Lung Cancer Biomarkers

Use of tumor markers in distinguishing lung adenocarcinoma-associated malignant pleural effusion from tuberculous pleural effusion

BACKGROUND

The distinction between lung adenocarcinoma-associated malignant pleural effusion (MPE) and tuberculous pleural effusion (TPE) continues to pose a challenge. This study sought to assess the supplementary value of tumor markers in enabling a differential diagnosis.

METHODS

Data concerning tumor markers, which included carcinoembryonic antigen (CEA), cancer antigen 125 (CA125), cancer antigen 153 (CA153), cancer antigen 724 (CA724), neuron-specific enolase (NSE), cytokeratin19 fragment (Cyfra21-1), and squamous cell carcinoma antigen (SCCA), in both serum and pleural effusion samples, were retrospectively compiled from lung adenocarcinoma-associated MPE and TPE patients. A comparative analysis of tumor marker concentrations between the two groups was performed to assess diagnostic utility, followed by a multiple logistic regression to control for confounding variables.

RESULTS

While gender, serum CA125 and SCCA, and pleural effusion SCCA manifested comparability between the groups, distinctions were noted in patient age and the concentration of other tumor markers in serum and pleural effusion, which were notably elevated in the MPE group. Multiple logistic regression demonstrated a positive association between the risk of lung adenocarcinoma-associated MPE and levels of CEA and CA153 in serum and pleural effusion, as well as Cyfra21-1 in serum (P < 0.05). The odds ratio for CEA surpassed that of CA153 and Cyfra21-1.

CONCLUSIONS

CEA and CA153 in serum and pleural effusion, and Cyfra21-1 in serum emerge as biomarkers possessing supplementary diagnostic value in distinguishing lung adenocarcinoma-associated MPE from TPE. The diagnostic efficacy of CEA is superior to CA153 and Cyfra21-1. Conversely, the utility of CA125, CA724, NSE, and SCCA appears constrained.

Sperm mitochondria dysfunction in response to testicular cancer

Testicular cancer is the most common form of cancer in young men of reproductive age and its incidence is increasing globally. With the currently successful treatment and 95% survival rate, there is a need for deeper understanding of testicular cancer-related infertility. Most patients with testicular cancer experience semen abnormalities prior to cancer therapy. However, the exact mechanism of the effect of testicular cancer on sperm anomalies is not known. Mitochondria are organelles that play a crucial role in both tumorigenesis and spermatogenesis and their malfunction may be an important factor resulting in sperm abnormalities in testicular cancer patients. Within the scope of this review, we will discuss current knowledge of testicular cancer-related alterations in the ATP production pathway, a possible pathophysiological switch from oxidative phosphorylation (OXPHOS) to glycolysis, as well as the role of oxidative stress promoting sperm dysfunction. In this regard, the review provides a summary of the impact of testicular cancer on sperm quality as a possible consequence of impaired mitochondrial function including the energy metabolic pathways that are known to be altered in the sperm of testicular cancer patients.

Oncogenic circ-SLC16A1 promotes progression of non-small cell lung cancer via regulation of the miR-1287-5p/profilin 2 axis

BACKGROUND

Circular RNAs (circRNAs) are single-stranded RNAs with covalently closed structures that have been implicated in cancer progression. However, the regulatory mechanisms remain largely unclear. So, the aim of this study was to reveal the role and regulatory mechanisms of circ-SLC16A1.

METHODS

In this study, next-generation sequencing was used to identify abnormally expressed circRNAs between cancerous and para-carcinoma tissues. Fluorescence in situ hybridization and quantitative reverse transcription polymerase chain reaction were performed to assess the expression patterns of circ-solute carrier family 16 member 1 (SLC16A1) in non-small cell lung cancer (NSCLC) cells and tissue specimens. The dual-luciferase reporter assay was utilized to identify downstream targets of circ-SLC16A1. Transwell migration, wound healing, 5-ethynyl-2'-deoxyuridine incorporation, cell counting, and colony formation assays were conducted to assess the proliferation and migration of NSCLC cells. A mouse tumor xenograft model was employed to determine the roles of circ-SLC16A1 in NSCLC progression and metastasis in vivo.

RESULTS

The results found that circ-SLC16A1 was upregulated in NSCLC cells and tissues. Downregulation of circ-SLC16A1 inhibited tumor growth by reducing proliferation, lung metastasis, and lymphatic metastasis of NSCLC cells, and arrested the cell cycle in the G1 phase. Also, silencing of circ-SLC16A1 promoted apoptosis of NSCLC cells. The results of bioinformatics analysis and the dual-luciferase reporter assay confirmed that microRNA (miR)-1287-5p and profilin 2 (PFN2) are downstream targets of circ-SLC16A1. PFN2 overexpression or circ-SLC16A1 inhibition restored proliferation and migration of NSCLC cells after silencing of circ-SLC16A1. PFN2 overexpression restored migration and proliferation of NSCLC cells post miR-1287-5p overexpression.

CONCLUSIONS

Collectively, these findings show that miR-1287-5p/PFN2 signaling was associated with downregulation of circ-SLC16A1 and reduced invasion and proliferation of NSCLC cells. So, circ-SLC16A1 is identified as a mediator of multiple pro-oncogenic signaling pathways in NSCLC and can be targeted to suppress tumor progression.

Determination of Tumor Marker Screening for Lung Cancer Using ROC Curves

Introduction

Lung cancer ranks first among malignant tumors worldwide and is a leading cause of cancer-related mortality in both men and women. Combining tumor marker testing is a strategy to screen individuals at high risk of pulmonary cancer and minimize pulmonary cancer mortality. Therefore, tumor marker screening is crucial. In this study, we analyzed combinations of tumor markers for lung cancer screening using receiver operating characteristic (ROC) curve analysis.

Methods

A retrospective descriptive study was conducted on patients diagnosed with lung cancer, as well as healthy and benign lung diseases, using data from the China Huludao Central Hospital database between January 2016 and July 2022. The t-test and ROC curve were utilized to assess the effectiveness of individual tumor marker and the combination of multiple tumor markers. Tumor markers are molecular products metabolized and secreted by tumor tissues, characterized by cells or body fluids. They serve as indicators of tumor stage and grading, monitor treatment response, and predict recurrence.

Results

In this study, 267 healthy participants, 385 patients with benign lesions, and 296 patients with lung cancer underwent tumor marker screening. The sensitivity of five tumor markers-CEA, CYFRA21-1, NSE, pro-GRP, and CA125-was found to be <55%. This study revealed that a single tumor marker had limited value in lung cancer screening. However, combining two or more markers yielded varying area under the curves (AUC), with no significant impact on screening accuracy. The combination of CEA + CA125 demonstrated the highest accuracy for lung cancer screening in healthy participants. At a cutoff of 0.447 for CEA + CA125, the combination showed a sensitivity of 0.676 and specificity of 0.846 for lung cancer screening. Conversely, for patients with benign lung lesions, the optimal combination was CEA + NSE, with a cutoff of 0.393, yielding a sensitivity of 0.645 and specificity of 0.766 for lung cancer screening.

Conclusion

The five tumor markers-CEA, CA125, CY211, NSE, GRP-show promising results in screening healthy individuals and patients with lung cancer. However, only CEA, NSE, and GRP effectively differentiate patients with benign lung lesions from those with lung cancer. A single tumor marker has limited utility in detecting and screening for lung cancer and should be combined with other tumor markers. CEA + CA125 emerges as a superior tumor marker for distinguishing healthy individuals from those with lung cancer, whereas the CEA + NSE combination is more effective in identifying tumor markers in patients with benign lung lesions and lung cancer.

Pre-analytical stability of the CEA, CYFRA 21.1, NSE, CA125 and HE4 tumor markers

BACKGROUND

For lung cancer, circulating tumor markers (TM) are available to guide clinical treatment decisions. To ensure adequate accuracy, pre-analytical instabilities need to be known and addressed in the pre-analytical laboratory protocols.

OBJECTIVE

This study investigates the pre-analytical stability of CA125, CEA, CYFRA 21.1, HE4 and NSE for the following pre-analytical variables and procedures; i) whole blood stability, ii) serum freeze-thaw cycles, iii) electric vibration mixing and iv) serum storage at different temperatures.

METHODS

Left-over patient samples were used and for every investigated variable six patient samples were used and analysed in duplicate. Acceptance criteria were based on analytical performance specifications based on biological variation and significant differences with baseline.

RESULTS

Whole blood was stable for at least 6 hours for all TM except for NSE. Two freeze-thaw cycles were acceptable for all TM except CYFRA 21.1. Electric vibration mixing was allowed for all TM except for CYFRA 21.1. Serum stability at 4°C was 7 days for CEA, CA125, CYFRA 21.1 and HE4 and 4 hours for NSE.

