Clinical significance of serum EGFR gene mutation and serum tumor markers in predicting tyrosine kinase inhibitor efficacy in lung adenocarcinoma

Tumor marker-based RecistTM is superior to RECIST as criteria to predict the long-term benefits of targeted therapy in advanced non-small-cell lung cancer with driver gene mutations

BACKGROUND

Tyrosine kinase inhibitors (TKIs) are standard first-line treatments for advanced non-small-cell lung cancer (NSCLC) with driver gene mutations. The Response Evaluation Criteria in Solid Tumors (RECIST) are limited in predicting long-term patient benefits. A tumour marker-based evaluation criteria, RecistTM, was used to investigate the potential for assessing targeted-therapy efficacy in lung cancer treatment.

METHODS

We retrospectively analysed patients with stage IIIA-IV NSCLC and driver gene mutations, whose baseline tumour marker levels exceeded the pre-treatment cut-off value three-fold and who received TKI-targeted therapy as a first-line treatment. We compared efficacy, progression-free survival (PFS), and overall survival (OS) between RecistTM and RECIST.

FINDINGS

The median PFS and OS differed significantly among treatment-response subgroups based on RecistTM but not RECIST. The predicted 1-, 2-, and 3-year disease-progression risk, according to area under the receiver operating characteristic curve, as well as the 1-, 3-, and 5-year mortality risk, differed significantly between RecistTM and RECIST. The median PFS and OS of tmCR according to RecistTM, was significantly longer than (CR+PR) according to RECIST. Imaging analysis revealed that the ΔPFS was 11.27 and 6.17 months in the intervention and non-intervention groups, respectively, suggesting that earlier intervention could extend patients' PFS.

INTERPRETATION

RecistTM can assess targeted-therapy efficacy in patients with advanced NSCLC and driver gene mutations, along with tumour marker abnormalities. RecistTM surpasses RECIST in predicting short- and long-term patient benefits, and allows the early identification of patients resistant to targeted drugs, enabling prompt intervention and extending the imaging-demonstrated time to progression.

Clinical impact of pleural fluid carcinoembryonic antigen on therapeutic strategy and efficacy in lung adenocarcinoma patients with malignant pleural effusion

BACKGROUND/AIMS

Epidermal growth factor receptor (EGFR) mutation is important in determining the treatment strategy for advanced lung cancer patients with malignant pleural effusion (MPE). Contrary to serum carcinoembryonic antigen (S-CEA) levels, the associations between pleural fluid CEA (PF-CEA) levels and EGFR mutation status as well as between PF-CEA levels and treatment efficacy have rarely been investigated in lung adenocarcinoma patients with MPE.

METHODS

This retrospective study enrolled lung adenocarcinoma patients with MPE and available PF-CEA levels and EGFR mutation results. The patients were categorized based on PF-CEA levels: < 10 ng/mL, 10-100 ng/mL, 100-500 ng/mL, and ≥ 500 ng/mL. The association between PF-CEA levels and EGFR mutation status as well as their therapeutic impact on overall survival was compared among the four groups.

RESULTS

This study included 188 patients. PF-CEA level was found to be an independent predictor of EGFR mutation but not S-CEA level. The EGFR mutation rates were higher as the PF-CEA levels increased, regardless of cytology results or sample types. Among EGFR-mutant lung adenocarcinoma patients receiving EGFR-tyrosine kinase inhibitor (TKI) treatment, those with high PF-CEA levels had significantly better survival outcomes than those with low PF-CEA levels.

CONCLUSION

High PF-CEA levels were associated with high EGFR mutation rate and may lead to a favorable clinical outcome of EGFR-TKI treatment in EGFR-mutant lung adenocarcinoma patients with MPE. These findings highlight the importance of actively investigating EGFR mutation detection in patients with suspected MPE and elevated PF-CEA levels despite negative cytology results.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Clinical Efficacy and Safety of First- or Second-Generation EGFR-TKIs after Osimertinib Resistance for EGFR Mutated Lung Cancer: A Prospective Exploratory Study

BACKGROUND

Osimertinib monotherapy is a common treatment for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC); however, standard treatment strategies for acquired resistance to this drug have not been established. In addition, the clinical significance of first-generation (1G) or second-generation (2G) EGFR-tyrosine kinase inhibitors (TKI) in patients with EGFR-mutant NSCLC and osimertinib resistance has not yet been fully evaluated.

