Multi-tumor analysis of cancer-stroma interactomes of patient-derived xenografts unveils the unique homeostatic process in renal cell carcinomas

A patient-derived T cell lymphoma biorepository uncovers pathogenetic mechanisms and host-related therapeutic vulnerabilities

Peripheral T cell lymphomas (PTCLs) comprise heterogeneous malignancies with limited therapeutic options. To uncover targetable vulnerabilities, we generate a collection of PTCL patient-derived tumor xenografts (PDXs) retaining histomorphology and molecular donor-tumor features over serial xenografting. PDX demonstrates remarkable heterogeneity, complex intratumor architecture, and stepwise trajectories mimicking primary evolutions. Combining functional transcriptional stratification and multiparametric imaging, we identify four distinct PTCL microenvironment subtypes with prognostic value. Mechanistically, we discover a subset of PTCLs expressing Epstein-Barr virus-specific T cell receptors and uncover the capacity of cancer-associated fibroblasts of counteracting treatments. PDXs' pre-clinical testing captures individual vulnerabilities, mirrors donor patients' clinical responses, and defines effective patient-tailored treatments. Ultimately, we assess the efficacy of CD5KO- and CD30- Chimeric Antigen Receptor T Cells (CD5KO-CART and CD30_CART, respectively), demonstrating their therapeutic potential and the synergistic role of immune checkpoint inhibitors for PTCL treatment. This repository represents a resource for discovering and validating intrinsic and extrinsic factors and improving the selection of drugs/combinations and immune-based therapies.

Advancements in Preclinical Models of Pancreatic Cancer

ABSTRACT

Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.

Consistency between Primary Uterine Corpus Malignancies and Their Corresponding Patient-Derived Xenograft Models

Patient-derived xenograft (PDX) models retain the characteristics of tumors and are useful tools for personalized therapy and translational research. In this study, we aimed to establish PDX models for uterine corpus malignancies (UC-PDX) and analyze their similarities. Tissue fragments obtained from 92 patients with uterine corpus malignancies were transplanted subcutaneously into immunodeficient mice. Histological and immunohistochemical analyses were performed to compare tumors of patients with PDX tumors. DNA and RNA sequencing were performed to validate the genetic profile. Furthermore, the RNA in extracellular vesicles (EVs) extracted from primary and PDX tumors was analyzed. Among the 92 cases, 52 UC-PDX models were established, with a success rate of 56.5%. The success rate depended on tumor histology and staging. The pathological and immunohistochemical features of primary and PDX tumors were similar. DNA sequencing revealed similarities in gene mutations between the primary and PDX tumors. RNA sequencing showed similarities in gene expressions between primary and PDX tumors. Furthermore, the RNA profiles of the EVs obtained from primary and PDX tumors were similar. As UC-PDX retained the pathological and immunohistochemical features and gene profiles of primary tumors, they may provide a platform for developing personalized medicine and translational research.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Pan-cancer molecular subtypes of metastasis reveal distinct and evolving transcriptional programs

Molecular mechanisms underlying cancer metastasis span diverse tissues of origin. Here, we synthesize and collate the transcriptomes of patient-derived xenografts and patient tumor metastases, and these data collectively represent 38 studies and over 3,000 patients and 4,000 tumors. We identify four expression-based subtypes of metastasis transcending tumor lineage. The first subtype has extensive copy alterations, higher expression of MYC transcriptional targets and DNA repair genes, and bromodomain inhibitor response association. The second subtype has higher expression of genes involving metabolism and prostaglandin synthesis and regulation. The third subtype has evidence of neuronal differentiation, higher expression of DNA and histone methylation genes and EZH2 transcriptional targets, and BCL2 inhibitor response association. The fourth subtype has higher expression of immune checkpoint and Notch pathway genes. The metastasis subtypes reflect expression differences from paired primaries, with subtype switching being common. These subtypes facilitate understanding of the molecular underpinnings of metastases beyond tissue-oriented domains, with therapeutic implications.

Endometrial Cancer Patient-Derived Xenograft Models: A Systematic Review

BACKGROUND

Because patient-derived xenograft (PDX) models resemble the original tumors, they can be used as platforms to find target agents for precision medicine and to study characteristics of tumor biology such as clonal evolution and microenvironment interactions. The aim of this review was to identify articles on endometrial cancer PDXs (EC-PDXs) and verify the methodology and outcomes.

METHODS

We used PubMed to research and identify articles on EC-PDX. The data were analyzed descriptively.

RESULTS

Post literature review, eight studies were selected for the systematic review. Eighty-five EC-PDXs were established from 173 patients with EC, with a total success rate of 49.1%. A 1-10 mm3 fragment was usually implanted. Fresh-fragment implantation had higher success rates than using overnight-stored or frozen fragments. Primary tumors were successfully established with subcutaneous implantation, but metastasis rarely occurred; orthotopic implantation via minced tumor cell injection was better for metastatic models. The success rate did not correspond to immunodeficiency grades, and PDXs using nude mice reduced costs. The tumor growth period ranged from 2 weeks to 13 months. Similar characteristics were observed between primary tumors and PDXs, including pathological findings, gene mutations, and gene expression.

CONCLUSION

EC-PDXs are promising tools for translational research because they closely resemble the features of tumors in patients and retain molecular and histological features of the disease.