Cancer Biomarkers Discovery and Validation: State of the Art, Problems and Future Perspectives

The role of seven tumor-associated autoantibodies in the diagnosis, staging and treatment guidance of lung cancer

BACKGROUND

This study assessed the diagnosis, staging and treatment guidance of lung cancer (LC) based on seven tumor-associated autoantibodies (TAAbs) -p53, PGP9.5, SOX2, GBU4-5, MAGE A1, CAGE, and GAGE7.

METHODS

ELISA was used to determine the TAAb serum levels in 433 patients diagnosed with LC (161 surgical patients) and 76 patients with benign lung disease (16 surgical patients). The statistical characteristic of the TAAbs was compared among patients with different clinicopathological features. Pre- to postoperative changes in TAAb levels were analyzed to determine their value of LC.

RESULTS

Among all patients, the positive rate of the seven TAAbs was 23.4%, sensitivity was 26.3%, accuracy was 36.3%, specificity was 93.4%, positive predictive value was 95.8%, and negative predictive value was 18.2%; the positive rate for the LC group (26.3%) was significantly higher than that for the benign group (6.6%; P < 0.001). Significant differences in the positive rate of the seven autoantibodies according to age (P < 0.001), smoking history (P = 0.009) and clinical LC stage (P < 0.001) were found. Smoking was positively associated with the positive of TAAbs (Τ = 0.118, P = 0.008). The positive rates of the seven TAAbs for squamous carcinoma (54.5%), other pathological types (44.4%) and poorly differentiated LC (57.1%) were significantly higher than those for the other types. The positive rate of GBU4-5 was highest among all TAAbs, and the SOX2 level in stage III-IV patients was much higher than that in other stages. For patients undergoing surgery, compared with the preoperative levels, the postoperative levels of the 7 markers, particularly p53 (P = 0.027), PGP9.5 (P = 0.007), GAGE7 (P = 0.014), and GBU4-5 (P = 0.002), were significantly different in the malignant group, especially in stage I-II patients, while no clear pre- to postoperative difference was observed in the benign group.

CONCLUSIONS

When the seven TAAbs was positive, it was very helpful for the diagnosis of LC. The 7 TAAbs was valuable for staging and guiding treatment of LC in surgical patients.

Thinking small to win big? A critical review on the potential application of extracellular vesicles for biomarker discovery and new therapeutic approaches in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly form of cancer, with limited progress in 5-year survival rates despite significant research efforts. The main challenges in treating PDAC include difficulties in early detection, and resistance to current therapeutic approaches due to aggressive molecular and microenvironment features. These challenges emphasize the importance of identifying clinically validated biomarkers for early detection and clinical management. Extracellular vesicles (EVs), particularly exosomes, have emerged as crucial mediators of intercellular communication by transporting molecular cargo. Recent research has unveiled their role in initiation, metastasis, and chemoresistance of PDAC. Consequently, utilizing EVs in liquid biopsies holds promise for the identification of biomarkers for early detection, prognosis, and monitoring of drug efficacy. However, numerous limitations, including challenges in isolation and characterization of homogeneous EVs populations, as well as the absence of standardized protocols, can affect the reliability of studies involving EVs as biomarkers, underscoring the necessity for a prudent approach. EVs have also garnered considerable attention as a promising drug delivery system and novel therapy for tumors. The loading of biomolecules or chemical drugs into exosomes and their subsequent delivery to target cells can effectively impede tumor progression. Nevertheless, there are obstacles that must be overcome to ensure the accuracy and efficacy of therapies relying on EVs for the treatment of tumors. In this review, we examine both recent advancements and remaining obstacles, exploring the potential of utilizing EVs in biomarker discovery as well as for the development of drug delivery vehicles.

Carbon dots and composite materials with excellent performances in cancer-targeted bioimaging and killing: a review

Carbon dots (CDs) are nanomaterials with excellent properties, including good biocompatibility, small size, ideal photoluminescence and surface modification, and are becoming one of the most attractive nanomaterials for the imaging, detection and treatment of tumors. Based on these advantages, CDs can be combined other materials to obtain composite particles with improved, even new, performance, mainly in photothermal and photodynamic therapies. This paper reviews the research progress of CDs and their composites in targeted tumor imaging, detection, diagnosis, drug delivery and tumor killing. It also discusses and proposes the challenges and perspectives of their future applications in these fields. This review provides ideas for future applications of novel CD-based materials in the diagnosis and treatment of cancer.

The Biomarker Toolkit - an evidence-based guideline to predict cancer biomarker success and guide development

BACKGROUND

An increased number of resources are allocated on cancer biomarker discovery, but very few of these biomarkers are clinically adopted. To bridge the gap between Biomarker discovery and clinical use, we aim to generate the Biomarker Toolkit, a tool designed to identify clinically promising biomarkers and promote successful biomarker translation.

METHODS

All features associated with a clinically useful biomarker were identified using mixed-methodology, including systematic literature search, semi-structured interviews, and an online two-stage Delphi-Survey. Validation of the checklist was achieved by independent systematic literature searches using keywords/subheadings related to clinically and non-clinically utilised breast and colorectal cancer biomarkers. Composite aggregated scores were generated for each selected publication based on the presence/absence of an attribute listed in the Biomarker Toolkit checklist.

