Advances in the Prevention, Diagnosis, Treatment, and Prognosis in Cancer after Renal Transplantation

As the optimal treatment for end-stage renal disease (ESRD), renal transplantation can significantly improve the quality of life and overall survival of ESRD patients, when compared to traditional therapies. However, the use of immunosuppressive drugs to avoid transplantation rejection potentially decreases the body’s tumor surveillance ability, and can result in the onset of cancer. Other factors, such as viral infections and environmental exposure, are closely related to the increase in frequency of various cancers, such as skin cancer, Kaposi’s sarcoma, non-Hodgkin lymphoma, and renal cell carcinoma in post-transplant patients. Cancer usually occurs at an advanced stage and leads to poor recipient prognosis. Therefore, precaution, early detection, early diagnosis, and early treatment remain essential to improving the survival of kidney graft recipients. Immune checkpoints such as CTLA4, PD-L1/PD-1, and IL-27 have been used for cancer therapy and prognosis after solid organ transplantation.

This Research Topic aims to collect the advances in renal transplantation and especially in post-transplant cancers, including prevention, early treatment, and biomarkers for prognosis to prolong the graft survival, eventually improving the quality of life in post-transplant patients. We welcome contributions of Original Research and Review articles on the following non-exhaustive list of themes:

1) Clinical or basic research on the mechanisms underlying tumor occurrence and development following a course of immunosuppressant therapy.
2) Clinical trials or basic research on the prevention of post-transplant cancer;
3) Investigation and validation of novel checkpoints for cancer treatment after renal transplantation;
4) Epidemiological cohort studies of one or more cancers after renal transplantation with sufficient size;
5) Advances in the screening strategies of the cancers in the process of tumor occurrence and development after renal transplantation;
6) Application of machine learning artificial intelligence technology, such as machine learning in the prognosis and diagnosis of cancer after renal transplantation;
7) Immunotherapy and the relevant mechanisms in renal transplantation, including but not limited to: Neotype immunosuppressant, antibody, and immune cells (such as B-regs, T-regs, and TFR cells) treatment in basic or clinical research;
8) Tolerance or rejection biomarkers and artificial intelligence in diagnosis and prognosis in post-renal transplantation;
9) Autoimmune diseases or post-transplant cancer caused by gene mutation or immunotherapy.

Note: Submissions consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data without experimental or in situ validation to support conclusions are not in scope for Frontiers in Oncology.