Background: Esophageal squamous cell carcinoma (ESCC) is the sixth most lethal cancer worldwide and the fourth most lethal cancer in China. Genomic characterization of tumors, particularly those of different stages, is likely to reveal additional oncogenic mechanisms. Although copy number alterations and somatic point mutations associated with the development of ESCC have been identified by array-based technologies and genome-wide studies, the genomic characterization of ESCCs from different stages of the disease has not been explored. Here, we have performed either whole-genome sequencing or whole-exome sequencing on 51 stage I and 53 stage III ESCC patients to characterize the genomic alterations that occur during the various clinical stages of ESCC, and further validated these changes in 36 atypical hyperplasia samples. Results: Recurrent somatic amplifications at 8q were found to be enriched in stage I tumors and the deletions of 4p-q and 5q were particularly identified in stage III tumors. In particular, the FAM84B gene was amplified and overexpressed in preclinical and ESCC tumors. Knockdown of FAM84B in ESCC cell lines significantly reduced in vitro cell growth, migration and invasion. Although the cancer-associated genes TP53, PIK3CA, CDKN2A and their pathways showed no significant difference between stage I and stage III tumors, we identified and validated a prevalence of mutations in NOTCH1 and in the NOTCH pathway that indicate that they are involved in the preclinical and early stages of ESCC. Conclusions: Our results suggest that FAM84B and the NOTCH pathway are involved in the progression of ESCC and may be potential diagnostic targets for ESCC susceptibility.

Introduction: With the gradual increase in the incidence of thyroid cancer, people’s attention to thyroid cancer has also gradually increased. Although the prognosis of thyroid cancer is rather mild compared to other cancers, it will still bring a heavy psychological burden on people who have been diagnosed. At present, the diagnosis of thyroid cancer mainly depends on ultrasound and percutaneous fine needle aspiration (pFNA). Due to the unsatisfactory accuracy of the diagnosis methods we use now, there are still some thyroid nodules that cannot be clearly diagnosed before surgery. Methods: In this article, we have searched for relevant research on blood markers of thyroid cancer in the past five years and categoried them into four groups. Discussion: Though we have not found a biomarker which can diagnose thyroid cancer both sensitively and specifically, we do found many substances that are related to it, and have the potential to recognize it and help the diagnosis. And perhaps combined models can do it better.

Background: Oxidative stress is a significant contributor to the development of various diseases, and the oxidative balance score (OBS) is a valuable tool for assessing the impact of dietary and lifestyle factors on oxidative stress in humans. Nevertheless, the precise relationship between OBS and thyroid function in adults remains elusive. Methods: This cross-sectional study comprised 6222 adult participants drawn from the National Health and Nutrition Examination Survey (NHANES) conducted from 2007 to 2012. Employing weighted multivariable linear regression modeling, the study estimated the connection between OBS quartiles and thyroid functions. The causal relationship between OBS components and thyroid function was analyzed by Mendelian randomization (MR). Results: We found a significant negative correlation between OBS and free thyroxine (FT4) and total thyroxine (TT4). Univariate and multivariate MR Analyses showed a causal relationship between BMI and FT4. Copper, smoking, and riboflavin showed a causal relationship with FT4 after moderation. Conclusion: We found that a lifestyle high in antioxidant exposure reduced FT4 and TT4 levels in the population. We suggest that BMI, Copper, and Riboflavin are important factors in the regulation of FT4 levels.

In this study, a nomogram was established and validated by assessing the risk factors for the development of pulmonary metastases in patients with non-papillary thyroid carcinoma (NPTC) and was used to predict the risk of developing pulmonary metastases. Demographic and clinicopathological variables of patients with NPTC from 2010 to 2015 in the Surveillance, Epidemiology, and End Results database were retrospectively analyzed, and independent risk factors were identified using χ² tests and full subset regression analysis. Based on this, a nomogram was developed and validated for predicting the risk of pulmonary metastasis in patients with NPTC. The predictive performance of the nomogram was calculated using the consistency index, and the clinical application value of the nomogram was evaluated using calibration curve and decision curve analyses. In addition, risk stratification of patients with NPTC based on these results was performed to facilitate early diagnosis and treatment of patients with pulmonary metastases in the clinic. Data from 1435 patients with NPTC were used for the analysis based on the inclusion and exclusion criteria. Statistical analysis yielded a high risk of pulmonary metastasis in patients with older age, high T-stage, poorly differentiated, undifferentiated thyroid carcinoma, follicular thyroid carcinoma (NOS), and the presence of other distant metastases. We further developed a nomogram with a consistency index of 0.898 (95% confidence interval: 0.880–0.920) in the training cohort and 0.895 (95% confidence interval: 0.862–0.927) in the validation cohort. The calibration curve and decision curve analyses also demonstrated the strong reliability and accuracy of this clinical prediction model. In this study, a nomogram was constructed to accurately identify patients with NPTC at a high risk of pulmonary metastasis, which will help clinicians in personalized decision-making.

Background: This study was conducted to develop nomograms and validate them by assessing risk factors for the development of central lymph node metastasis (CLNM) in patients with solitary papillary thyroid carcinoma of the isthmus (PTCI) for predicting the probability of CLNM. Methods: Demographic and clinicopathological variables of patients with solitary papillary thyroid carcinoma (PTC) from May 2018 to May 2023 at the First Hospital of Shanxi Medical University were retrospectively analyzed, and the lobar group and the isthmus group were divided according to tumor location. Patients with the same sex, age difference of less than 3 years, and equal gross tumor diameter were selected from the lobar group and compared with the paraisthmic tumor group. Independent risk factors were determined using univariate and multivariate logistic regression analysis. On this basis, clinical predictive nomograms were developed and validated. Results: Clinical data from 326 patients with solitary PTCI and 660 cases of solitary lobar PTC were used for analysis in our study. The incidence of solitary tumors CLNM located in the median isthmus, paracentral isthmus, and lobes was 69.8%, 40.9%, and 33.6%, respectively. Statistical analysis revealed that gender, age, isthmus location, maximum nodal diameter, the presence of possible CLNM in advance on preoperative ultrasound, chronic lymphocytic thyroiditis, and the lymphocyte/monocyte ratio were independent risk factors for preoperative CLNM in patients with solitary PTCI. Age, isthmus location, chronic lymphocytic thyroiditis, gross tumor diameter, presence of intraoperative extrathyroidal extension, and presence of metastasis in the Delphian lymph node on frozen section were independent risk factors for intraoperative CLNM. The concordance indices of nomograms for preoperative and intraoperative are 0.871 and 0.894 in the training set and 0.796 and 0.851 in the validation set, calibration curve and decision curve analysis also demonstrated the strong reliability and clinical applicability of this clinical prediction model. Conclusion: In this study, we concluded that solitary PTCI is more aggressive compared to solitary lobar PTC, and we constructed nomograms and risk stratification to accurately identify patients with solitary PTCI who are at high risk of developing CLNM, which will help clinicians in personalized decision making.