Biology subjects

Guerrero, P. A.

Publications and source records attributed to Guerrero, P. A..

16 recordsLinked to original sources

bioRxiv2026

Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer

Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3D pipeline in clinical samples that uses deep learning to classify sensitive and persistent tumor cell populations based on morphological features, enabling subsequent molecular characterization of intratumoral heterogeneity. We applied this automated 3D pipeline to a cohort of human pancreatic cancer samples treated with neoadjuvant chemotherapy, identifying heterogeneity in response to therapy both between and within tumors. Application of spatial proteomics to these sensitive and persistent regions identified enhanced epithelial-to-mesenchymal transition and non-classical cell states in persistent cells, confirming our morphological classification. Integration of spatial transcriptomics in multiple pancreatic cancer cohorts associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy. Our validated 3D multi-omic pipeline is now poised for application to clinical trials, enabling discovery of resistance mechanisms and design of new therapeutic combinations to circumvent resistance. Statement of significanceWe developed a novel 3D multi-omic pipeline to identify mechanisms of resistance to chemotherapy in clinical samples. This approach associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy and is poised for broader application in neoadjuvant clinical trials.

cancer biology↗

bioRxiv2025

Integrative analysis of genomic and transcriptomic data informs precancer progression in the pancreas

Pancreatic ductal adenocarcinoma (PDAC) arises from heterogeneous precursor lesions, including intraductal papillary mucinous neoplasms (IPMNs), but the features distinguishing indolent from progressive lesions remain unclear. We performed an integrative analysis of transcriptomic, genomic, and microenvironmental profiles of IPMNs to define multi-omic phenotypes. Using transfer learning, we projected IPMN-derived transcriptional programs onto spatial transcriptomic datasets from IPMNs and pancreatic intraepithelial neoplasias (PanINs). We identified two major phenotypes: one associated with cancer-associated fibroblasts and epithelial-to-mesenchymal transition, shared across IPMN, PanIN, and PDAC; and a second, glycolysis-enriched phenotype with a unique somatic mutation profile specific to IPMN. Spatial mapping further revealed grade-specific enrichment of transcriptional programs and distinct interactions with stromal and immune subtypes, underscoring the role of the precancer microenvironment in progression. These findings establish multi-omic phenotypes that unify genetic, transcriptional, and microenvironmental heterogeneity, providing a framework for distinguishing progressive from indolent precancers and a web-based public atlas for future exploration of these data and transcriptional phenotypes.

bioinformatics↗

bioRxiv2025

PIVOT: an open-source tool for multi-omic spatial data registration

Advances in spatial profiling have resulted in the generation of multi-omic atlases that span biological scales. In general, multiple workflows are required for image registration, coordinate registration, and spot deconvolution to integrate modalities. To improve the throughput of registration of multi-omic cohorts, we introduce PIVOT, a user-friendly and open-source interface for streamlined nonlinear registration. We demonstrate PIVOTs strengths through registration of three multi-omic datasets, and show comparison of its performance to existing workflows.

bioinformatics↗

bioRxiv2025

CDK8 remodels the tumor microenvironment to resist the therapeutic efficacy of targeted KRASG12D inhibition in pancreatic ductal adenocarcinoma

Mutations in KRAS are a dominant driver of pancreatic ductal adenocarcinoma (PDAC), with over 40% of PDAC patients presenting with KRASG12D mutations. The recent development of small molecule inhibitors targeting KRASG12D has enabled targeting of mutant KRAS signaling and suppression of PDAC; however, the contribution of the tumor microenvironment (TME) to the sustained therapeutic efficacy of KRASG12D inhibition and mechanism/s of resistance to KRASG12D suppression remain to be elucidated. Here, we employed spatial transcriptomics, single cell RNA sequencing, and CODEX-based spatial proteomics to evaluate cancer cell intrinsic and extrinsic responses to KRASG12D inhibition with MRTX1133. While KRASG12D inhibition initially increases CD11c+ cells with impactful T cell infiltration within proximity to cancer cells, long-term treatment with MRTX1133 resulted in reversal of the immune responses leading to KRASG12D therapy resistance promoted by CDK8, a multiprotein mediator complex associated kinase. CDK8 imparts resistance in part through induction of downstream CXCL2 chemokine secretion, inhibition of FAS expression, and remodeling of the TME to promote immune evasion. Targeting CDK8 by itself and in combination with CTLA-4 immunotherapy overcomes resistance to KRASG12D inhibition with prolonged survival with translational implications.

