Osteosarcoma is one of the most common malignant tumors in children and adolescents. It occurs in the metaphysis of long bones and is a type of aggressive malignant tumor. Although there are treatment methods such as surgery and chemotherapy, the mortality and disability of osteosarcoma patients are still high. With the emergence of more and more chemotherapy resistance, it is necessary to find new therapies to improve the chemotherapy sensitivity of osteosarcoma.

Drug-resistant MG-63 and U2OS cell strain was established in vitro by continuous exposure of human osteosarcoma cells to doxorubicin at gradually increasing concentrations，then determined for resistance index to doxorubicin by MTT method，for transcriptions of Livin mRNA by real-time polymerase chain reaction（RT⁃PCR），and for expressions of Livin proteins by Western blot．The technology of gene recombination was used to construct the eukaryotic expression vector pSilencer3.1-H1 neo-Livin. Then the pSilencer3.1-H1 neo-Livin was transfected into drug-resistant MG-63 cell by using Lipofectmine 2000. Expressions of Livin mRNA and protein in the transfected cells were respectively measured by RT-PCR and Western blot. The distribution of cell cycle phase and apoptosis were determined by flow cytometry. The analysis of chemotherapeutic sensitivity of drug-resistant MG-63 cell to doxorubicin was performed by MTT.

The recombinant eukaryotic expression vector pSilencer3.1-H1 neo-Livin was successfully constructed. The result of inverted microscope revealed that the drug-resistant MG-63 cell were irregularity and morphological diversity. Compared with those in osteosarcoma cells，the transcription levels of Livin mRNA and protein in drug-resistant osteosarcoma cell increased（P＜0.05）．The flow cytometry analysis showed there was higher percentage of apoptosis in transfected drug-resistant MG-63 cell. Compared with control groups，the expression of Livin mRNA and protein were both significantly decreased in the transfected drug-resistant osteosarcomacell（P＜0.05）. We also observed that suppression of Livin expression in osteosarcoma cells increased their chemosensitivity to doxorubicin.

This study showed that Livin shRNA inhibited the proliferation level and increased the sensitivity of drug-resistant osteosarcoma cell to doxorubicin, suggested that Livin is involved in drug resistance of human osteosarcoma and may serve as a promising therapeutic target for osteosarcoma.

The incidence of papillary thyroid carcinoma (PTC) has been rising annually, with papillary thyroid microcarcinoma (PTMC) accounting for more than half of the cases. While most PTMCs exhibit indolent growth and a favorable prognosis, some undergo clinical progression with poor outcomes. Thus, identifying biomarkers associated with PTC, particularly those related to PTMC progression, is crucial for precise risk stratification and treatment planning. This study utilized single-cell RNA sequencing on 19 surgical tissue specimens from 15 patients, including four para-tumor tissues, four non-progressive PTMCs, five progressive PTMCs, and six progressive PTCs. Key findings are corroborated through in vivo and in vitro experiments. Single-cell RNA sequencing and spatial transcriptomics characterized the cellular ecosystem within PTC, revealing multi-directional evolutionary patterns as PTMC progresses. Analysis of progression-specific alterations in intercellular communication networks highlighted the PROS1-MERTK signaling interaction as pivotal in PTMC progression. In vitro and in vivo models confirm that the PROS1-MERTK axis accelerates PTMC progression via paracrine and autocrine signaling. Furthermore, NFYB and FOXP2 are identified as activators of PROS1 transcription in fibroblasts, promoting PTMC progression through the MERTK/WNT/TGF-β signaling. These findings underscore the PROS1/MERTK axis as a critical component of the cellular microenvironment and a key regulatory mechanism in PTMC progression.

Sodium p-perfluorous nonenoxybenzenesulfonate (OBS) as a novel surrogate for perfluorooctanesulfonate (PFOS) has been extensively utilized in industrial manufacturing and daily life. However, studies on OBS-induced environmental health risks of obstructive biosynthesis (OBS) are currently limited, particularly the risk for thyroid diseases. Following the construction of in vivo (mouse) and in vitro (normal human primary thyrocytes) models of subchronic low-dose OBS exposure, we explored the thyroid-disrupting effects of OBS through multiomics approaches and experimental validations. Our results showed that subchronic exposure to low doses of OBS led to primary hypothyroidism in mice, presenting with reduced number and functional abnormalities of thyrocytes. Further in vitro assays confirmed that low-dose OBS-induced disulfidptosis, a newly discovered form of programmed cell death, in human primary thyrocytes. Meanwhile, exposure to low-dose OBS remarkably suppressed thyroid hormone synthesis pathways in mouse and human thyrocytes. The charted multiomic landscape of OBS-induced primary hypothyroidism in mammals revealed the thyroid toxicity and endocrine-disrupting properties of OBS, suggesting that it is not a safe alternative to PFOS.

In recent years, a growing body of evidence has suggested a correlation between Hashimoto's thyroiditis (HT) and the onset and progression of papillary thyroid carcinoma (PTC). However, the mechanism underlying the relationship between HT and PTC remains incompletely understood. This review discusses the literature on the correlation between PTC and HT and summarizes the research concerning the immunological interplay between these two conditions. It also delves into tumor-associated cells (such as CD8+ T cells), tumor-associated macrophages (TAMs), regulatory T cells (Tregs), and cancer-associated fibroblasts (CAFs), alongside other tumor-associated factors, including interleukins (ILs), interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), and hypoxia-inducible factor-1 (HIF-1), highlighting their roles in the interaction between PTC and HT. We also explore the strategic direction of immunotherapy in thyroid malignancies, particularly PTC with HT, and propose novel targeted immunotherapies for advanced thyroid cancer.

Inflammation within tumor microenvironments has been correlated to numerous malignancies. This study aims to explore its significance in thyroid cancer (TC).

Retrospective analysis of 157 thyroid carcinomas and 40 benign cases involved initial univariate analysis. The value of neutrophils/value of lymphocytes (NLR), value of platelets/value of lymphocytes (PLR), value of lymphocytes/value of monocytes (LMR), and value of platelets × value of neutrophils/value of lymphocytes (SII) indexes were related to TC characteristics and number and location of involved lymph nodes using χ2 or Fischer's exact tests for categorical variables and Student's t-tests for continuous ones. A 1:1 propensity score matching balanced malignant and benign TC groups based on age, sex, and tumor size was used. Post-matching, a multivariate logistic model integrated sex, age, Central lymph node metastases (CLNM), and SII index. Statistically significant immune index values underwent ROC curve analysis for determining cut-offs. Among the 157 malignant TC, median test and density plots were performed.

