A Novel Systematic Oxidative Stress Score Predicts the Prognosis of Patients with Operable Breast Cancer

Preoperative integrated oxidative stress score as a prognostic factor for predicting clinical outcomes in breast cancer patients received neoadjuvant chemotherapy: a real-world retrospective study

Objective: The current study aims to investigate the prognostic value of breast cancer integrated oxidative stress score (BCIOSS) in patients with breast cancer who received neoadjuvant chemotherapy (NACT). Methods: A retrospective analysis of 104 breast cancer patients who underwent NACT from June 2009 to December 2015 was performed. The differences of BCIOSS of breast cancers in regard to variables were analyzed using Chi-square test and Fisher's exact test. The Kaplan-Meier method was used to evaluate survival curve between low BCIOSS group and high BCIOSS group, and the two groups were compared by Log-rank tests at the individual index level. The univariate and multivariate Cox regression analyses were established by the important predictive factors determined based on univariate analysis. The nomograms were further conducted based on the factors by the multivariate analyses. Results: Patients were assigned to low BCIOSS group (BCIOSS≤2.54) or high BCIOSS group (BCIOSS>2.54) via ROC curve. BCIOSS was a latent prognostic factor for patient survival [DFS; hazard ratio (HR): 0.163, 95%CI: 0.045-0.596, P=0.006; and OS; HR: 0.168, 95%CI: 0.056-0.500, P=0.001]. Patients with a high BCIOSS had longer survival time than those with a low BCIOSS (DFS: χ2=7.317, P=0.0068; and OS: χ2=9.407, P=0.0022). Calibration curves shown that the predicted line conformed well to the reference line for the 5-year survival category. DCA revealed that the nomograms conducted had a better clinical predictive application than only by BCIOSS. Conclusion: BCIOSS is a latent prognostic factor, and patients with high oxidative stress scores have a better prognosis and longer survival time.

Expression Analysis of Oxidative Stress Markers 8-hydroxydeoxyguanosine and Protein Carbonyl in Breast Cancer and Their associations with Certain Immunological and Tumor Markers

OBJECTIVE

Breast cancer (BC) is a heterogeneous disease, recognized as a major public health problem worldwide, with several risk factors including oxidative stress, an imbalance between the production of reactive oxygen species (ROS) and antioxidant capacity. The aim of this study is to evaluate oxidative stress markers 8-Hydroxydeoxyguanosine (8-OHdG) and protein carbonyl and their associations with pathological and immunohistochemical parameters as well as the immune system in particular Interleukin-6 (IL-6) in BC patients from western Algeria.

METHODS

We analyzed serum concentrations of 8-OHdG and IL-6 by Eliza technique and protein carbonyl by derivatization of protein carbonyl groups with 2,4-dinitrophenylhydrazine (DNPH), then associated them with immunohistochemical and pathological parameters, as well as in the different molecular and histological groups of BC.

RESULTS

Our results show that there was no significant difference in serum concentrations of 8-OHdG and protein carbonyl, between controls and patients, and a negative correlation between these markers and lymph node count as well as with proliferation protein Ki-67. We also found a significant association between the DNA oxidation marker 8-OHdG and Human epidermal growth factor receptor 2 (HER2) expression. No association was found between oxidative stress markers and IL-6. Furthermore, no significant differences in serum levels of 8-OHdG and protein carbonyl were found in the different histological types and molecular classes of BC.

CONCLUSION

Our results show that our patients do not have oxidative stress and that physiological ROS concentrations represent a good prognostic indicator, particularly in cancer cell proliferation through their negative correlation with Ki-67, and also metastatic lymph node count. Moreover, HER2 probably has the capacity to modify the state of oxidative stress, notably DNA oxidation. Finally, different molecular and histological types of BC have the same oxidative stress level and antioxidant capacity.

The systemic oxidative stress index predicts clinical outcomes of esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy

Background

Strong correlations have been shown between systemic oxidative stress (SOS) and the occurrence, metastasis, and prognosis of many types of cancers. It is yet unknown how SOS levels relate to the prognosis of esophageal squamous cell carcinoma (ESCC). The current research aims to explore the prognostic role of systemic oxidative stress index (SOSI) on ESCC receiving neoadjuvant immunochemotherapy (nICT).

