Value of serum tumor markers for predicting EGFR mutations and positive ALK expression in 1089 Chinese non-small-cell lung cancer patients: A retrospective analysis

The clinicopathological features and possible physiological mechanisms of only the EGFR-T790M primary mutation in patients with lung adenocarcinoma

BACKGROUND

The treatment of non-small cell lung cancer (NSCLC) patients can be complicated by the presence of the EGFR-T790M mutation. Although primary or secondary EGFR-T790M mutations have been extensively studied worldwide, there are few reports on the clinicopathological characteristics and physiological mechanisms of lung adenocarcinoma (LUAD) with only the EGFR-T790M primary mutation.

METHODS

The clinical data of all LUAD patients with only the EGFR-T790M primary mutation were collected. Immunohistochemical staining was performed on cell cycle-related proteins, targeted therapy indicators, and prognosis-related proteins in the specimens obtained from puncture biopsies or surgeries.

OBJECTIVES

The aim of this study is to analyze the clinicopathological features and possible physiological mechanisms of only the EGFR-T790M primary mutation in LUAD, and to offer recommendations for clinical management.

RESULTS

Two patients who have only the T790M de novo mutation were both female (2/12,928, 0.02%). β-catenin and Cyclin D1 were both highly expressed. In case 1, IHC results showed a positive Ki67 and mutant P53 and there was a significant increase in serum CYFRA 21-1. Third-generation of EGFR TKIs resulted in a partial response (PR) time of less than 8 months in case 1. In case 2, the patient underwent surgical resection and adjuvant chemotherapy, resulting in a progression-free survival (PFS) time of 25 months.

CONCLUSION

The results suggest that abnormal activation of the Wnt signaling pathway may be specifically associated with the EGFR-T790M primary mutation in LUAD. Furthermore, it has been observed that patients with significant Ki67, mutant P53, and CYFRA 21-1 expression tend to have a poor prognosis.

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.

Analysis of variation of serum CEA, SCC, CYFRA21-1 in patients with lung cancer and their diagnostic value with EBUS-TBNA

Background

To explore the variation of serum carcinoembryonic antigen (CEA), cytokeratin 19 fragment (CYFRA21-1), and squamous cell carcinoma (SCC) antigen in patients with lung cancer (LC) and their diagnostic value with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA).

Methods

This study examined the diagnostic value of serum tumor marker testing and EBUS-TBNA joint detection for LC in 150 patients with suspected LC.

Results

Compared to benign patients, the serum levels of CYFRA21-1, SCC, and CEA in LC were higher (P<0.05). In patients with squamous cell carcinoma (LSCC), small cell lung cancer (SCLC), and lung adenocarcinoma, lung adenocarcinoma had higher serum CEA levels (P<0.05). In comparison, LSCC patients had higher serum SCC and CYFRA21-1 levels (P<0.05). As compared to each index detected alone, the AUC of combined detection of each index to diagnose LC and identify pathological types of LC was elevated.

Conclusions

The clinical significance of serum CYFRA21-1, SCC, and CEA conjugated with EBUS-TBNA is demonstrated for diagnostic purposes and identification of LC pathological types.

Comparison of clinical and MRI features of brain metastases between ALK+ and ALK- NSCLC

BACKGROUND

Non-small-cell lung cancer (NSCLC) is the primary cause of brain metastases (BM). This study aimed to investigate differences in clinical and magnetic resonance imaging (MRI) features of BM between anaplastic lymphoma kinase (ALK) gene fusion (ALK+) and ALK wild-type (ALK-) NSCLC, and to preliminarily assess the efficacy of radiotherapy for treating BM.

METHODS

A retrospective analysis included 101 epidermal growth factor receptor (EGFR)- NSCLC patients with BM: 41 with ALK gene fusion and 60 being ALK-. The brain MRI and clinical features were compared between different ALK status using the multivariate analysis, and a nomogram was constructed to predict ALK gene fusion. Fifty-six patients who did not undergo cerebral surgery and had complete pre- and post- treatment data were further divided based on whether they received radiotherapy. Log-rank test was used to compare the short-term effect of treatment between the two groups under different genotypes.

RESULTS

ALK+ BM exhibited decreased peritumoral brain edema size, lower peritumoral brain edema index (PBEI), and a more homogeneous contrast enhancement pattern compared to ALK- BM. Age (OR = 1.04; 95%CI: 1.02-1.06), time to BM (OR = 1.50; 95% CI: 1.04-2.14), PBEI (OR = 1.26; 95% CI: 0.97-1.62), smoking status (smoking index >400 vs. non-smoking status: OR = 1.42; 95% CI: 0.99-2.04) and contrast enhancement pattern (OR = 1.89; 95% CI: 1.28-2.78) were associated with ALK gene fusion. A nomogram based on these variables demonstrated acceptable predictive efficiency (AUC = 0.844). In the ALK+ group, patients who received radiotherapy did not show increased disease control rate (DCR) or progression-free survival (PFS). In contrast, in the ALK- group, those who received radiotherapy had improved objective response rate (ORR), DCR, and PFS compared to those who were only treated with systemic therapy.

CONCLUSIONS

The clinical and MRI features of BM can indicate the status of ALK in NSCLC. In the ALK- group, patients who received radiotherapy showed higher ORR, DCR, and PFS compared to those who did not.

The predictive value of serum tumor markers for EGFR mutation in non-small cell lung cancer patients with non-stage IA

Objective

The predictive value of serum tumor markers (STMs) in assessing epidermal growth factor receptor (EGFR) mutations among patients with non-small cell lung cancer (NSCLC), particularly those with non-stage IA, remains poorly understood. The objective of this study is to construct a predictive model comprising STMs and additional clinical characteristics, aiming to achieve precise prediction of EGFR mutations through noninvasive means.

Materials and methods

We retrospectively collected 6711 NSCLC patients who underwent EGFR gene testing. Ultimately, 3221 stage IA patients and 1442 non-stage IA patients were analyzed to evaluate the potential predictive value of several clinical characteristics and STMs for EGFR mutations.

Results

EGFR mutations were detected in 3866 patients (57.9 %) of all NSCLC patients. None of the STMs emerged as significant predictor for predicting EGFR mutations in stage IA patients. Patients with non-stage IA were divided into the study group (n = 1043) and validation group (n = 399). In the study group, univariate analysis revealed significant associations between EGFR mutations and the STMs (carcinoembryonic antigen (CEA), squamous cell carcinoma antigen (SCC), and cytokeratin-19 fragment (CYFRA21-1)). The nomogram incorporating CEA, CYFRA 21-1, pathology, gender, and smoking history for predicting EGFR mutations with non-stage IA was constructed using the results of multivariate analysis. The area under the curve (AUC = 0.780) and decision curve analysis demonstrated favorable predictive performance and clinical utility of nomogram. Additionally, the Random Forest model also demonstrated the highest average C-index of 0.793 among the eight machine learning algorithms, showcasing superior predictive efficiency.

Conclusion

CYFRA21-1 and CEA have been identified as crucial factors for predicting EGFR mutations in non-stage IA NSCLC patients. The nomogram and 8 machine learning models that combined STMs with other clinical factors could effectively predict the probability of EGFR mutations.

Correlation between carcinoembryonic antigen (CEA) expression and EGFR mutations in non-small-cell lung cancer: a meta-analysis

OBJECTIVES

The purpose of this meta-analysis was to investigate the relationship between serum carcinoembryonic antigen (CEA) expression and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC).

METHODS

Databases such as PubMed, Cochrane, EMBASE and Google Scholar were systematically searched to identify studies assessing the association of serum CEA expression with EGFR mutations. Across 19 studies, 4168 patients were included between CEA expression and EGFR mutations odds ratio (OR) conjoint analysis of correlations.

RESULTS

Compared with CEA-negative NSCLC, CEA-positive tumors had an increased EGFR mutation rate (OR = 1.85, 95% confidence interval: 1.48-2.32, P < 0.00001). This association was observed in both stage IIIB/IV patients (OR = 1.60, 95% CI: 1.18-2.15, P = 0.002) and stage I-IIIA (OR = 1.67, 95% CI: 1.01-2.77, P = 0.05) patients. In addition, CEA expression was associated with exon 19 (OR = 1.97, 95% CI: 1.25-3.11, P = 0.003) and exon 21 (OR = 1.51, 95% CI: 1.07-2.12, P = 0.02) EGFR mutations. In ADC pathological type had also showed the correlation (OR = 1.84, 95% CI: 1.31-2.57, P = 0.0004).

CONCLUSIONS

This meta-analysis indicated that serum CEA expression was associated with EGFR mutations in NSCLC patients. The results of this study suggest that CEA level may play a predictive role in the EGFR mutation status of NSCLC patients. Detecting serum CEA expression levels can give a good suggestion to those patients who are confused about whether to undergo EGFR mutation tests. Moreover, it may help better plan of the follow-up treatment.

Distinction of ALK fusion gene- and EGFR mutation-positive lung cancer with tumor markers

BACKGROUND

It is difficult to predict gene mutations individually based on clinical background alone. Tumor markers may help to predict each gene mutation. Identifying tumor markers that can predict gene mutation will facilitate timely genetic testing and intervention.

METHODS

We selected 134 cases of advanced or recurrent ALK-positive and 172 cases of advanced or recurrent EGFR-positive lung cancer from our clinical database. The cutoff values for the tumor markers were defined as 5.0 ng/mL or higher for carcinoembryonic antigen (CEA) and 3.5 ng/mL or higher for soluble fragment of cytokeratin 19 (CYFRA21-1) in accordance with the institutional standards. A positive CYFRA21-1:CEA ratio was defined as 0.7 or higher.

RESULTS

The CEA-positivity rate was 49% for ALK-positive lung cancers and 73% for EGFR-positive lung cancers, which was significantly different (p < 0.001). The CYFRA21-1 positivity rate was significantly higher in ALK-positive lung cancer (36%) compared with EGFR-positive lung cancer (23%) (p = 0.034). The median CYFRA21-1:CEA ratio was 0.395 for the ALK group, which was significantly higher compared with 0.098 for the EGFR group (p < 0.001). These trends were similar when excluding histology other than adenocarcinoma. The median time-to-treatment failure (TTF) for initial tyrosine kinase inhibitor (TKI) therapy was 308 days for the high CYFRA21-1:CEA ratio group and 617 days for the low CYFRA21-1:CEA ratio group for ALK-positive lung cancer (p = 0.100).

CONCLUSIONS

A higher proportion of patients with ALK-positive lung cancer were CYFRA21-1 positive and had higher CYFRA21-1:CEA ratios compared with EGFR-positive lung cancer patients.

