Biomarkers in Lung Cancer

Identification of volatile biomarkers for lung cancer from different histological sources: A comprehensive study

The identification of noninvasive volatile biomarkers for lung cancer is a significant clinical challenge. Through in vitro studies, the recognition of altered metabolism in cell volatile organic compound (VOC) emitting profile, along with the occurrence of oncogenesis, provides insight into the biochemical pathways involved in the production and metabolism of lung cancer volatile biomarkers. In this research, for the first time, a comprehensive comparative analysis of the volatile metabolites in NSCLS cells (A549), SCLC cells (H446), lung normal cells (BEAS-2B), as well as metabolites in both the oxidative stress (OS) group and control group. Specifically, the combination of eleven VOCs, including n-dodecane, acetaldehyde, isopropylbenzene, p-ethyltoluene and cis-1,3-dichloropropene, exhibited potential as volatile biomarkers for lung cancer originating from two different histological sources. Furthermore, the screening process in A549 cell lines resulted in the identification of three exclusive biomarkers, isopropylbenzene, formaldehyde and bromoform. Similarly, the exclusive biomarkers 1,2,4-trimethylbenzene, p-ethyltoluene, and cis-1,3-dichloropropene were present in the H446 cell line. Additionally, significant changes in trans-2-pentene, acetaldehyde, 1,2,4-trimethylbenzene, and bromoform were observed, indicating a strong association with OS. These findings highlight the potential of volatile biomarkers profiling as a means of noninvasive identification for lung cancer diagnosis.

Eg5 and Diseases: From the Well-Known Role in Cancer to the Less-Known Activity in Noncancerous Pathological Conditions

Eg5 is a protein encoded by KIF11 gene and is primarily involved in correct mitotic cell division. It is also involved in nonmitotic processes such as polypeptide synthesis, protein transport, and angiogenesis. The scientific literature sheds light on the ubiquitous functions of KIF11 and its involvement in the onset and progression of different pathologies. This review focuses attention on two main points: (1) the correlation between Eg5 and cancer and (2) the involvement of Eg5 in noncancerous conditions. Regarding the first point, several tumors revealed an overexpression of this kinesin, thus pushing to look for new Eg5 inhibitors for clinical practice. In addition, the evaluation of Eg5 expression represents a crucial step, as its overexpression could predict a poor prognosis for cancer patients. Referring to the second point, in specific pathological conditions, the reduced activity of Eg5 can be one of the causes of pathological onset. This is the case of Alzheimer's disease (AD), in which Aβ and Tau work as Eg5 inhibitors, or in acquired immune deficiency syndrome (AIDS), in which Tat-mediated Eg5 determines the loss of CD4+ T-lymphocytes. Reduced Eg5 activity, due to mutations of KIF11 gene, is also responsible for pathological conditions such as microcephaly with or without chorioretinopathy, lymphedema, or intellectual disability (MCLRI) and familial exudative vitreous retinopathy (FEVR). In conclusion, this review highlights the double impact that overexpression or loss of function of Eg5 could have in the onset and progression of different pathological situations. This emphasizes, on one hand, a possible role of Eg5 as a potential biomarker and new target in cancer and, on the other hand, the promotion of Eg5 expression/activity as a new therapeutic strategy in different noncancerous diseases.

The sensor applications for prostate and lung cancer biomarkers in terms of electrochemical analysis

Prostate and lung cancers are the most common types of cancer and affect a large part of the population around the world, causing deaths. Therefore, the rapid identification of cancer can profoundly impact reducing cancer-related death rates and protecting human lives. Significant resources have been dedicated to investigating new methods for early disease detection. Cancer biomarkers encompass various biochemical entities, including nucleic acids, proteins, sugars, small metabolites, cytogenetic and cytokinetic parameters, and whole tumor cells in bodily fluids. These tools can be utilized for various purposes, such as risk assessment, diagnosis, prognosis, treatment efficacy, toxicity evaluation, and predicting a return. Due to these versatile and critical purposes, there are widespread studies on the development of new, sensitive, and selective approaches for the determination of cancer biomarkers. This review illustrates the significant lung and prostate cancer biomarkers and their determination utilizing electrochemical sensors, which have the advantage of improved sensitivity, low cost, and simple analysis. Additionally, approaches such as improving sensitivity with nanomaterials and ensuring selectivity with MIPs are used to increase the performance of the sensor. This review aims to overview the most recent electrochemical biosensor applications for determining vital biomarkers of prostate and lung cancers in terms of nanobiosensors and molecularly imprinted polymer (MIP)-based biosensors.

Nuclear protein NOP2 serves as a poor-prognosis predictor of LUAD and aggravates the malignancy of lung adenocarcinoma cells

Recent studies have shown that NOP2, a nucleolar protein, is up-regulated in various cancers, suggesting a potential link to tumor aggressiveness and unfavorable outcomes. This study examines NOP2's role in lung adenocarcinoma (LUAD), a context where its implications remain unclear. Utilizing bioinformatics, we assessed 513 LUAD and 59 normal tissue samples from The Cancer Genome Atlas (TCGA) to explore NOP2's diagnostic and prognostic significance in LUAD. Additionally, in vitro experiments compared NOP2 expression between Beas-2b and A549 cells. Advanced databases and analytical tools, including LINKEDOMICS, STRING, and TISIDB, were employed to further elucidate NOP2's association with LUAD. Our findings indicate a significantly higher expression of NOP2 mRNA and protein in A549 cells compared to Beas-2b cells (P < 0.001). In LUAD, elevated NOP2 levels were linked to decreased Overall Survival (OS) and advanced clinical stages. Univariate Cox analysis revealed that high NOP2 expression correlated with poorer OS in LUAD (P < 0.01), a finding independently supported by multivariate Cox analysis (P < 0.05). The relationship between NOP2 expression and LUAD risk was presented via a Nomogram. Additionally, Gene Set Enrichment Analysis (GSEA) identified seven NOP2-related signaling pathways. A focal point of our research was the interplay between NOP2 and tumor-immune interactions. Notably, a negative correlation was observed between NOP2 expression and the immune infiltration levels of macrophages, neutrophils, mast cells, Natural Killer (NK) cells, and CD8 + T cells in LUAD. Moreover, the expression of NOP2 was related to the sensitivity of various chemotherapeutic drugs. In vitro, we found that downregulating NOP2 can decrease the proliferation, migration and invasion of A549 cells. Furthermore, NOP2 can regulate Caspase3-mediated apoptosis. Collectively, particularly regarding prognosis, immune infiltration and vitro experiments, these findings suggest NOP2's potential of serving as a poor-prognostic biomarker for LUAD and aggravating the malignancy of lung adenocarcinoma cells.