OBJECTIVE

We aimed to conduct a prospective multicenter observational study to evaluate the efficacy and safety of 1G and 2G EGFR-TKIs after the development of osimertinib resistance.

METHODS

Patients with EGFR-mutant NSCLC who received 1G or 2G EGFR-TKIs after developing resistance to osimertinib monotherapy were prospectively assessed at eight institutions in Japan. The primary endpoint was progression-free survival (PFS).

RESULTS

A total of 29 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. The objective response and disease control rates were 6.9% (2/29) and 58.6% (17/29), respectively. The median PFS was 1.9 months [95% confidence interval (CI): 1.3-5.3]. There was no significant difference in PFS between the 1G and 2G EGFR-TKI groups (3.7 versus 1.5 months, log-rank test p = 0.20). However, patients with normal cytokeratin 19 fragment (CYFRA 21-1) and pro-gastrin-releasing peptide (ProGRP) levels experienced longer PFS than those with elevated CYFRA 21-1 and/or ProGRP (5.5 versus 1.3 months, log-rank test p < 0.001).

CONCLUSION

Administration of 1G or 2G EGFR-TKIs after the development of osimertinib resistance has limited efficacy in patients with EGFR-mutant NSCLC. Moreover, normal CYFRA 21-1 and ProGRP levels could be promising indicators for 1G and 2G EGFR-TKI administration after osimertinib resistance development.

TRIAL REGISTRATION NUMBER

UMIN000044049.

The rational application of liquid biopsy based on next-generation sequencing in advanced non-small cell lung cancer

BACKGROUND

Plasma and tissue biopsy have both used for targeting actionable driver gene mutations in lung cancer, whose concordance is imperfect. A reliable method to predict the concordance is urgently needed to ease clinical application.

METHODS

A total of 1012 plasma samples, including 519 with paired-tissue biopsy samples, derived from lung adenocarcinoma patients were retrospectively enrolled. We assessed the associations of several clinicopathological characteristics and serum tumor markers with the concordance between plasma and tissue biopsies.

RESULTS

When carcinoembryonic antigen (CEA) levels were higher than thresholds of 15.01 ng/ml and 51.15 ng/ml, the positive predictive value of concordance reached 90% and 95%, respectively. When CEA levels were lower than thresholds of 5.19 ng/ml and 3.26 ng/mL, the negative predictive value of concordance reached 45% and 50%. The performance of CYFRA21-1 in predicting concordance was similar but inferior to CEA (AUC: 0.727 vs. 0.741, p = 0.633). The performance of CEA combined with CYFRA21-1 in predicting the concordance was similar to that of the combination of independent factors derived from the LASSO regression model (AUC: 0.796 vs. 0.818, p = 0.067). CEA (r = 0.47, p < 0.01) and CYFRA21-1 levels (r = 0.45, p < 0.05) were significantly correlated with the maximum variant allele frequency, respectively.

CONCLUSIONS

CEA combined with CYFRA21-1 could effectively predict the concordance between plasma and tissue biopsies, which could be used for evaluating the priority of plasma and tissue biopsies for gene testing to timely guide clinical applications in advanced lung adenocarcinoma patients.

Predicting EGFR mutation, ALK rearrangement, and uncommon EGFR mutation in NSCLC patients by driverless artificial intelligence: a cohort study

Background

Timely identification of epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement status in patients with non-small cell lung cancer (NSCLC) is essential for tyrosine kinase inhibitors (TKIs) administration. We aimed to use artificial intelligence (AI) models to predict EGFR mutations and ALK rearrangement status using common demographic features, pathology and serum tumor markers (STMs).

