Peripheral Soluble Immune Checkpoint-Related Proteins Were Associated with Survival and Treatment Efficacy of Osteosarcoma Patients, a Cohort Study.

BACKGROUND: The immune checkpoint blockade remains obscure in osteosarcoma (OS). We aim to explore the clinical significance of soluble immune checkpoint (ICK)-related proteins in OS. METHODS: We profiled 14 soluble ICK-related proteins (BTLA, GITR, HVEM, IDO, LAG-3, PD-1, PD-L1, PD-L2, TIM-3, CD28, CD80, CD137, CD27, and CTLA-4) in the plasma of 76 OS patients and matched controls. We evaluated the associations between the biomarkers and the risk of OS using unconditional multivariate logistic regression. The multivariate Cox model was utilized to develop the prediction model of OS. Immune subtypes were established from the identified biomarkers. Transcriptional data from GEO were analyzed to elucidate potential mechanisms. RESULTS: We found that sTIM3, sCD137, sIDO, and sCTLA4 were significantly correlated with OS risk (all p < 0.05). sBTLA, sPDL2, and sCD27 were significantly associated with the risk of lung metastasis, whereas sBTLA and sTIM3 were associated with the risk of disease progression. We also established an immune subtype based on sBTLA, sPD1, sTIM3, and sPDL2. Patients in the sICK-type2 subtype had significantly decreased progression-free survival (PFS) and lung metastasis-free survival (LMFS) than those in the sICK-type1 subtype (log-rank p = 2.8 × 10-2, 1.7 × 10-2, respectively). Interestingly, we found that the trend of LMFS and PFS in the subtypes of corresponding ICK genes' expression was opposite to the results in the blood (log-rank p = 2.6 × 10-4, 9.5 × 10-4, respectively). CONCLUSION: Four soluble ICK-related proteins were associated with the survival of OS patients. Soluble ICK-related proteins could be promising biomarkers for the outcomes and immunotherapy of OS patients, though more research is warranted.

Impaired lung function and lung cancer risk in 461 183 healthy individuals: a cohort study.

BACKGROUND: It has been known that smoking and various lung diseases including lung cancer can cause lung function impairment. However, the impact of different types of lung function impairments, such as preserved ratio impaired spirometry (PRISm) and airflow obstruction (AO), on the incidence and mortality of lung cancer in both general and never-smoker populations remains unclear. We wished to examine the effect of lung function impairments on lung cancer risks. METHODS: This was a retrospective cohort study (1 January 1994 to 31 December 2017) of individuals from a health surveillance programme in Taiwan who underwent baseline spirometry tests at the entry point. PRISm was defined as an FEV1/FVC (forced expiratory volume in 1 s/forced vital capacity) ratio >0.7 and FEV1 <0.8, while AO was defined as an FEV1/FVC ratio <0.7. Cox proportional hazards models and cubic spline curves were used to examine the associations between lung function impairments and lung cancer risks. RESULTS: The study included 461,183 individuals, of whom 14.3% had PRISm and 7.9% had AO. A total of 4038 cases of lung cancer and 3314 lung cancer-related deaths were identified during the 23 years of follow-up. Individuals with PRISm and AO exhibited a higher risk of lung cancer incidence and mortality compared with those with normal lung function. The adjusted HRs and 95% CIs were 1.14 (1.03 to 1.26) and 1.23 (1.10 to 1.37) in the overall cohort, and 1.08 (0.93 to 1.24), and 1.23 (1.05 to 1.45) in the never-smoker cohort. The risks of both developing and dying of lung cancer increased with the severity levels of lung function impairments and lower FEV1 values. CONCLUSION: Impaired lung function is associated with increased risks of developing lung cancer and subsequent mortality. The study highlights the importance of considering lung function in lung cancer screening for better candidate selection.

A multi-ancestry cerebral cortex transcriptome-wide association study identifies genes associated with smoking behaviors.

Transcriptome-wide association studies (TWAS) have provided valuable insight in identifying genes that may impact cigarette smoking. Most of previous studies, however, mainly focused on European ancestry. Limited TWAS studies have been conducted across multiple ancestries to explore genes that may impact smoking behaviors. In this study, we used cis-eQTL data of cerebral cortex from multiple ancestries in MetaBrain, including European, East Asian, and African samples, as reference panels to perform multi-ancestry TWAS analyses on ancestry-matched GWASs of four smoking behaviors including smoking initiation, smoking cessation, age of smoking initiation, and number of cigarettes per day in GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Multiple-ancestry fine-mapping approach was conducted to identify credible gene sets associated with these four traits. Enrichment and module network analyses were further performed to explore the potential roles of these identified gene sets. A total of 719 unique genes were identified to be associated with at least one of the four smoking traits across ancestries. Among those, 249 genes were further prioritized as putative causal genes in multiple ancestry-based fine-mapping approach. Several well-known smoking-related genes, including PSMA4, IREB2, and CHRNA3, showed high confidence across ancestries. Some novel genes, e.g., TSPAN3 and ANK2, were also identified in the credible sets. The enrichment analysis identified a series of critical pathways related to smoking such as synaptic transmission and glutamate receptor activity. Leveraging the power of the latest multi-ancestry GWAS and eQTL data sources, this study revealed hundreds of genes and relevant biological processes related to smoking behaviors. These findings provide new insights for future functional studies on smoking behaviors.

Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies.

OBJECTIVE: To investigate the associations across genetic and lifestyle factors with lifespan. DESIGN: A longitudinal cohort study. SETTING: UK Biobank. PARTICIPANTS: 353 742 adults of European ancestry, who were recruited from 2006 to 2010 and were followed up until 2021. EXPOSURES: A polygenic risk score for lifespan with long (highest quintile) risk categories and a weighted healthy lifestyle score, including no current smoking, moderate alcohol consumption, regular physical activity, healthy body shape, adequate sleep duration, and a healthy diet, categorised into favourable, intermediate, and unfavourable lifestyles. MAIN OUTCOME MEASURES: Lifespan defined as the date of death or the censor date minus the date of birth. RESULTS: Of the included 353 742 participants of European ancestry with a median follow-up of 12.86 years, 24 239 death cases were identified. Participants were grouped into three genetically determined lifespan categories including long (20.1%), intermediate (60.1%), and short (19.8%), and into three lifestyle score categories including favourable (23.1%), intermediate (55.6%), and unfavourable (21.3%). The hazard ratio (HR) of death for individuals with a genetic predisposition to a short lifespan was 1.21 (95% CI 1.16 to 1.26) compared to those with a genetic predisposition to a long lifespan. The HR of death for individuals in the unfavourable lifestyle category was 1.78 (95% CI 1.71 to 1.85), compared with those in the favourable lifestyle category. Participants with a genetic predisposition to a short lifespan and an unfavourable lifestyle had 2.04 times (95% CI 1.87 to 2.22) higher rates of death compared with those with a genetic predisposition to a long lifespan and a favourable lifestyle. No multiplicative interaction was detected between the polygenic risk score of lifespan and the weighted healthy lifestyle score (p=0.10). The optimal combination of healthy lifestyles, including never smoking, regular physical activity, adequate sleep duration, and a healthy diet, was derived to decrease risk of premature death (death before 75 years). CONCLUSION: Genetic and lifestyle factors were independently associated with lifespan. Adherence to healthy lifestyles could largely attenuate the genetic risk of a shorter lifespan or premature death. The optimal combination of healthy lifestyles could convey better benefits for a longer lifespan, regardless of genetic background.

A biological age model based on physical examination data to predict mortality in a Chinese population.

Biological age could be reflective of an individual's health status and aging degree. Limited estimations of biological aging based on physical examination data in the Chinese population have been developed to quantify the rate of aging. We developed and validated a novel aging measure (Balanced-AGE) based on readily available physical health examination data. In this study, a repeated sub-sampling approach was applied to address the data imbalance issue, and this approach significantly improved the performance of biological age (Balanced-AGE) in predicting all-cause mortality with a 10-year time-dependent AUC of 0.908 for all-cause mortality. This mortality prediction tool was found to be effective across different subgroups by age, sex, smoking, and alcohol consumption status. Additionally, this study revealed that individuals who were underweight, smokers, or drinkers had a higher extent of age acceleration. The Balanced-AGE may serve as an effective and generally applicable tool for health assessment and management among the elderly population.

