Simple Summary In the field of non-small cell lung cancer (NSCLC), there have been significant advancements in genomic data and bioinformatics tools, which have improved early diagnosis, treatment, and follow-up using biomarkers. Biomarkers provide measurable indicators of disease characteristics and help tailor treatment strategies in precision medicine. The integration of big data and artificial intelligence (AI) further enhances personalized medicine through advanced biomarker analysis. However, challenges exist in terms of limited evidence on the impact of new biomarkers on mortality and treatment efficacy, as well as data analysis and the adoption of precision medicine in clinical practice. Despite these obstacles, the integration of biomarkers into precision medicine has shown promise in improving patient outcomes in NSCLC. Continued research and advancements in biomarker discovery, utilization, and evidence generation are needed to overcome these challenges and further enhance precision medicine’s effectiveness in NSCLC. Abstract Non-small cell lung cancer (NSCLC) is a significant public health concern with high mortality rates. Recent advancements in genomic data, bioinformatics tools, and the utilization of biomarkers have improved the possibilities for early diagnosis, effective treatment, and follow-up in NSCLC. Biomarkers play a crucial role in precision medicine by providing measurable indicators of disease characteristics, enabling tailored treatment strategies. The integration of big data and artificial intelligence (AI) further enhances the potential for personalized medicine through advanced biomarker analysis. However, challenges remain in the impact of new biomarkers on mortality and treatment efficacy due to limited evidence. Data analysis, interpretation, and the adoption of precision medicine approaches in clinical practice pose additional challenges and emphasize the integration of biomarkers with advanced technologies such as genomic data analysis and artificial intelligence (AI), which enhance the potential of precision medicine in NSCLC. Despite these obstacles, the integration of biomarkers into precision medicine has shown promising results in NSCLC, improving patient outcomes and enabling targeted therapies. Continued research and advancements in biomarker discovery, utilization, and evidence generation are necessary to overcome these challenges and further enhance the efficacy of precision medicine. Addressing these obstacles will contribute to the continued improvement of patient outcomes in non-small cell lung cancer.

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Advances in Genomic Data and Biomarkers: Revolutionizing NSCLC Diagnosis and Treatment

APE1 is an essential endodeoxyribonuclease of the base excision repair pathway that maintains genome stability. It was identified as a pivotal factor favoring tumor progression and chemoresistance through the control of gene expression by a redox-based mechanism. APE1 is overexpressed and serum-secreted in different cancers, representing a prognostic and predictive factor and a promising non-invasive biomarker. Strategies directly targeting APE1 functions led to the identification of inhibitors showing potential therapeutic value, some of which are currently in clinical trials. Interestingly, evidence indicates novel roles of APE1 in RNA metabolism that are still not fully understood, including its activity in processing damaged RNA in chemoresistant phenotypes, regulating onco-miRNA maturation, and oxidized RNA decay. Recent data point out a control role for APE1 in the expression and sorting of onco-miRNAs within secreted extracellular vesicles. This review is focused on giving a portrait of the pros and cons of the last two decades of research aiming at the identification of inhibitors of the redox or DNA-repair functions of APE1 for the definition of novel targeted therapies for cancer. We will discuss the new perspectives in cancer therapy emerging from the unexpected finding of the APE1 role in miRNA processing for personalized therapy.

Revisiting Two Decades of Research Focused on Targeting APE1 for Cancer Therapy: The Pros and Cons

Abstract Gastric cancer (GC) is a common cancer worldwide with high mortality. Sirtuin 1 (SIRT1) and apurinic/apyrimidinic endodeoxyribonuclease 1 (APE1) are abnormally expressed in GC cells and related to p53, which is involved in ferroptosis. Thus, we explore the mechanism via which SIRT1, APE1, and p53 impact ferroptosis in GC cells. Specifically, GC cells were transfected with small-interfering RNA for SIRT1 (SiSIRT1) or small-interfering RNA for APE1 (SiAPE1) or with short-hairpin RNA for p53, and the cell viability, Fe2+, malondialdehyde (MDA), and glutathione (GSH) contents were detected by cell counting kit-8 assay and enzyme-linked immunosorbent assay. Western blot, immunofluorescence, and quantitative real-time polymerase chain reaction were conducted to quantify SIRT1, APE1, p53, solute carrier family 7 member 11 (SLC7A11), and glutathione peroxidase 4 (GPX4) levels in GC cells. Silencing of SIRT1 decreased viability, GSH content, and expressions of GPX4 and SLC7A11, while increased Fe2+, MDA content, and p53 expression in GC cells. Such aforementioned effects were reversed by APE1 overexpression. Also, SiAPE1 generated the same effects as SiSIRT1 on the above aspects, which was offset by p53 silencing. In short, SIRT1/APE1 promotes the growth of GC cells by targeting p53 to inhibit ferroptosis.

