Enhancement of a multianalyte serum biomarker panel to identify lymph node metastases in non-small cell lung cancer with circulating autoantibody biomarkers

The Evolving Landscape of B Cells in Cancer Metastasis

Metastasis is the leading cause of cancer mortality. Functional and clinical studies have documented diverse B-cell and antibody responses in cancer metastasis. The presence of B cells in tumor microenvironments and metastatic sites has been associated with diverse effects that can promote or inhibit metastasis. Specifically, B cells can contribute to the spread of cancer cells by enhancing tumor cell motility, invasion, angiogenesis, lymphangiogenesis, and extracellular matrix remodeling. Moreover, they can promote metastatic colonization by triggering pathogenic immunoglobulin responses and recruiting immune suppressive cells. Contrastingly, B cells can also exhibit antimetastatic effects. For example, they aid in enhanced antigen presentation, which helps activate immune responses against cancer cells. In addition, B cells play a crucial role in preventing the dissemination of metastatic cells from the primary tumor and secrete antibodies that can aid in tumor recognition. Here, we review the complex roles of B cells in metastasis, delineating the heterogeneity of B-cell activity and subtypes by metastatic site, antibody class, antigen (if known), and molecular phenotype. These important attributes of B cells emphasize the need for a deeper understanding and characterization of B-cell phenotypes to define their effects in metastasis.

Preoperative staging of the mediastinum is an essential and multidisciplinary task

Mediastinal staging is a crucial step in the management of patients with NSCLC. With the recent development of novel techniques, mediastinal staging has evolved from an activity of interest mainly for thoracic surgeons to a joint effort carried out by many specialists. In this regard, the debate of cases in MDT sessions is crucial for optimal management of patients. Current evidence-based clinical guidelines for preoperative NSCLC staging recommend that mediastinal staging should be performed with increasing invasiveness. Image-based techniques are the first approach, although they have limited accuracy and findings must be confirmed by pathology in almost all cases. In this setting, the advent of radiomics is promising. Invasive staging depends on procedural factors rather than diagnostic performance. The choice between endoscopy-based or surgical procedures should depend on the local expertise of each centre. As the extension of mediastinal disease in terms of number of involved lymph nodes and nodal stations affects prognosis and the choice of treatment, systematic samplings are preferred over random targeted samplings. Following this approach, a diagnosis of single mediastinal nodal involvement can be unreliable if all reachable mediastinal nodal stations have not been assessed. The performance of confirmatory mediastinoscopy after a negative endoscopy-based procedure is controversial but currently recommended. Current indications of invasive staging in patients with radiologically normal mediastinum have to be re-evaluated, especially for central tumour location.

Ubiquilin Networking in Cancers

Ubiquilins or UBQLNs, members of the ubiquitin-like and ubiquitin-associated domain (UBL-UBA) protein family, serve as adaptors to coordinate the degradation of specific substrates via both proteasome and autophagy pathways. The UBQLN substrates reveal great diversity and impact a wide range of cellular functions. For decades, researchers have been attempting to uncover a puzzle and understand the role of UBQLNs in human cancers, particularly in the modulation of oncogene's stability and nucleotide excision repair. In this review, we summarize the UBQLNs' genetic variants that are associated with the most common cancers and also discuss their reliability as a prognostic marker. Moreover, we provide an overview of the UBQLNs networks that are relevant to cancers in different ways, including cell cycle, apoptosis, epithelial-mesenchymal transition, DNA repairs and miRNAs. Finally, we include a future prospective on novel ubiquilin-based cancer therapies.

Discovering novel lung cancer associated antigens and the utilization of their autoantibodies in detection of lung cancer

OBJECTIVE

The identification of tumor-associated antigens (TAAs) and their corresponding autoantibodies in lung cancer (LC) may expand our vision of cancer immunity. This study aims to screen novel TAAs to distinguish LC from the healthy population.

METHODS

In our previous study, 35 genes encoding LC-associated TAAs were identified from the serological analysis of recombinant cDNA expression libraries (SEREX), and Oncomine database was further used to identify potential genes in cancer progression. Autoantibody to TAAs were tested by enzyme-linked immunosorbent assay (ELISA) in sera from 1379 participants in validation set and verification set.

