Branched-chain ketoacids secreted by glioblastoma cells via MCT1 modulate macrophage phenotype.

Elevated amino acid catabolism is common to many cancers. Here, we show that glioblastoma are excreting large amounts of branched-chain ketoacids (BCKAs), metabolites of branched-chain amino acid (BCAA) catabolism. We show that efflux of BCKAs, as well as pyruvate, is mediated by the monocarboxylate transporter 1 (MCT1) in glioblastoma. MCT1 locates in close proximity to BCKA-generating branched-chain amino acid transaminase 1, suggesting possible functional interaction of the proteins. Using in vitro models, we demonstrate that tumor-excreted BCKAs can be taken up and re-aminated to BCAAs by tumor-associated macrophages. Furthermore, exposure to BCKAs reduced the phagocytic activity of macrophages. This study provides further evidence for the eminent role of BCAA catabolism in glioblastoma by demonstrating that tumor-excreted BCKAs might have a direct role in tumor immune suppression. Our data further suggest that the anti-proliferative effects of MCT1 knockdown observed by others might be related to the blocked excretion of BCKAs.

STAT3:FOXM1 and MCT1 drive uterine cervix carcinoma fitness to a lactate-rich microenvironment.

Uterine cervix cancer is the second most common malignancy in women worldwide with human papillomavirus (HPV) as the etiologic factor. The two main histological variants, squamous cell carcinomas (SCC) and adenocarcinomas (AC), resemble the cell morphology of exocervix and endocervix, respectively. Cancer metabolism is a cancer hallmark conditioned by the microenvironment. As uterine cervix homeostasis is dependent on lactate, we hypothesized lactate plays a role in uterine cervix cancer progression. Using in vitro (SiHa-SCC and HeLa-AC) and BALB-c/SCID models, we demonstrated that lactate metabolism is linked to histological types, with SCC predominantly consuming and AC producing lactate. MCT1 is a key factor, allowing lactate consumption and being regulated in vitro by lactate through the FOXM1:STAT3 pathway. In vivo models showed that SCC (SiHa) expresses MCT1 and is dependent on lactate to grow, whereas AC (HeLa) expresses MCT1 and MCT4, with higher growth capacities. Immunohistochemical analysis of tissue microarrays (TMA) from human cervical tumors showed that MCT1 expression associates with the SCC type and metastatic behavior of AC, whereas MCT4 expression concomitantly increases from in situ SCC to invasive SCC and is significantly associated with the AC type. Consistently, FOXM1 expression is statistically associated with MCT1 positivity in SCC, whereas the expression of FOXO3a, a FOXM1 functional antagonist, is linked to MCT1 negativity in AC. Our study reinforces the role of the microenvironment in the metabolic adaptation of cancer cells, showing that cells that retain metabolic features of their normal counterparts are positively selected by the organ's microenvironment and will survive. In particular, MCT1 was shown to be a key element in uterine cervix cancer development; however, further studies are needed to validate MCT1 as a suitable therapeutic target in uterine cervix cancer.

Were the socio-economic determinants of municipalities relevant to the increment of COVID-19 related deaths in Brazil in 2020?

BACKGROUND: The COVID-19 pandemic in Brazil has been showing a pattern of distribution of related deaths associated with individual socioeconomic status (SES). However, little is known about the role of SES in the distribution of the mortality rate in different population, from an ecological perspective. OBJECTIVE: The objective of this study was to evaluate the role of socioeconomic factors in the distribution of the COVID-19-related mortality rate among Brazilian municipalities in 2020. METHODS: We conducted a retrospective, cross-sectional, observational, population-wide, and ecological study, using data of COVID-19-related deaths from the Influenza Epidemiological Surveillance Information System database (SIVEP-Gripe) and SES from the Social Vulnerability Index (SVI), the Human Development Index (HDI), the Geographic Index of the Socioeconomic Context and Social Studies (GeoSES), and 2010 Demographic Census (IBGE/Brazil). We computed crude, age- and sex-standardized, and the latter offset by the time of exposure to the epidemic mortality rates. To determine socioeconomic factors associated with mortality rates we used log-linear models with state codes as a random effect and Haversine variance-covariance matrix. RESULTS: 191,528 deaths were related to COVID-19 and distributed in 4,928 (88.55%) Brazilian municipalities. Whatever the socioeconomic indexes used, the R2 were very small to explain SMRT. Consistent across all socioeconomic indexes used, high-income, more educated, and well infrastructure municipalities generally had higher mortality rates. CONCLUSION: Excluding the effect of demographic structure and pandemic timing from mortality rates, the contribution of SES to explain differences in COVID-19-related mortality rates among municipalities in Brazil became very low. The impact of SES on COVID-19-related mortality may vary across levels of aggregation. Urban infrastructure, which includes mobility structures, more complex economic activities and connections, may have influenced the average municipal death rate.