Mechanism of hypoxia-induced exosome circ_0051799 regulating the progression of lung adenocarcinoma

This study attempted to investigate the effect of circ_0051799 on the immune microenvironment of lung adenocarcinoma (LUAD) and the relationship between circ_0051799 and exosomes. The number and morphology of exosomes were verified by nanoparticle tracking, transmission electron microscopy and western blotting. CCK8, EdU, Transwell and flow cytometry were used to verify the regulatory role of exosomes and circ_0051799 on tumor progression. Dual luciferase reporting and RNA immunoprecipitation were used to verify the targeted regulatory relationship between circ_0051799, miR-214-3p and IGF2BP3. WB was used to verify the role of the JAK/STAT pathway in circ_0051799 regulation. Ectopic tumor grafts and in situ models were used to validate in vivo their role in regulating LUAD progression. Hypoxic environment could alter but does not alter its shape. Exosomes can participate in the regulation of macrophage polarization by circ_0051799. In vitro and in vivo assays had shown that circ_0051799 could affect the proliferation and metastasis of LUAD through targeting miR-214-3p mediated IGF2BP3 regulated JAK/STAT pathway. This study found that hypoxia can affect LUAD process by promoting the regulation of macrophage polarization by exosome circ_0051799.

High SNHG expression may predict a poor lung cancer prognosis based on a meta-analysis

BACKGROUND

An increasing number of small nucleolar RNA host genes (SNHGs) have been revealed to be dysregulated in lung cancer tissues, and abnormal expression of SNHGs is significantly correlated with the prognosis of lung cancer. The purpose of this study was to conduct a meta-analysis to explore the correlation between the expression level of SNHGs and the prognosis of lung cancer.

METHODS

A comprehensive search of six related databases was conducted to obtain relevant literature. Relevant information, such as overall survival (OS), progression-free survival (PFS), TNM stage, lymph node metastasis (LNM), and tumor size, was extracted. Hazard ratios (HRs) and 95% confidence intervals (CIs) were pooled to evaluate the relationship between SNHG expression and the survival outcome of lung cancers. Sensitivity and publication bias analyses were performed to explore the stability and reliability of the overall results.

RESULTS

Forty publications involving 2205 lung cancer patients were included in this meta-analysis. The pooled HR and 95% CI values indicated a significant positive association between high SNHG expression and poor OS (HR: 1.890, 95% CI: 1.595-2.185), disease-free survival (DFS) (HR: 2.31, 95% CI: 1.57-3.39) and progression-free survival (PFS) (HR: 2.01, 95% CI: 0.66-6.07). The pooled odds ratio (OR) and 95% CI values indicated that increased SNHG expression may be correlated with advanced TNM stage (OR: 1.509, 95% CI: 1.267-1.799), increase risk of distant lymph node metastasis (OR: 1.540, 95% CI: 1.298-1.828), and large tumor size (OR: 1.509, 95% CI: 1.245-1.829). Sensitivity analysis and publication bias results showed that each result had strong reliability and robustness, and there was no significant publication bias or other bias.

CONCLUSION

Most SNHGs are upregulated in lung cancer tissues, and high expression of SNHGs predicts poor survival outcomes in lung cancer. SNHGs may be potential prognostic markers and promising therapeutic targets.

Mitochondria-related lncRNAs: predicting prognosis, tumor microenvironment and treatment response in lung adenocarcinoma

Lung cancer is the most common type of malignant tumor that affects people in China and even across the globe, as it exhibits the highest rates of morbidity and mortality. Lung adenocarcinoma (LUAD) is a type of lung cancer with a very high incidence. The purpose of this study was to identify potential biomarkers that could be used to forecast the prognosis and improve the existing therapy options for treating LUAD. Clinical and RNA sequencing data of LUAD patients were retrieved from the TCGA database, while the mitochondria-associated gene sets were acquired from the MITOMAP database. Thereafter, Pearson correlation analysis was carried out to screen mitochondria-associated lncRNAs. Furthermore, univariate Cox and Lasso regression analyses were used for the initial screening of the target lncRNAs for prognostic lncRNAs before they could be incorporated into a multivariate Cox Hazard ratio model. Then, the clinical data, concordance index, Kaplan-Meier (K-M) curves, and the clinically-relevant subjects that were approved by the Characteristic Curves (ROC) were employed for assessing the model's predictive value. Additionally, the differences in immune-related functions and biological pathway enrichment between high- and low-risk LUAD groups were examined. Nomograms were developed to anticipate the OS rates of the patients within 1-, 3-, and 5 years, and the differences in drug sensitivity and immunological checkpoints were compared. In this study, 2175 mitochondria-associated lncRNAs were screened. Univariate, multivariate, and Lasso Cox regression analyses were carried out to select 13 lncRNAs with an independent prognostic significance, and a prognostic model was developed. The OS analysis of the established prognostic prediction model revealed significant variations between the high- and low-risk patients. The AUC-ROC values after 1, 3, and 5 years were seen to be 0.746, 0.692, and 0.726, respectively. The results suggested that the prognostic model riskscore could be used as an independent prognostic factor that differed from the other clinical characteristics. After analyzing the findings of the study, it was noted that both the risk groups showed significant differences in their immune functioning, immunological checkpoint genes, and drug sensitivity. The prognosis of patients with LUAD could be accurately and independently predicted using a risk prediction model that included 13 mitochondria-associated lncRNAs.

