Objective: This study aims to determine inter-laboratory variation in HER2 IHC testing through a slide-exchange program between five main reference laboratories.
Method: A total of 20 breast carcinoma cases with different known HER2 expression and gene status were selected by the central laboratory in five testing rounds. Three unstained tissue sections from each case were sent to participating laboratories, which immunostained and interpreted the HER2 immunohistochemistry result. One of the stained slides was sent to one designated participating laboratory for evaluation. Results were analyzed by the central laboratory.
Results: A complete concordance was achieved in six IHC-positive and six IHC-negative cases, its gene status of which was confirmed by in-situ-hybridization (ISH) study. The discordant results were observed in six equivocal cases, one negative case and one positive case with a concordance rate of 50-88.3%. Interestingly, the negative discordant case actually displays tumor heterogeneity. Good inter-observer agreement was achieved for all participating laboratories (k = 0.713-1.0).
Conclusion: Standardization of HER2 testing method is important to achieve optimum inter-laboratory concordance. Discordant results were seen mainly in equivocal cases. Intra-tumoral heterogeneity may impact the final HER2 IHC scoring. The continuous quality evaluation is therefore paramount to achieve reliable HER2 results.
METHODS: mRNA was extracted from 44 fibroadenomas and 36 giant fibroadenomas, and transcriptomic profiling was performed to identify up- and down-regulated genes in the giant fibroadenomas as compared to the fibroadenomas.
RESULTS: A total of 40 genes were significantly up-regulated and 18 genes were significantly down-regulated in the giant fibroadenomas as compared to the fibroadenomas of the breast. The top 5 up-regulated genes were FN1, IL3, CDC6, FGF8 and BMP8A. The top 5 down-regulated genes were TNR, CDKN2A, COL5A1, THBS4 and BMPR1B. The differentially expressed genes (DEGs) were found to be associated with 5 major canonical pathways involved in cell growth (PI3K-AKT, cell cycle regulation, WNT, and RAS signalling) and immune response (JAK-STAT signalling). Further analyses using 3 supervised learning algorithms identified an 8-gene signature (FN1, CDC6, IL23A, CCNA1, MCM4, FLT1, FGF22 and COL5A1) that could distinguish giant fibroadenomas from fibroadenomas with high predictive accuracy.
CONCLUSION: Our findings demonstrated that the giant fibroadenomas are biologically distinct to fibroadenomas of the breast with overexpression of genes involved in the regulation of cell growth and immune response.
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.
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AIM: The objective of the present study was to investigate whether this polymorphism modulate the risk of disease recurrence in TNBC patients undergoing TAC chemotherapy regimen.
METHODS: Blood samples of 76 immunohistochemistry confirmed TNBC patients were recruited. The genotyping of CYP1B1 4326 C>G polymorphism was carried out using PCR-RFLP technique. The genotype patterns were categorized into homozygous wildtype, heterozygous and homozygous variant. Kaplan-Meier analysis followed by Cox proportional hazard regression model were performed to evaluate the TNBC patients' recurrence risk.
RESULTS: Out of 76 TNBC patients, 25 (33.0%) showed disease recurrence after one-year evaluation. Kaplan Meier analysis showed that TNBC patients who are carriers of CYP1B1 4326 GG variant genotypes (37.0%) had a significantly lower probability of disease-free rates as compared to TNBC patients who are carriers of CYP1B1 4326 CC/CG genotypes (71.0%). Univariate and multivariate Cox analysis demonstrated that TNBC patients who carried CYP1B1 4326 GG variant genotype had a significantly higher risk of recurrence with HR: 2.50 and HR: 4.18 respectively, even after adjustment as compared to TNBC patients who were carriers of CYP1B1 4326 CC and CG genotypes.
CONCLUSION: Our results demonstrate the potential use of CYP1B1 4325 GG variant genotype as a candidate biomarker in predicting risk of recurrence in TNBC patients undergoing TAC chemotherapy regimen.
METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.
RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.
CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).