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Biology subjects

Forde, D.

Publications and source records attributed to Forde, D..

3 recordsLinked to original sources

HBV seroepidemiology data for Africa provides insights into transmission and prevention

International goals for elimination of hepatitis B virus (HBV) infection set ambitious targets for 2030. In many African populations, HBV prevalence remains high ([&ge;]8%) despite the roll-out of infant HBV immunisation from the mid-1990s onwards. Enhanced efforts are now urgently required to improve an understanding of population epidemiology, in order to determine which interventions are most likely to be effective in advancing populations towards elimination goals. In populations with a high prevalence of infection, catch-up HBV vaccination of adults has sometimes been deployed as a preventive strategy. An alternative approach of test and treat could be applied as a tool to interrupt transmission. We used a systematic approach to investigate the relationship between prevalence of HBV infection (HBsAg) and exposure (anti-HBc) in Africa, and then applied a mathematical model to investigate the impact of catch-up vaccination and a test and treat strategy in Uganda, representing a high prevalence setting. We demonstrate a strong relationship between the prevalence of HBsAg and anti-HBc (p<0.0001), but with region-specific differences that may reflect different patterns of transmission. In high prevalence settings, catch-up vaccination may have a transient effect but this intervention does not contribute to a sustained decline in prevalence. In contrast, diagnosing and treating infection has a marked impact on reducing prevalence, equivalent to that of infant immunisation. Conclusion: We have developed a high-resolution picture of HBV epidemiology across Africa. Developing insights into regional differences provides an evidence base for the most effective interventions. In combination with robust neonatal immunisation programmes, testing and treating infection is likely to be of most impact in making advances towards elimination targets.

epidemiology↗

A novel signature derived from immunoregulatory and hypoxia genes predicts prognosis in liver and five other cancers

BackgroundDespite much progress in cancer research, its incidence and mortality continue to rise. A robust biomarker that would predict tumor behavior is highly desirable and could improve patient treatment and prognosis.\n\nMethodsIn a retrospective bioinformatics analysis involving patients with liver cancer (n=839), we developed a prognostic signature consisting of 45 genes associated with tumor-infiltrating lymphocytes and cellular responses to hypoxia. From this gene set, we were able to identify a second prognostic signature comprised of 8 genes. Its performance was further validated in five other cancers: head and neck (n=520), renal papillary cell (n=290), lung (n=515), pancreas (n=178) and endometrial (n=370).\n\nFindingsThe 45-gene signature predicted overall survival in three liver cancer cohorts: hazard ratio (HR)=1.82, P=0.006; HR=1.84, P=0.008 and HR=2.67, P=0.003. Additionally, the reduced 8-gene signature was sufficient and effective in predicting survival in liver and five other cancers: liver (HR=2.36, P=0.0003; HR=2.43, P=0.0002 and HR=3.45, P=0.0007), head and neck (HR=1.64, P=0.004), renal papillary cell (HR=2.31, P=0.04), lung (HR=1.45, P=0.03), pancreas (HR=1.96, P=0.006) and endometrial (HR=2.33, P=0.003). Receiver operating characteristic analyses demonstrated both signatures superior performance over current tumor staging parameters. Multivariate Cox regression analyses revealed that both 45-gene and 8-gene signatures were independent of other clinicopathological features in these cancers. Combining the gene signatures with somatic mutation profiles increased their prognostic ability.\n\nConclusionsThis study, to our knowledge, is the first to identify a gene signature uniting both tumor hypoxia and lymphocytic infiltration as a prognostic determinant in six cancer types (n=2,712). The 8-gene signature can be used for patient risk stratification by incorporating hypoxia information to aid clinical decision making.

cancer biology↗

Prognostic signatures of oxygen-sensing genes predict patient survival in ten cancers including those of the liver, pancreas and stomach

ObjectivesTumor hypoxia is associated with metastasis and resistance to chemotherapy and radiotherapy. Genes involved in oxygen-sensing are clinically relevant and have significant implications on prognosis.\n\nMethodsWe identified of two signatures, signature 1 (good prognosis) and signature 2 (adverse prognosis), each consisting of 5 genes using three pancreatic cancer cohorts (n=681). We validated the signatures performance in predicting survival in ten cancers using Cox regression and receiver operating characteristic (ROC) analyses.\n\nResultsSignature 1 and signature 2 were associated with good and poor overall survival respectively. Prognosis of signature 1 in 8 cohorts representing 6 cancers (n=2,627): bladder (hazard ratio [HR]=0.68, P=0.039), papillary renal cell (HR=0.35, P=0.013), liver (HR=0.64, P=0.033 and HR=0.49, P=0.025), lung (HR=0.66, P=0.014) and pancreatic (HR=0.42, P<0.001 and HR=0.64, P=0.04) and endometrial (HR=0.40, P<0.001). Prognosis of signature 2 in 12 cohorts representing 9 cancers (n=4,134): bladder (HR=1.46, P=0.039), cervical (HR=1.97, P=0.035), head and neck (HR=1.39, P=0.038), renal clear cell (HR=1.47, P=0.012), papillary renal cell (HR=3.89, P=0.0015), liver (HR=5.10, P<0.0001 and HR=2.26, P<0.001), lung (HR=1.54, P=0.011), pancreatic (HR=2.09, P=0.002, HR=1.46, P=0.018, and HR=1.99, P<0.0001) and stomach (HR=1.78, P=0.004). Multivariate Cox regression confirmed independent clinical relevance of signatures in these cancers. ROC analyses confirmed superior performance of signatures to current tumor staging benchmarks. KDM8 is a potential tumor suppressor downregulated in liver and pancreatic cancers and is an independent prognostic factor. KDM8 expression negatively correlated with cell cycle regulators. Low KDM8 in tumors was associated with loss of cell adhesion phenotype through HNF4A signaling.\n\nConclusionsPan-cancer signatures of oxygen-sensing genes used for risk assessment in 10 cancers (n=6,761) could guide individualized treatment plans.

cancer biology↗