RNF125 Modulates Tumor Immunity by Promoting Ubiquitination of PD-L1

Abstract In recent years, the incidence of tumors has been increasing, and the overall cure rate by traditional treatment methods does not exceed 20%. One of the most effective and promising strategies for comprehensive treatment of tumors is immunotherapy, such as treatment with the PD-1/PD-L1 antibody. Here, we showed that ring finger protein 125 (RNF125), an E3 ligase in the RING domain family, could interact with PD-L1 to reduce the stability of PD-L1 protein. In addition, RNF125 downregulated the expression of PD-L1 by promoting its ubiquitination at K48, whereas a mutation in the RING domain of RNF125 disrupted this function. A significant positive correlation between RNF125 and genes involved with tumor immunity was determined in cancer samples, as determined using data from The Cancer Genome Atlas (TCGA). Furthermore, we elucidated the effects of RNF125 on the occurrence and development of tumors in mice. Analyses of wild-type and RNF125 knockout mice transplanted with MC-38 cells revealed enhanced MC-38 tumor growth in KO mice. These data indicated that RNF125 could participate in tumor immunity by promoting the K48-linked ubiquitination of PD-L1 to affect the occurrence and development of tumors, providing a potential target for enhancing therapeutic efficacy for human cancer treatment.

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Molecular basis of distinct oestrogen responses in endometrial and breast cancer

Endocrine Related Cancer ◽

10.1530/erc-17-0563 ◽

2019 ◽

Vol 26 (1) ◽

pp. 31-46 ◽

Cited By ~ 6

Author(s):

Eva Baxter ◽

Karolina Windloch ◽

Greg Kelly ◽

Jason S Lee ◽

Frank Gannon ◽

...

Keyword(s):

Breast Cancer ◽

Transcriptional Activation ◽

The Cancer Genome Atlas ◽

Breast Cancers ◽

Oestrogen Receptor Alpha ◽

Limited Success ◽

Cancer Genome Atlas ◽

Using Data ◽

Oestrogen Signalling

Up to 80% of endometrial and breast cancers express oestrogen receptor alpha (ERα). Unlike breast cancer, anti-oestrogen therapy has had limited success in endometrial cancer, raising the possibility that oestrogen has different effects in both cancers. We investigated the role of oestrogen in endometrial and breast cancers using data from The Cancer Genome Atlas (TCGA) in conjunction with cell line studies. Using phosphorylation of ERα (ERα-pSer118) as a marker of transcriptional activation of ERα in TCGA datasets, we found that genes associated with ERα-pSer118 were predominantly unique between tumour types and have distinct regulators. We present data on the alternative and novel roles played by SMAD3, CREB-pSer133 and particularly XBP1 in oestrogen signalling in endometrial and breast cancer.

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The tissue differentiation and cancer manifolds in gene and protein expression spaces

10.1101/2021.08.20.457160 ◽

2021 ◽

Author(s):

J Nieves ◽

A Gonzalez

Keyword(s):

Protein Expression ◽

Cancer Progression ◽

Tissue Differentiation ◽

The Cancer Genome Atlas ◽

Normal Tissues ◽

Gene And Protein Expression ◽

Human Protein Atlas ◽

Cancer Genome Atlas ◽

Tissue Of Origin ◽

Using Data

AbstractIt is well known that, for a particular tissue, the homeostatic and cancer attractors are well apart both in gene expression and in protein expression spaces. By using data for 15 tissues and the corresponding tumors from The Cancer Genome Atlas, and for 49 normal tissues and 20 tumors from The Human Protein Atlas, we show that the set of normal attractors are also well separated from the set of tumors. Roughly speaking, one may say that there is a cancer progression axis orthogonal to the normal tissue differentiation and cancer manifolds. This separation suggests that therapies targeting common genes, which define the cancer axis, may be effective, irrespective of the tissue of origin.

