Highly Sensitive Marker Panel for Guidance in Lung Cancer Rapid Diagnostic Units

Biomarkers Suitable for Early Detection of Intrathoracic Cancers in Primary Care: A Systematic Review

Intrathoracic cancers, including lung cancer, mesothelioma, and thymoma, present diagnostic challenges in primary care. Biomarkers could resolve some challenges. We synthesized evidence on biomarker performance for intrathoracic cancer detection in low-prevalence settings. A search in Embase and MEDLINE included studies that recruited participants with suspected intrathoracic cancer and reported on at least one diagnostic measure for a validated, noninvasive biomarker. Studies were excluded if participants were recruited based on a preestablished diagnosis. A total of 52 studies were included, reporting on 108 individual biomarkers and panels. Carcinoembryonic antigen, CYFRA 21-1, and VEGF were evaluated for lung cancer and mesothelioma. For lung cancer, carcinoembryonic antigen and CYFRA 21-1 were the most studied, with AUCs of 0.48 to -0.90 and 0.48 to -0.83, respectively. Pro-gastrin-releasing peptide (Pro-GRP) and neuron-specific enolase (NSE) had the highest negative predictive values (NPV) (98.2% and 96.9%, respectively), whereas Early Cancer Detection Test - Lung (Early CDT) and miRNA signature classifier panels showed NPVs of 99.3% and 99.0%, respectively, in smokers. For mesothelioma, fibrillin-3 and mesothelin plus osteopontin had AUCs of 0.93 and 0.91, respectively. Thymoma panels (binding AcHR + StrAb and binding AcHR + modulating AcHR + StrAb) had 100% NPVs in patients with myasthenia gravis. The review highlights the performance of some biomarkers. However, few were evaluated in low-prevalence settings. Further evaluation is necessary before implementing these biomarkers for intrathoracic cancers in primary care.

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.

S100A8 and S100A9 in Cancer

S100A8 and S100A9 are Ca²⁺ binding proteins that belong to the S100 family. Primarily expressed in neutrophils and monocytes, S100A8 and S100A9 play critical roles in modulating various inflammatory responses and inflammation-associated diseases. Forming a common heterodimer structure S100A8/A9, S100A8 and S100A9 are widely reported to participate in multiple signaling pathways in tumor cells. Meanwhile, S100A8/A9, S100A8, and S100A9, mainly as promoters, contribute to tumor development, growth and metastasis by interfering with tumor metabolism and the microenvironment. In recent years, the potential of S100A8/A9, S100A9, and S100A8 as tumor diagnostic or prognostic biomarkers has also been demonstrated. In addition, an increasing number of potential therapies targeting S100A8/A9 and related signaling pathways have emerged. In this review, we will first expound on the characteristics of S100A8/A9, S100A9, and S100A8 in-depth, focus on their interactions with tumor cells and microenvironments, and then discuss their clinical applications as biomarkers and therapeutic targets. We also highlight current limitations and look into the future of S100A8/A9 targeted anti-cancer therapy.

Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

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.

Biomarkers for Comorbidities Modulate the Activity of T-Cells in COPD

In smoking-induced chronic obstructive pulmonary disease (COPD), various comorbidities are linked to systemic inflammation and infection-induced exacerbations. The underlying mechanisms are unclear but might provide therapeutic targets. T-cell activity is central in systemic inflammation and for infection-defense mechanisms and might be influenced by comorbidities. Hypothesis: Circulating biomarkers of comorbidities modulate the activity of T-cells of the T-helper type 1 (Th1) and/or T-cytotoxic type 1 (Tc1). T-cells in peripheral blood mononuclear cells (PBMCs) from non-smokers (NS), current smokers without COPD (S), and COPD subjects (total n = 34) were ex vivo activated towards Th1/Tc1 and were then stimulated with biomarkers for metabolic and/or cardiovascular comorbidities (Brain Natriuretic Peptide, BNP; chemokine (C-C motif) ligand 18, CCL18; C-X3-C motif chemokine ligand 1, CX3CL1; interleukin-18, IL-18) or for asthma- and/or cancer-related comorbidities (CCL22; epidermal growth factor, EGF; IL-17; periostin) each at 10 or 50 ng/mL. The Th1/Tc1 activation markers interferon-γ (IFNγ), tumor necrosis factor-α (TNFα), and granulocyte-macrophage colony-stimulating factor (GM-CSF) were analyzed in culture supernatants by Enzyme-Linked Immunosorbent Assay (ELISA). Ex-vivo activation induced IFNγ and TNFα without differences between the groups but GM-CSF more in S vs. NS. At 10 ng/mL, the different biomarkers increased or reduced the T-cell activation markers without a clear trend for one direction in the different categories of comorbidities or for the different T-cell activation markers. At 50 ng/mL, there was a clear shift towards suppressive effects, particularly for the asthma— and cancer-related biomarkers and in cells of S and COPD. Comorbidities might suppress T-cell immunity in COPD. This could explain the association of comorbidities with frequent exacerbations.

