Emerging molecular biomarkers--blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol. 2011;8:142-150. [PMID: 21364687 DOI: 10.1038/nrclinonc.2010.220]

Sub-zeptomole Detection of Biomarker Proteins Using a Microfluidic Immunoarray with Nanostructured Sensors

We report here a low-cost electrochemical immunoarray with unprecedented sensitivity in the sub-zeptomole range with up to 5 log-decades dynamic range for accurate, multiplexed protein determinations. The microfluidic array features eight carbon sensors coated with a dense layer of 5 nm gold-nanoparticles derivatized with primary antibodies. Analyte proteins are captured by secondary antibody-poly-HPR (horseradish peroxidase) bioconjugates containing 400 HRP enzyme labels, with amplified amperometric peaks developed using H2O2 activator and hydroquinone mediator. Prostate cancer biomarkers prostate specific antigen (PSA), vascular endothelial growth factor-D (VEGF-D), ETS-related gene protein (ERG), and insulin-like growth factor-1 (IGF-1) were measured simultaneously with sub-fg/mL LODs (0.08-0.22 zmol). These proteins were determined in serum of postprostatectomy cancer patients which had much lower levels than prostate cancer patients without surgery. This immunoassay protocol makes thousands of low-abundance proteins accessible to quantitative measurements down to zeptomole levels.

Detecting Endometrial Cancer by Blood Spectroscopy: A Diagnostic Cross-Sectional Study

Endometrial cancer is the sixth most common cancer in women, with a rising incidence worldwide. Current approaches for the diagnosis and screening of endometrial cancer are invasive, expensive or of moderate diagnostic accuracy, limiting their clinical utility. There is a need for cost-effective and minimally invasive approaches to facilitate the early detection and timely management of endometrial cancer. We analysed blood plasma samples in a cross-sectional diagnostic accuracy study of women with endometrial cancer (n = 342), its precursor lesion atypical hyperplasia (n = 68) and healthy controls (n = 242, total n = 652) using attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy and machine learning algorithms. We show that blood-based infrared spectroscopy has the potential to detect endometrial cancer with 87% sensitivity and 78% specificity. Its accuracy is highest for Type I endometrial cancer, the most common subtype, and for atypical hyperplasia, with sensitivities of 91% and 100%, and specificities of 81% and 88%, respectively. Our large-cohort study shows that a simple blood test could enable the early detection of endometrial cancer of all stages in symptomatic women and provide the basis of a screening tool in high-risk groups. Such a test has the potential not only to differentially diagnose endometrial cancer but also to detect its precursor lesion atypical hyperplasia—the early recognition of which may allow fertility sparing management and cancer prevention.

Zinc and Molybdenum Co-Doped BiVO4 Nanoarray for Photoelectrochemical Diethylstilbestrol Analysis Based on the Dual-Competitive System of Manganese Hexacyanoferrate Hydrate Nanocubes

This study proposes a competitive photoelectrochemical (PEC) immunosensor for detecting diethylstilbestrol (DES). The PEC sensing platform uses a zinc and molybdenum codoped BiVO₄ nanoarray ((Zn,Mo):BiVO₄) as the photoactive matrix and manganese hexacyanoferrate hydrate loading silicon dioxide layer composite nanocubes (MHCF@SiO₂ NCs) as the signal quencher. The (Zn,Mo):BiVO₄ nanoarray demonstrated brilliant PEC behavior, by virtue of the local electric field formed by the codoped Zn and Mo. This doping accelerated the electron transfer and improved the photoelectric conversion efficiency in BiVO₄ nanoarray under visible light. Furthermore, the nanoarray structure with its large surface area provided abundant binding sites for the immune response. As the MHCF@SiO₂ NCs-anti-DES competitively bonded with either free DES or bovine serum albumin conjugated DES (BSA-DES), hydrogen peroxide (H₂O₂) as electron donor was competitively consumed and meanwhile steric resistance blocked electrons transfer. For the above reasons, the photocurrent signal was reduced. Thus, the standard sample free DES was accurately detected, and the fabricated PEC immunosensor displayed an outstanding photocurrent response from 0.1 pg/mL to 50 ng/mL with a detection limit of 0.05 pg/mL. Simultaneously, the acceptable stability, selectivity, and reproducibility of the designed dual-competitive sensing platform suggest its applicability to small molecule detection.

Using Class-Specific Feature Selection for Cancer Detection with Gene Expression Profile Data of Platelets

A novel multi-classification method, which integrates the elastic net and probabilistic support vector machine, was proposed to solve this problem in cancer detection with gene expression profile data of platelets, whose problems mainly are a kind of multi-class classification problem with high dimension, small samples, and collinear data. The strategy of one-against-all (OVA) was employed to decompose the multi-classification problem into a series of binary classification problems. The elastic net was used to select class-specific features for the binary classification problems, and the probabilistic support vector machine was used to make the outputs of the binary classifiers with class-specific features comparable. Simulation data and gene expression profile data were intended to verify the effectiveness of the proposed method. Results indicate that the proposed method can automatically select class-specific features and obtain better performance of classification than that of the conventional multi-class classification methods, which are mainly based on global feature selection methods. This study indicates the proposed method is suitable for general multi-classification problems featured with high-dimension, small samples, and collinear data.

Noninvasive Detection of Colorectal Carcinomas Using Serum Protein Biomarkers

BACKGROUND

A major roadblock to reducing the mortality of colorectal cancer (CRC) is prompt detection and treatment, and a simple blood test is likely to have higher compliance than all of the current methods. The purpose of this report is to examine the utility of a mass spectrometry-based blood serum protein biomarker test for detection of CRC.

MATERIALS AND METHODS

Blood was drawn from individuals (n = 213) before colonoscopy or from patients with nonmetastatic CRC (n = 50) before surgery. Proteins were isolated from the serum of patients using targeted liquid chromatography-tandem mass spectrometry. We designed a machine-learning statistical model to assess these proteins.

RESULTS

When considered individually, over 70% of the selected biomarkers showed significance by Mann-Whitney testing for distinguishing cancer-bearing cases from cancer-free cases. Using machine-learning methods, peptides derived from epidermal growth factor receptor and leucine-rich alpha-2-glycoprotein 1 were consistently identified as highly predictive for detecting CRC from cancer-free cases. A five-marker panel consisting of leucine-rich alpha-2-glycoprotein 1, epidermal growth factor receptor, inter-alpha-trypsin inhibitor heavy-chain family member 4, hemopexin, and superoxide dismutase 3 performed the best with 70% specificity at over 89% sensitivity (area under the curve = 0.86) in the validation set. For distinguishing regional from localized cancers, cross-validation within the training set showed that a panel of four proteins consisting of CD44 molecule, GC-vitamin D-binding protein, C-reactive protein, and inter-alpha-trypsin inhibitor heavy-chain family member 3 yielded the highest performance (area under the curve = 0.75).