Global, regional, and national burden and quality of care of multiple myeloma, 1990-2019.

Background: Multiple myeloma (MM) is the second most common haematologic malignancy, presenting a great disease burden on the general population; however, the quality of care of MM is overlooked. We therefore assessed gains and disparity in quality of care worldwide from 1990 to 2019 based on a novel summary indicator - the quality of care index (QCI) - and examined its potential for improvement. Methods: Using the Global Burden of Disease 2019 data set, we calculated the QCI of MM for 195 countries and territories. We used the principal component analysis to extract the first principal component of ratios with the combinations of mortality to incidence, prevalence to incidence, disability-adjusted life years to prevalence, and years of life lost to years lived with disability as QCI. We also conducted a series of descriptive and comparative analyses of QCI disparities with age, gender, period, geographies, and sociodemographic development, and compared the QCI among countries with similar socio-demographic index (SDI) through frontier analysis. Results: The age-standardised rates of MM were 1.92 (95% uncertainty interval (UI) = 1.68, 2.12) in incidence and 1.42 (95% UI = 1.24, 1.52) in deaths per 100 000 population in 2019, and were predicted to increase in the future. The global age-standardised QCI increased from 51.31 in 1990 to 64.28 in 2019. In 2019, New Zealand had the highest QCI at 99.29 and the Central African Republic had the lowest QCI at 10.74. The gender disparity of QCI was reduced over the years, with the largest being observed in the sub-Saharan region. Regarding age, QCI maintained a decreasing trend in patients aged >60 in SDI quintiles. Generally, QCI improved with the SDI increase. Results of frontier analysis suggested that there is a potential to improve the quality of care across all levels of development spectrum. Conclusions: Quality of care of MM improved during the past three decades, yet disparities in MM care remain across different countries, age groups, and genders. It is crucial to establish local objectives aimed at enhancing MM care and closing the gap in health care inequality.

Combining Classic and Novel Neutrophil-Related Biomarkers to Identify Non-Small-Cell Lung Cancer.

BACKGROUND: Recent studies have revealed that neutrophils play a crucial role in cancer progression. This study aimed to explore the diagnostic value of neutrophil-related biomarkers for non-small-cell lung cancer (NSCLC). METHODS: We initially assessed the associations between classic neutrophil-related biomarkers (neutrophil-to-lymphocyte ratio (NLR), absolute neutrophil counts (NEU), absolute lymphocyte counts (LYM)) and NSCLC in 3942 cases and 6791 controls. Then, we measured 11 novel neutrophil-related biomarkers via Luminex Assays in 132 cases and 66 controls, individually matching on sex and age (±5 years), and evaluated their associations with NSCLC risk. We also developed the predictive models by sequentially adding variables of interest and assessed model improvement. RESULTS: Interleukin-6 (IL-6) (odds ratio (OR) = 10.687, 95% confidence interval (CI): 3.875, 29.473) and Interleukin 1 Receptor Antagonist (IL-1RA) (OR = 8.113, 95% CI: 3.182, 20.689) shows strong associations with NSCLC risk after adjusting for body mass index, smoking status, NLR, and carcinoembryonic antigen. Adding the two identified biomarkers to the predictive model significantly elevated the model performance from an area under the receiver operating characteristic curve of 0.716 to 0.851 with a net reclassification improvement of 97.73%. CONCLUSIONS: IL-6 and IL-1RA were recognized as independent risk factors for NSCLC, improving the predictive performance of the model in identifying disease.

Big data and artificial intelligence in cancer research.

The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from complex big data is rapidly evolving. However, challenges related to efficient data curation, in-depth analysis, and utilization remain. We provide a comprehensive overview of the current state of the art in big data and computational analysis, highlighting key applications, challenges, and future opportunities in cancer research. By sketching the current landscape, we seek to foster a deeper understanding and facilitate the advancement of big data utilization in oncology, call for interdisciplinary collaborations, ultimately contributing to improved patient outcomes and a profound understanding of cancer.

Urinary miRNAs Predict Metastasis in Patients With Clinically Localized Clear Cell Renal Cell Carcinoma Treated With Nephrectomy.

PURPOSE: Patients with clear cell renal cell carcinoma (ccRCC) might develop metastasis after surgery with curative intent. We aimed to characterize the expression levels of microRNAs in the urine (UmiRNAs) of patients before and after nephrectomy to determine the impact of UmiRNAs expression in the emergence of metastases. METHODS: We prospectively collected pre- and post-nephrectomy urine samples from 117 patients with clinically localized and locally advanced ccRCC. UmiRNAs were extracted, purified, and measured using RT-PCR. Relative quantifications (RQ) of 137 UmiRNAs were calculated through 2-∆∆ method. The post-surgery/pre-surgery RQs ratio represented the magnitude of the expression levels of the UmiRNAs. The association of UmiRNA expression and the development of distant metastases was tested with Cox regression model. RESULTS: Five UmiRNAs (miR-191-5p, miR-324-3p, miR-186-5p, miR-93-5p, miR-30b-5p) levels were upregulated before nephrectomy (p < .05). This conferred a 2- to 4-fold increased risk of metastasis, with miR-191-5p showing the most significant association with this endpoint (HR = 4.16, 95% CI = 1.38-12.58, p = .011). In a multivariate model stratified with stage and Fuhrman grade, we found that miR-191-5p, miR-324-3p, and miR-186-5p exhibited a strong association with metastasis development in patients with pathological T3 (pT3) tumors. Enrichment analysis with the most differentially expressed UmiRNAs showed that these UmiRNAs targeted genes that regulate cell survival and proliferation. CONCLUSION: Our study indicated UmiR-191-5p, UmiR-324-3p, and UmiR-186-5p are potential markers to predict the development of metastasis, particularly in pT3 patients. PATIENT SUMMARY: We compared changes of UmiRNAs expression detected pre- and postnephrectomy of patients with ccRCC. Our findings suggest that UmiRNA expression likely reflects tumor-specific changes that can be promising to predict the metastasis development, particularly in patients with non-metastatic locally advanced ccRCC. If confirmed, these findings may be useful for surveillance protocols for adjuvant therapy protocols.

6-Year trajectory of fasting plasma glucose (FPG) and mortality risk among individuals with normal FPG at baseline: a prospective cohort study.

BACKGROUND: Higher fasting plasma glucose (FPG) levels were associated with an increased risk of all-cause mortality; however, the associations between long-term FPG trajectory groups and mortality were unclear, especially among individuals with a normal FPG level at the beginning. The aims of this study were to examine the associations of FPG trajectories with the risk of mortality and identify modifiable lifestyle factors related to these trajectories. METHODS: We enrolled 50,919 individuals aged ≥ 20 years old, who were free of diabetes at baseline, in the prospective MJ cohort. All participants completed at least four FPG measurements within 6 years after enrollment and were followed until December 2011. FPG trajectories were identified by group-based trajectory modeling. We used Cox proportional hazards models to examine the associations of FPG trajectories with mortality, adjusting for age, sex, marital status, education level, occupation, smoking, drinking, physical activity, body mass index, baseline FPG, hypertension, dyslipidemia, cardiovascular disease or stroke, and cancer. Associations between baseline lifestyle factors and FPG trajectories were evaluated using multinomial logistic regression. RESULTS: We identified three FPG trajectories as stable (n = 32,481), low-increasing (n = 17,164), and high-increasing (n = 1274). Compared to the stable group, both the low-increasing and high-increasing groups had higher risks of all-cause mortality (hazard ratio (HR) = 1.18 (95% CI 0.99-1.40) and 1.52 (95% CI 1.09-2.13), respectively), especially among those with hypertension. Compared to participants with 0 to 1 healthy lifestyle factor, those with 6 healthy lifestyle factors were more likely to be in the stable group (ORlow-increasing = 0.61, 95% CI 0.51-0.73; ORhigh-increasing = 0.20, 95% CI 0.13-0.32). CONCLUSIONS: Individuals with longitudinally increasing FPG had a higher risk of mortality even if they had a normal FPG at baseline. Adopting healthy lifestyles may prevent individuals from transitioning into increasing trajectories.

Prediction of risk and overall survival of pancreatic cancer from blood soluble immune checkpoint-related proteins.

Background: Immune checkpoint inhibition holds promise as a novel treatment for pancreatic ductal adenocarcinoma (PDAC). The clinical significance of soluble immune checkpoint (ICK) related proteins have not yet fully explored in PDAC. Methods: We comprehensively profiled 14 soluble ICK-related proteins in plasma in 70 PDAC patients and 70 matched healthy controls. Epidemiological data of all subjects were obtained through structured interviews, and patients' clinical data were retrieved from electronical health records. We evaluated the associations between the biomarkers with the risk of PDAC using unconditional multivariate logistic regression. Consensus clustering (k-means algorithm) with significant biomarkers was performed to identify immune subtypes in PDAC patients. Prediction models for overall survival (OS) in PDAC patients were developed using multivariate Cox proportional hazards regression. Harrell's concordance index (C-index), time-dependent receiver operating characteristic (ROC) curve and calibration curve were utilized to evaluate performance of prediction models. Gene expressions of the identified ICK-related proteins in tumors from TCGA were analyzed to provide insight into underlying mechanisms. Results: Soluble BTLA, CD28, CD137, GITR and LAG-3 were significantly upregulated in PDAC patients (all q < 0.05), and elevation of each of them was correlated with PDAC increased risk (all p < 0.05). PDAC patients were classified into soluble immune-high and soluble immune-low subtypes, using these 5 biomarkers. Patients in soluble immune-high subtype had significantly poorer OS than those in soluble immune-low subtype (log-rank p = 9.7E-03). The model with clinical variables and soluble immune subtypes had excellent predictive power (C-index = 0.809) for the OS of PDAC patients. Furthermore, the immune subtypes identified with corresponding genes' expression in PDAC tumor samples in TCGA showed an opposite correlation with OS to that of immune subtypes based on blood soluble ICK-related proteins (log-rank p =0.02). The immune-high subtype tumors displayed higher cytolytic activity (CYT) score than immune-low subtype tumors (p < 2E-16). Conclusion: Five soluble ICK-related proteins were identified to be significantly associated with the risk and prognosis of PDAC. Patients who were classified as soluble immune-low subtype based on these biomarkers had better overall survival than those of the soluble immune-high subtype.

Risk of Death Associated With Reversion From Prediabetes to Normoglycemia and the Role of Modifiable Risk Factors.

Importance: Individuals with prediabetes have a higher risk of death than healthy individuals. However, previous findings have suggested that individuals with reversion from prediabetes to normoglycemia may not have a lower risk of death compared with individuals with persistent prediabetes. Objectives: To investigate the associations between changes in prediabetes status and risk of death and to elucidate the roles of modifiable risk factors in these associations. Design, Setting, and Participants: This population-based prospective cohort study used data from 45 782 participants with prediabetes from the Taiwan MJ Cohort Study who were recruited between January 1, 1996, and December 31, 2007. Participants were followed up from the second clinical visit to December 31, 2011, with a median (IQR) follow-up of 8 (5-12) years. Participants were categorized into 3 groups according to changes in their prediabetes status within a 3-year period after initial enrollment: reversion to normoglycemia, persistent prediabetes, and progression to diabetes. Cox proportional hazards regression models were used to examine the associations between changes in prediabetes status at baseline (ie, the second clinical visit) and risk of death. Data analysis was performed between September 18, 2021, and October 24, 2022. Main Outcomes and Measures: All-cause mortality, cardiovascular disease (CVD)-related mortality, and cancer-related mortality. Results: Of 45 782 participants with prediabetes (62.9% male; 100% Asian; mean [SD] age, 44.6 [12.8] years), 1786 (3.9%) developed diabetes and 17 021 (37.2%) reverted to normoglycemia. Progression from prediabetes to diabetes within a 3-year period was associated with higher risks of all-cause death (hazard ratio [HR], 1.50; 95% CI, 1.25-1.79) and CVD-related death (HR, 1.61; 95% CI, 1.12-2.33) compared with persistent prediabetes, while reversion to normoglycemia was not associated with a lower risk of all-cause death (HR, 0.99; 95% CI, 0.88-1.10), cancer-related death (HR, 0.91; 95% CI, 0.77-1.08), or CVD-related death (HR, 0.97; 95% CI, 0.75-1.25). Among individuals who were physically active, reversion to normoglycemia was associated with a lower risk of all-cause death (HR, 0.72; 95% CI, 0.59-0.87) compared with those with persistent prediabetes who were physically inactive. Among individuals with obesity, risk of death varied between those who experienced reversion to normoglycemia (HR, 1.10; 95% CI, 0.82-1.49) and those who had persistent prediabetes (HR, 1.33; 95% CI, 1.10-1.62). Conclusions and Relevance: In this cohort study, although reversion from prediabetes to normoglycemia within a 3-year period did not mitigate the overall risk of death compared with persistent prediabetes, risk of death associated with reversion to normoglycemia varied based on whether individuals were physically active or had obesity. These findings highlight the importance of lifestyle modification among those with prediabetes status.

