Clinical Research Directory

Biomarkers for Cancer Treatment

Circulating biomarkers, such as miRNAs and proteomics, undergo identifiable and measurable changes during and following treatment for cancer, compared to pre-treatment baseline. Some of these changes may be associated either with known treatment parameters or predictive for cardiac or lung toxicity. The aim is to identify and validate changes following treatment for cancer, compared to pre-treatment baseline, as well as differential miRNA expression in two-group comparisons (patients receiving radical RT/chemoRT for thoracic cancers versus IO-based complex SACT).

Hippo Signaling Pathway Proteins in Gingival Crevicular Fluid of Individuals With Periodontal Disease

Periodontal disease is a chronic inflammatory condition of the tooth-supporting tissues in which the host inflammatory response drives the destruction of alveolar bone and periodontal attachment. The Hippo signaling pathway is a conserved regulatory network that controls cell proliferation, apoptosis, and bone homeostasis, but its role in human periodontal disease remains unknown. This observational, case-control study compared the levels of Hippo signaling pathway proteins (YAP, TAZ, MST1, TEAD, LATS1, MAP4K4), the anti-apoptotic protein BCL-2, and the bone metabolism marker alkaline phosphatase (ALP) in gingival crevicular fluid across 75 systemically healthy participants grouped as periodontally healthy, gingivitis, or stage 3 grade B periodontitis. The aim was to determine whether these proteins are differentially expressed across periodontal health and disease states and whether they correlate with markers of apoptosis and bone metabolism.

MERC Proteins in Saliva and GCF in Periodontal Disease (ELISA Study)

This observational cross-sectional study investigates the levels of mitochondria-endoplasmic reticulum contact site (MERC) proteins in saliva and gingival crevicular fluid (GCF) of individuals with different periodontal conditions. MERCs are specialized regions where mitochondria and the endoplasmic reticulum physically connect, and they play important roles in calcium signaling, oxidative stress regulation, and cell death (apoptosis). Disruption of these contact sites has been linked to inflammatory diseases, including periodontal disease. The study includes 48 systemically healthy, non-smoking adults divided into three groups: periodontally healthy (n=16), gingivitis (n=16), and Stage III Grade B periodontitis (n=16). Five MERC-associated proteins (VAPB, PTPIP51, IP3R, GRP75, and VDAC) are measured in GCF and saliva samples using ELISA. Additionally, caspase-3 (a marker of apoptosis), reactive oxygen species (a marker of oxidative stress), and calcium levels are measured to explore relationships between MERC proteins and key cellular processes involved in periodontal tissue destruction. The purpose of this study is to determine whether MERC protein levels differ across periodontal conditions and to evaluate their associations with clinical periodontal parameters, oxidative stress, calcium metabolism, and apoptosis.

Plasma Exosomal RNA Signature for Prostate Cancer Bone Metastasis

Brief Summary: This prospective, multicenter study aims to discover, develop, and validate a plasma exosomal RNA-based signature as a rule-out test for predicting bone metastasis in prostate cancer, using baseline treatment-naïve PSMA PET as the gold standard. The study is designed in four sequential phases: Phase 1 (Discovery, n=250): High-throughput sequencing of plasma exosomal RNAs to identify differentially expressed candidate RNAs. Phase 2 (Model Development, n=300): Digital droplet PCR (ddPCR) analysis of candidates in an independent cohort to construct and lock the final multi-RNA predictive signature using appropriate machine learning methods. Phase 3 (Internal Validation, n=300): Independent validation of the locked signature in a consecutive cohort reflecting natural disease prevalence. Phase 4 (External Validation, n=150): Final independent validation in a multi-center cohort enriched for bone metastasis. Primary Outcome: To evaluate the diagnostic performance of the signature as a rule-out test for PSMA PET-defined bone metastasis. The primary performance metrics are: Sensitivity, with a prespecified target of ≥95% (to ensure minimal false negatives). Specificity at the threshold that achieves the ≥95% sensitivity. A specificity of ≥30% will be considered supportive of clinical utility. A specificity of ≥30% (or a lower bound of the 95% confidence interval exceeding 20%) will be considered supportive of clinical utility. Need: Current biomarkers lack sensitivity and specificity for early detection of bone metastasis. More importantly, existing tools lack adequate negative predictive value to safely rule out bone metastasis in low-risk patients, leading to over-imaging or delayed detection. There is an urgent need for a non-invasive rule-out test to safely defer PSMA PET/CT in very-low-risk patients. Plasma exosomal RNAs offer a promising liquid biopsy approach, but prospective multicenter studies with rigorous validation are lacking. Secondary Outcomes: 1. Secondary metrics include negative predictive value (NPV), positive predictive value (PPV), area under the ROC curve (AUC), calibration, and decision curve analysis. 2. Correlation between exosomal RNA levels and number of bone metastatic lesions (PSMA PET). 3. Association with PSA, PSMA PET SUVmax, and MRI findings. 4. Tissue-plasma correlation to confirm tumor origin (exploratory). 5. Mechanistic exploration of key candidates via in vitro/in vivo assays (exploratory). 6. Subgroup analyses by hormone sensitivity, metastatic pattern, Gleason grade (exploratory). Inclusion Criteria: 1. Histologically confirmed prostate cancer scheduled for baseline PSMA PET. 2. PSMA PET performed prior to any prostate cancer-related treatment. 3. Blood samples collected prior to any treatment AND prior to prostate biopsy. 4. Willing to undergo prostate biopsy if clinically indicated (after blood collection). 5. Written informed consent. 6. Age ≥18 years. Exclusion Criteria: 1. Any prior prostate cancer treatment before baseline PSMA PET. 2. Blood samples collected after prostate biopsy. 3. Other active malignancy within past two years (excluding non-melanoma skin cancer). 4. Inadequate blood sample quality or quantity. 5. Severe comorbidities interfering with study conduct.