CONCLUSIONS

The minimally invasive blood biomarker panels identified here could serve as screening/detection alternatives for CRC in a human population and potentially useful for staging of existing cancer.

Immunity against cancer cells may promote their proliferation and metastasis

Herein we present a concept in cancer where an immune response is detrimental rather than helpful. In the cancer setting, the immune system is generally considered to be helpful in curtailing the initiation and progression of tumors. In this work we show that a patient's immune response to their tumor can, in fact, either enhance or inhibit tumor cell growth. Two closely related autoantibodies to the growth factor receptor TrkB were isolated from cancer patients' B cells. Although highly similar in sequence, one antibody was an agonist while the other was an antagonist. The agonist antibody was shown to increase breast cancer cell growth both in vitro and in vivo, whereas the antagonist antibody inhibited growth. From a mechanistic point of view, we showed that binding of the agonist antibody to the TrkB receptor was functional in that it initiated downstream signaling identical to its natural growth factor ligand, brain-derived neurotrophic factor (BDNF). Our study shows that individual autoantibodies may play a role in cancer patients.

Metabolomics and Biomarker Discovery in Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of disability and mortality worldwide. The TBI pathogenesis can induce broad pathophysiological consequences and clinical outcomes attributed to the complexity of the brain. Thus, the diagnosis and prognosis are important issues for the management of mild, moderate, and severe forms of TBI. Metabolomics of readily accessible biofluids is a promising tool for establishing more useful and reliable biomarkers of TBI than using clinical findings alone. Metabolites are an integral part of all biochemical and pathophysiological pathways. Metabolomic processes respond to the internal and external stimuli resulting in an alteration of metabolite concentrations. Current high-throughput and highly sensitive analytical tools are capable of detecting and quantifying small concentrations of metabolites, allowing one to measure metabolite alterations after a pathological event when compared to a normal state or a different pathological process. Further, these metabolic biomarkers could be used for the assessment of injury severity, discovery of mechanisms of injury, and defining structural damage in the brain in TBI. Metabolic biomarkers can also be used for the prediction of outcome, monitoring treatment response, in the assessment of or prognosis of post-injury recovery, and potentially in the use of neuroplasticity procedures. Metabolomics can also enhance our understanding of the pathophysiological mechanisms of TBI, both in primary and secondary injury. Thus, this review presents the promising application of metabolomics for the assessment of TBI as a stand-alone platform or in association with proteomics in the clinical setting.

Application of C. elegans cancer screening test for the detection of pancreatic tumor in genetically engineered mice

Pancreatic ductal adenocarcinoma (PDAC) exhibits a very early onset of metastasis. Thus, early detection and treatment are pivotal to successful eradication of pancreatic cancers. Economical and non-invasive cancer screening systems is indispensable for this purpose. Previously our group developed a novel method to detect various kinds of human cancer using nematode Caenorhabditis elegans (C. elegans) that respond to cancer odor in urine; however, whether this method is useful for non-human species remains to be understood. In this study, we examined its effectiveness in the detection of murine pancreatic tumor spontaneously generated in genetically-engineered mice. We generated pancreas-specific Kras ^G12D and/or c-Met deletion mutant mice and measured the probability of spontaneous tumor generation in these mice. The chemotactic indexes of C. elegans to the urine samples of these mutant mice were measured. As previously described, oncogenic Kras^G12D was necessary to induce pancreatic intraepithelial neoplasia in this mouse model, while c-Met mutation did not show further effect. The chemotactic analysis indicated that C. elegans avoids urine of healthy recipient mice, while they tended to be attracted to urine of mice with Kras^G12D . Our study demonstrated that C. elegans can recognize the odor of pancreatic cancer in urine of Kras^G12D model mouse, suggesting the similarity of cancer odor between species. Our result facilitates further studies on mechanism of cancer detection by C. elegans.

Exosome-like nanoplatform modified with targeting ligand improves anti-cancer and anti-inflammation effects of imperialine

Currently, most anti-cancer therapies are still haunted by serious and deleterious adverse effects. Here, we report a highly biocompatible tumor cell-targeting delivery systems utilizing exosome-like vesicles (ELVs) that delivers a low-toxicity anti-cancer agent imperialine against non-small cell lung cancer (NSCLC). First, we introduced a novel micelle-aided method to efficiently load imperialine into intact ELVs. Then, integrin α3β1-binding octapeptide cNGQGEQc was modified onto ELV platform for tumor targeting as integrin α3β1 is overexpressed on NSCLC cells. This system not only significantly improved imperialine tumor accumulation and retention, but also had extremely low systemic toxicity both in vitro and in vivo. Our discoveries offer new ways to utilize ELV more efficiently for both drug loading and targeting. The solid pharmacokinetics improvement and extraordinary safety of this system also highlight possibilities of alternative long course cancer therapies using similar strategies.

Distinct methylation levels of mature microRNAs in gastrointestinal cancers

The biological significance of micro (mi)RNAs has traditionally been evaluated according to their RNA expression levels based on the assumption that miRNAs recognize and regulate their targets in an unvarying fashion. Here we show that a fraction of mature miRNAs including miR-17-5p, -21-5p, and -200c-3p and let-7a-5p harbor methyl marks that potentially alter their stability and target recognition. Importantly, methylation of these miRNAs was significantly increased in cancer tissues as compared to paired normal tissues. Furthermore, miR-17-5p methylation level in serum samples distinguished early pancreatic cancer patients from healthy controls with extremely high sensitivity and specificity. These findings provide a basis for diagnostic strategies for early-stage cancer and add a dimension to our understanding of miRNA biology.

In cancer it is assumed that microRNAs recognise and regulate their targets uniformly. Here, the authors show that in gastrointestinal cancers methylation of microRNAs may impact their stability, and that levels of microRNA methylation are distinct in pancreatic cancer patients compared to healthy controls with potential diagnostic implications.

Immunotherapy a New Hope for Cancer Treatment: A Review

Cancer is a major burden of disease worldwide with considerable impact on society. The tide of immunotherapy has finally changed after decades of disappointing results and has become a clinically validated treatment for many cancers. Immunotherapy takes many forms in cancer treatment, including the adoptive transfer of ex vivo activated T cells, oncolytic viruses, natural killer cells, cancer vaccines and administration of antibodies or recombinant proteins that either costimulate cells or block the so-called immune checkpoint pathways. Recently, cancer immunotherapy has received a high degree of attention, which mainly contains the treatments for programmed death ligand 1 (PD-L1), programmed death 1 (PD-1), chimeric antigen receptors (CARs) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4). Here, this paper reviewed the current understandings of the main strategies in cancer immunotherapy (adoptive cellular immunotherapy, immune checkpoint blockade, oncolytic viruses and cancer vaccines) and discuss the progress in the synergistic design of immune-targeting combination therapies.

