Comprehensive analysis of spliceosome genes and their mutants across 27 cancer types in 9070 patients: clinically relevant outcomes in the context of 3P medicine

Ye, Zhen; Bing, Aiying; Zhao, Shulian; Yi, Shuying; Zhan, Xianquan

doi:10.1007/s13167-022-00279-0

Cited by 9 publications

(6 citation statements)

References 49 publications

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“…In the present study, we performed the first characterization of the expression of various isoforms of two of these alternatively spliced genes— ADAM12 and MUC4 —in a metastatic cell line model. Our study supports previous efforts to analyze spliceosome genes in 9070 patients across 27 types of cancer within the context of 3PM medicine [ 18 ]. We have provided a detailed analysis of pre-selected genes that will develop the field of alternative splicing for biomarker discovery to help in establishing the concept of 3P medicine and making it clinically viable.…”

Section: Discussionsupporting

confidence: 88%

“…Altered splicing machinery has been linked to cancer [ 12 ]. More than 90% of genes are alternatively spliced, and disturbances to this complex machinery could result in the initiation and progression of cancer [ 13 , 14 ] Molecular changes in splicing genes and altered ratios of abundance of splice variants have been associated with the occurrence, increased progression and adverse prognosis of many types of cancer, including colorectal, breast, prostate and blood cancer [ 15 , 16 , 17 , 18 ]). Therefore, studying the alternative splicing (AS) events happening in CRC would allow for the identification of biomarkers that could be used for predictive diagnosis, prognosis, patient stratification and treatment selection.…”

Section: Introductionmentioning

confidence: 99%

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Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis

Althenayyan

AlMuhanna

AlAbdulrahman

et al. 2023

JPM

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There is a pertinent need to develop prognostic biomarkers for practicing predictive, preventive and personalized medicine (PPPM) in colorectal cancer metastasis. The analysis of isoform expression data governed by alternative splicing provides a high-resolution picture of mRNAs in a defined condition. This information would not be available by studying gene expression changes alone. Hence, we utilized our prior data from an exon microarray and found ADAM12 and MUC4 to be strong biomarker candidates based on their alternative splicing scores and pattern. In this study, we characterized their isoform expression in a cell line model of metastatic colorectal cancer (SW480 & SW620). These two genes were found to be good prognostic indicators in two cohorts from The Cancer Genome Atlas database. We studied their exon structure using sequence information in the NCBI and ENSEMBL genome databases to amplify and validate six isoforms each for the ADAM12 and MUC4 genes. The differential expression of these isoforms was observed between normal, primary and metastatic colorectal cancer cell lines. RNA-Seq analysis further proved the differential expression of the gene isoforms. The isoforms of MUC4 and ADAM12 were found to change expression levels in response to 5-Fluorouracil (5-FU) treatment in a dose-, time- and cell line-dependent manner. Furthermore, we successfully detected the protein isoforms of ADAM12 and MUC4 in cell lysates, reflecting the differential expression at the protein level. The change in the mRNA and protein expression of MUC4 and ADAM12 in primary and metastatic cells and in response to 5-FU qualifies them to be studied as potential biomarkers. This comprehensive study underscores the importance of studying alternatively spliced isoforms and their potential use as prognostic and/or predictive biomarkers in the PPPM approach towards cancer.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis

Althenayyan

AlMuhanna

AlAbdulrahman

et al. 2023

JPM

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“…34 Despite the extensive research devoted to investigating the pathophysiological mechanisms of this cancer, the precise etiology remains unknown. 35,36 Our study is grounded on single-cell RNA and highthroughput RNA sequencing data. We have discovered a potential anti-tumor immune mechanism involving the participation of TRIM28 in regulating immune cell infiltration, exhaustion, and the activity of the cGAS-STING pathway in CRPC.…”