Tumour markers with clinically controlled cut-offs for suspected cancer

BACKGROUND

Due to insufficient scientific evidence, panels of tumour markers (TMs) are currently not recommended for use in suspected cancer. However, recent well-designed studies have revealed a potential clinical value in lung cancer. We analysed the diagnostic accuracy of a panel of 11 circulating TMs with clinically controlled thresholds in the differentiation of cancer from nonmalignant diseases.

METHODS

We prospectively recruited 4776 consecutive patients presenting with focal or nonspecific symptoms suggestive of cancer who underwent testing for 11 serum TMs before diagnosis was known. The study abided by 2015 STARD guidelines. Tumour markers included, among others, carbohydrate antigen 19-9, carcinoembryonic antigen, alpha-fetoprotein, squamous cell carcinoma-associated antigen, prostate-specific antigen (males), neuron-specific enolase, progastrin-releasing peptide and carbohydrate antigen 125. Thresholds were adjusted for the presence of kidney failure, liver disease, effusions and dermatological disorders. Results showing ≥1 TMs with concentrations above threshold were considered positive.

RESULTS

Benign diseases were diagnosed in 3281 (68.7%) patients and cancer in 1495 (31.3%), with epithelial cancers in 1214 (77% at stage IV). When applying criteria for controlled thresholds, overall specificity was 98%. Overall sensitivity of the panel in epithelial cancers was 72.2%, positive predictive value 93% and negative predictive value 90.5%. The area under the receiver operating characteristic curve was 0.920 (95% confidence interval, 0.902-0.924).

CONCLUSIONS

By using clinically controlled cut-offs, the combined panel demonstrated an excellent ability to discriminate epithelial cancers from nonmalignant diseases. However, its use in clinical practice would need formal validation through a multicentre controlled trial assessing a panel-guided strategy vs. standard diagnosis.

The mechanism of sitagliptin inhibition of colorectal cancer cell lines' metastatic functionalities

The cell membrane glycoprotein CD26 with peptidase activity (DPP4) and/or its soluble CD26/DPP4 counterpart expression and/or activity are altered in several cancers. Its role in metastasis development was recently highlighted by the discovery of CD26⁺ cancer stem cell subsets and the fact that clinical DPP4 inhibitors showed antimetastatic effects in animal models. Also, diabetic patients treated with the DPP4 inhibitor sitagliptin showed greater overall survival after colorectal or lung cancer surgery than patients under other diabetic therapies. However, the mechanism of action of these inhibitors in this context is unclear. We studied the role of CD26 and its DPP4 enzymatic activity in malignant cell features such as cell-to-cell homotypic aggregation, cancer cell motility, and invasion in a panel of human colorectal cancer (CRC) cell lines, avoiding models that include the physiological role of DPP4 in chemotaxis. Present results indicate that CD26 participates in the induction of cell invasion, motility, and aggregation of CD26-positive CRC cell lines. Moreover, only invasion and motility assays, which are collagen matrix-dependent, showed a decrease upon treatment with the DPP4 inhibitor sitagliptin. Sitagliptin showed opposite effects to those of transforming growth factor-β1 on epithelial-to-mesenchymal transition and cell cycle, but this result does not explain its CD26/DPP4-dependent effect. These results contribute to the elucidation of the molecular mechanisms behind sitagliptin inhibition of metastatic traits. At the same time, this role of sitagliptin may help to define areas of medicine where DPP4 inhibitors might be introduced. However, they also suggest that additional tools against CD26 as a target might be used or developed for metastasis prevention in addition to gliptins.

TSPAN1, TMPRSS4, SDR16C5, and CTSE as Novel Panel for Pancreatic Cancer: A Bioinformatics Analysis and Experiments Validation

Pancreatic cancer is a lethal malignancy with a poor prognosis. This study aims to identify pancreatic cancer-related genes and develop a robust diagnostic model to detect this disease. Weighted gene co-expression network analysis (WGCNA) was used to determine potential hub genes for pancreatic cancer. Their mRNA and protein expression levels were validated through reverse transcription PCR (RT-PCR) and immunohistochemical (IHC). Diagnostic models were developed by eight machine learning algorithms and ten-fold cross-validation. Four hub genes (TSPAN1, TMPRSS4, SDR16C5, and CTSE) were identified based on bioinformatics. RT-PCR showed that the four hub genes were expressed at medium to high levels, IHC revealed that their protein expression levels were higher in pancreatic cancer tissues. For the panel of these four genes, eight models performed with 0.87-0.92 area under the curve value (AUC), 0.91-0.94 sensitivity, and 0.84-0.86 specificity in the validation cohort. In the external validation set, these models also showed good performance (0.86-0.98 AUC, 0.84-1.00 sensitivity, and 0.86-1.00 specificity). In conclusion, this study has identified four hub genes that might be closely related to pancreatic cancer: TSPAN1, TMPRSS4, SDR16C5, and CTSE. Four-gene panels might provide a theoretical basis for the diagnosis of pancreatic cancer.

