Atlas-Guided Discovery of Transcription Factors for T Cell Programming.

Accurately inferring transcription factor (TF) activity from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in computational biology. While existing methods rely on statistical models, motif enrichment, or prior-based inference, they often depend on deterministic assumptions about regulatory relationships and rely on static regulatory databases. Few approaches effectively integrate prior biological knowledge with data-driven inference to capture novel, dynamic, and context-specific regulatory interactions. To address these limitations, we develop scRegulate, a generative deep learning framework leveraging variational inference to estimate TF activities guided by experimental TF-target gene relationships and progressively adapted based on the input scRNA-seq data. By integrating structured biological constraints with a probabilistic latent space model, scRegulate offers a scalable and biologically grounded estimation of TF activity and gene regulatory network (GRN). Comprehensively benchmarking on public experimental and synthetic datasets demonstrates scRegulate's superior ability. Further, scRegulate accurately recapitulates experimentally validated TF knockdown effects on a Perturb-seq dataset for key TFs. Applied to experimental human PBMC scRNA-seq data, scRegulate infers cell-type-specific GRNs and identifies differentially active TFs aligned with known regulatory pathways. scRegulate's TF activity representations capture transcriptional heterogeneity, enabling accurate clustering of cell types. scRegulate is highly efficient, frequently an order of magnitude faster than common baselines. Collectively, our results establish scRegulate as a powerful, interpretable, and scalable framework for inferring TF activities and GRNs from single-cell transcriptomics. Results and scripts available at github.com/YDaiLab/scRegulate. Supplementary data are available at Bioinformatics online.

Monocytes and macrophages (Mos/Mϕs) play diverse roles in wound healing by adopting a spectrum of functional phenotypes; however, the regulation of such heterogeneity remains poorly defined. We enhanced our previously published Bayesian inference TF activity model, incorporating both single-cell RNA sequencing and single-cell ATAC sequencing data to infer transcription factor (TF) activity in Mos/Mϕs during skin wound healing. We found that wound Mos/Mϕs clustered into early-stage Mos/Mϕs, late-stage Mϕs, and APCs, and that each cluster showed differential chromatin accessibility and differential predicted TF activity that did not always correlate with mRNA or protein expression. Network analysis revealed two highly connected large communities involving a total of 19 TFs, highlighting TF cooperation in regulating wound Mos/Mϕs. This analysis also revealed a small community populated by NR4A1 and NFKB1, supporting a proinflammatory link between these TFs. Importantly, we validated a proinflammatory role for NR4A1 activity during wound healing, showing that Nr4a1 knockout mice exhibit decreased inflammatory gene expression in early-stage wound Mos/Mϕs, along with delayed wound re-epithelialization and impaired granulation tissue formation. In summary, our study provides insight into TF activity that regulates Mo/Mϕ heterogeneity during wound healing and provides a rational basis for targeting Mo/Mϕ TF networks to alter phenotypes and improve healing.

Simple SummaryCellCall is an R package tool that is used to analyze cell–cell communication based on transcription factor (TF) activities calculated by cell-type specificity of target genes and thus cannot directly handle two-condition comparisons. We developed CellCallEXT to complement CellCall. CellCallEXT can directly identify ligand–receptor (L–R) interactions that alter the expression profiles of downstream genes between two conditions, such as tumor and healthy tissue. Scoring in CellCallEXT quantitatively integrates expression of ligands, receptors, TFs, and target genes (TGs). The pathway enrichment analysis and visualization modules allow biologists to investigate how disease alters cell–cell communication. Furthermore, Reactome pathways were added into CellCallEXT to expand the L–R–TF database.(1) Background: Single-cell RNA sequencing (scRNA-seq) data are useful for decoding cell–cell communication. CellCall is a tool that is used to infer inter- and intracellular communication pathways by integrating paired ligand–receptor (L–R) and transcription factor (TF) activities from steady-state data and thus cannot directly handle two-condition comparisons. For tumor and healthy status, it can only individually analyze cells from tumor or healthy tissue and examine L–R pairs only identified in either tumor or healthy controls, but not both together. Furthermore, CellCall is highly affected by gene expression specificity in tissues. (2) Methods: CellCallEXT is an extension of CellCall that deconvolutes intercellular communication and related internal regulatory signals based on scRNA-seq. Information on Reactome was retrieved and integrated with prior knowledge of L–R–TF signaling and gene regulation datasets of CellCall. (3) Results: CellCallEXT was successfully applied to examine tumors and immune cell microenvironments and to identify the altered L–R pairs and downstream gene regulatory networks among immune cells. Application of CellCallEXT to scRNA-seq data from patients with deficiency of adenosine deaminase 2 demonstrated its ability to impute dysfunctional intercellular communication and related transcriptional factor activities. (4) Conclusions: CellCallEXT provides a practical tool to examine intercellular communication in disease based on scRNA-seq data.

Dental niche cells directly contribute to tooth reconstitution and morphogenesis.

Stem-like CD8 T cells are regulated by the transcription factor TCF1 and are key players in the response to immune checkpoint blockade (ICB). However, recent findings indicate that the dependance on TCF1+ stem-like T cells for ICB efficacy may not be equal across patients or in different tumor contexts. Here we leveraged TCF1 conditional knock-out (TCF1 cKO) mice to investigate how TCF1 instructs the early fate and functions of CD8 T cells upon ICB therapy in tumors that differ for immunogenicity and levels of tumor antigen expression. Strikingly, we discovered that TCF1 expression in CD8 T cells is required for ICB efficacy in poorly immunogenic B16OVA melanomas but is dispensable in highly immunogenic MC38OVA colorectal tumors. Single-cell RNA sequencing and immunophenotyping in the tumor draining lymph node (TDLN) revealed defective priming and expansion of tumor-specific TCF1 cKO T cells in B16OVA- but not MC38OVA-bearing mice treated with ICB. Conversely, ICB therapy efficiently expanded tumor-specific TCF1 WT T cells in the TDLN of both tumor models. In vitro, we found defective proliferation, reduced PD1 and CD28 up-regulation and reduced phosphorylation of key molecules downstream the T cell receptor pathway in TCF1 cKO T cells stimulated with low but not high TCR signals. These data indicate that TCF1 poises T cells for optimal responsiveness in suboptimal priming conditions such as those found in low antigen expressing tumors. Furthermore, in the absence of TCF1 we found the accumulation in the TDLN of a subset of tumor-specific naïve T cells poised to give rise to short-lived effectors, which are less suited to sustain anti-tumor responses in poorly immunogenic tumors where expansion of T cells retaining memory potential is required for durable responses. Single-cell RNA sequencing and immunophenotyping within the tumor microenvironment showed that in MC38OVA tumors both WT and TCF1 cKO mice expanded a CD8 subset sharing a signature with transitory effectors, which were shown to mediate ICB efficacy in chronic viral infection models. Expansion of cytotoxic CD8 T cells likely accounted for the strong anti-tumor response observed in both WT and TCF1 cKO mice. Conversely, B16OVA tumors failed to expand transitory effectors and accumulated Tox+ dysfunctional CD8 T cells. Importantly, in the absence of TCF1 dysfunctional T cells became destabilized, failed to persist and shared features with CD8 T cells found in patients that fail ICB. Altogether, the reduced priming of stem-like T cells in the TDLN combined with a destabilized dysfunctional T cell state in the tumor contributed to the failure of TCF1 cKO mice to sustain effective ICB responses in poorly immunogenic tumors. Our study highlights a role for TCF1 during the priming and early stages of the anti-tumor CD8 T cell response with important implications for guiding optimal therapeutic interventions in cancers with low frequency of TCF1+ CD8 T cells and low neoantigen expression. Citation Format: Giulia Escobar, Katherine Tooley, Joan Pages Oliveras, Linglin Huang, Hanning Cheng, Chang Xue, Davide Mangani, Natanael Hazel, Carola Rutigliani, Luca Biasco, Ana C. Anderson. Tumor context dictates reliance on TCF1 for response to immunotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4157.

6056 Background: Combination CTLA-4 and PD-1 ICB results in durable responses in patients with recurrent and metastatic HNSCC and therefore justifies further investigation in the induction or neoadjuvant setting. Methods: We investigated features of the tumor immune microenvironment (TIME) associated with MHR after induction CTLA-4 and PD-1 ICB in patients with newly diagnosed HPV-positive HNSCC. Tumor samples were collected at baseline and on treatment from 31 patients enrolled in a phase 2 trial of a 6-week cycle of CTLA-4 and PD-1 ICB induction followed by dose/volume-adapted IMRT (50-66Gy) concurrent with cycle 2. Tumors were evaluated for histological response and single-cell RNA sequencing (scRNA-seq) and scTCR-seq were performed on the 10X genomics platform. After stringent clustering and annotation of scRNA-seq data, 76,319 CD8+ and 78,622 CD4+ T cells with paired TCR sequence data were evaluable for transcriptomic, TCR repertoire and clonotype differentiation analysis. Results: Percent reduction in tumor viability on histology correlated significantly with reduction in tumor cell proportion in scRNA-seq data (R2= 0.7). Thirteen (48%) of 27 patients with paired samples (missing data due to COVID) had MHR, defined as ≤10% residual tumor viability on ICB treatment. Through TCR tracing, over 100 T cell clonotypes that expanded significantly (p < 0.05, Fisher’s exact) post-ICB were identified. Highly expanded clonotypes resided mainly in exhausted CD8+ T cell clusters and exhibited a tissue resident memory (TRM) phenotype. Examination of their functional states revealed a variety of T cell modulatory trajectories, including reverse transition from exhausted to less exhausted states and from memory to functional states. When compared to patients without MHR, those with MHR had significantly higher ICB-induced TCR clonotype expansion (p = 0.025, Wilcoxon), reductions of activated Tregs (p = 0.003, Wilcoxon) and terminally exhausted CD8+ T cells (p = 0.003, Wilcoxon), and increase of polyfunctional CD8+ T cells (p = 0.014, Wilcoxon). A lasso regression model associated T cell expansion, basal 7-gene TRM and 5-gene effector scores, and on-treatment proliferation score and effector cell proportion with percent reduction in tumor viability (R2 = 0.66). Conclusions: In HPV-HNSCC, induction CTLA4 and PD1 ICB lead to extensive reinvigoration of CD8+ T cell clonotypes with both an exhausted and TRM phenotype, revealing a high degree of plasticity of distinct T cell clones. Paired RNA and TCR profiling facilitated identification of potentially tumor reactive and ICB-responsive T cells and clonotypes and identified several TIME features associated with tumor cell death. Clinical trial information: NCT03799445 .