FINDINGS

Based on analysis of three independent microarrays in Oncomine, ten genes were consistently dysregulated in LC. The sera level and positive frequency of the anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 from LC patients were higher than normal control in validation set. The area under curve (AUC) of anti-TOP2A, anti-ACTR3, anti-RPS6KA5 and anti-PSIP1 was respectively 0.758, 0.787, 0.707, 0.668. The sensitivity of these four autoantibodies for LC detection ranged from 26.63 % to 32.07 % with the specificity over 90 %. Data from the verification set confirmed the results. Except that, the frequency of serum autoantibody against TOP2A (43.3 %) and ACTR3 (50.0 %) was significantly higher in early stage LC than late stage (23.6 % and 22.3 %, respectively).

CONCLUSION

TOP2A, ACTR3, RPS6KA5 and PSIP1 can elicit humoral immune response in LC and their autoantibodies have relationship with the tumorigenesis of LC. Anti-TOP2A and anti-ACTR3 have the potential to serve as a serological biomarkers in early stage LC.

Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer

Identification of biomarkers for early detection of lung cancer (LC) is important, in turn leading to more effective treatment and reduction of mortality. Serological proteome analysis (SERPA) was used to identify proteins around 34 kD as ECH1 and HNRNPA2B1, which had been recognized by serum autoantibody from 25 LC patients. In the validation study, including 90 sera from LC patients and 89 sera from normal individuals, autoantibody to ECH1 achieved an area under the curve (AUC) of 0.799 with sensitivity of 62.2% and specificity of 95.5% in discriminating LC from normal individuals, and showed negative correlation with tumor size (r_s = -0.256, p = 0.023). Autoantibody to HNRNPA2B1 performed an AUC of 0.874 with sensitivity of 72.2% and specificity of 95.5%, and showed negative correlation with lymph node metastasis (r_s = -0.279, p = 0.012). By using longitudinal preclinical samples, autoantibody to ECH1 showed an AUC of 0.763 with sensitivity of 60.0% and specificity of 89.3% in distinguishing early stage LC from matched normal controls, and elevated autoantibody levels could be detected greater than 2 y before LC diagnosis. ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and their autoantibody can be the potential biomarkers for the early detection of LC.

Identification of novel autoantigens via mass spectroscopy-based antibody-mediated identification of autoantigens (MS-AMIDA) using immune thrombocytopenic purpura (ITP) as a model disease

Immune thrombocytopenic purpura (ITP) is one of the best characterized autoimmune diseases. Autoantibodies (AABs) against platelet antigens are considered as the diagnostic hallmark of ITP, but are detectable in only 50% of patients. We designed and applied a novel proteomic approach termed Mass Spectroscopy-based Antibody-Mediated Identification of Autoantigens (MS-AMIDA) for platelet antigens. Patients were separated into patients with classical AABs [ITP(+)] and patients without AABs [ITP(-)]. Altogether, 181 potential AAGs were found in ITP(+) and 135 AAGs in ITP(-), with 34 and 23 AAGs reproducibly found in two runs of MS-AMIDA. After subtracting identifiers from the controls, 57 AAGs in ITP(+) and 29 AAGs in ITP(+) remained, with 16 AAGs commonly found in ITP(+) and ITP(-) patients. Label-free quantification (LFQ) revealed 15 potential AAGs that are quantitatively stronger in ITP. Dot blot validation was performed on hexokinase 1 (HK1), E1 pyruvate dehydrogenase (E1-PDH), coagulation factor XIII, filamin A (FLNA), non-muscle myosin 9. Eleven patients were found to have anti-HK1 AABs, one patient had anti-E1-PDH AABs, and two patients had anti-FLNA AABs. Most antigens were of intracellular origin with significant association with actin-cytoskeleton and regulation of programmed cell death. In conclusion, novel AAGs for ITP were identified using MS-AMIDA.

