Previous studies yielded controversial results about the alteration of lipid profiles in patients with subclinical hypothyroidism. We performed a meta-analysis to investigate the association between subclinical hypothyroidism and lipid profiles.

BACKGROUND TBC1 domain family member 24 (TBC1D24) pathogenic mutations affect its binding to ARF6 and then result in severe impairment of neuronal development. However, there are no reports about the expression and function of TBC1D24 in cancer. The aim of the present study was to evaluate the effect of proliferation, migration, and invasion after silencing TBC1D24 expression in breast cancer MCF-7 cells, and to elucidate the potential mechanism of TBC1D24 in breast cancer. MATERIAL AND METHODS The expression of TBC1D24 in breast cancer tissues and the adjacent non-tumor tissues was determined by S-P immunohistochemistry. The malignant behavior, including proliferation, migration, and invasion ability, was determined after silencing TBC1D24 in breast cancer MCF-7 cells. The expression of IGF1R was determined after silencing TBC1D24. The expression of TBC1D24 and IGF1R was detected after transfecting miR-30a mimics or inhibitors. The effect of TBC1D24 on MCF-7 cells growth in vivo was evaluated by a tumor xenograft study. RESULTS TBC1D24 expression was elevated and was associated with poor outcome in breast carcinoma. TBC1D24 high expression was significantly correlated with unfavorable OS and RFS for breast cancer patients (p<0.05). Silencing TBC1D24 inhibited the proliferation, migration, and invasion ability of MCF-7 cells. TBC1D24 and IGF1R expression were decreased when transfected with miR-30a mimics. However, TBC1D24 and IGF1R expression were increased when transfected with miR-30a inhibitors (p<0.05). Knockdown of TBC1D24 inhibited the expression of IGF1R, PI3K, and p-AKT (p<0.05). Knockdown of TBC1D24 abolished tumorigenicity of MCF-7 cells. The average volume and weight of tumors was lower after silencing TBC1D24 expression (P<0.05). CONCLUSIONS Silencing TBC1D24 inhibited MCF-7 cells growth in vitro and in vivo. TBC1D24 promoted breast carcinoma growth through the IGF1R/PI3K/AKT pathway. TBC1D24 is a potential therapeutic target for breast cancer.

BACKGROUND The aim of this study was to compare the microbiota community structure, assess differences in intestinal bacterial types, and identify metagenomic biomarkers for disparate stages of colorectal cancer formation. MATERIAL AND METHODS A total of 160 individuals were recruited: 61 cases with non-tumor colon were regarded as the normal group, 47 cases with histology-substantiated colorectal adenomas were regarded as the adenoma group, and 52 cases with invasive adenocarcinomas were regarded as the cancer group. Biopsy on the mucosa was performed on each subject. USEARCH was used to process the sequences data and generate OTUs. Gut mucosal microbiota from healthy controls, adenoma patients, and carcinoma patients were analyzed. RESULTS Principal coordinate analysis of unweighted and weighted UniFrac distance showed a separation in composition of microbiota in the 3 groups. Bacteria with potential tumorigenesis, like Bacteroides fragilis and Fusobacterium, were more common in the carcinoma group, while some SCFA (short chain fatty acids) - producing microbes were enriched in the normal group. The commensal Escherichia were more abundant in adenoma patients. CONCLUSIONS Our study provides insights into possible function of gut microbiota in diagnosis and treatment of colorectal cancer. Some bacteria, such as Butyricicoccus, E. coli, and Fusobacterium, can be used as potential biomarkers for normal, adenoma, and cancer groups, respectively.

BACKGROUND Previous studies have confirmed that progesterone has a protective effect on traumatic brain injury (TBI). In this paper, network pharmacology and molecular docking technology were used to further explore the potential mechanism of progesterone in the treatment of TBI. MATERIAL AND METHODS Based on network pharmacology, potential targets of progesterone for TBI were obtained. The network diagram of interactions between target proteins was established to screen the key targets of progesterone for TBI. The DAVID database was used to analyze its biological function and enrichment pathway, and to explore and determine the biological pathway of progesterone in treating TBI. Molecular docking technology was used to simulate the interaction between progesterone and key target proteins. RESULTS Progesterone can treat TBI by anti-inflammatory action, repairing damaged cell membranes, stabilizing the structure of the blood-brain barrier, alleviating brain edema, reducing neuronal apoptosis, and improving neurological function. The molecular mechanism involves the PI3K/Akt signaling pathway, MAPK signaling pathway, and Ras signaling pathway. CONCLUSIONS Progesterone is a potential clinical treatment for TBI. Exploring the potential targets and pathways of TBI therapy through network pharmacology can provide a direction for subsequent research.