Methods

Retrospective recruitment was used to identify 224 nICT-treated ESCC patients. In order to determine the integrative score of SOSI, logistic regression analyses were utilized to screen independent risk variables, with disease-free survival (DFS) serving as the dependent variable. Given the non-linear relationship between SOSI and DFS, the best threshold was determined using a restricted cubic spline (RCS) model. Independent variable determination was executed using a cox regression analysis. For prognostic prediction, a risk categorization method based on recursive partitioning analysis (RPA) was also created.

Results

Four SOS-related indicators, including albumin, creatinine, blood urea nitrogen, and direct bilirubin, were used to establish the SOSI. The ideal threshold of SOSI, shown by the non-linear relationship between DFS and SOSI (P<0.001), was used to compare between two groups. As a potential prognostic factor for those nICT-treated ESCC patients, SOSI showed a strong correlation with both DFS and overall survival (OS). Patients with low SOSI had better DFS (55.1% vs. 85.5%, P<0.001) and OS (72.6% vs. 79.1%, P=0.013). Then, a new staging that included TNM and SOSI based on RPA algorithms was produced. In terms of prognostication, the RPA model performed significantly better than TNM classification.

Conclusion

SOSI is a simple and useful score based on available SOS-related indices. In ESCC receiving nICT, low SOSI is found to be an important factor of better prognosis.

Association between serum urea nitrogen levels and prostate-specific antigens (NHANES 2003-2010)

BACKGROUND

Increasing evidence suggests that serum urea nitrogen may be a risk factor for prostate cancer (PCa) and influence serum prostate-specific antigen (PSA) concentrations, but direct evidence of a relationship between PSA and serum urea nitrogen levels in the general population is still lacking. The aim of this study was to demonstrate the relationship between serum urea nitrogen levels and prostate-specific antigen (PSA) and prostate cancer.

METHODS

We conducted a cross-sectional study using the National Health and Nutrition Examination Survey (NHANES, 2003-2010) database. We performed a multifactorial regression analysis of the association between serum urea nitrogen levels and PSA and PCa, followed by subgroup analyses.

RESULTS

A total of 5256 subjects were included in this study, and after adjusting for demographic, biological, and immunologic variables, we found that there was a threshold for blood urea nitrogen concentration below which every 1 ng/mL increase in serum urea nitrogen was associated with a 0.0325 ng/mL increase in PSA concentration (log2 transformed) (95% CI: 0.0064, 0.0586), and the P trend was was less than 0.05 and the difference was statistically significant. Sensitivity analyses using the generalized additive model (GAM) showed a linear relationship between serum urea nitrogen and serum PSA concentrations when blood urea nitrogen concentrations ranged from 0 ng/ml to 6.78 ng/ml.

CONCLUSION

Serum urea nitrogen was independently and positively correlated with serum PSA concentration when the concentration of serum urea nitrogen ranged from 0 ng/ml to 6.78 ng/ml.

Prognostic prediction of oxidative stress related hematological biomarkers in locally advanced cervical cancer patients undergoing chemoradiotherapy

OBJECTIVE

This investigation aimed to develop and validate a novel oxidative stress score for prognostic prediction in locally advanced cervical cancer (LACC) patients receiving chemoradiotherapy.

METHODS

A total of 301 LACC patients were enrolled and randomly divided into a training and a validation set. The association between oxidative stress parameters and prognosis was analyzed for oxidative stress score (OSS) establishment. A Cox regression model was conducted for overall survival (OS) and progression-free survival (PFS). A nomogram prediction model was developed using independent prognostic factors from the training set and validated in the validation set.

RESULTS

A novel OSS was established with four oxidative stress parameters, including albumin, total bilirubin, blood urea nitrogen, and lactate dehydrogenase. Multivariate regression analysis identified OSS as an independent prognostic factor for OS (p = 0.001) and PFS (p < 0.001). A predictive nomogram based on the OSS was established and validated. The C-indexes of the nomogram in the training set were 0.772 for OS and 0.781 for PFS, while in the validation set the C-indexes were 0.642 for OS and 0.621 for PFS.

