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

FTIR spectroscopy for assessment of hair from lung cancer patients and its application in monitoring the chemotherapy treatment effect

Lung cancer is the most common cancer and the leading cause of death in China. The current gold standard for clinical lung cancer diagnosis is based on histopathological examination of tumors, but it has the limitation for easy operation and convenient applications. Therefore, researchers are still striving to develop other tools and methods for non-invasive and rapid assessment of the health conditions of lung cancer patients. Hair, as a reflection of the metabolism of the body, is closely related to human health conditions. In principle, Fourier-transform infrared (FTIR) spectroscopy can probe the major chemical compositions in the hair. However, as indicated by previous studies, there is still the challenge to make good use of FTIR spectroscopy for achieving reliable analysis of hair from cancer patients. In this study, hair samples from 82 lung cancer patients were collected and subjected to FTIR measurements and analysis, which showed the protein content in the hair is closely related to the protein content in the blood serum of patients, and the contents of protein and lipid are statistically lower in the lung cancer patients. Furthermore, we demonstrated that FTIR spectroscopy could be employed to monitor the hair of lung cancer patients undergoing chemotherapy, and confirmed that the FTIR spectra of the hair may reflect the resultant effect of the chemotherapy. As such, this work validates the way of using FTIR spectroscopy in hair analysis for the assistance of medical diagnosis of lung cancer as well as monitoring the conditions of the patients under the medical treatment.

The Role of Biomarkers in Lung Cancer Screening

BACKGROUND

Lung Cancer Screening (LCS) is an evolving field with variations in its implementation in various countries. There are only scarce data from National LCS programs.

AIM

We aim to provide an up-to-date overview of the current evidence regarding the use of biomarkers in LCS.

MATERIALS AND METHODS

A multidisciplinary Task Force experts' panel collaborated and conducted a systematic literature search, followed by screening, review and synthesis of available evidence.

RESULTS

Biomarkers in LCS could be used to improve risk stratification in high-risk participants, improve clarification regarding indeterminate lung nodules and avoid overdiagnosis in suspicious lung findings. Currently, there seem to be promising biomarkers (blood/serum/breath) that have been studied in various trials; however, there is still a lack of solid evidence in clinical validation that would pave the way for their integration into LCS programs.

CONCLUSIONS

Biomarkers are the next logical step in improving the LCS pathway and its efficiency by playing an adjuvant role in a minimally invasive way. National LCS programs and pilot studies should integrate biomarkers to validate their accuracy in real-life LCS participants.

Unveiling the best predictive models for early‑onset metastatic cancer: Insights and innovations (Review)

Cancer metastasis is the primary cause of cancer deaths. Metastasis involves the spread of cancer cells from the primary tumors to other body parts, commonly through lymphatic and vascular pathways. Key aspects include the high mutation rate and the capability of metastatic cells to form invasive tumors even without a large initial tumor mass. Particular emphasis is given to early metastasis, occurring in initial cancer stages and often leading to misdiagnosis, which adversely affects survival and prognosis. The present review highlighted the need for improved understanding and detection methods for early metastasis, which has not been effectively identified clinically. The present review demonstrated the clinicopathological and molecular characteristics of early‑onset metastatic types of cancer, noting factors such as age, race, tumor size and location as well as the histological and pathological grade as significant predictors. In conclusion, the present review underscored the importance of early detection and management of metastatic types of cancer and called for improved predictive models, including advanced techniques such as nomograms and machine learning, so as to enhance patient outcomes, acknowledging the challenges and limitations of the current research as well as the necessity for further studies.

Determination of Tumor Marker Screening for Lung Cancer Using ROC Curves

Introduction

Lung cancer ranks first among malignant tumors worldwide and is a leading cause of cancer-related mortality in both men and women. Combining tumor marker testing is a strategy to screen individuals at high risk of pulmonary cancer and minimize pulmonary cancer mortality. Therefore, tumor marker screening is crucial. In this study, we analyzed combinations of tumor markers for lung cancer screening using receiver operating characteristic (ROC) curve analysis.

Methods

A retrospective descriptive study was conducted on patients diagnosed with lung cancer, as well as healthy and benign lung diseases, using data from the China Huludao Central Hospital database between January 2016 and July 2022. The t-test and ROC curve were utilized to assess the effectiveness of individual tumor marker and the combination of multiple tumor markers. Tumor markers are molecular products metabolized and secreted by tumor tissues, characterized by cells or body fluids. They serve as indicators of tumor stage and grading, monitor treatment response, and predict recurrence.

Results

In this study, 267 healthy participants, 385 patients with benign lesions, and 296 patients with lung cancer underwent tumor marker screening. The sensitivity of five tumor markers-CEA, CYFRA21-1, NSE, pro-GRP, and CA125-was found to be <55%. This study revealed that a single tumor marker had limited value in lung cancer screening. However, combining two or more markers yielded varying area under the curves (AUC), with no significant impact on screening accuracy. The combination of CEA + CA125 demonstrated the highest accuracy for lung cancer screening in healthy participants. At a cutoff of 0.447 for CEA + CA125, the combination showed a sensitivity of 0.676 and specificity of 0.846 for lung cancer screening. Conversely, for patients with benign lung lesions, the optimal combination was CEA + NSE, with a cutoff of 0.393, yielding a sensitivity of 0.645 and specificity of 0.766 for lung cancer screening.

Conclusion

The five tumor markers-CEA, CA125, CY211, NSE, GRP-show promising results in screening healthy individuals and patients with lung cancer. However, only CEA, NSE, and GRP effectively differentiate patients with benign lung lesions from those with lung cancer. A single tumor marker has limited utility in detecting and screening for lung cancer and should be combined with other tumor markers. CEA + CA125 emerges as a superior tumor marker for distinguishing healthy individuals from those with lung cancer, whereas the CEA + NSE combination is more effective in identifying tumor markers in patients with benign lung lesions and lung cancer.

A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer

Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n = 727), healthy controls (HEA, n = 1,092), as well as patients with small cell lung cancer (SCLC, n = 41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p < 0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.

Circulating Concentrations of advanced Glycation end Products, Carboxymethyl Lysine and Methylglyoxal are Associated With Renal Function in Individuals With Diabetes

OBJECTIVE

Diabetic kidney disease (DKD) is one of the most severe chronic complications of diabetes and is associated with higher level of advanced glycation end products (AGEs). The aim of this study was to investigate the diagnostic potential of combined detection of multiple serum AGEs in diagnosing DKD.

METHODS

Serum AGEs, Nε-(carboxymethyl) lysine (CML), Nε-(carboxyethyl) lysine, and methylglyoxal (MGO) levels were measured by enzyme-linked immunosorbent assay in 176 individuals with type 2 diabetes. Participants were classified into normoalbuminuria, microalbuminuria, and macroalbuminuria group according to their urinary albumin to creatinine ratio (UACR).

RESULTS

Higher serum AGEs levels were found to be positively correlated with U-Alb, UACR, and blood urea nitrogen in the study of 176 individuals with type 2 diabetes. CML and MGO levels were positively correlated with U-Alb, UACR, blood urea nitrogen, Scr, and uric acid, and negatively correlated with estimated glomerular filtration rate (P < .05). Multivariate logistic regression analysis showed that elevated levels of AGEs, CML, and MGO were independent risk factors for the progression of DKD (odds ratio = 1.861, 1.016, 7.607, P < .01). The sensitivity, specificity, and area under receiver operating characteristic curve of combined detection of AGEs, MGO, and CML were higher than those of three individual detections (area under the curve = 0.952, 0.772, 0.868, 0905, respectively, P < .05).

CONCLUSION

The combined detection of AGEs, CML, and MGO may improve the reliability of early diagnosis of DKD.

