An integrated inspection of the somatic mutations in a lung squamous cell carcinoma using next-generation sequencing

Stem Cell-derived Respiratory Epithelial Cell Cultures as Human Disease Models

Advances in stem cell biology and the understanding of factors that determine lung stem cell self-renewal have enabled long-term in vitro culture of human lung cells derived from airway basal and alveolar type II cells. Improved capability to expand and study primary cells long term, including in clonal cultures that are recently derived from a single cell, will allow experiments that address fundamental questions about lung homeostasis and repair, as well as translational questions in asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and lung cancer research. Here, we provide a brief history of postnatal lung epithelial cell culture and describe recent methodological advances. We further discuss the applications of primary cultures in defining "normal" epithelium, in modeling lung disease, and in future cell therapies.

Progress towards non-small-cell lung cancer models that represent clinical evolutionary trajectories

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Although advances are being made towards earlier detection and the development of impactful targeted therapies and immunotherapies, the 5-year survival of patients with advanced disease is still below 20%. Effective cancer research relies on pre-clinical model systems that accurately reflect the evolutionary course of disease progression and mimic patient responses to therapy. Here, we review pre-clinical models, including genetically engineered mouse models and patient-derived materials, such as cell lines, primary cell cultures, explant cultures and xenografts, that are currently being used to interrogate NSCLC evolution from pre-invasive disease through locally invasive cancer to the metastatic colonization of distant organ sites.

The impact of the Cancer Genome Atlas on lung cancer

The Cancer Genome Atlas (TCGA) has profiled more than 10,000 samples derived from 33 types of cancer to date, with the goal of improving our understanding of the molecular basis of cancer and advancing our ability to diagnose, treat, and prevent cancer. This review focuses on lung cancer as it is the leading cause of cancer-related mortality worldwide in both men and women. Particularly, non-small cell lung cancers (including lung adenocarcinoma and lung squamous cell carcinoma) were evaluated. Our goal was to demonstrate the impact of TCGA on lung cancer research under 4 themes: diagnostic markers, disease progression markers, novel therapeutic targets, and novel tools. Examples are given related to DNA mutation, copy number variation, messenger RNA, and microRNA expression along with methylation profiling.

Tumor heterogeneity and resistance to EGFR-targeted therapy in advanced nonsmall cell lung cancer: challenges and perspectives

Lung cancer, mostly nonsmall cell lung cancer, continues to be the leading cause of cancer-related death worldwide. With the development of tyrosine kinase inhibitors that selectively target lung cancer-related epidermal growth factor receptor mutations, management of advanced nonsmall cell lung cancer has been greatly transformed. Improvements in progression-free survival and life quality of the patients were observed in numerous clinical studies. However, overall survival is not prolonged because of later-acquired drug resistance. Recent studies reveal a heterogeneous subclonal architecture of lung cancer, so it is speculated that the tumor may rapidly adapt to environmental changes via a Darwinian selection mechanism. In this review, we aim to provide an overview of both spatial and temporal tumor heterogeneity as potential mechanisms underlying epidermal growth factor receptor tyrosine kinase inhibitor resistance in nonsmall cell lung cancer and summarize the possible origins of tumor heterogeneity covering theories of cancer stem cells and clonal evolution, as well as genomic instability and epigenetic aberrations in lung cancer. Moreover, investigational measures that overcome heterogeneity-associated drug resistance and new assays to improve tumor assessment are also discussed.

Unraveling tumor grading and genomic landscape in lung neuroendocrine tumors

Currently, grading in lung neuroendocrine tumors (NETs) is inherently defined by the histological classification based on cell features, mitosis count, and necrosis, for which typical carcinoids (TC) are low-grade malignant tumors with long life expectation, atypical carcinoids (AC) intermediate-grade malignant tumors with more aggressive clinical behavior, and large cell NE carcinomas (LCNEC) and small cell lung carcinomas (SCLC) high-grade malignant tumors with dismal prognosis. While Ki-67 antigen labeling index, highlighting the proportion of proliferating tumor cells, has largely been used in digestive NETs for assessing prognosis and assisting therapy decisions, the same marker does not play an established role in the diagnosis, grading, and prognosis of lung NETs. Next generation sequencing techniques (NGS), thanks to their astonishing ability to process in a shorter timeframe up to billions of DNA strands, are radically revolutionizing our approach to diagnosis and therapy of tumors, including lung cancer. When applied to single genes, panels of genes, exome, or the whole genome by using either frozen or paraffin tissues, NGS techniques increase our understanding of cancer, thus realizing the bases of precision medicine. Data are emerging that TC and AC are mainly altered in chromatin remodeling genes, whereas LCNEC and SCLC are also mutated in cell cycle checkpoint and cell differentiation regulators. A common denominator to all lung NETs is a deregulation of cell proliferation, which represents a biological rationale for morphologic (mitoses and necrosis) and molecular (Ki-67 antigen) parameters to successfully serve as predictors of tumor behavior (i.e., identification of pathological entities with clinical correlation). It is envisaged that a novel grading system in lung NETs based on the combined assessment of mitoses, necrosis, and Ki-67 LI may offer a better stratification of prognostic classes, realizing a bridge between molecular alterations, morphological features, and clinical behavior.