RESULTS

Systematic literature search identified 129 attributes associated with a clinically useful biomarker. These were grouped in four main categories including: rationale, clinical utility, analytical validity, and clinical validity. This checklist was subsequently developed using semi-structured interviews with biomarker experts (n=34); and 88.23% agreement was achieved regarding the identified attributes, via the Delphi survey (consensus level:75%, n=51). Quantitative validation was completed using clinically and non-clinically implemented breast and colorectal cancer biomarkers. Cox-regression analysis suggested that total score is a significant driver of biomarker success in both cancer types (BC: p>0.0001, 95.0% CI: 0.869-0.935, CRC: p>0.0001, 95.0% CI: 0.918-0.954).

CONCLUSIONS

This novel study generated a validated checklist with literature-reported attributes linked with successful biomarker implementation. Ultimately, the application of this toolkit can be used to detect biomarkers with the highest clinical potential and shape how biomarker studies are designed/performed.

Surface Plasmon Resonance (SPR) Sensor for Cancer Biomarker Detection

A biomarker is a physiological observable marker that acts as a stand-in and, in the best-case scenario, forecasts a clinically significant outcome. Diagnostic biomarkers are more convenient and cost-effective than directly measuring the ultimate clinical outcome. Cancer is among the most prominent global health problems and a major cause of morbidity and death globally. Therefore, cancer biomarker assays that are trustworthy, consistent, precise, and verified are desperately needed. Biomarker-based tumor detection holds a lot of promise for improving disease knowledge at the molecular scale and early detection and surveillance. In contrast to conventional approaches, surface plasmon resonance (SPR) allows for the quick and less invasive screening of a variety of circulating indicators, such as circulating tumor DNA (ctDNA), microRNA (miRNA), circulating tumor cells (CTCs), lipids, and proteins. With several advantages, the SPR technique is a particularly beneficial choice for the point-of-care identification of biomarkers. As a result, it enables the timely detection of tumor markers, which could be used to track cancer development and suppress the relapse of malignant tumors. This review emphasizes advancements in SPR biosensing technologies for cancer detection.

Combined Use of Ionic Liquid-Based Aqueous Biphasic Systems and Microfluidic Devices for the Detection of Prostate-Specific Antigen

Prostate cancer (PCa) is one of the cancer types that most affects males worldwide and is among the highest contributors to cancer mortality rates. Therefore, there is an urgent need to find strategies to improve the diagnosis of PCa. Microtechnologies have been gaining ground in biomedical devices, with microfluidics and lab-on-chip systems potentially revolutionizing medical diagnostics. In this paper, it is shown that prostate-specific antigen (PSA) can be detected through an immunoassay performed in a microbead-based microfluidic device after being extracted and purified from a serum sample through an aqueous biphasic system (ABS). Given their well-established status as ABS components for successful bioseparations, ionic liquids (ILs) and polymers were used in combination with buffered salts. Using both IL-based and polymer-based ABS, it was demonstrated that it is possible to detect PSA in non-physiological environments. It was concluded that the ABS that performed better in extracting the PSA from serum were those composed of tetrabutylammonium chloride ([N₄₄₄₄]Cl) and tetrabutylphosphonium bromide ([P₄₄₄₄]Br), both combined with phosphate buffer, and constituted by polyethylene glycol with a molecular weight of 1000 g/mol (PEG1000) with citrate buffer. In comparison with the assay with PSA prepared in phosphate-buffered saline (PBS) or human serum in which no ABS-mediated extraction was applied, assays attained lower limits of detection after IL-based ABS-mediated extraction. These results reinforce the potential of this method in future point-of-care (PoC) measurements.

FOXO3 gene hypermethylation and its marked downregulation in breast cancer cases: A study on female patients

Background

FOXO3, a member of the FOX transcription factor family, is frequently described as being deregulated in cancer. Additionally, notable role of FOXO3 can be easily recognized in the process of ageing and survival. Even though various studies have been done to acknowledge the tumour-suppressive or oncogenic role of FOXO3 in cancer, still there exist a lack of understanding in terms of cancer prognosis and treatment. Therefore, to provide better insight, our study aims to evaluate the role and function of FOXO3 in breast cancer in Indian female patients. We examined the FOXO3 expression levels in breast cancer samples by analyzing mRNA and protein expression along with its clinicopathological parameters.

Results

A total of 127 cases of breast cancer with equal normal cases (n=127) were assessed with methylation (MS-PCR), Immunohistochemistry (IHC), mRNA expression using Real-time PCR was analysed and 66.14% cases at mRNA level were found to be downregulated, while 81.10% of cases had little or very little protein expression. Our data state, the promoter hypermethylation of the FOXO3 gene and the downregulated protein expression are significantly correlated (p=0.0004). Additionally, we found a significant correlation between the level of FOXO3 mRNA with ER (p=0.04) and status of lymph node (p=0.01) along with this.

Conclusion

Data suggests the prognostic significance and the tumour-suppressive role of FOXO3 in breast cancer cases studied in India. However, there is a need for the extended research targeting FOXO3 to measure its clinical potential and develop well-defined therapeutic strategies.

The Rise of Extracellular Vesicles as New Age Biomarkers in Cancer Diagnosis: Promises and Pitfalls

Cell-to-cell interactions in the intricate microenvironment of tissue have a significant impact on the progression of cancer at every stage. Both cancer cells and stromal cells are responsible for the secretion of soluble chemical compounds as well as membrane-encased components, which both influence and govern the cell-to-cell interactions within the micro-environment of tumor cells. These membrane structures are identified as extracellular vesicles (EVs), which include exosomes and microvesicles. These nanosized vesicles are made up of bilayered proteolipids and have dimensions ranging from 50 to 1000 nm. It has been speculated that extracellular vesicles that originate from cancer cells perform a variety of functions in the development and progression of cancer which may involve the transport of regulatory materials, such as oncogenic proteins between nearby cells and to distant biological locations. In addition, their level in the serum of cancer patients is noticeably higher than those of healthy controls. The release of extracellular vesicles into the extracellular space is a continual process in both healthy and diseased cells. These extracellular vesicles hold molecular signatures that are defining features of health as well as disease. And hence, the EVs present in biological fluids provide unparalleled and noninvasive access to the necessary molecular details about the health status of the cells. Recent discoveries about these complex extracellular organelles have accelerated the discovery of cancer-specific biological markers as well as the development of unique diagnostic tools based on extracellular vesicles. In this mini-review, we aim to highlight the hopes and hypes associated with the applications of extracellular vesicles as biomarkers for cancer diagnosis.

Design, optimization, and application of multiplex rRT-PCR in the detection of respiratory viruses

Viral respiratory infections are common and serious diseases. Because there is no effective treatment method or vaccine for respiratory tract infection, early diagnosis is vital to identify the pathogen so as to determine the infectivity of the patient and to quickly take measures to curb the spread of the virus, if warranted, to avoid serious public health problems. Real-time reverse transcriptase PCR (rRT-PCR), which has high sensitivity and specificity, is the best approach for early diagnosis. Among rRT-PCR methods, multiplex rRT-PCR can resolve issues arising from various types of viruses, high mutation frequency, coinfection, and low concentrations of virus. However, the design, optimization, and validation of multiplex rRT-PCR are more complicated than singleplex rRT-PCR, and comprehensive research on multiplex rRT-PCR methodology is lacking. This review summarizes recent progress in multiplex rRT-PCR methodology, outlines the principles of design, optimization and validation, and describes a scheme to help diagnostic companies to design and optimize their multiplex rRT-PCR detection panel and to assist laboratory staff to solve problems in their daily work. In addition, the analytical validity, clinical validity and clinical utility of multiplex rRT-PCR in viral respiratory tract infection diagnosis are assessed to provide theoretical guidance and useful information for physicians to understand the test results.

A framework to predict the applicability of Oncotype DX, MammaPrint, and E2F4 gene signatures for improving breast cancer prognostic prediction

To improve cancer precision medicine, prognostic and predictive biomarkers are critically needed to aid physicians in deciding treatment strategies in a personalized fashion. Due to the heterogeneous nature of cancer, most biomarkers are expected to be valid only in a subset of patients. Furthermore, there is no current approach to determine the applicability of biomarkers. In this study, we propose a framework to improve the clinical application of biomarkers. As part of this framework, we develop a clinical outcome prediction model (CPM) and a predictability prediction model (PPM) for each biomarker and use these models to calculate a prognostic score (P-score) and a confidence score (C-score) for each patient. Each biomarker’s P-score indicates its association with patient clinical outcomes, while each C-score reflects the biomarker applicability of the biomarker’s CPM to a patient and therefore the confidence of the clinical prediction. We assessed the effectiveness of this framework by applying it to three biomarkers, Oncotype DX, MammaPrint, and an E2F4 signature, which have been used for predicting patient response, pathologic complete response versus residual disease to neoadjuvant chemotherapy (a classification problem), and recurrence-free survival (a Cox regression problem) in breast cancer, respectively. In both applications, our analyses indicated patients with higher C scores were more likely to be correctly predicted by the biomarkers, indicating the effectiveness of our framework. This framework provides a useful approach to develop and apply biomarkers in the context of cancer precision medicine.

Implications and pitfalls for cancer diagnostics exploiting extracellular vesicles

Early detection of cancer in order to facilitate timely therapeutic interventions is an unsolved problem in today's clinical diagnostics. Tumors are detected so far mostly after pathological symptoms have emerged (usually already in progressed disease states), within preventive screenings, or occasionally as incidental finding. The emergence of extracellular vesicle (EV) analytics in combination with liquid biopsy sampling opened a plethora of new possibilities for the detection of tumors (and other diseases). This review gives an overview of the diversity of currently known EV species and the relevant cargo molecules representing potential biomarkers to detect, identify and characterize tumor cells. A number of molecules reported in recent years to be valuable targets for different aspects of cancer diagnostics, are presented. Furthermore, we discuss (technical) challenges and pitfalls related to the various potential applications (screening, diagnosis, prognosis, monitoring) of liquid biopsy based EV analytics, and give an outlook to possible future directions of this emerging field in oncology.

Electrochemistry-Assisted Surface Plasmon Resonance Biosensor for Detection of CA 15-3

In this work, we describe an innovative methodology based on combined surface plasmon resonance (SPR) and electrochemical responses (eSPR) in the same immunoassay for screening CA 15-3 cancer biomarker with high sensitivity (and selectivity), in a very simple, label-free, accurate, and fully automated manner. Detection was achieved by performing two simple steps. In the first step, direct SPR was used to monitor CA 15-3 interaction with surface immobilized antibody. Two linear response ranges were obtained and the detection limit achieved is poor (LOD of 21 U mL^-1). However, in the second detection step, electrochemical measurements at the SPR gold surface were performed to measure the decrease of redox probe peak current upon antigen-antibody interaction, providing a suitable amplification strategy to lower detection levels of CA 15-3 (LOD of 0.0998 U mL^-1), without the need of additional complex and/or expensive amplification steps to enhance the sensitivity. Moreover, selectivity studies were performed against other common cancer biomarkers and the results showed that the eSPR immunosensor is selective for the CA 15-3 protein. Finally, the clinical applicability of the developed eSPR biosensing methodology was successfully applied to detect CA 15-3 in human serum samples at clinically relevant levels due to the high sensitivity of electrochemical readout. The same concept may be further extended to other proteins of interest.

