Knowledge mapping of anaplastic thyroid cancer treatments: a bibliometric analysis (2000-2023).

Context: Anaplastic thyroid cancer (ATC) is a relatively rare and extensively malignant kind of thyroid carcinoma. The poor prognosis and high mortality rate of ATC can be attributed to its invasive features and undifferentiated phenotype. At present, there is a lack of efficacious therapeutic options. In light of the elevated fatality rate, it is vital to possess a comprehensive comprehension of the scientific terrain pertaining to ATC. To gather the perspectives of different researchers about the topic of ATC treatment, we did a bibliometric network analysis, which offers a comprehensive view of the scholarly literature. Methodology: A systematic search was conducted on the WoSCC database to identify publications pertaining to ATC treatment between the years 2000 and 2023. In this bibliometric investigation, the tools VOSviewers, CiteSpace, and the R package "bibliometrix" were employed to investigate the general attributes, developmental framework, and academic frontiers of the subject matter. Results: 1223 publications in total, written by 6937 scholars from 53 areas and 1402 institutions and published in 358 scholarly journals, were analyzed. There has been a gradual increase in the quantity of publications pertaining to ATC treatment. The United States and China emerged as the most prominent nations. The University of Texas MD Anderson Cancer Center and Memorial Sloan Kettering Cancer Counseling Center are prominent research institutions in highly productive countries. The journal Thyroid holds a prominent position within its discipline, being widely recognized as both the most popular and highly co-cited publication. According to the available data, Maria Cabanillas has authored the highest number of published articles, while RC Smallridge has received the highest number of co-citations. It turned out that the prevailing keywords encompassed expression, therapy, apoptosis, survival, activation, proliferation, metastasis, and other related terms. Immunotherapy, targeted therapy, and prognostic factors are the emerging research hotspots and trends. Conclusions: This paper presents a complete overview of research trends and advancements in the treatment of ATC using bibliometric analysis. The acquisition of information will offer vital insights for funding and potential creative strategies in researching the treatment of ATC, which indicates the research frontiers as well as prevalent directions in recent years.

Isocitrate dehydrogenase 2 regulates the proliferation of triple-negative breast cancer through the ferroptosis pathway.

Triple-negative breast cancer (TNBC) is currently the type of breast cancer with the worst prognosis; it lacks specific treatments, such as ER/PR antagonistic endocrine and anti-HER2 targeted therapies. Although immunotherapy with immune checkpoints has shown some efficacy in many solid tumors, clinical data in TNBC suggest significant limitations. The essence of ferroptosis is the impaired metabolism of intracellular lipid oxides, which in turn causes the activation and abnormalities of the immune system, including ROS, and not only plays an important role in liver injury and organ aging but also a large amount of data points to the close correlation between the ferroptosis process and tumor development. In this study, through the analysis of large-throughput biological data of breast tumors, combined with the characteristics of the biological process of ferroptosis, the specific gene IDH2 was found to be significantly highly expressed in TNBC and functionally correlated with ferroptosis. Through clinical specimens validated at the gene and protein levels, in vitro tumor cell line validation, and in vivo mouse models, we found that the high expression of IDH2 in TNBC has a role in inhibiting the ferroptosis process in TNBC, thus promoting the proliferation of TNBC cells and other malignant features.

Comparison of lung ultrasound and chest radiography for detecting pneumonia in children: a systematic review and meta-analysis.

BACKGROUND: Lung ultrasound (LUS) is recommended as a reliable diagnostic alternative to chest X-ray (CXR) for detecting pneumonia in children. METHODS: PubMed, Embase, and Cochrane Library databases were used to identify eligible studies from their inception until April 2023. The investigated diagnostic parameters included sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the receiver operating characteristic curves (AUC). RESULTS: Twenty-six studies involving 3,401 children were selected for meta-analysis. The sensitivity, specificity, PLR, NLR, DOR, and AUC of LUS for detecting pneumonia in children were 0.95, 0.92, 12.31, 0.05, 108.53, and 0.98, respectively, while the sensitivity, specificity, PLR, NLR, DOR, and AUC of CXR were 0.92, 0.93, 24.63, 0.08, 488.54, and 0.99, respectively. The sensitivity of LUS was higher than that of CXR for detecting pneumonia in children (ratio: 1.03; 95% CI: 1.01-1.06; P = 0.018), whereas the DOR of LUS was significantly lower than that of CXR (ratio: 0.22; 95% CI: 0.06-0.85; P = 0.028). CONCLUSIONS: This study found that the diagnostic performance of LUS was comparable to that of CXR for detecting pneumonia, and the sensitivity of LUS was superior to that of CXR.

