Clinical equivalence of two cytokeratin markers in mon-small cell lung cancer: a study of tissue polypeptide antigen and cytokeratin 19 fragments

Auxiliary diagnosis of Lung Cancer on the basis of a Serum Protein Biomarker Panel

Objectives: In this study, we established a serum protein biomarker panel (consisting of Pro-SFTPB, CA125, Cyfra21-1, and CEA) and evaluated the feasibility and performance for the auxiliary diagnosis of lung cancer in the Chinese population.

Materials and Methods: The current study was a single-center study based on the Chinese population and performed in two cohorts (training cohort and validation cohort). Serum concentrations of Pro-SFTPB, CA125, Cyfra21-1, and CEA were measured by a bead-based flow fluorescence immunoassay. The discrimination performance of the model was assessed using sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC).

Results: For the biomarker panel model, the AUC was 0.88 (95% CI, 0.85-0.91) in the training cohort and 0.90 (95% CI, 0.86-0.92) in the validation data cohort, which was significantly greater than the AUC of each biomarker alone. For the nodule risk model, the AUC was improved to 0.96 (95% CI, 0.94-0.98) in the training cohort and 0.95 (95% CI, 0.93-0.97) in the validation cohort. In addition, the biomarker panel model yielded an AUC of 0.78 (95% CI, 0.74-0.81) for stage I & II lung cancer, better than the performance of individual biomarker alone.

Conclusions: It was demonstrated that 4-protein biomarker panel had a significant performance in identifying lung cancer patients from healthy controls, especially combining with the nodule size. Specifically, it yielded excellent discrimination for identifying early-stage lung cancer patients than individual biomarker alone. A future large-scale study is underway to further define the clinical application of this method for the early diagnosis of lung cancer among Chinese populations.

[Current Status and Progress of Early Lung Cancer Screening under the Normal State of COVID-19 Epidemic Prevention and Control]

Lung cancer is the malignant tumor with the highest incidence in China. Early detection and identification of symptomatic lung cancer patients and timely screen out asymptomatic patients from high-risk groups require multiple cooperation. At present, although combined imaging, serology, genomics, proteomics and other methods have been combined to screen for suspected lung cancer, there are still problems such as missed diagnosis and misdiagnosis. Meanwhile, the spread of the corona virus disease 2019 (COVID-19) epidemic has brought new challenges to early lung cancer screening. Under the normalization of epidemic prevention and control, the work of early lung cancer screening should be changed accordingly: improve the population's awareness of cancer prevention and control, strengthen the management of medical procedures, improve the efficiency of tumor detection, optimize detection technology, and utilize internet and big data platforms rationally. We should establish an ideal model, combining multiple screening methods, which is streamlined and efficient for early lung cancer screening under normal epidemic prevention and control.
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Discovering novel lung cancer associated antigens and the utilization of their autoantibodies in detection of lung cancer

OBJECTIVE

The identification of tumor-associated antigens (TAAs) and their corresponding autoantibodies in lung cancer (LC) may expand our vision of cancer immunity. This study aims to screen novel TAAs to distinguish LC from the healthy population.

METHODS

In our previous study, 35 genes encoding LC-associated TAAs were identified from the serological analysis of recombinant cDNA expression libraries (SEREX), and Oncomine database was further used to identify potential genes in cancer progression. Autoantibody to TAAs were tested by enzyme-linked immunosorbent assay (ELISA) in sera from 1379 participants in validation set and verification set.

FINDINGS

Based on analysis of three independent microarrays in Oncomine, ten genes were consistently dysregulated in LC. The sera level and positive frequency of the anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 from LC patients were higher than normal control in validation set. The area under curve (AUC) of anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 was respectively 0.758, 0.787, 0.707, 0.668. The sensitivity of these four autoantibodies for LC detection ranged from 26.63 % to 32.07 % with the specificity over 90 %. Data from the verification set confirmed the results. Except that, the frequency of serum autoantibody against TOP2A (43.3 %) and ACTR3 (50.0 %) was significantly higher in early stage LC than late stage (23.6 % and 22.3 %, respectively).

CONCLUSION

TOP2A, ACTR3, RPS6KA5 and PSIP1 can elicit humoral immune response in LC and their autoantibodies have relationship with the tumorigenesis of LC. Anti-TOP2A and anti-ACTR3 have the potential to serve as a serological biomarkers in early stage LC.

Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics

The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth or extent of targets is limited. Here, we report an antibody-free targeted cross-species glycoproteomic (TCSG) approach that enables direct dissection of human tumor parenchyma from murine tumor stroma at the molecular/protein level in tumor xenografts at a selectivity rate presently unattainable by other means. This approach was used to segment/dissect and obtain the protein complement phenotype of the tumor stroma and parenchyma of the metastatic human lung adenocarcinoma A549 xenograft, with no need for tissue microdissection prior to mass-spectrometry analysis. An extensive molecular map of the tumor proper and the associated microenvironment was generated along with the top functional N-glycosylated protein networks enriched in each compartment. Importantly, immunohistochemistry-based cross-validation of selected parenchymal and stromal targets applied on human tissue samples of lung adenocarcinoma and normal adjacent tissue is indicative of a noteworthy translational capacity for this unique approach that may facilitate identifications of novel targets for next generation antibody therapies and development of real time preclinical tumor models.

