Prognostic value of neuron specific enolase in patients with advanced and metastatic non-neuroendocrine non-small cell lung cancer

Label-Free Assessment of Neuron-Specific Enolase via Polydopamine over a Carbon-Nanotube-Based Flexible Immunosensor

A label-free electrochemical immunosensor was developed for the rapid and sensitive detection of neuron-specific enolase (NSE). The electropolymerization of dopamine in conjunction with highly conductive carbon nanotubes offers a simple and quick platform for the direct anchoring of antibodies without the assistance of any coupling agent as well as a blocking agent. The developed immunosensor exhibited a wider detection range from 120 pM (9 ng mL-1) to 3 nM (200 ng mL-1) for NSE with a high sensitivity of 3.9 μA pM-1 cm-2 in 0.1 M phosphate-buffered saline (PBS) at physiological pH (7.4). Moreover, the short recognition time (15 min) for the antigen enabled the detection to be fast and less invasive. Additionally, the evaluation of a rate constant at various concentrations of NSE via feedback mode of scanning electrochemical microscopy (SECM) explained the profound effect of antigen concentration on the rate of flow of electrons. Therefore, the proposed immunosensor can be a promising tool for the early detection of small cell lung cancer in a very short period of time with consistent accuracy.

Comprehensive proteomic profiling of lung adenocarcinoma: development and validation of an innovative prognostic model

Background

Lung adenocarcinoma (LUAD), a global leading cause of cancer deaths, remains inadequately addressed by current protein biomarkers. Our study focuses on developing a protein-based risk signature for improved prognosis of LUAD.

Methods

We employed the least absolute shrinkage and selection operator (LASSO)-COX algorithm on The Cancer Genome Atlas database to construct a prognostic model incorporating six proteins (CD49B, UQCRC2, SMAD1, FOXM1, CD38, and KAP1). The model's performance was assessed using principal component, Kaplan-Meier (KM), and receiver operating characteristic (ROC) analysis, indicating strong predictive capability. The model stratifies LUAD patients into distinct risk groups, with further analysis revealing its potential as an independent prognostic factor. Additionally, we developed a predictive nomogram integrating clinicopathologic factors, aimed at assisting clinicians in survival prediction. Gene set enrichment analysis (GSEA) and examination of the tumor immune microenvironment were conducted, highlighting metabolic pathways in high-risk genes and immune-related pathways in low-risk genes, indicating varied immunotherapy sensitivity. Validation through immunohistochemistry from the Human Protein Atlas (HPA) database and immunofluorescence staining of clinical samples was performed, particularly focusing on CD38 expression.

Results

Our six-protein model (CD49B, UQCRC2, SMAD1, FOXM1, CD38, KAP1) effectively categorized LUAD patients into high and low-risk groups, confirmed by principal component, KM, and ROC analyses. The model showed high predictive accuracy, with distinct survival differences between risk groups. Notably, CD38, traditionally seen as protective, was paradoxically associated with poor prognosis in LUAD, a finding supported by immunohistochemistry and immunofluorescence data. GSEA revealed that high-risk genes are enriched in metabolic pathways, while low-risk genes align with immune-related pathways, suggesting better immunotherapy response in the latter group.

Conclusions

This study presented a novel prognostic protein model for LUAD, highlighting the CD38 expression paradox and enhancing our understanding of protein roles in lung cancer progression. It offered new clinical tools for prognosis prediction and provided assistance for future lung cancer pathogenesis research.

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Prognostic value of blood-based protein biomarkers in non-small cell lung cancer: A critical review and 2008-2022 update

BACKGROUND

Therapeutic possibilities for non-small cell lung cancer (NSCLC) have considerably increased during recent decades.

OBJECTIVE

To summarize the prognostic relevance of serum tumor markers (STM) for early and late-stage NSCLC patients treated with classical chemotherapies, novel targeted and immune therapies.

METHODS

A PubMed database search was conducted for prognostic studies on carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase, squamous-cell carcinoma antigen, progastrin-releasing-peptide, CA125, CA 19-9 and CA 15-3 STMs in NSCLC patients published from 2008 until June 2022.

RESULTS

Out of 1069 studies, 141 were identified as meeting the inclusion criteria. A considerable heterogeneity regarding design, patient number, analytical and statistical methods was observed. High pretherapeutic CYFRA 21-1 levels and insufficient decreases indicated unfavorable prognosis in many studies on NSCLC patients treated with chemo-, targeted and immunotherapies or their combinations in early and advanced stages. Similar results were seen for CEA in chemotherapy, however, high pretherapeutic levels were sometimes favorable in targeted therapies. CA125 is a promising prognostic marker in patients treated with immunotherapies. Combinations of STMs further increased the prognostic value over single markers.

