Serum Levels of Sirtuin-1 in Patients with Lung Cancer and its Association with Karnofsky Performance Status

The role of Box A of HMGB1 in producing γH2AX associated DNA breaks in lung cancer

An ideal chemotherapeutic agent damages DNA, specifically in cancer cells, without harming normal cells. Recently, we used Box A of HMGB1 plasmid as molecular scissors to produce DNA gaps in normal cells. The DNA gap relieves DNA tension and increases DNA strength, preventing DNA double-strand breaks (DSBs). Since the formation of HMGB1-produced DNA gaps in cancers may differ from normal cells, the outcome of introducing Box A into cancer cells may be different. We demonstrated that in lung cancer cells, γH2AX foci and histone modification associating DSBs were produced by Box A. We transfected Box A plasmid into lung cancer cell lines to overexpress Box A and evaluated the expression levels of γH2AX foci and other DNA damage response (DDR) signaling cascade markers, including ATM, ATR, and p53. Then, we demonstrated the downstream effects of DSBs on lung cancer, lowering cell proliferation, decreasing cell migration, and promoting apoptosis. Thus, Box A in lung cancer promoted the opposite outcome to normal cells by breaking cancer DNA.

Role of Nicotinamide in the Pathogenesis of Actinic Keratosis: Implications for NAD+/SIRT1 Pathway

Actinic keratosis (AK) is a precursor to invasive squamous cell carcinoma, making early diagnosis and treatment essential to prevent progression. Among available therapeutic options, nicotinamide (NAM) has shown potential in reducing AK progression. NAM is a precursor of nicotinamide adenine dinucleotide (NAD+), which activates sirtuin (SIRT)1, a protein with anti-cancer properties. Although the role of SIRT1 in AK is still debated, no data currently exist on the systemic modulation of this protein in AK. Therefore, this study aims to evaluate whether NAM, by increasing serum NAD+ levels, may promote SIRT1 activation in peripheral blood mononuclear cells (PBMCs) in AK patients. Thirty patients were enrolled and treated with NAM for 24 months. Hematological, biochemical, and skin condition assessments were conducted, alongside the measurement of SIRT1 and NAD+ levels. A decrease in basophils, monocytes, total cholesterol, and blood glucose levels was observed in the study group, along with a reduction in AK lesions. Notably, NAM treatment significantly enhanced serum NAD+ levels, and nuclear SIRT1 activity in PBMCs. In conclusion, NAM administration significantly reduced AK progression in a NAD+/SIRT1-dependent manner, supporting its role as a chemopreventive agent in AK management.

Correlation Between Serum and Tissue SIRT1 Levels in Patients With Esophageal Squamous Cell Carcinoma

Background/Aim

Identifying prognostic and molecular markers as therapeutic targets for esophageal squamous cell carcinoma (ESCC) could enhance the efficacy of multidisciplinary treatments. While tissue expression of sirtuin 1 (SIRT1) has been linked to tumor progression in ESCC, prognostic significance of serum SIRT1 levels and their correlation with tissue SIRT1 remains unexplored. This study aimed to investigate the correlation between serum and tissue SIRT1 levels in patients with ESCC.

Patients and Methods

A total of 38 patients diagnosed with ESCC who were untreated preoperatively were recruited for this study. SIRT1 expression in the surgical specimens was assessed through immunostaining, while serum SIRT1 levels were measured using an enzyme-linked immunosorbent assay. We analyzed the association between tissue and serum SIRT1 levels, clinicopathological features, and patient prognosis.

Results

Positive SIRT1 expression in tissue was significantly associated with deeper tumor depth (p=0.020). It was also significantly associated with poorer overall survival (OS) and relapse-free survival (RFS) (p=0.041 and p=0.012, respectively). Elevated serum SIRT1 levels were significantly correlated with increased tumor depth and weight loss (p=0.012 and p=0.030). While higher serum SIRT1 levels tended to be associated with poorer OS (p=0.069), no significant correlation was found between SIRT1 expression in tissue and its concentration in serum.

Conclusion

SIRT1 tissue expression may be a valuable prognostic marker in ESCC. However, the clinical significance of serum SIRT1 levels appears to differ from that of its tissue expression. Future research is required to clarify the role of serum SIRT1 in ESCC.

Emerging role of sirtuins in non‑small cell lung cancer (Review)

Non‑small cell lung cancer (NSCLC) is a highly prevalent lung malignancy characterized by insidious onset, rapid progression and advanced stage at the time of diagnosis, making radical surgery impossible. Sirtuin (SIRT) is a histone deacetylase that relies on NAD+ for its function, regulating the aging process through modifications in protein activity and stability. It is intricately linked to various processes, including glycolipid metabolism, inflammation, lifespan regulation, tumor formation and stress response. An increasing number of studies indicate that SIRTs significantly contribute to the progression of NSCLC by regulating pathophysiological processes such as energy metabolism, autophagy and apoptosis in tumor cells through the deacetylation of histones or non‑histone proteins. The present review elaborates on the roles of different SIRTs and their mechanisms in NSCLC, while also summarizing novel therapeutic agents based on SIRTs. It aims to present new ideas and a theoretical basis for NSCLC treatment.