Systematic review of CYFRA 21-1 as a prognostic indicator and its predictive correlation with clinicopathological features in Non-small Cell Lung Cancer: A meta-analysis

AIM

To evaluate the value of Cytokeratin 19 fragment for its survival prognostic indicator and predictive correlation with clinicopathological features in Non-small Cell Lung Cancer.

METHODS

Eligible studies or databases for articles were retrieved via search systematically. Pooled effect was calculated to evaluate the association between Cytokeratin 19 fragment level and long-term overall survival, as well as the tumor clinicopathological features in Non-small Cell Lung Cancer patients. A fixed-effects or random-effects model was used to calculate the Pooled risk ratios (RRs) and corresponding 95 % confidence intervals (CIs).

RESULTS

Six studies were up to the selection criteria. This meta-analysis indicated that Cytokeratin 19 fragment high level expression correlated with lower 2-year overall survival (RR =0.47; 95%CI: 0.28-0.79), higher Tumor Node Metastasis stage (II+III+IV) (RR =1.43; 95%CI: 1.15-1.76) in Non-small Cell Lung Cancer. The pooled RR estimates indicated that there is no statistical significance of Cytokeratin 19 fragment level expression in the advanced Non-small Cell Lung Cancer (IIIB+IV) (RR =1.43, 95% CI: 0.85-2.43).

CONCLUSION

Cytokeratin 19 fragment is a negative prognosis indicator and its high level expression indicates higher Tumor Node Metastasis pathological stage (II+III+IV) in Non-small Cell Lung Cancer. In advanced Non-small Cell Lung Cancer, the level of serum Cytokeratin 19 fragment appears to provide more prognostic information than it does for clinical Tumor Node Metastasis stage information. Further studies are required to confirm our results.

Measurement of Lung Cancer Tumor Markers in a Glass Wool Company Workers Exposed to Respirable Synthetic Vitreous Fiber and Dust

Background:

Occupational exposures to respirable synthetic vitreous fiber (SVF) and dust are associated with many lung diseases including lung cancer. Low-dose computed tomography is used for screening patients who are highly suspicious of having lung carcinoma. However, it seems not to be cost-effective. Serum biomarkers could be a useful tool for the surveillance of occupational exposure, by providing the possibility of diagnosing lung cancer in its early stages.

Objective:

To determine if serum carcinoembryonic antigen (CEA) and cytokeratin fragment (CYFRA) 21-1 levels in workers exposed more than normal population to respirable SVF and dust may be used as indicators of progression towards lung cancer.

Methods:

An analytic cross-sectional study, including 145 personnel of a glass wool company, along with 25 age-matched healthy individuals, was conducted to investigate the relationship between occupational exposure to respirable SVFs and dust and serum levels of two lung/pleura serum tumor markers, CEA and CYFRA 21-1, measured by ELISA.

Results:

Individuals exposed to higher than the recommended levels of respirable SVF had higher serum concentrations of CEA and CYFRA 21-1, compared to controls (p=0.008 and 0.040, respectively), as well as in comparison to those exposed to lower than recommended OSHA levels (p=0.046 and 0.033, respectively). Workers with >9 years work experience, had significantly (p=0.045) higher levels of serum CYFRA 21-1 than those with ≤9 years of experience.

Conclusion:

It seems that working for >9 years in sites with detectable levels of respirable SVF and dust would increase the levels of known lung cancer serum tumor markers. Transferring these workers to sites with respirable SVF concentrations lower than the limit of detection in the air is recommended.

Development of a Protein Biomarker Panel to Detect Non-Small-Cell Lung Cancer in Korea

BACKGROUND

Lung cancer screening using low-dose computed tomography reduces lung cancer mortality. However, the high false-positive rate, cost, and potential harms highlight the need for complementary biomarkers. We compared the diagnostic performance of modified aptamer-based protein biomarkers with Cyfra 21-1.

PATIENTS AND METHODS

Participants included 100 patients diagnosed with lung cancer, and 100 control subjects from Asan Medical Center (Seoul, Korea). We investigated candidate biomarkers with new modified aptamer-based proteomic technology and developed a 7-protein panel that discriminates lung cancer from controls. A naive Bayesian classifier was trained using sera from 75 lung cancers and 75 controls. An independent set of 25 cases and 25 controls was used to verify performance of this classifier. The panel results were compared with Cyfra 21-1 to evaluate the diagnostic accuracy for lung nodules detected by computed tomography.

RESULTS

We derived a 7-protein biomarker classifier from the initial train set comprising: EGFR1, MMP7, CA6, KIT, CRP, C9, and SERPINA3. This classifier distinguished lung cancer cases from controls with an area under the curve (AUC) of 0.82 in the train set and an AUC of 0.77 in the verification set. The 7-marker naive Bayesian classifier resulted in 91.7% specificity with 75.0% sensitivity for the subset of individuals with lung nodules. The AUC of the classifier for lung nodules was 0.88, whereas Cyfra 21-1 had an AUC of 0.72.

