Self-supervised learning of T cell receptor sequences exposes core properties for T cell membership.

The T cell receptor (TCR) repertoire is an extraordinarily diverse collection of TCRs essential for maintaining the body's homeostasis and response to threats. In this study, we compiled an extensive dataset of more than 4200 bulk TCR repertoire samples, encompassing 221,176,713 sequences, alongside 6,159,652 single-cell TCR sequences from over 400 samples. From this dataset, we then selected a representative subset of 5 million bulk sequences and 4.2 million single-cell sequences to train two specialized Transformer-based language models for bulk (CVC) and single-cell (scCVC) TCR repertoires, respectively. We show that these models successfully capture TCR core qualities, such as sharing, gene composition, and single-cell properties. These qualities are emergent in the encoded TCR latent space and enable classification into TCR-based qualities such as public sequences. These models demonstrate the potential of Transformer-based language models in TCR downstream applications.

Ovarian cancer is detectable from peripheral blood using machine learning over T-cell receptor repertoires.

The extraordinary diversity of T cells and B cells is critical for body maintenance. This diversity has an important role in protecting against tumor formation. In humans, the T-cell receptor (TCR) repertoire is generated through a striking stochastic process called V(D)J recombination, in which different gene segments are assembled and modified, leading to extensive variety. In ovarian cancer (OC), an unfortunate 80% of cases are detected late, leading to poor survival outcomes. However, when detected early, approximately 94% of patients live longer than 5 years after diagnosis. Thus, early detection is critical for patient survival. To determine whether the TCR repertoire obtained from peripheral blood is associated with tumor status, we collected blood samples from 85 women with or without OC and obtained TCR information. We then used machine learning to learn the characteristics of samples and to finally predict, over a set of unseen samples, whether the person is with or without OC. We successfully stratified the two groups, thereby associating the peripheral blood TCR repertoire with the formation of OC tumors. A careful study of the origin of the set of T cells most informative for the signature indicated the involvement of a specific invariant natural killer T (iNKT) clone and a specific mucosal-associated invariant T (MAIT) clone. Our findings here support the proposition that tumor-relevant signal is maintained by the immune system and is coded in the T-cell repertoire available in peripheral blood. It is also possible that the immune system detects tumors early enough for repertoire technologies to inform us near the beginning of tumor formation. Although such detection is made by the immune system, we might be able to identify it, using repertoire data from peripheral blood, to offer a pragmatic way to search for early signs of cancer with minimal patient burden, possibly with enhanced sensitivity.

The temporal behavior of the murine T cell receptor repertoire following Immunotherapy.

Immunotherapy is now an essential tool for cancer treatment, and the unique features of an individual's T cell receptor repertoire are known to play a key role in its effectiveness. The repertoire, famously vast due to a cascade of cellular mechanisms, can be quantified using repertoire sequencing. In this study, we sampled the repertoire over several time points following treatment with anti-CTLA-4, in a syngeniec mouse model for colorectal cancer, generating a longitudinal dataset of T cell clones and their abundance. The dynamics of the repertoire can be observed in response to treatment over a period of four weeks, as clonal expansion of specific clones ascends and descends. The data made available here can be used to determine treatment and predict its effect, while also providing a unique look at the behavior of the immune system over time.

GENTLE: a novel bioinformatics tool for generating features and building classifiers from T cell repertoire cancer data.

