Dissecting the single-cell transcriptome network underlying esophagus non-malignant tissues and esophageal squamous cell carcinoma

Targeting glycolysis in esophageal squamous cell carcinoma: single-cell and multi-omics insights for risk stratification and personalized therapy

Background

Esophageal squamous cell carcinoma (ESCC) is closely linked to aberrant glycolytic metabolism, a hallmark of cancer progression, immune evasion, and therapy resistance. This study employs single-cell transcriptomics and multi-omics approaches to unravel glycolysis-mediated mechanisms in ESCC, with a focus on risk stratification and therapeutic opportunities.

Methods

Data from TCGA and GEO databases were integrated with single-cell RNA sequencing, bulk RNA sequencing, as well as clinical datasets to investigate glycolysis-associated cell subtypes and their clinical implications in ESCC. Analytical approaches encompassed cell subtype annotation, cell-cell communication network analysis, and gene regulatory network modeling. A glycolysis-related risk score model was built via non-negative matrix factorization (NMF) and Cox regression, and then experimentally verified through Western blotting. Drug sensitivity analyses were carried out to explore potential therapeutic strategies.

Results

Single-cell analysis identified epithelial cells as the dominant glycolysis-active subtype, and tumor tissues showed significantly higher glycolytic activity than adjacent normal tissues. Among malignant epithelial subpopulations, IGFBP3+Epi (IGFBP3-expressing epithelial cells) and LHX9+Epi (LHX9-expressing epithelial cells) had elevated glycolysis levels, which correlated with poor prognosis, immune suppression, and changes in the tumor microenvironment. The seven-gene glycolysis-based risk score model divided patients into high- and low-risk groups, demonstrating strong prognostic performance. Drug sensitivity analysis showed high-risk patients were more responsive to Navitoclax as well as Rapamycin, but low-risk ones were more sensitive to Afatinib and Erlotinib, highlighting the model's usefulness in guiding personalized treatment.

Conclusion

This research emphasizes the crucial role of glycolysis in ESCC progression a well as immune modulation, offering a novel glycolysis-related risk score model with significant prognostic and therapeutic implications. These findings provide a basis for risk-based stratification and tailored therapeutic strategies, advancing precision medicine in ESCC.

Deciphering the generation of heterogeneity in esophageal squamous cell carcinoma metastasis via single-cell multiomics analysis

BACKGROUND

Chromatin accessibility plays a crucial role in mediating transcriptional dysregulation and heterogeneity in Esophageal Squamous Cell Carcinoma (ESCC). Examining the chromatin accessibility of ESCC at single-cell level is imperative to understand how it activates oncogenes and contributes to the onset and metastasis of ESCC.

METHODS

We performed single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) on cancerous and adjacent noncancerous tissues from four ESCC patients who were pathological staged as T1a, T2b, T3b, or T4a, to investigate whether regulatory elements are pivotal in instigating cellular heterogeneity during ESCC metastasis. In conjunction, we integrated these data with 55 scRNA-seq datasets, ChIP-seq or CUT&Tag sequencing data, Hi-C sequencing data, bulk RNA-seq data, and bulk ATAC-seq data from ESCC cell lines to dissect the mechanisms underlying the heterogeneity of ESCC and tumor microenvironment (TME).

RESULTS

Our study identified enhancer-specific activation within epithelial cells orchestrated by the three-dimensional structure of chromatin that regulates SERPINH1 transcription, and promotes the epithelial-mesenchymal transition (EMT) and metastasis of ESCC. Additionally, chromatin element activation facilitated the expression of TNFSF4 in CD8 + exhausted T cells, thereby activating Tregs. Furthermore, we observed that chromatin accessibility promoted the differentiation of tumor-associated macrophages (TAMs) and cancer associated fibroblasts (CAFs).

CONCLUSIONS

In summary, utilizing multiomics analyses, we have revealed chromatin accessibility maps and illuminated the intricate molecular mechanisms that underlie cellular heterogeneity during ESCC metastasis, offering valuable insights to further advance research on tumor progression and deterioration.

Unraveling the tumor microenvironment of esophageal squamous cell carcinoma through single-cell sequencing: A comprehensive review

Esophageal squamous cell carcinoma (ESCC) is a highly heterogeneous and aggressive malignancy. The progression, invasiveness, and metastatic potential of ESCC are shaped by a multitude of cells within the tumor microenvironment (TME), including tumor cells, immune cells, endothelial cells, as well as fibroblasts and other cell types. Recent advancements in single-cell sequencing technologies have significantly enhanced our comprehension of the diverse landscape of ESCC. Single-cell multi-omics technology, particularly single-cell transcriptome sequencing, have shed light on the expression profiles of individual cells and the molecular characteristics of distinct tumor cell populations. This review summarizes the latest literature on single-cell research in the field of ESCC, aiming to elucidate the heterogeneity of tumor cells, immune cells, and stromal cells at the single-cell level. Furthermore, it explores the impact of cellular interactions within the TME on the progression of ESCC. By compiling a comprehensive overview of single-cell omics research on ESCC, this article aims to enhance our understanding of ESCC diagnosis and treatment by elucidating the intricate interplay within the TME. It explores the cellular composition, spatial arrangement, and functional attributes of the ESCC TME, offering potential therapeutic targets and biomarkers for personalized treatment strategies.

Single-cell RNA sequencing and spatial transcriptomics of esophageal squamous cell carcinoma with lymph node metastases

Esophageal squamous cell carcinoma (ESCC) patients often face a grim prognosis due to lymph node metastasis. However, a comprehensive understanding of the cellular and molecular characteristics of metastatic lymph nodes in ESCC remains elusive. In this study involving 12 metastatic ESCC patients, we employed single-cell sequencing, spatial transcriptomics (ST), and multiplex immunohistochemistry (mIHC) to explore the spatial and molecular attributes of primary tumor samples, adjacent tissues, metastatic and non-metastatic lymph nodes. The analysis of 161,333 cells revealed specific subclusters of epithelial cells that were significantly enriched in metastatic lymph nodes, suggesting pro-metastatic characteristics. Furthermore, stromal cells in the tumor microenvironment, including MMP3+IL24+ fibroblasts, APLN+ endothelial cells, and CXCL12+ pericytes, were implicated in ESCC metastasis through angiogenesis, collagen production, and inflammatory responses. Exhausted CD8+ T cells in a cycling status were notably prevalent in metastatic lymph nodes, indicating their potential role in facilitating metastasis. We identified distinct cell-cell communication networks and specific ligand-receptor pathways. Our findings were validated through a spatial transcriptome map and mIHC. This study enhances our comprehension of the cellular and molecular aspects of metastatic lymph nodes in ESCC patients, offering potential insights into novel therapeutic strategies for these individuals.

Spatial transcriptome profiling identifies DTX3L and BST2 as key biomarkers in esophageal squamous cell carcinoma tumorigenesis

BACKGROUND

Understanding the stepwise progression of esophageal squamous cell carcinoma (ESCC) is crucial for developing customized strategies for early detection and optimal clinical management. Herein, we aimed to unravel the transcriptional and immunologic alterations occurring during malignant transformation and identify clinically significant biomarkers of ESCC.

METHODS

Digital spatial profiling (DSP) was performed on 11 patients with early-stage ESCC (pT1) to explore the transcriptional alterations in epithelial, immune cell, and non-immune cell stromal compartments across regions of distinct histology, including normal tissues, low- and high-grade dysplasia, and cancerous tissues. Furthermore, single-cell spatial transcriptomics was performed using the CosMx Spatial Molecular Imaging (SMI) system on 4 additional patients with pT1 ESCC. Immunohistochemical (IHC) analysis was performed on consecutive histological sections of 20 pT1 ESCCs. Additionally, public bulk and single-cell RNA-sequencing (scRNA-seq) datasets were analyzed, and in vitro and in vivo functional studies were conducted.

RESULTS

Spatial transcriptional reprogramming and dynamic cell signaling pathways that determined ESCC progression were delineated. Increased infiltration of macrophages from normal tissues through dysplasia to cancerous tissues occurred. Macrophage subtypes were characterized using the scRNA-seq dataset. Cell-cell communication analysis of scRNA-seq and SMI data indicated that the migration inhibitory factor (MIF)-CD74 axis may exhibit pro-tumor interactions between macrophages and epithelial cells. DSP, SMI, and IHC data demonstrated that DTX3L expression in epithelial cells and BST2 expression in stromal cells increased gradually with ESCC progression. Functional studies demonstrated that DTX3L or BST2 knockdown inhibited ESCC proliferation and migration and decreased M2 polarization of tumor-associated macrophages.