/pdf/sirt1-ape1-promotes-the-viability-of-gastric-cancer-cells-by-1rr0jmi7.pdf

SIRT1/APE1 promotes the viability of gastric cancer cells by inhibiting p53 to suppress ferroptosis

Abstract Diagnosing low-grade and high-grade endometrial stromal sarcoma (LG-ESS and HG-ESS) is a challenge. This study aimed to identify biomarkers. 22 ESS cases were analyzed using Illumina microarrays. Differentially expressed genes (DEGs) were identified via Limma. DEGs were analyzed with String and Cytoscape. Core genes were enriched with GO and KEGG, their pan-cancer implications and immune aspects were studied. 413 DEGs were found by exome sequencing, 2174 by GSE85383 microarray. 36 common genes were identified by Venn analysis, and 10 core genes including RBFOX1, PCDH7, FAT1 were selected. Core gene GO enrichment included cell adhesion, T cell proliferation, and KEGG focused on related pathways. Expression was evaluated across 34 cancers, identifying immune DEGs IGF1 and AVPR1A. Identifying the DEGs not only helps improve our understanding of LG-ESS, HG-ESS but also promises to be potential biomarkers for differential diagnosis between LG-ESS and HG-ESS and new therapeutic targets. 

Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis

Expression Profile, Molecular Association, and Clinical Significance of POLD4 in Glioblastoma

Perception of hub genes engaged in metastatic gastric cancer (mGC) promotes novel ways to diagnose and treat the illness. The goal of this investigation is to recognize the hub genes and reveal its molecular mechanism. In order to explore the potential facts for gastric cancer, the expression profiles of two different datasets were used (GSE161533 and GSE54129). The genes were confirmed to be part of the PPI network for gastric cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. Responsible hub genes were identified. Data from Kaplan–Meier plotter confirmed the predictive value of these distinct genes in various stages of gastric malignancy. Upregulated and downregulated genes were identified to utilize for further analysis. Positive regulation by a host of viral process, positive regulation of granulocyte differentiation, negative regulation of histone H3–K9 methylation were found in DEGs analysis. In addition, five KEGG pathways were identified as an essential enhancer that include nucleotide excision repair; base excision repair; DNA replication; homologous recombination; and complement and coagulation cascades. POLE, BUB1B, POLD4, C3, BLM, CCT7, PRPF31, APEX1, PSMA7, and CDC45 were chosen as hub genes after combining the PPI results. Our study recommends that BUB1B, CCT7, APEX1, PSMA7, and CDC45 might be potential biomarkers for gastric cancer. These biomarkers are upregulated genes. Therefore, suppression of these genes will increase the survival rate in gastric cancer patients.

/pdf/in-silico-identification-of-hub-genes-as-observing-3ih53b6v.pdf

In Silico Identification of Hub Genes as Observing Biomarkers for Gastric Cancer Metastasis

