Current and Prospective Protein Biomarkers of Lung Cancer

Disposable Zirconium trisulfide-Reduced graphene oxide modified conducting thread based electrochemical biosensor for lung cancer diagnosis

Flexible technology in sensors have received much attention in monitoring of human health through various physiological indicators. Thus, it drawn a lot of interest in the development of flexible substrate for the diagnosis of various diseases via analysis of analytes. Present work focusses on the development of ecofriendly, portable, flexible, conducting thread (Th) and used as smart substrate for fabrication of biosensor towards ultrasensitive detection of the lung cancer biomarker (cytoskeleton-associated protein 4; CKAP4). The zirconium trisulfide-reduced graphene oxide nanocomposite and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) modified cotton thread based biosensor was fabricated via dip coating method. Next, successive immobilization of monoclonal antibodies of CKAP4 (anti-CKAP4) and bovine serum albumin (BSA) was performed via drop cast approach using fabricated electrode [nZrS3@rGO/PEDOT:PSS/Th]. The response of fabricated electrode (BSA/anti-CKAP4/ZrS3@rGO/PEDOT:PSS/Th) was recorded electrochemically versus CKAP4 concentration via chronoamperometry (CA). The results showed wider linear detection range of 6.25-800 pg mL-1, excellent sensitivity of 85.2 µA[log(pg mL-1)]-1cm-2 with good stability up to 42 days. The response of fabricated biosensor was supported by investigating response of CKAP4 biomarker present in patients of lung cancer (concentration as determined through enzyme-linked immunosorbent assay) and obtained results exhibited excellent correlation with that of standard samples.

A Multi-Omics Study of Epigenetic Changes in Type II Alveolar Cells of A/J Mice Exposed to Environmental Tobacco Smoke

Lung cancer remains a major contributor to cancer fatalities, with cigarette smoking known to be responsible for up to 80% of cases. Based on the ability of cigarette smoke to induce inflammation in the lungs and increased lung cancer incidence in smokers with inflammatory conditions such as COPD, we hypothesized that inflammation plays an important role in the carcinogenicity of cigarette smoke. To test this hypothesis, we performed multi-omic analyses of Type II pneumocytes of A/J mice exposed to cigarette smoke for various time periods. We found that cigarette smoke exposure resulted in significant changes in DNA methylation and hydroxymethylation, gene expression patterns, and protein abundance that were partially reversible and contributed to an inflammatory and potentially oncogenic phenotype.

Small-Cell Lung Cancer: Is Liquid Biopsy a New Tool Able to Predict the Efficacy of Immunotherapy?

Small-cell lung cancer (SCLC) cases represent approximately 15% of all lung cancer cases, remaining a recalcitrant malignancy with poor survival and few treatment options. In the last few years, the addition of immunotherapy to chemotherapy improved clinical outcomes compared to chemotherapy alone, resulting in the current standard of care for SCLC. However, the advantage of immunotherapy only applies to a few SCLC patients, and predictive biomarkers selection are lacking for SCLC. In particular, due to some features of SCLC, such as high heterogeneity, elevated cell plasticity, and low-quality tissue samples, SCLC biopsies cannot be used as biomarkers. Therefore, the characterization of the tumor and, subsequently, the selection of an appropriate therapeutic combination may benefit greatly from liquid biopsy. Soluble factors, circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) are now useful tools in the characterization of SCLC. This review summarizes the most recent data on biomarkers detectable with liquid biopsy, emphasizing their role in supporting tumor detection and their potential role in SCLC treatment choice.

PD-L1 on large extracellular vesicles is a predictive biomarker for therapy response in tissue PD-L1-low and -negative patients with non-small cell lung cancer

Immunotherapy has revolutionized the treatment of patients with non-small cell lung cancer (NSCLC). High expression of tissue PD-L1 (tPD-L1) is currently the only approved biomarker for predicting treatment response. However, even tPD-L1 low (1-49%) and absent (<1%) patients might benefit from immunotherapy but, to date, there is no reliable biomarker, that can predict response in this particular patient subgroup. This study aimed to test whether tumour-associated extracellular vesicles (EVs) could fill this gap. Using NSCLC cell lines, we identified a panel of tumour-related antigens that were enriched on large EVs (lEVs) compared to smaller EVs. The levels of lEVs carrying these antigens were significantly elevated in plasma of NSCLC patients (n = 108) and discriminated them from controls (n = 77). Among the tested antigens, we focused on programmed cell death ligand 1 (PD-L1), which is a well-known direct target for immunotherapy. In plasma lEVs, PD-L1 was mainly found on a population of CD45- /CD62P+ lEVs and thus seemed to be associated with platelet-derived vesicles. Patients with high baseline levels of PD-L1+ lEVs in blood showed a significantly better response to immunotherapy and prolonged survival. This was particularly true in the subgroup of NSCLC patients with low or absent tPD-L1 expression, thus identifying PD-L1-positive lEVs in plasma as a novel predictive and prognostic marker for immunotherapy.

Overexpression of SLC35F2 is a potential prognostic biomarker for lung adenocarcinoma

Objective

To explore the potential clinical and prognostic significance of Homo sapiens solute carrier family 35 member F2 (SLC35F2) in the context of lung adenocarcinoma (LUAD).

Methods

The expression pattern of SLC35F2 in LUAD tissues and normal tissues was analyzed in The Cancer Genome Atlas (TCGA) datasets and validated in 12 pairs of fresh clinical LUAD tissues and their corresponding adjacent normal tissues using quantitative real-time PCR (qRT-PCR) and western blotting. Immunohistochemistry (IHC) was used to assess the protein expression of SLC35F2 in 60 paraffin-embedded LUAD tissues, and its associations with clinicopathological parameters were further examined. The prognostic significance of SLC35F2 mRNA expression was also evaluated using the Kaplan-Meier method, and Cox regression models in LUAD patients from the TCGA database. The potential utility of SLC35F2 as an indicator of recurrence or metastasis was explored through the follow-up of selected clinical LUAD cases. Lastly, gene set enrichment analysis (GSEA) was conducted to investigate the underlying biological mechanisms and signaling pathways.

Results

Bioinformatics analysis utilizing the TCGA database indicated that SLC35F2 mRNA exhibited heightened expression in LUAD tissues when compared to normal tissues. These findings were further substantiated through the examination of 12 pairs of clinical LUAD tissues and their corresponding adjacent normal tissues, employing qRT-PCR and western blotting techniques. IHC results from a cohort of 60 LUAD patients demonstrated an up-regulation of SLC35F2 in 38 out of 60 individuals (63.3 %), which exhibited a significant correlation with tumor size, lymph node metastasis, and clinical stage (all P < 0.05). Both the Kaplan-Meier curve and the Cox proportional hazard analyses indicated a strong association between the up-regulation of SLC35F2 mRNA expression and unfavorable overall survival (OS) in patients with LUAD, as observed in the TCGA datasets (P < 0.05). The follow-up findings from select clinical LUAD cases provided evidence that the expression of SLC35F2 could serve as a dependable biomarker for monitoring the recurrence or metastasis. Additionally, the GSEA highlighted the enrichment of apoptosis, adhesion, small cell lung cancer (SCLC), and p53 signaling pathways in the subgroup of LUAD patients with elevated SLC35F2 expression.

Conclusion

SLC35F2 exhibited an up-regulated in both mRNA and protein expression, rendering it a valuable independent prognostic indicator for patients diagnosed with LUAD.