CONCLUSIONS

Spatial profiling comprehensively characterized the molecular and immunological hallmarks from normal tissue to ESCC, guiding the way to a deeper understanding of the tumorigenesis and progression of this disease and contributing to the prevention of ESCC. Within this exploration, we uncovered biomarkers that exhibit a robust correlation with ESCC progression, offering potential new avenues for insightful therapeutic approaches.

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Development and Validation of an 18F-FDG PET/CT-based Radiomics Nomogram for Predicting the Prognosis of Patients with Esophageal Squamous Cell Carcinoma

RATIONALE AND OBJECTIVES

The aim of this study was to develop and validate a nomogram, integrating clinical factors and radiomics features, capable of predicting overall survival (OS) in patients diagnosed with esophageal squamous cell carcinoma (ESCC).

METHODS

In this study, we retrospectively analyzed the case data of 130 patients with ESCC who underwent 18F-FDG PET/CT before treatment. Radiomics features associated with OS were screened by univariate Cox regression (p < 0.05). Further selection was performed by applying the least absolute shrinkage and selection operator Cox regression to generate the weighted Radiomics-score (Rad-score). Independent clinical risk factors were obtained by multivariate Cox regression, and a nomogram was constructed by combining Rad-score and independent risk factors. The predictive performance of the model for OS was assessed using the time-dependent receiver operating characteristic curve, concordance index (C-index), calibration curve, and decision curve analysis.

RESULTS

Five radiomics features associated with prognosis were finally screened, and a Rad-score was established. Multivariate Cox regression analysis revealed that surgery and clinical M stage were identified as independent risk factors for OS in ESCC. The combined clinical-radiomics nomogram exhibited C-index values of 0.768 (95% CI: 0.699-0.837) and 0.809 (95% CI: 0.695-0.923) in the training and validation cohorts, respectively. Ultimately, calibration curves and decision curves for the 1-, 2-, and 3-year OS demonstrated the satisfactory prognostic prediction and clinical utility of the nomogram.

CONCLUSION

The developed nomogram, leveraging 18F-FDG PET/CT radiomics and clinically independent risk factors, demonstrates a reliable prognostic prediction for patients with ESCC, potentially serving as a valuable tool for guiding and optimizing clinical treatment decisions in the future.

Single-cell transcriptomic landscape deciphers olfactory neuroblastoma subtypes and intra-tumoral heterogeneity

Olfactory neuroblastoma (ONB) is a rare malignancy known to originate from the olfactory epithelium. The complex tumor ecosystem of this pathology remains unclear. Here, we explored the cellular components within ten ONB tumors and one olfactory mucosa sample based on single-cell RNA profiles. We showed the intra-tumoral heterogeneity by identifying five unique expression programs among malignant epithelial cells. A distinct three-classification system (neural, basal, mesenchymal) for ONB was established according to the distinguished gene expression patterns. Biomarkers for categorizing bulk tumors into uncharacterized subtypes were elucidated. Different responses towards certain chemotherapy regimens could be cautiously inferred according to the molecular features representing the three tumor types, thus helping with precision chemotherapy. We also analyzed subclusters of the tumor microenvironment (TME) and the interactions among different cell types within the TME. The relative abundance of immunosuppressive tumor-associated macrophages suggests potential benefits of immunotherapies targeting macrophages.

Targeting esophageal carcinoma: molecular mechanisms and clinical studies

Esophageal cancer (EC) is identified as a predominant health threat worldwide, with its highest incidence and mortality rates reported in China. The complex molecular mechanisms underlying EC, coupled with the differential incidence of esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) across various regions, highlight the necessity for in-depth research targeting molecular pathogenesis and innovative treatment strategies. Despite recent progress in targeted therapy and immunotherapy, challenges such as drug resistance and the lack of effective biomarkers for patient selection persist, impeding the optimization of therapeutic outcomes. Our review delves into the molecular pathology of EC, emphasizing genetic and epigenetic alterations, aberrant signaling pathways, tumor microenvironment factors, and the mechanisms of metastasis and immune evasion. We further scrutinize the current landscape of targeted therapies, including the roles of EGFR, HER2, and VEGFR, alongside the transformative impact of ICIs. The discussion extends to evaluating combination therapies, spotlighting the synergy between targeted and immune-mediated treatments, and introduces the burgeoning domain of antibody-drug conjugates, bispecific antibodies, and multitarget-directed ligands. This review lies in its holistic synthesis of EC's molecular underpinnings and therapeutic interventions, fused with an outlook on future directions including overcoming resistance mechanisms, biomarker discovery, and the potential of novel drug formulations.

Single-cell sequencing reveals immune features of treatment response to neoadjuvant immunochemotherapy in esophageal squamous cell carcinoma

Neoadjuvant immunochemotherapy (nICT) has dramatically changed the treatment landscape of operable esophageal squamous cell carcinoma (ESCC), but factors influencing tumor response to nICT are not well understood. Here, using single-cell RNA sequencing paired with T cell receptor sequencing, we profile tissues from ESCC patients accepting nICT treatment and characterize the tumor microenvironment context. CXCL13+CD8+ Tex cells, a subset of exhausted CD8+ T cells, are revealed to highly infiltrate in pre-treatment tumors and show prominent progenitor exhaustion phenotype in post-treatment samples from responders. We validate CXCL13+CD8+ Tex cells as a predictor of improved response to nICT and reveal CXCL13 to potentiate anti-PD-1 efficacy in vivo. Post-treatment tumors from non-responders are enriched for CXCL13+CD8+ Tex cells with notably remarkable exhaustion phenotype and TNFRSF4+CD4+ Tregs with activated immunosuppressive function and a significant clone expansion. Several critical markers for therapeutic resistance are also identified, including LRRC15+ fibroblasts and SPP1+ macrophages, which may recruit Tregs to form an immunosuppressive landscape. Overall, our findings unravel immune features of distinct therapeutic response to nICT treatment, providing a rationale for optimizing individualized neoadjuvant strategy in ESCC.

Prognostic modeling and Emerging therapeutic targets Unveiled through single-cell sequencing in esophageal squamous Cell carcinoma

ESCC presents a significant global health challenge due to its high mortality rates and varying responses to treatment. This underscores the critical need for novel diagnostic and predictive biomarkers to improve treatment outcomes. Initially, we conducted single-cell transcriptome sequencing on a total of 128,688 cells obtained from 10 patients as part of our research. Utilizing machine learning and cross-validation techniques, we developed a model incorporating 12 genes that distinguish malignant cells from non-malignant ones. In vitro, we explored the effects of IGFBP2 knockdown on the proliferation, invasion, and migration of ESCC cells. The clinical relevance of IGFBP2 was confirmed through IHC and Kaplan-Meier survival analyses. Furthermore, using bioinformatics tools such as GSVA and xCell on public databases, we discovered that high expression of IGFBP2 is associated with an immunosuppressive tumor microenvironment in ESCC, characterized by reduced CD8+ T cell infiltration. This was validated then through IHC. In summary, our study integrates single-cell sequencing and sophisticated computational techniques to highlight IGFBP2 as a promising biomarker and therapeutic target in ESCC.

Impaired TGF-β signaling via AHNAK family mutations elicits an esophageal cancer subtype with sensitivities to genotoxic therapy and immunotherapy

BACKGROUND

Genome instability (GI) is a hallmark of esophageal squamous cell carcinoma (ESCC) while factors affecting GI remain unclear.

METHODS

Here, we aimed to characterize genomic events representing specific mechanisms of GI based on 201 ESCC samples and validated our findings at the patient, single-cell and cancer cell-line levels, including a newly generated multi-omics dataset of the trial NCT04006041.

RESULTS

A two-gene (AHNAK and AHNAK2) mutation signature was identified to define the "AHNAK1/2-mutant" cancer subtype. Single-cell-assisted multi-omics analysis showed that this subtype had a higher neoantigen load, active antigen presentation, and proficient CD8 + T cell infiltrations, which were validated at pan-cancer levels. Mechanistically, AHNAK1/2-mutant ESCC was characterized by impaired response of TGF-β and the inefficient alternative end-join repair (Alt-EJ) that might promote GI. Knockdown of AHNAK in ESCC cell lines resulted in more Alt-EJ events and increased sensitivities to cisplatin. Furthermore, this two-gene signature accurately predicted better responses to DNA-damaging therapy in various clinical settings (HR ≈ 0.25). The two-gene signature predicted higher pCR rates in ESCCs receiving neoadjuvant immunotherapy-involved treatment. Finally, a molecular classification scheme was built and outperformed established molecular typing models in the prognosis stratification of ESCC patients.