CONCLUSIONS

Critical pre-analytical processing step conditions were identified that, if not taken into account, will result in reporting of erroneous TM results.

Circulating noncoding RNAs: promising biomarkers in liquid biopsy for the diagnosis, prognosis, and therapy of NSCLC

As the second most common malignant tumor in the world, lung cancer is a great threat to human health. In the past several decades, the role and mechanism of ncRNAs in lung cancer as a class of regulatory RNAs have been studied intensively. In particular, ncRNAs in body fluids have attracted increasing attention as biomarkers for lung cancer diagnosis and prognosis and for the evaluation of lung cancer treatment due to their low invasiveness and accessibility. As emerging tumor biomarkers in lung cancer, circulating ncRNAs are easy to obtain, independent of tissue specimens, and can well reflect the occurrence and progression of tumors due to their correlation with some biological processes in tumors. Circulating ncRNAs have a very high potential to serve as biomarkers and hold promise for the development of ncRNA-based therapeutics. In the current study, there has been extensive evidence that circulating ncRNA has clinical significance and value as a biomarker. In this review, we summarize how ncRNAs are generated and enter the circulation, remaining stable for subsequent detection. The feasibility of circulating ncRNAs as biomarkers in the diagnosis and prognosis of non-small cell lung cancer is also summarized. In the current systematic treatment of non-small cell lung cancer, circulating ncRNAs can also predict drug resistance, adverse reactions, and other events in targeted therapy, chemotherapy, immunotherapy, and radiotherapy and have promising potential to guide the systematic treatment of non-small cell lung cancer.

Matrix Metalloproteinases Inhibitors in Cancer Treatment: An Updated Review (2013-2023)

Matrix metalloproteinases (MMPs) are identifiable members of proteolytic enzymes that can degrade a wide range of proteins in the extracellular matrix (ECM). MMPs can be categorized into six groups based on their substrate specificity and structural differences: collagenases, gelatinases, stromelysins, matrilysins, metalloelastase, and membrane-type MMPs. MMPs have been linked to a wide variety of biological processes, such as cell transformation and carcinogenesis. Over time, MMPs have been evaluated for their role in cancer progression, migration, and metastasis. Accordingly, various MMPs have become attractive therapeutic targets for anticancer drug development. The first generations of broad-spectrum MMP inhibitors displayed effective inhibitory activities but failed in clinical trials due to poor selectivity. Thanks to the evolution of X-ray crystallography, NMR analysis, and homology modeling studies, it has been possible to characterize the active sites of various MMPs and, consequently, to develop more selective, second-generation MMP inhibitors. In this review, we summarize the computational and synthesis approaches used in the development of MMP inhibitors and their evaluation as potential anticancer agents.

The rational application of liquid biopsy based on next-generation sequencing in advanced non-small cell lung cancer

BACKGROUND

Plasma and tissue biopsy have both used for targeting actionable driver gene mutations in lung cancer, whose concordance is imperfect. A reliable method to predict the concordance is urgently needed to ease clinical application.

METHODS

A total of 1012 plasma samples, including 519 with paired-tissue biopsy samples, derived from lung adenocarcinoma patients were retrospectively enrolled. We assessed the associations of several clinicopathological characteristics and serum tumor markers with the concordance between plasma and tissue biopsies.

RESULTS

When carcinoembryonic antigen (CEA) levels were higher than thresholds of 15.01 ng/ml and 51.15 ng/ml, the positive predictive value of concordance reached 90% and 95%, respectively. When CEA levels were lower than thresholds of 5.19 ng/ml and 3.26 ng/mL, the negative predictive value of concordance reached 45% and 50%. The performance of CYFRA21-1 in predicting concordance was similar but inferior to CEA (AUC: 0.727 vs. 0.741, p = 0.633). The performance of CEA combined with CYFRA21-1 in predicting the concordance was similar to that of the combination of independent factors derived from the LASSO regression model (AUC: 0.796 vs. 0.818, p = 0.067). CEA (r = 0.47, p < 0.01) and CYFRA21-1 levels (r = 0.45, p < 0.05) were significantly correlated with the maximum variant allele frequency, respectively.

CONCLUSIONS

CEA combined with CYFRA21-1 could effectively predict the concordance between plasma and tissue biopsies, which could be used for evaluating the priority of plasma and tissue biopsies for gene testing to timely guide clinical applications in advanced lung adenocarcinoma patients.

Secreted proteins MDK, WFDC2, and CXCL14 as candidate biomarkers for early diagnosis of lung adenocarcinoma

BACKGROUND

Early diagnosis of lung adenocarcinoma (LUAD), one of the most common types of lung cancer, is very important to improve the prognosis of patients. The current methods can't meet the requirements of early diagnosis. There is a pressing need to identify novel diagnostic biomarkers. Secretory proteins are the richest source for biomarker research. This study aimed to identify candidate secretory protein biomarkers for early diagnosis of LUAD by integrated bioinformatics analysis and clinical validation.

METHODS

Differentially expressed genes (DEGs) of GSE31210, gene expression data of early stage of LUAD, were analyzed by GEO2R. Upregulated DEGs predicted to encode secreted proteins were obtained by taking the intersection of the DEGs list with the list of genes encoding secreted proteins predicted by the majority decision-based method (MDSEC). The expressions of the identified secreted proteins in the lung tissues of early-stage LUAD patients were further compared with the healthy control group in mRNA and protein levels by using the UALCAN database (TCGA and CPTAC). The selected proteins expressed in plasma were further validated by using Luminex technology. The diagnostic value of the screened proteins was evaluated by receiver operating characteristic (ROC) analysis. Cell counting kit-8 assay was carried out to investigate the proliferative effects of these screened proteins.

RESULTS

A total of 2183 DEGs, including 1240 downregulated genes and 943 upregulated genes, were identified in the GSE31210. Of the upregulated genes, 199 genes were predicted to encode secreted proteins. After analysis using the UALCAN database, 16 molecules were selected for further clinical validation. Plasma concentrations of three proteins, Midkine (MDK), WAP four-disulfide core domain 2 (WFDC2), and C-X-C motif chemokine ligand 14 (CXCL14), were significantly higher in LUAD patients than in healthy donors. The area under the curve values was 0.944, 0.881, and 0.809 for MDK, WFDC2, and CXCL14, 0.962 when combined them. Overexpression of the three proteins enhanced the proliferation activity of A549 cells.

CONCLUSIONS

MDK, WFDC2, and CXCL14 were identified as candidate diagnostic biomarkers for early-stage LUAD and might also play vital roles in tumorigenesis.

Liquid Biopsy for Lung Cancer: Up-to-Date and Perspectives for Screening Programs

Lung cancer is the deadliest cancer worldwide. Tissue biopsy is currently employed for the diagnosis and molecular stratification of lung cancer. Liquid biopsy is a minimally invasive approach to determine biomarkers from body fluids, such as blood, urine, sputum, and saliva. Tumor cells release cfDNA, ctDNA, exosomes, miRNAs, circRNAs, CTCs, and DNA methylated fragments, among others, which can be successfully used as biomarkers for diagnosis, prognosis, and prediction of treatment response. Predictive biomarkers are well-established for managing lung cancer, and liquid biopsy options have emerged in the last few years. Currently, detecting EGFR p.(Tyr790Met) mutation in plasma samples from lung cancer patients has been used for predicting response and monitoring tyrosine kinase inhibitors (TKi)-treated patients with lung cancer. In addition, many efforts continue to bring more sensitive technologies to improve the detection of clinically relevant biomarkers for lung cancer. Moreover, liquid biopsy can dramatically decrease the turnaround time for laboratory reports, accelerating the beginning of treatment and improving the overall survival of lung cancer patients. Herein, we summarized all available and emerging approaches of liquid biopsy-techniques, molecules, and sample type-for lung cancer.

Blood protein biomarkers in lung cancer

Lung cancer has consistently ranked first as the cause of cancer-associated mortality. The 5-year survival rate has risen slowly, and the main obstacle to improving the prognosis of patients has been that lung cancer is usually diagnosed at an advanced or incurable stage. Thus, early detection and timely intervention are the most effective ways to reduce lung cancer mortality. Tumor-specific molecules and cellular elements are abundant in circulation, providing real-time information in a noninvasive and cost-effective manner during lung cancer development. These circulating biomarkers are emerging as promising tools for early detection of lung cancer and can be used to supplement computed tomography screening, as well as for prognosis prediction and treatment response monitoring. Serum and plasma are the main sources of circulating biomarkers, and protein biomarkers have been most extensively studied. In this review, we summarize the research progress on three most common types of blood protein biomarkers (tumor-associated antigens, autoantibodies, and exosomal proteins) in lung cancer. This review will potentially guide researchers toward a more comprehensive understanding of candidate lung cancer protein biomarkers in the blood to facilitate their translation to the clinic.