Discovering Panel of Autoantibodies for Early Detection of Lung Cancer Based on Focused Protein Array

Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers reveal low diagnostic performances, a panel approach is needed to provide more clues for early detection of LC. In the present research, potential TAAbs were screened in 150 serum samples by focused protein array based on 154 proteins encoded by cancer driver genes. Indirect enzyme-linked immunosorbent assay (ELISA) was used to verify and validate TAAbs in two independent datasets with 1,054 participants (310 in verification cohort, 744 in validation cohort). In both verification and validation cohorts, eight TAAbs were higher in serum of LC patients compared with normal controls. Moreover, diagnostic models were built and evaluated in the training set and the test set of validation cohort by six data mining methods. In contrast to the other five models, the decision tree (DT) model containing seven TAAbs (TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1), built in the training set, yielded the highest diagnostic value with the area under the receiver operating characteristic curve (AUC) of 0.897, the sensitivity of 94.4% and the specificity of 84.9%. The model was further assessed in the test set and exhibited an AUC of 0.838 with the sensitivity of 89.4% and the specificity of 78.2%. Interestingly, the accuracies of this model in both early and advanced stage were close to 90%, much more effective than that of single TAAbs. Protein array based on cancer driver genes is effective in screening and discovering potential TAAbs of LC. The TAAbs panel with TP53, NPM1, FGFR2, PIK3CA, GNA11, HIST1H3B, and TSC1 is excellent in early detection of LC, and they might be new target in LC immunotherapy.

Worm-Based Microfluidic Biosensor for Real-Time Assessment of the Metastatic Status

Simple Summary

We proposed a high-throughput screening and low-cost worm-based (WB) microfluidic biosensor to monitor biochemical cues related to metastasis. Caenorhabditis elegans placed in the WB biosensor chambers and exposed to samples conditioned with cancer cell clusters reflect differences in the chemotactic preference of worms. We observed a higher distribution of worms associated with samples of higher metastatic potential (p < 0.005). A chemotaxis index (CI) was defined to standardize the quantitative assessment from the WB biosensor, where increased metastatic potential was associated with higher CI levels (6.5 ± 1.37). We found that the secreted metabolite glutamate was a chemorepellent, and lower glutamate levels were associated with samples derived from more metastatic cancer cell clusters. In conclusion, WB biosensors could evaluate patient status in real time, thereby facilitating early detection of metastases and routine management.

Abstract

Background: Metastasis is a complex process that affects patient treatment and survival. To routinely monitor cancer plasticity and guide treatment strategies, it is highly desired to provide information about metastatic status in real-time. Here, we proposed a worm-based (WB) microfluidic biosensor to rapidly monitor biochemical cues related to metastasis in a well-defined environment. Compared to conventional biomarker-based methods, the WB biosensor allowed high throughput screening under low cost, requiring only visual quantification of outputs; Methods: Caenorhabditis elegans were placed in the WB biosensor and exposed to samples conditioned with cancer cell clusters. The chemotactic preference of these worms was observed under discontinuous imaging to minimize the impact on physiological activity; Results: A chemotaxis index (CI) was defined to standardize the quantitative assessment from the WB biosensor, where moderate (3.24–6.5) and high (>6.5) CI levels reflected increased metastasis risk and presence of metastasis, respectively. We demonstrated that the secreted metabolite glutamate was a chemorepellent, and larger clusters associated with increased metastatic potential also enhanced CI levels; Conclusions: Overall, this study provided a proof of concept for the WB biosensors in assessing metastasis status, with the potential to evaluate patient-derived cancer clusters for routine management.

The role of osteopontin in oral cancer: A brief review with emphasis on clinical applications

Osteopontin (OPN) is a calcium-binding glycol-phosphoprotein present in many physiologic and pathological processes. This protein can control bone cell adhesion, osteoclastic activity, and bone matrix mineralization. However, its participation in pathological processes such as atherosclerosis, sarcoidosis, tuberculosis, and cancer have been described. Some studies have shown that OPN may participate in the development and progression of oral cancer. Although the role of OPN in oral cancer is not fully understood, some studies have suggested that this protein may induce malignant phenotype of cells by activation of PI3K/AKT/mTOR pathway, which favors cell proliferation, invasion, metastasis, angiogenesis, and failure of treatment. This review discusses the possible mechanism of involvement of OPN in oral cancer and its potential clinical application in diagnosis and prognosis.

Study of the Spanish Society of Medical Oncology (SEOM) on the access to oncology drugs and predictive biomarkers in Spain

Purpose

The Spanish Society of Medical Oncology (SEOM) has carried out a study to analyse the conditions of access to oncology drugs in clinical practice in Spain. For the first time, the access of predictive biomarkers has also been analyzed.

Methods

A questionnaire was sent to 146 hospitals in Spain to collect information on the process of approval of 11 oncology drugs of an unquestionable clinical benefit and five predictive biomarkers of mandatory determination for specific treatments.

Results

Results highlight the still existing differences in the access of oncology drugs, as well as the newly identified differences in the access to predictive biomarkers between Autonomous Communities (AACC) in Spain, as well as between different hospitals within the same Autonomous Community.

Conclusions

The SEOM considers it necessary to reduce the differences identified, increase homogeneity, and improve conditions of access to oncology drugs and biomarkers, and makes proposals to address these issues.

