Evaluation of lung cancer by estimating ferritin in exhaled breath condensate

Emerging Biosensing Methods to Monitor Lung Cancer Biomarkers in Biological Samples: A Comprehensive Review

Lung cancer is the most commonly diagnosed of all cancers and one of the leading causes of cancer deaths among men and women worldwide, causing 1.5 million deaths every year. Despite developments in cancer treatment technologies and new pharmaceutical products, high mortality and morbidity remain major challenges for researchers. More than 75% of lung cancer patients are diagnosed in advanced stages, leading to poor prognosis. Lung cancer is a multistep process associated with genetic and epigenetic abnormalities. Rapid, accurate, precise, and reliable detection of lung cancer biomarkers in biological fluids is essential for risk assessment for a given individual and mortality reduction. Traditional diagnostic tools are not sensitive enough to detect and diagnose lung cancer in the early stages. Therefore, the development of novel bioanalytical methods for early-stage screening and diagnosis is extremely important. Recently, biosensors have gained tremendous attention as an alternative to conventional methods because of their robustness, high sensitivity, inexpensiveness, and easy handling and deployment in point-of-care testing. This review provides an overview of the conventional methods currently used for lung cancer screening, classification, diagnosis, and prognosis, providing updates on research and developments in biosensor technology for the detection of lung cancer biomarkers in biological samples. Finally, it comments on recent advances and potential future challenges in the field of biosensors in the context of lung cancer diagnosis and point-of-care applications.

Mapping the landscape of lung cancer breath analysis: A scoping review (ELCABA)

Lung cancer is the leading cause of cancer death worldwide due to its late-stage detection. Lung cancer screening, including low-dose computed tomography (low-dose CT), provides an initial clinical solution. Nevertheless, further innovations and refinements would help to alleviate remaining limitations. The non-invasive, gentle, and fast nature of breath analysis (BA) makes this technology highly attractive to supplement low-dose CT for an improved screening algorithm. However, BA has not taken hold in everyday clinical practice. One reason might be the heterogeneity and variety of BA methods. This scoping review is a comprehensive summary of study designs, breath analytical methods, and suggested biomarkers in lung cancer. Furthermore, this synthesis provides a framework with core outcomes for future studies in lung cancer BA. This work supports future research for evidence synthesis, meta-analysis, and translation into clinical routine workflows.

Deformable liposomal codelivery of vorinostat and simvastatin promotes antitumor responses through remodeling tumor microenvironment

The tumor microenvironment (TME) and its major component tumor-associated macrophages (TAM) play a pivotal role in the development of non-small cell lung cancer (NSCLC). An epigenetic drug-based combinatory therapeutic strategy was proposed and a deformable liposome system (D-Lipo) was developed for vorinostat and simvastatin codelivery for remodeling the TME. The application of deformable liposomes in systemic cancer drug delivery has been underexplored and its potential in cancer therapy is largely unknown. This work revealed that D-Lipo exhibited an enhanced intratumor infiltration ability. The proposed therapeutic strategy was characterized by a chemo-free regimen and TME remodeling function. D-Lipo efficiently inhibited the growth of the xenografted lung tumor. The anti-tumor mechanisms involved the repolarization of TAM from the M2 to M1 phenotype, anti-angiogenesis, and the consequent TME remodeling. As a result, the amounts of the anti-tumor M1 macrophages and the cytotoxic CD8+ T cells increased, while the amounts of the pro-tumor M2 macrophages and regulatory T cells (Tregs) reduced. It provides a promising avenue for epigenetic drug-based combination therapy for treating solid tumors.

Nutritional immunity: the impact of metals on lung immune cells and the airway microbiome during chronic respiratory disease

Nutritional immunity is the sequestration of bioavailable trace metals such as iron, zinc and copper by the host to limit pathogenicity by invading microorganisms. As one of the most conserved activities of the innate immune system, limiting the availability of free trace metals by cells of the immune system serves not only to conceal these vital nutrients from invading bacteria but also operates to tightly regulate host immune cell responses and function. In the setting of chronic lung disease, the regulation of trace metals by the host is often disrupted, leading to the altered availability of these nutrients to commensal and invading opportunistic pathogenic microbes. Similarly, alterations in the uptake, secretion, turnover and redox activity of these vitally important metals has significant repercussions for immune cell function including the response to and resolution of infection. This review will discuss the intricate role of nutritional immunity in host immune cells of the lung and how changes in this fundamental process as a result of chronic lung disease may alter the airway microbiome, disease progression and the response to infection.

Survival prediction model for non-small cell lung cancer based on somatic mutations

BACKGROUND

The 5-year survival rate of non-small cell lung cancer (NSCLC) is only 15%. Screening some combined gene mutations could predict the survival of NSCLC patients and also provide new ideas for the diagnosis and treatment of NSCLC. The present study aimed to identify signature mutations for survival prediction of NSCLC.

METHODS

Clinical and gene mutation information for 949 NSCLC patients was downloaded from TCGA. High frequency mutation and common mutation genes were analyzed based on 1000 cancer related genes. The LASSO-COX model was used to screen gene mutation points and analyze their survival, and then a survival prediction model was established. Fifty NSCLC patients were collected and 1000 targeted genes were enriched by targeted next generation sequencing. The results were used to verify the combination of common mutation genes and the function of the survival model, and then to clarify their clinical significance.

RESULTS

Ten variables were screened out after LASSO-COX analysis, including age, tumor stage, EGFR c.[2,573 T>G], PIK3CA c.[1624G>A], TP53 c.[375G>T], TP53 c.[527G>T], TP53 c.[733G>T], TP53 c.[734G>T], TP53 c.[743G>T], NFE2L2 c.[100C>G]. Except for TP53 c.[743G>T] and NFE2L2 c.[100C>G], the residual six hot spot mutations of EGFR, PIK3CA and TP53 could be regarded as a signature mutations for forecasting the survival time of NSCLC.

CONCLUSIONS

The combination of six hot spot mutations of EGFR, PIK3CA and TP53 is expected to be used for predicting the survival time of NSCLC.