Accurate detection of lung cancer-related microRNA through CRISPR/Cas9-assisted garland rolling circle amplification

BACKGROUND

MicroRNA (miRNA) is reported to be closely related to a variety of pathophysiological processes for carcinoma and considered a potential biomarker for the diagnosis of lung cancer with brain metastasis. However, developing an accurate and sensitive miRNA detection method has proven to be a challenge. The aim of the present study was to integrate the advantages of rolling circle amplification (RCA), clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated nucleases 9 (Cas9), and catalytic hairpin assembly (CHA) technologies to develop an miRNA detection method.

METHODS

In the present study, we developed a novel approach for the sensitive and accurate detection of miRNA through integrating garland RCA and CRISPR/Cas9-assisted signal generation. In this method, target miRNA cyclized dumbbell padlock and triggered the RCA process to form long single-stranded DNA products with a repeated hairpin structure. Double-stranded DNA sequences (dsDNA) were formed with the addition of complementary sequences. With the assistance of the Cas9 enzyme for specific recognition and cleavage of formed dsDNA, RCA products were disassembled into hairpin probes. The generated hairpin probe could be unfolded by target miRNA to initiate the CHA process for signal generation.

RESULTS

Through integration of the RCA and CHA processes, the method demonstrated favorable detection performance. The correlation equation between the signal and concentration of target miRNA was determined to be Y=312.3 × lgC + 2108, with a high correlation coefficient of 0.9786. The approach also exhibited high selectivity to the mismatched miRNAs.

CONCLUSIONS

Our method could be used in the screening, diagnosis, and prognosis of multiple diseases without complicated thermal cycling instrumentation.

Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 as novel diagnostic biomarkers for lung adenocarcinoma

Objective

TRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs) are recognized as novel and potential types of non-coding RNAs (ncRNAs), and several tRF/tiRNA signatures are closely associated with tumor diagnosis. This study aimed to analyze the expression profiles of plasma tRFs/tiRNAs and to clarify their diagnostic value in lung adenocarcinoma (LUAD).

Methods

The differential expression profiles of plasma tRFs/tiRNAs in patients with four patients with early LUAD, four patients with advanced LUAD, and four healthy controls were analyzed using high-throughput sequencing technology. Then, plasma tRFs/tiRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR), and their diagnostic efficiency was appraised by receiver operating characteristic curve analysis. The correlation of candidate plasma tRFs/tiRNAs with clinicopathological features was also analyzed. Finally, bioinformatics analysis was performed to explore and identify the potential biological pathways induced by tRFs/tiRNAs.

Results

The sequencing results revealed that tRFs/tiRNAs from plasma samples in patients with LUAD were differently expressed, supporting the necessity of exploring their potential as biomarkers. The validation results of qRT-PCR demonstrated that the expression level of tRF-1:29-Pro-AGG-1-M6 was downregulated in LUAD, while that of tRF-55:76-Tyr-GTA-1-M2 was upregulated, which was consistent with the sequencing data. The areas under the receiver operating characteristic curve of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 were 0.882 and 0.896, respectively, which have significant values in the diagnosis of LUAD. The expressions of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 in LUAD were obviously correlated with various clinicopathological features such as tumor–node–metastasis stage, node stage, and the expression levels of carcinoembryonic antigen. In addition, their expression was significantly altered from before to after tumor resection in LUAD patients. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses further indicated that tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 are widely distributed and apparently enriched in several tumor-related signaling pathways.

Conclusions

Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 may be promising components in the development of highly sensitive and non-invasive biomarkers for LUAD diagnosis.

Circulating TP73-AS1 and CRNDE serve as diagnostic and prognostic biomarkers for non-small cell lung cancer

BACKGROUND

Circulating long noncoding RNAs (lncRNAs) are considered a new class of biomarkers for the diagnosis and prognosis of various malignancies. We aimed to identify circulating lncRNAs as biomarkers for the diagnosis and prognosis of non-small cell lung cancer (NSCLC).

METHODS

The expression of 14 candidate lncRNAs was measured in matched cancer and ipsilateral normal lung tissues of 20 patients with NSCLC using quantitative reverse-transcription PCR. In plasma samples from training and testing sets, significantly and aberrantly expressed lncRNAs, TA73-AS1 and CRNDE, were further analyzed. Receiver operating characteristic (ROC) curves were constructed, and the areas under the ROC curves (AUC) were obtained to assess diagnostic performance. The Kaplan-Meier survival analysis was used to assess the impact of plasma TA73-AS1 and CRNDE expression on tumor-free survival (TFS) of patients with NSCLC. The effect of TP73-AS1 expression on NSCLC cells was investigated in vitro.

RESULTS

AUC values of plasma TA73-AS1 and CRNDE were 0.822 and 0.815 in the training set and 0.843 and 0.804 in the testing set, respectively, to distinguish NSCLC from healthy controls. The combination of plasma TP73-AS1, CRNDE, and two classical tumor markers, carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1), showed excellent diagnostic performance for NSCLC (AUC =0.927 in the training set; AUC = 0.925 in the testing set). Furthermore, the high expression of the two plasma lncRNAs correlated with worse TFS in patients with NSCLC. In vitro cell model studies revealed that TP73-AS1 overexpression facilitated NSCLC cell survival, invasion, and migration.

CONCLUSION

Circulating TP73-AS1 and CRNDE could be potential biomarkers for the diagnosis and prognostic prediction of NSCLC.

Proteomic Analysis of Human Sputum for the Diagnosis of Lung Disorders: Where Are We Today?

The identification of markers of inflammatory activity at the early stages of pulmonary diseases which share common characteristics that prevent their clear differentiation is of great significance to avoid misdiagnosis, and to understand the intrinsic molecular mechanism of the disorder. The combination of electrophoretic/chromatographic methods with mass spectrometry is currently a promising approach for the identification of candidate biomarkers of a disease. Since the fluid phase of sputum is a rich source of proteins which could provide an early diagnosis of specific lung disorders, it is frequently used in these studies. This report focuses on the state-of-the-art of the application, over the last ten years (2011-2021), of sputum proteomics in the investigation of severe lung disorders such as COPD; asthma; cystic fibrosis; lung cancer and those caused by COVID-19 infection. Analysis of the complete set of proteins found in sputum of patients affected by these disorders has allowed the identification of proteins whose levels change in response to the organism's condition. Understanding proteome dynamism may help in associating these proteins with alterations in the physiology or progression of diseases investigated.

Application of two-dimensional difference gel electrophoresis to identify protein changes between center, margin, and adjacent non-tumor tissues obtained from non-small-cell lung cancer with adenocarcinoma or squamous cell carcinoma subtype

Lung cancer is responsible for the most cancer-related mortality worldwide and the mechanism of its development is poorly understood. Proteomics has become a powerful tool offering vital knowledge related to cancer development. Using a two-dimensional difference gel electrophoresis (2D-DIGE) approach, we sought to compare tissue samples from non-small-cell lung cancer (NSCLC) patients taken from the tumor center and tumor margin. Two subtypes of NSCLC, adenocarcinoma (ADC) and squamous cell carcinoma (SCC) were compared. Data are available via ProteomeXchange with identifier PXD032736 and PXD032962 for ADC and SCC, respectively. For ADC proteins, 26 significant canonical pathways were identified, including Rho signaling pathways, a semaphorin neuronal repulsive signaling pathway, and epithelial adherens junction signaling. For SCC proteins, nine significant canonical pathways were identified, including hypoxia-inducible factor-1α signaling, thyroid hormone biosynthesis, and phagosome maturation. Proteins differentiating the tumor center and tumor margin were linked to cancer invasion and progression, including cell migration, adhesion and invasion, cytoskeletal structure, protein folding, anaerobic metabolism, tumor angiogenesis, EMC transition, epithelial adherens junctions, and inflammatory responses. In conclusion, we identified several proteins that are important for the better characterization of tumor development and molecular specificity of both lung cancer subtypes. We also identified proteins that may be important as biomarkers and/or targets for anticancer therapy.

Combined Microbiome and Metabolome Analysis Reveals a Novel Interplay Between Intestinal Flora and Serum Metabolites in Lung Cancer

As the leading cause of cancer death, lung cancer seriously endangers human health and quality of life. Although many studies have reported the intestinal microbial composition of lung cancer, little is known about the interplay between intestinal microbiome and metabolites and how they affect the development of lung cancer. Herein, we combined 16S ribosomal RNA (rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC-MS) technology to analyze intestinal microbiota composition and serum metabolism profile in a cohort of 30 lung cancer patients with different stages and 15 healthy individuals. Compared with healthy people, we found that the structure of intestinal microbiota in lung cancer patients had changed significantly (Adonis, p = 0.021). In order to determine how intestinal flora affects the occurrence and development of lung cancer, the Spearman rank correlation test was used to find the connection between differential microorganisms and differential metabolites. It was found that as thez disease progressed, L-valine decreased. Correspondingly, the abundance of Lachnospiraceae_UCG-006, the genus with the strongest association with L-valine, also decreased in lung cancer groups. Correlation analysis showed that the gut microbiome and serum metabolic profile had a strong synergy, and Lachnospiraceae_UCG-006 was closely related to L-valine. In summary, this study described the characteristics of intestinal flora and serum metabolic profiles of lung cancer patients with different stages. It revealed that lung cancer may be the result of the mutual regulation of L-valine and Lachnospiraceae_UCG-006 through the aminoacyl-tRNA biosynthesis pathway, and proposed that L-valine may be a potential marker for the diagnosis of lung cancer.