Ultrasensitive detection of NSE employing a novel electrochemical immunosensor based on a conjugated copolymer

In the current study a simple and highly specific label-free impedimetric neuron specific enolase (NSE) immunosensor based on a copolymer matrix-coated disposable electrode was designed and tested. The copolymer matrix was prepared using a very conductive EDOT monomer and semi-conductive thiophene-bearing epoxy groups (ThEp), and the combination of the two monomers enhanced the conductivity and protein loading capacity of the electrode surface. The P(ThEp-co-EDOT) copolymer matrix was prepared via a drop-casting process and anti-NSE recognition biomolecules were immobilized directly on the epoxy groups of the copolymer. After the coupling of NSE molecules on the P(ThEp-co-EDOT) copolymer matrix-coated electrode surface, the charge transfer resistance (Rct) of the biosensor changed dramatically. These changes in Rct were proportional to the NSE molecule amounts captured by anti-NSE molecules. Under optimized experimental conditions, the increment in the Rct value was proportional to the NSE concentration over a range of 0.01 to 25 pg mL-1 with a detection limit (LOD) of 2.98 × 10-3 pg mL-1. This copolymer-coated electrode provided a lower LOD than the other biosensors. In addition, the suggested electrochemical immuno-platform showed good selectivity, superior reproducibility, long-term stability, and high recovery of NSE in real serum (95.64-102.20%) and saliva (95.28-105.35%) samples. These results showed that the present system had great potential for electrochemical biosensing applications.

Detection of the DNA methylation of seven genes contribute to the early diagnosis of lung cancer

BACKGROUND

Low-dose Computed Tomography (CT) is used for the detection of pulmonary nodules, but the ambiguous risk evaluation causes overdiagnosis. Here, we explored the significance of the DNA methylation of 7 genes including TAC1, CDO1, HOXA9, ZFP42, SOX17, RASSF1A and SHOX2 in the blood cfDNA samples in distinguishing lung cancer from benign nodules and healthy individuals.

METHOD

A total of 149 lung cancer patients [72 mass and 77 ground-glass nodules (GGNs)], 5 benign and 48 healthy individuals were tested and analyzed in this study. The lasso-logistic regression model was built for distinguishing cancer and control/healthy individuals or IA lung cancer and non-IA lung cancer cases.

RESULTS

The positive rates of methylation of 7 genes were higher in the cancer group as compared with the healthy group. We constructed a model using age, sex and the ΔCt value of 7 gene methylation to distinguish lung cancer from benign and healthy individuals. The sensitivity, specificity and AUC (area under the curve) were 86.7%, 81.4% and 0.891, respectively. Also, we assessed the significance of 7 gene methylation together with patients' age and sex in distinguishing of GGNs type from the mass type. The sensitivity, specificity and AUC were 77.1%, 65.8% and 0.753, respectively. Furthermore, the methylation positive rates of CDO1 and SHOX2 were different between I-IV stages of lung cancer. Specifically, the positive rate of CDO1 methylation was higher in the non-IA group as compared with the IA group.

CONCLUSION

Collectively, this study reveals that the methylation of 7 genes has a big significance in the diagnosis of lung cancer with high sensitivity and specificity. Also, the 7 genes present with certain significance in distinguishing the GGN type lung cancer, as well as different stages.

Analysis of influencing factors of serum SCCA elevation in 309 CAP patients with normal CEA,NSE and CYFRA21-1

Introduction

Squamous cell carcinoma antigen (SCCA) is one of the auxiliary diagnostic indicators of lung squamous cell carcinoma, and an increase in serum SCCA can predict the occurrence of lung squamous cell carcinoma. However, whether SCCA is also elevated in pneumonia patients without malignancy is still not clear. Therefore, we studied influencing factors of elevated serum SCCA in patients with community-acquired pneumonia.

Methods

We retrospectively enrolled 309 patients who were admitted to the Respiratory department with normal serum Carcinoembryonic antigen (CEA), Neuron specific enolase (NSE), and Cytokeratin 19 fragment (CYFRA21-1) level and were diagnosed with community-acquired pneumonia (CAP). The patients' serum SCCA level, body temperature, age, sex, white blood cell (WBC) count, hypersensitive C-reactive protein (Hs-CRP) level, and serum amyloid A (SAA) were recorded. Logistic regression models were used to analyze the risk factors of SCCA elevation. The dose-response relationship between temperature and risk of SCCA increase was analyzed using Restricted cubic splines (RCS).

Results

Of the 309 patients, 143(46.3%) showed elevated SCCA levels. The logistic regression analysis revealed a significant influence of age and body temperature on elevated SCCA (P<0.05) levels. For every one-year increase in age, the probability of elevated SCCA decreased by 3% [OR=0.97,95%CI:0.95,0.99].For every 1°C increase in body temperature, the risk of elevated SCCA increased by 2.75 times [OR=3.75,95%CI:2.55,5.49].The patients were sorted into quartiles based on body temperature. Compared with patients in the Q1 of body temperature group, patients in the Q3 group were at 7.92 times higher risk [OR=7.92, 95%CI:3.27,19.16].and the risk of elevated SCCA was increased by 22.85 times in the Q4 group [OR=23.85,95%CI:8.38,67.89] after adjusting for age, gender, Hs-CRP, SAA, and WBC. RCS analysis showed there was a linear relationship between temperature index and risk of elevated SCCA.

Conclusion

In summary, for CAP patients with normal CEA,NSE and CYFRA21-1 level, age and body temperature are influencing factors of SCCA elevation. Higher body temperature has a strong association with the occurrence of SCCA elevation.

Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities

Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.

Circulating lung cancer biomarkers: From translational research to clinical practice

Fundamental studies on biomarkers as well as developed assays for their detection can provide valuable information facilitating clinical decisions. For patients with lung cancer, there are established circulating biomarkers such as serum progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), and cytokeratin-19 fragment (CYFRA21-1). There are also molecular biomarkers for targeted therapy such as epidermal growth factor receptor (EGFR) gene, anaplastic lymphoma kinase (ALK) gene, KRAS gene, and BRAF gene. However, there is still an unmet need for biomarkers that can be used for early detection and predict treatment response and survival. In this review, we describe the lung cancer biomarkers that are currently being used in clinical practice. We also discuss emerging preclinical and clinical studies on new biomarkers such as omics-based biomarkers for their potential clinical use to detect, predict, or monitor subtypes of lung cancer. Additionally, between-method differences in tumor markers warrant further development and improvement of the standardization and harmonization for each assay.

Comparison of serum tumor markers combined with dual-source CT in the diagnosis of lung cancer

BACKGROUND

The purpose of this study is to explore the clinical value of serum tumor markers combined with dual-source CT scanning in the diagnosis of lung cancer.

METHODS

One hundred-two patients with lung cancer (malignant tumor group), 50 patients with benign lesions (benign control group) and 50 healthy patients (normal control group) were selected as the research objects. The levels of serum carcinoembryonic antigen (CEA), cytokeratin 19 fragment antigen 21-1 (CYFRA21-1) and gastrin releasing peptide precursor 31-98 (Pro-GRP31-98) were detected using the electrochemiluminescence and enzyme-linked immunoassay in three groups of people. Simultaneously, Siemens' second-generation dual-source CT (Siemens AG, Munich, Germany) is used to scan the lungs of patients with lung cancer and benign lesions. Retrospective statistical analysis is utilized to explore the clinical value of serum tumor markers combined with dual-source CT examination in the diagnosis of lung cancer.

RESULTS

The levels of serum CEA, CYFRA21-1 and Pro-GRP31-98 in lung cancer patients were significantly higher than those in the benign control group and normal control group, and the difference was statistically significant (P<0.01). There was no statistical difference between the benign control group and the normal control group (P>0.05). The levels of serum CEA, CYFRA21-1, Pro-GRP31-98 had no significant correlation with the age, sex, and tumor site of lung cancer patients (P>0.05). However, the levels of serum CEA, CYFRA21-1, Pro-GRP31-98 have an obvious correlation with tumor size, clinical stage, histological type, combined pleural effusion, recurrence and metastasis after treatment (P<0.05). CT scans of 102 lung cancer patients showed 35 cases of central type, 67 cases of peripheral type, 71 cases with tumor diameter >5cm, 31 cases of ≤5cm and 67 cases of lymph node metastasis. The sensitivities of CEA, CYFRA21-1, Pro-GRP31-98, and dual-source CT in the diagnosis of lung cancer were 64.70%, 60.11%, 56.86% and 77.45%, and the accuracy was 75.00%, 72.37%, 69.74% and 82.89%, respectively. Compared with a single examination, the sensitivity and accuracy of combined examination for the diagnosis of lung cancer were significantly improved, which were 95.10% and 92.76%, respectively.

CONCLUSIONS

Joint examinations can effectively improve the rate of lung cancer diagnosis.

