Increased serum concentration of soluble alpha-chain receptor for interleukin-2 (sIL-2R) has been noted in patients with a variety of inflammatory conditions and lymphoid malignancies including T cell leukemia and lymphoma. Elevated sIL-2R serum levels seen in lymphoid malignancies appear to correlate with the clinical stage of disease. However, because sIL-2R is produced by normal activated lymphocytes, it has been uncertain whether serum sIL-2R in such conditions is derived from tumor cells or normal immune cells responding to the tumor. To address this question, we used a model of human (CD30+) anaplastic, large T cell lymphoma transplanted into immunodeficient SCID mice. Reverse transcription polymerase chain reaction of tumor RNA showed that the tumor, designated mJB6, contains mRNA for alpha-chain of human IL-2R. Furthermore, 15 to 25% of tumor cells stained with anti-human IL-2R alpha-chain mAb. Solid phase ELISA analysis of serum samples from mice bearing mJB6 lymphoma showed high concentrations of human sIL-2R. None of the control mice without lymphoma or with human nonlymphoid tumors (prostatic carcinoma, ovarian carcinoma, and glioblastoma multiforme) showed detectable human sIL-2R. The sIL-2R serum titers of mJB6-bearing mice correlated strongly with tumor volume (P < 0.0001). Tumors as small as 0.4 to 0.8 mm3 could be detected by this method. The sensitivity of sIL-2R ELISA exceeded at least 150 times the sensitivity of conventional radioisotopic tumor detection. Total resection of mJB6 tumors resulted in complete clearance of sIL-2R from the murine serum within 48 hours with a half-life of 6 hours. Accordingly, partial resection led to a significant decrease in sIL-2R followed by gradual increase with tumor regrowth. sIL-2R was also detected in the urine of mJB6-transplanted mice. As in serum, urine concentrations of sIL-2R were proportional to tumor mass (P < 0.02). Based on these findings we postulate that malignant cells are a major source of serum sIL-2R in patients with lymphoid tumors. In addition, our data further support monitoring sIL-2R concentration in body fluids as a sensitive method to detect change in tumor volume in such patients.
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Metabolites
December 2024
Division of Pulmonary, Critical Care, and Sleep, College of Medicine-Jacksonville, University of Florida, Jacksonville, FL 32209, USA.
Sarcoidosis is a granulomatous disease affecting multiple organ systems and poses a diagnostic challenge due to its diverse clinical manifestations and absence of specific diagnostic tests. Currently, blood biomarkers such as ACE, sIL-2R, CD163, CCL18, serum amyloid A, and CRP are employed to aid in the diagnosis and monitoring of sarcoidosis. Metabolomics holds promise for identifying highly sensitive and specific biomarkers.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu 610072, China; Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq. Electronic address:
Background: A recent study conducted by the laboratory of the first author revealed that major depression is composed of two distinct subtypes: major dysmood disorder (MDMD) and simple dysmood disorder (SDMD). The latter is a less severe phenotype with fewer aberrant biological pathways. MDMD, but not SDMD, patients were identified to have highly sensitized cytokine/growth factor networks using stimulated whole blood cultures.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
November 2024
Clinical Medical Center of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Background: Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cell lung cancer (NSCLC) patients.
Methods: Laboratory indices of the NSCLC patients at their initial visit were collected for quality control and exploratory analysis.
J Orthop
April 2025
Department of Orthopaedic Surgery, Teikyo University School of Medicine, 2-11-1 Kaga, Itabashi-Ku, Tokyo 173-8606, Japan.
Zhongguo Dang Dai Er Ke Za Zhi
October 2024
Institute of Pediatrics, Seventh Medical Centre, General Hospital of the Chinese People's Liberation Army, Beijing 100010, China.
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