A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer

Chang, Yu-Tien; Tsai, Wen‐Chiuan; Lin, Wei-Zhi; Wu, Chia-Chao; Yu, Jyh-Cherng; Tseng, Vincent S.; Liao, Guo‐Shiou; Hu, Je-Ming; Hsu, Huan-Ming; Chang, Yu‐Jia; Lin, Meng-Chiung; Chu, Chi‐Ming; Yang, Chien-Yi

doi:10.3389/fonc.2021.759952

Cited by 9 publications

(7 citation statements)

References 89 publications

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“…IGLC2 has a similar expression and functional pattern to LINC01871 in our study ( Figure 8 ). Chang et al (2021 ) found in a study of triple-negative breast cancer (TNBC) cohort that a high expression of IGLC2 was related to a favorable prognosis for TNBC patients, which is consistent with our results. In addition, IGLC2 is linked with the proliferation, migration, and invasion of MDA-MB-231 cells.…”

Section: Discussionsupporting

confidence: 93%

“…In addition, IGLC2 is linked with the proliferation, migration, and invasion of MDA-MB-231 cells. Pathway enrichment analysis showed that IGLC2 is related to the extracellular matrix–receptor interaction ( Chang et al, 2021 ). All these features make IGLC2 have the potential to be a biomarker to predict prognosis, even for identifying breast cancer patients who can benefit the most from immune checkpoint blockade treatment.…”

Section: Discussionmentioning

confidence: 99%

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Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

Gao

Lou

et al. 2022

Front. Genet.

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Breast cancer is a heterogeneous disease whose subtypes represent different histological origins, prognoses, and therapeutic sensitivity. But there remains a strong need for more specific biomarkers and broader alternatives for personalized treatment. Our study classified breast cancer samples from The Cancer Genome Atlas (TCGA) into three groups based on glycosylation-associated genes and then identified differentially expressed genes under different glycosylation patterns to construct a prognostic model. The final prognostic model containing 23 key molecules achieved exciting performance both in the TCGA training set and testing set GSE42568 and GSE58812. The risk score also showed a significant difference in predicting overall clinical survival and immune infiltration analysis. This work helped us to understand the heterogeneity of breast cancer from another perspective and indicated that the identification of risk scores based on glycosylation patterns has potential clinical implications and immune-related value for breast cancer.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

Gao

Lou

et al. 2022

Front. Genet.

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“…We also performed differential expression gene analysis for Tumor_edge_3 region based on the annotation results of PAST on BCS2, and identified the five most significant differential expression genes (DEGs) including IGHG3, IGKC, IGLC2, IGHG4 and IGHG1 with adjusted p -values of 1.11e-83, 1.86e-78, 9.18e-74, 9.18e-74 and 1.66e-69, respectively. According to previous literature, the linkage of IGHG1/3/4 provides information for prognosis of diseases like autoimmunity and malignancy 41 , IGKC , serving as a robust immune marker, could predict metastasis-free survival and response to chemotherapy 42 , and IGLC2 was proved to be a significant prognostic biomarker for triple-negative breast cancer patients 43 . The gene ontology (GO) enrichment for the top 10 DEGs of Tumor_edge_3 also significantly revealed lots of biological immune processes (Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

PAST: latent feature extraction with a Prior-based self-Attention framework for Spatial Transcriptomics

Zhang

Chen

et al. 2022

Preprint

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Rapid advances in spatial transcriptomics (ST) have revolutionized the interrogation of spatial heterogeneity and increased the demand for comprehensive methods to effectively characterize spatial domains. As a prerequisite for ST data analysis, spatial domain characterization is a crucial step for downstream analyses and biological implications. Here we propose PAST, a variational graph convolutional auto-encoder for ST, which effectively integrates prior information via a Bayesian neural network, captures spatial patterns via a self-attention mechanism, and enables scalable application via a ripple walk sampler strategy. Through comprehensive experiments on datasets generated by different technologies, we demonstrated that PAST could effectively characterize spatial domains and facilitate various downstream analyses, including ST visualization, spatial trajectory inference and pseudo-time analysis, by integrating spatial information and reference from various sources. Besides, we also show the advantages of PAST for accurate annotation of spatial domains in newly sequenced ST data and biological implications in the annotated domains.

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“…In humans, YWHAH might be associated with various cancers, and its polymorphisms are implicated to be genetically associated with schizophrenia. 76 In humans, Iglc2 or (Ig lambda-2 chain C region) gene has been recently linked to the prognosis of triple-negative breast cancer 77 and its deposition in AL-amyloid lesions is linked to a new disease entity of AL amyloidosis.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Sex-Specific Silica Nanoparticle Protein Corona Compositions Exposed to Male and Female BALB/c Mice Plasmas

Ashkarran

Gharibi

Grunberger

et al. 2022

ACS Bio Med Chem Au

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As various nanoparticles (NPs) are increasingly being used in nanomedicine products for more effective and less toxic therapy and diagnosis of diseases, there is a growing need to understand their biological fate in different sexes. Herein, we report a proof-of-concept result of sex-specific protein corona compositions on the surface of silica NPs as a function of their size and porosity upon incubation with plasma proteins of female and male BALB/c mice. Our results demonstrate substantial differences between male and female protein corona profiles on the surface of silica nanoparticles. By comparing protein abundances between male and female protein coronas of mesoporous silica nanoparticles and Stober silica nanoparticles of ∼100, 50, and 100 nm in diameter, respectively, we detected 17, 4, and 4 distinct proteins, respectively, that were found at significantly different concentrations for these constructs. These initial findings demonstrate that animal sex can influence protein corona formation on silica NPs as a function of the physicochemical properties. A more thorough consideration of the role of plasma sex would enable nanomedicine community to design and develop safer and more efficient diagnostic and therapeutic nanomedicine products for both sexes.

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A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer

Cited by 9 publications

References 89 publications

Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

Identification of a prognostic risk-scoring model and risk signatures based on glycosylation-associated cluster in breast cancer

PAST: latent feature extraction with a Prior-based self-Attention framework for Spatial Transcriptomics

Sex-Specific Silica Nanoparticle Protein Corona Compositions Exposed to Male and Female BALB/c Mice Plasmas

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