Single-Cell Transcriptome Analysis Reveals Inter-Tumor Heterogeneity in Bilateral Papillary Thyroid Carcinoma

Associations between preoperative thyroid parameters, aggressive clinicopathological features and risk of recurrence in differentiated thyroid cancer

OBJECTIVE

The study aimed (1) to investigate the association between aggressive clinicopathological characteristics and the American Thyroid Association (ATA) recurrence risk classification in differentiated thyroid cancer (DTC) patients, and (2) to investigate the prognostic value of preoperative thyroid parameters.

METHODS

A total of 3833 patients histologically confirmed DTC were recruited. Preoperative clinical and postoperative pathologic data were retrospectively collected. Participants were stratified into low recurrence risk and intermediate-to-high recurrence risk groups based on the ATA risk stratification system.

RESULTS

The study cohort had a mean age of 48.87 ± 8.08 years, and 1,465 (76.82%) were female. Male (OR = 1.37, p = .024), aged 52 years and older (OR = 2.01, p < .001), larger tumor size (OR = 3.71, p = 0.011), nerve invasion (OR = 6.69, p = .004), margin involvement (OR = 5.46, p < .001), multifocality (OR = 3.71, p < .001), and bilaterality (OR = 3.95, p < .001) were identified as risk factors for a higher ATA recurrence risk classification, in addition to established factors such as lymph node metastasis and angioinvasion, after adjusting for potential confounding variables. Higher preoperative levels of free triiodothyronine (FT3), FT3 to free thyroxine (FT3/FT4), and lower thyroid feedback quantile-based index (TFQI) levels were associated with a higher ATA recurrence risk classification. The comprehensive predictive model incorporating these variables demonstrated excellent discrimination (AUC = 0.836). Furthermore, higher FT3/FT4 levels and lower TFQI levels were associated with higher risk of lymph node metastases and angioinvasion.

CONCLUSIONS

Factors such as male sex, older age, multifocality, bilaterality, margin involvement, nerve invasion, larger tumor size, and preoperative thyroid parameters serve as complementary predictors for higher ATA recurrence risk in DTC, in addition to conventional risk factors. These insights contribute to a more nuanced understanding and optimization of current risk stratification methodologies.

A Pan-Cancer Comparative Analysis of The Cancer Genome Atlas Transcriptomic TIL-Immune Signatures

Efforts to understand the tumor microenvironment (TME) through basic science research and The Cancer Genome Atlas (TCGA) data analysis have led to the creation of unique immune transcriptomic signatures from tumor-infiltrating lymphocytes (TIL). However, no pan-cancer analysis has been conducted to compare the prognostic performance of these signatures using overall survival (OS) or progression-free interval (PFI) as endpoints. We compiled a library of 146 TIL-immune signatures and evaluated gene signature score correlation with OS and PFI for 9,961 available TCGA samples across 33 cancer types. Zhang CD8 TCS demonstrated higher accuracy in prognosticating both OS and PFI across the pan-cancer landscape, however, variability was seen across cancer types and germ cell origin. Cluster analysis compiled a group of six signatures (Oh.Cd8.MAIT, Grog.8KLRB1, Oh.TIL_CD4.GZMK, Grog.CD4.TCF7, Oh.CD8.RPL, Grog.CD4.RPL32) whose association with OS and PFI could potentially be conserved across multiple cancer types.

Exploring Immune-Related Ferroptosis Genes in Thyroid Cancer: A Comprehensive Analysis

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.

Bioinformatic analysis of serpina1 expression in papillary thyroid carcinoma and its potential association with Hashimoto's thyroiditis

PURPOSE

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.

METHODS

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.

RESULTS

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).

CONCLUSION

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.

Single-cell transcriptomics analysis reveals that the tumor-infiltrating B cells determine the indolent fate of papillary thyroid carcinoma

OBJECTIVE

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.

METHODS

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).

RESULTS

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.

CONCLUSION

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.

Thyroid Cancer-The Tumor Immune Microenvironment (TIME) over Time and Space

In thyroid cancer, the tumor immune microenvironment (TIME) plays a crucial role in cancer development, progression and response to treatment. Like many other cancers, thyroid cancer creates a complex network of interactions with immune cells directly (cell-to-cell) and via humoral mediators (i.e., cytokines). This dynamic microenvironment undergoes constant modification, which can lead to changes in the immunophenotype that might explain cancer progression, dedifferentiation and resistance to treatment. According to the cancer immunoediting hypothesis, cancerous tumors can shape their immune microenvironment to create an immunosuppressive milieu that allows them to evade classic immune surveillance. One mechanism by which this occurs is through the reprogramming of immune cells, often shifting their phenotypes from cytotoxic to regulatory. Recent research has shed light on cellular components and molecular interactions within the thyroid cancer TIME. Immune cells such as Tumor-Associated Lymphocytes (TALs), myeloid-derived suppressor cells (MDSCs), Tumor-Associated Macrophages (TAMs) and Double-Negative (DN) T cells seem to play key roles in shaping the immune response to thyroid cancer. Additionally, cytokines, chemokines and other signaling molecules contribute to the communication and regulation of immune cells within that microenvironment. By studying these interactions, researchers aim to uncover not just potential therapeutic targets but also biomarkers of thyroid cancer that could provide clues on severity and progression. Based on that knowledge, strategies such as the use of immune checkpoint inhibitors, antigen-specific targeted immunotherapies, and immunomodulatory agents are being explored to enhance the anti-tumor immune response and overcome cancer immunosuppressive mechanisms. In this review, we analyze the available literature and provide our own experience to unravel the complexity of the thyroid immune microenvironment. Continued research in this area holds promise for improving outcomes through the identification of immune markers of severity/progression of thyroid cancer and the development of innovative immunotherapeutic approaches.

Constructing methylation-driven ceRNA networks unveil tumor heterogeneity and predict patient prognosis

Cancer development involves a complex interplay between genetic and epigenetic factors, with emerging evidence highlighting the pivotal role of competitive endogenous RNA (ceRNA) networks in regulating gene expression. However, the influence of ceRNA networks by aberrant DNA methylation remains incompletely understood. In our study, we proposed DMceNet, a computational method to characterize the effects of DNA methylation on ceRNA regulatory mechanisms and apply it across eight prevalent cancers. By integrating methylation and transcriptomic data, we constructed methylation-driven ceRNA networks and identified a dominant role of lncRNAs within these networks in two key ways: (i) 17 cancer-shared differential methylation lncRNAs (DMlncs), including PVT1 and CASC2, form a Common Cancer Network (CCN) affecting key pathways such as the G2/M checkpoint, and (ii) 24 cancer-specific DMlncs construct unique ceRNA networks for each cancer type. For instance, in LUAD and STAD, hypomethylation drives DMlncs like PCAT6 and MINCR, disrupting the Wnt signaling pathway and apoptosis. We further investigated the characteristics of these methylation-driven ceRNA networks at the cellular level, revealing how methylation-driven dysregulation varies across distinct cell populations within the tumor microenvironment. Our findings also demonstrate the prognostic potential of cancer-specific ceRNA relationships, highlighting their relevance in predicting patient survival outcomes. This integrated transcriptomic and epigenomic analysis provides new insights into cancer biology and regulatory mechanisms.

An integrated single-cell and spatial transcriptomic atlas of thyroid cancer progression identifies prognostic fibroblast subpopulations

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.

Spatial and Single-Cell Transcriptomics Unraveled Spatial Evolution of Papillary Thyroid Cancer

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.

Nanomedicine mediated thyroid cancer diagnosis and treatment: an approach from generalized to personalized medicine

Thyroid cancer (TC) being the common endocrine malignancy is glooming steadily due to its poor prognosis. The treatment strategies of surgery, radiotherapy, and conventional chemotherapy are providing unsatisfactory output. However, combination therapy can negotiate the worse prognosis to the better, where chemoradiotherapy, radiotherapy with surgery, or dual chemotherapeutic drugs are being glorified. Chemotherapy includes the use of doxorubicin or taxanes generally with platinum-based drugs viz. cisplatin or carboplatin that are administered alone or along with multitarget tyrosine kinase inhibitors viz. Lenvatinib, Sorafenib, Sunitinib, Vandetanib, Pyrazolo-pyrimidine compounds, etc., single target tyrosine kinase inhibitors like Dabrafenib plus Trametinib and Vemurafenib against BRAF, Gefitinib against EGFR, Everolimus against mTOR, vascular disruptors like Fosbretabulin, and immunotherapy with viz. Spartalizumab and Pembrolizumab, are anti-PD-1/PD-L1 molecules. Hence, several trials are currently evaluating the possible beneficial role of combinatorial therapy in TC. Since TC is the outcome of multiple genetic alterations, it necessitates targeting the multiple factors in a single shot. These combination strategies for systemically delivering therapeutic drugs seem feasible only with the help of theranostic. To date, nanoparticle-based drug delivery systems (NDDS) have devoted themselves to diagnosis, bioimaging, imaging-assisted surgery, and therapy with high success rates. The ease of handling hybrid technologies is also selectively admirable. However, in this review, we have summarized the sequential progression of chemotherapeutic drugs to NDDS designed for Personalized Medicine (PM) against TC. Personalized medicine is an ever-growing field that will be explored in future discoveries in biomedicine, particularly cancer theranostics. Hence, our review presents a closer view of NDDS as a personalized treatment for TC. We have also discussed the primary challenges facing NDDS in meeting excellence in PM.

Appraising the effectiveness of immune cells on thyroid cancer: a Mendelian randomization study

BACKGROUND

The intricate interplay between the immune system and tumor plays a pivotal role in thyroid cancer (TC) pathogenesis, potentially influencing both the causation and therapeutic outcomes. Despite extensive research, existing literature offers ambiguous insights regarding the association between immune cell traits and thyroid cancer progression.

METHODS

To elucidate the potential causal relationships, we conducted an integrated two-sample Mendelian randomization (MR) analysis. This study utilized publicly genetic datasets to explore the causalities between 731 immune cell traits (categorized into four trait types across seven panels) and thyroid cancer. We ensured the robustness of our findings through comprehensive sensitivity analyses, meticulously assessing potential sources of bias such as pleiotropy.

RESULTS

After False Discovery Rate (FDR) correction, six immune cell traits were identified to be significantly associated with thyroid cancer risk (Inverse Variance Weighted, IVW): Absolute count of gamma delta T cells/ T-cell receptor gamma delta absolute count (TCRgd AC) 0.8464 (OR95% CI = 0.7477-0.9580, P = 0.0083, PFDR = 0.0103); CD8 on bright CD8 cells (CD8 on CD8br) 0.8867 (OR95% CI = 0.8159-0.9637, P = 0.0047, PFDR = 0.0093); CD127 on CD45RA negative CD4 T cells not regulatory T cells (CD127 on CD45RA- CD4 not Treg) 0.8969 (OR95% CI = 0.8192-0.9820, P = 0.0186, PFDR = 0.0186); CD80 on CD62L positive plasmacytoid dendritic cells (CD80 on CD62L+ plasmacytoid DC) 1.1091 (OR95% CI = 1.0267-1.1982, P = 0.0086, PFDR = 0.0103); CD80 on plasmacytoid DC 1.1283 (OR95% CI = 1.0462-1.2168, P = 0.0017, PFDR = 0.0093); Side scatter-area on bright CD8 cells (SSC - A on CD8br) 1.1622 (OR95% CI = 1.0507-1.2854, P = 0.0035, PFDR = 0.0093).

CONCLUSIONS

Our study demonstrated the causalities between immune cell traits and thyroid cancers by Mendelian randomization study, thus guiding future mechanism studies.

Comprehensive Analysis Reveals That ISCA1 Is Correlated with Ferroptosis-Related Genes Across Cancers and Is a Biomarker in Thyroid Carcinoma

BACKGROUND

ISCA1 (Iron-Sulfur Cluster Assembly 1) is involved in the assembly of iron-sulfur (Fe-S) clusters, which are vital for electron transport and enzyme activity. Some studies suggest the potential involvement of ISCA1 in tumor progression through interactions with ferroptosis-related genes (FRGs) and the tumor immune microenvironment (TME). However, there has been no systematic analysis of its role in FRGs and the TME or its predictive value for prognosis and immunotherapy response across different cancer types.

METHODS

In this study, we analyzed the expression and prognosis of ISCA1 RNA, CNV, methylation, and protein in multiple tumor tissues via data from the TCGA and CPTAC databases and clinical information. We conducted a comprehensive analysis of the correlations between ISCA1 and FRGs, immune-related genes (including immune regulatory genes and immune checkpoint genes), immune cell infiltration, immune infiltration scores, tumor stemness, and genomic heterogeneity.

RESULTS

We performed drug prediction and validation through molecular docking and molecular dynamics analysis to identify candidate drugs that could promote or inhibit ISCA1 RNA expression. Our findings revealed that ISCA1 could serve as a biomarker in thyroid carcinoma, play a role with different FRGs in various cell types, and mediate different ligand-receptor pathways for cell-cell communication.

CONCLUSIONS

Overall, our study highlights the potential of ISCA1 as a novel biomarker for predicting prognosis and immunotherapeutic efficacy in thyroid carcinoma and suggests its potential for developing novel antitumor drugs or improving immunotherapy.

A computational approach to assessing the prognostic implications of BRAF and RAS mutations in patients with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer, posing a growing clinical challenge. PTC exhibits two age-related peaks, with established risk factors including family history and radiation exposure. Managing even low-risk, localized PTC cases remain complex, with growing interest in active surveillance as an alternative to immediate surgery. This study employed single-cell RNA sequencing (scRNA-Seq) to explore the predictive value of BRAF and RAS mutations in PTC, shedding light on their impact on disease progression and outcomes. The analyses emphasized the significance of BRAF and RAS mutations in tumor advancement, particularly the unique BRAF V600E mutation associated with aggressive features. The methodology involved scRNA-Seq analysis of PTC and normal samples, unveiling distinct cell clusters and indicating upregulated BRAF and RAS genes. Pathway enrichment analysis highlighted altered biological processes and immune-related pathways in PTC. The study consolidated previous research showing the prevalence of BRAF and RAS mutations in PTC, subtypes with distinct molecular profiles, and the impact of TERT promoter mutations on disease severity. In summary, this study unveils the complex interplay of genetic mutations and the cellular microenvironment in PTC through scRNA-Seq. The upregulated BRAF and RAS genes suggest their roles as PTC drivers, and pathway enrichment reveals alterations in immune-related processes. This synthesis of prior research enhances our understanding of PTC's molecular foundations, informing better prognosis and personalized treatment approaches. These insights advance the landscape of PTC management and provide directions for further research.