Ancient genes can be served as pan-cancer diagnostic and prognostic biomarkers

One important challenge for cancer is efficient biomarkers monitoring its formation and developments remain greatly limited. Although the accumulated big omics data provide great opportunities to the above purpose, the biomarkers identified by the data‐driven strategy often do not work well in new datasets, which is one of the main bottlenecks limiting their utilities. Given that atavistic phenotype is generally observed in cancer cells, we have been suggested that the activity of progenitor genes in tumour could serve as an efficient cancer biomarker. For doing so, we first curated 77 progenitor genes and then proposed a quantitative score to evaluate cancer progenitorness. After applying progenitorness score to ~ 22 000 samples, 33 types of cancers from 81 datasets, this method generally performs well in the diagnosis, prognosis and therapy monitoring of cancers. This study proposed a potential pan‐cancer biomarker and revealed a significant role of atavism in the formation and development of cancers.

Nanoparticle-enabled blood tests for early detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is often detected too late to allow adequate treatments with the result that patients are condemned to sufferings and early death. Most efforts have been therefore aimed at identifying sensitive PDAC biomarkers. Although biomarkers have numerous advantages, sample size, intra-individual variability, existence of several biases and confounding variables and cost of investigation make their clinical application challenging. In recent years, nanotechnology is providing new options for early cancer detection. Among recent discoveries, the concept is emerging that the protein corona, i.e. the layer of plasma proteins that surrounds nanomaterials in bodily fluids, is personalized. In particular, the protein corona of cancer patients is significantly different from that of healthy individuals. Herein, we review this concept with a particular focus on clinical relevance. We also discuss the recently developed nanoparticle-enabled blood (NEB) tests that demonstrated to be promising in discriminating PDAC patients from healthy volunteers by global change of the nanoparticle-protein corona. We conclude with a critical discussion of research perspectives aimed at further improving the prediction ability of the test.

The ganglioside GD2 as a circulating tumor biomarker for neuroblastoma

BACKGROUND

G_D2 is a ganglioside that is ubiquitously expressed in the plasma membrane of neuroblastoma and is shed into the circulation.

PROCEDURE

G_D2 was measured with a high-pressure liquid chromatography/tandem mass spectrometry assay in serum or plasma from 40 children without cancer (controls) and in biobanked samples from 128 (73 high-risk) children with neuroblastic tumors at diagnosis, 56 children with relapsed neuroblastoma, 14 children with high-risk neuroblastoma after treatment, and 8 to 12 children each with 10 other common childhood cancers at diagnosis.

RESULTS

The C₁₈ (18 carbon fatty acid) lipoform was the predominant circulating form of G_D2 in controls and in patients with neuroblastoma. The median concentration of G_D2 in children with high-risk neuroblastoma at diagnosis was 167 nM (range, 16.1-1060 nM), which was 30-fold higher than the median concentration (5.6 nM) in controls. G_D2 was not elevated in serum from children with the differentiated neuroblastic tumors, ganglioneuroma (n = 10) and ganglioneuroblastoma-intermixed subtype (n = 12), and in children with 10 other childhood cancers. G_D2 concentrations were significantly higher in serum from children with MYCN-amplified tumors (P = 0.0088), high-risk tumors (P < 0.00001), International Neuroblastoma Staging System (INSS) stage 4 tumors (P < 0.00001), and in children who died (P = 0.034).

CONCLUSIONS

Circulating G_D2 appears to be a specific and sensitive tumor biomarker for high-risk/high-stage neuroblastoma and may prove to be clinically useful as a diagnostic or prognostic circulating tumor biomarker. G_D2 will be measured prospectively and longitudinally in children enrolled on a high-risk neuroblastoma treatment trial to assess its ability to measure response to treatment and predict survival.

FIBCD1 overexpression predicts poor prognosis in patients with hepatocellular carcinoma

Fibrinogen C domain-containing 1 (FIBCD1) is an acetyl-recognition receptor that affects the occurrence and development of certain tumors. However, the prognostic significance of FIBCD1 in hepatocellular carcinoma (HCC) remains unclear. This study aimed to explore FIBCD1 expression in HCC and to determine the prognostic value of FIBCD1 in patients with HCC. A total of 1,058 liver tissue samples with detailed and complete clinical information were collected, including 495 HCC samples. Tissue microarray immunohistochemistry analysis was used to evaluate FIBCD1 protein expression in the collected tissues. The Kaplan-Meier plotter online tool was used to investigate the association between FIBCD1 expression and prognosis of patients with HCC. Oncomine and the Gene Expression Profiling Interactive Analysis database were used for bioinformatics analysis of FIBCD1. Results showed that FIBCD1 expression was higher in HCC and was associated with tumor diameter (P=0.002), tumor number (P=0.001), tumor node metastasis stage (P<0.001), primary tumor (T; P<0.001), lymph node metastases (N; P=0.002), distant metastases (M; P=0.023), differentiation degree (P=0.003), vascular invasion (P<0.001) and liver cirrhosis (P=0.011). Patients with HCC and high FIBCD1 expression had worse overall survival than those with low FIBCD1 expression. High FIBCD1 expression (P<0.001), TNM stage (P=0.003), T (P<0.001), N (P=0.014), and vascular invasion (P<0.001) were independent prognostic factors in HCC. Hence, FIBCD1 may be a novel biomarker for prognosis evaluation of HCC.

