Dataset Information

A meta-analysis of the influence of body mass index on the clinicopathologic progression of papillary thyroid carcinoma.

ABSTRACT:

Background

Papillary thyroid carcinoma (PTC) incidence has been increasing worldwide. Obesity, that is, having a high body mass index, is associated with the incidence of several cancers including colon, breast, esophageal, and kidney cancer. However, the association between obesity and the clinical features of PTC is still unknown. This study aimed to determine the impact of obesity on the clinical features of PTC.

Method

A database search was conducted for articles published up to 2020 on obesity and clinical features of PTC. Data were extracted from articles that met the meta-analysis inclusion criteria.

Results

A total of 11 retrospective cohorts and 11,729 patients were included. Obesity was associated with the following variables in PTC patients: older age (difference in means = 1.95, 95% confidence interval [CI] 0.16-3.74, P = .03), male sex (odds ratio [OR] = 3.13, 95%CI 2.24-4.38, P < .00001), tumor size ≥1 cm (OR = 1.34, 95%CI 1.11-1.61, P < .002), multifocality (OR = 1.54, 95%CI 1.27-1.88, P < .0001), extrathyroidal extension (OR = 1.78, 95%CI 1.22-2.59, P = .003) and advanced tumor, node, metastasis stage (OR = 1.68, 95%CI 1.44-1.96, P < .00001). Preoperative serum thyroid-stimulating hormone level (difference in means = 0.09, 95%CI 0.35-0.52, P = .70), Vascular invasion (OR = 0.84, 95%CI 0.56-1.26, P = .41), lymph node metastasis (OR = 1.07, 95%CI 0.87-1.32, P = .50), distant metastasis (OR = 1.14, 95%CI 0.64-2.04, P = .66), and recurrence (OR = 1.45, 95%CI 0.97-2.15, P = .07) were not associated with obesity.

Conclusion

Obesity was associated with several poor clinicopathologic prognostic features: older age, male gender, tumor size ≥1 cm, extrathyroidal extension, multifocality, and advanced tumor/node/metastasis stage. However, thyroid-stimulating hormone level, vascular invasion, lymph node metastasis, distant metastasis, and recurrence were not associated with obesity in PTC.

SUBMITTER: Cui N

PROVIDER: S-EPMC8360437 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe association between adiposity and papillary thyroid carcinoma (PTC) has been reported in several studies, but its association with aggressive clinicopathologic features is not well-recognized. Our aim is to systematically review the literature to identify whether adiposity, expressed through Body Mass Index (BMI), is related to aggressive clinicopathologic features such as tumor-node-metastasis (TNM) stage, extrathyroidal extension (ETE), lymph node (LN) metastasis and multifocality in patients with PTC.MethodsA systematic search for articles was performed using the PubMed, EBSCO, and Cochrane Library for all articles published in English until December 2020. Specific keywords such as "papillary thyroid carcinoma", "Body Mass Index", "clinicopathologic features" were used in the search strategy. Two independent reviewers screened all retrieved articles based on predefined inclusion and exclusion criteria. Meta-analysis was performed in the studies that reported crude and adjusted odds ratios (OR). The methodological quality was assessed using the Newcastle-Ottawa Scale.ResultsA total of 11 retrospective cohort studies involving 26,196 participants included. Our findings showed that elevated BMI was significantly associated with ETE in both overweight (OR 1.26, 95% CI: 1.09-1.44) and obesity group (OR 1.45, 95% CI:1.26-1.64). Elevated BMI was also significantly associated with multifocality in overweight patients (OR 1.17, 95% CI:1.10-1.24) and obese patients (OR 1.45, 95% CI:1.29-1.62). Also, obesity was significantly associated with increased tumor size (OR 1.77, 95% CI:1.52-2.03) and with LN metastasis (OR 1.28, 95% CI: 1.12-1.44), whereas being overweight was significantly associated with advanced TNM stage (OR 1.55, 95% CI:1.27-1.83).ConclusionOur results provide strong evidence for the association between higher BMI and ETE, multifocality, and tumor size. Further studies with a larger number of participants are required to elucidate further the association of increased BMI with advanced TNM stage and LN metastasis.

Project description:BackgroundDespite extensive research, the papillary thyroid carcinoma (PTC) ecosystem is poorly characterized and, in particular, locoregional progression. Available evidence supports that single-cell transcriptome sequencing (Sc-RNA seq) can dissect tumor ecosystems.MethodsTissue samples from one PTC patient, including matched primary tumor (Ca), lymph node (LN) metastasis, and paracancerous tissue (PCa), were subjected to Sc-RNA seq with 10×Genomics. Dual-label immunofluorescence and immunohistochemistry were used to confirm the existence of cell subtypes in a separate cohort.Results11,805 cell transcriptomes were profiled, cell landscapes of PTC were composed of malignant follicular epithelial cells (MFECs), CD8+ and CD4+ T cells, B cells, vascular endothelial cells, fibroblasts and cancer-associated fibroblasts (CAFs). Between Ca and LN ecosystems, the proportions of MFEC and interstitial cells were similar, less than 1/25(229/6,694, 361/3,895), while the proportion of normal follicular epithelial cells (NFECs) and interstitial cells was > 2 in PCa (455/171). NFECs in PCa formed a separate cluster, while MFECs in Ca and LN exhibited a profound transcriptional overlap, and the interstitial cells among these samples had an overall concordance in their identity and representation, albeit with some distinctions in terms of the cell percentage per subset. A fraction of the B cell subpopulation in Ca expressed inhibitory receptors, while their respective ligand genes were clearly transcribed in T cell and malignant epithelial cell clusters, while some CD8+ T cells in both Ca and LN produced high levels of inhibitory receptors whose respective ligands were overexpressed in some CD4+ T cells. Three CAF subtypes in Ca and LN were identified, which may be due to mutual transitions.ConclusionsOur data provide new insights into the PTC ecosystem and highlight the differences in ecosystems in PTC progression, which updates our understanding of PTC biology and will improve individualized patient treatment.