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

Recent advances and future challenges in the diagnosis of neuroendocrine neoplasms

Neuroendocrine neoplasms (NEN) are a heterogeneous group of malignancies with increasing incidence, whose diagnosis is usually delayed, negatively impacting on patients' prognosis. The latest advances in pathological classifications, biomarker identification and imaging techniques may provide early detection, leading to personalized treatment strategies. In this narrative review the recent developments in diagnosis of NEN are discussed including progresses in pathological classifications, biomarker and imaging. Furthermore, the challenges that lie ahead are investigated. By discussing the limitations of current approaches and addressing potential roadblocks, we hope to guide future research directions in this field. This article is proposed as a valuable resource for clinicians and researchers involved in the management of NEN. Update of pathological classifications and the availability of standardized templates in pathology and radiology represent a substantially improvement in diagnosis and communication among clinicians. Additional immunohistochemistry markers may now enrich pathological classifications, as well as miRNA profiling. New and multi-analytical circulating biomarkers, as liquid biopsy and NETest, are being proposed for diagnosis but their validation and availability should be improved. Radiological imaging strives for precise, non-invasive and less harmful technique to improve safety and quality of life in NEN patient. Nuclear medicine may benefit of somatostatin receptors' antagonists and membrane receptor analogues. Diagnosis in NEN still represents a challenge due to their complex biology and variable presentation. Further advancements are necessary to obtain early and minimally invasive diagnosis to improve patients' outcomes.

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.

Combined use of CYFRA 21-1 and CA 125 predicts survival of patients with metastatic NSCLC and stable disease in IMpower150

BACKGROUND

Patients with non-small cell lung cancer (NSCLC) and stable disease (SD) have an unmet clinical need to help guide early treatment adjustments.

OBJECTIVE

To evaluate the potential of tumor biomarkers to inform on survival outcomes in NSCLC SD patients.

METHODS

This post hoc analysis included 480 patients from the IMpower150 study with metastatic NSCLC, treated with chemotherapy, atezolizumab and bevacizumab combinations, who had SD at first CT scan (post-treatment initiation). Patients were stratified into high- and low-risk groups (overall survival [OS] and progression-free survival [PFS] outcomes) based on serum tumor biomarker levels.

RESULTS

The CYFRA 21-1 and CA 125 biomarker combination predicted OS and PFS in patients with SD. Risk of death was ~4-fold higher for the biomarker-stratified high-risk versus low-risk SD patients (hazard ratio [HR] 3.80; 95% confidence interval [CI] 3.02-4.78; p < 0.0001). OS in patients with the low- and high-risk SD was comparable to that in patients with the CT-defined partial response (PR; HR 1.10; 95% CI 0.898-1.34) and progressive disease (PD) (HR 1.05; 95% CI 0.621-1.77), respectively. The findings were similar with PFS, and consistent across treatment arms.

CONCLUSIONS

Biomarker testing shows potential for providing prognostic information to help direct treatment in NSCLC patients with SD. Prospective clinical studies are warranted.ClinicalTrials.gov: NCT02366143.

Clinical perspectives on serum tumor marker use in predicting prognosis and treatment response in advanced non-small cell lung cancer

The optimal positioning and usage of serum tumor markers (STMs) in advanced non-small cell lung cancer (NSCLC) care is still unclear. This review aimed to provide an overview of the potential use and value of STMs in routine advanced NSCLC care for the prediction of prognosis and treatment response. Radiological imaging and clinical symptoms have shown not to capture a patient's entire disease status in daily clinical practice. Since STM measurements allow for a rapid, minimally invasive, and safe evaluation of the patient's tumor status in real time, STMs can be used as companion decision-making support tools before start and during treatment. To overcome the limited sensitivity and specificity associated with the use of STMs, tests should only be applied in specific subgroups of patients and different test characteristics should be defined per clinical context in order to answer different clinical questions. The same approach can similarly be relevant when developing clinical applications for other (circulating) biomarkers. Future research should focus on the approaches described in this review to achieve STM test implementation in advanced NSCLC care.

Improvement of differential diagnosis of lung cancer by use of multiple protein tumor marker combinations

BACKGROUND

Differential diagnosis of non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) in hospitalized patients is crucial for appropriate treatment choice.

OBJECTIVE

To investigate the relevance of serum tumor markers (STMs) and their combinations for the differentiation of NSCLC and SCLC subtypes.

METHODS

Between 2000 and 2003, 10 established STMs were assessed retrospectively in 311 patients with NSCLC, 128 with SCLC prior systemic first-line therapy and 51 controls with benign lung diseases (BLD), by automatized electrochemiluminescence immunoassay technology. Receiver operating characteristic (ROC) curves and logistic regression analyses were used to evaluate the diagnostic efficacy of both individual and multiple STMs with corresponding sensitivities at 90% specificity. Standards for Reporting of Diagnostic Accuracy (STARD guidelines) were followed.

