Biology subjects

Guo, J. A.

Publications and source records attributed to Guo, J. A..

8 recordsLinked to original sources

bioRxiv2025

GLIS3 Marks a Neural-like Progenitor Cell State that Drives Metastasis in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a high rate of recurrence and metastasis despite intensive therapy. The neural-like progenitor (NRP) transcriptional program is enriched in residual disease after neoadjuvant chemotherapy and radiotherapy; however, the mechanisms for increased NRP expression in the post-treatment setting remain unclear. Here, we find that NRP signatures are strongly enriched in tissue injury and regeneration, and NRP cancer cells co-express transcription factors involved in pancreatic development. We identify both cell autonomous and ligand mediated mechanisms for inducing NRP expression in vitro. We establish and characterize isogenic mouse organoid overexpression models for transcription factors associated with the NRP, classical, and basal-like states. We discovered that Glis3 is a key NRP-associated transcription factor that drives malignant properties including greater clonogenicity, tumor growth, and metastasis compared to isogenic models for the classical and basal-like states. Our work highlights the emergence of clinically relevant developmental regeneration programs in the post-treatment context.

cancer biology↗

bioRxiv2025

Distinct malignant cell states and myeloid glutamate signaling associated with aggressive pancreatic neuroendocrine tumors

Pancreatic neuroendocrine tumors (PNET) are rare malignancies of the endocrine pancreas with diverse clinical outcomes. While some PNETs are indolent, others are aggressive and metastasize quickly. However, clinically-relevant molecular stratification for PNET to predict outcomes and guide therapeutic decision-making is limited. Thus, there is an urgent need to understand the molecular heterogeneity of PNETs to refine prognostication and discover novel therapeutic vulnerabilities. We performed single-nucleus RNA sequencing on resected primary and metastatic PNETs (n = 20), including two PNETs with neoadjuvant treatment. We inferred gene expression programs (GEPs) of malignant and non-malignant cells and investigated associations with clinical outcomes. Next, we inferred interactions in the tumor microenvironment (TME) and performed transwell assays for functional validation. Finally, we explored genomic and transcriptomic evolution in a unique case study of an untreated primary PNET with two asynchronous hepatic metastases. A malignant GEP enriched for neural/synaptic signaling genes was associated with worse overall survival, broad chromosomal loss of heterozygosity, and alternative lengthening of telomeres. Another malignant GEP enriched for VEGF signaling increased throughout metastatic progression in our case study. We found that macrophage-derived glutamate drives polarization towards an immunosuppressive phenotype and activates the MAPK/ERK pathway in malignant cells to increase migratory capacity. This study provides a detailed single-nucleus transcriptomic classification of malignant, stromal, and immune cell types and states in PNETs, their interactions in the TME, and associations with clinical outcomes. The refined molecular taxonomy of PNET may guide the development of more efficacious biomarkers and therapeutic strategies.

cancer biology↗

bioRxiv2023

Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis

In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression. Our results uncovered a marked change in ligand-receptor interactions between cancer-associated fibroblasts and malignant cells in response to treatment, which was supported by orthogonal datasets, including an ex vivo tumoroid co-culture system. Overall, this study demonstrates that characterization of the tumor microenvironment using high-plex single-cell spatial transcriptomics allows for identification of molecular interactions that may play a role in the emergence of chemoresistance and establishes a translational spatial biology paradigm that can be broadly applied to other malignancies, diseases, and treatments.

cancer biology↗

bioRxiv2022

Precise DNA Cloning via PAMless CRISPR-SpRYgests

While restriction enzymes (REs) remain the gold-standard for manipulating DNA in vitro, they have notable drawbacks including a dependence on short binding motifs that constrain their ability to cleave DNA substrates. Here we overcome limitations of REs by developing an optimized molecular workflow that leverages the PAMless nature of a CRISPR-Cas enzyme named SpRY to cleave DNA at practically any sequence. Using SpRY for DNA digests (SpRYgests), we establish a method that permits the efficient cleavage of DNA substrates at any base pair. We demonstrate the effectiveness of SpRYgests using more than 130 gRNAs, illustrating the versatility of this approach to improve the precision of and simplify several cloning workflows, including those not possible with REs. We also optimize a rapid and simple one-pot gRNA synthesis protocol, which reduces cost and makes the overall SpRYgest workflow comparable to that of RE digests. Together, SpRYgests are straightforward to implement and can be utilized to improve a variety of DNA engineering applications.