Section: Discussionmentioning

confidence: 99%

The correlation between TRIM28 expression and immune checkpoints in CRPC

Xue,

Zuo,

Chang

et al. 2024

The FASEB Journal

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This study delves into the unexplored realm of castration‐resistant prostate cancer (CRPC) by investigating the role of TRIM28 and its intricate molecular mechanisms using high‐throughput single‐cell transcriptome sequencing and advanced bioinformatics analysis. Our comprehensive examination unveiled dynamic TRIM28 expression changes, particularly in immune cells such as macrophages and CD8+ T cells within CRPC. Correlation analyses with TCGA data highlighted the connection between TRIM28 and immune checkpoint expression and emphasized its pivotal influence on the quantity and functionality of immune cells. Using TRIM28 knockout mouse models, we identified differentially expressed genes and enriched pathways, unraveling the potential regulatory involvement of TRIM28 in the cGAS‐STING pathway. In vitro, experiments further illuminated that TRIM28 knockout in prostate cancer cells induced a notable anti‐tumor immune effect by inhibiting M2 macrophage polarization and enhancing CD8+ T cell activity. This impactful discovery was validated in an in situ transplant tumor model, where TRIM28 knockout exhibited a deceleration in tumor growth, reduced proportions of M2 macrophages, and enhanced infiltration of CD8+ T cells. In summary, this study elucidates the hitherto unknown anti‐tumor immune role of TRIM28 in CRPC and unravels its potential regulatory mechanism via the cGAS‐STING signaling pathway. These findings provide novel insights into the immune landscape of CRPC, offering promising directions for developing innovative therapeutic strategies.

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“…We merged the data of ALL patients in Phases I, II and III, and then excluded the following datasets: 1) duplicate patients with training cohort; 2) not BM sample; 3) without follow-up time; 4) unknown death or not; and 5) without detail clinical characteristic. The calculation of immune score, stromal score and tumor purity by employing the ESTIMATE algorithm for all downloaded dataset was performed by a custom script of Python 3.9.5 (Python Software Foundation, Delaware, USA) and “estimate” R package of R software 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria) [ 46 ]. The stromal and immune scores were calculated by perform single-sample gene set-enrichment analysis (ssGSEA) [ 47 , 48 ], and the tumor purity was calculated by using the following formula:

ESTIMATE score represents the sum of stromal score and immune score [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

“…The heatmap and volcano plots were generated by the “ggplot2” and “pheatmap” R packages, respectively [ 50 ]. The identification of the common DEGs from the immune score and stromal score groups was processed by Python script [ 46 ].…”

Section: Methodsmentioning

confidence: 99%

Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia

Hua

2022

Aging

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Acute lymphoblastic leukemia (ALL) is a common and life-threatening hematologic malignancy, its occurrence and progression are closely related to immune/stromal cell infiltration in the bone marrow (BM) microenvironment. However, no studies have described an immune/stromal cell infiltration-related gene (ISCIRG)-based prognostic signature for ALL. A total of 444 patients involving 437 bulk and 7 single-cell RNA-seq datasets were included in this study. Eligible datasets were searched and reviewed from the database of TCGA, TARGET project and GEO. Then an integrated bioinformatics analysis was performed to select optimal prognosis-related genes from ISCIRGs, construct a nomogram model for predicting prognosis, and assess the predictive power. After LASSO and multivariate Cox regression analyses, a seven ISCIRGs-based signature was proved to be able to significantly stratify patients into high-and low-risk groups in terms of OS. The seven genes were confirmed that directly related to the composition and status of immune/stromal cells in BM microenvironment by analyzing bulk and single-cell RNA-seq datasets. The calibration plot showed that the predicted results of the nomogram were consistent with the actual observation results of training/validation cohort. This study offers a reference for future research regarding the role of ISCIRGs in ALL and the clinical care of patients.

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Comprehensive analysis of spliceosome genes and their mutants across 27 cancer types in 9070 patients: clinically relevant outcomes in the context of 3P medicine

Cited by 9 publications

References 49 publications

Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis

Alternatively Spliced Isoforms of MUC4 and ADAM12 as Biomarkers for Colorectal Cancer Metastasis

The correlation between TRIM28 expression and immune checkpoints in CRPC

Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia

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