Quantitative proteomics in lung cancer

Comprehensive multi-omics analysis provides biological insights and therapeutic strategies for small-cell lung cancer

Integration of multi-omics analysis into small-cell lung cancer (SCLC) research. In the research of small-cell lung cancer, the integration of multi-omics analysis has become an important research direction. Multi-omics analysis includes the study of genomics, transcriptomics, proteomics, metabolomics, and other levels, which can help us to understand the pathogenesis and development process of diseases more comprehensively as well as develop novel therapeutics and biomarkers for further precision oncology.

[Overexpression of lncRNA FEZF1-AS1 promotes progression of non-small cell lung cancer via the miR-130a-5p/CCND1 axis]

OBJECTIVE

To explore the molecular mechanism by which FEZF1-AS1 overexpression promotes progression of nonsmall cell lung cancer (NSCLC) via the miR-130a-5p/CCND1 axis.

METHODS

TCGA database was used to analyze FEZF1-AS1 expression levels in NSCLC. FEZF1-AS1 expression was detected by qRT-PCR in clinical specimens of NSCLC tissues and NSCLC cell lines, and its correlation with clinical features of the patients were analyzed. The binding sites of FEZF1-AS1 with hsa-miR-130a-5p and those of hsa-miR-130a-5p with CCND1 were predicted. CCK8 assay, clone formation assay, scratch assay, and Transwell assay were employed to examine the effects of FEZF1-AS1 knockdown and hsa-miR-130a-5p inhibitor on proliferation, invasion, and migration abilities of lung cancer cell lines. Dual luciferase assay was used to verify the binding of FEZF1-AS1 with hsa-miR-130a-5p and the binding of hsa-miR-130a-5p with CCND1. Western blotting was performed to detect the changes in CCND1 protein expression level in H1299 and H358 cells following FEZF1-AS1 knockdown and treatment with hsa-miR-130a-5p inhibitor.

RESULTS

FEZF1-AS1 was highly expressed in NSCLC tissues in close correlation with lymph node metastasis and also in H1299 and H358 cell lines (all P < 0.05). FEZF1-AS1 knockdown obviously reduced proliferation, migration, and invasion abilities of NSCLC cells (P < 0.05). Dual luciferase assay confirmed the binding of hsa-miR-130a-5p with FEZF1-AS1 and CCND1 (P < 0.05), and hsa-miR-130a-5p inhibitor significantly inhibited proliferation, migration, and invasion of NSCLC cells (P < 0.05). FEZF1-AS1 knockdown significantly reduced CCND1 protein expression in NSCLC cells, and this effect was strongly inhibited by treatment with hsa-miR-130a-5p inhibitor (P < 0.05).

CONCLUSION

FEZF1-AS1 is highly expressed in NSCLC tissue in close correlation with lymph node metastasis to promote cancer progression through the miR-130a-5p/CCND1 axis.

Application of artificial intelligence in the diagnosis, treatment, and recurrence prediction of peritoneal carcinomatosis

Peritoneal carcinomatosis (PC) is a type of secondary cancer which is not sensitive to conventional intravenous chemotherapy. Treatment strategies for PC are usually palliative rather than curative. Recently, artificial intelligence (AI) has been widely used in the medical field, making the early diagnosis, individualized treatment, and accurate prognostic evaluation of various cancers, including mediastinal malignancies, colorectal cancer, lung cancer more feasible. As a branch of computer science, AI specializes in image recognition, speech recognition, automatic large-scale data extraction and output. AI technologies have also made breakthrough progress in the field of peritoneal carcinomatosis (PC) based on its powerful learning capacity and efficient computational power. AI has been successfully applied in various approaches in PC diagnosis, including imaging, blood tests, proteomics, and pathological diagnosis. Due to the automatic extraction function of the convolutional neural network and the learning model based on machine learning algorithms, AI-assisted diagnosis types are associated with a higher accuracy rate compared to conventional diagnosis methods. In addition, AI is also used in the treatment of peritoneal cancer, including surgical resection, intraperitoneal chemotherapy, systemic chemotherapy, which significantly improves the survival of patients with PC. In particular, the recurrence prediction and emotion evaluation of PC patients are also combined with AI technology, further improving the quality of life of patients. Here we have comprehensively reviewed and summarized the latest developments in the application of AI in PC, helping oncologists to comprehensively diagnose PC and provide more precise treatment strategies for patients with PC.

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

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

Systematic characterization of m6A proteomics across 12 cancer types: a multi-omics integration study

The modification patterns of N6-methyladenosine (m6A) regulators and interacting genes are deeply involved in tumors. However, the effect of m6A modification patterns on human proteomics remains largely unknown. We evaluated the molecular characteristics and clinical relevance of m6A modification proteomics patterns among 1013 pan-cancer samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). More than half of the m6A proteins were expressed at higher levels in tumor tissues and presented oncogenic characteristics. Furthermore, we performed multi-omics analyses integrating with transcriptomics data of m6A regulators and interactive coding and non-coding RNAs and developed a m6A multi-omics signature to identify potential m6A modification target proteins across global proteomics. It was significantly associated with overall survival in nine cancer types, tumor mutation burden (P = 0.01), and immune checkpoints including PD-L1 (P = 4.9 × 10-8) and PD-1 (P < 0.01). We identified 51 novel proteins associated with the multi-omics signature (PFDR < 0.05). These proteins were functional through pathway enrichment analyses. The protein with the highest hit frequency was CHORDC1, which was significantly up-regulated in tumor tissues in nine cancer types. Its higher abundance was significantly associated with a poorer prognosis in seven cancer types. The identified m6A target proteins might provide infomation for the study of molecular mechanism of cancer.

Proteome-wide Mendelian randomization identifies causal plasma proteins in lung cancer

Plasma proteins are promising biomarkers and potential drug targets in lung cancer. To evaluate the causal association between plasma proteins and lung cancer, we performed proteome-wide Mendelian randomization meta-analysis (PW-MR-meta) based on lung cancer genome-wide association studies (GWASs), protein quantitative trait loci (pQTLs) of 4,719 plasma proteins in deCODE and 4,775 in Fenland. Further, causal-protein risk score (CPRS) was developed based on causal proteins and validated in the UK Biobank. 270 plasma proteins were identified using PW-MR meta-analysis, including 39 robust causal proteins (both FDR-q < 0.05) and 78 moderate causal proteins (FDR-q < 0.05 in one and p < 0.05 in another). The CPRS had satisfactory performance in risk stratification for lung cancer (top 10% CPRS:Hazard ratio (HR) (95%CI):4.33(2.65-7.06)). The CPRS [AUC (95%CI): 65.93 (62.91-68.78)] outperformed the traditional polygenic risk score (PRS) [AUC (95%CI): 55.71(52.67-58.59)]. Our findings offer further insight into the genetic architecture of plasma proteins for lung cancer susceptibility.

SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies

NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment.

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning

BACKGROUND AND OBJECTIVE

The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime importance to improve the patient's survivability and quality of life. Being a heterogeneous disease at the molecular and cellular level, the biomarkers responsible for the heterogeneity aid in distinguishing NSCLC into its prominent subtypes-adenocarcinoma and squamous cell carcinoma. Moreover, if identified, these biomarkers could pave the path to targeted therapy. Through this work, a novel explainable AI (XAI)-guided deep learning framework is proposed that assists in discovering a set of significant NSCLC-relevant biomarkers using methylation data.

METHODS

The proposed framework is divided into two blocks- the first block combines an autoencoder and a neural network to classify NSCLC instances. The second block utilizes various eXplainable AI (XAI) methods, namely IntegratedGradients, GradientSHAP, and DeepLIFT, to discover a set of seven significant biomarkers.

