ObjectivesTo estimate the impact of the COVID-19 pandemic on cancer care services and overall (direct and indirect) excess deaths in people with cancer.MethodsWe employed near real-time weekly data on cancer care to determine the adverse effect of the pandemic on cancer services. We also used these data, together with national death registrations until June 2020 to model deaths, in excess of background (pre-COVID-19) mortality, in people with cancer. Background mortality risks for 24 cancers with and without COVID-19-relevant comorbidities were obtained from population-based primary care cohort (Clinical Practice Research Datalink) on 3 862 012 adults in England.ResultsDeclines in urgent referrals (median=−70.4%) and chemotherapy attendances (median=−41.5%) to a nadir (lowest point) in the pandemic were observed. By 31 May, these declines have only partially recovered; urgent referrals (median=−44.5%) and chemotherapy attendances (median=−31.2%). There were short-term excess death registrations for cancer (without COVID-19), with peak relative risk (RR) of 1.17 at week ending on 3 April. The peak RR for all-cause deaths was 2.1 from week ending on 17 April. Based on these findings and recent literature, we modelled 40% and 80% of cancer patients being affected by the pandemic in the long-term. At 40% affected, we estimated 1-year total (direct and indirect) excess deaths in people with cancer as between 7165 and 17 910, using RRs of 1.2 and 1.5, respectively, where 78% of excess deaths occured in patients with ≥1 comorbidity.ConclusionsDramatic reductions were detected in the demand for, and supply of, cancer services which have not fully recovered with lockdown easing. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is urgent to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks.

Background: Cancer and multiple non-cancer conditions are considered by the Centers for Disease Control and Prevention (CDC) as high risk conditions in the COVID-19 emergency. Professional societies have recommended changes in cancer service provision to minimize COVID-19 risks to cancer patients and health care workers. However, we do not know the extent to which cancer patients, in whom multi-morbidity is common, may be at higher overall risk of mortality as a net result of multiple factors including COVID-19 infection, changes in health services, and socioeconomic factors. Methods: We report multi-center, weekly cancer diagnostic referrals and chemotherapy treatments until April 2020 in England and Northern Ireland. We analyzed population-based health records from 3,862,012 adults in England to estimate 1-year mortality in 24 cancer sites and 15 non-cancer comorbidity clusters (40 conditions) recognized by CDC as high-risk. We estimated overall (direct and indirect) effects of COVID-19 emergency on mortality under different Relative Impact of the Emergency (RIE) and different Proportions of the population Affected by the Emergency (PAE). We applied the same model to the US, using Surveillance, Epidemiology, and End Results (SEER) program data. Results: Weekly data until April 2020 demonstrate significant falls in admissions for chemotherapy (45-66% reduction) and urgent referrals for early cancer diagnosis (70-89% reduction), compared to pre-emergency levels. Under conservative assumptions of the emergency affecting only people with newly diagnosed cancer (incident cases) at COVID-19 PAE of 40%, and an RIE of 1.5, the model estimated 6,270 excess deaths at 1 year in England and 33,890 excess deaths in the US. In England, the proportion of patients with incident cancer with ≥1 comorbidity was 65.2%. The number of comorbidities was strongly associated with cancer mortality risk. Across a range of model assumptions, and across incident and prevalent cancer cases, 78% of excess deaths occur in cancer patients with ≥1 comorbidity. Conclusion: We provide the first estimates of potential excess mortality among people with cancer and multimorbidity due to the COVID-19 emergency and demonstrate dramatic changes in cancer services. To better inform prioritization of cancer care and guide policy change, there is an urgent need for weekly data on cause-specific excess mortality, cancer diagnosis and treatment provision and better intelligence on the use of effective treatments for comorbidities.

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Hepatocellular carcinoma (HCC) is a leading cause of death, resulting in over 700 thousand deaths annually worldwide. Chemotherapy is the primary therapeutic strategy for patients with late-stage HCC. Heteronemin is a marine natural product isolated from Hippospongia sp. that has been found to protect against carcinogenesis in cholangiocarcinoma, prostate cancer, and acute myeloid leukemia. In this study, heteronemin was found to inhibit the proliferation of the HCC cell lines HA22T and HA59T and induce apoptosis via the caspase pathway. Heteronemin treatment also induced the formation of reactive oxygen species (ROS), which are associated with heteronemin-induced cell death, and to trigger ROS removal by mitochondrial SOD2 rather than cytosolic SOD1. The mitogen-activated protein kinase (MAPK) signaling pathway was associated with ROS-induced cell death, and heteronemin downregulated the expression of ERK, a MAPK that is associated with cell proliferation. Inhibitors of JNK and p38, which are MAPKs associated with apoptosis, restored heteronemin-induced cell death. In addition, heteronemin treatment reduced the expression of GPX4, a protein that inhibits ferroptosis, which is a novel form of nonapoptotic programmed cell death. Ferroptosis inhibitor treatment also restored heteronemin-induced cell death. Thus, with appropriate structural modification, heteronemin can act as a potent therapeutic against HCC.

The circadian clock regulates immune responses to microbes and affects pathogen replication, but the underlying molecular mechanisms are not well understood. Here we demonstrate that the circadian components BMAL1 and REV-ERBα influence several steps in the hepatitis C virus (HCV) life cycle, including particle entry into hepatocytes and RNA genome replication. Genetic knock out of Bmal1 and over-expression or activation of REV-ERB with synthetic agonists inhibits the replication of HCV and the related flaviruses dengue and Zika via perturbation of lipid signaling pathways. This study highlights a role for the circadian clock component REV-ERBα in regulating flavivirus replication.

Disruption of either the RDEA or REGA genes leads to rapid development in Dictyostelium. The RDEA gene product displays homology to certain H2-type phosphotransferases, while REGA encodes a cAMP phosphodiesterase with an associated response regulator. It has been proposed that RDEA activates REGA in a multistep phosphorelay. To test this proposal, we examined cAMP accumulation in rdeA and regA null mutants and found that these mutants show a pronounced accumulation of cAMP at the vegetative stage that is not observed in wild-type cells. This accumulation was due to a novel adenylyl cyclase and not to the known Dictyostelium adenylyl cyclases, aggregation stage adenylyl cyclase (ACA) or germination stage adenylyl cyclase (ACG), since it occurred in an acaA/rdeA double mutant and, unlike ACG, was inhibited by high osmolarity. The novel adenylyl cyclase was not regulated by G-proteins and was relatively insensitive to stimulation by Mn 2؉ ions. Addition of the cAMP phosphodiesterase inhibitor, 3-isobutyl-1-methylxanthine (IBMX) permitted detection of the novel adenylyl cyclase activity in lysates of an acaA/acgA double mutant. The fact that disruption of the RDEA gene as well as inhibition of the REGA-phosphodiesterase by IBMX permitted detection of the novel AC activity supports the hypothesis that RDEA activates REGA.

Preoperative TACE is not only associated with higher medical utilizations, but it is also correlated with higher mortality rates over a 5-year period. The preoperative TACE does not benefit patients with resectable HCC. The golden standard or clinical guidelines should be developed to provide better clinical decisions and decision support for HCC patients.

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.MethodsIn 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).ResultsThe 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.ConclusionsThis 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 = 2712). The 8-gene signature can be used for patient risk stratification by incorporating hypoxia information to aid clinical decision making.Electronic supplementary materialThe online version of this article (10.1186/s12967-019-1775-9) contains supplementary material, which is available to authorized users.