Association of frailty with the incidence risk of cardiovascular disease and type 2 diabetes mellitus in long-term cancer survivors: a prospective cohort study.

BACKGROUND: Comorbidities among cancer survivors remain a serious healthcare burden and require appropriate management. Using two widely used frailty indicators, this study aimed to evaluate whether frailty was associated with the incidence risk of cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) among long-term cancer survivors. METHODS: We included 13,388 long-term cancer survivors (diagnosed with cancer over 5 years before enrolment) free of CVD and 6101 long-term cancer survivors free of T2DM, at the time of recruitment (aged 40-69 years), from the UK Biobank. Frailty was assessed by the frailty phenotype (FP_Frailty, range: 0-5) and the frailty index (FI_Frailty, range: 0-1) at baseline. The incident CVD and T2DM were ascertained through linked hospital data and primary care data, respectively. The associations were examined using Cox proportional hazards regression models. RESULTS: Compared with non-frail participants, those with pre-frailty (FP_Frailty [met 1-2 of the components]: hazard ratio [HR]=1.18, 95% confidence interval [CI]: 1.05, 1.32; FI_Frailty [0.10< FI ≤0.21]: HR=1.51, 95% CI: 1.32, 1.74) and frailty (FP_Frailty [met ≥3 of the components]: HR=2.12, 95% CI: 1.73, 2.60; FI_Frailty [FI >0.21]: HR=2.19, 95% CI: 1.85, 2.59) had a significantly higher risk of CVD in the multivariable-adjusted model. A similar association of FI_Frailty with the risk of incident T2DM was observed. We failed to find such an association for FP_Frailty. Notably, the very early stage of frailty (1 for FP_Frailty and 0.1-0.2 for FI_Frailty) was also positively associated with the risk of CVD and T2DM (FI_Frailty only). A series of sensitivity analyses confirmed the robustness of the findings. CONCLUSIONS: Frailty, even in the very early stage, was positively associated with the incidence risk of CVD and T2DM among long-term cancer survivors, although discrepancies existed between frailty indicators. While the validation of these findings is required, they suggest that routine monitoring, prevention, and interventive programs of frailty among cancer survivors may help to prevent late comorbidities and, eventually, improve their quality of life. Especially, interventions are recommended to target those at an early stage of frailty when healthcare resources are limited.

Body mass index and survival after cancer diagnosis: A pan-cancer cohort study of 114 430 patients with cancer.

