Background Immune cells account for a large proportion of the tumour microenvironment in anaplastic thyroid carcinomas (ATCs). However, the expression pattern of immune-related genes (IRGs) in ATCs is unclear. Our study aimed to identify an immune-related signature indicating the dedifferentiation of thyroid cells. Methods We compared the differences in thyroid differentiation score (TDS), infiltration of immune cells and enriched pathways between ATCs and papillary thyroid carcinomas (PTCs) or normal thyroid tissues in the Gene Expression Omnibus database. Univariate and multivariable Cox analyses were used to screen prognosis-associated IRGs in The Cancer Genome Atlas database. After constructing a risk score, we investigated its predictive value for differentiation and survival by applying receiver operating characteristic and Kaplan–Meier curves. We further explored its associations with important immune checkpoint molecules, infiltrating immune cells and response to immunotherapy. Results Compared with PTCs or normal thyroid tissues, ATCs exhibited lower TDS values and higher enrichment of immune cells and activation of the inflammatory response. The quantitative analyses and immunohistochemical staining validated that most ATC cell lines and ATC tissues had higher expression of MMP9 and lower expression of SDC2 than normal thyroid samples and PTC. Higher risk scores indicates dedifferentiation and a worse prognosis. Additionally, the risk score was positively correlated with the immune checkpoint molecules PDL1, CTLA4, IDO1, and HAVCR2 and infiltration of multiple immune cells. Importantly, we found that the samples with higher risk scores tended to have a better response to immunotherapy than those with lower scores. Conclusion Our findings indicate that the risk score may not only contribute to the determination of differentiation and prognosis of thyroid carcinomas but also help the prediction of immune cells infiltration and immunotherapy response.

Background Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. The effect of traditional anti-tumor therapy is not ideal for the patients with recurrence, metastasis and radioiodine resistance. The abnormal expression of immune-related genes (IRGs) has critical roles in the etiology of PTC. However, the effect of IRGs on PTC prognosis remains unclear. Methods Based on The Cancer Genome Atlas (TCGA) and ImmPort databases, we integrated IRG expression profiles and progression-free intervals (PFIs) of PTC patients. First, we identified the differentially expressed IRGs and transcription factors (TFs) in PTC. Subsequently, an IRG model that can predict the PFI was constructed by using univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses of the differentially expressed IRGs in the TCGA. Additionally, a protein–protein interaction (PPI) network showed the interactions between the differentially expressed genes (DEGs), and the top 30 genes with the highest degree were extracted from the network. Then, the key IRG was identified by the intersection analysis of the PPI network and univariate Cox regression, which was verified the differential expression of by western blotting and immunohistochemistry (IHC). ssGSEA was performed to understand the correlation between the key IRG expression level and immune activity. Results A total of 355 differentially expressed IRGs and 43 differentially expressed TFs were identified in PTC patients. Then, eight IRGs were finally utilized to construct an IRG model. The respective areas under the curve (AUCs) of the IRG model reached 0.948, 0.820, and 0.831 at 1, 3 and 5 years in the training set. In addition, lactotransferrin (LTF) was determined as the key IRG related to prognosis. The expression level of LTF in tumor tissues was significantly lower than that in normal tissues. And the results of ssGSEA showed the expression level of LTF is closely related to immune activity. Conclusions These findings show that the prognostic model and key IRG may become promising molecular markers for the prognosis of PTC patients.

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

Background: To investigate reasonable treatment modalities and prognostic factors for patients with differentiated thyroid carcinoma (DTC) bone metastases (BM). Methods:The clinicopathological characteristics and follow-up data for all patients with DTC BM who

Background: Immune cells account for a large proportion of the tumour microenvironment in anaplastic thyroid carcinomas (ATCs). However, the expression pattern of immune-related genes (IRGs) in ATCs is unclear. Our study aimed to identify an immune-related signature indicating the dedifferentiation of thyroid cells.Methods: We compared the differences in thyroid differentiation score (TDS), infiltration of immune cells and enriched pathways between ATCs and papillary thyroid carcinomas (PTCs) or normal thyroid tissues in the Gene Expression Omnibus database. Univariate and multivariable Cox analyses were used to screen prognosis-associated IRGs in The Cancer Genome Atlas database. After constructing a risk score, we investigated its predictive value for differentiation and survival by applying receiver operating characteristic and Kaplan-Meier curves. We further explored its associations with important immune checkpoint molecules, infiltrating immune cells and response to immunotherapy. Results: Compared with PTCs or normal thyroid tissues, ATCs exhibited lower TDS values and higher enrichment of immune cells and activation of the inflammatory response. The quantitative analyses and immunohistochemical staining validated that most ATC cell lines and ATC tissues had higher expression of MMP9 and lower expression of SDC2 than normal thyroid samples and PTC. Higher risk scores indicates dedifferentiation and a worse prognosis. Additionally, the risk score was positively correlated with the immune checkpoint molecules PDL1, CTLA4, IDO1, and HAVCR2 and infiltration of multiple immune cells. Importantly, we found that the samples with higher risk scores tended to have a better response to immunotherapy than those with lower scores. Conclusion: Our findings indicate that the risk score may not only contribute to the determination of differentiation and prognosis of thyroid carcinomas but also help the prediction of immune cells infiltration and immunotherapy response.