Integrated 5-hydroxymethylcytosine and fragmentation signatures as enhanced biomarkers in lung cancer

Background

Lung cancer is one of most common cancers worldwide, with a 5-year survival rate of less than 20%, which is mainly due to late-stage diagnosis. Noninvasive methods using 5-hydroxymethylation of cytosine (5hmC) modifications and fragmentation profiles from 5hmC cell-free DNA (cfDNA) sequencing provide an opportunity for lung cancer detection and management.

Results

A total of 157 lung cancer patients were recruited to generate the largest lung cancer cfDNA 5hmC dataset, which mainly consisted of 62 lung adenocarcinoma (LUAD), 48 lung squamous cell carcinoma (LUSC) and 25 small cell lung cancer (SCLC) patients, with most patients (131, 83.44%) at advanced tumor stages. A 37-feature 5hmC model was constructed and validated to distinguish lung cancer patients from healthy controls, with areas under the curve (AUCs) of 0.8938 and 0.8476 (sensitivity = 87.50% and 72.73%, specificity = 83.87% and 80.60%) in two distinct validation sets. Furthermore, fragment profiles of cfDNA 5hmC datasets were first explored to develop a 48-feature fragmentation model with good performance (AUC = 0.9257 and 0.822, sensitivity = 87.50% and 78.79%, specificity = 80.65% and 76.12%) in the two validation sets. Another diagnostic model integrating 5hmC signals and fragment profiles improved AUC to 0.9432 and 0.8639 (sensitivity = 87.50% and 83.33%, specificity = 90.30% and 77.61%) in the two validation sets, better than models based on either of them alone and performing well in different stages and lung cancer subtypes. Several 5hmC markers were found to be associated with overall survival (OS) and disease-free survival (DFS) based on gene expression data from The Cancer Genome Atlas (TCGA).

Conclusions

Both the 5hmC signal and fragmentation profiles in 5hmC cfDNA data are sensitive and effective in lung cancer detection and could be incorporated into the diagnostic model to achieve good performance, promoting research focused on clinical diagnostic models based on cfDNA 5hmC data.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01233-7.

Integrating microRNA expression, miRNA-mRNA regulation network and signal pathway: a novel strategy for lung cancer biomarker discovery

Background

Since there are inextricably connections among molecules in the biological networks, it would be a more efficient and accurate research strategy to screen microRNA (miRNA) markers combining with miRNA-mRNA regulatory networks. The independent regulation mode is more “fragile” and “influential” than the co-regulation mode. miRNAs can be used as biomarkers if they can independently regulate hub genes with important roles in the PPI network, simultaneously the expression products of the regulated hub genes play important roles in the signaling pathways of related tissue diseases.

Methods

We collected miRNA expression of non-small cell lung cancer (NSCLC) from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Volcano plot and signal-to-noise ratio (SNR) methods were used to obtain significant differentially expressed (SDE) miRNAs from the TCGA database and GEO database, respectively. A human miRNA-mRNA regulatory network was constructed and the number of genes uniquely targeted (NOG) by a certain miRNA was calculated. The area under the curve (AUC) values were used to screen for clinical sensitivity and specificity. The candidate markers were obtained using the criteria of the top five maximum AUC values and NOG ≥ 3. The protein–protein interaction (PPI) network was constructed and independently regulated hub genes were obtained. Gene Ontology (GO) analysis and KEGG pathway analysis were used to identify genes involved in cancer-related pathways. Finally, the miRNA which can independently regulate a hub gene and the hub gene can participate in an important cancer-related pathway was considered as a biomarker. The AUC values and gene expression profile analysis from two external GEO datasets as well as literature validation were used to verify the screening capability and reliability of this marker.

Results

Fifteen SDE miRNAs in lung cancer were obtained from the intersection of volcano plot and SNR based on the GEO database and the TCGA database. Five miRNAs with the top five maximum AUC values and NOG ≥ 3 were screened out. A total of 61 hub genes were obtained from the PPI network. It was found that the hub gene GTF2F2 was independently regulated by miR-708-5p. Further pathway analysis indicated that GTF2F2 participates in protein expression by binding with polymerase II, and it can regulate transcription and accelerate tumor growth. Hence, miR-708-5p could be used as a biomarker. The good screening capability and reliability of miR-708-5p as a lung cancer marker were confirmed by AUC values and gene expression profiling of external datasets, and experimental literature. The potential mechanism of miR-708-5p was proposed.

Conclusions

This study proposes a new idea for lung cancer marker screening by integrating microRNA expression, regulation network and signal pathway. miR-708-5p was identified as a biomarker using this novel strategy. This study may provide some help for cancer marker screening.

Firefighters' occupational exposure: Contribution from biomarkers of effect to assess health risks

Firefighting is physically and physiologically exhausting besides encompassing exposure to toxic fire emissions. Biomonitoring studies from the past five years have been significantly contributing to characterize the occupational-related health effects in this group of professionals and to improve risk assessment. Therefore, this study gathers and critically discusses the most characterized biomarkers of effect (oxidative stress, DNA and protein damage, stress hormones, inflammation, and vascular, lung, and liver injury), including those potentially more promising to be explored in future studies, and their relation with health outcomes. Various studies proved an association between exposures to fire emissions and/or heat and significantly altered values of biomarkers of inflammation (soluble adhesion molecules, tumor necrosis factor, interleukins, and leucocyte count), vascular damage and tissue injury (pentraxin-3, vascular endothelial growth factor, and cardiac troponin T) in firefighting forces. Moreover, preliminary data of DNA damage in blood, urinary mutagenicity and 8-isoprostaglandin in exhaled breath condensate suggest that these biomarkers of oxidative stress should be further explored. However, most of the reported studies are based on cross-sectional designs, which limit full identification and characterization of the risk factors and their association with development of work-related diseases. Broader studies based on longitudinal designs and strongly supported by the analysis of several types of biomarkers in different biological fluids are further required to gain deeper insights into the firefighters occupational related health hazards and contribute to implementation of new or improved surveillance programs.

Salivary Biomarkers in Lung Cancer

A very low percentage of lung cancer (LC) cases are discovered at an early and treatable stage of the disease, leading to an abysmally low 5-year survival rate. This underscores the immediate necessity for improved diagnostic, prognostic, and predictive biomarkers for LC. Biopsied lung tissue, blood, and plasma are common sources used for LC diagnosis and monitoring of the disease. A growing number of studies have reported saliva to be a useful biological sample for early and noninvasive detection of oral and systemic diseases. Nevertheless, salivary biomarker discovery remains underresearched. Here, we have compiled the available literature to provide an overview of the current understanding of salivary markers for LC detection and provided perspectives for future clinical significance. Valuable markers with diagnostic and prognostic potentials in LC have been discovered in saliva, including metabolic (catalase activity, triene conjugates, and Schiff bases), inflammatory (interleukin 10, C-X-C motif chemokine ligand 10), proteomic (haptoglobin, zinc-α-2-glycoprotein, and calprotectin), genomic (epidermal growth factor receptor), and microbial candidates (Veillonella and Streptococcus). In combination, with each other and with other established screening methods, these salivary markers could be useful for improving early detection of the disease and ultimately improve the survival odds of LC patients. The existing literature suggests that saliva is a promising biological sample for identification and validation of biomarkers in LC, but how saliva can be utilized most effectively in a clinical setting for LC management is still under investigation.

New Trends in Precision Medicine: A Pilot Study of Pure Light Scattering Analysis as a Useful Tool for Non-Small Cell Lung Cancer (NSCLC) Diagnosis

Simple Summary

A reliable method for a fast diagnosis of non-small cell lung cancer (NSCLC) would greatly help in improving therapeutic success in personalized medicine approaches. Thus, in the present study, a new idea was proposed: a morphological single-cell analysis approach combined with a microfluidic device for liquid biopsy. The investigation of the NSCLC sample at different culturing times created the possibility of understanding the evolution of different cell types and their morphological changes, making the Circulating Tumour Cells (CTC) predominance against all other cell classes visible.