CONCLUSION

We have developed a protein biomarker panel to identify lung cancers from controls with a high accuracy. This integrated noninvasive approach to the evaluation of lung nodules deserves further prospective validation among larger cohorts of patients with lung nodules in screening strategy.

Multiplexed Serum Biomarkers for the Detection of Lung Cancer

Currently, there is no available biomarker for lung cancer diagnosis. Here we recruited 844 lung cancer patients and 620 healthy participants from six hospitals. A total of four serum proteins was identified and subsequently assessed in the training and validation cohorts. The concentrations of four serum proteins were found to be significantly higher in lung cancer patients compared with healthy participants. The area under the curve (AUC) for the 4-biomarker were 0.86 in the training cohort, and 0.87 in the validation cohort. The classification improved to a corrected AUC of 0.90 and 0.89 respectively following addition of sex, age and smoking status. Similar results were observed for early-stage lung cancer. Remarkably, in a blinded test with a suspicious pulmonary nodule, the adjusted prediction model correctly discriminated the patients with 86.96% sensitivity and 98.25% specificity. These results demonstrated the 4-biomarker panel improved lung cancer prediction beyond that of known risk factors. Moreover, the biomarkers were valuable in differentiating benign nodules which will remain indolent from those that are likely to progress and therefore might serve as an adjuvant diagnosis tool for LDCT scanning.

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A multicentric, case–control study was conducted to identify serum proteins for diagnosing lung cancer.

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A 4-marker panel improved lung cancer prediction beyond that of known risk factors.

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The biomarkers can detect lung cancer especially stage I–II from healthy controls or benign nodule patients.

Currently, low dose chest computed tomography (LDCT) leads to a high false-positive result. Here we identified a panel of four serum proteins, which provides the potential for accurate diagnosis of lung cancer in a multicentric study. More importantly, the biomarkers allowed accurate detection of lung cancer cases especially stage I-II cases from normal and benign nodule subjects. These results suggest that the 4-protein panel might be a useful biomarker for diagnosing lung cancer patients and help discriminate early stage patients, which may serve as an adjuvant diagnosis tool for LDCT scanning in the future.

Robust ultrasensitive tunneling-FET biosensor for point-of-care diagnostics

For point-of-care (POC) applications, robust, ultrasensitive, small, rapid, low-power, and low-cost sensors are highly desirable. Here, we present a novel biosensor based on a complementary metal oxide semiconductor (CMOS)-compatible silicon nanowire tunneling field-effect transistor (SiNW-TFET). They were fabricated “top-down” with a low-cost anisotropic self-stop etching technique. Notably, the SiNW-TFET device provided strong anti-interference capacity by applying the inherent ambipolarity via both pH and CYFRA21-1 sensing. This offered a more robust and portable general protocol. The specific label-free detection of CYFRA21-1 down to 0.5 fgml⁻¹ or ~12.5 aM was achieved using a highly responsive SiNW-TFET device with a minimum sub-threshold slope (SS) of 37 mVdec⁻¹. Furthermore, real-time measurements highlighted the ability to use clinically relevant samples such as serum. The developed high performance diagnostic system is expected to provide a generic platform for numerous POC applications.

Diagnostic utility of serum and pleural fluid carcinoembryonic antigen, and cytokeratin 19 fragments in patients with effusion from nonsmall cell lung cancer

Aims:

To assess the diagnostic value of CEA and CYFRA 21-1 (cytokeratin 19 fragments) in serum and pleural fluid in non small cell lung cancer with malignant pleural effusion (MPE).

Settings and Design:

Two subsets of patients were recruited with lymphocytic exudative effusion, one subset constituted diagnosed patients of NSCLC with malignant pleural effusion and the other subset of constituted with Tubercular pleural effusion.

Materials and Methods:

CYFRA 21-1 and CEA levels were measured using Electrochemilumiscence Immunoassay (ECLIA). The test principle used the Sandwich method. For both the tests, results are determined via a calibration curve which is instrument specifically generated by 2 - point calibration and a master curve provided via reagent barcode.

Statistical Analysis Used:

All data are expressed as means ± SD and percentage. All the parametric variables were analysed by student-t test where as non parametric variables were compared by Mann-Whitney U-test Statistical significance was accepted for P values < 0.05. Software used were SPSS 11.5, and MS excel 2007. In order to compare the performance of the tumor markers, receiver operating characteristic (ROC) curves were constructed and compared with area under the curve (AUC). The threshold for each marker was selected based on the best diagnostic efficacy having achieved equilibrium between sensitivity and specificity.

Results:

In cases serum CYFRA21-1 levels had mean value of 34.1 ± 29.9 with a range of 1.6-128.3 where as in controls serum CYFRA21-1 levels had mean value of 1.9 ± 1.0 with a range of 0.5–4.7. In cases serum CEA levels had mean value of 24.9 ± 47.3 with a range of 1.0, 267.9 where as in controls serum CEA levels had mean value of 1.9 ± 1.4 with a range of 0.2-6.8. The difference in the means of serum CYFRA 21-l (P = 0.000) and CEA (P = 0.046) were statistically significant. In cases pleural fluid CYFRA21-1 levels had mean value of 160.1 ± 177.1 with a range of 5.4–517.2 where as in controls pleural fluid CYFRA21-1 levels had mean value of 15.9 ± 5.7 with a range of 7.2-29.6. In cases CEA pleural fluid levels had mean value of 89.8 ± 207.4 with a range of 1.0–861.2 where as in controls CEA levels had mean value of 2.5 ± 2.3 with a range of 1–8.9. The difference in the means of CYERA 21-1 (P = 0.001) between cases and controls is statistically significant.

