Tumor-associated autoantibodies from mouse breast cancer models are found in serum of breast cancer patients.
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ABSTRACT:
SUBMITTER: Stanton SE
PROVIDER: S-EPMC8113561 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Serum autoantibodies against tumor-associated antigens (TAAs) have received much attention as potential biomarkers for early detection of cancers, since they can be detected in the early stages of cancers. Autoantibodies against Cancer Antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), Cancer Antigen 19-9 (CA19-9), c-Myc, p53, heat shock protein (Hsp)27 and Hsp70 have been suggested as potential markers for detecting several types of cancer. In the present study, the seven types of antibody listed above were evaluated for detecting cervical lesions. Enzyme-linked immunosorbent assays (ELISAs) were used to measure IgG levels of the autoantibodies in women with normal cytology, cervical intraepithelial neoplasia (CIN) I, CIN II, CIN III and cervical cancer. The increases of anti-CA15-3 and anti-CEA IgG in cervical cancer were more pronounced than the increases of the other markers, and the level of anti-CA19-9 IgG in CIN III stage was higher than in normal CIN I, CIN II or cervical cancer. A combination of ELISAs detecting anti-CA15-3, anti-CEA and anti-CA19-9 IgGs was found to reliably discriminate CINs from normal and to strongly differentiate cancer from normal (90.3% of sensitivity and 82.1% of specificity). We suggest that the combination of three ELISA may be useful for detecting cervical lesions.
| S-EPMC5739648 | biostudies-literature
Project description:ObjectiveWe performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC).MethodsWe searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test.ResultsThe systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35-0.40), specificity 89% (95% CI 0.86-0.91), diagnostic accuracy 65.9% (range 62.5-81.8%), AUC 0.52 (0.48-0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34-0.60), specificity 90% (95% CI 0.89-0.92), diagnostic accuracy 78.4% (range 67.5-88.8%), AUC 0.90 (0.87-0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively.ConclusionsSerum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.
| S-EPMC5547718 | biostudies-literature
Project description:BackgroundTumor-associated macrophages (TAMs) are critical components of the tumor microenvironment (TME) in prostate cancer. Commonly used orthotopic models do not accurately reflect the complete TME of a human patient or the natural initiation and progression of a tumor. Therefore, genetically engineered mouse models are essential for studying the TME as well as advancing TAM-targeted therapies. Two common transgenic (TG) models of prostate cancer are Hi-Myc and transgenic adenocarcinoma of the mouse prostate (TRAMP), but the TME and TAM characteristics of these models have not been well characterized.MethodsTo advance the Hi-Myc and TRAMP models as tools for TAM studies, macrophage infiltration and characteristics were assessed using histopathologic, flow cytometric, and expression analyses in these models at various timepoints during tumor development and progression.ResultsIn both Hi-Myc and TRAMP models, macrophages adopt a more pro-tumor phenotype in higher histological grade tumors and in older prostate tissue. However, the Hi-Myc and TRAMP prostates differ in their macrophage density, with Hi-Myc tumors exhibiting increased macrophage density and TRAMP tumors exhibiting decreased macrophage density compared to age-matched wild type mice.ConclusionsThe macrophage density and the adenocarcinoma cancer subtype of Hi-Myc appear to better mirror patient tumors, suggesting that the Hi-Myc model is the more appropriate in vivo TG model for studying TAMs and TME-targeted therapies.
| S-EPMC8720375 | biostudies-literature
Project description:It is well-recognized that solid tumors are genomically, anatomically, and physiologically heterogeneous. In general, more heterogeneous tumors have poorer outcomes, likely due to the increased probability of harboring therapy-resistant cells and regions. It is hypothesized that the genomic and physiologic heterogeneity are related, because physiologically distinct regions will exert variable selection pressures leading to the outgrowth of clones with variable genomic/proteomic profiles. To investigate this, methods must be in place to interrogate and define, at the microscopic scale, the cytotypes that exist within physiologically distinct subregions ("habitats") that are present at mesoscopic scales. MRI provides a noninvasive approach to interrogate physiologically distinct local environments, due to the biophysical principles that govern MRI signal generation. Here, we interrogate different physiologic parameters, such as perfusion, cell density, and edema, using multiparametric MRI (mpMRI). Signals from six different acquisition schema were combined voxel-by-voxel into four clusters identified using a Gaussian mixture model. These were compared with histologic and IHC characterizations of sections that were coregistered using MRI-guided 3D printed tumor molds. Specifically, we identified a specific set of MRI parameters to classify viable-normoxic, viable-hypoxic, nonviable-hypoxic, and nonviable-normoxic tissue types within orthotopic 4T1 and MDA-MB-231 breast tumors. This is the first coregistered study to show that mpMRI can be used to define physiologically distinct tumor habitats within breast tumor models. SIGNIFICANCE: This study demonstrates that noninvasive imaging metrics can be used to distinguish subregions within heterogeneous tumors with histopathologic correlation.
