Cytokine Networks and Survivin Peptide-Specific Cellular Immune Responses Predict Improved Survival in Patients With Glioblastoma Multiforme.

PURPOSE: We investigated serum cytokine and T-cell responses directed against tumour-associated antigens (TAAs) in association with survival of patients with glioblastoma multiforme (GBM). PATIENTS AND METHODS: Peripheral blood from 205 treatment-naïve patients with glioma (GBM = 145; non-GBM = 60) was obtained on the day of surgery to measure (i) circulating T-cells reacting to viral antigens and TAAs, in the presence or absence of cytokine conditioning with IL-2/IL-15/IL-21 or IL-2/IL-7, and (ii) serum cytokine levels (IL-4, IL-5, IL-6, TNF-α, IFN-γ and IL-17A). Patients were followed-up for at least 1000 days post-surgery. Survivin protein and gene expression in resected GBM tumour tissue were confirmed by immunohistochemistry and real-time polymerase chain reaction, respectively. Antigen-specific T-cell responses were gauged by ICS (intracellular cytokine production). Associations between patient survival and immunological reactivity patterns were analysed using univariate and multivariate statistics. RESULTS: Approximately 2% of patients with GBM and 18% of patients with non-GBM glioma, were alive beyond 1000 days of surgery. Univariate analysis indicated that the combination of three cytokines (IL-4/IL-5/IL-6, p = .0022; IFN-γ/TNF-α/IL-17A, p = .0083) but not a 'partial' combination of these cytokines, the IFN-γ immune response to EBV-EBNA-1 (p < .0001) as well as T-cell responses to the survivin97-111 peptide (p = .0152) correlated with longer survival among patients with GBM. Multivariate analysis identified survivin97-111-directed IFN-γ production with IL-2/IL-15/IL-21 conditioning (p = .024), and the combined presence of serum IFN-γ/TNF-α/IL-17a (p = .003) as independent predictors of survival. CONCLUSION: Serum cytokine patterns and lymphocyte reactivity to survivin97-111, particularly with IL-2, IL-15 and IL-21 conditioning may be instrumental in predicting survival among patients with GBM. This has implications for clinical follow-up of patients with GBM and the targeted development of immunotherapy for patients with CNS tumours.

NY-ESO-1- and survivin-specific T-cell responses in the peripheral blood from patients with glioma.

The prognosis for patients with glioblastoma is grim. Ex vivo expanded tumor-associated antigen (TAA)-reactive T-cells from patients with glioma may represent a viable source for anticancer-directed cellular therapies. Immunohistochemistry was used to test the survivin (n = 40 samples) and NY-ESO-1 (n = 38 samples) protein expression in tumor specimens. T-cells from peripheral blood were stimulated with TAAs (synthetic peptides) in IL-2 and IL-7, or using a combination of IL-2, IL-15 and IL-21. CD4+ and CD8+ T-cells were tested for antigen-specific proliferation by flow cytometry, and IFN-γ production was tested by ELISA. Twenty-eight out of 38 cancer specimens exhibited NY-ESO-1 protein expression, 2/38 showed a strong universal (4+) NY-ESO-1 staining, and 9/40 cancer lesions exhibited a strong (4+) staining for survivin. We could detect antigen-specific IFN-γ responses in 25% blood samples for NY-ESO-1 and 30% for survivin. NY-ESO-1-expanded T-cells recognized naturally processed and presented epitopes. NY-ESO-1 or survivin expression in glioma represents viable targets for anticancer-directed T-cells for the biological therapy of patients with glioma.

The validation of a novel method combining both HER2 immunohistochemistry and HER2 dual-colour silver in situ hybridization on one slide for gastric carcinoma testing.

BACKGROUND: HER2 status assessment is a prerequisite for the establishment of an appropriate treatment strategy in gastric cancer. Gastric cancers are very heterogeneous and separate evaluations of gene amplification and protein expression lead to uncertainties in localizing distinct clones and are time consuming. This study evaluates the equivalence of the novel method combining both gene and protein platforms on one slide. METHODS: Immunohistochemistry (IHC) and HER2 dual-colour silver in situ hybridization (SISH) as single methods (IHC/SISH) and gene-protein platform combining both methods on one slide (gene/protein) were performed in randomly collected 100 cases of gastric adenocarcinoma. Results of IHC/SISH were compared with gene/protein staining. RESULTS: 96 of 100 samples were assessable. In the gene/protein staining, pathologists were able to assess gene amplification and consequent protein expression at the single cell level. In comparison trials, gene amplification was observed in 14.6% by both, conventional SISH and gene/protein platform (agreement 100%; Kappa-coefficient κ = 1.0). Protein expression scores by IHC were 70.8% (0), 10.4% (1+), 9.4% (2+), and 9.4% (3+). Protein expression by gene/protein method were: 70.8% (0), 11.5% (1+), 7.3% (2+) and 10.4% (3+) of patients. There were complete concordances in IHC assessment of cases with score 0 (100.0%; κ = 1). High concordances are shown in score 1+ (98.96%; κ = 0.947) and 3+ (96.88%; κ = 0.825) cases and good concordances in 2+ cases (95.83%; κ = 0.728). CONCLUSIONS: This novel combined platform has the advantage of being able to evaluate both gene and the protein status in the same cancer cell and may be of particular interest for research and patient's care. ARTICLE CATEGORY: Disease Biomarker.