Conclusions:

CYFRA21-1 (serum - pleural fluid) is a sensitive marker for NSCLC with sensitivity of 96.7%, highest of any combination [Serum (CYFRA 21-1 - CEA). CEA (Serum + Pleural Fluid), Pleural Fluid (CYFRA 21-1 + CEA)] and specificity of 77.8%. Levels of CYFRA21-l (serum + pleural fluid) are increased in malignant pleural effusion, so it is better to be used in suspicious malignant pleural effusion showing negative cytology, particularly in the absence of a visible tumor and or unsuitability for invasive procedure.

Ultrasensitive Detection of Dual Cancer Biomarkers with Integrated CMOS-Compatible Nanowire Arrays

A direct, rapid, highly sensitive and specific biosensor for detection of cancer biomarkers is desirable in early diagnosis and prognosis of cancer. However, the existing methods of detecting cancer biomarkers suffer from poor sensitivity as well as the requirement of enzymatic labeling or nanoparticle conjugations. Here, we proposed a two-channel PDMS microfluidic integrated CMOS-compatible silicon nanowire (SiNW) field-effect transistor arrays with potentially single use for label-free and ultrasensitive electrical detection of cancer biomarkers. The integrated nanowire arrays showed not only ultrahigh sensitivity of cytokeratin 19 fragment (CYFRA21-1) and prostate specific antigen (PSA) with detection to at least 1 fg/mL in buffer solution but also highly selectivity of discrimination from other similar cancer biomarkers. In addition, this method was used to detect both CYFRA21-1 and PSA real samples as low as 10 fg/mL in undiluted human serums. With its excellent properties and miniaturization, the integrated SiNW-FET device opens up great opportunities for a point-of-care test (POCT) for quick screening and early diagnosis of cancer and other complex diseases.

Research progress in applying proteomics technology to explore early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer

According to the China tumor registry 2013 annual report , breast cancer, lung cancer, and ovarian cancer are three common cancers in China nowadays, with high mortality due to the absence of early diagnosis technology. However, proteomics has been widespreadly implanted into every field of life science and medicine as an important part of post-genomics era research. The development of theory and technology in proteomics has provided new ideas and research fields for cancer research. Proteomics can be used not only for elucidating the mechanisms of carcinogenesis focussing on whole proteins of the tissue or cell, but also seeking the biomarkers for diagnosis and therapy of cancer. In this review, we introduce proteomics principles, covering current technology used in exploring early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer.

Expression and function of GSTA1 in lung cancer cells

Glutathione S-transferase A1 (GSTA1) appears to be primarily involved in detoxification processes, but possible roles in lung cancer remain unclear. The objective of this study was to investigate the expression and function of GSTA1 in lung cancer cells. Real-time PCR and Western blotting were performed to assess expression in cancer cell lines and the normal lung cells, then verify the A549 cells line with stable overexpression. Localization of GSTA1 proteins was assessed by cytoimmunofluorescence. Three double-strand DNA oligoRNAs (SiRNAs) were synthesized prior to being transfected into A549 cells with Lipofectamine 2000, and then the most efficient SiRNA was selected. Expression of the GSTA1 gene in the transfected cells was determined by real-time PCR and Western blotting. The viability of the transfected cells were assessed by MTT. Results showed that the mRNA and protein expression of A549 cancer cells was higher than in MRC-5 normal cells. Cytoimmunofluorescence demonstrated GSTA1 localization in the cell cytoplasm and/or membranes. Transfection into A549 cells demonstrated that down-regulated expression could inhibit cell viability. Our data indicated that GSTA1 expression may be a target molecule in early diagnosis and treatment of lung cancer.

Urinary protein biomarkers in the early detection of lung cancer

The early detection of lung cancer has the potential to greatly impact disease burden through the timely identification and treatment of affected individuals at a manageable stage of development. The insufficient specificity demonstrated by currently used screening and diagnostic techniques has led to intense investigation into biomarkers as diagnostic tools. Urine may represent a noninvasive alternative matrix for diagnostic biomarker development. We performed an analysis of 242 biomarkers in urines obtained from 83 patients with non-small cell lung carcinomas (NSCLC), 74 patients diagnosed with benign pulmonary conditions, and 77 healthy donors. A large number of significant alterations were observed between the NSCLC and control groups. A multivariate analysis identified a three-biomarker panel consisting of IGFBP-1, sIL-1Ra, CEACAM-1, which discriminated NSCLC from healthy controls with a sensitivity/specificity of 84/95 in an initial training set and 72/100 in an independent validation set. This panel performed well among multiple subtypes of NSCLC and early-stage disease but demonstrated only limited efficacy for the discrimination of NSCLC from benign controls and limited specificity for patients with several other cancers and tuberculosis. These findings demonstrate that urine biomarkers may provide screening and diagnostic properties which exceed those reported for serum biomarkers and approach a level necessary for further clinical development.