Advances and Challenges in Nanomaterial-Based Electrochemical Immunosensors for Small Cell Lung Cancer Biomarker Neuron-Specific Enolase

Early and rapid detection of neuron-specific enolase (NSE) is highly significant, as it is putative biomarker for small-cell lung cancer as well as COVID-19. Electrochemical techniques have attracted substantial attention for the early detection of cancer biomarkers due to the important properties of simplicity, high sensitivity, specificity, low cost, and point-of-care detection. This work reviews the clinically relevant labeled and label-free electrochemical immunosensors developed so far for the analysis of NSE. The prevailing role of nanostructured materials as electrode matrices is thoroughly discussed. Subsequently, the key performances of various immunoassays are critically evaluated in terms of limit of detection, linear ranges, and incubation time for clinical translation. Electrochemical techniques coupled with screen-printed electrodes developing market level commercialization of NSE sensors is also discussed. Finally, the review concludes with the current challenges associated with available methods and provides a future outlook toward commercialization opportunities for easy detection of NSE.

Identification of protein signatures for lung cancer subtypes based on BPSO method

The objective of this study was to identify protein biomarkers that can distinguish between LUAD and LUSC, critical for personalized treatment plans. The proteomic profiling data of LUAD and LUSC samples from TCPA database, along with phenotype and survival information from TCGA database were downloaded and preprocessed for analysis. We used BPSO feature selection method and identified 10 candidate protein biomarkers that have better classifying performance, as analyzed by t-SNE and PCA algorithms. To explore the causalities among these proteins and their associations with tumor subtypes, we conducted the PCStable algorithm to construct a regulatory network. Results indicated that 4 proteins, MIG6, CD26, NF2, and INPP4B, were directly linked to the lung cancer subtypes and may be useful in guiding therapeutic decision-making. Besides, spearman correlation, Cox proportional hazard model and Kaplan-Meier curve was employed to validate the biological significance of the candidate proteins. In summary, our study highlights the importance of protein biomarkers in the classification of lung cancer subtypes and the potential of computational methods for identifying key biomarkers and understanding their underlying biological mechanisms.

Liquid biopsy for early detection of lung cancer

Lung cancer is the leading cause of cancer-related mortality worldwide. Early cancer detection plays an important role in improving treatment success and patient prognosis. In the past decade, liquid biopsy became an important tool for cancer diagnosis, as well as for treatment selection and response monitoring. Liquid biopsy is a broad term that defines a non-invasive test done on a sample of blood or other body fluid to look for cancer cells or other analytes that can include DNA, RNA, or other molecules released by tumor cells. Liquid biopsies mainly include circulating tumor DNA, circulating RNA, microRNA, proteins, circulating tumor cells, exosomes, and tumor-educated platelets. This review summarizes the progress and clinical application potential of liquid biopsy for early detection of lung cancer.

Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review

The development of a simple and fast cancer detection method is crucial since early diagnosis is a key factor in increasing survival rates for lung cancer patients. Among several diagnosis methods, the electrochemical sensor is the most promising one due to its outstanding performance, portability, real-time analysis, robustness, amenability, and cost-effectiveness. Conducting polymer (CP) composites have been frequently used to fabricate a robust sensor device, owing to their excellent physical and electrochemical properties as well as biocompatibility with nontoxic effects on the biological system. This review brings up a brief overview of the importance of electrochemical biosensors for the early detection of lung cancer, with a detailed discussion on the design and development of CP composite materials for biosensor applications. The review covers the electrochemical sensing of numerous lung cancer markers employing composite electrodes based on the conducting polyterthiophene, poly(3,4-ethylenedioxythiophene), polyaniline, polypyrrole, molecularly imprinted polymers, and others. In addition, a hybrid of the electrochemical biosensors and other techniques was highlighted. The outlook was also briefly discussed for the development of CP composite-based electrochemical biosensors for POC diagnostic devices.

Biomarkers of lung cancer for screening and in never-smokers-a narrative review

Background and Objective

Lung cancer is the leading cause of cancer-related mortality worldwide, partially attributed to late-stage diagnoses. In order to mitigate this, lung cancer screening (LCS) of high-risk patients is performed using low dose computed tomography (CT) scans, however this method is burdened by high false-positive rates and radiation exposure for patients. Further, screening programs focus on individuals with heavy smoking histories, and as such, never-smokers who may otherwise be at risk of lung cancer are often overlooked. To resolve these limitations, biomarkers have been posited as potential supplements or replacements to low-dose CT, and as such, a large body of research in this area has been produced. However, comparatively little information exists on their clinical efficacy and how this compares to current LCS strategies.

Methods

Here we conduct a search and narrative review of current literature surrounding biomarkers of lung cancer to supplement LCS, and biomarkers of lung cancer in never-smokers (LCINS).

Key Content and Findings

Many potential biomarkers of lung cancer have been identified with varying levels of sensitivity, specificity, clinical efficacy, and supporting evidence. Of the markers identified, multi-target panels of circulating microRNAs, lipids, and metabolites are likely the most clinically efficacious markers to aid current screening programs, as these provide the highest sensitivity and specificity for lung cancer detection. However, circulating lipid and metabolite levels are known to vary in numerous systemic pathologies, highlighting the need for further validation in large cohort randomised studies.

Conclusions

Lung cancer biomarkers is a fast-expanding area of research and numerous biomarkers with potential clinical applications have been identified. However, in all cases the level of evidence supporting clinical efficacy is not yet at a level at which it can be translated to clinical practice. The priority now should be to validate existing candidate markers in appropriate clinical contexts and work to integrating these into clinical practice.

The copious capabilities of non-coding RNAs in cancer regulation, diagnosis and treatment

Globally, cancer is one of the leading causes of mortality, accounting for 10 million deaths per year. Non-coding RNAs (ncRNAs) play integral and diverse roles in cancer, possessing the ability to both promote oncogenesis and impede tumor formation. This review discusses the various roles of microRNAs, transfer RNA-derived small RNAs, long non-coding RNAs and lncRNA-derived microproteins in cancer progression and prevention. We highlight the diagnostic and therapeutic potential of these ncRNAs, with a particular focus on detection in liquid biopsies and targeting of ncRNAs with small inhibitory molecules. Ultimately, the biological functions of cancer-associated ncRNAs, as well as the development of ncRNA-based technologies, are compelling areas for further research, holding the possibility of revolutionizing cancer treatment and diagnosis.

The Usefulness of the Ratio of Antigen-Autoantibody Immune Complexes to Their Free Antigens in the Diagnosis of Non-Small Cell Lung Cancer

Autoantibodies against specific lung cancer-associated antigens have been suggested for the performance of lung cancer diagnosis. This study aimed to evaluate the diagnostic performance of the antigen-autoantibody immune complex (AIC) against its free antigens for CYFRA21-1, ProGRP, neutrophil gelatinase-associated lipocalin (NGAL), and neuron-specific enolase (NSE) in non-small cell lung cancer (NSCLC). In total, 85 patients with NSCLC and 120 healthy controls (HCs) were examined using a 9-guanine DNA chip method. The ratios of AICs to their antigens and the combinations of ratios consisting of two to four markers were calculated. The levels of AICs for CYFRA21-1, ProGRP, NGAL, and NSE were higher than those for their free antigens in all participants. The levels of each free antigens distinguished patients with NSCLC from the HCs. The ratios of the AIC to its antigen and seven combinations of two to four ratios were significantly higher in patients with NSCLC than in the HCs. Excellent diagnostic performance was observed for all combination ratios (C4-1), with 85.9% sensitivity and 86.7% specificity at a 3.51 cut-off. Higher sensitivity was observed in the early stages (0-I) and adenocarcinoma than in stages II-IV and other pathological types. Combining all ratios of AICs and their antigens for all four markers was useful when diagnosing NSCLC.

Variability of serum CYFRA 21 - 1 and its susceptibility to clinical characteristics in individuals without cancer: a 4-year retrospective analysis

BACKGROUND

CYFRA 21 - 1 is a useful marker for diagnosing and monitoring lung cancer. However, its stability remains unclear. Moreover, while its applicability to screening is now being investigated, CYFRA 21 - 1 levels in individuals without cancer, who are targets for cancer screening, have not yet been the focus of research. Therefore, the present study investigated variability in and the factors increasing serum CYFRA 21 - 1 levels.

