Lung Cancer: One Disease or Many

Identification of an 11-miRNA-regulated and surface-protein genes signature predicts the prognosis of lung adenocarcinoma based on multi-omics study

Lung adenocarcinoma (LUAD) is one of the most prevalent and lethal cancers worldwide, signifying a critical need for improved prognostic tools. A growing number of studies have highlighted the role of microRNAs (miRNAs) and their regulatory functions in tumorigenesis and cancer progression. In this context, we performed an extensive analysis of bulk RNA- and miRNA-sequencing to identify LUAD-associated prognostic genes. A risk score system based on 11 miRNA-regulated and surface-protein genes was developed, which was later validated by internally and externally using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. Further single-cell RNA sequencing analysis revealed significant interactions between various cellular subpopulations within the tumor microenvironment, with the most pronounced differences observed between endothelial and epithelial cells. The mutational analysis highlighted TP53 as a key signaling pathway associated with the risk score. The study underscores that immune suppression, indicated by a positive association with regulatory T cells (Tregs) and an inverse correlation with M1-type macrophages, is prevalent in high-risk LUAD patients. These findings provide a promising prognostic tool for clinical outcomes of LUAD patients, facilitating future development of therapeutic strategies and enhancing our understanding of the regulatory function of miRNAs in LUAD.

Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.

A mouse model of lung cancer induced via intranasal injection for anticancer drug screening and evaluation of pathology

The pathologies and lethality of lung cancers are associated with smoking, lifestyle, and genomic factors. Several experimental mouse models of lung cancer, including those induced via intrapulmonary injection and intratracheal injection, have been reported for evaluating the pharmacological effect of drugs. However, these models are not sufficient for evaluating the efficacy of drugs during screening, as these direct injection models ignore the native processes of cancer progression in vivo, resulting in the inadequate pathological formation of lung cancer. In the present study, we developed a novel intranasal injection model of lung cancer simulating the native lung cancer pathology for anticancer drug screening. A mouse lung cancer cell line (Lewis lung carcinoma; LCC) was intranasally injected into mouse lungs, and injected cell number-dependent cancer proliferation was apparent in both the left and right lungs. Human non-small-cell lung cancer (NCI-H460) cells were also intranasally injected into nude mice and similarly showed injected cell number-dependent cancer growth. For the pharmacological evaluation of cisplatin, two different treatment frequencies were tested four times per month and twice a month. The intranasal injection model confirmed that cisplatin suppressed lung cancer progression to a greater extent under the more frequent treatment condition. In conclusion, these results indicated that our intranasal injection model is a powerful tool for investigating lung cancer pathology and may aid in the development of new anti-lung cancer agents.

Kinesin Family Member 18A (KIF18A) Contributes to the Proliferation, Migration, and Invasion of Lung Adenocarcinoma Cells In Vitro and In Vivo

Objective

To determine the expression levels of KIF18A in lung adenocarcinoma and its relationship with the clinicopathologic features of patients undergoing radical colectomy and explore the potential role in the progression of lung adenocarcinoma.

Methods

Immunohistochemical assays were performed to explore the expression levels of KIF18A in 82 samples of lung adenocarcinoma and corresponding normal tissues. According to the levels of KIF18A expression in lung adenocarcinoma tissue samples, patients were classified into the KIF18A high expression group and low expression group. Clinical data related to the perioperative clinical features (age, gender, smoking, tumor size, differentiation, clinical stage, and lymph node metastasis), the potential correlation between KIF18A expression levels, and clinical features were analyzed, and the effects of KIF18A on lung adenocarcinoma cell proliferation, migration, and invasion were measured by colony formation assay, MTT assay, wound healing assay, and transwell assays. The possible effects of KIF18A on tumor growth and metastasis were measured in mice through tumor growth and tumor metastasis assays in vivo.

Results

KIF18A in lung adenocarcinoma tissues. Further, KIF18A was significantly associated to clinical characteristic features including the tumor size (P = 0.033) and clinical stage (P = 0.041) of patients with lung adenocarcinoma. Our data also investigated that KIF18A depletion dramatically impairs the proliferation, migration, and invasion capacity of lung adenocarcinoma cells in vitro and inhibits tumor growth and metastasis in mice.

Conclusions

Our study reveals the involvement of KIF18A in the progression and metastasis of lung adenocarcinoma and provides a novel therapeutic target for the treatment of lung adenocarcinoma.

Implementation planning for lung cancer screening in China

Lung cancer is the leading cause of cancer-related deaths in China, with over 690 000 lung cancer deaths estimated in 2018. The mortality has increased about five-fold from the mid-1970s to the 2000s. Lung cancer low-dose computerized tomography (LDCT) screening in smokers was shown to improve survival in the US National Lung Screening Trial, and more recently in the European NELSON trial. However, although the predominant risk factor, smoking contributes to a lower fraction of lung cancers in China than in the UK and USA. Therefore, it is necessary to establish Chinese-specific screening strategies. There have been 23 associated programmes completed or still ongoing in China since the 1980s, mainly after 2000; and one has recently been planned. Generally, their entry criteria are not smoking-stringent. Most of the Chinese programmes have reported preliminary results only, which demonstrated a different high-risk subpopulation of lung cancer in China. Evidence concerning LDCT screening implementation is based on results of randomized controlled trials outside China. LDCT screening programmes combining tobacco control would produce more benefits. Population recruitment (e.g. risk-based selection), screening protocol, nodule management and cost-effectiveness are discussed in detail. In China, the high-risk subpopulation eligible for lung cancer screening has not as yet been confirmed, as all the risk parameters have not as yet been determined. Although evidence on best practice for implementation of lung cancer screening has been accumulating in other countries, further research in China is urgently required, as China is now facing a lung cancer epidemic.