CONCLUSION

This study confirmed that preoperative OSS could serve as a useful independent prognostic factor in LACC patients who received CCRT.

Gut Microbiome Interactions with Oxidative Stress: Mechanisms and Consequences for Health

Understanding how gut flora interacts with oxidative stress has been the subject of significant research in recent years. There is much evidence demonstrating the existence of the microbiome-oxidative stress interaction. However, the biochemical basis of this interaction is still unclear. In this narrative review, possible pathways of the gut microbiota and oxidative stress interaction are presented, among which genetic underpinnings play an important role. Trimethylamine-N-oxide, mitochondria, short-chain fatty acids, and melatonin also appear to play roles. Moreover, the relationship between oxidative stress and the gut microbiome in obesity, metabolic syndrome, chronic ethanol consumption, dietary supplements, and medications is considered. An investigation of the correlation between bacterial community features and OS parameter changes under normal and pathological conditions might provide information for the determination of new research methods. Furthermore, such research could contribute to establishing a foundation for determining the linkers in the microbiome-OS association.

Oxidative stress is two-sided in the treatment of acute myeloid leukemia

INTRODUCTION

Oxidative stress caused by elevated ROS, as a novel therapeutic mechanism, has been implicated in various tumors including AML. AML cells are chronically under oxidative stress, yet overreliance on ROS production makes tumor cells increasingly vulnerable to further damage. Reducing the cytotoxic effect of ROS on normal cells while killing leukemia stem cell (LSC) with high levels of reactive oxygen species is a new challenge for oxidative stress therapy in leukemia.

METHODS

By searching literature databases, we summarized recent relevant studies. The relationship of ROS on AML genes, signaling pathways, and transcription factors, and the correlation of ROS with AML bone marrow microenvironment and autophagy were summarized. In addition, we summarize the current status of research on ROS and AML therapeutics. Finally, we discuss the research progress on redox resistance in AML.

RESULTS

This review discusses the evidence showing the link between redox reactions and the progression of AML and compiles the latest research findings that will facilitate future biological studies of redox effects associated with AML treatment.

CONCLUSION

We believe that exploiting this unique oxidative stress property of AML cells may provide a new way to prevent relapse and drug resistance.

Development of machine learning-based malignant pericardial effusion-related model in breast cancer: Implications for clinical significance, tumor immune and drug-therapy

Background

Malignant pericardial effusion (MPE) is a common complication of advanced breast cancer (BRCA) and plays an important role in BRCA. This study is aims to construct a prognostic model based on MPE-related genes for predicting the prognosis of breast cancer.

Methods

The BRCA samples are analyzed based on the expression of MPE-related genes by using an unsupervised cluster analysis method. This study processes the data by least absolute shrinkage and selection operator and multivariate Cox analysis, and uses machine learning algorithms to construct BRCA prognostic model and develop web tool.

Results

BRCA patients are classified into three clusters and a BRCA prognostic model is constructed containing 9 MPE-related genes. There are significant differences in signature pathways, immune infiltration, immunotherapy response and drug sensitivity testing between the high and low-risk groups. Of note, a web-based tool (http://wys.helyly.top/cox.html) is developed to predict overall survival as well as drug-therapy response of BRCA patients quickly and conveniently, which can provide a basis for clinicians to formulate individualized treatment plans.

Conclusion

The MPE-related prognostic model developed in this study can be used as an effective tool for predicting the prognosis of BRCA and provides new insights for the diagnosis and treatment of BRCA patients.

The systemic oxidative stress score has a prognostic value on gastric cancer patients undergoing surgery

Background

Oxidative stress is strongly associated with the development, recurrence metastasis, and treatment of gastric cancer. It is yet unknown, though, how systemic oxidative stress levels relate to the surgically treated gastric cancer patients' clinical results. This research aims to investigate the prognostic effect of systemic oxidative stress score, also known as systematic oxidative stress score (SOS), on gastric cancer patients undergoing surgical treatment.