Glomus tumor in the lung parenchyma.

Glomus tumors are uncommon lesions of glomus cell origin with ultrastructural and immunohistochemical features of smooth muscle. In the majority of the cases reported in the literature glomus tumors are benign, but there are some rare cases in which they demonstrate aggressive and malignant clinical and histological features. Glomangiosarcomas of the lung are extremely rare malignant tumors, because of the fact that glomus bodies are rare or absent. Due to their rarity they are misdiagnosed. Surgical resection is considered to be the most effective treatment for this condition. We report a case of a 35 year old female with a pulmonary glomangiosarcoma.

The prognostic impact of epidermal growth factor receptor in patients with metastatic gastric cancer.

BACKGROUND: The epidermal growth factor receptor (EGFR) is a potential target of anticancer therapy in gastric cancer. However, its prognostic role in metastatic gastric or gastroesophageal junction (GE) cancer has not been established yet. METHODS: EGFR status was analyzed by immunohistochemistry (IHC) in paraffin-embedded samples from 357 patients who received chemotherapy in 4 first-line trials. Automated RNA extraction from paraffin and RT-quantitative PCR were additionally used to evaluate EGFR mRNA expression in 130 patients. RESULTS: EGFR protein expression (any grade) and overexpression (3+) were observed in 43% and 11% of patients, respectively. EGFR positivity correlated with intestinal type histology (p = 0.05), but not with other clinicopathologic characteristics. Median follow-up was 18.2 months. Median overall survival (OS) was similar in patients with EGFR positive vs. those with EGFR negative tumors, regardless whether positivity was defined as ≥1+ (10.6 vs. 10.9 months, p = 0.463) or as 3+ (8.6 vs. 10.8 months, p = 0.377). The multivariate analysis indicated that EGFR status is not an independent prognostic factor (hazard ratio 0.85, 0.56 to 1.12, p = 0.247). There were also no significant differences in overall survival when patients were categorized according to median (p = 0.116) or quartile (p = 0.767) distribution of EGFR mRNA gene expression. Similar distributions of progression-free survival according to EGFR status were observed. CONCLUSIONS: Unlike different cancer types where EGFR-positive disease is associated with an adverse prognostic value, EGFR positivity is not prognostic of patient outcome in metastatic gastric or GE cancer.

Pathological complete remission in patients with oesophagogastric cancer receiving preoperative 5-fluorouracil, oxaliplatin and docetaxel.

The aim of this study was to determine the pathological complete remission (pCR) rate, and its relationship to clinical outcome, in patients with adenocarcinoma of the stomach or oesophagogastric junction receiving preoperative 5-fluorouracil, leucovorin, oxaliplatin and docetaxel (FLOT) every 2 weeks. Data from these patients who received at least one cycle of preoperative FLOT followed by surgery were prospectively collected in three German centres. Outcome analyses were conducted and tumour samples were evaluated for pathological remission by a central pathologist. A total of 46 patients were included in this analysis. All patients had clinical T3- and/or N+-stages and 11 (23.9%) had distant metastases (M1). After a median of 4 (range 2-8) preoperative cycles, 8 of 46 patients (17.4%) achieved a pCR. The pCR rate was highest in tumours of intestinal type histology (30.8%) and in those located in the oesophagogastric junction (30.4%) and lowest in patients with diffuse/mixed type tumours (0%) or tumours located in the stomach (4.3%; p < 0.05 for both comparisons). Patients with pCR had 100% probability of overall and disease-free survival (DFS) during the observation period, which was significantly higher (p = 0.037 and p = 0.009, respectively) than the survival probability in patients without pCR. In conclusion, treatment intensification using FLOT was associated with significant pCR rates in patients with oesophagogastric cancer. The distribution of pCR appeared to be significantly different according to histological type and location of the tumours.

Prognostic impact of phosphorylated mitogen-activated protein kinase expression in patients with metastatic gastric cancer.