RESULTS

CYFRA 21-1 (cytokeratin-19 fragment), CEA (carcinoembryonic antigen) and NSE (neuron specific enolase) were significantly higher in all lung cancers vs BLD, reaching AUCs of 0.81 (95% CI 0.76-0.87), 0.78 (0.73-0.84), and 0.88 (0.84-0.93), respectively. By the three marker combination, the discrimination between benign and all malignant cases was improved resulting in an AUC of 0.93 (95% CI 0.90-0.96). In NSCLC vs. BLD, CYFRA 21-1, CEA and NSE were best discriminative STMs, with AUCs of 0.86 (95% CI 0.81-0.91), 0.80 (0.74-0.85), and 0.85 (0.79-0.91). The three marker combination also improved the AUC: 0.92; 95% CI 0.89-0.96). In SCLC vs. BLD, ProGRP (pro-gastrin-releasing peptide) and NSE were best discriminative STMs, with AUCs of 0.89 (95% CI 0.84-0.94) and 0.96 (0.93-0.98), respectively, and slightly improved AUC of 0.97 (95% CI 0.95-0.99) when in combination. Finally, discrimination between SCLC and NSCLC was possible by ProGRP (AUC 0.86; 95% CI 0.81-0.91), NSE (AUC 0.83; 0.78-0.88) and CYFRA 21-1 (AUC 0.69; 0.64-0.75) and by the combination of the 3 STMs (AUC 0.93; 0.91-0.96), with a sensitivity of 88% at 90% specificity.

CONCLUSIONS

The results confirm the power of STM combinations for the differential diagnosis of lung cancer from benign lesions and between histological lung cancer subtypes.

An Overview of Circulating Biomarkers in Neuroendocrine Neoplasms: A Clinical Guide

Neuroendocrine neoplasms (NENs) are a heterogeneous group of diseases that are characterized by different behavior and clinical manifestations. The diagnosis and management of this group of tumors are challenging due to tumor complexity and lack of precise and widely validated biomarkers. Indeed, the current circulating mono-analyte biomarkers (such as chromogranin A) are ineffective in describing such complex tumors due to their poor sensitivity and specificity. In contrast, multi-analytical circulating biomarkers (including NETest) are emerging as more effective tools to determine the real-time profile of the disease, both in terms of accurate diagnosis and effective treatment. In this review, we will analyze the capabilities and limitations of different circulating biomarkers focusing on three relevant questions: (1) accurate and early diagnosis; (2) monitoring of disease progression and response to therapy; and (3) detection of early relapse.

Pro-Gastrin-Releasing Peptide as a Biomarker in Lung Neuroendocrine Neoplasm

There is a lack of effective biomarkers for diagnosing lung neuroendocrine neoplasms (LNENs). A known small cell lung cancer (SCLC) biomarker is a pro-gastrin-releasing peptide (ProGRP), but not for all LNENs, especially for bronchopulmonary carcinoids. This study aimed to evaluate the diagnostic value of ProGRP and chromogranin A (CgA) in diagnosing LNENs. The ProGRP and CgA levels in 290 cases of LNENs and 54 healthy controls (HCs) were measured. The median ProGRP concentration in the group of LNEN patients was 136.4 pg/mL, higher than that of HCs at 6.5 pg/mL. Most of the LNEN cohort was well-differentiated tumors (typical and atypical carcinoids, n = 262, 91.7% of all LNENs). The sensitivity, specificity, and area under the curve (AUC) of ProGRP when distinguishing LNENs vs. HCs were 94.8%, 100%, and 0.995. CgA (AUC = 0.375) could not determine LNENs vs. HCs. Therefore, based on these results, ProGRP may be considered as an effective marker for diagnosing LNENs.

A nomogram combining thoracic CT and tumor markers to predict the malignant grade of pulmonary nodules ≤3 cm in diameter

Background

With the popularity of computed tomography (CT) of the thorax, the rate of diagnosis for patients with early-stage lung cancer has increased. However, distinguishing high-risk pulmonary nodules (HRPNs) from low-risk pulmonary nodules (LRPNs) before surgery remains challenging.

Methods

A retrospective analysis was performed on 1064 patients with pulmonary nodules (PNs) admitted to the Qilu Hospital of Shandong University from April to December 2021. Randomization of all eligible patients to either the training or validation cohort was performed in a 3:1 ratio. Eighty-three PNs patients who visited Qianfoshan Hospital in the Shandong Province from January through April of 2022 were included as an external validation. Univariable and multivariable logistic regression (forward stepwise regression) were used to identify independent risk factors, and a predictive model and dynamic web nomogram were constructed by integrating these risk factors.

Results

A total of 895 patients were included, with an incidence of HRPNs of 47.3% (423/895). Logistic regression analysis identified four independent risk factors: the size, consolidation tumor ratio, CT value of PNs, and carcinoembryonic antigen levels in blood. The area under the ROC curves was 0.895, 0.936, and 0.812 for the training, internal validation, and external validation cohorts, respectively. The Hosmer-Lemeshow test demonstrated excellent calibration capability, and the fit of the calibration curve was good. DCA has shown the nomogram to be clinically useful.

Conclusion

The nomogram performed well in predicting the likelihood of HRPNs. In addition, it identified HRPNs in patients with PNs, achieved accurate treatment with HRPNs, and is expected to promote their rapid recovery.