BACKGROUND: In the global effort to discover biomarkers for cancer prognosis, prediction tools have become essential resources. TCR (T cell receptor) repertoires contain important features that differentiate healthy controls from cancer patients or differentiate outcomes for patients being treated with different drugs. Considering, tools that can easily and quickly generate and identify important features out of TCR repertoire data and build accurate classifiers to predict future outcomes are essential. RESULTS: This paper introduces GENTLE (GENerator of T cell receptor repertoire features for machine LEarning): an open-source, user-friendly web-application tool that allows TCR repertoire researchers to discover important features; to create classifier models and evaluate them with metrics; and to quickly generate visualizations for data interpretations. We performed a case study with repertoires of TRegs (regulatory T cells) and TConvs (conventional T cells) from healthy controls versus patients with breast cancer. We showed that diversity features were able to distinguish between the groups. Moreover, the classifiers built with these features could correctly classify samples ('Healthy' or 'Breast Cancer')from the TRegs repertoire when trained with the TConvs repertoire, and from the TConvs repertoire when trained with the TRegs repertoire. CONCLUSION: The paper walks through installing and using GENTLE and presents a case study and results to demonstrate the application's utility. GENTLE is geared towards any researcher working with TCR repertoire data and aims to discover predictive features from these data and build accurate classifiers. GENTLE is available on https://github.com/dhiego22/gentle and https://share.streamlit.io/dhiego22/gentle/main/gentle.py .

A T cell repertoire timestamp is at the core of responsiveness to CTLA-4 blockade.

Biology of the response to anti-CTLA-4 involves the dynamics of specific T cell clones. Reasons for clinical success and failure of this treatment are still largely unknown. Here, we quantified the dynamics of the T cell receptor (TCR) repertoire, throughout 4 weeks involving treatment with anti-CTLA-4, in a syngeneic mouse model for colorectal cancer. These dynamics show an initial increase in clonality in tandem with a decrease in diversity, effects which gradually subside. Furthermore, response to treatment is tightly connected to the shared and public parts of the T cell repertoire. We were able to recognize time-dependent behaviors of specific TCR sequences and cell types and to show the response is dominated by specific motifs. We see that a single, specific time point might be useful to inform a physician of the true response to treatmentThe research further highlights the importance of temporal analyses of the immune response.

Breast cancer is marked by specific, Public T-cell receptor CDR3 regions shared by mice and humans.

The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires.

A single nucleotide variant of human PARP1 determines response to PARP inhibitors.

The introduction of novel cancer drugs and innovative treatments brings great hope for cancer patients, but also an urgent need to match drugs to suitable patients, since certain drugs that benefit one patient may actually harm others. The newly developed poly-ADP ribose polymerase (PARP) inhibitors (PARPis) are a group of pharmacological enzyme inhibitors used clinically for multiple indications. Several forms of cancer tend to be PARP dependent, making PARP an attractive target for cancer therapy. Specifically, PARPis are commonly used in BRCA-associated breast cancers patients, since unrepaired single-strand breaks are converted into double-strand breaks and BRCA-associated tumors cannot repair them by homologous recombination so that PARPi leads to tumor cell death, by a mechanism called "Synthetic Lethality". Unfortunately, not all patients respond to PARPi, and it is not currently possible to predict who will or will not respond. Here, we present a specific genomic marker, which reflects a single-nucleotide polymorphism of human PARP1 and correlates in vitro with response to PARPi, throughout all indications. In addition, we report that this SNP is associated with re-shaping mRNA, and mRNA levels, and influences the final protein structure to expose new binding sites while hiding others. The status of the SNP is therefore critical to patients' care, as it relates responses to PARPi to the PARP1-SNP carried.

Resistance to paclitaxel is associated with a variant of the gene BCL2 in multiple tumor types.

Paclitaxel, the most commonly used form of chemotherapy, is utilized in curative protocols in different types of cancer. The response to treatment differs among patients. Biological interpretation of a mechanism to explain this personalized response is still unavailable. Since paclitaxel is known to target BCL2 and TUBB1, we used pan-cancer genomic data from hundreds of patients to show that a single-nucleotide variant in the BCL2 sequence can predict a patient's response to paclitaxel. Here, we show a connection between this BCL2 genomic variant, its transcript structure, and protein abundance. We demonstrate these findings in silico, in vitro, in formalin-fixed paraffin-embedded (FFPE) tissue, and in patient lymphocytes. We show that tumors with the specific variant are more resistant to paclitaxel. We also show that tumor and normal cells with the variant express higher levels of BCL2 protein, a phenomenon that we validated in an independent cohort of patients. Our results indicate BCL2 sequence variations as determinants of chemotherapy resistance. The knowledge of individual BCL2 genomic sequences prior to the choice of chemotherapy may improve patient survival. The current work also demonstrates the benefit of community-wide, integrative omics data sources combined with in-lab experimentation and validation sets.