Methods

Development of the SOS Formula through Least Absolute Shrinkage and Selection Operator LASSO Cox Regression. By using optimal cut-off values, the 466 patients included in the study had been split into high SOS and low SOS groups. Utilizing Chi-square test and the Wilcoxon rank sum test, this research examined the relationship between SOS and clinical traits. With the aid of Kaplan-Meier and COX regression analysis, the prognosis of patients with gastric cancer was examined.

Results

SOS consisted of four oxidative stress-related laboratory indices. Univariate and multivariate COX regression analyses revealed that SOS, Age, CA724, Radical resection and TNM stage were crucial prognostic factors for OS, and the independent prognostic factors for PFS included Age, CA724, TNM stage and SOS. They could have their prognosis correctly predicted using a nomogram built around SOS and independent prognostic variables.

Conclusion

SOS is a practical and reasonably priced tool for determining a patient's prognosis for gastric cancer. More notably, SOS is an accurate prognostic factor for patients with advanced gastric cancer who has undergone radical surgery.

Construction of a 5-gene prognostic signature based on oxidative stress related genes for predicting prognosis in osteosarcoma

BACKGROUND

The understanding of the complex biological scenario of osteosarcoma will open the way to identifying new strategies for its treatment. Oxidative stress is a cancer-related biological scenario. At present, it is not clear the oxidative stress genes in affecting the prognosis and progression of osteosarcoma, the underlying mechanism as well as their impact on the classification of osteosarcoma subtypes.

METHODS

We selected samples and sequencing data from TARGET data set and GSE21257 data set, and downloaded oxidative stress related-genes (OSRGs) from MsigDB. Univariate Cox analysis of OSRG was conducted using TARGET data, and the prognostic OSRG was screened to conduct unsupervised clustering analysis to identify the molecular subtypes of osteosarcoma. Through least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression analysis of differentially expressed genes (DEGs) between subgroups, a risk assessment system for osteosarcoma was developed.

RESULTS

45 prognosis-related OSRGs genes were acquired, and two molecular subtypes of osteosarcoma were clustered. C2 cluster displayed prolonged overall survival (OS) accompanied with high degree of immune infiltration and enriched immune pathways. While cell cycle related pathways were enriched in C2 cluster. Based on DEGs between subgroups and Lasso analysis, 5 hub genes (ZYX, GJA5, GAL, GRAMD1B, and CKMT2) were screened to establish a robust prognostic risk model independent of clinicopathological features. High-risk group had more patients with cancer metastasis and death as well as C1 subtype with poor prognosis. Low-risk group exhibited favorable OS and high immune infiltration status. Additionally, the risk assessment system was optimized by building decision tree and nomogram.

CONCLUSIONS

This study defined two molecular subtypes of osteosarcoma with different prognosis and tumor immune microenvironment status based on the expression of OSRGs, and provided a new risk assessment system for the prognosis of osteosarcoma.

Hepatocellular carcinoma immune prognosis score predicts the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors

OBJECTIVE

The predictive biomarkers of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) still need to be further explored. This study aims to establish a new immune prognosis biomarker to predict the clinical outcomes of hepatocellular carcinoma patients receiving immune checkpoint inhibitors.

METHODS

The subjects of this study were 151 HCC patients receiving ICIs at Harbin Medical University Cancer Hospital from January 2018 to December 2021. This study collected a wide range of blood parameters from patients before treatment and used Cox's regression analysis to identify independent prognostic factors in blood parameters, as well as their β coefficient. The hepatocellular carcinoma immune prognosis score (HCIPS) was established through Lasso regression analysis and COX multivariate analysis. The cut-off value of HCIPS was calculated from the receiver operating characteristic (ROC) curve. Finally, the prognostic value of HCIPS was validated through survival analysis, stratified analyses, and nomograms.

RESULTS

HCIPS was composed of albumin (ALB) and thrombin time (TT), with a cut-off value of 0.64. There were 56 patients with HCIPS < 0.64 and 95 patients with HCIPS ≥ 0.64, patients with low HCIPS were significantly related to shorter progression-free survival (PFS) (13.10 months vs. 1.63 months, P < 0.001) and overall survival (OS) (14.83 months vs. 25.43 months, P < 0.001). HCIPS has also been found to be an independent prognostic factor in this study. In addition, the stratified analysis found a significant correlation between low HCIPS and shorter OS in patients with tumor size ≥ 5 cm (P of interaction = 0.032). The C-index and 95% CI of the nomograms for PFS and OS were 0.730 (0.680-0.779) and 0.758 (0.711-0.804), respectively.

