Biology subjects

Jaeger, A. M.

Publications and source records attributed to Jaeger, A. M..

8 recordsLinked to original sources

bioRxiv2026

Discovery and Targeting of a Cryptic Human Proteome

First-in-class therapeutics require first-in-class biology. Yet despite decades of genomic and proteomic cataloging, vast regions of the human transcriptome remain dark and their encoded proteins invisible. Here we present RyboCypher, an integrated RNA-sequencing and AI-assisted proteogenomics platform that systematically maps the RyboCypher-derived "dark" transcriptome to unannotated peptides, predicting and empirically identifying cryptic proteins across the uncharted genome. Applied to cancer cell lines, patient tumors, and matched healthy tissues, RyboCypher resolved [~]8.3 million dark RNA isoforms and [~]16 million candidate ORFs. Interrogating these against [~]0.5 billion MS/MS spectra from cellular proteomics, membrane proteomics, and immunopeptidomics datasets (comprising a total of >8,000 raw MS data files ([~]7TB of MS data), derived from 2,229 patient samples), we empirically identified [~]80,000 cryptic peptides ([~]10,000 cancer-associated or cancer-upregulated) at <1% FDR. Altogether, these datasets establish the CypherAtlas, a comprehensive proteogenomic atlas of an unreported proteome comprising thousands of novel proteins, including membrane proteins with targetable extracellular domains, and intracellular proteins accessible through antigen presentation. By linking dark-RNA transcripts, predicted proteins, and patient-level metadata across RyboDyns proprietary experimental data, CypherAtlas further provides the training substrate for multi-modal models such as DarkCypher, which is being developed to prioritize cryptic targets and to forecast their expression in new patient samples. As proof of therapeutic potential, we disclose evidence for a cancer-associated, cryptic protein expressed from the YBX1 locus, (cryptic YBX1; cYBX1) and demonstrate selective in vitro tumor cell killing through a cryptic peptide-MHC (pMHC) complex derived from this protein with a TCR-mimic (TCRm) antibody when formatted as antibody drug conjugates (ADCs). Together, RyboCypher and CypherAtlas establish the dark proteome as a vast and previously inaccessible reservoir of novel targetable biology, laying the foundation for the next generation of first-in-class therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/743124v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@104c385org.highwire.dtl.DTLVardef@1c065ccorg.highwire.dtl.DTLVardef@5b717forg.highwire.dtl.DTLVardef@1788694_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

CDH3-AS1 antisense RNA enhances P-cadherin translation and acts as a tumor suppressor in melanoma

Thousands of regulatory noncoding RNAs (ncRNAs) have been annotated; however, their functions in gene regulation and contributions to cancer formation remain poorly understood. To gain a better understanding of the influence of ncRNAs on gene regulation during melanoma progression, we mapped the landscape of ncRNAs in melanocytes and melanoma cells. Nearly half of deregulated genes in melanoma are ncRNAs, with antisense RNAs (asRNAs) comprising a large portion of deregulated ncRNAs. CDH3-AS1, the most significantly downregulated asRNA, overlaps the CDH3 gene, which encodes P-cadherin, a transmembrane glycoprotein involved in cell adhesion that was also reduced in melanoma. Overexpression of CDH3-AS1 increased cell aggregation and reduced xenograft tumor growth, mimicking the tumor-suppressive effects of CDH3. CDH3-AS1 interacted with CDH3 mRNA and enhanced P-cadherin protein levels. Interestingly, secondary structures at the CDH3 5 end regulated P-cadherin translation, and ribosome profiling revealed that CDH3-AS1 promotes ribosome occupancy at the CDH3 mRNA. Notably, ribosome occupancy was generally increased in mRNAs having cognate asRNA that are complementary to the 5UTR. Taken together, this study revealed the CDH3-AS1-mediated enhancement of P-cadherin translation, underscoring the broader potential of asRNAs as regulators of protein-coding genes and their role in diseases like melanoma.

