CTHRC1 promotes anaplastic thyroid cancer progression by upregulating the proliferation, migration, and invasion of tumor cells.

Anaplastic thyroid carcinoma (ATC) is an extremely aggressive tumor with a high mortality rate and poor prognosis. However, the pathogenesis of ATC is complex and poorly understood, and the effective treatment options are limited. Analysis of data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases showed that collagen triple helix repeat containing-1 (CTHRC1) was specifically upregulated in ATC tissues and was negatively correlated with overall survival (OS) in thyroid carcinoma patients. In vitro knockdown of CTHRC1 dramatically decreased the proliferation, migration, and invasion abilities of ATC cells, and in vivo studies in BALB/c nude mice confirmed that CTHRC1 knockdown significantly inhibited tumor growth. Mechanistically, CTHRC1 knockdown was found to suppress the Wnt/ß-catenin pathway and epithelial-mesenchymal transition (EMT) at the protein level. These findings suggest that CTHRC1 promotes the progression of ATC via upregulating tumor cell proliferation, migration, and invasion, which may be achieved by activating the Wnt/ß-catenin pathway and EMT.

Learning Curve of Robot-Assisted Lymph Node Dissection of the Left Recurrent Laryngeal Nerve: A Retrospective Study of 417 Patients.

OBJECTIVE: Left recurrent laryngeal nerve (no.106recL) lymph node dissection is a challenging procedure, and robotic-assisted minimally invasive esophagectomy (RAMIE) may have some advantages. This study aimed to determine the learning curve of no.106recL lymph node dissection. METHODS: The data of 417 patients who underwent McKeown RAMIE between June 2017 and June 2022 were retrospectively analyzed. The lymph node harvest of no.106recL was used to determine the learning curve, and the cumulative sum (CUSUM) method was employed to obtain the inflection point. RESULTS: A total of 404 patients (404/417, 96.9%) underwent robotic surgery. Based on the number of no.106recL lymph nodes harvested, the CUSUM learning curve was mapped and divided into three phases: phase I (1‒75 cases), phase II (76‒240 cases), and phase III (241‒404 cases). The median (IQR) number of no.106recL lymph node harvests were 1 (4), 3 (6,) and 4 (4) in each phase (p < 0.001). The lymph node dissection rate gradually increased from 62.7% in phase I to 82.9% in phase III (p = 0.001). The total and thoracic lymph node harvest gradually increased (p < 0.001), whereas operation time (p = 0.001) and blood loss gradually decreased (p < 0.001). Moreover, the incidence of total complication (p = 0.020) and recurrent laryngeal nerve injury (p = 0.001) significantly decreased, and the postoperative hospital stay gradually shortened (p < 0.001). CONCLUSION: Robotic no.106recL lymph node dissection has some advantages for patients with esophageal cancer. In this study, perioperative and clinical outcomes were significantly improved over the learning curve. However, further prospective studies are required to confirm our results.

Single-Cell RNA Sequencing Revealed a 3-Gene Panel Predicted the Diagnosis and Prognosis of Thyroid Papillary Carcinoma and Associated With Tumor Immune Microenvironment.

Objective: The objective of this research was to screen prognostic related genes of thyroid papillary carcinoma (PTC) by single-cell RNA sequencing (scRNA-seq), to construct the diagnostic and prognostic models based on The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) data, and to evaluate the association between tumor immune microenvironment and the prognostic model. Method: The differentially expressed genes (DEGs) and tumor evolution were analyzed by scRNA-seq based on public databases. The potential regulatory networks of DEGs related to prognosis were analyzed by multi-omics data in the THCA. Logistic regression and Cox proportional hazards regression were utilized to construct the diagnosis and prognostic model of PTC. The performance of the diagnostic model was verified by bulk RNA sequencing (RNA-seq) of our cohort. The tumor immune microenvironment associated with the prognostic model was evaluated using multi-omics data. In addition, qRT-PCR was performed on tumor tissues and adjacent normal tissues of 20 patients to verify the expression levels of DEGs. Results: The DEGs screened by scRNA-seq can distinguish between tumor and healthy samples. DEGs play different roles in the evolution from normal epithelial cells to malignant cells. Three DEGs ((FN1, CLU, and ANXA1)) related to prognosis were filtered, which may be regulated by DNA methylation, RNA methylation (m6A) and upstream transcription factors. The area under curve (AUC) of the diagnostic model based on 3-gene in the validation of our RNA-seq was 1. In the prognostic model based on 3-gene, the overall survival (OS) of high-risk patients was shorter. Combined with the clinical information of patients, a nomogram was constructed by using tumor size (pT) and risk score to quantify the prognostic risk. The age and tumor size of high-risk patients in the prognostic model were greater. In addition, the increase of tumor mutation burden (TMB) and diversity of T cell receptor (TCR), and the decrease of CD8+ T cells in high-risk group suggest the existence of immunosuppressive microenvironment. Conclusion: We applied the scRNA-seq pipeline to focus on epithelial cells in PTC, simulated the process of tumor evolution, and revealed a prognostic prediction model based on 3 genes, which is related to tumor immune microenvironment.