Variability of serum CYFRA 21 - 1 and its susceptibility to clinical characteristics in individuals without cancer: a 4-year retrospective analysis

BACKGROUND

CYFRA 21 - 1 is a useful marker for diagnosing and monitoring lung cancer. However, its stability remains unclear. Moreover, while its applicability to screening is now being investigated, CYFRA 21 - 1 levels in individuals without cancer, who are targets for cancer screening, have not yet been the focus of research. Therefore, the present study investigated variability in and the factors increasing serum CYFRA 21 - 1 levels.

METHODS

This retrospective study recruited 951 individuals undergoing annual medical examinations for six years. We used data obtained in the first four years. Variability in serum CYFRA 21 - 1 levels over a period of four years were investigated. CYFRA 21 - 1 was categorized as normal (≤ 3.5 ng/ml) or elevated (> 3.5 ng/ml). The rate of an elevated level in one visit and the transition from an elevated to normal level between visits were visualized. A multiple logistic regression model was used to study the relationships between the frequency of elevated CYFRA 21 - 1 levels and clinical characteristics, such as age, sex, body mass index, weight changes, and the smoking status.

RESULTS

Approximately 5% of subjects had elevated CYFRA 21 - 1 levels once in five tests over four years, while 15% had elevated CYFRA 21 - 1 levels once or more. Among subjects with elevated CYFRA 21 - 1 levels in one blood test, between 63 and 72% had normal levels in the next test. The median CYFRA 21 - 1 level in subjects with elevations in one blood test significantly decreased in the next test at all four time points. The frequency of elevated CYFRA 21 - 1 levels was associated with an older age [odds ratio (OR) = 6.99, 95% confidence interval (CI) = 3.01-16.2], current heavy smoking (OR = 3.46, 95% CI = 1.52-7.9), and weight loss (OR = 1.86, 95% CI = 1.07-3.24).

CONCLUSIONS

Variability in and the factors increasing serum CYFRA 21 - 1 levels beyond the cut-off value need to be considered when interpretating CYFRA 21 - 1 test results. The future application of CYFRA 21 - 1 to lung cancer screening may require more than a single measurement.

Application of Metal-Based Nanomaterials in In Vitro Diagnosis of Tumor Markers: Summary and Prospect

Cancer, which presents with high incidence and mortality rates, has become a significant health threat worldwide. However, there is currently no effective solution for rapid screening and high-quality treatment of early-stage cancer patients. Metal-based nanoparticles (MNPs), as a new type of compound with stable properties, convenient synthesis, high efficiency, and few adverse reactions, have become highly competitive tools for early cancer diagnosis. Nevertheless, challenges such as the difference between the microenvironment of detected markers and the real-life body fluids remain in achieving widespread clinical application of MNPs. This review provides a comprehensive review of the research progress made in the field of in vitro cancer diagnosis using metal-based nanoparticles. By delving into the characteristics and advantages of these materials, this paper aims to inspire and guide researchers towards fully exploiting the potential of metal-based nanoparticles in the early diagnosis and treatment of cancer.

Neuronal dysfunction in individuals at early stage of schizophrenia, A resting-state fMRI study

Schizophrenia has been associated with abnormal intrinsic brain activity, involving various cognitive impairments. Qualitatively similar abnormalities are seen in individuals at ultra-high risk (UHR) for psychosis. In this study, resting-state fMRI (rs-fMRI) data were collected from 44 drug-naïve first-episode schizophrenia (Dn-FES) patients, 48 UHR individuals, and 40 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC), were performed to evaluate resting brain function. A support vector machine (SVM) was applied for classification analysis. Compared to HCs, both clinical groups showed increased fALFF in the central executive network (CEN), decreased ReHo in the ventral visual pathway (VVP) and decreased FC in temporal-sensorimotor regions. Excellent performance was achieved by using fALFF value in distinguishing both FES (sensitivity=83.21%, specificity=80.58%, accuracy=81.37%, p=0.009) and UHR (sensitivity=75.88%, specificity=85.72%, accuracy=80.72%, p<0.001) from HC group. Moreover, the study highlighted the importance of frontal and temporal alteration in the pathogenesis of schizophrenia. However, no fMRI features were observed that could well distinguish Dn-FES from UHR group. To conclude, fALFF in the CEN may provide potential power for identifying individuals at the early stage of schizophrenia and the alteration in the frontal and temporal lobe may be important to these individuals.

Mucins as Potential Biomarkers for Early Detection of Cancer

Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients' sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.

Complete blood platelet and lymphocyte ratios increase diagnostic accuracy of periprosthetic joint infection following total hip arthroplasty

INTRODUCTION

Systemically, changes in serum platelet to lymphocyte ratio (PLR), platelet count to mean platelet volume ratio (PVR), neutrophil to lymphocyte ratio (NLR) and monocyte to lymphocyte (MLR) represent primary responses to early inflammation and infection. This study aimed to determine whether PLR, PVR, NLR, and MLR can be useful in diagnosing periprosthetic joint infection (PJI) in total hip arthroplasty (THA) patients.

METHODS

A total of 464 patients that underwent revision THA with calculable PLR, PVR, NLR, and MLR in 2 groups was evaluated: 1) 191 patients with a pre-operative diagnosis of PJI, and 2) 273 matched patients treated for revision THA for aseptic complications.

RESULTS

The sensitivity and specificity of PLR combined with erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), synovial white blood cell count (WBC) and synovial polymorphonuclear leukocytes (PMN) (97.9%; 98.5%) is significantly higher than only ESR combined with CRP, synovial WBC and synovial PMN (94.2%; 94.5%; p < 0.01). The sensitivity and specificity of PVR combined with ESR, CRP and synovial WBC, and synovial PMN (98.4%; 98.2%) is higher than only ESR combined with CRP, synovial WBC and synovial PMN (94.2%; 94.5%; p < 0.01).

CONCLUSION

The study results demonstrate that both PLR and PVR calculated from complete blood counts when combined with serum and synovial fluid markers have increased diagnostic sensitivity and specificity in diagnosing periprosthetic joint infection in THA patients.

LEVEL OF EVIDENCE

III, case-control retrospective analysis.

Liquid biopsy-based decision support algorithms for diagnosis and subtyping of lung cancer

OBJECTIVES

Pathologic subtyping of tissue biopsies is the gold standard for the diagnosis of lung cancer (LC), which could be complicated in cases of e.g. inconclusive tissue biopsies or unreachable tumors. The diagnosis of LC could be supported in a minimally invasive manner using protein tumor markers (TMs) and circulating tumor DNA (ctDNA) measured in liquid biopsies (LBx). This study evaluates the performance of LBx-based decision-support algorithms for the diagnosis of LC and subtyping into small- and non-small-cell lung cancer (SCLC and NSCLC) aiming to directly impact clinical practice.

MATERIALS AND METHODS

In this multicenter prospective study (NL9146), eight protein TMs (CA125, CA15.3, CEA, CYFRA 21-1, HE4, NSE, proGRP and SCCA) and ctDNA mutations in EGFR, KRAS and BRAF were analyzed in blood of 1096 patients suspected of LC. The performance of individual and combined TMs to identify LC, NSCLC or SCLC was established by evaluating logistic regression models at pre-specified positive predictive values (PPV) of ≥95% or ≥98%. The most informative protein TMs included in the multi-parametric models were selected by recursive feature elimination.

RESULTS

Single TMs could identify LC, NSCLC and SCLC patients with 46%, 25% and 40% sensitivity, respectively, at pre-specified PPVs. Multi-parametric models combining TMs and ctDNA significantly improved sensitivities to 65%, 67% and 50%, respectively.

CONCLUSION

In patients suspected of LC, the LBx-based decision-support algorithms allowed identification of about two-thirds of all LC and NSCLC patients and half of SCLC patients. These models therefore show clinical value and may support LC diagnostics, especially in patients for whom pathologic subtyping is impossible or incomplete.

Value of dual-source CT dual-energy parameters combined with serum detection of VEGF and CEA in the diagnosis of early lung cancer

To discuss the value of dual-source CT dual-energy parameters combined with serum detection of vascular endothelial growth factor (VEGF) and carcinoembryonic antigen (CEA) in the diagnosis of early lung cancer (LC). In total, 100 patients with lung lesions in our hospital from January 2020 to January 2022 were selected for retrospective study, and were divided into the lung cancer group (group A) and benign lung disease group (group B) according to the final results of pathological diagnosis, using dual-source CT dual-energy scanning combined with serum detection of VEGF and CEA to analyze the diagnostic values of single detection and combined detection. Among the 100 patients with lung lesions, there were 58 patients with LC and 42 patients with benign lung diseases after pathological examination, with no statistical difference in normalized iodine concentration (NIC) and the increased value of iodine at arterial phase between the two groups (P > 0.05). The NIC value of group A was higher than group B at venous phase (P < 0.05). The serum levels of VEGF and CEA in group A were higher than group B (P < 0.05). The area under the curve, specificity, sensitivity, Youden index and 95% CI of combined diagnosis were higher than single detection of NIC, VEGF and CEA at venous phase. The combined application of dual-source CT dual-energy parameters and serum detection of VEGF and CEA has higher diagnostic value in patients with early LC, which can provide effective reference for clinical diagnosis and treatment, with higher application value in clinic.