Methods

In this single-center study, demographic features, pathology, EGFR mutation status, ALK rearrangement, and levels of STMs were collected from Wuhan Union Hospital. One retrospective set (N = 1089) was used to train diagnostic performance using one deep learning model and five machine learning models, as well as the stacked ensemble model for predicting EGFR mutations, uncommon EGFR mutations, and ALK rearrangement status. A consecutive testing cohort (n = 1464) was used to validate the predictive models.

Results

The final AI model using the stacked ensemble yielded optimal diagnostic performance with areas under the curve (AUC) of 0.897 and 0.883 for predicting EGFR mutation status and 0.995 and 0.921 for predicting ALK rearrangement in the training and testing cohorts, respectively. Furthermore, an overall accuracy of 0.93 and 0.83 in the training and testing cohorts, respectively, were achieved in distinguishing common and uncommon EGFR mutations, which were key evidence in guiding TKI selection.

Conclusions

In this study, driverless AI based on robust variables could help clinicians identify EGFR mutations and ALK rearrangement status and provide vital guidance in TKI selection for targeted therapy in NSCLC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02053-2.

Establishment and Evaluation of EGFR Mutation Prediction Model Based on Tumor Markers and CT Features in NSCLC

Background

Lung cancer has become one of the leading causes of cancer deaths worldwide. EGFR gene mutation has been reported in up to 60% of Asian populations and is currently one of the main targets for genotype-targeted therapy for NSCLC.

Objective

The objective is to determine if a complex model combining serum tumor makers and computed tomographic (CT) features can predict epidermal growth factor receptor (EGFR) mutation with higher accuracy. Material and Methods. Retrospective analysis of the data of patients diagnosed with in nonsmall cell lung cancer (NSCLC) by EGFR gene testing was carried out in the Department of Thoracic Surgery, Jinan Central Hospital. Multivariate logistic regression analysis was used to determine the independent predictors of EGFR mutations, and logistic regression prediction models were developed. The subject operating characteristic curve (ROC) was plotted, and the area under the curve (AUC) was calculated to assess the accuracy and clinical application of the EGFR mutation prediction model.

Results

Logistic regression analysis identified the predictive factors of EGFR mutation including nonsmoking, high expression level of Carcinoembryonic Antigen (CEA), low expression level of cytokeratin 19 fragments (CYFRA21-1), and subsolid density containing ground-glass opacity (GGO) component. Using the results of multivariate logistic regression analysis, we built a statistically determined clinical prediction model. The AUC of the complex prediction model increased significantly from 0.735 to 0.813 (p = 0.014) when CT features are added and from 0.612 to 0.813 (p < 0.001) when serum variables are added. When P was 0.441, the sensitivity was 86.7% and the specificity was 65.8%.

Conclusion

A complex model combining serum tumor makers and CT features is more accurate in predicting EGFR mutation status in NSCLC patients than using either serum variables or imaging features alone. Our finding for EGFR mutation is urgently needed and helpful in clinical practice.

Clinicopathologic Features and Molecular Biomarkers as Predictors of Epidermal Growth Factor Receptor Gene Mutation in Non-Small Cell Lung Cancer Patients

Lung cancer ranks first in the incidence and mortality of cancer in the world, of which more than 80% are non-small cell lung cancer (NSCLC). The majority of NSCLC patients are in stage IIIB~IV when they are admitted to hospital and have no opportunity for surgery. Compared with traditional chemotherapy, specific targeted therapy has a higher selectivity and fewer adverse reactions, providing a new treatment direction for advanced NSCLC patients. Tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR-TKIs) are the widely used targeted therapy for NSCLC patients. Their efficacy and prognosis are closely related to the mutation status of the EGFR gene. Clinically, detecting EGFR gene mutation is often limited by difficulty obtaining tissue specimens, limited detecting technology, and economic conditions, so it is of great clinical significance to find indicators to predict EGFR gene mutation status. Clinicopathological characteristics, tumor markers, liquid biopsy, and other predictors are less invasive, economical, and easier to obtain. They can be monitored in real-time, which is supposed to predict EGFR mutation status and provide guidance for the accurate, individualized diagnosis and therapy of NSCLC patients. This article reviewed the correlation between the clinical indicators and EGFR gene mutation status in NSCLC patients.