RESULTS

The classification performance of the biomarkers discovered using the proposed framework is evaluated by employing multiple machine learning algorithms, among which the Multilayer Perceptron (MLP) algorithm-based model outperforms others, yielding a 10-fold cross-validation accuracy of 91.53%. An improved accuracy of 96.37% is achieved by integrating RNA-Seq, CNV, and methylation data. On performing statistical analysis using the Friedman and Nemenyi tests, the MLP model is found to be significantly better than other machine learning-based models. Further, the clinical efficacy of the resultant biomarkers is established based on their potential druggability, the likelihood of predicting NSCLC patients' survival, gene-disease association, and biological pathways targeted by them. While the biomarkers C18orf18, CCNT2, THOP1, and TNPO2, are found potentially druggable, the biomarkers CCDC15, SNORA9, THOP1, and TNPO2 are found prognostically relevant. On further analysis, some of the discovered biomarkers are found to be associated with around 104 diseases. Moreover, five KEGG, ten Reactome, and three Wiki pathways are found to be triggered by the biomarkers discovered.

CONCLUSION

In summary, the proposed framework uncovers a set of clinically effective biomarkers that accurately classify NSCLC. As a future course of work, efforts would be made to combine a variety of omics data with histopathological data to unveil more precise biomarkers for devising personalized therapy.

A review of Glycogen Synthase Kinase-3 (GSK3) inhibitors for cancers therapies

The intricate molecular pathways governing cancer development and progression have spurred intensive investigations into novel therapeutic targets. Glycogen Synthase Kinase-3 (GSK3), a complex serine/threonine kinase, has emerged as a key player with intricate roles in various cellular processes, including cell proliferation, differentiation, apoptosis, and metabolism. Harnessing GSK3 inhibitors as potential candidates for cancer therapy has garnered significant interest due to their ability to modulate key signalling pathways that drive oncogenesis. The review encompasses a thorough examination of the molecular mechanisms underlying GSK3's involvement in cancer progression, shedding light on its interaction with critical pathways such as Wnt/β-catenin, PI3K/AKT, and NF-κB. Through these interactions, GSK3 exerts influence over tumour growth, invasion, angiogenesis, and metastasis, rendering it an attractive target for therapeutic intervention. The discussion includes preclinical and clinical studies, showcasing the inhibitors efficacy across a spectrum of cancer types, including pancreatic, ovarian, lung, and other malignancies. Insights from recent studies highlight the potential synergistic effects of combining GSK3 inhibitors with conventional chemotherapeutic agents or targeted therapies, opening avenues for innovative combinatorial approaches. This review provides a comprehensive overview of the current state of research surrounding GSK3 inhibitors as promising agents for cancer treatment.

Lung proteomics combined with metabolomics reveals molecular characteristics of inflammation-related lung tumorigenesis induced by B(a)P and LPS

Inflammatory microenvironment may take a promoting role in lung tumorigenesis. However, the molecular characteristics underlying inflammation-related lung cancer remains unknown. In this work, the inflammation-related lung tumorigenesis mouse model was established by treated with B(a)P (1 mg/mouse, once a week for 4 weeks), followed by LPS (2.5 μg/mouse, once every 3 weeks for five times), the mice were sacrificed 30 weeks after exposure. TMT-labeled quantitative proteomics and untargeted metabolomics were used to interrogate differentially expressed proteins and metabolites in different mouse cancer tissues, followed by integrated crosstalk between proteomics and metabolomics through Spearman's correlation analysis. The result showed that compared with the control group, 103 proteins and 37 metabolites in B(a)P/LPS group were identified as significantly altered. By searching KEGG pathway database, proteomics pathways such as Leishmaniasis, Asthma and Intestinal immune network for IgA production, metabolomics pathways such as Vascular smooth muscle contraction, Linoleic acid metabolism and cGMP-PKG signaling pathway were enriched. A total of 22 pathways were enriched after conjoint analysis of the proteomic and metabolomics, and purine metabolism pathway, the unique metabolism-related pathway, which included significantly altered protein (adenylate cyclase 4, ADCY4) and metabolites (L-Glutamine, guanosine monophosphate (GMP), adenosine and guanosine) was found. Results suggested purine metabolism may contribute to the inflammation-related lung tumorigenesis, which may provide novel clues for the therapeutic strategies of inflammation-related lung cancer.

Plasma proteomic profiles predict individual future health risk

Developing a single-domain assay to identify individuals at high risk of future events is a priority for multi-disease and mortality prevention. By training a neural network, we developed a disease/mortality-specific proteomic risk score (ProRS) based on 1461 Olink plasma proteins measured in 52,006 UK Biobank participants. This integrative score markedly stratified the risk for 45 common conditions, including infectious, hematological, endocrine, psychiatric, neurological, sensory, circulatory, respiratory, digestive, cutaneous, musculoskeletal, and genitourinary diseases, cancers, and mortality. The discriminations witnessed high accuracies achieved by ProRS for 10 endpoints (e.g., cancer, dementia, and death), with C-indexes exceeding 0.80. Notably, ProRS produced much better or equivalent predictive performance than established clinical indicators for almost all endpoints. Incorporating clinical predictors with ProRS enhanced predictive power for most endpoints, but this combination only exhibited limited improvement when compared to ProRS alone. Some proteins, e.g., GDF15, exhibited important discriminative values for various diseases. We also showed that the good discriminative performance observed could be largely translated into practical clinical utility. Taken together, proteomic profiles may serve as a replacement for complex laboratory tests or clinical measures to refine the comprehensive risk assessments of multiple diseases and mortalities simultaneously. Our models were internally validated in the UK Biobank; thus, further independent external validations are necessary to confirm our findings before application in clinical settings.

A Dual Role for FADD in Human Precursor T-Cell Neoplasms

A reduction in FADD levels has been reported in precursor T-cell neoplasms and other tumor types. Such reduction would impact on the ability of tumor cells to undergo apoptosis and has been associated with poor clinical outcomes. However, FADD is also known to participate in non-apoptotic functions, but these mechanisms are not well-understood. Linking FADD expression to the severity of precursor T-cell neoplasms could indicate its use as a prognostic marker and may open new avenues for targeted therapeutic strategies. Using transcriptomic and clinical data from patients with precursor T-cell neoplasms, complemented by in vitro analysis of cellular functions and by high-throughput interactomics, our results allow us to propose a dual role for FADD in precursor T-cell neoplasms, whereby resisting cell death and chemotherapy would be a canonical consequence of FADD deficiency in these tumors, whereas deregulation of the cellular metabolism would be a relevant non-canonical function in patients expressing FADD. These results reveal that evaluation of FADD expression in precursor T-cell neoplasms may aid in the understanding of the biological processes that are affected in the tumor cells. The altered biological processes can be of different natures depending on the availability of FADD influencing its ability to exert its canonical or non-canonical functions. Accordingly, specific therapeutic interventions would be needed in each case.

Minichromosome maintenance gene family: potential therapeutic targets and prognostic biomarkers for lung squamous cell carcinoma

The minichromosome maintenance (MCM) gene family comprises of ten members with key roles in eukaryotic DNA replication and are associated with the occurrence and progression of many tumors. However, whether the MCM family contributes to lung squamous cell carcinoma (LUSC) is unclear. In this study, we performed bioinformatic analysis to identify the roles of MCM genes in patients with LUSC. We also evaluated their differential gene expression, prognostic correlation, DNA methylation, functional enrichment of genetic alterations, and immunomodulation. According to the Tumor Immune Estimation Resource database, the expression of MCM2-10 mRNA was elevated in LUSC tissues. According to the Gene Expression Profiling Interactive Analysis database, MCM2-8 and MCM10 were considerably upregulated in LUSC tissues, and protein levels of all MCMs were increased in LUSC tissues. In addition, among the MCM family members, the expression of MCM3 and MCM7 showed the strongest correlation with the prognoses of patients with LUSC. To clarify the role and mechanisms of the MCM family, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment studies were performed. We detected a significant correlation between the expression patterns of MCM family members and infiltrating immune cells. In conclusion, our results improve the understanding of the aberrant expression of MCM family members in LUSC. These findings demonstrate the potential of the MCM family as therapeutic targets and biomarkers for the diagnosis and prognosis of LUSC.

Effect of Cepharanthine on the Stemness of Lung Squamous Cell Carcinoma Based on Network Pharmacology and Bioinformatics

Background

Lung squamous cell carcinoma (LUSC) has poor survival prognosis and few clinical treatment options. We urgently need to explore new therapeutic drugs in clinical practice. Cepharanthine (CEP) has been shown to have anticancer effects in several tumors, but the mechanism of CEP in treating LUSC has not been reported.

Methods

SwissTargetPrediction, PharmMapper, and GeneCards were used to identify targets of CEP and LUSC. Further topological analysis was used to obtain hub genes via Cytoscape. Molecular docking was carried out to verify the combination of CEP with hub targets. Based on bioinformatics, we first analyzed the expression and survival of hub targets in LUSC and further analyzed the correlation between hub targets and cancer stemness, immune cell infiltration, and tumor mutation burden (TMB).

Results

A total of 41 targets were identified. Further topological analysis identified 6 hub genes: AURKA, CCNA2, CCNE1, CDK1, CHEK1, and PLK1. Molecular docking analysis showed that CEP had stable binding to all these 6 target proteins. In-depth bioinformatics analysis of these 6 targets showed that high expression of these targets were positively correlated with cancer stemness index and negatively correlated with tumor infiltrating immune cells. In immune subtype analysis, the expressions of these targets were significantly decreased in inflammatory tumors. In addition, we also found that the expressions of these targets were positively correlated with TMB.

Conclusion

Based on multidisciplinary analysis, we preliminarily identified potential targets of CEP for LUSC treatment and suggested that CEP may play a role in regulating LUSC stemness.

Doxorubicin-Loaded Extracellular Vesicles Enhance Tumor Cell Death in Retinoblastoma

Chemotherapy is often used to treat retinoblastoma; however, this treatment method has severe systemic adverse effects and inadequate therapeutic effectiveness. Extracellular vesicles (EVs) are important biological information carriers that mediate local and systemic cell-to-cell communication under healthy and pathological settings. These endogenous vesicles have been identified as important drug delivery vehicles for a variety of therapeutic payloads, including doxorubicin (Dox), with significant benefits over traditional techniques. In this work, EVs were employed as natural drug delivery nanoparticles to load Dox for targeted delivery to retinoblastoma human cell lines (Y-79). Two sub-types of EVs were produced from distinct breast cancer cell lines (4T1 and SKBR3) that express a marker that selectively interacts with retinoblastoma cells and were loaded with Dox, utilizing the cells’ endogenous loading machinery. In vitro, we observed that delivering Dox with both EVs increased cytotoxicity while dramatically lowering the dosage of the drug. Dox-loaded EVs, on the other hand, inhibited cancer cell growth by activating caspase-3/7. Direct interaction of EV membrane moieties with retinoblastoma cell surface receptors resulted in an effective drug delivery to cancer cells. Our findings emphasize the intriguing potential of EVs as optimum methods for delivering Dox to retinoblastoma.

A Novel Laser Angle Selection System for Computed Tomography-Guided Percutaneous Transthoracic Needle Biopsies

Purpose: To evaluate a novel laser angle selection system (LASS) for improving the efficiency of a computed tomography (CT)–guided percutaneous transthoracic needle biopsy (PTNB). Methods: Thirty-eight patients referred for CT-guided PTNB were randomly separated into a LASS-assisted puncture group (18 patients) or conventional freehand control group (20 patients). The puncture time, number of control CT scans, and patients’ radiation dose were compared for each group. Results: The lesion size, target-to-pleural distance, planned puncture depth, and angle of the two groups were not significantly different. LASS-assisted PTNB significantly reduced the number of control scans (1.7 ± 0.8 vs 3.5 ± 1.5, P < .001) and the mean operation time (12.0 ± 4.3 min vs 28.8 ± 13.3 min, P < .001) compared with the conventional method. The corresponding room time (27.1 ± 6.6 min vs 44.1 ± 14.4 min, P < .001) and total radiation dose (7.9 ± 1.0 mSv vs 10.1 ± 1.7 mSv, P < .001) of each procedure also decreased significantly. Fifty-six percent (10/18) of the operations hit the target on the first needle pass when using LASS compared with 10% (2/20) using the conventional method. Conclusions: Compared with a conventional method, this novel laser angle simulator improves puncture efficiency with fewer needle readjustments and reduces patient radiation dose.

lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2

Lung cancer (LC) is a prevailing primary tumor in the lung. lncRNA non-coding RNA activated by DNA damage (NORAD) is a popular target in human cancers. This experiment is designed to probe the mechanism of lncRNA in LC progression. NORAD expression in normal lung epithelial cells and LC cells was examined and then silenced to assess its effect on LC cell proliferation, invasion, and migration. Subcellular localization of NORAD was analyzed through online databases and then corroborated by fractionation of nuclear and cytoplasmic RNA assay. The target binding relations between NORAD and miR-28-3p and between miR-28-3p and E2F2 were verified. Eventually, LC cells with NORAD silencing were transfected with miR-28-3p inhibitor or pcDNA3.1-E2F2 to measure LC cell proliferation, invasion, and migration. NORAD was overexpressed in LC cells and NORAD knockout led to suppressed LC cell proliferation, invasion, and migration. Besides, NORAD targeted miR-28-3p and miR-28-3p targeted E2F2 transcription. Inhibiting miR-28-3p or overexpressing E2F2 could both annul the inhibitory role of si-NORAD in LC cell proliferation, invasion, and migration. Generally, our findings demonstrated that NORAD competitively bound to miR-28-3p with E2F2, to promote LC cell progression.

Advances in the application of proteomics in lung cancer

Although the incidence and mortality of lung cancer have decreased significantly in the past decade, it is still one of the leading causes of death, which greatly impairs people’s life and health. Proteomics is an emerging technology that involves the application of techniques for identifying and quantifying the overall proteins in cells, tissues and organisms, and can be combined with genomics, transcriptomics to form a multi-omics research model. By comparing the content of proteins between normal and tumor tissues, proteomics can be applied to different clinical aspects like diagnosis, treatment, and prognosis, especially the exploration of disease biomarkers and therapeutic targets. The applications of proteomics have promoted the research on lung cancer. To figure out potential applications of proteomics associated with lung cancer, we summarized the role of proteomics in studies about tumorigenesis, diagnosis, prognosis, treatment and resistance of lung cancer in this review, which will provide guidance for more rational application of proteomics and potential therapeutic strategies of lung cancer.

Circular RNA hsa_circ_0018189 drives non-small cell lung cancer growth by sequestering miR-656-3p and enhancing xCT expression

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the cancers with a high mortality rate. CircRNAs have emerged as an important regulatory factor in tumorigenesis in recent years. However, the detailed regulatory mechanism of a circular RNA cullin 2 (hsa_circ_0018189; hsa_circ_0018189) is still unclear in NSCLC.

METHODS

RNA levels of hsa_circ_0018189, microRNA (miR)-656-3p, and Solute carrier family seven member 11 (SLC7A11, xCT) were analyzed by real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR), and protein level was assessed by Western blot and immunohistochemical assay. Enzyme-linked immunosorbent assay was conducted to detect cell glutamine metabolism. Effects of hsa_circ_0018189 on cell proliferation, apoptosis, migration, and invasion were analyzed by corresponding assays. Luciferase reporter assay and RNA-immunoprecipitation assay confirmed the target relationship between miR-656-3p and hsa_circ_0018189 or xCT. The in vivo function of hsa_circ_0018189 was verified by xenograft mouse models.

RESULTS

Hsa_circ_0018189 abundance was overexpressed in NSCLC cells and samples. Deficiency of hsa_circ_0018189 lowered NSCLC cell proliferative, migrating, invading, and glutamine metabolism capacities, and hsa_circ_0018189 silencing inhibited the growth of tumors in vivo. Hsa_circ_0018189 could up-regulate xCT by sponging miR-656-3p. And miR-656-3p downregulation or xCT overexpression partly overturned hsa_circ_0018189 knockdown or miR-656-3p mimic-mediated repression of NSCLC cell malignancy.

CONCLUSION

Hsa_circ_0018189 drove NSCLC growth by interacting with miR-656-3p and upregulating xCT.

The emerging potentials of lncRNA DRAIC in human cancers

Long non-coding RNA (lncRNA) is a subtype of noncoding RNA that has more than 200 nucleotides. Numerous studies have confirmed that lncRNA is relevant during multiple biological processes through the regulation of various genes, thus affecting disease progression. The lncRNA DRAIC, a newly discovered lncRNA, has been found to be abnormally expressed in a variety of diseases, particularly cancer. Indeed, the dysregulation of DRAIC expression is closely related to clinicopathological features. It was also reported that DRAIC is key to biological functions such as cell proliferation, autophagy, migration, and invasion. Furthermore, DRAIC is of great clinical significance in human disease. In this review, we discuss the expression signature, clinical characteristics, biological functions, relevant mechanisms, and potential clinical applications of DRAIC in several human diseases.

PINTology: A short history of the lncRNA LINC-PINT in different diseases

LINC-PINT is a p53-induced long intergenic noncoding transcript that plays a crucial role in many diseases, especially cancer. This long noncoding RNA (lncRNA) gene produces in total 102 (LNCipedia) alternatively spliced variants (LINC-PINT:1 to LINC-PINT:102). The functions of known variants include RNA transcripts, host transcripts for circular RNA (circRNA) generation and as sources for the translation of short peptides. In most human tumors, LINC-PINT is down-regulated where it serves as a tumor suppressor. However, the diversity of its functions in other maladies signifies its general clinical importance. Current LINC-PINT molecular functions include RNA-protein interactions, miRNA sponging and epigenetic modulation with these mechanisms operating in different cellular contexts to exert effects on biological processes ranging from DNA damage responses, cell cycle and growth arrest, senescence, cell migration and invasion, and apoptosis. Genetic polymorphisms in LINC-PINT have also been functionally associated with cancer and other pathologies including the autoimmune diseases pemphigus foliaceus and arthritis. Hence, LINC-PINT shows great potential as a clinical biomarker, especially for the diagnosis and prognosis of cancer. In this review, we explore the current knowledge highlighting the distinctive molecular functions of LINC-PINT in specific cancers and other disease states. This article is categorized under: RNA in Disease and Development > RNA in Disease.

Bottom-Up Approach to the Discovery of Clinically Relevant Biomarker Genes: The Case of Colorectal Cancer

Traditional approaches to genome-wide marker discovery often follow a common top-down strategy, where a large scale ‘omics’ investigation is followed by the analysis of functional pathways involved, to narrow down the list of identified putative biomarkers, and to deconvolute gene expression networks, or to obtain an insight into genetic alterations observed in cancer. We set out to investigate whether a reverse approach would allow full or partial reconstruction of the transcriptional programs and biological pathways specific to a given cancer and whether the full or substantially expanded list of putative markers could thus be identified by starting with the partial knowledge of a few disease-specific markers. To this end, we used 10 well-documented differentially expressed markers of colorectal cancer (CRC), analyzed their transcription factor networks and biological pathways, and predicted the existence of 193 new putative markers. Incredibly, the use of a validation marker set of 10 other completely different known CRC markers and the same procedure resulted in a very similar set of 143 predicted markers. Of these, 138 were identical to those found using the training set, confirming our main hypothesis that a much-expanded set of disease markers can be predicted by starting with just a small subset of validated markers. Further to this, we validated the expression of 42 out of 138 top-ranked predicted markers experimentally using qPCR in surgically removed CRC tissues. We showed that 41 out of 42 mRNAs tested have significantly altered levels of mRNA expression in surgically excised CRC tissues. Of the markers tested, 36 have been reported to be associated with aspects of CRC in the past, whilst only limited published evidence exists for another three genes (BCL2, PDGFRB and TSC2), and no published evidence directly linking genes to CRC was found for CCNA1, SHC1 and TGFB3. Whilst we used CRC to test and validate our marker discovery strategy, the reported procedures apply more generally to cancer marker discovery.

Circ_SAR1A regulates the malignant behavior of lung cancer cells via the miR-21-5p/TXNIP axis

Background

Lung cancer is one of the most common malignancies globally and a significant component of cancer‐related deaths. The lack of early diagnosis accounts for detecting approximately 75% of cancer patients at an intermediate to an advanced stage, with a low 5‐year survival rate. Therefore, a more comprehensive understanding of the molecular mechanisms of lung cancer development is necessary to find reliable and effective therapeutic and diagnostic biomarkers.

Methods

circ_SAR1A, miR‐21‐5p, and TXNIP in lung cancer tissues, animal xenografts, and cell lines were validated by qRT‐PCR and western blotting analyses. RNase R digestion and nuclear/cytoplasm fractionation experiments were utilized to determine the stability and localization of circ_SAR1A in lung cancer cells. The binding between miR‐21‐5p and circ_SAR1A or TXNIP was confirmed by luciferase reporter, RNA pull‐down, Spearman's correlation, and rescue assays. CCK‐8, colony formation, flow cytometry, Transwell, and western blotting were utilized to illustrate the malignant behavior of lung cancer cells.

Results

circ_SAR1A and TXNIP were down‐regulated while miR‐21‐5p was up‐regulated in lung cancer samples and cells. circ_SAR1A was located predominantly in the cytoplasm; it inhibited lung cancer growth in vitro and in vivo by sponging to miR‐21‐5p. miR‐21‐5p silencing suppressed lung cancer malignancy by targeting TXNIP.

Conclusions

circ_SAR1A is a critical negative regulator of lung carcinogenesis. circ_SAR1A/miR‐21‐5p/TXNIP attenuation inhibited lung cancer progression, presenting an ideal diagnostic and a potential therapeutic target.

Low-Temperature Plasma-Activated Medium Inhibited Proliferation and Progression of Lung Cancer by Targeting the PI3K/Akt and MAPK Pathways

Low-temperature plasma, an engineered technology to generate various reactive species, is actively studied in cancer treatment in recent years, yet mainly by using a traditional 2D cell culture system. In this study, we explored the effect of the plasma-activated medium (PAM) on lung cancer cells in vitro and in vivo by using a 3D cell culture model. The results showed that PAM markedly inhibited 3D spheroid formation and downregulated stemness-related gene expression. We found that reactive oxygen species (ROS) penetrated throughout the whole spheroids and induced cell death surrounding and in the core of the tumor spheroid. Besides, PAM treatment suppressed migration and invasion of lung cancer cells and downregulated epithelial-mesenchymal transition- (EMT-) related gene expression. In the mouse xenograft model, the tumor volume was significantly smaller in the PAM-treated group compared with the control group. By using transcriptome sequencing, we found that PI3K/Akt and MAPK pathways were involved in the inhibition effects of PAM on lung cancer cells. Therefore, our results indicated that PAM exhibits potential anticancer effects on lung cancer and provides insight into further exploration of PAM-induced cell death and translational preclinical use.

Extracellular Vesicles Secreted by Corneal Myofibroblasts Promote Corneal Epithelial Cell Migration

Corneal epithelial wound healing is a multifaceted process that encompasses cell proliferation, migration, and communication from the corneal stroma. Upon corneal injury, bidirectional crosstalk between the epithelium and stroma via extracellular vesicles (EVs) has been reported. However, the mechanisms by which the EVs from human corneal keratocytes (HCKs), fibroblasts (HCFs), and/or myofibroblasts (HCMs) exert their effects on the corneal epithelium remain unclear. In this study, HCK-, HCF-, and HCM-EVs were isolated and characterized, and human corneal epithelial (HCE) cell migration was assessed in a scratch assay following PKH26-labeled HCK-, HCF-, or HCM-EV treatment. HCE cells proliferative and apoptotic activity following EV treatment was assessed. HCF-/HCM-EVs were enriched for CD63, CD81, ITGAV, and THBS1 compared to HCK-EV. All EVs were negative for GM130 and showed minimal differences in biophysical properties. At the proteomic level, we showed HCM-EV with a log >two-fold change in CXCL6, CXCL12, MMP1, and MMP2 expression compared to HCK-/HCF-EVs; these proteins are associated with cellular movement pathways. Upon HCM-EV treatment, HCE cell migration, velocity, and proliferation were significantly increased compared to HCK-/HCF-EVs. This study concludes that the HCM-EV protein cargo influences HCE cell migration and proliferation, and understanding these elements may provide a novel therapeutic avenue for corneal wound healing.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

Nuclear factor-kappa B (NF-κB) inhibition as a therapeutic target for plant nutraceuticals in mitigating inflammatory lung diseases

Nutraceuticals are dietary supplements that are used to improve health, postpone aging, prevent illnesses, and maintain the human body's correct functioning. Nutraceuticals are now garnering a lot of interest because of their nutritional and therapeutic benefits. The research indicating the relevance of nutraceuticals as a possible therapeutic candidate against inflammatory lung disease was covered in this review. Nowadays, inflammatory lung diseases such as chronic obstructive pulmonary disease (COPD), pulmonary fibrosis, asthma, pneumonia, lung cancer, becoming highly dreadful because of their associated fatality. Inflammation is one of the cores and common factors of these diseases which is mainly associated with nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation, NF-κB p65 and nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IκBα) phosphorylation, and initiation of the signaling pathway of the NF-κB. The secondary metabolites from natural sources are the active component that attenuates NF-κB and the associated pathway that inhibits inflammation in lung diseases. Nutraceuticals belonging to the chemical category polyphenols, alkaloids, terpenoids, flavonoids, tannins have the potential to combat the NF-κB pathway. Accordingly, this review discusses the medical value of nutraceuticals briefly and their ability to mitigate various inflammatory lung diseases through targeting inhibition of NF-κB.

The effect and mechanisms of melatonin on the proliferation and apoptosis of lung cancer cells

The aim of the present study was to observe the effects and mechianisms of melatonin on the proliferation and apoptosis of lung cancer (LC) cells. A549 cells were treated with a concentration gradient (0–100 μM) of melatonin for 24 hours, and cell viability was detected by XTT ((2,3-Bis-(2-methoxy-4-nitro-5-sulfophenyl) −2H-tetrazolium-5-carboxanilide)) colorimetry. Melatonin with a concentration of 50 μM was selected to interact with the LC cells for ten days, and then a colony formation assay was used to detect the proliferation of the LC cells. TUNEL (Terminal-deoxynucleoitidyl Transferase Mediated Nick End Labeling) staining was used to evaluate the amount of apoptosis in the two groups. Finally, Western blotting was used to detect the expression levels of related proteins in the p38MAP (mitogen-activated protein) signaling pathway. Meanwhile, another experiment, CCK-8 cell proliferation test, was conducted to detect the OD540 absorbance of LC cells at 24, 48, 72, and 96 hours. Melatonin inhibited the proliferation of LC cells in a concentration-dependent (5–100 μM) manner (P < 0.05), and inhibited the proliferation of LC cells in a time-dependent (0–96 hour) manner (P < 0.05). Melatonin (50 μM) could significantly inhibit the colony formation ability of LC cells (P < 0.05). The ratio of LC cells in the G0/G1 phase in the melatonin group increased, while the ratio of cells in the G2/M and S phase was significantly reduced (P < 0.05). Melatonin significantly promoted the apoptosis of LC cells (P < 0.05) and activate the phosphorylation of p38 (P < 0.05).

Diagnostic and prognostic value of CT perfusion parameters in patients with advanced NSCLC after chemotherapy

OBJECTIVE

To determine the short-term prognostic value of Computed Tomography (CT) perfusion parameters in patients with advanced non-small cell lung cancer (NSCLC) after chemotherapy.

METHODS

A total of 60 patients with NSCLC who received concurrent radiotherapy and chemotherapy were enrolled. Before therapy, CT perfusion imaging was conducted to scan their local lesions. Then, the CT perfusion-associated parameters were recorded, and evaluated. According to the Response Evaluation Criteria in Solid Tumors (RECIST), 42 out of 60 patients had remission after chemotherapy. The blood flow (BF), blood volume (BV), and permeability surface (PS) of the two groups were analyzed before therapy, and factors and parameters affecting the efficacy of concurrent radiotherapy and chemotherapy were discussed.

RESULTS

After chemotherapy, patients with remission showed lower BF, BV, and PS levels in pulmonary lesions than those without remission (all P<0.05). According to the 1-year follow-up results, 33 cases survived, and 27 cases died, and the survivors showed lower BF and PS levels than the dead (both P<0.05).

CONCLUSION

Patients with lower BF and PS in CT perfusion parameters obtained better chemotherapy efficacy, so BF and PS can be adopted to predict the survival of patients.

Targeted liquid chromatography-tandem mass spectrometry analysis of proteins: Basic principles, applications, and perspectives

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is now the main analytical method for the identification and quantification of peptides and proteins in biological samples. In modern research, identification of biomarkers and their quantitative comparison between samples are becoming increasingly important for discovery, validation, and monitoring. Such data can be obtained following specific signals after fragmentation of peptides using multiple reaction monitoring (MRM) and parallel reaction monitoring (PRM) methods, with high specificity, accuracy, and reproducibility. In addition, these methods allow measurement of the amount of post-translationally modified forms and isoforms of proteins. This review article describes the basic principles of MRM assays, guidelines for sample preparation, recent advanced MRM-based strategies, applications and illustrative perspectives of MRM/PRM methods in clinical research and molecular biology.

Identification of Differentially Expressed Circular RNAs as miRNA Sponges in Lung Adenocarcinoma

Background

Circular RNAs (circRNAs) may function as the decoys for microRNAs (miRNAs) or proteins, the templates for translation, and the sources of pseudogene generation. The purpose of this study is to determine the diagnostic circRNAs, which are related to lung adenocarcinoma (LUAD), that adsorb miRNAs on the basis of the competing endogenous RNA (ceRNA) hypothesis.

Methods

The differentially expressed circRNAs (DEcircRNAs) in LUAD were revealed by the microarray data (GSE101586 and GSE101684) that were obtained from the Gene Expression Omnibus (GEO) database. The miRNAs that were targeted by the DEcircRNAs were predicted with the CircInteractome, and the target mRNAs of the miRNAs were found by the miRDB and the TargetScan. The ceRNA network was built by the Cytoscape. The potential biological roles and the regulatory mechanisms of the circRNAs were investigated by the Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The expression of the host genes of circRNAs was examined by the Ualcan. The survival analysis was performed by the Kaplan-Meier plotter.