Evaluation of potential aging biomarkers in healthy individuals: telomerase, AGEs, GDF11/15, sirtuin 1, NAD+, NLRP3, DNA/RNA damage, and klotho

Aging is a natural process of gradual decrease in physical and mental capacity. Biological age (accumulation of changes and damage) and chronological age (years lived) may differ. Biological age reflects the risk of various types of disease and death from any cause. We selected potential biomarkers of aging - telomerase, AGEs, GDF11 and 15 (growth differentiation factor 11/15), sirtuin 1, NAD+ (nicotinamide adenine dinucleotide), inflammasome NLRP3, DNA/RNA damage, and klotho to investigate changes in their levels depending on age and sex. We included 169 healthy volunteers and divided them into groups according to age (under 35; 35-50; over 50) and sex (male, female; male and female under 35; 35-50, over 50). Markers were analyzed using commercial ELISA kits. We found differences in values depending on age and gender. GDF15 increased with age (under 30 and 35-50 p < 0.002; 35-50 and over 50; p < 0.001; under 35 and over 50; p < 0.001) as well as GDF11 (35-50 and over 50; p < 0.03; under 35 and over 50; p < 0.02), AGEs (under 30 and 35-50; p < 0.005), NLRP3 (under 35 over 50; p < 0.03), sirtuin 1 (35-50 and over 50; p < 0.0001; under 35 and over 50; p < 0.004). AGEs and GDF11 differed between males and females. Correlations were identified between individual markers, markers and age, and markers and sex. Markers that reflect the progression of biological aging vary with age (GDF15, GDF11, AGEs, NLRP3, sirtuin) and sex (AGEs, GDF11). Their levels could be used in clinical practice, determining biological age, risk of age-related diseases and death of all-causes, and initiating or contraindicating a therapy in the elderly based on the patient's health status.

Comparison of clinical efficacy between chrono-chemotherapy and conventional chemotherapy in patients with non-small cell lung cancer

This work focused on the clinical efficacy of chrono-chemotherapy and conventional chemotherapy on patients with non-small cell lung cancer (NSCLC), providing a theoretical basis for the clinical promotion of chrono-chemotherapy. 60 NSCLS patients in our hospital were randomly enrolled into a chrono-chemotherapy group and a conventional chemotherapy group, with 30 cases in each. Patients were treated with the standardized first-line treatment TP regimen (paclitaxel + cisplatin). After two cycles of chemotherapy, the clinical efficacy and adverse reactions of patients receiving various methods were observed. After the chemotherapy, CD3+, CD4+, and CD28+ increased while NK cells, B cells, and CD28- decreased in the conventional chemotherapy group (P<0.05); CD3+, CD4+, CD4+CD8+, B cells, and CD28+ increased while CD8+, NK cells, and CD28- decreased in chrono-chemotherapy group (P<0.05). The progression-free survival (PFS) of patients in the chrono-chemotherapy group (3.29 ± 0.46 years vs 2.56 ± 0.35 years) was longer (P<0.05). The quality of life (QOL) score in the chrono-chemotherapy group was higher (64.83 ± 1.54 points vs 51.72 ± 1.89 points) (P<0.05). The incidences of leukopenia (63.33%) and nausea and vomiting (53.33%) in the conventional chemotherapy group were higher than those in the chrono-chemotherapy group (30.00% and 30.00, respectively) (P<0.05). The chrono-chemotherapy could improve the cellular immune function of NSCLS patients, prolong their survival period, elevate the QOL, and reduce the side effects.

Comparison of nomogram and machine-learning methods for predicting the survival of non-small cell lung cancer patients

Background

Most patients with advanced non-small cell lung cancer (NSCLC) have a poor prognosis. Predicting overall survival using clinical data would benefit cancer patients by allowing providers to design an optimum treatment plan. We compared the performance of nomograms with machine-learning models at predicting the overall survival of NSCLC patients. This comparison benefits the development and selection of models during the clinical decision-making process for NSCLC patients.

Methods

Multiple machine-learning models were used in a retrospective cohort of 6586 patients. First, we modeled and validated a nomogram to predict the overall survival of NSCLC patients. Subsequently, five machine-learning models (logistic regression, random forest, XGBoost, decision tree, and light gradient boosting machine) were used to predict survival status. Next, we evaluated the performance of the models. Finally, the machine-learning model with the highest accuracy was chosen for comparison with the nomogram at predicting survival status by observing a novel performance measure: time-dependent prediction accuracy.

Results

Among the five machine-learning models, the accuracy of random forest model outperformed the others. Compared with the nomogram for time-dependent prediction accuracy with a follow-up time ranging from 12 to 60 months, the prediction accuracies of both the nomogram and machine-learning models changed as time varied. The nomogram reached a maximum prediction accuracy of 0.85 in the 60th month, and the random forest algorithm reached a maximum prediction accuracy of 0.74 in the 13th month.

Conclusions

Overall, the nomogram provided more reliable prognostic assessments of NSCLC patients than machine-learning models over our observation period. Although machine-learning methods have been widely adopted for predicting clinical prognoses in recent studies, the conventional nomogram was competitive. In real clinical applications, a comprehensive model that combines these two methods may demonstrate superior capabilities.