Unveiling Potential Targeted Therapeutic Opportunities for Co-Overexpressed Targeting Protein for Xklp2 and Aurora-A Kinase in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most prevalent and leading causes of cancer deaths globally, with limited diagnostic and clinically significant therapeutic targets. Identifying the genes and processes involved in developing and progressing LUAD is crucial for developing effective targeted therapeutics and improving patient outcomes. Therefore, the study aimed to explore the RNA sequencing data of LUAD from The Cancer Genome Atlas (TCGA) and gene expression profile datasets involving GSE10072, GSE31210, and GSE32863 from the Gene Expression Omnibus (GEO) databases. The differential gene expression and the downstream analysis determined clinically significant biomarkers using a network-based approach. These therapeutic targets predominantly enriched the dysregulation of mitotic cell cycle regulation and revealed the co-overexpression of Aurora-A Kinase (AURKA) and Targeting Protein for Xklp2 (TPX2) with high survival risk in LUAD patients. The hydrophobic residues of the AURKA-TPX2 interaction were considered as the target site to block the autophosphorylation of AURKA during the mitotic cell cycle. The tyrosine kinase inhibitor (TKI) dacomitinib demonstrated the strong binding potential to hinder TPX2, shielding the AURKA destabilization. This in silico study lays the foundation for repurposing targeted therapeutic options to impede the Protein-Protein Interactions (PPIs) in LUAD progression and aid in future translational investigations.

Trends in Lung Cancer Incidence and Mortality (1990-2019) in the United States: A Comprehensive Analysis of Gender and State-Level Disparities

PURPOSE

Lung cancer is the leading cause of cancer-related deaths in the United States. This study aims to analyze lung cancer incidence, mortality, and related statistics from 1990 to 2019, focusing on national- and state-level trends and exploring potential disparities between sexes.

METHODS

The Global Burden of Disease database was used to extract tracheal, bronchus, and lung cancer mortality data from 1990 to 2019 for both males and females and across all states of the United States. Age-standardized incidence rates, age-standardized mortality rates, disability-adjusted life years (DALYs), and mortality-to-incidence indices (MIIs) were studied to assess for gender-based, geographic, and temporal disparities. Joinpoint regression analysis was performed to further evaluate trends.

RESULTS

The incidence of these cancers in the United States decreased between 1990 and 2019 by 23.35%, with a more significant decline in males (37.73%) than females (1.41%). Similarly, for mortality, a decrease was observed for both sexes combined (26.83%), but much more significantly for males (40.23%) than females (6.01%). The MIIs decreased overall, but there were variations across states. DALYs decreased for both sexes combined, with males experiencing a larger reduction, but an increase was noted in some states for females.

CONCLUSION

This analysis reveals diverse trends pertaining to the incidence, mortality, and disability burden associated with lung cancer by sex and states in the United States, emphasizing the need for targeted interventions to reduce disparities. These findings contribute to our understanding of the current landscape of lung cancer and can inform future strategies for prevention, early detection, and management.

Correlation Between Intranodular Vessels and Tumor Invasiveness of Lung Adenocarcinoma Presenting as Ground-glass Nodules: A Deep Learning 3-Dimensional Reconstruction Algorithm-based Quantitative Analysis on Noncontrast Computed Tomography Images

PURPOSE

To evaluate the role of quantitative features of intranodular vessels based on deep learning in distinguishing pulmonary adenocarcinoma invasiveness.

MATERIALS AND METHODS

This retrospective study included 512 confirmed ground-glass nodules from 474 patients with 241 precursor glandular lesions (PGL), 126 minimally invasive adenocarcinomas (MIA), and 145 invasive adenocarcinomas (IAC). The pulmonary blood vessels were reconstructed on noncontrast computed tomography images using deep learning-based region-segmentation and region-growing techniques. The presence of intranodular vessels was evaluated based on the automatic calculation of vessel prevalence, vascular categories, and vessel volume percentage. Further comparisons were made between different invasive groups by the Mantel-Haenszel χ 2 test, χ 2 test, and analysis of variance.

RESULTS

The detection rate of intranodular vessels in PGL (33.2%) was significantly lower than that of MIA (46.8%, P = 0.011) and IAC (55.2%, P < 0.001), while the vascular categories were similar (all P > 0.05). Vascular changes were more common in IAC and MIA than in PGL, mainly in increased vessel volume percentage (12.4 ± 19.0% vs. 6.3 ± 13.1% vs. 3.9 ± 9.4%, P < 0.001). The average intranodular artery and vein volume percentage of IAC (7.5 ± 14.0% and 5.0 ± 10.1%) was higher than that of PGL (2.1 ± 6.9% and 1.7 ± 5.8%) and MIA (3.2 ± 9.1% and 3.1 ± 8.7%), with statistical significance (all P < 0.05).

CONCLUSIONS

The quantitative analysis of intranodular vessels on noncontrast computed tomography images demonstrated that the ground-glass nodules with increased internal vessel prevalence and volume percentages had higher possibility of tumor invasiveness.

