Personalized Cancer Therapy Guided by Photoacoustic Chemical Imaging (PACI) of Tumor Microenvironment (TME)

标题：光声化学成像(PACI)引导的个性化癌症治疗 肿瘤微环境(TME) 摘要： 肿瘤通常处于代谢状态改变，这会导致化学成分异常，例如 缺氧(低氧水平)、酸中毒(低pH水平)和高钾血症(高钾浓度)。这些 这三种物质形成了“治疗耐药三联体(O2，pH和K+)”，抑制癌症对放化疗的反应。 和免疫疗法。因为每个三合会成员的注意力与癌症的进展和 对治疗的反应，一种非侵入性、敏感和可靠的方法来评估他们的时间和空间 在体内非侵袭性的肿瘤微环境(TME)的分布是非常理想的。为了填补这一严重的 和长期存在的技术差距，我们引入了一套新颖的O2、pH和K+传感纳米探针，在 与新兴的光声成像技术相结合，可以定量绘制O2，pH， 体内实体瘤中的K+水平。这项拟议研究的中心假设是，由我们的 由灵敏的化学指示剂纳米探针驱动的光声化学成像(PACI)，我们可以成像 并定量评估TME耐药三联体(O2、pH和 K+)，在体内，以非侵入性的方式，在深达几厘米的地方，然后与癌症相关 通过放射治疗、化疗和免疫治疗对治疗的反应。这一假设将得到严格的检验。 采用患者来源异种原位移植(PDX)乳腺癌小鼠模型。要实现全面的 了解TME的PACI成像结果，了解该技术的能力和局限性 将比较各种PDX肿瘤模型和治疗情况。检视中央 假设，我们的研究将集中在三个具体目标上：目标1.了解肿瘤对放射治疗的反应 TME的PACI；目的2。了解TME的PACI对肿瘤化疗的反应；以及目标3。 通过TME的PACI了解肿瘤对免疫治疗的反应。 潜在影响：由于PDX原位肿瘤与癌症患者的原始肿瘤非常相似， 包括他们的TME，这些PDX肿瘤的化学成像，结合研究 癌症治疗反应的影像表现可能会对翻译研究产生很大影响 和乳腺癌的临床管理，例如帮助辨别最合适的治疗方案或 针对个别癌症患者的替代计划。到这个资助期结束时，我们将客观地测试和 彻底验证由敏感纳米探针驱动的新型PACI技术是否可以成像TME的 体内非侵入性PDX小鼠肿瘤的化学性质，用于预测肿瘤对放射治疗的反应。 化疗和免疫疗法。一旦成功验证，拟议的战略可能会为 影像引导的个性化癌症药物，从而有望确保最佳的治疗结果。

Title: Personalized Cancer Therapy Guided by Photoacoustic Chemical Imaging (PACI) of Tumor Microenvironment (TME) Abstract: Tumors are often found in an altered metabolic state, which leads to anomalous chemical composition, such as hypoxia (low oxygen level), acidosis (low pH level), and hyperkalemia (high potassium concentration). These three form a “therapy resistance triad (O2, pH, and K+)”, suppressing cancer’s responses to radio-, chemo-, and immuno-therapy. As each triad member’s concentration is strongly relevant to cancer progress and response to therapy, a non-invasive, sensitive, and reliable approach for evaluating their temporal and spatial distributions in the tumor microenvironment (TME) in vivo, non-invasively, is highly desirable. To fill this serious and long-standing gap in technology, we introduce a novel set of O2, pH, and K+ sensing nanoprobes that, in combination with the emerging photoacoustic imaging technology, enables quantitative mapping of the O2, pH, and K+ levels in solid tumors in vivo. The central hypothesis of this proposed research is that, enabled by our photoacoustic chemical imaging (PACI) powered with sensitive chemical indicator nanoprobes, we can image and quantitatively evaluate the spatio-temporal distributions of the TME’s therapy resistance triad (O2, pH, and K+), at depths of up to a few centimeters, in vivo and in a non-invasive fashion, and then correlate with cancer responses to treatments via radio-, chemo-, and immuno-therapy. This hypothesis will be examined rigorously using orthotopic patient derived xenograft (PDX) breast cancer mouse models. To enable a comprehensive understanding of the technology’s capabilities, as well as limitations, the imaging results from PACI of the TME will be compared for a wide variety of PDX tumor models and treatment situations. To examine the central hypothesis, our research will focus on three specific aims: Aim 1. Understand tumor response to radio-therapy by PACI of the TME; Aim 2. Understand tumor response to chemo-therapy by PACI of the TME; and Aim 3. Understand tumor response to immuno-therapy by PACI of the TME. Potential impact: As the orthotopic PDX tumors faithfully resemble the original tumors in cancer patients, including their TME, chemical imaging of these PDX tumors, combined with studying the correlations of the imaging findings with the cancer responses to therapies, could have a large impact on translational research and clinical management of breast cancer, e.g. helping to discriminate the most suitable treatment plan or alternative plan for individual cancer patients. By the end of this funding period, we will objectively test and thoroughly verify whether the novel PACI technology powered by sensitive nanoprobes can image the TME’s chemical properties of PDX mouse tumors in vivo, non-invasively, for predicting the cancer responses to radio- , chemo-, and immuno-therapy. Once successfully validated, the proposed strategy could shed new light on imaging-guided personalized cancer medicine, so as to hopefully ensure an optimal treatment outcome.