Prognostic Implications of Immune-Related Genes’ (IRGs) Signature Models in Cervical Cancer and Endometrial Cancer

Ding, Hao; Fan, Guanlan; Yi, Yuexiong; Zhang, Wei; Xiong, Xiaoxing; Mahgoub, Omer Kamal

doi:10.3389/fgene.2020.00725

Cited by 35 publications

(23 citation statements)

References 74 publications

(81 reference statements)

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“…Low risk patients significantly benefited from chemotherapeutic and immunotherapeutic treatments. In addition to tumor-infiltrating immune cells, immune-related gene sets such as RIPOR2, DAAM2, SORBS1, and CXCL8 ( Mei et al, 2020 ), or LTA, TFRC, TYK2, DLL4, CSK, JUND, NFATC4, SBDS, FLT1, IL17RD, IL3RA, SDC1, PLAU ( Ding et al, 2020 ), were proposed as prognostic genes to stratify CESC patients. However, neither of these studies took co-expression of immune networks into consideration.…”

Section: Discussionmentioning

confidence: 99%

Immune-Inhibitory Gene Expression is Positively Correlated with Overall Immune Activity and Predicts Increased Survival Probability of Cervical and Head and Neck Cancer Patients

Budhwani

Turrell

et al. 2021

Front. Mol. Biosci.

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Background: Limited immunotherapy options are approved for the treatment of cervical cancer and only 10–25% of patients respond effectively to checkpoint inhibition monotherapy. To aid the development of novel therapeutic immune targets, we aimed to explore survival-associated immune biomarkers and co-expressed immune networks in cervical cancer.Methods: Using The Cancer Genome Atlas (TCGA) Cervical Squamous Cell Carcinoma (CESC) data (n = 304), we performed weighted gene co-expression network analysis (WGCNA), and determined which co-expressed immune-related genes and networks are associated with survival probability in CESC patients under conventional therapy. A “Pan-Immune Score” and “Immune Suppression Score” was generated based on expression of survival-associated co-expressed immune networks and immune suppressive genes, which were subsequently tested for association with survival probablity using the TCGA Head Neck Squamous Cell Carcinoma (HNSCC) data (n = 528), representing a second SCC cancer type.Results: In CESC, WGCNA identified a co-expression module enriched in immune response related genes, including 462 genes where high expression was associated with increased survival probability, and enriched for genes associated with T cell receptor, cytokine and chemokine signaling. However, a high level of expression of 43 of the genes in this module was associated with decreased survival probability but were not enriched in particular pathways. Separately, we identified 20 genes associated with immune suppression including inhibitory immune checkpoint and regulatory T cell-related genes, where high expression was associated with increased survival probability. Expression of these 20 immune suppressive genes (represented as “Immune Suppression Score”) was highly correlated with expression of overall survival-associated immune genes (represented as “Pan-Immune Score”). However, high expression of seven immune suppression genes, including TWEAK-R, CD73, IL1 family and TGFb family genes, was significantly associated with decreased survival probability. Both scores also significantly associated with survival probability in HNSCC, and correlated with the previously established “Immunophenoscore.”Conclusion: CESC and HNSCC tumors expressing genes predictive of T cell infiltrates (hot tumors) have a better prognosis, despite simultaneous expression of many immune inhibitory genes, than tumors lacking expression of genes associated with T cell infiltrates (cold tumors) whether or not these tumor express immune inhibitory genes.

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Section: Discussionmentioning

confidence: 99%

Immune-Inhibitory Gene Expression is Positively Correlated with Overall Immune Activity and Predicts Increased Survival Probability of Cervical and Head and Neck Cancer Patients

Budhwani

Turrell

et al. 2021

Front. Mol. Biosci.

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“…Giuseppina et al found that a decrease in lymphotoxin-ß production by tumor cells was associated with a loss of follicular dendritic cell phenotype and diffuse growth of follicular lymphomas [27]. Recently, the gene was found to be associated with immune infiltration of breast and endometrial cancer tumors [28, 29]. The analysis using the TCGA dataset showed that TNFRSF9 was altered in approximately 5% of cases of Cholangiocarcinoma, adrenocortical carcinoma (ACC) and lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), with deep deletion being the dominant alteration (Supple.…”

Section: Discussionmentioning

confidence: 99%

Drug-driven reclassification of multiple tumour subtypes reveals intrinsic molecular concordance of therapy across histologically disparate cancers

Yan

Zheng

Zhang

et al. 2021

Preprint

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Cancers that are histologically defined as the same type of cancer often need a distinct therapy based on underlying heterogeneity; likewise, histologically disparate cancers can require similar treatment approaches due to intrinsic similarities. A comprehensive analysis integrated with drug response data and genomic alterations, particularly to reveal therapeutic concordance mechanisms across histologically disparate tumour subtypes, has not yet been fully exploited. In this study, we used pharmacogenomic profiling data provided from the Cancer Genome Project (CGP) in a systematic in silico investigation of the pharmacological subtypes of cancers and the intrinsic concordance of molecular mechanisms leading to similar therapeutic responses across histologically disparate tumour subtypes. We further developed a novel approach to redefine cell-to-cell similarity and drug-to-drug similarity from the therapeutic concordance, providing a new point of view to study cancer heterogeneity. Our study identified that histologically different tumours, such as malignant melanoma and colorectal adenocarcinoma, could belong to the same pharmacological subtype regarding drug sensitivity to MEK inhibitors, which was determined by their genomic alterations, high occurrence of BRAF or KRAS mutations. Therapeutic concordance for chemotherapy drugs was identified across histologically disparate hematological tumors mainly due to the extraordinary activation of the cell cycle in blood cancers. A subcluster of SCLC had a more similar profile with hematological tumors, and was associated with the malignant phenotype, with a higher level of MYC expression. We developed a website to store and visualize the pharmacological subtypes of drugs, as well as their connected genomic and expression alterations.

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“…Studies have established an immune-related prognostic signature and a glycolysis-related gene signature in EC, which have provided the basis for predicting prognostic risk in EC patients. 14 , 15 Another study identified several transcription factors related to the prognosis of EC patients. 16 Nevertheless, a prognostic signature based on transcription factors to systematically and accurately evaluate EC prognosis is lacking.…”

Section: Introductionmentioning

confidence: 99%

A Novel Transcription Factor-Based Prognostic Signature in Endometrial Cancer: Establishment and Validation

Yang

Cheng

et al. 2021

OTT

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Background Endometrial cancer (EC) is a common malignancy of the female reproductive system worldwide. Increasing evidence has suggested that many transcription factors are aberrantly expressed in various cancers. This study aimed to develop a transcription factor-based prognostic signature for EC. Methods Gene expression data and clinical data of EC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression and Multivariate Cox regression analysis was used to construct a prognostic signature. Then, the efficacy of the prognostic signature was validated in a training cohort, testing cohort and then the entire cohort. Correlations between clinical features and the model were also analyzed, and a nomogram based on the multivariate Cox analysis was developed. Furthermore, we verified the effect of a key transcription factor, E2F1, on biological functions of EC in vitro. Results We developed a nine-transcription factor (MSX1, HOXB9, E2F1, DLX4, BNC2, DLX2, PDX1, POU3F2, and FOXP3) prognostic signature. Compared with those in the low-risk group, patients in the high-risk group had worse clinical outcomes. The area under the curve (AUC) of this prognostic signature for 5-year survival was 0.806 in the training cohort, 0.710 in the testing cohort and 0.761 in the entire cohort. Gene set enrichment analysis (GSEA) revealed a correlation between the prognostic signature and various cancer signaling pathways, and a hub transcription factor regulatory network was constructed. The prognostic signature was confirmed to have independent predictive value. Finally, a nomogram based on the prognostic signature and clinical independent prognostic factors was also established and performed well according to the calibration curves. Further, knockdown of E2F1 inhibited invasion and metastasis of EC cells. Conclusion Our study developed and validated a transcription factor-based prognostic signature that accurately predicts prognosis of EC patients. Moreover, E2F1 may represent a potential target for the treatment of EC.

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Prognostic Implications of Immune-Related Genes’ (IRGs) Signature Models in Cervical Cancer and Endometrial Cancer

Cited by 35 publications

References 74 publications

Immune-Inhibitory Gene Expression is Positively Correlated with Overall Immune Activity and Predicts Increased Survival Probability of Cervical and Head and Neck Cancer Patients

Immune-Inhibitory Gene Expression is Positively Correlated with Overall Immune Activity and Predicts Increased Survival Probability of Cervical and Head and Neck Cancer Patients

Drug-driven reclassification of multiple tumour subtypes reveals intrinsic molecular concordance of therapy across histologically disparate cancers

A Novel Transcription Factor-Based Prognostic Signature in Endometrial Cancer: Establishment and Validation

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