Association of improved air quality with lower dementia risk in older women.

Late-life ambient air pollution is a risk factor for brain aging, but it remains unknown if improved air quality (AQ) lowers dementia risk. We studied a geographically diverse cohort of older women dementia free at baseline in 2008 to 2012 (n = 2,239, aged 74 to 92). Incident dementia was centrally adjudicated annually. Yearly mean concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated using regionalized national universal kriging models and averaged over the 3-y period before baseline (recent exposure) and 10 y earlier (remote exposure). Reduction from remote to recent exposures was used as the indicator of improved AQ. Cox proportional hazard ratios (HRs) for dementia risk associated with AQ measures were estimated, adjusting for sociodemographic, lifestyle, and clinical characteristics. We identified 398 dementia cases during follow up (median = 6.1 y). PM2.5 and NO2 reduced significantly over the 10 y before baseline. Larger AQ improvement was associated with reduced dementia risks (HRPM2.5 0.80 per 1.78 µg/m3, 95% CI 0.71-0.91; HRNO2 0.80 per 3.91 parts per billion, 95% CI 0.71-0.90), equivalent to the lower risk observed in women 2.4 y younger at baseline. Higher PM2.5 at baseline was associated with higher dementia risk (HRPM2.5 1.16 per 2.90 µg/m3, 95% CI 0.98-1.38), but the lower dementia risk associated with improved AQ remained after further adjusting for recent exposure. The observed associations did not substantially differ by age, education, geographic region, Apolipoprotein E e4 genotypes, or cardiovascular risk factors. Long-term AQ improvement in late life was associated with lower dementia risk in older women.

Mutational analysis of microsatellite-stable gastrointestinal cancer with high tumour mutational burden: a retrospective cohort study.

BACKGROUND: Genomic signatures contributing to high tumour mutational burden (TMB-H) independent from mismatch-repair deficiency (dMMR) or microsatellite instability-high (MSI-H) status are not well studied. We aimed to characterise molecular features of microsatellite stable (MSS) TMB-H gastrointestinal tumours. METHODS: Molecular alterations of 48 606 gastrointestinal tumours from Caris Life Sciences (CARIS) identified with next-generation sequencing were compared among MSS-TMB-H, dMMR/MSI-H, and MSS-TMB-low (L) tumours, using χ2 or Fisher's exact tests. Antitumour immune response within the tumour environment was predicted by analysing the infiltration of immune cells and immune signatures using The Cancer Genome Atlas database. The Kaplan-Meier method and the log-rank test were used to evaluate the impact of gene alterations on the efficacy of immune checkpoint inhibitors in MSS gastrointestinal cancers from the CARIS database, a Memorial Sloan Kettering Cancer Center cohort, and a Peking University Cancer Hospital cohort. FINDINGS: MSS-TMB-H was observed in 1600 (3·29%) of 48 606 tumours, dMMR/MSI-H in 2272 (4·67%), and MSS-TMB-L in 44 734 (92·03%). Gene mutations in SMAD2, MTOR, NFE2L2, RB1, KEAP1, TERT, and RASA1 might impair antitumour immune response despite TMB-H, while mutations in 16 other genes (CDC73, CTNNA1, ERBB4, EZH2, JAK2, MAP2K1, MAP2K4, PIK3R1, POLE, PPP2R1A, PPP2R2A, PTPN11, RAF1, RUNX1, STAG2, and XPO1) were related to TMB-H with enhanced antitumour immune response independent of dMMR/MSI-H, constructing a predictive model (modified TMB [mTMB]) for immune checkpoint inhibitor efficacy. Patients with any mutation in the mTMB gene signature, in comparison with patients with mTMB wildtype tumours, showed a superior survival benefit from immune checkpoint inhibitors in MSS gastrointestinal cancers in the CARIS cohort (n=95, median overall survival 18·77 months [95% CI 17·30-20·23] vs 7·03 months [5·73-8·34]; hazard ratio 0·55 [95% CI 0·31-0·99], p=0·044). In addition, copy number amplification in chromosome 11q13 (eg, CCND1, FGF genes) was more prevalent in MSS-TMB-H tumours than in the dMMR/MSI-H or MSS-TMB-L subgroups. INTERPRETATION: Not all mutations related to TMB-H can enhance antitumour immune response. More composite biomarkers should be investigated (eg, mTMB signature) to tailor treatment with immune checkpoint inhibitors. Our data also provide novel insights for the combination of immune checkpoint inhibitors and drugs targeting cyclin D1 or FGFs. FUNDING: US National Cancer Institute, Gloria Borges WunderGlo Foundation, Dhont Family Foundation, Gene Gregg Pancreas Research Fund, San Pedro Peninsula Cancer Guild, Daniel Butler Research Fund, Victoria and Philip Wilson Research Fund, Fong Research Project, Ming Hsieh Research Fund, Shanghai Sailing Program, China National Postdoctoral Program for Innovative Talents, China Postdoctoral Science Foundation, National Natural Science Foundation of China.

