Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients

<p>Abstract</p> <p>Background</p> <p>New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry.</p> <p>Methods</p> <p>LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry.</p> <p>Results</p> <p>Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001). <it>LRG1 </it>mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry.</p> <p>Conclusions</p> <p>Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.</p

Arachidonic acid metabolites: Effects on inflammation of fetal rabbit excisional wounds

Uncovered fetal rabbit excisional wounds do not exhibit any classic signs of healing; wounds covered with an impermeable cover do contract, reepithelialize, and exhibit inflammation. Prostaglandin E 2 (PGE 2 ) is elevated in amniotic fluid, acting as an immunosuppressant at the maternal-fetal interface. Full-thickness excisional wounds were made on 25-day gestational age rabbit fetuses. Half the wounds were covered with an impermeable cover. Tissue from covered, uncovered, and nonwounded fetuses was examined 72 h after wounding for arachidonic acid metabolites. Uncovered wounds had significantly ( P ≤0.05) elevated levels of PGE 2 , PGE 2α , and 12-HETE versus covered wounds and control tissue. Covered wounds had significantly elevated levels of 15-HETE compared to uncovered and control tissue. The elevated PGE 2 in uncovered wounds may act as a fetal immunosuppressant; covered wounds (lower PGE 2 ) developed cellular inflammation. Further investigations of these interactions may permit modulation of adult inflammation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44506/1/10753_2004_Article_BF00918814.pd

Comparação de maçã de cultivares mutantes de gala e de fuji quanto à maturação e qualidade na colheita e após a armazenagem.

Os cultivares de maçãs 'Gala' e 'Fuji' foram desenvolvidos por métodos convencionais de hibridação na década de 30 e, desde então, inúmeras variedades resultantes de mutações ocorridas naturalmente em macieiras desses cultivares têm sido identificadas (White, 1991)

Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study

Microscopic residual disease following complete cytoreduction (R0) is associated with a significant survival benefit for patients with advanced epithelial ovarian cancer (EOC). Our objective was to develop a prediction model for R0 to support surgeons in their clinical care decisions.Demographic, pathologic, surgical, and CA125 data were collected from GOG 182 records. Patients enrolled prior to September 1, 2003 were used for the training model while those enrolled after constituted the validation data set. Univariate analysis was performed to identify significant predictors of R0 and these variables were subsequently analyzed using multivariable regression. The regression model was reduced using backward selection and predictive accuracy was quantified using area under the receiver operating characteristic area under the curve (AUC) in both the training and the validation data sets.Of the 3882 patients enrolled in GOG 182, 1480 had complete clinical data available for the analysis. The training data set consisted of 1007 patients (234 with R0) while the validation set was comprised of 473 patients (122 with R0). The reduced multivariable regression model demonstrated several variables predictive of R0 at cytoreduction: Disease Score (DS) ( < 0.001), stage ( = 0.009), CA125 ( < 0.001), ascites ( < 0.001), and stage-age interaction ( = 0.01). Applying the prediction model to the validation data resulted in an AUC of 0.73 (0.67 to 0.78, 95% CI). Inclusion of DS enhanced the model performance to an AUC of 0.83 (0.79 to 0.88, 95% CI).We developed and validated a prediction model for R0 that offers improved performance over previously reported models for prediction of residual disease. The performance of the prediction model suggests additional factors (i.e. imaging, molecular profiling, etc.) should be explored in the future for a more clinically actionable tool