Tumor-derived Autoantibodies Identify Malignant Pulmonary Nodules.

Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.

Protein and glycomic plasma markers for early detection of adenoma and colon cancer.

OBJECTIVE: To discover and confirm blood-based colon cancer early-detection markers. DESIGN: We created a high-density antibody microarray to detect differences in protein levels in plasma from individuals diagnosed with colon cancer <3 years after blood was drawn (ie, prediagnostic) and cancer-free, matched controls. Potential markers were tested on plasma samples from people diagnosed with adenoma or cancer, compared with controls. Components of an optimal 5-marker panel were tested via immunoblotting using a third sample set, Luminex assay in a large fourth sample set and immunohistochemistry (IHC) on tissue microarrays. RESULTS: In the prediagnostic samples, we found 78 significantly (t-test) increased proteins, 32 of which were confirmed in the diagnostic samples. From these 32, optimal 4-marker panels of BAG family molecular chaperone regulator 4 (BAG4), interleukin-6 receptor subunit beta (IL6ST), von Willebrand factor (VWF) and CD44 or epidermal growth factor receptor (EGFR) were established. Each panel member and the panels also showed increases in the diagnostic adenoma and cancer samples in independent third and fourth sample sets via immunoblot and Luminex, respectively. IHC results showed increased levels of BAG4, IL6ST and CD44 in adenoma and cancer tissues. Inclusion of EGFR and CD44 sialyl Lewis-A and Lewis-X content increased the panel performance. The protein/glycoprotein panel was statistically significantly higher in colon cancer samples, characterised by a range of area under the curves from 0.90 (95% CI 0.82 to 0.98) to 0.86 (95% CI 0.83 to 0.88), for the larger second and fourth sets, respectively. CONCLUSIONS: A panel including BAG4, IL6ST, VWF, EGFR and CD44 protein/glycomics performed well for detection of early stages of colon cancer and should be further examined in larger studies.

Mining the pre-diagnostic antibody repertoire of TgMMTV-neu mice to identify autoantibodies useful for the early detection of human breast cancer.

BACKGROUND: The use of autoantibodies for the early detection of breast cancer has generated much interest as antibodies can be readily assayed in serum when antigen levels are low. Ideally, diagnostic autoantibodies would be identified in individuals who harbored pre-invasive disease/high risk lesions leading to malignancy. Prospectively collected human serum samples from these individuals are rare and not often available for biomarker discovery. We questioned whether transgenic animals could be used to identify cancer-associated autoantibodies present at the earliest stages of the malignant transformation of breast cancer. METHODS: We collected sera from transgenic mice (TgMMTV-neu) from the time of birth to death by spontaneous mammary tumors. Using sera from a time point prior to the development of tumor, i.e. "pre-diagnostic", we probed cDNA libraries derived from syngeneic tumors to identify proteins recognized by IgG antibodies. Once antigens were identified, selected proteins were evaluated via protein arrays, for autoantibody responses using plasma from women obtained prior to the development of breast cancer and matched controls. The ability of the antigens to discriminate cases from controls was assessed using receiver-operating-characteristic curve analyses and estimates of the area under the curve. RESULTS: We identified 6 autoantibodies that were present in mice prior to the development of mammary cancer: Pdhx, Otud6b, Stk39, Zpf238, Lgals8, and Vps35. In rodent validation cohorts, detecting both IgM and IgG antibody responses against a subset of the identified proteins could discriminate pre-diagnostic sera from non-transgenic control sera with an AUC of 0.924. IgG and IgM autoantibodies, specific for a subset of the identified antigens, could discriminate the samples of women who eventually developed breast cancer from case-matched controls who did not develop disease. The discriminatory potential of the pre-diagnostic autoantibodies was enhanced if plasma samples were collected greater than 5 months prior to a breast cancer diagnosis (AUC 0.68; CI 0.565-0.787, p=0.0025). CONCLUSION: Genetically engineered mouse models of cancer may provide a facile discovery tool for identifying autoantibodies useful for human cancer diagnostics.

Discovery and preliminary confirmation of novel early detection biomarkers for triple-negative breast cancer using preclinical plasma samples from the Women's Health Initiative observational study.