The SII index emerged as a predictor of malignancy in both univariate and multivariate analyses (p-value = 0.0202). The ROC curve indicated a cut-off SII value of 465.71, (specificity = 58% [95% CI: 0.43-0.73]; sensitivity = 80% [95% CI: 0.68-0.93]). Median SII index values for tumor sizes of 1 and >1 were 522.8 and 654.8, respectively (p-value = 0.016). When central lymph nodes metastases(CLNMs) was considered (CLNM = 0 vs. CLNM > 0), median SII values were 530.7 and 1121.7, respectively (p-value = 0.011).

The SII index appears to be a valuable tool in the presence of TC, showing correlations with malignancy, tumor size, and CLNMs.

Cervical lymph node metastasis is a major factor influencing recurrence after surgery for papillary thyroid cancer. Molecular markers that can predict the presence of lymph node metastasis and assess the aggressiveness of papillary thyroid microcarcinoma (PTMC) remain poorly understood. The research question addressed whether specific genes, such as thrombospondin-4 (THBS4), could serve as predictive biomarkers for guiding surgical strategies, particularly in cases where current imaging modalities fail to detect LNM in the central region, and the decision for prophylactic central neck dissection remains controversial.

Transcriptome sequencing was employed to screen for differentially expressed genes and perform enrichment analysis. The study defined two groups of PTMC patients: LNM(n=50) and NLNM(n=50). 10 samples from each group were used for transcriptome sequencing. The expression of THBS4 was evaluated in both groups. Additionally, the correlation between THBS4 expression and cancer-associated fibroblasts (CAFs), specifically the PDGFRA+ inflammatory CAFs, was investigated to understand the stromal regulatory protein's role in PTMC aggressiveness.

The analysis of sequencing data revealed that THBS4 expression was significantly higher in LNM PTMC compared to the NLNM group (Fold Change > 1.6 and P < 0.05). LNM PTMCs were also associated with a higher presence of PDGFRA+ inflammatory CAFs (P < 0.05), while no significant difference in the quantity of SMA+ myofibroblastic CAFs was observed between the two groups(P>0.05). Immunohistochemical analysis demonstrated increased THBS4(P < 0.01) and PDGFRA(P < 0.001) expression in LNM groups, while SMA staining showed no significant intergroup differences(P>0.05).

This study's findings indicate that THBS4 could be a potential biomarker for predicting the risk of lymph node metastasis in papillary thyroid microcarcinoma, thus potentially guiding more personalized surgical interventions. Further validation in larger patient cohorts and the interactions between THBS4 and CAFs are necessary.

Tumor microenvironment (TME) remodeling plays a pivotal role in thyroid cancer progression, yet its spatial dynamics remain unclear. In this study, we integrate spatial transcriptomics and single-cell RNA sequencing to map the TME architecture across para-tumor thyroid (PT) tissue, papillary thyroid cancer (PTC), locally advanced PTC (LPTC), and anaplastic thyroid carcinoma (ATC). Our integrative analysis reveals extensive molecular and cellular heterogeneity during thyroid cancer progression, enabling the identification of three distinct thyrocyte meta-clusters, including TG+IYG+ subpopulation in PT, HLA-DRB1+HLA-DRA+ subpopulation in early cancerous stages, and APOE+APOC1+ subpopulation in late-stage progression. We reveal stage-specific tumor leading edge remodeling and establish high-confidence cell-cell interactions, such as COL8A1-ITHB1 in PTC, LAMB2-ITGB4 in LPTC, and SERPINE1-PLAUR in ATC. Notably, both SERPINE1 expression level and SERPINE1+ fibroblast abundance correlate with malignant progression and prognosis. These findings provide a spatially resolved framework of TME remodeling, offering insights for thyroid cancer diagnosis and treatment.

Background: The increasing incidence and poor outcomes of recurrent thyroid cancer highlight the need for innovative therapies. Ferroptosis, a regulated cell death process linked to the tumour microenvironment (TME), offers a promising antitumour strategy. This study explored immune-related ferroptosis genes (IRFGs) in thyroid cancer to uncover novel therapeutic targets. Methods: CIBERSORTx and WGCNA were applied to data from TCGA-THCA to identify hub genes. A prognostic model composed of IRFGs was constructed using LASSO Cox regression. Pearson correlation was employed to analyse the relationships between IRFGs and immune features. Single-cell RNA sequencing (scRNA-seq) revealed gene expression in cell subsets, and qRT-PCR was used for validation. Results: Twelve IRFGs were identified through WGCNA, leading to the classification of thyroid cancer samples into three distinct subtypes. There were significant differences in patient outcomes among these subtypes. A prognostic risk score model was developed based on six key IRFGs (ACSL5, HSD17B11, CCL5, NCF2, PSME1, and ACTB), which were found to be closely associated with immune cell infiltration and immune responses within the TME. The prognostic risk score was identified as a risk factor for thyroid cancer outcomes (HR = 14.737, 95% CI = 1.95-111.65; p = 0.009). ScRNA-seq revealed the predominant expression of these genes in myeloid cells, with differential expression validated using qRT-PCR in thyroid tumour and normal tissues. Conclusions: This study integrates bulk and single-cell RNA sequencing data to identify IRFGs and construct a robust prognostic model, offering new therapeutic targets and improving prognostic evaluation for thyroid cancer patients.

We aimed to utilize network pharmacological analysis and molecular docking to elucidate the potential mechanisms of Banxia Decoction (BD) action in the treatment of Hashimoto's thyroiditis (HT).

Active compounds and HT-related targets were predicted using databases and the intersection of the results was taken. STRING and DAVID 6.8 tools were used to obtain the protein-protein interaction (PPI) network and perform GO and KEGG evaluations, respectively. Discovery Studio 2017 R2 was utilized to perform molecular docking and RT-qPCR was conducted to confirm hub gene expressions in clinical samples.

A total of 136 active compounds in BD were screened, and 74 potential targets related to HT were identified in BD. Further, 17 key targets in the PPI network were identified and HIF1A, EP300, PRKCA, and TERT were included for subnet analysis. Next, a network of "Chinese medicine-active compound-potential target-signal pathway" was obtained and the HIF-1 signaling pathway was identified as the key pathway. Finally, 8 active compounds and their stable binding to target proteins were confirmed by molecular docking; MAPK3, SRC, TERT, and HIF1A were upregulated in HT relative to the goiter samples.

The integration of network pharmacology and molecular docking provides a systematic framework for exploring the multi-component and multi-target characteristics of BD in HT, underscores the therapeutic potential of BD in HT by targeting genes and pathways involved in immune regulation and oxidative stress. These findings not only enhance our understanding of BD's pharmacological mechanisms but also lay the groundwork for the development of novel therapeutic strategies for HT.