| S-EPMC6677627 | biostudies-literature
Project description:BACKGROUND:Chronic inflammation is frequently observed on histological analysis of malignant and non-malignant prostate specimens. It is a suspected supporting factor for prostate diseases and their progression and a main cause of false positive PSA tests in cancer screening. We hypothesized that inflammation induces autoantibodies, which may be useful biomarkers. We aimed to identify and validate prostate inflammation associated serum autoantibodies in prostate cancer patients and evaluate the expression of corresponding autoantigens. METHODS:Radical prostatectomy specimens of prostate cancer patients (N = 70) were classified into high and low inflammation groups according to the amount of tissue infiltrating lymphocytes. The corresponding pre-surgery blood serum samples were scrutinized for autoantibodies using a low-density protein array. Selected autoantigens were identified in prostate tissue and their expression pattern analyzed by immunohistochemistry and qPCR. The identified autoantibody profile was cross-checked in an independent sample set (N = 63) using the Luminex-bead protein array technology. RESULTS:Protein array screening identified 165 autoantibodies differentially abundant in the serum of high compared to low inflammation patients. The expression pattern of three corresponding antigens were established in benign and cancer tissue by immunohistochemistry and qPCR: SPAST (Spastin), STX18 (Syntaxin 18) and SPOP (speckle-type POZ protein). Of these, SPAST was significantly increased in prostate tissue with high inflammation. All three autoantigens were differentially expressed in primary and/or castration resistant prostate tumors when analyzed in an inflammation-independent tissue microarray. Cross-validation of the inflammation autoantibody profile on an independent sample set using a Luminex-bead protein array, retrieved 51 of the significantly discriminating autoantibodies. Three autoantibodies were significantly upregulated in both screens, MUT, RAB11B and CSRP2 (p>0.05), two, SPOP and ZNF671, close to statistical significance (p = 0.051 and 0.076). CONCLUSIONS:We provide evidence of an inflammation-specific autoantibody profile and confirm the expression of corresponding autoantigens in prostate tissue. This supports evaluation of autoantibodies as non-invasive markers for prostate inflammation.
| S-EPMC4749310 | biostudies-literature
Project description:Recent advances in the development of new methods of cancer immunotherapy require the production of complex cancer animal models that reliably reflect the complexity of the tumor and its microenvironment. Mice are good animals to create tumor models because they are low cost, have a short reproductive cycle, exhibit high tumor growth rates, and can be easily genetically modified. However, the obvious problem of these models is the high failure rate observed in human clinical trials after promising results obtained in mouse models. In order to increase the reliability of the results obtained in mice, the tumor model should reflect the heterogeneity of the tumor, contain components of the tumor microenvironment, in particular immune cells, to which the action of immunotherapeutic drugs are directed. This review discusses the current immunocompetent and immunocompromised mouse models of human tumors that are used to evaluate the effectiveness of immunotherapeutic agents, in particular chimeric antigen receptor (CAR) T-cells and immune checkpoint inhibitors.
| S-EPMC7312663 | biostudies-literature
Project description: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.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.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).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.