CausNet: generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraints.

BACKGROUND: Finding a globally optimal Bayesian Network using exhaustive search is a problem with super-exponential complexity, which severely restricts the number of variables that can feasibly be included. We implement a dynamic programming based algorithm with built-in dimensionality reduction and parent set identification. This reduces the search space substantially and can be applied to large-dimensional data. We use what we call 'generational orderings' based search for optimal networks, which is a novel way to efficiently search the space of possible networks given the possible parent sets. The algorithm supports both continuous and categorical data, as well as continuous, binary and survival outcomes. RESULTS: We demonstrate the efficacy of our algorithm on both synthetic and real data. In simulations, our algorithm performs better than three state-of-art algorithms that are currently used extensively. We then apply it to an Ovarian Cancer gene expression dataset with 513 genes and a survival outcome. Our algorithm is able to find an optimal network describing the disease pathway consisting of 6 genes leading to the outcome node in just 3.4 min on a personal computer with a 2.3 GHz Intel Core i9 processor with 16 GB RAM. CONCLUSIONS: Our generational orderings based search for optimal networks is both an efficient and highly scalable approach for finding optimal Bayesian Networks and can be applied to 1000 s of variables. Using specifiable parameters-correlation, FDR cutoffs, and in-degree-one can increase or decrease the number of nodes and density of the networks. Availability of two scoring option-BIC and Bge-and implementation for survival outcomes and mixed data types makes our algorithm very suitable for many types of high dimensional data in a variety of fields.

CCNE1 and survival of patients with tubo-ovarian high-grade serous carcinoma: An Ovarian Tumor Tissue Analysis consortium study.

BACKGROUND: Cyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC. METHODS: Within the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated. RESULTS: High-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss. CONCLUSION: This study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

Air quality improvement and cognitive decline in community-dwelling older women in the United States: A longitudinal cohort study.