METHODS

This retrospective study recruited 951 individuals undergoing annual medical examinations for six years. We used data obtained in the first four years. Variability in serum CYFRA 21 - 1 levels over a period of four years were investigated. CYFRA 21 - 1 was categorized as normal (≤ 3.5 ng/ml) or elevated (> 3.5 ng/ml). The rate of an elevated level in one visit and the transition from an elevated to normal level between visits were visualized. A multiple logistic regression model was used to study the relationships between the frequency of elevated CYFRA 21 - 1 levels and clinical characteristics, such as age, sex, body mass index, weight changes, and the smoking status.

RESULTS

Approximately 5% of subjects had elevated CYFRA 21 - 1 levels once in five tests over four years, while 15% had elevated CYFRA 21 - 1 levels once or more. Among subjects with elevated CYFRA 21 - 1 levels in one blood test, between 63 and 72% had normal levels in the next test. The median CYFRA 21 - 1 level in subjects with elevations in one blood test significantly decreased in the next test at all four time points. The frequency of elevated CYFRA 21 - 1 levels was associated with an older age [odds ratio (OR) = 6.99, 95% confidence interval (CI) = 3.01-16.2], current heavy smoking (OR = 3.46, 95% CI = 1.52-7.9), and weight loss (OR = 1.86, 95% CI = 1.07-3.24).

CONCLUSIONS

Variability in and the factors increasing serum CYFRA 21 - 1 levels beyond the cut-off value need to be considered when interpretating CYFRA 21 - 1 test results. The future application of CYFRA 21 - 1 to lung cancer screening may require more than a single measurement.

Single-Droplet Microsensor for Ultra-Short Circulating EFGR Mutation Detection in Lung Cancer Based on Multiplex EFIRM Liquid Biopsy

Liquid biopsy is a rapidly emerging field that involves the minimal/non-invasive assessment of signature somatic mutations through the analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. Broadly speaking, the unmet need in liquid biopsy lung cancer detection is the lack of a multiplex platform that can detect a mutation panel of lung cancer genes using a minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here, we developed a non-PCR and non-NGS-based single-droplet-based multiplexing microsensor technology, "Electric-Field-Induced Released and Measurement (EFIRM) Liquid Biopsy" (m-eLB), for lung cancer-associated usctDNA. The m-eLB provides a multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode is coated with different probes for the ctDNA. This m-eLB prototype demonstrates accuracy for three tyrosine-kinase-inhibitor-related EGFR target sequences in synthetic nucleotides. The accuracy of the multiplexing assay has an area under the curve (AUC) of 0.98 for L858R, 0.94 for Ex19 deletion, and 0.93 for T790M. In combination, the 3 EGFR assay has an AUC of 0.97 for the multiplexing assay.

Analysis of Neuron-Specific enolase isozymes in human serum using immunoaffinity purification and liquid chromatography-tandem mass spectrometry quantification

Neuron-specific enolase (NSE) is a promising small-cell lung cancer (SCLC) biomarker composed of αγ and γγ isozyme dimers. As the conventional immunoassays are prone to interferences and cannot differentiate between the isozymes, we developed a multiplex immunoaffinity (IA) liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for the quantification of NSEα and NSEγ in human serum. A calibrator was prepared by performing cold denaturation of recombinantly expressed αα and γγ enolase dimers to induce a new dimer equilibrium that was determined to be approximately 1αγ:1γγ:1αα. Selective sample purification was achieved by performing IA extraction using an antibody specific towards NSEγ. The isolated αγ and γγ dimers were denatured and trypsin digested to allow quantification of the selected signature peptides and their corresponding isotopically labelled peptide internal standard. The obtained linear dynamic ranges were determined to be 1.5-56 ng/mL and 0.64-167 ng/mL for NSEα and NSEγ (R² = 0.88 and 0.97 respectively). Validation of the assay showed acceptable accuracy and precision for NSEα and NSEγ. The method was successfully applied to patient serum in which both isozymes were detected. Compared to the conventional immunoassay, substantially lower total NSE concentrations were measured in IA LC-MS/MS. With this multiplex IA LC-MS/MS assay, the clinical value of quantifying the individual isozymes can be explored. In addition, together with the calibrator described here, it may be applied to standardize NSE immunoassays across different platforms.

RGD-decorated PLGA nanoparticles improved effectiveness and safety of cisplatin for lung cancer therapy

Upon extensive pharmaceutical and biomedical research to treat lung cancer indicates that lung cancer remains one of the deadliest diseases and the leading cause of death in men and women worldwide. Lung cancer remains untreated and has a high mortality rate due to the limited potential for effective treatment with existing therapies. This highlights the urgent need to develop an effective, precise and sustainable solutions to treat lung cancer. In this study, we developed RGD receptor-targeted PLGA nanoparticles for the controlled and targeted co-delivery of cisplatin (CDDP) and upconversion nanoparticles (UCNP) in lung cancer therapy. Pluronic F127-RGD conjugate was synthesized by carbodiimide chemistry method and the conjugation was confirmed by FTIR and ¹HNMR spectroscopy techniques. PLGA nanoparticles were developed by the double emulsification method, then the surface of the prepared nanoparticles was decorated with Pluronic F127-RGD conjugate. The prepared formulations were characterized for their particle size, polydispersity index, zeta potential, surface morphology, drug encapsulation efficiency, and in vitro drug release and haemolysis studies. Pharmacokinetic studies and safety parameters in BAL fluid were assessed in rats. Histopathology of rat lung tissue was performed. The obtained results of particle sizes of the nanoparticle formulations were found 100-200 nm, indicating the homogeneity of dispersed colloidal nanoparticles formulations. Transmission Electron Microscopy (TEM) revealed the spherical shape of the prepared nanoparticles. The drug encapsulation efficiency of PLGA nanoparticles was found to range from 60% to 80% with different nanoparticles counterparts. RGD receptor-targeted PLGA nanoparticles showed controlled drug release for up to 72 h. Further, RGD receptor-targeted PLGA nanoparticles achieved higher cytotoxicity in compared to CFT, CFT, and Ciszest-50 (marketed CDDP injection). The pharmacokinetic study revealed that RGD receptor-targeted PLGA nanoparticles were 4.6-fold more effective than Ciszest-50. Furthermore, RGD receptor-targeted PLGA nanoparticles exhibited negligible damage to lung tissue, low systemic toxicity, and high biocompatible and safety in lung tissue. The results of RGD receptor-targeted PLGA nanoparticles indicated that it is a promising anticancer system that could further exploited as a potent therapeutic approach for lung cancer.

Liquid biopsy-based decision support algorithms for diagnosis and subtyping of lung cancer

OBJECTIVES

Pathologic subtyping of tissue biopsies is the gold standard for the diagnosis of lung cancer (LC), which could be complicated in cases of e.g. inconclusive tissue biopsies or unreachable tumors. The diagnosis of LC could be supported in a minimally invasive manner using protein tumor markers (TMs) and circulating tumor DNA (ctDNA) measured in liquid biopsies (LBx). This study evaluates the performance of LBx-based decision-support algorithms for the diagnosis of LC and subtyping into small- and non-small-cell lung cancer (SCLC and NSCLC) aiming to directly impact clinical practice.

MATERIALS AND METHODS

In this multicenter prospective study (NL9146), eight protein TMs (CA125, CA15.3, CEA, CYFRA 21-1, HE4, NSE, proGRP and SCCA) and ctDNA mutations in EGFR, KRAS and BRAF were analyzed in blood of 1096 patients suspected of LC. The performance of individual and combined TMs to identify LC, NSCLC or SCLC was established by evaluating logistic regression models at pre-specified positive predictive values (PPV) of ≥95% or ≥98%. The most informative protein TMs included in the multi-parametric models were selected by recursive feature elimination.

RESULTS

Single TMs could identify LC, NSCLC and SCLC patients with 46%, 25% and 40% sensitivity, respectively, at pre-specified PPVs. Multi-parametric models combining TMs and ctDNA significantly improved sensitivities to 65%, 67% and 50%, respectively.