CONCLUSIONS

As a new score established based on HCC patients receiving ICIs, HCIPS was significantly correlated with clinical outcomes in patients with ICIs and might serve as a new biomarker to predict HCC patients who cloud benefit from ICIs.

Systematic oxidative stress indices predicts prognosis in patients with urothelial carcinoma of the upper urinary tract after radical nephroureterectomy

BACKGROUND

Oxidative stress plays an important role in the occurrence and development of malignancy. However, the relationship between oxidative stress and upper urinary tract urothelial carcinoma (UTUC) prognosis remains elusive. This study aimed to evaluate the prognostic value of systematic oxidative stress indices as a predictor of patient outcomes in UTUC after radical nephroureterectomy.

METHODS

Clinical data for 483 patients with UTUC who underwent radical nephroureterectomy were analyzed. Patients were categorized according to an optimal value of systematic oxidative stress indices (SOSIs), including fibrinogen (Fib), gamma-glutamyl transpeptidase (γ-GGT), creatinine (CRE), lactate dehydrogenase (LDH) and albumin (ALB). Kaplan-Meier analyses were used to investigate associations of SOSIs with overall survival (OS) and progression-free survival (PFS). Moreover, associations between SOSIs and OS and PFS were assessed with univariate and multivariate analyses.

RESULTS

High values of Fib, γ-GGT, CRE, and LDH, and low values of ALB were associated with reduced OS. SOSIs status correlated with age, tumor site, surgical approach, hydronephrosis, tumor size, T stage, and lymph node status. The Kaplan-Meier survival analysis showed a significant discriminatory ability for death and progression risks in the two groups based on SOSIs. Multivariate Cox proportional hazards models showed that SOSIs were an independent prognostic indicator for OS (p = 0.007) and PFS (p = 0.021). SOSIs and clinical variables were selected to establish a nomogram for OS. The 1-, 3-, and 5-year AUC values were 0.77, 0.78, and 0.81, respectively. Calibration curves of the nomogram showed high consistencies between the predicted and observed survival probability. Decision curve analysis curves showed that the nomogram could well predict the 1-year, 3-year, and 5-year OS.

CONCLUSIONS

SOSIs are an independent unfavorable predictor of OS and PFS in patients diagnosed with UTUC undergoing RNU. Therefore, incorporating SOSIs into currently available clinical parameters may improve clinical decision-making.

Leveraging senescence-oxidative stress co-relation to predict prognosis and drug sensitivity in breast invasive carcinoma

Introduction

Female breast cancer has risen to be the most common malignancy worldwide, causing a huge disease burden for both patients and society. Both senescence and oxidative stress attach importance to cancer development and progression. However, the prognostic roles of senescence and oxidative stress remain obscure in breast cancer. In this present study, we attempted to establish a predictive model based on senescence-oxidative stress co-relation genes (SOSCRGs) and evaluate its clinical utility in multiple dimensions.

Methods

SOSCRGs were identified via correlation analysis. Transcriptome data and clinical information of patients with breast invasive carcinoma (BRCA) were accessed from The Cancer Genome Atlas (TCGA) and GSE96058. SVM algorithm was employed to process subtype classification of patients with BRCA based on SOSCRGs. LASSO regression analysis was utilized to establish the predictive model based on SOSCRGs. Analyses of the predictive model with regards to efficacy evaluation, subgroup analysis, clinical association, immune infiltration, functional strength, mutation feature, and drug sensitivity were organized. Single-cell analysis was applied to decipher the expression pattern of key SOSCRGs in the tumor microenvironment. Additionally, qPCR was conducted to check the expression levels of key SOSCRGs in five different breast cancer cell lines.

