CD147 protein molecule expression and chromosomal instability in the pathogenesis and prognosis of thyroid cancer.

Low-coverage whole genome sequencing was performed for tissue samples from thyroid patients who received surgery treatment from 2015 to 2021. The potential biological significance of CD147 protein in thyroid cancer was explored through correlation analysis of CD147 protein expression level and clinical features of thyroid cancer patients. Low coverage whole genome sequencing was performed on the extracted DNA samples. The copy number analysis software was used to analyze the sequencing data, calculate the copy number of CD147 gene, further verify the expression of CD147 gene, and analyze its association with clinical features. The relationship between CIN and high risk was evaluated in the internal cohort. The association of CIN with the disease-free survival was validated in the cohort from The Cancer Genome Atlas Program. Thyroglobulin plays a key role in regulating thyroid function and maintaining normal metabolic rate. By sequencing tissue samples from this study, we can gain a deeper understanding of the association between cin and thyroid disease. The percentage of high risk patients in the multiple CIN group (77.8 %) was significantly higher than that in the 22q negative group (31.3 %), BRAF V600E group (22.2 %) and all negative group (25.0 %; p = 0.043).

Exploring the Oncogenic Potential of TIMM8A: A Crucial Factor in Breast Cancer Tumorigenesis.

BACKGROUND: Female breast cancer has become the world's most common malignant tumor, displacing lung malignancy, and the incidence of malignant tumors has increased continuously in recent decades. However, the underlying molecular mechanisms of breast tumorigenesis have not been fully elucidated. By consulting the literature, we discovered that the TIMM8A gene could affect oxidative stress and apoptosis in patients with Mohr-Tranebjærg syndrome. However, the biological function of TIMM8A has yet to be explored. MATERIALS AND METHODS: We investigated the expression level of TIMM8A via bioinformatic analysis and performed immunohistochemistry, diagnostic value, immune infiltration, functional enrichment, and survival analyses. Nonetheless, in vitro, additional experiments were performed. We explored whether TIMM8A expression was greater in breast tumors than in nearby normal tissues through qRT‒PCR. The expression of TIMM8A was knocked down by siRNA. Then, we conducted proliferation tests (CCK-8 experiment and colony formation) and Transwell assays (migration and invasion assays) to determine the specific biological functions of TIMM8A in the MDA-MB-231 and BT-549 cell lines. RESULTS: Tumor samples exhibited higher TIMM8A expression and exon expression, whereas normal tissues had higher TIMM8A methylation. The expression level of TIMM8A was linked to immune infiltration and survival, making it a valuable prognostic indicator and effective diagnostic tool. Functional enrichment analysis of TIMM8A indicated potential pathways through which it may play a role. In vitro experiments demonstrated that suppressing TIMM8A significantly inhibited the viability, colony formation, migration, and invasion of breast carcinoma cell lines. CONCLUSION: This study revealed that TIMM8A is an oncogene and is critical for the tumorigenesis of breast carcinoma.

Preoperative prediction of lymph node metastasis in patients with papillary thyroid carcinoma by an artificial intelligence algorithm.

BACKGROUND: It is necessary to identify patients at risk of developing lymph node metastasis prior to papillary thyroid carcinoma (PTC) surgery. This can be challenging due to limiting factors, and an artificial intelligence algorithm may be a viable option. OBJECTIVE: In this study, we aimed to evaluate whether combining an artificial intelligence algorithm (support vector machine and probabilistic neural network) and clinico-pathologic data can preoperatively predict lymph node metastasis of papillary thyroid carcinoma (PTC). METHODS: We retrospectively examined 251 PTCs with lymph node metastasis and 194 PTCs without lymph node metastasis. The artificial intelligence algorithm included the support vector machine (SVM) and the probabilistic neural network (PNN). RESULTS: The ACR TI-RADS (Thyroid Imaging, Reporting and Data System), number of tumours, no well-defined margin, lymph node status and rim calcification on ultrasonography (US), age, sex, tumour size, and presence of Hashimoto's thyroiditis were significantly more frequent among PTCs with central lymph node metastasis than those without metastasis (P<0.05). The PNN classifier revealed an F1 score of 0.88 on the central lymph node metastasis test set. The SVM classifier revealed an F1 score of 0.93 on the lateral lymph node metastasis test set. Our study demonstrates that combining artificial intelligence algorithms and clinico-pathologic data can effectively predict the lymph node metastasis of papillary thyroid carcinoma prior to surgery.

Genetic landscape of breast cancer and mutation tracking with circulating tumor DNA in Chinese women.

Considerable efforts have been devoted to exploring the breast cancer mutational landscape to understand its genetic complexity. However, no studies have yet comprehensively elucidated the molecular characterization of breast tumors in Chinese women. This study aimed to determine the potential clinical utility of peripheral blood assessment for circulating tumor-derived DNA (ctDNA) and comprehensively characterize the female Chinese population's genetic mutational spectrum. We used Omi-Seq to create cancer profiles of 273 patients enrolled at The First Affiliated Hospital of Wenzhou Medical University. The gene landscape results indicate PIK3CA and TP53 as the most frequently detected genes, followed by ERBB2, in Chinese breast cancer patients. The accuracy of ERBB2 copy number variations in tissue/formalin-fixed and paraffin-embedded samples was 95% with 86% sensitivity and 99% specificity. Moreover, mutation numbers varied between different molecular cell-free DNA subtypes, with the basal-like patients harboring a higher number of variants than the luminal patients. Furthermore, ratio changes in the max ctDNA allele fraction highly correlated with clinical response measurements, including cancer relapse and metastasis. Our data demonstrate that ctDNA characterization using the Omi-Seq platform can extend the capacity of personalized clinical cancer management.

Downregulated CDH3 decreases proliferation, migration, and invasion in thyroid cancer.

BACKGROUND: Placental-Cadherin (CDH3), a cell adhesion molecule, is associated with the function of cells to bind with other cells and the extracellular matrix (ECM). CDH3 is highly expressed in many malignancies, and has been proved it could be a serum marker to monitor colorectal cancer, but the CDH3 expression levels in thyroid cancer is still not clear. In this article, we will illuminate the correlation between CDHs expression and thyroid cancer. MATERIALS AND METHODS: We analyzed the level of CDH3 expression in 60 pair of tissue samples (contrast thyroid cancer tissues with adjacent normal thyroid tissues) by Real-time PCR, and TCGA data portal. After that, we transfected small interfering RNA to silence CDH3 in thyroid cancer cell lines (KTC-1 and BCPAP) and confirmed the function of CDH3 by performed colony formation, migration, invasion, cell counting kit-8 and apoptosis assays. RESULTS: CDH3 was upregulated in thyroid cancer tissues compared to the adjacent normal tissues (T:N=71.87±39.88:5.35±5.91, P<0.0001) and TCGA (T:N=19.43±13.82:1.22±1.33, P<0.0001). In thyroid cell lines (KTC-1 and BCPAP) experiments showed that downregulated CDH3 inhibited proliferation, migration, and invasion. Meanwhile, inhibited CDH3 expression could upregulate E-cadherin, downregulated N-cadherin, which may control invasion and migration. CONCLUSION: Thyroid cancer cells CDH3 expression levels is a correlation with its ability to grow, migrate and invade.