Second and later-line erlotinib use in non-small cell lung cancer: real world outcomes and practice patterns overtime in Canada

Real-World Treatment Patterns and Survival Among Patients with Stage I-III, Non-Squamous, Non-Small Cell Lung Cancer Receiving Surgery as Primary Treatment

INTRODUCTION

Approximately half of patients with non-small cell lung cancer (NSCLC) present with early-stage disease at diagnosis. Real-world outcomes data are limited for this population but are of interest given recent and impending results from trials evaluating epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) and immunotherapies in neoadjuvant, adjuvant, and perioperative settings.

METHODS

A retrospective, longitudinal, population-level study was conducted in patients diagnosed with resected stage I-III non-squamous NSCLC in Ontario, Canada, between April 2010 and March 2019. Study outcomes included patient characteristics and median overall survival (mOS), with stratification by disease stage and treatment exposure. Patients receiving EGFR-TKIs (assumed EGFR mutation-positive by proxy) were a key population of interest.

RESULTS

Among 8255 cases, 4881 had stage I, 2124 had stage II, and 1250 had stage III NSCLC at diagnosis. The mean patient age was 68 years; 53.5% were female. In the overall cohort, 19.6% received adjuvant chemotherapy. Receipt of adjuvant chemotherapy was associated with significantly longer mOS than not receiving such therapy: stage II (7.6 [95% confidence interval: 6.5-8.5] vs. 4.4 [4.0-4.9] years) or stage III (4.4 [3.6-5.1] vs. 2.7 [2.3-3.3] years), both p < 0.0001. Patients receiving treatment (EGFR-TKIs and chemotherapy) were assumed to have experienced disease recurrence/relapse; mOS was longer among those receiving an EGFR-TKI than among those receiving chemotherapy (2.3 [1.8-3.0] vs. 1.1 [1.0-1.3] years).

CONCLUSION

In Ontario, between 2010 and 2019, uptake of adjuvant therapy was low among patients with resected NSCLC, despite such therapy being associated with improved survival. Patients assumed to have recurred/relapsed had markedly reduced mOS, regardless of subsequent therapy, compared with those who did not relapse/recur. Novel peri-adjuvant treatment options are needed to enhance outcomes after lung resection.

Lipid metabolism-related gene signatures for predicting the prognosis of lung adenocarcinoma

Background

Lung cancer is one of the most common epithelial malignancies worldwide, accounting for the highest number of new cases and deaths. Metabolism is the sum of chemical reactions that produce energy to keep an organism alive. Several studies have shown that glucose and lipid metabolic disorders are common phenomena related to cancer cell genesis and progression.

Methods

We screened the differentially expressed genes (DEGs) of lung adenocarcinoma (LUAD) samples of The Cancer Genome Atlas (TCGA) database, the Gene Set Enrichment Analysis (GSEA), and Gene Card database metabolism-related data, the metabolism-related DEGs of LUAD, as well as the univariate Cox regression analysis genes, for identifying significant outcome-related genes. The least absolute shrinkage and gene selection operator (LASSO) analysis was performed to establish the best risk model.

Results

Our study aimed to establish a lipid metabolism-related model for predicting LUAD prognosis. Furthermore, our model's prognosis prediction power was evaluated by survival analysis. This study finally identified 11 DEGs related to lipid metabolism that were significantly associated with the prognosis of lung adenocarcinoma. It provided a new idea for the treatment of high-risk lung adenocarcinoma patients.

Conclusions

The constructed clinical prognosis model of lung adenocarcinoma related to lipid metabolism provides a new idea for clinical treatment of lung adenocarcinoma.

Prognosis and Immunotherapy Response With a Novel Golgi Apparatus Signature-Based Formula in Lung Adenocarcinoma

The Golgi apparatus (GA) is a cellular organelle that participates in the packaging, modification, and transport of proteins and lipids from the endoplasmic reticulum to be further fabricated before being presented to other cellular components. Recent studies have demonstrated that GA facilitates numerous cellular processes in cancer development. Therefore, this study aimed to establish a novel lung adenocarcinoma (LUAD) risk evaluation model based on GA gene signatures. In this study, we used TCGA-LUAD (n = 500) as the training cohort and GSE50081 (n = 127), GSE68465 (442), and GSE72094 (398) as the validation cohorts. Two immunotherapy datasets (GSE135222 and GSE126044) were also obtained from a previous study. Based on machine algorithms and bioinformatics methods, a GA gene-related risk score (GARS) was established. We found that the GARS independently predicted the prognosis of LUAD patients and remained effective across stages IA to IIIA. Then, we identified that the GARS was highly correlated with mutations in P53 and TTN. Further, this study identified that GARS is related to multiple immune microenvironmental characteristics. Furthermore, we investigated GSE135222 and GSE126044 and found that a lower GARS may be indicative of an improved therapeutic effect of PD-1/PD-L1 therapy. We also found that high GARS may lead to a better response to multiple anticancer drugs. Finally, we established a nomogram to better guide clinical application. To our knowledge, this is the first study to demonstrate a novel GA signature-based risk score formula to predict clinical prognosis and guide the treatment of LUAD patients.