Background: cell-free DNA (cfDNA) in plasma primarily originates from hematopoietic cells in healthy individuals, but in cancer patients, it includes circulating tumor DNA from dead tumor cells. cfDNA mutation analysis is already used in clinical practice for biomarker research and treatment decisions. Recent studies have shown that cfDNA fragmentation patterns reflect tumor tissue chromatin status. Inferring transcription factor (TF) activity from cfDNA TF binding site (TFBS) coverage patterns offer a minimally invasive assay to understand cancer biology with limited sequencing depth. However, the accuracy of TF activity inference has only been examined for a few well-known TFs such as AR and ESR1. We conducted a comparative analysis of 377 TF activities between cfDNA whole genome sequence (WGS) and tumor Assay for Transposase-Accessible Chromatin using sequencing (ATAC-sequencing). Methods: Two liver cancer cell lines, HepG2 with a gain-of-function CTNNB1 mutation and HuH7 with wild-type CTNNB1, were used to generate xenograft models. ATAC-sequencing/RNA-sequencing and WGS were performed on the tumors and pooled plasma-derived cfDNA from each model. TCF/LEF family TF activities, downstream targets of CTNNB1, were compared between models with different CTNNB1 mutation statuses in both tumor ATAC-sequencing and cfDNA WGS. For 377 TFs with at least 10, 000 TFBS, the correlation of TF activities between tumor ATAC-sequencing and cfDNA WGS was examined in each model. Furthermore, tumor model-specific TFs were identified based on ATAC-sequencing, followed by comparison of cfDNA TFBS coverage of these TFs between the two models. Results: In pilot analysis with TCF/LEF family TFs, both tumor ATAC- sequencing and cfDNA WGS from HepG2 xenograft model showed higher TCF7 and TCF7L2 activities compared to HuH7. In an expanded analysis of 377 TFs, we found a significant and strong correlation between tumor and cfDNA TF activities (Spearman’s rank correlation coefficients for HepG2 and HuH7: -0.90 and -0.86, respectively). For tumor model-specific TFs, “HepG2-HIGH” and “HuH7-HIGH” which are composed of 29 and 18 TFs with the highest variance between models, cfDNA TFBS coverage of these two groups of TFs also showed significant differences between tumors (p<0.05). Conclusion: Our results indicate that cfDNA can accurately estimate the activity of over 300 TFs in tumor. To assess the potential utility of cfDNA TFBS analysis in clinical samples, further studies are warranted. Citation Format: Ryuji Tamaki, Koji Sagane, Shuyu Dan Li, Taisuke Hoshi. Comparative analysis of transcription factor activities derived from low-pass whole genome sequencing of cell-free DNA and from ATAC-sequencing of tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5899.

Inhibitor of DNA binding (Id) proteins bind to and inhibit the function of basic helix-loop-helix (bHLH) transcription factors including those that regulate pancreatic development. Moreover, bone morphogenetic proteins (BMPs) regulate the expression of Ids. We hypothesized that BMP4 and Id proteins play a role in the expansion and differentiation of epithelial progenitor cells. We demonstrate that BMP4 induces the expression of Id2 along with the expansion of AR42J pancreatic epithelial cells. Furthermore, neutralization of BMP4 significantly reduced duct epithelial cell expansion in a mouse model of islet regeneration. BMP4 stimulation promotes Id2 binding to the bHLH transcription factor NeuroD, which is required for the differentiation of pancreatic islet cells. Therefore, our results indicate that BMP4 stimulation blocks the differentiation of endocrine progenitor cells and instead promotes their expansion thereby revealing a novel paradigm of signaling explaining the balance between expansion and differentiation of pancreatic duct epithelial progenitors. Understanding the mechanisms of BMP and Id function elucidates a key step during pancreas embryogenesis, which is important knowledge for expanding pancreatic progenitors in vitro.

Immune checkpoint blockade can provide clinical benefit for patients with advanced cancer. Here, we report durable disease control over many years following PD-L1 blockade through induction of a viral antigen-specific T cell response in an adult patient with recurrent respiratory papillomatosis. Antigen-specific T cell response assays, single cell RNA-sequencing, and RNA-scope was used to study clinical tissues. An HPV6 E2-specific T cell clone restricted to HLA-B*55, present at low frequency in the pre-treatment papilloma, significantly expanded after six doses of PD-L1 blockade and remained present and functional at the site of initial response in the larynx as a tissue resident memory T cell for 4 years. An associated reduction in E2 target gene was observed following treatment. Although demonstrated in a single exceptional responder, these results highlight that immune checkpoint blockade may induce durable, viral antigen-specific immunity of sufficient magnitude to control disease in patients with nonmalignant disorders.

