Prognostic impact of pleural effusion in EGFR-mutant non-small cell lung cancer patients without brain metastasis

Evolving landscape of treatments targeting the microenvironment of liver metastases in non-small cell lung cancer

ABSTRACT

Liver metastases (LMs) are common in lung cancer. Despite substantial advances in diagnosis and treatment, the survival rate of patients with LM remains low as the immune-suppressive microenvironment of the liver allows tumor cells to evade the immune system. The impact of LMs on the outcomes of immune checkpoint inhibitors in patients with solid tumors has been the main focus of recent translational and clinical research. Growing evidence indicates that the hepatic microenvironment delivers paracrine and autocrine signals from non-parenchymal and parenchymal cells. Overall, these microenvironments create pre- and post-metastatic conditions for the progression of LMs. Herein, we reviewed the epidemiology, physiology, pathology and immunology, of LMs associated with non-small cell lung cancer and the role and potential targets of the liver microenvironment in LM in each phase of metastasis. Additionally, we reviewed the current treatment strategies and challenges that should be overcome in preclinical and clinical investigations. These approaches target liver elements as the basis for future clinical trials, including combinatorial interventions reported to resolve hepatic immune suppression, such as immunotherapy plus chemotherapy, immunotherapy plus radiotherapy, immunotherapy plus anti-angiogenesis therapy, and surgical resection.

EGFR mutation testing from pleural effusions of non-small cell lung cancer patients at the institute for oncology and radiology of Serbia

BACKGROUND

The use tumor-derived cell-free DNA extracted from body fluids is being evaluated for genetic testing in lung cancer. The aim of this study was to explore the feasibility and utility of implementation of EGFR molecular testing from pleural effusions in non-small cell lung cancer in the clinical diagnostics workflow.

PATIENTS AND METHODS

This study included patients diagnosed with primary lung adenocarcinoma in the period July 2016 to June 2023. EGFR mutation testing was performed by qPCR (Cobas®) and dPCR. Testing was performed from 211 plasma samples when tissue was unavailable at diagnosis, and from 301 plasma samples and 18 pleural effusions at progression on first/second generation of EGFR TKIs. Descriptive methods of statistical analysis were used to summarize the sample data. Fisher's exact test, McNemar's test, Cohen's kappa tests were used for statistical analyses. Two-sided p-values <0.05 were considered statistically significant.

RESULTS

A significantly higher detection rate of the T790M mutation in pleural effusion was obtained compared to blood (50% and 20%, p=0.047). When comparing the detection success rate of the resistant T790M mutation in pleural effusion and blood, a statistically significant difference was obtained in favor of pleural effusion (50% vs. 21.87%, p=0.01).

CONCLUSIONS

Superior performance of pleural effusions compared to blood plasma was shown both in the analysis of success rate and in the detection of the resistant T790M mutation, at progression on EGFR TKIs. Pleural effusion should be considered in this setting whenever available, especially in countries with limited health resources.

Can quantitative peritumoral CT radiomics features predict the prognosis of patients with non-small cell lung cancer? A systematic review

OBJECTIVES

To provide an overarching evaluation of the value of peritumoral CT radiomics features for predicting the prognosis of non-small cell lung cancer and to assess the quality of the available studies.

METHODS

The PubMed, Embase, Web of Science, and Cochrane Library databases were searched for studies predicting the prognosis in patients with non-small cell lung cancer (NSCLC) using CT-based peritumoral radiomics features. Information about the patient, CT-scanner, and radiomics analyses were all extracted for the included studies. Study quality was assessed using the Radiomics Quality Score (RQS) and the Prediction Model Risk of Bias Assessment Tool (PROBAST).

RESULTS

Thirteen studies were included with 2942 patients from 2017 to 2022. Only one study was prospective, and the others were all retrospectively designed. Manual segmentation and multicenter studies were performed by 69% and 46% of the included studies, respectively. 3D-Slicer and MATLAB software were most commonly used for the segmentation of lesions and extraction of features. The peritumoral region was most frequently defined as dilated from the tumor boundary of 15 mm, 20 mm, or 30 mm. The median RQS of the studies was 13 (range 4-19), while all of included studies were assessed as having a high risk of bias (ROB) overall.

CONCLUSIONS

Peritumoral radiomics features based on CT images showed promise in predicting the prognosis of NSCLC, although well-designed studies and further biological validation are still needed.

KEY POINTS

• Peritumoral radiomics features based on CT images are promising and encouraging for predicting the prognosis of non-small cell lung cancer. • The peritumoral region was often dilated from the tumor boundary of 15 mm or 20 mm because these were considered safe margins. • The median Radiomics Quality Score of the included studies was 13 (range 4-19), and all of studies were considered to have a high risk of bias overall.

Preoperative neutrophil-to-lymphocyte ratio (preNLR) for the assessment of tumor characteristics in lung adenocarcinoma patients with brain metastasis

•

A relationship between preoperative Neutrophil-to-Lymphocyte ratio (preNLR) and brain metastasis characteristics such as tumor location and peritumoral brain edema is proposed.