Impact of Hashimoto's thyroiditis on the tumor microenvironment in papillary thyroid cancer: insights from single-cell analysis

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.

The neurotransmitter calcitonin gene-related peptide shapes an immunosuppressive microenvironment in medullary thyroid cancer

Neurotransmitters are key modulators in neuro-immune circuits and have been linked to tumor progression. Medullary thyroid cancer (MTC), an aggressive neuroendocrine tumor, expresses neurotransmitter calcitonin gene-related peptide (CGRP), is insensitive to chemo- and radiotherapies, and the effectiveness of immunotherapies remains unknown. Thus, a comprehensive analysis of the tumor microenvironment would facilitate effective therapies and provide evidence on CGRP's function outside the nervous system. Here, we compare the single-cell landscape of MTC and papillary thyroid cancer (PTC) and find that expression of CGRP in MTC is associated with dendritic cell (DC) abnormal development characterized by activation of cAMP related pathways and high levels of Kruppel Like Factor 2 (KLF2), correlated with an impaired activity of tumor infiltrating T cells. A CGRP receptor antagonist could offset CGRP detrimental impact on DC development in vitro. Our study provides insights of the MTC immunosuppressive microenvironment, and proposes CGRP receptor as a potential therapeutic target.

Clinicopathological features affecting the efficacy in 131I ablation therapy of papillary thyroid carcinoma with lymph node metastasis

Background

Lymph node metastasis is the major cause of increased recurrence and death in patients with papillary thyroid carcinoma (PTC). We evaluate the clinicopathologic factors affecting excellent response (ER) in patients with PTC with lymph node metastasis following operation and 131I ablation therapy.

Methods

A total of 423 patients with PTC with lymph node metastasis who underwent thyroidectomy and postoperative 131I ablation therapy were enrolled. The relationship between clinicopathological factors affecting ER achievement was analyzed.

Results

Multivariate analysis showed that the foci diameter (≤1 cm), unifocal, combination with Hashimoto's thyroiditis (HT), lymph node metastases rate (LR) (≤40%), no postoperative lymph node metastasis, low preablative stimulated thyroglobulin (ps-Tg) level (≤3.87 ng/mL), and the time of 131I ablation therapy (one time) were positively correlated with the ER achievement [odds ratio (OR): 1.744, 3.114, 3.920, 4.018, 2.074, 9.767, and 49.491, respectively; all p < 0.05]. The receiver operating characteristic (ROC) curves showed that the cutoff values of ps-Tg and LR were 4.625 ng/mL and 50.50%, respectively. The AUC of ROC of ps-Tg and LR for predicting ER achievement was 0.821 and 0.746, respectively. The Tg and the cumulative risk of non-ER elevated with the increase of LR, especially for the high-level ps-Tg (>4.625 ng/mL) group.

Conclusion

The foci diameter and number, combination with HT, LR, and ps-Tg level are independent factors for ER. Ps-Tg level and LR are valid predictive factors for the efficacy of 131I therapy in patients with PTC. The predictive value of the cumulative risk of non-ER can be improved by the combination of ps-Tg and LR.

Increased Thyroid DPP4 Expression Is Associated With Inflammatory Process in Patients With Hashimoto Thyroiditis

CONTEXT

Dipeptidyl peptidase-4 (DPP4) is originally described as a surface protein in lymphocytes. Lymphocyte infiltration and subsequent destruction of thyroid tissue have been considered as the central pathological mechanism in Hashimoto thyroiditis (HT).

OBJECTIVE

The present study aimed to investigate DPP4 expression in peripheral blood and thyroid tissue in HT patients, and explore the role of DPP4 in the pathophysiological process of HT.

METHODS

This case-control study recruited 40 drug-naive HT patients and 81 control individuals. Peripheral blood and thyroid specimens were collected for assessing the expression and activity of DPP4. Moreover, single-cell RNA sequencing (scRNA-seq) analysis of 6 "para-tumor tissues" samples from scRNA-seq data set GSE184362 and in vitro cell experiments were also conducted.

RESULTS

The HT patients had similar DPP4 serum concentration and activity as the controls. However, the expression and activity of DPP4 was significantly increased in the thyroid of the HT group than in the control group. The scRNA-seq analysis showed that DPP4 expression was significantly increased in the HT group, and mainly expressed in T cells. Further in vitro studies showed that inhibition of lymphocyte DPP4 activity with sitagliptin downregulated the production of inflammatory factors in co-cultured thyroid cells.