Decision letter: Single-cell RNA sequencing of the Strongylocentrotus purpuratus larva reveals the blueprint of major cell types and nervous system of a non-chordate deuterostome

Remarkable progress has been made in the field of anti-tumor immunity, nevertheless many questions are still open. Thus, even though memory T cells have been implicated in long-term anti-tumor protection, particularly in prevention of cancer recurrence, the bases of their variable effectiveness in tumor patients are poorly understood. Two types of memory T cells have been described according to their traffic pathways: recirculating and tissue-resident memory T cells. Recirculating tumor-specific memory T cells are found in the cell infiltrate of solid tumors, in the lymph and in the peripheral blood, and they constantly migrate in and out of lymph nodes, spleen, and bone marrow. Tissue-resident tumor-specific memory T cells (TRM) permanently reside in the tumor, providing local protection.Anti-PD-1/PD-L1, a type of immune checkpoint blockade (ICB) therapy, can considerably re-invigorate T cell response and lead to successful tumor control, even in patients at advanced stages. Indeed, ICB has led to unprecedented successes against many types of cancers, starting a ground-breaking revolution in tumor therapy. Unfortunately, not all patients are responsive to such treatment, thus further improvements are urgently needed. The mechanisms underlying resistance to ICB are still largely unknown. A better knowledge of the dynamics of the immune response driven by the two types of memory T cells before and after anti-PD-1/PD-L1 would provide important insights on the variability of the outcomes. This would be instrumental to design new treatments to overcome resistance.Here we provide an overview of T cell contribution to immunity against solid tumors, focusing on memory T cells. We summarize recent evidence on the involvement of recirculating memory T cells and TRM in anti-PD-1/PD-L1-elicited antitumor immunity, outline the open questions in the field, and propose that a synergic action of the two types of memory T cells is required to achieve a full response. We argue that a T-centric vision focused on the specific roles and the possible interplay between TRM and recirculating memory T cells will lead to a better understanding of anti-PD-1/PD-L1 mechanism of action, and provide new tools for improving ICB therapeutic strategy.

BackgroundPathological response to neoadjuvant ICB is established as a biomarker of long-term disease control in several solid tumors.1 To determine tumor microenvironment (TME) features associated with pathological response, we performed...

p202a is a member of the interferon-inducible murine p200 family of proteins. These proteins share 1 or 2 partially conserved 200 amino acid segments of the a or the b type. The known biological activities of p202a include among others the regulation of muscle differentiation, cell proliferation, and apoptosis. These biological activities of p202a can be correlated with the inhibition of the activity of several transcription factors. Thus, the binding of p202a results in the inhibition of the sequence-specific binding to DNA of the c-Fos, c-Jun, E2F1, E2F4, MyoD, myogenin, and c-Myc transcription factors. This study concerns the mechanisms by which p202a inhibits the activity of NF-kappaB, a transcription factor involved among others in host defense, inflammation, immunity, and the apoptotic response. NF-kappaB consists of p50 and p65 subunits. We demonstrate that p202a can inhibit in vitro and in vivo the binding to DNA of p65 homodimers and p50/65 heterodimers, whereas it increases the binding of p50 homodimers. Thus p202a can impair NF-kappaB activity both by inhibiting the binding to DNA of the transcriptionally active p65 homodimers and p50/p65 heterodimers and by boosting the binding of the repressive p50 homodimers. p202a can bind p50 and p65 in vitro and in vivo, and p202a can be part of the p50 homodimer complex bound to DNA. p50 binds in p202a to the a type segment, whereas p65 binds to the b type segment. Transfected ectopic p202a increases the apoptotic effect of tumor necrosis factor (at least in part) by inhibiting NF-kappaB and its antiapoptotic activity.

