Identification and characterization of colorectal-cancer-associated SNPs on the SMAD7 locus.

PURPOSE: Genome-wide association studies have identified SMAD7 as a colorectal cancer (CRC) susceptibility gene. However, its underlying mechanism has not yet been characterized. This study screened functional SNPs (fSNPs) related to colorectal cancer through Reel-seq and obtained regulatory proteins on functional SNPs. METHODS: The candidate fSNPs on the SMAD7 locus were screened by Reel-seq method. Eight SNPs such as rs8085824 were identified as functional SNPs by luciferase reporter assay and EMSA, SDCP-MS and AIDP-WB revealed that HNRNPK can specifically bind to the rs8085824-C allele. The knockdown of HNRNPK by RNAi proved that HNRNPK could affect cell function by regulating SMAD7. RESULTS: Eight functional SNPs was found on the SMAD7 locus in linkage disequilibrium (LD) with R2 > 0.8, i.e., rs12953717, rs7227023, rs34007497, rs58920878, rs8085824, rs4991143, rs4939826, and rs7227023. We also identified allele-imbalanced binding of HNRNPK to rs8085824, H1-3 to rs12953717, THOC6 to rs7227023, and DDX21 to rs58920878. Further functional analysis revealed that these proteins are the regulatory proteins that modulate the expression of SMAD7 in the human colorectal cancer cell line DLD1. In particular, we discovered that siRNA knockdown of HNRNPK inhibits cell proliferation and cell clonal formation by downregulating SMAD7, as the decreased cell proliferation and cell clonal formation in the siRNA HNRNPK knockdown cells was restored by SMAD7 overexpression. CONCLUSION: Our findings reveal a mechanism which underlies the contribution of the fSNP rs8085824 on the SMD7 locus to CRC susceptibility.

Construction and next-generation sequencing analysis of a large phage-displayed VNAR single-domain antibody library from six naïve nurse sharks.

Background: Shark new antigen receptor variable domain (VNAR) antibodies can bind restricted epitopes that may be inaccessible to conventional antibodies. Methods: Here, we developed a library construction method based on polymerase chain reaction (PCR)-Extension Assembly and Self-Ligation (named "EASeL") to construct a large VNAR antibody library with a size of 1.2 × 1010 from six naïve adult nurse sharks (Ginglymostoma cirratum). Results: The next-generation sequencing analysis of 1.19 million full-length VNARs revealed that this library is highly diversified because it covers all four classical VNAR types (Types I-IV) including 11% of classical Type I and 57% of classical Type II. About 30% of the total VNARs could not be categorized as any of the classical types. The high variability of complementarity determining region (CDR) 3 length and cysteine numbers are important for the diversity of VNARs. To validate the use of the shark VNAR library for antibody discovery, we isolated a panel of VNAR phage binders to cancer therapy-related antigens, including glypican-3, human epidermal growth factor receptor 2 (HER2), and programmed cell death-1 (PD1). Additionally, we identified binders to viral antigens that included the Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS) spike proteins. The isolated shark single-domain antibodies including Type I and Type II VNARs were produced in Escherichia coli and validated for their antigen binding. A Type II VNAR (PE38-B6) has a high affinity (Kd = 10.1 nM) for its antigen. Conclusions: The naïve nurse shark VNAR library is a useful source for isolating single-domain antibodies to a wide range of antigens. The EASeL method may be applicable to the construction of other large diversity gene expression libraries.

Assessing Statewide All-Cause Future One-Year Mortality: Prospective Study With Implications for Quality of Life, Resource Utilization, and Medical Futility.

BACKGROUND: For many elderly patients, a disproportionate amount of health care resources and expenditures is spent during the last year of life, despite the discomfort and reduced quality of life associated with many aggressive medical approaches. However, few prognostic tools have focused on predicting all-cause 1-year mortality among elderly patients at a statewide level, an issue that has implications for improving quality of life while distributing scarce resources fairly. OBJECTIVE: Using data from a statewide elderly population (aged ≥65 years), we sought to prospectively validate an algorithm to identify patients at risk for dying in the next year for the purpose of minimizing decision uncertainty, improving quality of life, and reducing futile treatment. METHODS: Analysis was performed using electronic medical records from the Health Information Exchange in the state of Maine, which covered records of nearly 95% of the statewide population. The model was developed from 125,896 patients aged at least 65 years who were discharged from any care facility in the Health Information Exchange network from September 5, 2013, to September 4, 2015. Validation was conducted using 153,199 patients with same inclusion and exclusion criteria from September 5, 2014, to September 4, 2016. Patients were stratified into risk groups. The association between all-cause 1-year mortality and risk factors was screened by chi-squared test and manually reviewed by 2 clinicians. We calculated risk scores for individual patients using a gradient tree-based boost algorithm, which measured the probability of mortality within the next year based on the preceding 1-year clinical profile. RESULTS: The development sample included 125,896 patients (72,572 women, 57.64%; mean 74.2 [SD 7.7] years). The final validation cohort included 153,199 patients (88,177 women, 57.56%; mean 74.3 [SD 7.8] years). The c-statistic for discrimination was 0.96 (95% CI 0.93-0.98) in the development group and 0.91 (95% CI 0.90-0.94) in the validation cohort. The mortality was 0.99% in the low-risk group, 16.75% in the intermediate-risk group, and 72.12% in the high-risk group. A total of 99 independent risk factors (n=99) for mortality were identified (reported as odds ratios; 95% CI). Age was on the top of list (1.41; 1.06-1.48); congestive heart failure (20.90; 15.41-28.08) and different tumor sites were also recognized as driving risk factors, such as cancer of the ovaries (14.42; 2.24-53.04), colon (14.07; 10.08-19.08), and stomach (13.64; 3.26-86.57). Disparities were also found in patients' social determinants like respiratory hazard index (1.24; 0.92-1.40) and unemployment rate (1.18; 0.98-1.24). Among high-risk patients who expired in our dataset, cerebrovascular accident, amputation, and type 1 diabetes were the top 3 diseases in terms of average cost in the last year of life. CONCLUSIONS: Our study prospectively validated an accurate 1-year risk prediction model and stratification for the elderly population (≥65 years) at risk of mortality with statewide electronic medical record datasets. It should be a valuable adjunct for helping patients to make better quality-of-life choices and alerting care givers to target high-risk elderly for appropriate care and discussions, thus cutting back on futile treatment.

Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.

BACKGROUND: As a high-prevalence health condition, hypertension is clinically costly, difficult to manage, and often leads to severe and life-threatening diseases such as cardiovascular disease (CVD) and stroke. OBJECTIVE: The aim of this study was to develop and validate prospectively a risk prediction model of incident essential hypertension within the following year. METHODS: Data from individual patient electronic health records (EHRs) were extracted from the Maine Health Information Exchange network. Retrospective (N=823,627, calendar year 2013) and prospective (N=680,810, calendar year 2014) cohorts were formed. A machine learning algorithm, XGBoost, was adopted in the process of feature selection and model building. It generated an ensemble of classification trees and assigned a final predictive risk score to each individual. RESULTS: The 1-year incident hypertension risk model attained areas under the curve (AUCs) of 0.917 and 0.870 in the retrospective and prospective cohorts, respectively. Risk scores were calculated and stratified into five risk categories, with 4526 out of 381,544 patients (1.19%) in the lowest risk category (score 0-0.05) and 21,050 out of 41,329 patients (50.93%) in the highest risk category (score 0.4-1) receiving a diagnosis of incident hypertension in the following 1 year. Type 2 diabetes, lipid disorders, CVDs, mental illness, clinical utilization indicators, and socioeconomic determinants were recognized as driving or associated features of incident essential hypertension. The very high risk population mainly comprised elderly (age>50 years) individuals with multiple chronic conditions, especially those receiving medications for mental disorders. Disparities were also found in social determinants, including some community-level factors associated with higher risk and others that were protective against hypertension. CONCLUSIONS: With statewide EHR datasets, our study prospectively validated an accurate 1-year risk prediction model for incident essential hypertension. Our real-time predictive analytic model has been deployed in the state of Maine, providing implications in interventions for hypertension and related diseases and hopefully enhancing hypertension care.

Estimating One-Year Risk of Incident Chronic Kidney Disease: Retrospective Development and Validation Study Using Electronic Medical Record Data From the State of Maine.

BACKGROUND: Chronic kidney disease (CKD) is a major public health concern in the United States with high prevalence, growing incidence, and serious adverse outcomes. OBJECTIVE: We aimed to develop and validate a model to identify patients at risk of receiving a new diagnosis of CKD (incident CKD) during the next 1 year in a general population. METHODS: The study population consisted of patients who had visited any care facility in the Maine Health Information Exchange network any time between January 1, 2013, and December 31, 2015, and had no history of CKD diagnosis. Two retrospective cohorts of electronic medical records (EMRs) were constructed for model derivation (N=1,310,363) and validation (N=1,430,772). The model was derived using a gradient tree-based boost algorithm to assign a score to each individual that measured the probability of receiving a new diagnosis of CKD from January 1, 2014, to December 31, 2014, based on the preceding 1-year clinical profile. A feature selection process was conducted to reduce the dimension of the data from 14,680 EMR features to 146 as predictors in the final model. Relative risk was calculated by the model to gauge the risk ratio of the individual to population mean of receiving a CKD diagnosis in next 1 year. The model was tested on the validation cohort to predict risk of CKD diagnosis in the period from January 1, 2015, to December 31, 2015, using the preceding 1-year clinical profile. RESULTS: The final model had a c-statistic of 0.871 in the validation cohort. It stratified patients into low-risk (score 0-0.005), intermediate-risk (score 0.005-0.05), and high-risk (score ≥ 0.05) levels. The incidence of CKD in the high-risk patient group was 7.94%, 13.7 times higher than the incidence in the overall cohort (0.58%). Survival analysis showed that patients in the 3 risk categories had significantly different CKD outcomes as a function of time (P<.001), indicating an effective classification of patients by the model. CONCLUSIONS: We developed and validated a model that is able to identify patients at high risk of having CKD in the next 1 year by statistically learning from the EMR-based clinical history in the preceding 1 year. Identification of these patients indicates care opportunities such as monitoring and adopting intervention plans that may benefit the quality of care and outcomes in the long term.