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On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles

10.1101/000315 ◽

2013 ◽

Author(s):

Ying-Wooi Wan ◽

Claire Mach ◽

Genevera I. Allen ◽

Matthew Anderson ◽

Zhandong Liu

Keyword(s):

Ovarian Cancer ◽

Cancer Survival ◽

Human Cancer ◽

The Cancer Genome Atlas ◽

Detection Algorithms ◽

Level 3 ◽

Cancer Genome Atlas ◽

Ovarian Cancer Survival ◽

Generation Sequencing

Dysregulated microRNA (miRNA) expression is a well-established feature of human cancer. However, the role of specific miRNAs in determining cancer outcomes remains unclear. Using Level 3 expression data from the Cancer Genome Atlas (TCGA), we identified 61 miRNAs that are associated with overall survival in 469 ovarian cancers profiled by microarray (p<0.01). We also identified 12 miRNAs that are associated with survival when miRNAs were profiled in the same specimens using Next Generation Sequencing (miRNA-Seq) (p<0.01). Surprisingly, only 1 miRNA transcript is associated with ovarian cancer survival in both datasets. Our analyses indicate that this discrepancy is due to the fact that miRNA levels reported by the two platforms correlate poorly, even after correcting for potential issues inherent to signal detection algorithms. Further investigation is warranted.

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Identification of ST7 Alteration Profile, Frequency of Alteration and Correlation with ST7-Related Genes using TCGA Data

Walailak Journal of Science and Technology (WJST) ◽

10.48048/wjst.2019.6226 ◽

2019 ◽

Vol 16 (3) ◽

pp. 217-230

Author(s):

Nurdina CHARONG ◽

Moltira PROMKAN

Keyword(s):

Disease Free Survival ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Free Survival ◽

Cancer Genome Atlas ◽

Stomach Adenocarcinoma ◽

Using Data ◽

Liver Hepatocellular Carcinoma ◽

Disease Free ◽

Genome Atlas

ST7 (Suppression of Tumorigenicity 7) was reported as a protein playing a role in maintaining cellular structure. This study aims to investigate the ST7 alteration profiles and frequency of alteration in different cancers using data from The Cancer Genome Atlas (TCGA). The correlation between alterations of ST7 and angiogenesis-related genes, SERPINE1, MMP13, and VEGFA, was determined and the relation between ST7 and genes involved in suppression of ST7 transcription, PRMT5 and SMARCA4, were also analyzed. Data of 6 cancer groups from The Cancer Genome Atlas (TCGA) including ovarian serous cystadenocarcinoma (OSC), liver hepatocellular carcinoma (LHC), bladder urothelial adenocarcinoma (BUA), stomach adenocarcinoma (SC), prostate adenocarcinoma (PRAD) and glioblastoma multiforme (GBM) were downloaded for this study. The results indicated that 3 alteration patterns including amplification, missense mutation, and deletion were observed in 6 cancer studies. Gene pair between ST7 and SERPINE1 indicated the co-occurrent alteration in BUC, OSC and SC (p < 0.05). However, no association between alterations of these 2 genes and survival events in our study was observed. Shorter overall survival rate and disease-free survival were found in BUC patients with ST7, PRMT5, and SMARCA4 alterations. These findings suggest that using TCGA data can target the potential genes involved in carcinogenesis. Combining ST7 with PRMT5 and SMARCA4 could be used as indicators for analyzing the patient survival in BUC patients and may serve as the potential therapeutic target for cancer in the future.

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pyCancerSig: subclassifying human cancer with comprehensive single nucleotide, structural and microsatellite mutational signature deconstruction from whole genome sequencing

10.1101/785410 ◽

2019 ◽

Author(s):

Jessada Thutkawkorapin ◽

Jesper Eisfeldt ◽

Emma Tham ◽

Daniel Nilsson

Keyword(s):