Network Representation of T-Cell Repertoire- A Novel Tool to Analyze Immune Response to Cancer Formation.

The T cell repertoire potentially presents complexity compatible, or greater than, that of the human brain. T cell based immune response is involved with practically every part of human physiology, and high-throughput biology needed to follow the T-cell repertoire has made great leaps with the advent of massive parallel sequencing [1]. Nevertheless, tools to handle and observe the dynamics of this complexity have only recently started to emerge [e.g., 2, 3, 4] in parallel with sequencing technologies. Here, we present a network-based view of the dynamics of the T cell repertoire, during the course of mammary tumors development in a mouse model. The transition from the T cell receptor as a feature, to network-based clustering, followed by network-based temporal analyses, provides novel insights to the workings of the system and provides novel tools to observe cancer progression via the perspective of the immune system. The crux of the approach here is at the network-motivated clustering. The purpose of the clustering step is not merely data reduction and exposing structures, but rather to detect hubs, or attractors, within the T cell receptor repertoire that might shed light on the behavior of the immune system as a dynamic network. The Clone-Attractor is in fact an extension of the clone concept, i.e., instead of looking at particular clones we observe the extended clonal network by assigning clusters to graph nodes and edges to adjacent clusters (editing distance metric). Viewing the system as dynamical brings to the fore the notion of an attractors landscape, hence the possibility to chart this space and map the sample state at a given time to a vector in this large space. Based on this representation we applied two different methods to demonstrate its effectiveness in identifying changes in the repertoire that correlate with changes in the phenotype: (1) network analysis of the TCR repertoire in which two measures were calculated and demonstrated the ability to differentiate control from transgenic samples, and, (2) machine learning classifier capable of both stratifying control and trangenic samples, as well as to stratify pre-cancer and cancer samples.

Melanoma miRNA trafficking controls tumour primary niche formation.

Melanoma originates in the epidermis and becomes metastatic after invasion into the dermis. Prior interactions between melanoma cells and dermis are poorly studied. Here, we show that melanoma cells directly affect the formation of the dermal tumour niche by microRNA trafficking before invasion. Melanocytes, cells of melanoma origin, are specialized in releasing pigment vesicles, termed melanosomes. In melanoma in situ, we found melanosome markers in distal fibroblasts before melanoma invasion. The melanosomes carry microRNAs into primary fibroblasts triggering changes, including increased proliferation, migration and pro-inflammatory gene expression, all known features of cancer-associated fibroblasts (CAFs). Specifically, melanosomal microRNA-211 directly targets IGF2R and leads to MAPK signalling activation, which reciprocally encourages melanoma growth. Melanosome release inhibitor prevented CAF formation. Since the first interaction of melanoma cells with blood vessels occurs in the dermis, our data suggest an opportunity to block melanoma invasion by preventing the formation of the dermal tumour niche.

hsa-miR-9 controls the mobility behavior of glioblastoma cells via regulation of MAPK14 signaling elements.

BACKGROUND: Glioblastoma Multiforme (GBM) is the most common and lethal primary tumor of the brain. GBM is associated with one of the worst 5-year survival rates among all human cancers, despite much effort in different modes of treatment. RESULTS: Here, we demonstrate specific GBM cancer phenotypes that are governed by modifications to the MAPAKAP network. We then demonstrate a novel regulation mode by which a set of five key factors of the MAPKAP pathway are regulated by the same microRNA, hsa-miR-9.We demonstrate that hsa-miR-9 overexpression leads to MAPKAP signaling inhibition, partially by interfering with the MAPK14/MAPKAP3 complex. Further, hsa-miR-9 overexpression initiates re-arrangement of actin filaments, which leads us to hypothesize a mechanism for the observed phenotypic shift. CONCLUSION: The work presented here exposes novel microRNA features and situates hsa-miR-9 as a therapeutic target, which governs metastasis and thus determines prognosis in GBM through MAPKAP signaling.