Analysis of circulating non-coding RNAs in a non-invasive and cost-effective manner

Non-coding RNAs (ncRNAs) participate in regulation of gene expression, and are highly relevant to pathological development. They are found to be stably present in diverse body fluids, including those in the circulatory system, which can be sampled non-invasively for clinical tests. Thus, circulating ncRNAs have great potential to be disease biomarkers. However, tremendous efforts are desired to discover and utilize ncRNAs as biomarkers in clinical diagnosis, calling for technological advancement in analysis of circulating ncRNAs in biospecimens. Hence, this review summarizes the recent developments in this area, highlighting the works devoted to cancer diagnosis and prognosis. Three main directions are focused: 1) Extraction and purification of ncRNAs from body fluids; 2) Quantification of the purified circulating ncRNAs; and 3) Microfluidic platforms for integration of both steps to enable point-of-care diagnostics. These technologies have laid a solid foundation to move forward the applications of circulating ncRNAs in disease diagnosis and cure.

Plasma cell-free DNA integrity: a potential biomarker to monitor the response of breast cancer to neoadjuvant chemotherapy

Background

Although the clinical significance of neoadjuvant chemotherapy (NACT) is widely recognized, there is still no effective means to monitor the therapeutic response in real time. The present study aimed to investigate the significance of the cell-free DNA (cfDNA) concentration and integrity (cfDI) to monitor the response of breast cancer to NACT.

Methods

Twenty-nine patients with breast cancer receiving NACT were included in this study. Patients’ peripheral blood was drawn before, in the mid-term, and at the end of chemotherapy. The cfDNA concentration and cfDI were assessed using absolute quantitative PCR.

Results

The results showed that the cfDNA concentration and cfDI pre-NACT were not obviously correlated with the patients’ clinical characteristics. The mean cfDI value increased significantly when the patients received NACT (P<0.05), and an increasing cfDI was associated with tumor shrinkage and reduced Ki67 levels (P<0.05). In addition, the cfDI after NACT was inversely correlated with the number of metastatic lymph nodes, and the cfDI value of patients with a pathologically complete response was significantly higher than that of patients with distant metastasis after surgery.

Conclusions

This study suggested that cfDI could be used as an indicator to monitor the therapeutic response to NACT; however, more research is needed to confirm this conclusion.

Plasma C-MYC level manifesting as an indicator in progression of breast cancer

Aim: To investigate whether plasma C-MYC level could be an indicator in clinical progression of breast cancer. Materials & methods: Plasma level of C-MYC expression was detected by quantitative real time PCR and the level of c-myc protein in breast cancer tissues was detected by immunohistochemistry. The expression level of C-MYC mRNA in supernatant of cancer cells culture was measured compared with the nonbreast cancer cells. Results: Plasma C-MYC level was significantly higher in patients with breast cancer than that in the controls, which associated with clinical stages, lymph node status, etc. Receiver operating characteristic curve analysis showed the sensitivity and specificity of plasma C-MYC level for diagnosis of breast cancer were 63.6 and 81.8%, respectively. The expression of c-myc protein in breast cancer tissues was associated with plasma C-MYC level, even C-MYC level in supernatant of cancer cells was elevated. Conclusion: Plasma C-MYC level might be a potential indicator in progression of breast cancer.

Predictive value of the serum RASSF10 promoter methylation status in gastric cancer

Background

This study aimed to investigate whether the detection of methylation in the promoter of the Ras association domain family 10 gene (RASSF10) in the serum of patients with gastric cancer (GC) by methylation-specific PCR (MSP) can be used as a diagnostic and prognostic indicator of GC.

Methods

We used MSP to examine RASSF10 methylation levels in the serum and/or tumor samples from 100 GC patients, 50 patients with chronic atrophic gastritis (CAG), and 45 healthy controls (HC). We also analyzed clinicopathological and follow-up data.

Results

Our results showed that the rate of serum RASFF10 promoter methylation among patients with GC (49/100) was higher than in those with CAG (1/50) or HC (0/45). Moreover, the RASSF10 methylation status was consistent between serum and tumor tissues. GC patients with serum RASSF10 promoter methylation had significantly shorter overall survival and disease-free survival times than GC patients without serum RASSF10 promoter methylation. Multivariable Cox regression analysis showed that serum RASSF10 promoter methylation and lymph node metastasis both correlated with reduced survival in GC patients.

Conclusions

Detection of the serum RASSF10 methylation status by MSP is feasible as a diagnostic and prognostic indicator of GC.

The Advent of Salivary Breast Cancer Biomarker Detection Using Affinity Sensors

Breast Cancer is one of the world's most notorious diseases affecting two million women in 2018 worldwide. It is a highly heterogeneous disease, making it difficult to treat. However, its linear progression makes it a candidate for early screening programs, and the earlier its detection the higher the chance of recovery. However, one key hurdle for breast cancer screening is the fact that most screening techniques are expensive, time-consuming, and cumbersome, making them impractical for use in several parts of the world. One current trend in breast cancer detection has pointed to a possible solution, the use of salivary breast cancer biomarkers. Saliva is an attractive medium for diagnosis because it is readily available in large quantities, easy to obtain at low cost, and contains all the biomarkers present in blood, albeit in lower quantities. Affinity sensors are devices that detect molecules through their interactions with biological recognition molecules. Their low cost, high sensitivity, and selectivity, as well as rapid detection time make them an attractive alternative to traditional means of detection. In this review article, we discuss the current status of breast cancer diagnosis, its salivary biomarkers, as well as the current trends in the development of affinity sensors for their detection.