Results

A total of 246 SOSCRGs were identified. Two breast cancer subtypes were determined based on SOSCRGs and subtype 1 showed an active immune landscape. A SOSCRGs-based predictive model was subsequently developed and the risk score was clarified as independent prognostic predictors in breast cancer. A novel nomogram was constructed and exhibited favorable predictive capability. We further ascertained that the infiltration levels of immune cells and expressions of immune checkpoints were significantly influenced by the risk score. The two risk groups were characterized by distinct functional strengths. Sugar metabolism and glycolysis were significantly upregulated in the high risk group. The low risk group was deciphered to harbor PIK3CA mutation-driven tumorigenesis, while TP53 mutation was dominant in the high risk group. The analysis further revealed a significantly positive correlation between risk score and TMB. Patients in the low risk group may also sensitively respond to several drug agents. Single-cell analysis dissected that ERRFI1, ETS1, NDRG1, and ZMAT3 were expressed in the tumor microenvironment. Moreover, the expression levels of the seven SOSCRGs in five different breast cancer cell lines were quantified and compared by qPCR respectively.

Conclusion

Multidimensional evaluations verified the clinical utility of the SOSCRGs-based predictive model to predict prognosis, aid clinical decision, and risk stratification for patients with breast cancer.

An oxidative stress biomarkers predict prognosis in gastric cancer patients receiving immune checkpoint inhibitor

Objective

The development and advance of gastric cancer are inextricably linked to oxidative and antioxidant imbalance. Although immunotherapy has been shown to be clinically effective, the link between oxidative stress and gastric cancer patients treated with immune checkpoint inhibitor (ICIs) remains unknown. This study aims at looking into the prognostic value of oxidative stress scores in gastric cancer patients treated with ICIs.

Methods

By taking the propagation to receiver operating characteristic (ROC) we got the best cut-off values, and divided 265 patients receiving ICIs and chemotherapy into high and low GC-Integrated Oxidative Stress Score (GIOSS) groups. We also used Kaplan-Meier and COX regression models to investigate the relationship between oxidative stress biomarkers and prognosis.

Results

Through both univariate and multivariate analyses, it's shown that GIOSS severs as an independent prognostic factor for progression-free survival (PFS) and Overall survival (OS). Based on GIOSS cutoff values, patients with high GIOSS levels, compared to those with low levels exhibited shorter PFS and OS, both in the high GIOSS group, which performed poorly in the ICIs subgroup and other subgroup analyses.

Conclusion

GIOSS is a biomarker that responds to systemic oxidative stress in the body and can predict prognosis in patients with gastric cancer who are taking ICIs. Additionally, it might come to medical professionals' aid in making more effective or more suitable treatment plans for gastric cancer.

The Effects of Oncological Treatment on Redox Balance in Patients with Uveal Melanoma

(1) Background: Uveal malignant melanoma is the most common adult eye cancer and presents metabolic reprogramming that affects the tumoral microenvironment by altering the redox balance and producing oncometabolites. (2) Methods: The study prospectively evaluated patients undergoing enucleation surgery or stereotactic radiotherapy for uveal melanoma by following systemic oxidative-stress redox markers serum lipid peroxides, total albumin groups and total antioxidant levels (3) Results: Serum antioxidants and lipid peroxides were elevated from pre-treatment to longer-term follow-up. Antioxidants inversely correlated to lipid peroxides: higher in stereotactic radiosurgery patients pre/6/12/18 months post-treatment (p = 0.001-0.049) versus higher lipid peroxides in enucleation surgery patients pre/after/6 months post-treatment (p = 0.004-0.010). An increased variance in serum antioxidants was observed for enucleation surgery patients (p < 0.001), however enucleation did not increase mean serum antioxidants or albumin thiols; only lipid peroxides were increased post-enucleation (p < 0.001) and at 6-month follow-up (p = 0.029). Mean albumin thiols were increased for 18- and 24-month follow-ups (p = 0.017-0.022). Males who had enucleation surgery presented higher variance in serum determinations and overall higher lipid peroxides values pre/post-treatment and at the 18-month follow-up. (4) Conclusions: Initial oxidative stress-inducing events of surgical enucleation or stereotactic radiotherapy for uveal melanoma are followed by a longer-term inflammatory cascade gradually subsiding at later follow-ups.