CONCLUSION

Protein STMs, especially CYFRA 21-1, have prognostic potential in early and advanced stage NSCLC. For future STM investigations, better adherence to comparable study designs, analytical methods, outcome measures and statistical evaluation standards is recommended.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Assessment of Specific Tumoral Markers, Inflammatory Status, and Vitamin D Metabolism before and after the First Chemotherapy Cycle in Patients with Lung Cancer

Background: We aimed to investigate the changes of inflammatory status reflected by serum levels of chitotriosidase (CHT) and neopterin, and how specific tumor markers such as neuron-specific enolase (NSE) and squamous cell carcinoma antigen (SCCA), as well as vitamin D metabolism assessed by vitamin D receptor (VDR) and 25-hydroxy vitamin D3 (25OHD3), were modified after the first cycle of chemotherapy in patients with lung cancer. Methods: We performed this first pilot study on twenty patients diagnosed with lung cancer by investigating the serum concentrations of CHT, neopterin, NSE, SCCA, VDR and 25OHD3 before and after the first cycle of chemotherapy. Results: The post-treatment values of NSE were significantly lower compared to the pre-treatment levels (14.37 vs. 17.10 ng/mL, p = 0.031). We noticed a similar trend in neopterin levels, but the difference was only marginally significant (1.44 vs. 1.17 ng/mL, p = 0.069). On the contrary, the variations of circulating SCCA, CHT, neopterin, VDR and 25OHD3, before and after treatment, did not reach statistical significance. Conclusion: Only circulating NSE was treatment responsive to the first chemotherapy cycle in patients with lung cancer, while inflammatory markers and vitamin D status were not significantly modified.

Postoperative venous thromboembolism after surgery for stage IA non-small-cell lung cancer: A single-center, prospective cohort study

BACKGROUND

Venous thromboembolism (VTE) is a common postoperative complication of lung cancer, but the incidence and risk stratification of postoperative VTE in stage IA non-small-cell lung cancer (NSCLC) patients remains unclear, therefore we conducted a single-center prospective study.

METHODS

A total of 314 consecutive patients hospitalized for lung cancer surgery and diagnosed with stage IA NSCLC from January 2017 to July 2021 were included. The patients were divided into the VTE group and the non-VTE group according to whether VTE occurred after the operation. The patient's age, operation time, D-dimer (D-D) value, tumor pathology, and Caprini score were recorded. The different items were compared and included in logistic regression analysis to obtain independent risk factors, and the area under the receiver operating characteristics curve (AUC) was calculated.

RESULTS

The incidence of VTE was 7.3%. Significant differences in age, operation time, preoperative and postoperative day 1 D-D value, neuron-specific enolase value, forced expiratory volume in 1 second, maximum ventilation, carbon monoxide diffusion capacity, and pathological diameter were noted between the two groups. Age (95% confidence interval [CI] 1.056-1.216) and postoperative day 1 D-D value (95% CI 1.125-1.767) were independent risk factors. The incidence of VTE in the low-, medium-, and high-risk groups with Caprini scores was 0%, 7.3%, and 11.5%, respectively. The AUC of the Caprini score was 0.704 (p < 0.05).

CONCLUSIONS

The incidence of postoperative VTE in patients with stage IA NSCLC was 7.3%. Age and postoperative day 1 D-D value were independent risk factors for VTE. The Caprini score has a certain value in the diagnosis of postoperative VTE of stage IA NSCLC.

Clinical Significance of Tumor Markers for Advanced Thymic Carcinoma: A Retrospective Analysis from the NEJ023 Study

Simple Summary

Advanced thymic carcinoma (ATC) is rare. Owing to its rarity, there is limited information on the prognostic factors, and the optimal serum tumor markers are also unknown. We conducted a multi-institutional retrospective study of patients with ATC. In this study, we collected data on patient characteristics, progression-free survival (PFS), overall survival (OS), and tumor marker values, and investigated the relationship between tumor marker values and PFS/OS. We found that the neuron-specific enolase (NSE) level may be a useful prognostic tumor marker for ATC, regardless of histology. The findings of the analysis limited to squamous cell carcinoma suggested that the NSE and squamous cell carcinoma antigen levels may be useful prognostic factors.

Abstract

The optimal tumor marker for predicting the prognosis of advanced thymic carcinoma (ATC) remains unclear. We conducted a multi-institutional retrospective study of patients with ATC. A total of 286 patients were treated with chemotherapy. Clinicopathological information, including serum tumor markers, was evaluated to determine the overall survival (OS) and progression-free survival (PFS). The carcinoembryonic antigen, cytokeratin-19 fragment, squamous cell carcinoma (SCC) antigen, progastrin-releasing peptide, neuron-specific enolase (NSE), and alpha-fetoprotein levels were evaluated. In the Kaplan–Meier analysis, the OS was significantly shorter in the patients with elevated NSE levels than in those with normal NSE levels (median, 20.3 vs. 36.8 months; log-rank test p = 0.029; hazard ratio (HR), 1.55; 95% confidence interval (CI), 1.05–2.31 (Cox proportional hazard model)); a similar tendency regarding the PFS was observed (median, 6.4 vs. 11.0 months; log-rank test p = 0.001; HR, 2.04; 95% CI, 1.31–3.18). No significant differences in the OS and PFS were observed among the other tumor markers. In both univariate and multivariate analyses of the patients with SCC only, the NSE level was associated with the OS and PFS. Thus, the NSE level may be a prognostic tumor marker for thymic carcinoma, regardless of histology.