Power-free polydimethylsiloxane femtoliter-sized arrays for bead-based digital immunoassays

A novel microfluidic chip employing power-free polydimethylsiloxane (PDMS) femtoliter-sized arrays was developed for the detection of low concentrations of protein biomakers by isolating individual paramagnetic beads in single wells. Arrays of femtoliter-sized wells were fabricated with PDMS using well-developed molding techniques. Paramagnetic beads were functionalized with specific antibodies to capture the antigens. These antigens were labeled with enzymes via conventional multistep immunosandwich approach. After suspending in aqueous solutions of enzyme substrate, the solutions were delivered to the arrays using a conventional micropipette. The aqueous solutions were introduced into the microwells by capillarity and the beads were loaded into microwells by gravity. A fluorocarbon oil was then flowed into the chip to remove excess beads from the surface of the array and meanwhile isolated the femtoliter-sized wells. All processes were achieved by conventional micropipette, without external pumping systems and valves. Finally, the arrays were imaged using standard fluorescence imaging after incubation 30 min for digital counting enzyme molecules. It was demonstrated that the chip platform possessed the performance of digital counting with a linear dynamic range from 1 aM to 1 fM for the detection of biotinylated β-galactosidase (BβG), achieving a limit of detection (LOD) of 930 zM. Using this chip, a digital immunoassay to detect Tumor Necrosis Factor α (TNF- α) was developed. Since the chip fabrication is low-cost and circumvents the surface modification, we expect it can become a new chip-based digital immunoassay platform for ultrasensitive diagnostic of biomarkers.

The contribution and perspectives of proteomics to uncover ovarian cancer tumor markers

Despite all the advances in understanding the mechanisms involved in ovarian cancer (OC) development, many aspects still need to be unraveled and understood. Tumor markers (TMs) are of special interest in this disease. Some aspects of clinical management of OC might be improved by the use of validated TMs, such as differentiating subtypes, defining the most appropriate treatment, monitoring the course of the disease, or predicting clinical outcome. The Food and Drug Administration (FDA) has approved a few TMs for OC: CA125 (cancer antigen 125; monitoring), HE4 (Human epididymis protein; monitoring), ROMA (Risk Of Malignancy Algorithm; HE4+CA125; prediction of malignancy) and OVA1 (Vermillion's first-generation Multivariate Index Assay [MIA]; prediction of malignancy). Proteomics can help advance the research in the field of TMs for OC. A variety of biological materials are being used in proteomic analysis, among them tumor tissues, interstitial fluids, tumor fluids, ascites, plasma, and ovarian cancer cell lines. However, the discovery and validation of new TMs for OC is still very challenging. The enormous heterogeneity of histological types of samples and the individual variability of patients (lifestyle, comorbidities, drug use, and family history) are difficult to overcome in research protocols. In this work, we sought to gather relevant information regarding TMs, OC, biological samples for proteomic analysis, as well as markers and algorithms approved by the FDA for use in clinical routine.

Gene expression analysis in peripheral blood cells of patients with hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC): identification of NRF2 pathway activation

Hereditary leiomyomatosis and renal cell cancer syndrome (HLRCC) is a very rare disease that is inherited in an autosomal dominant manner. Affected patients may develop from cutaneous and uterine leiomyomas to type 2 papillary renal cell carcinoma (Schmidt and Linehan, Int J Nephrol Renovasc Dis 7:253-260, 2014). HLRCC is caused by germline mutations in the FH gene, which produces the fumarate hydratase protein that participates in the tricarboxylic acid cycle during the conversion of fumarate to malate. In FH-deficient cells, high concentrations of fumarate lead to a series of intricate events, which seem to be responsible for the malignant transformation (Yang et al., J Clin Invest 123(9):3652-3658, 2013) (Bardella et al., J Pathol 225(1):4-11, 2011). Among these events, one that is gaining attention is the pathological activation of the nuclear factor erythroid 2-related factor 2 (NRF2) pathway, which has been found in several types of cancer and is implicated in the expression of genes associated with antioxidant responses (Linehan and Rouault, Clin Cancer Res 19(13):3345-3352, 2013). In this article, we present the results of a gene expression analysis performed on peripheral blood cells from patients with HLRCC syndrome, where upregulation of numerous NRF2 targets and the differential expression of two key genes, Jun dimerization protein 2 (JDP2) and Phosphoglycerate mutase family member 5 (PGAM5), which are involved in the control of this pathway, was observed.

Serum miR-16 as a potential biomarker for human cancer diagnosis: results from a large-scale population

BACKGROUND

Cancer is a serious public health problem worldwide, and difficulty in early diagnosis has been the chief obstacle to improve the prognosis of patients. Recently, microRNAs (miRNAs) were widely studied to be potential biomarkers for cancer detection. miR-16 is a prevalent but sophisticated one. In the current study, we aimed to assess the diagnostic value of serum miR-16 for cancer detection.

METHODS

A total of 1458 cancer patients, containing ten types of cancers, and 1457 non-cancer controls were recruited in this study. qRT-PCR was used for the amplification of miRNAs. In addition, a meta-analysis of reported studies was performed to confirm our findings systematically.

RESULTS

Consequently, miR-16 was down-regulated in ESCC, GCA and GNCA patients compared with NCs (all P < 0.001), while up-regulated in PDAC patients (P = 0.001), LAC, LSCC and EEC patients (all P < 0.001). But no significant differences were observed in CRC, EOC and TC patients when compared to NCs (P = 0.747, 0.235 and 0.268, respectively). The areas under the receiver operating characteristic (ROC) curve of miR-16 in GCA, ESCC, LAC, LSCC, GNCA, PDAC and EEC were 0.881, 0.780, 0.757, 0.693, 0.602, 0.614 and 0.681, respectively. Results of meta-analysis showed that miR-16 achieved an overall pooled sensitivity of 0.72, specificity of 0.79, and AUC of 0.85, suggesting that miR-16 was a promising biomarker in cancer detection.

CONCLUSIONS

We provided a comprehensive view of the diagnostic value of serum miR-16 in cancer diagnosis, and confirmed that circulating miR-16 could play an important role in cancer detection.

Glycosylation Profiling of Tumor Marker in Plasma Using Bead-Based Immunoassay

As one of the most important posttranslational modifications, glycosylation plays critical roles in protein folding, trafficking, cell differentiation, immune recognition, etc. The alteration of glycosylation is closely associated with the pathological processes during and after caner development, and thus holds great value in cancer detection. In this chapter, we describe a protocol on the glycosylation profiling of tumor marker in plasma using bead-based immunoassay with CA125 as a model, including bead coupling, coupling control, glycosylation assay, as well as the plasma screening for breast cancer patients. This protocol can be used to profile the glycosylation of protein markers in clinical plasma or serum samples for different human cancers.

Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial

Background

Current guidelines for lung cancer screening increased a positive scan threshold to a 6 mm longest diameter. We extracted radiomic features from baseline and follow‐up screens and performed size‐specific analyses to predict lung cancer incidence using three nodule size classes (<6 mm [small], 6‐16 mm [intermediate], and ≥16 mm [large]).