RNA-Seq and Network Analysis Revealed Interacting Pathways in TGF-β-Treated Lung Cancer Cell Lines

Whole transcriptome shotgun sequencing (RNA-Seq) is a useful tool for analyzing the transcriptome of a biological sample. With appropriate statistical and bioinformatic processing, this platform is capable of identifying significant differences in gene expression within the transcriptome and permits pathway and network analyses to determine how these genes interact biologically. In this study, we examined gene expression in two lung adenocarcinoma cell lines (H358 and A459) that were treated with transforming growth factor-β (TGF-β) as a model for induction of the epithelial-to-mesenchymal transition (EMT), commonly associated with disease progression. We performed this study in order to illustrate a workflow for identifying interesting genes and processes that are regulated early in EMT and to determine their gene pathway/network relationships and regulation. With this, we identified 137 upregulated and 32 downregulated genes common to both cell lines after TGF-β treatment that represent components of multiple canonical pathways and biological networks associated with the induction of EMT. These findings were also verified against reposited Affymetrix U133a expression profiles from multiple trials examining metastatic progression in patient cohorts (n = 731 total) to further establish the clinical relevance and translational significance of the model system. Together, these findings help validate the relevance of the TGF-β model for the study of EMT and provide new insights into early events in EMT.

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis-SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood-based biomarker studies.

Circulating angiogenesis biomarkers are associated with disease progression in lung adenocarcinoma

BACKGROUND

Dysregulation of angiogenesis is known to be associated with tumorigenesis and metastatic progression in multiple carcinomas. The aim of this study was to evaluate the prognostic value of circulating angiogenesis biomarkers in lung adenocarcinoma progression. For that, we hypothesize that circulating levels of biomarkers characteristic for discrete processes within angiogenesis are associated with specific phases of disease progression. Appreciation of these profiles may have important implications for disease detection and prognostication.

METHODS

Patients with lung adenocarcinoma enrolled in the study were grouped as follows: node negative (T1a-3N0M0; n = 69), node positive (T1a-4N1-2M0; n = 60), and disseminated disease (TxNxM1; n = 68). All serum specimens were assayed for 17 angiogenesis biomarkers on the Luminex platform and statistically evaluated by analysis of variance for median differences in biomarker concentration at distinct phases of disease progression and by log rank methods for associations with clinical outcome.

RESULTS

We found circulating hepatocyte growth factor, heparin-binding epidermal growth factor, epidermal growth factor, and vascular endothelial growth factor-C levels significantly elevated (p < 0.05) in patients with node positive versus node negative disease. Similarly, median serum concentrations of bone morphogenic protein-9, endoglin, fibroblast growth factor-1, fibroblast growth factor-2, interleukin-8, placental growth factor, vascular endothelial growth factor-C, and vascular endothelial growth factor-D were significantly (p < 0.05) higher in patients with disseminated disease than in patients with node positive disease. Five biomarkers total were strongly prognostic (p < 0.05) for overall survival in the node negative cohort.

CONCLUSIONS

Angiogenesis is a process central to lung adenocarcinoma progression. We describe the modulation in serum angiogenesis biomarker concentrations through the various phases of non-small cell lung cancer progression. Additional refinement efforts are under way to enhance test performance, followed by additional validation studies.

Autoantibodies in breast cancer

In addition to their historical role, autoantibodies appear promising as biomarkers to facilitate diagnosis, improve patient outcome and decrease mortality in cancer. Autoantibodies may also be useful in the identification of subjects at risk for cancer, that is, those bearing premalignant changes. Numerous studies have demonstrated that cancer serum contains a variety of autoantibodies that react with autologous cellular antigens, that is, tumor-associated antigens. Interestingly, some of these antigens are involved in signal transduction, cell cycle regulation, cell proliferation, and apoptosis. As such, identification of these molecules has additional importance for development of novel anticancer drugs and vaccines. This review focuses on the use of autoantibodies in breast cancer, a major public health problem. We also address the need for additional research to validate this approach in cancer diagnostics and therapeutics in general.

Use of autoantibodies to detect the onset of breast cancer

The widespread use of screening mammography has resulted in increased detection of early-stage breast disease, particularly for in situ carcinoma and early-stage breast cancer. However, the majority of women with abnormalities noted on screening mammograms are not diagnosed with cancer because of several factors, including radiologist assessment, patient age, breast density, malpractice concerns, and quality control procedures. Although magnetic resonance imaging is a highly sensitive detection tool that has become standard for women at very high risk of developing breast cancer, it lacks sufficient specificity and costeffectiveness for use as a general screening tool. Therefore, there is an important need to improve screening and diagnosis of early-invasive and noninvasive tumors, that is, in situ carcinoma. The great potential for molecular tools to improve breast cancer outcomes based on early diagnosis has driven the search for diagnostic biomarkers. Identification of tumor-specific markers capable of eliciting an immune response in the early stages of tumor development seems to provide an effective approach for early diagnosis. The aim of this review is to describe several autoantibodies identified during breast cancer diagnosis. We will focus on these molecules highlighted in the past two years and discuss the potential future use of autoantibodies as biomarkers of early-stage breast cancer.

