Insulin signaling establishes a developmental trajectory of adipose regulatory T cells.

Systematic characterizations of adipose regulatory T (Treg) cell subsets and their phenotypes remain uncommon. Using single-cell ATAC-sequencing and paired single-cell RNA and T cell receptor (TCR) sequencing to map mouse adipose Treg cells, we identified CD73hiST2lo and CD73loST2hi subsets with distinct clonal expansion patterns. Analysis of TCR-sharing data implied a state transition between CD73hiST2lo and CD73loST2hi subsets. Mechanistically, we revealed that insulin signaling occurs through a HIF-1α-Med23-PPAR-γ axis to drive the transition of CD73hiST2lo into a CD73loST2hi adipose Treg cell subset. Treg cells deficient in insulin receptor, HIF-1α or Med23 have decreased PPAR-γ expression that in turn promotes accumulation of CD73hiST2lo adipose Treg cells and physiological adenosine production to activate beige fat biogenesis. We therefore unveiled a developmental trajectory of adipose Treg cells and its dependence on insulin signaling. Our findings have implications for understanding the dynamics of adipose Treg cell subsets in aged and obese contexts.

The diverse role of RNA methylation in esophageal cancer.

Esophageal cancer is one of the major life-threatening diseases in the world. RNA methylation is the most common post-transcriptional modification and a wide-ranging regulatory system controlling gene expression. Numerous studies have revealed that dysregulation of RNA methylation is critical for cancer development and progression. However, the diverse role of RNA methylation and its regulators in esophageal cancer remains to be elucidated and summarized. In this review, we focus on the regulation of major RNA methylation, including m 6A, m 5C, and m 7G, as well as the expression patterns and clinical implications of its regulators in esophageal cancer. We systematically summarize how these RNA modifications affect the "life cycle" of target RNAs, including mRNA, microRNA, long non-coding RNA, and tRNA. The downstream signaling pathways associated with RNA methylation during the development and treatment of esophageal cancer are also discussed in detail. Further studies on how these modifications function together in the microenvironment of esophageal cancer will draw a clearer picture of the clinical application of novel and specific therapeutic strategies.

MondoA-Thioredoxin-Interacting Protein Axis Maintains Regulatory T-Cell Identity and Function in Colorectal Cancer Microenvironment.

BACKGROUND & AIMS: The metabolic features and function of intratumoral regulatory T cells (Tregs) are ambiguous in colorectal cancer. Tumor-infiltrating Tregs are reprogrammed to exhibit high glucose-depleting properties and adapt to the glucose-restricted microenvironment. The glucose-responsive transcription factor MondoA is highly expressed in Tregs. However, the role of MondoA in colorectal cancer-infiltrating Tregs in response to glucose limitation remains to be elucidated. METHODS: We performed studies using mice, in which MondoA was conditionally deleted in Tregs, and human colorectal cancer tissues. Seahorse and other metabolic assays were used to assess Treg metabolism. To study the role of Tregs in antitumor immunity, we used a subcutaneous MC38 colorectal cancer model and induced colitis-associated colorectal cancer in mice by azoxymethane and dextran sodium sulfate. RESULTS: Our analysis of single-cell RNA sequencing data of patients with colorectal cancer revealed that intratumoral Tregs featured low activity of the MondoA-thioredoxin-interacting protein (TXNIP) axis and increased glucose uptake. Although MondoA-deficient Tregs were less immune suppressive and selectively promoted T-helper (Th) cell type 1 (Th1) responses in a subcutaneous MC38 tumor model, Treg-specific MondoA knockout mice were more susceptible to azoxymethane-DSS-induced colorectal cancer. Mechanistically, suppression of the MondoA-TXNIP axis promoted glucose uptake and glycolysis, induced hyperglycolytic Th17-like Tregs, which facilitated Th17 inflammation, promoted interleukin 17A-induced of CD8+ T-cell exhaustion, and drove colorectal carcinogenesis. Blockade of interleukin 17A reduced tumor progression and minimized the susceptibility of MondoA-deficient mice to colorectal carcinogenesis. CONCLUSIONS: The MondoA-TXNIP axis is a critical metabolic regulator of Treg identity and function in the colorectal cancer microenvironment and a promising target for cancer therapy.