A Novel Systematic Oxidative Stress Score Predicts the Survival of Patients with Early-Stage Lung Adenocarcinoma

This study aimed to construct an effective nomogram based on the clinical and oxidative stress-related characteristics to predict the prognosis of stage I lung adenocarcinoma (LUAD). A retrospective study was performed on 955 eligible patients with stage I LUAD after surgery at our hospital. The relationship between systematic-oxidative-stress biomarkers and the prognosis was analyzed. The systematic oxidative stress score (SOS) was established based on three biochemical indicators, including serum creatinine (CRE), lactate dehydrogenase (LDH), and uric acid (UA). SOS was an independent prognostic factor for stage I LUADs, and the nomogram based on SOS and clinical characteristics could accurately predict the prognosis of these patients. The nomogram had a high concordance index (C-index) (0.684, 95% CI, 0.656-0.712), and the calibration curves for recurrence-free survival (RFS) probabilities showed a strong agreement between the nomogram prediction and actual observation. Additionally, the patients were divided into two groups according to the cut-off value of risk points based on the nomogram, and a significant difference in RFS was observed between the high-risk and low-risk groups (p < 0.0001). SOS is an independent prognostic indicator for stage I LUAD. These things considered, the constructed nomogram based on SOS could accurately predict the survival of those patients.

Systematic Oxidative Stress Indexes Associated with the Prognosis in Patients with T Lymphoblastic Lymphoma/Leukemia

Background

T lymphoblastic lymphoma/leukemia (T-LBL/ALL) is an aggressive malignant tumor with 5-year overall survival (OS) rate reached 80% after high-dose chemotherapy. Due to the relatively low incidence of T-LBL/ALL, only a few risk factors have been identified. The occurrence and prognosis of malignant tumors are closely related to oxidative stress, but the prognostic relationship between T-LBL/ALL and systematic oxidative stress indexes has not been reported yet.

Methods

A total of 258 T-LBL/ALL patients were retrospectively analyzed. The relationship between systematic oxidative stress indexes, such as creatinine (CRE), gamma-glutamyl transpeptidase (γ-GGT), albumin (ALB), alkaline phosphatase (ALP), fibrinogen (FBG), C-reactive protein (CRP) and total bilirubin (TBIL), and survival of T-LBL/ALL patients, was analyzed. The weight of indexes was used to calculate the patients' oxidative stress risk score. The independent prognostic value of oxidative stress risk grouping (OSRG) was analyzed.

Results

Higher CRE, CRP, and lower ALB were associated with poorer OS in T-LBL/ALL patients. The OSRG established by CRE, ALB, and CRP was an independent prognostic factor for OS of T-LBL/ALL patients. Patients in the high-risk group were more likely to be patients older than 14 years old and patients with superior vena cava obstruction syndrome (SVCS), pleural effusion, pericardial effusion, and mediastinal mass.

Conclusion

For OS in T-LBL/ALL patients, OSRG was observed as an independent prognostic factor, which provided a new idea for accurate prognostic prediction.

Early Prediction for Prediabetes and Type 2 Diabetes Using the Genetic Risk Score and Oxidative Stress Score

We aimed to use a genetic risk score (GRS) constructed with prediabetes and type 2 diabetes-related single nucleotide polymorphisms (SNPs) and an oxidative stress score (OSS) to construct an early-prediction model for prediabetes and type 2 diabetes (T2DM) incidence in a Korean population. The study population included 549 prediabetes and T2DM patients and 1036 normal subjects. The GRS was constructed using six prediabetes and T2DM-related SNPs, and the OSS was composed of three recognized oxidative stress biomarkers. Among the nine SNPs, six showed significant associations with the incidence of prediabetes and T2DM. The GRS was profoundly associated with increased prediabetes and T2DM (OR = 1.946) compared with individual SNPs after adjusting for age, sex, and BMI. Each of the three oxidative stress biomarkers was markedly higher in the prediabetes and T2DM group than in the normal group, and the OSS was significantly associated with increased prediabetes and T2DM (OR = 2.270). When BMI was introduced to the model with the OSS and GRS, the area under the ROC curve improved (from 69.3% to 70.5%). We found that the prediction model composed of the OSS, GRS, and BMI showed a significant prediction ability for the incidence of prediabetes and T2DM.