Abstract

Background: To date, in personalized medicine approaches, single-cell analyses such as circulating tumour cells (CTC) are able to reveal small structural cell modifications, and therefore can retrieve several biophysical cell properties, such as the cell dimension, the dimensional relationship between the nucleus and the cytoplasm and the optical density of cellular sub-compartments. On this basis, we present in this study a new morphological measurement approach for the detection of vital CTC from pleural washing in individual non-small cell lung cancer (NSCLC) patients. Materials and methods: After a diagnosis of pulmonary malignancy, pleural washing was collected from nine NSCLC patients. The collected samples were processed with a density gradient separation process. Light scattering analysis was performed on a single cell. The results of this analysis were used to obtain the cell’s biophysical pattern and, later on, as basis for Machine Learning (ML) on unknown samples. Results: Morphological single-cell analysis followed by ML show a predictive picture for an NSCLC patient, screening that it is possible to distinguish CTC from other cells. Moreover, we find that the proposed measurement approach was fast, reliable, label-free, identifying and count CTC in a biological fluid. Conclusions: Our findings demonstrate that CTC Biophysical Profile by Pure Light Scattering in NSCLC could be used as a promising diagnostic candidate in NSCLC patients.

Construction of a Prognostic Model in Lung Adenocarcinoma Based on Ferroptosis-Related Genes

Background: Lung adenocarcinoma is one of the most common malignant tumors of the respiratory system, ranking first in morbidity and mortality among all cancers. This study aims to establish a ferroptosis-related gene-based prognostic model to investigate the potential prognosis of lung adenocarcinoma. Methods: We obtained gene expression data with matching clinical data of lung adenocarcinoma from the The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The ferroptosis-related genes (FRGs) were downloaded from three subgroups in the ferroptosis database. Using gene expression differential analysis, univariate Cox regression, and LASSO regression analysis, seven FRGs with prognostic significance were identified. The result of multivariate Cox analysis was utilized to calculate regression coefficients and establish a risk-score formula that divided patients with lung adenocarcinoma into high-risk and low-risk groups. The TCGA results were validated using GEO data sets. Then we observed that patients divided in the low-risk group lived longer than the overall survival (OS) of the other. Then we developed a novel nomogram including age, gender, clinical stage, TNM stage, and risk score. Results: The areas under the curves (AUCs) for 3- and 5-years OS predicted by the model were 0.823 and 0.852, respectively. Calibration plots and decision curve analysis also confirmed the excellent predictive performance of the model. Subsequently, gene function enrichment analysis revealed that the identified FRGs are important in DNA replication, cell cycle regulation, cell adhesion, chromosomal mutation, oxidative phosphorylation, P53 signaling pathway, and proteasome processes. Conclusions: Our results verified the prognostic significance of FRGs in patients with lung adenocarcinoma, which may regulate tumor progression in a variety of pathways.

Clinical Significance of CYFRA21-1, AFP, CA-153, CEA, and CA-199 in the Diagnosis of Lung Cancer Ocular Metastasis in Hypertension Population

Purpose: To detect lung metastases, we conducted a retrospective study to improve patient prognosis.

Methods: Hypertension patients with ocular metastases (OM group; n = 58) and without metastases (NM group; n = 1,217) were selected from individuals with lung cancer admitted to our hospital from April 2005 to October 2019. The clinical characteristics were compared by Student's t-test and chi-square test. Independent risk factors were identified by binary logistic regression, and their diagnostic value evaluated by receiver operating characteristic curve analysis.

Results: Age and sex did not differ significantly between OM and NM groups; There were significant differences in pathological type and treatment. Adenocarcinoma was the main pathological type in the OM group (67.24%), while squamous cell carcinoma was the largest proportion (46.43%) in the NM group, followed by adenocarcinoma (34.10%). The OM group were treated with chemotherapy (55.17%), while the NM group received both chemotherapy (39.93%) and surgical treatment (37.06%). Significant differences were detected in the concentrations of cancer antigen (CA)−125, CA-199, CA-153, alpha fetoprotein (AFP), carcinoembryonic antigen (CEA), cytokeratin fraction 21-1 (CYFRA21-1), total prostate-specific antigen, alkaline phosphatase, and hemoglobin (Student's t-test). Binary logistic regression analysis indicated that CA-199, CA-153, AFP, CEA, and CYRFA21-1 were independent risk factors for lung cancer metastasis. AFP (98.3%) and CEA (89.3%) exhibited the highest sensitivity and specificity, respectively, while CYRFA21-1 had the highest area under the ROC curve value (0.875), with sensitivity and specificity values of 77.6 and 87.0%, respectively. Hence, CYFRA21-1 had the best diagnostic value.

An Inflammation-Related Nine-Gene Signature to Improve Prognosis Prediction of Lung Adenocarcinoma

Background

A novel predictive model was rarely reported based on inflammation-related genes to explore clinical outcomes of lung adenocarcinoma (LUAD) patients.

Methods

Using TCGA database, we screened nine inflammation-related genes with a prognostic value, and LASSO regression was applied for model construction. The predictive value of the prognostic signature developed from inflammation-related genes was assessed by survival assays and multivariate assays. PCA and t-SNE analysis were performed to demonstrate clustering abilities of risk scores.

Results

Thirteen inflammation-related genes (BTG2, CCL20, CD69, DCBLD2, GPC3, IL7R, LAMP3, MMP14, NMUR1, PCDH7, PIK3R5, RNF144B, and TPBG) with prognostic values were finally identified. LASSO regression further screened nine candidates (BTG2, CCL20, CD69, IL7R, MMP14, NMUR1, PCDH7, RNF144B, and TPBG). Then, a prognostic prediction model using the above nine genes was constructed. A reliable clustering ability of risk score was demonstrated by PCA and t-SNE assays in 500 LUAD patients. The survival assays revealed that the overall survivals of the high-risk group were distinctly poorer than those of the low-risk group with 1-, 3-, and 5-year AUC values of 0.695, 0.666, and 0.694, respectively. Finally, multivariate assays demonstrated the scoring system as an independent prognostic factor for overall survival.

Conclusions

Our study shows that the signature of nine inflammation-related genes can be used as a prognostic marker for LUAD.

Clinical Utility of Circulating Tumor Cells in the Early Detection of Lung Cancer in Patients with a Solitary Pulmonary Nodule

Objective: Lung cancer is the most common cancer and can appear as a solitary pulmonary nodule. Early detection of lung cancer in this patient population would be beneficial for the disease management. In this study, the potential application of circulating tumor cells (CTCs) on early detection of lung cancer in this population was investigated. Methods: The number of CTCs in bronchoalveolar lavage fluid and serum levels of tumor-related markers, cancer antigen 125 (CA125), carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) were measured in patients with a solitary pulmonary nodule. The association between CTCs and lung cancer was examined. The diagnosis performances of CTCs and selected tumor-related markers were compared. Results: The CTC positivity was significantly associated with lung cancer (P = .009). The sensitivity of CTCs and CA125, CEA, NSE, and CA125/CEA/NSE was 75%, 5.6%, 0%, 25%, and 33%, respectively. The sensitivity of CTCs was improved from 75% to 83% by the combination with CA125 or NSE. Conclusion: CTCs may be helpful for the early detection of lung cancer in patients with a solitary pulmonary nodule.

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.

Circular RNA_0001946 is insufficiently expressed in tumor tissues, while its higher expression correlates with less lymph node metastasis, lower TNM stage, and improved prognosis in NSCLC patients

Objective

Circular RNA_0001946 (circ_0001946) inhibits tumor progression but promotes chemosensitivity in non‐small‐cell lung cancer (NSCLC); however, its correlation with tumor features and prognosis in NSCLC patients is still unclear; therefore, this study aimed to investigate these issues.

Methods

A total of 284 NSCLC patients were retrospectively analyzed. Circ_0001946 expression in tumor (n = 284) and adjacent (n = 125) tissues was detected by the reverse transcription‐quantitative polymerase chain reaction. Meanwhile, patients’ clinical characteristics, recurrence, and survival data were extracted from the electrical database.

Results

Circ_0001946 expression in adjacent tissues was over 3‐folds as that in tumor tissues (P < .001). Meanwhile, higher tumor circ_0001946 expression was correlated with less lymph node metastasis (P < .001) and decreased TNM stage (P = .001), but did not correlate with other clinicopathological features. Moreover, higher tumor circ_0001946 expression was associated with prolonged disease‐free survival (DFS) (P < .001) and overall survival (OS) (P < .001), respectively. Subgroup analyses revealed that higher tumor circ_0001946 was correlated with improved DFS in patients with TNM stage I, II, or III, respectively (all P < .05), while only correlated with prolonged OS in patients with TNM stage III (P = .037), but not in patients with TNM stage I or II. Further multivariate Cox's proportional hazard regression analyses suggested that higher tumor circ_0001946 expression could independently predict improved DFS (P < .001, hazard ratio (HR) = 0.719) and OS (P < .001, HR = 0.746), respectively.