Defining and characterizing the critical transition state prior to the type 2 diabetes disease.

BACKGROUND: Type 2 diabetes mellitus (T2DM), with increased risk of serious long-term complications, currently represents 8.3% of the adult population. We hypothesized that a critical transition state prior to the new onset T2DM can be revealed through the longitudinal electronic medical record (EMR) analysis. METHOD: We applied the transition-based network entropy methodology which previously identified a dynamic driver network (DDN) underlying the critical T2DM transition at the tissue molecular biological level. To profile pre-disease phenotypical changes that indicated a critical transition state, a cohort of 7,334 patients was assembled from the Maine State Health Information Exchange (HIE). These patients all had their first confirmative diagnosis of T2DM between January 1, 2013 and June 30, 2013. The cohort's EMRs from the 24 months preceding their date of first T2DM diagnosis were extracted. RESULTS: Analysis of these patients' pre-disease clinical history identified a dynamic driver network (DDN) and an associated critical transition state six months prior to their first confirmative T2DM state. CONCLUSIONS: This 6-month window before the disease state provides an early warning of the impending T2DM, warranting an opportunity to apply proactive interventions to prevent or delay the new onset of T2DM.

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing-Based Algorithm With Statewide Electronic Medical Records.

BACKGROUND: Diabetes case finding based on structured medical records does not fully identify diabetic patients whose medical histories related to diabetes are available in the form of free text. Manual chart reviews have been used but involve high labor costs and long latency. OBJECTIVE: This study developed and tested a Web-based diabetes case finding algorithm using both structured and unstructured electronic medical records (EMRs). METHODS: This study was based on the health information exchange (HIE) EMR database that covers almost all health facilities in the state of Maine, United States. Using narrative clinical notes, a Web-based natural language processing (NLP) case finding algorithm was retrospectively (July 1, 2012, to June 30, 2013) developed with a random subset of HIE-associated facilities, which was then blind tested with the remaining facilities. The NLP-based algorithm was subsequently integrated into the HIE database and validated prospectively (July 1, 2013, to June 30, 2014). RESULTS: Of the 935,891 patients in the prospective cohort, 64,168 diabetes cases were identified using diagnosis codes alone. Our NLP-based case finding algorithm prospectively found an additional 5756 uncodified cases (5756/64,168, 8.97% increase) with a positive predictive value of .90. Of the 21,720 diabetic patients identified by both methods, 6616 patients (6616/21,720, 30.46%) were identified by the NLP-based algorithm before a diabetes diagnosis was noted in the structured EMR (mean time difference = 48 days). CONCLUSIONS: The online NLP algorithm was effective in identifying uncodified diabetes cases in real time, leading to a significant improvement in diabetes case finding. The successful integration of the NLP-based case finding algorithm into the Maine HIE database indicates a strong potential for application of this novel method to achieve a more complete ascertainment of diagnoses of diabetes mellitus.

Overexpression and immunosuppressive functions of transforming growth factor 1, vascular endothelial growth factor and interleukin-10 in epithelial ovarian cancer.

OBJECTIVE: Transforming growth factor-1 (TGF-ß1), vascular endothelial growth factor (VEGF), and interleukin-10 (IL-10) may be critical cytokines in the microenvironment of a tumor, playing roles in immune suppression. This study was conducted to elucidate the roles and immunosuppressive functions of these cytokines in epithelial ovarian cancer (EOC). METHODS: The expression levels of TGF-ß1, VEGF and IL-10 in malignant tissue were evaluated by immune- histochemistry and compared with corresponding borderline, benign, and tumor-free tissues. Moreover, relationships among the levels of these cytokines and correlations between expression and the prognosis of EOC were analyzed by Pearson rank correlations and multi-factor Logistic regression. The roles of TGF-ß1, VEGF, and IL-10 in the immunosuppressive microenvironment of ovarian cancer were studied through dendritic cell (DC) maturation and CD4+CD25+FoxP3+ Treg generation in vitro experiments. RESULTS: TGF-ß1, VEGF, and IL-10 were expressed in 100%, 74.69%, and 54.96% of EOC patients, respectively. TGF-ß1 was an independent prognostic factor for EOC. IL-10 was significantly co-expressed with VEGF. In vitro, VEGF and TGF-ß1 strongly interfered with DC maturation and consequently led to immature DCs, which secreted high levels of IL-10 that accumulated around the tumor site. TGF-ß1 and IL-10 induced Treg generation without antigen presentation in DCs. CONCLUSIONS: TGF-ß1, VEGF and IL-10 play important roles in EOC and can lead to frequent immune evasion events.

Human epididymis protein 4 (HE4) as a serum tumor biomarker in patients with ovarian carcinoma.