BACKGROUND: Late-life exposure to ambient air pollution is a modifiable risk factor for dementia, but epidemiological studies have shown inconsistent evidence for cognitive decline. Air quality (AQ) improvement has been associated with improved cardiopulmonary health and decreased mortality, but to the best of our knowledge, no studies have examined the association with cognitive function. We examined whether AQ improvement was associated with slower rate of cognitive decline in older women aged 74 to 92 years. METHODS AND FINDINGS: We studied a cohort of 2,232 women residing in the 48 contiguous US states that were recruited from more than 40 study sites located in 24 states and Washington, DC from the Women's Health Initiative (WHI) Memory Study (WHIMS)-Epidemiology of Cognitive Health Outcomes (WHIMS-ECHO) study. They were predominantly non-Hispanic White women and were dementia free at baseline in 2008 to 2012. Measures of annual (2008 to 2018) cognitive function included the modified Telephone Interview for Cognitive Status (TICSm) and the telephone-based California Verbal Learning Test (CVLT). We used regionalized universal kriging models to estimate annual concentrations (1996 to 2012) of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) at residential locations. Estimates were aggregated to the 3-year average immediately preceding (recent exposure) and 10 years prior to (remote exposure) WHIMS-ECHO enrollment. Individual-level improved AQ was calculated as the reduction from remote to recent exposures. Linear mixed effect models were used to examine the associations between improved AQ and the rates of cognitive declines in TICSm and CVLT trajectories, adjusting for sociodemographic (age; geographic region; race/ethnicity; education; income; and employment), lifestyle (physical activity; smoking; and alcohol), and clinical characteristics (prior hormone use; hormone therapy assignment; depression; cardiovascular disease (CVD); hypercholesterolemia; hypertension; diabetes; and body mass index [BMI]). For both PM2.5 and NO2, AQ improved significantly over the 10 years before WHIMS-ECHO enrollment. During a median of 6.2 (interquartile range [IQR] = 5.0) years of follow-up, declines in both general cognitive status (ß = -0.42/year, 95% CI: -0.44, -0.40) and episodic memory (ß = -0.59/year, 95% CI: -0.64, -0.54) were observed. Greater AQ improvement was associated with slower decline in TICSm (ßPM2.5improvement = 0.026 per year for improved PM2.5 by each IQR = 1.79 µg/m3 reduction, 95% CI: 0.001, 0.05; ßNO2improvement = 0.034 per year for improved NO2 by each IQR = 3.92 parts per billion [ppb] reduction, 95% CI: 0.01, 0.06) and CVLT (ßPM2.5 improvement = 0.070 per year for improved PM2.5 by each IQR = 1.79 µg/m3 reduction, 95% CI: 0.02, 0.12; ßNO2improvement = 0.060 per year for improved NO2 by each IQR = 3.97 ppb reduction, 95% CI: 0.005, 0.12) after adjusting for covariates. The respective associations with TICSm and CVLT were equivalent to the slower decline rate found with 0.9 to 1.2 and1.4 to 1.6 years of younger age and did not significantly differ by age, region, education, Apolipoprotein E (ApoE) e4 genotypes, or cardiovascular risk factors. The main limitations of this study include measurement error in exposure estimates, potential unmeasured confounding, and limited generalizability. CONCLUSIONS: In this study, we found that greater improvement in long-term AQ in late life was associated with slower cognitive declines in older women. This novel observation strengthens the epidemiologic evidence of an association between air pollution and cognitive aging.

Germline polymorphisms in genes maintaining the replication fork predict the efficacy of oxaliplatin and irinotecan in patients with metastatic colorectal cancer.

BACKGROUND: The TIMELESS-TIPIN complex protects the replication fork from replication stress induced by chemotherapeutic drugs. We hypothesised genetic polymorphisms of the TIMELESS-TIPIN complex may affect the response, progression-free survival (PFS), and overall survival (OS) of cytotoxic drugs in patients with metastatic colorectal cancer (mCRC). METHODS: We analysed data from the MAVERICC trial, which compared FOLFOX/bevacizumab and FOLFIRI/bevacizumab in untreated patients with mCRC. Genomic DNA extracted from blood samples was genotyped using an OncoArray. Eight functional single nucleotide polymorphisms (SNPs) in TIMELESS and TIPIN were tested for associations with clinical outcomes. RESULTS: In total, 324 patients were included (FOLFOX/bevacizumab arm, n = 161; FOLFIRI/bevacizumab arm, n = 163). In the FOLFOX/bevacizumab arm, no SNPs displayed confirmed associations with survival outcomes. In the FOLFIRI/bevacizumab arm, TIMELESS rs2291739 was significantly associated with OS in multivariate analysis (G/G vs. any A allele, hazard ratio = 3.06, 95% confidence interval = 1.49-6.25, p = 0.004). TIMELESS rs2291739 displayed significant interactions with treatment regarding both PFS and OS. CONCLUSIONS: TIMELESS rs2291739 might have different effects on therapeutic efficacy between oxaliplatin- and irinotecan-based chemotherapies. Upon further validation, our findings may be useful for personalised approaches in the first-line treatment of mCRC.

Partition: a surjective mapping approach for dimensionality reduction.