CONCLUSION

In patients suspected of LC, the LBx-based decision-support algorithms allowed identification of about two-thirds of all LC and NSCLC patients and half of SCLC patients. These models therefore show clinical value and may support LC diagnostics, especially in patients for whom pathologic subtyping is impossible or incomplete.

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.

Characterizing microbiota and metabolomics analysis to identify candidate biomarkers in lung cancer

Background

Lung cancer is the leading malignant disease and cause of cancer-related death worldwide. Most patients with lung cancer had insignificant early symptoms so that most of them were diagnosed at an advanced stage. In addition to factors such as smoking, pollution, lung microbiome and its metabolites play vital roles in the development of lung cancer. However, the interaction between lung microbiota and carcinogenesis is lack of systematically characterized and controversial. Therefore, the purpose of this study was to excavate the features of the lung microbiota and metabolites in patients and verify potential biomarkers for lung cancer diagnosis.

Methods

Lung tissue flushing solutions and bronchoalveolar lavage fluid samples came from patients with lung cancer and non-lung cancer. The composition and variations of the microbiota and metabolites in samples were explored using muti-omics technologies including 16S rRNA amplicon sequencing, metagenomics and metabolomics.

Results

The metabolomics analysis indicated that 40 different metabolites, such as 9,10-DHOME, sphingosine, and cysteinyl-valine, were statistically significant between two groups (VIP > 1 and P < 0.05). These metabolites were significantly enriched into 11 signal pathways including sphingolipid, autophagy and apoptosis signaling pathway (P < 0.05). The analysis of lung microbiota showed that significant changes reflected the decrease of microbial diversity, changes of distribution of microbial taxa, and variability of the correlation networks of lung microbiota in lung cancer patients. In particular, we found that oral commensal microbiota and multiple probiotics might be connected with the occurrence and progression of lung cancer. Moreover, our study found 3 metabolites and 9 species with significantly differences, which might be regarded as the potential clinical diagnostic markers associated with lung cancer.

Conclusions

Lung microbiota and metabolites might play important roles in the pathogenesis of lung cancer, and the altered metabolites and microbiota might have the potential to be clinical diagnostic markers and therapeutic targets associated with lung cancer.

Preoperative blood markers for prediction of recurrence-free survival after surgical treatment of patients with stage III lung adenocarcinoma

The possibility of the preoperative level of 42 indicators characterizing the cellular composition and metabolism in blood of patients with stage III lung adenocarcinoma (AC) to predict their relapse-free survival was studied. Blood samples of 451 patients with newly diagnosed AK stage III after their surgical treatment (resection volume - R0) have been investigated. The duration of the relapse-free period (period of observation - 1 year), cellular composition of the blood, concentration of C-RP, albumin, Cyfra 21-1 antigens, SCC, TPA, chemokines CXCL5, CXCL8, pyruvate kinase TuM2 PK isoenzyme, HIF-1α and hyaluronic acid in blood serum so as the proportion of blood cells with CXCR1 and CXCR2, CD44V6 receptors in blood serum were measured. To determine the dependence of the duration of the relapse-free period after the treatment on the observation time, Kaplan-Meier graphs were built. The relationship between the determined parameters and survival was judged using single- and multi-factor Cox proportional hazard models. Comparison of groups with different risk of AK recurrence was performed using the Log Rank test and χ2. The assessment of the predictive information content of laboratory tests was carried out using ROC analysis. It was shown that the concentration of monocytes, eosinophilic leukocytes, the relative quantity of lymphocytes with CXCR1 receptor, the level of Cyfra 21-1 before surgical treatment were associated with the duration of the relapse-free period. A regression equation was compiled, which included the level of Cyfra 21-1, relative content of lymphocytes with CXCR1, and the eosinophilic leukocytes / monocytes ratio. Based on the threshold value Y=0,597, a Kaplan-Meier plot of patient survival was built and the results of it correspond to the TNM stratification. The prognostic sensitivity of the results of the equation - 85,7%, the specificity - 94,7%.

The Potential of MicroRNAs as Clinical Biomarkers to Aid Ovarian Cancer Diagnosis and Treatment

Ovarian cancer is a commonly diagnosed malignancy in women. When diagnosed at an early stage, survival outcomes are favourable for the vast majority, with up to 90% of ovarian cancer patients being free of disease at 5 years follow-up. Unfortunately, ovarian cancer is typically diagnosed at an advanced stage due to the majority of patients remaining asymptomatic until the cancer has metastasised, resulting in poor outcomes for the majority. While the molecular era has facilitated the subclassification of the disease into distinct clinical subtypes, ovarian cancer remains managed and treated as a single disease entity. MicroRNAs (miRNAs) are small (19-25 nucleotides), endogenous molecules which are integral to regulating gene expression. Aberrant miRNA expression profiles have been described in several cancers, and have been implicated to be useful biomarkers which may aid cancer diagnostics and treatment. Several preliminary studies have identified candidate tumour suppressor and oncogenic miRNAs which may be involved in the development and progression of ovarian cancer, highlighting their candidacy as oncological biomarkers; understanding the mechanisms by which these miRNAs regulate the key processes involved in oncogenesis can improve our overall understanding of cancer development and identify novel biomarkers and therapeutic targets. This review highlights the potential role of miRNAs which may be utilised to aid diagnosis, estimate prognosis and enhance therapeutic strategies in the management of primary ovarian cancer.

Plasma Proteomics Enable Differentiation of Lung Adenocarcinoma from Chronic Obstructive Pulmonary Disease (COPD)

Chronic obstructive pulmonary disease (COPD) is a major risk factor for the development of lung adenocarcinoma (AC). AC often develops on underlying COPD; thus, the differentiation of both entities by biomarker is challenging. Although survival of AC patients strongly depends on early diagnosis, a biomarker panel for AC detection and differentiation from COPD is still missing. Plasma samples from 176 patients with AC with or without underlying COPD, COPD patients, and hospital controls were analyzed using mass-spectrometry-based proteomics. We performed univariate statistics and additionally evaluated machine learning algorithms regarding the differentiation of AC vs. COPD and AC with COPD vs. COPD. Univariate statistics revealed significantly regulated proteins that were significantly regulated between the patient groups. Furthermore, random forest classification yielded the best performance for differentiation of AC vs. COPD (area under the curve (AUC) 0.935) and AC with COPD vs. COPD (AUC 0.916). The most influential proteins were identified by permutation feature importance and compared to those identified by univariate testing. We demonstrate the great potential of machine learning for differentiation of highly similar disease entities and present a panel of biomarker candidates that should be considered for the development of a future biomarker panel.

Simple diagnosis of cancer by detecting CEA and CYFRA 21-1 in saliva using electronic sensors

One way of early diagnosis of cancer is by detecting the biomarkers that get introduced into easily accessible body fluids. We report the development of portable and rapid electronic biosensors for quantitative detection of two secretive cancer biomarkers-Carcinoembryonic antigen (CEA) and Cytokeratin fragment 19 (CYFRA 21-1). The reduced graphene oxide (rGO)/ melamine (MEL)/antibodies/ bovine serum albumin (BSA) based devices were tested for 1 pg/mL to 800 ng/mL of CEA and CYFRA 21-1. The responses of the sensors ranged from 7.14 to 59.1% and from 6.18 to 64% for 1 pg/mL to 800 ng/mL CEA and CYFRA 21-1 respectively. A read-out circuit was assembled to develop a portable prototype which was used to assess the concentrations of the two antigens present in saliva samples of 14 subjects. The prototype could accurately discriminate between 9 oral squamous cell carcinoma patients and 5 healthy controls.