The recommendation encouraging patients with cancer to keep a normal body mass index (BMI) is largely extrapolated from data on risk of developing cancer. We tested the prospective association between peri-diagnostic (within 1 year post-diagnosis) BMI and all-cause mortality in patients with incident cancers. During 7.2 years of follow-up, 42% (48,340) of the 114 430 patients with cancer died. Spline analysis revealed that compared with a BMI of 22.5, a BMI lower than 22.5 was associated with increased risk of all-cause mortality across 24 cancer types. A BMI higher than 22.5 was associated with reduced all-cause mortality, while a non-linear association was observed; the lowest risk was found at a BMI of 29.6-34.2, and the risk started to return to and above unity at very high BMI values. The reduced mortality risk of high BMI was observed in 23 of 24 cancer types and maintained after attempts to remove potential selection bias, confounding by smoking and comorbidities, and reserve causality. Compared with a normal BMI of 18.5-24.9, the hazard ratios were 0.85 (95% confidence interval [CI], 0.83-0.87) for an overweight BMI (25-29.9) and 0.82 (0.80-0.85) for an obese BMI (≥30), and the associations were generally consistent across cancer types and various subgroups. Obese BMI was associated with increased life expectancy, up to 6 years among men and 3 years among women. In conclusion, while overweight/obese BMI increases the risk of developing cancer in the general population, overweight/obese peri-diagnostic BMI was associated with longer survival in cancer patients.

Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer.

Background: Immune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure. Methods: We evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation. Results: We found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset. Conclusion: Our study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients.

Predictive Utility of Mortality by Aging Measures at Different Hierarchical Levels and the Response to Modifiable Life Style Factors: Implications for Geroprotective Programs.

Background: Aging, as a multi-dimensional process, can be measured at different hierarchical levels including biological, phenotypic, and functional levels. The aims of this study were to: (1) compare the predictive utility of mortality by three aging measures at three hierarchical levels; (2) develop a composite aging measure that integrated aging measures at different hierarchical levels; and (3) evaluate the response of these aging measures to modifiable life style factors. Methods: Data from National Health and Nutrition Examination Survey 1999-2002 were used. Three aging measures included telomere length (TL, biological level), Phenotypic Age (PA, phenotypic level), and frailty index (FI, functional level). Mortality information was collected until December 2015. Cox proportional hazards regression and multiple linear regression models were performed. Results: A total of 3,249 participants (20-84 years) were included. Both accelerations (accounting for chronological age) of PA and FI were significantly associated with mortality, with HRs of 1.67 [95% confidence interval (CI) = 1.41-1.98] and 1.59 (95% CI = 1.35-1.87), respectively, while that of TL showed non-significant associations. We thus developed a new composite aging measure (named PC1) integrating the accelerations of PA and FI, and demonstrated its better predictive utility relative to each single aging measure. PC1, as well as the accelerations of PA and FI, were responsive to several life style factors including smoking status, body mass index, alcohol consumption, and leisure-time physical activity. Conclusion: This study demonstrates that both phenotypic (i.e., PA) and functional (i.e., FI) aging measures can capture mortality risk and respond to modifiable life style factors, despite their inherent differences. Furthermore, the PC1 that integrated phenotypic and functional aging measures outperforms in predicting mortality risk in comparison with each single aging measure, and strongly responds to modifiable life style factors. The findings suggest the complementary of aging measures at different hierarchical levels and highlight the potential of life style-targeted interventions as geroprotective programs.

"Sugar-Sweetened Beverages" Is an Independent Risk From Pancreatic Cancer: Based on Half a Million Asian Cohort Followed for 25 Years.

Although the link between sugar-sweetened beverages (SSB) and pancreatic cancer has been suggested for its insulin-stimulating connection, most epidemiological studies showed inconclusive relationship. Whether the result was limited by sample size is explored. This prospective study followed 491,929 adults, consisting of 235,427 men and 256,502 women (mean age: 39.9, standard deviation: 13.2), from a health surveillance program and there were 523 pancreatic cancer deaths between 1994 and 2017. The individual identification numbers of the cohort were matched with the National Death file for mortality, and Cox models were used to assess the risk. The amount of SSB intake was recorded based on the average consumption in the month before interview by a structured questionnaire. We classified the amount of SSB intake into 4 categories: 0-<0.5 serving/day, ≥0.5-<1 serving per day, ≥1-<2 servings per day, and ≥2 servings per day. One serving was defined as equivalent to 12 oz and contained 35 g added sugar. We used the age and the variables at cohort enrolment as the reported risks of pancreatic cancers. The cohort was divided into 3 age groups, 20-39, 40-59, and ≥60. We found young people (age <40) had higher prevalence and frequency of sugar-sweetened beverages than the elderly. Those consuming 2 servings/day had a 50% increase in pancreatic cancer mortality (HR = 1.55, 95% CI: 1.08-2.24) for the total cohort, but a 3-fold increase (HR: 3.09, 95% CI: 1.44-6.62) for the young. The risk started at 1 serving every other day, with a dose-response relationship. The association of SSB intake of ≥2 servings/day with pancreatic cancer mortality among the total cohort remained significant after excluding those who smoke or have diabetes (HR: 2.12, 97% CI: 1.26-3.57), are obese (HR: 1.57, 95% CI: 1.08-2.30), have hypertension (HR: 1.90, 95% CI: 1.20-3.00), or excluding who died within 3 years after enrollment (HR: 1.67, 95% CI: 1.15-2.45). Risks remained in the sensitivity analyses, implying its independent nature. We concluded that frequent drinking of SSB increased pancreatic cancer in adults, with highest risk among young people.

