Immune Cell Infiltration as Signatures for the Diagnosis and Prognosis of Malignant Gynecological Tumors

Expression Profile of Thymidine Kinase Genes in Cervical Squamous Cell Carcinoma Confirmed by Various Detection Methods

Background

Thymidine kinases (TKs) are key enzymes involved in DNA synthesis and repair, with alterations in their expression associated with various cancers. Thymidine kinase 1 (TK1) and TK2 are cytosolic enzyme proteins that catalyze the addition of a gamma-phosphate group to thymidine. The existing literature on TK1 in cervical squamous cell carcinoma (CESC) fails to address the clinical role of TK1 overexpression and its possible molecular mechanism in CESC. The clinical significance of TK2 in CESC is also unknown. The objective was to explore the differential expression, clinical significance, and molecular mechanisms of TK1 and TK2 in CESC.

Methods

The researchers collected global high-throughput data, extracted the expression levels of TK1 and TK2, and calculated the integrated standardized mean difference (SMD) and summarized receiver's operating characteristics (sROC) of TK1 or TK2 mRNA to investigate the expression profiles of TK genes fully and objectively in 918 CESC tissues and 360 control tissues. In-house tissue microarrays for immunohistochemical testing were used to verify the protein level of TK1 in 62 CESC tissues and control tissues. The growth effect of TK1 and TK2 in CESC cell lines was assessed using Chronos dependency scores derived from CRISPR knockout screen in the Achilles project. We also analyzed the potential mechanism of TK genes by studying the relationship between TK gene expression and immune infiltration, gene alternations as well as the related signal pathways.

Results

The various detection methods employed all confirmed that the TK1 expression is upregulated and TK2 is downregulated in CESC tissues (SMD: 2.44, 95% confidence interval (CI): 1.36 - 3.51, area under curve (AUC): 0.88, 95% CI: 0.85 - 0.90; SMD: -0.69, 95% CI: -1.25 to -0.14, AUC: 0.75, 95% CI: 0.71 - 0.78). Inhibition of TK1 expression by CRISPR knockout had negative influence on the biological functions of 11 CESC cell lines. The expression of TK2 was negatively correlated with the malignant progression of CESC. Expression of TK genes showed significant association with the immune infiltration of macrophages, CD4+ T cells, and neutrophils. Genes related with TK1 or TK2 were involved in pathways related to DNA replication, proteasome, and homologous recombination.

Conclusions

Clinically, these findings suggest that the differential expression of TK1 and TK2 could serve as potential biomarkers, as well as therapeutic targets for personalized treatment strategies in CESC patients.

Proteomics and Bioinformatics Investigations Link Overexpression of FGF8 and Associated Hub Genes to the Progression of Ovarian Cancer and Poor Prognosis

Ovarian cancer's asymptomatic nature, high recurrence rate, and resistance to platinum-based chemotherapy highlight the need to find and characterize new diagnostic and therapeutic targets. While prior studies have linked aberrant expression of fibroblast growth factor 8 (FGF8) to various cancer types, its precise role has remained elusive. Recently, we observed that FGF8 silencing reduces the cancer-promoting properties of ovarian cancer cells, and thus, this study aimed to understand how FGF8 regulates the development of ovarian cancer. LC-MS/MS-based quantitative proteomics analysis identified 418 DEPs, and most of them were downregulated in FGF8-silenced ovarian cancer cells. Many of these DEPs are associated with cancer progression and unfavorable prognosis. To decipher the biological significance of DEPs, bioinformatics analyses encompassing gene ontology, pathway analysis, protein-protein interaction networks, and expression analysis of hub genes were carried out. Hub genes identified in the FGF8 protein network were upregulated in ovarian cancer compared to controls and were linked to poor prognosis. Subsequently, the expression of hub genes was correlated with patient survival and regulation of the tumor microenvironment. Conclusively, FGF8 and associated hub genes help in the progression of ovarian cancer, and their overexpression may lead to higher immune infiltration, poor prognosis, and poor survival.

