The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer

Ferroptosis-related gene transferrin receptor protein 1 expression correlates with the prognosis and tumor immune microenvironment in cervical cancer

Background

Ferroptosis is a non-apoptotic iron-dependent form of cell death implicated in various cancer pathologies. However, its precise role in tumor growth and progression of cervical cancer (CC) remains unclear. Transferrin receptor protein 1 (TFRC), a key molecule associated with ferroptosis, has been identified as influencing a broad range of pathological processes in different cancers. However, the prognostic significance of TFRC in CC remains unclear. The present study utilized bioinformatics to explore the significance of the ferroptosis-related gene TFRC in the progression and prognosis of CC.

Methods

We obtained RNA sequencing data and corresponding clinical information on patients with CC from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases. Using least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of five ferroptosis-related genes (FRGs) for the prognostic prediction of CC. We investigated the relationship between TFRC gene expression and immune cell infiltration by employing single-sample GSEA (ssGSEA) analysis. The potential functional role of the TFRC gene was evaluated through gene set enrichment analysis (GSEA). Immunohistochemistry and qPCR was employed to assess TFRC mRNA and protein expression in 33 cases of cervical cancer. Furthermore, the relationship between TFRC mRNA expression and overall survival (OS) was investigated in patients.

Results

CC samples had significantly higher TFRC gene expression levels than normal tissue samples. Higher TFRC gene expression levels were strongly associated with higher cancer T stages and OS events. The findings of multivariate analyses illustrated that the OS in CC patients with high TFRC expression is shorter than in patients with low TFRC expression. Significant increases were observed in the levels of TFRC mRNA and protein expression in patients diagnosed with CC.

Conclusion

Increased TFRC expression in CC was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration. In addition, it highlights ferroptosis as a promising therapeutic target for CC.

Cytokines and soluble mediators as architects of tumor microenvironment reprogramming in cancer therapy

Navigating the intricate landscape of the tumor microenvironment (TME) unveils a pivotal arena for cancer therapeutics, where cytokines and soluble mediators emerge as double-edged swords in the fight against cancer. This review ventures beyond traditional perspectives, illuminating the nuanced interplay of these elements as both allies and adversaries in cancer dynamics. It critically evaluates the evolving paradigms of TME reprogramming, spotlighting innovative strategies that target the sophisticated network of cytokines and mediators. Special focus is placed on unveiling the therapeutic potential of novel cytokines and mediators, particularly their synergistic interactions with extracellular vesicles, which represent underexplored conduits for therapeutic targeting. Addressing a significant gap in current research, we explore the untapped potential of these biochemical players in orchestrating immune responses, tumor proliferation, and metastasis. The review advocates for a paradigm shift towards exploiting these dynamic interactions within the TME, aiming to transcend conventional treatments and pave the way for a new era of precision oncology. Through a critical synthesis of recent advancements, we highlight the imperative for innovative approaches that harness the full spectrum of cytokine and mediator activities, setting the stage for breakthrough therapies that offer heightened specificity, reduced toxicity, and improved patient outcomes.

Tryptophan metabolism enzymes are potential targets in ovarian clear cell carcinoma

AIM

As the second most prevalent subtype of epithelial ovarian cancers, ovarian clear cell carcinoma (OCCC) is known for its chemoresistance to conventional platinum-based therapy. In this work, we examined the tryptophan (Trp) metabolism enzymes' differential expression in patients with OCCC to assess the potential for personalised treatment.

METHODS

A total of 127 OCCC tissues were used to construct tissue microarrays, and immunohistochemistry (IHC) staining of the Trp enzymes IDO1, IDO2, TDO2 and IL4I1 was performed. The correlations between Trp enzyme expression and clinical characteristics were analysed.

RESULTS

Positive IDO1, IDO2, TDO2 and IL4I1 staining was identified in 26.8%, 94.5%, 75.6% and 82.7% of OCCC respectively. IDO1-positive samples were more common in the chemoresistant group than in the platinum-sensitive group (46.7% vs. 19.8%). Moreover, positive expression of IDO1, TDO2 and IL4I1 was related to advanced stage, metastasis, bilateral tumours, endometriosis and tumour rupture (p < 0.05) respectively. Univariate analysis revealed a significant association between bilateral tumours, lymph node metastasis, advanced stage, distant metastasis and aberrant cytology with a poor prognosis for OCCC, while the absence of residual tumour was correlated with a favourable outcome (p < 0.05). However, only bilateral tumours and lymph node metastases were related to a poor prognosis after multivariate analysis.

CONCLUSION

This is the first study to investigate the expression of the Trp enzymes IDO1, IDO2, TDO2 and IL4I1 in OCCC tissues. IDO2, TDO2 and IL4I1 were detected in the majority of OCCC. Clinical traits were correlated with IDO1, IDO2, TDO2 and IL4I1 expression. IDO1 may be used as a therapeutic target given the large percentage of chemoresistant cases with IDO1 expression. These results will aid the development of personalised therapies for OCCC.

The sub-molecular characterization identification for cervical cancer

Background

The efficacy of therapy in cervical cancer (CESC) is blocked by high molecular heterogeneity. Thus, the sub-molecular characterization remains primarily explored for personalizing the treatment of CESC patients.

Methods

Datasets with 741 CESC patients were obtained from TCGA and GEO databases. The NMF algorithm, random forest algorithm, and multivariate Cox analysis were utilized to construct a classifier for defining the sub-molecular characterization. Then, the biological characteristics, genomic variations, prognosis, and immune landscape in molecular subtypes were explored. The significance of classifier genes was validated by quantitative Real-Time PCR, cell transfection, cell colony formation assay, wound healing assay, cell proliferation assay, and Western blot.