Thyroid cancer includes papillary thyroid carcinoma (PTC) and anaplastic thyroid carcinoma (ATC). While PTC has an excellent prognosis, ATC has a dismal prognosis, necessitating the identification of novel targets in ATC to aid in ATC diagnosis and treatment. Therefore, we analyzed ATC single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) data from the Gene Expression Omnibus (GEO), retrieved immune-related genes from the ImmPort database, and identified differentially expressed immune genes within single-cell subgroups. The AUCell package in R was used to calculate activity scores for single-cell subgroups and identify active cell populations. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on differentially expressed genes (DEGs) in active cell populations. Then, we integrated thyroid-cancer scRNA-seq and bulk RNA-seq data to identify overlapping DEGs. Relevant transcription factors (TFs) were retrieved from the TRRUST database. A protein-protein interaction (PPI) network for key TFs was created using the STRING database. Simultaneously, drugs associated with key TFs were obtained from DGIdb. ScRNA-seq cluster analysis showed that T/natural killer (NK) cells were more distributed in ATC and that thyrocytes cells were more distributed in PTC. We obtained 264 differential immune genes (DIGs) from the IMMPORT database and integrated scRNA-seq cluster analysis to identify the active cell T/NK cells and myeloid cells. Integrated bulk RNA-seq analysis obtained common immune genes (CIGs) such as TMSB4X, NFKB1, TNFRSF1B, and B2M. The nine CIG-related TFs (CEBPB, SPI1, NFKB1, RUNX1, NFE2L2, REL, CIITA, KLF6, and CEBPD) in myeloid cells and three TFs (NFKB1, FOXO1, and NR3C1) in T/NK cells were obtained from the TRRUST database. The key genes we identified represent potential targets for treating ATC.

Background: Although patients with anaplastic thyroid cancer (ATC) generally have a poor prognosis and there are currently no effective treatment options, survival and response to therapy vary between patients. Genomic and transcriptomic profiles of ATC have been reported; however, a comprehensive study of the tumor microenvironment (TME) of ATC is still lacking. This study aimed to elucidate the TME characteristics associated with ATC and their prognostic implications. Methods: We analyzed bulk RNA transcriptomic data from 1,634 samples-including 476 normal thyroid tissues, 25 benign thyroid adenomas, 340 RAS-like and 719 BRAFV600E-like differentiated thyroid cancers (DTC-R and DTC-B, respectively), and 74 ATCs. We assessed the TME and molecular characteristics of these thyroid cancer subtypes using deconvolution analysis. Results: The TME of ATC was characterized by a high abundance of immune cells and fibroblasts and a low abundance of epithelial cells compared to other thyroid histologies. During its malignant evolution, ATC exhibited an ecotype more closely related to DTC-B than RAS-like DTC (DTC-R). Furthermore, we identified two distinct molecular subtypes within ATC with significant differences in their TMEs. We termed the subtype with increased immune cells and fibroblasts as ATC-immune-fibroblast (ATC-IF) and the subtype with elevated epithelial and endothelial cells as ATC-epithelial-endothelial (ATC-E). The ATC-IF group had worse disease-specific survival (log-rank p = 0.035), higher ERK scores, and lower thyroid differentiation scores than the ATC-E group. While both ATC subtypes had elevated immune cells and fibroblasts compared to DTC-R and DTC-B, this increase was more pronounced in ATC-IF, with a marked rise in myeloid lineage cells and promigratory fibroblasts. Immune checkpoint gene expression and epithelial-mesenchymal transition scores were significantly higher in the ATC-IF group than in the ATC-E group. Conclusion: ATC shows a TME distinct from that of DTC and can be further divided into two molecular subtypes-each with its own unique TME. The ATC-IF group, with a poorer prognosis and higher ERK score, is enriched in immune cells and fibroblasts, which may represent potential therapeutic targets.

Thyroid cancer (TC) is the most prevalent endocrine malignancy worldwide. This study aimed to explore the molecular subtypes and improve the selection of targeted therapies. We used multi-omics data from 539 patients with DNA methylation, gene mutations, mRNA, lncRNA, and miRNA expressions. This study employed consensus clustering algorithms to identify molecular subtypes and used various bioinformatics tools to analyze genetic alterations, signaling pathways, immune infiltration, and responses to chemotherapy and immunotherapy. Two prognostically relevant TC subtypes, CS1 and CS2, were identified. CS2 was associated with a poorer prognosis of shorter progression-free survival times (P < 0.001). CS1 exhibited higher copy number alterations but a lower tumor mutation burden than CS2. CS2 exhibited activation in cell proliferation and immune-related pathways. Drug sensitivity analysis indicated CS2's higher sensitivity to cisplatin, doxorubicin, paclitaxel, and sunitinib, whereas CS1 was more sensitive to bicalutamide and FH535. The different activated pathways and sensitivity to drugs for the subtypes were further validated in an external cohort. Twenty-four paired tumors and adjacent normal tissues by immunohistochemical staining further demonstrated the prognostic value of CXCL17. In conclusion, we identified two distinct molecular subtypes of TC with significant implications for prognosis, genetic alterations, pathway activation, and treatment response.

Previous studies have suggested that SERPINA1 may promote a better prognosis in papillary thyroid carcinoma (PTC) along with Hashimoto's thyroiditis (HT). This study aims to further explore the role of the SERPINA1 gene in PTC and its relationship with HT using multiple databases.

Transcriptomic data from The Cancer Genome Atlas (TCGA) were utilized to analyze differences in SERPINA1 expression between PTC patients with and without HT. The expression levels of SERPINA1 in tumor tissues and its association with tumor characteristics were assessed using the Wilcoxon test across both patient groups. The impact of SERPINA1 expression on immune cell infiltration in PTC was evaluated using the CIBERSORT tool. Single-cell transcriptomic data from the Gene Expression Omnibus (GEO) were further analyzed to identify SERPINA1-expressing subpopulations based on Thyroid Differentiation Score (TDS) and pseudotime analysis. Gene Set Variation Analysis (GSVA) was employed to characterize pathways associated with SERPINA1, inferring its potential functions. Finally, CellChat was used to investigate key ligand-receptor interactions between SERPINA1-positive subpopulations and other cell types.

TCGA data analysis reveals that, compared to normal thyroid tissue, the transcriptional level of SERPINA1 is significantly elevated in PTC tissues. Moreover, the expression of SERPINA1 is closely linked to certain clinical pathological features of PTC and the infiltration of immune cells in the tumor microenvironment. Single-cell transcriptome analysis reveals that SERPINA1 is primarily expressed in thyrocytes and myeloid cells. In thyrocytes, SERPINA1 is associated with complement-related proteins (e.g., C3, CD55). In poorly differentiated thyrocytes, it is linked to protease inhibitors and epithelial-mesenchymal transition (EMT) pathways, while in moderately differentiated thyrocytes, it associates with apolipoproteins APOE and APOC1. In macrophages, SERPINA1 is highly expressed in HT-associated macrophages and unpolarized macrophages, correlating with inflammation and extracellular matrix regulation pathways. Cell-cell interaction analysis indicates that SERPINA1-positive cells interact with other cells in the tumor microenvironment through macrophage migration inhibitory factor (MIF) and fibronectin 1 (FN1).

