A Review of the Effects of Cervical Cancer Standard Treatment on Immune Parameters in Peripheral Blood, Tumor Draining Lymph Nodes, and Local Tumor Microenvironment

Lumican is a potential predictor on the efficacy of concurrent chemoradiotherapy in cervical squamous cell carcinoma

Purpose

To identify new novel biomarkers for predicting the efficacy of concurrent chemoradiotherapy(CCRT) in cervical squamous cell carcinoma(CESC).

Methods

Gene expression datasets GSE56363, GSE5787, and GSE168009 were analyzed to identify candidate genes to predict the efficacy of CCRT in CESC. Single-cell RNA sequencing (scRNA-seq) data from GSE168652 and CESC patients in The Cancer Genome Atlas(TCGA) were systematically analyzed to explore possible molecular mechanisms. Kaplan-Meier evaluated the correlation between LUM (Lumican) and prognostic significance. The expression of LUM protein in biopsy tissues before CCRT was detected by immunohistochemistry in 15 CESC patients.

Results

LUM mRNA levels were significantly upregulated in nonresponders of CESC.patients receiving CCRT and positively correlated with poor therapeutic effect. Furthermore, high expression of LUM influenced the immune microenvironment in CESC patient-derived organoids treated with CCRT. LUM overexpression in CESC cells induced resistance to CCRT, potentially via immune landscape modulation. Gene Set Enrichment Analysis (GSEA) revealed that possible mechanisms underlying resistance to CCRT might involve the PARs and IL1 signaling pathway affecting the immune landscape.

Conclusions

High LUM expression is correlated with poor efficacy in CESC patients receiving CCRT, possibly through the PARs and IL1 signaling pathway affecting the immune landscape.

Inhibition of IDH3α Enhanced the Efficacy of Chemoimmunotherapy by Regulating Acidic Tumor Microenvironments

In recent years, chemoimmunotherapy has become effective in some advanced cancers, but its effect is still limited. Transcriptional upregulation of isocitrate dehydrogenase 3α (IDH3α) can promote tumor initiation and progression. However, it is not clear whether the aberrant expression of IDH3α is related to the efficacy of chemoimmunotherapy in cancers. Here, we found that IDH3α was elevated in uterine cervical cancer (UCC) and lung adenocarcinoma (LUAD) samples by using public databases. High expression of IDH3α could promote the epithelial–mesenchymal transition (EMT), alter the intracellular redox status, promote glycolysis, and induce an acidic microenvironments in cancer cells. Furthermore, we found that inhibition of IDH3α combined with chemoimmunotherapy (cisplatin and programmed cell death ligand 1 (PD-L1) antibodies) activated the cGAS–STING pathway, promoted CD8+ T cell infiltration, and decreased tumor growth in mouse models of cervical cancer. In conclusion, our data indicate that silencing IDH3α sensitizes tumors to chemoimmunotherapy by modulating the acidic microenvironment and activating the cGAS–STING pathway.

The current understanding of the immune landscape relative to radiotherapy across tumor types

Radiotherapy is part of the standard of care treatment for a great majority of cancer patients. As a result of radiation, both tumor cells and the environment around them are affected directly by radiation, which mainly primes but also might limit the immune response. Multiple immune factors play a role in cancer progression and response to radiotherapy, including the immune tumor microenvironment and systemic immunity referred to as the immune landscape. A heterogeneous tumor microenvironment and the varying patient characteristics complicate the dynamic relationship between radiotherapy and this immune landscape. In this review, we will present the current overview of the immunological landscape in relation to radiotherapy in order to provide insight and encourage research to further improve cancer treatment. An investigation into the impact of radiation therapy on the immune landscape showed in several cancers a common pattern of immunological responses after radiation. Radiation leads to an upsurge in infiltrating T lymphocytes and the expression of programmed death ligand 1 (PD-L1) which can hint at a benefit for the patient when combined with immunotherapy. In spite of this, lymphopenia in the tumor microenvironment of 'cold' tumors or caused by radiation is considered to be an important obstacle to the patient's survival. In several cancers, a rise in the immunosuppressive populations is seen after radiation, mainly pro-tumoral M2 macrophages and myeloid-derived suppressor cells (MDSCs). As a final point, we will highlight how the radiation parameters themselves can influence the immune system and, therefore, be exploited to the advantage of the patient.

A risk prediction model mediated by genes of APOD/APOC1/SQLE associates with prognosis in cervical cancer

Cervical cancer is one of the most common gynecological malignancies. Due to the high heterogeneity of cervical cancer accelerating cancer progression, it is necessary to identify new prognostic markers and treatment regimens for cervical cancer to improve patients' survival rates. We purpose to construct and verify a risk prediction model for cervical cancer patients. Based on the analysis of data from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), differences of genes in normal and cancer samples were analyzed and then used analysis of WGCNA along with consistent clustering to construct single-factor + multi-factor risk models. After regression analysis, the target genes were obtained as prognostic genes and prognostic risk models were constructed, and the validity of the risk model was confirmed using the receiver operating characteristic curve (ROC) and Kaplan-Meier curve. Subsequently, the above model was verified on the GSE44001 data validation followed by independent prognostic analysis. Enrichment analysis was conducted by grouping the high and low risks of the model. In addition, differences in immune analysis (immune infiltration, immunotherapy), drug sensitivity, and other levels were counted by the high and low risks groups. In our study, three prognostic genes including APOD, APOC1, and SQLE were obtained, and a risk model was constructed along with validation based on the above-mentioned analysis. According to the model, immune correlation and immunotherapy analyses were carried out, which will provide a theoretical basis and reference value for the exploration and treatment of cervical cancer.