Fmrp Interacts with Adar and Regulates RNA Editing, Synaptic Density and Locomotor Activity in Zebrafish.

Fragile X syndrome (FXS) is the most frequent inherited form of mental retardation. The cause for this X-linked disorder is the silencing of the fragile X mental retardation 1 (fmr1) gene and the absence of the fragile X mental retardation protein (Fmrp). The RNA-binding protein Fmrp represses protein translation, particularly in synapses. In Drosophila, Fmrp interacts with the adenosine deaminase acting on RNA (Adar) enzymes. Adar enzymes convert adenosine to inosine (A-to-I) and modify the sequence of RNA transcripts. Utilizing the fmr1 zebrafish mutant (fmr1-/-), we studied Fmrp-dependent neuronal circuit formation, behavior, and Adar-mediated RNA editing. By combining behavior analyses and live imaging of single axons and synapses, we showed hyperlocomotor activity, as well as increased axonal branching and synaptic density, in fmr1-/- larvae. We identified thousands of clustered RNA editing sites in the zebrafish transcriptome and showed that Fmrp biochemically interacts with the Adar2a protein. The expression levels of the adar genes and Adar2 protein increased in fmr1-/- zebrafish. Microfluidic-based multiplex PCR coupled with deep sequencing showed a mild increase in A-to-I RNA editing levels in evolutionarily conserved neuronal and synaptic Adar-targets in fmr1-/- larvae. These findings suggest that loss of Fmrp results in increased Adar-mediated RNA editing activity on target-specific RNAs, which, in turn, might alter neuronal circuit formation and behavior in FXS.

Shift in GATA3 functions, and GATA3 mutations, control progression and clinical presentation in breast cancer.

INTRODUCTION: GATA binding protein 3 (GATA3) is a regulator of mammary luminal cell differentiation, and an estrogen receptor (ER) associated marker in breast cancer. Tumor suppressor functions of GATA3 have been demonstrated primarily in basal-like breast cancers. Here, we focused on its function in luminal breast cancer, where GATA3 is frequently mutated, and its levels are significantly elevated. METHODS: GATA3 target genes were identified in normal- and luminal cancer- mammary cells by ChIP-seq, followed by examination of the effects of GATA3 expressions and mutations on tumorigenesis-associated genes and processes. Additionally, mutations and expression data of luminal breast cancer patients from The Cancer Genome Atlas were analyzed to characterize genetic signatures associated with GATA3 mutations. RESULTS: We show that some GATA3 effects shift from tumor suppressing to tumor promoting during tumorigenesis, with deregulation of three genes, BCL2, DACH1, THSD4, representing major GATA3-controlled processes in cancer progression. In addition, we identify an altered activity of mutant GATA3, and distinct associated genetic signatures. These signatures depend on the functional domain mutated; and, for a specific subgroup, are shared with basal-like breast cancer patients, who are a clinical group with regard to considerations of mode of treatment. CONCLUSIONS: The GATA3 dependent mechanisms may call for special considerations for proper prognosis and treatment of patients.

PAX6 regulates melanogenesis in the retinal pigmented epithelium through feed-forward regulatory interactions with MITF.

During organogenesis, PAX6 is required for establishment of various progenitor subtypes within the central nervous system, eye and pancreas. PAX6 expression is maintained in a variety of cell types within each organ, although its role in each lineage and how it acquires cell-specific activity remain elusive. Herein, we aimed to determine the roles and the hierarchical organization of the PAX6-dependent gene regulatory network during the differentiation of the retinal pigmented epithelium (RPE). Somatic mutagenesis of Pax6 in the differentiating RPE revealed that PAX6 functions in a feed-forward regulatory loop with MITF during onset of melanogenesis. PAX6 both controls the expression of an RPE isoform of Mitf and synergizes with MITF to activate expression of genes involved in pigment biogenesis. This study exemplifies how one kernel gene pivotal in organ formation accomplishes a lineage-specific role during terminal differentiation of a single lineage.

