Gene Expression Profiling Reveals Distinct Molecular Subtypes of Esophageal Squamous Cell Carcinoma in Asian Populations

Hypoxia promotes histone H3K9 lactylation to enhance LAMC2 transcription in esophageal squamous cell carcinoma

Hypoxia promotes tumorigenesis and lactate accumulation in esophageal squamous cell carcinoma (ESCC). Lactate can induce histone lysine lactylation (Kla, a recently identified histone marks) to regulate transcription. However, the functional consequence of histone Kla under hypoxia in ESCC remains to be explored. Here, we reveal that hypoxia facilitates histone H3K9la to enhance LAMC2 transcription for proliferation of ESCC. We found that global level of Kla was elevated under hypoxia, and thus identified the landscape of histone Kla in ESCC by quantitative proteomics. Furthermore, we show a significant increase of H3K9la level induced by hypoxia. Next, MNase ChIP-seq and RNA-seq analysis suggest that H3K9la is enriched at the promoter of cell junction genes. Finally, we demonstrate that the histone H3K9la facilitates the expression of LAMC2 for ESCC invasion by in vivo and in vitro experiments. Briefly, our study reveals a vital role of histone Kla triggered by hypoxia in cancer.

Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.

Neoadjuvant Chemoradiotherapy Upregulates the Immunogenicity of Cold to Hot Tumors in Esophageal Cancer Patients

Objective

To test the hypothesis that neoadjuvant chemoradiotherapy (NACRT) is more effective against hot esophageal squamous cell carcinoma (ESCC) and that it may upregulate tumor immunogenicity.

Background

There have been several recent reports showing the efficacy of immune check-point inhibitors (ICIs) against esophageal cancer, especially immunologically hot tumors. In addition, several studies have suggested that chemotherapy and radiotherapy may convert cold tumors to hot tumors.

Methods

Of 105 ESCC patients who underwent surgery after NACRT between 2010 and 2018 at our hospital, 99 whose biopsy tissue samples were obtained were enrolled. Based on immunohistochemical analysis, tumors that were FOXA1 (+) and/or EYA2 (+) were defined as hot tumors, others were cold tumors. We then investigated the association between tumor immunogenicity and clinicopathological features.

Results

The 29 patients with hot tumors before NACRT had a significantly better 5-year disease-specific survival (DSS) rate than the remaining 70 patients with cold tumors (85% vs 64%; P = 0.036). In a multivariate analysis, tumor immunogenicity was a significant independent predictor of DSS. Of 68 patients without a pathological complete response (non-pCR) in their primary tumor, 51 (75%) had hot tumors after NACRT. Moreover, 75% (36/48) of tumors that were cold before NACRT were converted to hot tumors after NACRT.

Conclusions

Patients with hot ESCC tumors treated with NACRT plus esophagectomy had a better prognosis than those with cold tumors. NACRT upregulated cold tumor immunogenicity to hot tumors, suggesting NACRT may increase the sensitivity of ESCC to adjuvant ICIs.

Diclofenac exhibits cytotoxic activity associated with metabolic alterations and p53 induction in ESCC cell lines and decreases ESCC tumor burden in vivo

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive forms of human malignancy, often displaying limited therapeutic response. Here, we examine the non-steroidal anti-inflammatory drug diclofenac (DCF) as a novel therapeutic agent in ESCC using complementary in vitro and in vivo models. DCF selectively reduced viability of human ESCC cell lines TE11, KYSE150, and KYSE410 as compared with normal primary or immortalized esophageal keratinocytes. Apoptosis and altered cell cycle profiles were documented in DCF-treated TE11 and KYSE 150. In DCF-treated TE11, RNA-Sequencing identified differentially expressed genes and Ingenuity Pathway Analysis predicted alterations in pathways associated with cellular metabolism and p53 signaling. Downregulation of proteins associated with glycolysis was documented in DCF-treated TE11 and KYSE150. In response to DCF, TE11 cells further displayed reduced levels of ATP, pyruvate, and lactate. Evidence of mitochondrial depolarization and superoxide production was induced by DCF in TE11 and KYSE150. In DCF-treated TE11, the superoxide scavenger MitoTempo improved viability, supporting a role for mitochondrial reactive oxygen species in DCF-mediated toxicity. DCF treatment resulted in increased expression of p53 in TE11 and KYSE150. p53 was further identified as a mediator of DCF-mediated toxicity in TE11 as genetic depletion of p53 partially limited apoptosis in response to DCF. Consistent with the anticancer activity of DCF in vitro, the drug significantly decreased tumor burdene in syngeneic ESCC xenograft tumors and 4-nitroquinoline 1-oxide-mediated ESCC lesions in vivo. These preclinical findings identify DCF as an experimental therapeutic that should be explored further in ESCC.

