Tumor-associated macrophages (TAMs) can promote cancer initiation and progression by releasing cytokines. Previously, we have found the density of TAMs correlated with lymph node metastasis in papillary thyroid carcinoma (PTC). However, the mechanisms of how TAMs promote PTC progression remain unclear. In this study, we first showed that the TAMs density in the tumor core was associated with progressive PTC features and TAMs conditioned medium enhanced PTC cells invasion. Cytokine profiling identified a mixed M1/M2 phenotype and CXCL8 was the most consistently abundant cytokine in PTC-derived TAMs. CXCL8 receptors, CXCR1 and CXCR2, were positively stained in PTC cell lines and tissues, though no association with lymph node metastasis or extrathyroid extension. PTC cell invasion was abrogated by anti-CXCL8-neutralizing antibody, whereas addition of exogenous recombinant human CXCL8 enhanced the invasiveness. More importantly, CXCL8 promoted PTC metastasis in vivo. No difference was found for TAMs-derived CXCL8 expression in patients with and without lymph node metastasis or extrathyroid extension. These findings indicated that TAMs may facilitate PTC cell metastasis through CXCL8 and its paracrine interaction with CXCR1/2.

Background: Tumor-associated macrophages (TAMs) have recently been recognized as being important players in the tumoriogenesis of many cancers, including advanced thyroid cancer. However, a role in papillary thyroid carcinoma (PTC), the most prevalent thyroid cancer, has not been established. We hypothesized that TAMs also facilitate tumor progression in PTC. Methods: We investigated TAMs density in both benign thyroid lesions and PTC tumors by CD68 immunostaining. CD68-positive cell density was further associated with the clinicopathological characteristics of PTC patients. Finally, TAMs were isolated from PTC tumors and phenotyped by cytokine and receptor profiling. Results: The overall density of TAMs was found to be significantly higher in PTC tumors, compared with thyroid goiter and follicular adenoma. The density of TAMs was positively associated with lymph node metastasis in TNM (tumor-node-metastasis) stages III/VI compared with stages I/II. No association was observed in other common tumor features, including the BRAF mutation. The isolated TAMs presented with high levels of M2-associated cytokine and receptors, making M2 the predominant TAM phenotype. Conclusions: TAMs may play a functional role in the progression of PTC.

Activating rearranged during transfection (RET) mutations function as the initiating causative mutation for multiple endocrine neoplasia type 2A (MEN2A). However, no conclusive findings regarding the non-RET genetic events have been reported. This is the first study, to our knowledge, examining genomic alterations in matched MEN2A-associated tumors. We performed exome sequencing and SNP array analysis of matched MEN2A tumors and germline DNA. Somatic alterations were validated in an independent set of patients using Sanger sequencing. Genes of functional interest were further evaluated. The germline RET mutation was found in all MEN2A-component tumors. Thirty-two somatic mutations were identified in the nine MEN2A-associated tumors, of which 28 (87.5%) were point mutations and 4 (12.5%) were small insertions, duplications, or deletions. We sequenced all the mutations as well as coding sequence regions of the 12 genes in an independent sample set including 35 medullary thyroid cancers (20 MEN2A) and 34 PCCs (22 MEN2A), but found no recurrent mutations. Recurrent alterations were found in 13 genes with either mutations or alterations in copy number, including an EIF4G1 mutation (p. E1147V). Mutation of EIF4G1 led to increased cell proliferation and RET/MAPK phosphorylation, while knockdown of EIF4G1 led to reduced cell proliferation and RET/MAPK phosphorylation in TT, MZ-CRC1, and PC-12 cells. We found fewer somatic mutations in endocrine tumors compared with non-endocrine tumors. RET was the primary driver in MEN2A-associated tumors. However, low-frequency alterations such as EIF4G1 might participate in MEN2A-associated tumorigenesis, possibly by regulating the activity of the RET pathway.

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Objective: To explore the value of quantitative parameters of artificial intelligence and computed tomography (CT) signs in identifying pathological subtypes of lung adenocarcinoma appearing as ground-glass nodules (GGNs). Methods: CT images of 224 GGNs from 210 individuals were collected retrospectively and pathologically classified into atypical adenomatous hyperplasia (AAH)/adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) groups. Artificial intelligence was used to identify GGNs and to obtain quantitative parameters, and CT signs were recognized manually. The mixed predictive model based on logistic multivariate regression was evaluated. Results: Of the 224 GGNs, 55, 93, and 76 were AAH/AIS, MIA, IAC, respectively. In terms of artificial intelligence parameters, from AAH/AIS to MIA, and IAC, there was a gradual increase in two-dimensional mean diameter, three-dimensional mean diameter, mean CT value, maximum CT value, and volume of GGNs (all P < 0.0001). Except for the CT signs of the location, and the tumor-lung interface, there were significant differences among the three groups in the density type, shape, vacuole signs, air bronchogram, lobulation, spiculation, pleural indentation, and vascular convergence signs (all P < 0.05). The areas under the curve (AUC) of predictive model 1 for identifying the AAH/AIS and MIA and model 2 for identifying MIA and IAC were 0.779 and 0.918, respectively, which were greater than the quantitative parameters independently (all P < 0.05). Conclusion: Artificial intelligence parameters are valuable for identifying subtypes of early lung adenocarcinoma, and when combined with CT signs to improve its diagnostic efficacy.