Expression changes and clinical significance of serum neuron-specific enolase and squamous cell carcinoma antigen in lung cancer patients after radiotherapy

OBJECTIVE

To explore the changes and clinical significance of serum Neuron-Specific Enolase (NSE) and Squamous Cell Carcinoma antigen (SCC) in patients with lung cancer before and after radiotherapy.

METHODS

82 patients with lung cancer were treated with radiotherapy, and effective clinical intervention was given during the radiotherapy process. The patients were followed up for 1 year after radiotherapy and were divided into a recurrence and metastasis group (n = 28) and a non-recurrence and metastasis group (n = 54) according to their prognosis. Another 54 healthy volunteers examined in the present study's hospital during the same period were selected as the control group. To compare the changes of NSE and SCC levels in serum in patients with lung cancer at admission and after radiotherapy, and to explore their clinical significance.

RESULTS

After intervention, NSE and SCC levels in the serum of the two groups of patients were significantly lower than those before intervention, and the levels of CD4⁺ and CD4⁺/CD8⁺ were significantly higher than those before intervention (p < 0.05); the level of CD8⁺ was not significantly different from that before intervention (p > 0.05). And NSE and SCC levels in the intervention group were significantly lower than those in the routine group, the levels of CD4⁺, CD4⁺/CD8⁺ were significantly higher than those in the routine group (p < 0.05).

CONCLUSION

NSE and SCC in serum can preliminarily evaluate the effect of radiotherapy in patients with lung cancer and have a certain predictive effect on prognosis.

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.

A Comprehensive Survey on the Progress, Process, and Challenges of Lung Cancer Detection and Classification

Lung cancer is the primary reason of cancer deaths worldwide, and the percentage of death rate is increasing step by step. There are chances of recovering from lung cancer by detecting it early. In any case, because the number of radiologists is limited and they have been working overtime, the increase in image data makes it hard for them to evaluate the images accurately. As a result, many researchers have come up with automated ways to predict the growth of cancer cells using medical imaging methods in a quick and accurate way. Previously, a lot of work was done on computer-aided detection (CADe) and computer-aided diagnosis (CADx) in computed tomography (CT) scan, magnetic resonance imaging (MRI), and X-ray with the goal of effective detection and segmentation of pulmonary nodule, as well as classifying nodules as malignant or benign. But still, no complete comprehensive review that includes all aspects of lung cancer has been done. In this paper, every aspect of lung cancer is discussed in detail, including datasets, image preprocessing, segmentation methods, optimal feature extraction and selection methods, evaluation measurement matrices, and classifiers. Finally, the study looks into several lung cancer-related issues with possible solutions.

The Potential Role of MUC16 (CA125) Biomarker in Lung Cancer: A Magic Biomarker but with Adversity

Lung cancer is the second most commonly diagnosed cancer in the world. In terms of the diagnosis of lung cancer, combination carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) detection had higher sensitivity, specificity, and diagnostic odds ratios than CEA detection alone. Most individuals with elevated serum CA125 levels had lung cancer that was either in stage 3 or stage 4. Serum CA125 levels were similarly elevated in lung cancer patients who also had pleural effusions or ascites. Furthermore, there is strong evidence that human lung cancer produces CA125 in vitro, which suggests that other clinical illnesses outside of ovarian cancer could also be responsible for the rise of CA125. MUC16 (CA125) is a natural killer cell inhibitor. As a screening test for lung and ovarian cancer diagnosis and prognosis in the early stages, CA125 has been widely used as a marker in three different clinical settings. MUC16 mRNA levels in lung cancer are increased regardless of gender. As well, increased expression of mutated MUC16 enhances lung cancer cells proliferation and growth. Additionally, the CA125 serum level is thought to be a key indicator for lung cancer metastasis to the liver. Further, CA125 could be a useful biomarker in other cancer types diagnoses like ovarian, breast, and pancreatic cancers. One of the important limitations of CA125 as a first step in such a screening technique is that up to 20% of ovarian tumors lack antigen expression. Each of the 10 possible serum markers was expressed in 29-100% of ovarian tumors with minimal or no CA125 expression. Therefore, there is a controversy regarding CA125 in the diagnosis and prognosis of lung cancer and other cancer types. In this state, preclinical and clinical studies are warranted to elucidate the clinical benefit of CA125 in the diagnosis and prognosis of lung cancer.

Blood–brain barrier and brain structural changes in lung cancer patients with non-brain metastases

Purpose

To explore the relationship between blood-brain barrier (BBB) leakage and brain structure in non-brain metastasis lung cancer (LC) by magnetic resonance imaging (MRI) as well as to indicate the possibility of brain metastasis (BM) occurrence.

Patients and methods

MRI were performed in 75 LC patients and 29 counterpart healthy peoples (HCs). We used the Patlak pharmacokinetic model to calculate the average leakage in each brain region according to the automated anatomical labeling (AAL) atlas. The thickness of the cortex and the volumes of subcortical structures were calculated using the FreeSurfer base on Destrieux atlas. We compared the thickness of the cerebral cortex, the volumes of subcortical structures, and the leakage rates of BBB, and evaluated the relationships between these parameters.

Results

Compared with HCs, the leakage rates of seven brain regions were higher in patients with advanced LC (aLC). In contrast to patients with early LC (eLC), the cortical thickness of two regions was decreased in aLCs. The volumes of twelve regions were also reduced in aLCs. Brain regions with increased BBB penetration showed negative correlations with thinner cortices and reduced subcortical structure volumes (P<0.05, R=-0.2 to -0.50). BBB penetration was positively correlated with tumor size and with levels of the tumor marker CYFRA21-1 (P<0.05, R=0.2–0.70).

Conclusion

We found an increase in BBB permeability in non-BM aLCs that corresponded to a thinner cortical thickness and smaller subcortical structure volumes. With progression in LC staging, BBB shows higher permeability and may be more likely to develop into BM.

The Indicative Value of Serum Tumor Markers for Metastasis and Stage of Non-Small Cell Lung Cancer

Objective: This study aimed to explore the roles of serum tumor markers for metastasis and stage of non-small cell lung cancer (NSCLC). Methods: This study recruited 3272 NSCLC patients admitted to the Tianjin Union Medical Center and the Tianjin Medical University Cancer Institute and Hospital. The predictive abilities of some serum tumor markers (carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC-Ag), cytokeratin-19 fragment (CYFRA 21-1), neuron-specific enolase (NSE), pro-gastrin-releasing peptide (ProGRP), total prostate-specific antigen (TPSA) and carbohydrate antigen 199 (CA199)) for NSCLC metastasis (intrapulmonary, lymphatic and distant metastasis) and clinical stage were analyzed. Results: Tumor markers exhibited different numerical and proportional distributions in NSCLC patients. Elevated CEA, CYFRA 21-1 and CA199 levels were indicative of tumor metastasis and stage. Increased CEA and CA199 provided an accurate prediction of intrapulmonary and distant metastasis with the area under the receiver operator characteristic curve (AUC) of 0.69 both (p < 0.001); Increased CEA, CYFRA 21-1 and CA199 provided an accurate prediction of lymphatic metastasis with the AUC of 0.62 (p < 0.001). Conclusion: Combined detection of serum tumor markers can indicate tumor metastasis and stage in NSCLC patients.

A machine learning-based diagnostic model for children with autism spectrum disorders complicated with intellectual disability

Background

Early detection of children with autism spectrum disorder (ASD) and comorbid intellectual disability (ID) can help in individualized intervention. Appropriate assessment and diagnostic tools are lacking in primary care. This study aims to explore the applicability of machine learning (ML) methods in diagnosing ASD comorbid ID compared with traditional regression models.

