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Biomedical subjects

Jierui Xu

Publications and source records attributed to Jierui Xu.

3 recordsLinked to original sources

A Clinically Integrated Pediatric Patient-Derived Xenograft Program Enables Evaluation of Cohort and Patient-Specific Biology and Therapeutic Strategies.

UNLABELLED: Preclinical translational research has increasingly utilized patient-derived xenograft (PDX) models for mechanistic and experimental therapeutic studies, yet most existing models have been developed from adult cancer types. We describe the establishment of a PDX program to expand the availability of pediatric-specific PDXs for preclinical research and enable studies of pediatric cancer histologies, including ultrarare diseases. Processes for PDX generation were integrated into established clinical workflows to facilitate universal model generation. Methodologies for tissue procurement, processing, and cryopreservation were optimized to enable intra- and interinstitutional PDX model generation. Over a 6-year span, 388 PDX tumor models representing more than 40 diagnoses were generated, including ultrarare tumors and longitudinal models established from pretherapy, posttherapy, and relapse tumors from the same patient. Genomic characterization of these PDXs demonstrates excellent concordance and recapitulation of molecular alterations of the source tumor. Successful PDX generation was enhanced from relapsed samples, was higher in sarcomas compared with other solid tumor types, and was a negative prognosticator for clinical outcome. With a broad portfolio of molecularly annotated models, we demonstrate utility for validating cross-histology biomarker-driven therapeutic strategies by demonstrating antitumor activity of an MAT2A inhibitor in MTAP-deficient PDXs. Universal model creation also allows for experimental validation of therapeutic hypotheses on a patient-specific basis, as we describe the characterization of a novel RAF1 fusion (EPB41L2::RAF1) in an osteosarcoma PDX. Development of a diverse collection of pediatric PDX models enables hypothesis-driven and cross-histology studies that expand our understanding of cancer biology and aid ongoing drug prioritization efforts in rare tumors. SIGNIFICANCE: A clinically integrated, genomically annotated pediatric PDX portfolio supported by systematic benchmarking of model generation facilitates exploratory biomarker-driven and patient-specific translational studies.

Humans

Integrated clinicogenomic analysis reveals the evolution and metastatic tropisms of advanced colorectal cancer.

We performed an integrated clinical and genomic analysis of over 7,000 consecutively sequenced colorectal cancer (CRC) samples to comprehensively characterize genetic drivers and metastatic tropisms of CRC. We find that genomic evolutionary changes, such as clonal mutations and oncogenic mutant allelic imbalance, selectively enhance the impact of recurrent oncogenic alterations. We identify the relative timing of organ-specific metastasis, showing sequential metastatic progression in microsatellite stable CRC with brain and adrenal metastases as late events; metastatic sites that cluster together, such as lung, bone, and brain metastases; and genomic events that enhance or decrease risk for each metastatic site, with WNT pathway activation as overall protective while RAS pathway activation increased risk for spread to all metastatic sites. Our data suggest that despite the heterogeneity in CRC, genomic evolution increases the impact of recurrent alterations, and integrating information about tumor primary location and genomics can be used to predict organ-specific metastasis risk.

Humans

sedimix: a workflow for the analysis of hominin nuclear DNA sequences from sediments.

SUMMARY: Sediment DNA-the recovery of genetic material from archaeological sediments-is an exciting new frontier in ancient DNA research, offering the potential to study individuals at a given archaeological site without destructive sampling. In recent years, several studies have demonstrated the promise of this approach by extracting hominin DNA from prehistoric sediments, including those dating back to the Middle or Late Pleistocene. However, a lack of open-source workflows for analysis of hominin sediment DNA samples poses a challenge for data processing and reproducibility of findings across studies. Here, we introduce a snakemake workflow, sedimix, for processing genomic sequences from archaeological sediment DNA samples to identify hominin sequences and generate relevant summary statistics to assess the reliability of the pipeline. By performing simulations and comparing our results to two published studies with human DNA from ∼25,000 years ago (including shotgun data from a sediment sample and capture data from touch DNA recovered from a deer tooth pendant) we demonstrate that sedimix yields accurate and reliable inferences. sedimix offers a reliable and adaptable framework to aid in the analysis of sediment DNA datasets and improve reproducibility across studies. AVAILABILITY AND IMPLEMENTATION: sedimix is available as an open-source software with the associated code, example data, and user manual with installation instructions available at https://github.com/jierui-cell/sedimix. A permanent archived version of this release is available via Zenodo: https://doi.org/10.5281/zenodo.17244854.

Animals