Squamous cell carcinoma of the head and neck (HNSCC) is one of the six most common malignancies. HNSCC has both a high incidence and poor prognosis, and its prognostic factors remain unclear. Ferroptosis is a newly discovered form of programmed cell death that is iron-dependent. Increasing evidence indicates that targeting ferroptosis may present a new form of anti-tumor treatment. However, the prognostic value of ferroptosis-related genes (FRGs) in HNSCC is unclear. This study was designed to identify molecular markers associated with ferroptosis that influence prognosis in patients with HNSCC. We used HNSCC tumor and normal data from The Cancer Genome Atlas (TCGA) to identify prognosis-related FRGs. An FRG-based prognostic risk score was constructed, and its prognostic value for patients with HNSCC was evaluated using receiver operating characteristic curve (ROC) and nomogram analyses. The model was validated using the Gene Expression Omnibus (GEO) database. Univariate Cox regression analysis in patients with HNSCC revealed 11 FRGs that were significantly associated with overall survival (OS). We constructed a ferroptosis risk score model based on five genes and divided the patients into different risk groups based on its median value. Kaplan-Meier curve analysis showed that patients with a higher ferroptosis risk score had shorter OS (TCGA training set: P < 0.001, TCGA validation set: P < 0.05,GEO validation set: P < 0.001), and Gene Expression Profiling Interactive Analysis (GEPIA) further verified the relationships between these five genes and prognosis in patients with HNSCC. Multivariate Cox regression analysis showed that the risk score remained an independent predictor of OS after the exclusion of clinical confounders (HR > 1, P < 0.01). Significant differences in gene function enrichment analysis and immune cell infiltration status were identified between the two groups. The prognostic model can be used to predict the prognosis of patients with HNSCC. Moreover, the five FRGs may affect ferroptosis in HNSCC and thereby represent potential treatment targets. These results provide new directions for HNSCC treatment.

Background: Patients with well-differentiated thyroid carcinoma can achieve long-term survival after reasonable treatments, but there is no standard treatment mode for poorly or undifferentiated thyroid carcinoma and its prognosis is very poor. Immune cells, especially tumor-associated macrophages, account for a large proportion of the tumor microenvironment of anaplastic thyroid carcinomas (ATCs). However, whether immune-related genes can mediate the dedifferentiation of thyroid cells is unclear.Methods: We initially compared the differences of thyroid differentiation score, infitration of immune cells and enriched pathways between ATCs and papillary thyroid carcionma (PTCs) or normal thyroid tissues in Gene Expression Omnibus database. Then, The Cancer Genome Atlas database was used to screen out the prognosis associated IRGs. A risk score was constructed and we next investigated its predictive value for differentiation by applying receiver operating characteristic (ROC) curves and correlation analyses. Kaplan-Meier curves were used to evaluated its prognostic value. We further explored the associations of the risk score with important immune checkpoint molecules, infiltrating immune cells and response to immunotherapy.Results: Compared with PTCs or normal thyroid tissues, ATCs exhibited lower thyroid differentiation scores, higher infiltration of most immune cells and higher activation of inflammatory response. The risk score composed of MMP9 and SDC2 was significantly increased in ATCs and low differentiated PTCs. Moreover, it showed favorable predictive value for differentiation and survival. Higher risk score displayed dedifferentiation status and a worse prognosis. Additionly, the risk score was positively correlated with immune checkpoint molecules PDL1, CTLA4, IDO1, HAVCR2 and infiltration of multiple immune cells. Importantly, we found that samples with higher risk score tend to have a better response to immune checkpoint agents than lower ones.Conclusion: Our findings indicate that the risk score may not only contribute to the judgement of differentiation and prognosis of thyroid cancer, but also help to the prediction of immune cell infiltration and immune checkpoint inhibitor response.

Preceding studies have identified that noncoding RNA plays a significant role in the occurrence and development of tumors. Colorectal cancer (CRC) has attracted increasing attention due to its high incidence and mortality rate. Based on Cancer Genome Atlas (TCGA) database analysis, it was found that compared with normal tissues, HNF1A-AS1 and INHBA were highly expressed in CRC tissues; miR-214 was relatively low expressed, and it is predicted to specifically target the3' untranslated region (3'UTR region) of INHBA. Besides, the result was consistent with the quantitative reverse transcription PCR (RT-qPCR) verification results of 17 CRC cases and adjacent tissues collected clinically. Western Blot (WB) manifested that INHBA protein was highly expressed in CRC tissues, which was consistent with the results of CRC cell lines (HT29, SW480). Immunohistochemical (IHC) staining demonstrated that INHBA protein was brownish yellow, overwhelming majority of INHBA protein were located in the cytoplasm, and expression level was significantly higher than that in adjacent tissues. Based on previous studies, the biological process of INHBA-mediated TGF-β/Smad signaling pathway inducing the proliferation and invasion of CRC has been partially confirmed, but the upstream signaling molecules and mechanisms which regulating INHBA remain unclear. Herein, benefiting from bioinformatics, preliminary experimental results and previous research, they provide basis for the follow-up study on the regulation of HNF1A-AS1/miR-214/INHBA signal axis in CRC.