MOTIVATION: Large amounts of information generated by genomic technologies are accompanied by statistical and computational challenges due to redundancy, badly behaved data and noise. Dimensionality reduction (DR) methods have been developed to mitigate these challenges. However, many approaches are not scalable to large dimensions or result in excessive information loss. RESULTS: The proposed approach partitions data into subsets of related features and summarizes each into one and only one new feature, thus defining a surjective mapping. A constraint on information loss determines the size of the reduced dataset. Simulation studies demonstrate that when multiple related features are associated with a response, this approach can substantially increase the number of true associations detected as compared to principal components analysis, non-negative matrix factorization or no DR. This increase in true discoveries is explained both by a reduced multiple-testing challenge and a reduction in extraneous noise. In an application to real data collected from metastatic colorectal cancer tumors, more associations between gene expression features and progression free survival and response to treatment were detected in the reduced than in the full untransformed dataset. AVAILABILITY AND IMPLEMENTATION: Freely available R package from CRAN, https://cran.r-project.org/package=partition. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Association of HLA Genotype With T-Cell Activation in Human Immunodeficiency Virus (HIV) and HIV/Hepatitis C Virus-Coinfected Women.

BACKGROUND: Global immune activation and HLA alleles are each associated with the pathogenesis of human immunodeficiency virus (HIV) and hepatitis C virus . METHODS: We evaluated the relationship between 44 HLA class I and 28 class II alleles and percentages of activated CD8 (CD8+CD38+DR+) and CD4 (CD4+CD38+DR+) T cells in 586 women who were naive to highly active antiretroviral therapy. We used linear generalized estimating equation regression models, adjusting for race/ethnicity, age, HIV load, and hepatitis C virus infection and controlling for multiplicity using a false discovery rate threshold of 0.10. RESULTS: Ten HLA alleles were associated with CD8 and/or CD4 T-cell activation. Lower percentages of activated CD8 and/or CD4 T cells were associated with protective alleles B*57:03 (CD8 T cells, -6.6% [P = .002]; CD4 T cells, -2.7% [P = .007]), C*18:01 (CD8 T cells, -6.6%; P < .0008) and DRB1*13:01 (CD4 T cells, -2.7%; P < .0004), and higher percentages were found with B*18:01 (CD8 T cells, 6.2%; P < .0003), a detrimental allele. Other alleles/allele groups associated with activation included C*12:03, group DQA1*01:00, DQB1*03:01, DQB1*03:02, DQB1*06:02, and DQB1*06:03. CONCLUSION: These findings suggest that a person's HLA type may play a role in modulating T-cell activation independent of viral load and sheds light on the relationship between HLA, T-cell activation, immune control, and HIV pathogenesis.

Infectious mononucleosis, immune genotypes, and non-Hodgkin lymphoma (NHL): an InterLymph Consortium study.

PURPOSE: We explored the interaction between non-Hodgkin lymphoma (NHL), infectious mononucleosis (IM) history, and immune-related genotypes in a pooled case-control analysis. METHODS: A total of 7,926 NHL patients and 10,018 controls from 12 case-control studies were included. Studies were conducted during various time periods between 1988 and 2008, and participants were 17-96 years of age at the time of ascertainment/recruitment. Self-reported IM history and immune response genotypes were provided by the InterLymph Data Coordinating Center at Mayo Clinic. Odds ratios (OR) were estimated using multivariate logistic regression, and interactions were estimated using the empirical Bayes method. PACT was used to account for multiple comparisons. RESULTS: There was evidence of an interaction effect between IM history and two variants on T-cell lymphoma (TCL) risk: rs1143627 in interleukin-1B (IL1B) (pinteraction = 0.04, ORinteraction = 0.09, 95% confidence interval [CI] 0.01, 0.87) and rs1800797 in interleukin-6 (IL6) (pinteraction = 0.03, ORinteraction = 0.08, 95% CI 0.01, 0.80). Neither interaction effect withstood adjustment for multiple comparisons. There were no statistically significant interactions between immune response genotypes and IM on other NHL subtypes. CONCLUSIONS: Genetic risk variants in IL1B and IL6 may affect the association between IM and TCL, possibly by influencing T-cell activation, growth, and differentiation in the presence of IM, thereby decreasing risk of immune cell proliferation.

Correction to: Infectious mononucleosis, immune genotypes, and non-Hodgkin lymphoma (NHL): an InterLymph Consortium study.

Unfortunately, the word "Group" is missed in the article title of the original publication. It has been corrected by this erratum.

AMPK variant, a candidate of novel predictor for chemotherapy in metastatic colorectal cancer: A meta-analysis using TRIBE, MAVERICC and FIRE3.