Detection and Differentiation of Xanthomonas translucens Pathovars translucens and undulosa from Wheat and Barley by Duplex Quantitative PCR.

Two probe-based quantitative PCR (qPCR) systems, namely P-Xtt and P-Xtu, were developed to diagnose cereal bacterial leaf streak pathogens Xanthomonas translucens pv. translucens and pv. undulosa, respectively. P-Xtt is specific to pv. translucens, and P-Xtu is specific to pv. undulosa, pv. cerealis, pv. secalis, and pv. pistaciae. P-Xtt and P-Xtu worked on all accessible strains of pv. translucens and pv. undulosa, respectively. Both systems could detect 100 copies of the target gBlock DNA. The two systems could be used in both singleplex qPCR and duplex qPCR with similar efficiencies. On genomic DNA from strains of various X. translucens pathovars, both singleplex and duplex qPCR could specifically detect and differentiate pv. translucens and pv. undulosa. The duplex qPCR could detect pv. translucens and pv. undulosa from genomic DNA of 1,000 bacterial cells. On infected barley and wheat grain samples and on one infected wheat leaf sample, the duplex qPCR showed similar efficiency compared to a previously published qPCR system but with the additional capability of pathovar differentiation. The duplex qPCR system developed in this study will be useful in studies on bacterial leaf streak and detection/differentiation of the pathogens.

Role of macrophage colony stimulating factor and interferon regulatory factor 7 in modulating the immune profile of mouse testicular macrophages.

Testicular macrophages (TM) are critical for the function of the testis by regulating homeostasis and inflammatory responses. However, the mechanisms by which TM fulfil these roles remain elusive. In this study, we explored the impact of two key testicular microenvironmental factors, namely 25-hydroxycholesterol (25HC), an oxysterol related to sex hormones and macrophage colony-stimulating factor (M-CSF), a factor crucial for macrophage survival and differentiation, on the regulation of the TM phenotype. Specifically, we examined their role in controlling the expression of the transcription factor interferon regulatory factor 7 (Irf7), a factor critical for maintaining the alternative macrophage phenotype. To achieve this, we used an in vitro bone marrow-derived macrophage (BMDM) model as a surrogate for TM to investigate the roles of 25HC and M-CSF in regulating the expression of Irf7 during the polarization of murine TM. M-CSF was identified as the main regulator of Irf7 expression, while 25HC production is a consequence of Irf7 activation in BMDM. In turn, 25HC plays a role in a negative feedback loop on the expression levels of Irf7 in BMDM. Using flow cytometry in Irf7-/- mouse testis the CD64loMHChi TM subpopulation was found to be decreased. Together with lower IL-10 protein levels in Irf7-/- TM this indicates a shift towards an M1-like macrophage profile. In summary, our data indicates that M-CSF could act as an inducer of high Irf7 expression levels in the mouse testis. However, the exact role of the high 25HC concentration in the testis in maintaining the local immune milieu still needs further study.

Couples' skills training intervention in young breast cancer patients with fear of cancer recurrence: A randomized controlled trial.

PURPOSE: This study adapted the Chinese version of the Couple Skills Training intervention program to couples of young breast cancer patients in China and investigated its effects on fear of cancer recurrence (FCR), cancer-related communication, and level of hope among the couples. METHODS: Ninety young breast cancer patients and their spouses were recruited and randomly assigned to the intervention group (45 couples) and the control group (45 couples). Couples in the intervention group received skills training and were assessed at baseline, post-intervention, and 3 months post-intervention to measure outcomes. Differences in scores between the two groups were analyzed using two-sample t-tests and generalized estimating equations (GEE) controlling for demographic and health-related variables. RESULTS: Couples' skills training intervention effectively reduced FCR and improved cancer-related communication in young breast cancer patients compared to the control group (both p < 0.001). Spouses' expectations significantly increased (p < 0.001). At 3 months post-intervention, couples in the intervention group showed significant improvements in FCR, cancer-related communication, and hope (all p < 0.001). CONCLUSION: Couples' skills training interventions are beneficial for helping young breast cancer patients cope with FCR. Couples-based interventions play a crucial role in addressing FCR in these patients and their spouses. Future research should consider larger samples and longer follow-up periods to enhance intervention effectiveness. CLINICAL TRIAL CENTER REGISTRATION NUMBER: This study has also been registered with the Chinese Clinical Trial Registry (No: ChiCTR2200063327).

