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- Maróti, Zoltán, et al.
(författare)
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The genetic origin of Huns, Avars, and conquering Hungarians
- 2022
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Ingår i: Current Biology. - : Elsevier BV. - 0960-9822 .- 1879-0445. ; 32:13, s. 2858-2870, 2858–2870.e1–e7
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Tidskriftsartikel (refereegranskat)abstract
- Huns, Avars, and conquering Hungarians were migration-period nomadic tribal confederations that arrived in three successive waves in the Carpathian Basin between the 5th and 9th centuries. Based on the historical data, each of these groups are thought to have arrived from Asia, although their exact origin and relation to other ancient and modern populations have been debated. Recently, hundreds of ancient genomes were analyzed from Central Asia, Mongolia, and China, from which we aimed to identify putative source populations for the above-mentioned groups. In this study, we have sequenced 9 Hun, 143 Avar, and 113 Hungarian conquest period samples and identified three core populations, representing immigrants from each period with no recent European ancestry. Our results reveal that this “immigrant core” of both Huns and Avars likely originated in present day Mongolia, and their origin can be traced back to Xiongnus (Asian Huns), as suggested by several historians. On the other hand, the “immigrant core” of the conquering Hungarians derived from an earlier admixture of Mansis, early Sarmatians, and descendants of late Xiongnus. We have also shown that a common “proto-Ugric” gene pool appeared in the Bronze Age from the admixture of Mezhovskaya and Nganasan people, supporting genetic and linguistic data. In addition, we detected shared Hun-related ancestry in numerous Avar and Hungarian conquest period genetic outliers, indicating a genetic link between these successive nomadic groups. Aside from the immigrant core groups, we identified that the majority of the individuals from each period were local residents harboring “native European” ancestry.
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| 2. |
- Megyesfalvi, Zsolt, et al.
(författare)
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Expression patterns and prognostic relevance of subtype-specific transcription factors in surgically resected small-cell lung cancer : an international multicenter study
- 2022
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Ingår i: Journal of Pathology. - : Wiley. - 0022-3417 .- 1096-9896. ; 257:5, s. 674-686
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Tidskriftsartikel (refereegranskat)abstract
- The tissue distribution and prognostic relevance of subtype-specific proteins (ASCL1, NEUROD1, POU2F3, YAP1) present an evolving area of research in small-cell lung cancer (SCLC). The expression of subtype-specific transcription factors and P53 and RB1 proteins were measured by immunohistochemistry (IHC) in 386 surgically resected SCLC samples. Correlations between subtype-specific proteins and in vitro efficacy of various therapeutic agents were investigated by proteomics and cell viability assays in 26 human SCLC cell lines. Besides SCLC-A (ASCL1-dominant), SCLC-AN (combined ASCL1/NEUROD1), SCLC-N (NEUROD1-dominant), and SCLC-P (POU2F3-dominant), IHC and cluster analyses identified a quadruple-negative SCLC subtype (SCLC-QN). No unique YAP1-subtype was found. The highest overall survival rates were associated with non-neuroendocrine subtypes (SCLC-P and SCLC-QN) and the lowest with neuroendocrine subtypes (SCLC-A, SCLC-N, SCLC-AN). In univariate analyses, high ASCL1 expression was associated with poor prognosis and high POU2F3 expression with good prognosis. Notably, high ASCL1 expression influenced survival outcomes independently of other variables in a multivariate model. High POU2F3 and YAP1 protein abundances correlated with sensitivity and resistance to standard-of-care chemotherapeutics, respectively. Specific correlation patterns were also found between the efficacy of targeted agents and subtype-specific protein abundances. In conclusion, we investigated the clinicopathological relevance of SCLC molecular subtypes in a large cohort of surgically resected specimens. Differential IHC expression of ASCL1, NEUROD1, and POU2F3 defines SCLC subtypes. No YAP1-subtype can be distinguished by IHC. High POU2F3 expression is associated with improved survival in a univariate analysis, whereas elevated ASCL1 expression is an independent negative prognosticator. Proteomic and cell viability assays of human SCLC cell lines revealed distinct vulnerability profiles defined by transcription regulators.
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| 3. |
- Szeitz, Beáta, et al.
(författare)
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In-depth proteomic analysis reveals unique subtype-specific signatures in human small-cell lung cancer
- 2022
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Ingår i: Clinical and Translational Medicine. - : Wiley. - 2001-1326. ; 12:9, s. 1060-1060
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Small-cell lung cancer (SCLC) molecular subtypes have been primarily characterized based on the expression pattern of the following key transcription regulators: ASCL1 (SCLC-A), NEUROD1 (SCLC-N), POU2F3 (SCLC-P) and YAP1 (SCLC-Y). Here, we investigated the proteomic landscape of these molecular subsets with the aim to identify novel subtype-specific proteins of diagnostic and therapeutic relevance.METHODS: Pellets and cell media of 26 human SCLC cell lines were subjected to label-free shotgun proteomics for large-scale protein identification and quantitation, followed by in-depth bioinformatic analyses. Proteomic data were correlated with the cell lines' phenotypic characteristics and with public transcriptomic data of SCLC cell lines and tissues.RESULTS: Our quantitative proteomic data highlighted that four molecular subtypes are clearly distinguishable at the protein level. The cell lines exhibited diverse neuroendocrine and epithelial-mesenchymal characteristics that varied by subtype. A total of 367 proteins were identified in the cell pellet and 34 in the culture media that showed significant up- or downregulation in one subtype, including known druggable proteins and potential blood-based markers. Pathway enrichment analysis and parallel investigation of transcriptomics from SCLC cell lines outlined unique signatures for each subtype, such as upregulated oxidative phosphorylation in SCLC-A, DNA replication in SCLC-N, neurotrophin signalling in SCLC-P and epithelial-mesenchymal transition in SCLC-Y. Importantly, we identified the YAP1-driven subtype as the most distinct SCLC subgroup. Using sparse partial least squares discriminant analysis, we identified proteins that clearly distinguish four SCLC subtypes based on their expression pattern, including potential diagnostic markers for SCLC-Y (e.g. GPX8, PKD2 and UFO).CONCLUSIONS: We report for the first time, the protein expression differences among SCLC subtypes. By shedding light on potential subtype-specific therapeutic vulnerabilities and diagnostic biomarkers, our results may contribute to a better understanding of SCLC biology and the development of novel therapies.
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