Serum levels of epidermal growth factor and HER-2 neu in non small-cell lung cancer: prognostic correlation

Nanoproteomics deciphers the prognostic value of EGFR family proteins-based liquid biopsy

Monitoring tumor-associated protein status in serum can effectively track tumors and avoid time-consuming, costly, and invasive tissue biopsy. Epidermal growth factor receptor (EGFR) family proteins are often recommended in the clinical management of multiple solid tumors. However, the low-abundance of serum EGFR (sEGFR) family proteins hinders the depth-understanding of their function and tumor management. Herein, a nanoproteomics approach coupling with aptamer-modified MOFs (NMOFs-Apt) with mass spectrometry was developed for the enrichment and quantitative analysis of sEGFR family proteins. This nanoproteomics approach exhibited high sensitivity and specificity for sEGFR family protein quantification, with the limit of quantification as low as 1.00 nM. After detecting 626 patients' sEGFR family proteins with various malignant tumors, we concluded that the levels of serum proteins had a moderate concordance with tissue counterparts. Metastatic breast cancer patients with a high level of serum human epidermal growth factor receptor 2 (sHER2) and a low level of sEGFR had a poor prognosis, and patients with a sHER2 decrease of more than 20% had longer disease-free time after receiving chemotherapy. This nanoproteomics method provided a simple and effective approach for low-abundant serum protein detection and our results clarified the potential of sHER2 and sEGFR as cancer markers.

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.

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.

Analysis of the prognostic value of soluble epidermal growth factor receptor plasma concentration in advanced non-small-cell lung cancer patients

BACKGROUND

Epidermal growth factor receptor (EGFR) is overexpressed in a variety of epithelial malignancies including lung cancer. A soluble fragment of the EGFR extracellular domain (sEGFR) can be detected in the blood of patients who have non-small-cell lung cancer (NSCLC), but its clinical/ prognostic role must be further elucidated.

METHODS

sEGFR concentration was retrospectively determined by enzyme-linked immunosorbent assay in plasma samples from 308 advanced NSCLC patients (before treatment) and 109 healthy controls and correlated with clinico-pathological variables.

RESULTS

The concentration of sEGFR was lower in NSCLC patients than in controls (P < .0001). sEGFR behaves as a sensitive but not specific screening biomarker. No significant associations were observed between sEGFR concentration and demographic/clinical characteristics such as gender, Eastern Cooperative Oncology Group performance status, stage, and number or location of the metastatic sites. sEGFR was lower in patients with progressive disease or in squamous cell carcinoma compared with adenocarcinoma, but these differences were not significant. Patients with sEGFR ≤ 34.56 ng/mL showed a shorter overall survival (median 9.1 versus 12.2 months, P = .019) than others. Moreover, in multivariate analysis, sEGFR remained a significant independent prognostic marker.

CONCLUSION

Low baseline sEGFR is associated with reduced survival in advanced NSCLC. Therefore, our findings in this large cohort of patients suggest that the determination of sEGFR concentration provides valuable prognostic information.

Prognostic significance of telomerase activity and some tumor markers in non-small cell lung cancer

The prognosis of non small cell lung cancer (NSCLC) has remained disappointing over the last decades even in localized stages. Numerous prognostic factors have been investigated which might select patients for additional treatment. The objective of the current study was to assess the prognostic significance of telomerase activity, serum anti-p53 antibodies (anti-p53a), c-erbB-2 and CEA in patients with NSCLC. The study included 60 patients with histological proven NSCLC besides 60 controls (30 smokers and 30 nonsmokers). Patients were divided into four stages according to their histopathology. All patients were subjected to; determination of telomerase activity by telomeric repeat amplification protocol (TRAP) assay in tumor tissue specimens and adjacent normal lung tissues, also, determination of preoperative serum anti-p53a, c-erbB-2 and CEA. Telomerase activity was detected in 40 of 60 (66.6%) of NSCLC tissue specimens using the TRAP assay. As regard the stages, telomerase activity was positive in 5 of 15 patients (33.3%) with stage I NSCLC, in 11 of 20 patients (55%) with stage II NSCLC, in 9 of 10 patients (90%) with stage III NSCLC and in all patients (100%) with stage IV NSCLC. More cases of positive telomerase activity were observed in the group with advanced disease and in the group with poorly differentiated tumors. Telomerase activity was not detected in any normal lung tissue. The concentrations of serum anti-p53a, c-erbB-2, CEA were significantly higher in patients with NSCLC in comparison to the smoker and nonsmoker controls and their levels increased according to the stage of disease. Logistic regression test showed a relation between telomerase positivity and anti- p53a but no relation with c-erbB2, CEA. Telomerase activity was detected in most of NSCLC tissues; it was detected more frequently in advanced disease than early-stage disease. Anti-p53, c-erbB-2 and CEA were significantly higher in patients with NSCLC than controls and this increment was more evident in late stages of the disease. So, these biological markers might be useful predictors of prognosis. They may be helpful in defining groups of patients with NSCLC who could benefit from adjuvant treatments, also these markers can be used as therapeutic targets.

Immunotherapy in the landscape of new targeted treatments for non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide. Active immunotherapies and molecules targeting tyrosine kinase receptors both offer new avenues for the treatment of NSCLC. Furthermore, their combinations or their administration along with standard treatments enlarges the potential for clinical benefit. Moreover, the discovery of biomarkers predicting the response to these new therapies should allow a better selection of patients susceptible to optimally benefit from these treatments. In this paper, we review the most promising active immunotherapies, antibodies and small molecules in the context of NSCLC management, focusing on compounds in phase III clinical development.

Aspirin inhibits ErbB2 to induce apoptosis in cervical cancer cells

The use of aspirin is associated with a lower risk of many cancer types. However, there are few reports about cervical cancer. The proto-oncogene ErbB2 is overexpressed in cervical cancer, and considered as a therapeutic target. In the present study, we investigated whether aspirin had therapeutic value in cervical cancer and examined the effects of aspirin on the amplification and expression of ErbB2. To investigate the effects of aspirin on apoptosis and proliferation, we tested apoptosis by Hoechst 33258 staining and Annexin V-FITC/PI method; MTT assay and colony formation assay were used to detect proliferation. Induction of apoptosis and inhibition of proliferation were observed in HeLa cells incubated with aspirin. Western blot and immunocytochemical staining showed that aspirin induced a dose- and time-dependent reduction of ErbB2 expression that was due to proteosome-mediated degradation of this protein. To further investigate the underlying mechanism by which aspirin exerts its apoptosis effects, we studied the ErbB2 downstream cell survival signaling pathways and the expression of anti-apoptosis gene Bcl-2. We found that aspirin inhibited the activation of extracellular signal-regulated kinase (ERK) and AKT. The inhibition of Bcl-2 expression was also observed. These data reveal that aspirin significantly induces apoptosis and inhibits proliferation, which maybe via inhibiting ErbB2 downstream cell survival signaling pathways. Taken together, our article describes a novel mechanism of action for anti-tumor activity of aspirin and implicates aspirin as a novel agent for cervical cancer.