RL-LABEL: A Deep Reinforcement Learning Approach Intended for AR Label Placement in Dynamic Scenarios.

Labels are widely used in augmented reality (AR) to display digital information. Ensuring the readability of AR labels requires placing them in an occlusion-free manner while keeping visual links legible, especially when multiple labels exist in the scene. Although existing optimization-based methods, such as force-based methods, are effective in managing AR labels in static scenarios, they often struggle in dynamic scenarios with constantly moving objects. This is due to their focus on generating layouts optimal for the current moment, neglecting future moments and leading to sub-optimal or unstable layouts over time. In this work, we present RL-LABEL, a deep reinforcement learning-based method intended for managing the placement of AR labels in scenarios involving moving objects. RL-LABEL considers both the current and predicted future states of objects and labels, such as positions and velocities, as well as the user's viewpoint, to make informed decisions about label placement. It balances the trade-offs between immediate and long-term objectives. We tested RL-LABEL in simulated AR scenarios on two real-world datasets, showing that it effectively learns the decision-making process for long-term optimization, outperforming two baselines (i.e., no view management and a force-based method) by minimizing label occlusions, line intersections, and label movement distance. Additionally, a user study involving 18 participants indicates that, within our simulated environment, RL-LABEL excels over the baselines in aiding users to identify, compare, and summarize data on labels in dynamic scenes.

Multi-scale feature fusion for pavement crack detection based on Transformer.

Automated pavement crack image segmentation presents a significant challenge due to the difficulty in detecting slender cracks on complex pavement backgrounds, as well as the significant impact of lighting conditions. In this paper, we propose a novel approach for automated pavement crack detection using a multi-scale feature fusion network based on the Transformer architecture, leveraging an encoding-decoding structure. In the encoding phase, the Transformer is leveraged as a substitute for the convolution operation, which utilizes global modeling to enhance feature extraction capabilities and address long-distance dependence. Then, dilated convolution is employed to increase the receptive field of the feature map while maintaining resolution, thereby further improving context information acquisition. In the decoding phase, the linear layer is employed to adjust the length of feature sequence output by different encoder block, and the multi-scale feature map is obtained after dimension conversion. Detailed information of cracks can be restored by fusing multi-scale features, thereby improving the accuracy of crack detection. Our proposed method achieves an F1 score of 70.84% on the Crack500 dataset and 84.50% on the DeepCrack dataset, which are improvements of 1.42% and 2.07% over the state-of-the-art method, respectively. The experimental results show that the proposed method has higher detection accuracy, better generalization and better crack detection results can be obtained under both high and low brightness conditions.

An enzyme-free method for isolating testicular macrophages from rodent models.

Macrophages are the major type of immune cell in the testis of both humans and rodents. Testicular macrophages (TMs) play critical roles in maintaining the testicular microenvironment, such as Leydig cell-dependent hormone production, spermatogenesis, and immune balance. A substantial number of studies have used rodent models to investigate the functions of TMs with various methods and harvest macrophages from the testis. Studies have demonstrated that enzyme digestion, an essential part of these methods, can improve the number and purity of TMs while unavoidably altering the immunoprofile of macrophages, which is detrimental for further study in terms of immune investigation. Here, we modified the existing method of microglia isolation and set up a novel method without the enzyme digestion step to isolate TMs. According to the characteristics of testicular tissue looseness and the physical and biological characteristics of macrophages, by combining mechanical separation, gradient centrifugation, and immuno-magnetic bead selection, we can effectively avoid the enzymatic digestion of testis tissue and maintain the immune characteristics of macrophages. Additionally, we verified the purity of TM with flow cytometry (FC) at approximately 91-95%, and the production of tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6) was lower than that isolated with enzyme digestion. In contrast to the traditional method, this novel protocol can assist those who have no convenient access to fluorescence-activated cell sorting (FACS) to isolate a sufficient number of TMs and, most importantly, avoid altering the immunoprofile of TMs without enzyme digestion.

Exploration of epithelial-mesenchymal transition-related lncRNA signature and drug sensitivity in breast cancer.