Results

In comparison with normal lung tissues, LUAD tissues contained 7 overlapping cancer-specific DEcircRNAs with 294 miRNA response elements (MREs). Among the 7 DEcircRNAs, 3 circRNAs (hsa_circ_0072088, hsa_circ_0003528, and hsa_circ_0008274) were upregulated and 4 circRNAs (hsa_circ_0003162, hsa_circ_0029426, hsa_circ_0049271, and hsa_circ_0043256) were downregulated. A circRNA-miRNA-mRNA regulatory network, which included 33 differentially expressed miRNAs (DEmiRNAs) and 2007 differentially expressed mRNAs (DEmRNAs), was constructed. These mRNAs were enriched in the biological function of cell-cell adhesion, response to hypoxia, and stem cell differentiation and were involved in the PI3K-Akt signaling, HIF-1 signaling, and cAMP signaling pathways.

Conclusion

Our results indicated that 7 DEcircRNAs could have diagnostic value for LUAD. Additionally, the circRNAs-mediated ceRNA network might provide a novel perspective into unraveling the pathogenesis and progression of LUAD.

LncRNA LINC00520 aggravates cell proliferation and migration in lung adenocarcinoma via a positive feedback loop

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological subtype of primary lung cancer. To identify the biomarker of diagnosis for LUAD is of great significance. Long non-coding RNAs (lncRNAs) were previously revealed to exert vital effects in numerous cancers. LncRNA long intergenic non-protein coding RNA 520 (LINC00520) served as an oncogene in various cancers. Therefore, our study was specially designed to probe the role of LINC00520 in LUAD.

RESULTS

LINC00520 expression was detected by RT-qPCR. Next, function of LINC00520 in LUAD was verified by in vitro loss-of-function experiments. DNA pull down, ChIP, RIP, and luciferase reporter assays were conducted to reveal the regulatory mechanism of LINC00520. We found that LINC00520 was upregulated in LUAD. Additionally, LINC00520 upregulation is associated with the poor prognosis for patients with LUAD. Furthermore, LINC00520 downregulation suppressed LUAD cell proliferation and migration and induced cell apoptosis. Forkhead box P3 (FOXP3) is identified as the transcription factor to transcriptionally activate LINC00520. Moreover, LINC00520 positively upregulated FOXP3 expression via sponging miR-3611 in LUAD cells. Subsequently, rescue experiments delineated that miR-3611 downregulation or FOXP3 overexpression reversed the effects of silenced LINC00520 on proliferative and migratory capabilities in LUAD cells.

CONCLUSION

This study innovatively indicated that lncRNA LINC00520 facilitated cell proliferative and migratory abilities in LUAD through interacting with miR-3611 and targeting FOXP3, which may provide a potential novel insight for treatment of LUAD.

Identification of prognostic markers by weighted gene co-expression network analysis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8⁺ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (AURKB, CDC20, TPX2 and KIF2C) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of AURKB, CDC20, TPX2, and KIF2C correlated with the poor prognosis of these patients. In vitro experiments confirmed that CDC20 knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8⁺ T cell infiltration-related biomarkers and therapeutic targets.

From Donor to the Lab: A Fascinating Journey of Primary Cell Lines

Primary cancer cell lines are ex vivo cell cultures originating from resected tissues during biopsies and surgeries. Primary cell cultures are objects of intense research due to their high impact on molecular biology and oncology advancement. Initially, the patient-derived specimen must be subjected to dissociation and isolation. Techniques for tumour dissociation are usually reliant on the organisation of connecting tissue. The most common methods include enzymatic digestion (with collagenase, dispase, and DNase), chemical treatment (with ethylene diamine tetraacetic acid and ethylene glycol tetraacetic acid), or mechanical disaggregation to obtain a uniform cell population. Cells isolated from the tissue specimen are cultured as a monolayer or three-dimensional culture, in the form of multicellular spheroids, scaffold-based cultures (i.e., organoids), or matrix-embedded cultures. Every primary cell line must be characterised to identify its origin, purity, and significant features. The process of characterisation should include different assays utilising specific (extra- and intracellular) markers. The most frequently used approaches comprise immunohistochemistry, immunocytochemistry, western blot, flow cytometry, real-time polymerase chain reaction, karyotyping, confocal microscopy, and next-generation sequencing. The growing body of evidence indicates the validity of the usage of primary cancer cell lines in the formulation of novel anti-cancer treatments and their contribution to drug development.

Shiquan Yuzhen Decoction inhibits angiogenesis and tumor apoptosis caused by non-small cell lung cancer and promotes immune response

BACKGROUND

TCM treatment for lung carcinoma has been reported by many researches. Shiquan Yuzhen Decoction can be used in the clinical treatment of lung carcinoma, but its specific mechanism is still under exploration at present.

METHODS

The active ingredients and mechanism of Shiquan Yuzhen Decoction on non-small cell lung carcinoma were discussed by network pharmacology. The main active ingredients, targets and disease genes of non-small cell lung carcinoma of Shiquan Yuzhen Decoction were screened through relevant databases. Lewis lung carcinoma bearing mice model was established by inoculating Lewis lung carcinoma cells to C57BL/6 mice under the right armpit. Different doses of Shiquan Yuzhen Decoction were used to observe the apoptosis and angiogenesis changes of tumor tissues in mice.

RESULTS

A total of 26 key active compounds meeting the evaluation of generic properties and 182 main targets were screened out. The multi-level network model shows that Shiquan Yuzhen Decoction can regulate the target gene network of non-small cell lung carcinoma. And it can inhibit tumor growth in tumor-bearing mice, induce apoptosis of tumor cells, and evidently increase the activities of Caspase-3, 8 and 9. The dose of 17.4 g/kg can evidently inhibit the formation of microvessels in transplanted tumor tissues, improve the sensitivity of mice's diet and activities, increase the spleen index of tumor-bearing mice, and inhibit inflammatory factors.

CONCLUSION

Shiquan Yuzhen Decoction can evidently improve the quality of life of Lewis lung carcinoma-bearing mice and inhibit tumor growth in mice, which is a potential clinical treatment plan.

Prospective Identification of Elevated Circulating CDCP1 in Patients Years before Onset of Lung Cancer

Increasing evidence points to a role for inflammation in lung carcinogenesis. A small number of circulating inflammatory proteins have been identified as showing elevated levels prior to lung cancer diagnosis, indicating the potential for prospective circulating protein concentration as a marker of early carcinogenesis. To identify novel markers of lung cancer risk, we measured a panel of 92 circulating inflammatory proteins in 648 prediagnostic blood samples from two prospective cohorts in Italy and Norway (women only). To preserve the comparability of results and protect against confounding factors, the main statistical analyses were conducted in women from both studies, with replication sought in men (Italian participants). Univariate and penalized regression models revealed for the first time higher blood levels of CDCP1 protein in cases that went on to develop lung cancer compared with controls, irrespective of time to diagnosis, smoking habits, and gender. This association was validated in an additional 450 samples. Associations were stronger for future cases of adenocarcinoma where CDCP1 showed better explanatory performance. Integrative analyses combining gene expression and protein levels of CDCP1 measured in the same individuals suggested a link between CDCP1 and the expression of transcripts of LRRN3 and SEM1. Enrichment analyses indicated a potential role for CDCP1 in pathways related to cell adhesion and mobility, such as the WNT/β-catenin pathway. Overall, this study identifies lung cancer-related dysregulation of CDCP1 expression years before diagnosis. SIGNIFICANCE: Prospective proteomics analyses reveal an association between increased levels of circulating CDCP1 and lung carcinogenesis irrespective of smoking and years before diagnosis, and integrating gene expression indicates potential underlying mechanisms.See related commentary by Itzstein et al., p. 3441.