cancer biology↗

bioRxiv2023

Integrated spatial transcriptomics and lipidomics of precursor lesions of pancreatic cancer identifies enrichment of long chain sulfatide biosynthesis as an early metabolic alteration

BackgroundThe development of diverse spatial profiling technologies has provided an unprecedented insight into molecular mechanisms driving cancer pathogenesis. Here, we conducted the first integrated cross-species assessment of spatial transcriptomics and spatial metabolomics alterations associated with progression of intraductal papillary mucinous neoplasms (IPMN), bona fide cystic precursors of pancreatic ductal adenocarcinoma (PDAC). MethodsMatrix Assisted Laster Desorption/Ionization (MALDI) mass spectrometry (MS)-based spatial imaging and Visium spatial transcriptomics (ST) (10X Genomics) was performed on human resected IPMN tissues (N= 23) as well as pancreata from a mutant Kras;Gnas mouse model of IPMN. Findings were further compared with lipidomic analyses of cystic fluid from 89 patients with histologically confirmed IPMNs, as well as single-cell and bulk transcriptomic data of PDAC and normal tissues. ResultsMALDI-MS analyses of IPMN tissues revealed long-chain hydroxylated sulfatides, particularly the C24:0(OH) and C24:1(OH) species, to be selectively enriched in the IPMN and PDAC neoplastic epithelium. Integrated ST analyses confirmed that the cognate transcripts engaged in sulfatide biosynthesis, including UGT8, Gal3St1, and FA2H, were co-localized with areas of sulfatide enrichment. Lipidomic analyses of cystic fluid identified several sulfatide species, including the C24:0(OH) and C24:1(OH) species, to be significantly elevated in patients with IPMN/PDAC compared to those with low-grade IPMN. Targeting of sulfatide metabolism via the selective galactosylceramide synthase inhibitor, UGT8-IN-1, resulted in ceramide-induced lethal mitophagy and subsequent cancer cell death in vitro, and attenuated tumor growth of mutant Kras;Gnas allografts. Transcript levels of UGT8 and FA2H were also selectively enriched in PDAC transcriptomic datasets compared to non-cancerous areas, and elevated tumoral UGT8 was prognostic for poor overall survival. ConclusionEnhanced sulfatide metabolism is an early metabolic alteration in cystic pre-cancerous lesions of the pancreas that persists through invasive neoplasia. Targeting sulfatide biosynthesis might represent an actionable vulnerability for cancer interception.

cancer biology↗

bioRxiv2023

Oncogenic KrasG12D specific non-covalent small molecule inhibitor reprograms tumor microenvironment and reverses early precursor lesions and in combination with immunotherapy regresses advanced PDAC in a CD8+ T cells dependent manner

Pancreatic ductal adenocarcinoma (PDAC) is associated with mutations in Kras, a known oncogenic driver of PDAC; and the KRASG12D mutation is present in nearly half of PDAC patients. Recently, a non-covalent small molecule inhibitor (MRTX1133) was identified with specificity to the KrasG12D mutant protein. Here we explore the impact of KrasG12D inhibition by MRTX1133 on advanced PDAC and its influence on the tumor microenvironment. Employing different orthotopic xenograft and syngeneic tumor models, eight different PDXs, and two different autochthonous genetic models, we demonstrate that MRTX1133 reverses early PDAC growth, increases intratumoral CD8+ effector T cells, decreases myeloid infiltration, and reprograms cancer associated fibroblasts. Autochthonous genetic mouse models treated with MRTX1133 leads to regression of both established PanINs and advanced PDAC. Regression of advanced PDAC requires CD8+ T cells and immune checkpoint blockade therapy (iCBT) synergizes with MRTX1133 to eradicate PDAC and prolong overall survival. Mechanistically, inhibition of mutant Kras in advanced PDAC and human patient derived organoids (PDOs) induces Fas expression in cancer cells and facilitates CD8+T cell mediated death. These results demonstrate the efficacy of MRTX1133 in different mouse models of PDAC associated with reprogramming of stromal fibroblasts and a dependency on CD8+ T cell mediated tumor clearance. Collectively, this study provides a rationale for a synergistic combination of MRTX1133 with iCBT in clinical trials.

cancer biology↗

bioRxiv2022

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. Statement of significanceWe have developed an approach to interrogate changes in cancer molecular subtypes and differentially expressed genes, through the analysis and deconvolution of RNA sequencing of plasma EVs. Serial analyses of tumor-encoded transcriptomes in liquid biopsies can enable facile cancer detection and monitor for recurrences and therapy-induced tumor evolution.