Dynamic control in metabolic engineering: Theories, tools, and applications.

Metabolic engineering has allowed the production of a diverse number of valuable chemicals using microbial organisms. Many biological challenges for improving bio-production exist which limit performance and slow the commercialization of metabolically engineered systems. Dynamic metabolic engineering is a rapidly developing field that seeks to address these challenges through the design of genetically encoded metabolic control systems which allow cells to autonomously adjust their flux in response to their external and internal metabolic state. This review first discusses theoretical works which provide mechanistic insights and design choices for dynamic control systems including two-stage, continuous, and population behavior control strategies. Next, we summarize molecular mechanisms for various sensors and actuators which enable dynamic metabolic control in microbial systems. Finally, important applications of dynamic control to the production of several metabolite products are highlighted, including fatty acids, aromatics, and terpene compounds. Altogether, this review provides a comprehensive overview of the progress, advances, and prospects in the design of dynamic control systems for improved titer, rate, and yield metrics in metabolic engineering.

Heterogeneity coordinates bacterial multi-gene expression in single cells.

For a genetically identical microbial population, multi-gene expression in various environments requires effective allocation of limited resources and precise control of heterogeneity among individual cells. However, it is unclear how resource allocation and cell-to-cell variation jointly shape the overall performance. Here we demonstrate a Simpson's paradox during overexpression of multiple genes: two competing proteins in single cells correlated positively for every induction condition, but the overall correlation was negative. Yet this phenomenon was not observed between two competing mRNAs in single cells. Our analytical framework shows that the phenomenon arises from competition for translational resource, with the correlation modulated by both mRNA and ribosome variability. Thus, heterogeneity plays a key role in single-cell multi-gene expression and provides the population with an evolutionary advantage, as demonstrated in this study.

Perspectives on long pentraxin 3 and rheumatoid arthritis: several potential breakthrough points relying on study foundation of the past.

Rheumatoid arthritis (RA) is a systemic chronic autoimmune inflammatory disease which is mainly characterized by synovitis and results in a severe burden for both the individual and society. To date, the underlying mechanisms of RA are still poorly understood. Pentraxin 3 (PTX3) is a typical long pentraxin protein which has been highly conserved during evolution. Meanwhile, functions as well as properties of PTX3 have been extensively studied. Several studies identified that PTX3 plays a predominate role in infection, inflammation, immunity and tumor. Interestingly, PTX3 has also been verified to be closely associated with development of RA. We therefore accomplished an elaboration of the relationships between PTX3 and RA. Herein, we mainly focus on the associated cell types and cognate cytokines involved in RA, in combination with PTX3. This review infers the insight into the interaction of PTX3 in RA and aims to provide novel clues for potential therapeutic target of RA in clinic.

Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system.

Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based 'library vs library' Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome-lysosome fusion. This concept can also be applied to other systems to screen protein-RNA and protein-DNA interactions and delineate signaling landscape in cells.

Dynamic metabolic control: towards precision engineering of metabolism.

Advances in metabolic engineering have led to the synthesis of a wide variety of valuable chemicals in microorganisms. The key to commercializing these processes is the improvement of titer, productivity, yield, and robustness. Traditional approaches to enhancing production use the "push-pull-block" strategy that modulates enzyme expression under static control. However, strains are often optimized for specific laboratory set-up and are sensitive to environmental fluctuations. Exposure to sub-optimal growth conditions during large-scale fermentation often reduces their production capacity. Moreover, static control of engineered pathways may imbalance cofactors or cause the accumulation of toxic intermediates, which imposes burden on the host and results in decreased production. To overcome these problems, the last decade has witnessed the emergence of a new technology that uses synthetic regulation to control heterologous pathways dynamically, in ways akin to regulatory networks found in nature. Here, we review natural metabolic control strategies and recent developments in how they inspire the engineering of dynamically regulated pathways. We further discuss the challenges of designing and engineering dynamic control and highlight how model-based design can provide a powerful formalism to engineer dynamic control circuits, which together with the tools of synthetic biology, can work to enhance microbial production.