CONCLUSION

DPP4 expression was significantly increased in the thyroid of the HT group compared with the control group, and was mainly localized in the lymphocytes. Inhibition of lymphocyte DPP4 activity reduced the production of inflammatory factors in co-cultured thyroid cells. Therefore, inhibition of DPP4 may have a beneficial effect by alleviating inflammatory reactions in HT patients.

TIM3 activates the ERK1/2 pathway to promote invasion and migration of thyroid tumors

BACKGROUND

This study aims to study the possible action mechanism of T-cell immunoglobulin and mucin domain 3 (TIM3) on the migratory and invasive abilities of thyroid carcinoma (TC) cells.

METHODS

GSE104005 and GSE138198 datasets were downloaded from the GEO database for identifying differentially expressed genes (DEGs). Functional enrichment analysis and protein-protein interaction (PPI) analysis were performed on the common DEGs in GSE104005 and GSE138198 datasets. Subsequently, in order to understand the effect of a common DEG (TIM3) on TC cells, we performed in vitro experiments using FRO cells. The migratory and invasive abilities of FRO cells were detected by wound scratch assay and Transwell assay. Proteins expression levels of the phosphorylated (p)-extracellular signal-regulated kinase (ERK)1/2, matrix metalloproteinase-2 (MMP-2) and MMP-9 were determined via Western blotting after ERK1/2 inhibition in TIM3-NC group and TIM3-mimic group.

RESULTS

316 common DEGs were identified in GSE104005 and GSE138198 datasets. These DEGs were involved in the biological process of ERK1 and ERK2 cascade. TIM3 was significantly up-regulated in TC. In vitro cell experiments showed that TIM3 could promote migration and invasion of TC cells. Moreover, TIM3 may affect the migration, invasive abilities of TC cells by activating the ERK1/2 pathway.

CONCLUSION

The above results indicate that TIM3 may affect the migratory and invasive of TC cells by activating the ERK1/2 pathway.

Research progress of immunotherapy against anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is the most aggressive type of thyroid cancer. While ATC is rare, its mortality is high. Standard treatments, such as surgery, radiotherapy, and chemotherapy, have demonstrated limited efficacy in managing ATC. However, the advent of immunotherapy has significantly improved the prognosis for patients with ATC. Immunotherapy effectively targets and eliminates tumor cells by using the power of the body's immune cells. The neoantigen is an atypical protein generated by somatic mutation, is exclusively observed in neoplastic cells, and is devoid of central tolerance. Neoantigens exhibit enhanced specificity towards tumor cells and display robust immunogenic properties. Currently, neoantigen therapy is primarily applied in immune checkpoint inhibitors and cellular immunotherapy, encompassing adoptive immunotherapy and tumor vaccines. This study discusses the mechanism, tumor microenvironment, clinical trials, adverse events, limitations and future directions associated with ATC immunotherapy.

Clinical value of ultrasound parameters PI, TTP, and MTT in assessing cervical lymph node metastasis of papillary thyroid carcinoma

OBJECTIVE

To determine the clinical value of ultrasound in assessing cervical lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC).

METHODS

The medical records of 179 PTC patients treated in Shandong Provincial Qianfoshan Hospital between March 2016 and March 2019 were collected. The patients were assigned to a transfer group (54 cases) and a non-transfer group (125 cases) according to their pathologic results. The ultrasound parameters (peak intensity (PI), time to peak (TTP), and mean transit time (MTT)) of the two groups were compared. Then, multivariate logistic regression was used to analysis the results, and receiver operating characteristic (ROC) curves were plotted to evaluate the value of risk factors in predicting CLNM.

RESULTS

The transfer group showed notably lower PI, TTP and MTT than the non-transfer group (P<0.001), and focus diameter, microcalcification, multiple foci, PI, TTP, and MTT were identified as independent risk factors for LNM in patients (P<0.05). According to the ROC curve, the areas under the curves (AUCs) of microcalcification, multiple foci, and PI were all smaller than 0.7; the AUCs of focus diameter and MTT were smaller than 0.8, and the AUC of TTP was 0.855.

CONCLUSION

PI, TTP, and MTT all decrease in PTC patients with CLNM, and TTP has a strong predictor for CLNM in them, with an AUC of 0.855.

TIPARP as a prognostic biomarker and potential immunotherapeutic target in male papillary thyroid carcinoma

BACKGROUND

Male patients with papillary thyroid carcinoma (PTC) tend to have poorer prognosis compared to females, partially attributable to a higher rate of lymph node metastasis (LNM). Developing a precise predictive model for LNM occurrence in male PTC patients is imperative. While preliminary predictive models exist, there is room to improve accuracy. Further research is needed to create optimized prognostic models specific to LNM prediction in male PTC cases.