FERM domain-containing protein FRMD6 activates the mTOR signaling pathway and promotes lung cancer progression

FRMD6, a member of the 4.1 ezrin-radixin-moesin domain-containing protein family, has been reported to inhibit tumor progression in multiple cancers. Here, we demonstrate the involvement of FRMD6 in lung cancer progression. We find that FRMD6 is overexpressed in lung cancer tissues relative to in normal lung tissues. In addition, the enhanced expression of FRMD6 is associated with poor outcomes in patients with lung squamous cell carcinoma (n = 75, P = 0.0054) and lung adenocarcinoma (n = 94, P = 0.0330). Cell migration and proliferation in vitro and tumor formation in vivo are promoted by FRMD6 but are suppressed by the depletion of FRMD6. Mechanistically, FRMD6 interacts and colocalizes with mTOR and S6K, which are the key molecules of the mTOR signaling pathway. FRMD6 markedly enhances the interaction between mTOR and S6K, subsequently increasing the levels of endogenous pS6K and downstream pS6 in lung cancer cells. Furthermore, knocking out FRMD6 inhibits the activation of the mTOR signaling pathway in Frmd6-/- gene KO MEFs and mice. Altogether, our results show that FRMD6 contributes to lung cancer progression by activating the mTOR signaling pathway.

Identification of immune activation-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a major subtype of non-small cell lung cancer (NSCLC) with a highly heterogeneous tumor microenvironment. Immune checkpoint inhibitors (ICIs) are more effective in tumors with a pre-activated immune status. However, the potential of the immune activation-associated gene (IAG) signature for prognosis prediction and immunotherapy response assessment in LUAD has not been established. Therefore, it is critical to explore such gene signatures.

Methods

RNA sequencing profiles and corresponding clinical parameters of LUAD were extracted from the TCGA and GEO databases. Unsupervised consistency clustering analysis based on immune activation-related genes was performed on the enrolled samples. Subsequently, prognostic models based on genes associated with prognosis were built using the last absolute shrinkage and selection operator (LASSO) method and univariate Cox regression. The expression levels of four immune activation related gene index (IARGI) related genes were validated in 12 pairs of LUAD tumor and normal tissue samples using qPCR. Using the ESTIMATE, TIMER, and ssGSEA algorithms, immune cell infiltration analysis was carried out for different groups, and the tumor immune dysfunction and rejection (TIDE) score was used to evaluate the effectiveness of immunotherapy.

Results

Based on the expression patterns of IAGs, the TCGA LUAD cohort was classified into two clusters, with those in the IAG-high pattern demonstrating significantly better survival outcomes and immune cell infiltration compared to those in the IAG-low pattern. Then, we developed an IARGI model that effectively stratified patients into different risk groups, revealing differences in prognosis, mutation profiles, and immune cell infiltration within the tumor microenvironment between the high and low-risk groups. Notably, significant disparities in TIDE score between the two groups suggest that the low-risk group may exhibit better responses to ICIs therapy. The IARGI risk model was validated across multiple datasets and demonstrated exceptional performance in predicting overall survival in LUAD, and an IARGI-integrated nomogram was established as a quantitative tool for clinical practice.

Conclusion

The IARGI can serve as valuable biomarkers for evaluating the tumor microenvironment and predicting the prognosis of LUAD patients. Furthermore, these genes probably provide valuable guidance for establishing effective immunotherapy regimens for LUAD patients.

PYCR1 promotes the malignant progression of lung cancer through the JAK-STAT3 signaling pathway via PRODH-dependent glutamine synthesize

BACKGROUND

Lung cancer is a serious threat to human life. It is of great significance to elucidate the pathogenesis of lung cancer and search for new markers. This study evaluate the clinical value of pyrroline-5-carboxylate reductase 1 (PYCR1) and explore its role and mechanisms in the malignant progression of lung cancer.

METHODS

PYCR1 expression and its relationship with prognosis were analyzed using a bioinformatics database. Enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry were utilized to examine the expression of PYCR1 in lung cancer tissues and peripheral blood. PYCR1-overexpressing lung cancer cells were constructed, then the cell proliferative, migration, and invasion ability was examined by the MTT and Transwell assays. siRNA against PRODH and STAT3 inhibitor sttatic was used to further elucidate the underlying mechanisms. Luciferase and CHIP assays were carried out for validate the how PYCR1 regulated PD-L1 expression via STAT3. Xenograft experiment was performed to determine the role of PYCR1 in vivo.

RESULTS

Database analysis showed that PYCR1 expression was significantly increased in lung cancer tissues, and its high expression predicted poor prognosis. Lung cancer tissue and peripheral blood of patients showed obviously increased PYCR1 expression, and the sensitivity and specificity of serum PYCR1 in the diagnosis of lung cancer were 75.7% and 60%, respectively. PYCR1 overexpression enhanced the proliferative, migration, and invasion abilities of lung cancer cells. Both PRODH silence and stattic effectively attenuated the function of PYCR1. Animal experiment and IHC data indicated that PYCR1 could activated STAT3 phosphorylation and PD-L1, as well as suppressed T cell infiltration in lung cancer. Finally, we also validated that PYCR1 promoted PD-L1 transcription by elevating STAT3 binding to the gene promoter.

CONCLUSION

PYCR1 has certain value in the diagnosis and prognosis of lung cancer. Moreover, through regulating JAK-STAT3 signaling pathway, PYCR1 significantly participated in process of lung cancer progression via the metabolism link between proline and glutamine, indicating that PYCR1 might be also a novel therapeutic target.

Depleting DDX1 sensitizes non-small cell lung cancer cells to chemotherapy by attenuating cancer stem cell traits

AIMS

DEAD-box helicase 1 (DDX1) has oncogenic properties in several human cancers. However, the clinical significance and biological role of DDX1 in non-small cell lung cancer (NSCLC) remain elusive. Here, we examined the chemotherapeutic relevance of DDX1 in NSCLC.

MAIN METHODS

We used the UALCAN database, Western blot analysis, and immunohistochemical and RT-qPCR assays to assess DDX1 expression in NSCLC cell lines (H1650 and A549) and patient tissues. The role of DDX1 in the chemosensitivity of NSCLC cells and the underlying mechanisms were determined using colony formation, CCK-8, flow cytometry, wound healing, Transwell, tumor sphere formation, and immunostaining assays, together with a xenograft tumor model in nude mice.

KEY FINDINGS

Our study revealed that DDX1 was overexpressed in NSCLC cell lines and tissues. We further found that depleting DDX1 increased the sensitivity of NSCLC cells to the chemotherapy drug cisplatin, increased cell apoptosis, and inhibited cell migration and invasion. Co-immunoprecipitation assays revealed that DDX1 bound to ADAR1, and increased ADAR1 protein expression. Furthermore, we found that ADAR1 mediated cancer-promoting effects, independent of deaminase activity, by binding to RAC3 mRNA. Our findings not only show that DDX1 mediates chemosensitivity to cisplatin via the ADAR1/RAC3 axis but also highlight the importance of ADARs as essential RNA-binding proteins for cell homeostasis, as well as cancer progression.

SIGNIFICANCE

Our results suggest that DDX1 plays an important role in the development and progression of human NSCLC and that DDX1 may serve as a therapeutic target in NSCLC patients.

Lung cancer screening

Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.

Assessment of circulating biomarkers for detection of lung cancer in a high-risk cohort

BACKGROUND

There is an urgent need for early detection of lung cancer. Screening with low-dose computed tomography (LDCT) is now implemented in the US. Supplementary use of a lung cancer biomarker with high specificity is desirable.

OBJECTIVE

To assess the diagnostic properties of a biomarker panel consisting of cytokeratin 19 fragment (CYFRA 21-1), carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125).

METHODS

A cohort of 250 high-risk patients was investigated on suspicion of lung cancer. Ahead of diagnostic work-up, blood samples taken. Cross-validated prediction models were computed to assess lung cancer detection properties.

RESULTS

In total 32% (79/250) of patients were diagnosed with lung cancer. Area under the curve (AUC) for the three biomarkers was of 0.795, with sensitivity/specificity of 57%/93% and negative predictive value of 83%. When combining the biomarkers with US screening criteria, the AUC was 0.809, while applying only US screening criteria on the cohort, yielded an AUC of 0.62. The ability of the biomarkers to detect stage I-II lung cancer was substantially lower; AUC 0.54.

CONCLUSIONS

In a high-risk cohort, the detection properties of the three biomarkers were acceptable compared to current LDCT screening criteria. However, the ability to detect early stage lung cancer was low.

The Potential Role of MUC16 (CA125) Biomarker in Lung Cancer: A Magic Biomarker but with Adversity

Lung cancer is the second most commonly diagnosed cancer in the world. In terms of the diagnosis of lung cancer, combination carcinoembryonic antigen (CEA) and cancer antigen 125 (CA125) detection had higher sensitivity, specificity, and diagnostic odds ratios than CEA detection alone. Most individuals with elevated serum CA125 levels had lung cancer that was either in stage 3 or stage 4. Serum CA125 levels were similarly elevated in lung cancer patients who also had pleural effusions or ascites. Furthermore, there is strong evidence that human lung cancer produces CA125 in vitro, which suggests that other clinical illnesses outside of ovarian cancer could also be responsible for the rise of CA125. MUC16 (CA125) is a natural killer cell inhibitor. As a screening test for lung and ovarian cancer diagnosis and prognosis in the early stages, CA125 has been widely used as a marker in three different clinical settings. MUC16 mRNA levels in lung cancer are increased regardless of gender. As well, increased expression of mutated MUC16 enhances lung cancer cells proliferation and growth. Additionally, the CA125 serum level is thought to be a key indicator for lung cancer metastasis to the liver. Further, CA125 could be a useful biomarker in other cancer types diagnoses like ovarian, breast, and pancreatic cancers. One of the important limitations of CA125 as a first step in such a screening technique is that up to 20% of ovarian tumors lack antigen expression. Each of the 10 possible serum markers was expressed in 29-100% of ovarian tumors with minimal or no CA125 expression. Therefore, there is a controversy regarding CA125 in the diagnosis and prognosis of lung cancer and other cancer types. In this state, preclinical and clinical studies are warranted to elucidate the clinical benefit of CA125 in the diagnosis and prognosis of lung cancer.

Exploration and validation of hub genes in lung adenocarcinoma based on bioinformatics analysis

BACKGROUND

Genomic abnormality is a crucial factor for lung cancer development. This study used bioinformatics analysis to explore the hub genes involved in lung adenocarcinoma.

METHODS

The GeneCards, Comparative Toxicogenomics Database (CTD), and DISEASES databases were used to screen the genes associated with lung adenocarcinoma. The hub genes were then identified using WebGestalt. The Cancer Genome Atlas (TCGA), UALCAN, and the Human Protein Atlas (HPA) were used to validate the expression of hub genes. The predictive effects of hub genes on the risk of lung adenocarcinoma were evaluated using receiver operating characteristic (ROC) curve analysis. The Tumor-Immune System Interaction Database (TISIDB) was used to estimate the correlation between hub genes and immune infiltration.

RESULTS

A total of 21 genes were defined as common genes associated with lung adenocarcinoma, and from these, AKT1, CD44, and CDKN2A were identified as hub genes. Significant differences in the hub gene mRNA and protein expression were observed between lung adenocarcinoma samples and normal samples derived from the TCGA and UALCAN databases. The area under the ROC curve (AUC) for AKT1, CD44, and CDKN2A in predicting lung adenocarcinoma risk was 0.847, 0.880, and 0.805, respectively, with sensitivity of 89.8%, 93.2%, and 94.9%, respectively. TISIDB analysis indicated that AKT1, CD44, and CDKN2A expression had a strong relationship with immune infiltration in lung adenocarcinoma.