Releasing the potential power of terpene synthases by a robust precursor supply platform.

Terpenoids represent the largest family of natural products. Their structural diversity is largely due to variable skeletons generated by terpene synthases. However, terpene skeletons found in nature are much more than those generated from known terpene synthases. Most promiscuous terpene synthases (i.e. those that can generate more than one product) have not been comprehensively characterised. Here, we first demonstrated that the promiscuous terpene synthases can produce more variable terpenoids in vivo by converting precursor polyisoprenoid diphosphates of different lengths (C10, C15, C20, C25). To release the synthetic potential of these enzymes, we integrated the engineered MVA pathway, combinatorial biosynthesis, and point mutagenesis to depict the comprehensive product profiles. In total, eight new terpenoids were characterised by NMR and three new skeletons were revealed. This work highlights the key role of metabolic engineering for natural product discovery.

Immune microenvironment heterogeneity of concurrent adenocarcinoma and squamous cell carcinoma in multiple primary lung cancers.

The molecular profiles and tumor immune microenvironment (TIME) of multiple primary lung cancers (MPLCs) presenting as concurrent lung adenocarcinoma (ADC) and squamous cell carcinoma (SQCC) remain unknown. We aimed to clarify these factors. We performed whole-exome sequencing (WES), RNA sequencing (RNA-Seq), and multiplex immunohistochemistry (mIHC) for five patients with concurrent ADC and SQCC. We found the genetic mutations were similar between ADC and SQCC groups. RNA-Seq revealed that the gene expression and pathways enriched in ADC and SQCC groups were quite different. Gene set enrichment analysis (GSVA) showed that nine gene sets were significantly differentially expressed between the ADC and SQCC groups (p < 0.05), with four gene sets relevant to squamous cell features upregulated in the SQCC group and five gene sets upregulated in the ADC group. Reactome enrichment analysis of differentially expressed genes showed that the immune function-related pathways, including programmed cell death, innate immune system, interleukin-12 family signaling, and toll-like receptor 2/4 pathways, etc. were significantly enriched. Transcriptomic TIME analysis, with mIHC in patient specimens and in vivo validation, showed tumor-infiltrating immune cells were significantly more enriched and diverse in ADC, especially CD8 + T cells. Our results revealed that the transcriptomic profiles and TIME features were quite different between ADC and SQCC lesions. ADC lesions exhibited a more active TIME than SQCC lesions in MPLCs.

FOXP3+ regulatory T cell perturbation mediated by the IFNγ-STAT1-IFITM3 feedback loop is essential for anti-tumor immunity.

Targeting tumor-infiltrating regulatory T cells (Tregs) is an efficient way to evoke an anti-tumor immune response. However, how Tregs maintain their fragility and stability remains largely unknown. IFITM3 and STAT1 are interferon-induced genes that play a positive role in the progression of tumors. Here, we showed that IFITM3-deficient Tregs blunted tumor growth by strengthening the tumor-killing response and displayed the Th1-like Treg phenotype with higher secretion of IFNγ. Mechanistically, depletion of IFITM3 enhances the translation and phosphorylation of STAT1. On the contrary, the decreased IFITM3 expression in STAT1-deficient Tregs indicates that STAT1 conversely regulates the expression of IFITM3 to form a feedback loop. Blocking the inflammatory cytokine IFNγ or directly depleting STAT1-IFITM3 axis phenocopies the restored suppressive function of tumor-infiltrating Tregs in the tumor model. Overall, our study demonstrates that the perturbation of tumor-infiltrating Tregs through the IFNγ-IFITM3-STAT1 feedback loop is essential for anti-tumor immunity and constitutes a targetable vulnerability of cancer immunotherapy.

Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces.

The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces.

Genome-wide promoter responses to CRISPR perturbations of regulators reveal regulatory networks in Escherichia coli.

Elucidating genome-scale regulatory networks requires a comprehensive collection of gene expression profiles, yet measuring gene expression responses for every transcription factor (TF)-gene pair in living prokaryotic cells remains challenging. Here, we develop pooled promoter responses to TF perturbation sequencing (PPTP-seq) via CRISPR interference to address this challenge. Using PPTP-seq, we systematically measure the activity of 1372 Escherichia coli promoters under single knockdown of 183 TF genes, illustrating more than 200,000 possible TF-gene responses in one experiment. We perform PPTP-seq for E. coli growing in three different media. The PPTP-seq data reveal robust steady-state promoter activities under most single TF knockdown conditions. PPTP-seq also enables identifications of, to the best of our knowledge, previously unknown TF autoregulatory responses and complex transcriptional control on one-carbon metabolism. We further find context-dependent promoter regulation by multiple TFs whose relative binding strengths determined promoter activities. Additionally, PPTP-seq reveals different promoter responses in different growth media, suggesting condition-specific gene regulation. Overall, PPTP-seq provides a powerful method to examine genome-wide transcriptional regulatory networks and can be potentially expanded to reveal gene expression responses to other genetic elements.

Bi-terminal fusion of intrinsically-disordered mussel foot protein fragments boosts mechanical strength for protein fibers.

Microbially-synthesized protein-based materials are attractive replacements for petroleum-derived synthetic polymers. However, the high molecular weight, high repetitiveness, and highly-biased amino acid composition of high-performance protein-based materials have restricted their production and widespread use. Here we present a general strategy for enhancing both strength and toughness of low-molecular-weight protein-based materials by fusing intrinsically-disordered mussel foot protein fragments to their termini, thereby promoting end-to-end protein-protein interactions. We demonstrate that fibers of a ~60 kDa bi-terminally fused amyloid-silk protein exhibit ultimate tensile strength up to 481 ± 31 MPa and toughness of 179 ± 39 MJ*m-3, while achieving a high titer of 8.0 ± 0.70 g/L by bioreactor production. We show that bi-terminal fusion of Mfp5 fragments significantly enhances the alignment of ß-nanocrystals, and intermolecular interactions are promoted by cation-π and π-π interactions between terminal fragments. Our approach highlights the advantage of self-interacting intrinsically-disordered proteins in enhancing material mechanical properties and can be applied to a wide range of protein-based materials.

A risk score combining co-expression modules related to myeloid cells and alternative splicing associates with response to PD-1/PD-L1 blockade in non-small cell lung cancer.

Background: Comprehensive analysis of transcriptomic profiles of non-small cell lung cancer (NSCLC) may provide novel evidence for biomarkers associated with response to PD-1/PD-L1 immune checkpoint blockade (ICB). Methods: We utilized weighted gene co-expression network analysis (WGCNA) to analyze transcriptomic data from two NSCLC datasets from Gene Expression Omnibus (GSE135222 and GSE126044) that involved patients received ICB treatment. We evaluated the correlation of co-expression modules with ICB responsiveness and functionally annotated ICB-related modules using pathway enrichment analysis, single-cell RNA sequencing, flow cytometry and alternative splicing analysis. We built a risk score using Lasso-COX regression based on hub genes from ICB-related modules. We investigated the alteration of tumor microenvironment between high- and low- risk groups and the association of the risk score with previously established predictive biomarkers. Results: Our results identified a black with positive correlation and a blue module with negative correlation to ICB responsiveness. The black module was enriched in pathway of T cell activation and antigen processing and presentation, and the genes assigned to it were consistently expressed on myeloid cells. We observed decreased alternative splicing events in samples with high signature scores of the blue module. The Lasso-COX analysis screened out three genes (EVI2B, DHX9, HNRNPM) and constructed a risk score from the hub genes of the two modules. We validated the predictive value of the risk score for poor response to ICB therapy in an in-house NSCLC cohort and a pan-cancer cohort from the KM-plotter database. The low-risk group had more immune-infiltrated microenvironment, with higher frequencies of precursor exhausted CD8+ T cells, tissue-resident CD8+ T cells, plasmacytoid dendritic cells and type 1 conventional dendritic cells, and a lower frequency of terminal exhausted CD8+ T cells, which may explain its superior response to ICB therapy. The significant correlation of the risk score to gene signature of tertiary lymphoid structure also implicated the possible mechanism of this predictive biomarker. Conclusions: Our study identified two co-expression modules related to ICB responsiveness in NSCLC and developed a risk score accordingly, which could potentially serve as a predictive biomarker for ICB response.

