The tumor microenvironment is a highly complex ecosystem of diverse cell types, which shape cancer biology and impact the responsiveness to therapy. Here, we analyze the microenvironment of ...esophageal squamous cell carcinoma (ESCC) using single-cell transcriptome sequencing in 62,161 cells from blood, adjacent nonmalignant and matched tumor samples from 11 ESCC patients. We uncover heterogeneity in most cell types of the ESCC stroma, particularly in the fibroblast and immune cell compartments. We identify a tumor-specific subset of CST1
myofibroblasts with prognostic values and potential biological significance. CST1
myofibroblasts are also highly tumor-specific in other cancer types. Additionally, a subset of antigen-presenting fibroblasts is revealed and validated. Analyses of myeloid and T lymphoid lineages highlight the immunosuppressive nature of the ESCC microenvironment, and identify cancer-specific expression of immune checkpoint inhibitors. This work establishes a rich resource of stromal cell types of the ESCC microenvironment for further understanding of ESCC biology.
Esophageal cancer (EC) is a type of aggressive cancer without clinically relevant molecular subtypes, hindering the development of effective strategies for treatment. To define molecular subtypes of ...EC, we perform mass spectrometry-based proteomic and phosphoproteomics profiling of EC tumors and adjacent non-tumor tissues, revealing a catalog of proteins and phosphosites that are dysregulated in ECs. The EC cohort is stratified into two molecular subtypes-S1 and S2-based on proteomic analysis, with the S2 subtype characterized by the upregulation of spliceosomal and ribosomal proteins, and being more aggressive. Moreover, we identify a subtype signature composed of ELOA and SCAF4, and construct a subtype diagnostic and prognostic model. Potential drugs are predicted for treating patients of S2 subtype, and three candidate drugs are validated to inhibit EC. Taken together, our proteomic analysis define molecular subtypes of EC, thus providing a potential therapeutic outlook for improving disease outcomes in patients with EC.
Abstract
Squamous cell carcinomas (SCCs) comprise one of the most common histologic types of human cancer. Transcriptional dysregulation of SCC cells is orchestrated by
tumor protein p63 (TP63)
, a ...master transcription factor (TF) and a well-researched SCC-specific oncogene. In the present study, both Gene Set Enrichment Analysis (GSEA) of SCC patient samples and in vitro loss-of-function assays establish fatty-acid metabolism as a key pathway downstream of TP63. Further studies identify
sterol regulatory element binding transcription factor 1 (SREBF1)
as a central mediator linking TP63 with fatty-acid metabolism, which regulates the biosynthesis of fatty-acids, sphingolipids (SL), and glycerophospholipids (GPL), as revealed by liquid chromatography tandem mass spectrometry (LC-MS/MS)-based lipidomics. Moreover, a feedback co-regulatory loop consisting of SREBF1/TP63/
Kruppel like factor 5 (KLF5)
is identified, which promotes overexpression of all three TFs in SCCs. Downstream of SREBF1, a non-canonical, SCC-specific function is elucidated: SREBF1 cooperates with TP63/KLF5 to regulate hundreds of cis-regulatory elements across the SCC epigenome, which converge on activating cancer-promoting pathways. Indeed, SREBF1 is essential for SCC viability and migration, and its overexpression is associated with poor survival in SCC patients. Taken together, these data shed light on mechanisms of transcriptional dysregulation in cancer, identify specific epigenetic regulators of lipid metabolism, and uncover SREBF1 as a potential therapeutic target and prognostic marker in SCC.
Esophageal cancer is the seventh most common cancer in the world. Although traditional treatment methods such as radiotherapy and chemotherapy have good effects, their side effects and drug ...resistance remain problematic. The repositioning of drug function provides new ideas for the research and development of anticancer drugs. We previously showed that the Food and Drug Administration–approved drug sulconazole can effectively inhibit the growth of esophageal cancer cells, but its molecular mechanism is not clear. Here, our study demonstrated that sulconazole had a broad spectrum of anticancer effects. It can not only inhibit the proliferation but also inhibit the migration of esophageal cancer cells. Both transcriptomic sequencing and proteomic sequencing showed that sulconazole could promote various types of programmed cell death and inhibit glycolysis and its related pathways. Experimentally, we found that sulconazole induced apoptosis, pyroptosis, necroptosis, and ferroptosis. Mechanistically, sulconazole triggered mitochondrial oxidative stress and inhibited glycolysis. Finally, we showed that low-dose sulconazole can increase radiosensitivity of esophageal cancer cells. Taken together, these new findings provide strong laboratory evidence for the clinical application of sulconazole in esophageal cancer.
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•Sulconazole has a broad spectrum of anticancer effects.•Sulconazole induces PANoptosis of esophageal cancer cells.•Sulconazole triggers mitochondrial oxidative stress and inhibits glycolysis.•Sulconazole increase the radiosensitivity of esophageal cancer cells.
This article reports that sulconazole induces PANoptosis, which is a combination of cell apoptosis, pyroptosis, necroptosis, and ferroptosis, in esophageal cancer cells. Mechanistically, sulconazole triggers oxidative stress and inhibits glycolysis via downregulating HKs and inhibiting the PI3K/AKT, MEK/ERK, STAT3 pathways. Finally, sulconazole increases radiosensitivity of esophageal cancer cells. This study provides experimental evidence for the clinical application of sulconazole.
The importance of intratumoral heterogeneity has been highlighted by the identification and characterization of cancer stem cells (CSCs). Based on the differential responsiveness to a Sox2 reporter, ...SRR2, we had found a novel dichotomy in esophageal squamous cell carcinoma (ESCC) cells, with reporter-responsive (RR) cells showing more CSC-like features than reporter-unresponsive (RU) cells. Specifically, RR cells exhibited significantly higher tumorsphere formation capacity, proportions of CD44(High) cells, chemoresistance to cisplatin, and tumorigenic potential in vivo. H2 O2 , a potent inducer of oxidative stress and reactive oxygen species, was found to induce a conversion from RU to RR cells; importantly, converted RR cells acquired CSC-like features. The PI3K/AKT/c-MYC signalling axis is important in this context, since pharmacologic blockade of PI3K-AKT or siRNA knockdown of c-MYC effectively inhibited the RR phenotype and its associated CSC-like features, as well as the H2 O2 -induced RU/RR conversion. In a cohort of 188 ESCC patient samples, we found a significant correlation between strong c-MYC expression and a short overall survival (p = .009). In conclusion, we have described a novel intratumoral heterogeneity in ESCC. The identification of the PI3K/AKT/c-MYC axis as a driver of CSC-like features carries therapeutic implications. Stem Cells 2016;34:2040-2051.
Oesophageal squamous cell carcinoma (OSCC) and adenocarcinoma (OAC) are distinct cancers in terms of a number of clinical and epidemiological characteristics, complicating the design of clinical ...trials and biomarker developments. We analysed 1048 oesophageal tumour-germline pairs from both subtypes, to characterise their genomic features, and biological and clinical significance.
Previously exome-sequenced samples were re-analysed to identify significantly mutated genes (SMGs) and mutational signatures. The biological functions of novel SMGs were investigated using cell line and xenograft models. We further performed whole-genome bisulfite sequencing and chromatin immunoprecipitation (ChIP)-seq to characterise epigenetic alterations.
OSCC and OAC displayed nearly mutually exclusive sets of driver genes, indicating that they follow independent developmental paths. The combined sample size allowed the statistical identification of a number of novel subtype-specific SMGs, mutational signatures and prognostic biomarkers. Particularly, we identified a novel mutational signature similar to Catalogue Of Somatic Mutations In Cancer (COSMIC)signature 16, which has prognostic value in OSCC. Two newly discovered SMGs,
and
, were validated as important tumour-suppressors specific to the OSCC subtype. We further identified their additional loss-of-function mechanisms.
was homozygously deleted specifically in OSCC and other squamous cell cancers (SCCs). Notably,
is associated with super-enhancer in healthy oesophageal mucosa; DNA hypermethylation in its super-enhancer reduced active histone markers in squamous cancer cells, suggesting an epigenetic inactivation of a super-enhancer-associated SCC suppressor.
These data comprehensively contrast differences between OSCC and OAC at both genomic and epigenomic levels, and reveal novel molecular features for further delineating the pathophysiological mechanisms and treatment strategies for these cancers.
Background
Nodal-skip metastasis (NSM) is found in esophageal squamous cell carcinoma (ESCC), but its prognostic role is controversial. This study aimed to investigate the prognostic value of NSM for ...thoracic ESCC patients.
Methods
Categorization of NSM was according to the N groupings of Japan Esophagus Society (JES) staging system, which is dependent on tumor location. Using the Kaplan–Meier method and Cox-regression analysis, this study retrospectively analyzed the overall survival (OS) for 2325 ESCC patients after radical esophagectomy at three high-volume esophageal cancer centers. Predictive models also were constructed.
Results
The overall NSM rate was 20% (229/1141): 37.4% in the in upper, 12.9% in the middle, and 22.2% in the lower thoracic ESCC. The patients with NSM always had a better prognosis than those without NSM. Furthermore, NSM was an independent prognostic factor for thoracic ESCC patients (hazard ratio HR, 0.633; 95% confidence interval CI, 0.499–0.803;
P
< 0.001). By integrating the prognostic values of NSM and N stage, the authors proposed the new N staging system. The categories defined by the new N staging system were more homogeneous in terms of OS than those defined by the current N system. Moreover, the new N system was shown to be an independent prognostic factor also for thoracic ESCC patients (HR, 1.607; 95% CI, 1.520–1.700;
P
< 0.001). Overall, the new N system had slightly better homogeneity, discriminatory ability, and monotonicity of gradient than the current N system.
Conclusions
This study emphasized the prognostic power of NSM and developed a modified node-staging system to improve the efficiency of the current International Union for Cancer Control (UICC)/American Joint Committee on Cancer (AJCC) N staging system.
•Clinical, serum proteomic, and radiomic data were integrated to develop classification models.•The models can accurately predict CCRT response of ESCC patients.•Nomogram models integrating ...multi-omics data achieved the best prediction performance.
Concurrent chemo-radiotherapy (CCRT) is the preferred non-surgical treatment for patients with locally advanced esophageal squamous cell carcinoma (ESCC). Unfortunately, some patients respond poorly, which leads to inappropriate or excessive treatment and affects patient survival. To accurately predict the response of ESCC patients to CCRT, we developed classification models based on the clinical, serum proteomic and radiomic data.
A total of 138 ESCC patients receiving CCRT were enrolled in this study and randomly split into a training cohort (n = 92) and a test cohort (n = 46). All patients were classified into either complete response (CR) or incomplete response (non-CR) groups according to RECIST1.1. Radiomic features were extracted by 3Dslicer. Serum proteomic data was obtained by Olink proximity extension assay. The logistic regression model with elastic-net penalty and the R-package “rms” v6.2–0 were applied to construct classification and nomogram models, respectively. The area under the receiver operating characteristic curves (AUC) was used to evaluate the predictive performance of the models.
Seven classification models based on multi-omics data were constructed, of which Model-COR, which integrates five clinical, five serum proteomic, and seven radiomic features, achieved the best predictive performance on the test cohort (AUC = 0.8357, 95 % CI: 0.7158–0.9556). Meanwhile, patients predicted to be CR by Model-COR showed significantly longer overall survival than those predicted to be non-CR in both cohorts (Log-rank P = 0.0014 and 0.027, respectively). Furthermore, two nomogram models based on multi-omics data also performed well in predicting response to CCRT (AUC = 0.8398 and 0.8483, respectively).
We developed and validated a multi-omics based classification model and two nomogram models for predicting the response of ESCC patients to CCRT, which achieved the best prediction performance by integrating clinical, serum Olink proteomic, and radiomic data. These models could be useful for personalized treatment decisions and more precise clinical radiotherapy and chemotherapy for ESCC patients.
Increasing evidence shows that dysregulated long non-coding RNAs (lncRNAs) can serve as potential biomarkers for cancer prognosis. However, lncRNA signatures, as potential prognostic biomarkers for ...esophageal squamous cell carcinoma (ESCC), have been seldom reported.
Based on our previous transcriptome RNA sequencing analysis from 15 paired ESCC tissues and adjacent normal tissues, we selected 10 lncRNAs with high score rank and characterized the expression of those lncRNAs, by qRT-PCR, in 138 ESCC and paired adjacent normal samples. These 138 patients were divided randomly into training (n = 77) and test (n = 59) groups. A prognostic signature of lncRNAs was identified in the training group and validated in the test group and in an independent cohort (n = 119). Multivariable Cox regression analysis evaluated the independence of the signature in overall survival (OS) and disease-free survival (DFS) prediction. GO and KEGG pathway analysis, combined with cell transwell and proliferation assays, are applied to explore the function of the three lncRNAs.
A novel three-lncRNA signature, comprised of RP11-366H4.1.1 (ENSG00000248370), LINC00460 (ENSG00000233532) and AC093850.2 (ENSG00000230838), was identified. The signature classified patients into high-risk and low-risk groups with different overall survival (OS) and disease-free survival (DFS). For the training group, median OS: 23.1 months vs. 39.1 months, P < 0.001; median DFS: 15.2 months vs. 33.3 months, P < 0.001. For the test group, median OS: 23 months vs. 59 months, P < 0.001; median DFS: 16.4 months vs. 50.8 months, P < 0.001. For the independent cohort, median OS: 22.4 months vs. 60.4 months, P < 0.001). The signature indicates that patients in the high-risk group show poor OS and DFS, whereas patients with a low-risk group show significantly better outcome. The independence of the signature was validated by multivariable Cox regression analysis. GO and KEGG pathway analysis for 588 protein-coding genes-associated with the three lncRNAs indicated that the three lncRNAs were involved in tumorigenesis. In vitro assays further demonstrated that the three lncRNAs promoted the migration and proliferation of ESCC cells.
The three-lncRNA signature is a novel and potential predictor of OS and DFS for patients with ESCC.
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