Astrocytoma is the most frequently occurring nervous system cancer in humans. Glioblastoma (GBM) is the most severe form of astrocytoma ([WHO] grade IV), and GBM patients rarely live beyond 5 years. Understanding how transcription factor regulatory networks contribute to the severity of astrocytoma will help identify novel therapeutic strategies for GBM. Nuclear Respiratory Factor 1 (NRF1) is a transcription factor (TF) that we have previously demonstrated as being active in cancer and having the ability to participate in crosstalk with other TFs such as the E2Fs and MYC. We have previously demonstrated that NRF1 gene networks are associated with increased NRF1 gene expression and GBM patient survival outcomes. Here, we examined the TF activity landscape that is differentially expressed in GBM compared to non-tumor tissue and in lower grade (I, II, and III) astrocytoma and their role in disease severity. Activities of 247 TFs including NRF1 were examined using patient mRNA expression data from four independent public datasets including the TCGA. The R package ‘limma' with ‘voom' was used to calculate the differential expression of each gene in the microarray and RNA-Seq datasets included in the present study, and then LRPath was employed to determine TF activity. NRF1 transcription factor (TF) activity is upregulated in glioma, correlates with disease aggressiveness, and is associated with cancer hallmarks and key functional pathways known to be dysregulated in cancer. Further analysis of data from all four patient cohorts including TCGA showed that NRF1 TF activity positively correlates with NFE2L2, E2F1, and RFX1, and negatively correlates with MEF2. Differential activity of these TFs is associated with astrocytoma disease severity. Protein-protein interaction networks (PPIN) were then generated for the TF combinations separately for male and female patients. Downstream gene ontology pathway analysis of the TF target genes revealed that DNA repair (GO:0006281), histone modification (GO:0016570), mitotic cell cycle (GO:0000278), and regulation of neurotransmitter level (GO: 0001505) genes regulated by NFE2L2, E2F1, and RFX1 are upregulated corresponding to increased NRF1 activity, while tissue development (GO: 0009888) genes regulated by MEF2 are down-regulated corresponding to increased NRF1 activity. These findings suggest that aberrant transcription factor activity of NRF1, NFE2L2, E2F1, MEF2, and RFX1 may be involved in the pathogenesis and severity of astrocytoma. Further analysis of these TF-regulated gene signatures combined with patient clinical outcomes will help pave the way for next generation targeted therapies and drug combination strategies for GBM patients. Citation Format: Kaumudi Bhawe, Quentin Felty, Changwon Yoo, Deodutta Roy. Aberrant transcription factor activity of NRF1, NFE2L2, E2F1, RFX1, and MEF2 associated with severity of astrocytoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4391.

A high proportion of oncogenes and tumor suppressor genes encode transcription factors. Deregulated expression or activation and inactivation of transcription factors as well as mutations and translocations play critical roles in tumorigenesis. Furthermore, the majority of oncogenic signaling pathways converge on sets of transcription factors that ultimately control gene expression patterns resulting in tumor formation and progression as well as metastasis. Under normal physiological conditions whole sets of genes with similar functions are regulated by highly specific, tightly regulated upstream transcriptional regulators, whereas in cancer aberrant activation of these transcription factors leads to deregulated expression of multiple gene sets associated with tumor development and progression. The activity of these transcription factors can be modulated by multiple mechanisms including posttranslational modifications. Activation or inactivation of transcription factors promote cancer development, cell survival and proliferation and induce tumor angiogenesis. Since many of these transcription factors are inactive under normal physiological conditions and their expression and activities are tightly regulated, these transcription factors represent highly desirable and logical points of therapeutical interference in cancer development and progression. Three major families of transcription factors have emerged as important players in human cancer and are validated targets in drug discovery for cancer therapy: 1) the NF-kappaB and AP-1 families of transcription factors, 2) the STAT family members and 3) the steroids receptors. This review aims to elucidate the divergent molecular mechanisms involved in the deregulated activation of transcription factor signaling in malignant transformation, although additional transcription factor families such as the Ets factors, ATF family members, basic helix-loop-helix transcription factors etc. are additional critical transcriptional regulators in human cancer. We explore new approaches to specifically inhibit these transcription factors in cancer in order to validate them as a drug targets. Efforts to develop novel viral vectors for therapeutic applications are also discussed.