| 11. |
- Schott, Benjamin H., et al.
(author)
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Modeling of variables in cellular infection reveals CXCL10 levels are regulated by human genetic variation and the Chlamydia-encoded CPAF protease
- 2020
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 10:1
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Journal article (peer-reviewed)abstract
- Susceptibility to infectious diseases is determined by a complex interaction between host and pathogen. For infections with the obligate intracellular bacterium Chlamydia trachomatis, variation in immune activation and disease presentation are regulated by both host genetic diversity and pathogen immune evasion. Previously, we discovered a single nucleotide polymorphism (rs2869462) associated with absolute abundance of CXCL10, a pro-inflammatory T-cell chemokine. Here, we report that levels of CXCL10 change during C. trachomatis infection of cultured cells in a manner dependent on both host and pathogen. Linear modeling of cellular traits associated with CXCL10 levels identified a strong, negative correlation with bacterial burden, suggesting that C. trachomatis actively suppresses CXCL10. We identified the pathogen-encoded factor responsible for this suppression as the chlamydial protease- or proteasome-like activity factor, CPAF. Further, we applied our modeling approach to other host cytokines in response to C. trachomatis and found evidence that RANTES, another T-cell chemoattractant, is actively suppressed by Chlamydia. However, this observed suppression of RANTES is not mediated by CPAF. Overall, our results demonstrate that CPAF suppresses CXCL10 to evade the host cytokine response and that modeling of cellular infection parameters can reveal previously unrecognized facets of host-pathogen interactions.
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| 12. |
- Schweinsberg, Martin, et al.
(author)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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In: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
-
Journal article (peer-reviewed)abstract
- In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists' gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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| 13. |
- Zivanovic, Andrej, et al.
(author)
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Co-evolution of AR gene copy number and structural complexity in endocrine therapy resistant prostate cancer
- 2023
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In: NAR Cancer. - : Oxford University Press. - 2632-8674. ; 5:3
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Journal article (peer-reviewed)abstract
- Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. Resolving this is important for developing new therapies and predictive biomarkers. Here, we analyzed 41 CRPC tumors and 6 patient-derived xenografts (PDXs) using linked-read DNA-sequencing, and identified 7 tumors that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. Analysis of PDX models by optical genome mapping and fluorescence in situ hybridization showed that AR residing on extrachromosomal DNA (ecDNA) was an underlying mechanism, and was associated with elevated levels and diversity of AR expression. This study identifies co-evolution of AR gene copy number and structural complexity via ecDNA as a mechanism associated with endocrine therapy resistance.
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