<p>This study investigates the therapeutic potential of a nanosilica-cysteine composite loaded with arsenic trioxide (SC-As) in combination with cisplatin (CIS), paclitaxel (PTX), and doxorubicin (DOX) for lung/breast cancer treatment. Through comprehensive synthesis, characterization (ATR-FTIR, XRD, SEM, TEM, DLS), and cytotoxicity assessments, SC-As demonstrated superior potency with IC₅₀ values as low as 7.29 ± 1.40 µM in lung cancer (A549) and 8.60 ± 1.20 µM in breast cancer (MCF-7) cell lines. This study employs a dual-modal approach, combining in silico computational predictions (CompuSyn) with in vitro experiments to evaluate synergistic chemotherapy regimens, ensuring robust validation of therapeutic outcomes. The computational synergy analysis and the experimental validation in lung cancer cell lines revealed synergistic interactions between SC-As and CIS (CI &lt; 1), enabling significant dose reductions (DRI &gt; 1). Conversely, antagonism was observed with PTX and DOX in A549 cells, though H1299 cells exhibited unanticipated synergistic interactions with PTX/DOX. Given that H1299 cells represent a more aggressive and metastatic form of lung cancer, these results suggest that PTX and DOX combinations may have enhanced therapeutic potential in treating highly malignant lung cancer subtypes. These findings underscore the composite’s potential as a targeted delivery system and highlight the necessity of integrating computational predictions with empirical validation to optimize combinatorial efficacy and minimize toxicity, providing a foundation for future in vivo and clinical studies.</p>

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A dual-modal approach to lung cancer treatment: in vitro and in silico. Evaluation of a hybrid nanocomposite for synergistic chemotherapy

  • Omar Alnasra,
  • Fawwaz I. Khalili,
  • Lama Hamadneh,
  • Mohammad Alwahsh,
  • Rana Omar,
  • Amani AlDoridee,
  • Aya Hasan

摘要

This study investigates the therapeutic potential of a nanosilica-cysteine composite loaded with arsenic trioxide (SC-As) in combination with cisplatin (CIS), paclitaxel (PTX), and doxorubicin (DOX) for lung/breast cancer treatment. Through comprehensive synthesis, characterization (ATR-FTIR, XRD, SEM, TEM, DLS), and cytotoxicity assessments, SC-As demonstrated superior potency with IC₅₀ values as low as 7.29 ± 1.40 µM in lung cancer (A549) and 8.60 ± 1.20 µM in breast cancer (MCF-7) cell lines. This study employs a dual-modal approach, combining in silico computational predictions (CompuSyn) with in vitro experiments to evaluate synergistic chemotherapy regimens, ensuring robust validation of therapeutic outcomes. The computational synergy analysis and the experimental validation in lung cancer cell lines revealed synergistic interactions between SC-As and CIS (CI < 1), enabling significant dose reductions (DRI > 1). Conversely, antagonism was observed with PTX and DOX in A549 cells, though H1299 cells exhibited unanticipated synergistic interactions with PTX/DOX. Given that H1299 cells represent a more aggressive and metastatic form of lung cancer, these results suggest that PTX and DOX combinations may have enhanced therapeutic potential in treating highly malignant lung cancer subtypes. These findings underscore the composite’s potential as a targeted delivery system and highlight the necessity of integrating computational predictions with empirical validation to optimize combinatorial efficacy and minimize toxicity, providing a foundation for future in vivo and clinical studies.