Development and validation of a plasma biomarker panel for discerning clinical significance of indeterminate pulmonary nodules

INTRODUCTION

The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography-based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography-based screening and promote its rapid implementation.

METHODS

We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules.

RESULTS

Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2Rα, stromal cell-derived factor-1α+β, tumor necrosis factor α, and macrophage inflammatory protein 1 α. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%.

CONCLUSION

We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.

Combining multiple serum biomarkers in tumor diagnosis: A clinical assessment

The present study aimed to assess the diagnostic/prognostic value of various clinical tumor markers, including carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin 19 (CYFRA21-1), α-fetoprotein (AFP), carbohydrate antigen-125 (CA-125), carbohydrate antigen-19.9 (CA-19.9) and ferritin, individually or in combination. The electro-chemiluminescence immunization method was performed to detect the levels of seven tumor markers in 560 cancer patients and 103 healthy subjects for comparison. The serum levels of the seven markers measured in cancer patients were higher compared to healthy subjects (P<0.05 for AFP and P<0.001 for the remaining six markers). Different markers had different sensitivity towards different types of tumors. Combining more markers significantly increased the ratios of positive diagnosis in the tumors. The diagnostic sensitivities of combining seven markers were particularly high in digestive, urinary and skeletal tumors (82, 92 and 83%, respectively). Gynecological tumors have exhibited a constant yet relatively low positive diagnosis irrespective of the use of a single marker or combined markers. However, the increase in sensitivity when combining markers was accompanied by a decrease in specificity. Generally, combining more markers increased the tumor detection rates, while a combination of the seven markers provided the highest detection rate. Combined detection showed a particularly high sensitivity in detecting respiratory, digestive and urinary system tumors, with the lowest sensitivity observed in gynecological tumors. As a result, combining tumor markers may play an important role in early tumor detection/diagnosis while the loss of specificity can be tolerated.

Cytokeratin-19 fragments, nucleosomes and neuron-specific enolase as early measures of chemotherapy response in non-small cell lung cancer

AIM

To investigate the reduction in the serum level of cytokeratin-19 fragments (CYFRA 21-1), nucleosomes and neuron-specific enolase (NSE) as early measures of the response to chemotherapy in non-small cell lung cancer (NSCLC).

METHODS

Forty-two consecutive patients with locally advanced NSCLC were included. All patients received platinum-based chemotherapy. Staging investigations and quantification of CYFRA 21-1, nucleosomes and NSE (using enzyme-linked immunosorbent assay, ELISA) were performed before the start of treatment and after the second cycle of chemotherapy. According to the response to chemotherapy, patients were classified into 3 groups: (I) disease regression, (II) stable disease, and (III) progressive disease. The reduction in the levels of tumor markers was correlated with the response to chemotherapy.

RESULTS

After the second cycle of chemotherapy, groups I and II had significantly decreased serum levels of CYFRA 21-1 (p<0.05). Similarly, the concentration of nucleosomes was significantly lower than the baseline levels in groups I (p=0.0008) and II (p=0.003). The reduction of both CYFRA 21-1 and nucleosome levels was not significant for patients in group III. In all groups the reduction of NSE levels in response to chemotherapy was not significant. As a marker of response to chemotherapy, CYFRA 21-1 showed the highest sensitivity (88.9%) and specificity (77.4%) compared with nucleosomes (77.8% and 58.1% respectively) and NSE (66.7% and 51.8% respectively).

CONCLUSION

The reduction in the serum level of CYFRA 21-1 and nucleosomes may be used for early identification of NSCLC patients with good response to chemotherapy.

Serum biomarker profiles as diagnostic tools in lung cancer

BACKGROUND

Computed tomography (CT) scanning has emerged as an effective means of early detection for lung cancer. Despite marked improvement over earlier methodologies, the low level of specificity demonstrated by CT scanning has limited its clinical implementation as a screening tool. A minimally-invasive biomarker-based test that could further characterize CT-positive patients based on risk of malignancy would greatly enhance its clinical efficacy.

METHODS

We performed an analysis of 81 serum proteins in 92 patients diagnosed with lung cancer and 172 CT-screened control individuals. We utilize a series of bioinformatics algorithms including Metropolis-Monte Carlo, artificial neural networks, Naïve Bayes, and additive logistic regression to identify multimarker panels capable of discriminating cases from controls with high levels of sensitivity and specificity in distinct training and independent validation sets.

RESULTS

A three-biomarker panel comprised of MIF, prolactin, and thrombospondin identified using the Metropolis-Monte Carlo algorithm provided the best classification with a %Sensitivity/Specificity/Accuracy of 74/90/86 in the training set and 70/93/82 in the validation set. This panel was effective in the classification of control individuals demonstrating suspicious pulmonary nodules and stage I lung cancer patients.