Proteomics applications in biomarker discovery and pathogenesis for abdominal aortic aneurysm

Introduction: Abdominal aortic aneurysm (AAA) is a common, complex, and life-threatening disease. Currently, the pathogenesis of AAA is not well understood. No biomarkers or specific drugs are available for AAA in clinical applications. Proteomics is a powerful tool in biomarker discovery, exploration of pathogenesis, and drug target identification.Areas covered: We review the application of mass spectrometry-based proteome analysis in AAA patients within the last ten years. Differentially expressed proteins associated with AAA were identified in multiple sample sources, including vascular tissue, intraluminal thrombus, tissue secretome, blood, and cells. Some potential disease biomarkers, pathogenic mechanisms, or therapeutic targets for AAA were discovered using proteome analysis. The challenges and prospects of proteomics applied to AAA are also discussed.Expert opinion: Since most of the previous proteomic studies used relatively small sample sizes, some promising biomarkers need to be validated in multicenter cohorts to accelerate their clinical application. With the rapid development of mass spectrometry technology, modification-specific proteomics and multi-omics research in the future will enhance our understanding of the pathogenesis of AAA and promote biomarker discovery and drug development for clinical translation.

The predictive prognostic values of CBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 in lung cancer

Background

Lung cancer is one of the most malignant tumors. However, neither the pathogenesis of lung cancer nor the prognosis markers are completely clear. The purpose of this study is to screen the diagnostic or prognostic markers of lung cancer.

Methods

TCGA and GEO datasets were used to analyze the relationship between lung cancer-related genes and lung cancer samples. Common differential genes were screened, and a univariate Cox regression analysis was used to screen survival related genes. A univariable Cox proportional hazards regression analysis was used to verify the genes and construct risk model. The key factors affecting the prognosis of lung cancer were determined by univariate and multivariate regression analyses. The ROC curve, AUC and the survival of each risk gene was analyzed. Finally, the biological functions of high- and low-risk patients were explored by GSEA and an immune-infiltration analysis.

Results

Based on the common differential genes, 13 genes significantly related to lung cancer survival were identified. Eight risk genes (CBFA2T3, DENR, EGLN1, FUT2, FUT4, PCDH7, PHF14, and STX3) were screened out. The results showed that risk status may be an independent prognostic factor, and the risk score predicted the prognosis of lung cancer. CBFA2T3 and STX3 are protective genes, while DENR, EGLN1, FUT4 and PCDH7 are dangerous genes. These 6 genes can be used as independent lung cancer prognosis markers. The corresponding biological functions of genes expressed in high-risk patients were mostly related to tumor proliferation and inflammatory infiltration. Neutrophil, CD8⁺T, Macrophage M0, Macrophage M1- and mDC-activated cells were high in high-risk status samples.

Conclusions

CBFA2T3, STX3, DENR, EGLN1, FUT4, and PCDH7 are important participants in the occurrence and development of lung cancer. High-risk patients display serious inflammatory infiltration. This study not only provides insight into the mechanism of occurrence and development of lung cancer, but also provides potential targets for targeted therapy of lung cancer.

Tianlongkechuanling Inhibits Pulmonary Fibrosis Through Down-Regulation of Arginase-Ornithine Pathway

Background: Pulmonary Fibrosis (PF) is an interstitial lung disease characterized by excessive accumulation of extracellular matrix in the lungs, which disrupts the structure and gas exchange of the alveoli. There are only two approved therapies for PF, nintedanib (Nib) and pirfenidone. Therefore, the use of Chinese medicine for PF is attracting attention. Tianlongkechuanling (TL) is an effective Chinese formula that has been applied clinically to alleviate PF, which can enhance lung function and quality of life.

Purpose: The potential effects and specific mechanisms of TL have not been fully explored, yet. In the present study, proteomics was performed to explore the therapeutic protein targets of TL on Bleomycin (BLM)-induced Pulmonary Fibrosis.

Method: BLM-induced PF mice models were established. Hematoxylineosin staining and Masson staining were used to analyze histopathological changes and collagen deposition. To screen the differential proteins expression between the Control, BLM, BLM + TL and BLM + Nib (BLM + nintedanib) groups, quantitative proteomics was performed using tandem mass tag (TMT) labeling with nanoLC-MS/MS [nano liquid chromatographymass spectrometry]). Changes in the profiles of the expressed proteins were analyzed using the bioinformatics tools Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein–protein interactions (PPI) were established by STRING. Expressions of α-smooth muscle actin (α-SMA), Collagen I (Col1a1), Fibronectin (Fn1) and enzymes in arginase-ornithine pathway were detected by Western blot or RT-PCR.

Result: TL treatments significantly ameliorated BLM-induced collagen deposition in lung tissues. Moreover, TL can inhibit the protein expressions of α-SMA and the mRNA expressions of Col1a1 and Fn1. Using TMT technology, we observed 253 differentially expressed proteins related to PPI networks and involved different KEGG pathways. Arginase-ornithine pathway is highly significant. The expression of arginase1 (Arg1), carbamoyltransferase (OTC), carbamoy-phosphate synthase (CPS1), argininosuccinate synthase (ASS1), ornithine aminotransferase (OAT) argininosuccinate lyase (ASL) and inducible nitric oxide synthase (iNOS) was significantly decreased after TL treatments.

Conclusion: Administration of TL in BLM-induced mice resulted in decreasing pulmonary fibrosis. Our findings propose that the down regulation of arginase-ornithine pathway expression with the reduction of arginase biosynthesis is a central mechanism and potential treatment for pulmonary fibrosis with the prevention of TL.

Quantitative Proteomic Approach Reveals Altered Metabolic Pathways in Response to the Inhibition of Lysine Deacetylases in A549 Cells under Normoxia and Hypoxia

Growing evidence is showing that acetylation plays an essential role in cancer, but studies on the impact of KDAC inhibition (KDACi) on the metabolic profile are still in their infancy. Here, we analyzed, by using an iTRAQ-based quantitative proteomics approach, the changes in the proteome of KRAS-mutated non-small cell lung cancer (NSCLC) A549 cells in response to trichostatin-A (TSA) and nicotinamide (NAM) under normoxia and hypoxia. Part of this response was further validated by molecular and biochemical analyses and correlated with the proliferation rates, apoptotic cell death, and activation of ROS scavenging mechanisms in opposition to the ROS production. Despite the differences among the KDAC inhibitors, up-regulation of glycolysis, TCA cycle, oxidative phosphorylation and fatty acid synthesis emerged as a common metabolic response underlying KDACi. We also observed that some of the KDACi effects at metabolic levels are enhanced under hypoxia. Furthermore, we used a drug repositioning machine learning approach to list candidate metabolic therapeutic agents for KRAS mutated NSCLC. Together, these results allow us to better understand the metabolic regulations underlying KDACi in NSCLC, taking into account the microenvironment of tumors related to hypoxia, and bring new insights for the future rational design of new therapies.

Enkurin domain containing 1 (ENKD1) regulates the proliferation, migration and invasion of non-small cell lung cancer cells

Non-small cell lung cancer (NSCLC) is the most common cause of cancer mortality worldwide. NSCLC has an aggressive phenotype and poor prognosis, and is quite heterogeneous without effective and specific targeted therapies. Therefore, exploring new tumor markers and drug targets for NSCLC is crucial towards individualized treatment. Here, we demonstrate that enkurin domain containing 1 (ENKD1), a protein with unknown structure and function, is significantly downregulated in NSCLC tumor tissues compared with their non-tumor counterparts. We also show that ENKD1 expression is decreased in NSCLC cells compared to normal human lung epithelial cells. EdU incorporation, wound healing, and transwell invasion assays reveal that ENKD1 regulates the proliferation, migration, and invasion of NSCLC cells. Collectively, these results suggest that ENKD1 plays an important role in NSCLC progression and that ENKD1 is a tumor marker and a potential molecular drug target for the treatment of NSCLC patients.

Studies in lung cancer cytokine proteomics: a review

INTRODUCTION

Proteins are molecules that have role in the progression of the diseases. Proteomics is a tool that can play an effective role in identifying diagnostic and therapeutic biomarkers for lung cancer. Cytokines are proteins that play a decisive role in activating body's immune system in lung cancer. They can increase the growth of the tumor (oncogenic cytokines) or limit tumor growth (anti-tumor cytokines) by regulating related signaling pathways such as proliferation, growth, metastasis, and apoptosis.

