Advances in adjuvant systemic therapy for non-small-cell lung cancer

Non-small-cell lung cancer remains a leading cause of death around the world. For most cases, the only chance of cure comes from resection for localised disease, however relapse rates remain high following surgery. Data has emerged over recent years regarding the utility of adjuvant chemotherapy for improving disease-free and overall survival of patients following curative resection. This paper reviews the clinical trials that have been conducted in this area along with the studies integrating radiation therapy in the adjuvant setting. The role of prognostic gene signatures are reviewed as well as ongoing clinical trials including those incorporating biological or targeted therapies.     

对256例服用吉非替尼非小细胞肺癌患者的药学监护体会

目的 探讨对256例服用吉非替尼非小细胞肺癌患者实施药学监护的过程、方法 及其作用。方法 选取2017年10月至2019年10月在我院肿瘤科住院的服用吉非替尼的非小细胞肺癌患者256例,对照组给予常规药物治疗,观察组在药物治疗基础上给予针对性药学监护措施,对其不良反应相应给予不同的应对方案,整理、归纳和分析两组的治疗总有效率、不良反应总发生率和因不良反应导致的总停药率。结果 观察组的治疗总有效率为48.44%,明显高于对照组的28.12%,差异有统计学意义(P0.05);两组不良反应总发生率比较,差异无统计学意义(P0.05);观察组因不良反应导致的总停药率为25.78%,明显低于对照组的40.63%,差异有统计学意义(P0.05)。结论 通过对吉非替尼不良反应的针对性药学监护,使其疗效显著升高、停药率显著降低,大大提高了患者的依从性。     

Personalized medicine for non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is a heterogeneous illness associated with a high mortality rate. Personalized therapy may improve treatment outcomes by identification of a specific genotypic anomaly and target-specific therapy. The most significant development in recent years was the discovery of activated EGF receptor (EGFR) mutations at exons 19 and 21. Patients with EGFR mutations respond dramatically to EGFR tyrosine kinase inhibitors such as gefitinib or erlotinib, resulting in longer progression-free survival. Multiple randomized studies, including the Iressa Pan-Asia Study and WJTOG3405, have confirmed the role of EGFR tyrosine kinase inhibitors as standard first-line therapy for patients with the EGFR mutation. In this article, we summarize the current nonpersonalized therapies and examine the available and investigational personalized therapies for patients with resectable early-stage, unresectable locally advanced, or metastatic disease.     

Correlation of PD-L1 Expression with Tumor Mutation Burden and Gene Signatures for Prognosis in Early-Stage Squamous Cell Lung Carcinoma

Objectives

Anti–programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) immunotherapy has demonstrated success in the treatment of advanced NSCLC. Recently, PD-1/PD-L1 blockade also has demonstrated interesting results in small trials of neoadjuvant treatment in stage IB to IIIA NSCLC. In addition, several clinical trials using anti–PD-1/PD-L1 immunotherapy as an adjuvant or neoadjuvant treatment in patients with resectable stage NSCLC are ongoing. However, few analyses of anti–PD-1/PD-L1 immunotherapy–related biomarkers in early-stage squamous cell lung carcinoma (SqCLC) have been reported. In this study, we evaluated PD-L1 protein expression, tumor mutation burden, and expression of an immune gene signature in early-stage SqCLC, providing data for identifying the potential role for patients with anti–PD-1/PD-L1 treatment in early-stage SqCLC.

Factor analysis for survival time prediction with informative censoring and diverse covariates

Fulfilling the promise of precision medicine requires accurately and precisely classifying disease states. For cancer, this includes prediction of survival time from a surfeit of covariates. Such data presents an opportunity for improved prediction, but also a challenge due to high dimensionality. Furthermore, disease populations can be heterogeneous. Integrative modeling is sensible, as the underlying hypothesis is that joint analysis of multiple covariates provides greater explanatory power than separate analyses. We propose an integrative latent variable model that combines factor analysis for various data types and an exponential proportional hazards (EPH) model for continuous survival time with informative censoring. The factor and EPH models are connected through low-dimensional latent variables that can be interpreted and visualized to identify subpopulations. We use this model to predict survival time. We demonstrate this model's utility in simulation and on four Cancer Genome Atlas datasets: diffuse lower-grade glioma, glioblastoma multiforme, lung adenocarcinoma, and lung squamous cell carcinoma. These datasets have small sample sizes, high-dimensional diverse covariates, and high censorship rates. We compare the predictions from our model to three alternative models. Our model outperforms in simulation and is competitive on real datasets. Furthermore, the low-dimensional visualization for diffuse lower-grade glioma displays known subpopulations.     

New therapeutics based on emerging concepts in pulmonary fibrosis

Introduction: Fibrosis is an irreversible pathological endpoint in many chronic diseases, including pulmonary fibrosis. Idiopathic pulmonary fibrosis (IPF) is a progressive and often fatal condition characterized by (myo)fibroblast proliferation and transformation in the lung, expansion of the extracellular matrix, and extensive remodeling of the lung parenchyma. Recent evidence indicates that IPF prevalence and mortality rates are growing in the United States and elsewhere. Despite decades of research on the pathogenic mechanisms of pulmonary fibrosis, few therapeutics have succeeded in the clinic, and they have failed to improve IPF patient survival.

Areas covered: Based on a literature search and our own results, we discuss the key cellular and molecular responses that contribute to (myo)fibroblast actions and pulmonary fibrosis pathogenesis; this includes signaling pathways in various cells that aberrantly and persistently activate (myo)fibroblasts in fibrotic lesions and promote scar tissue formation in the lung.

Expert opinion: Lessons learned from recent failures and successes with new therapeutics point toward approaches that can target multiple pro-fibrotic processes in IPF. Advances in preclinical modeling and single-cell genomics will also accelerate novel discoveries for effective treatment of IPF.