Meta-analysis of efficacy and adverse events of erlotinib-based targeted therapies for advanced/metastatic non-small cell lung cancer

G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma

BACKGROUND

Liver Hepatocellular carcinoma (LIHC) exhibits a high incidence of liver cancer with escalating mortality rates over time. Despite this, the underlying pathogenic mechanism of LIHC remains poorly understood.

MATERIALS & METHODS

To address this gap, we conducted a comprehensive investigation into the role of G6PD in LIHC using a combination of bioinformatics analysis with database data and rigorous cell experiments. LIHC samples were obtained from TCGA, ICGC and GEO databases, and the differences in G6PD expression in different tissues were investigated by differential expression analysis, followed by the establishment of Nomogram to determine the percentage of G6PD in causing LIHC by examining the relationship between G6PD and clinical features, and the subsequent validation of the effect of G6PD on the activity, migration, and invasive ability of hepatocellular carcinoma cells by using the low expression of LI-7 and SNU-449. Additionally, we employed machine learning to validate and compare the predictive capacity of four algorithms for LIHC patient prognosis.

RESULTS

Our findings revealed significantly elevated G6PD expression levels in liver cancer tissues as compared to normal tissues. Meanwhile, Nomogram and Adaboost, Catboost, and Gbdt Regression analyses showed that G6PD accounted for 46%, 31%, and 49% of the multiple factors leading to LIHC. Furthermore, we observed that G6PD knockdown in hepatocellular carcinoma cells led to reduced proliferation, migration, and invasion abilities. Remarkably, the Decision Tree C5.0 decision tree algorithm demonstrated superior discriminatory performance among the machine learning methods assessed.

CONCLUSION

The potential diagnostic utility of G6PD and Decision Tree C5.0 for LIHC opens up a novel avenue for early detection and improved treatment strategies for hepatocellular carcinoma.

Safety profile of tyrosine kinase inhibitors used in non-small-cell lung cancer: An analysis from the Italian pharmacovigilance database

Introduction

Non-small cell lung cancer (NSCLC) is often caused by molecular alterations that can be detected by predictive biomarkers including mutations or amplifications of several genes. Several tyrosine kinase inhibitors (TKIs) have been approved in Europe by the European Medicines Agency (EMA) for NSCLC. The aim of this study was to analyze the onset of adverse drug reactions (ADRs) related to TKIs in NSCLC through a spontaneous reporting system (SRS) database.

Methods

All ADR reports having as suspected drug afatinib (AFT), alectinib (ALEC), brigatinib (BRG), ceritinib (CER), crizotinib (CRIZ), erlotinib (ERL), gefitinib (GEF), lorlatinib (LORL), nintedanib (NTB), and osimertinib (OSI) recorded into the Report Reazioni Avverse dei Medicinali (RAM) system database for national data and into the Italian SRS database for Sicilian data and collected from 2006 to 2021 have been evaluated. A descriptive analysis of basal demographic and drug-related characteristics was performed. A case-by-case methodology was conducted paying particular attention to all serious ADR reports collected in Sicily, focusing on type of seriousness, age, sex, concomitant drugs, and comorbidities.

Results

Of the 3,048 Italian reports, most of ADRs were related to ERL (n = 1,448), followed by AFT (n = 435) and GEF (n = 366). ADR reports were slightly more frequent in females (52.2%) and in the age group >65 years (53.0%). A higher number of cases were related to skin disorders (n = 1,766; 57.9%), followed by gastrointestinal disorders (n = 1,024; 33.6%), general disorders and administration site conditions (n = 536; 17.6%), and infections (n = 483; 15.8%). The case-by-case assessment of Sicilian ADRs showed that 33 cases were serious (12.5%) and mainly involved ERL (n = 17; 51.5%), occurring in males with a higher onset of respiratory diseases (30.3%) such as respiratory failure, interstitial lung disease and dyspnea.

Discussion

The analysis of spontaneous ADR reports of TKIs confirmed, in general, well-known risks, which often include skin, gastrointestinal, general, liver, and respiratory diseases as well as infections. However, more attention should be paid to the occurrence of serious life-threatening ADRs including respiratory failure, interstitial lung disease, and cardiogenic shock, especially in young patients.

Combination strategies based on epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors for cancer patients: Pooled analysis and subgroup analysis of efficacy and safety

BACKGROUND

Combination therapy based on epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is an emerging trend in cancer treatment, but the clinical value of EGFR-TKIs combination therapy remains controversial. Thus, we conducted a comprehensive analysis of randomized controlled trials (RCTs) comparing EGFR-TKIs combination therapies with monotherapies, aiming to evaluate the safety and efficacy of EGFR-TKIs based combination therapy and to find a more beneficial combination strategy.

METHODS

We searched for clinical studies that evaluated EGFR-TKIs combination therapy in cancer. We extracted data from these studies to evaluate the relative risk (RR) of overall response rate (ORR) and grade 3/4 treatment-related adverse events (AEs), the hazard ratios (HRs) of overall survival (OS), and progression-free survival (PFS).

RESULTS

Fourteen RCTs were identified (n = 3774). Treatments included combinations of EGFR-TKIs and chemotherapy, combinations of EGFR-TKIs and radiotherapy, and combinations of EGFR-TKIs and bevacizumab. EGFR-TKIs combination therapies showed higher ORR [RR: 1.62; 95% confidence interval (95% CI):1.16-2.26; P = .005], PFS (HR: 0.76; 95% CI: 0.64-0.89; P = .001), and OS (HR: 0.88; 95% CI: 0.79-0.97; P = .013) values than monotherapies. However, higher grade 3/4 treatment-related AEs (RR: 1.79; 95% CI: 1.02-3.15; P = .000) were observed in combination therapy than in monotherapy.

CONCLUSION

Our pooled analysis and subgroup analysis results showed that the addition of chemotherapy to EGFR-TKIs better benefits PFS and safety. Adding bevacizumab was associated with better ORR and OS. The efficacy and safety of a bevacizumab-EGFR-TKIs-chemotherapy combination should be investigated further.