MCP-1/MCPIP-1 Signaling Modulates the Effects of IL-1β in Renal Cell Carcinoma through ER Stress-Mediated Apoptosis

In renal cell carcinoma (RCC), interleukin (IL)-1β may be a pro-metastatic cytokine. However, we have not yet noted the clinical association between tumoral expression or serum level of IL-1β and RCC in our patient cohort. Herein, we investigate molecular mechanisms elicited by IL-1β in RCC. We found that IL-1β stimulates substantial monocyte chemoattractant protein (MCP)-1 production in RCC cells by activating NF-kB and AP-1. In our xenograft RCC model, intra-tumoral MCP-1 injection down-regulated Ki67 expression and reduced tumor size. Microarray analysis revealed that MCP-1 treatment altered protein-folding processes in RCC cells. MCP-1-treated RCC cells and xenograft tumors expressed MCP-1-induced protein (MCPIP) and molecules involved in endoplasmic reticulum (ER) stress-mediated apoptosis, namely C/EBP Homologous Protein (CHOP), protein kinase-like ER kinase (PERK), and calnexin (CNX). ER stress-mediated apoptosis in MCP-1-treated RCC cells was confirmed using Terminal deoxynucleotidyl transferase dUTP Nick-End Labeling (TUNEL) assay. Moreover, ectopic MCPIP expression increased PERK expression in Human embryonic kidney (HEK)293 cells. Our meta-analysis revealed that low MCP-1 levels reduce 1-year post-nephrectomy survival in patients with RCC. Immunohistochemistry indicated that in some RCC biopsy samples, the correlation between MCP-1 or MCPIP expression and tumor stages was inverse. Thus, MCP-1 and MCPIP potentially reduce the IL-1β-mediated oncogenic effect in RCC; our findings suggest that ER stress is a potential RCC treatment target.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Time-Resolved Digital Immunoassay for Rapid and Sensitive Quantitation of Procalcitonin with Plasmonic Imaging

Timely diagnosis of acute diseases improves treatment outcomes and saves lives, but it requires fast and precision quantification of biomarkers. Here, we report a time-resolved digital immunoassay based on plasmonic imaging of binding of single nanoparticles to biomarkers captured on a sensor surface. The real-time and high contrast of plasmonic imaging lead to fast and precise counting of the individual biomarkers over a wide dynamic range. We demonstrated the detection principle, evaluated the performance of the method using procalcitonin (PCT) as an example, and achieved a limit of detection of ∼2.8 pg/mL, dynamic range of 4.2-12500 pg/mL, for a total detection time of ∼25 min.

A Biomimetic Lipid Membrane Device Reveals the Interaction of Cancer Biomarkers with Human Serum Lipidic Moieties

A major problem for the detection of cancer biomarkers in plasma or serum is that common clinical practice does not require the patient to be in a fasting state. Considering that lipoproteins are the main population affected by food intake, the authors hypothesized that biomarkers could be embedded in lipid particles and thereby opens a new avenue for detection. Using the recently published biomarker, soluble VE-cadherin (sVE), the authors tested our hypothesis using techniques of biophysics, biochemistry and the tools of nanobiotechnology on serum samples from kidney cancer patients (n = 106). Optical density as well as contact angle measurements of serum revealed heterogeneity in the particle content of the serum samples. Isolation of the lipidic moieties by ultracentrifugation showed that sVE was detected in this compartment. Further, isolation of lipoprotein subclasses by precipitation with sodium phosphotungstate and MgCl₂ , showed that HDL carried the majority of sVE. Immunoprecipitation of sVE confirmed that it was associated with Apolipoprotein A1, a major compound of HDL. Using a biomimetic lipid bilayer membrane coupled with impedance spectroscopy the authors quantified, in real-time, that the sVE adsorbed to the lipid bilayer membrane without altering its structure. Taken together, these results show for the first time a direct interaction of a cancer biomarker with lipids. The authors anticipate these results to prompt fasting for future blood tests for large-scale studies in the biomarkers research field.

Hemostatic biomarkers in cancer progression

Malignant disease is characterized by a hemostatic imbalance, usually shifted towards a procoagulant direction, and a high incidence of thrombotic complications. The mechanisms of hemostasis that are critically involved in thrombosis are also implicated in tumor progression, angiogenesis, and metastatic spread. As there is a close relationship between cancer and the clotting system, circulating biomarkers of activation of various hemostasis compartments (i.e. coagulation, fibrinolysis, platelets, endothelium, and other blood cells) have been extensively studied to predict cancer outcomes along with predicting the thrombotic risk. In this review, we will summarize the results of published studies and will focus on ongoing research and future directions of clotting activation bioproducts as biomarkers of cancer disease and progression.

A review of the most promising biomarkers for early diagnosis and prognosis prediction of tongue squamous cell carcinoma

BACKGROUND

There is a great interest in developing biomarkers to enhance early detection and clinical management of tongue squamous cell carcinoma (TSCC). However, the developmental path towards a clinically valid biomarker remains extremely challenging. Ideally, the initial key step in moving a newly discovered biomarker towards clinical implementation is independent replication. Therefore, the focus of this review is on biomarkers that consistently showed clinical relevance in two or more publications.

METHODS

We searched PubMed database for relevant papers across different TSCC sample sources, i.e., body fluids (saliva, serum/plasma) and tissues. No restriction regarding the date of publication was applied except for immunohistochemistry (IHC); only studies published between 2010 and June 2017 were included.

RESULTS

The search strategy identified 1429 abstracts, of which 96 papers, examining 150 biomarkers, were eventually included. Of these papers, 66% were exploratory studies evaluating single or a panel of biomarkers in one publication. Ultimately, based on studies that had undergone validation for their clinical relevance in at least two independent studies, we identified 10 promising candidates, consisting of different types of molecules (IL-6, IL-8, and Prolactin in liquid samples; HIF-1α, SOX2, E-cadherin, vimentin, MALAT1, TP53, and NOTCH1 in tissue biopsies) CONCLUSIONS: Although more exploratory research is needed with newer methods to identify biomarkers for TSCC, rigorous validation of biomarkers that have already shown unbiased assessment in at least two publications should be considered a high priority. Further research on these promising biomarkers or their combination in multi-institutional studies, could provide new possibilities to develop a specific panel for early diagnosis, prognosis, and individualized treatments.

Predictive Markers of Response to Everolimus and Sunitinib in Neuroendocrine Tumors

Neuroendocrine tumors (NETs) represent a large and heterogeneous group of malignancies with various biological and clinical characteristics, depending on the site of origin and the grade of tumor proliferation. In NETs, as in other cancer types, molecularly targeted therapies have radically changed the therapeutic landscape. Recently two targeted agents, the mammalian target of rapamycin inhibitor everolimus and the tyrosine kinase inhibitor sunitinib, have both demonstrated significantly prolonged progression free survival in patients with advanced pancreatic NETs. Despite these important therapeutic developments, there are still significant limitations to the use of these agents due to the lack of accurate biomarkers for predicting tumor response and efficacy of therapy. In this review, we provide an overview of the current clinical data for the evaluation of predictive factors of response to/efficacy of everolimus and sunitinib in advanced pancreatic NETs. Surrogate indicators discussed include circulating and tissue markers, as well as non-invasive imaging techniques.

Overexpression of FIBCD1 Is Predictive of Poor Prognosis in Gastric Cancer

OBJECTIVES

Fibrinogen C domain containing 1 (FIBCD1) is a newly identified acetyl group recognition receptor. The aim of this study was to evaluate the prognostic significance of FIBCD1 in gastric cancer.

METHODS

This study included 706 samples, and the clinical data of all patients were recorded in detail. We studied messenger RNA (mRNA) and protein expression of FIBCD1 in cancerous and normal tissues by quantitative real-time polymerase chain reaction (n = 54) and tissue microarray immunohistochemistry analysis (n = 706), respectively.

RESULTS

mRNA and protein expression levels of FIBCD1 were significantly higher in gastric cancer than in normal tissues. High FIBCD1 protein level showed significant correlations with age (P = .011), TNM stage (P < .001), serum carcinoembryonic antigen (CEA) level (P = .002), and the expression of human epidermal growth factor receptor 2 (P < .001). Kaplan-Meier survival analysis revealed that patients with gastric cancer with high levels of FIBCD1 had a significantly shorter survival time than those with low expression levels. In univariate analysis, high FIBCD1 expression, older age, histologic type, differentiation, TNM stage, serum CEA, and serum CA19-9 level correlated with overall survival. Multivariate analysis suggested that FIBCD1 expression was an independent prognostic factor.

CONCLUSIONS

FIBCD1 may be a novel biomarker to evaluate the prognosis of gastric cancer.

CA 19-9 Pancreatic Tumor Marker Fluorescence Immunosensing Detection via Immobilized Carbon Quantum Dots Conjugated Gold Nanocomposite

The clinical detection of carbohydrate antigen 19-9 (CA 19-9), a tumor marker in biological samples, improves and facilitates the rapid screening and diagnosis of pancreatic cancer. A simple, low cost, fast, and green synthesis method to prepare a viable carbon quantum dots/gold (CQDs/Au) nanocomposite fluorescence immunosensing solution for the detection of CA 19-9 was reported. The present method is conducted by preparing glucose-derived CQDs using a microwave-assisted method. CQDs were employed as reducing and stabilizing agents for the preparation of a CQDs/Au nanocomposite. The immobilized anti-CA 19-9-labeled horseradish peroxidase enzyme (Ab-HRP) was anchored to the surface of a CQDs/Au nanocomposite by a peptide interaction between the carboxylic and amine active groups. The CA 19-9 antigen was trapped by another monoclonal antibody that was coated on the surface of microtiter wells. The formed sandwich capping antibody-antigen-antibody enzyme complex had tunable fluorescence properties that were detected under excitation and emission wavelengths of 420 and 530 nm. The increase in fluorescence intensities of the immunoassay sensing solution was proportional to the CA 19-9 antigen concentration in the linear range of 0.01-350 U mL-1 and had a lower detection limit of 0.007 U mL-1. The proposed CQDs/Au nanocomposite immunoassay method provides a promising tool for detecting CA 19-9 in human serum.

Theranostic-PDT with the antibody anti isoform 4 SOD mitocondrial labeled with PpIX in the lung cancer cell line A-549

BACKGROUND

In this work, a drug product composed of an IgM antibody derived from a hybridoma subclone 4C1F6D5G7B8 was prepared and further labeled with PpIX to be used in cell lines A-549 and MRC-5. The aim of this work was to evaluate the potential theranostic activity of the obtained product together with photodynamic therapy (PDT).

METHODS

The IgM antibody labeled with PpIX was used in different concentrations to perform theranostics with PDT in cell lines A-549 and MRC-5 in order to identify the specificity of IgM antibody in lung cancer cells by means of a LED-irradiation system set at 630 nm. The location of the conjugate was further determined by confocal microscopy.