Advances in genome-scale metabolic models of industrially important fungi.

Many fungal species have been used industrially for production of biofuels and bioproducts. Developing strains with better performance in biomanufacturing contexts requires a systematic understanding of cellular metabolism. Genome-scale metabolic models (GEMs) offer a comprehensive view of interconnected pathways and a mathematical framework for downstream analysis. Recently, GEMs have been developed or updated for several industrially important fungi. Some of them incorporate enzyme constraints, enabling improved predictions of cell states and proteome allocation. Here, we provide an overview of these newly developed GEMs and computational methods that facilitate construction of enzyme-constrained GEMs and utilize flux predictions from GEMs. Furthermore, we highlight the pivotal roles of these GEMs in iterative design-build-test-learn cycles, ultimately advancing the field of fungal biomanufacturing.

High-dimensional single-cell proteomics analysis of esophageal squamous cell carcinoma reveals dynamic alterations of the tumor immune microenvironment after neoadjuvant therapy.

BACKGROUND: Dynamic alterations of the tumor immune microenvironment in esophageal squamous cell carcinoma (ESCC) after different neoadjuvant therapies were understudied. METHODS: We used mass cytometry with a 42-antibody panel for 6 adjacent normal esophageal mucosa and 26 tumor samples (treatment-naïve, n=12; postneoadjuvant, n=14) from patients with ESCC. Single-cell RNA sequencing of previous studies and bulk RNA sequencing from The Cancer Genome Atlas were analyzed, flow cytometry, immunohistochemistry, and immunofluorescence analyses were performed. RESULTS: Poor tumor regression was observed in the neoadjuvant chemotherapy group. Radiotherapy-based regimens enhanced CD8+ T cells but diminished regulatory T cells and promoted the ratio of effector memory to central memory T cells. Immune checkpoint blockade augmented NK cell activation and cytotoxicity by increasing the frequency of CD16+ NK cells. We discovered a novel CCR4+CCR6+ macrophage subset that correlated with the enrichment of corresponding chemokines (CCL3/CCL5/CCL17/CCL20/CCL22). We established a CCR4/CCR6 chemokine-based model that stratified ESCC patients with differential overall survival and responsiveness to neoadjuvant chemoradiotherapy combined with immunotherapy, which was validated in two independent cohorts of esophageal cancer with neoadjuvant treatment. CONCLUSIONS: This work reveals that neoadjuvant therapy significantly regulates the cellular composition of the tumor immune microenvironment in ESCC and proposes a potential model of CCR4/CCR6 system to predict the benefits from neoadjuvant chemoradiotherapy combined with immunotherapy.

Potential roles of PIWI-interacting RNAs in lung cancer.

Lung cancer is a malignant tumor with high morbidity and mortality in the world today. Emerging evidence suggests that PIWI-interacting RNAs (piRNAs) are aberrantly expressed in various human cancers, including lung cancer. Despite of the poorly understood mechanism, piRNAs may work as carcinogenic roles or tumor suppressors by engaging in a variety of cancer-associated signaling pathways. Therefore, they might serve as potential therapeutic targets, diagnostic indicators, or prognostic indicators in lung cancer. This review will discuss the new findings of piRNAs, including their biosynthetic processes, mechanisms of gene suppression, and the significance of these piRNAs tested in lung cancer samples to determine their involvement in cancer progression.

Considerations for the Surgical Management of Thoracic Cancers During the COVID-19 Pandemic: Rational Strategies for Thoracic Surgeons.

Objective: The novel Coronavirus Disease 2019 (COVID-19) has resulted in a global health crisis since first case was identified in December 2019. As the pandemic continues to strain global public health systems, elective surgeries for thoracic cancer, such as early-stage lung cancer and esophageal cancer (EC), have been postponed due to a shortage of medical resources and the risk of nosocomial transmission. This review is aimed to discuss the influence of COVID-19 on thoracic surgical practice, prevention of nosocomial transmission during the pandemic, and propose modifications to the standard practices in the surgical management of different thoracic cancer. Methods: A literature search of PubMed, Medline, and Google Scholar was performed for articles focusing on COVID-19, early-stage lung cancer, and EC prior to 1 July 2021. The evidence from articles was combined with our data and experience. Results: We review the challenges in the management of different thoracic cancer from the perspectives of thoracic surgeons and propose rational strategies for the diagnosis and treatment of early-stage lung cancer and EC during the COVID-19 pandemic. Conclusions: During the COVID-19 pandemic, the optimization of hospital systems and medical resources is to fight against COVID-19. Indolent early lung cancers, such as pure ground-glass nodules/opacities (GGOs), can be postponed with a lower risk of progression, while selective surgeries of more biologically aggressive tumors should be prioritized. As for EC, we recommend immediate or prioritized surgeries for patients with stage Ib or more advanced stage and patients after neoadjuvant therapy. Routine COVID-19 screening should be performed preoperatively before thoracic surgeries. Prevention of nosocomial transmission by providing appropriate personal protective equipment (PPE), such as N-95 respirator masks with eye protection to healthcare workers, is necessary.

Anti-tumor effects of dual PI3K-HDAC inhibitor CUDC-907 on activation of ROS-IRE1α-JNK-mediated cytotoxic autophagy in esophageal cancer.

BACKGROUND: PI3K-Akt pathway activation and the expression of histone deacetylases (HDACs) are highly increased in esophageal cancer, suggesting that inhibition of such targets may be a viable therapeutic strategy. Herein, we aimed to evaluate the anti-tumor effect of CUDC-907, a dual PI3K-HDAC inhibitor, in esophageal squamous cell carcinoma (ESCC). METHODS: The anti-tumor effects of CUDC-907 in ESCC were evaluated using cell counting kit-8, flow cytometry, and western blot. mRNA-sequencing was used to explore the mechanism underlying CUDC-907 anti-tumor effects. The relations of reactive oxygen species (ROS), lipocalin 2 (LCN2), and CUDC-907 were determined by flow cytometry, rescue experiments, and western blot. The activation of the IRE1α-JNK-CHOP signal cascade was confirmed by western blot. The in vivo inhibitory effects of CUDC-907 were examined by a subcutaneous xenograft model in nude mice. RESULTS: CUDC-907 displayed effective inhibition in the proliferation, migration, and invasion of ESCC cells. Through an mRNA-sequencing and functional enrichment analysis, autophagy was found to be associated with cancer cells death. CUDC-907 not only inhibited the PI3K-Akt-mTOR pathways to result in autophagy, but also induced ROS accumulation to activate IRE1α-JNK-CHOP-mediated cytotoxic autophagy by downregulating LCN2 expression. Consistently, the in vivo anti-tumor effects of CUDC-907 accompanied by the downregulated expression of p-mTOR and LCN2 and upregulated expression of p-IRE1α and LC3B-II were evaluated in a xenograft mouse model. CONCLUSION: Our findings suggested the clinical development and administration of CUDC-907 might act as a novel treatment strategy for ESCC. A more in-depth understanding of the anti-tumor effect of CUDC-907 in ESCC will benefit the clinically targeted treatment of ESCC.