Central Compartment Lymph Nodes Have Distinct Metastatic Patterns in Different Age Groups.

BACKGROUND AND PURPOSE: Central compartment lymph node metastasis (CLNM) is a manifestation of tumor aggressiveness and an indicator of tumor prognosis. The purpose of this study was to construct a nomogram for evaluating CLNM patterns in papillary thyroid carcinoma (PTC) in different age groups. METHOD: A total of 907 patients diagnosed with PTC from August 2014 to December 2018 were enrolled. A nomogram illustrating CLNM was generated using the results of multivariate logistic regression analysis. RESULTS: According to the best Youden index, we set the cut-off age at 45 years. Multivariate logistic regression analysis showed that in patients aged <45 years, large tumor size (P<0.05), extra-thyroid extension (P<0.05) and thyroglobulin level >40 ng/ml (OR=2.985, 95% CI 1.379-6.462; P<0.05) were independent risk factors; meanwhile, Hashimoto's thyroiditis (OR=0.532, 95% CI 0.324-0.874; P<0.05) was a protective factor of CLNM. In the subgroup with age ≥45 years, large tumor size (P<0.05), extra-thyroid extension (P<0.05), unclear margin (OR=1.604, 95% CI 1.065-2.416; P<0.05), male gender (OR=2.009, 95% CI 1.257-3.212; P<0.05) were independent risk factors for CLNM. In the subgroup with age <45 years, an area under the curve (AUC) of 0.729 (95% CI 0.680-0.777); P<0.05) was obtained. In the ≥45 years subgroup, the AUC was 0.668 (95% CI 0.619-0.716; P<0.05). CONCLUSION: CLNM of PTC in different age groups may have distinct patterns. Based on the potential risk factors for CLNM in patients with different age stratification, a user-friendly predictive model was established.

Integrated bioinformatics analysis for the identification of key genes and signaling pathways in thyroid carcinoma.

Thyroid carcinoma (TC) is one of the most common types of endocrine neoplasm with poor prognosis due to its aggressive behavior. Biomarkers for early diagnosis and prevention of TC are in urgent demand. By using a bioinformatics analysis, the present study aimed to identify essential genes and pathways associated with TC. First, the GSE27155 and GSE50901 expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were obtained using the two microarray datasets and further subjected to integrated analysis. A gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed 45 common DEGs in the two datasets. GO and KEGG pathway analysis indicated that the biological functions of the DEGs included protein binding, cardiac muscle cell potential involved in contraction, aldehyde dehydrogenase activity, the TGF-ß receptor signaling pathway and the canonical Wnt signaling pathway. A protein-protein interaction network was also constructed and visualized to display the nodes of the top 9 up- and 36 downregulated common DEGs. The integrated bioinformatics analysis indicated that potassium inwardly rectifying channel subfamily J member 2 (KCNJ2) was the most significantly upregulated DEG. The transcriptional levels of KCNJ2 were confirmed to be elevated in TC tissues compared with those in normal tissues using reverse transcription-quantitative PCR analysis. Furthermore, the expression level of KCNJ2 was significantly associated with the 5-year survival rate of patients with TC, which was determined using the Kaplan-Meier method. In TC cell lines, KCNJ2 was also upregulated as compared with that in a normal control cell line. Finally, small interfering RNA was used to knock down the expression of KCNJ2, which was demonstrated to inhibit cell proliferation, migration and invasion, while increasing apoptosis in TC cells. In conclusion, in the present study, KCNJ2 was screened as an oncogene with a crucial role in TC development and progression and may represent a promising candidate biomarker and therapeutic target for TC.

T Cell Receptor Beta-Chain Profiling of Tumor Tissue, Peripheral Blood and Regional Lymph Nodes From Patients With Papillary Thyroid Carcinoma.

Objective: To study the characteristics of the T cell receptor (TCR) repertoire in cancer tissue, peripheral blood and regional lymph nodes (LNs) from patients with papillary thyroid carcinoma (PTC). Methods: PTC tissue, peripheral blood mononuclear cells (PBMCs) and regional LNs of six patients with papillary thyroid carcinoma were harvested. T cell receptor beta-chain (TCRß) profiling was performed though high-throughput sequencing (HTS), and IMonitor, MiXCR and VDJtools were used to analyze the characteristics of the TCR repertoire. Results: The results of IMonitor and those of MiXCR and VDJtools were very similar. The unique CDR3 of TCRß from LNs was higher than that of PBMCs, and the CDR3 of TCRß from LNs was higher than that of PTC tissue. Shannon's diversity index, D50, inverse Simpson index_mean and normalized Shannon's diversity index_mean of CDR3 from LNs were higher than those of PTCs and PBMCs. The HEC (high expansion clones) rate of CDR3 sequences at the amino acid level in PTC tissue was higher than that of PBMCs, which was higher than that of LNs. The V-J HEC rate of CDR3 was highest in PTC tissue, followed by PBMCs and LNs. Conclusion: TCR CDR3 profiling showed differences among and within the PBMCs, PTC tissues and regional LNs of PTC, including unique CDR3, CDR3 HEC at the amino acid level, CDR3 V-J HEC at the amino acid level, Shannon's diversity index and D50. The TCRß repertoire of PTC tissue, peripheral blood and regional LNs of PTC provide a reference for further study of immunity mechanisms against PTC.