Compared to normal thyroid tissue or cells, the expression level of SERPINA1 is elevated in PTC. In cancer cells, SERPINA1 may be associated with the complement system and complement regulator functions. In poorly differentiated thyrocytes, SERPINA1 may primarily function as a protease inhibitor and is closely related to FN1. In moderately differentiated thyrocytes, SERPINA1 is associated with apolipoproteins. In unpolarized macrophages, the function of SERPINA1 may be to act as a serine protease inhibitor, participating in the remodeling of the extracellular matrix. In macrophages within an HT environment, the elevated expression of SERPINA1 may serve as a protective mechanism to limit inflammation. In the tumor microenvironment coexisting with HT, SERPINA1 outside the tumor cells may enter the tumor cells through lipid metabolism pathways. The potential role of SERPINA1 in PTC progression is complex, and the findings of this study require further validation.

Active surveillance (AS) offers a viable alternative to surgical intervention for the management of indolent papillary thyroid carcinoma (PTC), helping to minimize the incidence of unnecessary treatment. However, the broader adoption of AS is hindered by the need for more reliable diagnostic markers. This study aimed to identify the differences between indolent and progressive PTC and find new targets for biomarker development and therapeutic strategies.

We used single-cell RNA sequencing (scRNA-seq) to analyze cellular differences in 10 early-stage PTC tumors. Findings were validated in an additional 25 tumors using cell co-culture, migration assays, immunofluorescence staining, flow cytometry, and analysis of data from The Cancer Genome Atlas (TCGA).

Tumor-infiltrating B cells (TIL-B), particularly germinal center B cells (GC-B), were more abundant in indolent PTC. These cells suppressed thyroid cell proliferation in both indolent and progressive cases, though indolent PTC had a higher capacity to recruit peripheral B cells. In indolent cases, TIL-B cells showed increased proliferation and formed clusters within tertiary lymphoid structures (TLS). PTPRC-CD22 interactions were identified as potential drivers of TIL-B cell proliferation. Markers linked to GC-B cells, such as LMO2, were highlighted as potential diagnostic and prognostic indicators for indolent PTC.

This study provides insights into the cellular landscape of early-stage PTC, revealing distinct tumor and immune microenvironment features in indolent and progressive cases. These findings advance the understanding of indolent PTC biology and support the development of reliable diagnostic and prognostic biomarkers.

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

This study investigates the role of membrane-associated protein 17 (MAP17) and the Akt signaling pathway in the progression of papillary thyroid carcinoma (PTC).

We conducted a series of in vitro experiments using PTC cell lines (HTori-3 and TPC-1). Cells were divided into three groups: control, MAP17 inhibitor negative control (NC), and MAP17 inhibitor treatment. Cell viability was assessed at 0, 24, 48, and 72 hours using the Cell Counting Kit-8 (CCK-8) assay. Apoptosis levels were measured by flow cytometry, and protein and mRNA expression of MAP17, phosphorylated Akt (p-AKT), and Akt were analyzed by Western blot and qRT-PCR.

Cell viability in the control, MAP17 inhibitor NC, and MAP17 inhibitor groups increased significantly over time (P < 0.05). Notably, in both HTori-3 and TPC-1 cells, the MAP17 inhibitor significantly reduced cell viability compared to the control and NC groups at 24, 48, and 72 hours (P < 0.05). Furthermore, apoptosis levels were significantly higher in the MAP17 inhibitor group compared to the control and NC groups (P < 0.05). Western blot and qRT-PCR analyses revealed that MAP17 and p-Akt protein and mRNA levels were significantly higher in the control and NC groups compared to the MAP17 inhibitor group (P < 0.05). However, no significant differences in total Akt protein or mRNA levels were observed across groups.

Our findings suggest that MAP17 and the Akt signaling pathway play a crucial role in promoting the progression of PTC. Inhibition of MAP17 suppresses cell viability and induces apoptosis, indicating that MAP17 may be a promising therapeutic target for PTC. The data also highlight the potential for targeting the MAP17-Akt axis in developing future treatments for PTC.

Thyroid cancer is a prevalent malignancy requiring accurate subtype identification for effective treatment planning and prognosis evaluation. Deep learning has emerged as a valuable tool for analyzing tumor microenvironment features and distinguishing between pathological subtypes, yet the interplay between microenvironment characteristics and clinical outcomes remains unclear.

Pathological tissue slices, gene expression data, and protein expression data were collected from 118 thyroid cancer patients with various subtypes. The data underwent preprocessing, and 10 AI models, including EfficientNetB0, were compared. EfficientNetB0 was selected, trained, and validated, with microenvironment features such as tumor-immune cell interactions and extracellular matrix (ECM) composition extracted from the samples.

The study demonstrated the high accuracy of the EfficientNetB0 model in differentiating papillary, follicular, medullary, and anaplastic thyroid carcinoma subtypes, surpassing other models in performance metrics. Additionally, the model revealed significant correlations between microenvironment features and pathological subtypes, impacting disease progression, treatment response, and patient prognosis.

The research establishes the effectiveness of the EfficientNetB0 model in identifying thyroid cancer subtypes and analyzing tumor microenvironment features, providing insights for precise diagnosis and personalized treatment. The results enhance our understanding of the relationship between microenvironment characteristics and pathological subtypes, offering potential molecular targets for future treatment strategies.

Disruption of circadian rhythm was found to be associated with immune infiltration and thyroid cancer. However, the role of clock circadian regulator (CLOCK) in the progression of thyroid cancer and its immune microenvironment remains largely unexplored. Therefore, our aim was to explore the role and potential mechanism of CLOCK in thyroid cancer.

Single cell sequencing analysis and bulk RNA sequencing analysis was used for LASSO regression and Kaplan-Meier survival estimates. Potential mechanism analysis were gained through KEGG/GO analysis, GSEA analysis and PPI network. In vivo and in vitro experiment was used for further validation.

The result showed CLOCK protein was overexpressed in thyroid cancer compared with normal tissue in both thyroid specific mouse model and human sample. A prognostic model incorporating CLOCK and other related genes (FAT4, OR6K2, STK40, TMEM63A, HRCT1, SUPT5H, and OR2C3) was developed using LASSO regression. Functional assay and bioinformatics analysis indicated that CLOCK knockdown hindered tumor growth and the activity of MAPK signaling. Besides, analyses of gene enrichment, signaling pathways, and immune checkpoints suggested that CLOCK might inhibit immune infiltration within the tumor microenvironment. Confirmatory in vitro experiments and immunohistochemical assays in human samples further linked high CLOCK expression to reduced T cell cytotoxicity and infiltration.

