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.

Chat-ePRO: Development and pilot study of an electronic patient-reported outcomes system based on ChatGPT.

OBJECTIVE: Chatbots have the potential to improve user compliance in electronic Patient-Reported Outcome (ePRO) system. Compared to rule-based chatbots, Large Language Model (LLM) offers advantages such as simplifying the development process and increasing conversational flexibility. However, there is currently a lack of practical applications of LLMs in ePRO systems. Therefore, this study utilized ChatGPT to develop the Chat-ePRO system and designed a pilot study to explore the feasibility of building an ePRO system based on LLM. MATERIALS AND METHODS: This study employed prompt engineering and offline knowledge distillation to design a dialogue algorithm and built the Chat-ePRO system on the WeChat Mini Program platform. In order to compare Chat-ePRO with the form-based ePRO and rule-based chatbot ePRO used in previous studies, we conducted a pilot study applying the three ePRO systems sequentially at the Sir Run Run Shaw Hospital to collect patients' PRO data. RESULT: Chat-ePRO is capable of correctly generating conversation based on PRO forms (success rate: 95.7 %) and accurately extracting the PRO data instantaneously from conversation (Macro-F1: 0.95). The majority of subjective evaluations from doctors (>70 %) suggest that Chat-ePRO is able to comprehend questions and consistently generate responses. Pilot study shows that Chat-ePRO demonstrates higher response rate (9/10, 90 %) and longer interaction time (10.86 s/turn) compared to the other two methods. CONCLUSION: Our study demonstrated the feasibility of utilizing algorithms such as prompt engineering to drive LLM in completing ePRO data collection tasks, and validated that the Chat-ePRO system can effectively enhance patient compliance.

Dual treatment with kynurenine pathway inhibitors and NAD+ precursors synergistically extends life span in Drosophila.

Tryptophan catabolism is highly conserved and generates important bioactive metabolites, including kynurenines, and in some animals, NAD+. Aging and inflammation are associated with increased levels of kynurenine pathway (KP) metabolites and depleted NAD+, factors which are implicated as contributors to frailty and morbidity. Contrastingly, KP suppression and NAD+ supplementation are associated with increased life span in some animals. Here, we used DGRP_229 Drosophila to elucidate the effects of KP elevation, KP suppression, and NAD+ supplementation on physical performance and survivorship. Flies were chronically fed kynurenines, KP inhibitors, NAD+ precursors, or a combination of KP inhibitors with NAD+ precursors. Flies with elevated kynurenines had reduced climbing speed, endurance, and life span. Treatment with a combination of KP inhibitors and NAD+ precursors preserved physical function and synergistically increased maximum life span. We conclude that KP flux can regulate health span and life span in Drosophila and that targeting KP and NAD+ metabolism can synergistically increase life span.

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.

NEAT1 repression by MED12 creates chemosensitivity in p53 wild-type breast cancer cells.

Breast cancer is often treated with chemotherapy. However, the development of chemoresistance results in treatment failure. Long non-coding RNA nuclear paraspeckle assembly transcript 1 (NEAT1) has been shown to contribute to chemoresistance in breast cancer cells. In studying the transcriptional regulation of NEAT1 using multi-omics approaches, we showed that NEAT1 is up-regulated by 5-fluorouracil in breast cancer cells with wild-type cellular tumor antigen p53 but not in mutant-p53-expressing breast cancer cells. The regulation of NEAT1 involves mediator complex subunit 12 (MED12)-mediated repression of histone acetylation marks at the promoter region of NEAT1. Knockdown of MED12 but not coactivator-associated arginine methyltransferase 1 (CARM1) induced histone acetylation at the NEAT1 promoter, leading to elevated NEAT1 mRNAs, resulting in a chemoresistant phenotype. The MED12-dependent regulation of NEAT1 differs between wild-type and mutant p53-expressing cells. MED12 depletion led to increased expression of NEAT1 in a wild-type p53 cell line, but decreased expression in a mutant p53 cell line. Chemoresistance caused by MED12 depletion can be partially rescued by NEAT1 knockdown in p53 wild-type cells. Collectively, our study reveals a novel mechanism of chemoresistance dependent on MED12 transcriptional regulation of NEAT1 in p53 wild-type breast cancer cells.