AMP-activated protein kinase (AMPK) is a key sensor of energy homeostasis and regulates cell metabolism, proliferation and chemotherapy/radiotherapy sensitivities. This study aimed to explore the relationship between the AMPK pathway-related single nucleotide polymorphisms (SNPs) and clinical outcomes in patients with metastatic colorectal cancer (mCRC). We analyzed a total of 884 patients with mCRC enrolled in three randomized clinical trials (TRIBE, MAVERICC and FIRE-3: where patients were treated with FOLFIRI, mFOLFOX6 or FOLFOXIRI combined with bevacizumab or cetuximab as the first-line chemotherapy). The association between AMPK pathway-related SNPs and clinical outcomes was analyzed across the six treatment cohorts, using a meta-analysis approach. Our meta-analysis showed that AMPK pathway had significant associations with progression-free survival (PFS; p < 0.001) and overall survival (OS; p < 0.001), but not with tumor response (TR; p = 0.220): PRKAA1 rs13361707 was significantly associated with favorable PFS (log HR = -0.219, SE = 0.073, p = 0.003), as well as PRKAA1 rs10074991 (log HR = -0.215, SE = 0.073, p = 0.003), and there were suggestive associations of PRKAG1 rs1138908 with unfavorable OS (log HR = 0.170, SE = 0.083, p = 0.041), and of UBE2O rs3803739 with unfavorable PFS (log HR = 0.137, SE = 0.068, p = 0.042) and OS (log HR = 0.210, SE = 0.077, p = 0.006), although these results were not significant after false discovery rate adjustment. AMPK pathway-related SNPs may be predictors for chemotherapy in mCRC. Upon validation, our findings would provide novel insight for selecting treatment strategies.

Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search.

OBJECTIVES: There is evidence to suggest that asthma pathogenesis is affected by both genetic and epigenetic variation independently, and there is some evidence to suggest that genetic-epigenetic interactions affect risk of asthma. However, little research has been done to identify such interactions on a genome-wide scale. The aim of this studies was to identify genes with genetic-epigenetic interactions associated with asthma. METHODS: Using asthma case-control data, we applied a novel nonparametric gene-centric approach to test for interactions between multiple SNPs and CpG sites simultaneously in the vicinities of 18,178 genes across the genome. RESULTS: Twelve genes, PF4, ATF3, TPRA1, HOPX, SCARNA18, STC1, OR10K1, UPK1B, LOC101928523, LHX6, CHMP4B, and LANCL1, exhibited statistically significant SNP-CpG interactions (false discovery rate = 0.05). Of these, three have previously been implicated in asthma risk (PF4, ATF3, and TPRA1). Follow-up analysis revealed statistically significant pairwise SNP-CpG interactions for several of these genes, including SCARNA18, LHX6, and LOC101928523 (p = 1.33E-04, 8.21E-04, 1.11E-03, respectively). CONCLUSIONS: Joint effects of genetic and epigenetic variation may play an important role in asthma pathogenesis. Statistical methods that simultaneously account for multiple variations across chromosomal regions may be needed to detect these types of effects on a genome-wide scale.

Gene Expression Profiling in Blood Provides Reproducible Molecular Insights into Asthma Control.

RATIONALE: Maintaining optimal symptom control remains the primary objective of asthma treatment. Better understanding of the biologic underpinnings of asthma control may lead to the development of improved clinical and pharmaceutical approaches. OBJECTIVES: To identify molecular pathways and interrelated genes whose differential expression was associated with asthma control. METHODS: We performed gene set enrichment analyses of asthma control in 1,170 adults with asthma, each with gene expression data derived from either whole blood (WB) or unstimulated CD4+ T lymphocytes (CD4), and a self-reported asthma control score representing either the preceding 6 months (chronic) or 7 days (acute). Our study comprised a discovery WB cohort (n = 245, chronic) and three independent, nonoverlapping replication cohorts: a second WB set (n = 448, acute) and two CD4 sets (n = 300, chronic; n = 77, acute). MEASUREMENTS AND MAIN RESULTS: In the WB discovery cohort, we found significant overrepresentation of genes associated with asthma control in 1,106 gene sets from the Molecular Signatures Database (false discovery rate, <5%). Of these, 583 (53%) replicated in at least one replication cohort (false discovery rate, <25%). Suboptimal control was associated with signatures of eosinophilic and granulocytic inflammatory signals, whereas optimal control signatures were enriched for immature lymphocytic patterns. These signatures included two related biologic processes related to activation by TREM-1 (triggering receptor expressed on myeloid cells 1) and lipopolysaccharide. CONCLUSIONS: Together, these results demonstrate the existence of specific, reproducible transcriptomic components in blood that vary with degree of asthma control and implicate a novel biologic target (TREM-1).

cit: hypothesis testing software for mediation analysis in genomic applications.

