnosis and treatment. Chemotherapy is often associated with limited targeting to the tumor, side effects and low solubility that leads to insufficient drug reaching the tumor. Overcoming these drawbacks of chemotherapy by equipping NPs with theranostic capability which is leading to the development of novel strategies. This review provides a synopsis of current progress in theranostic applications for lung cancer diagnosis and therapy using NPs including liposome, polymeric NPs, quantum dots, gold NPs, dendrimers, carbon nanotubes and magnetic NPs.