Triple-negative breast cancer is a particularly aggressive and lethal breast cancer subtype that is more likely to be interval-detected rather than screen-detected. The purpose of this study is to discover and initially validate novel early detection biomarkers for triple-negative breast cancer using preclinical samples. Plasma samples collected up to 17 months before diagnosis from 28 triple-negative cases and 28 matched controls from the Women's Health Initiative Observational Study were equally divided into a training set and a test set and interrogated by a customized antibody array. Data were available on 889 antibodies; in the training set, statistically significant differences in case versus control signals were observed for 93 (10.5 %) antibodies at p < 0.05. Of these 93 candidates, 29 were confirmed in the test set at p < 0.05. Areas under the curve for these candidates ranged from 0.58 to 0.79. With specificity set at 98 %, sensitivity ranged from 4 to 68 % with 20 candidates having a sensitivity ≥ 20 % and 6 having a sensitivity ≥ 40 %. In an analysis of KEGG gene sets, the pyrimidine metabolism gene set was upregulated in cases compared to controls (p = 0.004 in the testing set) and the JAK/Stat signaling pathway gene set was downregulated (p = 0.003 in the testing set). Numerous potential early detection biomarkers specific to triple-negative breast cancer in multiple pathways were identified. Further research is required to followup on promising candidates in larger sample sizes and to better understand their potential biologic importance as our understanding of the etiology of triple-negative breast cancer continues to grow.

Embryo-scale, single-cell spatial transcriptomics.

Spatial patterns of gene expression manifest at scales ranging from local (e.g., cell-cell interactions) to global (e.g., body axis patterning). However, current spatial transcriptomics methods either average local contexts or are restricted to limited fields of view. Here, we introduce sci-Space, which retains single-cell resolution while resolving spatial heterogeneity at larger scales. Applying sci-Space to developing mouse embryos, we captured approximate spatial coordinates and whole transcriptomes of about 120,000 nuclei. We identify thousands of genes exhibiting anatomically patterned expression, leverage spatial information to annotate cellular subtypes, show that cell types vary substantially in their extent of spatial patterning, and reveal correlations between pseudotime and the migratory patterns of differentiating neurons. Looking forward, we anticipate that sci-Space will facilitate the construction of spatially resolved single-cell atlases of mammalian development.

Differences in Serum Biomarkers Between Combined Glucosamine and Chondroitin Versus Celecoxib in a Randomized, Double-blind Trial in Osteoarthritis Patients.

BACKGROUND: Non-steroidal anti-inflammatory drugs, e.g., celecoxib, are commonly used for inflammatory conditions, but can be associated with adverse effects. Combined glucosamine hydrochloride plus chondroitin sulfate (GH+CS) are commonly used for joint pain and have no known adverse effects. Evidence from in vitro, animal and human studies suggest that GH+CS have anti-inflammatory activity, among other mechanisms of action. OBJECTIVE: We evaluated the effects of GH+CS versus celecoxib on a panel of 20 serum proteins involved in inflammation and other metabolic pathways. METHODS: Samples were from a randomized, parallel, double-blind trial of pharmaceutical grade 1500 mg GH + 1200 mg CS (n=96) versus 200 mg celecoxib daily (n=93) for 6- months in knee osteoarthritis (OA) patients. Linear mixed models adjusted for age, sex, body mass index, baseline serum protein values, and rescue medicine use assessed the intervention effects of each treatment arm adjusting for multiple testing. RESULTS: All serum proteins except WNT16 were lower after treatment with GH+CS, while about half increased after celecoxib. Serum IL-6 was significantly reduced (by 9%, P=0.001) after GH+CS, and satisfied the FDR<0.05 threshold. CCL20, CSF3, and WNT16 increased after celecoxib (by 7%, 9% and 9%, respectively, P<0.05), but these serum proteins were no longer statistically significant after controlling for multiple testing. CONCLUSION: The results of this study using samples from a previously conducted trial in OA patients, demonstrate that GH+CS reduces circulating IL-6, an inflammatory cytokine, but is otherwise comparable to celecoxib with regard to effects on other circulating protein biomarkers.

Development of blood-based biomarker tests for early detection of colorectal neoplasia: Influence of blood collection timing and handling procedures.

