Neoschaftoside & Lung Cancer: Systems Biology Insights

The global burden of lung cancer continues to rise, with projections indicating a significant increase in both incidence and mortality through 2050. Recent analyses, including data from GLOBOCAN 2022 (Zhou et al., 2024) and corroborating studies (Li et al., 2023), paint a stark picture: lung cancer remains the leading cause of cancer-related death worldwide, and its impact is disproportionately felt in developing nations. However, the landscape of lung cancer treatment is rapidly evolving, driven by advances in targeted therapies and immunotherapies, alongside ongoing efforts to overcome treatment resistance.

The “Deep Dive” reveals a complex interplay of factors contributing to this escalating crisis. While smoking remains the primary risk factor (Shankar et al., 2019), environmental and occupational exposures also play a significant role. Furthermore, the increasing sophistication of diagnostic techniques is leading to earlier detection, but this doesn’t necessarily translate to improved outcomes without effective treatment strategies. The rise of personalized medicine, tailoring treatment to the specific genetic mutations driving an individual’s cancer (Kerr, 2012), is a key area of focus. Specifically, mutations in EGFR are prevalent, and while third-generation EGFR inhibitors like osimertinib have shown initial promise (Hirsch et al., 2017; Dickerson & Diab, 2024), resistance inevitably develops (Fu et al., 2022; Koulouris et al., 2022; Gomatou et al., 2023; Cooper et al., 2022). Similar challenges exist with ALK and ROS1 rearrangements (Fabbri et al., 2023).

Beyond targeted therapies, research is expanding to address platinum-based chemotherapy resistance (Yusoh et al., 2025; Stefàno et al., 2024) and to combine radiation therapy with immunotherapies (Simone et al., 2015). Interestingly, a growing body of research is investigating the potential of natural products to combat cancer. Studies on Ailanthus altissima (Wang et al., 2018, 2021; Caramelo et al., 2021; Li et al., 2021) and other plants (Paudel et al., 2021; Desaipatti et al., 2025) demonstrate promising antitumor activity, potentially through mechanisms like inducing pyroptosis (Sannino et al., 2018) or targeting specific cancer pathways. Computational modeling and molecular docking studies (Alegaon et al., 2025; Kavalapure et al., 2024; Friesner et al., 2006, 2004) are accelerating the identification of novel drug candidates from these natural sources.

The Forward Look: The next five years will likely see a continued emphasis on overcoming treatment resistance. Combination therapies – blending targeted agents, immunotherapies, and potentially natural compounds – will be crucial. We can anticipate increased use of liquid biopsies for early detection of resistance mutations and more sophisticated genomic profiling to identify patients most likely to benefit from specific treatments. The integration of artificial intelligence and machine learning to analyze complex datasets (like those generated by radiomics – Khodabakhshi et al., 2021) will also accelerate drug discovery and personalized treatment strategies. Furthermore, research into the tumor microenvironment (Yang et al., 2021) and the role of co-occurring mutations (Qiu et al., 2021; Aguiar et al., 2018) will be essential for developing more effective and durable therapies. Finally, the exploration of novel targets, such as PRKCA in cisplatin resistance (Sun et al., 2024), and the development of innovative drug delivery systems will be critical in the fight against this devastating disease (Hendriks et al., 2024).