Precise prediction of the sensitivity of platinum chemotherapy in SCLC: Establishing and verifying the feasibility of a CT-based radiomics nomogram

Objectives

To develop and validate a CT-based radiomics nomogram that can provide individualized pretreatment prediction of the response to platinum treatment in small cell lung cancer (SCLC).

Materials

A total of 134 SCLC patients who were treated with platinum as a first-line therapy were eligible for this study, including 51 patients with platinum resistance (PR) and 83 patients with platinum sensitivity (PS). The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were applied for feature selection and model construction. The selected texture features were calculated to obtain the radiomics score (Rad-score), and the predictive nomogram model was composed of the Rad-score and the clinical features selected by multivariate analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to assess the performance of the nomogram.

Results

The Rad-score was calculated using 10 radiomic features, and the resulting radiomics signature demonstrated good discrimination in both the training set (area under the curve [AUC], 0.727; 95% confidence interval [CI], 0.627–0.809) and the validation set (AUC, 0.723; 95% CI, 0.562–0.799). To improve diagnostic effectiveness, the Rad-score created a novel prediction nomogram by combining CA125 and CA72-4. The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.900; 95% CI, 0.844-0.947) and the validation set (AUC, 0.838; 95% CI, 0.534-0.735). The radiomics nomogram proved to be clinically beneficial based on decision curve analysis.

Conclusion

We developed and validated a radiomics nomogram model for predicting the response to platinum in SCLC patients. The outcomes of this model can provide useful suggestions for the development of tailored and customized second-line chemotherapy regimens.

Detection of Changes in CEA and ProGRP Levels in BALF of Patients with Peripheral Lung Cancer and the Relationship with CT Signs

Objective

To investigate the relationship between the detection of changes in the levels of carcinoembryonic antigen (CEA) and progastrin-releasing peptide (ProGRP) in bronchoalveolar lavage fluid (BALF) and CT signs in patients with peripheral lung cancer.

Methods

Retrospective analysis of 108 patients with perihilar lung cancer who attended our hospital from January 2019 to January 2022, 54 cases were randomly selected as the observation group and 50 cases as the control group. Patients in both groups received CT examination and BALF test at the same time to observe and compare the differences in serum levels, the relationship between CT signs and serum indices, and the diagnostic value of peripheral lung cancer between the two groups.

Results

The serum levels of ProGrp, CEA, CA211, and NSE in the observation group were significantly higher than those in the control group, and the difference was statistically significant (P < 0.05). The morphology, density, mass enhancement pattern, bronchial morphology, obstructive signs, and lymph node fusion of CT signs were compared between the observation group and the control group, indicating that CT signs were more helpful for the localization, diagnosis, and staging of lung cancer. The results of ROC curve analysis showed that the AUC value of low-dose CT combined with serum ProGrp, CEA, CA211, and NSE was 0.892, sensitivity was 96.21%, and specificity of 90.05%, which were significantly higher than those of the single tests, respectively. The positive likelihood ratio was 84.41% and the negative likelihood ratio was 87.11%.

Conclusion

The combination of CT signs and serum tumour markers helps to improve the detection rate, sensitivity, and specificity of lung cancer, which has a high diagnostic rate for lung cancer and may provide evidence for the early diagnosis of lung cancer.

Pulmonary carcinoid tumour with remarkably high levels of pro-gastrin-releasing peptide: A case report

An 86-year-old woman presented with chronic cough and chest pain. Computed tomography revealed two masses in the right lower lobe of the lung accompanied by multiple lymphadenopathies and metastasis to the rib. The pro-gastrin-releasing peptide (ProGRP) levels were notably elevated (888 pg/mL). Based on these findings, our initial clinical diagnosis was small-cell lung cancer. However, the pathological diagnosis turned out to be an atypical carcinoid. The patient was finally treated with everolimus. Clinicians should be aware that carcinoid tumours are sometimes difficult to distinguish from small-cell lung cancer with respect to high ProGRP levels and multiple metastases.

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.

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.

Clinicopathological characteristics of IgG4-related lung disease

Background

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

Methods

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

Results

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

Conclusions

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

Comprehensive in Vitro Characterization of the LSD1 Small Molecule Inhibitor Class in Oncology

Lysine-specific demethylase 1 (LSD1 or KDM1A) is a chromatin modifying enzyme playing a key role in the cell cycle and cell differentiation and proliferation through the demethylation of histones and nonhistone substrates. In addition to its enzymatic activity, LSD1 plays a fundamental scaffolding role as part of transcription silencing complexes such as rest co-repressor (CoREST) and nucleosome remodeling and deacetylase (NuRD). A host of classical amine oxidase inhibitors such as tranylcypromine, pargyline, and phenelzine together with LSD1 tool compounds such as SP-2509 and GSK-LSD1 have been extensively utilized in LSD1 mechanistic cancer studies. Additionally, several optimized new chemical entities have reached clinical trials in oncology such as ORY-1001 (iadademstat), GSK2879552, SP-2577 (seclidemstat), IMG-7289 (bomedemstat), INCB059872, and CC-90011 (pulrodemstat). Despite this, no single study exists that characterizes them all under the same experimental conditions, preventing a clear interpretation of published results. Herein, we characterize the whole LSD1 small molecule compound class as inhibitors of LSD1 catalytic activity, disruptors of SNAIL/GFI1 (SNAG)-scaffolding protein-protein interactions, inducers of cell differentiation, and potential anticancer treatments for hematological and solid tumors to yield an updated, unified perspective of this field. Our results highlight significant differences in potency and selectivity among the clinical compounds with iadademstat being the most potent and reveal that most of the tool compounds have very low activity and selectivity, suggesting some conclusions derived from their use should be taken with caution.

