Cognitive status and behavioral problems in older hospitalized patients

OBJECTIVES: (a) To determine the quantity and quality of behavioral problems in older hospitalized patients on acute care units; (b) to determine the burden of these behaviors on staff; and (c) to identify predictors of behavioral problems. METHODS: Upon admission, patients performed the Mini-Mental State Exam (MMSE), the Geriatric Depression Scale (GDS), and information was obtained on age, ethnicity, level of education, living arrangement, and psychiatric history. Two days post-admission, a clinical staff member caring for each patient, performed the Neuropsychiatric Inventory-Questionnaire (NPI-Q) to assess patients' behavioral problems and staff distress. PARTICIPANTS AND SETTING: Forty-two patients, over 60 years of age, admitted to medical and surgical units of the Veterans Affairs Hospitals in Palo Alto and San Francisco, participated. RESULTS: Twenty-three of 42 (55%) patients exhibited behavioral problems. Anxiety, depression, irritability, and agitation/aggression were the most frequently observed behaviors. The severity of the behavioral problems was significantly correlated with staff distress. Lower performance on the MMSE at admission was significantly associated with higher NPI-Q ratings. Specifically, of those cases with scores less than or equal to 27 on the MMSE, 66% had behavioral problems during hospitalization, compared to only 31% of those with scores greater than 27. CONCLUSION: Behavioral problems in older hospitalized patients appear to occur frequently, are a significant source of distress to staff, and can result in the need for psychiatric consultation. Assessment of the mental status of older adults at admission to hospital may be valuable in identifying individuals at increased risk for behavioral problems during hospitalization

Immunogenic cell death pathway polymorphisms for predicting oxaliplatin efficacy in metastatic colorectal cancer

Background Immunogenic cell death (ICD) is a tumor cell death involving both innate and adaptive immune responses. Given published findings that oxaliplatin, but not irinotecan, drives ICD, we investigated whether single nucleotide polymorphisms (SNPs) in the ICD pathway are associated with the efficacy of oxaliplatin-based chemotherapy in metastatic colorectal cancer (mCRC). Methods Two randomized clinical trials data were analyzed: discovery cohort, FOLFOX/bevacizumab arm (MAVERICC); validation cohort, FOLFOXIRI/bevacizumab arm (TRIBE); and two control cohorts, FOLFIRI/bevacizumab arms (both trials). Genomic DNA extracted from blood samples was genotyped. Ten SNPs in the ICD pathway were tested for associations with clinical outcomes. Results In total, 648 patients were included. In the discovery cohort, three SNPs were significantly associated with clinical outcomes in univariate analysis: CALR rs1010222 with progression-free survival (G/G vs any A, HR=0.61, 95% CI 0.43-0.88), ANXA1 rs1050305 with overall survival (OS) (A/A vs any G, HR=1.87, 95% CI 1.04-3.35), and LRP1 rs1799986 with OS (C/C vs any T, HR=1.69, 95% CI 1.07-2.70). Multivariate analysis confirmed the trend, but statistical significance was not reached. In the validation cohort, ANXA1 rs1050305, and LRP1 rs1799986 were validated to have the significant associations with clinical outcome. No significant associations of these SNPs were observed in the two control cohorts. Treatment-by-SNP interaction test confirmed the predictive values. Conclusions The predictive utility of ICD-related SNPs for the efficacy of oxaliplatin-based chemotherapy was demonstrated, warranting further validation studies to be translated into personalized treatment strategies using conventional cytotoxic agents in mCRC

Emergence of Anti-Cancer Drug Resistance: Exploring the Importance of the Microenvironmental Niche via a Spatial Model

Practically, all chemotherapeutic agents lead to drug resistance. Clinically, it is a challenge to determine whether resistance arises prior to, or as a result of, cancer therapy. Further, a number of different intracellular and microenvironmental factors have been correlated with the emergence of drug resistance. With the goal of better understanding drug resistance and its connection with the tumor microenvironment, we have developed a hybrid discrete-continuous mathematical model. In this model, cancer cells described through a particle-spring approach respond to dynamically changing oxygen and DNA damaging drug concentrations described through partial differential equations. We thoroughly explored the behavior of our self-calibrated model under the following common conditions: a fixed layout of the vasculature, an identical initial configuration of cancer cells, the same mechanism of drug action, and one mechanism of cellular response to the drug. We considered one set of simulations in which drug resistance existed prior to the start of treatment, and another set in which drug resistance is acquired in response to treatment. This allows us to compare how both kinds of resistance influence the spatial and temporal dynamics of the developing tumor, and its clonal diversity. We show that both pre-existing and acquired resistance can give rise to three biologically distinct parameter regimes: successful tumor eradication, reduced effectiveness of drug during the course of treatment (resistance), and complete treatment failure

MultiCellDS : a community-developed standard for curating microenvironment-dependent multicellular data