CONCLUSIONS

The selected serum biomarker panel demonstrated a high diagnostic utility in the current study and performance characteristics which compare favorably with previous reports. Further advancements may lead to the development of a diagnostic tool useful as an adjunct to CT-scanning.

CYFRA 21-1 as a prognostic and predictive marker in advanced non-small-cell lung cancer in a prospective trial: CALGB 150304

BACKGROUND

Cytokeratin 19 and its soluble fragment CYFRA have been studied as markers that may be associated with response to therapy and survival in non-small-cell lung cancer (NSCLC). As a prospective correlative study of Cancer and Leukemia Group B 30203, a randomized phase II trial of carboplatin/gemcitabine with eicosanoid modulators (celecoxib, zileuton, or both) in advanced NSCLC, serum CYFRA levels were obtained before and during treatment.

METHODS

Serum CYFRA levels were measured at baseline and after the first cycle of treatment using an electrochemoluminescent assay. Paired specimens were available from 88 patients. The logarithms of the initial concentration and of the difference in concentrations were analyzed for association with overall survival (OS) and failure-free survival (FFS).

RESULTS

Lower baseline CYFRA levels were associated with both longer OS and FFS (p < 0.0001 and p = 0.0003). In addition, larger reductions in CYFRA levels correlated with longer OS and FFS (p = 0.0255 and p = 0.0068).

CONCLUSION

CYFRA and change in CYFRA were found to be reliable markers for response to chemotherapy for NSCLC; however, a precise threshold to mark response has yet to be determined.

A multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from high-risk individuals found to be cancer-free by CT screening

INTRODUCTION

Clinical decision making in the setting of computed tomography (CT) screening could benefit from accessible biomarkers that help predict the level of lung cancer risk in high-risk individuals with indeterminate pulmonary nodules.

METHODS

To identify candidate serum biomarkers, we measured 70 cancer-related proteins by Luminex xMAP (Luminex Corporation) multiplexed immunoassays in a training set of sera from 56 patients with biopsy-proven primary non-small-cell lung cancer and 56 age-, sex-, and smoking-matched CT-screened controls.

RESULTS

We identified a panel of 10 serum biomarkers-prolactin, transthyretin, thrombospondin-1, E-selectin, C-C motif chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor, receptor tyrosine-protein kinase, erbb-2, cytokeratin fragment 21.1, and serum amyloid A-that distinguished lung cancer patients from controls with an estimated balanced accuracy (average of sensitivity and specificity) of 76.0 ± 3.8% from 20-fold internal cross-validation. We then iteratively evaluated this model in an independent test and verification case/control studies confirming the initial classification performance of the panel. The classification performance of the 10-biomarker panel was also analytically validated using enzyme-linked immunosorbent assays in a second independent case/control population, further validating the robustness of the panel.

CONCLUSIONS

The performance of this 10-biomarker panel-based model was 77.1% sensitivity/76.2% specificity in cross-validation in the expanded training set, 73.3% sensitivity/93.3% specificity (balanced accuracy 83.3%) in the blinded verification set with the best discriminative performance in stage I/II cases: 85% sensitivity (balanced accuracy 89.2%). Importantly, the rate of misclassification of CT-screened controls was not different in most control subgroups with or without airflow obstruction or emphysema or pulmonary nodules. These biomarkers have potential to aid in the early detection of lung cancer and more accurate interpretation of indeterminate pulmonary nodules detected by CT screening.

Proteome differences between male and female fetal cells in amniotic fluid

In mammals, sex development is genetically and hormonally regulated. The process starts with the establishment of chromosomal structures (XY or XX), followed by the expression of sex-dependent genes. In order to elucidate the differential protein profiles between male and female amniocytes, a proteomic approach has been performed in this study. Here, we utilized a proteomics-based approach including 2D-DIGE and MALDI-TOF MS analysis to obtain differentially expressed proteins between male and female amniocytes. After resolving protein samples with 2D-DIGE technique, 45 proteins corresponding to 28 unique proteins were differentially expressed between male and female amninocytes from three independent batches of amniotic fluid. Of all of these unique identified spots, five of them (annexin A1, cathepsin D, cytoskeletal 19, protein disulfide-isomerase, and vimentin) exhibited more than 1.5-fold upregulation or downregulation in at least two independent experiments. Importantly, the identified proteins involved in protein degradation and protein folding display upregulated in male amniocytes, implying the differential regulations of protein degradation and protein folding during sex development. In conclusion, the identified differentially expressed proteins may be employed as potential signatures for the sex development. Moreover, the established proteomic platform might further utilize to discover the potential biomarkers for the prenatal genetic disorders in fetus.

Lung cancer serum biomarker discovery using label-free liquid chromatography-tandem mass spectrometry

INTRODUCTION

Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer and the relatively favorable survival associated with early-stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit.

METHODS

We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry in a set of pooled non-small cell lung cancer case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by liquid chromatography-tandem mass spectrometry. The tandem mass spectrum data were searched against the human proteome database, and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting-derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring mass spectrometry assays.

RESULTS

A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (p < 0.01). Functional analysis with Ingenuity Pathway Analysis tools showed significant enrichment of inflammatory response proteins, key molecules in cell-cell signaling and interaction network, and differential physiological responses for the two common non-small cell lung cancer subtypes.