Covalent inhibition of epidermal growth factor receptor using a long-lived iridium(III)-afatinib probe

The overexpression and overactivation of epidermal growth factor receptor (EGFR) are frequently observed in human cancers, including squamous cell carcinoma and adenocarcinoma. In this study, a covalent EGFR probe was developed by conjugating afatinib to an iridium(III) scaffold. Complex 1 showed enhanced luminescence in living epidermoid squamous carcinoma A431 cells compared to other cell lines, via engaging EGFR as confirmed via CETSA and knockdown experiments. Moreover, complex 1 inhibited downstream targets of EGFR in cellulo with repression persisting after removal of the complex, indicating an irreversible mode of inhibition. Finally, complex 1 showed potent antiproliferative activity against A431 cells with comparable potency to afatinib alone. To our knowledge, complex 1 is the first EGFR covalent inhibitor based on an iridium scaffold reported in the literature, with the potential to be further explored as a theranostic agent in the future.

Machine learning-based radiomics strategy for prediction of acquired EGFR T790M mutation following treatment with EGFR-TKI in NSCLC

The epidermal growth factor receptor (EGFR) Thr790 Met (T790M) mutation is responsible for approximately half of the acquired resistance to EGFR-tyrosine kinase inhibitor (TKI) in non-small-cell lung cancer (NSCLC) patients. Identifying patients at diagnosis who are likely to develop this mutation after first- or second-generation EGFR-TKI treatment is crucial for better treatment outcomes. This study aims to develop and validate a radiomics-based machine learning (ML) approach to predict the T790M mutation in NSCLC patients at diagnosis. We collected retrospective data from 210 positive EGFR mutation NSCLC patients, extracting 1316 radiomics features from CT images. Using the LASSO algorithm, we selected 10 radiomics features and 2 clinical features most relevant to the mutations. We built models with 7 ML approaches and assessed their performance through the receiver operating characteristic (ROC) curve. The radiomics model and combined model, which integrated radiomics features and relevant clinical factors, achieved an area under the curve (AUC) of 0.80 (95% confidence interval [CI] 0.79-0.81) and 0.86 (0.87-0.88), respectively, in predicting the T790M mutation. Our study presents a convenient and noninvasive radiomics-based ML model for predicting this mutation at the time of diagnosis, aiding in targeted treatment planning for NSCLC patients with EGFR mutations.

Identification of EGFR mutation status in male patients with non-small-cell lung cancer: role of 18F-FDG PET/CT and serum tumor markers CYFRA21-1 and SCC-Ag

BACKGROUND

The high incidence of epidermal growth factor receptor (EGFR) mutations is usually found in female patients with lung adenocarcinoma who have never-smoked. However, reports concerning male patients are scarce. Thus, this study aimed to explore a novel approach based on ¹⁸F-fluoro-2-deoxy-2-deoxyglucose (¹⁸F-FDG) PET/CT and serum tumor markers (STMs) to determine EGFR mutation status in male patients with non-small-cell lung cancer (NSCLC).

METHODS

A total of 121 male patients with NSCLC were analyzed between October 2019 and March 2022. All patients underwent ¹⁸F-FDG PET/CT scan before treatment and monitored 8 STMs (cytokeratin 19 fragment [CYFRA21-1], squamous cell carcinoma-related antigen [SCC-Ag], carcinoembryonic antigen [CEA], neuron-specific enolase [NSE], carbohydrate antigen [CA] 50, CA125, CA72-4, and ferritin). A comparison was done between EGFR mutant and wild-type patients in terms of the maximum standardized uptake value of primary tumors (pSUV_max) and 8 STMs. We performed receiver operating characteristic (ROC) curve and multiple logistic regression analyses to determine predictors for EGFR mutation status.

RESULTS

EGFR mutations were detected in 39 patients (32.2%). Compared with patients with EGFR wild-type, EGFR-mutant patients had lower concentrations of serum CYRFA21-1 (2.65 vs. 4.01, P = 0.002) and SCC-Ag (0.67 vs. 1.05, P = 0.006). No significant differences of CEA, NSE, CA 50, CA125, CA72-4 and ferritin were found between the two groups. The presence of EGFR mutations was significantly associated with low pSUV_max (< 8.75), low serum SCC-Ag (< 0.79 ng/mL) and CYFRA21-1 (< 2.91 ng/mL) concentrations. The area under ROC curve values were 0.679, 0.655, 0.685 and 0.754, respectively, for low CYFRA21-1, SCC-Ag, pSUV_max and the combination of these three factors.

CONCLUSIONS

We demonstrated that low concentrations of CYFRA21-1 and SCC-Ag, as well as low pSUV_max, were associated with EGFR mutations, and that the combination of these factors resulted in a higher differentiation of EGFR mutation status in male patients with NSCLC.

Prognostic value of CYFRA 21 - 1 and Ki67 in advanced NSCLC patients with wild-type EGFR

BACKGROUND

The prognostic value of cytokeratin 19 fragment (CYFRA 21 - 1) and Ki67 in advanced non-small cell lung cancer (NSCLC) patients with wild-type epidermal growth factor receptor (EGFR) remains to be explored.

METHODS

In this study, 983 primary NSCLC patients from January 2016 to December 2019 were retrospectively reviewed. Finally, 117 advanced NSCLC patients with wild-type EGFR and 37 patients with EGFR mutation were included and prognostic value of CYFRA 21 - 1 and Ki67 were also identified.

