Cancer risk in patients with osteoporosis: a population-based cohort study

Potential value and advances in research on bone mineral density (BMD) measurement in the auxiliary clinical assessment of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide and its prognosis is highly heterogeneous, being related not only to underlying chronic liver disease but also to the severity of cancer cachexia. Nutritional factors play a crucial role in influencing the prognosis of HCC. Despite musculoskeletal imbalance being consistently reported as a predictor of perioperative mortality in patients with HCC, this condition is often overlooked in clinical management. Bone mineral density (BMD), which serves as a marker of nutritional status, can be assessed through CT by measuring the pixel density of the vertebral bone. Recent clinical studies have indicated that BMD serves not only as a significant risk factor for development of HCC in cirrhotic patients but also potentially functions as an independent prognostic indicator for post-treatment outcomes in patients with HCC. Preoperative abdominal CT scans provide a convenient and cost-effective method to measure BMD, offering significant assistance in prognostic evaluation of patients with HCC. A thorough grasp of the liver-bone connection, along with the conduct of higher-quality studies and the establishment of standardized methods and cutoff values for BMD measurement, could enhance approaches to manage HCC.

Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis

BACKGROUND

Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge.

METHODS

PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by "limma" packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes' function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers.

RESULTS

A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC).

CONCLUSIONS

ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.

Association Between Papillary Thyroid Carcinoma and Vertebral Fracture

Suppression of TSH levels associated with levothyroxine treatment is a known risk factor for fracture. However, it is unclear whether patients with papillary thyroid carcinoma (PTC) have a higher risk of vertebral fracture (VF) before TSH suppression. The aim of the study was to examine whether the risk of VF is higher in PTC than in healthy subjects. A hospital-based, matched case-control study was conducted comparing PTC and healthy individuals. We enrolled 43 postoperative patients with PTC scheduled for radioiodine therapy and 43 age- and sex-matched healthy controls. Serum and urinary biological parameters, bone mineral density (BMD), and presence of VFs were evaluated in both groups. We compared these indices using χ2 and Mann-Whitney U-test and analyzed the association between PTC and VF by logistic regression analysis. The PTC group had higher BMI, HbA1c and phosphorus, and lower intact PTH than the control group. Lumbar and femoral neck BMD did not differ between the two groups. Prevalence of VFs was significantly higher in the PTC group (44.1%) than in the control group (16.3%). Multivariate logistic regression analyses adjusted for age, sex, and BMI identified PTC as being associated with the presence of VFs (odds ratio, 5.63; 95% confidence interval: 1.82 to 17.5). This relationship remained significant after additional adjustment for HbA1c and BMD. There is an association between PTC and a risk of VF independent of sex, BMI, glucose metabolism, and BMD, suggesting the importance of fracture risk assessment before TSH suppression.

Papillary thyroid carcinoma is a risk factor for severe osteoporosis

INTRODUCTION

Thyroid-stimulating hormone (TSH)-suppressive therapy is recommended after surgical treatment in high-risk papillary thyroid carcinoma (PTC) patients. TSH-suppressive therapy is a known risk factor for osteoporosis and fractures. However, whether patients with PTC themselves are at a higher risk of osteoporosis than healthy individuals remains unclear. This study aimed to clarify whether PTC is a risk factor for osteoporosis.

MATERIALS AND METHODS

Serum and urinary biochemical parameters, bone mineral density (BMD), and presence of vertebral fractures (VFs) and non-VFs were evaluated in 35 PTC patients and 35 age- and sex-matched healthy individuals. We compared the parameters between PTC and control subjects and performed multiple logistic regression analyses after adjustments for variables.

RESULTS

Patients with PTC had higher body mass index (BMI) and hemoglobin (Hb)A1c, as well as lower eGFR and intact PTH than controls (p < 0.05, each). There were no significant differences in the prevalence of osteoporosis and VFs and non-VFs between patients with PTC and controls. However, the prevalence of severe osteoporosis diagnosed according to WHO criteria was significantly higher in PTC subjects (34.3%) than in controls (11.4%, p < 0.05). Multivariate logistic regression analyses adjusted for age, BMI, eGFR and HbA1c identified PTC as being associated with the presence of severe osteoporosis (odds ratio, 4.20; 95% confidence interval, 1.05-16.8; p < 0.05).

CONCLUSIONS

We identified PTC as a risk factor for severe osteoporosis, independent of BMI, renal function and glucose profile.