Assessment of a Large-Scale Unbiased Malignant Pleural Effusion Proteomics Study of a Real-Life Cohort

Simple Summary

Pleural effusion (PE) occurs as a consequence of various pathologies. Malignant effusion due to lung cancer is one of the most frequent causes. A method for accurate differentiation of malignant from benign PE is an unmet clinical need. Proteomics profiling of PE has shown promising results. However, mass spectrometry (MS) analysis typically involves the tedious elimination of abundant proteins before analysis, and clinical annotation of proteomics profiled cohorts is limited. This study compares the proteomes of malignant PE and nonmalignant PE, identifies lung cancer malignant markers in agreement with other studies, and identifies markers strongly associated with patient survival.

Abstract

Background: Pleural effusion (PE) is common in advanced-stage lung cancer patients and is related to poor prognosis. Identification of cancer cells is the standard method for the diagnosis of a malignant PE (MPE). However, it only has moderate sensitivity. Thus, more sensitive diagnostic tools are urgently needed. Methods: The present study aimed to discover potential protein targets to distinguish malignant pleural effusion (MPE) from other non-malignant pathologies. We have collected PE from 97 patients to explore PE proteomes by applying state-of-the-art liquid chromatography-mass spectrometry (LC-MS) to identify potential biomarkers that correlate with immunohistochemistry assessment of tumor biopsy or with survival data. Functional analyses were performed to elucidate functional differences in PE proteins in malignant and benign samples. Results were integrated into a clinical risk prediction model to identify likely malignant cases. Sensitivity, specificity, and negative predictive value were calculated. Results: In total, 1689 individual proteins were identified by MS-based proteomics analysis of the 97 PE samples, of which 35 were diagnosed as malignant. A comparison between MPE and benign PE (BPE) identified 58 differential regulated proteins after correction of the p-values for multiple testing. Furthermore, functional analysis revealed an up-regulation of matrix intermediate filaments and cellular movement-related proteins. Additionally, gene ontology analysis identified the involvement of metabolic pathways such as glycolysis/gluconeogenesis, pyruvate metabolism and cysteine and methionine metabolism. Conclusion: This study demonstrated a partial least squares regression model with an area under the curve of 98 and an accuracy of 0.92 when evaluated on the holdout test data set. Furthermore, highly significant survival markers were identified (e.g., PSME1 with a log-rank of 1.68 × 10⁻⁶).

Chemical composition, in vitro and in silico evaluation of essential oil from Eucalyptus tereticornis leaves for lung cancer

Chemical composition of the essential oil (EO) of Eucalyptus tereticornis leaves was studied by gas chromatography-mass spectrometry. Forty-five constituents were identified in the oil hydrodistilled from the sample collected from Ghudda Village, Bathinda (Pb), India of which eucalyptol (34.39%) and ledol (9.92%) were the major constituents. In vitro antioxidant and anticancer potential of EO was analysed by DPPH 2,2-diphenylpicrylhydrazyl (DPPH) and MTT assay. The percentage free radical scavenging activity was found to be 63.77%. The antiproliferative activity was analysed using MTT assay in adenocarcinomic human alveolar basal epithelial A549 cancer cell line and showed IC₅₀ value of 47.14 µg/ml. In silico study of EO, constituents were performed using Maestro 12.9 against EGFR (PDB ID-2RGP). Five constituents from EO showed high dockscore as compared to standard Mobicertinib which indicated the effectiveness of oil constituents against lung cancer.

Toxicologic Concerns with Current Medical Nanoparticles

Nanotechnology is one of the scientific advances in technology. Nanoparticles (NPs) are small materials ranging from 1 to 100 nm. When the shape of the supplied nanoparticles changes, the physiological response of the cells can be very different. Several characteristics of NPs such as the composition, surface chemistry, surface charge, and shape are also important parameters affecting the toxicity of nanomaterials. This review covered specific topics that address the effects of NPs on nanomedicine. Furthermore, mechanisms of different types of nanomaterial-induced cytotoxicities were described. The distributions of different NPs in organs and their adverse effects were also emphasized. This review provides insight into the scientific community interested in nano(bio)technology, nanomedicine, and nanotoxicology. The content may also be of interest to a broad range of scientists.

Diagnostic value of abnormal chromosome 3p genes in small‑cell lung cancer

The diagnosis of small cell lung carcinoma (SCLC) remains a great challenge. Changes in chromosome 3p (chr3) genes are usually observed in the pathogenesis of lung cancer, which suggests that these chr3 genes may be a diagnostic marker in the early stage of SCLC. The present study explored the diagnostic value of the chr3 gene in SCLC using Bioinformatics. Furthermore, reverse transcription-quantitative PCR (RT-qPCR) was used to reveal the expression patterns of diagnostic biomarkers in human pulmonary alveolar epithelial cells and in the SCLC cell line NCI-H146. A total of 33 differentially expressed (DE) chr3 genes and 1,156 module genes associated with clinical features of patients with SCLC were identified and functional enrichment analysis indicated that all these genes were significantly enriched in cell cycle terms. The area under the receiver operating characteristic curve demonstrated that the overlapping genes of the DE-chr3 and module genes, namely cell division cycle 25 A (CDC25A), FYVE and coiled-coil domain autophagy adaptor 1 (FYCO1) and lipid raft linker 1 (RFTN1), were relatively accurate in distinguishing normal from SCLC samples, and may thus be considered diagnostic biomarkers. CDC25A was overexpressed in SCLC samples, while FYCO1 and RFTN1 were highly expressed in normal samples, as evidenced by the RT-qPCR results. Single-gene gene set enrichment analysis suggested that the diagnostic biomarkers were significantly associated with cell cycle, ATP-binding cassette transporter, immune cell differentiation, immune response and multiple respiratory disease pathways. Furthermore, a total of 141 drugs were predicted by The Comparative Toxicogenomics Database to be able to modulate the expression of the diagnostic biomarkers, of which 8 drugs were shared among the three aforementioned diagnostic biomarkers. The present study identified three novel and powerful diagnostic biomarkers for SCLC based on chr3 genes. Suggestions for the development and selection of drugs for clinical treatment based on diagnostic biomarkers were also provided.

Nanomaterial-assisted microfluidics for multiplex assays

Simultaneous detection of different biomarkers from a single specimen in a single test, allowing more rapid, efficient, and low-cost analysis, is of great significance for accurate diagnosis of disease and efficient monitoring of therapy. Recently, developments in microfabrication and nanotechnology have advanced the integration of nanomaterials in microfluidic devices toward multiplex assays of biomarkers, combining both the advantages of microfluidics and the unique properties of nanomaterials. In this review, we focus on the state of the art in multiplexed detection of biomarkers based on nanomaterial-assisted microfluidics. Following an overview of the typical microfluidic analytical techniques and the most commonly used nanomaterials for biochemistry analysis, we highlight in detail the nanomaterial-assisted microfluidic strategies for different biomarkers. These highly integrated platforms with minimum sample consumption, high sensitivity and specificity, low detection limit, enhanced signals, and reduced detection time have been extensively applied in various domains and show great potential in future point-of-care testing and clinical diagnostics.

Insights into the Unique Lung Microbiota Profile of Pulmonary Tuberculosis Patients Using Metagenomic Next-Generation Sequencing

The microbiota plays an important role in human health and disease development. The lung microbiota profile in pulmonary tuberculosis (TB) patients and the effects of anti-TB treatment on the profile need to be determined thoroughly and comprehensively. This study primarily aimed to determine the lung microbiota profile associated with pulmonary TB and characterize the longitudinal changes during anti-TB treatment. A total of 53 participants, comprising 8 healthy individuals, 12 untreated pulmonary TB patients, 15 treated pulmonary TB patients, 11 cured pulmonary TB patients, and 7 lung cancer patients, were recruited in the present study. Bronchioalveolar lavage fluid (BALF) samples were collected from the above participants, and throat swabs were taken from healthy individuals. Microbiomes in the samples were examined using metagenomic next-generation sequencing (mNGS). Differences in microbiota profiles were determined through a comparison of the indicated groups. Our findings indicated that the BALF samples displayed decreased richness and diversity of the microbiota compared to those of the throat swab samples, and these two kinds of samples exhibited obvious separation on principal-coordinate analysis (PCoA) plots. Untreated pulmonary TB patients displayed a unique lung microbiota signature distinct from that of healthy individuals and lung cancer patients. Our data first demonstrated that anti-TB treatment with first-line drugs increases alpha diversity and significantly affects the beta diversity of the lung microbiota, while it also induces antibiotic resistance genes (ARGs). IMPORTANCE Characterization of the lung microbiota could lead to a better understanding of the pathogenesis of pulmonary TB. Here, we applied the metagenomic shotgun sequencing instead of 16S rRNA sequencing method to characterize the lung microbiota using the BALF samples instead of sputum. We found that alterations in the lung microbiota are associated with TB infection and that anti-TB treatment significantly affects the alpha and beta diversity of the lung microbiota in pulmonary TB patients. These findings could help us better understand TB pathogenesis.