INTRODUCTION: Blood-based, cancer-associated biomarkers are susceptible to a variety of well-known preanalytical factors. The influence of bowel preparation before a diagnostic colonoscopy on biomarker levels is, however, poorly investigated. The present study assessed the influence of bowel preparation on colorectal cancer-associated biomarkers. In addition, the effect of single versus double centrifugation of plasma biomarkers was assessed. METHODS: Blood samples were collected pre- and post-bowel preparation from 125 subjects scheduled for first time diagnostic colonoscopy due to symptoms attributable to CRC. The samples were separated into serum and EDTA plasma, and analyzed by four independent collaborators for: 1) the proteins AFP, CA19-9, CEA, hs-CRP, CyFra21-1, Ferritin, Galectin-3 and TIMP-1, 2) the proteins BAG4, IL6ST, vWF, CD44 and EGFR, 3) the glycoprotein Galectin-3 ligand, and 4) cell-free DNA (cfDNA). Statistical analysis of biomarker data has been performed using mixed modelling, including repeated measures. RESULTS: The biomarkers generally showed negligible variation between pre- and post-bowel preparation except for CyFra21-1, Ferritin, BAG4 and cfDNA. CyFra21-1 levels were systematically reduced with 29% (95% CI 21-36%) by bowel preparation (p ≤ 0.0001). Ferritin was not significantly different between pre- and post-bowel preparation (p = 0.07), however the estimated difference (increase) was 18%. BAG4 was systematically reduced by 12% (95% CI 1-22%, p = 0.04), while cfDNA showed a significant increase of 28% (95% CI 17-39%, p < 0.0001). Double centrifugation compared to single centrifugation showed reduced vWF (ratio 0.86, p ≤ 0.0001) and CD44 (ratio 0.85, p = 0.016), but increased IL6ST levels (ratio 1.18, p = 0.014). CONCLUSIONS: Results of the present study demonstrated systematic, statistically significant differences between pre-bowel and post-bowel preparation levels for three independent blood-based biomarkers (BAG4, CyFra21-1, cfDNA), illustrating the importance of timing of sample collection for biomarker analyses.

Proteome Profiling Uncovers an Autoimmune Response Signature That Reflects Ovarian Cancer Pathogenesis.

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53-MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

Label-free detection of cancer biomarker candidates using surface plasmon resonance imaging.

In this work, we present an antibody array for the detection of cancer biomarker candidates by a surface plasmon resonance (SPR) imaging sensor with polarization contrast. Responses from the SPR imaging sensor are shown to be similar to those from a conventional spectroscopy-based SPR sensor. Antibodies are spotted onto a self-assembled monolayer (SAM) composed of oligo(ethylene glycol) (OEG)-containing alkanethiol chains. Detection of two cancer biomarker candidates, activated leukocyte cell adhesion molecule/CD 166 (ALCAM) and transgelin-2 (TAGLN2), is demonstrated. Limits of detection for ALCAM and TAGLN2 are established at 6 ng/mL and 3 ng/mL, respectively, in buffer. No cross-reactivity is observed between immobilized antibodies and nonspecific antigen. Biomarker candidates are also detected in a 10% human serum solution.

Whole Genome-Derived Tiled Peptide Arrays Detect Prediagnostic Autoantibody Signatures in Non-Small-Cell Lung Cancer.

The majority of non-small-cell lung cancer (NSCLC) cases are diagnosed at advanced stages, primarily because earlier stages of the disease are either asymptomatic or may be attributed to other causes such as infection or long-term effects from smoking. Therefore, early detection of NSCLC would likely increase response and survival rates due to timely intervention. Here, we utilize a novel approach based on whole genome-derived tiled peptide arrays to identify epitopes associated with autoantibody reactivity in NSCLC as a potential means for early detection. Arrays consisted of 2,781,902 tiled peptides representing 20,193 proteins encoded in the human genome. Analysis of 86 prediagnostic samples and 86 matched normal controls from a high-risk cohort revealed 48 proteins with three or more reactive epitopes in NSCLC samples relative to controls. Independent mass spectrometry analysis identified 40 of the 48 proteins in prediagnostic sera from NSCLC samples, of which, 21 occurred in the immunoglobulin-bound fraction. In addition, 63 and 34 proteins encompassed three or more epitopes that were distinct for squamous cell lung cancer and lung adenocarcinoma, respectively. Collectively, these data show that tiled peptide arrays provide a means to delineate epitopes encoded across the genome that trigger an autoantibody response associated with tumor development. SIGNIFICANCE: This study provides a modality for early diagnosis of NSCLC for precision oncology that can be applied to other cancer types.

