Multiomics Empowers Predictive Pancreatic Cancer Immunotherapy.

Advances in cancer immunotherapy, particularly immune checkpoint inhibitors, have dramatically improved the prognosis for patients with metastatic melanoma and other previously incurable cancers. However, patients with pancreatic ductal adenocarcinoma (PDAC) generally do not respond to these therapies. PDAC is exceptionally difficult to treat because of its often late stage at diagnosis, modest mutation burden, and notoriously complex and immunosuppressive tumor microenvironment. Simultaneously interrogating features of cancer, immune, and other cellular components of the PDAC tumor microenvironment is therefore crucial for identifying biomarkers of immunotherapeutic resistance and response. Notably, single-cell and multiomics technologies, along with the analytical tools for interpreting corresponding data, are facilitating discoveries of the systems-level cellular and molecular interactions contributing to the overall resistance of PDAC to immunotherapy. Thus, in this review, we will explore how multiomics and single-cell analyses provide the unprecedented opportunity to identify biomarkers of resistance and response to successfully sensitize PDAC to immunotherapy.

Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic responders.

Pancreatic adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. We generated a spatial multi-omics atlas encompassing 26 PDAC tumors from patients treated with combination immunotherapies. Using machine learning-enabled H&E image classification models and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within TLS niches spanning across distinct morphologies and immunotherapies. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation in pathological responders, confirmed with spatial proteomics and BCR profiling. Our study also identifies spatial features of pathologic immune responses, revealing TLS maturation colocalizing with IgG/IgA distribution and extracellular matrix remodeling. HIGHLIGHTS: Integrated multi-modal spatial profiling of human PDAC tumors from neoadjuvant immunotherapy clinical trials reveal diverse spatial niches enriched in TLS.TLS maturity is influenced by tumor location and the cellular neighborhoods in which TLS immune cells are recruited.Unsupervised machine learning of genome-wide signatures on spatial transcriptomics data characterizes the TLS-enriched TME and associates TLS transcriptomes with survival outcomes in PDAC.Interactions of spatially variable gene expression patterns showed TLS maturation is coupled with immunoglobulin distribution and ECM remodeling in pathologic responders.Intratumoral plasma cell and immunoglobin gene expression spatial dynamics demonstrate trafficking of TLS-driven humoral immunity in the PDAC TME. Significance: We report a spatial multi-omics atlas of PDAC tumors from a series of immunotherapy neoadjuvant clinical trials. Intratumorally, pathologic responders exhibit mature TLS that propagate plasma cells into malignant niches. Our findings offer insights on the role of TLS-associated humoral immunity and stromal remodeling during immunotherapy treatment.

Barcoding intracellular reverse transcription enables high-throughput phenotype-coupled T cell receptor analyses.

Assays linking cellular phenotypes with T cell or B cell antigen receptor sequences are crucial for characterizing adaptive immune responses. Existing methodologies are limited by low sample throughput and high cost. Here, we present INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach that combines molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility.

Loss of TDP-43 function and rimmed vacuoles persist after T cell depletion in a xenograft model of sporadic inclusion body myositis.

Sporadic inclusion body myositis (IBM) is the most common acquired muscle disease in adults over age 50, yet it remains unclear whether the disease is primarily driven by T cell­mediated autoimmunity. IBM muscle biopsies display nuclear clearance and cytoplasmic aggregation of TDP-43 in muscle cells, a pathologic finding observed initially in neurodegenerative diseases, where nuclear loss of TDP-43 in neurons causes aberrant RNA splicing. Here, we show that loss of TDP-43­mediated splicing repression, as determined by inclusion of cryptic exons, occurs in skeletal muscle of subjects with IBM. Of 119 muscle biopsies tested, RT-PCR­mediated detection of cryptic exon inclusion was able to diagnose IBM with 84% sensitivity and 99% specificity. To determine the role of T cells in pathogenesis, we generated a xenograft model by transplanting human IBM muscle into the hindlimb of immunodeficient mice. Xenografts from subjects with IBM displayed robust regeneration of human myofibers and recapitulated both inflammatory and degenerative features of the disease. Myofibers in IBM xenografts showed invasion by human, oligoclonal CD8+ T cells and exhibited MHC-I up-regulation, rimmed vacuoles, mitochondrial pathology, p62-positive inclusions, and nuclear clearance and cytoplasmic aggregation of TDP-43, associated with cryptic exon inclusion. Reduction of human T cells within IBM xenografts by treating mice intraperitoneally with anti-CD3 (OKT3) suppressed MHC-I up-regulation. However, rimmed vacuoles and loss of TDP-43 function persisted. These data suggest that T cell depletion does not alter muscle degenerative pathology in IBM.