These findings underscore the pivotal role of CLOCK in thyroid cancer prognosis and immune suppression, highlighting its potential as a target for therapeutic intervention and prognostic assessment in thyroid cancer management.

Gastrointestinal metastases are rare in patients with thyroid carcinoma (TC), and their underlying mechanisms remain unclear. Thus, in this study, we aimed to explore the spatial distribution characteristics of TCs and associated gastrointestinal metastatic cells.

We used spatial transcriptomics to generate an atlas that captures spatial gene expression patterns in papillary thyroid cancer (PTC), anaplastic thyroid carcinoma (ATC), ATC-associated lymphatic metastasis (ATC-LM), and rare ATC-associated gastric metastasis (ATC-GM).

We demonstrated that tumor-specific myeloid cells with high SFRP4 expression were correlated with TC dedifferentiation and poor prognosis. Moreover, we validated their close localization to CD44+ tissue stem cells using immunofluorescence staining and spatial transcriptomics. We also demonstrated that ATC-LM and ATC-GM tissues exhibited high levels of CD44+PKHD1L1+ cells, which could serve as markers for these two pathological types.

These findings highlight the dynamic changes in cell composition, intercellular communication, and potential markers associated with TC dedifferentiation and distant metastasis. Further research based on our findings may contribute to improving diagnostic and therapeutic strategies for patients with TC.

Tyrosine kinase inhibitors (TKIs) are crucial for improving the survival rates of individuals with metastatic thyroid cancer. Moreover, systemic inflammation and malnutrition are known to negatively affect metastatic thyroid cancer prognosis. Evaluating nutritional status at the start of treatment can improve survival rates. Purpose: This study investigated the correlation between the hemoglobin, albumin, lymphocyte count, and platelet (HALP) score and prognosis of patients with metastatic thyroid cancer undergoing first-line TKI therapy. Methods: We retrospectively analyzed data from 44 patients between January 2010 and June 2024. The primary outcomes evaluated in the study were time to treatment failure (TTF) and overall survival (OS); HALP scores were categorized as low (≤29.21) and high (>29.21) based on receiver operating characteristic analysis. Results: The 1-year survival rate was significantly lower in the low HALP score group compared to the high HALP score group (50% vs. 96.3%). Multivariate Cox regression analysis revealed that low HALP scores, elevated leukocyte counts, and lymphopenia were independent predictors of shorter TTF (HR = 0.272, p = 0.011) and OS (HR = 0.208, p = 0.028). Conclusions: The results obtained in the present study demonstrate that the HALP score has prognostic significance for patients with metastatic thyroid cancer who are undergoing first-line TKI treatment. In metastatic thyroid cancer patients, interventions focused on improving nutritional status at the start, during initiation, and throughout the TKI treatment may enhance treatment effectiveness. However, further prospective studies involving larger patient cohorts are necessary to validate our results.

Differentiated thyroid cancer (DTC) generally has a favorable prognosis, and radioactive iodine (RAI) therapy is typically used for metastatic DTC that continues to progress and poses life-threatening risks. However, resistance to RAI in metastatic DTC significantly impairs treatment effectiveness. This study aims to identify potential compounds that may influence RAI efficacy. We conducted untargeted metabolomics on pre-treatment serum samples from 42 RAI-refractory DTC (RAIR-DTC) patients and 52 RAI-sensitive patients. The results revealed significantly elevated levels of two per- and polyfluoroalkyl substances (PFAS), PFDA and PFNA, in RAI-resistant patients. This accumulation was significantly negatively correlated with the expression of the sodium-iodide symporter (NIS), which reflects the differentiation status and iodide uptake capability of thyroid cancer. Furthermore, high levels of PFDA and PFNA exposure were significantly associated with poor prognosis in patients undergoing RAI therapy. In vivo exposure simulations in a murine model showed that PFAS exposure significantly increased the malignant progression of thyroid cancer, reduced iodine uptake ability, and promoted dedifferentiation. Overall, these findings provide novel insights into the development of RAIR-DTC, highlighting the importance of continuous monitoring and control of PFAS exposure in cancer patients.

P-selectin (SELP) expression in tumor cells has been implicated in promoting tumor progression and treatment resistance across various cancers. However, our prior study identified SELP expression in a specific subpopulation of endothelial cells within cervical cancer (CC) and potentially linked to anti-cancer immune response. The precise mechanisms by which SELP influences anti-cancer immunity and its involvement in radiotherapy response in CC, however, remain elusive. To address these gaps, this study analyzed tumor tissue samples from 205 CC patients undergoing radiotherapy, scRNA-seq data from 42,159 cells of eight patients, and bulk RNA-sequencing data from 187 radiotherapy-treated patients. The results revealed that elevated SELP expression in tumor endothelial cells (TECs) was significantly correlated with improved survival outcomes in patients treated with radiotherapy. The SELPhigh group exhibited a prominent enrichment of immune-related pathways, coupled with a diminished enrichment in epithelial cell proliferation and angiogenesis pathways. Notably, this group demonstrated increased infiltration of CD8+ T cells and enhanced expression of chemokine receptors, including ACKR1. Furthermore, our data suggest that SELP+ TECs engage in crosstalk with CD8+ T cells via the ACKR1-CCL5 axis, which is associated with improved radiotherapy efficacy. In conclusion, these findings underscore the pivotal role of SELP+ TEC:CD8+ T cell interactions through the ACKR1-CCL5 pathway in enhancing radiotherapy response in CC. Targeting this crosstalk may offer novel therapeutic strategies to mitigate treatment resistance and improve patient survival.

Thyroid differentiation score (TDS), calculated based on mRNA expression levels of 16 genes controlling thyroid metabolism and function, has been proposed as a measure to quantify differentiation in papillary thyroid carcinoma (PTC).

The objective of this study is to determine whether TDS is associated with survival outcomes across patient cohorts.

Two independent cohorts of patients with PTC were used: (1) The Cancer Genome Atlas (TCGA) thyroid cancer study (N = 372), (2) MD Anderson Cancer Center (MDACC) cohort (N = 111). The primary survival outcome of interest was progression-free interval (PFI). Association with overall survival (OS) was also explored. The Kaplan-Meier method and Cox proportional hazards models were used for survival analyses.