Prognostic role of long non-coding RNA USP30-AS1 in ovarian cancer: insights into immune cell infiltration in the tumor microenvironment

Ovarian cancer represents a formidable gynecologic malignancy bearing a dismal prognosis owing to the dearth of reliable early detection approaches and a high recurrence rate. Long non-coding RNAs (lncRNAs) have garnered immense attention as key orchestrators involved in diverse biological processes and take part in cancer initiation and progression. The present study investigated the potential significance of lncRNA USP30-AS1 in ovarian cancer prognosis, as well as its putative association with immune cell infiltration in tumor immune microenvironment (TIME). By analyzing publicly available datasets, we identified six lncRNAs with prognostic prediction ability, including USP30-AS1. The results revealed a significant positive correlation of USP30-AS1 expression with the infiltration of immune cells such as Th1 cells, TFH, CD8 T cells, B cells, antigen-presenting dendritic cells (aDC), and plasmacytoid dendritic cells (pDC) in ovarian cancer specimens. These findings provide compelling evidence of the potential involvement of lncRNA in the regulation of the TME in ovarian carcinoma. The outcomes from this study underscore the potential of USP30-AS1 as a promising prognostic biomarker for ovarian cancer. Additionally, the findings offer significant insights into the plausible role of lncRNAs in modulating immune activities, thus adding to our understanding of the disease biology. Additional investigations are necessary to unravel the molecular mechanisms underpinning these connections and validate the results seen in independent cohorts and experimental models.

Efficient Redirection of NK Cells by Genetic Modification with Chemokine Receptors CCR4 and CCR2B

Natural killer (NK) cells are a subset of lymphocytes that offer great potential for cancer immunotherapy due to their natural anti-tumor activity and the possibility to safely transplant cells from healthy donors to patients in a clinical setting. However, the efficacy of cell-based immunotherapies using both T and NK cells is often limited by a poor infiltration of immune cells into solid tumors. Importantly, regulatory immune cell subsets are frequently recruited to tumor sites. In this study, we overexpressed two chemokine receptors, CCR4 and CCR2B, that are naturally found on T regulatory cells and tumor-resident monocytes, respectively, on NK cells. Using the NK cell line NK-92 as well as primary NK cells from peripheral blood, we show that genetically engineered NK cells can be efficiently redirected using chemokine receptors from different immune cell lineages and migrate towards chemokines such as CCL22 or CCL2, without impairing the natural effector functions. This approach has the potential to enhance the therapeutic effect of immunotherapies in solid tumors by directing genetically engineered donor NK cells to tumor sites. As a future therapeutic option, the natural anti-tumor activity of NK cells at the tumor sites can be increased by co-expression of chemokine receptors with chimeric antigen receptors (CAR) or T cell receptors (TCR) on NK cells can be performed in the future.

Diagnosis and prognosis prediction model for digestive system tumors based on immunologic gene sets

According to 2020 global cancer statistics, digestive system tumors (DST) are ranked first in both incidence and mortality. This study systematically investigated the immunologic gene set (IGS) to discover effective diagnostic and prognostic biomarkers. Gene set variation (GSVA) analysis was used to calculate enrichment scores for 4,872 IGSs in patients with digestive system tumors. Using the machine learning algorithm XGBoost to build a classifier that distinguishes between normal samples and cancer samples, it shows high specificity and sensitivity on both the validation set and the overall dataset (area under the receptor operating characteristic curve [AUC]: validation set = 0.993, overall dataset = 0.999). IGS-based digestive system tumor subtypes (IGTS) were constructed using a consistent clustering approach. A risk prediction model was developed using the Least Absolute Shrinkage and Selection Operator (LASSO) method. DST is divided into three subtypes: subtype 1 has the best prognosis, subtype 3 is the second, and subtype 2 is the worst. The prognosis model constructed using nine gene sets can effectively predict prognosis. Prognostic models were significantly associated with tumor mutational burden (TMB), tumor immune microenvironment (TIME), immune checkpoints, and somatic mutations. A composite nomogram was constructed based on the risk score and the patient's clinical information, with a well-fitted calibration curve (AUC = 0.762). We further confirmed the reliability and validity of the diagnostic and prognostic models using other cohorts from the Gene Expression Omnibus database. We identified diagnostic and prognostic models based on IGS that provide a strong basis for early diagnosis and effective treatment of digestive system tumors.

A predictive nomogram model for postoperative delirium in elderly patients following laparoscopic surgery for gynecologic cancers

BACKGROUND

This study aimed to investigate potential risk factors associated with postoperative delirium (POD) in elderly patients following laparoscopic surgery for gynecologic cancers and construct a nomogram predictive model based on these factors.