Conclusion

Circ_0001946 is insufficiently expressed in tumor tissues, whereas its higher expression correlates with less lymph node metastasis, reduced TNM stage, and improved prognosis in NSCLC patients.

MZT2A promotes NSCLC viability and invasion by increasing Akt phosphorylation via the MOZART2 domain

Mitotic spindle organizing protein 2A (MZT2A) is localized at the centrosome and regulates microtubule nucleation activity in cells. This study assessed the role of MZT2A in non-small-cell lung cancer (NSCLC). Differential MZT2A expression was bioinformatically assessed using TCGA database, the GEPIA database, and Kaplan-Meier survival data to determine the association between MZT2A expression and NSCLC prognosis. Furthermore, NSCLC tissue specimens were evaluated by immunohistochemistry. MZT2A was overexpressed or knocked down in NSCLC cells using cDNA and siRNA, respectively. The cells were subjected to various assays and treated with the selective Akt inhibitor LY294002 or co-transfected with galectin-3-binding protein (LGALS3BP) siRNA. MZT2A mRNA and protein levels were upregulated in NSCLC lesions and MTZ2A expression was associated with poor NSCLC prognosis. MZT2A protein was also highly expressed in NSCLC cells compared with the expression in normal bronchial cells. MZT2A expression promoted NSCLC cell viability and invasion, whereas MTZ2A siRNA had the opposite effect on NSCLC cells in vitro. At the protein level, MZT2A induced Akt phosphorylation, promoting NSCLC proliferation and invasion (but the selective Akt inhibitor blocked these effects) through upregulation of LGALS3BP via the MTZ2A MOZART2 domain, whereas LGALS3BP siRNA suppressed MTZ2A activity in NSCLC cells. The limited in vivo experiments confirmed the in vitro data. In conclusion, MZT2A exhibits oncogenic activity by activating LGALS3BP and Akt in NSCLC. Future studies will assess MTZ2A as a biomarker to predict NSCLC prognosis or as a target in the control of NSCLC progression.

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

Nucleolar and spindle‑associated protein 1 promotes non‑small cell lung cancer progression and serves as an effector of myocyte enhancer factor 2D

As a potential oncogene, nucleolar and spindle-associated protein 1 (NUSAP1) is involved in the regulation of tumor cell proliferation, metastasis and drug resistance. However, the role of NUSAP1 in non-small cell lung cancer (NSCLC) remains unclear. The present study aimed to investigate the biological function and underlying molecular mechanisms of NUSAP1 in NSCLC. NUSAP1 expression was measured in NSCLC tissues and cell lines via immunohistochemistry and western blotting, respectively. NSCLC cell lines stably inhibiting NUSAP1 were established to investigate its effects on cell proliferation, colony formation and invasion, and on in vivo tumorigenicity. Additionally, the upstream and downstream mechanisms of NUSAP1 in regulating NSCLC progression were investigated. The results indicated that NUSAP1 expression was upregulated in NSCLC tissues and cell lines. High NUSAP1 expression was associated with tumor size, TNM stage, lymph node metastasis and poor patient survival, whereas knockdown of NUSAP1 inhibited NSCLC cell proliferation, colony formation and invasion. Furthermore, downregulation of NUSAP1 decreased the growth of NSCLC xenografts in vivo. In addition, myocyte enhancer factor 2D (MEF2D) directly targeted the NUSAP1 promoter, thereby enhancing the mRNA and protein expression levels of NUSAP1. Moreover, the results demonstrated that MEF2D expression was upregulated in NSCLC tissues and was positively correlated with NUSAP1 expression. MEF2D-knockdown decreased NSCLC cell proliferation, colony formation and invasion. NUSAP1 upregulation reversed the effects of MEF2D-knockdown on NSCLC progression. Furthermore, it was observed that MEF2D-knockdown inhibited the accumulation and nuclear translocation of β-catenin, thereby repressing the activation of the Wnt/β-catenin signaling pathway in NSCLC cells, whereas NUSAP1 upregulation rescued the effects of MEF2D-knockdown on the activation of the Wnt/β-catenin signaling pathway. In conclusion, the findings of the present study indicated that the MEF2D/NUSAP1 signaling pathway promoted NSCLC progression by inducing the activation of Wnt/β-catenin signaling, and this novel mechanism may represent a potential treatment target for patients with NSCLC.

Biomarkers for recurrent pressure injury risk in persons with spinal cord injury

Objective: To investigate potential linkages between pressure injury (PrI) recurrence following spinal cord injury (SCI) and muscle-based and circulatory biomarkers, specifically fatty metabolites and inflammatory cytokines. Design: Observational study. Setting: Tertiary Care Center. Participants: 30 individuals with complete or incomplete SCI. Study participants either had never developed a PrI (Group I) or had a history of recurrent PrI (Group II). Interventions: Not applicable. Outcome Measures: Gluteal muscle histology, immunohistochemistry, muscle-based and circulatory fatty metabolites and inflammatory cytokines. Results: Gluteal intramuscular adipose tissue (IMAT) was greater than 15% in most Group II (83%) individuals. Muscle tissue histology confirmed intramuscular structural differences. Fatty acid binding protein 4 (FABP4) and fatty acid binding protein 3 (FABP3) were reliably detected in muscle and blood and significantly correlated with IMAT (P < 0.001). FABP4 was significantly higher in Group II muscle and blood (P < 0.05). FABP3 was significantly higher in Group I muscle (P < 0.05). Circulatory FABP3 levels were lower for Group I. Inflammatory biomarkers were more reliably detected in blood. Colony-Stimulating Factor-1 was slightly higher in Group II muscle. Circulatory interleukin-13 was significantly higher (P < 0.01) in Group I. Vascular endothelial growth factor (VEGF-A) was significantly increased (P < 0.05) in Group I muscle and blood. Conclusion: Identifying individuals with SCI at highest risk for recurrent PrI may impact patient management. IMAT content evaluation illustrates that muscle quality is a key biomarker. Low circulatory inflammatory biomarker expression potentially limits clinical significance for between group differences. Circulatory levels of FABP4 hold great potential as a recurrent PrI risk biomarker.

Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer

Simple Summary

The traditional approach in identifying cancer related protein biomarkers has focused on evaluation of a single peptide/protein in tissue or circulation. At best, this approach has had limited success for clinical applications, since multiple pathological tumor pathways may be involved during initiation or progression of cancer which diminishes the significance of a single candidate protein/peptide. Emerging sensitive proteomic based technologies like liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics can provide a platform for evaluating serial serum or plasma samples to interrogate secreted products of tumor–host interactions, thereby revealing a more “complete” repertoire of biological variables encompassing heterogeneous tumor biology. However, several challenges need to be met for successful application of serum/plasma based proteomics. These include uniform pre-analyte processing of specimens, sensitive and specific proteomic analytical platforms and adequate attention to study design during discovery phase followed by validation of discovery-level signatures for prognostic, predictive, and diagnostic cancer biomarker applications.

Abstract

Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

Evaluation of Thiol/Disulfide Homeostasis in Lung Cancer

OBJECTIVES

Lung cancer is one of the most common causes of mortality all around the world. The increased production of reactive oxygen species occurs with cell damage, and cysteine is an important factor in preventing oxidative damage by its functional thiol group. The objective of this study was to evaluate the relationship between thiol/disulfide homeostasis (TDH) and the risk factors, disease severity, and physical condition of patients with lung cancer.

MATERIALS AND METHODS

This is a prospective, controlled, nonblinded study, which included healthy volunteers and patients diagnosed with lung cancer who had not yet started any treatment.

RESULTS

There were 45 male (90%) and five female (5%) patients (mean age 64±9 years), and 41 male (82%) and nine female (18%) healthy volunteers (mean age 65±17 years) were included in this research. Overall, the thiol levels were lower in patients than the control group (p<0.001). The native thiol level means were 275±72 μmol/l in the patient group and 414±80 μmol/l in the control group, and the total thiol level means were 309±74 and 451±79 μmol/l, respectively. However, the disulfide parameter was not statistically significantly different between the two groups. There were no correlations between the tumor size and overall survival and the total thiol, native thiol, and disulfide levels.

CONCLUSION

This study showed that there is a significant relationship between lung cancer and TDH, but there were no correlations with the disease stage and the clinical performance status.

Early Detection of Non-Small Cell Lung Cancer by Using a 12-microRNA Panel and a Nomogram for Assistant Diagnosis

Background: We previously identified a 12-microRNA (miRNA) panel (miRNA-17, miRNA-146a, miRNA-200b, miRNA-182, miRNA-155, miRNA-221, miRNA-205, miRNA-126, miRNA-7, miRNA-21, miRNA-145, and miRNA-210) that aided in the early diagnosis of non-small cell lung cancer (NSCLC). We validated the diagnostic value of this miRNA panel and compared it with that of traditional tumor markers and radiological diagnosis. We constructed a nomogram based on the miRNA panel's results to predict the risk of NSCLC.