14-3-3 and ß-catenin are secreted on extracellular vesicles to activate the oncogenic Wnt pathway.

Aberrant activation of the canonical Wnt signal transduction pathway is involved in a large number of human diseases. ß-catenin, the key effector protein of the canonical Wnt pathway, functions in the nucleus with T-cell factor/lymphoid enhancer factor (TCF/LEF) to activate expression of Wnt target genes. Here we show that members of the 14-3-3 protein family bind disheveled-2 (Dvl-2) and glycogen synthase-3ß (GSK-3ß) to attenuate the interaction between GSK-3ß and ß-catenin. Importantly, 14-3-3 and ß-catenin form "bleb-like" structures and are secreted via extracellular vesicles to induce Wnt signaling activity in target cells. Our data suggest a novel way of transducing the oncogenic Wnt signal in which ß-catenin is regulated by 14-3-3ζ through the formation of "oncosomes" that contain both the 14-3-3 and ß-catenin proteins.

SENP5 mediates breast cancer invasion via a TGFßRI SUMOylation cascade.

Identifying novel mechanisms, which are at the core of breast cancer biology, is of critical importance. Such mechanisms may explain response to treatment, reveal novel targets or drive detection assays. To uncover such novel mechanisms, we used survival analysis on gene expression datasets encompassing 1363 patients. By iterating over the compendia of genes, we screened for their significance as prognosis biomarkers and identified SUMO-specific protease 5 (SENP5) to significantly stratify patients into two survival groups across five unrelated tested datasets. According to these findings, low expression of SENP5 is associated with good prognosis among breast cancer patients. Following these findings, we analyzed SENP5 silencing and show it is followed by inhibition of anchorage-independence growth, proliferation, migration and invasion in breast cancer cell lines. We further show that these changes are conducted via regulation of TGFßRI levels. These data relate to recent reports about the SUMOylation of TGFßRI. Following TGFßRI changes in expression, we show that one of its target genes, MMP9, which plays a key role in degrading the extracellular matrix and contributes to TGFß-induced invasion, is dramatically down regulated upon SENP5 silencing. This is the first report represents SENP5-TGFß-MMP9 cascade and its mechanistic involvement in breast cancer.

CD24 knockout prevents colorectal cancer in chemically induced colon carcinogenesis and in APC(Min)/CD24 double knockout transgenic mice.

Increased expression of CD24 is seen in a large variety of solid tumors, including up to 90% of gastrointestinal (GI) tumors. Stable derivatives of SW480 colorectal cancer (CRC) cells that overexpress CD24 proliferate faster, and increase cell motility, saturation density, plating efficiency, and growth in soft agar. They also produce larger tumors in nude mice as compared to the parental SW480 cells. Most significantly, even depletion of one copy of the CD24 allele in the APC(Min/+) mice of a transgenic mouse model led to a dramatic reduction in tumor burden in all sections of the small intestine. Homozygous deletion of both CD24 alleles resulted in complete abolishment of tumor formation. Moreover, CD24 knockout mice exhibited resistance to chemically induced inflammation-associated CRC. Finally, a new signal transduction pathway is suggested: namely, CD24 expression downstream to COX2 and PGE2 synthesis, which is directly regulated by ß-catenin. CD24 is shown in vitro and in vivo as being an important oncogene in the gut, and one that plays a critical role in the initiation and progression of carcinogenesis.

The metabolic regulator PGC-1α links hepatitis C virus infection to hepatic insulin resistance.