METHODS

We conducted a comprehensive search of publicly available microarray datasets to identify candidate genes continuously upregulated or downregulated during PTC progression in male patients only. Univariate Cox analysis and lasso regression were utilized to construct an 11-gene signature predictive of LNM. TIPARP emerged as a key candidate gene, which we validated at the protein level using immunohistochemical staining. A prognostic nomogram incorporating the signature and clinical factors was developed based on the TCGA cohort.

RESULTS

The 11-gene signature demonstrated good discriminative performance for LNM prediction in training and validation datasets. High TIPARP expression associated with advanced stage, high T stage, and presence of LNM. A prognostic nomogram integrating the signature and clinical variables reliably stratified male PTC patients into high and low recurrence risk groups.

CONCLUSIONS

We identified a robust 11-gene signature and prognostic nomogram for predicting LNM occurrence in male PTC patients. We propose TIPARP as a potential contributor to inferior outcomes in males, warranting further exploration as a prognostic biomarker and immunotherapeutic target. Our study provides insights into the molecular basis for gender disparities in PTC.

Development and Validation of Potential Molecular Subtypes and Signatures of Thyroid Carcinoma Based on Aging-related Gene Analysis

BACKGROUND/AIM

Thyroid carcinoma (THCA) is a cancer of the endocrine system that most commonly affects women. Aging-associated genes play a critical role in various cancers. Therefore, we aimed to gain insight into the molecular subtypes of thyroid cancer and whether senescence-related genes can predict the overall prognosis of THCA patients.

MATERIALS AND METHODS

Thyroid carcinoma (THCA) transcriptome-related expression profiles were obtained from The Cancer Genome Atlas (TCGA) database. These profiles were randomly divided into training and validation subsets at a ratio of 1:1. Unsupervised clustering algorithms were used to compare differences between the two subtypes; prognosis-related senescence genes were used to further construct our prognostic models by univariate and multivariate Cox analyses and construct a nomogram to predict the 1-, 3-, and 5-year overall survival probability of THCA patients. In addition, we performed gene set enrichment analysis (GSEA) to predict the immune microenvironment and somatic mutations between the different risk groups. Finally, real-time PCR was used to verify the expression levels of key model genes.

RESULTS

The 'ConsensusClusterPlus' R package was used to cluster thyroid cancer into two categories (Cluster1 and Cluster2) on the basis of 46 differentially expressed aging-related genes (DE-ARGs); patients in Cluster1 demonstrated a better prognosis than those in Cluster2. Cox analysis was used to screen six prognosis-related DE-ARGs. Finally, our real-time PCR results confirmed our hypothesis.

CONCLUSION

Differences exist between the two subtypes of thyroid cancer that help guide treatment decisions. The six DE-ARG genes have a high predictive value for risk stratifying THCA patients.

Exploring the advances of single-cell RNA sequencing in thyroid cancer: a narrative review

Thyroid cancer, a prevalent form of endocrine malignancy, has witnessed a substantial increase in occurrence in recent decades. To gain a comprehensive understanding of thyroid cancer at the single-cell level, this narrative review evaluates the applications of single-cell RNA sequencing (scRNA-seq) in thyroid cancer research. ScRNA-seq has revolutionised the identification and characterisation of distinct cell subpopulations, cell-to-cell communications, and receptor interactions, revealing unprecedented heterogeneity and shedding light on novel biomarkers for therapeutic discovery. These findings aid in the construction of predictive models on disease prognosis and therapeutic efficacy. Altogether, scRNA-seq has deepened our understanding of the tumour microenvironment immunologic insights, informing future studies in the development of effective personalised treatment for patients. Challenges and limitations of scRNA-seq, such as technical biases, financial barriers, and ethical concerns, are discussed. Advancements in computational methods, the advent of artificial intelligence (AI), machine learning (ML), and deep learning (DL), and the importance of single-cell data sharing and collaborative efforts are highlighted. Future directions of scRNA-seq in thyroid cancer research include investigating intra-tumoral heterogeneity, integrating with other omics technologies, exploring the non-coding RNA landscape, and studying rare subtypes. Overall, scRNA-seq has transformed thyroid cancer research and holds immense potential for advancing personalised therapies and improving patient outcomes. Efforts to make this technology more accessible and cost-effective will be crucial to ensuring its widespread utilisation in healthcare.

A novel prognostic signature and immune microenvironment characteristics associated with disulfidptosis in papillary thyroid carcinoma based on single-cell RNA sequencing

