Due to our incomplete understanding of intricate cancer biology and the lack of preclinical models that properly mimic tumor complexity, therapies in clinical oncology studies have a high failure rate, a significant contributor to the high failure rate in clinical oncology studies. Currently, widespread usage of patient-derived xenograft (PDX) models is being established, allowing us to objectively evaluate the model’s ability to mimic and study critical clinical situations. These options include tumor heterogeneity and clonal development, tumor microenvironment contributions, discovering new medicines and biomarkers, and drug-resistance mechanisms.
Different Cancer and PDX Models
According to biomarker research for predictive and prognostic malignancies in individualized cancer therapy, clinical judgment and experience are more significant than clinical data reported. The following is a list of different kinds of cancer.
Gallbladder’s Cancer
Biliary tumors are uncommon but highly aggressive with poor outcomes. Their limited incidence hampered treatment trials. Therefore, research models are essential. Successful biliary cancer PDX models may be used to guide future high-risk patient therapy.
Neck and Head Cancer
Creating PDX models from head and neck cancer samples at various stages of the disease for clinical trials of head and neck cancer is possible, retaining their human donor’s genetic characteristics. In addition, chemotherapy and radiation may also treat them, enabling therapeutically helpful research.
Endometrial Cancer
An EC molecular classification was recently performed, providing a technique improving EC categorization together with histological results and optimizing patient therapy. PDX models were previously used in clinical trials for endometrial cancer, primarily as a customized tool for assessing the efficacy of therapies and identifying biomarkers for treatment response.
Acute Myeloid Leukemia
AML varies in myeloid hematopoiesis. Xenografts (PDX) are usually transient and non-transferable. They do not cause symptoms or death. Since blood cancer PDX models are permanent and may be used in clinical trials to study disease recurrence after treatment challenges and the efficacy of new medicines in treating drug-resistant cancers.
Cerebral Cancer
Patient survival in pediatric oncology has improved in recent decades, but most children with malignant brain tumors have a poor prognosis. Current pediatric brain cancer PDXs are produced into immunosuppressed rats or mice by xenografting fresh tissue, freshly acquired cell suspensions, or short-cropped neurospheres.
Cholangiocarcinoma
Cholangiocarcinoma is a low-prognosis type of cancer. This fatal disease needs excellent customized therapies. Biliary tumors are rare but aggressive with a bad prognosis. Their rarity complicates successful experiments.
Prostate Cancer
Prostate cancer is a complicated, diverse illness that poses significant difficulties to medication development and research. Preclinical models such as patient-derived xenografts (PDX) must thus be employed to evaluate medications primarily targeted for prostate cancer. Unfortunately, prostate cancer research for PDX models is challenging.
Testicular Cancer
Testicular cancer is one of the most frequent malignancies in young men aged 20–40, increasing globally. Testicular cancer models are usually considered the best method to anticipate drug effectiveness before clinical trials. These models may also be utilized for mechanistic research and preclinical testing of new testicular cancer treatments.
Conclusion
Preclinical models are essential in translational cancer research, from understanding disease biology to creating new therapeutic methods. Despite substantial limitations in the ability of PDX models to predict clinical outcomes, they remain the model of choice for preclinical research at present. Thus, continuing multi-institutional efforts are underway to develop and distribute these tools to optimize the translation potential of significant, well-annotated PDX resources. This research provides an in-depth evaluation of the current status of PDX models while addressing possible opportunities and challenges for future PDX development.