Prevalent cases in observational studies of cancer survival: do they bias hazard ratio estimates?

Observational epidemiological studies often include prevalent cases recruited at various times past diagnosis. This left truncation can be dealt with in non-parametric (Kaplan–Meier) and semi-parametric (Cox) time-to-event analyses, theoretically generating an unbiased hazard ratio (HR) when the proportional hazards (PH) assumption holds. However, concern remains that inclusion of prevalent cases in survival analysis results inevitably in HR bias. We used data on three well-established breast cancer prognosticators – clinical stage, histopathological grade and oestrogen receptor (ER) status – from the SEARCH study, a population-based study including 4470 invasive breast cancer cases (incident and prevalent), to evaluate empirically the effectiveness of allowing for left truncation in limiting HR bias. We found that HRs of prognostic factors changed over time and used extended Cox models incorporating time-dependent covariates. When comparing Cox models restricted to subjects ascertained within six months of diagnosis (incident cases) to models based on the full data set allowing for left truncation, we found no difference in parameter estimates (P=0.90, 0.32 and 0.95, for stage, grade and ER status respectively). Our results show that use of prevalent cases in an observational epidemiological study of breast cancer does not bias the HR in a left truncation Cox survival analysis, provided the PH assumption holds true

Loss of RhoB Expression Enhances the Myelodysplastic Phenotype of Mammalian Diaphanous-Related Formin mDia1 Knockout Mice

Myelodysplastic syndrome (MDS) is characterized by ineffective hematopoiesis and hyperplastic bone marrow. Complete loss or interstitial deletions of the long arm of chromosome 5 occur frequently in MDS. One candidate tumor suppressor on 5q is the mammalian Diaphanous (mDia)-related formin mDia1, encoded by DIAPH1 (5q31.3). mDia-family formins act as effectors for Rho-family small GTP-binding proteins including RhoB, which has also been shown to possess tumor suppressor activity. Mice lacking the Drf1 gene that encodes mDia1 develop age-dependent myelodysplastic features. We crossed mDia1 and RhoB knockout mice to test whether the additional loss of RhoB expression would compound the myelodysplastic phenotype. Drf1−/−RhoB−/− mice are fertile and develop normally. Relative to age-matched Drf1−/−RhoB+/− mice, the age of myelodysplasia onset was earlier in Drf1−/−RhoB−/− animals—including abnormally shaped erythrocytes, splenomegaly, and extramedullary hematopoiesis. In addition, we observed a statistically significant increase in the number of activated monocytes/macrophages in both the spleen and bone marrow of Drf1−/−RhoB−/− mice relative to Drf1−/−RhoB+/− mice. These data suggest a role for RhoB-regulated mDia1 in the regulation of hematopoietic progenitor cells

Genetic Variants in TGF-β Pathway Are Associated with Ovarian Cancer Risk

The transforming growth factor-β (TGF-β) signaling pathway is involved in a diverse array of cellular processes responsible for tumorigenesis. In this case-control study, we applied a pathway-based approach to evaluate single-nucleotide polymorphisms (SNPs) in the TGF-β signaling pathway as predictors of ovarian cancer risk. We systematically genotyped 218 SNPs from 21 genes in the TGF-β signaling pathway in 417 ovarian cancer cases and 417 matched control subjects. We analyzed the associations of these SNPs with ovarian cancer risk, performed haplotype analysis and identified potential cumulative effects of genetic variants. We also performed analysis to identify higher-order gene-gene interactions influencing ovarian cancer risk. Individual SNP analysis showed that the most significant SNP was SMAD6: rs4147407, with an adjusted odds ratio (OR) of 1.60 (95% confidence interval [CI], 1.14–2.24, P = 0.0066). Cumulative genotype analysis of 13 SNPs with significant main effects exhibited a clear dose-response trend of escalating risk with increasing number of unfavorable genotypes. In gene-based analysis, SMAD6 was identified as the most significant gene associated with ovarian cancer risk. Haplotype analysis further revealed that two haplotype blocks within SMAD6 were significantly associated with decreased ovarian cancer risk, as compared to the most common haplotype. Gene-gene interaction analysis further categorized the study population into subgroups with different ovarian cancer risk. Our findings suggest that genetic variants in the TGF-β signaling pathway are associated with ovarian cancer risk and may facilitate the identification of high-risk subgroups in the general population

TGF-β1 genotype and phenotype in breast cancer and their associations with IGFs and patient survival