Loss of tumor intrinsic PD-L1 confers resistance to drug-induced apoptosis in human colon cancer.

Colorectal cancer (CRC) with BRAF (V600E) is associated with microsatellite instability (MSI) that predicts response to immune checkpoint inhibitors. We demonstrated the interrogation of TCGA RNA-seq human datasets revealed that BRAFV600E tumors had significantly higher Programmed Death Ligand 1 (PD-L1) mRNA compared to non-mutated BRAF CRCs. Also, MSI-H tumors were evaluated as higher PD-L1 than MSS CRCs. Inhibition of MEK/ERK by cobimetinib or CDK inhibitor dinaciclib was shown to attenuate mutant BRAF-induced PD-L1 coincident with reduced c-JUN and YAP expression whose combined knockdown reduced PD-L1. Using TCGA datasets, PD-L1 mRNA expression in human colon cancers was significantly associated with YAP expression. The deletion of PD-L1 can reduce tumor cell growth shown by clonogenic assay. Analysis of the role of PD-L1 as a mediator of chemosensitivity was then performed. Knockout of PD-L1 was shown to attenuate the induction of DNA double-strand breaks (pH2AX) and caspase-3 cleavage by 5-fluorouracil (5-FU) and paclitaxel compared to parental CRC cells. Results were confirmed in PD-L1 knockout MC38 murine CRC cells where re-expression of wild-type PD-L1 promoted DNA damage and apoptosis. We also performed the clonogenic assay and flow cytometry to prove that loss of PD-L1 attenuated DNA damage and apoptosis induced by diverse anti-cancer drugs that could be reversed by restoration of wild-type PD-L1. Mechanistically, knockout of PD-L1 reduced chemosensitivity in association with reductions in p-AKT and in BH3-only proteins BIM and BIK, rather than STAT3 in CRC cells. However, STAT3 had a significant role in melanoma, which shows the heterogeneity of cancers. In summary, BRAFV600E can upregulate PD-L1 expression that was induced by c-jun and YAP to enhance chemotherapy-induced apoptosis. Together, we demonstrate a potential role for PD-L1 as a regulator of chemotherapy-induced apoptosis whose deletion or suppression confers chemoresistance. These findings expand the understanding of PD-L1 functions to include nonimmune mechanisms and suggest the potential use of PD-L1 as a biomarker of response to cytotoxic chemotherapy.

Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three independent datasets. At the patient-level, CRCNet achieves an area under the precision-recall curve (AUPRC) of 0.882 (95% CI: 0.828-0.931), 0.874 (0.820-0.926) and 0.867 (0.795-0.923). CRCNet exceeds average endoscopists performance on recall rate across two test sets (91.3% versus 83.8%; two-sided t-test, p < 0.001 and 96.5% versus 90.3%; p = 0.006) and precision for one test set (93.7% versus 83.8%; p = 0.02), while obtains comparable recall rate on one test set and precision on the other two. At the image-level, CRCNet achieves an AUPRC of 0.990 (0.987-0.993), 0.991 (0.987-0.995), and 0.997 (0.995-0.999). Our study warrants further investigation of CRCNet by prospective clinical trials.

Lymph node metastasis in young and middle-aged papillary thyroid carcinoma patients: a SEER-based cohort study.

BACKGROUND: Lymph node metastasis (LNM) occurs frequently in young papillary thyroid carcinoma (PTC) patients, though the mortality rates are low. We aimed to analyze the relationship between age at diagnosis and LNM in PTC at a population level to elucidate the clinical behavior of PTC. METHODS: Data of adult patients with surgically treated PTC and follicular thyroid carcinoma (FTC) were identified from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2015) to investigate the relationship between age and clinical characteristics by curve estimation. The adjusted odds ratio of age and LNM rate were determined. RESULTS: A total of 50,347 PTC (48,166) and FTC (2181) (median age: 45 and 50 years, respectively) patients met the inclusion criteria; 44.5% of those with PTC (21,428) had LNM. Rank-sum test analysis indicated differences in distribution of age in LNM-positive and LNM-negative PTC. The relationship between age, tumor size and LNM showed a quadratic curve in PTC. The mean tumor diameter and LNM rate correlated linearly with age in 18-59-year-old patients. LNM rate decreased with age (R2 = 0.932, P < .0001), especially women (R2 = 0.951, P < .0001). CONCLUSION: In young and middle-aged PTC patients, LNM may resolve spontaneously with delayed diagnosis and management. Active surveillance of low-risk PTC is justified.