Background: Disulfidptosis is a newly discovered form of regulated cell death. The research on disulfidptosis and tumor progression remains unclear. Our research aims to explore the relationship between disulfidptosis-related genes (DRGs) and the clinical outcomes of papillary thyroid carcinoma (PTC), and its interaction on the tumor microenvironment. Methods: The single-cell RNA seq data of PTC was collected from GEO dataset GSE191288. We illustrated the expression patterns of disulfidptosis-related genes in different cellular components in thyroid cancer. LASSO analyses were performed to construct a disulfidptosis associated risk model in TCGA-THCA database. GO and KEGG analyses were used for functional analyses. CIBERSORT and ESTIMATE algorithm helped with the immune infiltration estimation. qRT‒PCR and flow cytometry was performed to validate the hub gene expression and immune infiltration in clinical samples. Results: We clustered PTC scRNA seq data into 8 annotated cell types. With further DRGs based scoring analyses, we found endothelial cells exhibited the most relationship with disulfidptosis. A 4-gene risk model was established based on the expression pattern of DRGs related endothelial cell subset. The risk model showed good independent prognostic value in both training and validation dataset. Functional enrichment and genomic feature analysis exhibited the significant correlation between tumor immune infiltration and the signature. The results of flow cytometry and immune infiltration estimation showed the higher risk scores was related to immuno-suppressive tumor microenvironment in PTC. Conclusion: Our study exhibited the role of disulfidptosis based signature in the regulation of tumor immune microenvironment and the survival of PTC patients. A 4-gene prognostic signature (including SNAI1, STC1, PKHD1L1 and ANKRD37) was built on the basis of disulfidptosis related endothelial cells. The significance of clinical outcome and immune infiltration pattern was validated robustly.

Computational single cell oncology: state of the art

Single cell computational analysis has emerged as a powerful tool in the field of oncology, enabling researchers to decipher the complex cellular heterogeneity that characterizes cancer. By leveraging computational algorithms and bioinformatics approaches, this methodology provides insights into the underlying genetic, epigenetic and transcriptomic variations among individual cancer cells. In this paper, we present a comprehensive overview of single cell computational analysis in oncology, discussing the key computational techniques employed for data processing, analysis, and interpretation. We explore the challenges associated with single cell data, including data quality control, normalization, dimensionality reduction, clustering, and trajectory inference. Furthermore, we highlight the applications of single cell computational analysis, including the identification of novel cell states, the characterization of tumor subtypes, the discovery of biomarkers, and the prediction of therapy response. Finally, we address the future directions and potential advancements in the field, including the development of machine learning and deep learning approaches for single cell analysis. Overall, this paper aims to provide a roadmap for researchers interested in leveraging computational methods to unlock the full potential of single cell analysis in understanding cancer biology with the goal of advancing precision oncology. For this purpose, we also include a notebook that instructs on how to apply the recommended tools in the Preprocessing and Quality Control section.

New Insights into Immune Cells and Immunotherapy for Thyroid Cancer

Thyroid cancer (TC) is the most common endocrine malignancy worldwide, and the incidence of TC has gradually increased in recent decades. Differentiated thyroid cancer (DTC) is the most common subtype and has a good prognosis. However, advanced DTC patients with recurrence, metastasis and iodine refractoriness, as well as more aggressive subtypes such as poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC), still pose a great challenge for clinical management. Therefore, it is necessary to continue to explore the inherent molecular heterogeneity of different TC subtypes and the global landscape of the tumor immune microenvironment (TIME) to find new potential therapeutic targets. Immunotherapy is a promising therapeutic strategy that can be used alone or in combination with drugs targeting tumor-driven genes. This article focuses on the genomic characteristics, tumor-associated immune cell infiltration and immune checkpoint expression of different subtypes of TC patients to provide guidance for immunotherapy.

Mapping the tumor microenvironment in clear cell renal carcinoma by single-cell transcriptome analysis

Introduction: Clear cell renal cell carcinoma (ccRCC) is associated with unfavorable clinical outcomes. To identify viable therapeutic targets, a comprehensive understanding of intratumoral heterogeneity is crucial. In this study, we conducted bioinformatic analysis to scrutinize single-cell RNA sequencing data of ccRCC tumor and para-tumor samples, aiming to elucidate the intratumoral heterogeneity in the ccRCC tumor microenvironment (TME). Methods: A total of 51,780 single cells from seven ccRCC tumors and five para-tumor samples were identified and grouped into 11 cell lineages using bioinformatic analysis. These lineages included tumor cells, myeloid cells, T-cells, fibroblasts, and endothelial cells, indicating a high degree of heterogeneity in the TME. Copy number variation (CNV) analysis was performed to compare CNV frequencies between tumor and normal cells. The myeloid cell population was further re-clustered into three major subgroups: monocytes, macrophages, and dendritic cells. Differential expression analysis, gene ontology, and gene set enrichment analysis were employed to assess inter-cluster and intra-cluster functional heterogeneity within the ccRCC TME. Results: Our findings revealed that immune cells in the TME predominantly adopted an inflammatory suppression state, promoting tumor cell growth and immune evasion. Additionally, tumor cells exhibited higher CNV frequencies compared to normal cells. The myeloid cell subgroups demonstrated distinct functional properties, with monocytes, macrophages, and dendritic cells displaying diverse roles in the TME. Certain immune cells exhibited pro-tumor and immunosuppressive effects, while others demonstrated antitumor and immunostimulatory properties. Conclusion: This study contributes to the understanding of intratumoral heterogeneity in the ccRCC TME and provides potential therapeutic targets for ccRCC treatment. The findings emphasize the importance of considering the diverse functional roles of immune cells in the TME for effective therapeutic interventions.

Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell-cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

Reveal the potential molecular mechanism of circRNA regulating immune-related mRNA through sponge miRNA in the occurrence and immune regulation of papillary thyroid cancer

BACKGROUND

Papillary thyroid cancer (PTC) is the most common endocrine malignant tumour. The purpose of this study was to explore the potential molecular mechanism of circRNA regulating immune-related mRNA through sponge miRNA in the occurrence and immune regulation of PTC.

METHODS

All data were downloaded from public databases, such as GEO, Immport and TCGA. Differentially expressed (DE) mRNAs (DEmRNAs), DEmiRNAs and DEcircRNAs were identified using metaMA and limma packages. Subsequently, immune-related DEmRNAs were screened, and circRNA-miRNA-mRNA (ceRNA) regulatory network was constructed. In addition, functional annotation, protein-protein interaction (PPI) network construction, immune cell infiltration analysis and Pearson correlation analysis were performed. Finally, qRT-PCR validation and cell experiments were also performed.

RESULTS

In total, 2962 DEmRNAs, 78 DEmiRNAs and 51 DEcircRNAs were obtained. Subsequently, 195 immune-related DEmRNAs were obtained based on Immport database. Cytokine-cytokine receptor interaction was the only signalling pathway obtained in KEGG analysis. Then, 8 hub immune-related DEmRNAs were identified based on PPI network and CytoHubba plug-in. Subsequently, ceRNA sub-network containing hub immune-related DEmRNAs was extracted from ceRNA regulatory network. In ceRNA sub-network, hsa_circ_0082182-hsa-miR-18b-5p-FGF1/PDGFC, hsa_circ_0016404-hsa-miR-1275-FGF1/CTSB/IL13RA1, hsa_circ_0070100-hsa-miR-27a-3p/hsa-miR-27b-3p-TGFBR3, hsa_circ_0060055/hsa_circ_0038718-hsa-miR-150-3p-CXCL14, hsa_circ_0030427/hsa_circ_0002917-hsa-miR-22-3p-BMP7 and hsa_circ_0030427/hsa_circ_0002917-hsa-miR-125a-5p-LIFR axes were identified. Moreover, FGF1, PDGFC, CTSB, IL13RA1, TGFBR3, CXCL14, BMP7, LIFR, hsa-miR-125a-5p, hsa-miR-1275, hsa-miR-150-3p, hsa-miR-18b-5p and hsa-miR-27b-3p were also found to have good diagnostic accuracy and may be potential novel diagnostic markers for PTC. XCell analysis showed that the levels of immune cell infiltration (including Tregs, HSC, DC and Monocytes) were significantly different between the PTC and the control groups. Knockdown of the expression of hsa_circ_0082182 significantly inhibits the activity, proliferation, migration and invasion of TPC-1 cells.

CONCLUSION

Several circRNA-miRNA-mRNA axes identified in this study may be related to the occurrence, progression and survival of PTC. This lays a theoretical foundation for further understanding the molecular mechanism of PTC, and also contributes to clinical management and research.

The Immune Landscape of Papillary Thyroid Cancer in the Context of Autoimmune Thyroiditis

Simple Summary

The association between papillary thyroid cancer and Hashimoto’s thyroiditis went through a long-standing human debate recently elucidated by the establishment of a novel mouse model. Papillary thyroid carcinoma is an excellent model for studying the tumor immune microenvironment because it is naturally accompanied by immune cells, making it a good candidate for the treatment with immune checkpoint inhibitors.

Abstract

Papillary thyroid cancer (PTC) often co-occurs with Hashimoto’s thyroiditis, an association that has long been reported in clinical studies, remaining controversial. Experimental evidence has recently shown that pre-existing thyroiditis has a beneficial effect on PTC growth and progression by a distinctive expansion of effector memory CD8 T cells. Although the link between inflammation and PTC might involve different components of the immune system, a deep characterization of them which includes T cells, B cells and tertiary lymphoid structures, Mye-loid cells, Neutrophils, NK cells and dendritic cells will be desirable. The present review article considers the role of the adaptive and innate immune response surrounding PTC in the context of Hashimoto’s thyroiditis. This review will focus on the current knowledge by in vivo and in vitro studies specifically performed on animals’ models; thyroid cancer cells and human samples including (i) the dual role of tumor-infiltrating lymphocytes; (ii) the emerging role of B cells and tertiary lymphoid structures; (iii) the role of myeloid cells, dendritic cells, and natural killer cells; (iv) the current knowledge of the molecular biomarkers implicated in the complex link between thyroiditis and PTC and the potential implication of cancer immunotherapy in PTC patients in the context of thyroiditis.