cancer biology↗

bioRxiv2022

Spatial Transcriptomics of Intraductal Papillary Mucinous Neoplasms of The Pancreas Identifies NKX6-2 Expression as a Driver of Gastric Differentiation and Indolent Biological Potential

Intraductal Papillary Mucinous Neoplasms (IPMNs) of the pancreas are bona fide precursor lesions of pancreatic ductal adenocarcinoma (PDAC). The most common subtype of IPMNs harbor a gastric foveolar-type epithelium, and these low-grade mucinous neoplasms are harbingers of IPMNs with high-grade dysplasia and cancer. The molecular underpinning of gastric differentiation in IPMNs is unknown, although identifying drivers of this indolent phenotype might enable opportunities for intercepting progression to high-grade IPMN and cancer. We conducted spatial transcriptomics on a cohort of IPMNs, followed by orthogonal and cross species validation studies, which established the transcription factor NKX6-2 as a key determinant of gastric cell identity in low-grade IPMNs. Loss of NKX6-2 expression is a consistent feature of IPMN progression, while re-expression of NKX6-2 in murine IPMN lines recapitulates the aforementioned gastric transcriptional program and glandular morphology. Our study identifies NKX6-2 as a previously unknown transcription factor driving indolent gastric differentiation in IPMN pathogenesis. SignificanceImproved understanding of the molecular features driving IPMN development and differentiation is critical to prevent cancer progression and enhance risk stratification. Our study employed spatial profiling technologies to characterize the epithelium and microenvironment of IPMN, which revealed a previously unknown link between NKX6-2 expression and gastric differentiation in IPMNs, the latter associated with an indolent biological potential.

cancer biology↗

bioRxiv2022

Integrated Molecular Characterization of Intraductal Papillary Mucinous Neoplasms: An NCI Cancer Moonshot Precancer Atlas Pilot Project

Intraductal papillary mucinous neoplasms (IPMNs) are cystic precursor lesions to pancreatic ductal adenocarcinoma (PDAC). IPMNs undergo multistep progression from low grade (LG) to high grade (HG) dysplasia, culminating in invasive neoplasia. While patterns of IPMN progression have been analyzed using multi-region sequencing for somatic mutations, there is no integrated assessment of molecular events, including copy number alterations (CNAs) and transcriptomics changes, that accompany IPMN progression. We performed laser capture microdissection on surgically resected IPMNs of varying grades of histological dysplasia obtained from 24 patients (total of 74 independent histological lesions), followed by whole exome and whole transcriptome sequencing. Overall, HG IPMNs displayed a significantly greater aneuploidy score than LG lesions, with chromosome 1q amplification, in particular, being associated with HG progression and with cases that harbored cooccurring PDAC. Furthermore, the combined assessment of single nucleotide variants (SNVs) and CNAs identified both linear and branched evolutionary trajectories, underscoring the heterogeneity in the progression of LG lesions to HG and PDAC. At the transcriptome level, upregulation of MYC-regulated targets and downregulation of transcripts associated with the MHC class I antigen presentation machinery was a common feature of progression to HG. Taken together, this work emphasizes the role of 1q copy number amplification as a putative biomarker of high-risk IPMNs, underscores the importance of immune evasion even in non-invasive precursor lesions, and supports a previously underappreciated role of CNA-driven branching evolution as an avenue for IPMN progression. Our study provides important molecular context for risk stratification and cancer interception opportunities in IPMNs. SignificanceIntegrated molecular analysis of genomic and transcriptomic alterations in the multistep progression of intraductal papillary mucinous neoplasms (IPMNs), which are bona fide precursors of pancreatic cancer, identifies features associated with progression of low-risk lesions to high-risk lesions and cancer, which might enable patient stratification and cancer interception strategies.

cancer biology↗

bioRxiv2021

CLPTM1L is a lipid scramblase involved in glycosylphosphatidylinositol biosynthesis

