Clinical and Immunological Biomarkers for Systemic Lupus Erythematosus

Yu, Haitao; Nagafuchi, Yasuo; Fujio, Keishi

doi:10.3390/biom11070928

Cited by 92 publications

(59 citation statements)

References 119 publications

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“…Previously, we discovered that the initial lymphatic metastasis of COAD may be highly related to the “KEGG systemic lupus erythematosus” pathway. Systemic lupus erythematosus is characterized by overactivation of the immune system, abnormal function of many immune cells, and the production of antibodies that attack their components [ 29 – 31 ]. These can significantly affect the tumor microenvironment.…”

Section: Resultsmentioning

confidence: 99%

Six Genes Associated with Lymphatic Metastasis in Colon Adenocarcinoma Linked to Prognostic Value and Tumor Immune Cell Infiltration

Wang

Yin

Yang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Objective. The aim of the study is to explore the relationship between lymphatic metastasis genes, prognosis, and immune cell infiltration in patients with colon cancer. Methods. Based on the Cancer Genome Atlas Program (TCGA) database, differentially expressed genes and prognostic genes related to colon adenocarcinoma (COAD) lymphatic metastasis were screened and intersected. We used lasso and univariate Cox regression analysis to screen core genes and establish a preliminary prediction model. GO and KEGG enrichment analysis was used for lymphatic metastasis-related genes, and single GSEA was used for the final screening results. Finally, we evaluated the relationship between identified genes and immune cell infiltration. Results. A total of 1727 genes were differentially expressed between COAD patients with TNM stages of N0 and N1. After further screening, six core genes (RNU4-2, ZNF556, RNVU1-15, NSA2P6, RN7SL767P, and RN7SL473P) were obtained, and a preliminary prediction model was established, in which ZNF556 was a risk factor, and the rest were protective factors. Single GSEA showed that pathways such as systemic lupus erythematosus might play an important role in the initial lymphatic metastasis of COAD. GO and KEGG enrichment analysis of 1727 genes supported this result. Immune infiltration analysis showed that six genes were significantly correlated with T cell and NK cell families. Conclusion. Six core genes may affect COAD initial lymphatic metastasis through the systemic lupus erythematosus pathway and immune cell infiltration.

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Section: Resultsmentioning

confidence: 99%

Six Genes Associated with Lymphatic Metastasis in Colon Adenocarcinoma Linked to Prognostic Value and Tumor Immune Cell Infiltration

Wang

Yin

Yang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“… 22 Therefore, the rapid, sensitive, and specific evaluation of disease activity for patients with SLE is important for both short‐term and long‐term diagnosis and treatment planning. 23 …”

Section: Discussionmentioning

confidence: 99%

“…22 Therefore, the rapid, sensitive, and specific evaluation of disease activity for patients with SLE is important for both short-term and long-term diagnosis and treatment planning. 23 Autoimmune and inflammatory reaction in SLE patients can damage vascular endothelium, break the balance between procoagulant and anticoagulant, cause coagulation and fibrinolysis disorders, and lead to high risk of thrombosis and atherosclerosis. 24 FIB is an important biomarker in the coagulation system, which has been proved to be closely related to disease activity and organ damage.…”

Section: Discussionmentioning

confidence: 99%

The predictive value of fibrinogen‐to‐albumin ratio in the active, severe active, and poor prognosis of systemic lupus erythematosus: A single‐center retrospective study

Dai

Chen

et al. 2022

Clinical Laboratory Analysis

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Objective To evaluate the prediction and effect of fibrinogen‐to‐albumin ratio (FAR) on active, severe active, and poor prognosis of systemic lupus erythematosus (SLE). Methods One hundred and sixty‐eight patients with SLE who were treated in our hospital were enrolled, the clinical data, laboratory indexes, and disease prognosis of all patients were collected and analyzed. Results Triglyceride (TG), FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while complement 3 (C3) was the protective factor of active SLE, the odds ratio (OR) values were 2.968, 3.698, 2.114, 2.727, and 0.652, respectively ( p < 0.05). FAR, ESR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of severe active SLE, the OR values were 3.791, 1.953, 2.187, and 0.742, respectively ( p < 0.05). SLE disease activity index (SLEDAI), TG, FAR, and anti‐dsDNA (+) were the influencing factors, while C3 was the protective factor of poor prognosis SLE, the OR values were 3.024, 2.293, 3.012, 2.323, and 0.801, respectively ( p < 0.05). FAR and FIB were positively correlated with SLEDAI, while ALB was negatively correlated with SLEDAI, the related coefficient ( r ) were 0.398, 0.267, −0.270, respectively. The receiver operating curve (ROC) analysis showed that the predictive values of FAR for active, severe active and poor prognosis SLE were 0.769, 0.769, and 0.734, respectively, were significant higher than FIB and ALB ( p < 0.05). Conclusion Fibrinogen‐to‐albumin ratio was an influencing factor of active, severe active, and poor prognosis SLE had higher predictive value than FIB and ALB for the activity and prognosis of SLE.

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“…On the other hand, many clinical and omics-based markers for different clinical outcomes have been identified using machine learning (ML) techniques. However, clinical markers are often subject to enormous variability across patients, and omics experiments are often not validated in external cohorts due to the enormous biases caused by the use of different technical platforms [ 18 ]. Therefore, it is necessary to analyze in detail the connections between the molecular portraits and their implications in the medical environment, but also to use a standardized approach to incorporate this knowledge in practice reproducibly.…”

Section: Introductionmentioning

confidence: 99%

Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression

Toro-Domínguez

Martorell-Marugán

Martínez-Bueno

et al. 2022

Briefings in Bioinformatics

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Objectives Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions. Methods Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores. Results MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes. Conclusions MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions.

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Clinical and Immunological Biomarkers for Systemic Lupus Erythematosus

Cited by 92 publications

References 119 publications

Six Genes Associated with Lymphatic Metastasis in Colon Adenocarcinoma Linked to Prognostic Value and Tumor Immune Cell Infiltration

Six Genes Associated with Lymphatic Metastasis in Colon Adenocarcinoma Linked to Prognostic Value and Tumor Immune Cell Infiltration

The predictive value of fibrinogen‐to‐albumin ratio in the active, severe active, and poor prognosis of systemic lupus erythematosus: A single‐center retrospective study

Scoring personalized molecular portraits identify Systemic Lupus Erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression

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