Background: BCL2, a key regulator of apoptosis promoting cancer cell survival, is aberrantly expressed in many hematologic malignancies. The BCL2 inhibitor, venetoclax, is standard of care for the treatment of newly diagnosed AML in adults unfit for induction chemotherapy. Although venetoclax-based treatments have improved outcomes for pts with AML, there are concerns surrounding disease resistance after continued use and adverse events (AEs) such as gastrointestinal toxicities and neutropenia. Clinical findings have shown that 20-30% of pts using venetoclax are refractory to treatment, and a majority of pts who initially achieve remission ultimately relapse (N Engl J Med. 2020;383(7):617-629). The highly selective investigational BCL2 inhibitor, BGB-11417, demonstrated more potent antitumor activity than venetoclax in preclinical studies (Cancer Res. 2020;80[suppl, abstr]:3077). Aims: To present preliminary safety and efficacy results of BGB-11417 in combination with azacitidine in pts with AML enrolled in BGB-11417-103 (NCT04771130). Methods: BGB-11417-103 is an ongoing phase 1b/2, global, multicenter, dose-escalation and expansion study evaluating the combination of BGB-11417 and azacitidine in pts with AML (either treatment-naïve [TN] unfit for intensive induction chemotherapy or relapsed/refractory [R/R]), myelodysplastic syndrome, or myelodysplastic syndrome/myeloproliferative neoplasm. Pts who received prior azacitidine or BCL2 inhibitors were excluded. For pts with AML, the 10-day regimen consisted of BGB-11417 at 40 mg (Cohort 1), 80 mg (Cohort 2), or 160 mg (Cohort 3) in combination with azacitidine (75 mg/m2 x 7 days). In Cycle 1, a 4-day ramp-up of BGB-11417 was utilized starting at 1/8 of the target dose. The window to assess dose-limiting toxicity (DLT) was up to Day 28 for nonhematologic toxicities and Day 42 or initiation of Cycle 2 for hematologic toxicities. Treatment-emergent AEs were graded per Common Terminology Criteria for AEs v5.0. Responses were assessed using the 2017 European LeukemiaNet criteria (Blood. 2017;129(4):424-447). All pts gave informed consent. Results: As of 10 January 2022, 27 pts with AML were treated with the combination therapy (6 in Cohort 1; 15 in Cohort 2; 6 in Cohort 3; Table). Median age was 80 yrs (TN; 18 pts) and 70 yrs (R/R AML; 9 pts); 44% of pts had adverse karyotype. Median prior line of therapy for R/R AML was 1 (range 1-2). At a median study follow-up of 2.1 months and median duration of treatment of 1.84 months (range 0.3-7.6), 2 of 23 evaluable pts experienced DLTs (Grade 4 neutropenia and Grade 4 thrombocytopenia at the 80 mg x 10 day dose level), which did not meet the safety stopping protocol criteria. Laboratory tumor lysis syndrome (TLS) was observed in 1 pt with a known history of chronic kidney disease treated with 160 mg x 10 day; pt was asymptomatic and TLS resolved within 4 days. Most common nonhematologic AEs were constipation (37%) and azacitidine injection-site reaction (33%). Most common Grade ≥3 hematologic AEs were neutropenia (44%), thrombocytopenia (41%), and anemia (37%). No pts required dose reductions of BGB-11417. Majority (n=17; 63%) of pts are continuing study treatment. Ten pts discontinued due to AEs (n=3), proceeding to transplant (n=3), consent withdrawal (n=2), or disease progression (n=2). Preliminary CR/CRh rates for TN and R/R were 56% and 44%, respectively. Seven of the 9 CRs were achieved by end of Cycle 1. Image:Summary/Conclusion: Preliminary results show that a 10-day regimen of BGB-11417 plus azacitidine resulted in a majority of CR observed by the end of Cycle 1 and was well tolerated in pts with AML. 

P590: preliminary safety and efficacy of bgb-11417, a potent and selective b-cell lymphoma 2 (bcl2) inhibitor, in patients (pts) with acute myeloid leukemia (aml)

This work elucidates the idea of finding probable critical genes linked to breast adenocarcinoma. In this study, the GEO database gene expression profile data set (GSE70951) was retrieved to look for genes that were expressed variably across breast adenocarcinoma samples and healthy tissue samples. The genes were confirmed to be part of the PPI network for breast cancer pathogenesis and prognosis. In Cytoscape, the CytoHubba module was used to discover the hub genes. For correlation analysis, the predictive biomarker of these hub genes, as well as GEPIA, was used. A total of 155 (85 upregulated genes and 70 downregulated genes) were identified. By integrating the PPI and CytoHubba data, the major key/hub genes were selected from the results. The KM plotter is employed to find the prognosis of those major pivot genes, and the outcome shows worse prognosis in breast adenocarcinoma patients. Further experimental validation will show the predicted expression levels of those hub genes. The overall result of our study gives the consequences for the identification of a critical gene to ease the molecular targeting therapy for breast adenocarcinoma. It could be used as a prognostic biomarker and could lead to therapy options for breast adenocarcinoma.

/pdf/biomarkers-for-breast-adenocarcinoma-using-in-silico-11i30c0d.pdf

Biomarkers for Breast Adenocarcinoma Using In Silico Approaches

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In Silico Identification of Hub Genes as Observing Biomarkers for Gastric Cancer Metastasis

P590: preliminary safety and efficacy of bgb-11417, a potent and selective b-cell lymphoma 2 (bcl2) inhibitor, in patients (pts) with acute myeloid leukemia (aml)

Biomarkers for Breast Adenocarcinoma Using In Silico Approaches