In both cohorts, TDS was associated with tumor and nodal stage at diagnosis as well as tumor driver mutation status. High TDS was associated with longer PFI on univariable analyses across cohorts. After adjusting for overall stage, TDS remained significantly associated with PFI in the MDACC cohort only (adjusted hazard ratio [aHR] 0.67, 95% CI 0.52-0.85). In subgroup analyses stratified by tumor driver mutation status, higher TDS was most consistently associated with longer PFI in BRAFV600E-mutated tumors in the MDACC cohort after adjusting for overall stage (TCGA: aHR 0.60, 95% CI 0.33-1.07; MDACC: aHR 0.59, 95% CI 0.42-0.82). For OS, increasing TDS was associated with longer OS in the overall MDACC cohort (aHR = 0.78, 95% CI 0.63-0.96), where the median duration of follow-up was 12.9 years.

TDS quantifies the spectrum of differentiation status in PTC and may serve as a potential prognostic biomarker in PTC, mostly promisingly in BRAFV600E-mutated tumors.

Thyroid cancer progression from curable well-differentiated thyroid carcinoma to highly lethal anaplastic thyroid carcinoma is distinguished by tumor cell de-differentiation and recruitment of a robust stromal infiltrate. Combining an integrated thyroid cancer single-cell sequencing atlas with spatial transcriptomics and bulk RNA-sequencing, we define stromal cell subpopulations and tumor-stromal cross-talk occurring across the histologic and mutational spectrum of thyroid cancer. We identify distinct inflammatory and myofibroblastic cancer-associated fibroblast (iCAF and myCAF) populations and perivascular-like populations. The myCAF population is only found in malignant samples and is associated with tumor cell invasion, BRAF V600E mutation, lymph node metastasis, and disease progression. Tumor-adjacent myCAFs abut invasive tumor cells with a partial epithelial-to-mesenchymal phenotype. Tumor-distant iCAFs infiltrate inflammatory autoimmune thyroid lesions and anaplastic tumors. In summary, our study provides an integrated atlas of thyroid cancer fibroblast subtypes and spatial characterization at sites of tumor invasion and de-differentiation, defining the stromal reorganization central to disease progression.

Papillary thyroid carcinoma (PTC) is the predominant form of thyroid cancer globally, especially when lymph node metastasis (LNM) occurs. Molecular heterogeneity, driven by genetic alterations and tumor microenvironment components, contributes to the complexity of PTC. Understanding these complexities is essential for precise risk stratification and therapeutic decisions.

This study involved a comprehensive analysis of 521 patients with PTC from our hospital and 499 patients from The Cancer Genome Atlas (TCGA). The real-world cohort 1 comprised 256 patients with stage I-III PTC. Tissues from 252 patients were analyzed by DNA-based next-generation sequencing, and tissues from four patients were analyzed by single-cell RNA sequencing (scRNA-seq). Additionally, 586 PTC pathological sections were collected from TCGA, and 275 PTC pathological sections were collected from the real-world cohort 2. A deep-learning multi-modal model was developed using matched histopathology images, genomic, transcriptomic, and immune cell data to predict LNM and disease-free survival (DFS).

This study included a total of 1011 PTC patients, comprising 256 patients from cohort 1, 275 patients from cohort 2, and 499 patients from TCGA. In cohort 1, the authors categorized PTC into four molecular subtypes based on BRAF, RAS, RET, and other mutations. BRAF mutations were significantly associated with LNM and impacted DFS. ScRNA-seq identified distinct T-cell subtypes and reduced B-cell diversity in BRAF-mutated PTC with LNM. The study also explored cancer-associated fibroblasts and macrophages, highlighting their associations with LNM. The deep-learning model was trained using 405 pathology slides and RNA sequences from 328 PTC patients and validated with 181 slides and RNA sequences from 140 PTC patients in the TCGA cohort. It achieved high accuracy, with an area under the curve (AUC) of 0.86 in the training cohort, 0.84 in the validation cohort, and 0.83 in the real-world cohort 2. High-risk patients in the training cohort had significantly lower DFS rates ( P <0.001). Model AUCs were 0.91 at 1 year, 0.93 at 3 years, and 0.87 at 5 years. In the validation cohort, high-risk patients also had lower DFS ( P <0.001); the AUCs were 0.89, 0.87, and 0.80 at 1, 3, and 5 years. The authors utilized the GradCAM algorithm to generate heatmaps from pathology-based deep-learning models, which visually highlighted high-risk tumor areas in PTC patients. This enhanced clinicians' understanding of the model's predictions and improved diagnostic accuracy, especially in cases with lymph node metastasis.

The artificial intelligence (AI)-based analysis uncovered vital insights into PTC molecular heterogeneity, emphasizing BRAF mutations' impact. The integrated deep-learning model shows promise in predicting metastasis, offering valuable contributions to improved diagnostic and therapeutic strategies.

Recurrence and metastasis are the major issues for papillary thyroid cancer (PTC). Current morphological and molecular classification systems are not satisfied for PTC diagnosis due to lacking variant-specific morphological criteria and high signal-to-noise in mutation-based diagnosis, respectively. Importantly, intratumor heterogeneity is largely lost in current molecular classification system, which can be resolved by single cell RNA sequencing (scRNA-seq). However, scRNA-seq loses spatial information and morphological features. Herein, scRNA-seq is integrated and spatially-resolved transcriptomics (SRT) to elaborate the mechanisms underlying the spatial heterogeneity, malignancy and metastasis of PTCs by associating transcriptome and local morphology. This results demonstrated that PTC cells evolved with multiple routes, driven by the enhanced aerobic metabolism and the suppressed mRNA translation and protein synthesis and the involvement of cell-cell interaction. Two curated malignant and metastatic footprints can discriminate PTC cells from normal thyrocytes. Ferroptosis resistance contributed to PTC evolution. This results will advance the knowledge of intratumor spatial heterogeneity and evolution of PTCs at spatial and single-cell levels, and propose better diagnostic strategy.

Thyroid cancer is one of the most common endocrine tumors worldwide, especially among women and the metastatic mechanism of papillary thyroid carcinoma remains poorly understood.

Thyroid cancer tissue samples were obtained for single-cell RNA-sequencing and spatial transcriptomics, aiming to intratumoral and antimetastatic heterogeneity of advanced PTC. The functions of APOE in PTC cell proliferation and invasion were confirmed through in vivo and in vitro assays. Pseudotime analysis and CellChat were performed to explore the the molecular mechanisms of the APOE in PTC progression.

We identified a subpopulation of tumor cells with lower expression levels of APOE, associated with advanced stages of PTC and cervical metastasis. APOE overexpression significantly reduced tumor cell proliferation and invasion, both in vitro and in vivo, by activating the ABCA1-LXR axis. APOE- tumor cells may promote tumor growth by interacting with dendritic cells and CD4+ T cells via CD99- rather than CD6-regulated signaling. We established a machine learning-based scRNA-seq data, 13-gene signature predictive of lymph node metastasis.

We identified a distinct APOE- tumor cell population associated with cervical metastasis and poor prognosis. Our results and models have potential clinical, prognostic, and therapeutic implications for advanced PTC.