biochemistry↗

bioRxiv2021

Global-scale CRISPR gene editor specificity profiling by ONE-seq identifies population-specific, variant off-target effects

Defining off-target profiles of gene-editing nucleases and CRISPR base editors remains an important challenge for use of these technologies, therapeutic or otherwise. Existing methods can identify off-target sites induced by these gene editors on an individual genome but are not designed to account for the broad diversity of genomic sequence variation that exists within populations of humans or other organisms. Here we describe OligoNucleotide Enrichment and sequencing (ONE-seq), a novel in vitro method that leverages customizable, high-throughput DNA synthesis technology instead of purified genomic DNA (gDNA) from individual genomes to profile gene editor off-target sites. We show that ONE-seq matches or exceeds the sensitivity of existing single-genome methods for identifying bona fide CRISPR-Cas9 off-target sites in cultured human cells and in vivo in a liver-humanized mouse model. In addition, ONE-seq outperforms existing best-in-class single-genome methods for defining off-target sites of CRISPR-Cas12a nucleases, cytosine base editors (CBEs), and adenine base editors (ABEs), unveiling previously undescribed bona fide off-target sites for all these editors in human cells. Most importantly, we leveraged ONE-seq to generate the first experimentally-derived population-scale off-target profiles for Cas9 nucleases that define the impacts of sequence variants from >2,500 individual human genome sequences in the 1000 Genomes Project database. Notably, some of the variants we identified that lead to increased mutation frequencies at off-target sites are enriched in specific human populations. We validated that novel population-specific, variant-sensitive off-target sites nominated by ONE-seq in vitro can show increased frequencies of mutations in human lymphoblastoid cells (LCLs) harboring these sequence variants. Collectively, our results demonstrate that ONE-seq is a highly sensitive off-target nomination method that can uniquely be used to identify population subgroup-linked differences in off-target profiles of gene editors. ONE-seq provides an important new pathway by which to assess the impacts of global human genetic sequence diversity on the specificities of gene editors, thereby enabling a broader and more all-inclusive approach for profiling off-target effects of these transformative therapeutic technologies.

molecular biology↗

bioRxiv2020

Single-nucleus and spatial transcriptomics of archival pancreatic cancer reveals multi-compartment reprogramming after neoadjuvant treatment

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

genomics↗

bioRxiv2018

CRISPR-SURF: Discovering regulatory elements by deconvolution of CRISPR tiling screen data

Tiling screens using CRISPR-Cas technologies provide a powerful approach to map regulatory elements to phenotypes of interest, but computational methods that effectively model these experimental approaches for different CRISPR technologies are not readily available. Here we present CRISPR-SURF, a deconvolution framework to identify functional regulatory regions in the genome from data generated by CRISPR-Cas nuclease, CRISPR interference (CRISPRi), or CRISPR activation (CRISPRa) tiling screens. We validated CRISPR-SURF on previously published and new data, identifying both experimentally validated and new potential regulatory elements. With CRISPR tiling screens now being increasingly used to elucidate the regulatory architecture of the non-coding genome, CRISPRSURF provides a generalizable and accessible solution for the discovery of regulatory elements.

bioinformatics↗

bioRxiv2018

In vivo CRISPR-Cas gene editing with no detectable genome-wide off-target mutations

CRISPR-Cas genome-editing nucleases hold substantial promise for human therapeutics1-5 but identifying unwanted off-target mutations remains an important requirement for clinical translation6, 7. For ex vivo therapeutic applications, previously published cell-based genome-wide methods provide potentially useful strategies to identify and quantify these off-target mutation sites8-12. However, a well-validated method that can reliably identify off-targets in vivo has not been described to date, leaving the question of whether and how frequently these types of mutations occur. Here we describe Verification of In Vivo Off-targets (VIVO), a highly sensitive, unbiased, and generalizable strategy that we show can robustly identify genome-wide CRISPR-Cas nuclease off-target effects in vivo. To our knowledge, these studies provide the first demonstration that CRISPR-Cas nucleases can induce substantial off-target mutations in vivo, a result we obtained using a deliberately promiscuous guide RNA (gRNA). More importantly, we used VIVO to show that appropriately designed gRNAs can direct efficient in vivo editing without inducing detectable off-target mutations. Our findings provide strong support for and should encourage further development of in vivo genome editing therapeutic strategies.

molecular biology↗