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Abstract：
Tumor or target heterogeneity (TH) implies presence of variable cellular populations having different genomic characteristics within the same tumor, or in different tumor sites of the same patient. The challenge is to identify this heterogeneity, as it has emerged as the most common cause of \'treatment resistance\', to current therapeutic agents. We have focused our discussion on \'Prostate Cancer\' and \'Neuroendocrine Tumors\', and looked at the established methods for demonstrating heterogeneity, each with its advantages and drawbacks. Also, the available theranostic radiotracers targeting PSMA and somatostatin receptors combined with targeted systemic agents, have been described. Lu-177 labeled PSMA and DOTATATE are the \'standard of care\' radionuclide therapeutic tracers for management of progressive treatment-resistant prostate cancer and NET. These approved therapies have shown reasonable benefit in treatment outcome, with improvement in quality of life parameters. Various biomarkers and predictors of response to radionuclide therapies targeting TH which are currently available and those which can be explored have been elaborated in details. Imaging-based features using artificial intelligence (AI) need to be developed to further predict the presence of TH. Also, novel theranostic tools binding to newer targets on surface of cancer cell should be explored to overcome the treatment resistance to current treatment regimens.
摘要：
肿瘤或靶异质性(TH)意味着在同一肿瘤内存在具有不同基因组特征的可变细胞群。或同一患者的不同肿瘤部位。挑战是识别这种异质性，因为它已经成为“治疗抵抗”的最常见原因，目前的治疗剂。我们将讨论重点放在“前列腺癌”和“神经内分泌肿瘤”上，并研究了证明异质性的既定方法，每一个都有其优点和缺点。此外，现有的针对PSMA和生长抑素受体的治疗诊断放射性示踪剂与靶向全身药物相结合，已被描述。Lu-177标记的PSMA和DOTATATE是“治疗标准”放射性核素治疗示踪剂，用于治疗进行性治疗抗性前列腺癌和NET。这些批准的疗法在治疗结果方面显示出合理的益处，随着生活质量参数的提高。已经详细阐述了目前可用的和可以探索的对靶向TH的放射性核素治疗的反应的各种生物标志物和预测因子。需要开发使用人工智能（AI）的基于成像的特征，以进一步预测TH的存在。此外，应探索与癌细胞表面新靶点结合的新型治疗诊断工具,以克服对现有治疗方案的治疗耐药性.