CONCLUSIONS

These hub genes, AKT1, CD44, and CDKN2A, may represent tumor biomarkers that may contribute to the understanding, diagnosis, and treatment of lung adenocarcinoma.

Comprehensive Analysis of the Molecular Characteristics and Prognosis value of AT II-associated Genes in Non-small Cell Lung Cancer

Alveolar type II (AT II) is a key structure of the distal lung epithelium and essential to maintain normal lung homeostasis. Dedifferentiation of AT II cells is significantly correlated with lung tumor progression. However, the potential molecular mechanism and clinical significance of AT II-associated genes for lung cancer has not yet been fully elucidated. In this study, we comprehensively analyzed the gene expression, prognosis value, genetic alteration, and immune cell infiltration of eight AT II-associated genes (AQP4, SFTPB, SFTPC, SFTPD, CLDN18, FOXA2, NKX2-1, and PGC) in Nonsmall Cell Lung Cancer (NSCLC). The results have shown that the expression of eight genes were remarkably reduced in cancer tissues and observably relating to clinical cancer stages. Survival analysis of the eight genes revealed that low-expression of CLDN18, FOXA2, NKX2-1, PGC, SFTPB, SFTPC, and SFTPD were significantly related to a reduced progression-free survival (FP), and low CLDN18, FOXA2, and SFTPD mRNA expression led to a short postprogression survival (PPS). Meanwhile, the alteration of 8 AT II-associated genes covered 273 out of 1053 NSCLC samples (26%). Additionally, the expression level of eight genes were significantly correlated with the infiltration of diverse immune cells, including six types of CD4+T cells, macrophages, neutrophils, B cells, CD8+ T cells, and dendritic cells. In summary, this study provided clues of the values of eight AT II-associated genes as clinical biomarkers and therapeutic targets in NSCLC and might provide some new inspirations to assist the design of new immunotherapies.

Circular RNAs Hsa_circ_101555 and Hsa_circ_008068 as Diagnostic Biomarkers for Early-Stage Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a life-threatening disease worldwide with a high mortality rate. The early diagnosis of LUAD is crucial for improving subsequent treatment and prognosis. However, biomarkers for early detection remain a clinical challenge in LUAD. Here, we aimed to develop circular RNAs (circRNAs) in circulating plasma from LUAD patients as valuable diagnostic biomarkers in LUAD.

Methods

CircRNA expression was determined by circRNA microarray in three pairs of LUAD tumour tissues and patient-matched normal lung tissues. Hsa_circ_101555 and hsa_circ_008068 were selected as potential biomarkers in LUAD tissues and plasma by RT-PCR, respectively. The diagnostic value was analysed by the area under the curve (AUC) and the receiver operating characteristic (ROC) test.

Results

Our results showed that 6261 circRNAs were upregulated and 7238 circRNAs were downregulated in LUAD tumour tissues compared with patient-matched normal lung tissues. Hsa_circ_101555 and hsa_circ_008068 were filtered as biomarkers for early-stage LUAD. Q-PCR results showed that hsa_circ_101555 and hsa_circ_008068 were significantly upregulated in both LUAD cancer tissues and circulating plasma. Hsa_circ_101555 and hsa_circ_008068 were positively associated with tumour differentiation, tumour size and CEA (P<0.05). The ROC analysis showed that hsa_circ_101555 and hsa_circ_008068 had a better diagnostic potential compared to the traditional biomarkers (CEA, SCC, CYFRA21-1) in the detection of early-stage LUAD.

Conclusion

The circular RNAs hsa_circ_101555 and hsa_circ_008068 could serve as novel diagnostic biomarkers for early-stage LUAD.

Construction and evaluation of a nomogram for predicting survival in patients with lung cancer

BACKGROUND

Lung cancer is a heterogeneous disease with a severe disease burden. Because the prognosis of patients with lung cancer varies, it is critical to identify effective biomarkers for prognosis prediction.

METHODS

A total of 2325 lung cancer patients were integrated into four independent sets (training set, validation set I, II and III) after removing batch effects in our study. We applied the microarray data algorithm to screen the differentially expressed genes in the training set. The most robust markers for prognosis were identified using the LASSO-Cox regression model, which was then used to create a Cox model and nomogram.

RESULTS

Through LASSO and multivariate Cox regression analysis, eight genes were identified as prognosis-associated hub genes, followed by the creation of prognosis-associated risk scores (PRS). The results of the Kaplan-Meier analysis in the three validation sets demonstrate the good predictive performance of PRS, with hazard ratios of 2.38 (95% confidence interval (CI), 1.61-3.53) in the validation set I, 1.35 (95% CI, 1.06-1.71) in the validation set II, and 2.71 (95% CI, 1.77-4.18) in the validation set III. Additionally, the PRS demonstrated superior survival prediction in subgroups by age, gender, p-stage, and histologic type (p < 0.0001). The complex model integrating PRS and clinical risk factors also have a good predictive performance for 3-year overall survival.

CONCLUSIONS

In this study, we developed a PRS signature to help predict the survival of lung cancer. By combining it with clinical risk factors, a nomogram was established to quantify the individual risk assessments.

Development of a prognostic pyroptosis-related gene signature for head and neck squamous cell carcinoma patient

Objective

Head and neck squamous cell carcinoma (HNSCC) is a major threat to public health. Pyroptosis is a form of inflammatory programmed cell death that is still incompletely understood. The role of pyroptotic cell death in HNSCC remains to be fully defined. As such, the present study was developed to explore the potential prognostic utility of a pyroptosis-related gene (PRG) signature in HNSCC.