Method

From January 2017 to December 2021, 241 children with ASD, with an average age of 6.41 ± 1.96, diagnosed in the Developmental Behavior Department of the Children's Hospital Affiliated with the Medical College of Zhejiang University were included in the analysis. This study trained the traditional diagnostic models of Logistic regression (LR), Support Vector Machine (SVM), and two ensemble learning algorithms [Random Forest (RF) and XGBoost]. Socio-demographic and behavioral observation data were used to distinguish whether autistic children had combined ID. The hyperparameters adjustment uses grid search and 10-fold validation. The Boruta method is used to select variables. The model's performance was evaluated using discrimination, calibration, and decision curve analysis (DCA).

Result

Among 241 autistic children, 98 (40.66%) were ASD comorbid ID. The four diagnostic models can better distinguish whether autistic children are complicated with ID, and the accuracy of SVM is the highest (0.836); SVM and XGBoost have better accuracy (0.800, 0.838); LR has the best sensitivity (0.939), followed by SVM (0.952). Regarding specificity, SVM, RF, and XGBoost performed significantly higher than LR (0.355). The AUC of ML (SVM, 0.835 [95% CI: 0.747-0.944]; RF, 0.829 [95% CI: 0.738-0.920]; XGBoost, 0.845 [95% CI: 0.734-0.937]) is not different from traditional LR (0.858 [95% CI: 0.770-0.944]). Only SVM observed a good calibration degree. Regarding DCA, LR, and SVM have higher benefits in a wider threshold range.

Conclusion

Compared to the traditional regression model, ML model based on socio-demographic and behavioral observation data, especially SVM, has a better ability to distinguish whether autistic children are combined with ID.

A Population-Based Study on the Prognostic factors and Efficacy of Adjuvant Chemotherapy in the Postoperative Stage for Patients with Stage IIA Non-Small Cell Lung Cancer

Objective

This study aimed to design a nomogram survival prediction by means of the figures retrieved from the Surveillance, Epidemiology, and End Results (SEER) source bank, and to predict the overall survival (OS) of patients with stage IIA non-small cell lung cancer (NSCLC) after surgery.

Methods

Data for 4511 patients who had been diagnosed with postoperative stage IIA NSCLC were collected from the SEER databank, while information on 528 patients was acquired from the Chongqing University Cancer Hospital for the external validation cohort. The independent risk factors that affected the prognosis were identified using a multivariate Cox proportional hazards regression model (also used to conduct a nomogram). A survival analysis between the low- and the high-risk groups was performed using the Kaplan-Meier method. Furthermore, a subgroup analysis was conducted of the two groups using the Kaplan-Meier method to determine whether the patients had received adjuvant chemotherapy.

Results

The following five variables were integrated into the nomogram: sex (female: HR 1.73, 95% CI 0.64-0.83), age (≥60: HR 1.61, 95% CI 1.39-1.87), differentiation grade (grade II: HR 2.19, 95% CI 1.66-2.88; grade III: HR 2.65, 95% CI 2.00-3.51; grade IV: HR 3.17, 95% CI 1.99-5.03), surgery (lobectomy: HR 0.72, 95% CI 0.59-0.86), and lymph node resection (>12: HR 0.82, 95% CI 0.70-0.96). Furthermore, the patients selected were categorized into high- and low-risk groups. The OS rate was significantly lower in the high-risk group than in the low-risk group (P < 0.001). Finally, adjuvant chemotherapy was highly correlated with OS in the high-risk set (P = 0.035); however, adjuvant chemotherapy was not related to OS in the low-risk set.

Conclusion

A nomogram was created as a reliable, convenient scheme that could predict OS, and it was determined that the high-risk feature patients identified by the nomogram gained benefits from adjuvant chemotherapy.

Miniaturized microfluidic-based nucleic acid analyzer to identify new biomarkers of biopsy lung cancer samples for subtyping

Identifying new biomarkers is necessary and important to diagnose and treat malignant lung cancer. However, existing protein marker detection methods usually require complex operation steps, leading to a lag time for diagnosis. Herein, we developed a rapid, minimally invasive, and convenient nucleic acid biomarker recognition method, which enabled the combined specific detection of 11 lung cancer typing markers in a microliter reaction system after only one sampling. The primers for the combined specific detection of 11 lung cancer typing markers were designed and screened, and the microfluidic chip for parallel detection of the multiple markers was designed and developed. Furthermore, a miniaturized microfluidic-based analyzer was also constructed. By developing a microfluidic chip and a miniaturized nucleic acid analyzer, we enabled the detection of the mRNA expression levels of multiple biomarkers in rice-sized tissue samples. The miniaturized nucleic acid analyzer could detect ≥10 copies of nucleic acids. The cell volume of the typing reaction on the microfluidic chip was only 0.94 μL, less than 1/25 of that of the conventional 25-μL Eppendorf tube PCR method, which significantly reduced the testing cost and significantly simplified the analysis of multiple biomarkers in parallel. With a simple injection operation and reverse transcription loop-mediated isothermal amplification (RT-LAMP), real-time detection of 11 lung cancer nucleic acid biomarkers was performed within 45 min. Given these compelling features, 86 clinical samples were tested using the miniaturized nucleic acid analyzer and classified according to the cutoff values of the 11 biomarkers. Furthermore, multi-biomarker analysis was conducted by a machine learning model to classify different subtypes of lung cancer, with an average area under the curve (AUC) of 0.934. This method shows great potential for the identification of new nucleic acid biomarkers and the accurate diagnosis of lung cancer.

Based on clinical Ki-67 expression and serum infiltrating lymphocytes related nomogram for predicting the diagnosis of glioma-grading

Background

Compelling evidence indicates that elevated peripheral serum lymphocytes are associated with a favorable prognosis in various cancers. However, the association between serum lymphocytes and glioma is contradictory. In this study, a nomogram was established to predict the diagnosis of glioma-grading through Ki-67 expression and serum lymphocytes.

Methods

We performed a retrospective analysis of 239 patients diagnosed with LGG and 178 patients with HGG. Immunohistochemistry was used to determine the Ki-67 expression. Following multivariate logistic regression analysis, a nomogram was established and used to identify the most related factors associated with HGG. The consistency index (C-index), decision curve analysis (DCA), and a calibration curve were used to validate the model.

Results

The number of LGG patients with more IDH1/2 mutations and 1p19q co-deletion was greater than that of HGG patients. The multivariate logistic analysis identified Ki-67 expression, serum lymphocyte count, and serum albumin (ALU) as independent risk factors associated with HGG, and these factors were included in a nomogram in the training cohort. In the validation cohort, the nomogram demonstrated good calibration and high consistency (C-index = 0.794). The Spearman correlation analysis revealed a significant association between HGG and serum lymphocyte count (r = −0.238, P &lt;0.001), ALU (r = −0.232, P &lt;0.001), and Ki-67 expression (r = 0.457, P &lt;0.001). Furthermore, the Ki-67 expression was negatively correlated with the serum lymphocyte count (r = −0.244, P &lt;0.05). LGG patients had lower Ki-67 expression and higher serum lymphocytes compared with HGG patients, and a combination of these two variables was significantly higher in HGG patients.

Conclusion

The constructed nomogram is capable of predicting the diagnosis of glioma-grade. A decrease in the level of serum lymphocyte count and increased Ki-67 expression in HGG patients indicate that their immunological function is diminished and the tumor is more aggressive.