PLEK2 and IFI6, representing mesenchymal and immune-suppressive microenvironment, predicts resistance to neoadjuvant immunotherapy in esophageal squamous cell carcinoma

BACKGROUND

Immunotherapy has largely improved clinical outcome of patients with esophageal squamous cell carcinoma (ESCC). However, a proportion of patients still fail to benefit. Thus, biomarkers predicting therapeutic resistance and underlying mechanism needs to be investigated.

METHODS

Transcriptomic profiling was applied in FFPE tissues from 103 ESCC patients, including surgical samples from 66 treatment-naïve patients with long-term follow-up, and endoscopic biopsies from 37 local advanced ESCC cases receiving neoadjuvant immunotherapy plus chemotherapy. Unsupervised clustering indicated an aggressive phenotype with mesenchymal character in 66 treatment-naïve samples. Univariant logistic regression was applied to identify candidate biomarkers potentially predicted resistance to neoadjuvant immunotherapy within the range of mesenchymal phenotype enriched genes. These biomarkers were further validated by immunohistochemistry. Putative mechanisms mediating immunotherapy resistance, as indicated by microenvironment and immune cell infiltration, were evaluated by transcriptomic data, and validated by multiplex immunofluorescence.

RESULTS

PLEK2 and IFI6, highly expressed in mesenchymal phenotype, were identified as novel biomarkers relating to non-MPR in neoadjuvant immunotherapy cohort [PLEK2high, OR (95% CI): 2.15 (1.07-4.33), P = 0.032; IFI6high, OR (95% CI): 2.21 (1.16-4.23), P = 0.016). PLEK2high and IFI6 high ESCC patients (versus low expressed patients) further exhibit higher chance of non-major pathological remissions (90%, P = 0.004) in neoadjuvant immunotherapy cohort and high mortality (78.9%, P = 0.05), poor prognosis in retrospective cohort. PLEK2high/IFI6high ESCC recapitulated mesenchymal phenotype, characterized by extracellular matrix composition and matrix remodeling. In addition, PLEK2high or IFI6high ESCC displayed an immune-unfavored microenvironment, represented by positive correlating with regulatory T cells, Helper 2 T cell as well as less infiltration of B cells, effector T cells and mast cells.

CONCLUSIONS

PLEK2 and IFI6 was discovered of first time to identify a distinct ESCC subpopulation cannot be benefited from neoadjuvant immunotherapy and present a poor survival, which putatively associated with mesenchymal and immune-suppressive microenvironment.

Effectiveness of Immune Checkpoint Inhibitors in Patients With Advanced Esophageal Squamous Cell Carcinoma: A Meta-analysis Including Low PD-L1 Subgroups

Importance

Immune checkpoint inhibitors (ICIs) have improved survival outcomes of patients with advanced esophageal squamous cell carcinoma in both first- and second-line settings. However, the benefit of ICIs in patients with low programmed death ligand 1 (PD-L1) expression remains unclear.

Objective

To derive survival data for patient subgroups with low PD-L1 expression from clinical trials comparing ICIs with chemotherapy in esophageal squamous cell carcinoma and to perform a pooled analysis.

Data Sources

Kaplan-Meier curves from the randomized clinical trials were extracted after a systematic search of Scopus, Embase, PubMed, and Web of Science from inception until October 1, 2021.

Study Selection

Randomized clinical trials that investigated the effectiveness of anti-PD-1-based regimens for advanced esophageal squamous cell carcinoma and that reported overall survival (OS), progression-free survival, or duration of response were included in this meta-analysis.

Data Extraction and Synthesis

Kaplan-Meier curves of all-comer populations, subgroups with high PD-L1, and those with low PD-L1 (when available) were extracted from published articles. A graphic reconstructive algorithm was used to calculate time-to-event outcomes from these curves. In studies with unreported curves for subgroups with low PD-L1 expression, KMSubtraction was used to impute survival data. KMSubtraction is a workflow to derive unreported subgroup survival data with from subgroups. An individual patient data pooled analysis including previously reported and newly imputed subgroups was conducted for trials with the same treatment line and PD-L1 scoring system. Data analysis was conducted from January 1, 2022, to June 30, 2022.

