Introduction: Lung cancer is among the leading causes of cancer-related mortality worldwide, In general, with their diverse subtypes, they are recognized as significant risk factors impacting human health.(Li et al., 2021; Panpan et al., 2024) Despite advances in early detection and therapeutic strategies, the prognosis for some subtypes specially non-small cell lung cancer (NSCLC) remains poor, highlighting the need for a deeper understanding of its molecular mechanisms.(Yin et al., 2020)
Hexokinases , pivotal enzymes in glucose metabolism, has garnered attention for its role in cancer biology.(Meng et al., 2021) According to recent studies, two distinct sub-groups have been identified: HK1 and HK2, Based on the definition, HK2 Positioned on the mitochondrial membrane.(Tan et al., 2025) HK2 not only drives glycolysis but also influences mitochondrial dynamics and cellular survival mechanisms.(Wei et al., 2025) Emerging evidence suggests that HK2 contributes to lung cancer progression through enhanced proliferation, migration, invasion, and metabolic reprogramming.(Yang et al., n.d.) Furthermore, findings from drug, biological, and genetic studies have revealed the isoform of HK2 has a close association with the Warburg effect, highlighting its pivotal role in cancer progression (Panpan et al., 2024). These insights have sparked extensive research efforts aimed at developing effective interventions to disrupt this metabolic cycle and target cancer cells more precisely (R. Li et al., 2022).
Thereby this easily explore This essay will explore the multifaceted role of hexokinase enzymes in lung cancer, with a particular focus on HK2, and evaluate their potential as therapeutic targets.
Methods: Data Sources
Genetic variation data were obtained from the National Center for Biotechnology Information (NCBI) resources(www.ncbi.nlm.nih.gov), specifically the dbSNP database and the NCBI Gene database. findings are restricted to the human Hexokinase family (HK1 and HK2). The structure the Methods section allows reharesal practice recommendations that emphasizes the logical for reproducibility and validity (Willis, 2023).
Gene and SNP Identification
For each gene of interest, all reported single nucleotide polymorphisms (SNPs) were retrieved using the dbSNP search tool. Filters were applied to include only human variants. Where available, functional annotations and clinical annotations were collected. To avoid common pitfalls in describing methodological steps, outlined by Crowe and Cash (2023).
Data Extraction
For each SNP, the following information was extracted: reference SNP ID (rsID), chromosomal location, variant type, allele frequency, and clinical significance as reported in dbSNP or ClinVar. In accordance with professional guidance, methods were drafted concurrently with data collection and aligned with the order of results presentation (AJE, 2022) (Table 1).
Literature Screening
Each SNP was cross-referenced against PubMed to identify previously reported associations with lung cancer. Search queries combined the rsID with disease-specific terms (e.g., “lung cancer”, “NSCLC”, “SCLC”, “adenocarcinoma”). The GWAS Catalog was also consulted for SNPs previously implicated in cancer susceptibility.
Prioritization and Analysis
Identified SNPs were categorized according to their functional class (coding, non-coding, regulatory). Variants were prioritized if they met one or more of the following criteria: (i) reported or predicted functional impact on protein sequence or splicing; (ii) annotation as pathogenic/likely pathogenic or risk allele; (iii) evidence of association with lung cancer in published studies or GWAS datasets; and/or (iv) rare allele frequency (minor allele frequency <0.05). Where relevant, schematic workflows were prepared to summarize the SNP selection pipeline, consistent with the methodological transparency guidelines of Pollock (2023).
Results: Abstract
Lung cancer remains a leading cause of cancer mortality worldwide, with subtypes such as non-small cell lung cancer (NSCLC) showing poor prognosis despite advancements in therapy (Li et al., 2021; Panpan et al., 2024). Hexokinases (HK), especially HK1 and HK2 isoforms, are critical enzymes in glucose metabolism and have gained attention for their roles in cancer biology (Meng et al., 2021). Hexokinase catalyzes the phosphorylation of glucose to glucose-6-phosphate, the first irreversible step in glycolysis, trapping glucose inside the cell and enabling its metabolism. HK2, located on the outer mitochondrial membrane, not only promotes glycolysis but also supports mitochondrial dynamics and cellular survival pathways (Tan et al., 2025; Wei et al., 2023).
In cancer cells, HK2 is often overexpressed, contributing to the Warburg effect, where cancer cells rely on glycolysis for energy even in the presence of oxygen. This metabolic reprogramming supports enhanced proliferation, migration, and survival of tumor cells (Yang et al., n.d.; Panpan et al., 2024). This study focuses on genetic variations in HK genes to understand their potential impact on lung cancer susceptibility.
Using data sourced from the NCBI databases (dbSNP and Gene), single nucleotide polymorphisms (SNPs) in the HK1 and HK2 genes were systematically identified, annotated, and analyzed. SNPs were prioritized based on their functional significance, allele frequency, and reported associations with lung cancer in literature and GWAS datasets (Willis, 2023; Crowe & Cash, 2023). Our analysis highlights several SNPs with potential pathogenic roles, supporting the hypothesis that genetic variations in hexokinase enzymes might contribute to lung cancer development and could serve as molecular targets for therapeutic intervention.
This investigation underscores the importance of integrating genetic data with clinical evidence to enhance our understanding of lung cancer pathogenesis and to foster development of targeted metabolic therapies.
Conclusion: Finally, knowing that various articles have mentioned the effect of the hexokinase enzyme in lung cancer, we examined the mechanism of action of this enzyme through the genes involved.
Keywords: Hexokinase, Lung cancer, Glucose metabolism, Cancer progression