Development and validation of a plasma biomarker panel for discerning clinical significance of indeterminate pulmonary nodules

INTRODUCTION

The recent findings of the National Lung Screening Trial showed 24.2% of individuals at high risk for lung cancer having one or more indeterminate nodules detected by low-dose computed tomography-based screening, 96.4% of which were eventually confirmed as false positives. These positive scans necessitate additional diagnostic procedures to establish a definitive diagnosis that adds cost and risk to the paradigm. A plasma test able to assign benign versus malignant pathology in high-risk patients would be an invaluable tool to complement low-dose computed tomography-based screening and promote its rapid implementation.

METHODS

We evaluated 17 biomarkers, previously shown to have value in detecting lung cancer, against a discovery cohort, comprising benign (n = 67) cases and lung cancer (n = 69) cases. A Random Forest method based analysis was used to identify the optimal biomarker panel for assigning disease status, which was then validated against a cohort from the Mayo Clinic, comprising patients with benign (n = 61) or malignant (n = 20) indeterminate lung nodules.

RESULTS

Our discovery efforts produced a seven-analyte plasma biomarker panel consisting of interleukin 6 (IL-6), IL-10, IL-1ra, sIL-2Rα, stromal cell-derived factor-1α+β, tumor necrosis factor α, and macrophage inflammatory protein 1 α. The sensitivity and specificity of our panel in our validation cohort is 95.0% and 23.3%, respectively. The validated negative predictive value of our panel was 93.8%.

CONCLUSION

We developed a seven-analyte plasma biomarker panel able to identify benign nodules, otherwise deemed indeterminate, with a high degree of accuracy. This panel may have clinical utility in risk-stratifying screen-detected lung nodules, decrease unnecessary follow-up imaging or invasive procedures, and potentially avoid unnecessary morbidity, mortality, and health care costs.

A multiplexed serum biomarker immunoassay panel discriminates clinical lung cancer patients from high-risk individuals found to be cancer-free by CT screening

INTRODUCTION

Clinical decision making in the setting of computed tomography (CT) screening could benefit from accessible biomarkers that help predict the level of lung cancer risk in high-risk individuals with indeterminate pulmonary nodules.

METHODS

To identify candidate serum biomarkers, we measured 70 cancer-related proteins by Luminex xMAP (Luminex Corporation) multiplexed immunoassays in a training set of sera from 56 patients with biopsy-proven primary non-small-cell lung cancer and 56 age-, sex-, and smoking-matched CT-screened controls.

RESULTS

We identified a panel of 10 serum biomarkers-prolactin, transthyretin, thrombospondin-1, E-selectin, C-C motif chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor, receptor tyrosine-protein kinase, erbb-2, cytokeratin fragment 21.1, and serum amyloid A-that distinguished lung cancer patients from controls with an estimated balanced accuracy (average of sensitivity and specificity) of 76.0 ± 3.8% from 20-fold internal cross-validation. We then iteratively evaluated this model in an independent test and verification case/control studies confirming the initial classification performance of the panel. The classification performance of the 10-biomarker panel was also analytically validated using enzyme-linked immunosorbent assays in a second independent case/control population, further validating the robustness of the panel.

CONCLUSIONS

The performance of this 10-biomarker panel-based model was 77.1% sensitivity/76.2% specificity in cross-validation in the expanded training set, 73.3% sensitivity/93.3% specificity (balanced accuracy 83.3%) in the blinded verification set with the best discriminative performance in stage I/II cases: 85% sensitivity (balanced accuracy 89.2%). Importantly, the rate of misclassification of CT-screened controls was not different in most control subgroups with or without airflow obstruction or emphysema or pulmonary nodules. These biomarkers have potential to aid in the early detection of lung cancer and more accurate interpretation of indeterminate pulmonary nodules detected by CT screening.