CONCLUSIONS

We identified a set of candidate serum biomarkers with statistically significant differential abundance across the lung cancer case/control pools, which, when validated, could improve lung cancer early detection.

New biomarkers for lung cancer

IMPORTANCE OF THE FIELD

Despite many efforts to improve early detection, lung cancer remains the leading cause of cancer deaths. Stage is the main determinant of prognosis and the basis for deciding treatment options. Screening tests for lung cancer have not been successful so far.

AREAS COVERED IN THE REVIEW

The article reviews the available literature related to biomarkers in use at present and those that could be used for early diagnosis, staging, prognosis, response to therapy and prediction of recurrence. The single biomarkers are analysed, divided according to the technological methods used and the locations of sampling.

WHAT THE READER WILL GAIN

The reader will gain knowledge on biomarkers in use and those now under study. The reader will also gain insights into the difficulties pertaining to the development of biomarkers, results reproducibility and clinical application.

TAKE HOME MESSAGE

Although some markers seem to be promising, at present there is no consensus on the proven value of their clinical use in lung cancer. The future lies probably in a panel of biomarkers instead of individual assays, or in predictive models derived from the integration of clinical variables and gene expression profiles.

Lung fibrosis and lung cancer incidence in beagle dogs that inhaled 238PuO2 or 239PuO2

Determination of radiation protection guidelines for persons working with plutonium has been complicated by limited human data on the biological behavior and subsequent health effects from internally deposited plutonium. One solution has been the use of animal models to predict likely health effects in humans. To compare the relationships between plutonium inhalation and lung fibrosis and lung cancer, data from life-span studies of beagle dogs given a single exposure to either plutonium-238 dioxide (238PuO2) or plutonium-239 dioxide(239PuO2) were analyzed. Estimates of the cumulative hazard of lung fibrosis and lung cancer after exposure to either were generated. The hazard of lung fibrosis was not consistent with a linear no-threshold model, although the magnitude of the threshold differed by radionuclide. In dogs given 239PuO2,the best model of lung fibrosis incorporated a linear dose response function; a linear-quadratic dose-response function fit the data better in dogs given 238PuO2. At any given cumulative dose, the lung fibrosis hazard was greater for dogs given 238PuO2. In dogs given 238PuO2, with or without covariates, aquadratic dose-response function for lung cancer hazard fit better than a linear no-threshold model. In dogs given 239PuO2, models of lung cancer with the dose-response function as the sole predictor variable were consistent with a linear no-threshold model; however, a quadratic dose-response function with a cell-killing term fit better. These findings have implications for radiation protection because, while lung cancer hazard was dependent on cumulative dose, regardless of isotope, the lung fibrosis hazard depended on both cumulative dose and isotope.

Biomarkers for the lung cancer diagnosis and their advances in proteomics

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.

The concentration of selected cancer markers (TPA, TPS, CYFRA 21-1, CEA) in workers occupationally exposed to arsenic (As) and some heavy metals (Pb, Cd) during a two-year observation study

OBJECTIVE

Molecular epidemiology studies have lately been focused on occupational cancer associated with exposure to chemical carcinogens in work environment. Measuring serum levels of tumour markers ie. the substances produced in transformed cells, is a modern method used in the prevention or early detection of cancer. A two-year observation study was constructed to investigate the relationship between arsenic, lead, and cadmium concentrations and the levels of cancer markers: TPA (tissue polipeptide antigen), TPS (tissue polipeptide specific antigen), and CYFRA 21-1 in 69 male workers occupationally exposed to As and Pb, and environmentally exposed to Cd via tobacco smoking.

RESULTS

Significant correlations were found between CEA and blood Cd concentrations or between CEA and period of work under exposure. Multiple regression tests revealed also relationships between some cancer markers and the work period, and thereby the lifetime exposure to heavy metals. Duration of work under exposure significantly influenced TPA and TPS concentrations in these models. All the metals examined were found to have influence on the concentration of cancer markers, except for CYFRA 21-1, but the direction of this influence varied. Lead (especially FEP level) and cadmium were also among the metals affecting TPA concentration profile, although the multiple regression ratio for Cd-TPA correlation was negative.

CONCLUSIONS

The strong positive correlation between blood concentrations of Cd and CEA, the marker of abnormal cellular differentiation, may reflect neoplastic transformation of normal cells stimulated by some carcinogens (e.g. cadmium). All the examined carcinogenic, or potentially carcinogenic metals (As, Cd, Pb) belong to the group of factors having impact on serum TPS and/or TPA concentrations in exposed workers. No correlation was found between CYFRA 21-1 and any metal studied but it is plausible that changes in the concentration level of this marker might be revealed after a longer observation period.