Calprotectin in Lung Diseases

Calprotectin (CLP) is a heterodimer formed by two S-100 calcium-binding cytosolic proteins, S100A8 and S100A9. It is a multifunctional protein expressed mainly by neutrophils and released extracellularly by activated or damaged cells mediating a broad range of physiological and pathological responses. It has been more than 20 years since the implication of S100A8/A9 in the inflammatory process was shown; however, the evaluation of its role in the pathogenesis of respiratory diseases or its usefulness as a biomarker for the appropriate diagnosis and prognosis of lung diseases have only gained attention in recent years. This review aimed to provide current knowledge regarding the potential role of CLP in the pathophysiology of lung diseases and describe how this knowledge is, up until now, translated into daily clinical practice. CLP is involved in numerous cellular processes in lung health and disease. In addition to its anti-microbial functions, CLP also serves as a molecule with pro- and anti-tumor properties related to cell survival and growth, angiogenesis, DNA damage response, and the remodeling of the extracellular matrix. The findings of this review potentially introduce CLP in daily clinical practice within the spectrum of respiratory diseases.

Correlations between angiopoietin-2 gene polymorphisms and lung cancer progression in a Chinese Han population

Lung cancer is the most common malignancy in China and is associated with a poor survival rate amongst Han Chinese. The high mortality is largely attributed to late-stage diagnosis, when treatment is largely ineffective. Identification of genetic variants could potentially assist with earlier diagnosis and thus more effective treatment. The development and progression of lung cancer is stimulated by angiopoietin-2 (Ang2), a ligand for Tie2, an endothelial tyrosine kinase. Patients with lung cancer with higher serum Ang2 levels have significantly poorer survival than patients with lower serum Ang2 levels. We explored the effects of Ang2 single nucleotide polymorphisms (SNPs) on lung cancer susceptibility. We used lung cancer tissue and serum samples to measure Ang2 expression in a Chinese Han population. Five Ang2 SNPs (rs2442598, rs734701, rs1823375, 11137037, and rs12674822) were analyzed using TaqMan SNP genotyping in 695 patients with lung cancer and 900 cancer-free controls. Carriers of the variant GT allele of rs12674822 had a higher risk of lung cancer than wild-type (GG) carriers, while the presence of the CC genotype at rs11137037 was associated with higher clinical stage disease compared with having the AA genotype. Our study is the first to document a correlation between Ang2 polymorphisms and lung cancer development and progression in people of Chinese Han ethnicity.

CSF-1 and Ang-2 serum levels - prognostic and diagnostic partners in non-small cell lung cancer

Background

Lung cancer is the most incident and lethal form of cancer, with late diagnosis as a major determinant of its bad prognosis. Immunotherapies targeting immune checkpoints improve survival, but positive results encompass only 30%–40% of the patients, possibly due to alternative pathways to immunosuppression, including tumour-associated macrophages (TAM). Colony stimulating factor-1 (CSF-1) is implicated in TAM differentiation and recruitment to tumours and in tumour angiogenesis, through a special setting of Tie-2-expressing macrophages, which respond to angiopoietin-2 (Ang-2). We evaluated the role of serum levels of CSF-1 in non-small cell lung cancer (NSCLC) prognosis and whether these could serve as biomarkers for NSCLC detection, along with Ang-2.

Participants and methods

We prospectively studied an unselected cohort of 145 patients with NSCLC and a group of 30 control individuals. Serum levels of Ang-2 and CSF-1 were measured by ELISA prior to treatment.

Results

Serum levels of CSF-1 and Ang-2 are positively correlated (p<0.000001). Individuals with high serum levels of CSF-1 have a 17-fold risk for NSCLC presence and patients with combined High Ang-2/CSF-1 serum levels present a 5-fold increased risk of having NSCLC. High Ang-2/CSF-1 phenotype is also associated with worst prognosis in NSCLC.

Conclusions

Combined expression of CSF-1 and Ang-2 seems to contribute to worst prognosis in NSCLC and it is worthy to understand the basis of this unexplored partnership. Moreover, we think CSF-1 could be included as a biomarker in NSCLC screening protocols that can improve the positive predictive value of the current screening modalities, increase overall cost effectiveness and potentially improve lung cancer survival.