Glycosylphosphatidylinositols (GPIs) are membrane anchors of many eukaryotic cell surface proteins. Biosynthesis of GPIs is initiated at the cytosolic face of the endoplasmic reticulum (ER) and the second intermediate, glucosaminyl-phosphatidylinositol (GlcN-PI), is translocated across the membrane to the lumenal face for later biosynthetic steps and attachment to proteins. The mechanism of the lumenal translocation of GlcN-PI is unclear. We report that Cleft lip and palate transmembrane protein 1-like protein (CLPTM1L), an ER membrane protein of unknown function, is a lipid scramblase involved in GPI biosynthesis. Purified CLPTM1L scrambles GlcN-PI, PI, and several other phospholipids in vitro. Knockout of CLPTM1L gene in mammalian cultured cells partially decreased GPI-anchored proteins due to impaired usage of GlcN-PI, suggesting a major role of CLPTM1L in lumenal translocation of GlcN-PI. One-Sentence SummaryCLPTM1L translocates glucosaminyl-phosphatidylinositol across the membrane during glycosylphosphatidylinositol biosynthesis.

biochemistry↗

bioRxiv2021

Loss of Rnf43 accelerates Kras-mediated neoplasia and remodels the tumor immune microenvironment in pancreatic adenocarcinoma

RNF43 is an E3 ubiquitin ligase that is recurrently mutated in pancreatic ductal adenocarcinoma (PDAC) and precursor cystic neoplasms of the pancreas. The impact of RNF43 mutations on PDAC is poorly understood and autochthonous models have not been sufficiently characterized. In this study we describe a genetically engineered mouse model (GEMM) of PDAC with conditional expression of oncogenic Kras and deletion of the catalytic domain of Rnf43 (KRC) in exocrine cells. We demonstrate that Rnf43 loss results in an increased incidence of high-grade cystic lesions of the pancreas and PDAC. Importantly, KRC mice have a significantly decreased survival compared to mice containing only an oncogenic Kras mutation. By use of single cell RNA sequencing we demonstrated that KRC tumor progression is accompanied by a decrease in macrophages, as well as an increase in T and B lymphocytes with evidence of increased immune checkpoint molecule expression and affinity maturation, respectively. This was in stark contrast to the tumor immune microenvironment observed in the Kras/Tp53 driven PDAC GEMM. Furthermore, expression of the chemokine, CXCL5, was found to be specifically decreased in KRC cancer cells by means of epigenetic regulation and emerged as a putative candidate for mediating the unique KRC immune landscape. This GEMM establishes RNF43 as a bona fide tumor suppressor gene in PDAC and puts forth a rationale for an immunotherapy approach in this subset of PDAC cases.

cancer biology↗

bioRxiv2021

Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution.

Intratumoral heterogeneity (ITH) is a hallmark of cancer. The advent of single-cell technologies has helped uncover ITH in a high-throughput manner in different cancers across varied contexts. Here we apply single-cell sequencing technologies to reveal striking ITH in assumptively oligoclonal pancreatic ductal adenocarcinoma (PDAC) cell lines. Our findings reveal a high degree of both genomic and transcriptomic heterogeneity in established and globally utilized PDAC cell lines, custodial variation induced by growing apparently identical PDAC cell lines in different laboratories, and profound transcriptomic shifts in transitioning from 2D to 3D spheroid growth models. Our findings also call into question the validity of widely available immortalized, non-transformed pancreatic lines as contemporaneous "control" lines in experiments. Further, while patient-derived organoid (PDOs) are known to reflect the cognate in vivo biology of the parental tumor, we identify transcriptomic shifts during ex vivo passage that might hamper their predictive abilities over time. The impact of these findings on rigor and reproducibility of experimental data generated using established preclinical PDAC models between and across laboratories is uncertain, but a matter of concern.

cancer biology↗

bioRxiv2020

Differing total mRNA expression shapes the molecular and clinical phenotype of cancer

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-individual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

genomics↗

bioRxiv2020

Diversity Across the Pancreatic Ductal Adenocarcinoma Disease Spectrum Revealed by Network-Anchored Functional Genomics