PKP1 and MYC create a feedforward loop linking transcription and translation in squamous cell lung cancer

PURPOSE

Plakophilin 1 (PKP1) is well-known as an important component of the desmosome, a cell structure specialized in spot-like cell-to-cell adhesion. Although desmosomes have generally been associated with tumor suppressor functions, we recently found that PKP1 is recurrently overexpressed in squamous cell lung cancer (SqCLC) to exert an oncogenic role by enhancing the translation of MYC (c-Myc), a major oncogene. In this study, we aim to further characterize the functional relationship between PKP1 and MYC.

METHODS

To determine the functional relationship between PKP1 and MYC, we performed correlation analyses between PKP1 and MYC mRNA expression levels, gain/loss of function models, chromatin immunoprecipitation (ChIP) and promoter mutagenesis followed by luciferase assays.

RESULTS

We found a significant correlation between the mRNA levels of MYC and PKP1 in SqCLC primary tumor samples. In addition, we found that MYC is a direct transcription factor of PKP1 and binds to specific sequences within its promoter. In agreement with this, we found that MYC knockdown reduced PKP1 protein expression in different SqCLC models, which may explain the PKP1-MYC correlation that we found. Conversely, we found that PKP1 knockdown reduced MYC protein expression, while PKP1 overexpression enhanced MYC expression in these models.

CONCLUSIONS

Based on these results, we propose a feedforward functional relationship in which PKP1 enhances MYC translation in conjunction with the translation initiation complex by binding to the 5'-UTR of MYC mRNA, whereas MYC promotes PKP1 transcription by binding to its promoter. These results suggest that PKP1 may serve as a therapeutic target for SqCLC.

Metabolomic Fingerprinting for the Detection of Early-Stage Lung Cancer: From the Genome to the Metabolome

The five-year survival rate of lung cancer patients is very low, mainly because most newly diagnosed patients present with locally advanced or metastatic disease. Therefore, early diagnosis is key to the successful treatment and management of lung cancer. Unfortunately, early detection methods of lung cancer are not ideal. In this brief review, we described early detection methods such as chest X-rays followed by bronchoscopy, sputum analysis followed by cytological analysis, and low-dose computed tomography (LDCT). In addition, we discussed the potential of metabolomic fingerprinting, compared to that of other biomarkers, including molecular targets, as a low-cost, high-throughput blood-based test that is both feasible and affordable for early-stage lung cancer screening of at-risk populations. Accordingly, we proposed a paradigm shift to metabolomics as an alternative to molecular and proteomic-based markers in lung cancer screening, which will enable blood-based routine testing and be accessible to those patients at the highest risk for lung cancer.

Improving the diagnostic efficacy of squamous cell carcinoma antigen for oral squamous cell carcinoma via saponin disruption of serum extracellular vesicles

BACKGROUND

The diagnostic value of squamous cell carcinoma antigen (SCCA) for oral squamous cell carcinoma (OSCC) is insufficient. Recently, extracellular vesicles (EVs) have displayed great potential for improving diagnostic efficacy. However, one of the main challenges that restricts the application of EVs is the lack of a clinically suitable separation method for the intra-vesicular protein detection.

METHODS

Saponin was used to destroy serum EVs membranes for releasing the intra-vesicular SCCA into the serum, circumventing the purification process of EVs. The concentrations of SCCA were measured and compared in 113 healthy people and 73 OSCC patients pre- and post-saponin treatment.

RESULTS

The concentration of serum SCCA significantly increased after saponin destroyed the membrane of EVs. The area under the curve (AUC) of serum SCCA for OSCC diagnosis was 0.6444 (95% CI, 0.5595 to 0.7293). The diagnostic AUC of serum EVs-derived SCCA reached 0.7969 (95% CI, 0.735 to 0.8588).

CONCLUSIONS

The results suggested that serum EVs disrupted by saponin could improve the diagnostic efficacy of SCCA for OSCC, which provides a simple, rapid, and high-throughput method to detect the intra-vesicular proteins of EVs and holds great potential for clinical application.

Dual-template rectangular nanotube molecularly imprinted polypyrrole for label-free impedimetric sensing of AFP and CEA as lung cancer biomarkers

A high-performance sensing layer based on dual-template molecularly imprinted polymer (DMIP) was fabricated and successfully applied for one-by-one detection of carcinoembryonic antigen (CEA) and alpha-fetoprotein (AFP) as lung cancer biomarkers. The plastic antibodies of AFP and CEA were created into the electropolymerized polypyrrole (PPy) on a fluorine-doped tin oxide (FTO) electrode. Raman spectroscopy, field emission scanning electron microscopy (FE-SEM), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) tests were performed to pursue the formation and characterization of the sensing layer. Methyl orange (MO) increased the conductivity of PPy and induced the formation of MO doped PPy (PPy-MO) rectangular-shaped nanotubes. Using impedimetric detection, the rebinding of the template antigens was evaluated, the charge transfer resistance increased as the concentration of AFP and CEA increased. The linear dynamic ranges of 5-10⁴ and 10-10⁴ pg mL^-1 and detection limits of 1.6 and 3.3 pg mL^-1 were obtained for CEA and AFP, respectively. Given satisfactory results in the determination of AFP and CEA in the human serum samples, high sensitivity, and good stability of DMIP sensor made it a promising method for sensing of AFP and CEA in serum samples.

Potential of Stem Cells and CART as a Potential Polytherapy for Small Cell Lung Cancer

Despite the increasing urgency of the problem of treating small cell lung cancer (SCLC), information on the causes of its development is fragmentary. There is no complete understanding of the features of antitumor immunity and the role of the microenvironment in the development of SCLC resistance. This impedes the development of new methods for the diagnosis and treatment of SCLC. Lung cancer and chronic obstructive pulmonary disease (COPD) have common pathogenetic factors. COPD is a risk factor for lung cancer including SCLC. Therefore, the search for effective approaches to prevention, diagnosis, and treatment of SCLC in patients with COPD is an urgent task. This review provides information on the etiology and pathogenesis of SCLC, analyses the effectiveness of current treatment options, and critically evaluates the potential of chimeric antigen receptor T cells therapy (CART therapy) in SCLC. Moreover, we discuss potential links between lung cancer and COPD and the role of endothelium in the development of COPD. Finally, we propose a new approach for increasing the efficacy of CART therapy in SCLC.

