Plasma osteopontin velocity differentiates lung cancers from controls in a CT screening population

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

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

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

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.

Diagnostic Value of the Survivin Autoantibody in Four Types of Malignancies

BACKGROUND

Tumor-associated antigen overexpression, which has been reported in many types of cancers, may trigger autoantibody secretion. The present study was designed to test whether levels of circulating autoantibodies to survivin protein-derived antigens is altered in liver, esophageal, breast, and lung cancers.

METHODS

Patients with liver (144), esophageal (159), breast (124), and lung cancers (267), and healthy volunteers (362) were recruited for the study, and serum samples were collected for ELISA autoantibody analysis.

RESULTS

Compared with the control group, survivin autoantibody levels were significantly higher in serum from patients with breast cancer and lung cancer, but were significantly lower in serum from patients with liver cancer (p < 0.05). In stage I and II lung cancer, the best-fit areas under the receiver operating characteristic curve was 0.731 (standard error [SE] = 0.023; 95% confidence interval [CI] 0.687-0.776) and the sensitivity, with 90% specificity, was 23.7%.

CONCLUSION

Analysis across four types of malignancies revealed that the survivin autoantibody had good specificity and sensitivity in lung cancer. Circulating autoantibodies to survivin could be a potential biomarker for the early lung cancer diagnosis.

Metabolome-based biomarkers: their potential role in the early detection of lung cancer

Lung cancer is the leading cause of cancer-related death worldwide, and a major problem affecting its mortality is the late diagnosis of the majority of cases, where treatment options are limited and overall prognosis is very bad. Currently, a low-dose computed tomography (LD-CT) screening in the high-risk group is the only available diagnostic strategy that could reduce mortality due to this malignancy. However, the LD-CT screening test suffers from a high false positive rate. Hence, complementation of LD-CT examination with blood-based biomarkers is a rational approach to increase efficacy and reduce the cost of early lung cancer screening programs. Several molecular signatures that discriminate between patients with early lung cancer and healthy individuals have been proposed in recent years, which are based on components of serum/plasma metabolome. However, none of these signatures has been validated by independent studies based on material collected during real lung cancer screening. Therefore, the validation of the real diagnostic value of these otherwise promising candidates remains a critical step in this challenging field of cancer diagnostics.

The relationship between tumor volume changes and serial plasma osteopontin detection during radical radiotherapy of non-small-cell lung cancer

The prognostic quality of increased osteopontin (OPN) plasma levels has been demonstrated for the chemotherapy and surgery of lung cancer. There is also evidence in the literature that tumor volume impacts prognosis in definitive radiotherapy (RT) of (lung) cancer. We previously demonstrated that elevated plasma levels of OPN before, and increasing OPN plasma levels after RT significantly correlate with survival and outcome after curative-intent RT of non-small-cell lung cancer (NSCLC). Tumor volume was also associated with prognosis. The present prospective clinical study investigated the prognostic interrelation of OPN plasma levels and tumor volume and their changes in the radical RT of NSCLC. We evaluated a subset of patients (n=27) with inoperable, non-metastasized NSCLC of the previously published patient collective. Patients were treated with radical radiochemotherapy (2 Gy ad 66 Gy). OPN plasma concentrations were determined by ELISA before (t0), at the end (t1), and 4 weeks after RT (t2). GTV was delineated PET- and CT-correlated before RT (GTV1) and after 40 Gy (GTV2). The course of OPN during and after RT and the change of GTV during RT was monitored over time and correlated with prognosis. Median GTV2 after 40 Gy (63 ml) was significantly lower than pre-RT GTV1 (90 ml, P<0.0001). Median OPN before (t0), at the end of (t1) and four weeks after RT (t2) was 846, 777 and 624 ng/ml and not significantly different. GTV significantly declined by 39 ml during RT (P<0.0001) and OPN non-significantly decreased by 56 ng/ml during (t0 to t1) and by 54 ng/ml after RT (t1 to t2). No correlations were determined between absolute OPN and GTV values or their relative changes during RT. In univariate analysis, only GTV2 significantly predicted overall survival (OS, P=0.03). In multivariate analysis, both OPN t1 (P<0.001) and GTV2 (P=0.001) remained significant predictors of OS. Relative OPN plasma level changes after (t1 to t2) and GTV changes during RT (GTV 1 to GTV 2) significantly predicted OS (P=0.02). The combination of absolute GTV values before RT (GTV1) and GTV changes during RT (GTV1 to 2) were significantly associated with OS in both uni- and multivariate analysis (P=0.03). The combination of absolute OPN plasma levels and their changes with GTV and its changes did not reach statistical significance. The lack of a significant correlation between OPN and GTV together with the finding that OPN and GTV remained independent predictors of survival outcome but were not associated with OS in combination supports the hypothesis that tumor volume (GTV) and OPN plasma levels (both their changes and absolute values) are not interrelated in terms of prognosis but do possess each parameter separately, a prognostic quality in the radical RT of NSCLC which justifies further prospective studies to validate these results.