RESULTS

The patients age, smoking history and the Eastern Corporative Oncology Group (ECOG) performance scores were significantly different between CYFRA21-1 positive and negative groups (p < 0.05), while no significant differences were found in Ki67 high and low groups. The results of over survival (OS) demonstrated that patients with CYFRA21-1 positive had markedly shorter survival time than CYFRA21-1 negative (p < 0.001, For whole cohorts; p = 0.002, For wild-type EGFR). Besides, patients with wild-type EGFR also had shorter survival times than Ki67 high group. Moreover, In CYFRA 21 - 1 positive group, patients with Ki67 high had obviously shorter survival time compared to patients with Ki67 low (median: 24vs23.5 months; p = 0.048). However, Ki67 could not be used as an adverse risk factor for patients with EGFR mutation. Multivariate cox analysis showed that age (HR, 1.031; 95%CI, 1.003 ~ 1.006; p = 0.028), Histopathology (HR, 1.760; 95%CI,1.152 ~ 2.690; p = 0.009), CYFRA 21 - 1 (HR, 2.304; 95%CI,1.224 ~ 4.335; p = 0.01) and Ki67 (HR, 2.130; 95%CI,1.242 ~ 3.652; p = 0.006) served as independent prognostic risk factor for advanced NSCLC patients.

CONCLUSIONS

Our finding indicated that CYFRA 21 - 1 was an independent prognostic factor for advanced NSCLC patients and Ki67 status could be a risk stratification marker for CYFRA 21 - 1 positive NSCLC patients with wild-type EGFR.

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.

Increased levels of N6-methyladenosine in peripheral blood RNA: a perspective diagnostic biomarker and therapeutic target for non-small cell lung cancer

OBJECTIVES

Due to lack of effective biomarkers for non-small cell lung cancer (NSCLC), many patients are diagnosed at an advanced stage, which leads to poor prognosis. Dysregulation of N6-methyladenosine (m⁶A) RNA contributes significantly to tumorigenesis and tumor progression. However, the diagnostic value of m⁶A RNA status in peripheral blood to screen NSCLC remains unclear.

METHODS

Peripheral blood samples from 152 NSCLC patients and 64 normal controls (NCs) were applied to assess the m⁶A RNA levels. Bioinformatics and qRT-PCR analysis were performed to identify the specific immune cells in peripheral blood cells and investigate the mechanism of the alteration of m⁶A RNA levels.

RESULTS

Robust elevation of m⁶A RNA levels of peripheral blood cells was exhibited in the NSCLC group. Moreover, the m⁶A levels increased as NSCLC progressed, and reduced after treatment. The m⁶A levels contained area under the curve (AUC) was 0.912, which was remarkably greater than the AUCs for CEA (0.740), CA125 (0.743), SCC (0.654), and Cyfra21-1 (0.730). Furthermore, the combination of these traditional biomarkers with m⁶A levels elevated the AUC to 0.970. Further analysis established that the expression of m⁶A erasers FTO and ALKBH5 were both markedly reduced and negatively correlated with m⁶A levels in peripheral blood of NSCLC. Additionally, GEO database and flow cytometry analysis implied that FTO and ALKBH5 attributes to peripheral CD4⁺ T cells proportion and activated the immune functions of T cells.

CONCLUSIONS

These findings unraveled that m⁶A RNA of peripheral blood immune cells was a prospective biomarker for the diagnosis of NSCLC.

[Research Progress of Treatment for NSCLC in Young Patients]

Non-small cell lung cancer (NSCLC) young patients (≤45 years old), despite their low prevalence, have unique clinical and pathological features. Its morbidity has been on the rise in recent years. With the concept of individualized lung cancer treatment, related researches are gradually gaining attention. In addition, the treatment response and prognosis in NSCLC young patients are different from older patients, so the study of NSCLC young patients is of great clinical significance. This article reviews the clinical manifestations, treatment and prognosis of NSCLC young patients.
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Association between squamous cell carcinoma antigen level and EGFR mutation status in Chinese lung adenocarcinoma patients

Background

To investigate the association between squamous cell carcinoma antigen (SCCAg) level and epidermal growth factor receptor (EGFR) mutation status in Chinese lung adenocarcinoma patients.

Methods

We retrospectively analyzed 293 patients with lung adenocarcinoma, divided into EGFR mutant group (n = 178) and EGFR wild‐type group (n = 115). The general data and laboratory parameters of the two groups were compared. We used univariable and multivariable logistic regression to analyze the association between SCCAg level and EGFR mutation. Generalized additive model was used for curve fitting, and a hierarchical binary logistic regression model was used for interaction analysis.

Results

Squamous cell carcinoma antigen level in the EGFR wild‐type group was significantly higher than that in the mutant group (p < 0.001). After adjusting for confounding factors, we found that elevated SCCAg was associated with a lower probability of EGFR mutation, with an OR of 0.717 (95% CI: 0.543–0.947, p = 0.019). For the tripartite SCCAg groups, the increasing trend of SCCAg was significantly associated with the decreasing probability of EGFR mutation (p for trend = 0.015), especially for Tertile 3 versus Tertile 1 (OR = 0.505; 95% CI: 0.258–0.986; p = 0.045). Curve fitting showed that there was an approximate linear negative relationship between continuous SCCAg and EGFR mutation probability (p = 0.020), which was first flattened and then decreased (p < 0.001). The association between the two was consistent among different subgroups, suggesting no interaction (all p > 0.05).