Exhaled Aldehydes as Biomarkers for Lung Diseases: A Narrative Review

Breath analysis provides great potential as a fast and non-invasive diagnostic tool for several diseases. Straight-chain aliphatic aldehydes were repeatedly detected in the breath of patients suffering from lung diseases using a variety of methods, such as mass spectrometry, ion mobility spectrometry, or electro-chemical sensors. Several studies found increased concentrations of exhaled aldehydes in patients suffering from lung cancer, inflammatory and infectious lung diseases, and mechanical lung injury. This article reviews the origin of exhaled straight-chain aliphatic aldehydes, available detection methods, and studies that found increased aldehyde exhalation in lung diseases.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

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

KLRK1 as a prognostic biomarker for lung adenocarcinoma cancer

Lung cancer is one of the most common malignancy worldwide and causes estimated 1.6 million deaths each year. Cancer immunosurveillance has been found to play an important role in lung cancer and may be related with its prognosis. KLRK1, encoding NKG2D, is a homodimeric lectin-like receptor. However, there has not been one research of KLRK1 as a biomarker in lung cancer. Data including patients` clinical characteristics and RNAseq information of KLRK1 from TCGA were downloaded. A total of 1019 patients with lung cancer were included in this study, among which 407 patients were female and 611 patients were male. Evaluations of mRNA expression, diagnostic value by ROC (receiver operating characteristic) curves and prognostic value by survival curve, Cox model and subgroup analysis were performed. The level of KLRK1 expression in lung adenocarcinoma cancer tissues and normal lung tissues was detected by qRT-PCR. The CCK-8 assay investigated the proliferation rate and the wound healing assay assessed the migratory ability in vitro. The expression of KLRK1 in tumor was lower than that in normal tissue. KLRK1 expression was associated with gender, histologic grade, stage, T classification and vital status. Patients with high KLRK1 expression presented an improved overall survival (P = 0.0036) and relapse free survival (P = 0.0031). KLRK1 was found to have significant prognostic value in lung adenocarcinoma (P = 0.015), stage I/II (P = 0.03), older patients (P = 0.0052), and male (P = 0.0047) by subgroup overall survival analysis, and in lung adenocarcinoma (P = 0.0094), stage I/II (P = 0.0076), older patients (P = 0.0072), and male (P = 0.0033) by subgroup relapse free survival analysis. Lung adenocarcinoma cancer patients with high KLRK1 expression presented an improved overall survival (P = 0.015) and relapse free survival (P = 0.0094). In vitro studies indicated that KLRK1 inhibited tumor cell proliferation and migration. KLRK1 was an independent prognostic factor and high KLRK1 expression indicated a better overall and relapse free survival. KLRK1 may be a prognostic biomarker for lung adenocarcinoma cancer.

A method establishment and comparison of in vivo lung cancer model development platforms for evaluation of tumour metabolism and pharmaceutical efficacy

BACKGROUND

Currently, the identification of accurate biomarkers for the diagnosis of patients with early-stage lung cancer remains difficult. Fortunately, metabolomics technology can be used to improve the detection of plasma metabolic biomarkers for lung cancer. In a previous study, we successfully utilised machine learning methods to identify significant metabolic markers for early-stage lung cancer diagnosis. However, a related research platform for the investigation of tumour metabolism and drug efficacy is still lacking.

HYPOTHESIS/PURPOSE

A novel methodology for the comprehensive evaluation of the internal tumour-metabolic profile and drug evaluation needs to be established.

METHODS

The optimal location for tumour cell inoculation was identified in mouse chest for the non-traumatic orthotopic lung cancer mouse model. Microcomputed tomography (micro-CT) was applied to monitor lung tumour growth. Proscillaridin A (P.A) and cisplatin (CDDP) were utilised to verify the anti-lung cancer efficacy of the platform. The top five clinically valid biomarkers, including proline, L-kynurenine, spermidine, taurine and palmitoyl-L-carnitine, were selected as the evaluation indices to obtain a suitable lung cancer mouse model for clinical metabolomics research by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS).

RESULTS

The platform was successfully established, achieving 100% tumour development rate and 0% surgery mortality. P.A and CDDP had significant anti-lung cancer efficacy in the platform. Compared with the control group, four biomarkers in the orthotopic model and two biomarkers in the metastatic model had significantly higher abundance. Principal component analysis (PCA) showed a significant separation between the orthotopic/metastatic model and the control/subcutaneous/KRAS transgenic model. The platform was mainly involved in arginine and proline metabolism, tryptophan metabolism, and taurine and hypotaurine metabolism.

CONCLUSION

This study is the first to simulate clinical metabolomics by comparing the metabolic phenotype of plasma in different lung cancer mouse models. We found that the orthotopic model was the most suitable for tumour metabolism. Furthermore, the anti-tumour drug efficacy was verified in the platform. The platform can very well match the clinical reality, providing better lung cancer diagnosis and securing more precise evidence for drug evaluation in the future.

Prognostic significance of postoperative longitudinal change of serum carcinoembryonic antigen level in patients with stage I lung adenocarcinoma completely resected by single-port video-assisted thoracic surgery: a retrospective study

Background

Patients with stage I lung adenocarcinoma (LUAD) have varying postoperative prognosis. This study aimed to investigate the prognostic significance of postoperative longitudinal change of serum carcinoembryonic antigen (CEA) level in patients with stage I LUAD.

Methods

The study cohort comprised 241 patients with stage I LUAD completely resected with single-port video-assisted thoracic surgery (VATS). The patients were categorized into 4 groups according to the postoperative longitudinal change of serum CEA levels measured in the third and sixth months after surgery: the NN group (continuously normal), HN group (increase first and then decrease), NH group (decrease first and then increase), and HH group (continuously high). Recurrence-free survival (RFS) was analyzed by the Kaplan-Meier method and compared by log-rank test. A nomogram was developed to predict recurrence in the stage I LUAD patients.

Results

In univariate analysis, differentiation (P<0.001), visceral pleural invasion (VPI) (P=0.025), tumor diameter (P<0.001), tumor-node-metastasis (TNM) stage (P=0.008), preoperative CEA levels (≥10.0 vs. <10.0 ng/mL, P<0.001), and postoperative CEA grouping (NH/HH vs. NN/HN, P<0.001) were significant prognostic factors for stage I LUAD patients. Multivariate analysis showed that tumor diameter (P=0.009) and postoperative CEA grouping (P<0.001) were considered to be independent prognostic factors of postoperative recurrence of stage I LUAD. Tumor diameter (≥20 mm) and postoperative CEA (NH/HH vs. NN/HN) were associated with worse RFS. Receiver operating characteristic (ROC) curve analysis showed that postoperative CEA (NH/HH vs. NN/HN) have high sensitivity (64.7%) and specificity (83.2%) for early prediction of postoperative recurrence of stage I LUAD. The area under curve (AUC) value was 0.745. The nomogram based on multivariate Cox regression had a concordance index (value of 0.789). The calibration plot showed that the predicted probabilities closely matched the observed probabilities.

Conclusions

Longitudinal change in serum CEA level after surgery was found to be an independent unfavorable prognostic factor in completely resected stage I LUAD patients. The NH group and HH group were significantly associated with worse RFS. A nomogram was established to predict the postoperative recurrence of patients with stage I LUAD.

The Ki-67 Proliferation Index-Related Nomogram to Predict the Response of First-Line Tyrosine Kinase Inhibitors or Chemotherapy in Non-small Cell Lung Cancer Patients With Epidermal Growth Factor Receptor-Mutant Status

Background: The correlation between Ki-67 and epidermal growth factor receptor (EGFR)- or Kristen rat sarcoma viral oncogene homolog (KRAS)-mutant status in advanced or postoperative-recurrent non-small cell lung cancer (NSCLC) has fewer studies reported, and the prognostic role of Ki-67 with first-line EGFR-tyrosine kinase inhibitors (TKIs) or chemotherapy remains controversial. Methods: A total of 295 patients were tested for EGFR-mutant status in advanced or postoperative-recurrent NSCLC and received first-line EGFR-TKIs or chemotherapy for treatment. Ki-67 expression was retrospectively analyzed by immunohistochemistry. The Kaplan-Meier method was used to calculate survival rates. The multivariate Cox proportional hazards model was used to generate a nomogram. The established nomogram was validated using the calibration plots. Results: The expression levels of Ki-67 were divided into low (<60%, n = 186) and high (≥60%, n = 109) groups, based on the receiver operating characteristic curve. The expression levels of Ki-67 were found to be higher in patients with KRAS mutations when compared to KRAS wildtype, and EGFR wildtype was higher than EGFR mutations. The median overall survival (OS) of the low Ki-67 expression group was significantly longer than that of the high Ki-67 group, no matter in all NSCLC, EGFR mutations, EGFR wildtype, KRAS-mutant status, EGFR-TKIs, or chemotherapy of patients (P < 0.05). Subgroup analysis showed that the KRAS wildtype or EGFR mutations combine with low Ki-67 expression group had the longest median OS than KRAS mutations or EGFR wildtype combine with Ki-67 high expression group (P < 0.05). In the training cohort, the multivariate Cox analysis identified age, serum lactate dehydrogenase (LDH), serum Cyfra211, EGFR mutations, and Ki-67 as independent prognostic factors, and a nomogram was developed based on these covariates. The calibration curve for predicting the 12-, 24-, and 30-month OS showed an optimal agreement between the predicted and actual observed outcomes. Conclusions: The Ki-67 expression-based nomogram can well predict the efficacy of first-line therapy in NSCLC patients with EGFR- or KRAS-mutant status, high expression levels of Ki-67 correlated with a poor prognosis.