A subpopulation of tumor cells with lower expression levels of APOE was strongly associated with more advanced stages and metastasis of PTC. APOE-negative (APOE-) cellsoverall exhibited weaker interactions with immune cells. A machine-learning bioinformatics model based on scRNA-seq data of in-situ thyroid cancer tissue was established to predict lymph node metastasis.

Thyroid cancer treatment has recently been revolutionized by the introduction of specific targeted therapies (e.g. BRAFV600E or highly selective RET inhibitors), anti-angiogenic agents (e.g. tyrosine kinase inhibitors (TKIs)) and immune checkpoint inhibitors, which significantly ameliorate outcomes in selected groups of thyroid cancer patients. Targeted and anti-angiogenic treatments are characterized by transient and partial efficacy, due to primary or secondary tumor resistance mechanisms, and toxicity profile. Immune therapy-based approaches are producing preliminary results. Herein, we review and prospectively discuss immune microenvironment in non-medullary and medullary thyroid cancers and its interplays with angiogenic microenvironment (endothelial cells and pericytes). In addition, we discuss how these interactions might be targeted using combined therapies. Furthermore, we will review chimeric antigen receptor (CAR) T cells treatment that potentially may ensure a more durable and effective response in advanced thyroid cancers. In sum, angiogenic and immune microenvironments show functional connectivity in TCs. Therapies with anti-angiogenic and immune checkpoint inhibitors combined with specific targeted therapy inhibitors with a tolerable toxicity profile may overcome drug resistance and provide better clinical outcomes than single agents.

We aimed to establish a useful molecular marker for differentiating between follicular thyroid carcinoma (FTC) and follicular adenoma (FA). RNA was extracted from the invasive front and paired tumor center tissues from three FTC cases using laser microdissection for cDNA microarray analysis, revealing high expression of gamma-glutamyl cyclotransferase (GGCT) in the invasive front. Subsequently, immunohistochemical (IHC) staining of GGCT was performed with formalin-fixed paraffin-embedded (FFPE) sections of FTC (n = 32), FA (n = 64), and follicular tumor of uncertain malignant potential (FT-UMP, n = 5). The GGCT expression score (range: 0-300) was calculated by multiplying the intensity score (0-3) and percentage of positive cells. The Ki-67 labeling index was also assessed in 20 FTC and 25 FA cases from the same cohort. The GGCT expression score was higher in FTC than in FA (118.5 ± 51.4 vs. 57.3 ± 34.7, P < 0.0001). With the GGCT expression score, using a cutoff value of 101.1, the differentiation between FTC and FA was possible with a sensitivity of 68.8 % and specificity of 87.5 % (AUC = 0.832). With the Ki-67 labeling index, applying a cutoff value of 4.0 %, the distinction between FTC and FA resulted in a sensitivity of 50.0 % and specificity of 80.0 % (AUC = 0.677). The GGCT expression score was positively related to the Ki-67 labeling index in the FTC cases. (Spearman's ρ = 0.5293, P = 0.0164). Therefore, GGCT is a potential marker for differentiating FTC from FA. The GGCT expression of FTC may be indicative of its invasive and proliferative activity.

Transforming growth factor beta receptor III (TGFBR3) has been shown to play a tumor-suppressive role in a variety of cancers. However, its role in papillary thyroid cancer (PTC) remains unknown.

TGFBR3 expression levels in PTC were analyzed utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Edu, wound healing, and Transwell assays were used to evaluate cell proliferation, migration, and invasion. Transcriptome sequencing, quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR), and Western blotting were used to detect the underlying mechanism of TGFBR3 in PTC progression.

This study demonstrated that TGFBR3 expression was significantly down-regulated in PTC compared to normal thyroid tissues. Low expression of TGFBR3 was associated with poor prognosis of patients with PTC. Furthermore, TGFBR3 expression positively correlated with thyroid differentiation score. In investigating the biological impact of TGFBR3 overexpression in PTC cell lines, we found that the proliferation, migration, and invasion of PTC cells were significantly inhibited in response to TGFBR3 overexpression. Moreover, we also demonstrated that overexpression of TGFBR3 inhibited the PI3K/AKT pathway and epithelial-mesenchymal transformation processes. Lastly, TGFBR3 expression was found to be involved in tumor immune infiltration, highlighting its potential influence on immune dynamics within the tumor microenvironment in PTC.

TGFBR3 plays a tumor-suppressive role in PTC progression by inhibiting the PI3K/AKT pathway and epithelial mesenchymal transformation.

This research sought to evaluate the clinical value of systemic immune-inflammation index and systemic inflammation response index in predicting the response to radioactive iodine (RAI) therapy in individuals diagnosed with differentiated thyroid cancer.

This retrospective study included 406 patients with differentiated thyroid cancer who received initial RAI therapy and follow-up from December 2019 to December 2023. Patients were divided into two groups based on imaging and serum indicators to evaluate the response to radioactive iodine treatment: the ER group (excellent response) and the non-ER group (suboptimal response). Systemic immune-inflammation index and systemic inflammation response index were calculated based on peripheral blood cell counts before treatment. Multivariable logistic regression analysis was used to assess the independent associations of these indices with the therapeutic response to radioiodine treatment. Receiver operating characteristic (ROC) curves were graphed and the area under the curve (AUC) was calculated to evaluate their predictive ability.

Compared to the ER group, patients in the non-ER group had significantly elevated systemic immune-inflammation index and systemic inflammation response index levels (p < 0.001). After adjusting for confounding factors, there was a significant association between these indices and the response to radioactive iodine treatment in patients with differentiated thyroid cancer. The optimal cutoff values for predicting the response to RAI treatment were 668.91 for systemic immune-inflammation index (AUC=0.692, sensitivity 58.2%, specificity 73.1%, 95% CI: 0.639-0.745, p < 0.001) and 0.47 for systemic inflammation response index (AUC=0.664, sensitivity 85.6%, specificity 42.7%, 95% CI: 0.612-0.717, p < 0.001).

Systemic immune-inflammation index and systemic inflammation response index could be valuable for predicting the response to RAI treatment in individuals diagnosed with differentiated thyroid cancer. Further research is needed to explore their practical utility, and these novel inflammation markers could serve as adjunct tools in clinical practice.