molecular biology↗

bioRxiv2022

Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma

Lymphocytes play a key role in immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. Here, we used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of tumor-bearing lung tissues from a Kras/p53 (KP) mouse model and human resections. Networks of directly interacting lymphocytes ( lymphonets) emerge as a distinctive feature of the anti-cancer immune response. Lymphonets nucleate from small T-cell clusters and incorporate B cells with increasing size. CXCR3-mediated trafficking modulates lymphonet size and number, but neoantigen expression directs intratumoral localization. Lymphonets preferentially harbor TCF1+/PD1+ progenitor CD8 T cells involved in responses to immune checkpoint blockade (ICB). Upon treatment of mice with ICB therapy or a neoantigen-targeted vaccine, lymphonets retain progenitor and gain cytotoxic CD8 T-cell populations, likely via progenitor differentiation. These data show that lymphonets create a spatial environment supportive of CD8 T-cell anti-tumor responses.

cancer biology↗

bioRxiv2021

Multiscale profiling of enzyme activity in cancer

Diverse processes in cancer are mediated by enzymes, which most proximally exert their function through their activity. Methods to quantify enzyme activity, rather than just expression, are therefore critical to our ability to understand the pathological roles of enzymes in cancer and to harness this class of biomolecules as diagnostic and therapeutic targets. Here we present an integrated set of methods for measuring specific enzyme activities across the organism, tissue, and cellular levels, which we unify into a methodological hierarchy to facilitate biological discovery. We focus on proteases for method development and validate our approach through the study of tumor progression and treatment response in an autochthonous model of Alk-mutant lung cancer. To quantitatively measure activity dynamics over time, we engineered multiplexed, peptide-based nanosensors to query protease activity in vivo. Machine learning analysis of sensor measurements revealed dramatic protease dysregulation in lung cancer, including significantly enhanced proteolytic cleavage of one peptide, S1 (Padj < 0.0001), which returned to healthy levels within three days after initiation of targeted therapy. Next, to link these organism-level observations to the in situ context, we established a multiplexed assay for on-tissue localization of enzyme activity and pinpointed S1 cleavage to endothelial cells and pericytes of the tumor vasculature. Lastly, to directly link enzyme activity measurements to cellular phenotype, we designed a high-throughput method to isolate and characterize proteolytically active cells, uncovering profound upregulation of pro-angiogenic transcriptional programs in S1-positive cells. Together, these methods allowed us to discover that protease production by angiogenic vasculature responds rapidly to targeted therapy against oncogene-addicted tumor cells, identifying a highly dynamic interplay between tumor cells and their microenvironment. This work provides a generalizable framework to functionally characterize enzyme activity in cancer.

bioengineering↗

bioRxiv2021

Mismatch repair deficiency is not sufficient to increase tumor immunogenicity

DNA mismatch repair deficiency (MMRd) in human cancer is associated with high tumor mutational burden (TMB), frameshift mutation-derived neoantigens, increased T cell infiltration, and remarkable responsiveness to immune checkpoint blockade (ICB) therapy. Nevertheless, about half of MMRd tumors do not respond to ICB for unclear reasons. While tumor cell line transplant models of MMRd have reinforced the importance of TMB in immune response, critical questions remain regarding the role of immunosurveillance in the evolution of MMRd tumors induced in vivo. Here, we developed autochthonous mouse models of lung and colon cancer with highly efficient ablation of MMR genes via in vivo CRISPR/Cas9 targeting. Surprisingly, MMRd in these models did not result in increased immunogenicity or response to ICB. Mechanistically, we showed this lack of immunogenicity to be driven by profound intratumoral heterogeneity (ITH). Studies in animals depleted of T cells further demonstrated that immunosurveillance in MMRd tumors has no impact on TMB but shapes the clonal architecture of neoantigens by exacerbating ITH. These results provide important context for understanding immune evasion in cancers with high TMB and have major implications for therapies aimed at increasing TMB.

cancer biology↗

bioRxiv2021

Deciphering the tumor-specific immunopeptidome in vivo with genetically engineered mouse models

