Phammann0195
Immune checkpoint inhibitors (ICIs), by unleashing the anticancer response of the immune system, can improve survival of patients affected by several malignancies, but may trigger a broad spectrum of adverse events, including autoimmune hypophysitis. ICI-related hypophysitis mainly manifests with anterior hypopituitarism, while the simultaneous involvement of both anterior and posterior pituitary (i.e., panhypophysitis) has rarely been described.
In June 2015, a 64-year-old man affected by liver metastases of a uveal melanoma was referred to us due to polyuria and polydipsia. Two months prior, he had started ipilimumab therapy (3 mg/kg iv every 21 days). The treatment was well-tolerated (only mild asthenia and diarrhea were reported). A few days before the fourth cycle, the patient complained of intense headaches, profound fatigue, nocturia, polyuria (up to 10 L urine/daily), and polydipsia. Laboratory tests were consistent with adrenal insufficiency, hypothyroidism, and transient central diabetes insipidolydipsia.
As ICIs are increasingly used as anticancer agents, the damage to anterior and/or posterior pituitary can be progressively encountered by oncologists and endocrinologists in their clinical practice. Patients on ICIs and their caregivers should be informed about that risk and be empowered to alert the referring specialists early, at the onset of panhypopituitarism symptoms, including polyuria/polydipsia.
Previous studies have shown thatmiR-100-5p expression is abnormal in prostate cancer. However, the role and regulatory mechanism of miR-100-5p requires further investigation. Thus, the aim of this study was to observe the effects of miR-100-5p on the proliferation, migration and invasion of prostate cancer (PCa) cells and to explore the potential related regulatory mechanism.
Differential miRNA expression analysis was performed using next-generation sequencing (NGS) in the patients with PCa and benign prostatic hyperplasia (BPH). The expression levels of miR-100-5p were detected using real-time fluorescence quantitative PCR (qRT-PCR). PCa cells were transfected with NC-mimics or miR-100-5p mimics, inhibitor by using liposome transfection. Moreover, the CCK-8 proliferation assay, colony formation assay, cell scratch assay and Transwell assay were used to detect the effects of miR-100-5p on cell proliferation, migration, and invasion. read more In addition, the target gene of miR-100-5p was verified by luciferase reps in PCa cells, and it can suppress PCacell proliferation, migration and invasion, the mechanism of which is related to downregulating the expression of mTOR.
miR-100-5p is expressed at low levels in PCa cells, and it can suppress PCa cell proliferation, migration and invasion, the mechanism of which is related to downregulating the expression of mTOR.
The prognostic stratification of colon cancer using only the tumor-node-metastasis (TNM) stage has some limitations. We sought to increase the accuracy of stratifying patients with stage III colon cancer by constructing a prognostic model combining carcinoembryonic antigen (CEA) with TNM.
We retrospectively analyzed the data generated from stage III colon cancer patients who had early postoperative CEA measurement from 21 to 100 days after surgery from 2006 to 2017. CEA value was processed using restricted cubic splines (RCS) method. The prognostic model was developed using cox proportional hazards regression.
The time later than 20 days after surgery was optimal for measuring CEA, which was determined by comparing the prognostic value for preoperative and postoperative CEA (N = 2,049), and by evaluating the relationship between the hazard ratio (HR) and postoperative CEA measuring time. Postoperative CEA, T stage and N stage were selected into the final model, and the mean integrated-AUC (iAUC) was 0.78 with 1,000 × bootstrap resampling, which was higher than the model using only T and N stages (TN model; mean iAUC, 0.66). The net reclassification improvement (NRI) was 15% when compared with TN model. Patients could be divided into high and low risk groups by the model, and 3-year disease-free survival (DFS) were 53.7% and 87.0%, respectively (HR, 4.30; 95% CI, 2.65 to 6.96; P < 0.001). Similar results were found in the validation set.
Stage III colon cancer could be stratified more accurately using the new prognostic model combining postoperative CEA with T and N stage.
Stage III colon cancer could be stratified more accurately using the new prognostic model combining postoperative CEA with T and N stage.
Large-cell neuroendocrine carcinoma (LCNEC) is a rare subtype of pulmonary cancer with poor survival. Optimal adjuvant chemotherapy for resected LCNEC is controversial till now; clinical features together with the prognostic factors in LCNEC should be clarified better.
Clinicopathological characteristics, driven genes' status (EGFR, ALK, and ROS1), adjuvant chemotherapy strategy for 94 surgical resected LCNECs were extracted from digital database, tumor relapse or progression, and survival were analyzed with clinical profiles.
Driven gene mutants were scarce in LCNEC, 8.3% (4/48) samples harbored EGFR mutations, 5.8% (3/52) with ALK positive, and none of ROS1 positive. A total of 44 patients suffered tumor relapse or progression during follow-up. Tumor/lymph node (N) stage, serum carcinoembryonic antigen (CEA) level before surgery, different adjuvant chemotherapies were associated with tumor relapse (
< 0.05); poorer disease-free survival (DFS) appeared in N2/stage III, serum CEA positive and pemeted to be a better choice which should be confirmed by further prospective investigations.
Endometrioid endometrial adenocarcinoma (EEA) is one of the most common tumors in the female reproductive system. With the further understanding of immune regulation mechanism in tumor microenvironment, immunotherapy is emerging in tumor treatment. However, there are few systematic studies on EEA immune infiltration.
In this study, prognostic tumor-infiltrating immune cells (TIICs) and related genes of EEA were comprehensively analyzed for the first time through the bioinformatics method with CIBERSORT algorithm as the core. Gene expression profile data were downloaded from the TCGA database, and the abundance ratio of TIICs was obtained. Kaplan-Meier analysis and Cox regression analysis were used to identify prognostic TIICs. EEA samples were grouped according to the risk score in Cox regression model. Differential analysis and functional enrichment analyses were performed on high- and low-risk groups to find survival-related hub genes, which were verified by Tumor Immune Estimation Resource (TIMER).
Four TIICs including memory CD4+ T cells, regulatory T cells, natural killer cells and dendritic cells were identified.
