Background: The androgen receptor (AR) has emerged as a potential therapeutic target for AR-positive triple-negative breast cancer (TNBC). However, conflicting reports regarding AR’s prognostic role in TNBC are putting its usefulness in question. Some studies conclude that AR positivity indicates a good prognosis in TNBC, whereas others suggest the opposite, and some show that AR status has no significant bearing on the patients’ prognosis. Methods: We evaluated the prognostic value of AR in resected primary tumors from TNBC patients from six international cohorts {US (n = 420), UK (n = 239), Norway (n = 104), Ireland (n = 222), Nigeria (n = 180), and India (n = 242); total n = 1407}. All TNBC samples were stained with the same anti-AR antibody using the same immunohistochemistry protocol, and samples with ≥1% of AR-positive nuclei were deemed AR-positive TNBCs. Results: AR status shows population-specific patterns of association with patients’ overall survival after controlling for age, grade, population, and chemotherapy. We found AR-positive status to be a marker of good prognosis in US and Nigerian cohorts, a marker of poor prognosis in Norway, Ireland and Indian cohorts, and neutral in UK cohort. Conclusion: AR status, on its own, is not a reliable prognostic marker. More research to investigate molecular subtype composition among the different cohorts is warranted.
According to our data, TNF A -238G>A and IL-10 -1082A>G, -819C>T and -592C>A may be associated with the development of prostate cancer and BPH. We could also notice higher frequency of TNF A and IL-10 risk haplotypes in smoker and alcohol user. Interestingly, IL-10 risk haplotype was positively associated with aggressiveness of tumor. This information can be used for the early diagnosis of disease and to improve tissue-specific treatment's efficacy which will be moving ultimately towards the discovery of personalized therapy.
Objective. Triple-negative breast cancer (TNBC) accounts for 15-25% of breast cancers. It is increasingly recognized that TNBC is a motley disease. TNBC and basal-like (BL) subtype are different molecular classes of breast cancer with a high degree of overlap. However, a smaller fraction lacks the expression of basal markers in spite of being TNBC and is called non-basal-like (NBL). e aim of this study is to assess the clinicopathological features in TNBC and compare its BL and NBL subtypes. Material and Methods. A total of 200 subjects fulfilling the inclusion criteria of study were identified from the electronic medical records of institution. e tumor sections of subjects were immunohistochemically stained for basal markers, namely, 34βE12, c-Kit, and EGFR, in order to differentiate between BL and NBL subtypes. Comprehensive data were assembled from subjects' clinical records. e features of TNBC and their associations with the two subtypes were assessed using statistical analyses. Results. TNBC constituted 22% of all breast cancers. e family history of cancer was observed to be significantly associated with stage (p � 0.013). e proportions of BL and NBL subtypes were equal. Of all parameters compared between two subtypes, only lymphovascular invasion was found to have statistically significant difference (p � 0.019).ough no statistical significant difference between overall survival (OS) and disease-free survival (DFS) of two subgroups was found, BL subtype has slightly shorter DFS and OS compared to NBL. Conclusion. Both BL and NBL subtypes occur in equal proportions; hence, basalness and triple negativity are not synonyms. ough BL and NBL are prognostically similar, BL subtype shows a trend towards slightly shorter DFS and OS compared to NBL.
Background and objectivesThe second wave of coronavirus disease-19 (COVID-19) had several severe consequences in the form of rising cases, deaths, and overwhelming health infrastructure in India. However, the similarities and differences between the characteristics of the first and second waves have yet to be explained. The objectives of the study were to compare the incidence, clinical management, and mortality rates between two waves.
Methods
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