BACKGROUND: Ovarian cancer remains a leading cause of death from gynecological malignancy. Early diagnosis is the most important determinant of survival. For more than 25 years, cancer antigen 125 (CA 125) has been the criterion standard biomarker for the diagnosis and management of women with epithelial ovarian cancer. This study evaluated human epididymis protein 4 (HE4), a novel ovarian cancer biomarker, both alone and in combination with CA 125 as a diagnostic marker for ovarian cancer in a Chinese population. METHODS: Sera from 491 Chinese women with ovarian cancer or nonmalignant disorders and healthy women were analyzed. Sensitivities and specificities for both biomarkers and the combination were determined using predefined cutoffs (HE4>150 pmol/L and CA 125>35 U/mL) and receiver operator characteristic curves to define cutoffs based on 95% and 98% sensitivities. RESULTS: At baseline, serum HE4 and CA 125 levels were significantly higher in the ovarian cancer group versus the 5 reference groups. Using predefined cutoffs, HE4 specificity for ovarian cancer ranged from 90% to 100%; CA 125 specificity ranged from 36% (benign gynecologic disease) to 99%. Combining both markers yielded specificity for ovarian cancer of 100%. Using receiver operator characteristic curve analysis, the cutoff for 95% and 98% specificity was 102.6 and 150.2 pmol/L for HE4, respectively, and 127.2 and 325.5 U/mL for CA 125, respectively; the sensitivity of CA 125 for distinguishing ovarian cancer from benign gynecologic disease was 54% (95% specificity) and 28% (98% specificity), improving to 78% and 68%, respectively, with the addition of HE4. CONCLUSIONS: Human epididymis protein 4 used in conjunction with CA 125 yields improved specificity for ovarian cancer compared with the use of CA 125 alone, generally similar to results seen in non-Chinese populations.

Up-regulation of mitochondrial antioxidation signals in ovarian cancer cells with aggressive biologic behavior.

OBJECTIVE: Recently, a high frequency of mutations in mitochondrial DNA (mtDNA) has been detected in ovarian cancer. To explore the alterations of proteins in mitochondria in ovarian cancer, a pair of human ovarian carcinoma cell lines (SKOV3/SKOV3.ip1) with different metastatic potentials was examined. METHODS: Cancer cells SKOV3.ip1 were derived from the ascitic tumor cells of nude mice bearing a tumor of ovarian cancer cells SKOV3. SKOV3.ip1 exhibited a higher degree of migration potential than its paired cell line SKOV3. The proteins in the mitochondria of these two cells were isolated and separated by 2-D gel electrophoresis. The differently expressed proteins were extracted and identified using matrix assisted laser desorption ionisation/time-of-flight/time-of-flight (MALDI-TOF/TOF), and finally a selected protein candidate was further investigated by immunohistochemistry (IHC) method in nude mice bearing tumor tissues of these two cells. RESULTS: A total of 35 spots with different expressions were identified between the two cells using 2D-polyacrylamide gel electrophoresis (PAGE) approach. Among them, 17 spots were detected only in either SKOV3 or SKOV3.ip1 cells. Eighteen spots expressed different levels, with as much as a three-fold difference between the two cells. Twenty spots were analyzed using MALDI-TOF/TOF, and 11 of them were identified successfully; four were known to be located in mitochondria, including superoxide dismutase 2 (SOD2), fumarate hydratase (FH), mitochondrial ribosomal protein L38 (MRPL38), and mRNA turnover 4 homolog (MRTO4). An increased staining of SOD2 was observed in SKOV3.ip1 over that of SKOV3 in IHC analysis. CONCLUSIONS: Our results indicate that the enhanced antioxidation and metabolic potentials of ovarian cancer cells might contribute to their aggressive and metastatic behaviors. The underlying mechanism warrants further study.

[Variation feature of receptor binding sites of H1N1 influenza hemagglutinin in different hosts].

Recent outbreak of H1N1 virus worldwide has caused 16 226 deaths in over 213 countries and districts. Binding between the virus and the receptor on the host cell surface is the key initial event for the infection, which results in the fusion of viral host cell membrane. Hemagglutinin (HA) is the viral protein that mediates the receptor binding and membrane fusion. The receptor binding sites (RBSs) are located at the membrane-distal part of each subunit of the HA trimer and are formed by three secondary structure elements, 190 helix (residues 190 to 198), 130 loop (residues 135 to 138), and 220 loop (residues 221 to 228). HA1 with 327 amino acid sequences in length was collected from 1221 H1N1 viruses between 1918 and 2009, and bioinformatic studies were carried out through sequence comparison, entropy calculation for each amino acid residue, and 3D structure modeling. The results showed that the RBSs of different viruses with different hosts have different entropies, and the RBSs in HA1 with different hosts have different favorite amino acid sequences. The 3D modeling indicates the subtly conformation changes in the 190 helix region between different HA1s in H1N1. This study explores new characters of the RBS structure in different HA1s, and provides new information for the further investigation of the infection mechanism.

[Measurement of serum human epididymis secretory protein 4 combined with CA125 assay in differential diagnosis of endometriosis cyst and ovarian benign and malignant tumors].