Background: Breast cancer (BRCA) has become the most diagnosed cancer worldwide for female and seriously endanger female health. The epithelial-mesenchymal transition (EMT) process is associated with metastasis and drug resistance in BRCA patients. However, the prognostic value of EMT-related lncRNA in BRCA still needs to be revealed. The aim of this study is to construct an EMT-related lncRNA (ERL) signature with accuracy predictive ability for the prognosis of BRCA patients. Methods: RNA-seq expression data and Clinical characteristics obtained from the TCGA (The Cancer Genome Atlas) were used in the study. First, we identified the EMT-related lncRNA by the Pearson correlation analysis. An EMT-related lncRNAs prognostic risk signature was constructed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was validated using Kaplan-Meier (KM) survival analysis, ROC curve and C-index. Finally, a nomogram was constructed for clinical practice in evaluating the patients with BRCA and validated by calibration curve and decision curve analysis (DCA). We also evaluated the drug sensitivity of signature lncRNA and the tumor immune cell infiltration in breast cancer. Results: We constructed a 10-lncRNA risk score signature based on the lncRNAs associated with the EMT process. We could assign BRCA patients to the high- and low-risk group according to the median risk score. The prognostic risk signature showed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of the immune cell subtype. Drug sensitivity analysis proved ERLs signature could effectively predict the sensitivity of patients to common chemotherapy drugs in BRCA and provide guidance for chemotherapy drugs for high-risk and low-risk patients. Conclusion: Our ERL signature and nomogram have excellent prognostic value and could become reliable tools for clinical guidance.

This is the Table I Want! Interactive Data Transformation on Desktop and in Virtual Reality.

Data transformation is an essential step in data science. While experts primarily use programming to transform their data, there is an increasing need to support non-programmers with user interface-based tools. With the rapid development in interaction techniques and computing environments, we report our empirical findings about the effects of interaction techniques and environments on performing data transformation tasks. Specifically, we studied the potential benefits of direct interaction and virtual reality (VR) for data transformation. We compared gesture interaction versus a standard WIMP user interface, each on the desktop and in VR. With the tested data and tasks, we found time performance was similar between desktop and VR. Meanwhile, VR demonstrates preliminary evidence to better support provenance and sense-making throughout the data transformation process. Our exploration of performing data transformation in VR also provides initial affirmation for enabling an iterative and fully immersive data science workflow.

T cells, NK cells, and tumor-associated macrophages in cancer immunotherapy and the current state of the art of drug delivery systems.

The immune system provides full protection for the body by specifically identifying 'self' and removing 'others'; thus protecting the body from diseases. The immune system includes innate immunity and adaptive immunity, which jointly coordinate the antitumor immune response. T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are the main tumor-killing immune cells active in three antitumor immune cycle. Cancer immunotherapy focusses on activating and strengthening immune response or eliminating suppression from tumor cells in each step of the cancer-immunity cycle; thus, it strengthens the body's immunity against tumors. In this review, the antitumor immune cycles of T cells, natural killer (NK) cells and tumor-associated macrophages (TAMs) are discussed. Co-stimulatory and co-inhibitory molecules in the three activity cycles and the development of drugs and delivery systems targeting these molecules are emphasized, and the current state of the art of drug delivery systems for cancer immunotherapy are summarized.

The E3 ligase HERC5 promotes antimycobacterial responses in macrophages by ISGylating the phosphatase PTEN.

Innate immune signaling in macrophages during viral infection is regulated by ISGylation, the covalent attachment of the ubiquitin-like protein interferon-stimulated gene 15 (ISG15) to protein targets. Here, we explored the role of ISGylation in the macrophage response to infection with Mycobacterium tuberculosis. In human and mouse macrophages, the E3 ubiquitin ligases HERC5 and mHERC6, respectively, mediated the ISGylation of the phosphatase PTEN, which promoted its degradation. The decreased abundance of PTEN led to an increase in the activity of the PI3K-AKT signaling pathway, which stimulated the synthesis of proinflammatory cytokines. Bacterial growth was increased in culture and in vivo when human or mouse macrophages were deficient in the major E3 ISG15 ligase. The findings expand the role of ISGylation in macrophages to antibacterial immunity and suggest that HERC5 signaling may be a candidate target for adjunct host-directed therapy in patients with tuberculosis.

Prophylactic Central Neck Dissection Based on Preoperative Imaging and Intraoperative Surgeon's Palpation Versus Total Thyroidectomy Alone for Papillary Thyroid Cancer.