Potentially useful biomarkers for the diagnosis, treatment and prognosis of lung cancer

Lung cancer ranks top in both incidence and mortality in most part of the world. Scientists strive to explore biomarkers and their possible role in the diagnosis, treatment and prognosis of lung cancer. The ultimate goal is to discover biomarkers that can be tested in clinical trials and finally applied to patient care. Highly elevated concentrations of cytokeratin 19 fragment, tissue polypeptide antigen and squamous cell carcinoma antigen in non-small cell lung cancer particularly for squamous cell carcinoma, carcinoembryonic antigen and cancer antigen 125 in adenocarcinoma or non-small cell lung cancer, as well as progastrin-releasing peptide and neuron specific enolase in small cell lung cancer are suggestive biomarkers for the malignancy. Despite extensive studies, most results still remain controversial. Even with the report of high percent sensitivity and specificity, validation by clinical trials in large cohorts of patients is necessary before the cancer-related phenotypes can be translated into the clinic as reliable biomarkers. Nevertheless, identifications of biomarkers are leading to more understanding of the molecular pathways involved in lung cancer. It is hoped that understanding the connections between cellular pathways will help to reduce the suffering and loss of life caused by the lethal disease. This article summarizes the pre-clinical and translational researches against lung cancer in relation to biomarker discovery and validation. It is intended for policy makers, researchers, clinicians and other health professionals, offering a variety of useful biomarkers and updated data of clinical trials for lung cancer.

Recommendations For Clinical Use Of Tumor Markers In Lung Cancer

Kancer pluća predstavlja jedan od najozbiljnijih problema moderne onkologije. Uprkos kontinuiranom napretku u dijagnostičkim metodama, kod 50-70% pacijenata s kancerom pluća, bolest se dijagnostikuje u uznapredovalom stadijumu, isključujuci na taj način mogućnost radikalne terapije. Određivanje tumorskih markera kod kancera pluća može biti od pomoći u postavljanju dijagnoze, praćenju pacijenta i terapije, a takođe može da pruži dodatne informacije u prognostičke svrhe. U daljem tekstu opisani su odgovarajući serumski markeri kod dve glavne forme tumora pluća-mikrocelularnog i nemikrocelularnog (SCLC i NSCLC), kao i abnormalne supstance identifikovane u tumorima pluća ili njihovim metastazama, kao što su molekularni markeri, markeri prognoze u primeni neoadjuvantne ili adjuvantne terapije i mikrometastazama koštane srži ili limfnom čvoru.

Lung Cancer - Clinical Implications

Karcinom pluća je najčešće maligno oboljenje kod muškog pola, a u žena na drugom mestu (nakon raka dojke). Klinička podela na nemikrocelularni (NSCLC) i mikrocelularni (SCLC) odražava različito biološko ponašanje i sledstveno razlike u terapijskom pristupu. Od velike važnosti bi bilo postojanje biomarkera koji bi omogućili razlikovanje ova dva tipa karcinoma pluća, naročito u slučajeva kada nije izvodljiva invazivna dijagnostika kao i u praćenju efekata terapije i ranom otkrivanju relapsa bolesti. Rezultati velikih retrospektivnih ili prospektivnih studija ukazuju na izvesnu vrednost specifičnih markera ili kombinacija ovih markera za dijagnostičke i diferencijalno dijagnostičke svrhe. Merenje četiri serum tumor markera, CYFRA 21-1, CEA, NSE i ProGRP ima opravdanja da bi se identifikovao vodeći marker i na taj način predpostavio verovatni histološki tip tumora. Serijska određivanja odgovarajućeg tumor markera može takođe biti od pomoći da se utvrdi kompletnost uklanjanja tumora i utvrdi relaps bolesti u okultnom kliničkom stadijumu.

CYFRA 21-1 is a prognostic determinant in non-small-cell lung cancer: results of a meta-analysis in 2063 patients

The purpose of this study was to determine the prognostic significance of a high pretreatment serum CYFRA 21-1 level (a cytokeratin 19 fragment) adjusted for the effects of well-known co-variables in non-small-cell lung cancer (NSCLC). This meta-analysis based on individual updated data gathered comprehensive databases from published or unpublished controlled studies dealing with the prognostic effect of serum CYFRA 21-1 level at presentation in NSCLC of any stage (nine institutions, 2063 patients). Multivariate regression was carried out with the Cox model. The proportional hazard assumption for each of the selected variables retained in the final model was originally checked by log minus log plots baseline hazard ratio. The follow-up ranged from 25 to 78 months. A total of 1616 events were recorded. In the multivariate analysis performed at the 1-year end point, a high pretreatment CYFRA 21-1 level was an unfavourable prognostic determinant in all centres except one (Hazard ratio (95% confidence interval): 1.88 (1.64–2.15), P<10⁻⁴). Other significant variables were stage of the disease, age and performance status. Within the first 18 months, the procedure disclosed a nearly similar hazard ratio for patients having a high pretreatment serum CYFRA 21-1 level (1.62 (1.42–1.86), P<10⁻⁴). For patients who did not undergo surgery, the hazard ratio during the first year of follow-up was 1.78 (1.54–2.07), P<10⁻⁴. Finally, in the surgically treated population, at the 2-year end point, a high pretreatment CYFRA 21-1 and a locally advanced stage remained unfavourable prognostic determinants. In conclusion CYFRA 21-1 might be regarded as a putative co-variable in analysing NSCLC outcome inasmuch as a high serum level is a significant determinant of poor prognosis whatever the planned treatment.