Methods

PRG expression patterns and the associated mutational landscape in HNSCC were analyzed, after which a 6-gene prognostic model was constructed through least absolute shrinkage and selection operator (LASSO) and Cox regression analyses using the TCGA dataset, followed by validation with two GEO datasets (GSE41643 and GSE65858). The relative expression of the genes in the prognostic model was assessed via RT-qPCR in tumor and paired adjacent normal tissue samples from a 32-patient cohort. Potential predictors of patient outcomes associated with this 6-gene model were identified through topological degree analyses of a protein–protein interaction network. Moreover, the prognostic value of NLRP3 as a predictor of HNSCC patient prognosis was established through immunohistochemical (IHC) analyses of samples from 176 HNSCC patients. Lastly, in vitro studies were performed to further demonstrate the relevance of NLRP3 in the context of HNSCC development.

Results

Differentially expressed PRGs were able to readily differentiate between HNSCC tumors and normal tissues. Risk scores derived from the 6-gene PRG model were independent predictors of HNSCC patient prognosis, and genes that were differentially expressed between low- and high-risk groups were associated with tumor immunity. RT-qPCR assays also showed the potential protective role of NLRP3 in HNSCC patients. IHC analyses further supported the value of NLRP3 as a predictor of HNSCC patient outcomes. Invasion and migration assays demonstrated the potential role of NLRP3 in the inhibition of HNSCC development.

Conclusions

Overall, these results highlight a novel prognostic gene signature that offers value in the context of HNSCC patient evaluation, although additional research will be essential to elucidate the mechanisms linking these PRGs to HNSCC outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02476-3.

Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm

Cancer driver gene is a type of gene with abnormal alterations that initiate or promote tumorigenesis. Driver genes can be used to reveal the fundamental pathological mechanisms of tumorigenesis. These genes may have pathological changes at different omics levels. Thus, identifying cancer driver genes involving two or more omics levels is essential. In this study, a computational investigation was conducted on lung cancer driver genes. Four omics levels, namely, epigenomics, genomics, transcriptomics, and post-transcriptomics, were involved. From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. A following screen procedure was performed to extract essential driver genes, which contained three tests: permutation, association, and function tests, which can exclude false-positive genes and screen essential ones. Finally, the intersection operation was performed to obtain novel driver genes involving two omic levels. The analyses on obtained genes indicated that they were associated with fundamental pathological mechanisms of lung cancer at two corresponding omics levels.

Evaluation of EpCAM-specific exosomal lncRNAs as potential diagnostic biomarkers for lung cancer using droplet digital PCR

Accumulating evidence demonstrated that long non-coding RNAs (lncRNAs) derived from exosomes had the potential to be diagnostic markers for lung cancer. However, the diagnostic value of lncRNAs from epithelial cell adhesion molecule (EpCAM)-positive exosomes remains unclear. In the study, serum EpCAM-positive exosomes were isolated with magnetic beads, and their role in lung cancer was investigated in vitro and in vivo. The copy numbers of lncRNAs RP11-77G23.5 and PHEX-AS1 in EpCAM-specific exosomes were quantified by droplet digital PCR (ddPCR). The diagnostic value of RP11-77G23.5 and PHEX-AS1 was tested in the training cohort and verified in the validation cohort. We found that EpCAM-specific exosomes could promote lung cancer development in vitro and in vivo. RP11-77G23.5 and PHEX-AS1 were significantly elevated in EpCAM-specific exosomes from lung cancer patients and could distinguish malignant from benign lung tumors. The amounts of RP11-77G23.5 were statistically higher in the subtype of lung adenocarcinoma (LUAC) than that of lung squamous cell carcinoma (LUSC), showing its capability to subtype LUAC and LUSC, while PHEX-AS1 exhibited distinct expression signatures between lower and higher tumor stages, and without and with distant metastasis, indicating its association with lung cancer progression. In conclusion, the EpCAM-specific exosomal lncRNAs RP11-77G23.5 and PHEX-AS1 may be promising diagnostic biomarkers for lung cancer. KEY MESSAGES: Serum EpCAM-positive exosomes promote lung cancer development in vitro and in vivo. Two EpCAM-specific exosomal lncRNAs can be simultaneously detected by RT-ddPCR. EpCAM-specific exosomal RP11-77G23.5 has the potential to subtype LUAC and LUSC. EpCAM-specific exosomal PHEX-AS1 is associated with lung cancer progression.

Co-delivery of gefitinib and hematoporphyrin by aptamer-modified fluorinated dendrimer for hypoxia alleviation and enhanced synergistic chemo-photodynamic therapy of NSCLC

Although epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs)-based molecular targeted therapy are proved to be effective in the treatment of non-small cell lung cancer (NSCLC) with EGFR mutation, its efficacy is limited by the acquired drug resistance. The combination of EGFR-TKIs with photodynamic therapy (PDT) has been explored to combat NSCLC with promising synergistic results. However, hypoxic tumor microenvironment is associated with the development of EGFR-TKIs resistance and severely limits the efficacy of PDT. Here, we synthesized an aptamer modified fluorinated dendrimer (APF) as a drug carrier and prepared nanocomplexes APFHG by encapsulation of gefitinib (Gef) and hematoporphyrin (Hp). APF has good oxygen-carrying capacity, high drug entrapment efficiency, and could release Gef and Hp in response to intracellular pH. APF can specifically recognize EGFR-positive NSCLC cells and effectively improve the tumor hypoxic microenvironment due to the targeting effect of aptamer and the good oxygen-carrying capacity of the fluorinated dendrimer. Under the laser irradiation, APFHG can significantly increase the production of the intracellular reactive oxygen species and produce a synergistic therapeutic effect in inhibition of cellular growth and induction of cell cycle arrest and apoptosis on both Gef-sensitive and Gef-resistant EGFR-mutant NSCLC cells through PDT/molecular targeted therapy. This work indicates that fluorinated dendrimer could be a potent drug delivery platform to overcome hypoxia-related resistance and the co-delivery of EGFR-TKI and photosensitizer by the fluorinated dendrimer could be a promising therapeutic approach for reversal of EGFR-TKIs resistance in EGFR mutation-positive NSCLC.