OBJECTIVE: To investigate the value of human epididymis secretory protein 4(HE4) combined with CA125 assay in differential diagnosis of endometriosis cyst and ovarian malignant tumor. METHODS: The level of HE4 and CA125 were measured by enzyme-linked immunosorbent assay (ELISA) in the serum specimens of 46 cases in endometriosis cyst group, 36 cases in malignant ovarian tumor group, 60 cases in benign ovarian diseases and 50 women in healthy women group. Those results were shown with median level. The normal range were 0-150 pmol/L in HE4 and 0-35 kU/L, which either one was more than the threshold value defined as positive index. The sensitivity of assay was evaluated by receiver operating characteristic (ROC) curve, the relation and value of HE4 or CA125 alone and combination assay in diagnosis of endometriosis was analyzed by Mann-Whitney U test and correlation analysis. RESULTS: (1) HE4: the median levels of HE4 were 52.4, 51.0, 50.0 pmol/L in group of endometriosis, normal control and benign ovarian tumor, which didn't show statistical difference. However, HE4 was 507.5 pmol/L in ovarian cancer group, which was significantly higher than those of 3 groups (P<0.05). (2) CA125: there were significant different in median level of CA125 was observed as 743.0 kU/L in ovarian cancer, 84.9 kU/L in endoemtriosis, 15.4 kU/L in benign ovarian disease, and 11.5 kU/L in healthy women (P<0.05). (3) The single assay: when compared with that in endometriosis group, receiver operating characteristic area under the curve (ROC-AUC) were 0.933 in HE4 alone and 0.821 in CA125 alone assay in ovarian cancer group. The specificity was 95% and the sensitivity was 79.6% and 49.0%. (4) The combination assay: when compared with those in endometriosis group, the ROC-AUC was 0.936, the specificity was 95% and the sensitivity was 81.0% in ovarian cancer. CONCLUSIONS: Measurement of HE4 could be used in differential diagnosis of endometriosis cyst. And the combination of HE4 and CA(125) assay could discriminate ovarian endometriosis cysts from ovarian malignant tumors effectively.

Screening for genes associated with ovarian cancer prognosis.

BACKGROUND: Human epithelial ovarian cancer cell line SKOV3.ip1 is more invasive and metastatic compared with its parental line SKOV3. A total of 17 000 human genome complementary DNA microarrays were used to compare the gene expression patterns of the two cell lines. Based on this, the gene expression profiles of 22 patients with ovarian cancer were analyzed by cDNA microarray, and screened the 2-fold differentially expressed genes compared with the normal ones. We screened genes relevant to clinical prognosis of serous ovarian cancer by determining the expression profiles of ovarian cancer genes to investigate cell receptor and immunity-associated genes, and as groundwork, identify ovarian cancer-associated antigens at the gene level. METHODS: Total RNA was extracted from 22 patients with ovarian cancer and DNA microarrays were prepared. After scanning, hybridization signals were collected and the genes that were differentially expressed twice as compared with the normal ones were screened. RESULTS: We screened 236 genes relevant to the prognosis of ovarian cancer from the 17 000 human genome cDNA microarrays. According to gene classification, 48 of the 236 genes were cell receptor or immunity-associated genes, including 2 genes related to the International Federation of Gynecology and Obstetrics (FIGO) stage, 4 genes to histological grade, 18 genes to lymph node metastasis, 11 genes to residual disease, and 13 genes to the reactivity to chemotherapy. Several functionally important genes including fibronectin 1, pericentriolar material 1, beta-2-microglobulin, PPAR binding protein were identified through review of the literature. CONCLUSIONS: The cDNA microarray of ovarian cancer genes developed in this study was effective and high throughput in screening the ovarian cancer-associated genes differentially expressed. Through the studies of the cell receptor and immunity-associated genes we expect to identify the molecular biology index of ovarian cancer-associated antigens.

[Specific immune cell therapy against ovarian cancer in vivo and in vitro].

BACKGROUND & OBJECTIVE: 6B11minibody (6B11mini), an anti-idiotypic vaccine against human ovarian cancer, has been proven to induce specific humoral and cellular immunity against ovarian cancer in vivo and in vitro. This study was to investigate the safety and efficacy of using 6B11mini as an antigen to treat ovarian cancer. METHODS: After being loaded with purified 6B11mini, dendritic cells (DCs) were co-cultured with peripheral blood mononucleocytes (PBMNC) and stimulated by various cytokines, including CD3 monoclonal antibody,interleukin-2, interferon-gamma, to obtain 6B11mini-ovarian-cytokine-induced-killer cells (6B11-O-CIK). Tumor-forming ability was determined using soft agar colony-forming assay in vitro and nude mice xenografts in vivo. The acute toxicity of 6B11-OCIK at different doses was observed in BALB/c mice. Cytotoxicity of 6B11-OCIK to different target cells was detected using 51Cr release test in vitro. The ovarian tumor model was established using severe combined immune deficiency (SCID) mice transplanted with human ovarian cancer cell line SKOV3. The tumor growth was detected after injection of 6B11-OCIK into SCID mice. Injection of CIK, PBMNC and physiological saline were used as controls. RESULTS: After a cultural period of 14 days in soft agar, SKOV3 cell clones were well formed with a ratio of 50%; while 6B11-OCIK, CIK and PBMNC did not form any clones. All nude mice injected with human cervical carcinoma cell line HeLa (positive control) grew tumors after 14 days, and mice injected with 6B11-OCIK, CIK, PBMNC and normal human fetal lung fibroblast WI-38 cells did not form tumors after 13 weeks. BALB/c mice did not show any abnormal response half an hour after the administration of 6B11-OCIK cells at different doses. Mice were sacrificed 13 days after treatments, but no distinct abnormality of the main organs were found. 6B11-OCIK exerted specific cytotoxicity against tumor cells with positive OC166-9, which was related to the limitation of MHC. The tumor weights of SCID mice transplanted with SKOV3 cells were significantly lighter in 6B11-OCIK treatment group than in the saline group(P=0.023); while the tumor weights were not significantly different between the 6B11-OCIK group with CIK and the PBMNC group(P=0.540; P=0.285). CONCLUSIONS: The application of 6B11-OCIK in vivo has reached the safety standard. 6B11-OCIK has the inhibitory effect on the growth of ovarian cancer cells.