Retrospective analysis of eleven gene mutations, PD-L1 expression and clinicopathological characteristics in non-small cell lung cancer patients

OBJECTIVES

To investigate the associations among expression of programmed cell death ligand 1 (PD-L1), eleven mutated genes, and clinicopathological characteristics in 273 patients with non-small cell lung cancer (NSCLC).

METHODS

We retrospectively examined tumor PD-L1 expression in 247 surgically resected primary and 26 advanced NSCLC patients by immunohistochemistry using SP263 antibody assay. Gene mutations of EGFR, TP53, KRAS, PIK3CA, ERBB2, MET, RET, ALK, BRAF, ROS1, and APC were examined by NGS sequence. Data analysis was carried out using SPSS 22.0. The associations among PD-L1 expression, eleven mutated genes and clinicopathological characteristics were assessed by univariate and multivariate analysis.

RESULTS

Among the total 273 patients, 68 (24.9%) patients were positive for PD-L1 expression. Data showed that mutated rate of EGFR gene was the highest with 63.0% (172/273), followed by TP53 (11.7%, 32/273) and KRAS (5.5%, 15/273). The female, non-smoker, and patients with adenocarcinoma (ADC) were more likely to have EGFR mutations. Multivariate logistic regression showed that PD-L1 expression was significantly associated with Non-ADC, lymphatic invasion, EGFR wild type and TP53 mutation (p = 0.041, <0.001, 0.004 and 0.014, respectively). Moreover, PD-L1 expression in adenocarcinoma was associated with lymphatic invasion, mutation of TP53 and KRAS gene (p = 0.012, <0.025 and 0.041, respectively).

CONCLUSIONS

Mutations of EGFR, KRAS and TP53 should be routinely detected in clinical practice to better guide the immunotherapy for NSCLC patients. Future investigations are warranted to illustrate the potential mechanisms between driver mutations and PD-L1 expression for guiding immunotherapy in patients with NSCLC.

Spatially-resolved dual-potential sandwich electrochemiluminescence immunosensor for the simultaneous determination of carbohydrate antigen 19-9 and carbohydrate antigen 24-2

A new electrochemiluminescence (ECL) immunosensor based on spatially-resolved dual-potential technology was designed for the simultaneous determination of carbohydrate antigen 19-9 (CA 19-9) and carbohydrate antigen 24-2 (CA 242). Luminol-AgNPs@ZIF-67 was used as the anodic probe, and Pt nanoparticle-functionalized graphitic carbon nitride nanosheets (g-C₃N₄@PtNPs) were used as the cathodic probe. Two spatially-resolved areas on the dual-disk glassy carbon electrode (DDGCE) were modified with a AuNPs film by electrodeposition to improve the conductivity of the sensing interface. By recording the ECL responses at two different excitation potentials, the linear range for CA 19-9 was determined to be 0.0001-10 U/mL, with a limit of detection of 31 μU/mL. The linear range for CA 242 was 0.0005-10 U/mL, with a limit of detection of 0.16 mU/mL. Moreover, the ECL immunosensor possessed high selectivity and stability and successfully detected CA 19-9 and CA 242 in real samples. This immunosensor provides a new platform for clinical immunoassays.

Nano-silica embedded polydimethylsiloxane on interdigitated sensor as adhesive polymer for detecting lung cancer mutation