Results

The CESC patients were classified into two subtypes, and the high classifier-score patients with significant differences in ECM-receptor interaction, PI3K-Akt signaling pathway, and MAPK signaling pathway showed a poorer prognosis in OS (p < 0.001), DFI (p = 0.016), PFI (p < 0.001) and DSS (p < 0.001), and with high the M0 Macrophage and resting Mast cells infiltration and low HLA family gene expression. Moreover, the constructed classifier owns a high identified accuracy in the tumor/normal groups (AUC: 0.993), the tumor/CIN1-CIN3 groups (AUC: 0.963), and normal/CIN1-CIN3 groups (AUC: 0.962), and the total prediction performance is better than currently published signatures in CESC (C-index: 0,763). The combined prediction performance further indicated that Nomogram (AUC = 0.837) is superior to the classifier (AUC = 0.835) and Stage (AUC = 0.568), and the C-index of calibration curves is 0.784. The potential biological function of classifier genes indicated that silencing GALNT2 inhibited the cancer cell's proliferation, migration, and colony formation; Conversely, the cancer cell's proliferation, migration, and colony formation were increased after the upregulation of GALNT2. The Epithelial-Mesenchymal Transition Experiment showed that GALNT2 knockdown might reduce the levels of Snail and Vimentin proteins and increase E-cadherin; Conversely, the levels of Snail and Vimentin proteins were increased, E-cadherin was reduced by GALNT2 upregulation.

Conclusion

The classifier we constructed may help improve our understanding of subtype characteristics and provide a new strategy for developing CESC therapeutics. Remarkably, GALNT2 may be an option to directly target drivers in CESC cancer therapy.

Cancer-associated fibroblasts-derived FMO2 as a biomarker of macrophage infiltration and prognosis in epithelial ovarian cancer

OBJECTIVE

Recent molecular profiling revealed that cancer-associated fibroblasts (CAFs) are essential for matrix remodeling and tumor progression. Our study aimed to investigate the role of flavin-containing monooxygenase 2 (FMO2) in epithelial ovarian cancer (EOC) as a novel CAF-derived prognostic biomarker.

METHODS

Primary fibroblasts were isolated from EOC samples. Microdissection and single-cell RNA sequencing (scRNA-seq) datasets (including TCGA, GSE9891, GSE63885, GSE118828 and GSE178913) were retrieved to determine the expression profiles. Gene set enrichment analysis (GSEA) was used to explore the correlation between FMO2 and stromal activation as well as immune infiltration. The predictive value of FMO2 and combined macrophage infiltration level was verified in an independent EOC cohort (n = 113).

RESULTS

We demonstrated that FMO2 was upregulated in tumor stroma and correlated with fibroblast activation. Besides, FMO2 had the predictive power for worse clinical outcome of EOC patients. In the mesenchymal subtype of EOC, the FMO2-defined signature revealed that FMO2 contributed to infiltration of tumor-infiltrating lymphocytes. Moreover, we confirmed the positive correlation between FMO2 and CD163+ cell infiltration level in EOC tissues, and showed that combination of FMO2 expression with CD163+ cell infiltration level in the tumor stroma could predict poor overall survival (HR = 3.63, 95% CI = 1.93-6.84, p = 0.0008). Additionally, FMO2 also predicted the prognosis of patients with ovarian cancer based on the expression of immune checkpoints (such as PD-L1 and PD1).

CONCLUSION

Our results address the tumor-supporting role of FMO2 in EOC and its association with immune components, and it might be a prospective target for stroma-oriented therapies against EOC.

Trends in metabolic signaling pathways of tumor drug resistance: A scientometric analysis

Background

Cancer chemotherapy resistance is one of the most critical obstacles in cancer therapy. Since Warburg O first observed alterations in cancer metabolism in the 1950s, people gradually found tumor metabolism pathways play a fundamental role in regulating the response to chemotherapeutic drugs, and the attempts of targeting tumor energetics have shown promising preclinical outcomes in recent years. This study aimed to summarize the knowledge structure and identify emerging trends and potential hotspots in metabolic signaling pathways of tumor drug resistance research.

Methods

Publications related to metabolic signaling pathways of tumor drug resistance published from 1992 to 2022 were retrieved from the Web of Science Core Collection database. The document type was set to articles or reviews with language restriction to English. Two different scientometric software including Citespace and VOS viewer were used to conduct this scientometric analysis.

Results

A total of 2,537 publications including 1,704 articles and 833 reviews were retrieved in the final analysis. The USA made the most contributions to this field. The leading institution was the University of Texas MD Anderson Cancer Center. Avan A was the most productive author, and Hanahan D was the key researcher with the most co-citations, but there is no leader in this field yet. Cancers was the most influential academic journal, and Oncology was the most popular research field. Based on keywords occurrence analysis, these selected keywords could be roughly divided into five main topics: cluster 1 (study of cancer cell apoptosis pathway); cluster 2 (study of resistance mechanisms of different cancer types); cluster 3 (study of cancer stem cells); cluster 4 (study of tumor oxidative stress and inflammation signaling pathways); and cluster 5 (study of autophagy). The keywords burst detection identified several keywords as new research hotspots, including “tumor microenvironment,” “invasion,” and “target”.

Conclusion

Tumor metabolic reprogramming of drug resistance research is advancing rapidly. This study serves as a starting point, providing a thorough overview, the development landscape, and future opportunities in this field.