[Identification of T cell epitopes from ovarian cancer associated anti-idiotype antibody].

OBJECTIVE: To identify the T cell epitopes from ovarian cancer associated anti-idiotypic antibody 6B11 in order to explore the molecular basis of 6B11 induced cellular immune responses against ovarian cancer. METHODS: Potential human leukocyte antigen (HLA) A0201 ligands were predicted by using SYFPEITHI algorithm and tested by the T2 binding assay for screening of HLA-A2 binding peptides from 6B11 complimentary determining region (CDR). Cytotoxic T lymphocytes (CTL) to 6B11 or peptides were generated by 3 rounds of in vitro stimulation with 6B11 or peptide-pulsed dendritic cells (DC), and then tested by (51)Cr-release assay to ascertain the CTL epitope of 6B11. Cell proliferation assay was performed by using 6B11 specific CTL as responder cells and peptide-pulsed DC as stimulators to ascertain the helper T lymphocyte (Th) epitope of 6B11. Cytokine assay and interferon-gamma ELISPOT assay were performed to verify the CTL and Th epitope of 6B11 further. RESULTS: Light chain CDR3 peptide (VL CDR3) of 6B11 induced specific CTL to kill HLA-A2 and target antigen positive ovarian cancer cells, which could be blocked by anti human major histocompatibility complex (MHC) I antibody. Heavy chain CDR3 peptide (VH CDR3) of 6B11 stimulated the proliferation of 6B11-primed CTL, which could be blocked mainly by anti human MHC-II antibody, and further experiments showed that part of the VH CDR3 peptide-primed CTL killed K562 cells. Peptides in VL CDR3 and VH CDR3 were the CTL and Th epitope mimicking the original antigen of 6B11 respectively. Collaboration of 6B11 CTL and Th epitope, or 6B11 CTL epitope and keyhole limpet hemocyanin (KLH), the former was more powerful in inducing specific cellular immune responses against ovarian cancer. 6B11 or corresponding CTL and Th epitope specific CTL secreted high levels of interleukin-2 (1630, 1503 ng/L) and interferon-gamma (5620, 5421 ng/L), while basal level of interleukin-4 was detected (253, 274 ng/L). ELISPOT assay confirmed the existence of specific interferon-gamma secreting cells in 6B11 or epitopes specific CTL (196/1 x 10(6) T cell, 184/1 x 10(6) T cell). CONCLUSIONS: VL CDR3 and VH CDR3 peptides of 6B11 are the CTL and Th epitopes mimicking original antigen which could duplicate the activity of intact 6B11 to induce the cellular immune responses against ovarian cancer. The results have significant theoretical and practical value in application of anti-idiotypic antibody as anti tumor vaccine. The acquired CTL and Th epitopes as constituents of future multiple peptides against ovarian cancer could be used in peptide vaccine based ovarian cancer therapy.

[The values of serum human epididymis secretory protein 4 and CA(125) assay in the diagnosis of ovarian malignancy].