In Situ Formation of Au-Glycopolymer Nanoparticles for Surface-Enhanced Raman Scattering-Based Biosensing and Single-Cell Immunity

Successful synthesis of glyconanoparticles has attracted much attention due to their various biointeractive capabilities, but it is still a challenge to understand different single-cell responses to exogenous particles among cell populations. Herein, we designed polyaniline-containing galactosylated gold nanoparticles (Au@PGlyco NPs) via in situ polymerization of ortho-nitrophenyl-β-galactoside assisted by Au nucleation. The nanogold-carrying polyaniline block produced electromagnetic enhancement in surface-enhanced Raman scattering (SERS). The underlying polymerization mechanism of ortho-nitrophenyl compounds via the formation of Au nanoparticles was investigated. Depending on how the galactoside moiety reacted with β-galactosidase derived from bacteria, the Au@PGlyco NPs-mediated SERS biosensor could detect low amounts of bacteria (∼1 × 102 CFU/mL). In addition, a high accumulation of Au@PGlyco NPs mediated the immune response of tumor-associated M2 macrophages to the immunogenic M1 macrophage transition, which was elicited by reactive oxygen levels biostimulation using single-cell SERS-combined fluorescence imaging. Our study suggested that Au@PGlyco NPs may serve as a biosensing platform with the labeling capacity on galactose-binding receptors expressed cell and immune regulation.

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.

Identification of a novel DNA aptamer that selectively targets lung cancer serum

Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment is critical to improving the 5 year survival rate of lung cancer. The identification of new options for early-stage diagnosis and therapy of lung cancer still represents a crucial challenge. Therefore, a new diagnostic method is urgently needed. In this study, we used a new modified SELEX, called serum-SELEX, to isolate aptamers that can specifically bind lung cancer serum, without any prior knowledge of their target. Among the obtained candidate aptamer sequences, Ap-LC-19 was identified as the optimal aptamer probe with the lowest dissociation constant (K d) value of 15 ± 8.6 nM and higher affinity assessed by qPCR. Furthermore, this molecule could be a suitable aptamer for lung cancer serum and could be used as a recognition element in aptamer-based biosensors for efficient early diagnosis of lung cancer or as an innovative tool for targeted therapy. In addition, we performed MALDI-TOF MS followed by secondary peptide sequencing MS analysis for the identification of the aptamer targeted proteins. CLEC3B could be useful biomarkers for early detection of lung cancer and in monitoring its evolution.

High CTSL2 expression predicts poor prognosis in patients with lung adenocarcinoma

Cathepsin like 2 (CTSL2) is a lysosomal cysteine protease, and may be associated with tumor metastasis. However, CTSL2 has not been reported as a biomarker in lung adenocarcinoma (LUAD). In this study, bioinformatics analysis using data from The Cancer Genome Atlas was performed. Wilcoxon rank-sum test and chi-square test were carried out. Kaplan-Meier and Cox regression were performed to evaluate the effect of CTSL2 expression in the overall survival. Our results indicated that CTSL2 in tumor was significantly higher than that in normal tissue (P < 0.001). High CTSL2 expression was significantly associated with age (P = 0.02), vital status (P < 0.001), and T classification (P = 0.03), and correlated with poor overall survival (HR = 1.62, 95% CI = 1.21–2.18, P = 0.001). CTSL2 expression was an independent risk factor for overall survival in patients with LUAD (HR = 1.52, 95% CI = 1.12–2.05, P = 0.006). A nomogram was plotted for illustration of CTSL2 expression on the risk of LUAD. Furthermore, in vitro cell experiments showed the CTSL2 promoted the proliferation and migration of A549 cells. In summary, high CTSL2 expression predicts poor prognosis in patients with LUAD.

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

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

Malignancy Prediction Capacity and Possible Prediction Model of Circulating Tumor Cells for Suspicious Pulmonary Lesions

More and more undetermined lung lesions are being identified in routine lung cancer screening. The aim of this study was to try to establish a malignancy prediction model according to the tumor presentations. From January 2017 to December 2018, 50 consecutive patients who were identified with suspicious lung lesions were enrolled into this study. Medical records were reviewed and tumor macroscopic and microscopic presentations were collected for analysis. Circulating tumor cells (CTC) were found to differ between benign and malignant lesions (p = 0.03) and also constituted the highest area under the receiver operation curve other than tumor presentations (p = 0.001). Since tumor size showed the highest sensitivity and CTC revealed the best specificity, a malignancy prediction model was proposed. Akaike information criterion (A.I.C.) of the combined malignancy prediction model was 26.73, which was lower than for tumor size or CTCs alone. Logistic regression revealed that the combined malignancy prediction model showed marginal statistical trends (p = 0.0518). In addition, the 95% confidence interval of combined malignancy prediction model showed less wide range than tumor size ≥ 0.7 cm alone. The calculated probability of malignancy in patients with tumor size ≥ 0.7 cm and CTC > 3 was 97.9%. By contrast, the probability of malignancy in patients whose tumor size was < 0.7 cm, and CTC ≤ 3 was 22.5%. A combined malignancy prediction model involving tumor size followed by the CTC count may provide additional information to assist decision making. For patients who present with tumor size ≥ 0.7 cm and CTC counts > 3, aggressive management should be considered, since the calculated probability of malignancy was 97.9%.

Age-stratified and gender-specific reference intervals of six tumor markers panel of lung cancer: A geographic-based multicenter study in China

Background

Serum biomarkers have been widely adopted in clinical practice for assisting lung cancer diagnoses, therapeutic monitoring, and prognostication. The function of a well‐performing tumor biomarker depends on a reliable reference interval (RI) with consideration of the study subjects’ age, gender, and geographical location. This study aimed to establish a RI for each of 6 lung cancer biomarkers for use in the whole country of China on Mindray platform.

Methods

The levels of serum 6 lung cancer biomarkers—namely progastrin‐releasing peptide (ProGRP), neuron‐specific enolase (NSE), squamous cell carcinoma antigen (SCC), carcinoembryonic antigen (CEA), cytokeratin‐19 fragment (CYFRA21‐1), and human epididymis protein 4 (HE4)—were measured utilizing the chemiluminescence immunoassay on the Mindray CL‐6000i platform following the laboratory standard operating procedures in apparently healthy Chinese individuals on large cohort, multicenter, and geographical consideration bases. The CLSI EP28‐A3C guideline was followed for the enrollment of study subjects.

Results

The age‐stratified, gender‐specific RIs for ProGRP, NSE, SCC, CEA, CYFRA21‐1, and HE4 lung cancer biomarkers in the Chinese population have been established as described in the results and discussion in this work. In addition, various levels of the six lung cancer biomarkers among nine geographical locations in China have been observed.

Conclusions

The sample volume of study cohort, age, and geographical location should be considered upon establishing a reliable biomarker RI. A RI for each of six lung cancer biomarkers has been established. The results from this study would be helpful for clinical laboratories in interpreting the analytical results and for clinicians in patient management.

Application of circulating genetically abnormal cells in the diagnosis of early-stage lung cancer

PURPOSE

Lung cancer is the leading cause of cancer-related death worldwide. The early detection of lung cancer is crucial for the diagnosis of this disease. Therefore, an effective and noninvasive method for the early diagnosis of lung cancer is urgently needed.

METHODS

To evaluate the diagnostic performance of circulating genetically abnormal cells (CACs) in early lung cancer, a total of 63 participants who completed CAC detection by Zhuhai SanMed Biotech Inc. and obtained pathological results from January to December 2020 were included in our study; 50 patients had lung cancer and 13 patients had benign lung disease. The levels of lung cancer-related markers in peripheral blood and the chest computed tomography (CT) imaging characteristics of these patients were collected before pathological acquisition.

RESULTS

The positive rate of CAC was 90.0% in the lung cancer group and 23.1% in the benign lung disease group, and the difference was statistically significant (P < 0.01). The area under the receiver operating characteristic (ROC) curve of CAC was 0.837, the sensitivity was 90%, and the specificity was 76.9%. The area under the ROC curve and sensitivity were both higher than those of the combined or single serum tumor marker test.