Effective immunosurveillance of cancer requires the presentation of peptide antigens on major histocompatibility complex Class I (MHC-I). Recent developments in proteomics have improved the identification of peptides that are naturally presented by MHC-I, collectively known as the "immunopeptidome". Current approaches to profile tumor immunopeptidomes have been limited to in vitro investigation, which fails to capture the in vivo repertoire of MHC-I peptides, or bulk tumor lysates, which are obscured by the lack of tumor-specific MHC-I isolation. To overcome these limitations, we report here the engineering of a Cre recombinase-inducible affinity tag into the endogenous mouse MHC-I gene and targeting of this allele to the KrasLSL-G12D/+; p53fl/fl (KP) mouse model (KP; KbStrep). This novel approach has allowed us to isolate tumor-specific MHC-I peptides from autochthonous pancreatic ductal adenocarcinoma (PDAC) and lung adenocarcinoma (LUAD) in vivo. With this powerful analytical tool, we were able to profile the evolution of the LUAD immunopeptidome through tumor progression and show that in vivo MHC-I presentation is shaped by post-translational mechanisms. We also uncovered novel, putative LUAD tumor associated antigens (TAAs). Many peptides that were recurrently presented in vivo exhibited very low expression of the cognate mRNA, provoking reconsideration of antigen prediction pipelines that triage peptides according to transcript abundance. Beyond cancer, the KbStrep allele is compatible with a broad range of Cre-driver lines to explore antigen presentation in vivo in the pursuit of understanding basic immunology, infectious disease, and autoimmunity.

cancer biology↗

bioRxiv2020

Transcriptional subtype-specific microenvironmental crosstalk and tumor cell plasticity in metastatic pancreatic cancer

Bulk transcriptomic studies have defined classical and basal-like gene expression subtypes in pancreatic ductal adenocarcinoma (PDAC) that correlate with survival and response to chemotherapy; however, the underlying mechanisms that govern these subtypes and their heterogeneity remain elusive. Here, we performed single-cell RNA-sequencing of 23 metastatic PDAC needle biopsies and matched organoid models to understand how tumor cell-intrinsic features and extrinsic factors in the tumor microenvironment (TME) shape PDAC cancer cell phenotypes. We identify a novel cancer cell state that co-expresses basal-like and classical signatures, demonstrates upregulation of developmental and KRAS-driven gene expression programs, and represents a transitional intermediate between the basal-like and classical poles. Further, we observe structure to the metastatic TME supporting a model whereby reciprocal intercellular signaling shapes the local microenvironment and influences cancer cell transcriptional subtypes. In organoid culture, we find that transcriptional phenotypes are plastic and strongly skew toward the classical expression state, irrespective of genotype. Moreover, we show that patient-relevant transcriptional heterogeneity can be rescued by supplementing organoid media with factors found in the TME in a subtype-specific manner. Collectively, our study demonstrates that distinct microenvironmental signals are critical regulators of clinically relevant PDAC transcriptional states and their plasticity, identifies the necessity for considering the TME in cancer modeling efforts, and provides a generalizable approach for delineating the cell-intrinsic versus -extrinsic factors that govern tumor cell phenotypes.

cancer biology↗

bioRxiv2020

Spatially-Resolved Live Cell Tagging and Isolation Using Protected Photoactivatable Cell Dyes

Whether cultured in vitro or part of a complex tissue in vivo, a cells phenotype and function are significantly influenced by dynamic interactions with its microenvironment. To explicitly examine how a cells spatiotemporal activity impacts its behavior, we developed and validated a strategy termed SPACECAT--Spatially PhotoActivatable Color Encoded Cell Address Tags--to annotate, track, and isolate specific cells in a non-destructive, viability-preserving manner. In SPACECAT, a biological sample is immersed in a photocaged fluorescent molecule, and cells within a location of interest are labeled for further study by uncaging that molecule with user-patterned near-UV light. SPACECAT offers high spatial precision and temporal stability across diverse cell and tissue types, and is compatible with common downstream assays, including flow cytometry and single-cell RNA-Seq. Illustratively, we leveraged this approach in patient-derived intestinal organoids, a spatially complex system less amenable to genetic manipulations, to select for crypt-like regions enriched in stem-like and actively mitotic cells. Moreover, we demonstrate its applicability and utility on ex vivo tissue sections from four healthy organs and an autochthonous lung tumor model, uncovering spatially-biased gene expression patterns among immune cell subsets and identifying rare myeloid phenotypes enriched around tumor/healthy border regions. In sum, our method provides a minimally invasive and broadly applicable approach to link cellular spatiotemporal features and/or behavioral phenotypes with diverse downstream assays, enabling fundamental insights into the connections between tissue microenvironments and biological (dys)function.

systems biology↗