Exchanging and understanding scientific data and their context represents a significant barrier to advancing research, especially with respect to information siloing. Maintaining information provenance and providing data curation and quality control help overcome common concerns and barriers to the effective sharing of scientific data. To address these problems in and the unique challenges of multicellular systems, we assembled a panel composed of investigators from several disciplines to create the MultiCellular Data Standard (MultiCellDS) with a use-case driven development process. The standard includes (1) digital cell lines, which are analogous to traditional biological cell lines, to record metadata, cellular microenvironment, and cellular phenotype variables of a biological cell line, (2) digital snapshots to consistently record simulation, experimental, and clinical data for multicellular systems, and (3) collections that can logically group digital cell lines and snapshots. We have created a MultiCellular DataBase (MultiCellDB) to store digital snapshots and the 200+ digital cell lines we have generated. MultiCellDS, by having a fixed standard, enables discoverability, extensibility, maintainability, searchability, and sustainability of data, creating biological applicability and clinical utility that permits us to identify upcoming challenges to uplift biology and strategies and therapies for improving human health

Elevated MED28 expression predicts poor outcome in women with breast cancer

Abstract Background MED28 (also known as EG-1 and magicin) has been implicated in transcriptional control, signal regulation, and cell proliferation. MED28 has also been associated with tumor progression in in vitro and in vivo models. Here we examined the association of MED28 expression with human breast cancer progression. Methods Expression of MED28 protein was determined on a population basis using a high-density tissue microarray consisting of 210 breast cancer patients. The association and validation of MED28 expression with histopathological subtypes, clinicopathological variables, and disease outcome was assessed. Results MED28 protein expression levels were increased in ductal carcinoma in situ and invasive ductal carcinoma of the breast compared to non-malignant glandular and ductal epithelium. Moreover, MED28 was a predictor of disease outcome in both univariate and multivariate analyses with higher expression predicting a greater risk of disease-related death. Conclusions We have demonstrated that MED28 expression is increased in breast cancer. In addition, although the patient size was limited (88 individuals with survival information) MED28 is a novel and strong independent prognostic indicator of survival for breast cancer

Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies

Androgen-Regulated Expression of Arginase 1, Arginase 2 and Interleukin-8 in Human Prostate Cancer

BACKGROUND: Prostate cancer (PCa) is the most frequently diagnosed cancer in North American men. Androgen-deprivation therapy (ADT) accentuates the infiltration of immune cells within the prostate. However, the immunosuppressive pathways regulated by androgens in PCa are not well characterized. Arginase 2 (ARG2) expression by PCa cells leads to a reduced activation of tumor-specific T cells. Our hypothesis was that androgens could regulate the expression of ARG2 by PCa cells. METHODOLOGY/PRINCIPAL FINDINGS: In this report, we demonstrate that both ARG1 and ARG2 are expressed by hormone-sensitive (HS) and hormone-refractory (HR) PCa cell lines, with the LNCaP cells having the highest arginase activity. In prostate tissue samples, ARG2 was more expressed in normal and non-malignant prostatic tissues compared to tumor tissues. Following androgen stimulation of LNCaP cells with 10 nM R1881, both ARG1 and ARG2 were overexpressed. The regulation of arginase expression following androgen stimulation was dependent on the androgen receptor (AR), as a siRNA treatment targeting the AR inhibited both ARG1 and ARG2 overexpression. This observation was correlated in vivo in patients by immunohistochemistry. Patients treated by ADT prior to surgery had lower ARG2 expression in both non-malignant and malignant tissues. Furthermore, ARG1 and ARG2 were enzymatically active and their decreased expression by siRNA resulted in reduced overall arginase activity and l-arginine metabolism. The decreased ARG1 and ARG2 expression also translated with diminished LNCaP cells cell growth and increased PBMC activation following exposure to LNCaP cells conditioned media. Finally, we found that interleukin-8 (IL-8) was also upregulated following androgen stimulation and that it directly increased the expression of ARG1 and ARG2 in the absence of androgens. CONCLUSION/SIGNIFICANCE: Our data provides the first detailed in vitro and in vivo account of an androgen-regulated immunosuppressive pathway in human PCa through the expression of ARG1, ARG2 and IL-8

MultiCellDS: a community-developed standard for curating microenvironment-dependent multicellular data

Exchanging and understanding scientific data and their context represents a significant barrier to advancing research, especially with respect to information siloing. Maintaining information provenance and providing data curation and quality control help overcome common concerns and barriers to the effective sharing of scientific data. To address these problems in and the unique challenges of multicellular systems, we assembled a panel composed of investigators from several disciplines to create the MultiCellular Data Standard (MultiCellDS) with a use-case driven development process. The standard includes (1) digital cell lines, which are analogous to traditional biological cell lines, to record metadata, cellular microenvironment, and cellular phenotype variables of a biological cell line, (2) digital snapshots to consistently record simulation, experimental, and clinical data for multicellular systems, and (3) collections that can logically group digital cell lines and snapshots. We have created a MultiCellular DataBase (MultiCellDB) to store digital snapshots and the 200+ digital cell lines we have generated. MultiCellDS, by having a fixed standard, enables discoverability, extensibility, maintainability, searchability, and sustainability of data, creating biological applicability and clinical utility that permits us to identify upcoming challenges to uplift biology and strategies and therapies for improving human health