Transforming growth factor-β (TGF-β)-mediated signals play complicated roles in the development and progression of breast tumour. The purposes of this study were to analyse the genotype of TGF-β1 at T29C and TGF-β1 phenotype in breast tumours, and to evaluate their associations with IGFs and clinical characteristics of breast cancer. Fresh tumour samples were collected from 348 breast cancer patients. TGF-β1 genotype and phenotype were analysed with TaqMan® and ELISA, respectively. Members of the IGF family in tumour tissue were measured with ELISA. Cox proportional hazards regression analysis was performed to assess the association of TGF-β1 and disease outcomes. Patients with the T/T (29%) genotype at T29C had the highest TGF-β1, 707.9 pg mg−1, followed by the T/C (49%), 657.8 pg mg−1, and C/C (22%) genotypes, 640.8 pg mg−1, (P=0.210, T/T vs C/C and C/T). TGF-β1 concentrations were positively correlated with levels of oestrogen receptor, IGF-I, IGF-II and IGFBP-3. Survival analysis showed TGF-β1 associated with disease progression, but the association differed by disease stage. For early-stage disease, patients with the T/T genotype or high TGF-β1 had shorter overall survival compared to those without T/T or with low TGF-β1; the hazard ratios (HR) were 3.54 (95% CI: 1.21–10.40) for genotype and 2.54 (95% CI: 1.10–5.89) for phenotype after adjusting for age, grade, histotype and receptor status. For late-stage disease, however, the association was different. The T/T genotype was associated with lower risk of disease recurrence (HR=0.13, 95% CI: 0.02–1.00), whereas no association was found between TGF-β1 phenotype and survival outcomes. The study suggests a complex role of TGF-β1 in breast cancer progression, which supports the finding of in vitro studies that TGF-β1 has conflicting effects on tumour growth and metastasis

Do genetic factors protect for early onset lung cancer? A case control study before the age of 50 years

<p>Abstract</p> <p>Background</p> <p>Early onset lung cancer shows some familial aggregation, pointing to a genetic predisposition. This study was set up to investigate the role of candidate genes in the susceptibility to lung cancer patients younger than 51 years at diagnosis.</p> <p>Methods</p> <p>246 patients with a primary, histologically or cytologically confirmed neoplasm, recruited from 2000 to 2003 in major lung clinics across Germany, were matched to 223 unrelated healthy controls. 11 single nucleotide polymorphisms of genes with reported associations to lung cancer have been genotyped.</p> <p>Results</p> <p>Genetic associations or gene-smoking interactions was found for <it>GPX1(Pro200Leu) </it>and <it>EPHX1(His113Tyr)</it>. Carriers of the Leu-allele of <it>GPX1(Pro200Leu) </it>showed a significant risk reduction of OR = 0.6 (95% CI: 0.4–0.8, p = 0.002) in general and of OR = 0.3 (95% CI:0.1–0.8, p = 0.012) within heavy smokers. We could also find a risk decreasing genetic effect for His-carriers of <it>EPHX1(His113Tyr) </it>for moderate smokers (OR = 0.2, 95% CI:0.1–0.7, p = 0.012). Considered both variants together, a monotone decrease of the OR was found for smokers (OR of 0.20; 95% CI: 0.07–0.60) for each protective allele.</p> <p>Conclusion</p> <p>Smoking is the most important risk factor for young lung cancer patients. However, this study provides some support for the T-Allel of <it>GPX1(Pro200Leu) </it>and the C-Allele of <it>EPHX1(His113Tyr) </it>to play a protective role in early onset lung cancer susceptibility.</p

Prognostic gene expression signature for high-grade serous ovarian cancer.

BACKGROUND: Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC. PATIENTS AND METHODS: Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies. RESULTS: Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years. CONCLUSION: The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches

A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in non-coding regions, and causal genes underlying these associations remain largely unknown. Here we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian-tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P<2.2×10-6, we identified 35 genes including FZD4 at 11q14.2 (Z=5.08, P=3.83×10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly-associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and 3 genes remained (P<1.47 x 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis

Mitochondrial dysfunction and biogenesis: do ICU patients die from mitochondrial failure?

Mitochondrial functions include production of energy, activation of programmed cell death, and a number of cell specific tasks, e.g., cell signaling, control of Ca2+ metabolism, and synthesis of a number of important biomolecules. As proper mitochondrial function is critical for normal performance and survival of cells, mitochondrial dysfunction often leads to pathological conditions resulting in various human diseases. Recently mitochondrial dysfunction has been linked to multiple organ failure (MOF) often leading to the death of critical care patients. However, there are two main reasons why this insight did not generate an adequate resonance in clinical settings. First, most data regarding mitochondrial dysfunction in organs susceptible to failure in critical care diseases (liver, kidney, heart, lung, intestine, brain) were collected using animal models. Second, there is no clear therapeutic strategy how acquired mitochondrial dysfunction can be improved. Only the benefit of such therapies will confirm the critical role of mitochondrial dysfunction in clinical settings. Here we summarized data on mitochondrial dysfunction obtained in diverse experimental systems, which are related to conditions seen in intensive care unit (ICU) patients. Particular attention is given to mechanisms that cause cell death and organ dysfunction and to prospective therapeutic strategies, directed to recover mitochondrial function. Collectively the data discussed in this review suggest that appropriate diagnosis and specific treatment of mitochondrial dysfunction in ICU patients may significantly improve the clinical outcome

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference