Serpin Family A Member 1 Is Prognostic and Involved in Immunological Regulation in Human Cancers

Kuai, Xingwang; Lv, Jiaying; Zhang, Junyu; Xu, Manyu; Ji, Juling

doi:10.3390/ijms241411566

Cited by 4 publications

(3 citation statements)

References 38 publications

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“…Its prognostic value was observed across multiple cancer types, yet its role varies among different malignancies. A recent study by Kuai X. et al found that increased SERPINA1 expression is linked to improved overall survival rates in BRCA, COAD, SARC, and SKCM, but worse survival rates in GBMLGG, HNSC, LGG, LIHC, and LUSC ( Kuai et al, 2023 ). This research further confirmed its important function as a standalone predictor in forecasting the outcome of breast cancer.…”

Section: Discussionmentioning

confidence: 99%

Unraveling breast cancer prognosis: a novel model based on coagulation-related genes

Lei,

Li,

Yang

et al. 2024

Front. Mol. Biosci.

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ObjectiveBreast cancer is highly heterogeneous, presenting challenges in prognostic assessment. Developing a universally applicable prognostic model could simplify clinical decision-making. This study aims to develop and validate a novel breast cancer prognosis model using coagulation-related genes with broad clinical applicability.MethodsA total of 203 genes related to coagulation were obtained from the KEGG database, and the mRNA data of 1,099 tumor tissue samples and 572 samples of normal tissue were retrieved from the TCGA-BRCA cohort and GTEx databases. The R package “limma” was utilized to detect variations in gene expression related to coagulation between the malignancies and normal tissue. A model was constructed in the TCGA cohort through a multivariable Cox regression analysis, followed by validation using the GSE42568 dataset as the testing set. Constructing a nomogram incorporating clinical factors to enhance the predictive capacity of the model. Utilizing the ESTIMATE algorithm to investigate the immune infiltration levels in groups with deferent risk. Performing drug sensitivity analysis using the “oncoPredict” package.ResultsA risk model consisting of six coagulation-associated genes (SERPINA1, SERPINF2, C1S, CFB, RASGRP1, and TLN2) was created and successfully tested for validation. Identified were 6 genes that serve as protective factors in the model’s development. Kaplan-Meier curves revealed a worse prognosis in the high-risk group compared to the low-risk group. The ROC analysis showed that the model accurately forecasted the overall survival (OS) of breast cancer patients at 1, 3, and 5 years. Nomogram accompanied by calibration curves can also provide better guidance for clinical decision-making. The low-risk group is more likely to respond well to immunotherapy, whereas the high-risk group may show improved responses to Gemcitabine treatment. Furthermore, individuals in distinct risk categories displayed different responses to various medications within the identical therapeutic category.ConclusionWe established a breast cancer prognostic model incorporating six coagulation-associated genes and explored its clinical utility. This model offers valuable insights for clinical decision-making and drug selection in breast cancer patients, contributing to personalized and precise treatment advancements.

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Section: Discussionmentioning

confidence: 99%

Unraveling breast cancer prognosis: a novel model based on coagulation-related genes

Lei,

Li,

Yang

et al. 2024

Front. Mol. Biosci.

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“…SerpinA knockout alters the expression of genes related to inflammation and lipid metabolism in the liver [51,54]. SerpinA is also associated with the prognosis of patients with hepatic cancer [54,55]. Based on the above evidence, serpinA is thought to be involved in different hepatosteatosis conditions in db-HF and db-HC mice.…”

Section: Discussionmentioning

confidence: 99%

Calorie Restriction Using High-Fat/Low-Carbohydrate Diet Suppresses Liver Fat Accumulation and Pancreatic Beta-Cell Dedifferentiation in Obese Diabetic Mice

Lei,

Ishida,

Yoshino

et al. 2024

Nutrients

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In diabetes, pancreatic β-cells gradually lose their ability to secrete insulin with disease progression. β-cell dysfunction is a contributing factor to diabetes severity. Recently, islet cell heterogeneity, exemplified by β-cell dedifferentiation and identified in diabetic animals, has attracted attention as an underlying molecular mechanism of β-cell dysfunction. Previously, we reported β-cell dedifferentiation suppression by calorie restriction, not by reducing hyperglycemia using hypoglycemic agents (including sodium-glucose cotransporter inhibitors), in an obese diabetic mice model (db/db). Here, to explore further mechanisms of the effects of food intake on β-cell function, db/db mice were fed either a high-carbohydrate/low-fat diet (db-HC) or a low-carbohydrate/high-fat diet (db-HF) using similar calorie restriction regimens. After one month of intervention, body weight reduced, and glucose intolerance improved to a similar extent in the db-HC and db-HF groups. However, β-cell dedifferentiation did not improve in the db-HC group, and β-cell mass compensatory increase occurred in this group. More prominent fat accumulation occurred in the db-HC group livers. The expression levels of genes related to lipid metabolism, mainly regulated by peroxisome proliferator-activated receptor α and γ, differed significantly between groups. In conclusion, the fat/carbohydrate ratio in food during calorie restriction in obese mice affected both liver lipid metabolism and β-cell dedifferentiation.

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“…It belongs to the serine protease inhibitor family, also known as serpins. Alpha 1 antitrypsin is produced in the liver and plays a critical role in inhibiting neutrophil elastase, which helps fight infection and prevent lung damage [ 124 ]. alpha1-AT’s inhibition of proteases may reduce the breakdown of the extracellular matrix, thereby reducing the rate of AAA growth.…”

Section: Prognostic Protein Categorization and Functionsmentioning

confidence: 99%

Current Prognostic Biomarkers for Abdominal Aortic Aneurysm: A Comprehensive Scoping Review of the Literature

Khan,

Abu-Raisi,

Feasson

et al. 2024

Biomolecules

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Abdominal aortic aneurysm (AAA) is a progressive dilatation of the aorta that can lead to aortic rupture. The pathophysiology of the disease is not well characterized but is known to be caused by the general breakdown of the extracellular matrix within the aortic wall. In this comprehensive literature review, all current research on proteins that have been investigated for their potential prognostic capabilities in patients with AAA was included. A total of 45 proteins were found to be potential prognostic biomarkers for AAA, predicting incidence of AAA, AAA rupture, AAA growth, endoleak, and post-surgical mortality. The 45 proteins fell into the following seven general categories based on their primary function: (1) cardiovascular health, (2) hemostasis, (3) transport proteins, (4) inflammation and immunity, (5) kidney function, (6) cellular structure, (7) and hormones and growth factors. This is the most up-to-date literature review on current prognostic markers for AAA and their functions. This review outlines the wide pathophysiological processes that are implicated in AAA disease progression.

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Serpin Family A Member 1 Is Prognostic and Involved in Immunological Regulation in Human Cancers

Cited by 4 publications

References 38 publications

Unraveling breast cancer prognosis: a novel model based on coagulation-related genes

Unraveling breast cancer prognosis: a novel model based on coagulation-related genes

Calorie Restriction Using High-Fat/Low-Carbohydrate Diet Suppresses Liver Fat Accumulation and Pancreatic Beta-Cell Dedifferentiation in Obese Diabetic Mice

Current Prognostic Biomarkers for Abdominal Aortic Aneurysm: A Comprehensive Scoping Review of the Literature

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