Conclusion

There is a negative association between SCCAg level and EGFR mutation probability in Chinese lung adenocarcinoma patients.

Effects of Afatinib on Development of Non-Small-Cell Lung Cancer by Regulating Activity of Wnt/β-Catenin Signaling Pathway

Lung cancer has been one of the deadliest cancers in the world. Afatinib is an ErbB family irreversible blocker that was authorized by the FDA and EMA in 2013 for the treatment of advanced EGFR mutation-positive NSCLC. Therefore, we aim to discover the impact of Afatinib on the development of non-small-cell lung cancer (NSCLC) via modulating the Wnt/β-catenin signaling pathway. The objective remission rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) in 22 patients with clinical NSCLC were analyzed as follow-up targets after Afatinib therapy. The differences between the effects of Afatinib treatment and DDP+PEM treatment for conventional chemotherapy were used to measure NSCLC cell proliferation by CCK-8 assay; then those on NSCLC apoptosis were measured by flow cytometry. Patients who received Afatinib had better ORR, DCR, PFS, and OS than those in the conventional chemotherapy group. Meanwhile, CCK-8 assay shows that the number of colony formation of NSCLC cells after Afatinib treatment was less than that in the DDP+PEM group. And NSCLC apoptosis was higher than that in the DDP+PEM group. Phenomenologically, experimental results show that Afatinib can affect the behaviors of NSCLC cells. After treating NSCLC cells with Afatinib, the protein expressions of three serum tumor markers (CEA, CA125, and CY-FRA21-1) were detected by Western blotting, with the findings indicating that the protein expressions in NSCLC cells treated with Afatinib were lower than those of the DDP+PEM group, which indicates that Afatinib treatment can reduce the expressions of tumor markers, and inhibit the development of tumors. Afatinib can affect the progression of NSCLC by modulating the Wnt/β-catenin signaling pathway's activity as a new potential therapeutic drug for NSCLC.

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.

Machine Learning-Based Radiomics for Prediction of Epidermal Growth Factor Receptor Mutations in Lung Adenocarcinoma

Identifying an epidermal growth factor receptor (EGFR) mutation is important because EGFR tyrosine kinase inhibitors are the first-line treatment of choice for patients with EGFR mutation-positive lung adenocarcinomas (LUAC). This study is aimed at developing and validating a radiomics-based machine learning (ML) approach to identify EGFR mutations in patients with LUAC. We retrospectively collected data from 201 patients with positive EGFR mutation LUAC (140 in the training cohort and 61 in the validation cohort). We extracted 1316 radiomics features from preprocessed CT images and selected 14 radiomics features and 1 clinical feature which were most relevant to mutations through filter method. Subsequently, we built models using 7 ML approaches and established the receiver operating characteristic (ROC) curve to assess the discriminating performance of these models. In terms of predicting EGFR mutation, the model derived from radiomics features and combined models (radiomics features and relevant clinical factors) had an AUC of 0.79 (95% confidence interval (CI): 0.77-0.82), 0.86 (0.87-0.88), respectively. Our study offers a radiomics-based ML model using filter methods to detect the EGFR mutation in patients with LUAC. This convenient and low-cost method may be of help to noninvasively identify patients before obtaining tumor sample for molecule testing.

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.

Establishment of Multiple Parameter Reference Intervals for Different Age Groups in Qingdao, China

In this article, we have explored the establishment of multiple parameter reference intervals for different age groups in Qingdao, China. According to the age of subjects, the healthy adult population of different ages in Qingdao was randomly selected as the research object. According to the age of subjects, they were divided into 18–24-year-old, 25–39-year-old, 40–49-year-old, 50–64-year-old, and >65-year-old groups, respectively. The sample size of each age group was 120 male and female samples, and 60 male and female samples of >65-year-old subjects were selected. The data of subjects were collected, a questionnaire survey was completed, serum samples were collected, and the parameters of male and female groups of different ages in Qingdao were compared. The parameters of the male and female groups were compared in the same age group. The reference intervals of parameters of the male and female groups were compared in different ages. There were significant differences in the levels of FBG, AST, BUN, Cr, Hb, FT3, TT3, FT4, TT4, VB12, PROG, CYFRA 21-1, and SCC among men of different ages (P < 0.05). Among them, the levels of FBG, AST, BUN, VB12, CYFRA 21-1, and SCC in >65-year-old men were significantly higher than those in 18–24-years-old men, and the levels of Hb, FT3, TT3, FT4, TT4 in >65-year-old men were significantly lower than those in 18–24-year-old men (P < 0.05). There were significant differences in FBG, ALT, AST, BUN, Cr, Hb, TSH, FT3, TT3, FT4, TT4, VB12, CYFRA 21-1, anti-TPO, and ferritin levels among women of different ages (P < 0.05). Among them, the levels of FBG, ALT, AST, BUN, and ferritin in women aged >65 were significantly higher than those in women aged 18–24 (P < 0.05). The levels of FBG, ALT, AST, BUN, Cr, Hb, FT3, TT3, FT4, TT4, and VB12 in women aged 50–64 were significantly higher than those in women aged 25–39, and the levels of TSH were significantly lower than those in women aged 25–39 and significantly higher than those of the female population aged 40–49 (P < 0.05). The levels of ALT, AST, BUN, Cr, Hb, FT3, TT3, FT4 and ferritin in males aged 18–24 were significantly higher than those in females, while the levels of TSH, VB12 in males aged 18–24 were significantly lower than those in females (P < 0.05). The levels of FBG, ALT, AST, BUN, Cr, Hb, FT3, TT3, FT4 and ferritin in males aged 25–39 were significantly higher than those in females, while the levels of TSH, VB12, CYFRA 21-1 in males aged 25–39 were significantly lower than those in females (P < 0.05). The levels of FBG, ALT, AST, BUN, Cr, Hb, FT3, TT3, FT4, CYFRA 21-1 and ferritin in males aged 40-49 were significantly higher than those in females, and the levels of VB12, anti-TG, anti-TPO in males aged 40-49 were significantly lower than those in females (P < 0.05). The levels of FBG, ALT, BUN, Cr, FT3, TT3 and ferritin in males aged 50-64 were significantly higher than those in females, while the levels of VB12, anti-TG in males aged 50-64 were significantly lower than those in females (P < 0.05). The levels of Cr, Hb and ferritin in males >65 years old were significantly higher than those in females (P < 0.05). The reference intervals of various parameters are different among different ages and genders. The establishment of multiparameter reference intervals for different age groups in Qingdao, China, is of great significance for the early diagnosis and evaluation of various diseases in Qingdao, China, so as to reduce the missed diagnosis rate of diseases and improve people's quality of life.