Circulating progastrin-releasing peptide in the diagnosis of Small Cell Lung Cancer (SCLC) and in therapeutic monitoring

Introduction:

Progastrin-releasing peptide (proGRP), a precursor of GRP, has been recently reported as a putative circulating biomarker for differential diagnosis between non–small cell lung cancer (NSCLC) and SCLC. We evaluated the diagnostic effectiveness of proGRP to differentiate patients with NSCLC and SCLC and the usefulness of combined measurement of proGRP and neuron-specific enolase (NSE) for diagnosing SCLC.

Methods:

Serum proGRP, NSE, cytokeratin 19 fragment 21-1 (CYFRA 21.1), squamous cell carcinoma antigen (SCC Ag) and carcinoembryonic antigen (CEA) were prospectively collected and measured in patients with a new diagnosis of lung cancer. Serum proGRP was also measured in healthy subjects. The serum proGRP, NSE, CYFRA 21.1 and CEA concentrations were determined by an electrochemiluminescence immunoassay and the serum SCC Ag concentration was determined by an automated immunofluorescence assay. Differences between proGRP and NSE in patients with SCLC and NSCLC were evaluated and compared using Mann-Whitney test.

Results:

A total of 77 patients affected by SCLC (n = 17) and NSCLC (n = 60) were enrolled in the present study. Moreover, 50 cases of healthy subjects were analyzed for proGRP. SCLC patients showed a significantly higher proGRP (1,484 pg/mL; range 168-3,777) levels compared to NSCLC patients (45 pg/mL; range 31.7-60.6), p<0.0001. In healthy subjects the median proGRP level was 36.1 (28.8-43.5) pg/mL, significantly lower than SCLC patients. ProGRP showed a higher specificity when compared to NSE, with a difference in proportion of 47.5% (95% confidence interval 32.5% to 62.5%, p<0.001). Serial measurements of proGRP in SCLC patients showed a decrease in responsive chemotherapy patients.

Conclusions:

ProGRP is an accurate biomarker for diagnosis of SCLC and for discrimination of SCLC from NSCLC.

Circulating biomarkers for monitoring therapy response and detection of disease progression in lung cancer patients

Liquid biopsies have become of interest as minimally invasive ways to monitor treatment response in lung cancer patients. Circulating tumor DNA (ctDNA) and protein biomarkers are evaluated for their added value in monitoring therapy response and early detection of disease progression. Plasma and serum samples of non-small cell or small cell lung cancer patients were analyzed for driver mutations in ctDNA (EGFR, KRAS or BRAF) using droplet digital PCR and protein biomarkers (CA125, CEA, CA15.3, Cyfra 21-1, HE4, NSE, proGRP and SCCA) using electrochemiluminescence immunoassays. Biomarker concentration changes were compared with the outcome of CT-scans during therapy. The median difference of the concentration of ctDNA, CA125 and Cyfra21-1 was significantly lower in patients with partial response (PR) compared to patients with progressive disease (PD) on the first evaluation CT-scan (P<0.001, P=0.042 and P=0.020, respectively). A substantial agreement between ctDNA or CA125 response and radiographic response was observed (k=0.692 and k=0.792, respectively). The median difference of the concentration of ctDNA and Cyfra21-1 was also significantly lower in PR patients compared to PD patients at the last CT-scan during therapy (P<0.001 and P=0.026, respectively). An almost perfect agreement between ctDNA and radiographic response (k=0.827) and a moderate agreement between Cyfra21-1 response and radiographic response was observed (k=0.553). Serial testing of the concentration of ctDNA, Cyfra21-1, and possibly CA125 could be a useful added tool for monitoring therapy response and early detection of disease progression in lung cancer patients.