OBJECTIVE: To evaluate the value of human epididymis secretory protein 4 (HE4) and CA(125) in the diagnosis of ovarian malignancy. METHODS: HE4 and CA(125) in the serum specimens of malignant ovarian tumor group (30 cases), benign ovarian diseases (110 cases; 45 benign ovarian tumor, 57 endometriotic diseases and 8 pelvic inflammation were included) and healthy women group (137 cases) were assayed double blindly. The levels and the diagnosis efficiency of the HE4 and CA(125) were analyzed. RESULTS: (1) The median levels of HE4 and CA(125) were significantly higher in malignant ovarian tumor group (244 pmol/L and 601 kU/L respectively) than those of the benign ovarian diseases group (32 pmol/L and 22 kU/L respectively) and healthy women group (32 pmol/L and 11 kU/L respectively) (P = 0.000 - 0.029). The median levels of CA(125) were also higher in endometriotic diseases and pelvic inflammation groups (53 and 41 kU/L respectively) than those of benign ovarian tumor group and healthy women group (12 and 11 kU/L respectively; P = 0.000 - 0.031). (2) The positive rate of HE4 was lower than that of CA(125) in malignant ovarian tumor group (P = 0.036). HE4 was negative in benign diseases and healthy women groups. But the positive rates of CA(125) were 56.1% and 5/8 respectively in endometriotic diseases and pelvic inflammation groups and there were significant differences compared with HE4 (P = 0.000). (3) The HE4 assay had advantage over the CA(125) assay in receiver operating characteristic-area under the curve (ROC-AUC) and sensitivity with a specificity of 100% when ovarian malignancy was compared with controls having benign diseases and healthy women, benign tumor or benign diseases groups respectively. The CA(125) assay had advantage over the HE4 assay in ROC-AUC and sensitivity with the same specificity when ovarian cancers were compared with controls having healthy women group. (4) Combined assay of HE4 and CA(125) was better than CA(125) alone when ovarian malignancy was compared with controls having any group. (5) Combined assay was better than HE4 alone in ROC-AUC and sensitivity with the same specificity when ovarian cancers were compared with controls having benign diseases and healthy women or healthy women groups. And combined assay was lower in the ROC-AUC and the sensitivity with specificity of 100% than HE4 when ovarian cancers were compared with controls having benign tumors or benign diseases groups respectively. (6) The diagnosis efficiency of the HE4 assay at the level 86 pmol/L determined in ROC curve with controls having benign diseases and healthy women group and at the 95% reference level 50 pmol/L of healthy women or 150 pmol/L recommended by the kit respectively was compared. The sensitivity of 50 pmol/L was 73% higher than 150 pmol/L and 86 pmol/L, while the specificity and positive predictive value were lower (P = 0.002, P = 0.000). The specificity, accuracy and positive predictive value of HE4 assay at the set point of 150 pmol/L and 86 pmol/L were 100%, 96% and 96%. The set point of 86 pmol/L had advantage over 150 pmol/L at the sensitivity of diagnosis, 70% and 63% respectively. But the positive predictive value was 95% lower than 150 pmol/L, being 100%. There was no significant difference (P = 0.883, P = 0.883). CONCLUSIONS: The specificity of HE4 assay is higher than CA(125) assay in the diagnosis of ovarian cancer and HE4 combined with CA(125) assay can improve the diagnoses. The set point of 150 pmol/L is advantageous for the accurate diagnosis, while the set point of 86 pmol/L is advantageous for the screening of malignant ovarian cancer.

Cytotoxic effects of T cells induced by fusion protein 6B11-pulsed dendritic cells on ovarian carcinoma cells.

INTRODUCTION: 6B11 anti-idiotype minibody, a fusion protein, has been shown to mimic ovarian carcinoma associated antigen OC166-9. This study was designed to determine whether 6B11 anti-idiotype minibody-pulsed dendritic cells (DCs) can induce cytotoxic T cells against ovarian cancer cells. METHODS: Monocytes were isolated from peripheral blood mononuclear cells collected from patients with epithelial ovarian carcinoma (n=10). The monocytes-derived immature DCs were stimulated by cytokines, and mature DCs were pulsed with 6B11 anti-idiotype-minibody or murine F(ab)'2 fragments. The proliferation of autologous T cells induced by DCs was determined by 3H-thymidine uptake. The cytotoxicity of DC-activated T cells against autologous carcinoma cells was determined by 51Cr-release assay. RESULTS: Purified T cells demonstrated strong proliferation following incubation with 6B11 anti-idiotype minibody-pulsed DCs in 4 of 10 patients. The specific cytotoxicity of purified T cells against autologous carcinoma cells was induced after stimulation with 6B11 anti-idiotype minibody-pulsed DCs in 5 of 10 patients with cytotoxic effects ranging from 25 to 95%. In contrast, isotype murine F(ab)'2 fragments-pulsed DCs did not induce T cell proliferation and cytotoxicity against the targets. Additionally, the cytotoxic effect was partially inhibited by anti-MHC class-I antibody indicating that the cytotoxic effects are antigen-specific. CONCLUSION: 6B11 anti-idiotype-antibody-pulsed DCs can induce T cell proliferation and T cell-mediated cytotoxicity against autologous ovarian tumor cells in vitro. The cytotoxic effects of T cells against autologous tumor cells are antigen-specific. These data implicate the rationale for the use of 6B11 anti-idiotype minibody as immunotherapy against ovarian carcinoma.

Humoral immune responses induced by anti-idiotypic antibody fusion protein of 6B11scFv/hGM-CSF in BALB/c mice.