Local recurrence and distal metastasis negatively impact the survival and quality of life in patients with papillary thyroid cancer (PTC). Therefore, identifying potential biomarkers and therapeutic targets for PTC is clinically crucial. In this study, we performed a multiomics analysis that identified a subset of CD36+ proinflammatory macrophages within the tumor microenvironment of PTC. The recruitment of CD36+ macrophages to premalignant regions strongly correlated with unfavorable outcomes in PTC, and the presence of tumor-infiltrating CD36+ macrophages was determined to be a risk factor for recurrence. The CD36+ macrophages exhibited interactions with metabolically active ZCCHC12+ tumor cells. By secreting SPP1, the CD36+ macrophages activated the PI3K-AKT signaling pathway, thereby promoting proliferation of the cancer cells. Dysregulation of iodine metabolism was closely related to the acquisition of the pro-inflammatory phenotype in macrophages. Iodine supplementation inhibited the activation of proinflammatory signaling and impeded the development of CD36+ macrophages by enhancing DUSP2 expression. Overall, our findings shed light on the intricate cross-talk between CD36+ macrophages and ZCCHC12+ tumor cells, providing valuable insights for the treatment and prognosis of PTC.

Growing evidence highlights the importance of tumor endothelial cells (TECs) in the tumor microenvironment (TME) for promoting tumor growth and evading immune responses. Immunomodulatory endothelial cells (IMECs) represent a distinct plastic phenotype of ECs that exerts the ability to modulate immunity in health and disease. This review discusses our current understanding of IMECs in cancer biology, scrutinizing insights from single-cell reports to compare their characteristics and function dynamics across diverse tumor types, conditions, and species. We investigate possible implications of exploiting IMECs in the context of cancer treatment, particularly examining their influence on the efficacy of existing therapies and the potential to leverage them as targets in optimizing immunotherapeutic strategies.

Thyroid cancer (TC) remains a significant clinical challenge worldwide, with a subset of patients facing aggressive disease progression and therapeutic resistance. Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have emerged as promising therapeutic approaches for various malignancies, yet their efficacy in TC remains uncertain. The objective of this study was to investigate PD-L1 expression in aggressive TC and its association with histological subtypes, molecular mutation, and progression-free survival.

This is a retrospective study of patients with advanced TC seen in two tertiary health care centers. Included in this study were patients with advanced TC with recurrence or progression on therapy for whom tumor molecular profiling and PD-L1 status were available. Kaplan-Meier estimators were utilized to analyze the progression-free survival (PFS) between patients with PD-L1 positive and negative status in Anaplastic TC (ATC) subgroup.

A total of 176 patients with advanced thyroid cancer were included (48.9% female). Of the patients, 13 had ATC, 11 Medullary TC (MTC), 81 Papillary TC Classic Variant (PTCCV), 20 Follicular TC (FTC), 8 Oncocytic TC (OTC), 10 Poorly Differentiated TC (PDTC), and 30 had the Papillary TC Follicular Variant (PTCFV). BRAF mutation was present in 41%, TERT in 30%, RAS in 19%, TP53 in 10%, and RET in 8.6% of patients. PD-L1 positivity was significantly different across different TC types and histological subtypes (p < 0.01): Patients with OTC had the highest frequency of PD-L1 positivity (71%), followed by ATC (69%), PTCCV (28.5%), and FTC (11%). Patients with MTC and PTCFV did not exhibit any PD-L1 positivity. TP53 mutation was positively associated with PD-L1 expression (21.6% vs. 7.5%, p = 0.03), and RAS mutation was negatively associated with PD-L1 expression (8.1% vs. 24.2% p = 0.04). Among patients with ATC, positive PD-L1 expression was associated with lower PFS (p = 0.002).

PD-L1 expression varies across different TC types and histological subtypes and may be modulated by the mutational landscape. PD-L1 expression in ATC is associated with shorter PFS. Follow up studies are warranted to elucidate the molecular mechanism driving the observed differences in immune pathways, potentially paving the way for the development of more effective and personalized immune therapies for patients with aggressive TC.

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a poor prognosis and limited treatment options. Bulk genomic characterization of ACC has not yielded obvious therapeutic or immunotherapeutic targets, yet novel therapies are needed. We hypothesized that elucidating the intratumoral cellular heterogeneity by single nuclei RNA sequencing analyses would yield insights into potential therapeutic vulnerabilities of this disease. In addition to characterizing the immune cell and fibroblast landscape, our analyses of single nuclei gene expression profiles identified an adrenal cortex cell cluster exhibiting a program of replication stress and DNA damage response in primary and metastatic ACC. In vitro assessment of replication stress and DNA damage response using an ACC cell line and a series of newly-derived hormonally active patient-derived tumor organoids revealed ATR sensitivity. These findings provide novel mechanistic insight into ACC biology and suggest that an underlying dependency on ATR may be leveraged therapeutically in advanced ACC.

Previous studies have indicated that ψ-modified small RNAs play crucial roles in tumor metastasis. However, the ψ-modified small RNAs during metastasis of PTC are still unclear.

We compared the pseudouridine synthase 7 (PUS7) alteration between metastatic and non-metastatic PTCs, and investigated its correlation with clinicopathological features. Additionally, we employed a small RNA ψ modification microarray to examine the small RNA ψ modification profile in both metastatic and non-metastatic PTCs, as well as paired paracancerous tissues. The key molecule involved in ψ modification, pre-miR-8082, was identified and found to regulate the expression of CD47. Experiments in vitro were conducted to further investigate the function of PUS7 and CD47 in PTC.

Our results demonstrated that PUS7 was down-regulated in PTC and was closely associated with metastasis. Moreover, the ψ modification of pre-miR-8082 was found to be decreased, resulting in down-expression of pre-miR-8082 and miR-8082, leading to the loss of the inhibitory effect on CD47, thereby promoting tumor migration.

Our study demonstrates that PUS7 promotes the inhibition of CD47 and inhibits metastasis of PTC cells by regulating the ψ modification of pre-miR-8082. These results suggest that PUS7 and ψ pre-miR-8082 may serve as potential targets and diagnostic markers for PTC metastasis.

This study investigates the impact of Hashimoto's thyroiditis (HT), an autoimmune disorder, on the papillary thyroid cancer (PTC) microenvironment using a dataset of 140,456 cells from 11 patients. By comparing PTC cases with and without HT, we identify HT-specific cell populations (HASCs) and their role in creating a TSH-suppressive environment via mTE3, nTE0, and nTE2 thyroid cells. These cells facilitate intricate immune-stromal communication through the MIF-(CD74+CXCR4) axis, emphasizing immune regulation in the TSH context. In the realm of personalized medicine, our HASC-focused analysis within the TCGA-THCA dataset validates the utility of HASC profiling for guiding tailored therapies. Moreover, we introduce a novel, objective method to determine K-means clustering coefficients in copy number variation inference from bulk RNA-seq data, mitigating the arbitrariness in conventional coefficient selection. Collectively, our research presents a detailed single-cell atlas illustrating HT-PTC interactions, deepening our understanding of HT's modulatory effects on PTC microenvironments. It contributes to our understanding of autoimmunity-carcinogenesis dynamics and charts a course for discovering new therapeutic targets in PTC, advancing cancer genomics and immunotherapy research.