Hybrid surface platform for the simultaneous detection of proteins and DNAs using a surface plasmon resonance imaging sensor.

In this work, we present a novel surface and assay for the simultaneous detection of DNA and protein analytes on a surface plasmon resonance (SPR) imaging sensor. A mixed DNA/oligo (ethylene glycol) (OEG) self-assembled monolayer (SAM) is created using a microarrayer. Thiol-modified single-stranded DNA sequences are spotted onto a gold-coated glass substrate. Backfilling with an OEG-modified alkanethiol creates a protein-resistant surface background. Antibodies conjugated to complementary single-stranded DNA sequences are immobilized on the surface through DNA hybridization. By converting only part of the DNA array into a protein array, simultaneous detections of DNA and protein analytes are possible. A model system of two cDNA sequences and two human pregnancy hormones are used to demonstrate the assay. No cross-reactivity was observed between DNA or protein analytes and nontargeted immobilized cDNA sequence or antibodies. A response from a detection of a single analyte in a mixture of protein and DNA analytes corresponds well with that of a single-analyte solution.

Zwitterionic polymers exhibiting high resistance to nonspecific protein adsorption from human serum and plasma.

This study examined six different polymer and self-assembled monolayer (SAM) surface modifications for their interactions with human serum and plasma. It was demonstrated that zwitterionic polymer surfaces are viable alternatives to more traditional surfaces based on poly(ethylene glycol) (PEG) as nonfouling surfaces. All polymer surfaces were formed using atom transfer radical polymerization (ATRP) and they showed an increased resistance to nonspecific protein adsorption compared to SAMs. This improvement is due to an increase in the surface packing density of nonfouling groups on the surface, as well as a steric repulsion from the flexible polymer brush surfaces. The zwitterionic polymer surface based on carboxybetaine methacrylate (CBMA) also incorporates functional groups for protein immobilization in the nonfouling background, making it a strong candidate for many applications such as in diagnostics and drug delivery.

Quantitative and simultaneous detection of four foodborne bacterial pathogens with a multi-channel SPR sensor.

We report the quantitative and simultaneous detection of four species of bacteria, Escherichia coli O157:H7, Salmonella choleraesuis serotype typhimurium, Listeria monocytogenes, and Campylobacter jejuni, using an eight-channel surface plasmon resonance (SPR) sensor based on wavelength division multiplexing. Detection curves showing SPR response versus analyte concentration were established for each species of bacteria in buffer at pH 7.4, apple juice at native pH 3.7, and apple juice at an adjusted pH of 7.4, as well as for a mixture containing all four species of bacteria in buffer. Control experiments were performed to show the non-fouling characteristics of the sensor surface as well as the specificity of the amplification antibodies used in this study. The limit of detection (LOD) for each of the four species of bacteria in the tested matrices ranges from 3.4 x 10(3) to 1.2 x 10(5) cfu/ml. Detection curves in buffer of an individual species of bacteria in a mixture of all four species of bacteria correlated well with detection curves of the individual species of bacteria alone. SPR responses were higher for bacteria in apple juice at pH 7.4 than in apple juice at pH 3.7. This difference in sensor response could be partly attributed to the pH dependence of antibody-antigen binding.

An Autoimmune Response Signature Associated with the Development of Triple-Negative Breast Cancer Reflects Disease Pathogenesis.

