Oesophageal squamous cell carcinoma (ESCC) is a lethal malignancy. Immune checkpoint inhibitors (ICIs) showed great clinical benefits for patients with ESCC. We aimed to construct a model predicting prognosis and response to ICIs by integrating diverse programmed cell death (PCD) forms. Genes related to 14 PCDs were collected to generate multi-gene signatures, including apoptosis, necroptosis, pyroptosis, ferroptosis, and cuproptosis. Bulk and single-cell RNA transcriptome datasets were used to develop and validate the model. We assessed the functions of two necroptosis-related genes in ESCC cells by Western blot, co-immunoprecipitation (Co-IP), LDH release assay, CCK-8, and migration assay, followed by immunohistochemistry (IHC) staining on samples of patients with ESCC (n = 67). We built and validated a 16-gene prognostic combined cell death index (CCDI) by combining immunogenic cell death (ICD) and necroptosis signatures. The CCDI could also predict response to ICIs in cancer, as shown by Tumour Immune Dysfunction and Exclusion (TIDE) analysis, confirmed in four independent ICI clinical trials. Trajectory analysis revealed that HOOK1 and CUL4A might affect ESCC cell fate. We found that HOOK1 induced necroptosis and inhibited the proliferation and migration of ESCC cells, while CUL4A exhibited the opposite effects. Co-IP assay confirmed that HOOK1 and CUL4A promoted and reduced necrosome formation in ESCC cells. Data from patients with ESCC further supported that HOOK1 and CUL4A might be a tumour suppressor and oncogene, respectively. We constructed a CCDI model with potential in predicting prognosis and response to ICIs in cancer. HOOK1 and CUL4A in the CCDI model are crucial prognostic biomarkers in ESCC. The Natural Science Foundation of China [82172786], The National Cancer Center Climbing Fund of China [NCC201908B06], The Natural Science Foundation of Heilongjiang Province [LH2021H077].

Background: The ubiquitin-conjugating enzyme E2 T (UBE2T) has been shown to contribute to several types of cancer. However, no publication has reported its implication in esophageal squamous cell cancer (ESCC).Methods: We explored several public databases, including The Cancer Genome Atlas (TCGA), Oncomine, and gene expression Omnibus (GEO). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and gene set enrichment analysis (GSEA) were adopted to explore involved signaling pathways. We used R software to develop prognostic gene signatures with the LASSO and stepwise Cox regression analysis, separately. Immunohistochemistry staining was performed to detect UBE2T in 90 ESCC patients, followed by survival analysis. We also used an R package pRRophetic to evaluate chemotherapy sensitivity for the TCGA–ESCC cohort.Results: We found significantly increased UBE2T transcript levels and DNA copy numbers in ESCC tissues. UBE2T was associated with the p53 signaling pathway, cell cycle, Fanconi anemia pathway, and DNA replication, as indicated by Go, KEGG pathway enrichment analysis. These pathways were also upregulated in ESCC. The prognostic signatures with UBE2T-associated genes could stratify ESCC patients into low- and high-risk groups with significantly different overall survival in the TCGA–ESCC cohort. We also validated the association of UBE2T with unfavorable survival in 90 ESCC patients recruited for this study. Moreover, we found that the low-risk group was significantly more sensitive to chemotherapy than the high-risk group.Conclusions: UBE2T is involved in the development of ESCC, and gene signatures derived from UBE2T-associated genes are predictive of prognosis in ESCC.

The family with sequence similarity 72 Member A (FAM72A) is overexpressed in several types of cancer. However, its contributions to tumorigenesis remain largely unknown. Based on The Cancer Genome Atlas (TCGA) database, FAM72A was upregulated across 33 types of cancer. Accordingly, high levels of FAM72A predicted inferior outcomes in half of the cancer types using survival analysis (the Kaplan-Meier curve and univariate Cox regression model). Receiver operating characteristic (ROC) analysis demonstrated that FAM72A showed high accuracy in distinguishing cancerous tissues from normal ones. FAM72A was correlated with immune and stromal scores and immune cell infiltrations in various tumors. Moreover, FAM72A was also associated with tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint genes. Immunophenoscore (IPS) further validated that the FAM72A^low tumor showed high immunogenicity and tended to respond to anti-PD1/PDL1/PDL2, anti-CTLA4 treatment, and combined immunotherapies. We also investigated the functional role of FAM72A in lung adenocarcinoma (LUAD). In vitro studies demonstrated that the ectopic expression of FAM72A accelerated the proliferation and migration of NSCLC cells, whereas silencing FAM72A showed the opposite effects on them. In short, FAM72A had prognostic potential and correlated with tumor immunogenicity in various tumors. Functional analysis indicated that FAM72A is an oncogene in LUAD.