Human Cancer ◽

The Cancer Genome Atlas ◽

Driver Mutations ◽

Learning Technology ◽

Single Nucleotide ◽

File Formats ◽

Learning Technique ◽

Cancer Genome Atlas ◽

Python Package ◽

Non Negative Matrix Factorization

AbstractBackgroundDNA damage accumulates over the course of cancer development. The often-substantial amount of somatic mutations in cancer poses a challenge to traditional methods to characterize tumors based on driver mutations. However, advances in machine learning technology can take advantage of this substantial amount of data.ResultsWe developed a command line interface python package, pyCancerSig, to perform sample profiling by integrating single nucleotide variation (SNV), structural variation (SV) and microsatellite instability (MSI) profiles into a unified profile. It also provides a command to decipher underlying cancer processes, employing an unsupervised learning technique, Non-negative Matrix Factorization, and a command to visualize the results. The package accepts common standard file formats (vcf, bam). The program was evaluated using a cohort of breast- and colorectal cancer from The Cancer Genome Atlas project (TCGA). The result showed that by integrating multiple mutations modes, the tool can correctly identify cases with known clear mutational signatures and can strengthen signatures in cases with unclear signal from an SNV-only profile.ConclusionspyCancerSig has demonstrated its capability in identifying known and unknown cancer processes, and at the same time, illuminates the association within and between the mutation modes.

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The Study of the Expression of CGB1 and CGB2 in Human Cancer Tissues

Genes ◽

10.3390/genes11091082 ◽

2020 ◽

Vol 11 (9) ◽

pp. 1082

Author(s):

Piotr Białas ◽

Aleksandra Śliwa ◽

Anna Szczerba ◽

Anna Jankowska

Keyword(s):

Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Squamous Cell ◽

Human Cancer ◽

Germ Cell Tumors ◽

Lung Squamous Cell Carcinoma ◽

Cervical Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Cancer Genome Atlas ◽

Cancer Tissues

Human chorionic gonadotropin (hCG) is a well-known hormone produced by the trophoblast during pregnancy as well as by both trophoblastic and non-trophoblastic tumors. hCG is built from two subunits: α (hCGα) and β (hCGβ). The hormone-specific β subunit is encoded by six allelic genes: CGB3, CGB5, CGB6, CGB7, CGB8, and CGB9, mapped to the 19q13.32 locus. This gene cluster also encompasses the CGB1 and CGB2 genes, which were originally considered to be pseudogenes, but as documented by several studies are transcriptionally active. Even though the protein products of these genes have not yet been identified, based on The Cancer Genome Atlas (TCGA) database analysis we showed that the mutual presence of CGB1 and CGB2 transcripts is a characteristic feature of cancers of different origin, including bladder urothelial carcinoma, cervical squamous cell carcinoma, esophageal carcinoma, head and neck squamous cell carcinoma, ovarian serous cystadenocarcinoma, lung squamous cell carcinoma, pancreatic adenocarcinoma, rectum adenocacinoma, testis germ cell tumors, thymoma, uterine corpus endometrial carcinoma and uterine carcinosarcoma.

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Expression profiles and prognostic roles of m6A writers, erasers and readers in gastric cancer

Future Oncology ◽

10.2217/fon-2020-0630 ◽

2021 ◽

Vol 17 (20) ◽

pp. 2605-2620

Author(s):

Jing-Jing Jing ◽

Xu Zhao ◽

Hao Li ◽

Li-ping Sun ◽

Yuan Yuan

Keyword(s):

Gastric Cancer ◽

Expression Profiles ◽

Tumor Stage ◽

The Cancer Genome Atlas ◽

Pathological Stage ◽

Rna Methylation ◽

Web Resources ◽

Cancer Genome Atlas ◽

M6a Rna Methylation ◽

Using Data

Aim: To explore the expression profiles of N6-methyladenosine (m6A) enzymes (writers, erasers and readers) and their associations with gastric cancer (GC) prognosis. Methods: Gene expression was analyzed using the UALCAN and Oncomine web resources. The prognostic roles of these genes in GC were analyzed using data from The Cancer Genome Atlas. Results: Thirteen m6A enzymes were found to be upregulated in GC tissues. The expression of m6A writers METTL3, RBM15 and WTAP was associated with pathological stage. The m6A eraser FTO was related to tumor stage and ALKBH5 expression was related to GC prognosis. The m6A reader YTHDF3 expression was associated with tumor stage. YTHDC2 was associated with survival of GC patients. Conclusion: Abnormal changes of key genes involved in m6A RNA methylation may have an important impact on GC development and prognosis.

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Preserved miR-361-3p Expression Is an Independent Prognostic Indicator of Favorable Survival in Cervical Cancer

Disease Markers ◽

10.1155/2018/8949606 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 9

Author(s):

Shikai Liu ◽

Lili Song ◽

Hairong Yao ◽

Liang Zhang ◽

Dongkui Xu ◽

...