MOTIVATION: The challenges of successfully applying causal inference methods include: (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. RESULTS: The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P-values and optionally permutation-based FDR estimates (q-values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. CONCLUSION: Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. AVAILABILITY AND IMPLEMENTATION: The cit open-source R package is freely available from the CRAN website (https://cran.r-project.org/web/packages/cit/index.html) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available (http://www.gnu.org/software/gsl/). CONTACT: joshua.millstein@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

NPPB is a novel candidate biomarker expressed by cancer-associated fibroblasts in epithelial ovarian cancer.

Most solid tumors contain cancer-associated fibroblasts (CAFs) that support tumorigenesis and malignant progression. However, the cellular origins of CAFs in epithelial ovarian cancers (EOCs) remain poorly understood, and their utility as a source of clinical biomarkers for cancer diagnosis has not been explored in great depth. Here, we report establishing in vitro and in vivo models of CAFs in ovarian cancer development. Normal ovarian fibroblasts and mesenchymal stem cells cultured in the presence of EOC cells acquired a CAF-like phenotype, and promoted EOC cell migration in vitro. CAFs also promoted ovarian cancer growth in vivo in both subcutaneous and intraperitoneal murine xenograft assays. Molecular profiling of CAFs identified gene expression signatures that were highly enriched for extracellular and secreted proteins. We identified novel candidate CAF-specific biomarkers for ovarian cancer including NPPB, which was expressed in the stroma of 60% primary ovarian cancer tissues (n = 145) but not in the stroma of normal ovaries (n = 4). NPPB is a secreted protein that was also elevated in the blood of 50% of women with ovarian cancer (n = 8). Taken together, these data suggest that the tumor stroma is a novel source of biomarkers, including NPPB, that may be of clinical utility for detection of EOC.

Alteration of select gene expression patterns in individuals infected with HIV-1.

Multiple human proteins have been shown to both support and restrict viral replication, and confirmation of virus-associated changes in the expression of these genes is relevant for future therapeutic efforts. In this study a well-characterized panel of 49 individuals either infected with HIV-1 or uninfected was compiled and analyzed for the effect of HIV infection status, viral load, and antiretroviral treatment on specific gene expression. mRNA was extracted and reverse transcribed from purified CD4+ cells, and quantitative real-time PCR was utilized to scrutinize differences in the expression of four host genes that have been demonstrated to either stimulate (HSP90 and LEDGF/p75) or restrict (p21/WAF1 and APOBEC3G) proviral integration. HIV infection status was associated with slight to moderate alterations in the expression of all four genes. After adjusting for age, mRNA expression levels of HSP90, LEDGF/p75 and APOBEC3G were found to all be decreased in infected patients compared to healthy controls by 1.43-, 1.26-, and 4.71-fold, respectively, while p21/WAF1 expression was increased 2.35-fold. Furthermore, individuals receiving raltegravir exhibited a 1.28-fold reduction in LEDGF/p75 compared to those on non-raltegravir antiretroviral treatment. Identification of these and similar HIV-induced changes in gene expression may be valuable for delineating the extent of host cell molecular mechanisms stimulating viral replication.

CausNet-partial : 'Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints.

