Prognostic value, immune signature and molecular mechanisms of the APOBEC family members APOBEC1, APOBEC3A, APOBEC3G and APOBEC3H in pancreatic adenocarcinoma

Duan, Yunjie; Du, Yongxing; Gu, Zongting; Zheng, Xiaohao; Wang, Chengfeng

doi:10.3389/fmolb.2022.1036287

Cited by 5 publications

(1 citation statement)

References 48 publications

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“…Allelic differences in the mismatch repair gene Msh3 m odify the stability of repeats in mice and in tumours (Maksimov et al., 2023). Evolving populations of cancer cells can co‐opt established mechanisms that generate variation, such as enzymatic cytosine deamination by AID/APOBEC (Conticello, 2008; Duan et al., 2022). For example, not only is APOBEC1 expressed in oesophageal adenocarcinomas, but its mutational signature is observed there (Saraconi et al., 2014).…”

Section: Introductionmentioning

confidence: 99%

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

Caporale

2024

The Journal of Physiology

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Darwin recognized that ‘a grand and almost untrodden field of inquiry will be opened, on the causes and laws of variation.’ However, because the Modern Synthesis assumes that the intrinsic probability of any individual mutation is unrelated to that mutation's potential adaptive value, attention has been focused on selection rather than on the intrinsic generation of variation. Yet many examples illustrate that the term ‘random’ mutation, as widely understood, is inaccurate. The probabilities of distinct classes of variation are neither evenly distributed across a genome nor invariant over time, nor unrelated to their potential adaptive value. Because selection acts upon variation, multiple biochemical mechanisms can and have evolved that increase the relative probability of adaptive mutations. In effect, the generation of heritable variation is in a feedback loop with selection, such that those mechanisms that tend to generate variants that survive recurring challenges in the environment would be captured by this survival and thus inherited and accumulated within lineages of genomes. Moreover, because genome variation is affected by a wide range of biochemical processes, genome variation can be regulated. Biochemical mechanisms that sense stress, from lack of nutrients to DNA damage, can increase the probability of specific classes of variation. A deeper understanding of evolution involves attention to the evolution of, and environmental influences upon, the intrinsic variation generated in gametes, in other words upon the biochemical mechanisms that generate variation across generations. These concepts have profound implications for the types of questions that can and should be asked, as omics databases become more comprehensive, detection methods more sensitive, and computation and experimental analyses even more high throughput and thus capable of revealing the intrinsic generation of variation in individual gametes. These concepts also have profound implications for evolutionary theory, which, upon reflection it will be argued, predicts that selection would increase the probability of generating adaptive mutations, in other words, predicts that the ability to evolve itself evolves. image

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Section: Introductionmentioning

confidence: 99%

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

Caporale

2024

The Journal of Physiology

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APOBEC3A drives metastasis of high-grade serous ovarian cancer by altering epithelial-to-mesenchymal transition

Devenport,

Tran,

Harris

et al. 2024

Preprint

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High-grade serous ovarian cancer (HGSOC) is the most prevalent and aggressive histological subtype of ovarian cancer, and often presents with metastatic disease. The drivers of metastasis in HGSOC remain enigmatic. APOBEC3A (A3A), an enzyme that generates mutations across various cancers, has been proposed as a mediator of tumor heterogeneity and disease progression. However, the role of A3A in HGSOC has not been explored. Through analysis of genome sequencing from primary HGSOC, we observed an association between high levels of APOBEC3 mutagenesis and poor overall survival. We experimentally addressed this correlation by modeling A3A activity in HGSOC cell lines and mouse models which resulted in increased metastatic behavior of HGSOC cells in culture and distant metastatic spread in vivo. A3A activity in both primary and cultured HGSOC cells yielded consistent alterations in expression of epithelial-mesenchymal-transition (EMT) genes resulting in hybrid EMT and mesenchymal signatures, and providing a mechanism for their increased metastatic potential. Our findings define the prevalence of A3A mutagenesis in HGSOC and implicate A3A as a driver of HGSOC metastasis via EMT, underscoring its clinical relevance as a potential prognostic biomarker. Our study lays the groundwork for the development of targeted therapies aimed at mitigating the deleterious impact of A3A-driven EMT in HGSOC.

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Stage II oesophageal carcinoma: peril in disguise associated with cellular reprogramming and oncogenesis regulated by pseudogenes

Pravallika,

Rajasekaran

2024

BMC Genomics

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Introduction Pseudogenes have been implicated for their role in regulating cellular differentiation and organismal development. However, their role in promoting cancer-associated differentiation has not been well-studied. This study explores the tumour landscape of oesophageal carcinoma to identify pseudogenes that may regulate events of differentiation to promote oncogenic transformation. Materials and method De-regulated differentiation-associated pseudogenes were identified using DeSeq2 followed by ‘InteractiVenn’ analysis to identify their expression pattern. Gene expression dependent and independent enrichment analyses were performed with GSEA and ShinyGO, respectively, followed by quantification of cellular reprogramming, extent of differentiation and pleiotropy using three unique metrics. Stage-specific gene regulatory networks using Bayesian Network Splitting Average were generated, followed by network topology analysis. MEME, STREME and Tomtom were employed to identify transcription factors and miRNAs that play a regulatory role downstream of pseudogenes to initiate cellular reprogramming and further promote oncogenic transformation. The patient samples were stratified based on the expression pattern of pseudogenes, followed by GSEA, mutation analysis and survival analysis using GSEA, MAF and ‘survminer’, respectively. Results Pseudogenes display a unique stage-wise expression pattern that characterizes stage II (SII) ESCA with a high rate of cellular reprogramming, degree of differentiation and pleiotropy. Gene regulatory network and associated topology indicate high robustness, thus validating high pleiotropy observed for SII. Pseudogene-regulated expression of SOX2, FEV, PRRX1 and TFAP2A in SII may modulate cellular reprogramming and promote oncogenesis. Additionally, patient stratification-based mutational analysis in SII signifies APOBEC3A (A3A) as a potential hallmark of homeostatic mutational events of reprogrammed cells which in addition to de-regulated APOBEC3G leads to distinct events of hypermutations. Further enrichment analysis for both cohorts revealed the critical role of combinatorial expression of pseudogenes in cellular reprogramming. Finally, survival analysis reveals distinct genes that promote poor prognosis in SII ESCA and patient-stratified cohorts, thus providing valuable prognostic bio-markers along with markers of differentiation and oncogenesis for distinct landscapes of pseudogene expression. Conclusion Pseudogenes associated with the events of differentiation potentially aid in the initiation of cellular reprogramming to facilitate oncogenic transformation, especially during SII ESCA. Despite a better overall survival of SII, patient stratification reveals combinatorial de-regulation of pseudogenes as a notable marker for a high degree of cellular differentiation with a unique mutational landscape.

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Prognostic value, immune signature and molecular mechanisms of the APOBEC family members APOBEC1, APOBEC3A, APOBEC3G and APOBEC3H in pancreatic adenocarcinoma

Cited by 5 publications

References 48 publications

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

Evolutionary feedback from the environment shapes mechanisms that generate genome variation

APOBEC3A drives metastasis of high-grade serous ovarian cancer by altering epithelial-to-mesenchymal transition

Stage II oesophageal carcinoma: peril in disguise associated with cellular reprogramming and oncogenesis regulated by pseudogenes

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