BACKGROUND & AIMS: Chronic hepatitis C virus (HCV) infection is strongly associated with insulin resistance and diabetes mellitus. Peroxisome proliferator-activated receptor-gamma co-activator 1α (PGC-1α) is a transcriptional co-activator involved in the initiation of gluconeogenesis in the liver. Increased hepatic expression of PGC-1α has been implicated in insulin resistance. We investigated whether modulation of PGC-1α levels following HCV infection underlies HCV-associated hepatic insulin resistance. METHODS: HCV genomes were expressed in hepatoma cells followed by analysis of PGC-1α and gluconeogenesis levels. RESULTS: PGC-1α was robustly induced in HCV infected cells. PGC-1α induction was accompanied by an elevated expression of the gluconeogenic gene glucose-6 phosphatase (G6Pase) and increased glucose production. The induction of gluconeogenesis is HCV dependent, since interferon treatment abolishes PGC-1α and G6Pase elevation and decreases glucose output. Moreover, PGC-1α knockdown resulted in a significant reduction of G6Pase levels in HCV full length replicon cells, emphasizing the central role of PGC-1α in the exaggerated gluconeogenic response observed in HCV patients. Treatment of HCV replicon cells with the antioxidant N-acetylcysteine resulted in reduction of PGC-1α levels, suggesting that HCV-induced oxidative stress promoted PGC-1α upregulation. Finally, both PGC-1α and G6Pase RNA levels were significantly elevated in liver samples of HCV infected patients, highlighting the clinical relevance of these results. CONCLUSIONS: PGC-1α is robustly induced following HCV infection, resulting in an upregulated gluconeogenic response, thereby linking HCV infection to hepatic insulin resistance. Our results suggest that PGC-1α is a potential molecular target for the treatment of HCV-associated insulin resistance.

The EDD E3 ubiquitin ligase ubiquitinates and up-regulates beta-catenin.

Wnt/ß-catenin signaling plays a central role in development and is also involved in a diverse array of diseases. ß-Catenin activity is tightly regulated via a multiprotein complex that includes the kinase glycogen synthase kinase-3ß (GSK-3ß). GSK-3ß phosphorylates ß-catenin, marking it for ubiquitination and degradation via the proteasome. Thus in regulation of the Wnt pathway, the ubiquitin system is known to be involved mostly in mediating the turnover of ß-catenin, resulting in reduced Wnt signaling levels. Here we report that an arm of the ubiquitin system increases ß-catenin protein levels. We show that GSK-3ß directly interacts with the E3 ubiquitin ligase identified by differential display (EDD) that also binds ß-catenin. Expression of EDD leads to enhanced nuclear accumulation of both GSK-3ß and ß-catenin and results in up-regulation of ß-catenin expression levels and activity. Importantly, EDD ubiquitinates ß-catenin through Lys29- or Lys11-linked ubiquitin chains, leading to enhanced stability of ß-catenin. Our results demonstrate a role for the ubiquitin system in up-regulation of the Wnt signaling pathway, suggesting that EDD could function as a colorectal oncogene.

Restoration of APC gene function in colorectal cancer cells by aminoglycoside- and macrolide-induced read-through of premature termination codons.

Adenomatous polyposis coli (APC) is a multifunctional tumour suppressor protein that negatively regulates the Wnt signalling pathway. The APC gene is ubiquitously expressed in tissues and organs, including the large intestine and central nervous system. The majority of patients with sporadic and hereditary colorectal cancer have mutations in the gene encoding APC. Approximately 30% of these mutations are single nucleotide changes that result in premature stop codons (nonsense mutations). A potential therapeutic approach for treatment of this subset of patients is the use of aminoglycosides and macrolides that induce nonsense mutation read-through and restore levels of full-length protein. We have used reporter plasmids and colorectal cancer cell lines to demonstrate that several aminoglycosides and tylosin, a member of the macrolide family, induced read-through of nonsense mutations in the APC gene. In xenograft experiments and in the Apc(Min/+) mouse model, these compounds ameliorated the tumorigenic clinical symptoms caused by nonsense mutations in the APC gene.