BACKGROUND: We have previously developed and characterized a monoclonal anti-idiotype antibody, designated 6B11, which mimics an ovarian carcinoma associated antigen OC166 - 9 and whose corresponding monoclonal antibody is COC166 - 9 (Ab1). In this study, we evaluate the humoral immune responses induced by the fusion protein 6B11 single-chain variable fragment (scFv)/human granulocyte macrophage colony-stimulating factor (hGM-CSF) and 6B11scFv in BALB/c mice. METHODS: The fusion protein 6B11scFv/hGM-CSF was constructed by fusing a recombinant single-chain variable fragment of 6B11scFv to GM-CSF. BALB/c mice were administrated by 6B11scFv/hGM-CSF and 6B11scFv, respectively. RESULTS: The fusion protein 6B11scFv/hGM-CSF retained binding to the anti-mouse F (ab) 2' and was also biologically active as measured by proliferation of human GM-CSF dependent cell TF1 in vitro. After immunization with the 6B11scFv/hGM-CSF and 6B11ScFv, BALB/c mice showed significantly enhanced Ab3 antibody responses to 6B11scFv/hGM-CSF compared with the 6B11scFv alone. The level of Ab3 was the highest after the first week and maintained for five weeks after the last immunization. Another booster was given when the Ab3 titer descended, and it would reach to the high level in a week. CONCLUSION: The fusion protein 6B11scFv/hGM-CSF can induce humoral immunity against ovarian carcinoma in vivo. We also provide the theoretical foundation for the application of the fusion protein 6B11scFv/hGM-CSF for active immunotherapy of ovarian cancer.

[In vitro study of the antitumor immune responses induced by anti-idiotypic minibody vaccine of ovarian cancer].

OBJECTIVE: To evaluate whether anti-tumor immune response can be induced in vitro with 6B11 anti-idiotypic minibody. and to explore its probability as ovarian cancer vaccine. METHODS: Separated human peripheral blood mononuclear cells (PBMC) were stimulated and cultured by 6B11 minibody. The proliferations of PBMC and cytotoxin were observed by (3)HTdR and (51)Cr release test respectively. ELISA(Enzyme-Linked Immunosorbent Assay) test and Immune Flow Cytometry were used to analyze IFN-gamma in supernatant of the cultured cdlls and the change of T lymphocyte phenotype of PBMC with 6B11 minibody stimulated. RESULTS: 6B11 minibody could stimulate PBMC to proliferate, the best dose was 20 mg/L; it performed cytotoxin function to ovarian carcinoma cell line expressing OC166-9. IFN-gamma maintained at high level after stimulation. It stimulated proliferation of CD3(+) T cell and CD4(+) from PBMC after stimulation respectively. CD8(+) T cell proliferation was not clear. There was significant difference between stimulation and unstimulation in CD4(+)/CD8(+) ratio. CONCLUSION: 6B11 anti-idiotypic minibody can induce both humoral and cellular immunity against ovarian carcinoma in vitro. This paper has provided strong experimental evidence for clinical use of 6B11 minibody as anti-idiotype vaccines against ovarian carcinoma.

[Induction of T cell responses against autologous ovarian cancer by anti-idiotype minibody-pulsed dendritic cells].

BACKGROUND & OBJECTIVE: Immunotherapy of sensitizing dendritic cells (DCs) with antigen,protein,and frozen cancer cell has been widely used in treating various cancers. The 6B11 anti-idiotype-antibody,a fusion protein prepared by our research center,can mimic ovarian cancer-associated antigen OC166-9. This study was to induce T cell cytotoxicity against autologous tumor cells of patients with ovarian cancer by 6B11 anti-idiotype-antibody. METHODS: Peripheral blood samples were collected from 10 patients with epithelial ovarian cancer,Monocytes were isolated and cultured to obtain DCs. Immature DCs were stimulated with 6B11 anti-idiotype-antibody (MINI-DC group); unpulsed DCs (unpulsed-DC group),mouse F(ab) '2 fragments pulsed DCs [F(ab)'2-DC group],and T cells alone (T group) were served as controls. Mature DCs were harvested. (3)H-thymidine ((3)H-TdR) incorporation approach was used to measure effect of DCs on stimulating auto-T cell proliferation. Cytotoxicity of DC-activated T cells against auto-tumor cells was measured with (51)Cr 6-h release test,tumor cell lines,SKOV3,HLE,and K562, were used as controls. RESULTS: In 4 cases,cpm value of (3)H-TdR incorporation,as symbol of auto-T cell proliferation, in MINI-DC group was significantly higher than those in control groups. In 5 cases,specific cytotoxicity effect of T cells on auto-tumor cells was observed in MINI-DC group at effect-target ratio of 20:1,the toxicity effect of T cells in MINI-DC group was 25%-100%,significantly higher than those in F(ab)'2-DC group (18%-40%), unpulsed-DC group (13%-43%),and T group (9%-58%). In 4 cases,the toxicity effect of T cells in MINI-DC group, at effect-target ratio of 20:1,on auto-tumor cells was 25%-100%, higher than those on SKOV3 cells (5%-51%),HLE cells (2%-38%),and K562 cells (2%-25%). Moreover,the toxicity effect of T cells in MINI-DC group on auto-tumor cells can be partially blocked by anti-MHC-I antibody,which indicated that the toxicity was antigen-specific. CONCLUSION: DCs loaded with 6B11 anti-idiotype antibody that mimic ovarian cancer antigen can induce antigen specific T cell cytotoxicity against auto-ovarian tumor cells in vitro.