Development and Validation of a Concise Prediction Scoring System for Asian Lung Cancer Patients with EGFR Mutation Before Treatment

Purpose We aimed to determine the epidermal growth factor receptor (EGFR) genetic profile of lung cancer in Asians, and develop and validate a non-invasive prediction scoring system for EGFR mutation before treatment. Methods This was a single-center retrospective cohort study using data of patients with lung cancer who underwent EGFR detection (n = 1450) from December 2014 to October 2020. Independent predictors were filtered using univariate and multivariate logistic regression analyses. According to the weight of each factor, a prediction scoring system for EGFR mutation was constructed. The model was internally validated using bootstrapping techniques and temporally validated using prospectively collected data (n = 210) between November 2020 and June 2021.Results In 1450 patients with lung cancer, 723 single mutations and 51 compound mutations were observed in EGFR. Thirty-nine cases had two or more synchronous gene mutations. We developed a scoring system according to the independent clinical predictors and stratified patients into risk groups according to their scores: low-risk (score <4), moderate-risk (score 4-8), and high-risk (score >8) groups. The C-statistics of the scoring system model was 0.754 (95% CI 0.729-0.778). The factors in the validation group were introduced into the prediction model to test the predictive power of the model. The results showed that the C-statistics was 0.710 (95% CI 0.638-0.782). The Hosmer–Lemeshow goodness-of-fit showed that χ² = 6.733, P = 0.566. Conclusions The scoring system constructed in our study may be a non-invasive tool to initially predict the EGFR mutation status for those who are not available for gene detection 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.

Concomitant genetic alterations are associated with plasma D-dimer level in patients with non-small cell lung cancer

Objective: D-dimer is correlated to the poor prognosis of non-small cell lung cancer. The study aimed to investigate the association between plasma D-dimer and concomitant mutations in non-small cell lung cancer. Methods: A total of 517 non-small cell lung cancer patients were recruited and tested for ALK, BRAF, EGFR, HER2/ERBB2, KRAS, MET, PIK3CA, RET and ROS1 mutation by next-generation sequencing. Multiple gene mutation information, clinical baseline data and laboratory test data were analyzed statistically. Results: All patients were divided into three groups: wild-type group, single-gene mutation group and concomitant mutation group. The analysis of D-dimer, uric acid, gender, family history, smoking history, histology and distant metastasis all showed significant differences in the three groups (p < 0.05). D-dimer was considered as a risk factor for concomitant mutations according to the unordered multiple logistic regression analysis. The receiver operating characteristic curve analysis indicated that D-dimer had an important predictive value for the occurrence of concomitant mutations (AUC: 0.94; sensitivity: 88.71%; specificity: 86.46). There was significantly shorter median progression-free survival in the concomitant mutation group compared with the single mutation group (7.70 months vs 14.00 months; p = 0.0133). Conclusion: Plasma D-dimer is significantly associated with concomitant mutations and may be regarded as a potent predictor of concomitant mutations for non-small cell lung cancer patients.

Immunomodulatory Drugs for the Treatment of B Cell Malignancies

Accumulating evidence suggests that the tumor microenvironment (TME) is involved in disease progression and drug resistance in B cell malignancies, by supporting tumor growth and facilitating the ability of malignant cells to avoid immune recognition. Immunomodulatory drugs (IMiDs) such as lenalidomide have some direct anti-tumor activity, but critically also target various cellular compartments of the TME including T cells, NK cells, and stromal cells, which interfere with pro-tumor signaling while activating anti-tumor immune responses. Lenalidomide has delivered favorable clinical outcomes as a single-agent, and in combination therapy leads to durable responses in chronic lymphocytic leukemia (CLL) and several non-Hodgkin lymphomas (NHLs) including follicular lymphoma (FL), diffuse large B cell lymphoma (DLBCL), and mantle cell lymphoma (MCL). Recently, avadomide, a next generation cereblon E3 ligase modulator (CELMoD), has shown potent anti-tumor and TME immunomodulatory effects, as well as promising clinical efficacy in DLBCL. This review describes how the pleiotropic effects of IMiDs and CELMoDs could make them excellent candidates for combination therapy in the immuno-oncology era-a concept supported by preclinical data, as well as the recent approval of lenalidomide in combination with rituximab for the treatment of relapsed/refractory (R/R) FL.