The repertoire of antigens associated with the development of an autoimmune response in breast cancer has relevance to detection and treatment strategies. We have investigated the occurrence of autoantibodies associated with the development of triple-negative breast cancer (TNBC) in the before diagnosis setting and in samples collected at the time of diagnosis of TNBC. Lysate arrays containing protein fractions from the TNBC MDA-MB-231 cell line were hybridized with TNBC plasmas from the Women's Health Initiative cohort, collected before clinical diagnosis and with plasmas from matched controls. An immune response directed against spliceosome and glycolysis proteins was observed with case plasmas as previously reported in estrogen receptor(+) breast cancer. Importantly, autoantibodies directed against networks involving BRCA1, TP53, and cytokeratin proteins associated with a mesenchymal/basal phenotype were distinct to TNBC before diagnosis samples. Concordant autoantibody findings were observed with mouse plasma samples collected before occurrence of palpable tumors from a C3(1)-T triple negative mouse model. Plasma samples collected at the time of diagnosis of stage II TNBC and from matched healthy controls were subjected to proteomic analysis by mass spectrometry to identify Ig-bound proteins yielding a predominance of cytokeratins, including several associated with a mesenchymal/basal phenotype among cases compared with controls. Our data provide evidence indicative of a dynamic repertoire of antigens associated with a humoral immune response reflecting disease pathogenesis in TNBC.

Proteomic profiling of the autoimmune response to breast cancer antigens uncovers a suppressive effect of hormone therapy.

PURPOSE: Proteomics technologies are well suited for harnessing the immune response to tumor antigens for diagnostic applications as in the case of breast cancer. We previously reported a substantial impact of hormone therapy (HT) on the proteome. Here, we investigated the effect of HT on the immune response toward breast tumor antigens. EXPERIMENTAL DESIGN: Plasmas collected 0-10 months prior to diagnosis of ER+ breast cancer from 190 postmenopausal women and 190 controls that participated in the Women's Health Initiative Observational Study were analyzed for the effect of HT on IgG reactivity against arrayed proteins from MCF-7 or SKBR3 breast cancer cell line lysates following extensive fractionation. RESULTS: HT user cases exhibited significantly reduced autoantibody reactivity against arrayed proteins compared to cases who were Not Current users. An associated reduced level of IL-6 and other immune-related cytokines was observed among HT users relative to nonusers. CONCLUSION AND CLINICAL RELEVANCE: Our findings suggest occurrence of a global altered immune response to breast cancer-derived proteins associated with HT. Thus a full understanding of factors that modulate the immune response is necessary to translate autoantibody panels into clinical applications.

Autoantibody signatures involving glycolysis and splicesome proteins precede a diagnosis of breast cancer among postmenopausal women.

We assessed the autoantibody repertoire of a mouse model engineered to develop breast cancer and the repertoire of autoantibodies in human plasmas collected at a preclinical time point and at the time of clinical diagnosis of breast cancer. In seeking to identify common pathways, networks, and protein families associated with the humoral response, we elucidated the dynamic nature of tumor antigens and autoantibody interactions. Lysate proteins from an immortalized cell line from a MMTV-neu mouse model and from MCF7 human breast cancers were spotted onto nitrocellulose microarrays and hybridized with mouse and human plasma samples, respectively. Immunoglobulin-based plasma immunoreactivity against glycolysis and spliceosome proteins was a predominant feature observed both in tumor-bearing mice and in prediagnostic human samples. Interestingly, autoantibody reactivity was more pronounced further away than closer to diagnosis. We provide evidence for dynamic changes in autoantibody reactivity with tumor development and progression that may depend, in part, on the extent of antigen-antibody interactions.

Evaluation of known oncoantibodies, HER2, p53, and cyclin B1, in prediagnostic breast cancer sera.

Serum autoantibodies, directed against oncogenic proteins, have been frequently detected in the sera of patients with breast cancer. It is unknown whether serum antibodies that are identified in patients with established disease could also be detected in patients with newly diagnosed disease or even predate the diagnosis of breast cancer. Using sera collected at the time of treatment, at the time of diagnosis, or before the time of diagnosis, the current study aimed to address the temporal relationship between breast cancer development and serum antibody response. Starting from serum antibodies to eight known breast cancer antigens, we first identified four serum antibodies, HER2/neu, p53, carcinoembryonic antigen (CEA), and cyclin B1, which are significantly increased in the sera collected from patients with breast cancer at the time of treatment. These antibodies were also elevated in breast cancer sera collected at the time of diagnosis. Finally, comparison of antibody responses in prediagnostic samples from women before the development of breast cancer and in controls showed that antibodies to the HER2/neu and p53 can be detected in sera that were collected on average more than 150 days before a breast cancer diagnosis. These results showed that serum autoantibodies commonly reported in sera from patients with established disease can also be detected in prediagnostic sera and may be useful for the early detection of breast cancer.