Main Outcomes and Measures

Primary outcomes included Kaplan-Meier curves and hazard ratios (HRs) for OS for subgroups with low PD-L1 expression. Secondary outcomes included progression-free survival and duration of response.

Results

The randomized clinical trials CheckMate-648, ESCORT-1st, KEYNOTE-590, ORIENT-15, KEYNOTE-181, ESCORT, RATIONALE-302, ATTRACTION-3, and ORIENT-2 were included, totaling 4752 patients. In the pooled analysis of first-line trials that evaluated a tumor proportion score (CheckMate-648 and ESCORT-1st), no significant benefit in OS was observed with immunochemotherapy compared with chemotherapy in the subgroup of patients who had a tumor proportion score lower than 1% (HR, 0.91; 95% CI, 0.74-1.12; P = .38) compared with chemotherapy. In the pooled analysis of first-line trials that evaluated combined positive score (KEYNOTE-590 and ORIENT-15), there was a significant but modest OS benefit for immunochemotherapy compared with chemotherapy in the subgroup with a combined positive score lower than 10 (HR, 0.77; 95% CI, 0.62-0.94; P = .01).

Conclusions and Relevance

Findings suggest a lack of survival benefit of ICI-based regimens in the first-line setting compared with chemotherapy alone in the subgroup with a tumor proportion score lower than 1%.

The Molecular Characterization of Genetic Abnormalities in Esophageal Squamous Cell Carcinoma May Foster the Development of Targeted Therapies

Esophageal cancer is among the most common tumors in the world and is associated with poor outcomes, with a 5-year survival rate of about 10-20%. Two main histological subtypes are observed: esophageal squamous cell carcinoma (ESCC), more frequent among Asian populations, and esophageal adenocarcinoma (EAC), the predominant type in Western populations. The development of molecular analysis techniques has led to the definition of the molecular alterations observed in ESCC, consistently differing from those observed in EAC. The genetic alterations observed are complex and heterogeneous and involve gene mutations, gene deletions and gene amplifications. However, despite the consistent progress in the definition of the molecular basis of ESCC, precision oncology for these patients is still virtually absent. The recent identification of molecular subtypes of ESCC with clinical relevance may foster the development of new therapeutic strategies. It is estimated that about 40% of the genetic alterations observed in ESCC are actionable. Furthermore, the recent introduction of solid tumor immunotherapy with immune checkpoint inhibitors (ICIs) showed that a minority of ESCC patients are responsive, and the administration of ICIs, in combination with standard chemotherapy, significantly improves overall survival over chemotherapy in ESCC patients with advanced disease.

Molecular subtyping of esophageal squamous cell carcinoma by large-scale transcriptional profiling: Characterization, therapeutic targets, and prognostic value

The tumor heterogeneity of the transcriptional profiles is independent of genetic variation. Several studies have successfully identified esophageal squamous cell carcinoma (ESCC) subtypes based on the somatic mutation profile and copy number variations on the genome. However, transcriptome-based classification is limited. In this study, we classified 141 patients with ESCC into three subtypes (Subtype 1, Subtype 2, and Subtype 3) via tumor sample gene expression profiling. Differential gene expression (DGE) analysis of paired tumor and normal samples for each subtype revealed significant difference among subtypes. Moreover, the degree of change in the expression levels of most genes gradually increased from Subtype 1 to Subtype 3. Gene set enrichment analysis (GSEA) identified the representative pathways in each subtype: Subtype 1, abnormal Wnt signaling pathway activation; Subtype 2, inhibition of glycogen metabolism; and Subtype 3, downregulation of neutrophil degranulation process. Weighted gene co-expression network analysis (WGCNA) was used to elucidate the finer regulation of biological pathways and discover hub genes. Subsequently, nine hub genes (CORO1A, CD180, SASH3, CD52, CD300A, CD14, DUSP1, KIF14, and MCM2) were validated to be associated with survival in ESCC based on the RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database. The clustering analysis of ESCC granted better understanding of the molecular characteristics of ESCC and led to the discover of new potential therapeutic targets that may contribute to the clinical treatment of ESCC.