NSE, positively regulated by LINC00657-miR-93-5p axis, promotes small cell lung cancer (SCLC) invasion and epithelial-mesenchymal transition (EMT) process

Background: Neuron specific enolase (NSE) is a specific biomarker for SCLC. However, the biological roles and aberrant expression of NSE in SCLC have not been well illustrated. Methods: The expression of NSE, miR-93-5p and LINC00657 in SCLC tissues and cell lines were detected using real time quantitative PCR (qRT-PCR) or immunohistochemistry. CCK8 assay was performed to detect cell proliferation. Cell migration and invasion capabilities were investigated by transwell assay. Epithelial-mesenchymal transition (EMT) process was verified by detecting epithelial marker E-cadherin and mesenchymal marker N-cadherin. The direct interactions between miR-93-5p and NSE or LINC00657 were predicted by bioinformatics tools and verified using dual luciferase reporter assay. Results: Upregulated expression of NSE in SCLC tumor tissues were positively associated with advanced tumor stage, distant metastasis and poor overall survival. Overexpression of NSE promoted cell proliferation, migration, invasion and EMT in SCLC cells, while silence of NSE inhibited these effects. Mechanically, NSE expression was positively correlated with LINC00657, and negatively correlated with miR-93-5p. Moreover, NSE was positively regulated by LINC00657 through sponging of miR-93-5p. LINC00657 and miR-93-5p promoted SCLC cell migration, invasion and EMT by NSE-mediated manner. Conclusion: Overall, our study revealed a novel role of NSE in SCLC. NSE was positively regulated by LINC00657 through competitively interacting with miR-93-5p, which may be potential targets for SCLC patients.

In Silico and In Vitro Analysis of lncRNA XIST Reveals a Panel of Possible Lung Cancer Regulators and a Five-Gene Diagnostic Signature

Simple Summary

Long non-coding RNAs (lncRNA) have been associated with a number of diseases including cancer. A well-studied lncRNA called XIST (X-inactive specific transcript) acts as a major effector of the X-inactivation process. It is expressed on the inactive X chromosome providing a dosage equivalence between males and females. Recently XIST has been implicated in the development of lung cancer. Using a bioinformatics approach, we demonstrate the XIST is over-expressed in female patients compared to males. When XIST gene was silenced in two different cell lines (of male and female origin), a number of genes were differentially expressed; playing a role in signal transduction pathways, energy balance and metabolism, thus providing a better insight of the role of this lncRNA in cancer. Finally, we showed that expression of XIST with another 4 genes provided a strong diagnostic potential to discriminate lung cancer from healthy controls.

Abstract

Long non-coding RNAs (lncRNAs) perform a wide functional repertoire of roles in cell biology, ranging from RNA editing to gene regulation, as well as tumour genesis and tumour progression. The lncRNA X-inactive specific transcript (XIST) is involved in the aetiopathogenesis of non-small cell lung cancer (NSCLC). However, its role at the molecular level is not fully elucidated. The expression of XIST and co-regulated genes TSIX, hnRNPu, Bcl-2, and BRCA1 analyses in lung cancer (LC) and controls were performed in silico. Differentially expressed genes (DEGs) were determined using RNA-seq in H1975 and A549 NSCLC cell lines following siRNA for XIST. XIST exhibited sexual dimorphism, being up-regulated in females compared to males in both control and LC patient cohorts. RNA-seq revealed 944 and 751 DEGs for A549 and H1975 cell lines, respectively. These DEGs are involved in signal transduction, cell communication, energy pathways, and nucleic acid metabolism. XIST expression associated with TSIX, hnRNPu, Bcl-2, and BRCA1 provided a strong collective feature to discriminate between controls and LC, implying a diagnostic potential. There is a much more complex role for XIST in lung cancer. Further studies should concentrate on sex-specific changes and investigate the signalling pathways of the DEGs following silencing of this lncRNA.

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

Background

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

Patients and method

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

Result

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

Conclusion

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

Multifunctional neuron-specific enolase: its role in lung diseases

Neuron-specific enolase (NSE), also known as gamma (γ) enolase or enolase-2 (Eno2), is a form of glycolytic enolase isozyme and is considered a multifunctional protein. NSE is mainly expressed in the cytoplasm of neurons and neuroendocrine cells, especially in those of the amine precursor uptake and decarboxylation (APUD) lineage such as pituitary, thyroid, pancreas, intestine and lung. In addition to its well-established glycolysis function in the cytoplasm, changes in cell localization and differential expression of NSE are also associated with several pathologies such as infection, inflammation, autoimmune diseases and cancer. This article mainly discusses the role and diagnostic potential of NSE in some lung diseases.

Value of serum tumor markers for predicting EGFR mutations in non-small cell lung cancer patients

OBJECTIVES

We investigated whether serum tumor markers (STMs) represent a valuable noninvasive tool to predict epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) patients.

METHODS

A retrospective analysis was performed for 143 NSCLC patients at the Peking University International Hospital from December 2014 to December 2019. EGFR mutations in the tumor tissues were identified by amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) and next generation sequencing (NGS). The relationships between EGFR mutation and several clinicopathological features were analyzed.

RESULT

EGFR mutation were found more frequently in female (56.67%, P = 0.01), never-smokers (55.26%, P = 0.004), and those with lung adenocarcinoma (ADC) (52.17%, P < 0.001). The positive mutation rate for the EGFR gene were higher in the squamous cell carcinoma antigen (SCCA)group (≤1.5 ng/ml) and in the gastrin-releasing peptide precursor (preGRP) increased group (≥69.2 pg/ml), and this difference was statistically significant (P < 0.05). Univariate logistic regression analysis demonstrated that females (Odd ratio [OR]: 2.435, 95% confidence interval [CI]: 1.232, 4.813, P = 0.01) and never-smokers (OR = 0.370; CI = 0.186, 0.734; P = 0.004), lung adenocarcinoma patients (OR = 9.091; CI = 2.599, 21.800; P = 0.001), the SCC group (≤1.5 ng/ml) (OR = 0.331, CI = 0.120, 0.914; P = 0.033), and the preGRP group (≥69.2 pg/ml) (OR = 5.478, CI = 1.462, 20.528; P = 0.012) patients were risk factors for EGFR gene mutation. Multivariate logistic regression analysis demonstrated that lung ADC and proGRP elevation were independent risk factors for predicting EGFR gene positivity (P < 0.05).

