Nanotechnology-based personalized treatment of metastatic ovarian cancer

这是一个跨学科项目的申请，该项目旨在开发个性化化疗的新方法。 妇科癌症。来自国家癌症研究所的估计表明，超过11.6万名女性在 美国将被诊断出患有妇科癌症，约有3.4万人死于这类癌症 在2021年。尽管外科手术和放射治疗取得了进展，但化疗仍然是一项重要的 妇科恶性肿瘤的治疗选择，特别是局部晚期和转移性肿瘤。然而， 化疗的疗效在很大程度上受到癌细胞固有的和获得性的耐药性的限制。 细胞毒性药物。我们建议开发和验证一种基于纳米技术的个性化方法 基于个体基因构建的卵巢癌(最致命的妇科癌症)的治疗 病人肿瘤的侧写。根据目前翻译研究的结果，以下处理 在本项目完成后，将为未来的临床试验提出方案。病人的样本 在肿瘤清除手术过程中将获得肿瘤及其周围正常组织和肿瘤轮廓数据 (预定义基因和蛋白质的表达)将被获取和分析。基于这一分析，有几个 将选出分子靶点和最有效的抗癌药物(S)。最后，一个复杂的混合体 含有药物(S)/小干扰RNA(S)/靶向肽的纳米载体靶向递送系统(TDS)将被 从预先合成的库中选择，患者将接受所选TDS设计的鸡尾酒治疗 特别是针对他们的个体肿瘤。选定的系统将包括基于脂质的载体，即肿瘤靶向 部分，最有效的药物(S)和小干扰RNA(S)，根据基因图谱为每个患者选择 病人的肿瘤。预计这种个性化治疗将有效地抑制耐药性和 肿瘤生长，特别是抑制转移的发展和限制治疗的不良副作用 有耐心的。这项拟议研究的主要目标是确定组织中基因/蛋白质的表达谱。 从卵巢癌患者分离的样本预测肿瘤反应和抗癌耐药性 具有不同作用机制的药物。我们还将开发一套含有抗癌药物(S)或 针对不同的mRNAs的小干扰RNA(S)在患者的肿瘤中过度表达。最后，基因图谱和 将对患者的肿瘤组织和恶性腹水样本进行蛋白质表达表型分析 患有卵巢癌。癌细胞将从手术过程中获得的新鲜样本中分离出来。基于 遗传图谱的结果将在体外(在细胞培养模型上)和在 活体(在皮下小鼠癌症模型上)使用从每个个体患者和 将制定卵巢癌个性化治疗的建议。

This is an application for an interdisciplinary project to develop a novel approach for personalized chemotherapy of gynecologic cancers. Estimates from the National Cancer Institute indicate that more than 116,000 women in the United States will be diagnosed with a gynecologic cancer and about 34,000 die from these types of cancer in 2021. Despite advances in surgical and radiation treatments, chemotherapy continues to be an important treatment option for gynecologic malignancies, especially for locally advanced and metastatic tumors. However, the efficacy of chemotherapy is substantially limited by the intrinsic and acquired resistance of cancer cells to cytotoxic drugs. We are proposing to develop and validate a nanotechnology-based approach of personalized treatment of ovarian carcinoma (most lethal type of gynecological cancers) constructed on the individual genetic profile of the patient’s tumor. Based on the results of the present translational research the following treatment protocol will be proposed for future clinical trials after the completion of the present project. Samples of a patient’s tumor and normal surrounding tissues will be obtained during the tumor debulking surgery and tumor profile data (the expression of predefined genes and proteins) will be obtained and analyzed. Based on this analysis, several molecular targets and the most effective anticancer drug(s) will be selected. Finally, a mixture of complex nanocarrier-based targeted delivery systems (TDS) containing drug(s)/siRNA(s)/targeted peptide will be selected from the pre-synthesized bank and the patient will be treated with the chosen cocktail of TDS designed specifically for their individual tumor. The selected systems will include the lipid-based carrier, the tumor targeting moiety, the most effective drug(s) and siRNA(s) selected for each individual patient based on a genetic profile of the patient’s tumor. It is expected that such personalized therapy will effectively suppress drug resistance and tumor growth, inhibit the development of metastases and limit adverse side effects of therapy in the particular patient. The main goals of the proposed research are to identify profiles of gene/protein expression in tissue samples isolated from patients with ovarian cancer that predict tumor response and resistance to anticancer drugs with different mechanisms of action. We also will develop a set of TDSs containing anticancer drug(s) or siRNA(s) targeted to different mRNAs overexpressed in the tumor of the patient. Finally, a genetic profile and protein expression phenotype will be performed on samples of tumor tissues and malignant ascites from patients with ovarian carcinoma. Cancer cells will be isolated from fresh samples obtained during surgery. Based on the results of the genetic profiling, a mixture of TDS will be created and tested in vitro (on cell culture model) and in vivo (on subcutaneous murine cancer model) using cancer cells isolated from each individual patient and recommendations for the personalized treatment of ovarian cancer will be developed.