Keyword(s):

Cervical Cancer ◽

Prognostic Indicator ◽

Bioinformatic Analysis ◽

The Cancer Genome Atlas ◽

Primary Therapy ◽

Free Survival ◽

Kaplan Meier ◽

Cancer Genome Atlas ◽

Using Data ◽

Independent Indicator

In this study, we aimed to assess the independent prognostic value of miR-361-3p in terms of overall survival (OS) and recurrence-free survival (RFS) in cervical cancer, as well as its possible regulative network. A retrospective analysis was performed by using data from the Cancer Genome Atlas-Cervical Cancer (TCGA-CESC). Results showed that decreased miR-361-3p expression was associated with lymphovascular invasion and poor responses to primary therapy. The patients with recurrence and the deceased cases had substantially lower miR-361-3p expression compared to their respective controls. By generating Kaplan-Meier curves of OS and RFS, we found that high miR-361-3p expression was associated with better survival outcome. More importantly, univariate and multivariate analysis confirmed that high miR-361-3p expression was an independent indicator of favorable OS (HR: 0.377, 95% CI: 0.233–0.608, p<0.001) and RFS (HR: 0.398, 95% CI: 0.192–0.825, p=0.013). By performing bioinformatic analysis, we identified 24 genes that were negatively correlated with miR-361-3p expression. Among the potential targeting genes, SOST, MTA1, TFRC, and YAP1 are involved in some important signaling pathways modulating cervical cancer cell invasion, migration, and drug sensitivity. Therefore, it is meaningful to verify the potential regulative effect of miR-361-3p on the expression of these genes in the future.

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Bayesian approach to determining penetrance of pathogenic SDH variants

Journal of Medical Genetics ◽

10.1136/jmedgenet-2018-105427 ◽

2018 ◽

Vol 55 (11) ◽

pp. 729-734 ◽

Cited By ~ 13

Author(s):

Diana E Benn ◽

Ying Zhu ◽

Katrina A Andrews ◽

Mathilda Wilding ◽

Emma L Duncan ◽

...

Keyword(s):

Bayesian Approach ◽

Genetic Variants ◽

The Cancer Genome Atlas ◽

Pathogenic Variants ◽

Combining Data ◽

Disease Penetrance ◽

Cancer Genome Atlas ◽

Observational Cohort ◽

Using Data ◽

Hereditary Pheochromocytoma

BackgroundUntil recently, determining penetrance required large observational cohort studies. Data from the Exome Aggregate Consortium (ExAC) allows a Bayesian approach to calculate penetrance, in that population frequencies of pathogenic germline variants should be inversely proportional to their penetrance for disease. We tested this hypothesis using data from two cohorts for succinate dehydrogenase subunits A, B and C (SDHA–C) genetic variants associated with hereditary pheochromocytoma/paraganglioma (PC/PGL).MethodsTwo cohorts were 575 unrelated Australian subjects and 1240 unrelated UK subjects, respectively, with PC/PGL in whom genetic testing had been performed. Penetrance of pathogenic SDHA–C variants was calculated by comparing allelic frequencies in cases versus controls from ExAC (removing those variants contributed by The Cancer Genome Atlas).ResultsPathogenic SDHA–C variants were identified in 106 subjects (18.4%) in cohort 1 and 317 subjects (25.6%) in cohort 2. Of 94 different pathogenic variants from both cohorts (seven in SDHA, 75 in SDHB and 12 in SDHC), 13 are reported in ExAC (two in SDHA, nine in SDHB and two in SDHC) accounting for 21% of subjects with SDHA–C variants. Combining data from both cohorts, estimated lifetime disease penetrance was 22.0% (95% CI 15.2% to 30.9%) for SDHB variants, 8.3% (95% CI 3.5% to 18.5%) for SDHC variants and 1.7% (95% CI 0.8% to 3.8%) for SDHA variants.ConclusionPathogenic variants in SDHB are more penetrant than those in SDHC and SDHA. Our findings have important implications for counselling and surveillance of subjects carrying these pathogenic variants.

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