Concordant release of glycolysis proteins into the plasma preceding a diagnosis of ER+ breast cancer.

Although the identification of peripheral blood biomarkers would enhance early detection strategies for breast cancer, the discovery of protein markers has been challenging. In this study, we sought to identify coordinated changes in plasma proteins associated with breast cancer based on large-scale quantitative mass spectrometry. We analyzed plasma samples collected up to 74 weeks before diagnosis from 420 estrogen receptor (ER)(+) cases and matched controls enrolled in the Women's Health Initiative cohort. A gene set enrichment analysis was applied to 467 quantified proteins, linking their corresponding genes to particular biologic pathways. On the basis of differences in the concentration of individual proteins, glycolysis pathway proteins exhibited a statistically significant difference between cases and controls. In particular, the enrichment was observed among cases in which blood was drawn closer to diagnosis (effect size for the 0-38 weeks prediagnostic group, 1.91; P, 8.3E-05). Analysis of plasmas collected at the time of diagnosis from an independent set of cases and controls confirmed upregulated levels of glycolysis proteins among cases relative to controls. Together, our findings indicate that the concomitant release of glycolysis proteins into the plasma is a pathophysiologic event that precedes a diagnosis of ER(+) breast cancer.

Increased plasma levels of the APC-interacting protein MAPRE1, LRG1, and IGFBP2 preceding a diagnosis of colorectal cancer in women.

Longitudinal blood collections from cohort studies provide the means to search for proteins associated with disease before clinical diagnosis. We investigated plasma samples from the Women's Health Initiative (WHI) cohort to determine quantitative differences in plasma proteins between subjects subsequently diagnosed with colorectal cancer (CRC) and matched controls that remained cancer-free during the period of follow-up. Proteomic analysis of WHI samples collected before diagnosis of CRC resulted in the identification of six proteins with significantly (P < 0.05) elevated concentrations in cases compared with controls. Proteomic analysis of two CRC cell lines showed that five of the six proteins were produced by cancer cells. Microtubule-associated protein RP/EB family member 1 (MAPRE1), insulin-like growth factor-binding protein 2 (IGFBP2), leucine-rich alpha-2-glycoprotein (LRG1), and carcinoembryonic antigen (CEA) were individually assayed by enzyme linked immunosorbent assay (ELISA) in 58 pairs of newly diagnosed CRC samples and controls and yielded significant elevations (P < 0.05) among cases relative to controls. A combination of these four markers resulted in a receiver operating characteristics curve with an area under the curve value of 0.841 and 57% sensitivity at 95% specificity. This combination rule was tested in an independent set of WHI samples collected within 7 months before diagnosis from cases and matched controls resulting in 41% sensitivity at 95% specificity. A panel consisting of CEA, MAPRE1, IGFBP2, and LRG1 has predictive value in prediagnostic CRC plasmas.

Direct detection of carcinoembryonic antigen autoantibodies in clinical human serum samples using a surface plasmon resonance sensor.

The ability to detect biomarkers in human serum is important for cancer diagnostics. The work presented focuses on the establishment of a surface plasmon resonance (SPR) biosensor as a means for detecting varying levels of autoantibody biomarkers in human serum samples. Carcinoembryonic antigen (CEA) is a biomarker that is present in human serum. It is thought that CEA levels become elevated in patients with colon and ovarian cancer, causing a corresponding increase in the autoantibody level in human serum. Detection of this CEA autoantibody increase could be used to diagnose cancer in patients. Using a SPR biosensor, human serum samples were screened directly for CEA antibody levels. Results using a sandwich assay with a SPR sensor demonstrated the same linear trend as seen from an established enzyme-linked immunosorbent assay (ELISA) method. Serum samples from five healthy individuals were used to establish a threshold value for differentiating a cancerous serum sample from a negative sample with a 95% confidence. Three serum samples from cancer patients with positive CEA antibody levels as evaluated by ELISA were used to test the criterion.