Analysis of neoadjuvant chemotherapy for breast cancer: a 20-year retrospective analysis of patients of a single institution.

BACKGROUND: Neoadjuvant chemotherapy (NAC) has been widely applied in operable breast cancer patients. This study aim to identify the predictive factors of overall survival(OS) and recurrence free survival (RFS) in breast cancer patients who received NAC from a single Chinese institution. PATIENTS AND METHODS: There were 646 patients recruited in this study. All the patients were treated at department of Surgical Oncology, Sir Run Run Shaw Hospital between February 25, 1999 and August 22, 2018. The relevant clinicopathological and follow-up data were collected retrospectively. RFS and OS were assessed using the Kaplan-Meier method. Multivariate Cox proportional hazards model was also employed. Multi-variate logistic regression model was simulated to predict pathologic complete response (pCR). RESULTS: In total, 118 patients (18.2%) achieved pCR during NAC. The 5-year OS was 94.6% versus 78.1% in patients with and without pCR, respectively (P < 0.001). The 5-year RFS was 95.3% and 72.7%, respectively (P < 0.001). No difference was detected among molecular subtypes of 5-year RFS in patients obtained pCR. Factors independently predicting RFS were HER2-positive subtype (hazard ratio(HR), 1.906; P = 0.004), triple-negative breast cancer (TNBC) (HR,2.079; P = 0.003), lymph node positive after NAC(HR,2.939; P < 0.001), pCR (HR, 0.396;P = 0.010), and clinical stage III (HR,2.950; P = 0.016). Multi-variate logistic regression model was simulated to predict the pCR rate after NAC, according to clinical stage, molecular subtype, ki-67, LVSI, treatment period and histology. In the ROC curve analysis, the AUC of the nomogram was 0.734 (95%CI,0.867-12.867). CONCLUSIONS: Following NAC, we found that pCR positively correlated with prognosis and the molecular subtype was a prognostic factor.

HCN channels sense temperature and determine heart rate responses to heat.

Heart rate increases with heat, [1-3] constituting a fundamental physiological relationship in vertebrates. Each normal heartbeat is initiated by an action potential generated in a sinoatrial nodal pacemaker cell. Pacemaker cells are enriched with hyperpolarization activated cyclic nucleotide-gated ion channels (HCN) that deliver cell membrane depolarizing inward current that triggers action potentials. HCN channel current increases due to cAMP binding, a mechanism coupling adrenergic tone to physiological 'fight or flight' heart rate acceleration. However, the mechanism(s) for heart rate response to thermal energy is unknown. We used thermodynamical and homology computational modeling, site-directed mutagenesis and mouse models to identify a concise motif on the S4-S5 linker of the cardiac pacemaker HCN4 channels (M407/Y409) that determines HCN4 current (If) and cardiac pacemaker cell responses to heat. This motif is required for heat sensing in cardiac pacemaker cells and in isolated hearts. In contrast, the cyclic nucleotide binding domain is not required for heat induced HCN4 current increases. However, a loss of function M407/Y409 motif mutation prevented normal heat and cAMP responses, suggesting that heat sensing machinery is essential for operating the cAMP allosteric pathway and is central to HCN4 modulation. The M407/Y409 motif is conserved across all HCN family members suggesting that HCN channels participate broadly in coupling heat to changes in cell membrane excitability.

Patients achieved pCR during neoadjuvant chemotherapy had better outcome than adjuvant chemotherapy setting in breast cancer: A comparative study.