INTRODUCTION: To compare the overall morbidity and recurrence of papillary thyroid cancer (PTC) after total thyroidectomy (TT) with or without prophylactic central compartment neck dissection (CCND) in cases of both preoperative and intraoperative nonsuspicious central lymph nodes (CLNs). METHODS: A total of 570 PTC patients who harbored no preoperative and intraoperative suspicious CLNs at two institutions were enrolled. They were randomly assigned to TT alone or TT with prophylactic CCND (pCCND) after intraoperative assessment of CLNs during the surgery. Lymph nodes that were hard or large enough to be palpated were regarded as suspicious metastatic lymph nodes during the surgery. The characteristics, postoperative complications, and locoregional recurrence of the two groups were recorded and compared. RESULTS: With a median follow-up of 5 y, the rates of lymph node recurrence in the TT alone and TT with pCCND groups were similar (7.3% versus 4.6%, P = 0.247), but there were significantly higher rates of overall morbidity (6.6% versus 19.1%, P < 0.001) when pCCND was performed. CONCLUSIONS: pCCND is not recommended for patients with clinically node-negative PTC preoperatively and intraoperatively because of the high complication rate and lack of benefit of reducing recurrence.

The Ball is in Our Court: Conducting Visualization Research With Sports Experts.

Most sports visualizations rely on a combination of spatial, highly temporal, and user-centric data, making sports a challenging target for visualization. Emerging technologies, such as augmented and mixed reality (AR/XR), have brought exciting opportunities along with new challenges for sports visualization. We share our experience working with sports domain experts and present lessons learned from conducting visualization research in SportsXR. In our previous work, we have targeted different types of users in sports, including athletes, game analysts, and fans. Each user group has unique design constraints and requirements, such as obtaining real-time visual feedback in training, automating the low-level video analysis workflow, or personalizing embedded visualizations for live game data analysis. In this article, we synthesize our best practices and pitfalls we identified while working on SportsXR. We highlight lessons learned in working with sports domain experts in designing and evaluating sports visualizations and in working with emerging AR/XR technologies. We envision that sports visualization research will benefit the larger visualization community through its unique challenges and opportunities for immersive and situated analytics.

Development of a Duplex qPCR System for Detection and Quantification of the Two Canola Blackleg Pathogens Leptosphaeria biglobosa and L. maculans.

Two probe-based qPCR systems, namely P-Lb and P-Lm, specific to the canola blackleg pathogens Leptosphaeria biglobosa and L. maculans, respectively, were developed, and their efficiencies were tested. Each of the two systems targets a single-copy gene exclusively present in the corresponding species. The specificities of the two systems on the species level and their ubiquities on the subspecies level were confirmed by in silico sequence analyses and testing on L. biglobosa (17 strains), L. maculans (10 strains), and other plant pathogens (31 species). For sensitivities, the two systems were tested on synthesized DNA fragments (gBlock) of the targeted regions, from which a standard curve was generated for each system. In addition, standard curves were also generated on gBlocks for duplex qPCR in which the two systems were used in the same reaction. The two systems were further tested in both singleplex and duplex qPCR on DNA samples extracted from fungal spores, inoculated canola cotyledons, and naturally infected canola stubble samples collected from commercial fields. Our data indicated that the two systems are specific to L. biglobosa and L. maculans, respectively, and one reaction could detect as few as 200 spores of either species. When used in duplex qPCR on DNA samples with various origins, the two systems generated similar results as in singleplex qPCR. The duplex qPCR system, along with the sample preparation and DNA extraction specified in this study, constituted a first-reported duplex qPCR protocol for detection and quantification of the two blackleg pathogens from field samples.

Development of the expression and prognostic significance of m5 C-related LncRNAs in breast cancer.

BACKGROUND: 5-Methylcytosine (m5C) methylation is a major epigenetic RNA modification and is closely related to tumorigenesis in various cancers. This study aimed to explore the prognostic value of m5C-related lncRNAs in breast cancer. METHODS: Clinical characteristics and RNA-seq expression data from TCGA (The Cancer Genome Atlas) were used in the study. First, we performed differentially expressed gene (DEG) analysis and constructed a PPI network for the 12 m5C regulators. Then, we identified the m5C-related LncRNAs by the "cor. test." An m5C-related lncRNA prognostic risk signature was developed using univariate Cox regression and Lasso-penalized Cox regression analyses. The model's performance was determined using Kaplan-Meier (KM) survival analysis and ROC curves. Finally, a nomogram was constructed for clinical application in evaluating patients with BRCA. We also researched the drug sensitivity of signature lncRNAs and immune cell infiltration. Finally, we validated the expression of the signature lncRNAs through qRT-PCR in a breast cancer cell line and a breast epithelial cell line. RESULTS: Overall, we constructed an 11-lncRNA risk score signature based on the lncRNAs associated with m5C regulators. According to the median risk score, we divided BRCA patients into high- and low-risk groups. The prognostic risk signature displayed excellent accuracy and demonstrated sufficient independence from other clinical characteristics. The immune cell infiltration analysis showed that the prognostic risk signature was related to the infiltration of immune cell subtypes. Drug sensitivity proved that our prognostic risk signature potentially has therapeutic value. CONCLUSIONS: The m5C-related lncRNA signature reliably predicted the prognosis of breast cancer patients and may provide new insight into the breast cancer tumor immune microenvironment.