Methods

We extracted 219 features from baseline (T0) nodules and 219 delta features which are the change from T0 to first follow‐up (T1). Nodules were identified for 160 incidence cases diagnosed with lung cancer at T1 or second follow‐up screen (T2) and for 307 nodule‐positive controls that had three consecutive positive screens not diagnosed as lung cancer. The cases and controls were split into training and test cohorts; classifier models were used to identify the most predictive features.

Results

The final models revealed modest improvements for baseline and delta features when compared to only baseline features. The AUROCs for small‐ and intermediate‐sized nodules were 0.83 (95% CI 0.76‐0.90) and 0.76 (95% CI 0.71‐0.81) for baseline‐only radiomic features, respectively, and 0.84 (95% CI 0.77‐0.90) and 0.84 (95% CI 0.80‐0.88) for baseline and delta features, respectively. When intermediate and large nodules were combined, the AUROC for baseline‐only features was 0.80 (95% CI 0.76‐0.84) compared with 0.86 (95% CI 0.83‐0.89) for baseline and delta features.

Conclusions

We found modest improvements in predicting lung cancer incidence by combining baseline and delta radiomics. Radiomics could be used to improve current size‐based screening guidelines.

A Microwell-Assisted Multiaptamer Immunomagnetic Platform for Capture and Genetic Analysis of Circulating Tumor Cells

Detection of circulating tumor cells (CTCs) in peripheral blood is of paramount significance for cancer diagnosis, progress evaluation, and individualized therapy. However, the rareness and heterogeneity of CTCs introduces significant challenges in the capture of cancer cells as well as downstream genetic analysis. In this work, a microwell-assisted multiaptamer immunomagnetic platform (MMAIP) is proposed for highly efficient capture of CTCs with minimum influence of heterogeneity. Assisted by a microwell chip, the purity of CTCs is greatly improved, thus meeting the requirement of downstream gene analysis. This is, as far as is known, the first aptamer based platform enabling mutation analysis of the captured CTCs from cancer patients, which will contribute to the practical application of aptamers in clinics.

Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay

BACKGROUND

The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer.

OBJECTIVE

To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year.

METHODS

Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4-30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran's Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort.

RESULTS

Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%.

CONCLUSION

The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk.

Droplet microfluidics for high-sensitivity and high-throughput detection and screening of disease biomarkers

Biomarkers are nucleic acids, proteins, single cells, or small molecules in human tissues or biological fluids whose reliable detection can be used to confirm or predict disease and disease states. Sensitive detection of biomarkers is therefore critical in a variety of applications including disease diagnostics, therapeutics, and drug screening. Unfortunately for many diseases, low abundance of biomarkers in human samples and low sample volumes render standard benchtop platforms like 96-well plates ineffective for reliable detection and screening. Discretization of bulk samples into a large number of small volumes (fL-nL) via droplet microfluidic technology offers a promising solution for high-sensitivity and high-throughput detection and screening of biomarkers. Several microfluidic strategies exist for high-throughput biomarker digitization into droplets, and these strategies have been utilized by numerous droplet platforms for nucleic acid, protein, and single-cell detection and screening. While the potential of droplet-based platforms has led to burgeoning interest in droplets, seamless integration of sample preparation technologies and automation of platforms from biological sample to answer remain critical components that can render these platforms useful in the clinical setting in the near future. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices Therapeutic Approaches and Drug Discovery > Emerging Technologies Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease.

A blood biomarker for monitoring response to anti-EGFR therapy

BACKGROUND AND OBJECTIVE

To monitor therapies targeted to epidermal growth factor receptors (EGFR) in non-small cell lung cancer (NSCLC), we investigated Peroxiredoxin 6 (PRDX6) as a biomarker of response to anti-EGFR agents.

METHODS

We studied cells that are sensitive (H3255, HCC827) or resistant (H1975, H460) to gefitinib. PRDX6 was examined with either gefitinib or vehicle treatment using enzyme-linked immunosorbent assays. We created xenograft models from one sensitive (HCC827) and one resistant cell line (H1975) and monitored serum PRDX6 levels during treatment.

RESULTS

PRDX6 levels in cell media from sensitive cell lines increased significantly after gefitinib treatment vs. vehicle, whereas there was no significant difference for resistant lines. PRDX6 accumulation over time correlated positively with gefitinib sensitivity. Serum PRDX6 levels in gefitinib-sensitive xenograft models increased markedly during the first 24 hours of treatment and then decreased dramatically during the following 48 hours. Differences in serum PRDX6 levels between vehicle and gefitinib-treated animals could not be explained by differences in tumor burden.

CONCLUSIONS

Our results show that changes in serum PRDX6 during the course of gefitinib treatment of xenograft models provide insight into tumor response and such an approach offers several advantages over imaging-based strategies for monitoring response to anti-EGFR agents.

Parallel profiling of cancer cells and proteins using a graphene oxide functionalized ac-EHD SERS immunoassay

Circulating biomarkers have emerged as promising non-invasive, real-time surrogates for cancer diagnosis, prognosis and monitoring of the therapeutic response. Current bio-sensing techniques mostly involve detection of either circulating cells or proteins which are inadequate in unfolding complex pathologic transformations. Herein, we report parallel detection of cellular and molecular markers (protein) for cancer using a multiplex platform featuring (i) graphene oxide (GO) functionalization that increases the active surface area and more importantly reduces the functionalization steps for rapid detection, (ii) alternating-current electrohydrodynamic (ac-EHD) fluid flow that provides delicate micro-mixing to enhance target-sensor interactions thereby minimizing non-specific binding and (iii) surface enhanced Raman scattering (SERS) for multiplex detection. We find that our platform possesses high sensitivity for detecting both proteins and cells. More importantly, this platform not only detects the cancer cells but also can simultaneously monitor the heterogeneous expression of cell surface proteins which could be clinically useful to determine effective patient therapy. We demonstrate the specific and sensitive detection of breast cancer cells from a mixture of non-target cells and report the heterogeneous expression of human epidermal growth factor receptor 2 (HER2) proteins on the individual cancer cell surface. Concurrently, we detect as low as 100 fg mL^-1 HER2 and Mucin 16 proteins spiked in blood serum.