A whole-exome case-control association study to characterize the contribution of rare coding variation to pancreatic cancer risk.

Pancreatic cancer is a deadly disease that accounts for approximately 5% of cancer deaths worldwide, with a dismal 5-year survival rate of 10%. Known genetic risk factors explain only a modest proportion of the heritable risk of pancreatic cancer. We conducted a whole-exome case-control sequencing study in 1,591 pancreatic cancer cases and 2,134 cancer-free controls of European ancestry. In our gene-based analysis, ATM ranked first, with a genome-wide significant p value of 1 × 10-8. The odds ratio for protein-truncating variants in ATM was 24, which is substantially higher than prior estimates, although ours includes a broad 95% confidence interval (4.0-1000). SIK3 was the second highest ranking gene (p = 3.84 × 10-6, false discovery rate or FDR = 0.032). We observed nominally significant association signals in several genes of a priori interest, including BRCA2 (p = 4.3 × 10-4), STK11 (p = 0.003), PALB2 (p = 0.019), and TP53 (p = 0.037), and reported risk estimates for known pathogenic variants and variants of uncertain significance (VUS) in these genes. The rare variants in established susceptibility genes explain approximately 24% of log familial relative risk, which is comparable to the contribution from established common susceptibility variants (17%). In conclusion, this study provides new insights into the genetic susceptibility of pancreatic cancer, refining rare variant risk estimates in known pancreatic cancer susceptibility genes and identifying SIK3 as a novel candidate susceptibility gene. This study highlights the prominent importance of ATM truncating variants and the underappreciated role of VUS in pancreatic cancer etiology.

Cohort profile: The National Colorectal Cancer Cohort (NCRCC) study in China.

PURPOSE: The National Colorectal Cancer Cohort (NCRCC) study aims to specifically assess risk factors and biomarkers related to endpoints across the colorectal cancer continuum from the aetiology through survivorship. PARTICIPANTS: The NCRCC study includes the Colorectal Cancer Screening Cohort (CRCSC), which recruited individuals who were at high risk of CRC between 2016 and 2020 and Colorectal Cancer Patients Cohort (CRCPC), which recruited newly diagnosed patients with CRC between 2015 and 2020. Data collection was based on questionnaires and abstraction from electronic medical record. Items included demographic and lifestyle factors, clinical information, survivorship endpoints and other information. Multiple biospecimens including blood, tissue and urine samples were collected. Participants in CRCSC were followed by a combination of periodic survey every 5 years and annual linkage with regional or national cancer and death registries for at least 10 years. In CRCPC, follow-up was conducted with both active and passive approaches at 6, 12, 18, 24, 36, 48 and 60 months after surgery. FINDINGS TO DATE: A total of 19 377 participants and 15 551 patients with CRC were recruited in CRCSC and in CRCPC, respectively. In CRCSC, 48.0% were men, and the average age of participants at enrolment was 58.7±8.3 years. In CRCPC, 61.4% were men, and the average age was 60.3±12.3 years with 18.9% of participants under 50 years of age. FUTURE PLANS: Longitudinal data and biospecimens will continue to be collected. Based on the cohorts, several studies to assess risk factors and biomarkers for CRC or its survivorship will be conducted, ultimately providing research evidence from Chinese population and optimising evidence-based guidelines across the CRC continuum.