PURPOSE: Pathological complete response(pCR) during neoadjuvant chemotherapy(NAC) has been proposed as a predictor for better prognosis in breast cancer. However, few studies compare the outcomes of patients receiving NAC and adjuvant chemotherapy(AC). METHODS: We retrospectively matched the patients who received NAC(N = 462) and AC(N = 462) by age, time of diagnosis, and primary clinical stage using the propensity score match in breast cancer patients treated in Sir Run Run Shaw Hospital with the median follow up of 67 months. Death from breast cancer and recurrence were used as endpoints. A multivariable Cox models were used to estimate the hazard ratios for breast-cancer specific survival (BCSS) and DFS. A multivariable logistic regression model was simulated to predict pCR. RESULTS: In patients who received NAC, 18.0%(83/462) patients achieved pCR, while the rest of the patients did not. pCR subgroup demonstrated significant better BCSS and DFS than patients receiving AC(BCSS: HR = 0.39, 95% CI:0.12-0.93, P = 0.03; DFS: HR = 0.16, 95%CI 0.009-0.73, P = 0.013) and non-pCR patients(BCSS: HR = 0.32, 95%CI 0.10-0.77, P = 0.008; DFS: HR = 0.12, 95%CI 0.007-0.55, P = 0.002). Patients who received AC demonstrated insignificant survival compared to non-pCR patients(BCSS: HR= 0.82, 95%CI 0.62-1.10, P = 0.19; DFS: HR = 0.75, 95%CI 0.53-1.07, P = 0.12). Patients with AC had significant better DFS than non-pCR patients(HR = 0.33, 95% CI 0.10-0.94, P = 0.04) in luminal B Her2+ patients. More NAC cycles(>2), TNBC, lower cT stage, and mixed histology indicate higher possibility of pCR(AUC = 0.89). CONCLUSION: pCR patients with NAC indicated better prognosis than patients receiving AC or non-pCR patients from NAC. The timing of chemotherapy may need carefully pondering in luminal B Her2+ patients.

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.

CaMKII as a Therapeutic Target in Cardiovascular Disease.

CaMKII (the multifunctional Ca2+ and calmodulin-dependent protein kinase II) is a highly validated signal for promoting a variety of common diseases, particularly in the cardiovascular system. Despite substantial amounts of convincing preclinical data, CaMKII inhibitors have yet to emerge in clinical practice. Therapeutic inhibition is challenged by the diversity of CaMKII isoforms and splice variants and by physiological CaMKII activity that contributes to learning and memory. Thus, uncoupling the harmful and beneficial aspects of CaMKII will be paramount to developing effective therapies. In the last decade, several targeting strategies have emerged, including small molecules, peptides, and nucleotides, which hold promise in discriminating pathological from physiological CaMKII activity. Here we review the cellular and molecular biology of CaMKII, discuss its role in physiological and pathological signaling, and consider new findings and approaches for developing CaMKII therapeutics.

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.

Corrigendum: STAT5a Confers Doxorubicin Resistance to Breast Cancer by Regulating ABCB1.

[This corrects the article DOI: 10.3389/fonc.2021.697950.].

Deoxyribonucleic Acid 5-Hydroxymethylation in Cell-Free Deoxyribonucleic Acid, a Novel Cancer Biomarker in the Era of Precision Medicine.

Aberrant methylation has been regarded as a hallmark of cancer. 5-hydroxymethylcytosine (5hmC) is recently identified as the ten-eleven translocase (ten-eleven translocase)-mediated oxidized form of 5-methylcytosine, which plays a substantial role in DNA demethylation. Cell-free DNA has been introduced as a promising tool in the liquid biopsy of cancer. There are increasing evidence indicating that 5hmC in cell-free DNA play an active role during carcinogenesis. However, it remains unclear whether 5hmC could surpass classical markers in cancer detection, treatment, and prognosis. Here, we systematically reviewed the recent advances in the clinic and basic research of DNA 5-hydroxymethylation in cancer, especially in cell-free DNA. We further discuss the mechanisms underlying aberrant 5hmC patterns and carcinogenesis. Synergistically, 5-hydroxymethylation may act as a promising biomarker, unleashing great potential in early cancer detection, prognosis, and therapeutic strategies in precision oncology.

STAT5a Confers Doxorubicin Resistance to Breast Cancer by Regulating ABCB1.

Chemoresistance is a daunting challenge to the prognosis of patients with breast cancer. Signal transducer and activator of transcription (STAT) 5a plays vital roles in the development of various cancers, but its function in breast cancer is controversial, and its role in chemoresistance in breast cancer remains unexplored. Here we identified STAT5a as a chemoresistance inducer that regulates the expression of ABCB1 in breast cancer and can be targeted by pimozide, an FDA-approved psychotropic drug. First, we found that STAT5a and ABCB1 were expressed at higher levels in doxorubicin-resistant cell lines and chemoresistant patients, and their expression was positively correlated. Then, we confirmed the essential roles of STAT5a and ABCB1 in doxorubicin resistance in breast cancer cells and the regulation of ABCB1 transcription by STAT5a. Subsequently, the efficacy of pimozide in inhibiting STAT5a and sensitizing doxorubicin-resistant breast cancer cells was tested. Finally, we verified the role of STAT5a in doxorubicin resistance in breast cancer and the efficacy of pimozide in reversing this resistance in vivo. Our study demonstrated the vital role of STAT5a in doxorubicin resistance in breast cancer. Targeting STAT5a might be a promising strategy for treating doxorubicin-resistant breast cancer. Moreover, repurposing pimozide for doxorubicin resensitization is attractive due to the safety profile of pimozide.

Impact of Wuhan lockdown on the spread of COVID-19 in China: a study based on the data of population mobility.

This study aimed to quantitatively assess the effectiveness of the Wuhan lockdown measure on controlling the spread of coronavirus diesase 2019 (COVID-19). : Firstly，estimate the daily new infection rate in Wuhan before January 23，2020 when the city went into lockdown by consulting the data of Wuhan population mobility and the number of cases imported from Wuhan in 217 cities of Mainland China. Then estimate what the daily new infection rate would have been in Wuhan from January 24 to January 30th if the lockdown measure had been delayed for 7 days，assuming that the daily new infection in Wuhan after January 23 increased in a high，moderate and low trend respectively (using exponential, linear and logarithm growth models). Based on that，calculate the number of infection cases imported from Wuhan during this period. Finally，predict the possible impact of 7-day delayed lockdown in Wuhan on the epidemic situation in China using the susceptible-exposed-infectious-removed (SEIR) model. : The daily new infection rate in Wuhan was estimated to be 0.021%，0.026%，0.029%，0.033% and 0.070% respectively from January 19 to January 23. And there were at least 20 066 infection cases in Wuhan by January 23，2020. If Wuhan lockdown measure had been delayed for 7 days，the daily new infection rate on January 30 would have been 0.335% in the exponential growth model，0.129% in the linear growth model，and 0.070% in the logarithm growth model. Correspondingly，there would have been 32 075，24 819 and 20 334 infection cases travelling from Wuhan to other areas of Mainland China，and the number of cumulative confirmed cases as of March 19 in Mainland China would have been 3.3-3.9 times of the officially reported number. Conclusions: Timely taking city-level lockdown measure in Wuhan in the early stage of COVID-19 outbreak is essential in containing the spread of the disease in China.

Predicting COVID-19 epidemiological trend by applying population mobility data in two-stage modeling.