Plasma ALU-247, ALU-115, and cfDNA Integrity as Diagnostic and Prognostic Biomarkers for Breast Cancer

Diagnosis of breast cancer (BC) by using sensitive and specific biomarkers is necessary. Cell-free DNA is a candidate biomarker in various cancers. Contrasting, shorted uniformed DNA released from apoptotic non-diseased cells, DNA released from malignant cells varies in size. DNA integrity is a ratio between 247 and 115 bp. So, this study was designed to investigate the role of plasma ALU-247, ALU-115, and DNA integrity as possible diagnostic and prognostic markers in BC patients as compared to plasma CA15.3. The concentrations of selected parameters were determined for 40 patients with BC (2 stage I, 31 stage II, 2 stage III, and 5 stage IV) and 10 healthy volunteers by quantitative real-time PCR and ELISA. The sensitivities of ALU-247, ALU-115, and cfDI as biomarkers for BC were evaluated and compared with CA15.3. Also, disease-free survival and overall survival were estimated. For all parameters, the concentrations in patients were significantly higher than in the control group; association with tumor stage and high sensitivities was observed. The studied parameters failed to predict survival or relapse in BC patients before surgery. Plasma ALU-247, ALU-115, and DNA integrity may prove to have clinical utility in BC diagnosis. Elevated preoperative CA15.3 was shown to be directly related to tumor burden, which may improve its diagnostic capability. Those selected parameters could be effectively used together with plasma CA15.3 for BC screening at early stage. Furthermore, both ALU-247 and ALU-115 seem to be preoperative prognostic markers for BC.

Target-activatable gold nanoparticle-based aptasensing for protein biomarkers using stimuli-responsive aggregation

An ultrasensitive and selective light-scattering (LS) aptasensor for prostate specific antigen (PSA) was developed based on bifunctional DNA decorated gold nanoparticles (Au NPs) by use of target stimuli-responsive assembly. Both binding sequence poly adenine (poly(dA), Domain I) and the recognition sequence aptamer (Domain II) of bifunctional ssDNA were in favor of the sensitivity for the fabricated light-scattering aptasensor due to modulated the lateral spacing of DNA on Au NPs surface and possessed strong antigen binding affinity, respectively. And they efficiently promoted the Au NPs aggregation and activated the signal of light-scattering of aptasensor. The formation of aptamer-PSA complex induced conformational transformation of the aptamer on the surface of the Au NPs-based aptasensor and then tuned the interparticle distance of gold nanoparticle assemblies. The larger scattering particles, the higher light-scattering intensity. Target stimuli-responsive aggregation behavior of Au NPs lit up the light-scattering signal of aptasensor. As the concentration of PSA increased, the light-scattering intensity gradually enhanced. The aptasensor response for PSA detection was in the linear range from 0.01 ng/mL to 20 ng/mL with the detection limit of 2 pg/mL. The thiol-free Au NPs-based light-scattering aptasensor has exceptional performances with ultrasensitivity and high selectivity besides the advantage of economic and facile fabrication. Moreover, the proposed target-activated aptasensor was applied for the detection of PSA in serum samples and demonstrated great potential in clinical applications.

Screening for Multiple Autoantibodies in Plasma of Patients with Breast Cancer

BACKGROUND/AIM

Autoantibodies have potential as circulating biomarkers for early cancer detection. This study aimed to screen for known autoantibodies in human plasma using an Autoantibody Profiling System (APS) and quantify the levels in plasma of donors with/without breast cancer.

MATERIALS AND METHODS

Plasma from nine female donors diagnosed with breast cancer (test group) and nine matched donors with no personal history of cancer (reference group) were screened with an APS containing probes for 30 autoantibodies. Autoantibody levels ≥1.5 times the mean concentration of the group were considered elevated, and test/reference ratios ≥1.3 were considered higher in the test group compared to the reference group.

RESULTS

Twenty percent of the probes detected elevated levels of autoantibodies against proteins involved in different cancer mechanisms. Amongst these, the levels of autoantibodies against interleukin 29 (IL29), osteoprotegerin (OPG), survivin (SUR), growth hormone (GRH) and resistin (RES) were significantly higher in the cancer group compared to the reference group (p<0.05), whereas the level of autoantibody against cytotoxic T-lymphocyte associated antigen-4 (CTLA4) was not significantly different between the two groups (p=0.38).

CONCLUSION

Disease-relevant autoantibodies were detected in the plasma of patients with breast cancer and donors without breast cancer. This means that identifying the type and level of autoantibodies in samples will be important in determining their significance in the disease process. A microtiter plate-based array system could be a fast and inexpensive screening method for identifying and quantifying autoantibodies in human plasma.

Recurrence-Associated Long Non-coding RNA Signature for Determining the Risk of Recurrence in Patients with Colon Cancer

Patients with colon cancer are often faced a high risk of disease recurrence within 5 years of treatment that is the major cause of cancer mortality. Reliable molecular markers were required to improve the most effective personalized therapy. Here, we identified a recurrence-associated six-lncRNA (long non-coding RNA) signature (LINC0184, AC105243.1, LOC101928168, ILF3-AS1, MIR31HG, and AC006329.1) that can effectively distinguish between high and low risk of cancer recurrence from 389 patients of a discovery dataset, and validated its robust performance in four independent datasets comprising a total of 906 colon cancer patients. We found that the six-lncRNA signature was an independent predictive factor of disease recurrence in multivariate analysis and was superior to the performance of clinical factors and known gene signature. Furthermore, in silico functional analysis showed that the six-lncRNA-signature-associated coding genes are significantly enriched in proliferation and angiogenesis, cell death, as well as critical cancer pathways that could play important roles in colon cancer recurrence. Together, the six-lncRNA signature holds great potential for recurrence risk assessment and personalized management of colon cancer patients.

Automated 3D-Printed Microfluidic Array for Rapid Nanomaterial-Enhanced Detection of Multiple Proteins

We report here the fabrication and validation of a novel 3D-printed, automated immunoarray to detect multiple proteins with ultralow detection limits. This low cost, miniature immunoarray employs electrochemiluminescent (ECL) detection measured with a CCD camera and employs touch-screen control of a micropump to facilitate automated use. The miniaturized array features prefilled reservoirs to deliver sample and reagents to a paper-thin pyrolytic graphite microwell detection chip to complete sandwich immunoassays. The detection chip achieves high sensitivity by using single-wall carbon nanotube-antibody conjugates in the microwells and employing massively labeled antibody-decorated RuBPY-silica nanoparticles to generate ECL. The total cost of an array is $0.65, and an eight-protein assay can be done in duplicate for $0.14 per protein with limits of detection (LOD) as low as 78-110 fg mL-1 in diluted serum. The electronic control system costs $210 in components. Utility of the automated immunoarray was demonstrated by detecting an eight-protein prostate cancer biomarker panel in human serum samples in 25 min. The system is well suited to future clinical and point-of-care diagnostic testing and could be used in resource-limited environments.

