Investigation of an FGFR-Signaling-Related Prognostic Model and Immune Landscape in Head and Neck Squamous Cell Carcinoma

Spatial Transcriptomic and Metabolomic Landscapes of Oral Submucous Fibrosis-Derived Oral Squamous Cell Carcinoma and its Tumor Microenvironment

In South and Southeast Asia, the habit of chewing betel nuts is prevalent, which leads to oral submucous fibrosis (OSF). OSF is a well-established precancerous lesion, and a portion of OSF cases eventually progress to oral squamous cell carcinoma (OSCC). However, the specific molecular mechanisms underlying the malignant transformation of OSCC from OSF are poorly understood. In this study, the leading-edge techniques of Spatial Transcriptomics (ST) and Spatial Metabolomics (SM) are integrated to obtain spatial location information of cancer cells, fibroblasts, and immune cells, as well as the transcriptomic and metabolomic landscapes in OSF-derived OSCC tissues. This work reveals for the first time that some OSF-derived OSCC cells undergo partial epithelial-mesenchymal transition (pEMT) within the in situ carcinoma (ISC) region, eventually acquiring fibroblast-like phenotypes and participating in collagen deposition. Complex interactions among epithelial cells, fibroblasts, and immune cells in the tumor microenvironment are demonstrated. Most importantly, significant metabolic reprogramming in OSF-derived OSCC, including abnormal polyamine metabolism, potentially playing a pivotal role in promoting tumorigenesis and immune evasion is discovered. The ST and SM data in this study shed new light on deciphering the mechanisms of OSF-derived OSCC. The work also offers invaluable clues for the prevention and treatment of OSCC.

Integrated bioinformatics analysis of SEMA3C in tongue squamous cell carcinoma using machine-learning strategies

Tongue squamous cell carcinoma (TSCC) is an aggressive oral cancer with a high incidence of metastasis and poor prognosis. We aim to identify and verify potential biomarkers for TSCC using bioinformatics analysis. To begin with, we examined clinical and RNA expression information of individuals with TSCC from the Gene Expression Omnibus (GEO) database. Differential expression analysis and functional analysis were conducted. Multiple machine-learning strategies were next employed to screen and determine the hub gene, and receiver operating characteristic (ROC) analysis was used to assess diagnostic value. Semaphorin3C (SEMA3C) was identified as a critical biomarker, presenting high diagnostic accuracy for TSCC. In the validation cohorts, SEMA3C exhibited high expression levels in TSCC. The high expression of SEMA3C was a poor prognostic factor in TSCC by the Kaplan-Meier curve. Based on the Gene Ontology (GO) analysis, SEMA3C was mapped in terms related to cell adhesion, positive regulation of JAK-STAT, positive regulation of stem cell maintenance, and positive regulation of NF-κB activity. Single-cell RNA sequencing (ScRNA-seq) analysis showed cells expressing SEMA3C were predominantly tumor cells. Then, we further verified that SEMA3C had high expression in TSCC clinical samples. In addition, the knockdown of SEMA3C suppressed the proliferation, migration, and invasion of TSCC cells in vitro. This study is the first to report the involvement of SEMA3C in TSCC, suggesting that upregulated SEMA3C could be a novel and critical potential biomarker for future predictive diagnostics, prevention, prognostic assessment, and personalized medical services in TSCC.

A novel oxidative stress-related gene signature as an indicator of prognosis and immunotherapy responses in HNSCC

PURPOSE

To identify molecular subtypes of oxidative stress-related genes in head and neck squamous cell carcinoma (HNSCC) and to construct a scoring model of oxidative stress-related genes.

METHODS

R language based scRNA-seq and bulk RNA-seq analyses were used to identify molecular isoforms of oxidative stress-related genes in HNSCC. An oxidative stress-related gene scoring (OSRS) model was constructed, which were verified through online data and immunohistochemical staining of clinical samples.

RESULTS

Using TCGA-HNSCC datasets, nine predictive genes for overall patient survival, rarely reported in previous similar studies, were screened. AREG and CES1 were identified as prognostic risk factors. CSTA, FDCSP, JCHAIN, IFFO2, PGLYRP4, SPOCK2 and SPINK6 were identified as prognostic factors. Collectively, all genes formed a prognostic risk signature model for oxidative stress in HNSCC, which were validated in GSE41613, GSE103322 and PRJEB23709 datasets. Immunohistochemical staining of SPINK6 in nasopharyngeal cancer samples validated the gene panel. Subsequent analysis indicated that subgroups of the oxidative stress prognostic signature played important roles during cellular communication, the immune microenvironment, the differential activation of transcription factors, oxidative stress and immunotherapeutic responses.

CONCLUSIONS

The risk model might predict HNSCC prognosis and immunotherapeutic responses.

NRF2/HO-1 axis, BIRC5, and TP53 expression in ESCC and its correlation with clinical pathological characteristics and prognosis

BACKGROUND

Many types of cancer exhibit high nuclear factor erythroid 2-related factor 2 (NRF2), which is effective in resisting drugs and radiation. However, the role of NRF2 gene expression in predicting the prognosis of esophageal squamous cell carcinoma (ESCC) remains unclear.

