Secretome Profiling and Computational Biology of Human Leiomyoma Samples Unravel Molecular Signatures with Potential for Diagnostic and Therapeutic Interventions

Genome-wide association analysis to search for new loci associated with stroke risk in Northwestern Chinese population

BACKGROUND AND PURPOSE

Genetic factors play an important role in the pathogenesis of stroke(S). This study aimed to screen the loci associated with S risk in northwestern Chinese population by genome-wide association analysis (GWAS).

METHODS

A total of 1394 subjects, including 682 S patients and 692 controls, were enrolled in this study. SPSS 25.0 software was used for statistical analysis, and the independent sample t-test as well as Chi-square test were used to analyze the differences in age and gender between the case and control groups. The Precision Medicine Diversity Array (PMDA) genotyping chip was used in this study. The genotyping platform was the Gene Titan multi-channel instrument, and the Axiom Analysis Suite 6.0 software was used for the data analyzing. Besides, the LASSO analysis, SNP-SNP and GO/KEGG analysis were conducted to analyze the association between significant loci and S risk.

RESULTS

A total of 30 SNPs were found to be associated with the S risk based on additive model (p < 5 × 10-8). After the LASSO screening, 22 SNPs showed the diagnostic value in S. The SNPs interaction analysis further screened the SNP-SNP interaction groups associated with the S risk(p < 0.05). Finally, the GO/KEGG analysis discovered the suggestive significance loci could be involved in the S development mainly by immune-related functions and pathways.

CONCLUSION

This study discovered 30 S related SNPs and analyzed the potential pathways associated with genes located on the 30 SNPs, which were beneficial for enriching the genetic mechanism analysis of S in northwestern Chinese population.

Lumican, a Multifunctional Cell Instructive Biomarker Proteoglycan Has Novel Roles as a Marker of the Hypercoagulative State of Long Covid Disease

This study has reviewed the many roles of lumican as a biomarker of tissue pathology in health and disease. Lumican is a structure regulatory proteoglycan of collagen-rich tissues, with cell instructive properties through interactions with a number of cell surface receptors in tissue repair, thereby regulating cell proliferation, differentiation, inflammation and the innate and humoral immune systems to combat infection. The exponential increase in publications in the last decade dealing with lumican testify to its role as a pleiotropic biomarker regulatory protein. Recent findings show lumican has novel roles as a biomarker of the hypercoagulative state that occurs in SARS CoV-2 infections; thus, it may also prove useful in the delineation of the complex tissue changes that characterize COVID-19 disease. Lumican may be useful as a prognostic and diagnostic biomarker of long COVID disease and its sequelae.

Components of the Lectin Pathway of Complement in Solid Tumour Cancers

The complement system is an important branch of the humoral innate immune response that can be activated via three distinct pathways (classical, alternative, lectin), contributing to keeping/restoring homeostasis. It can also interact with cellular innate immunity and with components of acquired immunity. Cross-talk between the complement system and other enzyme-dependent cascades makes it a more influential defence system, but on the other hand, over- or chronic activation can be harmful. This short review is focused on the dual role of the lectin pathway of complement activation in human solid tumour cancers, including those of the female reproductive system, lung, and alimentary tract, with emphasis on the aforementioned cross-talk.

Circulating Proteins Associated with Response and Resistance to Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Simple Summary

The goal of this study was to find circulating proteins that can be easily sampled and incorporated into a clinical setting to improve predictive treatment response in HER2-positive breast cancer patients receiving neoadjuvant chemotherapy. We looked for potential biomarkers in serum, which we identified using two proteomics techniques: qualitative LC-MS/MS and a quantitative assay that assessed protein expression between responders and non-responders HER2-positive breast cancer patients to neoadjuvant chemotherapy.

Abstract

Despite the increasing use of neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer (BC) patients, the clinical problem of predicting individual treatment response remains unanswered. Furthermore, the use of ineffective chemotherapeutic regimens should be avoided. Serum biomarker levels are being studied more and more for their ability to predict therapy response and aid in the development of personalized treatment regimens. This study aims to identify effective protein networks and biomarkers to predict response to NAC in HER2-positive BC patients through an exhaustive large-scale LC-MS/MS-based qualitative and quantitative proteomic profiling of serum samples from responders and non-responders. Serum samples from HER2-positive BC patients were collected before NAC and were processed by three methods (with and without nanoparticles). The qualitative analysis revealed differences in the proteomic profiles between responders and non-responders, mainly in proteins implicated in the complement and coagulation cascades and apolipoproteins. Qualitative analysis confirmed that three proteins (AFM, SERPINA1, APOD) were correlated with NAC resistance. In this study, we show that serum biomarker profiles can predict treatment response and outcome in the neoadjuvant setting. If these findings are further developed, they will be of significant clinical utility in the design of treatment regimens for individual BC patients.