:To predict the epidemiological trend of coronavirus disease 2019 (COVID-19) by mathematical modeling based on the population mobility and the epidemic prevention and control measures. : As of February 8，2020，the information of 151 confirmed cases in Yueqing，Zhejiang province were obtained，including patients' infection process，population mobility between Yueqing and Wuhan，etc. To simulate and predict the development trend of COVID-19 in Yueqing, the study established two-stage mathematical models，integrating the population mobility data with the date of symptom appearance of confirmed cases and the transmission dynamics of imported and local cases. : It was found that in the early stage of the pandemic，the number of daily imported cases from Wuhan (using the date of symptom appearance) was positively associated with the number of population travelling from Wuhan to Yueqing on the same day and 6 and 9 days before that. The study predicted that the final outbreak size in Yueqing would be 170 according to the number of imported cases estimated by consulting the population number travelling from Wuhan to Yueqing and the susceptible-exposed-infectious-recovered (SEIR) model; while the number would be 165 if using the reported daily number of imported cases. These estimates were close to the 170，the actual monitoring number of cases in Yueqing as of April 27，2020. : The two-stage modeling approach used in this study can accurately predict COVID-19 epidemiological trend.

Establishment and Characterization of a HER2-Positive Cell Line Derived From the Pleural Effusion of a Drug-Resistant Breast Cancer Patient.

Drug resistance is a daunting challenge in the treatment of breast cancer, making it an urgent problem to solve in studies. Cell lines are important tools in basic and preclinical studies; however, few breast cell lines from drug-resistant patients are available. Herein, we established a novel HER2-positive breast cancer cell line from the pleural effusion of a drug-resistant metastatic breast cancer patient. This cell line has potent proliferative capability and tumorigenicity in nude mice but weak invasive and colony-forming capability. The molecular subtype of the cell line and its sensitivity to chemotherapeutics and HER2-targeting agents are different from those of its origin, suggesting that the phenotype changes between the primary and metastatic forms of breast cancer.

Quinone oxidoreductase 1 is overexpressed in gastric cancer and associated with outcome of adjuvant chemotherapy and survival.

BACKGROUND: Quinine oxidoreductase 1 (NQO1) plays a vital role in protecting normal cells against oxidative damage and electrophilic attack. It is highly expressed in many solid tumors, suggesting a role in cancer development and progression. However, the role of NQO1 in gastric cancer and its effect on cancer development and prognosis have not been fully investigated. AIM: To investigate the clinical relevance of NQO1 protein expression in gastric cancer and to explore the potential of NQO1 to serve as a prognostic biomarker and therapeutic target. METHODS: In this retrospective study, gastric cancer specimens of 175 patients who were treated between 1995 and 2011 were subjected to immunohistochemistry analyses for NQO1. The correlation of NQO1 expression with gastric cancer prognosis and clinical and pathological parameters was investigated. RESULTS: NQO1 protein was overexpressed in 59.43% (104/175) of the analyzed samples. Overexpression of NQO1 was associated with a significantly inferior prognosis. In addition, multivariate analysis suggested that NQO1 overexpression, along with tumor stage and patient age, are prominent prognostic biomarkers for gastric cancer. Moreover, NQO1 overexpression was correlated to a better response to 5-fluorouracil (5-FU)-based adjuvant chemotherapy. CONCLUSION: NQO1 overexpression is associated with a significantly poor prognosis and better response to 5-FU in patients with gastric cancer. These findings are relevant for improving therapeutic approaches for gastric cancer patients.

CaMKII oxidation is a critical performance/disease trade-off acquired at the dawn of vertebrate evolution.

Antagonistic pleiotropy is a foundational theory that predicts aging-related diseases are the result of evolved genetic traits conferring advantages early in life. Here we examine CaMKII, a pluripotent signaling molecule that contributes to common aging-related diseases, and find that its activation by reactive oxygen species (ROS) was acquired more than half-a-billion years ago along the vertebrate stem lineage. Functional experiments using genetically engineered mice and flies reveal ancestral vertebrates were poised to benefit from the union of ROS and CaMKII, which conferred physiological advantage by allowing ROS to increase intracellular Ca2+ and activate transcriptional programs important for exercise and immunity. Enhanced sensitivity to the adverse effects of ROS in diseases and aging is thus a trade-off for positive traits that facilitated the early and continued evolutionary success of vertebrates.