BACKGROUND: This study was designed to investigate the expression of phosphorylated mitogen-activated protein kinase (p-MAPK/Erk1 and Erk2) and its correlation with outcomes in patients with metastatic gastric cancer. METHODS: p-MAPK was detected by immunohistochemistry using monoclonal antibodies in a total of 223 formalin-fixed, paraffin-embedded samples obtained from 156 patients who received first-line chemotherapy in a phase III trial. RESULTS: p-MAPK was positive in 93 (59.6%) and negative in 63 (40.4%) of the 156 patients evaluated. Similar rates of p-MAPK positivity were found in primaries (53%) and metastatic lesions (61.4%). Overall survival was significantly shorter in p-MAPK-positive patients (13.7 vs. 8.5 months) in the univariate analysis. However, this prognostic value disappeared as a trend in the multivariate analysis (p = 0.1). There was a strong, positive correlation between p-MAPK and the MIB-1 proliferation index, but MIB-1 did not predict outcomes. CONCLUSION: p-MAPK expression could be a potential negative prognostic parameter in patients with metastatic gastric cancer treated with chemotherapy.

Intratumoral T-cell infiltrates and MHC class I expression in patients with stage IV melanoma.

The infiltration of tumors by T cells has been shown to correlate with prolonged patients' survival. However, it remains unclear why only some tumors are infiltrated with T cells. This study was designed to investigate possible correlations between intratumoral T-cell infiltrates and the expression of cancer-associated antigens and MHC class I and II molecules in patients with melanoma. Fresh frozen samples from 124 stage IV melanoma patients were analyzed by immunohistochemistry for the expression of Melan-A/MART-1, tyrosinase, gp100, NY-ESO-1, and MHC class I and II. Intratumoral T-cell and B-cell infiltrates were detected by staining with anti-CD4, anti-CD8, anti-CD3, and L26 antibodies. The NY-ESO-1 serum antibody status was assessed by Western blot analysis. Intratumoral CD8+ and CD4+ T cells were detected in 63.9% and 71.3% of patients, respectively. We observed a significant heterogeneity of the expression of the melanocyte differentiation antigens, NY-ESO-1, and MHC class I and II molecules. The only significant correlation was found between the expression of MHC class I and the presence of CD4+ and CD8+ T cells (P < 0.0001). There was a strong association between these two variables with respect to the density and distribution of infiltrating T cells and the pattern of MHC class I expression (focal versus homogenous). Intratumoral T-cell infiltration is closely correlated with the MHC class I expression but not with the expression of differentiation antigens, cancer-associated antigens, or MHC class II molecules. These results may have implications for the definition of prognostic variables and for the identification of patients who may benefit from antigen-specific cancer immunotherapy.

Preoperative neural network using combined magnetic resonance imaging variables, prostate-specific antigen, and gleason score for predicting prostate cancer biochemical recurrence after radical prostatectomy.

OBJECTIVES: To develop and test an artificial neural network (ANN) for predicting biochemical recurrence based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate-specific antigen (PSA) measurement, and biopsy Gleason score, after radical prostatectomy and to investigate whether it is more accurate than logistic regression analysis (LRA) in men with clinically localized prostate cancer. METHODS: We evaluated 191 consecutive men who had undergone retropubic radical prostatectomy for clinically localized prostate cancer. None of the men had lymph node metastasis as determined by adequate follow-up and pathologic criteria. The preoperative predictive variables included clinical TNM stage, serum PSA level, biopsy Gleason score, and pMRI findings. The predicted result was biochemical failure (PSA level of 0.1 ng/mL or greater). The patient data were randomly split into four cross-validation sets and used to develop and validate the LRA and ANN models. The predictive ability of the ANN was compared with that of LRA, Han tables, and the Kattan nomogram using area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: Of the 191 patients, 57 (30%) developed disease progression at a median follow-up of 64 months (mean 61, range 2 to 86). Using all the input variables, the AUROC of the ANN was significantly greater (P <0.05) than the AUROC of LRA, Han tables, or the Kattan nomogram for the prediction of PSA recurrence 5 years after radical prostatectomy (0.897 +/- 0.063 versus 0.785 +/- 0.060, 0.733 +/- 0.061, and 0.737 +/- 0.071, respectively). Removing the pMRI findings from the previous models, the AUROC of the ANN decreased statistically significantly (P <0.05) and was comparable to the AUROC of conventional predictive tools (P >0.05). CONCLUSIONS: Using the pMRI findings, the ANN was superior to LRA, predictive tables, and nomograms to predict biochemical recurrence accurately. Confirmatory studies are warranted.

Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen, and Gleason score to predict prostate cancer recurrence after radical prostatectomy.