RESULTS

The theranostic with conjugate Ab-PpIX in the A-549 cell lines showed fluorescence by confocal microscopy, whereas the MRC-5 cell line showed no reactivity. The PDT with the conjugate in the cell line A-549 decreased its viability 70% compared to the control. On the contrary, with the MRC-5 cell line no viability diference was shown. The confocal microscopy applied to the cell line A-549 showed that the Ab-PpIX was majorly located at the cytoplasm.

CONCLUSION

Ab-PpIX showed therapeutical potential in lung cancer cells A-549 and had no activity in non-cancerous lung cells (MCR-5).

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Serial-omics characterization of equine urine

Horse urine is easily collected and contains molecules readily measurable using mass spectrometry that can be used as biomarkers representative of health, disease or drug tampering. This study aimed at analyzing microliter levels of horse urine to purify, identify and quantify proteins, polar metabolites and non-polar lipids. Urine from a healthy 12 year old quarter horse mare on a diet of grass hay and vitamin/mineral supplements with limited pasture access was collected for serial-omics characterization. The urine was treated with methyl tert-butyl ether (MTBE) and methanol to partition into three distinct layers for protein, non-polar lipid and polar metabolite content from a single liquid-liquid extraction and was repeated two times. Each layer was analyzed by high performance liquid chromatography—high resolution tandem mass spectrometry (LC-MS/MS) to obtain protein sequence and relative protein levels as well as identify and quantify small polar metabolites and lipids. The results show 46 urine proteins, many related to normal kidney function, structural and circulatory proteins as well as 474 small polar metabolites but only 10 lipid molecules. Metabolites were mostly related to urea cycle and ammonia recycling as well as amino acid related pathways, plant diet specific molecules, etc. The few lipids represented triglycerides and phospholipids. These data show a complete mass spectrometry based—omics characterization of equine urine from a single 333 μL mid-stream urine aliquot. These omics data help serve as a baseline for healthy mare urine composition and the analyses can be used to monitor disease progression, health status, monitor drug use, etc.

HEXIM1 as a Robust Pharmacodynamic Marker for Monitoring Target Engagement of BET Family Bromodomain Inhibitors in Tumors and Surrogate Tissues

An increasing number of BET family protein inhibitors have recently entered clinical trials. It has been reported that attempts of monitoring target engagement of the BET bromodomain inhibitor OTX015 using literature-described putative pharmacodynamic markers, such as c-Myc, BRD2, etc., failed to detect pharmacodynamic marker responses in AML patients treated at active dose and those with clinical responses. Here, we report the identification and characterization of HEXIM1 and other genes as robust pharmacodynamic markers for BET inhibitors. Global gene expression profiling studies were carried out using cancer cells and surrogate tissues, such as whole blood and skin, to identify genes that are modulated by BET family proteins. Candidate markers were further characterized for concentration- and time-dependent responses to the BET inhibitor ABBV-075 in vitro and in vivo HEXIM1 was found to be the only gene that exhibited robust and consistent modulation by BET inhibitors across multiple cancer indications and surrogate tissues. Markers such as SERPINI1, ZCCHC24, and ZMYND8 were modulated by ABBV-075 and other BET inhibitors across cancer cell lines and xenograft tumors but not in blood and skin. Significant downregulation of c-Myc, a well-publicized target of BET inhibitors, was largely restricted to hematologic cancer cell lines. Incorporating well-characterized pharmacodynamic markers, such as HEXIM1 and other genes described here, can provide a better understanding of potential efficacy and toxicity associated with inhibiting BET family proteins and informs early clinical decisions on BET inhibitor development programs. Mol Cancer Ther; 16(2); 388-96. ©2016 AACR.

Detecting Tumor Metastases: The Road to Therapy Starts Here

Metastasis is the complex process by which primary tumor cells migrate and establish secondary tumors in an adjacent or distant location in the body. Early detection of metastatic disease and effective therapeutic options for targeting these detected metastases remain impediments to effectively treating patients with advanced cancers. If metastatic lesions are identified early, patients might maximally benefit from effective early therapeutic interventions. Further, monitoring patients whose primary tumors are effectively treated for potential metastatic disease onset is also highly valuable. Finally, patients with metastatic disease can be monitored for efficacy of specific therapeutic interventions through effective metastatic detection techniques. Thus, being able to detect and visualize metastatic lesions is key and provides potential to greatly improve overall patient outcomes. In order to achieve these objectives, researchers have endeavored to mechanistically define the steps involved in the metastatic process as well as ways to effectively detect metastatic progression. We presently overview various preclinical and clinical in vitro and in vivo assays developed to more efficiently detect tumor metastases, which provides the foundation for developing more effective therapies for this invariably fatal component of the cancerous process.

Analytical pitfalls and challenges in clinical metabolomics

Metabolomics-based strategies have become an integral part of modern clinical research, allowing for a better understanding of pathophysiological conditions and disease mechanisms, as well as providing innovative tools for more adequate diagnostic and prognosis approaches. Metabolomics is considered an essential tool in precision medicine, which aims for personalized prevention and tailor-made treatments. Nevertheless, multiple pitfalls may be encountered in clinical metabolomics during the entire workflow, hampering the quality of the data and, thus, the biological interpretation. This review describes the challenges underlying metabolomics-based experiments, discussing step by step the potential pitfalls of the analytical process, including study design, sample collection, storage, as well as preparation, chromatographic and electrophoretic separation, detection and data analysis. Moreover, it offers practical solutions and strategies to tackle these challenges, ensuring the generation of high-quality data.