Identifying Lung Cancer Cell Markers with Machine Learning Methods and Single-Cell RNA-Seq Data

Non-small cell lung cancer is a major lethal subtype of epithelial lung cancer, with high morbidity and mortality. The single-cell sequencing technique plays a key role in exploring the pathogenesis of non-small cell lung cancer. We proposed a computational method for distinguishing cell subtypes from the different pathological regions of non-small cell lung cancer on the basis of transcriptomic profiles, including a group of qualitative classification criteria (biomarkers) and various rules. The random forest classifier reached a Matthew’s correlation coefficient (MCC) of 0.922 by using 720 features, and the decision tree reached an MCC of 0.786 by using 1880 features. The obtained biomarkers and rules were analyzed in the end of this study.

Carboxypeptidase E mRNA: Overexpression predicts recurrence and death in lung adenocarcinoma cancer patients

BACKGROUND

Effective biomarkers for prediction of recurrence of lung adenocarcinoma cancer (LADC) patients are needed to determine treatment strategies post-surgery to improve outcome.

OBJECTIVE

This study evaluates the efficacy of carboxypeptidase E (CPE) mRNA including its splice isoforms, CPE-ΔN, as a biomarker for predicting recurrence in adenocarcinoma patients.

METHODS

RNA was extracted from resected tumors from 86 patients with different stages of non-small cell LADC. cDNA was synthesized and qRT-PCR carried out to determine the copy numbers of CPE/CPE-ΔN mRNA. Patients were followed for 7 years post-tumor resection to determine recurrence and death.

RESULTS

ROC curve analysis showed the overall AUC for CPE/CPE-ΔN copy number was 0.563 in predicting recurrence and 0.563 in predicting death. Kaplan-Meier survival analysis showed statistical difference (p= 0.018), indicating that patients with high CPE/CPE-ΔN copy numbers had a shorter time of disease-free survival and also shorter time to death (p= 0.035). Subgroup analyses showed that association of disease-free survival time with CPE/CPE-ΔN copy number was stronger among stage I and II LADC patients (p= 0.047).

CONCLUSIONS

CPE/CPE-ΔN mRNA is a potentially useful biomarker for predicting recurrence and death in LADC patients, especially in identifying patients at high risk of recurrence at early stages I and II.

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challenging to detect using current techniques due to the diseases’ location (inaccessibility to biopsy) and size (below normal CT/MRI resolution). In this review, we present a new method for lung disease detection and treatment in small airways based on exhaled aerosols, whose patterns are uniquely related to the health of the lungs. Proof-of-concept studies are first presented in idealized lung geometries. We subsequently describe the recent developments in feature extraction and classification of the exhaled aerosol images to establish the relationship between the images and the underlying airway remodeling. Different feature extraction algorithms (aerosol density, fractal dimension, principal mode analysis, and dynamic mode decomposition) and machine learning approaches (support vector machine, random forest, and convolutional neural network) are elaborated upon. Finally, future studies and frequent questions related to clinical applications of the proposed aerosol breath testing are discussed from the authors’ perspective. The proposed breath testing has clinical advantages over conventional approaches, such as easy-to-perform, non-invasive, providing real-time feedback, and is promising in detecting symptomless lung diseases at early stages.

Females and Males Show Differences in Early-Stage Transcriptomic Biomarkers of Lung Adenocarcinoma and Lung Squamous Cell Carcinoma

The incidence and mortality rates of lung cancers are different between females and males. Therefore, sex information should be an important part of how to train and optimize a diagnostic model. However, most of the existing studies do not fully utilize this information. This study carried out a comparative investigation between sex-specific models and sex-independent models. Three feature selection algorithms and five classifiers were utilized to evaluate the contribution of the sex information to the detection of early-stage lung cancers. Both lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) showed that the sex-specific models outperformed the sex-independent detection of early-stage lung cancers. The Venn plots suggested that females and males shared only a few transcriptomic biomarkers of early-stage lung cancers. Our experimental data suggested that sex information should be included in optimizing disease diagnosis models.

Molecular biomarkers in early stage lung cancer

Low dose computed tomography (LDCT) screening, together with the recent advances in targeted and immunotherapies, have shown to improve non-small cell lung cancer (NSCLC) survival. Furthermore, screening has increased the number of early stage-detected tumors, allowing for surgical resection and multimodality treatments when needed. The need for improved sensitivity and specificity of NSCLC screening has led to increased interest in combining clinical and radiological data with molecular data. The development of biomarkers is poised to refine inclusion criteria for LDCT screening programs. Biomarkers may also be useful to better characterize the risk of indeterminate nodules found in the course of screening or to refine prognosis and help in the management of screening detected tumors. The clinical implications of these biomarkers are still being investigated and whether or not biomarkers will be included in further decision-making algorithms in the context of screening and early lung cancer management still needs to be determined. However, it seems clear that there is much room for improvement even in early stage lung cancer disease-free survival (DFS) rates; thus, biomarkers may be the key to refine risk-stratification and treatment of these patients. Clinicians’ capacity to register, integrate, and analyze all the available data in both high risk individuals and early stage NSCLC patients will lead to a better understanding of the disease’s mechanisms, and will have a direct impact in diagnosis, treatment, and follow up of these patients. In this review, we aim to summarize all the available data regarding the role of biomarkers in LDCT screening and early stage NSCLC from a multidisciplinary perspective. We have highlighted clinical implications, the need to combine risk stratification, clinical data, radiomics, molecular information and artificial intelligence in order to improve clinical decision-making, especially regarding early diagnostics and adjuvant therapy. We also discuss current and future perspectives for biomarker implementation in routine clinical practice.

Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician's Point of View

Starting from the work of Ulivi and colleagues, we aim to summarize the research area of biomarkers for early diagnosis and early stage lung cancer.