Cancers are highly complex ecosystems composed of molecularly distinct sub-populations of tumor cells, each exhibiting a unique spectrum of genetic features and phenotypes, and embedded within a complex organ context. To substantially improve clinical outcomes, there is a need to comprehensively define inter- and intra-tumor phenotypic diversity, as well as to understand the genetic dependencies that underlie discrete molecular subpopulations. To this end, we integrated CRISPR-based co-dependency annotations with a tissue-specific co-expression network developed from patient-derived models to establish CoDEX, a framework to quantitatively associate gene-cluster patterns with genetic vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). Using CoDEX, we defined multiple prominent anticorrelated gene-cluster signatures and specific pathway dependencies, both across genetically distinct PDAC models and intratumorally at the single-cell level. Of these, one differential signature recapitulated the characteristics of classical and basal-like PDAC molecular subtypes on a continuous scale. Anchoring genetic dependencies identified through functional genomics within the gene-cluster signature defined fundamental vulnerabilities associated with transcriptomic signatures of PDAC subtypes. Subtype-associated dependencies were validated by feature-barcoded CRISPR knockout of prioritized basal-like-associated genetic vulnerabilities (SMAD4, ILK, and ZEB1) followed by scRNAseq in multiple PDAC models. Silencing of these genes resulted in a significant and directional clonal shift toward the classical-like signature of more indolent tumors. These results validate CoDEX as a novel, quantitative approach to identify specific genetic dependencies within defined molecular contexts that may guide clinical positioning of targeted therapeutics.

cancer biology↗

bioRxiv2020

Elucidation of tumor-stromal heterogeneity and the ligand-receptor interactome by single cell transcriptomics in real-world pancreatic cancer biopsies

Precision medicine approaches in pancreatic ductal adenocarcinoma (PDAC) are imperative for improving disease outcomes. However, the long-term fidelity of recently deployed ex vivo preclinical platforms, such as patient-derived organoids (PDOs) remains unknown. Through single-cell RNA sequencing (scRNA-seq), we identify substantial transcriptomic evolution of PDOs propagated from the parental tumor, which may alter predicted drug sensitivity. In contrast, scRNA-seq is readily applicable to limited biopsies from human primary and metastatic PDAC and identifies most cancers as being an admixture of previously described epithelial transcriptomic subtypes. Integrative analyses of our data provide an in-depth characterization of the heterogeneity within the tumor microenvironment, including cancer-associated fibroblast (CAF) subclasses, and predicts for a multitude of ligand-receptor interactions, revealing potential targets for immunotherapy approaches. While PDOs continue to enable prospective therapeutic prediction, our analysis also demonstrates the complementarity of using orthogonal de novo biopsies from PDAC patients paired with scRNA-seq to inform clinical decision-making. Statement of SignificanceThe application of single-cell RNA sequencing to diagnostic pancreatic cancer biopsies provides in-depth transcriptomic characterization of the tumor epithelium and microenvironment, while minimizing potential artifacts introduced by an intervening ex vivo passaging step. Thus, this approach can complement the use of patient-derived organoids in implementing precision oncology.

cancer biology↗

bioRxiv2018

Single Cell Transcriptomics of Pancreatic Cancer Precursors Demonstrates Epithelial and Microenvironmental Heterogeneity as an Early Event in Neoplastic Progression

BackgroundEarly detection of pancreatic ductal adenocarcinoma (PDAC) remains elusive. Precursor lesions of PDAC, specifically, intraductal papillary mucinous neoplasms (IPMNs) represent a bona fide pathway to invasive neoplasia, although the molecular correlates of progression remain to be fully elucidated. Single cell transcriptomics provides a unique avenue for dissecting both the epithelial and microenvironmental heterogeneity that accompany multistep progression from non-invasive IPMNs to PDAC.\n\nMethodsSingle cell RNA-sequencing was performed through droplet-based sequencing on 5,403 cells from two low-grade IPMNs (LGD-IPMN), two high-grade IPMNs (HGD-IPMN), and two PDACs (all surgically resected).\n\nResultsAnalysis of single cell transcriptomes revealed heterogeneous alterations within the epithelium and the tumor microenvironment during the progression of non-invasive dysplasia to invasive cancer. While HGD-IPMNs expressed many core-signaling pathways described in PDAC, LGD-IPMNs harbored subsets of single cells with a transcriptomic profile that overlapped with invasive cancer. Notably, a pro-inflammatory immune component was readily seen in low-grade IPMNs, comprised of cytotoxic T-cells, activated T-helper cells, and dendritic cells, which was progressively depleted during neoplastic progression, accompanied by infiltration of myeloid-derived suppressor cells. Finally, stromal myofibroblast populations were heterogeneous, and acquired a previously described tumor-promoting and immune-evading phenotype during invasive carcinogenesis.\n\nConclusionsThis study demonstrates the ability to perform high resolution profiling of the transcriptomic changes that occur during multistep progression of cystic PDAC precursors to cancer. Notably, single cell analysis provides an unparalleled insight into both the epithelial and microenvironmental heterogeneity that accompany early cancer pathogenesis, and might be a useful substrate to identify targets for cancer interception.

pathology↗