CONCLUSION

STMs are associated with mutant EGFR status and could be integrated with other clinical factors to facilitate the classification of EGFR mutation status among NSCLC patients.

Selective application of neuroendocrine markers in the diagnosis and treatment of small cell lung cancer

AIMS

Here, we explored the potential application and selection of neuroendocrine biomarkers in the diagnosis and treatment of small cell lung cancer.

METHODS

We retrospectively analyzed 118 patients with small cell lung cancer (SCLC), 166 patients with non-small cell lung cancer (NSCLC), 33 patients with benign lung disease (BLD), and 200 healthy individuals admitted to Zhejiang Provincial People's Hospital between January 1, 2015 and May 31, 2019. All the patients were newly diagnosed with either SCLC, NSCLC, or BLD and previously untreated. Peripheral blood levels of ProGRP, NSE, CEA, and CYFRA21-1 were analyzed during the follow-up treatment, and 2-fold upper limit of reference intervals were defined as effective elevation. We used paired results to analyze the diagnostic efficiency of proGRP and NSE on SCLC.

RESULTS

In the 118 SCLC patients, proGRP levels were significantly higher compared with NSE levels. The diagnostic efficiencies of NSE and ProGRP for SCLC were 0.8554 and 0.9053, respectively. The combined diagnostic efficiency (0.9426) was higher relative to NSE, but there was no significant difference compared with proGRP. The effective elevation rate of proGRP was 45.3% higher than that of NSE in the limited stage of SCLC. In the extensive disease of SCLC patients, 70.7% cases had more than 10-fold increase in proGRP value, whereas 56.9% cases had less than 5-fold increase in NSE value. Compared with pre-treatment, the median concentrations of proGRP increased by 204.0% higher than that of NSE (71.3%) in the progressive group. Besides, the dynamic change in imaging characteristics and tumor size had a strong correlation with the levels of proGRP.

SIGNIFICANCE

ProGRP is a reliable neuroendocrine biomarker in SCLC. The effective elevation of proGRP has a potential diagnostic and efficacy value in the evaluation of SCLC. However, the combined detection of proGRP and NSE does not significantly improve the diagnosis of lung cancer.

The MiR-17-92 Gene Cluster is a Blood-Based Marker for Cancer Detection in Non-Small-Cell Lung Cancer

Background

Lung cancer is one of the most malignant cancers threatening human health. The miR-17-92 gene cluster is a highly conserved oncogene cluster encoding 6 miRNAs: miR-17, miR-18a, miR-19a, miR-19b-1, miR-20a and miR-92a. This study explored whether these miRNAs can be used as diagnostic markers for non-small-cell lung cancer (NSCLC).

Methods

Serum samples were collected from healthy subjects (n = 23) and NSCLC patients at various stages (n = 74). Serum RNA was extracted by the TRIzol-glycogen method, and cDNA libraries were constructed by reverse transcription. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect the expression levels of the 6 miRNAs.

Results

The expression levels of the 6 miRNAs varied in different stages of NSCLC. Thus, 2 receiver operating characteristic (ROC) curves, that is, normal subjects and stage I-III patients and normal subjects and stage IV patients, of each miRNA were established to determine the interval of normal ΔCt values. The 2 areas under the curve (AUCs) of each miRNA were investigated (miR-17: 0.8097 and 1.000; miR-18a: 0.7388 and 0.9907; miR-19a/19b: 0.8451 and 0.5104; miR-20a: 0.8975 and 1.000; miR-92a: 0.8097 and 0.8342). In addition, a high positive correlation was discovered between miR-17 and miR-20a expression. Combining these 2 miRNAs can improve the screening effect of NSCLC.

Conclusion

The miR-17-92 gene cluster can likely serve as a diagnostic marker in NSCLC.

