Results: High cytoplasmic OPN staining was observed in 100% of gastric carcinomas, 85% of colorectal carcinomas, 82% of transitional cell carcinomas of the renal pelvis, 81% of pancreatic carcinomas, 72% of renal cell carcinomas, 71% of lung and endometrial carcinomas, 70% of esophageal carcinomas, 58% of squamous cell carcinomas of the head and neck, and 59% of ovarian carcinomas. Although OPN expression was identified in a good number of bladder, prostate, and brain tumors, the majority of 6 skin cancers, 11 of 14 salivary gland cancers, 2 thyroid carcinomas, and 23 of 26 breast cancers revealed low OPN positivity or were negative. When considering all sites, OPN expression significantly correlated with tumor stage (Spearman's correlation coefficient, P ‫؍‬ 0.0002). OPN score and stage were also significantly correlated for specific cancer sites including bladder (P ‫؍‬ 0.01), colon (P ‫؍‬ 0.004), kidney (P ‫؍‬ 0.0001), larynx (P ‫؍‬ 0.035), mouth (P ‫؍‬ 0.046), and salivary gland (P ‫؍‬ 0.011).Conclusions: This study reports the broad distribution of OPN in human tumors from different body sites, suggesting involvement of this protein in tumor formation. The strong correlation between pathological stage and OPN across multiple tumor types suggests a role for OPN in tumor progression.

Purpose-Development of a radiosensitivity predictive assay is a central goal of radiation oncology. We reasoned a gene expression model could be developed to predict intrinsic radiosensitivity and treatment response in patients.Methods and Materials-Radiosensitivity (determined by survival fraction at 2 Gy) was modeled as a function of gene expression, tissue of origin, ras status (mut/wt), and p53 status (mut/wt) in 48 human cancer cell lines. Ten genes were identified and used to build a rank-based linear regression algorithm to predict an intrinsic radiosensitivity index (RSI, high index = radioresistance). This model was applied to three independent cohorts treated with concurrent chemoradiation: head-and-neck cancer (HNC, n = 92); rectal cancer (n = 14); and esophageal cancer (n = 12).Results-Predicted RSI was significantly different in responders (R) vs. nonresponders (NR) in the rectal (RSI R vs. NR 0.32 vs. 0.46, p = 0.03), esophageal (RSI R vs. NR 0.37 vs. 0.50, p = 0.05) and combined rectal/esophageal (RSI R vs. NR 0.34 vs. 0.48, p = 0.001511) cohorts. Using a threshold RSI of 0.46, the model has a sensitivity of 80%, specificity of 82%, and positive predictive value of 86%. Finally, we evaluated the model as a prognostic marker in HNC. There was an improved 2-year locoregional control (LRC) in the predicted radiosensitive group (2-year LRC 86% vs. 61%, p = 0.05).Conclusions-We validate a robust multigene expression model of intrinsic tumor radiosensitivity in three independent cohorts totaling 118 patients. To our knowledge, this is the first time that a systems biology-based radiosensitivity model is validated in multiple independent clinical datasets.

Interpretation of clinical trials to alter the decline in β-cell function after diagnosis of type 1 diabetes depends on a robust understanding of the natural history of disease. Combining data from the Type 1 Diabetes TrialNet studies, we describe the natural history of β-cell function from shortly after diagnosis through 2 years post study randomization, assess the degree of variability between patients, and investigate factors that may be related to C-peptide preservation or loss. We found that 93% of individuals have detectable C-peptide 2 years from diagnosis. In 11% of subjects, there was no significant fall from baseline by 2 years. There was a biphasic decline in C-peptide; the C-peptide slope was −0.0245 pmol/mL/month (95% CI −0.0271 to −0.0215) through the first 12 months and −0.0079 (−0.0113 to −0.0050) from 12 to 24 months (P < 0.001). This pattern of fall in C-peptide over time has implications for understanding trial results in which effects of therapy are most pronounced early and raises the possibility that there are time-dependent differences in pathophysiology. The robust data on the C-peptide obtained under clinical trial conditions should be used in planning and interpretation of clinical trials.

Purpose The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials Radiosensitivity, as represented by the Survival Fraction at 2 Gy (SF2) was modeled in 48 human cancer cell lines. We apply a linear regression algorithm that integrates gene expression with biological variables including: ras status (mut/wt), tissue of origin (TO) and p53 status (mut/wt). Results The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression. This network was reduced to a 10-hub network that includes: c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1 and IRF1. Nine targets associated with radiosensitization drugs link to the network, demonstrating clinical relevance. Furthermore, the model identifies four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis along with TO and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included: DNA repair, cell cycle, apoptosis and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon and breast cancers. Conclusions We developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We propose this platform will play a central role in the integration of biology into clinical radiation oncology practice.