Multiplexed microRNA Expression Profiling by Combined Asymmetric PCR and Label-Free Detection using Silicon Photonic Sensor Arrays

Analysis methods based upon the quantitative, real-time polymerase chain reaction are extremely powerful; however, they face intrinsic limitations in terms of target multiplexing. In contrast, silicon photonic microring resonators represent a modularly multiplexable sensor array technology that is well-suited to the analysis of targeted biomarker panels. In this manuscript we employ an asymmetric polymerase chain reaction approach to selectively amplify copies of cDNAs generated from targeted miRNAs before multiplexed, label-free quantitation through hybridization to microring resonator arrays pre-functionalized with capture sequences. This method, which shows applicability to low input amounts and a large dynamic range, was demonstrated for the simultaneous detection of eight microRNA targets from twenty primary brain tumor samples with expression profiles in good agreement with literature precedent.

Simple and label-free pathogen enrichment via homobifunctional imidoesters using a microfluidic (SLIM) system for ultrasensitive pathogen detection in various clinical specimens

Diseases caused by pathogenic microorganisms including bacteria and viruses can cause serious medical issues including death and result in huge economic losses. Despite the myriad of recent advances in the rapid and accurate detection of pathogens, large volume clinical samples with a low concentration of pathogens continue to present challenges for diagnosis and surveillance. We here report a simple and label-free approach via homobifunctional imidoesters (HIs) with a microfluidic platform (SLIM) to efficiently enrich and extract pathogens at low concentrations from clinical samples. The SLIM system consists of an assembled double microfluidic chip for streamlining large volume processing and HIs for capturing pathogens and isolating nucleic acids by both electrostatic and covalent interaction without a chaotropic detergent or bulky instruments. The SLIM system significantly increases the enrichment and extraction rate of pathogens (up to 80% at 10 CFU (colony forming unit) in a 1 mL volume within 50 min). We demonstrated its clinical utility in large sample volumes from 46 clinical specimens including environmental swabs, saliva, and blood plasma. The SLIM system showed higher sensitivity with these samples and could detect pathogens that were below the threshold of detection with other methods. Finally, by combining our SLIM approach with an isothermal optical sensor, pathogens could be detected at a very high sensitivity in blood plasma samples within 80 min via enrichment, extraction and detection steps. Our SLIM system thus provides a simple, reliable, cost-effective and ultrasensitive pathogen diagnosis platform for use with large volume clinical samples and would thus have significant utility for various infectious diseases.

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SLIM system significantly increases the enrichment and extraction rate of pathogens.

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Demonstrated its clinical utility in large sample volumes from 46 clinical specimens.

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A simple, reliable, cost-effective and ultrasensitive pathogen diagnosis platform.

IDH2 is a novel diagnostic and prognostic serum biomarker for non-small-cell lung cancer

Lung cancer is the most common leading cause of cancer‐related death worldwide. Late diagnosis contributes to a high mortality rate and poor survival of this cancer. In our previous study, we found that IDH2 polymorphism rs11540478 is a risk factor for lung cancer. Here, we examined IDH2 protein expression in culture medium in which two non‐small‐cell lung cancer (NSCLC) cell lines, H460 and A549, were growing. We found that the IDH2 protein was elevated in the culture supernatant fraction in a time‐ and cell number‐dependent manner. Next, we used ELISA methods to examine IDH2 protein level in serum from patients with NSCLC and healthy controls. We found that IDH2 protein levels in serum could distinguish NSCLC patients from healthy controls with an AUC (area under the curve) of 0.83 (95% confidence interval = 0.79–0.88). The IDH2 level was decreased in serum from NSCLC postsurgical patients compared with the paired presurgical serum. High serum IDH2 levels appear to correlate with poor survival in patients with NSCLC. These results suggest that IDH2 levels in the serum could be a new effective biomarker for the diagnosis and prognosis of NSCLC.

Ultrasensitive and specific fluorescence detection of a cancer biomarker via nanomolar binding to a guanidinium-modified calixarene

We designed a water-soluble guanidinium-modified calix[5]arene to target lysophosphatidic acid (LPA), an ideal biomarker for early diagnosis of ovarian and other gynecologic cancers, achieving binding on the nanomolar level. An indicator displacement assay, coupled with differential sensing, enabled ultrasensitive and specific detection of LPA. Moreover, we show that using a calibration line, the LPA concentration in untreated serum can be quantified in the biologically relevant low μM range with a detection limit of 1.7 μM. The reported approach is feasible for diagnosing ovarian and other gynecologic cancers, particularly at their early stages.

Prognostic and diagnostic potential of isocitrate dehydrogenase 1 in esophageal squamous cell carcinoma

We aimed to investigate the pattern of expression and clinical significance of isocitrate dehydrogenase 1(IDH1) in esophageal squamous cell carcinoma (ESCC). The IDH1 expression was determined by quantitative real-time polymerase chain reaction, immunohistochemistry, and Western blot analysis using 38 pairs of frozen tissues. Enzyme-linked immunosorbent assay was employed to measure 67 pairs of serum samples from patients and their controls to evaluate its diagnostic value. Immunohistochemistry analysis of 111 formalin-fixed paraffin embedded tissue samples was conducted for explaining its prognostic value. After shRNA transfection, CCK8 and clonal efficiency assays were carried on for verifying the function of IDH1 in vitro. Increased expression at mRNA (P < 0.001) and protein levels (immunohistochemistry: P < 0.001, Western blot analysis: P < 0.001) were observed. Similarly, the IDH1 expression in serum from patients with ESCC was significantly upregulated relative to that from healthy controls (P < 0.001). Kaplan–Meier curve indicated that IDH1 upregulation predicted worse overall survival (OS) and progression-free survival (PFS). Univariate and multivariate analyses identified IDH1 expression as an independent prognostic factor for OS and PFS. Furthermore, OD450 values and colony numbers were decreased in sh-IDH1 groups (all P < 0.05). In conclusion, IDH1 is upregulated in patients with ESCC and can be used as a good potential biomarker for diagnosis and prognosis.

Quantification of altered tissue turnover in a liquid biopsy: a proposed precision medicine tool to assess chronic inflammation and desmoplasia associated with a pro-cancerous niche and response to immuno-therapeutic anti-tumor modalities

Immuno-therapy has begun to revolutionize cancer treatment. However, despite the significant progress achieved in regard to the duration of clinical benefits, a substantial number of patients do not respond to these therapies. To improve the outcome of patients receiving immuno-therapy, there is a need for novel biomarkers that can predict and monitor treatment. Tumor microenvironment alterations, more specifically the state of chronic inflammation and desmoplasia (tumor fibrosis), are important factors to consider in this context. Here, we discuss the potential for quantification of altered tissue turnover in a liquid biopsy as a proposed precision medicine tool to assess chronic inflammation and desmoplasia in the immuno-oncology (IO) setting. We highlight the need for novel non-invasive biomarkers in IO and the importance of addressing tumor microenvironment alterations. We focus on desmoplasia and extracellular matrix (ECM) remodeling, and how the composition of the ECM defines T-cell permissiveness in the tumor microenvironment and opens up the possibility for associated liquid biopsy biomarkers. Moreover, we address the importance of the assessment of chronic inflammation, primarily macrophage activity, in a liquid biopsy.