•

The corresponding spearman correlations of peritumoral brain edema and preoperative NLR between different tumor location was performed.

•

A prognostic nomogram, that provide survival predictions for brain metastasis on lung adenocarcinoma (LUAD) patients has been established.

Objectives

Brain metastases from lung adenocarcinoma cause significant patient mortality. This study aims to evaluate the role of preoperative Neutrophil-to-Lymphocyte ratio (preNLR) in predicting the survival and prognosis of Lung adenocarcinoma (LUAD) patients with brain metastasis (BM) and provide more references for predicting peritumoral edema.

Methods

We retrospectively reviewed 125 LUAD-BM patients who had undergone surgical resection from December 2015 to December 2020. The clinical characteristic, demographic, MRI data, and preNLR within 24–48 h before craniotomy were collected. Patients were divided into two groups based on preNLR (high NLR and low NLR), with cutoff values determined by receiver operating characteristic (ROC) analysis. Association between preoperative NLR and clinical features was determined by using Pearson chi-squared tests. Uni- and multivariate analyzes were performed to compare the overall survival (OS) of clinical features.

Results

The patients were divided into NLR-low (64 patients) and NLR-high (61 patients) groups based on receiver operating characteristic analysis of NLR area. According to correlation analysis, a high preNLR (NLR≥2.8) is associated with the both supra- and infratentorial location involved (P = 0.017) and a greater incidence of severe peritumoral edema (P = 0.038). By multivariable analysis, age ≥ 65 years (P = 0.011), KPS < 70 (P = 0.043), elevated preNLR (P = 0.013), extracerebral metastases (P = 0.003), EGFR/ALK+ (P = 0.037), postoperative radiotherapy (P = 0.017) and targeted therapy (P = 0.007) were independent prognostic factors. OS nomogram was constructed based on cox model and model performance was examined (AUC = 0.935).

Conclusions

PreNLR may serve as a prognosis indicator in LUAD patients with brain metastasis, and high preNLR tends to be positively associate with multiple locations and severe peritumoral edema.

Comparison of Different Tyrosine Kinase Inhibitors for Treatment of Poor Performance Status Patients with EGFR-Mutated Lung Adenocarcinoma

Simple Summary

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are standard treatments in patients with EGFR-mutated lung adenocarcinoma. However, the clinical data regarding EGFR-TKI efficacy in patients with poor performance status (PS ≥ 2) are limited. We reviewed the clinical outcomes and safety of EFGR-TKI use in patients with poor PS and identified the independent and favorable prognostic factors for progression-free survival and overall survival. We found that patients treated with 40 mg afatinib had better survival results, although only a non-significant trend toward superiority was observed in the multivariable analysis. Dose adjustment was an independent prognostic factor for PFS and OS. This study provided evidence of the use of EGFR-TKIs for patients with poor PS.

Abstract

The aim of this retrospective study was to investigate the tolerability and survival outcomes of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) treatment in patients with a performance status ≥ 2. The data for 517 patients treated with EGFR-TKIs between January 2011 and January 2018 at a regional hospital in northern Taiwan were analyzed. Clinical and pathological features were collected, and univariate as well as multivariable analyses were undertaken to identify potential prognostic factors. The overall objective response rate, median progression-free survival (PFS), and median overall survival (OS) were 56.3%, 11.4 months, and 15.3 months, respectively. The mutation status (exon 19 deletion), locally advanced disease, dose adjustment, and the lack of liver and pleural metastasis were independent and favorable prognostic factors for PFS. Age < 60 years, mutation status (exon 19 deletion), dose adjustment, and lack of lung, liver, and no pleural metastasis were independent and favorable prognostic factors for OS. GFR-TKIs demonstrated acceptable efficacy and safety in the current cohort. Dose adjustment was identified as an independent prognostic factor for both PFS and OS, regardless of which EGFR-TKIs were used. The current research provided novel evidence of the clinical prescription of frontline EGFR-TKIs for EGFR-mutated lung adenocarcinoma patients with a PS score ≥2.

Identifying Lung Cancer Cell Markers with Machine Learning Methods and Single-Cell RNA-Seq Data

Non-small cell lung cancer is a major lethal subtype of epithelial lung cancer, with high morbidity and mortality. The single-cell sequencing technique plays a key role in exploring the pathogenesis of non-small cell lung cancer. We proposed a computational method for distinguishing cell subtypes from the different pathological regions of non-small cell lung cancer on the basis of transcriptomic profiles, including a group of qualitative classification criteria (biomarkers) and various rules. The random forest classifier reached a Matthew’s correlation coefficient (MCC) of 0.922 by using 720 features, and the decision tree reached an MCC of 0.786 by using 1880 features. The obtained biomarkers and rules were analyzed in the end of this study.