METHODS: We studied ER-α expression in 84 cases of PTC obtained within an eight-year period (2011-2018) by immunohistochemical technique (IHC). Associations between ER-α expression and clinicopathological features were evaluated using Fisher's exact test. The statistical significance was set at p < 0.05.
RESULTS: ER-α was expressed in 13.1% of all the PTC cases examined (n=11/84). There were no associations observed between ER-α expression and lymph node metastasis (p=1.000), tumour size (p=0.970), extrathyroidal extension (p=0.677), variants of PTC (p=1.000), age groups (p=0.188), gender (p=0.725) or race (p=0.920).
CONCLUSION: There was no evidence in this study to support the application of ER-α as prediction marker for lymph node metastasis or disease aggressiveness in PTC. Given that the scope of this study was limited to the protein expression of ER- α, we also propose the inclusion of molecular analysis of ESR1 gene expression, as well as inclusion of detailed clinical and radiological findings in future research investigating the role of ER-α in prognostication of PTC.
MATERIALS AND METHODS: A total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.
RESULTS: There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001).
CONCLUSION: Breast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR.
STUDY DESIGN: The present study was conducted on 151 women with gynecological cancers as the case group and 152 healthy women with no history of such cancers as control group. The dematographic details of participants from both control and case groups were collected using a checklist, and the pattern of their fingerprints was prepared and examined. The data were analyzed for their significance using chi-square test and t- test. Odds ratio with 95% confidence intervals were calculated.
RESULTS: Dermatoglyphic analysis showed that arch and loop patterns significantly changed in cases group as compared to control. However, the odds ratio suggested that loop pattern in 6 or more fingers might be a risk factor for developing gynecological cancers.
CONCLUSION: Our results showed that there is an association between fingerprint patterns and gynecological cancers and so, dermatoglyphic analysis may aid in the early diagnosis of these cancers.