Identification and Affinity Determination of Protein-Antibody and Protein-Aptamer Epitopes by Biosensor-Mass Spectrometry Combination

Analytical methods for molecular characterization of diagnostic or therapeutic targets have recently gained high interest. This review summarizes the combination of mass spectrometry and surface plasmon resonance (SPR) biosensor analysis for identification and affinity determination of protein interactions with antibodies and DNA-aptamers. The binding constant (KD) of a protein-antibody complex is first determined by immobilizing an antibody or DNA-aptamer on an SPR chip. A proteolytic peptide mixture is then applied to the chip, and following removal of unbound material by washing, the epitope(s) peptide(s) are eluted and identified by MALDI-MS. The SPR-MS combination was applied to a wide range of affinity pairs. Distinct epitope peptides were identified for the cardiac biomarker myoglobin (MG) both from monoclonal and polyclonal antibodies, and binding constants determined for equine and human MG provided molecular assessment of cross immunoreactivities. Mass spectrometric epitope identifications were obtained for linear, as well as for assembled ("conformational") antibody epitopes, e.g., for the polypeptide chemokine Interleukin-8. Immobilization using protein G substantially improved surface fixation and antibody stabilities for epitope identification and affinity determination. Moreover, epitopes were successfully determined for polyclonal antibodies from biological material, such as from patient antisera upon enzyme replacement therapy of lysosomal diseases. The SPR-MS combination was also successfully applied to identify linear and assembled epitopes for DNA-aptamer interaction complexes of the tumor diagnostic protein C-Met. In summary, the SPR-MS combination has been established as a powerful molecular tool for identification of protein interaction epitopes.

[Predicting the risk of tumor progression in patients with early stages of adenocarcinoma and squamous cell lung carcinoma based on laboratory parameters]

Non-small cell carcinoma (NSCLC) prevails in the structure of the incidence of lung cancer. In patients with I stage NSCLC, only 60-70% overcome the 5-year survival barrier, and at II stage it decreases to 35-40%. The reason for such a high mortality rate is almost always a relapse of the disease. The main histological forms of NSCLC - adenocarcinoma (AC) and squamous cell carcinoma (SCLC) - differ in the course, protocols and effectiveness of the treatment. Comparative survival data for AK and PCLC are controversial, and reliable biomarkers for determining the risk of tumor progression are lacking. In thus study we have investigated the possibility of using laboratory parameters characterizing the level of some blood proteins involved in carcinogenesis in patients with early stages of AC and SCLC to determine the risk of disease progression. We retrospectively analyzed the duration of the relapse-free period after surgical treatment for one year in 1250 patients (816 with stages I and II of adenocarcinoma, G1-3 and 434 with early stages of SCLC, G1-3). In 81 patients with AC and 36 - with SCLC (stages I-II, G1-3) the level of CYFRA 21-1 and SCC by electrochemiluminescent method, chemokines CXCL5, CXCL8, TPA, pyruvate kinase M2, HIF-1α and hyaluronic acid by enzyme immunoassay, receptors CXCR1, CXCR2, CD44v6 by flow cytometry were determined. Using the Kaplan-Meier graphical analysis, groups of low (stage I G1-2 + stage II G1) and high (stage I G3 + stage II G2-3) risk of tumor progression were identified. In the case of the one-year survival rate of patients with AC was higher than with SCLC. In patients with AC and a high risk of tumor recurrence, compared with a low one, the level of CYFRA 21-1, the mean intensity of fluorescence (MFI) of the CXCR1 receptor in granulocytes, and the relative content of the CXCR2 receptor in lymphocytes were higher. In the case of rapid progression of SCLC in patients, the relative content of the CXCR2 receptor in lymphocytes, the proportion of monocytes equipped with the CD44v6 receptor, and the SCC level were higher than with slow progression. Regression equations, including combinations of the above parameters (threshold value for AC - 0,512, for SCLC - 0,409, sensitivity - 91,9% and 90,0%, specificity - 90,0% and 87,5%, respectively), allow to predict the probability of tumor recurrence.

The role of SAXS and molecular simulations in 3D structure elucidation of a DNA aptamer against lung cancer

Aptamers are short, single-stranded DNA or RNA oligonucleotide molecules that function as synthetic analogs of antibodies and bind to a target molecule with high specificity. Aptamer affinity entirely depends on its tertiary structure and charge distribution. Therefore, length and structure optimization are essential for increasing aptamer specificity and affinity. Here, we present a general optimization procedure for finding the most populated atomistic structures of DNA aptamers. Based on the existed aptamer LC-18 for lung adenocarcinoma, a new truncated LC-18 (LC-18t) aptamer LC-18t was developed. A three-dimensional (3D) shape of LC-18t was reported based on small-angle X-ray scattering (SAXS) experiments and molecular modeling by fragment molecular orbital or molecular dynamic methods. Molecular simulations revealed an ensemble of possible aptamer conformations in solution that were in close agreement with measured SAXS data. The aptamer LC-18t had stronger binding to cancerous cells in lung tumor tissues and shared the binding site with the original larger aptamer. The suggested approach reveals 3D shapes of aptamers and helps in designing better affinity probes.

Molecular Origin of Blood-Based Infrared Spectroscopic Fingerprints*

Infrared spectroscopy of liquid biopsies is a time- and cost-effective approach that may advance biomedical diagnostics. However, the molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the method's applicability. Here we probe 148 human blood sera and reveal the origin of the variations in their IMFs. To that end, we supplemented infrared spectroscopy with biochemical fractionation and proteomic profiling, providing molecular information about serum composition. Using lung cancer as an example of a medical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as a pattern, may be instrumental for detecting malignancy. Tying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, a framework that could be applied to probing of any disease.

Application across species of a one health approach to liquid sample handling for respiratory based -omics analysis

Airway inflammation is highly prevalent in horses, with the majority of non-infectious cases being defined as equine asthma. Currently, cytological analysis of airway derived samples is the principal method of assessing lower airway inflammation. Samples can be obtained by tracheal wash (TW) or by lavage of the lower respiratory tract (bronchoalveolar lavage (BAL) fluid; BALF). Although BALF cytology carries significant diagnostic advantages over TW cytology for the diagnosis of equine asthma, sample acquisition is invasive, making it prohibitive for routine and sequential screening of airway health. However, recent technological advances in sample collection and processing have made it possible to determine whether a wider range of analyses might be applied to TW samples. Considering that TW samples are relatively simple to collect, minimally invasive and readily available in the horse, it was considered appropriate to investigate whether, equine tracheal secretions represent a rich source of cells and both transcriptomic and proteomic data. Similar approaches have already been applied to a comparable sample set in humans; namely, induced sputum. Sputum represents a readily available source of airway biofluids enriched in proteins, changes in the expression of which may reveal novel mechanisms in the pathogenesis of respiratory diseases, such as asthma and chronic obstructive pulmonary disease. The aim of this study was to establish a robust protocol to isolate macrophages, protein and RNA for molecular characterization of TW samples and demonstrate the applicability of sample handling to rodent and human pediatric bronchoalveolar lavage fluid isolates. TW samples provided a good quality and yield of both RNA and protein for downstream transcriptomic/proteomic analyses. The sample handling methodologies were successfully applicable to BALF for rodent and human research. TW samples represent a rich source of airway cells, and molecular analysis to facilitate and study airway inflammation, based on both transcriptomic and proteomic analysis. This study provides a necessary methodological platform for future transcriptomic and/or proteomic studies on equine lower respiratory tract secretions and BALF samples from humans and mice.

Serum HSP90-Alpha and Oral Squamous Cell Carcinoma : A Prospective Biomarker

AIM

Current study aims to perform differential protein expression analysis of serum samples from Oral squamous cell carcinoma (OSCC) patients and healthy controls in search of potential diagnostic and/or prognostic biomarker(s).

OBJECTIVE

OSCC is diagnosed late, resulting in poor survival and high mortality. Identification of non-invasive prognostic biomarker is of utmost importance for early diagnosis and proper management of the disease; hence we used proteomic approach to identify potential biomarkers from serum.

METHODS

Serum samples (OSCC n=45 and control n=30) were depleted and proteins were separated using 2-D gel electrophoresis followed by identification by mass spectrometric analysis. Gene expression analysis of identified proteins in malignant and normal tissue was also performed to complement proteomics studies.

RESULTS

Among differentially expressed proteins, a noteworthy observation was up regulation of Heat shock protein alpha (HSP90α) from serum of oral cancer patients. We also observed elevated levels of Haptoglobin (HP) along with down regulation of Type II keratin cytoskeletal 1(KRT1) and serum Albumin (ALB) in oral cancer patients. Gene expression studies of identified proteins in malignant and normal tissue revealed a similar pattern with the exception of KRT1. We believe that elevated levels of serum HSP90 alpha might be used as a potential biomarker.