Utility of isocitrate dehydrogenase 1 as a serum protein biomarker for the early detection of non-small-cell lung cancer: A multicenter in vitro diagnostic clinical trial

We aimed to verify the expression status and diagnostic significance of isocitrate dehydrogenase 1 (IDH1) in non-small-cell lung cancer (NSCLC), especially during early stages. Serum IDH1 levels were measured by ELISA. A total of 1223 participants (660 patients with NSCLC, 276 healthy controls [HCs], 95 patients with benign pulmonary conditions [BPCs], 135 patients with other cancers [OCs], and 57 samples with interfering factors) were divided into a training cohort and a validation cohort according to 3 testing centers. The IDH1 concentrations in the NSCLC group were obviously higher than those in the control groups (P < .001). Area under the receiver operating characteristic curves (AUCs) for discriminating NSCLC patients from controls (HC, BPC, and OC) were 0.870 and 0.745 (sensitivity, 63.3% and 55.0%; specificity, 86.8% and 86.3%) in the training cohort and validation cohort, respectively. The AUCs for discriminating stage 0-IA lung cancer patients from HCs were 0.907 and 0.788 (sensitivity, 58.6% and 59.1%; specificity, 92.9% and 89.3%) in 2 cohorts, respectively. Isocitrate dehydrogenase 1 showed specificity for NSCLC and had no diagnostic value for other common cancers. Furthermore, IDH1 was significantly reduced in postoperative serum. Isocitrate dehydrogenase 1 shows clinical utility as a serum protein biomarker for the early diagnosis of NSCLC.

Local extraction and detection of early stage breast cancers through a microneedle and nano-Ag/MBL film based painless and blood-free strategy

Early diagnosis is the key to the good prognosis of breast cancer. At present, clinical tumor diagnosis is mainly through serum analysis, which is painful and can only detect relatively advanced tumors that have already metastasized from the glands into the blood circulation. Here, we developed an earlier diagnostic method (before tumor cells entering the blood) of breast cancers through a convenient and painless process with blood-free samples. The microneedles were utilized to insert into the animals' testing areas, while the tissue fluid was collected through our synthesized breathable thin film. The obtained tissue fluid sample was then incubated to form blue products. In the area where tumors occurred, the blue changes were more obvious than the healthy area, a semi-localization and semi-quantitative detection of the tumorous area thus could be realized. The results of corresponding animal experiments showed that, after the injection of tumor cells, the proposed nano-Ag based colorimetric method can detect the occurrence of breast cancers in 7 days. What is more, these early tumors could be effectively suppressed through classical DOX treatment. For comparison, the classical blood test needed 14 days to validate the occurrence of breast cancers. The subsequent human tests further demonstrated the feasibility of the present method. The development of this work could provide a more convenient, accurate and comfortable technology to support for the early screening and diagnosis of cancer patients, so as to fundamentally reduce the mortality of the breast cancers.

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

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

Use of cholesterol and soluble tumour markers CEA and syndecan-2 in pleural effusions in cases of inconclusive cytology

Aims

In order to improve diagnostics in pleural effusions, additional value of effusion cholesterol, carcinoembryonic antigen (CEA) and syndecan-2 assays to cytology was studied.

Methods

Biomarkers were measured in effusion supernatants from 247 patients, of whom 126 had malignant pleural involvement, and their additional diagnostic efficacy to cytology was assessed.

Results

Syndecan-2 measurement, although gave detectable concentrations in all effusions with highest median value in mesotheliomas, was non-discriminative between different pathological conditions. CEA concentrations exceeding 5 ng/mL cut-off point indicated carcinomas, regardless of pleural involvement, which gave a sensitivity of 62% and specificity of 100% for carcinoma. Cholesterol concentration over 1.21 mmol/L cut-off value indicated neoplastic pleural involvement with 99% sensitivity and ‘merely’ 69% specificity, the latter mainly due to raised levels being associated also with benign inflammatory effusions. Combined CEA and cholesterol determinations increased the sensitivity for diagnosing carcinomatosis from 70% with cytology alone to 84% and established the correct diagnosis in 16 of 31 carcinomatosis cases with inconclusive cytology. Cholesterol measurement alone, with elevated level, in combination with absence of substantial number of inflammatory cells in effusion sediment proved to be a magnificent marker for neoplastic pleural involvement with 99% efficacy, and recognised all 36 such cases with inconclusive cytology.

Conclusions

Simultaneous measurement of CEA and cholesterol concentrations in effusion, or at least cholesterol alone, in combination with non-inflammatory fluid cytology, provides additional specific information about neoplastic pleural involvement, and can therefore be used as an adjunct to cytology, above all, in inconclusive cases.

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

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

Clinical implications for pro-GRP in small cell lung cancer. A single center experience

BACKGROUND

Recently, pro-gastrin-releasing peptide (pro-GRP) became available as an alternative sensitive, specific and reliable tumor marker for patients with small cell lung cancer (SCLC), both in limited (LD) and diffuse disease (DD).

METHODS

We retrospectively analyzed pro-GRP, neuron-specific enolase (NSE) and CEA in patients with SCLC and non-small cell lung cancer (NSCLC). Serum pro-GRP level was measured with electrochemiluminescence at our laboratory (cutoff 77.8 pg/mL). Continuous variables were analyzed with the Mann-Whitney test, contingency data with Fisher's exact test. Receiver operator characteristic (ROC) curve analysis was performed to identify threshold values to set the highest sensitivity (Sn) and specificity (Sp) values.

