METHODS: The expression of PXMP4 mRNA in HCC tissues and corresponding adjacent tissues was detected by Q-PCR, and the expression of PXMP4 protein was detected by Western blot and immunohistochemistry. The correlation of PXMP4 protein expression with clinicopathological features and prognosis of HCC was analyzed.
RESULTS: The expression levels of PXMP4 mRNA and protein in HCC tissues were significantly higher than those in adjacent tissues (P < 0.05), and its high expression was significantly correlated with tumor differentiation, lymph node metastasis, depth of invasion and TNM stage (P < 0.05). Patients with high expression of PXMP4 had a poor prognosis (P < 0.05).
CONCLUSION: The high expression of PXMP4 may promote the occurrence and development of HCC, and inhibition of PXMP4 may be one of the potential molecular targets for targeted therapy of HCC.
METHODS: We retrieved 4 previously reported SMCA, performed additional immunohistochemical and targeted next-generation sequencing (NGS). We also investigated the use of NKX3.1 as a marker for SMCA in the context of its prevalence and extent (using H-score) in a mixed cohort of retrospectively and prospectively tested head and neck lesions (n = 223) and non-neoplastic tissues (n = 66).
RESULTS: NKX3.1 positivity was confirmed in normal mucous acini as well as in mucous acinar class of lesions (5/6, mean H-score: 136.7), including mucinous adenocarcinomas (3/4), SG-IPMN (1/1), and microsecretory adenocarcinoma (MSA) (1/1). All SMCA were positive. Fluorescence in situ hybridization for SS18 rearrangements were negative in all successfully tested cases (0/3). NGS was successful in two cases (cases 3 and 4). Case 3 demonstrated a PTEN c.655C>T p.Q219* mutation and a SEC16A::NOTCH1 fusion while case 4 (clinically aggressive) showed a PTEN c.1026+1G>A p.K342 splice site variant, aTP53 c.524G>A p.R175H mutation and a higher tumor mutation burden (29 per Mb). PTEN immunohistochemical loss was confirmed in both cases and a subset of tumor cells showed strong (extreme) staining for P53 in Case 4.
CONCLUSION: Despite a partial myoepithelial phenotype, SMCA, along with mucinous adenocarcinomas/SG-IPMN and MSA, provisionally constitute a mucous acinar class of tumors based on morphology and NKX3.1 expression. Like salivary mucinous adenocarcinomas/SG-IPMN, SMCA also show alterations of the PTEN/PI3K/AKT pathway and may show progressive molecular alterations. We document the first extramammary tumor with a SEC16A::NOTCH1 fusion.
METHODS: Using multi-region sampled RNA-seq data of 90 patients, we performed patient-specific differential expression testing, together with the patients' matched adjacent normal samples.
RESULTS: Comparing the results from conventional DE analysis and patient-specific DE analyses, we show that the conventional DE analysis omits some genes due to high inter-individual variability present in both tumour and normal tissues. Dysregulated genes shared in small subgroup of patients were useful in stratifying patients, and presented differential prognosis. We also showed that the target genes of some of the current targeted agents used in HCC exhibited highly individualistic dysregulation pattern, which may explain the poor response rate.
DISCUSSION/CONCLUSION: Our results highlight the importance of identifying patient-specific DE genes, with its potential to provide clinically valuable insights into patient subgroups for applications in precision medicine.
MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.
RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.
CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.
METHODS: In this study, plasma miRNA profiles from eight early-stage breast cancer patients and nine age-matched (± 2 years) healthy controls were characterized by miRNA array-based approach, followed by differential gene expression analysis, Independent T-test and construction of Receiver Operating Characteristic (ROC) curve to determine the capability of the assays to discriminate between breast cancer and the healthy control.
RESULTS: Based on the 372-miRNAs microarray profiling, a set of 40 differential miRNAs was extracted regarding to the fold change value at 2 and above. We further sub grouped 40 miRNAs of breast cancer patients that were significantly expressed at 2-fold change and higher. In this set, we discovered that 24 miRNAs were significantly upregulated and 16 miRNAs were significantly downregulated in breast cancer patients, as compared to the miRNA expression of healthy subjects. ROC curve analysis revealed that seven miRNAs (miR-125b-5p, miR-142-3p, miR-145-5p, miR-193a-5p, miR-27b-3p, miR-22-5p and miR-423-5p) had area under curve (AUC) value > 0.7 (AUC p-value < 0.05). Overlapping findings from differential gene expression analysis, ROC analysis, and Independent T-Test resulted in three miRNAs (miR-27b-3p, miR-22-5p, miR-145-5p). Cohen's effect size for these three miRNAs was large with d value are more than 0.95.
CONCLUSION: miR-27b-3p, miR-22-5p, miR-145-5p could be potential biomarkers to distinguish breast cancer patients from healthy controls. A validation study for these three miRNAs in an external set of samples is ongoing.
.