CONCLUSION

Our findings suggest the contribution of HSP90 alpha and other identified proteins in oral pathology as pro/anti apoptotic modulators, thus they are being considered as predictive biomarkers.

Bio-Nanocarriers for Lung Cancer Management: Befriending the Barriers

Lung cancer is a complex thoracic malignancy developing consequential to aberrations in a myriad of molecular and biomolecular signaling pathways. It is one of the most lethal forms of cancers accounting to almost 1.8 million new annual incidences, bearing overall mortality to incidence ratio of 0.87. The dismal prognostic scenario at advanced stages of the disease and metastatic/resistant tumor cell populations stresses the requisite of advanced translational interdisciplinary interventions such as bionanotechnology. This review article deliberates insights and apprehensions on the recent prologue of nanobioengineering and bionanotechnology as an approach for the clinical management of lung cancer. The role of nanobioengineered (bio-nano) tools like bio-nanocarriers and nanobiodevices in secondary prophylaxis, diagnosis, therapeutics, and theranostics for lung cancer management has been discussed. Bioengineered, bioinspired, and biomimetic bio-nanotools of considerate translational value have been reviewed. Perspectives on existent oncostrategies, their critical comparison with bio-nanocarriers, and issues hampering their clinical bench side to bed transformation have also been summarized.

Needle Trap Device-GC-MS for Characterization of Lung Diseases Based on Breath VOC Profiles

Volatile organic compounds (VOCs) have been assessed in breath samples as possible indicators of diseases. The present study aimed to quantify 29 VOCs (previously reported as potential biomarkers of lung diseases) in breath samples collected from controls and individuals with lung cancer, chronic obstructive pulmonary disease and asthma. Besides that, global VOC profiles were investigated. A needle trap device (NTD) was used as pre-concentration technique, associated to gas chromatography-mass spectrometry (GC-MS) analysis. Univariate and multivariate approaches were applied to assess VOC distributions according to the studied diseases. Limits of quantitation ranged from 0.003 to 6.21 ppbv and calculated relative standard deviations did not exceed 10%. At least 15 of the quantified targets presented themselves as discriminating features. A random forest (RF) method was performed in order to classify enrolled conditions according to VOCs' latent patterns, considering VOCs responses in global profiles. The developed model was based on 12 discriminating features and provided overall balanced accuracy of 85.7%. Ultimately, multinomial logistic regression (MLR) analysis was conducted using the concentration of the nine most discriminative targets (2-propanol, 3-methylpentane, (E)-ocimene, limonene, m-cymene, benzonitrile, undecane, terpineol, phenol) as input and provided an average overall accuracy of 95.5% for multiclass prediction.

Serum Exosomes and Their miRNA Load-A Potential Biomarker of Lung Cancer

Early detection of lung cancer in screening programs is a rational way to reduce mortality associated with this malignancy. Low-dose computed tomography, a diagnostic tool used in lung cancer screening, generates a relatively large number of false-positive results, and its complementation with molecular biomarkers would greatly improve the effectiveness of such programs. Several biomarkers of lung cancer based on different components of blood, including miRNA signatures, were proposed. However, only a few of them have been positively validated in the context of early cancer detection yet, which imposes a constant need for new biomarker candidates. An emerging source of cancer biomarkers are exosomes and other types of extracellular vesicles circulating in body fluids. Hence, different molecular components of serum/plasma-derived exosomes were tested and showed different levels in lung cancer patients and healthy individuals. Several studies focused on the miRNA component of these vesicles. Proposed signatures of exosome miRNA had promising diagnostic value, though none of them have yet been clinically validated. These signatures involved a few dozen miRNA species overall, including a few species that recurred in different signatures. It is worth noting that all these miRNA species have cancer-related functions and have been associated with lung cancer progression. Moreover, a few of them, including known oncomirs miR-17, miR-19, miR-21, and miR-221, appeared in multiple miRNA signatures of lung cancer based on both the whole serum/plasma and serum/plasma-derived exosomes.

A label-free immunosensor for the detection of a new lung cancer biomarker, GM2 activator protein, using a phosphomolybdic acid/polyethyleneimine coated gold nanoparticle composite

A novel electrochemical immunosensor for the detection of a new lung cancer biomarker based on a polyoxometalate-adsorbed poly(ethylenimine)-coated gold nanoparticle modified electrode.

MUC Glycoproteins: Potential Biomarkers and Molecular Targets for Cancer Therapy

MUC proteins have great significance as prognostic and diagnostic markers as well as a potential target for therapeutic interventions in most cancers of glandular epithelial origin. These are high molecular weight glycosylated proteins located in the epithelial lining of several tissues and ducts. Mucins belong to a heterogeneous group of large O-glycoproteins that can be either secreted or membrane-bound. Glycosylation, a post-translational modification affects the biophysical, functional and biochemical properties and provides structural complexity for these proteins. Aberrant expression and glycosylation of mucins contribute to tumour survival and proliferation in many cancers, which in turn activates numerous signalling pathways such as NF-kB, ERα, HIF, MAPK, p53, c-Src, Wnt and JAK-STAT, etc. This subsequently induces cancer cell growth, proliferation and metastasis. The present review mainly demonstrates the functional aspects of MUC glycoproteins along with its unique signalling mechanism and role of aberrant glycosylation in cancer progression and therapeutics. The importance of MUC proteins and its subtypes in a wide spectrum of cancers including but not limited to breast cancer, colorectal cancer, endometrial and cervical cancer, lung cancer, primary liver cancer, pancreatic cancer, prostate cancer and ovarian cancer has been exemplified with significance in targeting the same. Several patents associated with the MUC proteins in the field of cancer therapy are also emphasized in the current review.

9G TestTM Cancer/Lung: A Desirable Companion to LDCT for Lung Cancer Screening

Simple Summary

Lung cancer is the most common cause of cancer-related deaths globally. Patients diagnosed at early-stage (0–I) have a higher survival rate than the metastasized stages (III–IV). Thus, there is great potential to reduce mortality by diagnosing lung cancer at stage 0~I through community screening. LDCT is a promising method, but it has a high false-positive rate. Therefore, a biomarker test that can be used in combination with LDCT for lung cancer screening to reduce false-positive rates is highly awaited. The present study evaluated the applicability of 9G test^TM Cancer/Lung test to detect stage 0~IV lung cancer. 9G test^TM Cancer/Lung test detects stage I, stage II, stage III, and stage IV cancers with the sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3%. These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer.

Abstract

A complimentary biomarker test that can be used in combination with LDCT for lung cancer screening is highly desirable to improve the diagnostic capacity of LDCT and reduce the false-positive rates. Most importantly, the stage I lung cancer detection rate can be dramatically increased by the simultaneous use of a biomarker test with LDCT. The present study was conducted to evaluate 9G test^TM Cancer/Lung’s sensitivity and specificity in detecting Stage 0~IV lung cancer. The obtained results indicate that the 9G test^TM Cancer/Lung can detect lung cancer with overall sensitivity and specificity of 75.0% (69.1~80.3) and 97.3% (95.0~98.8), respectively. The detection of stage I, stage II, stage III, and stage IV cancers with sensitivities of 77.5%, 78.1%, 67.4%, and 33.3%, respectively, at the specificity of 97.3% have never been reported before. The receiver operating characteristic curve analysis allowed us to determine the population-weighted AUC of 0.93 (95% CI, 0.91–0.95). These results indicate that the 9G test^TM Cancer/Lung can be used in conjunction with LDCT to screen lung cancer. Furthermore, obtained results indicate that the use of 9G test^TM Cancer/Lung with LDCT for lung cancer screening can increase stage I cancer detection, which is crucial to improve the currently low 5-year survival rates.