METHODS

Eligible elderly patients who underwent laparoscopic surgery for gynecologic cancers were enrolled and grouped according to the development of POD within postoperative 7 days. Potential risk factors were assessed by the univariate and multivariate logistic regression analyses. A nomogram model was constructed based on these factors and evaluated by R.

RESULTS

A total of 226 elderly patients were enrolled in the final data analysis and 39 patients had suffered POD with an incidence of 17.3%. Older age, modified frailty index (mFI) ≥ 0.225, C-reactive protein (CRP) ≥ 8.0, systemic immune-inflammation index (SII), and albumin/fibrinogen ratio (AFR) were five independent risk factors for POD by univariate and multivariate analyses. The area under the curve (AUC) of the constructed nomogram model based on these five factors was 0.833.

CONCLUSIONS

The constructed nomogram model based on age, CRP, SII, mFI, and AFR could effectively predict POD in elderly patients with gynecologic cancers.

ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG May Serve as Diagnostic and Prognostic Biomarkers in Endometrial Carcinoma

Uterine Corpus Endometrial Carcinoma (UCEC), the most common gynecologic malignancy in developed countries, remains to be a major public health problem. Further studies are surely needed to elucidate the tumorigenesis of UCEC. Herein, intersecting 203 differentially expressed genes (DEGs) were identified with the GSE17025, GSE63678, and The Cancer Genome Atlas-UCEC datasets. The Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment analysis and protein-protein interaction (PPI) network were performed on those 203 DEGs. Intriguingly, 6 of the top 10 nodes in the PPI network were related to unfavorable prognosis, that is, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG. The mRNA and protein expression levels of the 6 hub genes were elevated in UCEC tissues compared to normal tissues. Higher expression of the 6 hub genes was associated with poor prognostic clinicopathological characteristics. The receiver operating characteristic curve suggested the significant diagnostic ability of the 6 hub genes for UCEC. Then, underlying pathogeneses of UCEC including promoter methylation level, TP53 mutation status, genomic genetic variation, and immune cells infiltration were analyzed. The mRNA expression level of the 6 hub genes was also higher in cervical squamous cell carcinoma and endocervical adenocarcinoma, uterine carcinosarcoma, and ovarian serous cystadenocarcinoma tissues than in corresponding normal tissues. In conclusion, ASPM, CDC20, DLGAP5, BUB1B, CDCA8, and NCAPG may be considered diagnostic and prognostic biomarkers in UCEC.

Significance of TEAD Family in Diagnosis, Prognosis and Immune Response for Ovarian Serous Carcinoma

PURPOSE

To explore the molecular profiles of transcriptional enhanced associate domain (TEAD) family in ovarian serous carcinoma (OSC).

METHODS

In this study, we use bioinformatics methods including GEPIA, GE-mini, Oncomine 3.0, Kaplan-Meier plotter, cBioPortal, WebGestalt, TIMER2.0 and DiseaseMeth2.0, and in vitro experimental RT-PCR to assess the expression profiles and prognostic significance of TEAD family in OSC.

RESULTS

According to the bioinformatics analysis, TEAD family was abnormally expressed in OSC. In terms of prognosis, Kaplan-Meier plotter indicated that OSC patients with high level of TEAD4 showed poor overall survival (OS), progression-free survival (PFS) and post progression survival (PPS). TEAD family also had significantly diagnostic values for OSC patients. Tumor Immune Estimation Resource (TIMER) algorithm indicated that TEAD family was significantly associated with different types of infiltrating immune cells, including B cells, macrophages, dendritic cells, neutrophils, CD8+ T cells and CD4+ T cells. Gene set enrichment analysis of TEAD family-associated coexpression genes was further explored. In in vitro experiments, the RT-PCR results showed the upregulated TEAD2/4 in OSC tissues and cells (A2780 and TOV112D). Moreover, decreased expression of TEAD2 could induce the ferroptosis through increasing the ROS accumulation.

CONCLUSION

Thus, TEAD family correlated with the diagnosis, prognosis and immune infiltration in OSC. These results could provide comprehensive understanding of TEAD family in the diagnosis and prognosis of OSC patients.