CONCLUSION

Our study extended our understanding of the AHNAK family in promoting GI and selecting treatment responders of ESCC.

Single-cell transcriptomic analysis reveals a decrease in the frequency of macrophage-RGS1high subsets in patients with osteoarticular tuberculosis

BACKGROUND

Cell subsets differentially modulate host immune responses to Mycobacterium tuberculosis (MTB) infection. However, the nature and functions of these subsets against osteoarticular tuberculosis (OTB) are unclear. Here, we aimed to understand the phenotypes and functions of immune cell subsets in patients with OTB using single-cell RNA sequencing (scRNA-Seq).

METHODS

Pathological and healthy adjacent tissues were isolated from patients with OTB and subjected to scRNA-Seq. Unsupervised clustering of cells was performed based on gene expression profiles, and uniform manifold approximation and projection was used for clustering visualization.

RESULTS

Thirteen cell subsets were identified in OTB tissues. scRNA-seq datasets of patients and healthy controls (HCs) showed that infection changed the frequency of immune cell subsets in OTB tissues. Myeloid cell examination revealed nine subsets. The frequency of macrophage-RGS1high subsets decreased in OTB tissues; this increased MTB susceptibility in an SLC7A11/ferroptosis-dependent manner. Immunohistochemistry assays and flow cytometry for patients with OTB and osteoarticular bacterial infection (OBI) and HCs verified that the frequency of macrophage-RGS1high subset decreased in OTB tissues and blood samples, thereby distinguishing patients with OTB from HCs and patients with OBI.

CONCLUSION

The macrophage-RGS1high subset levels were decreased in patients with OTB, and would be up-regulated after effective treatment. Therefore, the clinical significance of this study is to discover that macrophage-RGS1high subset may serve as a potential biomarker for OTB diagnosis and treatment efficacy monitoring.

B cells present a double-sided effect in digestive system tumors: a review for tumor microenvironment

Over the past few years, there has been an increasing interest in investigating tumor-infiltrating lymphocytes. B lymphocytes (B cells) are extensively distributed within tertiary lymphoid structure (TLS) as multifaceted subgroups and are intimately linked to the anti-tumor properties of TLS, as well as the survival and prognostication of individuals. While the investigation of T lymphocytes in the TLS has advanced to the level of clinical practice, the study of B cells remains limited. The principal impediment to the utilization of B cells in immunotherapy is their notable dual impact on tumors. Compared with tumors in other parts and systems, the function of B cells in the microenvironment of digestive system tumors to promote tumors proliferation, differentiation and migration cannot be ignored. Therefore, this review collects the studies of B cell subsets in tumor microenvironments, particularly related single cell sequencing research. The multifaceted role and function of B cells are investigated in esophageal, liver, colorectal, gastric and pancreatic cancers. And through the identification of B cell subsets and specific markers, this review attempts to explain the reasons why B cells produce different tumor-promoting effects in those tumors. The insights gleaned from this review may provide potential help and support the development of B cell-based immunotherapies.

Tumor niche network-defined subtypes predict immunotherapy response of esophageal squamous cell cancer

Despite the promising outcomes of immune checkpoint inhibitors (ICIs), resistance to ICI presents a new challenge. Therefore, selecting patients for specific ICI applications is crucial for maximizing therapeutic efficacy. Herein, we curated 69 human esophageal squamous cell cancer (ESCC) patients' tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network and transcriptional signatures of T cells and myeloid cells define distinct ESCC subtypes characterized by T cell exhaustion, and interleukin (IL) and interferon (IFN) signaling. Furthermore, this approach classifies ESCC patients into ICI responders and non-responders, as validated by whole tumor transcriptomes and liquid biopsy-based single-cell transcriptomes of anti-PD-1 ICI responders and non-responders. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and potentially predicting ICI responses in ESCC patients.

Single-cell RNA sequencing reveals the MIF-ACKR3 receptor-ligand interaction between iCAFs and tumor cells in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor of the gastrointestinal tract with a high morbidity and mortality rate. The heterogeneity of ESCC poses challenges in treatment and contributes to the poor prognosis of patients. Therefore, it is crucial to gain a better understanding of the tumor microenvironment (TME) heterogeneity and identify novel therapeutic targets.

METHODS

To solve this problem, we performed a single-cell RNA sequencing (scRNA-seq) analysis of ESCC samples obtained from the GEO database.

RESULTS

A total of 31,283 single cells were categorized into nine cell types, which included four non-immune cells (epithelial cells, endothelial cells, fibroblasts, schwann cells) and five immune cells (T cells, macrophages, mast cells, neutrophils, B cells). Our study revealed the presence of immunosuppressive tumor microenvironments in ESCC. We have also identified not only inflammatory cancer-associated fibroblast (iCAFs) and myofibroblastic cancer-associated fibroblasts (myCAFs) but also a subset of antigen presenting cancer-associated fibroblasts (apCAFs) which express high levels of HLA class II molecules in ESCC. Furthermore, our analysis of cell communication showed up-regulation of MIF-ACKR3 interaction between iCAFs and tumor cells in tumors compared to normal tissues. Finally, it was demonstrated that macrophage migration inhibitory factor (MIF) facilitates tumor cell migration and invasion through interacting with ACKR3 in vitro.

CONCLUSIONS

This study exposes the features of the tumor microenvironment of ESCC via scRNA-seq and examines the dynamics of various cellular subpopulations, thus facilitating the identification of future therapeutic targets for ESCC.

Cuproptosis/OXPHOS tendency prediction of prognosis and immune microenvironment of esophageal squamous cell carcinoma: Bioinformatics analysis and experimental validation

BACKGROUND

Cuproptosis is a newly discovered cell death mechanism that relies on mitochondrial respiration, for which oxidative phosphorylation (OXPHOS) is an essential part. However, the detailed mechanisms of cuproptosis associated with OXPHOS in esophageal squamous cell carcinoma (ESCC) and how this correlation affects prognosis still remains unclear.

METHODS

scRNA-seq data of ESCC were downloaded from SRA (Sequence Read Archive) database. "AUCell" algorithm was used to grouping epithelial cells according to cuproptosis and OXPHOS score. Cell-cell communication, Pseudo-time Trajectory and transcription factor enrichment analysis were repectively conducted by "CellChat", "monocle3" package and "pySCENIC" algorithm. Univariate and LASSO cox regression analysis were used to construct the prognostic cuproptosis-OXPHOS signature. Finally, CCK-8 assay and DCFH-DA staining assay were respectively validated the sensitive and ROS production of elesclomol.

RESULTS

scRNA-seq data were analyzed to identify 10 core cell types. According to the median scores for cuproptosis and OXPHOS, malignant epithelial cells were divided into double high, double low, and mixed groups. The double high group distributed at the end of the pseudo-time trajectory and harbored HMGA1(+) as specific transcriptional regulons. Knockdown of HMGA1 partly reversed the inhibition of cell viability visualized by CCK-8 assay, while reactive oxygen species (ROS) production by elesclomol was enhanced after HMGA1 silencing. Furthermore, the immunosuppressive signal was significantly increased in the double high group detected by 'CellChat' in single-cell data and 'ssGSEA' in bulk data followed by 'CIBERSORTx' algorithm. Finally, a new cuproptosis-OXPHOS prognostic signature (CNN2, ATP6V0E1, PSMD6, CCDC25, IGFBP2, MT1E, and RPS4Y1) was constructed for the prediction of the prognosis, and a high-risk group corresponding to a more sensitive tendency to erlotinib, dasatinib, and bosutinib treatment was identified.

CONCLUSIONS

Our study revealed the relationship between OXPHOS and tendency of cuproptosis in ESCC, and malignant cells with this characteristic exerted immunosuppressive signals and indicated poor prognosis. Furthermore, we constructed the regulatory network in high cuproptosis-OXPHOS ESCC and identified HMGA1 as a potential regulator molecule of cuproptosis mediated by elesclomol.

Single-cell transcriptomic analysis reveals the landscape of epithelial-mesenchymal transition molecular heterogeneity in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a prevalent and highly lethal malignant disease. The epithelial-mesenchymal transition (EMT) is crucial in promoting ESCC development. However, the molecular heterogeneity of ESCC and the potential inhibitory strategies targeting EMT remain poorly understood. In this study, we analyzed high-resolution single-cell transcriptome data encompassing 209,231 ESCC cells from 39 tumor samples and 16 adjacent samples obtained from 44 individuals. We identified distinct cell populations exhibiting heterogeneous EMT characteristics and identified 87 EMT-associated molecules. The expression profiles of these EMT-associated molecules showed heterogeneity across different stages of ESCC progression. Moreover, we observed that EMT primarily occurred in early-stage tumors, before lymph node metastasis, and significantly promoted the rapid deterioration of ESCC. Notably, we identified SERPINH1 as a potential novel marker for ESCC EMT. By classifying ESCC patients based on EMT gene sets, we found that those with high EMT exhibited poorer prognosis. Furthermore, we predicted and experimentally validated drugs targeting ESCC EMT, including dactolisib, docetaxel, and nutlin, which demonstrated efficacy in inhibiting EMT and metastasis in ESCC. Through the integration of scRNA-seq, RNA-seq, and TCGA data with experimental validation, our comprehensive analysis elucidated the landscape of EMT during the entire course of ESCC development and metastasis. These findings provide valuable insights and a reference for refining ESCC clinical treatment strategies.

Single-cell profiling of response to neoadjuvant chemo-immunotherapy in surgically resectable esophageal squamous cell carcinoma

BACKGROUND

The efficacy of neoadjuvant chemo-immunotherapy (NAT) in esophageal squamous cell carcinoma (ESCC) is challenged by the intricate interplay within the tumor microenvironment (TME). Unveiling the immune landscape of ESCC in the context of NAT could shed light on heterogeneity and optimize therapeutic strategies for patients.

METHODS

We analyzed single cells from 22 baseline and 24 post-NAT treatment samples of stage II/III ESCC patients to explore the association between the immune landscape and pathological response to neoadjuvant anti-PD-1 combination therapy, including pathological complete response (pCR), major pathological response (MPR), and incomplete pathological response (IPR).

RESULTS

Single-cell profiling identified 14 major cell subsets of cancer, immune, and stromal cells. Trajectory analysis unveiled an interesting link between cancer cell differentiation and pathological response to NAT. ESCC tumors enriched with less differentiated cancer cells exhibited a potentially favorable pathological response to NAT, while tumors enriched with clusters of more differentiated cancer cells may resist treatment. Deconvolution of transcriptomes in pre-treatment tumors identified gene signatures in response to NAT contributed by specific immune cell populations. Upregulated genes associated with better pathological responses in CD8 + effector T cells primarily involved interferon-gamma (IFNγ) signaling, neutrophil degranulation, and negative regulation of the T cell apoptotic process, whereas downregulated genes were dominated by those in the immune response-activating cell surface receptor signaling pathway. Natural killer cells in pre-treatment tumors from pCR patients showed a similar upregulation of gene expression in response to IFNγ but a downregulation of genes in the neutrophil-mediated immunity pathways. A decreased cellular contexture of regulatory T cells in ESCC TME indicated a potentially favorable pathological response to NAT. Cell-cell communication analysis revealed extensive interactions between CCL5 and its receptor CCR5 in various immune cells of baseline pCR tumors. Immune checkpoint interaction pairs, including CTLA4-CD86, TIGIT-PVR, LGALS9-HAVCR2, and TNFSF4-TNFRSF4, might serve as additional therapeutic targets for ICI therapy in ESCC.

CONCLUSIONS

This pioneering study unveiled an intriguing association between cancer cell differentiation and pathological response in esophageal cancer patients, revealing distinct subgroups of tumors for which neoadjuvant chemo-immunotherapy might be effective. We also delineated the immune landscape of ESCC tumors in the context of clinical response to NAT, which provides clinical insights for better understanding how patients respond to the treatment and further identifying novel therapeutic targets for ESCC patients in the future.

Construction of a prognostic model with CAFs for predicting the prognosis and immunotherapeutic response of lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is one of the subtypes of lung cancer (LC) that contributes to approximately 25%-30% of its prevalence. Cancer-associated fibroblasts (CAFs) are key cellular components of the TME, and the large number of CAFs in tumour tissues creates a favourable environment for tumour development. However, the function of CAFs in the LUSC is complex and uncertain. First, we processed the scRNA-seq data and classified distinct types of CAFs. We also identified prognostic CAFRGs using univariate Cox analysis and conducted survival analysis. Additionally, we assessed immune cell infiltration in CAF clusters using ssGSEA. We developed a model with a significant prognostic correlation and verified the prognostic model. Furthermore, we explored the immune landscape of LUSC and further investigated the correlation between malignant features and LUSC. We identified CAFs and classified them into three categories: iCAFs, mCAFs and apCAFs. The survival analysis showed a significant correlation between apCAFs and iCAFs and LUSC patient prognosis. Kaplan-Meier analysis showed that patients in CAF cluster C showed a better survival probability compared to clusters A and B. In addition, we identified nine significant prognostic CAFRGs (CLDN1, TMX4, ALPL, PTX3, BHLHE40, TNFRSF12A, VKORC1, CST3 and ADD3) and subsequently employed multivariate Cox analysis to develop a signature and validate the model. Lastly, the correlation between CAFRG and malignant features indicates the potential role of CAFRG in promoting tumour angiogenesis, EMT and cell cycle alterations. We constructed a CAF prognostic signature for identifying potential prognostic CAFRGs and predicting the prognosis and immunotherapeutic response for LUSC. Our study may provide a more accurate prognostic assessment and immunotherapy targeting strategies for LUSC.

Prognostic Risk Models Using Epithelial Cells Identify β-Sitosterol as a Potential Therapeutic Target Against Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal malignancy that leads to epithelial cancer. The association between epithelial cell heterogeneity, prognosis, and immune response in this cancer remains uncertain. This study aimed to investigate epithelial cell heterogeneity in ESCC and develop a predictive risk model using the identified cell types.

Methods

Single-cell RNA sequencing (scRNA-seq) and differential ESCC gene data were accessed from the Gene Expression Omnibus. Functional enrichment analysis, inferCNV, cell development trajectories, and intercellular communication were analyzed following epithelial cell characterization. Differentially expressed ESCC (n = 773) and epithelial cell marker genes (n = 3407) were intersected to obtain core genes, and epithelial cell-related prognostic genes were identified. LASSO regression analysis was used to construct a prognostic model. The external dataset GSE53624 was used to further validate the stability of the model. Drug sensitivity predictions, and immune cell infiltration were analyzed. Molecular docking clarified the possible therapeutic role of β-sitosterol in ESCC. Finally, wound healing assay, cell colony, and transwell assay were constructed to detect the effects of the core gene PDLIM2 on ESCC cell proliferation, invasion, and migration.

Results

Eight cell clusters were identified, and epithelial cells were categorized into tumor and paratumor groups. The tumor group possessed more chromosomal variants than the paratumor group. Epithelial cells were associated with multiple cell types and significantly correlated with the Wnt, transforming growth factor, and epidermal growth factor signaling pathways. From 231 intersected genes, five core genes were screened for use in the risk model: CTSL, LAPTM4B, MYO10, NCF2, and PDLIM2. These genes may contribute to the cancerous transformation of normal esophageal epithelial cells and thereby act as biomarkers and potential therapeutic targets in patients with ESCC. β-Sitosterol furthermore displayed excellent docking potential with these genes. Meanwhile, further experiments demonstrated that the gene PDLIM2 plays a major role in the progression of oesophageal squamous carcinoma.

Conclusion

We successfully developed a risk model for the prognosis of ESCC based on epithelial cells that addresses the response of ESCC to immunotherapy and offers novel cancer treatment options.

Autophagy Contributes to Homeostasis in Esophageal Epithelium Where High Autophagic Vesicle Level Marks Basal Cells With Limited Proliferation and Enhanced Self-Renewal Potential

BACKGROUND & AIMS

Autophagy plays roles in esophageal pathologies both benign and malignant. Here, we aim to define the role of autophagy in esophageal epithelial homeostasis.

METHODS

We generated tamoxifen-inducible, squamous epithelial-specific Atg7 (autophagy related 7) conditional knockout mice to evaluate effects on esophageal homeostasis and response to the carcinogen 4-nitroquinoline 1-oxide (4NQO) using histologic and biochemical analyses. We fluorescence-activated cell sorted esophageal basal cells based on fluorescence of the autophagic vesicle (AV)-identifying dye Cyto-ID and then subjected these cells to transmission electron microscopy, image flow cytometry, three-dimensional organoid assays, RNA sequencing, and cell cycle analysis. Three-dimensional organoids were subjected to passaging, single-cell RNA sequencing, cell cycle analysis, and immunostaining.

RESULTS

Genetic autophagy inhibition in squamous epithelium resulted in increased proliferation of esophageal basal cells under homeostatic conditions and also was associated with significant weight loss in mice treated with 4NQO that further displayed perturbed epithelial tissue architecture. Esophageal basal cells with high AV level (Cyto-IDHigh) displayed limited organoid formation capability on initial plating but passaged more efficiently than their counterparts with low AV level (Cyto-IDLow). RNA sequencing suggested increased autophagy in Cyto-IDHigh esophageal basal cells along with decreased cell cycle progression, the latter of which was confirmed by cell cycle analysis. Single-cell RNA sequencing of three-dimensional organoids generated by Cyto-IDLow and Cyto-IDHigh cells identified expansion of 3 cell populations and enrichment of G2/M-associated genes in the Cyto-IDHigh group. Ki67 expression was also increased in organoids generated by Cyto-IDHigh cells, including in basal cells localized beyond the outermost cell layer.

CONCLUSIONS

Autophagy contributes to maintenance of the esophageal proliferation-differentiation gradient. Esophageal basal cells with high AV level exhibit limited proliferation and generate three-dimensional organoids with enhanced self-renewal capacity.

Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics

Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.

Multi-omics analysis reveals NNMT as a master metabolic regulator of metastasis in esophageal squamous cell carcinoma

Metabolic reprogramming has been observed in cancer metastasis, whereas metabolic changes required for malignant cells during lymph node metastasis of esophageal squamous cell carcinoma (ESCC) are still poorly understood. Here, we performed single-cell RNA sequencing (scRNA-seq) of paired ESCC tumor tissues and lymph nodes to uncover the reprogramming of tumor microenvironment (TME) and metabolic pathways. By integrating analyses of scRNA-seq data with metabolomics of ESCC tumor tissues and plasma samples, we found nicotinate and nicotinamide metabolism pathway was dysregulated in ESCC patients with lymph node metastasis (LN+), exhibiting as significantly increased 1-methylnicotinamide (MNA) in both tumors and plasma. Further data indicated high expression of N-methyltransferase (NNMT), which converts active methyl groups from the universal methyl donor, S-adenosylmethionine (SAM), to stable MNA, contributed to the increased MNA in LN+ ESCC. NNMT promotes epithelial-mesenchymal transition (EMT) and metastasis of ESCC in vitro and in vivo by inhibiting E-cadherin expression. Mechanically, high NNMT expression consumed too much active methyl group and decreased H3K4me3 modification at E-cadherin promoter and inhibited m6A modification of E-cadherin mRNA, therefore inhibiting E-cadherin expression at both transcriptional and post-transcriptional level. Finally, a detection method of lymph node metastasis was build based on the dysregulated metabolites, which showed good performance among ESCC patients. For lymph node metastasis of ESCC, this work supports NNMT is a master regulator of the cross-talk between cellular metabolism and epigenetic modifications, which may be a therapeutic target.

Effect of sodium stibogluconate in recruiting and awakening immune cells in the pleural fluid of pancreatic cancer: preparation for immunotherapy

Ascites and pleural effusion are recognized complications of pancreatic cancer. These diseases are accompanied by ascites and pleural effusion, and drug treatment is limited by high costs, long hospital stays, and failure rates. Immunotherapy may offer new option, but in most patients with late stages of cancer, immune cells may lose the ability to recognize tumor cells, how to activate their immune cells is a major problem, sodium glucosidate (SSG) is injected into ascites as a protein tyrosine phosphatase inhibitor to wake up immune cells and prepare for immunotherapy. We used single-cell RNA sequencing (scRNA-seq) to investigate whether and how SSG injected into ascites of pancreatic cancer elicits an immune response. Our study showed that the process of SSG fusion treatment of ascites and pleural effusion, the interaction between TandNK cells, MPs cells, monocytes and neutrophils was induced, and large numbers of genes were expressed, resulting in upregulation of immune response, which also approved that SSG is not only used as a protein tyrosine phosphatase inhibitor, but also it works as a protein tyrosine phosphatase inhibitor. It can also be used to regulate immune cell function, recruiting immune cells to the right place with the help of PD-1 or PD-L1 to fight cancer cells in ascites and pleural effusions in cancer patients.

Chemical immune conization of precancerous cervical lesions awakens immune cells and restores normal HPV negative and abnormal proliferation

Background

Cervical cancer is one of the most common and deadly cancers in women, which is closely linked to the persistent infection of high-risk human papillomavirus (HPV). Current treatment of cervical cancer involves radical hysterectomy, radiotherapy, and chemotherapy or a combination.

Objective

We investigated if hapten-enhanced intratumoral chemotherapy (HEIC) was effective in boosting immunity for effective treatment of precancerous cervical lesions and HPV infection.

Study design

We used single-cell RNA sequencing (scRNA-Seq) to obtain transcriptome profiles of 40,239 cells from biopsies of precancerous cervical lesions from the cervix directly from one patient before the start of HEIC and approximately 1 week after HEIC. The blood samples were taken at the same time as biopsies. We compared the expression characteristics of malignant epithelial cells and immune cells, including epithelial cells, endothelial cells (ECs), fibroblasts, mural cells, T cells, B cells, T and NK neutrophils, mast cells, microparticles (MPs), and platelets, as well as the dynamic changes in cell percentage and cell subtype heterogeneity.

Results

Intratumoral injection of chemotherapy drug plus hapten induces an acute immune response in precancerous cervical lesions with HPV and further awakens immune cells to prevent the abnormal proliferation of the precancerous cells.

Conclusion

HEIC provides a potential treatment method for cervical cancer and HPV infection tailored to each patient's condition.

PLK1 regulating chemoradiotherapy sensitivity of esophageal squamous cell carcinoma through pentose phosphate pathway/ferroptosis

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is the most common pathological type of esophageal cancer in China, accounting for more than 90 %. Most patients were diagnosed with advanced-stage ESCC, for whom new adjuvant therapy is recommended. Therefore, it is urgent to explore new therapeutic targets for ESCC. Ferroptosis, a newly discovered iron-dependent programmed cell death, has been shown to play an important role in carcinogenesis by many studies. This study explored the effect of Polo like kinase 1 (PLK1) on chemoradiotherapy sensitivity of ESCC through ferroptosis METHODS: In this study, we knocked out the expression of PLK1 (PLK1-KO) in ESCC cell lines (KYSE150 and ECA109) with CRISPR/CAS9. The effects of PLK1-knock out on G6PD, the rate-limiting enzyme of pentose phosphate pathway (PPP), and downstream NADPH and GSH were explored. The lipid peroxidation was observed by flow cytometry, and the changes in mitochondria were observed by transmission electron microscopy. Next, through the CCK-8 assay and clone formation assay, the sensitivity to cobalt 60 rays, paclitaxel, and cisplatin were assessed after PLK1-knock out, and the nude mouse tumorigenesis experiment further verified it. The regulation of transcription factor YY1 on PLK1 was evaluated by dual luciferase reporter assay. The expression and correlation of PLK1 and YY1, and their impact on prognosis were analyzed in more than 300 ESCC cases from the GEO database and our center. Finally, the above results were further proved by single-cell sequencing.

RESULTS

After PLK1 knockout, the expression of G6PD dimer and the level of NADPH and GSH in KYSE150 and ECA109 cells significantly decreased. Accordingly, lipid peroxidation increased, mitochondria became smaller, membrane density increased, and ferroptosis was more likely to occur. However, with the stimulation of exogenous GSH (10 mM), there was no significant difference in lipid peroxidation and ferroptosis between the PLK1-KO group and the control group. After ionizing radiation, the PLK1-KO group had higher lipid peroxidation ratio, more cell death, and was more sensitive to radiation, while exogenous GSH (10 mM) could eliminate this difference. Similar results could also be observed when receiving paclitaxel combined with cisplatin and chemoradiotherapy. The expression of PLK1, G6PD dimer, and the level of NADPH and GSH in KYSE150, ECA109, and 293 T cells stably transfected with YY1-shRNAs significantly decreased, and the cells were more sensitive to radiotherapy and chemotherapy. ESCC patients from the GEO database and our center, YY1 and PLK1 expression were significantly positively-correlated, and the survival of patients with high expression of PLK1 was significantly shorter. Further analysis of single-cell sequencing specimens of ESCC in our center confirmed the above results.

CONCLUSION

In ESCC, down-regulation of PLK1 can inhibit PPP, and reduce the level of NADPH and GSH, thereby promoting ferroptosis and improving their sensitivity to radiotherapy and chemotherapy. Transcription factor YY1 has a positive regulatory effect on PLK1, and their expressions were positively correlated. PLK1 may be a target for predicting and enhancing the chemoradiotherapy sensitivity of ESCC.

Progenitor-like exhausted SPRY1+CD8+ T cells potentiate responsiveness to neoadjuvant PD-1 blockade in esophageal squamous cell carcinoma

Neoadjuvant immune checkpoint blockade (ICB) demonstrates promise in operable esophageal squamous cell carcinoma (ESCC), but lacks available efficacy biomarkers. Here, we perform single-cell RNA-sequencing of tumors from patients with ESCC undergoing neoadjuvant ICB, revealing a subset of exhausted CD8+ T cells expressing SPRY1 (CD8+ Tex-SPRY1) that displays a progenitor exhausted T cell (Tpex) phenotype and correlates with complete response to ICB. We validate CD8+ Tex-SPRY1 cells as an ICB-specific predictor of improved response and survival using independent ICB-/non-ICB cohorts and demonstrate that expression of SPRY1 in CD8+ T cells enforces Tpex phenotype and enhances ICB efficacy. Additionally, CD8+ Tex-SPRY1 cells contribute to proinflammatory phenotype of macrophages and functional state of B cells, which thereby promotes antitumor immunity by enhancing CD8+ T cell effector functions. Overall, our findings unravel progenitor-like CD8+ Tex-SPRY1 cells' role in effective responses to ICB for ESCC and inform mechanistic biomarkers for future individualized immunotherapy.

Identification of a Prognostic Gene Signature Based on Lipid Metabolism-Related Genes in Esophageal Squamous Cell Carcinoma

Background

Dysregulation of lipid metabolism is common in cancer. However, the molecular mechanism underlying lipid metabolism in esophageal squamous cell carcinoma (ESCC) and its effect on patient prognosis are not well understood. The objective of our study was to construct a lipid metabolism-related prognostic model to improve prognosis prediction in ESCC.

Methods

We downloaded the mRNA expression profiles and corresponding survival data of patients with ESCC from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We performed differential expression analysis to identify differentially expressed lipid metabolism-related genes (DELMGs). We used Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to establish a risk model in the GEO cohort and used data of patients with ESCC from the TCGA cohort for validation. We also explored the relationship between the risk model and the immune microenvironment via infiltrated immune cells and immune checkpoints.

Results

The result showed that 132 unique DELMGs distinguished patients with ESCC from the controls. We identified four genes (ACAA1, ACOT11, B4GALNT1, and DDHD1) as prognostic gene expression signatures to construct a risk model. Patients were classified into high- and low-risk groups as per the signature-based risk score. We used the receiver operating characteristic (ROC) curve and the Kaplan-Meier (KM) survival analysis to validate the predictive performance of the 4-gene signature in both the training and validation sets. Infiltrated immune cells and immune checkpoints indicated a difference in the immune status between the two risk groups.

Conclusion

The results of our study indicated that a prognostic model based on the 4-gene signature related to lipid metabolism was useful for the prediction of prognosis in patients with ESCC.

Multi-omics analyses reveal spatial heterogeneity in primary and metastatic oesophageal squamous cell carcinoma

BACKGROUND

Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ).

METHODS

Primary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed.

RESULTS

WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion.

CONCLUSIONS

This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.

Dissecting the single-cell transcriptome network of macrophage and identifies a signature to predict prognosis in lung adenocarcinoma

PURPOSE

The tumor immune microenvironment (TME) plays a vital role in tumorigenesis, progression, and treatment. Macrophages, as an important component of the tumor microenvironment, play an essential role in antitumor immunity and TME remodeling. In this study, we aimed to explore the different functions of different origins macrophages in TME and their value as potential predictive markers of prognosis and treatment.

METHODS

We performed single-cell analysis using 21 lung adenocarcinoma (LUAD), 12 normal, and four peripheral blood samples from our data and public databases. A prognostic prediction model was then constructed using 502 TCGA patients and explored the potential factors affecting prognosis. The model was validated using data from 4 different GEO datasets with 544 patients after integration.

RESULTS

According to the source of macrophages, we classified macrophages into alveolar macrophages (AMs) and interstitial macrophages (IMs). AMs mainly infiltrated in normal lung tissue and expressed proliferative, antigen-presenting, scavenger receptors genes, while IMs occupied the majority in TME and expressed anti-inflammatory, lipid metabolism-related genes. Trajectory analysis revealed that AMs rely on self-renew, whereas IMs originated from monocytes in the blood. Cell-to-cell communication showed that AMs interacted mainly with T cells through the MHC I/II signaling pathway, while IMs mostly interacted with tumor-associated fibrocytes and tumor cells. We then constructed a risk model based on macrophage infiltration and showed an excellent predictive power. We further revealed the possible reasons for its potential prognosis prediction by differential genes, immune cell infiltration, and mutational differences.

CONCLUSION

In conclusion, we investigated the composition, expression differences, and phenotypic changes of macrophages from different origins in lung adenocarcinoma. In addition, we developed a prognostic prediction model based on different macrophage subtype infiltration, which can be used as a valid prognostic biomarker. New insights were provided into the role of macrophages in the prognosis and potential treatment of LUAD patients.

Tertiary lymphoid structures correlate with enhancement of antitumor immunity in esophageal squamous cell carcinoma

BACKGROUND

Tertiary lymphoid structures (TLSs) are associated with a favorable prognosis in several cancers. However, the correlation between TLSs and outcomes of esophageal squamous cell carcinoma (ESCC) and the impact of TLSs on the tumor immune microenvironment (TIME) remain unknown.

METHODS

We pathologically evaluated the significance of TLSs in ESCC focusing on TLS maturation using 180 ESCC specimens and performed single-cell RNA sequencing (scRNA-seq) using 14 ESCC tissues to investigate functional differences of immune cells according to TLS presence.

RESULTS

TLS+ cases had better recurrence-free-survival (RFS) (p < 0.0001) and overall survival (OS) (p = 0.0016) compared with TLS- cases. Additionally, mature TLS+ cases had better RFS and OS compared with immature TLS+ cases (p = 0.019 and p = 0.015) and TLS- cases (p < 0.0001 and p = 0.0002). The scRNA-seq showed that CD8+ T cells in TLS+ tumors expressed high levels of cytotoxic signatures and antigen-presentation of dendritic cells (DCs) was enhanced in TLS+ tumors. Immunohistochemistry showed that the densities of tumor-infiltrating CD8+ T cells and DCs were significantly higher in TLS+ tumors than those in TLS- tumors.

CONCLUSIONS

These data suggest the prognostic and functional significance of TLSs in ESCC and provides new insights into TLSs on the TIME.

Pleckstrin-2 promotes tumour immune escape from NK cells by activating the MT1-MMP-MICA signalling axis in gastric cancer

Immune escape is a major challenge in tumour immunotherapy. Pleckstrin-2(PLEK2) plays a critical role in tumour progression, but its role in immune escape in gastric cancer (GC) remains uncharacterized. RNA sequencing was used to explore the differentially expressed genes in a GC cell line that was resistant to the antitumor effect of Natural killer (NK) cells. Apoptosis and the expression of IFN-γ and TNF-α were detected by flow cytometry (FCM). PLEK2 expression was examined by Western blotting and immunohistochemistry (IHC). PLEK2 was upregulated in MGC803R cells that were resistant to the antitumor effect of NK cells. PLEK2 knockout increased the sensitivity of GC cells to NK cell killing. PLEK2 expression was negatively correlated with MICA and positively correlated with MT1-MMP expression both in vitro and in vivo. PLEK2 promoted Sp1 phosphorylation through the PI3K-AKT pathway, thereby upregulating MT1-MMP expression, which ultimately led to MICA shedding. In mouse xenograft models, PLEK2 knockout inhibited intraperitoneal metastasis of GC cells and promoted NK cell infiltration. In summary, PLEK2 suppressed NK cell immune surveillance by promoting MICA shedding, which serves as a potential therapeutic target for GC.

Autophagy contributes to homeostasis in esophageal epithelium where high autophagic vesicle content marks basal cells with limited proliferation and enhanced self-renewal potential

Background & Aims

Autophagy has been demonstrated to play roles in esophageal pathologies both benign and malignant. Here, we aim to define the role of autophagy in esophageal epithelium under homeostatic conditions.

Methods

We generated tamoxifen-inducible, squamous epithelial-specific Atg7 (autophagy related 7) conditional knockout mice to evaluate effects on esophageal homeostasis and response to the carcinogen 4-nitroquinoline 1-oxide (4NQO) using histological and biochemical analyses. We FACS sorted esophageal basal cells based upon fluorescence of the autophagic vesicle (AV)-identifying dye Cyto-ID, then subjected these cells to transmission electron microscopy, image flow cytometry, 3D organoid assays, RNA-Sequencing (RNA-Seq), and cell cycle analysis. 3D organoids were subjected to passaging, single cell (sc) RNA-Seq, cell cycle analysis, and immunostaining.

Results

Genetic autophagy inhibition in squamous epithelium resulted in increased proliferation of esophageal basal cells. Esophageal basal cells with high AV level (Cyto-ID High ) displayed limited organoid formation capability upon initial plating but passaged more efficiently than their counterparts with low AV level (Cyto-ID Low ). RNA-Seq suggested increased autophagy in Cyto- ID High esophageal basal cells along with decreased cell cycle progression, the latter of which was confirmed by cell cycle analysis. scRNA-Seq of 3D organoids generated by Cyto-ID Low and Cyto- ID High cells identified expansion of 3 cell populations, enrichment of G2/M-associated genes, and aberrant localization of cell cycle-associated genes beyond basal cell populations in the Cyto- ID High group. Ki67 expression was also increased in organoids generated by Cyto-ID High cells, including in cells beyond the basal cell layer. Squamous epithelial-specific autophagy inhibition induced significant weight loss in mice treated with 4NQO that further displayed perturbed epithelial tissue architecture.

Conclusions

High AV level identifies esophageal epithelium with limited proliferation and enhanced self-renewal capacity that contributes to maintenance of the esophageal proliferation- differentiation gradient in vivo .

The DMRTA1-SOX2 positive feedback loop promotes progression and chemotherapy resistance of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most prevalent causes of cancer-related death in patients worldwide. Resistance to immunotherapy and chemotherapy results in worse survival outcomes in ESCC. It is urgent to explore the underlying molecular mechanism of immune evasion and chemoresistance in ESCC. Here, we conducted RNA-sequencing analysis in ten ESCC tissues from cisplatin-based neoadjuvant chemotherapy patients. We found that DMRTA1 was extremely upregulated in the non-pathologic complete response (non-pCR) group. The proliferation rate of esophageal squamous carcinoma cells was markedly decreased after knockdown of DMRTA1 expression, which could increase cisplatin sensitivity in ESCC. Additionally, suppression of DMRTA1 could decrease the immune escape of esophageal squamous carcinoma cells. Further mechanistic studies suggest that DMRTA1 can promote its expression by binding to the promoter of SOX2, which plays important roles in the progression and chemoresistance of ESCC in the form of positive feedback. Therefore, DMRTA1 could be a potential target to suppress immune escape and overcome chemoresistance in ESCC.

Key Genetic Determinants Driving Esophageal Squamous Cell Carcinoma Initiation and Immune Evasion

BACKGROUND & AIMS

Despite recent progress in identifying aberrant genetic and epigenetic alterations in esophageal squamous cell carcinoma (ESCC), the mechanism of ESCC initiation remains unknown.

METHODS

Using CRISPR/Cas 9-based genetic ablation, we targeted 9 genes (TP53, CDKN2A, NOTCH1, NOTCH3, KMT2D, KMT2C, FAT1, FAT4, and AJUBA) in murine esophageal organoids. Transcriptomic phenotypes of organoids and chemokine released by organoids were analyzed by single-cell RNA sequencing. Tumorigenicity and immune evasion of organoids were monitored by allograft transplantation. Human ESCC single-cell RNA sequencing data sets were analyzed to classify patients and find subsets relevant to organoid models and immune evasion.

RESULTS

We established 32 genetically engineered esophageal organoids and identified key genetic determinants that drive ESCC initiation. A single-cell transcriptomic analysis uncovered that Trp53, Cdkn2a, and Notch1 (PCN) triple-knockout induces neoplastic features of ESCC by generating cell lineage heterogeneity and high cell plasticity. PCN knockout also generates an immunosuppressive niche enriched with exhausted T cells and M2 macrophages via the CCL2-CCR2 axis. Mechanistically, CDKN2A inactivation transactivates CCL2 via nuclear factor-κB. Moreover, comparative single-cell transcriptomic analyses stratified patients with ESCC and identified a specific subtype recapitulating the PCN-type ESCC signatures, including the high expression of CCL2 and CD274/PD-L1.

CONCLUSIONS

Our study unveils that loss of TP53, CDKN2A, and NOTCH1 induces esophageal neoplasia and immune evasion for ESCC initiation and proposes the CCL2 blockade as a viable option for targeting PCN-type ESCC.

Advances in single-cell RNA sequencing and its applications in cancer research

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

Systemic treatments for resectable carcinoma of the esophagus

One of the most prevalent malignancies in the world is esophageal cancer (EC). The 5-year survival rate of EC remains pitiful despite treatment advancements. Neoadjuvant chemoradiotherapy in conjunction with esophagectomy is the standard of care for patients with resectable disease. The pathological complete response rate, however, is not acceptable. A distant metastasis or a locoregional recurrence will occur in about half of the patients. To increase the clinical effectiveness of therapy, it is consequently vital to investigate cutting-edge and potent therapeutic modalities. The approach to the management of resectable EC using immunotherapy has been considerably altered by immune checkpoint inhibitors. Systemic immunotherapy has recently been shown to have the potential to increase the survival of patients with resectable EC, according to growing clinical data. A combination of chemotherapy, radiation, and immunotherapy may have a synergistic antitumor impact because, according to mounting evidence, these treatments can stimulate the immune system via a number of different pathways. In light of this, it makes sense to consider the value of neoadjuvant immunotherapy for patients with surgically treatable EC. In this review, we clarify the rationale for neoadjuvant immunotherapy in resectable EC patients, recap the clinical outcomes of these approaches, go through the upcoming and ongoing investigations, and emphasize the difficulties and unmet research requirements.

Exploring cell competition for the prevention and therapy of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is characterized by the development of cancer in the esophageal squamous epithelium through a step-by-step accumulation of genetic, epigenetic, and histopathological alterations. Recent studies have demonstrated that cancer-associated gene mutations exist in histologically normal or precancerous clones of the human esophageal epithelium. However, only a small proportion of such mutant clones will develop ESCC, and most ESCC patients develop only one cancer. This suggests that most of these mutant clones are kept in a histologically normal state by neighboring cells with higher competitive fitness. When some of the mutant cells evade cell competition, they become "super-competitors" and develop into clinical cancer. It is known that human ESCC is composed of a heterogeneous population of cancer cells that interact with and influence their environment and neighbors. During cancer therapy, these cancer cells not only respond to therapeutic agents but also compete with each other. Therefore, competition between ESCC cells within the same ESCC tumor is a constantly dynamic process. However, it remains challenging to fine-tune the competitive fitness of various clones for therapeutic benefits. In this review, we will explore the role of cell competition in carcinogenesis, cancer prevention, and therapy, using NRF2, NOTCH pathway, and TP53 as examples. We believe that cell competition is a research area with promising targets for clinical translation. Manipulating cell competition may help improve the prevention and therapy of ESCC.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma

Background

N6-methyladenosine (m⁶A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m⁶A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown.

Methods

The single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells.

Results

According to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m⁶A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m⁶A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m⁶A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74⁺CD44) ligand-receptor pairings facilitated communication between m⁶A-associated subtypes of TME cells and cancer cells.

Conclusion

Overall, our study demonstrated for the first time the function of m⁶A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

Roles of circRNA dysregulation in esophageal squamous cell carcinoma tumor microenvironment

Esophageal squamous cell carcinoma (ESCC) is the most prevalent histological esophageal cancer characterized by advanced diagnosis, metastasis, resistance to treatment, and frequent recurrence. In recent years, numerous human disorders such as ESCC, have been linked to abnormal expression of circular RNAs (circRNAs), suggesting that they are fundamental to the intricate system of gene regulation that governs ESCC formation. The tumor microenvironment (TME), referring to the area surrounding the tumor cells, is composed of multiple components, including stromal cells, immune cells, the vascular system, extracellular matrix (ECM), and numerous signaling molecules. In this review, we briefly described the biological purposes and mechanisms of aberrant circRNA expression in the TME of ESCC, including the immune microenvironment, angiogenesis, epithelial-to-mesenchymal transition, hypoxia, metabolism, and radiotherapy resistance. As in-depth research into the processes of circRNAs in the TME of ESCC continues, circRNAs are promising therapeutic targets or delivery systems for cancer therapy and diagnostic and prognostic indicators for ESCC.

The genomic signature of resistance to platinum-containing neoadjuvant therapy based on single-cell data

BACKGROUND

Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT.

METHODS

Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro.

RESULTS

485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin.

CONCLUSIONS

NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.

Single-cell RNA-sequencing data reveals the genetic source of extracellular vesicles in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is invasive cancer and the complex mechanisms underlying carcinogenesis remain unclear. Extracellular vesicles (EVs), secreted by most cell types, serve as a critical factor in tumorigenesis via intercellular communications. Our study aims to investigate the cellular origin of EVs in ESCC, and unveil the unknown molecular and cellular mechanisms underlying cell-cell communications. Six ESCC patients were enrolled and single-cell RNA sequencing (scRNA-seq) analyses were conducted to screen different cell subpopulations. The genetic origin of EVs was tracked using the supernatant from different cellular extracts. Nanoparticle tracking analysis (NTA), western blot analysis, and transmission electron microscopy (TEM) were performed for validation. Using scRNA-seq analysis, eleven cell subpopulations were identified in ESCC. Differences in gene expression in EVs between malignant and non-malignant esophageal tissues were found. Our findings demonstrated that epithelial cells releasing EVs were the most prevalent in malignant tissues, while endothelial cells and fibroblasts releasing EVs were predominant in non-malignant tissues. Furthermore, the high levels of gene expression in EVs released from these cells were correlated significantly with a worse prognosis. Our findings revealed the genetic origin of EVs in malignant and non-malignant esophageal tissues and provided a comprehensive overview of the associated cell-cell interactions in ESCC.

Integration analysis based on fatty acid metabolism robustly predicts prognosis, dissecting immunity microenvironment and aiding immunotherapy for soft tissue sarcoma

Background: Soft tissue sarcoma (STS) is a highly malignant tumor with a dismal prognosis. Presently, the dysregulation of fatty acid metabolism has received increasing attention in tumor research, but fewer reports are relevant to STS.

Methods: Based on fatty acid metabolism-related genes (FRGs), a novel risk score for STS was developed utilizing univariate analysis and least absolute shrinkage selection operator (LASSO) Cox regression analyses in the STS cohort, which were further validated using the external validation cohort from other databases. Furthermore, independent prognostic analysis, C-index, ROC curves, and nomogram were carried out to investigate the predictive performance of fatty acid-related risk scores. We also analysed the differences in enrichment pathways, the immune microenvironment, gene mutations, and immunotherapy response between the two distinct fatty acid score groups. Moreover, the real-time quantitative polymerase chain reaction (RT-qPCR) was used to further verify the expression of FRGs in STS.

Results: A total of 153 FRGs were retrieved in our study. Next, a novel fatty acid metabolism-related risk score (FAS) was constructed based on 18 FRGs. The predictive performance of FAS was also verified in external cohorts. In addition, the independent analysis, C-index, ROC curve, and nomograph also revealed that FAS could serve as an independent prognostic factor for the STS patients. Meanwhile, our results demonstrated that the STS cohort in two distinct FAS groups had different copy number variations, immune cell infiltration, and immunotherapy responses. Finally, the in vitro validation results demonstrated that several FRGs included in the FAS exhibited abnormal expression in STS.

Conclusion: Altogether, our work comprehensively and systematically clarifies fatty acid metabolism’s potential roles and clinical significance in STS. The novel individualized score based on fatty acid metabolism may be provided as a potential marker and treatment strategy in STS.

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer

Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed of tumor and stromal cellular components; at the genetic levels, they comprise genetically distinct tumor clones; at the phenotypic levels, cells in distinct microenvironmental niches acquire diverse phenotypic features. This heterogeneity affects almost every process of esophageal cancer progression from onset to metastases and recurrence, etc. Intertumoral and intratumoral heterogeneity are major obstacles in the treatment of esophageal cancer, but also offer the potential to manipulate the heterogeneity themselves as a new therapeutic strategy. The high-dimensional, multi-faceted characterization of genomics, epigenomics, transcriptomics, proteomics, metabonomics, etc. of esophageal cancer has opened novel horizons for dissecting tumor heterogeneity. Artificial intelligence especially machine learning and deep learning algorithms, are able to make decisive interpretations of data from multi-omics layers. To date, artificial intelligence has emerged as a promising computational tool for analyzing and dissecting esophageal patient-specific multi-omics data. This review provides a comprehensive review of tumor heterogeneity from a multi-omics perspective. Especially, we discuss the novel techniques single-cell sequencing and spatial transcriptomics, which have revolutionized our understanding of the cell compositions of esophageal cancer and allowed us to determine novel cell types. We focus on the latest advances in artificial intelligence in integrating multi-omics data of esophageal cancer. Artificial intelligence-based multi-omics data integration computational tools exert a key role in tumor heterogeneity assessment, which will potentially boost the development of precision oncology in esophageal cancer.

Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma

Lymph node metastasis, the leading cause of mortality in esophageal squamous carcinoma (ESCC) with a highly complex tumor microenvironment, remains underexplored. Here, the transcriptomes of 85 263 single cells are analyzed from four ESCC patients with lymph node metastases. Strikingly, it is observed that the metastatic microenvironment undergoes the emergence or expansion of interferon induced IFIT3+ T, B cells, and immunosuppressive cells such as APOC1+ APOE+ macrophages and myofibroblasts with highly expression of immunoglobulin genes (IGKC) and extracellular matrix component and matrix metallopeptidase genes. A poor-prognostic epithelial-immune dual expression program regulating immune effector processes, whose activity is significantly enhanced in metastatic malignant epithelial cells and enriched in CD74+ CXCR4+ and major histocompatibility complex (MHC) class II genes upregulated malignant epithelia cells is discovered. Comparing with primary tumor, differential intercellular communications of metastatic ESCC microenvironment are revealed and furtherly validated via multiplexed immunofluorescence and immunohistochemistry staining, which mainly rely on the crosstalk of APOC1+ APOE+ macrophages with tumor and stromal cell. The data highlight potential molecular mechanisms that shape the lymph-node metastatic microenvironment and may inform drug discovery and the development of new strategies to target these prometastatic nontumor components for inhibiting tumor growth and overcoming metastasis to improve clinical outcomes.

Tumor Niche Network-Defined Subtypes Predict Immunotherapy Response of Esophageal Squamous Cell Cancer

Despite the promising outcomes of immune checkpoint blockade (ICB), resistance to ICB presents a new challenge. Therefore, selecting patients for specific ICB applications is crucial for maximizing therapeutic efficacy. Herein we curated 69 human esophageal squamous cell cancer (ESCC) patients' tumor microenvironment (TME) single-cell transcriptomic datasets to subtype ESCC. Integrative analyses of the cellular network transcriptional signatures of T cells, myeloid cells, and fibroblasts define distinct ESCC subtypes characterized by T cell exhaustion, Interferon (IFN) a/b signaling, TIGIT enrichment, and specific marker genes. Furthermore, this approach classifies ESCC patients into ICB responders and non-responders, as validated by liquid biopsy single-cell transcriptomics. Our study stratifies ESCC patients based on TME transcriptional network, providing novel insights into tumor niche remodeling and predicting ICB responses in ESCC patients.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.

Potent molecular-targeted therapies for advanced esophageal squamous cell carcinoma

Esophageal cancer (EC) remains a public health concern with a high mortality and disease burden worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant histological subtype of EC that has unique etiology, molecular profiles, and clinicopathological features. Although systemic chemotherapy, including cytotoxic agents and immune checkpoint inhibitors, is the main therapeutic option for recurrent or metastatic ESCC patients, the clinical benefits are limited with poor prognosis. Personalized molecular-targeted therapies have been hampered due to the lack of robust treatment efficacy in clinical trials. Therefore, there is an urgent need to develop effective therapeutic strategies. In this review, we summarize the molecular profiles of ESCC based on the findings of pivotal comprehensive molecular analyses, highlighting potent therapeutic targets for establishing future precision medicine for ESCC patients, with the most recent results of clinical trials.