Methods: Eighty-two participants with pulmonary nodules on a CT scan and who underwent a pathological examination and surgical treatment were enrolled in our study. Patients were randomly divided into a training group or a validation group. The miRNA concentrations were quantified by RT-PCR and log-transformed for analysis. The cutoff value was determined in the training group and then applied in the validation group. A comparison between the miRNAs and traditional tumor markers [CEA, NSE, and cytokeratin 19 fragment 21-1 (Cyfra21-1)] and radiological diagnosis was performed. A nomogram based on the miRNA panel's results to predict the risk of NSCLC was constructed.

Results: The expression level of these 12 miRNAs was significantly higher in NSCLC patients than in benign patients. In the validation group, the specificity and positive predictive value were 96.4 and 95.8%, respectively, which were significantly higher than those using traditional tumor markers or radiological diagnosis. The sensitivity was 42.6%, which was also higher than that using tumor markers. Moreover, the sensitivity increased to 63.6% when the nodule diameters were larger than 2 cm. The miRNAs and seven clinical factors were integrated into the nomogram, and the calibration curves showed optimal agreement between the predicted and actual probabilities.

Conclusions: Our miRNA panel has clinical value for the early detection of NSCLC. A nomogram was constructed and internally validated, and the results indicate that it can assist clinicians in making treatment recommendations in the clinic.

Progress in research on the role of fibrinogen in lung cancer

Lung cancer is one of the most prevalent malignancies worldwide. Local recurrence and distant metastasis remain the major causes of treatment failure. It has been recognized that the process of tumor growth and metastasis involves multiple interactions between tumor and host. Various biomarkers have been used for predicting tumor recurrence, metastasis, and prognosis in patients with lung cancer. However, these biomarkers are still controversial and require further validation. The relationship between malignancy and coagulation system disorders has been explored for more than a century. Fibrinogen is the most abundant plasma coagulation factor synthesized mainly by hepatic cells. Increased plasma fibrinogen levels were observed in various carcinomas such as gastric cancer, colon cancer, and pancreatic cancer. Recent studies have also investigated the role of fibrinogen in patients with lung cancer. This review aimed to address the role of fibrinogen in lung cancer.

Ancient genes can be served as pan-cancer diagnostic and prognostic biomarkers

One important challenge for cancer is efficient biomarkers monitoring its formation and developments remain greatly limited. Although the accumulated big omics data provide great opportunities to the above purpose, the biomarkers identified by the data‐driven strategy often do not work well in new datasets, which is one of the main bottlenecks limiting their utilities. Given that atavistic phenotype is generally observed in cancer cells, we have been suggested that the activity of progenitor genes in tumour could serve as an efficient cancer biomarker. For doing so, we first curated 77 progenitor genes and then proposed a quantitative score to evaluate cancer progenitorness. After applying progenitorness score to ~ 22 000 samples, 33 types of cancers from 81 datasets, this method generally performs well in the diagnosis, prognosis and therapy monitoring of cancers. This study proposed a potential pan‐cancer biomarker and revealed a significant role of atavism in the formation and development of cancers.

Proteomic and genomic biomarkers for Non-Small Cell Lung Cancer: Peroxiredoxin, Haptoglobin, and Alpha-1 antitrypsin

Background

The development of lung cancer is a multifactorial process that involves the environmental and genetic factors. The mortality rate of this cancer is higher than breast, colorectal, and prostate cancers. In this study, we try to analyze the proteome of patients with Non‐Small Cell Lung Cancer (NSCLC) and compare it with the healthy samples.

Methods

This study has compared 30 lung tissue samples from patients with NSCLC and 30 healthy samples using proteomics and RT‐PCR. Hence, tissue samples were obtained from the surgical ward in sterile conditions, and then, protein extraction applied to them. At the next stage, two‐dimensional electrophoresis and mass spectrometry LCMS/MS were performed for protein isolation and sequencing, respectively.

Results

The proteome analysis identified more than 40 differences in proteomic pattern of normal lung tissues compared to lung tissues with NSCLC. Peroxiredoxin, Haptoglobin, and Alpha‐1 antitrypsin proteins were identified. Molecularly, it has also been shown that the two main proteins of Peroxiredoxin‐2 and Alpha‐1 antitrypsin were upregulated, and the expression of Haptoglobin protein was downregulated in cancer tissue.

Conclusion

The results of this study showed that there are some differences in term of protein content between the normal and cancerous lung tissues. Further studies are needed to evaluate these proteins that investigate whether these proteins can candidate as biomarkers to use in the early diagnosis of patients with NSCLC.

Biochemical Markers of Saliva in Lung Cancer: Diagnostic and Prognostic Perspectives

The aim of the work is to study the metabolic characteristics of saliva in lung cancer for use in early diagnosis and determining the prognosis of the disease. The patient group included 425 lung cancer patients, 168 patients with non-cancerous lung diseases, and 550 healthy volunteers. Saliva samples were collected from all participants in the experiment before treatment and 34 biochemical saliva parameters were determined. Participants were monitored for six years to assess survival rates. The statistical analysis was performed by means of Statistica 10.0 (StatSoft) program and R package (version 3.2.3). To construct the classifier, the Random Forest method was used; the classification quality was assessed using the cross-validation method. Prognostic factors were analyzed by multivariate analysis using Cox's proportional hazard model in a backward step-wise fashion to adjust for potential confounding factors. A complex of metabolic changes occurring in saliva in lung cancer is described. Seven biochemical parameters were identified (catalase, triene conjugates, Schiff bases, pH, sialic acids, alkaline phosphatase, chlorides), which were used to construct the classifier. The sensitivity and specificity of the method were 69.5% and 87.5%, which is practically not inferior to the diagnostic characteristics of markers routinely used in the diagnosis of lung cancer. Significant independent factors in the poor prognosis of lung cancer are imidazole compounds (ICs) above 0.478 mmol/L and salivary lactate dehydrogenase activity below 545 U/L. Saliva has been shown to have great potential for the development of diagnostic and prognostic tests for lung cancer.

Circulating Tumor Cells as a Screening and Diagnostic Marker for Early-Stage Non-Small Cell Lung Cancer

Background

Circulating tumor cells (CTCs) have become potential diagnostic biomarker for several types of cancer, including lung cancer. In this study, we aim to determine whether CTCs detected by CellCollector can be used for early-stage diagnosis of lung cancer.

Methods

In this study, we recruited 64 volunteers, among whom 44 were suspected lung cancer patients requiring surgical treatment and 20 were healthy volunteers. We simultaneously analyzed PD-L1 expression in CTCs isolated using the GILUPI CellCollector and copy number variation by next-generation sequencing (NGS).

Results

We enrolled a total of 44 patients with suspected lung cancer who required surgery and 20 healthy volunteers. The patients were classified into 4 groups based on their pathological results: benign disease, in situ cancer, microinvasive, and invasive. The CTCs detection rate for each group was 10.00% (1/10), 45% (5/11), 50% (7/14), and 67% (6/9), respectively. Among the patients with lung cancer, the CTCs detection rate increased with disease progression. The rate of CTCs positivity was 52.94% (18/34) in patients who were diagnosed with lung cancer by pathology and 10% (1/10) in patients with benign disease. CTCs were not detected in the control group. The area under the receiver operating characteristic (ROC) curve, a measure for distinguishing patients with primary lung cancer, was 0.715 (95% CI 0.549-0.880, P=0.041). The sensitivity and specificity of the in vivo CTCs detection strategy for the diagnosis of early-stage lung cancer were 52.94% and 90%, respectively. CTCs were associated with clinical pathology but not with the size and location of the nodules.

Conclusion

CTCs isolation using the CellCollector in vivo detection method might be effective for distinguishing between benign and malignant nodules and may be used for early-stage diagnosis of lung cancer.

Prediction of Pleural Invasion in Challenging Non-Small-Cell Lung Cancer Patients Using Serum and Imaging Markers

Introduction. Preoperative detection of pleural invasion in lung cancer patients is key to curative surgical treatment. We tried to predict pleural invasion in non-small-cell lung cancer patients with <100 ml pleural fluid.

Methods

Patients admitted from August 1, 2011, to December 31, 2018, were retrospectively retrieved. Records of serum and imaging markers were analyzed.

Results

Among 7004 patients who received surgery, 43 cases with <100 ml pleural fluid who had pleural invasion were included, and another 108 cases without pleural invasion were enrolled as controls. There were no differences in squamous cell carcinoma antigen (SCC) or neuron-specific enolase (NSE) values between the pleural invasion and noninvasion groups (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (p = 0.30 and 0.14, respectively), but there were significant differences in carcinoembryonic antigen (CEA) and cytokeratin 19 fragment (CYFRA21-1) values (.