Progastrin-Releasing Peptide Precursor and Neuron-Specific Enolase Predict the Efficacy of First-Line Treatment with Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitors Among Non-Small-Cell Lung Cancer Patients Harboring EGFR Mutations

Purpose

Lung cancer is the leading cause of cancer-related mortality and non-small-cell lung cancer (NSCLC) accounts for 80–90% of all lung cancers. However, biomarkers to predict the prognosis of NSCLC patients upon treatment with tyrosine kinase inhibitors remain unreliable. Different types of EGFR mutations can help predict the efficacy of tyrosine kinase inhibitor (TKI) treatment among advanced NSCLC patients harboring them. However, survival varies among individuals harboring the same mutation after targeted therapy. This study aimed to investigate the value of serum tumor markers (STMs) and EGFR mutations in the prognostic assessment of progression-free survival (PFS) in advanced-stage EGFR-mutated NSCLC.

Patients and Methods

A retrospective clinical review was performed on 81 NSCLC patients harboring EGFR mutations and for whom STM data, measured before commencement of first‐line treatment with tyrosine kinase inhibitors, were available. Associations among EGFR mutations, STMs, baseline clinical features, and PFS were analyzed. Kaplan−Meier method was used to plot survival curves, and Cox logistic regression models were used to identify independent prognostic factors.

Results

Exon 19 deletion (19-del) in EGFR, negative neuron-specific enolase (NSE), negative pro-gastrin-releasing peptide precursor (ProGRP) value, and “never smoking” status were significantly associated with improved PFS (P=0.007, P=0.001, P<0.001, and P<0.001, respectively). Multivariate Cox analysis revealed that 19-del in EGFR, never smoking, negative ProGRP value, and negative NSE were independent predictors of PFS.

Conclusion

This study demonstrated that 19-del in EGFR may predict longer PFS in advanced-stage EGFR-mutated NSCLC treated with TKIs. Additionally, longer PFS can be predicted by serum tumor markers with negative ProGRP value, negative NSE value before initial treatment, and “never smoking.” Therefore, in addition to the EGFR mutation type and smoking status, physicians can also prognosticate the PFS of tyrosine kinase inhibitors treatment according to the values of ProGRP and NSE before treatment.

Maintained Complete Response and Long-Term Survival in Epidermal Growth Factor Receptor Mutated Metastatic Non-Small Cell Lung Cancer with Erlotinib

The prognosis of advanced non-small cell lung cancer (NSCLC) has significantly improved for certain patients with the development of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs). However, metastatic NSCLC patients with long-term survival are still rare.

Our 66-year-old male patient was admitted to the hospital for treatment of pneumonia. A chest CT scan done revealed a left upper lobe mass; computed tomography (CT)-guided fine-needle aspiration (FNA) was done in 2010 revealing adenocarcinoma. A staging positron emission tomography (PET) scan did not reveal evidence of metastatic disease. He underwent left upper lobectomy and the pathologic stage was IB, moderately differentiated adenocarcinoma with positive angiolymphatic invasion. He was offered adjuvant systemic therapy, but he opted for surveillance. In 2012, a CT scan showed disease recurrence in the left upper lobe, which was confirmed with a biopsy. He was deemed non-surgical by thoracic oncology. Systemic therapy was initiated with carboplatin/pemetrexed and Avastin; after four cycles of treatment, the CT scan showed stable disease. Mutation analysis sent before chemotherapy revealed EGFR mutation for which chemotherapy was stopped and he was started on switch maintenance with erlotinib 150 mg in October 2012, then the dose was reduced to 100 mg secondary to grades 2-3 acneiform rash. Follow-up CT scans in January 2016 showed complete remission, which is maintained with no evidence of disease as of today.

Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality in the United States. Surgical excision is the standard treatment for stage I disease. Despite the long-term survival without adjuvant therapy, the disease recurrence rate ranges between 27% and 38% after resection. Different histologic subtypes vary in pathologic and molecular features, leading to differences in treatment and prognosis. In the adenocarcinoma subtype, five-year progression-free survival in patients with EGFR mutation treated with an EGFR-TKI is 14.6% as compared to less than 5% in unselected patients with distant-stage NSCLC. The association between exon 19 deletions, which represent about 45% of overall EGFR mutations and half of the sensitizing ones, and prolonged survival in patients with advanced NSCLC treated with EGFR-TKIs has been reported by several groups. Our case reports long-term survival in a patient with EGFR mutation-positive NSCLC with no evidence of disease for eight years since he started erlotinib treatment. Is there an option to discontinue maintenance erlotinib at this point? The answer to this question is not known, but this is a remarkably maintained response that is a good area to study patient’s characteristics leading to differences in response.

METTL14 Inhibits Hepatocellular Carcinoma Metastasis Through Regulating EGFR/PI3K/AKT Signaling Pathway in an m6A-Dependent Manner

Purpose

Hepatocellular carcinoma (HCC) ranks as the fourth leading cause of cancer-related deaths worldwide. N6-methyladenosine (m6A) RNA methylation is the most common modification of messenger RNAs (mRNAs). The prognosis of HCC patients with metastasis remains poor. Our study aimed to elucidate the regulatory role of m6A on HCC metastasis.

