Big Data and Artificial Intelligence in Drug Discovery for Gastric Cancer: Current Applications and Future Perspectives.

Gastric cancer (GC) represents a significant global health burden, ranking as the fifth most common malignancy and the fourth leading cause of cancer-related death worldwide. Despite recent advancements in GC treatment, the five-year survival rate for advanced-stage GC patients remains low. Consequently, there is an urgent need to identify novel drug targets and develop effective therapies. However, traditional drug discovery approaches are associated with high costs, time-consuming processes, and a high failure rate, posing challenges in meeting this critical need. In recent years, there has been a rapid increase in the utilization of artificial intelligence (AI) algorithms and big data in drug discovery, particularly in cancer research. AI has the potential to improve the drug discovery process by analyzing vast and complex datasets from multiple sources, enabling the prediction of compound efficacy and toxicity, as well as the optimization of drug candidates. This review provides an overview of the latest AI algorithms and big data employed in drug discovery for GC. Additionally, we examine the various applications of AI in this field, with a specific focus on therapeutic discovery. Moreover, we discuss the challenges, limitations, and prospects of emerging AI methods, which hold significant promise for advancing GC research in the future.

Long-term outcomes in patients with Burkitt lymphoma older than 65 years: an analysis of the Texas Cancer Registry.

Burkitt lymphoma (BL) is an extremely aggressive but curable subtype of non-Hodgkin lymphoma. While younger patients have excellent outcomes in response to aggressive chemoimmunotherapy, the rarity of this disease in older patients and limitations caused by age, comorbidities, and performance status may negate survival advantages. This analysis assessed outcomes of older adults with BL through data provided by the Texas Cancer Registry (TCR). Patients ≥65 years with BL were assessed. Patients were dichotomized into 1997-2007 and 2008-2018. Median overall survival (OS) and disease-specific survival (DSS) were assessed using Kaplan-Meier methodology, and covariates including age, race, sex, stage, primary site, and poverty index were analyzed using Pearson Chi-squared analysis. Odds ratio (OR) with 95% confidence intervals (CI) was used to assess factors contributing to patients not offered systemic therapy. P value <0.05 was considered statistically significant. Non-BL mortality events were also categorized. There were 325 adults, 167 in 1997-2007 and 158 in 2008-2018; 106 (63.5%) and 121 (76.6%) received systemic therapy, a trend that increased with time (p = 0.010). Median OS for 1997-2007 and 2008-2018 was 5 months (95% CI 2.469, 7.531) and 9 months (95% CI 0.000, 19.154) (p = 0.013), and DSS was 72 months (95% CI 56.397, 87.603) (p = 0.604) and not reached, respectively. For patients that received systemic therapy, median OS was 8 months (95% CI 1.278, 14.722) and 26 months (95% CI 5.824, 46.176) (p = 0.072), respectively, and DSS was 79 months (95% CI: 56.416, 101.584) and not reached, respectively (p = 0.607). Age ≥75 years (HR 1.39 [95% CI 1.078, 1.791], p = 0.011) and non-Hispanic whites (HR 1.407 [95% CI 1.024, 1.935], p = 0.035) had poorer outcomes, and patients at the 20-100% poverty index (OR 0.387 [95% CI 0.163, 0.921], p = 0.032) and increasing age at diagnosis (OR 0.947 [95% CI 0.913, 0.983], p = 0.004) were less likely to receive systemic therapy. Of 259 (79.7%) deaths, 62 (23.9%) were non-BL deaths, and 6 (9.6%) of these were from a second cancer. This two-decade analysis of older Texas patients with BL indicates a significant improvement in OS over time. Although patients were more likely to receive systemic therapy over time, treatment disparities existed in patients residing in poverty-stricken regions of Texas and in advancing age. These statewide findings reflect an unmet national need to find a systemic therapeutic strategy that can be tolerated by and augment outcomes in the growing elderly population.

Overcharging of the Zinc Ion in the Structure of the Zinc-Finger Protein Is Needed for DNA Binding Stability.

Zinc-finger structure, in which a Zn2+ ion binds to four cysteines or histidines in a tetrahedral structure, is a very common motif of nucleic acid-binding proteins. The corresponding interaction model is present in 3% of the genes in the human genome. As a result, the zinc finger has been extremely useful in various therapeutic and research capacities and in biotechnology. In a stable configuration of the zinc finger, the cysteine amino acids are deprotonated and become negatively charged. Thus, the Zn2+ ion is overscreened by four cysteine charges (overcharged). Whether this overcharged configuration is also stable when such a negatively charged zinc finger binds to a negatively charged DNA molecule is unknown. We investigated how the deprotonated state of cysteine influences its structure, dynamics, and function in binding to DNA molecules by using an all-atom molecular dynamics simulation up to the microsecond range of an androgen receptor protein dimer. Our results showed that the deprotonated state of cysteine residues is essential for the mechanical stabilization of the functional, folded conformation. This state stabilizes not only the protein structure but also the protein-DNA binding complex. The differences in the structural and energetic properties of the two sequence-identical monomers are also investigated and show the strong influence of DNA on the structure of the zinc-finger protein dimer upon complexation. Our result can potentially lead to a better molecular understanding of one of the most common classes of zinc fingers.

Hodgkin's lymphoma with HLH and complete remission with brentuximab-based therapy.

A 63-year-old man presented to the hospital with generalised weakness, fatigue and a 22 kg weight loss 4 months after being diagnosed with sarcoidosis on a mediastinal lymph node biopsy, with minimal improvement in symptoms on prednisone and methotrexate therapy. On arrival, he was found to have a haemoglobin of 57 g/L and platelet count of 82×109/L. Further work-up revealed six of eight diagnostic criteria for haemophagocytic lymphohistiocytosis (HLH): fever >38.9°C, splenomegaly, cytopaenia, hypertriglyceridaemia, haemophagocytosis and elevated ferritin >31 000 ng/mL. He was also found to have Epstein-Barr viraemia with greater than 17 000 copies. Bone marrow biopsy showed the presence of haemophagocytic histiocytes and evidence of classic Hodgkin's lymphoma. He was started on HLH-94 protocol. Later treatment was switched to lymphoma-directed therapy and he finished six cycles of A+AVD (brentuximab vedotin, doxorubicin, vinblastine and dacarbazine) with end-of-treatment positron emission tomography/CT and bone marrow negative for lymphoma.