METHODS

The association between NRF2, heme oxygenase-1 (HO-1), baculovirus IAP repeat 5 (BIRC5), P53 gene expression levels and their relationship to immune-infiltrating cells were assessed using the Cancer Genome Atlas dataset, the Human Protein Atlas and the TISDB database. The expression of NRF2, HO-1, BIRC5, and TP53 in 118 ESCC patients was detected by immunohistochemistry, and the relationship between their expression level and clinicopathological parameters and prognosis was analyzed.

RESULTS

In ESCC, NRF2 overexpression was significantly associated with Han ethnicity, lymph node metastasis, and distant metastasis. HO-1 overexpression was significantly associated with differentiation, advanced clinical staging, lymph node metastasis, nerve invasion, and distant metastasis. BIRC5 overexpression was significantly associated with Han ethnicity and lymph node metastasis. TP53 overexpression was significantly associated with Han ethnicity and T staging. The NRF2/HO-1 axis expression was positively correlated with BIRC5 and TP53. Kaplan-Meier and multivariate Cox regression analysis showed that NRF2, BIRC5, and TP53 genes co-expression was an independent prognostic risk factor. TISIDB dataset analysis showed that immune-infiltrating cells were significantly negatively correlated with NRF2 and BIRC5.

CONCLUSION

NRF2, BIRC5, and TP53 axis gene expressions are predictors of poor prognosis for ESCC. The overexpression of the NRF2/HO-1/BIRC5 axis may not be related to immune-infiltrating cells.

The impact of liver fibrosis on the progression of hepatocellular carcinoma via a hypoxia-immune-integrated prognostic model

The impact of liver fibrosis on the deterioration of hepatocellular carcinoma (HCC) remains controversial. We hope to explore this issue through establishing a fibrosis-hypoxia-glycolysis-immune related prognostic model. Liver fibrosis-related genes from Molecular Signatures Database were used to evaluate the degree of fibrosis in HCC patients from the TCGA database. The patients were divided into two groups using the fibrosis-related expression matrix based on the algorithm uniform manifold approximation and projection (UMAP) and evaluated for fibrosis by UMAP cluster and gene enrichment analysis. Prognostic model was constructed by differential analysis, LASSO, and multivariate regression analysis. Immune-infiltration analysis was performed by CIBERSORT. Quantitative PCR and immunohistochemistry were performed to measure the gene expression levels in HCC patients from our hospital. In 365 HCC patients from the TCGA database, 111 HCC patients with high fibrosis score have a worse prognosis than those with low fibrosis based on 129 genes related to liver fibrosis, which may be caused by the interaction between fibrosis, angiogenesis, hypoxia, glycolysis, inflammatory response, and high immune infiltration. We constructed a Fibrosis-Hypoxia-Glycolysis-Immune Prognostic Model (FHGISig), which could significantly predict disease progression in HCC patients. Furthermore, we revealed a close correlation between FHGISig and immune cell infiltration level as well as immune checkpoints. Finally, PCR results found TFF3 mRNA was significantly lower in cirrhotic HCC patients compared with non-cirrhotic ones. Liver fibrosis is a poor-prognostic factor for HCC, and our FHGISig could significantly predict disease progression, which could also be a potential predictive marker for immunotherapy in HCC patients.

A Novel CXCR4-Targeted Diphtheria Toxin Nanoparticle Inhibits Invasion and Metastatic Dissemination in a Head and Neck Squamous Cell Carcinoma Mouse Model

Loco-regional recurrences and metastasis represent the leading causes of death in head and neck squamous cell carcinoma (HNSCC) patients, highlighting the need for novel therapies. Chemokine receptor 4 (CXCR4) has been related to loco-regional and distant recurrence and worse patient prognosis. In this regard, we developed a novel protein nanoparticle, T22-DITOX-H6, aiming to selectively deliver the diphtheria toxin cytotoxic domain to CXCR4⁺ HNSCC cells. The antimetastatic effect of T22-DITOX-H6 was evaluated in vivo in an orthotopic mouse model. IVIS imaging system was utilized to assess the metastatic dissemination in the mouse model. Immunohistochemistry and histopathological analyses were used to study the CXCR4 expression in the cancer cells, to evaluate the effect of the nanotoxin treatment, and its potential off-target toxicity. In this study, we report that CXCR4⁺ cancer cells were present in the invasive tumor front in an orthotopic mouse model. Upon repeated T22-DITOX-H6 administration, the number of CXCR4⁺ cancer cells was significantly reduced. Similarly, nanotoxin treatment effectively blocked regional and distant metastatic dissemination in the absence of systemic toxicity in the metastatic HNSCC mouse model. The repeated administration of T22-DITOX-H6 clearly abrogates tumor invasiveness and metastatic dissemination without inducing any off-target toxicity. Thus, T22-DITOX-H6 holds great promise for the treatment of CXCR4⁺ HNSCC patients presenting worse prognosis.