Non-small cell lung cancer (NSCLC) incited by epidermal growth factor receptor (EGFR) mutation makes up ∼85% of lung cancer diagnosed and death cases worldwide. The presented study introduced an alternative approach in detecting EGFR mutation using nano-silica integrated with polydimethylsiloxane (PDMS) polymer on interdigitated electrode (IDE) sensor. A 400 μm gap-sized aluminum IDE was modified with nano-polymer layer, which was made up of silica nanoparticles and PDMS polymer. IDE and PDMS-coated IDE (PDMS/IDE) were imaged using electron microscopes that reveals its smooth and ideal sensor morphology. The nano-silica-integrated PDMS/IDE surface was immobilized with EGFR probe and target to specify the lung cancer detection. The sensor specificity was justified through the insignificant current readouts with one-base mismatch and noncomplementary targets. The sensitivity of nano-silica-integrated PDMS/IDE was examined with mutant target spiked in human serum, where the resulting current affirms the detection of EGFR mutation. Based on the slope of the calibration curve, the sensitivity of nano-silica-integrated PDMS/IDE was 2.24E-9 A M^-1 . The sensor recognizes EGFR mutation lowest at 1 aM complementary mutant target; however, the detection limit obtained based on 3σ calculation is 10 aM with regression value of 0.97.

Aluminosilicate Nanocomposite on Genosensor: A Prospective Voltammetry Platform for Epidermal Growth Factor Receptor Mutant Analysis in Non-small Cell Lung Cancer

Lung cancer is one of the most serious threats to human where 85% of lethal death caused by non-small cell lung cancer (NSCLC) induced by epidermal growth factor receptor (EGFR) mutation. The present research focuses in the development of efficient and effortless EGFR mutant detection strategy through high-performance and sensitive genosensor. The current amplified through 250 µm sized fingers between 100 µm aluminium electrodes indicates the voltammetry signal generated by means of the mutant DNA sequence hybridization. To enhance the DNA immobilization and hybridization, ∼25 nm sized aluminosilicate nanocomposite synthesized from the disposed joss fly ash was deposited on the gaps between aluminium electrodes. The probe, mutant (complementary), and wild (single-base pair mismatch) targets were designed precisely from the genomic sequences denote the detection of EGFR mutation. Fourier-transform Infrared Spectroscopy analysis was performed at every step of surface functionalization evidences the relevant chemical bonding of biomolecules on the genosensor as duplex DNA with peak response at 1150 cm⁻¹ to 1650 cm⁻¹. Genosensor depicts a sensitive EGFR mutation as it is able to detect apparently at 100 aM mutant against 1 µM DNA probe. The insignificant voltammetry signal generated with wild type strand emphasizes the specificity of genosensor in the detection of single base pair mismatch. The inefficiency of genosensor in detecting EGFR mutation in the absence of aluminosilicate nanocomposite implies the insensitivity of genosensing DNA hybridization and accentuates the significance of aluminosilicate. Based on the slope of the calibration curve, the attained sensitivity of aluminosilicate modified genosensor was 3.02E-4 A M⁻¹. The detection limit of genosensor computed based on 3σ calculation, relative to the change of current proportional to the logarithm of mutant concentration is at 100 aM.

THAP7 promotes cell proliferation by regulating the G1/S phase transition via epigenetically silencing p21 in lung adenocarcinoma

PURPOSE

Lung adenocarcinoma (LUAD) is one of the most common cancers worldwide. The THanatos-Associated Proteins (THAP) family plays an essential role in multiple cancers. However, the role of THAP7 in cancers has remained elusive.

METHODS

THAP7 expression status in LUAD tissues was analysed by using the Oncomine database and qRT-PCR, and its expression level in LUAD cell lines was detected by qRT-PCR and Western blotting. The role of THAP7 in LUAD cells was determined by proliferation, colony formation, and cell cycle analyses. In vivo role of THAP7 was studied on xenograft models. Luciferase reporter assays and chromatin immunoprecipitation (ChIP) were used to determine the activity and acetylation of the p21 promoter.

RESULTS

THAP7 expression was increased in LUAD tissues and cell lines. Moreover, the high expression of THAP7 was correlated with poor prognosis. The overexpression of THAP7 accelerated the G1/S phase transition and promoted tumour growth both in vitro and in vivo. A mechanistic study revealed that THAP7 reduced the acetylation of histone H3 on the p21 promoter to suppress p21 transcription.

CONCLUSION

For the first time, we demonstrated the function of THAP7 in LUAD, and our findings suggested that THAP7 may be a potential molecular therapy target in LUAD.