Define the Two Molecular Subtypes of Epithelioid Malignant Pleural Mesothelioma

Malignant pleural mesothelioma (MPM) is a fatal disease of respiratory system. Despite the availability of invasive biomarkers with promising results, there are still significant diagnostic and therapeutic challenges in the treatment of MPM. One of three main mesothelioma cell types, epithelioid mesothelioma makes up approximately 70% of all mesothelioma cases. Different observational findings are under process, but the molecular heterogeneity and pathogenesis of epithelioid malignant pleural mesothelioma (eMPM) are still not well understood. Through molecular analysis, expression profiling data were used to determine the possibility and optimal number of eMPM molecular subtypes. Next, clinicopathological characteristics and different molecular pathways of each subtype were analyzed to prospect the clinical applications and advanced mechanisms of eMPM. In this study, we identified two distinct epithelioid malignant pleural mesothelioma subtypes with distinct gene expression patterns. Subtype I eMPMs were involved in steroid hormone biosynthesis, porphyrin and chlorophyll metabolism, and drug metabolism, while subtype II eMPMs were involved in rational metabolism, tyrosine metabolism, and chemical carcinogenesis pathways. Additionally, we identified potential subtype-specific therapeutic targets, including CCNE1, EPHA3, RNF43, ROS1, and RSPO2 for subtype I and CDKN2A and RET for subtype II. Considering the need for potent diagnostic and therapeutic biomarkers for eMPM, we are anticipating that our findings will help both in exploring underlying mechanisms in the development of eMPM and in designing targeted therapy for eMPM.

Stratification From Heterogeneity of the Cell-Death Signal Enables Prognosis Prediction and Immune Microenvironment Characterization in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is the primary subtype of esophageal cancer (EC) characterized by a high incidence rate and extremely poor prognosis worldwide. Previous studies suggested that the specific cell death signal was linked to different immune subtypes in multiple cancers, while a comprehensive investigation on ESCC is to be performed yet. In the current study, we dissected different cell death signals in ESCC tumors and then integrated that functional information to stratify ESCC patients into different immunogenic cell death (ICD) subtypes. By systematically analyzing the transcriptomes of 857 patients and proteomic profile of 124 patients, we found that the signals of necroptosis, pyroptosis, and ferroptosis are positively associated with activated immunity in ESCC. We identified two ICD pattern terms, namely, ICD-high and ICD-low subtypes that positively correlated to both progression-free survival and overall survival. In addition, cell fraction deconvolution analysis revealed that more infiltrated leukocytes were enriched in ICD-high types, especially antigen-presenting cells, such as dendritic cells and macrophages. With the XGBoost algorithm, we further developed a 14-gene signature which can simplify the subtyping for allocating new samples, by which we validated the prognosis value of the signature and proved that the ICD score scheme could serve as a promising biomarker for stratifying patients with immunotherapy in several immune checkpoint blockade treatment cohorts. Collectively, we successfully constructed the ICD scheme, which enables predicting of the prognosis or immunotherapy efficacy in ESCC patients and uncovered the critical interplay between cell death signals and immune status in ESCC.

Molecular subclassification of gastrointestinal cancers based on cancer stem cell traits

Human gastrointestinal malignancies are highly heterogeneous cancers. Clinically, heterogeneity largely contributes to tumor progression and resistance to therapy. Heterogeneity within gastrointestinal cancers is defined by molecular subtypes in genomic and transcriptomic analyses. Cancer stem cells (CSCs) have been demonstrated to be a major source of tumor heterogeneity; therefore, assessing tumor heterogeneity by CSC trait-guided classification of gastrointestinal cancers is essential for the development of effective therapies. CSCs share critical features with embryonic stem cells (ESCs). Molecular investigations have revealed that embryonic genes and developmental signaling pathways regulating the properties of ESCs or cell lineage differentiation are abnormally active and might be oncofetal drivers in certain tumor subtypes. Currently, multiple strategies allow comprehensive identification of tumor subtype-specific oncofetal signatures and evaluation of subtype-specific therapies. In this review, we summarize current knowledge concerning the molecular classification of gastrointestinal malignancies based on CSC features and elucidate their clinical relevance. We also outline strategies for molecular subtype identification and subtype-based therapies. Finally, we explore how clinical implementation of tumor classification by CSC subtype might facilitate the development of more effective personalized therapies for gastrointestinal cancers.

Identification of Distinct Molecular Subtypes of Endometrioid Adenocarcinoma

Endometrial carcinoma (EC) is one of the most common gynecological cancers worldwide. Endometrioid adenocarcinoma (EAC) is the major form of EC, accounting for 75–80% of cases. Currently, there is no molecular classification system for EAC, so there are no corresponding targeted treatments. In this study, we identified two distinct molecular subtypes of EAC with different gene expression patterns and clinicopathologic characteristics. Subtype I EAC cases, accounting for the majority of cases (56%), were associated with an earlier stage, a more well-differentiated grade, a lower tumor invasion rate, and a more favorable prognosis, and the median tumor necrosis percent (15%) was also significantly higher in subtype I EAC. In contrast, subtype II EAC represents high-grade EAC, with a higher tumor invasion rate and tumor weight. The up-regulated genes in subtype I EAC were associated with the immune response, defense response, cell motion, and cell motility pathway, whereas the up-regulated genes in subtype II EAC were associated with the cell cycle, DNA replication, and RNA processing pathways. Additionally, we identified three potential subtype-specific biomarkers, comprising MDM2 (MDM2 proto-oncogene) for subtype I, and MSH2 (mutS homolog 2) and MSH6 (mutS homolog 6) for subtype II.

Identification of Clinical Relevant Molecular Subtypes of Pheochromocytoma

Pheochromocytoma (PCC) is a rare neuroendocrine tumor of the adrenal gland with a high rate of mortality if diagnosed at a late stage. Common symptoms of pheochromocytoma include headache, anxiety, palpitation, and diaphoresis. Different treatments are under observation for PCC but there is still no effective treatment option. Recently, the gene expression profiling of various tumors has provided new subtype-specific options for targeted therapies. In this study, using data sets from TCGA and the GSE19422 cohorts, we identified two distinct PCC subtypes with distinct gene expression patterns. Genes enriched in Subtype I PCCs were involved in the dopaminergic synapse, nicotine addiction, and long-term depression pathways, while genes enriched in subtype II PCCs were involved in protein digestion and absorption, vascular smooth muscle contraction, and ECM receptor interaction pathways. We further identified subtype specific genes such as ALK, IGF1R, RET, and RSPO2 for subtype I and EGFR, ESR1, and SMO for subtype II, the overexpression of which led to cell invasion and tumorigenesis. These genes identified in the present research may serve as potential subtype-specific therapeutic targets to understand the underlying mechanisms of tumorigenesis. Our findings may further guide towards the development of targeted therapies and potential molecular biomarkers against PCC.

A Prognostic Signature Based on Immunogenomic Profiling Offers Guidance for Esophageal Squamous Cell Cancer Treatment

Our study aimed to develop an immune prognostic signature that could provide accurate guidance for the treatment of esophageal squamous cell cancer (ESCC). By implementing Single-Sample Gene Set Enrichment Analysis (ssGSEA), we established two ESCC subtypes (Immunity High and Immunity Low) in GSE53625 based on immune-genomic profiling of twenty-nine immune signature. We verified the reliability and reproducibility of this classification in the TCGA database. Immunity High could respond optimally to immunotherapy due to higher expression of immune checkpoints, including PD1, PDL1, CTLA4, and CD80. We used WGCNA analysis to explore the underlying regulatory mechanism of the Immunity High group. We further identified differentially expressed immune-related genes (CCR5, TSPAN2) in GSE53625 and constructed an independent two-gene prognostic signature we internally validated through calibration plots. We established that high-risk ESCC patients had worse overall survival (P=0.002, HR=2.03). Besides, high-risk ESCC patients had elevated levels of infiltrating follicle-helper T cells, naïve B cells, and macrophages as well as had overexpressed levels of some immune checkpoints, including B3H7, CTLA4, CD83, OX40L, and GEM. Moreover, through analyzing the Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk group demonstrated drug resistance to some chemotherapy and targeted drugs such as paclitaxel, gefitinib, erlotinib, and lapatinib. Furthermore, we established a robust nomogram model to predict the clinical outcome in ESCC patients. Altogether, our proposed immune prognostic signature constitutes a clinically potential biomarker that will aid in evaluating ESCC outcomes and promote personalized treatment.

A model for predicting prognosis in patients with esophageal squamous cell carcinoma based on joint representation learning

Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancer types with a poor prognosis due to the lack of symptoms in the early stages and a delayed diagnosis. The present study aimed to identify the risk factors significantly associated with prognosis and to search for novel effective diagnostic modalities for patients with early-stage ESCC. mRNA and methylation data of patients with ESCC and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database, and the representation features were screened using deep learning autoencoder. The univariate Cox regression model was used to select the prognosis-related features from the representation features. K-means clustering was used to cluster the TCGA samples. Support vector machine classifier was constructed based on the top 75 features mostly associated with the risk subgroups obtained from K-means clustering. Two ArrayExpress datasets were used to verify the reliability of the obtained risk subgroups. The differentially expressed genes and methylation genes (DEGs and DMGs) between the risk subgroups were analyzed, and pathway enrichment analysis was performed. A total of 500 representation features were produced. Using K-means clustering, the TCGA samples were clustered into two risk subgroups with significantly different overall survival rates. Joint multimodal representation strategy, which showed a good model fitness (C-index=0.760), outperformed early-fusion autoencoder strategy. The joint representation learning-based classification model had good robustness. A total of 1,107 DEGs and 199 DMGs were screened out between the two risk subgroups. The DEGs were involved in 70 pathways, the majority of which were correlated with metastasis and proliferation of various cancer types, including cytokine-cytokine receptor interaction, cell adhesion molecules PPAR signaling pathway, pathways in cancer, transcriptional misregulation in cancer and ECM-receptor interaction pathways. The two survival subgroups obtained via the joint representation learning-based model had good robustness, and had prognostic significance for patients with ESCC.

Gene expression profile identifies distinct molecular subtypes and potential therapeutic genes in Merkel cell carcinoma

Merkel cell carcinoma (MCC) is a rare primary cutaneous neoplasm of neuroendocrine carcinoma of the skin. About 80% of the MCC occurs due to Merkel cell polyomavirus (MCPyV) and 20% of the tumors usually occur due to severe UV exposure which is a more aggressive type of MCC. It tends to have an increased incidence rate among elderly and immunosuppressed individuals. On therapeutic level, sub-classification of MCC through molecular subtyping has emerged as a promising technique for MCC prognosis. In current study, two consistent distinct molecular subtypes of MCCs were identified using gene expression profiling data. Subtypes I MCCs were associated with spliceosome, DNA replication and cellular pathways. On the other hand, genes overexpressed in subtype II were found active in TNF signalling pathway and MAPK signalling pathway. We proposed different therapeutic targets based on subtype specificity, such as PTCH1, CDKN2A, AURKA in case of subtype I and MCL1, FGFR2 for subtype II. Such findings may provide fruitful knowledge to understand the intrinsic subtypes of MCCs and the pathways involved in distinct subtype oncogenesis, and will further advance the knowledge in developing a specific therapeutic strategy for these MCC subtypes.

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Merkel cell carcinoma (MCC) a rare and highly aggressive neuroendocrine carcinoma of the skin

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Sub-classification of MCC through molecular subtyping

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Identification of two distinct molecular subtypes of MCCs using gene expression profiling data

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Classification of different therapeutic targets based on subtype specificity

Analysis of Differentially Expressed Genes in a Chinese Cohort of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a leading malignancy in China with both high incidence and mortality. Towards improving outcomes, clinically-relevant biomarkers are urgently needed for use as prognostic and treatment targets. Herein we applied RNA-seq for deep sequencing of ten matched pairs of ESCC and adjacent non-cancerous tissues (NT) from Chinese patients. Transcriptomic data mapped to approximately 64% of all annotated genes with 2,047 and 708 unigenes being differentially up-regulated and down-regulated, respectively, between ESCCs and NT samples (p<0.05). Dividing cases by pathological grade revealed significant differentially expressed genes (DEG) between ESCC and NT in both low and high differentiation cases (p<0.05) whereas gene expression differences were not significantly different between high and low differentiation ESCC tissues (p=0.053). Moreover, the majority of ESCC and NT tissues formed clusters in principal component analyses. The veracity of the DEG list was validated in a larger cohort of 45 patient samples, with down-regulated CLIC3, up-regulated CLIC4 and unchanged expression of CLIC2 confirmed in ESCC using quantitative PCR and Western blotting. Our data reveal both previously identified ESCC biomarkers along with novel candidates and represent a ready resource of DEGs in ESCC for further investigation.

OSacc: Gene Expression-Based Survival Analysis Web Tool For Adrenocortical Carcinoma

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan–Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at http://bioinfo.henu.edu.cn/ACC/ACCList.jsp.

Biological Significance of Tumor Heterogeneity in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common and aggressive malignancy, with hitherto dismal clinical outcome. Genomic analyses of patient samples reveal a complex heterogeneous landscape for ESCC, which presents in both intertumor and intratumor forms, manifests at both genomic and epigenomic levels, and contributes significantly to tumor evolution, drug resistance, and metastasis. Here, we review the important molecular characteristics underlying ESCC heterogeneity, with an emphasis on genomic aberrations and their functional contribution to cancer evolutionary trajectories. We further discuss how novel experimental tools, including single-cell sequencing and three-dimensional organoids, may advance our understanding of tumor heterogeneity. Lastly, we suggest that deciphering the mechanisms governing tumor heterogeneity holds the potential to developing precision therapeutics for ESCC patients.