Conclusions

Serum CEA and CYFRA21-1, location of original lung cancer (right mid lobe), maximum diameter, CT-detectable pleural fluid, pleural sign by CT, and PET/CT-predicted pleural invasion were good markers for the prediction of pleural invasion in non-small-cell lung cancer patients.

Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Objective: To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD).

Materials and methods Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination.

Results We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001).

Conclusions We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.

Exploration of Serum Exosomal LncRNA TBILA and AGAP2-AS1 as Promising Biomarkers for Diagnosis of Non-Small Cell Lung Cancer

Non-small cell lung cancer is the most common type of cancer with a poor prognosis, and development of an effective diagnostic method is urgently needed. Exosomal lncRNAs, a class of transcripts longer than 200 nucleotides packaged into exosomes, have been defined as an ideal diagnostic biomarker for cancer. However, little is known about the clinical utility of exosomal lncRNAs in NSCLC. Here, we aimed to identify exosomal lncRNAs as promising biomarkers for NSCLC diagnosis. First, serum exosomes from NSCLC patients were successfully isolated by a polymer precipitation kit and then identified by TEM, NTA and western blot analysis. A total of nine candidate lncRNAs were detected by qRT-PCR in a training set. The two exosomal lncRNA TBILA and AGAP2-AS1 were screened out for the higher levels in NSCLC patients than that of healthy controls in a validation set. And there was a significant positive correlation between these exosomal lncRNAs levels and tumor size, lymph node metastasis and TNM stage. Additionally, we validated that these exosomal lncRNAs were stable in serum. Next, we evaluated the diagnostic efficiency of exosomal lncRNAs in NSCLC patients by ROC curve analysis. The data showed that individual TBILA or AGAP2-AS1 exhibited better diagnostic efficiency in NSCLC patients with different tumor pathologic subtypes and early stage, whereas the combination of lncRNAs did not provide better results than individual lncRNAs. Notably, the combination of two exosomal lncRNAs and the serum tumor biomarker Cyfra21-1 widely used in clinical practices further improved the diagnostic accuracy for NSCLC patients. This study suggests that exosomal lncRNA TBILA and AGAP2-AS1 may be promising biomarkers for diagnosis of NSCLC.

Blood Chromogranin A Is Not Effective as a Biomarker for Diagnosis or Management of Bronchopulmonary Neuroendocrine Tumors/Neoplasms

BACKGROUND

Identification of circulating tumor markers for clinical management in bronchopulmonary (BP) neuroendocrine tumors/neoplasms (NET/NEN) is of considerable clinical interest. Chromogranin A (CgA), a "universal" NET biomarker, is considered controversial as a circulating biomarker of BPNEN.

AIM

Assess utility of CgA in the diagnosis and management of BPNEN in a multicentric study.

MATERIAL AND METHODS

CgA diagnostic metrics were assessed in lung NET/NENs (n = 200) and controls (n = 140), randomly assigned to a Training and Test set (100 BPC and 70 controls in each). Assay specificity was evaluated in neoplastic lung disease (n = 137) and nonneoplastic lung disease (n = 77). CgA efficacy in predicting clinical status was evaluated in the combined set of 200 NET/NENs. CgA levels in bronchopulmonary neuroendocrine tumor (BPNET) subtypes (atypical [AC] vs. typical [TC]) and grade was examined. The clinical utility of an alteration of CgA levels (±25%) was evaluated in a subset of 49 BPNET over 12 months. CgA measurement was by NEOLISATM kit (EuroDiagnostica).

RESULTS

Sensitivity and specificity in the training set were 41/98%, respectively. Test set data were 42/87%. Training set area under receiver operator characteristic analysis differentiated BPC from control area under the curve (AUC) 0.61 ± 0.05 p = 0.015. Test set the data were AUC 0.58 ± 0.05, p = 0.076. In the combined set (n = 200), 67% BPNET/NEN (n = 134) had normal CgA levels. CgA levels did not distinguish histological subtypes (TC vs. AC, AUC 0.56 ± 0.04, p = 0.21), grade (p = 0.45-0.72), or progressive from stable disease (AUC 0.53 ± 0.05 p = 0.47). There was no correlation of CgA with Ki-67 index (Pearson r = 0.143, p = 0.14). For nonneoplastic diseases (chronic obstructive pulmonary disorder and idiopathic pulmonary fibrosis), CgA was elevated in 26-37%. For neoplastic disease (NSCLC, squamous cell carcinoma), CgA was elevated in 11-16%. The neuroendocrine SCLC also exhibited elevated CgA (50%). Elevated CgA was not useful for differentiating BPNET/NEN from these other pathologies. Monitoring BPNET/NEN over a 12-month period identified neither CgA levels per se nor changes in CgA were reflective of somatostatin analog treatment outcome/efficacy or the natural history of the disease (progression).

CONCLUSIONS

Blood CgA levels are not clinically useful as a biomarker for lung BPNET/NEN. The low specificity and elevations in both nonneoplastic as well as other common neoplastic lung diseases identified limited clinical utility for this biomarker.

Serum microRNA-135a as a diagnostic biomarker in non-small cell lung cancer

The purpose of our research was to evaluate diagnostic performance of serum microRNA-135a (miR-135a) in non-small cell lung cancer (NSCLC).Quantitative real time-polymerase chain reaction was employed to detect the expression serum of miR-135a in NSCLC patients and controls. The influence of serum miR-135a level on clinical characteristics of NSCLC patients was explored through the Chi-square test. Serum carcinoembryonic antigen (CEA) level was estimated via enzyme-linked immunosorbent assay. Receiver operating characteristic (ROC) curve was plotted to elucidate diagnostic roles of serum miR-135a and CEA in NSCLC.The expression level of serum miR-135a was significantly lower in NSCLC patients than in healthy controls (0.40 ± 0.29 vs 1.00 ± 0.40, P < .001). Moreover, miR-135a expression was related to lymph node metastasis (P = .021), tumor differentiation (P = .020), and tumor node metastasis stage (P = .031). ROC curve showed serum miR-135a level could discriminate NSCLC patients from healthy controls (P < .0001) with a corresponding cutoff value of 0.665, and a sensitivity and specificity of 81.3% and 83.1%, respectively. The area under the curve was 0.888. In diagnosis analysis on the combination of miR-135a and CEA, when its specificity was maintained at 90%, diagnosis cut-off point reached 0.678.Serum miR-135a level is significantly downregulated in NSCLC and serves as a potential diagnostic biomarker for the disease.

A seven-long noncoding RNA signature predicts overall survival for patients with early stage non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common cancer and cause of cancer-related mortality globally. Increasing evidence suggested that the long non-coding RNAs (lncRNAs) were involved in cancer-related death. To explore the possible prognostic lncRNA biomarkers for NSCLC patients, in the present study, we conducted a comprehensive lncRNA profiling analysis based on 1902 patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. In the discovery phase, we employed 682 patients from the combination of four GEO datasets (GSE30219, GSE31546, GSE33745 and GSE50081) and conducted a seven-lncRNA formula to predict overall survival (OS). Next, we validated our risk-score formula in two independent datasets, TCGA (n=994) and GSE31210 (n=226). Stratified analysis revealed that the seven-lncRNA signature was significantly associated with OS in stage I patients from both discovery and validation groups (all P<0.001). Additionally, the prognostic value of the seven-lncRNA signature was also found to be favorable in patients carrying wild-type KRAS or EGFR. Bioinformatical analysis suggested that the seven-lncRNA signature affected patients’ prognosis by influencing cell cycle-related pathways. In summary, our findings revealed a seven-lncRNA signature that predicted OS of NSCLC patients, especially in those with early tumor stage and carrying wild-type KRAS or EGFR.

Identification of protein changes in the blood plasma of lung cancer patients subjected to chemotherapy using a 2D-DIGE approach

A comparative analysis of blood samples (depleted of albumin and IgG) obtained from lung cancer patients before chemotherapy versus after a second cycle of chemotherapy was performed using two-dimensional difference gel electrophoresis (2D-DIGE). The control group consisted of eight patients with non-cancerous lung diseases, and the experimental group consisted of four adenocarcinoma (ADC) and four squamous cell carcinoma (SCC) patients. Analyses of gels revealed significant changes in proteins and/or their proteoforms between control patients and lung cancer patients, both before and after a second cycle of chemotherapy. Most of these proteins were related to inflammation, including acute phase proteins (APPs) such as forms of haptoglobin and transferrin, complement component C3, and clusterin. The variable expression of APPs can potentially be used for profiling lung cancer. The greatest changes observed after chemotherapy were in transferrin and serotransferrin, which likely reflect disturbances in iron turnover after chemotherapy-induced anaemia. Significant changes in plasma proteins between ADC and SCC patients were also revealed, suggesting use of plasma vitronectin as a potential marker of SCC.