Prognostic and predictive value of a mRNA signature in peripheral T‐cell lymphomas: A mRNA expression analysis

Tu, Jiannan; Kuang, Zhixing; Xie, Xiaoxiao; Wu, Shizhen; Wu, Ting; Chen, Shengchi

doi:10.1111/jcmm.15851

Cited by 9 publications

(5 citation statements)

References 60 publications

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“…CCN1, LAPTM5, and ArhGAP15 are among the most common genes. CCN1 is linked to HDAC1 inhibition 40 , and LAPTM5 has been identified as an mRNA signature for PTCL 41 . For ArhGAP15, one of its gene family, ArhGAP30, is associated with histone acetylation, which is known to facilitate p53 acetylation 42 .…”

Section: Resultsmentioning

confidence: 99%

Molecular data representation based on gene embeddings for cancer drug response prediction

Park,

Lee

2023

Sci Rep

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Cancer drug response prediction is a crucial task in precision medicine, but existing models have limitations in effectively representing molecular profiles of cancer cells. Specifically, when these models represent molecular omics data such as gene expression, they employ a one-hot encoding-based approach, where a fixed gene set is selected for all samples and omics data values are assigned to specific positions in a vector. However, this approach restricts the utilization of embedding-vector-based methods, such as attention-based models, and limits the flexibility of gene selection. To address these issues, our study proposes gene embedding-based fully connected neural networks (GEN) that utilizes gene embedding vectors as input data for cancer drug response prediction. The GEN allows for the use of embedding-vector-based architectures and different gene sets for each sample, providing enhanced flexibility. To validate the efficacy of GEN, we conducted experiments on three cancer drug response datasets. Our results demonstrate that GEN outperforms other recently developed methods in cancer drug prediction tasks and offers improved gene representation capabilities. All source codes are available at https://github.com/DMCB-GIST/GEN/.

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Section: Resultsmentioning

confidence: 99%

Molecular data representation based on gene embeddings for cancer drug response prediction

Park,

Lee

2023

Sci Rep

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“…As a tumor suppressor, LAPTM5 mainly has a negative regulatory effect on receptor-mediated signaling in T cells or B cells ( 36 , 37 ). Although the direct impact of LAPTM5 on cancer cells has attracted much attention in recent years, data concerning ER + BC have not been reported.…”

Section: Discussionmentioning

confidence: 99%

Spine‑specific downregulation of LAPTM5 expression promotes the progression and spinal metastasis of estrogen receptor‑positive breast cancer by activating glutamine‑dependent mTOR signaling

Meng

Liang

et al. 2022

Int J Oncol

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Estrogen receptor-positive (ER + ) breast cancer (BC) is a malignancy that is prone to metastasis to the spine, which is difficult to treat and often results in poor prognosis. However, the mechanism underlying the tumorigenesis and spinal metastasis of ER + BC remains unclear. Lysosomal protein transmembrane 5 (LAPTM5) has been reported as a tumor suppressor in several types of cancer, but its role in ER + BC has not been described. Here, by analyzing a gene sequencing dataset and ER + BC tissues, tumor-adjacent normal tissues and spinal metastatic tissues from patients and mouse models, we found that LAPTM5 expression is negatively related to the progression and spinal metastasis of ER + BC. Subsequently, in vitro experiments demonstrated that downregulation of LAPTM5 expression promoted the proliferation, migration, and chemoresistance of ER + BC cells by activating glutamine-dependent mTOR signaling. A high level of CX3CL1 could inhibit LAPTM5 expression, explaining how ER + BC metastasized to the spine. Thus, we found that LAPTM5 functions as a tumor suppressor in ER + BC and that the CX3CL/CX3CR1/LAPTM5/glutamine axis mediates the spinal metastasis of ER + BC. This axis may be a promising therapeutic target for ER + BC.

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“…MacroH2A1 is one of the many genes on chromosome 5q that is frequently lost in MDS 42 . In T‐cell lymphoma and AML, macroH2A1 mRNA and macroH2A2 protein, respectively, are part of signatures that are associated with elevated risk and poor prognosis 63 , 64 . Taken together, the knowledge about the involvement of H2A variants in hematopoietic malignancies until now is limited, but point to tumor‐promoting roles of H2A.B, while macroH2A1.1 might act as a possible differentiation‐promoting tumor suppressor.…”

Section: The Diverse Group Of H2a Variantsmentioning

confidence: 99%

Histone Variants and Their Chaperones in Hematological Malignancies

et al. 2023

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Epigenetic regulation occurs on the level of compacting DNA into chromatin. The functional unit of chromatin is the nucleosome, which consists of DNA wrapped around a core of histone proteins. While canonical histone proteins are incorporated into chromatin through a replication-coupled process, structural variants of histones, commonly named histone variants, are deposited into chromatin in a replication-independent manner. Specific chaperones and chromatin remodelers mediate the locus-specific deposition of histone variants. Although histone variants comprise one of the least understood layers of epigenetic regulation, it has been proposed that they play an essential role in directly regulating gene expression in health and disease. Here, we review the emerging evidence suggesting that histone variants have a role at different stages of hematopoiesis, with a particular focus on the histone variants H2A, H3, and H1. Moreover, we discuss the current knowledge on how the dysregulation of histone variants can contribute to hematopoietic malignancies.

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Prognostic and predictive value of a mRNA signature in peripheral T‐cell lymphomas: A mRNA expression analysis

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 9 publications

References 60 publications

Molecular data representation based on gene embeddings for cancer drug response prediction

Molecular data representation based on gene embeddings for cancer drug response prediction

Spine‑specific downregulation of LAPTM5 expression promotes the progression and spinal metastasis of estrogen receptor‑positive breast cancer by activating glutamine‑dependent mTOR signaling

Histone Variants and Their Chaperones in Hematological Malignancies

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