CONCLUSIONS

This study preliminarily concludes that the CAC test, as a noninvasive test, has high sensitivity and specificity for the early diagnosis of lung cancer. This test is expected to help with the early detection of disease in lung cancer patients.

A circular network of coregulated sphingolipids dictates lung cancer growth and progression

Background

Sphingolipid metabolism is among the top dysregulated pathways in non-small cell lung carcinomas (NSCLC). However, the molecular control of sphingolipid metabolic reprogramming in cancer progression remains unclear.

Methods

We first determined the correlation between sphingolipid metabolic gene expression and patient prognosis. We then carried out sphingolipidomics analysis of health individual and NSCLC patient sera as well as B3GNT5 and GAL3ST1 genetically perturbed NSCLC cell lines. We used these cell lines to perform tumorigenesis study to determine the cellular role of B3GNT5 and GAL3ST1 in cancer growth and progression.

Findings

The expression of B3GNT5 and GAL3ST1 among sphingolipid metabolic enzymes is most significantly associated with patient prognosis, whilst sphingolipidomics analysis of healthy individual and NSCLC patient sera identifies their metabolites, lacto/neolacto-series glycosphingolipid and sulfatide species, as potential biomarkers that were more effective than current clinical biomarkers for staging patients. Further network analysis of the sphingolipidomes reveals a circular network of coregulated sphingolipids, indicating that the lacto/neolacto-series glycosphingolipid/sulfatide balance functions as a checkpoint to determine sphingolipid metabolic reprograming during patient progression. Sphingolipidomics analysis of B3GNT5/GAL3ST1 genetically perturbed NSCLC cell lines confirms their key regulatory role in sphingolipid metabolism, while B3GNT5 and GAL3ST1 expression has an opposite role on tumorigenesis.

Interpretation

Our results provide new insights whereby B3GNT5 and GAL3ST1 differentially regulate sphingolipid metabolism in lung cancer growth and progression.

Funding

This work was supported by the Natural Science Foundation of China (81872142, 81920108028); Guangzhou Science and Technology Program (201904020008); Guangdong Science and Technology Department (2020A0505100029, 2019A1515011802, 2020A1515011280, 2020B1212060018, 2020B1212030004); China Postdoctoral Science Foundation (2019M650226, 2019M650227).

Dielectrophoresis assisted high-throughput detection system for multiplexed immunoassays

Digital ELISA is introduced as a novel platform with unique advantages for detecting multiple kinds of single-molecule in the sample. How to improve the sensitivity of detection is the direction of current related research. Here, we report an immunoassay method that applied electrokinetic effects to isolate the individual encoded beads and confine in micro-wells to improve the efficiency of cytokines detection simultaneously. The microfluidic design provided a non-uniform electric field to induce dielectrophoresis (DEP) force and to manipulate the beads. Two wavelengths of excitation light excited the encoded beads for simultaneous detection of reporters. The light was confined to the bottom slide via the principle of total internal reflection. Finally, the concentration of captured cytokines was obtained by picking up each bead from the image and then integrating the intensity of fluorescent light emitted from the reporters. The results demonstrated that the fill percentage of encoded beads was raised from 10-20% to 60-80% via DEP effect. By comparing the fluorescence color of the particle, itself and its surface, the concentration of four target cytokines, IL-2, IL-6, IL-10 and TNF-α, were calculated to the pg/ml level. The spike and recovery experiments verified the efficiency, more than 70% of the target molecules were captured. The reliability of our method was verified by flow cytometry as well. In conclusion, we expect the application of DEP can increase the sensitivity of digital ELISA for multiple rapid detection.

Combined assay of Circulating Tumor DNA and Protein Biomarkers for early noninvasive detection and prognosis of Non-Small Cell Lung Cancer

Purpose: Early diagnosis of lung cancer is critical to curtailing cancer-related deaths. We aimed to develop a highly sensitive assay for the analysis of circulating tumor DNA (ctDNA) to detect non-small cell lung cancer (NSCLC) in the early stages. Materials and Methods: We detected EGFR and KRAS mutations in paired plasma and tumor tissue samples from 147 NSCLC patients. Of these, EGFR/KRAS ctDNA mutations and protein biomarkers were comparatively analyzed in 87 individuals. In addition, tissue samples of 20 patients were subjected to repeat multi-gene detection, and pre- and post-operative paired samples of 28 patients were subjected to multi-gene detection. Clinical information was obtained to complement the prognostic value of the combined assay results and post-operative new ctDNA mutation status. Results: EGFR/KRAS mutations were highly consistent in ctDNA and tumor DNA. Combining the detection of EGFR and KRAS mutations in ctDNA with the detection of protein biomarkers increased cancer detection sensitivity to 74.7% (65/87). None of the healthy controls tested positive using the combined assay (100% specificity). Combined assay results independently associated with recurrence-free survival. Post-operative new ctDNA mutation status independently associated with overall survival and recurrence-free survival. Conclusion: The detection of ctDNA may be exploited for early diagnosis of NSCLC, as highlighted by the developed assay. Further, the combined assay results and post-operative new ctDNA mutation status are promising prognostic indicators in NSCLC patients.

Development and Validation of a Novel Nomogram for Predicting Tumor-Distant-Metastasis in Patients with Early T1-2 Stage Lung Adenocarcinoma

Background

Distant metastasis in early T1-2 (diameter≤5 cm) stage lung adenocarcinoma (ET-LUAD) patients largely affect treatment strategies in clinical practice. However, the associated mechanism remains unclear and related studies is less. This study aimed to establish and validate a novel nomogram to predict the risk of distant metastasis in ET-LUAD.

Methods

A total of 258 patients diagnosed with ET-LUAD and not receiving any treatment were recruited into this study. The patients were randomly divided into a training cohort and validation cohort in a ratio of 1:2. Univariate and multivariate logistic regression analysis was used to select the most significant predictive risk factors associated with distant metastasis in the training cohort. The established nomogram was validated by the consistency index (C-index), calibration curve, and decision curve analysis (DCA).

Results

There were 124 patients with confirmed distant metastasis and 134 patients with non-distant metastases ET-LUAD were enrolled in the study. Multivariate logistic hazards regression analysis identified independent risk factors associated with distant metastasis to include platelet-to-lymphocyte ratios (PLR), lactate dehydrogenase (LDH), neural-specific enolase (NSE), carcinoembryonic antigen (CEA) and cytokeratin 19 fragments (Cyfra211), which were included in the establishment of the nomogram. The nomogram achieved a high consistency (C-index=0.792), good calibration, and high clinical application value in the validation cohort.

Conclusion

The established nomogram can be used to predict distant metastasis in high-risk ET-LUAD nonmetastasis patients and can also be used by doctors to guide preventive and individualized treatment for ET-LUAD patients.

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis

Background

Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square (χ²) tests.

Results

As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all P values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels (P value < 0.05). The performance was similar even when analyzed individually by LC subtypes.

Conclusion

The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy.

STK1p as a prognostic biomarker for overall survival in non-small-cell lung carcinoma, based on real-world data

Aim:

A prospective investigation of serum thymidine kinase 1 concentration (STK1p) was performed to evaluate its prognostic value in patients with non-small-cell lung carcinoma (NSCLCs).

Patients & methods:

The STK1p values of 127 patients were determined by an enhanced chemiluminescent dot blot assay. The patients were recruited from March 2011 to December 2017.

Results:

Kaplan–Meier plot showed that patients with elevated STK1p values had worse overall survival (OS), especially patients of early/middle stages. Multi-variable COX regression showed that STK1p value and combined treatment surgery + chemotherapy were independent prognostic factors for favorable OS.

Conclusion:

STK1p is helpful in predicting OS of early/middle stages (I–IIIA) NSCLCs patients following a nonrandomized individual adapted treatment, but is may be not recommended in advanced stages (IIIB + IV) of NSCLCs.

Lung cancer is one of the most common types of tumors, with a high mortality rate. We investigate if thymidine kinase 1 in serum (STK1p) is a reliable prognostic marker for survival in non-small-cell lung carcinoma. We recruited 127 patients in this study. STK1p level was determined using a high-sensitive chemiluminescent dot blot assay. Patients with elevated STK1p values had worse overall survival, especially patients in the early/middle cancer stages. Analysis showed that STK1p is an independent prognostic factors for overall survival. We concluded that STK1p is helpful predicting the efficacy of treatment in non-small-cell lung carcinoma for those in the early/middle stages.