BACKGROUND Colon cancer is one of the most common malignant cancers and causes millions of deaths each year. There are still no effective treatments for colon cancer patients who are at advanced stage. Tumor necrosis factor-alpha (TNF-α) might be a good therapy target due to its widely-accepted roles in regulating multiple important biological processes, especially in promoting inflammation. MATERIAL AND METHODS We evaluated the expression of TNF-α in 108 human colon cancer tissue samples and 2 colon cancer cell lines (CT26 and HCT116), and analyzed its prognostic values. Further, we explored the roles and mechanism of anti-TNF-α treatment in combination with chemotherapy in vitro and in vivo. RESULTS We found that TNF-α was highly expressed in colon cancer cell lines. The survival analysis and Cox regression analysis indicated that high TNF-α was an independent adverse prognosticator of colon cancer. In addition, anti-TNF-α treatment enhanced the effects of chemotherapy in the xenograft mouse model through inducing ADCC and CDC effects. CONCLUSIONS We conclude that TNF-α is an independent adverse prognosticator of colon cancer, and anti-TNF-α might benefit colon cancer patients.

BACKGROUND Limited efficacy of immune checkpoint blockades was observed in clinical trials in colorectal (CRC) patients, especially in the microsatellite-stable patients. Interleukin-6 (IL-6) is critical in modeling immune responses in cancers. However, the effects of targeting IL-6 in combination with immune checkpoint blockades is unknown in CRC. MATERIAL AND METHODS In the present study, we investigated the profile of IL-6 expression in tumor tissues of CRC patient and we established CRC mouse models with various IL-6 expression levels using CT26 cells and MC38 cells. Effects of anti-IL-6 and anti-PD-L1 combination treatment were tested in these models. RESULTS A total of 105 CRC patients were included in this study, with 41 (39%) females and 64 (61%) males. Sixty patients showed IL-6 high expression and 45 patients showed IL-6 low expression. The patients with IL-6 high expression tended to have shorter survival (median survival time of 25.5 months) than the patients with IL-6 low expression (median survival time of 46 months, P value=0.013). In the CRC mouse models, tumors with IL-6 overexpression tended to grow faster than the tumors with IL-6 knockout. The numbers of CD8+ T cells and CD4+ T cells were decreased in IL-6 overexpressed tumors. On the contrary, myeloid-derived suppressor cells and regulatory/suppressor T cells were more numerous in tumors with IL-6 overexpression. PD-L1 expression was upregulated in the tumors with IL-6 overexpression. Importantly, an IL-6 blockade reversed the anti-PD-L1 resistance and prolonged tumor-bearing mouse survival. CONCLUSIONS Our study indicates that IL-6 induces strong immunosuppression in the CRC microenvironment by recruiting immunosuppression cells and impairing T cell infiltration. Inhibition of IL-6 enhanced the efficacy of anti-PD-L1 in CRC, providing a novel strategy to overcome anti-PD-L1 resistance in CRC.

BACKGROUND To determine the difference in size-specific dose estimates (SSDEs), separately based on effective diameter (deff) and water equivalent diameter (dw) of the central slice of the scan range in computed tomography coronary angiography (CTCA). MATERIAL AND METHODS There were 134 patients who underwent CTCA examination, were electronically retrieved. SSDEs (SSDEdeff and SSDEdw) were calculated using 2 approaches: deff and dw. The median SSDEs and mean absolute relative difference of SSDEs were calculated. Linear regression model was used to assess the absolute relative difference of SSDEs based on the ratio of deff to dw. RESULTS The median values of SSDEdeff and SSDEdw were 18.26 mGy and 20.56 mGy, respectively (P<0.01). The former was about 10.08% smaller than the latter. The mean absolute relative difference of SSDEs was 10.48%, ranging from 0.33% to 24.16%. A considerably positive correlation was found between the absolute relative difference of SSDEs and the ratio of deff to dw (R²=0.9561, r=0.979, P<0.01). CONCLUSIONS The value of SSDEdeff was smaller by an average of about 10.08% than SSDEdw in CTCA, and the absolute relative difference increased linearly with the ratio of effective diameter to water equivalent diameter.