Potential Role of MicroRNA-375 as Biomarker in Human Cancers Detection: A Meta-Analysis

The association between circulating microRNA-375 (miR-375) expression and cancers has been studied; however, the results are inconsistent. We searched PubMed, Embase, and Web of Science for studies concerning the diagnostic value of miR-375 for cancer. The bivariate meta-analysis model was employed to summarize sensitivity, specificity, and diagnostic odds ratio (DOR) for miR-375 in the diagnosis of cancer. Summary receiver operating characteristic (SROC) curve analysis and the area under the curve (AUC) were also used to check the overall test performance. A total of 645 cancer patients and 421 cancer-free individuals from 12 studies were contained in this meta-analysis. The summary estimates revealed that the pooled sensitivity was 78% (95% confidence interval (CI): 64%-87%), the specificity was 74% (95% CI: 62%-84%), the DOR was 10.04 (95% CI: 6.01-16.77), and the AUC was 0.82 (95% CI: 0.79-0.85). In addition, we found that the diagnostic effect of miR-375 varies according to the race and cancer type. Our data suggest that miR-375 profiling has a potential to be used as a screening test for cancers but the specific race and cancer should be considered. More studies on the diagnostic value of miR-375 for cancer are needed in the future.

Identification of Serological Biomarkers for Early Diagnosis of Lung Cancer Using a Protein Array-Based Approach

Lung cancer (LC) remains the leading cause of mortality from malignant tumors worldwide. Currently, a lack of serological biomarkers for early LC diagnosis is a major roadblock for early intervention and prevention of LC. To undertake this challenge, we employed a two-phase strategy to discover and validate a biomarker panel using a protein array-based approach. In Phase I, we obtained serological autoimmune profiles of 80 LC patients and 20 healthy subjects on HuProt arrays, and identified 170 candidate proteins significantly associated with LC. In Phase II, we constructed a LC focused array with the 170 proteins, and profiled a large cohort, comprised of 352 LC patients, 93 healthy individuals, and 101 patients with lung benign lesions (LBL). The comparison of autoimmune profiles between the early stage LC and the combined group of healthy and LBL allowed us to identify and validate a biomarker panel of p53, HRas, and ETHE1 for diagnosis of early stage LC with 50% sensitivity at >90% specificity. Finally, the performance of this biomarker panel was confirmed in ELISA tests. In summary, this study represents one of the most comprehensive proteome-wide surveys with one of the largest (i.e. 1,101 unique samples) and most diverse (i.e. nine disease groups) cohorts, resulting in a biomarker panel with good performance.

Integrating multiple fitting regression and Bayes decision for cancer diagnosis with transcriptomic data from tumor-educated blood platelets

The application of machine learning in cancer diagnostics has shown great promise and is of importance in clinic settings. Here we consider applying machine learning methods to transcriptomic data derived from tumor-educated platelets (TEPs) from individuals with different types of cancer. We aim to define a reliability measure for diagnostic purposes to increase the potential for facilitating personalized treatments. To this end, we present a novel classification method called MFRB (for Multiple Fitting Regression and Bayes decision), which integrates the process of multiple fitting regression (MFR) with Bayes decision theory. MFR is first used to map multidimensional features of the transcriptomic data into a one-dimensional feature. The probability density function of each class in the mapped space is then adjusted using the Gaussian probability density function. Finally, the Bayes decision theory is used to build a probabilistic classifier with the estimated probability density functions. The output of MFRB can be used to determine which class a sample belongs to, as well as to assign a reliability measure for a given class. The classical support vector machine (SVM) and probabilistic SVM (PSVM) are used to evaluate the performance of the proposed method with simulated and real TEP datasets. Our results indicate that the proposed MFRB method achieves the best performance compared to SVM and PSVM, mainly due to its strong generalization ability for limited, imbalanced, and noisy data.

Integrated Genomic Medicine: A Paradigm for Rare Diseases and Beyond

Individualized medicine, or the tailoring of therapeutic interventions to a patient's unique genetic, biochemical, physiological, exposure and behavioral profile, has been enhanced, if not enabled, by modern biomedical technologies such as high-throughput DNA sequencing platforms, induced pluripotent stem cell assays, biomarker discovery protocols, imaging modalities, and wireless monitoring devices. Despite successes in the isolated use of these technologies, however, it is arguable that their combined and integrated use in focused studies of individual patients is the best way to not only tailor interventions for those patients, but also shed light on treatment strategies for patients with similar conditions. This is particularly true for individuals with rare diseases since, by definition, they will require study without recourse to other individuals, or at least without recourse to many other individuals. Such integration and focus will require new biomedical scientific paradigms and infrastructure, including the creation of databases harboring study results, the formation of dedicated multidisciplinary research teams and new training programs. We consider the motivation and potential for such integration, point out areas in need of improvement, and argue for greater emphasis on improving patient health via technological innovations, not merely improving the technologies themselves. We also argue that the paradigm described can, in theory, be extended to the study of individuals with more common diseases.

Use of Dimethyl Pimelimidate with Microfluidic System for Nucleic Acids Extraction without Electricity

The isolation of nucleic acids in the lab on a chip is crucial to achieve the maximal effectiveness of point-of-care testing for detection in clinical applications. Here, we report on the use of a simple and versatile single-channel microfluidic platform that combines dimethyl pimelimidate (DMP) for nucleic acids (both RNA and DNA) extraction without electricity using a thin-film system. The system is based on the adaption of DMP into nonchaotropic-based nucleic acids and the capture of reagents into a low-cost thin-film platform for use as a microfluidic total analysis system, which can be utilized for sample processing in clinical diagnostics. Moreover, we assessed the use of the DMP system for the extraction of nucleic acids from various samples, including mammalian cells, bacterial cells, and viruses from human disease, and we also confirmed that the quality and quantity of the nucleic acids extracted were sufficient to allow for the robust detection of biomarkers and/or pathogens in downstream analysis. Furthermore, this DMP system does not require any instruments and electricity, and has improved time efficiency, portability, and affordability. Thus, we believe that the DMP system may change the paradigm of sample processing in clinical diagnostics.