Labeling Out-of-View Objects in Immersive Analytics to Support Situated Visual Searching.

Augmented Reality (AR) embeds digital information into objects of the physical world. Data can be shown in-situ, thereby enabling real-time visual comparisons and object search in real-life user tasks, such as comparing products and looking up scores in a sports game. While there have been studies on designing AR interfaces for situated information retrieval, there has only been limited research on AR object labeling for visual search tasks in the spatial environment. In this article, we identify and categorize different design aspects in AR label design and report on a formal user study on labels for out-of-view objects to support visual search tasks in AR. We design three visualization techniques for out-of-view object labeling in AR, which respectively encode the relative physical position (height-encoded), the rotational direction (angle-encoded), and the label values (value-encoded) of the objects. We further implement two traditional in-view object labeling techniques, where labels are placed either next to the respective objects (situated) or at the edge of the AR FoV (boundary). We evaluate these five different label conditions in three visual search tasks for static objects. Our study shows that out-of-view object labels are beneficial when searching for objects outside the FoV, spatial orientation, and when comparing multiple spatially sparse objects. Angle-encoded labels with directional cues of the surrounding objects have the overall best performance with the highest user satisfaction. We discuss the implications of our findings for future immersive AR interface design.

Weighted gene co-expression network reveals driver genes contributing to phenotypes of anaplastic thyroid carcinoma and immune checkpoint identification for therapeutic targets.

Background: Anaplastic thyroid carcinoma (ATC) is a rare but extremely malignant tumor, with a rapid growth rate and early metastasis thus leading to poor survival of patients. The molecular mechanisms underlying these aggressive traits of ATC remain unknown, which impedes the substantial progress in treatment to prolong ATC patient survival. Methods: We applied weighted gene co-expression network analysis (WGCNA) to identify ATC-specific modules. The Metascape web and R package clusterProfiler were employed to perform enrichment analysis. Combined with differentially expressed gene analysis, we screened out the most potential driver genes and validated them using receiver operator characteristic (ROC) analysis, quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blotting, immunohistochemistry (IHC), and triple immunofluorescence staining. Results: A gene expression matrix covering 75 normal samples, 83 papillary thyroid carcinoma (PTC), 26 follicular thyroid carcinoma (FTC), 19 poor-differentiated thyroid carcinoma (PDTC), and 41 ATC tissue samples were integrated, based on which we detected three most potential ATC-specific modules and found that hub genes of these modules were enriched in distinct biological signals. Hub genes in the turquoise module were mainly enriched in mitotic cell cycle, tube morphogenesis, and cell differentiation, hub genes in the magenta module were mainly clustered in the extracellular matrix organization, positive regulation of cell motility, and regulation of Wnt signaling pathway, while hub genes in the blue module primarily participated in the inflammatory response, innate immune response, and adaptive immune response. We showed that 9 top genes, 8 transcription factors (TFs), and 4 immune checkpoint genes (ICGs) were differentially expressed in ATC compared to other thyroid samples and had high diagnostic values for ATC, among which, 9 novel ATC-specific genes (ADAM12, RNASE2, CASP5, KIAA1524, E2F7, MYBL1, SRPX2, HAVCR2, and TDO2) were validated with our clinical samples. Furthermore, we illustrated that ADAM12, RNASE2, and HAVCR2 were predominantly present in the cytoplasm. Conclusion: Our study identified a set of novel ATC-specific genes that were mainly related to cell proliferation, invasion, metastasis, and immunosuppression, which might throw light on molecular mechanisms underlying aggressive phenotypes of ATC and provide promisingly diagnostic biomarkers and therapeutic targets.