Patients and Methods

All HCC patients were enrolled from The Affiliated Huai’an No. 1 People’s Hospital of Nanjing Medical University. The expression levels of gene were tested by quantitative polymerase chain reaction (qPCR), Western blot, or immunohistochemistry (IHC) analysis. Wound healing assay, Transwell invasion assay, and lung metastasis model were implemented to investigate the migration and invasion ability of HCC cells. Candidate targets were selected by a comprehensive analysis of RNA-sequencing and m6A-sequencing of HepG2 cells.

Results

In this study, we demonstrated that METTL14 was significantly downregulated in HCC and significantly associated with the prognosis of HCC patients. METTL14 knockdown promoted the migration, invasion, and epithelial–mesenchymal transition (EMT) of HCC cells in vitro and in vivo. In addition, overlapping RNA-sequencing and m6A-sequencing data, we identified EGFR as a direct target of METTL14 in HCC. Mechanistically, METTL14 was found to inhibit HCC cell migration, invasion, and EMT through modulating EGFR/PI3K/AKT signaling pathway in an m6A-dependent manner.

Conclusion

Targeting METTL14/EGFR/PI3K/AKT signaling pathway may facilitate the development of a new treatment strategy against the metastasis of HCC.

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.

Clinicopathological Features in Elderly ALK-rearranged Non-small Cell Lung Cancer Patients

AIM

To clarify the clinicopathological features in elderly anaplastic lymphoma kinase (ALK) rearranged non-small cell lung cancer (NSCLC) patients.

PATIENTS AND METHODS

A retrospective study was performed in 129 ALK rearranged NSCLC patients diagnosed between April 2008 and March 2019 in fifteen Institutions of the Ibaraki prefecture, Japan.

RESULTS

Median age of patients was 63 years. In 59 patients aged 65 and older, the proportions of patients with advanced stage and those treated with ALK-tyrosine kinase inhibitor (TKI) were lower than those younger than 65 years. There was no difference in overall survival (OS) between the two age groups. Among the elderly patients, no difference was observed in OS between the patients aged 65-69 and those aged 70 and older. In 89 patients treated with TKI, no significant differences were observed in the progression-free survival of TKIs and OS between patients aged 65 and older and those younger than 65, respectively.

CONCLUSION

Evaluation of ALK gene status and TKI treatment are desirable even for elderly patients.

Serum CEA and CYFRA Levels in ALK-rearranged NSCLC Patients: Correlation With Distant Metastasis

AIM

To clarify the correlation between serum levels of carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA) and metastasis and survival in anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) patients.

PATIENTS AND METHODS

CEA and CYFRA levels in 131 ALK-rearranged NSCLC patients were determined using fluorescence in situ hybridization (FISH), real time-reverse transcription polymerase chain reaction, and immunohistochemistry, using biopsy specimens, cytology specimens, and plasma specimens. Cut-off value of each marker was determined as 10 ng/ml.

RESULTS

In logistic regression analysis, higher levels of both markers had a positive relationship with bone metastases, and higher levels of CYFRA was relevant to liver metastases, and multiple-organ metastases. However, these markers were not proven to be poor prognostic factors in Cox's proportional model analysis.

CONCLUSION

Elevated serum CEA and CYFRA levels seem to provide useful clinical information about presence of bone and liver metastasis and multiple-organ metastases, although they were not a powerful indicator of prognosis. These two markers may suggest the extension of metastasis and would be helpful in considering treatment options.

Analysis of lung biopsies using the 2015 WHO criteria and detection of sensitizing mutations--a single-institution experience of 5032 cases

BACKGROUND

A specialized classification for small biopsies was added to the 2015 WHO classification of lung tumors. The purpose of this study is to explore and summarize the experience of applying the newly proposed classifications and criteria to clinical practice.

METHODS

We used the 2015 WHO criteria to sort out 5032 small lung biopsies from a group of Chinese patients, and demonstrated their clinicopathological features, mutational status and the relationship between these factors.

RESULTS

The most common diagnosis was primary lung carcinoma (3130, 62.2%), among which adenocarcinoma (1421, 28.2%) was the most frequent histological type. The mutational assays using ARMS-PCR technology demonstrated that EGFR was positive in 56.1% cases(499/889, from adenocarcinoma and NSCC, favor adenocarcinoma), ALK in 5.7% cases(12/211, from NSCC, which comprised all the primary lung carcinomas except small cell carcinomas), and ROS1 in 0.9% cases(2/211, from NSCC). Another 898 NSCC specimens went through an immunohistochemical (IHC) examination for ALK (D5F3) and 38 of them were positive (4.2%). The overall mutation rate of ALK was 4.5% (50/1119). There was no significant difference between ARMS-PCR and immunohistochemistry in the positive rate of ALK mutation detection (P = 0.359). EGFR mutations (P = 0.02) and ALK mutations (P < 0.001) both decreased with an increasing patient age. Furthermore, the amount of EGFR mutations was higher in adenocarcinoma (64.1% vs 34.1%, P < 0.001) than in NSCC, favor adenocarcinoma. In contrast, ALK mutations were more common in NSCC, favor adenocarcinoma (4.2% vs 8.4%, P = 0.021).

CONCLUSIONS

This single-center study exhibited a large subset of small lung biopsies from a Chinese institution and demonstrated that applying the 2015 WHO classification for small lung biopsies can help predict the mutational status of primary lung carcinomas.