gastric-mucosa-quantitative-polymerase-chain-reaction-analysis-for

Gastric Mucosa Quantitative Polymerase Chain Reaction Analysis for Detecting <em>Helicobacter pylori</em> and Antibiotic Resistance

Helicobacter pylori is a main pathogen that infects nearly half of the global population and is threatening public health due to its increasing antibiotic ...

Southern Medical University

The balance of blood CD8CD28/CD8CD28 T cells has been verified to be vital for patients with ulcerative colitis (UC), but their role in inflammatory bowel disease (IBD) remains unknown. This investigation aimed to evaluate the efficiency of the balance in predicting the active stage in IBD patients.

CD8CD28/CD8CD28 T cell equilibrium can predict the active stage for patients with inflammatory bowel disease.

Crohn disease (CD) with complications such as penetrating, stricturing, and perianal disease is called complicated CD. The aim of this study is to test the efficiency with which the CD8CD28/CD8CD28 cell balance can predict a subsequent active stage in patients with newly diagnosed complicated CD.Seventeen patients with complicated CD and 48 CD patients with no complications were enrolled. Blood CD8 T cells were tested from all of the 65 newly diagnosed CD patients upon enrollment. The potential risk factors were compared between the 2 groups. A 30-week follow-up was performed, and the efficiency of the CD8 cell balance at predicting active CD was analyzed using receiver-operating characteristic curves. The cumulative remission lasting rates (CRLRs) were analyzed using the Kaplan-Meier method.Compared with the control CD group, patients with complicated CD were predominantly male and younger in age; they also had lower body mass indices (BMIs), higher Crohn disease activity indices (CDAIs), higher immunosuppressant and steroid prescription rates, and significantly higher surgical rates. The CD8CD28/CD8CD28 balance was associated with BMI, CDAI, steroids, and surgery. The CD8CD28/CD8CD28 ratios were significantly lower at week 0 and on the 6th, 22nd, and 30th week during follow-up with a shorter lasting time of remission for the complicated CD patients. The CD8CD28/CD8CD28 ratio could accurately predict the active stage for the patients with complicated CD, and the highest sensitivity (89.2%) and specificity (85.3%) were found when the ratio was 1.03. Treatment with steroids and surgery, along with a significantly lower CD8CD28/CD8CD28 ratio and lower CRLRs, was closely related to a worse outcome for the patients with complicated CD.Patients requiring steroids and surgery experience more severe disease activity and thus a disequilibrated immunological balance, which could be the main reason for a decreased CD8CD28/CD8CD28 ratio. This ratio can sensitively predict the active stage for patients with complicated CD, and more care should be taken when this ratio is <1.03.

Decreased CD8+CD28+/CD8+CD28- T cell ratio can sensitively predict poor outcome for patients with complicated Crohn disease.

Oxidized low-density lipoprotein (ox-LDL), which is abnormally increased in the serum of colorectal cancer (CRC) patients consuming a high-fat diet (HFD), may be one of the risk factors for the development of CRC. Ox-LDL exerts a regulatory effect on macrophages and may influence CRC through the tumor microenvironment. The role of ox-LDL in CRC remains unclear.

Oxidized low-density lipoprotein stimulates CD206 positive macrophages upregulating CD44 and CD133 expression in colorectal cancer with high-fat diet.

The T Cell Receptor (TCR) significantly contributes to tumor immunity, whereas the intricate interplay with the Hepatocellular Carcinoma (HCC) microenvironment and clinical significance remains largely unexplored. Here, we aimed to examine the function of TCR signaling in tumor immunity and its clinical significance in HCC. Our objective was to employ TCR signaling genes and a machine learning-based integrative methodology to construct a prognostic prediction system termed the TCR score. Herein, we revealed that the TCR score serves as an independent risk factor for overall survival in HCC patients, demonstrating stable and robust performance. The accuracy of the TCR score significantly exceeds that of traditional clinical variables and published signatures. Additionally, the immune infiltration was abundant in patients with low TCR scores. Single-cell cohort analysis further demonstrates that patients with low TCR scores possess an immune-active tumor microenvironment (TME), with T/NK cells enhancing interactions with myeloid cells through signaling networks such as MIF, MK, and SPP1. In response to these changes in the TME, patients with high TCR scores exhibit poorer outcomes and shorter survival in immunotherapy cohorts. In vitro experiments demonstrated that the key TCR signaling biomarker SOS1 knockdown significantly suppresses the HCC cells' capability to proliferate, invade, and migrate while enhancing tumor cell apoptosis. The TCR score could function as a robust and potential tool to predict immune activity and improve clinical outcomes for HCC patients.

Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma.

Clear cell renal cell carcinoma (ccRCC), the most prevalent renal cancer subtype, is frequently associated with poor prognosis. RHO-GTPase signaling genes have been implicated in tumor aggressiveness and unfavorable survival, but their potential in risk stratification and therapeutic guidance for ccRCC patients remains unexplored. Univariate regression identified prognostically relevant RHO-GTPase signaling genes, followed by consensus clustering for ccRCC subtype classification. LASSO regression selected key genes to construct a six-gene risk model. The model was evaluated for prognostic stratification, immune status, immunotherapy response, and chemotherapy sensitivity. Key genes were analyzed at the genomic, single-cell, and protein levels to explore underlying mechanisms. Among 62 prognostically relevant RHO-GTPase signaling genes, six (ARHGAP11B, NUF2, PLK1, CYFIP2, IQGAP2, and VAV3) were identified to form a robust prognostic signature. This model stratified patients into high- and low-risk groups, with high-risk patients demonstrating significantly worse outcomes. The model exhibited excellent predictive accuracy (AUC > 0.7 in training and validation cohorts). High-risk patients were characterized by an immunosuppressive microenvironment and reduced sensitivity to immunotherapy. Drug sensitivity analysis revealed 107 agents correlated with the risk score, underscoring therapeutic relevance. Mechanistically, the six key genes showed distinct expression patterns, cellular distribution, and positive correlation with VHL mutations, highlighting their potential as actionable drug targets. This study established a novel six-gene RHO-GTPase signaling model for predicting prognosis, immune status, and therapeutic responses in ccRCC, which offers potential for improving patient stratification and guiding personalized treatment strategies.

Article	Year
CD8CD28/CD8CD28 T cell equilibrium can predict the active stage for patients with inflammatory bowel disease. Clinics and research in hepatology and gastroenterology\| PubMed ID: 28502591	2017
Decreased CD8+CD28+/CD8+CD28- T cell ratio can sensitively predict poor outcome for patients with complicated Crohn disease. Medicine\| PubMed ID: 28658115	2017
Oxidized low-density lipoprotein stimulates CD206 positive macrophages upregulating CD44 and CD133 expression in colorectal cancer with high-fat diet. World journal of gastroenterology\| PubMed ID: 36160648	2022
Machine learning-based integration reveals immunological heterogeneity and the clinical potential of T cell receptor (TCR) gene pattern in hepatocellular carcinoma. Apoptosis : an international journal on programmed cell death\| PubMed ID: 39904860	2025
Activation of RHO-GTPase gene pattern correlates with adverse clinical outcome and immune microenvironment in clear cell renal cell carcinoma. Clinical and experimental medicine\| PubMed ID: 39998699	2025

Zhong-Wen Zheng

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