| S-EPMC6070323 | biostudies-other
Project description:IntroductionGenomic variability limits the efficacy of breast cancer therapy. To simplify the study of the molecular complexity of breast cancer, researchers have used mouse mammary tumor models. However, the degree to which mouse models model human breast cancer and are reflective of the human heterogeneity has yet to be demonstrated with gene expression studies on a large scale.MethodsTo this end, we have built a database consisting of 1,172 mouse mammary tumor samples from 26 different major oncogenic mouse mammary tumor models.ResultsIn this dataset we identified heterogeneity within mouse models and noted a surprising amount of interrelatedness between models, despite differences in the tumor initiating oncogene. Making comparisons between models, we identified differentially expressed genes with alteration correlating with initiating events in each model. Using annotation tools, we identified transcription factors with a high likelihood of activity within these models. Gene signatures predicted activation of major cell signaling pathways in each model, predictions that correlated with previous genetic studies. Finally, we noted relationships between mouse models and human breast cancer at both the level of gene expression and predicted signal pathway activity. Importantly, we identified individual mouse models that recapitulate human breast cancer heterogeneity at the level of gene expression.ConclusionsThis work underscores the importance of fully characterizing mouse tumor biology at molecular, histological and genomic levels before a valid comparison to human breast cancer may be drawn and provides an important bioinformatic resource.
| S-EPMC4078930 | biostudies-literature
Project description:Obesity is associated with an increase in cancer-specific mortality in women with breast cancer. Elevated cholesterol, particularly low-density lipoprotein cholesterol (LDL-C), is frequently seen in obese women. Here, we aimed to determine the importance of elevated circulating LDL, and LDL receptor (LDLR) expression in tumor cells, on the growth of breast cancer using mouse models of hyperlipidemia. We describe two novel immunodeficient mouse models of hyperlipidemia (Rag1-/-/LDLR-/- and Rag1-/-/ApoE (apolipoprotein E)-/- mice) in addition to established immunocompetent LDLR-/- and ApoE-/- mice. The mice were used to study the effects of elevated LDL-C in human triple-negative (MDA-MB-231) and mouse Her2/Neu-overexpressing (MCNeuA) breast cancers. Tumors derived from MCNeuA and MDA-MB-231 cells had high LDLR expression and formed larger tumors in mice with high circulating LDL-C concentrations than in mice with lower LDL-C. Silencing the LDLR in the tumor cells led to decreased growth of Her2/Neu-overexpressing tumors in LDLR-/- and ApoE-/- mice, with increased Caspase 3 cleavage. Additionally, in vitro, silencing the LDLR led to decreased cell survival in serum-starved conditions, associated with Caspase 3 cleavage. Examining publically available human data sets, we found that high LDLR expression in human breast cancers was associated with decreased recurrence-free survival, particularly in patients treated with systemic therapies. Overall, our results highlight the importance of the LDLR in the growth of triple-negative and HER2-overexpressing breast cancers in the setting of elevated circulating LDL-C, which may be important contributing factors to the increased recurrence and mortality in obese women with breast cancer.
| S-EPMC5690879 | biostudies-literature
Project description:Gastric cancer is the second leading cause of cancer death in the world, and effective diagnosis is extremely important for good outcome. We assessed the diagnostic potential of an autoantibody panel that may provide a novel tool for the early detection of gastric cancer. We analyzed data from patients with gastric cancer and normal controls in test and validation cohorts. Autoantibody levels were measured against a panel of six tumor-associated antigens (TAAs) by ELISA: p53, heat shock protein 70, HCC-22-5, peroxiredoxin VI, KM-HN-1, and p90 TAA. We assessed serum autoantibodies in 100 participants in the test cohort. The validation cohort comprised 248 participants. Autoantibodies to at least one of the six antigens showed a sensitivity/specificity of 49.0% (95% confidence interval [CI], 39.2-58.8%)/92.4% (95% CI, 87.2-97.6%), and 52.0% (95% CI, 42.2-61.8%)/90.5% (95% CI, 84.8-96.3%) in the test and validation cohorts, respectively. In the validation cohort, no significant differences were seen when patients were subdivided based on age, sex, depth of tumor invasion, lymph node metastasis, distant metastasis, peritoneal dissemination, or TNM stage. Patients who were positive for more than two antibodies in the panel tended to have a worse prognosis than those who were positive for one or no antibody. Measurement of autoantibody response to multiple TAAs in an optimized panel assay to discriminate patients with early stage gastric cancer from normal controls may aid in the early detection of gastric cancer.
| S-EPMC5378227 | biostudies-literature