Mass spectrometry-based metabolic signatures of sex steroids in breast cancer

Diverse role of androgen action in human breast cancer

Breast cancer is a hormone-dependent cancer, and sex steroids play a pivotal role in breast cancer progression. Estrogens are strongly associated with breast cancers, and the estrogen receptor (estrogen receptor α; ERα) is expressed in 70-80% of human breast carcinoma tissues. Although antiestrogen therapies (endocrine therapies) have significantly improved clinical outcomes in ERα-positive breast cancer patients, some patients experience recurrence after treatment. In addition, patients with breast carcinoma lacking ERα expression do not benefit from endocrine therapy. The androgen receptor (AR) is also expressed in >70% of breast carcinoma tissues. Growing evidence supports this novel therapeutic target for the treatment of triple-negative breast cancers that lack ERα, progesterone receptor, and human EGF receptor 2, and ERα-positive breast cancers, which are resistant to conventional endocrine therapy. However, the clinical significance of AR expression is still controversial and the biological function of androgens in breast cancers is unclear. In this review, we focus on the recent findings concerning androgen action in breast cancers and the contributions of androgens to improved breast cancer therapy.

Bioprocess of Microbial Melanin Production and Isolation

Melanin is one of the most abundant pigments found in the biosphere. Owing to its high biocompatibility and diverse biological activities, it has been widely applied as a functional biomaterial in the cosmetic, pharmaceutical, biopolymer, and environmental fields. In this study, the production of melanin was comprehensively reviewed concerning bioconversion and isolation processes. First, several melanogenic microbes, including fungi and bacteria, were summarized. Melanin production was classified by host and melanin type and was analyzed by titers in g/L in addition to reaction conditions, including pH and temperature. The production was further interpreted using a space-time yields chart, which showed two distinct classifications in productivity, and reaction conditions were analyzed using a pH-temperature-titer chart. Next, the extraction process was summarized by crude and pure melanin preparation procedures, and the extraction yields were highlighted. Finally, the recent applications of melanin were briefly summarized, and prospects for further application and development in industrial applications were suggested.

Convolutional neural network in proteomics and metabolomics for determination of comorbidity between cancer and schizophrenia

The association between cancer risk and schizophrenia is widely debated. Despite many epidemiological studies, there is still no strong evidence regarding the molecular basis for the comorbidity between these two pathological conditions. The vast majority of assays have been performed using clinical records of schizophrenic patients or those undergoing cancer treatment and monitored for sufficient time to find shared features between the considered conditions. We performed mass spectrometry-based proteomic and metabolomic investigations of patients with different cancer phenotypes (breast, ovarian, renal, and prostate) and patients with schizophrenia. The resulting vast quantity of proteomic and metabolomic data were then processed using systems biology and one-dimensional (1D) convolutional neural network (1DCNN) machine learning approaches. Traditional systematic approaches permit the segregation of schizophrenia and cancer phenotypes on the level of biological processes, while 1DCNN recognized "signatures" that could segregate distinct cancer phenotypes and schizophrenia at the comorbidity level. The designed network efficiently discriminated unrelated pathologies with a model accuracy of 0.90 and different subtypes of oncophenotypes with an accuracy of 0.94. The proposed strategy integrates systematic analysis of identified compounds and application of 1DCNN model for unidentified ones to reveal the similarity between distinct phenotypes.

Liquid chromatography-mass spectrometry applications for quantification of endogenous sex hormones

Liquid chromatography, coupled with tandem mass spectrometry, presents a powerful tool for the quantification of the sex steroid hormones 17-β estradiol, progesterone and testosterone from biological matrices. The importance of accurate quantification with these hormones, even at endogenous levels, has evolved with our understanding of the role these regulators play in human development, fertility and disease risk and manifestation. Routine monitoring of these analytes can be accomplished by immunoassay techniques, which face limitations on specificity and sensitivity, or using gas chromatography-mass spectrometry. LC-MS/MS is growing in capability and acceptance for clinically relevant quantification of sex steroid hormones in biological matrices and is able to overcome many of the limitations of immunoassays. Analyte specificity has improved through the use of novel derivatizing agents, and sensitivity has been refined through the use of high-resolution chromatography and mass spectrometric technology. This review highlights these innovations, among others, in LC-MS/MS steroid hormone analysis captured in the literature over the last decade.