These data support further evaluation of molecular staging to discriminate good from poor prognosis patients, with the potential to direct adjuvant therapy.

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Myelodysplastic syndromes (MDS) are characterized by ineffective hematopoiesis with potential for progression to acute myeloid leukemia (AML). We compared natural killer (NK) cytolytic function in 48 MDS patients with 37 healthy donors and found reduced activity in the patient population (K562 cytolysis, 19% ؎ 21% SD versus 40% ؎ 17%) (P < .001). NK cytotoxicity in MDS patients was reduced against 3 disparate tumor targets with differential activating receptor requirement, suggesting global defects in NK function. Reduced NK function in MDS was significantly associated with higher International Prognostic Score (P ‫؍‬ .01), abnormal karyotype (P ‫؍‬ .05), the presence of excess blasts (P ‫؍‬ .01), and ageadjusted bone marrow hypercellularity (P ‫؍‬ .04). MDS patients had a display of the activating receptor NKp30, and NKG2D down-regulation closely correlated with impaired NK function (P ‫؍‬ . IntroductionThe myelodysplastic syndromes (MDS) are stem cell malignancies that display hematologic heterogeneity but share features of ineffective hematopoiesis and a potential for progression to acute myeloid leukemia (AML). 1,2 Multiple factors have been implicated in the pathogenesis of MDS, including cytogenetic and molecular abnormalities and disturbance in cellular immunity. Abnormal natural killer (NK) function, including reduced antibody-dependent cell cytotoxicity (ADCC) and diminished direct NK cell cytolytic function, have been previously described; however, the biologic mechanisms underlying these changes have not be defined. [3][4][5][6][7] Normal NK cells, ␥␦ T cells, and some ␣␤ T cells mediate their biologic action through 3 families of NK receptors: killer cell immunoglobulin-like receptors (KIRs), C lectin-like (NKG2) family receptors, and natural cytotoxicity receptors ([NCRs] eg, NKp30, NKp44, and NKp46). 8 Regulation of innate immunity occurs through balanced signaling by these families of NK receptors with activating and inhibitory function. [9][10][11] Constitutively expressed activating receptors such as NKp46 and NKp30 along with NKG2D mediate most non-major histocompatibility complex (non-MHC)-induced tumor-specific cytotoxicity by NK cells, and the activation-restricted NCR (NKp44) increases NK cytotoxicity after cytokine activation. 12 Although many NK receptors with both activating and inhibitory function have been identified and details of their downstream signaling pathways have been elucidated, a void exists in the identification of activatory NK ligands and the pathologic situations in which they are induced in tumor and virally infected cells. The best-characterized NK receptor ligands are the stress-inducible MHC class I-related chain A (MICA), MICB, and UL16-binding proteins (ULBPs), which constitute the major cellular ligands for human NKG2D. [13][14][15][16][17] In addition to viralinduced expression, NKG2D ligands are often expressed by tumor cells. 18,19 Ligands for NKp30, NKp44, and NKp46 have not yet been delineated.In MDS, the pathogenesis and clinical implications of reduced NK ...

Purpose We evaluated the efficacy of gemcitabine versus gemcitabine and carboplatin in patients with advanced non–small-cell lung cancer (NSCLC) and a performance status (PS) of 2 and assessed if tumoral RRM1 and ERCC1 protein levels are predictive of response to therapy. Patients and Methods A randomized phase III trial was conducted in community-based oncology practices. Tumor specimens were collected a priori and shipped to a single laboratory for blinded determination of in situ RRM1 and ERCC1 protein expression levels by an automated quantitative immunofluorescent-based technology. Results One hundred seventy patients were randomly assigned. Overall median survival was 5.1 months for gemcitabine and 6.7 months for gemcitabine and carboplatin (P = .24). RRM1 (range, 5.3 to 105.6; median, 34.1) and ERCC1 (range, 5.2 to 131.3; median, 34.7) values were significantly and inversely correlated with disease response (r = −0.41; P = .001 for RRM1; r = −0.39; P = .003 for ERCC1; ie, response was better for patients with low levels of expression). A model for response prediction that included RRM1, ERCC1, and treatment arm, was highly predictive of the treatment response observed (P = .0005). We did not find statistically significant associations between survival and RRM1 or ERCC1 levels. Conclusion Single-agent chemotherapy remains the standard of care for patients with advanced NSCLC and poor PS. Quantitative analysis of RRM1 and ERCC1 protein expression in routinely collected tumor specimens in community oncology practices is predictive of response to gemcitabine and gemcitabine and carboplatin therapy. Oncologists should consider including in situ expression analysis for these proteins into their therapeutic decisions.