Nicotine-induced survival signaling in lung cancer cells is dependent on their p53 status while its down-regulation by curcumin is independent

<p>Abstract</p> <p>Background</p> <p>Lung cancer is the most lethal cancer and almost 90% of lung cancer is due to cigarette smoking. Even though nicotine, one of the major ingredients of cigarette smoke and the causative agent for addiction, is not a carcinogen by itself, several investigators have shown that nicotine can induce cell proliferation and angiogenesis. We observed that the proliferative index of nicotine is different in the lung cancer cell lines H1299 (p53-/-) and A549 (p53+/+) which indicates that the mode of up-regulation of survival signals by nicotine might be different in cells with and without p53.</p> <p>Results</p> <p>While low concentrations of nicotine induced activation of NF-κB, Akt, Bcl2, MAPKs, AP1 and IAPs in H1299, it failed to induce NF-κB in A549, and compared to H1299, almost 100 times higher concentration of nicotine was required to induce all other survival signals in A549. Transfection of WT-p53 and DN-p53 in H1299 and A549 respectively, reversed the mode of activation of survival signals. Curcumin down-regulated all the survival signals induced by nicotine in both the cells, irrespective of their p53 status. The hypothesis was confirmed when lower concentrations of nicotine induced NF-κB in two more lung cancer cells, Hop-92 and NCI-H522 with mutant p53 status. Silencing of p53 in A549 using siRNA made the cells susceptible to nicotine-induced NF-κB nuclear translocation as in A549 DN-p53 cells.</p> <p>Conclusions</p> <p>The present study reveals a detrimental role of nicotine especially in lung cancer patients with impaired p53 status and identifies curcumin as a potential chemopreventive.</p

Gemcitabine with Cisplatin Versus Hepatic Arterial Infusion Pump Chemotherapy for Liver-Confined Unresectable Intrahepatic Cholangiocarcinoma

Background: A post-hoc analysis of ABC trials included 34 patients with liver-confined unresectable intrahepatic cholangiocarcinoma (iCCA) who received systemic chemotherapy with gemcitabine and cisplatin (gem-cis). The median overall survival (OS) was 16.7 months and the 3-year OS was 2.8%. The aim of this study was to compare patients treated with systemic gem-cis versus hepatic arterial infusion pump (HAIP) chemotherapy for liver-confined unresectable iCCA. Methods: We retrospectively collected consecutive patients with liver-confined unresectable iCCA who received gem-cis in two centers in the Netherlands to compare with consecutive patients who received HAIP chemotherapy with or without systemic chemotherapy in Memorial Sloan Kettering Cancer Center. Results: In total, 268 patients with liver-confined unresectable iCCA were included; 76 received gem-cis and 192 received HAIP chemotherapy. In the gem-cis group 42 patients (55.3%) had multifocal disease compared with 141 patients (73.4%) in the HAIP group (p = 0.023). Median OS for gem-cis was 11.8 months versus 27.7 months for HAIP chemotherapy (p &lt; 0.001). OS at 3 years was 3.5% (95% confidence interval [CI] 0.0–13.6%) in the gem-cis group versus 34.3% (95% CI 28.1–41.8%) in the HAIP chemotherapy group. After adjusting for male gender, performance status, baseline hepatobiliary disease, and multifocal disease, the hazard ratio (HR) for HAIP chemotherapy was 0.27 (95% CI 0.19–0.39). Conclusions: This study confirmed the results from the ABC trials that survival beyond 3 years is rare for patients with liver-confined unresectable iCCA treated with palliative gem-cis alone. With HAIP chemotherapy, one in three patients was alive at 3 years.</p

Recurrence After Liver Resection of Colorectal Liver Metastases: Repeat Resection or Ablation Followed by Hepatic Arterial Infusion Pump Chemotherapy

Background: The aim of this study was to investigate the effectiveness of adjuvant hepatic arterial infusion pump (HAIP) chemotherapy after complete resection or ablation of recurrent colorectal liver metastases (CRLM). Methods: A retrospective cohort study was conducted of patients from two centers who were treated with resection and/or ablation of recurrent CRLM only between 1992 and 2018. Overall survival (OS) and hepatic disease-free survival (hDFS) were estimated using the Kaplan–Meier method. The Cox regression method was used to calculate hazard ratios (HRs) with corresponding 95% confidence intervals (CI). Results: Of 374 eligible patients, 81 (22%) were treated with adjuvant HAIP chemotherapy. The median follow-up for survivors was 65 months (IQR 32–118 months). Patients receiving adjuvant HAIP were more likely to have multifocal disease and receive perioperative systemic chemotherapy at time of resection for recurrence. A median hDFS of 46 months (95% CI 29–81 months) was found in patients treated with adjuvant HAIP compared with 18 months (95% CI 15–26 months) in patients treated with resection and/or ablation alone (p = 0.001). The median OS and 5-year OS were 89 months (95% CI 52–126 months) and 66%, respectively, in patients treated with adjuvant HAIP compared with 57 months (95% CI 47–67 months) and 47%, respectively, in patients treated with resection and/or ablation only (p = 0.002). Adjuvant HAIP was associated with superior hDFS (adjusted HR 0.599, 95% CI 0.38–0.93, p = 0.02) and OS (adjusted HR 0.59, 95% CI 0.38–0.92, p = 0.02) in multivariable analysis. Conclusion: Adjuvant HAIP chemotherapy after resection and/or ablation of recurrent CRLM is associated with superior hDFS and OS

Multi-institutional development and external validation of a nomogram to predict recurrence after curative resection of pancreatic neuroendocrine tumors

Objective: To develop a nomogram estimating the probability of recurrence free at 5 years after resection for localized grade 1 (G1)/ grade 2 (G2) pancreatic neuroendocrine tumors (PanNETs). Background: Among patients undergoing resection of PanNETs, approximately 17% experience recurrence. It is not established which patients are at risk, with no consensus on optimal follow-up. Method: A multi-institutional database of patients with G1/G2 PanNETs treated at 2 institutions was used to develop a nomogram estimating the rate of freedom from recurrence at 5 years after curative resection. A second cohort of patients from 3 additional institutions was used to validate the nomogram. Prognostic factors were assessed by univariate analysis using Cox regression model. The nomogram was internally validated using bootstrap resampling method and on the external cohort. Performance was assessed by concordance index (c-index) and a calibration curve. Results: The nomogram was constructed using a cohort of 632 patients. Overall, 68% of PanNETs were G1, the median follow-up was 51 months, and we observed 74 recurrences. Variables included in the nomogram were the number of positive nodes, tumor diameter, Ki-67, and vascular/perineural invasion. The model bias-corrected c-index from the internal validation was 0.85, which was higher than European Neuroendocrine Tumors Society/American Joint Committee on Cancer 8th staging scheme (c-index 0.76, P = &lt;0.001). On the external cohort of 328 patients, the nomogram c-index was 0.84 (95% confidence interval 0.79–0.88). Conclusion: Our externally validated nomogram predicts the probability of recurrence-free survival at 5 years after PanNETs curative resection, with improved accuracy over current staging systems. Estimating individual recurrence risk will guide the development of personalized surveillance programs after surgery

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors1,2, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies

Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe

Estimating global injuries morbidity and mortality : methods and data used in the Global Burden of Disease 2017 study

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.Peer reviewe

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019 : A systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC