Autophagy-Related Three-Gene Prognostic Signature for Predicting Survival in Esophageal Squamous Cell Carcinoma

A novel fatty acid metabolism-related signature identifies MUC4 as a novel therapy target for esophageal squamous cell carcinoma

Fatty acid metabolism has been identified as an emerging hallmark of cancer, which was closely associated with cancer prognosis. Whether fatty acid metabolism-related genes (FMGs) signature play a more crucial role in biological behavior of esophageal squamous cell carcinoma (ESCC) prognosis remains unknown. Thus, we aimed to identify a reliable FMGs signature for assisting treatment decisions and prognosis evaluation of ESCC. In the present study, we conducted consensus clustering analysis on 259 publicly available ESCC samples. The clinical information was downloaded from The Cancer Genome Atlas (TCGA, 80 ESCC samples) and Gene Expression Omnibus (GEO) database (GSE53625, 179 ESCC samples). A consensus clustering arithmetic was used to determine the FMGs molecular subtypes, and survival outcomes and immune features were evaluated among the different subtypes. Kaplan-Meier analysis and the receiver operating characteristic (ROC) was applied to evaluate the reliability of the risk model in training cohort, validation cohort and all cohorts. A nomogram to predict patients' 1-year, 3-year and 5-year survival rate was also studied. Finally, CCK-8 assay, wound healing assay, and transwell assay were implemented to evaluate the inherent mechanisms of FMGs for tumorigenesis in ESCC. Two subtypes were identified by consensus clustering, of which cluster 2 is preferentially associated with poor prognosis, lower immune cell infiltration. A fatty acid (FA) metabolism-related risk model containing eight genes (FZD10, TACSTD2, MUC4, PDLIM1, PRSS12, BAALC, DNAJA2 and ALOX12B) was established. High-risk group patients displayed worse survival, higher stromal, immune and ESTIMATE scores than in the low-risk group. Moreover, a nomogram revealed good predictive ability of clinical outcomes in ESCC patients. The results of qRT-PCR analysis revealed that the MUC4 and BAALC had high expression level, and FZD10, PDLIM1, TACSTD2, ALOX12B had low expression level in ESCC cells. In vitro, silencing MUC4 remarkably inhibited ESCC cell proliferation, invasion and migration. Our study fills the gap of FMGs signature in predicting the prognosis of ESCC patients. These findings revealed that cluster subtypes and risk model of FMGs had effects on survival prediction, and were expected to be the potential promising targets for ESCC.

Autophagy and nuclear morphometry are associated with histopathologic features in esophageal squamous cell carcinoma

Less than 15% of patients with esophageal squamous cell carcinoma (ESCC) survive 5 years after diagnosis. A better understanding of the biology of these tumors and the development of clinical biomarkers is needed. Autophagy is a physiological mechanism involved in the turnover of cellular components that plays a key role in cancer. This study evaluated the differential levels of three key regulators of autophagy (SQSTM1, MAP1LC3B, and BECN1) in patients with ESCC, associating autophagy with histopathologic features, including the grade of differentiation, mitotic rate, inflammation score, and the intensity of tumor-infiltrating lymphocytes. Nuclear morphometry of the tumor parenchyma was also assessed, associating it with autophagy and histopathology. All three markers significantly increased in patients with ESCC compared to the control group. Based on the mean expression of each protein in the control group, 57% of patients with ESCC had high levels of all three markers compared to control patients (14%). The most frequent profiles found in ESCC were BECNhigh/MAP1LC3high and BECNhigh/SQSTM1high. According to the TCGA database, we found that the main autophagy genes were upregulated in ESCC. Moreover, high levels of autophagy markers were associated with a poor prognosis. Considering nuclear morphometry, ESCC samples showed a significant reduction in nuclear area, which was strongly negatively correlated with autophagy. Finally, the percentage of normal nuclei was associated with tumor differentiation, while poorly differentiated tumors showed lower SQSTM1 levels. ESCC progression may involve increased autophagy and changes in nuclear structure, associated with clinically relevant histopathological features. KEY MESSAGES: Autophagy markers are co-increased in primary ESCC. Autophagy negatively correlates with nuclear morphometry in ESCC parenchyma. Autophagy and nuclear morphometry are associated with histopathological features. Autophagy is increased in ESCC-TCGA database and associated with poor prognosis.

A prognostic nomogram that includes MPV in esophageal squamous cell carcinoma

BACKGROUND

Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients.

METHODS

The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity.

RESULTS

Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts.

CONCLUSIONS

The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.

Regulation and Functions of α6-Integrin (CD49f) in Cancer Biology

Over the past decades, our knowledge of integrins has evolved from being understood as simple cell surface adhesion molecules to receptors that have a complex range of intracellular and extracellular functions, such as delivering chemical and mechanical signals to cells. Consequently, they actively control cellular proliferation, differentiation, and apoptosis. Dysregulation of integrin signaling is a major factor in the development and progression of many tumors. Many reviews have covered the broader integrin family in molecular and cellular studies and its roles in diseases. Nevertheless, further understanding of the mechanisms specific to an individual subunit of different heterodimers is more useful. Thus, we describe the current understanding of and exploratory investigations on the α6-integrin subunit (CD49f, VLA6; encoded by the gene itga6) in normal and cancer cells. The roles of ITGA6 in cell adhesion, stemness, metastasis, angiogenesis, and drug resistance, and as a diagnosis biomarker, are discussed. The role of ITGA6 differs based on several features, such as cell background, cancer type, and post-transcriptional alterations. In addition, exosomal ITGA6 also implies metastatic organotropism. The importance of ITGA6 in the progression of a number of cancers, including hematological malignancies, suggests its potential usage as a novel prognostic or diagnostic marker and useful therapeutic target for better clinical outcomes.

Characteristics and response to next-generation sequencing-guided therapy in locally advanced or metastatic esophageal cancer

Esophageal cancer (EC) is a main cause of cancer-related deaths. However, genomic alterations and the clinical value of next-generation sequencing (NGS) in advanced or metastatic EC for precision therapy remain largely unclear. Herein, we performed comprehensive analyses on a cohort of 47 individuals with advanced or metastatic EC who underwent NGS between May 2017 and February 2020. Eventually, 227 mutated genes were identified in the cohort. TP53, NQO1, DPYD, GSTM1, XRCC1 and ERCC1 were the most mutated genes and associated with immune cell infiltration, autophagy and hypoxia. Patients who received NGS-guided treatments exhibited better objective remission rate (ORR) (72.22%), disease control rate (DCR) (88.89%), overall survival (OS) (P = .0019) and progression-free survival (PFS) (P = .0077) than those not receiving NGS-guided therapies. The multivariate analyses further demonstrated that the NGS-guided therapy was an independently prognostic factor (OS: hazard radio [HR] 0.31, 95% coincidence interval [CI] 0.1-0.97, P = .04). In conclusion, we depicted a comprehensive mutational landscape of 47 patients with locally advanced or metastatic EC and illustrated the utility of NGS testing to guide clinical management in improving ORR, DCR, OS and PFS.

A more novel and robust gene signature predicts outcome in patients with esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The tumor microenvironment (TME) mainly comprises tumor cells and tumor-infiltrating immune cells mixed with stromal components. The latest research has displayed that tumor immune cell infiltration (ICI) is closely connected with the ESCC patients' clinical prognosis. This study was designed to construct a gene signature based on the ICI of ESCC to predict prognosis.

METHODS

Based on the selection criteria we set, the eligible ESCC cases from the GSE53625 and TCGA-ESCA datasets were chosen for the training cohort and the validation cohort, respectively. Unsupervised clustering detailed grouped ESCC cases of the training cohort based on the ICI profile. We determined the differential expression genes (DEGs) between the ICI clusters, and, subsequently, we adopted the univariate Cox analysis to recognize DEGs with prognostic potential. These screened DEGs underwent a Lasso regression, which then generated a gene signature. The harvested signature's predictive ability was further examined by the Kaplan-Meier analysis, Cox analysis, ROC, IAUC, and IBS. More importantly, we listed similar studies in the most recent year and compared theirs with ours. We performed the functional annotation, immune relevant signature correlation analysis, and immune infiltrating analysis to thoroughly understand the functional mechanism of the signature and the immune cells' roles in the gene signature's predicting capacity.

RESULTS

A sixteen-gene signature (ARSD, BCAT1, BIK, CLDN11, DLEU7-AS1, GGH, IGFBP2, LINC01037, LINC01446, LINC01497, M1AP, PCSK2, PCSK5, PPP2R2A, TIGD7, and TMSB4X) was generated from the Lasso model. We then confirmed the signature as having solid and stable prognostic capacity by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GSEA uncovered the specifically mechanism of action related to the gene signature. Two immune relevant signatures, including GZMA and LAG3 were identified associating with our signature. The immune-infiltrating analysis identified crucial roles of resting mast cells, which potentially support the sixteen-gene signature's prognosis ability.

CONCLUSIONS

We discovered a robust sixteen-gene signature that can accurately predict ESCC prognosis. The immune relevant signatures, GZMA and LAG3, and resting mast cells infiltrating were closely linked to the sixteen-gene signature's ability.

FADD as a key molecular player in cancer progression

Cancer is a leading disease-related cause of death worldwide. Despite advances in therapeutic interventions, cancer remains a major global public health problem. Cancer pathogenesis is extremely intricate and largely unknown. Fas-associated protein with death domain (FADD) was initially identified as an adaptor protein for death receptor-mediated extrinsic apoptosis. Recent evidence suggests that FADD plays a vital role in non-apoptotic cellular processes, such as proliferation, autophagy, and necroptosis. FADD expression and activity of are modulated by a complicated network of processes, such as DNA methylation, non-coding RNA, and post-translational modification. FADD dysregulation has been shown to be closely associated with the pathogenesis of numerous types of cancer. However, the detailed mechanisms of FADD dysregulation involved in cancer progression are still not fully understood. This review mainly summarizes recent findings on the structure, functions, and regulatory mechanisms of FADD and focuses on its role in cancer progression. The clinical implications of FADD as a biomarker and therapeutic target for cancer patients are also discussed. The information reviewed herein may expand researchers’ understanding of FADD and contribute to the development of FADD-based therapeutic strategies for cancer patients.