BK polyomavirus (BKV) frequently causes nephropathy (BKVN) in kidney transplant recipients (KTRs). BKV has also been implicated in the etiology of bladder and kidney cancers. We characterized BKV variants from two KTRs who developed BKVN followed by renal carcinoma. Both patients showed a swarm of BKV sequence variants encoding non-silent mutations in surface loops of the viral major capsid protein. The temporal appearance and disappearance of these mutations highlights the intra-patient evolution of BKV. Some of the observed mutations conferred resistance to antibody-mediated neutralization. The mutations also modified the spectrum of receptor glycans engaged by BKV during host cell entry. Intriguingly, all observed mutations were consistent with DNA damage caused by antiviral APOBEC3 cytosine deaminases. Moreover, APOBEC3 expression was evident upon immunohistochemical analysis of renal biopsies from KTRs. These results provide a snapshot of in-host BKV evolution and suggest that APOBEC3 may drive BKV mutagenesis in vivo.

Patients suffering from Epidermodysplasia verruciformis (EV), a rare inherited skin disease, display a particular susceptibility to persistent infection with cutaneous genus beta-human papillomavirus (beta-HPV), such as HPV type 8. They have a high risk to develop non-melanoma skin cancer at sun-exposed sites. In various models evidence is emerging that cutaneous HPV E6 proteins disturb epidermal homeostasis and support carcinogenesis, however, the underlying mechanisms are not fully understood as yet. In this study we demonstrate that microRNA-203 (miR-203), a key regulator of epidermal proliferation and differentiation, is strongly down-regulated in HPV8-positive EV-lesions. We provide evidence that CCAAT/enhancer-binding protein α (C/EBPα), a differentiation-regulating transcription factor and suppressor of UV-induced skin carcinogenesis, directly binds the miR-203 gene within its hairpin region and thereby induces miR-203 transcription. Our data further demonstrate that the HPV8 E6 protein significantly suppresses this novel C/EBPα/mir-203-pathway. As a consequence, the miR-203 target ΔNp63α, a proliferation-inducing transcription factor, is up-regulated, while the differentiation factor involucrin is suppressed. HPV8 E6 specifically down-regulates C/EBPα but not C/EBPβ expression at the transcriptional level. As shown in knock-down experiments, C/EBPα is regulated by the acetyltransferase p300, a well-described target of cutaneous E6 proteins. Notably, p300 bound significantly less to the C/EBPα regulatory region in HPV8 E6 expressing keratinocytes than in control cells as demonstrated by chromatin immunoprecipitation. In situ analysis confirmed congruent suprabasal expression patterns of C/EBPα and miR-203 in non-lesional skin of EV-patients. In HPV8-positive EV-lesions both factors are potently down-regulated in vivo further supporting our in vitro data. In conclusion our study has unraveled a novel p300/C/EBPα/mir-203-dependent mechanism, by which the cutaneous HPV8 E6 protein may expand p63-positive cells in the epidermis of EV-patients and disturbs fundamental keratinocyte functions. This may drive HPV-mediated pathogenesis and may potentially also pave the way for skin carcinogenesis in EV-patients.

Allogeneic hematopoietic cell transplantation (HCT) effectively treats high-risk hematologic diseases but can entail HCT-specific complications, which may be minimized by appropriate patient management, supported by accurate, individual risk estimation. However, almost all HCT risk scores are limited to a single risk assessment before HCT without incorporation of additional data. We developed machine learning models that integrate both baseline patient data and time-dependent laboratory measurements to individually predict mortality and cytomegalovirus (CMV) reactivation after HCT at multiple time points per patient. These gradient boosting machine models provide well-calibrated, time-dependent risk predictions and achieved areas under the receiver-operating characteristic of 0.92 and 0.83 and areas under the precision-recall curve of 0.58 and 0.62 for prediction of mortality and CMV reactivation, respectively, in a 21-day time window. Both models were successfully validated in a prospective, non-interventional study and performed on par with expert hematologists in a pilot comparison.

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