Citrullination of a phage-displayed human peptidome library reveals the fine specificities of rheumatoid arthritis-associated autoantibodies.

BACKGROUND: Post-translational modifications (PTMs) on proteins can be targeted by antibodies associated with autoimmunity. Despite a growing appreciation for their intrinsic role in disease, there is a lack of highly multiplexed serological assays to characterize the fine specificities of PTM-directed autoantibodies. METHODS: In this study, we used the programmable phage display technology, Phage ImmunoPrecipitation Sequencing (PhIP-Seq), to profile rheumatoid arthritis (RA) associated anti-citrullinated protein antibody (ACPA) reactivities. FINDINGS: Using both unmodified and peptidylarginine deiminase (PAD)-modified phage display libraries consisting of ~250,000 overlapping 90 amino acid peptide tiles spanning the human proteome, PTM PhIP-Seq robustly identified antibodies to citrulline-dependent epitopes. INTERPRETATION: PTM PhIP-Seq was used to quantify key differences among RA patients, including PAD isoform specific ACPA profiles, and thus represents a powerful tool for proteome-scale antibody-binding analyses. FUNDING: This research is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA). The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of ODNI, IARPA, or the US Government. The US Government is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright annotation therein. This study was made possible by a National Institute of General Medical Sciences (NIGMS) grant R01 GM136724 (HBL). MFK was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) grant T32AR048522. ED was supported by the Rheumatology Research Foundation.

Ultra-efficient sequencing of T Cell receptor repertoires reveals shared responses in muscle from patients with Myositis.

BACKGROUND: Myositis, or idiopathic inflammatory myopathy (IIM), is a group disorders of unknown etiology characterized by the inflammation of skeletal muscle. The role of T cells and their antigenic targets in IIM initiation and progression is poorly understood. T cell receptor (TCR) repertoire sequencing is a powerful approach for characterizing complex T cell responses. However, current TCR sequencing methodologies are complex, expensive, or both, greatly limiting the scale of feasible studies. METHODS: Here we present Framework Region 3 AmplifiKation sequencing ("FR3AK-seq"), a simplified multiplex PCR-based approach for the ultra-efficient and quantitative analysis of TCR complementarity determining region 3 (CDR3) repertoires. By using minimal primer sets targeting a conserved region immediately upstream of CDR3, undistorted amplicons are analyzed via short read, single-end sequencing. We also introduce the novel algorithm Inferring Sequences via Efficiency Projection and Primer Incorporation ("ISEPPI") for linking CDR3s to their associated variable genes. FINDINGS: We find that FR3AK-seq is sensitive and quantitative, performing comparably to two different industry standards. FR3AK-seq and ISEPPI were used to efficiently and inexpensively characterize the T cell infiltrates of surgical muscle biopsies obtained from 145 patients with IIM and controls. A cluster of closely related TCRs was identified in samples from patients with sporadic inclusion body myositis (IBM). INTERPRETATION: The ease and minimal cost of FR3AK-seq removes critical barriers to routine, large-scale TCR CDR3 repertoire analyses, thereby democratizing the quantitative assessment of human TCR repertoires in disease-relevant target tissues. Importantly, discovery of closely related TCRs in muscle from patients with IBM provides evidence for a shared antigen-driven T cell response in this disease of unknown pathogenesis. FUNDING: This work was supported by NIH grant U24AI118633 and a Prostate Cancer Foundation Young Investigator Award.