AREAS COVERED

In the present study, a total of 223 papers including 196 research papers and 27 review papers, extracted from PubMed and Scopus and published from 1997 to present, are reviewed. The most important involved-cytokines in lung cancer including TNF-α, IFN- γ, TGF-β, VEGF and interleukins such as IL-6, IL-17, IL-8, IL-10, IL-22, IL-1β and IL-18 are introduced. Also, the pathological and biological role of such cytokines in cancer signaling pathways is explained.

EXPERT OPINION

In lung cancer, the cytokine expression changes under the physiological conditions of the immune system, and inflammatory cytokines are associated with the progression of lung cancer. Therefore, the cytokine expression profile can be used in the diagnosis, prognosis, prediction of therapeutic responses, and survival of patients with lung cancer.

FENDRR: A pivotal, cancer-related, long non-coding RNA

Long non-coding RNAs (lncRNAs) have more than 200 nucleotides and do not encode proteins. Based on numerous studies, lncRNAs have emerged as new and crucial regulators of biological function and have been implicated in the pathogenesis of a variety of diseases, especially cancers. Specific lncRNAs have been identified as novel molecular biomarkers for cancer diagnosis, prognosis, and treatment efficacy. Fetal-lethal non-coding developmental regulatory RNA (FENDRR, also known as FOXF1-AS1) is a novel lncRNA that is located at chr3q13.31 and has four exons and 3099 nucleotides, and its genomic site is located at chr3q13.31. FENDRR is abnormally expressed in a variety of cancers and is significantly associated with different clinical characteristics. In addition, FENDRR has shown potential as a biomarker for cancer diagnosis, prognosis, and treatment. In this review, we summarize the current understanding of FENDRR and its mechanistic role in cancer progression. We also discuss recent insights into the clinical significance of FENDRR for cancer diagnosis, prognosis, and treatment.

Gefitinib reduces oocyte quality by disturbing meiotic progression

Gefitinib is a first-line anti-cancer drug for the treatment of advanced non-small cell lung cancer (NSCLC). It has been reported that gefitinib can generate several drug-related adverse effects, including nausea, peripheral edema, decreased appetite and rash. However, the reproductive toxicity of gefitinib has not been clearly defined until now. Here we assessed the effects of gefitinib on oocyte quality by examining the critical events and molecular changes of oocyte maturation. Gefitinib at 1, 2, 5 or 10 μM concentration was added to culture medium (M2). We found that gefitinib at its median peak concentration of 1 μM did not affect oocyte maturation, but 5 μM gefitinib severely blocked oocyte meiotic progression as indicated by decreased rates of germinal vesicle breakdown (GVBD) and polar body extrusion (PBE). We further showed that gefitinib treatment increased phosphorylation of CDK1 at the site of Try15, inhibited cyclin B1 entry into the nucleus, and disrupted normal spindle assembly, chromosome alignment and mitochondria dynamics, finally leading to the generation of aneuploidy and early apoptosis of oocytes. Our study reported here provides valuable evidence for reproductive toxicity of gefitinib administration employed for the treatment of cancer patients.

Downregulation of long non-coding RNA LINC-PINT serves as a diagnostic and prognostic biomarker in patients with non-small cell lung cancer

Long non-coding RNAs (lncRNAs) play an important role in gene regulation. Several lncRNAs have been demonstrated to be associated with the diagnosis and prognosis of non-small cell lung cancer (NSCLC). The present study aimed to investigate the role of lncRNA long intragenic non-protein-coding RNA p53-induced transcript (LINC-PINT) in NSCLC to identify a novel non-invasive biomarker for the diagnosis and prognosis of patients with NSCLC. Reverse transcription-quantitative PCR analysis was performed to detect LINC-PINT expression in the tissue and serum samples of patients with NSCLC. The diagnostic and prognostic values of LINC-PINT were assessed via the receiver operating characteristic curve, and Kaplan-Meier and Cox regression analyses, respectively. The results demonstrated that LINC-PINT expression was significantly downregulated in NSCLC serum samples and tissues. In addition, serum LINC-PINT exhibited diagnostic value in patients with NSCLC, and may be used to predict prognosis. Furthermore, aberrant LINC-PINT expression in tumor tissues was significantly associated with lymph node metastasis, tumor size, differentiation and TNM stage. Taken together, the results of the present study suggest that lncRNA LINC-PINT may be an independent diagnostic and prognostic biomarker in NSCLC.

Differential Expression and Bioinformatics Analysis of circRNA in Non-small Cell Lung Cancer

Circular RNA (CircRNA) plays an important role in tumorigenesis and progression of non-small cell lung cancer (NSCLC), but the pathogenesis of NSCLC caused by circRNA has not been fully elucidated. This study aimed to investigate differentially expressed circRNAs and identify the underlying pathogenesis hub genes of NSCLC by comprehensive bioinformatics analysis. Data of gene expression microarrays (GSE101586, GSE101684, and GSE112214) were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed circRNAs (DECs) were obtained by the “limma” package of R programs and the overlapping operation was implemented of DECs. CircBase database and Cancer-Specific CircRNA database (CSCD) were used to find miRNAs binding to DECs. Target genes of the found miRNAs were identified utilizing Perl programs based on miRDB, miRTarBase, and TargetScan databases. Functional and enrichment analyses of selected target genes were performing using the “cluster profiler” package. Protein-protein interaction (PPI) network was constructed by the Search Tool for the STRING database and module analysis of selected hub genes was performed by Cytoscape 3.7.1. Survival analysis of hub genes were performed by Gene Expression Profiling Interactive Analysis (GEPIA). Respectively, 1 DEC, 249 DECs, and 101 DECs were identified in GSE101586, GSE101684, and GSE112214. A total of eight overlapped circRNAs, 43 miRNAs and 427 target genes were identified. Gene Ontology (GO) enrichment analysis showed these target genes were enriched in biological processes of regulation of histone methylation, Ras protein signal transduction and covalent chromatin modification etc. Pathway enrichment analysis showed these target genes are mainly involved in AMPK signaling pathway, signaling pathways regulating pluripotency of stem cells and insulin signaling pathway etc. A PPI network was constructed based on 427 target genes of the 43 miRNAs. Ten hub genes were found, of which the expression of MYLIP, GAN, and CDC27 were significantly related to NSCLC patient prognosis. Our study provide a deeper understanding the circRNAs-miRNAs-target genes by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of NSCLC. MYLIP, GAN, and CDC27 genes might serve as novel biomarker for precise treatment and prognosis of NSCLC in the future.

A Quest for New Cancer Diagnosis, Prognosis and Prediction Biomarkers and Their Use in Biosensors Development

Traditional techniques for cancer diagnosis, such as nuclear magnetic resonance, ultrasound and tissue analysis, require sophisticated devices and highly trained personnel, which are characterized by elevated operation costs. The use of biomarkers has emerged as an alternative for cancer diagnosis, prognosis and prediction because their measurement in tissues or fluids, such as blood, urine or saliva, is characterized by shorter processing times. However, the biomarkers used currently, and the techniques used for their measurement, including ELISA, western-blot, polymerase chain reaction (PCR) or immunohistochemistry, possess low sensitivity and specificity. Therefore, the search for new proteomic, genomic or immunological biomarkers and the development of new noninvasive, easier and cheaper techniques that meet the sensitivity and specificity criteria for the diagnosis, prognosis and prediction of this disease has become a relevant topic. The purpose of this review is to provide an overview about the search for new cancer biomarkers, including the strategies that must be followed to identify them, as well as presenting the latest advances in the development of biosensors that possess a high potential for cancer diagnosis, prognosis and prediction, mainly focusing on their relevance in lung, prostate and breast cancers.