OBJECTIVE: An artificial neural network analysis (ANNA) was developed to predict the biochemical recurrence more effectively than regression models based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate specific antigen (PSA) and biopsy Gleason score in patients with clinically organ-confined prostate cancer after radical prostatectomy (RP). METHODS: Two-hundred-and-ten patients undergoing retropubic RP with pelvic lymphadenectomy were evaluated. Predictive study variables included clinical TNM classification, preoperative serum PSA, biopsy Gleason score, transrectal ultrasound (TRUS) findings, and pMRI findings. The predicted result was a biochemical failure (PSA >or=0.1 ng/ml). Using a five-way cross-validation method, the predicted ability of ANNA for a validation set of 200 randomly selected patients was compared with those of Cox regression analysis and "Kattan nomogram" by area under the receiver operating characteristic curve (AUC) analysis. RESULTS: Seventy-three patients (35%) failed at median follow-up of 61 (mean: 60, range: 2-94) months. Using similar input variables, the AUC of ANNA (0.765, 95% Confidence Interval [CI]: 0.704-0.825) was comparable (p > 0.05) to those for Cox regression (0.738, 95%CI: 0.691-0.819) and Kattan nomogram (0.728, 95%CI: 0.644-0.819). Contrarily, adding the pMRI findings, the ANNA is significantly (p < 0.05) superior to any other predictive model (0.897, 95%CI: 0.841-0.977). The Gleason score represented the most influential predictor (relative weight: 2.4) of PSA recurrence, followed by pMRI (2.2), and PSA (2.0). CONCLUSION: ANNA is superior to regression models to predict accurately biochemical recurrence. The relative importance of pMRI and the utility of ANNA to predict the PSA failure in patients referred for RP must be confirmed in further trials.

Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen and Gleason score to predict prostate cancer stage.

PURPOSE: We developed an artificial neural network analysis (ANNA) to predict prostate cancer pathological stage more effectively than logistic regression (LR) based on the combined use of prostate specific antigen (PSA), biopsy Gleason score and pelvic coil magnetic resonance imaging (pMRI) in patients with clinically organ confined disease before radical prostatectomy. MATERIALS AND METHODS: In 201 consecutive patients undergoing radical retropubic prostatectomy with pelvic lymphadenectomy the radiological-pathological correlation was evaluated using pMRI. Predictive variables were clinical TNM classification, preoperative serum PSA, biopsy Gleason score and pMRI findings. The predicted results were organ confined vs nonorgan confined disease and lymphatic vs no lymphatic involvement. The predicted ability of ANNA with several parameters in a set of 160 randomly selected test data was compared with that of LR and the Partin tables by area under the receiver operating characteristic curve analysis. RESULTS: The overall accuracy of ANNA and LR was 88% and 91%, and 77% and 84% for nonorgan confined and lymphatic involvement, respectively. For nonorgan confined disease and lymph node involvement the area under the curve of ANNA (0.895 and 0.899) was significantly larger than that of LR and the Partin tables (0.722 and 0.751, and 0.750 and 0.733, respectively, p <0.05). Gleason score represented the most influential predictor (relative weight 2.05) of nonorgan confined disease, followed by pMRI findings (1.96), PSA (1.73) and clinical stage (0.89). CONCLUSIONS: ANNA is superior to LR for accurately predicting pathological stage. The relative importance of pMRI findings and the usefulness of ANNA for predicting pathological stage in individuals must be confirmed in a prospective trial.

Preoperative neural network using combined magnetic resonance imaging variables, prostate-specific antigen, and Gleason score to predict positive surgical margins.

OBJECTIVES: To assess whether artificial neural network analysis (ANNA) predicts for positive surgical margins (PSMs) more effectively than logistic regression analysis (LRA) according to the combined use of the findings of pelvic coil magnetic resonance imaging (pMRI) and other preoperatively available tumor variables in patients with clinically organ-confined prostate cancer after radical prostatectomy. METHODS: A total of 205 patients with clinically localized prostate cancer, who underwent retropubic radical prostatectomy were evaluated. The predictive variables included clinical TNM stage, prostate-specific antigen (PSA) level, PSA density, biopsy Gleason score, percentage of cancer in biopsy specimens, and pMRI findings. The predicted outcome was PSMs. The patient data were randomly split into four cross-validation sets and used to develop and validate the ANNA and LRA models. For comparison, the area under the receiver operating characteristic curve was used. RESULTS: The overall PSM rate was 22% (n = 45). Using all input parameters, the accuracy of the ANNA and LRA was 84% and 75% for the prediction of PSMs, respectively. The area under the receiver operating characteristic curve of the ANNA (0.872 +/- 0.014) was significantly greater statistically (P <0.001) than that for LRA (0.791 +/- 0.006). The simplified ANNA models that used the pMRI findings in addition to PSA and Gleason score were as accurate as the model that used all the variables (P = 0.89). A high percentage of cancer in the biopsy specimens, pMRI findings, and high PSA density were equally the most influential predictors (relative weight 1.881, 1.964, and 1.493, respectively). CONCLUSIONS: All the ANNA models in this study were superior to LRA in the prediction of PSMs. The ANNA using pMRI findings, PSA level, and Gleason score as input variables performed as well as the ANNA using all the input parameters. Additional studies seem warranted.