Background: In our recent work, we developed a novel dynamic programming algorithm to find optimal Bayesian networks (BNs) with parent set constraints. This 'generational orderings' based dynamic programming search algorithm - CausNet - efficiently searches the space of possible BNs given the possible parent sets. The algorithm supports both continuous and categorical data, as well as continuous, binary and survival outcomes. In the present work, we develop a variant of CausNet - CausNet-partial - which searches the space of 'partial generational orderings', which further reduces the search space and is suited for finding smaller sparse optimal Bayesian networks; and can be applied to 1000s of variables. Results: We test this method both on synthetic and real data. Our algorithm performs better than three state-of-art algorithms that are currently used extensively to find optimal BNs. We apply it to simulated continuous data and also to a benchmark discrete Bayesian network ALARM, a Bayesian network designed to provide an alarm message system for patient monitoring. We first apply the original CausNet and then CausNet-partial varying the partial order from 5 to 2. CausNet-partial discovers small sparse networks with drastically reduced runtime as expected from theory. Conclusions: Our partial generational orderings based search for small optimal networks, is both an efficient and highly scalable approach for finding optimal sparse and small Bayesian Networks and can be applied to 1000s of variables. Using specifiable parameters - correlation, FDR cutoffs, in-degree, and partial order - one can increase or decrease the number of nodes and density of the networks. Availability of two scoring option - BIC and Bge - and implementation for survival outcomes and mixed data types makes our algorithm very suitable for many types of high dimensional data in a variety of fields.

Exploring Predictive and Prognostic Biomarkers in Colorectal Cancer: A Comprehensive Review.

Colorectal cancer (CRC) remains the second leading cause of cancer-related mortality worldwide. While immune checkpoint inhibitors have significantly improved patient outcomes, their effectiveness is mostly limited to tumors with microsatellite instability (MSI-H/dMMR) or an increased tumor mutational burden, which comprise 10% of cases. Advancing personalized medicine in CRC hinges on identifying predictive biomarkers to guide treatment decisions. This comprehensive review examines established tissue markers such as KRAS and HER2, highlighting their roles in resistance to anti-EGFR agents and discussing advances in targeted therapies for these markers. Additionally, this review summarizes encouraging data on promising therapeutic targets and highlights the clinical utility of liquid biopsies. By synthesizing current evidence and identifying knowledge gaps, this review provides clinicians and researchers with a contemporary understanding of the biomarker landscape in CRC. Finally, the review examines future directions and challenges in translating promising biomarkers into clinical practice, with the goal of enhancing personalized medicine approaches for colorectal cancer patients.

Predictive value of CDC37 gene expression for targeted therapy in metastatic colorectal cancer.

BACKGROUND: CDC37 is a key determinant of client kinase recruitment to the HSP90 chaperoning system. We hypothesized that kinase-specific dependency on CDC37 alters the efficacy of targeted therapies for metastatic colorectal cancer (mCRC). MATERIAL AND METHODS: Two independent mCRC cohorts were analyzed to compare the survival outcomes between CDC37-high and CDC37-low patients (stratified by the median cutoff values): the CALGB/SWOG 80405 trial (226 and 207 patients receiving first-line bevacizumab- and cetuximab-containing chemotherapies, respectively) and Japanese retrospective (50 refractory patients receiving regorafenib) cohorts. A dataset of specimens submitted to a commercial CLIA-certified laboratory was utilized to characterize molecular profiles of CDC37-high (top quartile, N = 5055) and CDC37-low (bottom quartile, N = 5055) CRCs. RESULTS: In the bevacizumab-treated group, CDC37-high patients showed significantly better progression-free survival (PFS) (median 13.3 vs 9.6 months, hazard ratio [HR] 0.59, 95% confidence interval [CI] 0.44-0.79, p < 0.01) than CDC37-low patients. In the cetuximab-treated group, CDC37-high and CDC37-low patients had similar outcomes. In the regorafenib-treated group, CDC37-high patients showed significantly better overall survival (median 11.3 vs 6.0 months, HR 0.24, 95% CI 0.11-0.54, p < 0.01) and PFS (median 3.5 vs 1.9 months, HR 0.51, 95% CI 0.28-0.94, p = 0.03). Comprehensive molecular profiling revealed that CDC37-high CRCs were associated with higher VEGFA, FLT1, and KDR expressions and activated hypoxia signature. CONCLUSIONS: CDC37-high mCRC patients derived more benefit from anti-VEGF therapies, including bevacizumab and regorafenib, but not from cetuximab. Molecular profiles suggested that such tumors were dependent on angiogenesis-relating pathways.