RESULTS

A total of 65 patients were studied (49 men, median age 67 years, range 27-79). Thirty-seven patients had SCLC (29 DD, 8 LD) and 28 advanced NSCLC. Median pro-GRP level was 919 pg/mL (range 22-147,350) in SCLC and 32 pg/mL (range 10-119.2) in NSCLC (p<0.0001). NSE was 4.38-fold higher in SCLC patients (p = 0.0005); CEA did not reveal significant differences between groups. Pro-GRP Sn and Sp were 86.4% and 96.4%, respectively. With ROC curve analysis, a cutoff value of 329.3 pg/mL showed a Sn of 75.8% and Sp of 87.5% in discriminating DD from LD. Pro-GRP was not influenced by either liver metastases or renal impairment.

CONCLUSIONS

Pro-GRP is sensitive for SCLC diagnosis. Since high marker levels are related to high disease burden, pro-GRP may have a negative prognostic significance. Follow-up studies are required to define its role in clinical practice in monitoring responses to treatment and early relapses.

Tissue and Blood Biomarkers in Lung Cancer: A Review

Lung cancer is the most common cause of cancer-related death, worldwide. Historically, lung cancer has been divided into two main histological types: small cell and nonsmall cell (NSC) type with the latter being subdivided into adenocarcinoma, squamous cell type, and large cell type. The treatment of the NSC lung cancer (NSCLC), especially the adenocarcinoma subtype, has been transformed in the last decade by the availability of predictive biomarkers for molecularly targeted therapies. Currently, for patients with advanced adenocarcinomas, testing for sensitizing mutations in epidermal growth factor receptor (EGFR) is mandatory prior to the administration of anti-EGFR inhibitors such as erlotinib, gefitinib, afatinib, or osimertinib. For patients unable to provide tumor tissue, EGFR mutational analysis may be performed on plasma. For predicting response to crizotinib, testing for ALK and ROS1 gene rearrangement is necessary. The presence of ALK rearrangements is also a prerequisite for treatment with ceritinib, alectinib, or brigatinib. For predicting response to single agent pembrolizumab in the first-line treatment of patients with advanced adenocarcinoma or squamous cell NSCLCs, PD-L1 should be measured by an approved assay (e.g., PD-L1 IHC 22C3 pharmDx method). Although not widely used, serum biomarkers such as neuron-specific enolase, progastrin-releasing peptide, carcinoembryonic antigen, CYFRA 21-1, and squamous cell carcinoma antigen may help in the differential diagnosis of lung cancer when a tissue diagnosis is not possible. Serum biomarkers may also be of use in determining prognosis and monitoring response to systemic therapies. With the increasing use of biomarkers, personalized treatment especially for patients with adenocarcinoma-type NSCLC is finally on the horizon.

Prognostic value of serum CYFRA 21-1 1 in patients with anal canal squamous cell carcinoma treated with radio(chemo)therapy

BACKGROUND

We aimed to assess the prognostic value of CYFRA 21-1 in a series of patients with anal canal squamous cell carcinoma treated by radiation-based therapy.

METHODS

All patients with anal cancer referred between September 2005 and July 2013 were considered. Patients with diagnosis of anal squamous cell carcinoma and in whom pre- and post-treatment serum CYFRA 21-1 levels were available were included. Serum CYFRA 21-1 levels at initial workup and after therapy were collected. Survival rates were estimated using the Kaplan-Meier method. Cox regression analysis was used to evaluate prognostic variables for prediction of outcomes.

RESULTS

Eighty-two patients were included. Median follow-up was 60 months (range: 8-128). Pre-treatment serum CYFRA 21-1 levels were significantly correlated with tumour stage (p < 0.001). Normal post-treatment serum CYFRA 21-1 level was significantly correlated with tumour complete response (p = 0.004). Elevated post-treatment serum CYFRA 21-1 level was significantly associated with poorer progression-free survival (p = 0.02) and overall survival (p = 0.003). T stage and post-treatment serum CYFRA 21-1 were independent prognostic factors for overall survival (p = 0.04 and 0.03, respectively).

CONCLUSIONS

Serum CYFRA 21-1 appears to be a useful marker for the monitoring of anal squamous cell carcinoma patients. Elevated post-treatment value appears to be correlated with treatment failure.

Development of diagnostic model of lung cancer based on multiple tumor markers and data mining

Objective

To develop early intelligent discriminative model of lung cancer and evaluate the efficiency of diagnosis value.

Methods

Based on the genetic polymorphism profile of CYP1A1-rs1048943, GSTM1, mEH-rs1051740, XRCC1-rs1799782 and XRCC1-rs25489 and the methylations of p16 and RASSF1A gene, and the length of telomere in the peripheral blood from 200 lung cancer patients and 200 health persons, the discriminative model was established through decision tree and ANN technique.

Results

ACU of the discriminative model based on multiple tumour markers increased by about 10%; The accuracy rate of decision tree model and ANN model for testing set were 93.00% and 89.62% respectively. The ROC analysis showed the decision tree model’s AUC is 0.929 (0.894∼0.964), the ANN model’s AUC is 0.894 (0.853∼0.935). However, the classify accuracy rate and AUC of Fisher discriminatory analysis model are all about 0.7.

Conclusion

The early intelligent discriminative model of lung cancer based on multiple tumor markers and data mining techniques has a higher accuracy rate and might be useful for early diagnosis of lung cancer.

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

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