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What are the Different Types of Cancer and PDX Models?

Posted on July 3, 2021November 29, 2021 by Travis Lanford

New treatments in clinical oncology studies have a high failure rate due to our imperfect knowledge of complicated cancer biology and the scarcity of preclinical models that accurately replicate tumor complexity. Patient-derived xenograft (PDX) models are already widely used, allowing us to objectively evaluate platform capability to mimic and study critical clinical situations. As a result, tumor heterogeneity and clonal development, contributions to the tumor microenvironment, the discovery of new medicines and biomarkers, and drug-resistance mechanisms are all possible.

The Different Types of Cancer 

According to biomarker studies for predictive and prognostic malignancies, clinical judgment and expertise are more essential than published clinical data in developing customized cancer therapy. The following is a list of cancer types.

Gallbladder Cancer 

Biliary tumors are uncommon malignancies that are incredibly aggressive and have poor outcomes. Their rarity made it challenging to conduct appropriate treatment studies. As a result, new research platforms are badly needed. However, successful PDX models for biliary cancer are feasible and may guide the treatment of future high-risk patients.

Neck and Head

It is possible to engrave PDXs from head and neck cancer samples at various phases of the disease for clinical studies of head and neck cancer. They maintain their human donor’s genetic characteristics. In addition, chemotherapy and radiation may also be used to treat them, allowing for therapeutic research.

Endometrial Cancer 

Endometrial cancer research for molecular classification was recently completed, resulting in a technique that consistently improves EC categorization while optimizing patient therapy by combining histological results. PDX models have been used in EC before, mainly as a customized tool for assessing the efficacy of novel therapies and identifying treatment-response biomarkers; however, there are currently no global or holistic methods to their use.

Acute Myeloid Leukemia

Models generated from xenografts (PDX) are usually transient and non-transferable. As a result, they do not cause any symptoms or death. However, because of the risk of blood cancer, because PDX models are permanent, they may be used in clinical trials to look at disease recurrence after a treatment challenge and the efficacy of novel medicines in treating drug-resistant cancers.

Brain Cancer

In recent decades, patient survival in pediatric oncology has improved in many areas, but the prognosis for most children with malignant brain tumors has remained dismal. PDXs for juvenile brain cancer are currently made by xenografting fresh tissue, newly obtained cell suspensions.

Cholangiocarcinoma

Cholangiocarcinoma is a biliary malignancy with a poor prognosis. This fatal disease requires excellent, individually customized therapies. Bile tumors are uncommon. They are aggressive and have a terrible prognosis. Their rarity makes it challenging to conduct successful therapy studies.

Prostate Cancer

Prostate cancer is a complicated, multifaceted illness that poses significant obstacles to medication development and scientific study.  Preclinical models such as patient-derived xenografts (PDX) must be utilized to evaluate medications primarily designed to treat prostate cancer. Unfortunately, prostate cancer studies for PDX models are challenging to come by.

Testicular Cancer

Testicular cancer is one of the most frequent malignancies in young men aged 20 to 40.PDX models are widely considered the most promising method for predicting drug effectiveness before clinical trials. In addition, these models may also be utilized for mechanistic research and preclinical testing of new testicular cancer trials and treatments.

 

Conclusion

Preclinical models are critical in translational cancer research, from understanding disease biology to creating new therapeutic methods. PDX models remain the model of choice for preclinical research at present, despite significant limitations in their ability to predict clinical outcomes. As a result, continuous multi-institutional efforts are underway to develop and distribute these tools to optimize the translation potential of substantial, well-annotated PDX resources. This research examines the present status of PDX models and discusses possible opportunities and issues for future PDX development.

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