Serum mass profile signature as a biomarker of early lung cancer

OBJECTIVES

Circulating molecular biomarkers of lung cancer may allow the pre-selection of candidates for computed tomography screening or increase its efficacy. We aimed to identify features of serum mass profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program.

METHODS

Blood samples were collected during a low-dose computed tomography (LD-CT) screening program performed by one institution (Medical University of Gdansk, Poland). MALDI-ToF mass spectrometry was used to characterize the low-molecular-weight (1000-14,000Da) serum fraction. The analysis comprised 95 patients with early stage lung cancer (including 30 screen-detected cases) and a matched group of 285 healthy controls. The cases were split into two independent cohorts (discovery and validation), analyzed separately 6 months apart.

RESULTS

Several molecular components of serum (putatively components of endogenous peptidome) discriminating patients with early lung cancer from controls were identified in a discovery cohort. This allowed building an effective cancer classifier as a model tuned to maximize negative predictive value, with an area under the curve (AUC) of 0.88, a negative predictive value of 100%, and a positive predictive value of 48%. However, the classifier performed worse in a validation cohort including independent sample sets (AUC 0.73, NPV 88% and PPV 30%).

CONCLUSIONS

We developed a serum mass profile-based signature identifying patients with early lung cancer. Although this marker has insufficient value as a stand-alone preselecting tool for LD-CT screening, its potential clinical usefulness in evaluation of indeterminate pulmonary nodules deserves further investigation.

The prognostic value of osteopontin expression in non-small cell lung cancer: a meta-analysis

To investigate the association of Osteopontin (OPN) expression in tumor tissue with clinicopathological features of non-small cell lung carcinoma (NSCLC) patients. Publications assessing the clinicopathological characteristics and prognostic significance of OPN in expression NSCLC were identified up to March 2014. A meta-analysis of eligible studies was performed using standard statistical methods to clarify the association between OPN expression and these clinical parameters. A total of eleven studies met the inclusion criteria, and included 1536 cases of NSCLC tumor tissue and 340 cases of normal lung tissue. The OPN expression rate in NSCLC tissue was higher than normal tissue [Odds ratio (OR) 6.427; 95% confidence interval (CI) 4.689-8.808; P = 0.000]. Simultaneously, we also found that OPN expression was positively associated with stage (OR 0.332; 95% CI 0.250-0.440; P = 0.000), lymph node metastasis (OR 3.094; 95% CI 2.295-4.172; P = 0.000), tumor size (tumor size <3 cm vs. ≥3 cm; OR 0.484; 95% CI 0.303-0.773; P = 0.002) and pathology (OR 0.611; 95% CI 0.466-0.800; P = 0.000). It was unrelated that OPN expression in NSCLC tissue with and degree of differentiation and other clinical features (P > 0.05). Experimental findings indicate that, OPN plays a crucial role in the development of NSCLC.