Biology subjects

Kirsch, S.

Publications and source records attributed to Kirsch, S..

3 recordsLinked to original sources

bioRxiv2023

Quiescence-inducing 3D-engineered matrix uncovers mechanosensitive and drug protective FHL2-p21 signaling axis

Resected tumors frequently relapse with distant metastasis, despite systemic treatment. Cellular dormancy has been identified as an important mechanism underlying such drug resistance enabling late relapse. Nonetheless, hurdles associated with detection and isolation of disseminated cancer cells (DCCs) in disease-free patients urge the need for in vitro models of dormant cells suited for drug discovery. Here, we explore dormancy-inducing 3D-engineered matrices, which generate mechanical confinement and induce growth arrest and survival against chemotherapy in cancer cells. We characterized the dormant phenotype of solitary cells by P-ERKlow:P-p38high dormancy signaling ratio, along with Ki67-expression. As underlying mechanism, we identified stiffness-dependent nuclear localization of the four-and-a-half LIM domains 2 (FHL2) protein, leading to p53-independent high p21Cip1/Waf1 nuclear expression, validated in murine and human tissue. Suggestive of a resistance-causing role, cells in the dormancy-inducing matrix became sensitive against chemotherapy upon FHL2 downregulation. Thus, our biomaterial-based approach will enable systematic screens for novel compounds suited to eradicate potentially relapsing, dormant cancer cells. TeaserUsing semi-synthetic bioengineered hydrogels, we reveal a mechanosensitive and drug protective mechanism of dormant cancer cells in tissues

bioengineering↗

bioRxiv2021

Artifacts in EEG-based BCI therapies: friend or foe?

EEG-based brain-computer interfaces (BCI) have promising therapeutic potential beyond traditional neurofeedback training, such as enabling personalized and optimized virtual reality (VR) neurorehabilitation paradigms where the timing and parameters of the visual experience is synchronized with specific brain-states. While BCI algorithms are often designed to focus on whichever portion of a signal is most informative, in these brain-state-synchronized applications, it is of critical importance that the resulting decoder is sensitive to physiological brain activity representative of various mental states, and not to artifacts, such as those arising from naturalistic movements. In this study, we compare the relative classification accuracy with which different motor tasks can be decoded from both extracted brain activity and artifacts contained in the EEG signal. EEG data was collected from 17 chronic stroke patients while performing six different head, hand, and arm movements in a realistic VR-based neurorehabilitation paradigm. Results show that the artifactual component of the EEG signal is significantly more informative than brain activity with respect to classification accuracy. This finding is consistent across different feature extraction methods and classification pipelines. While informative brain signals can be recovered with suitable cleaning procedures, we recommend that features should not be designed solely to maximize classification accuracy, as this could select for remaining artifactual components. We also propose the use of machine learning approaches that are interpretable to verify that classification is driven by physiological brain-states. In summary, whereas informative artifacts are a helpful friend in BCI-based communication applications, they can be a problematic foe in the estimation of physiological brain states.

neuroscience↗

bioRxiv2020

Interleukin-6 trans-signaling is a candidate mechanism to drive progression of human DCCs during periods of clinical latency

Although thousands of breast cancer cells disseminate and home to bone marrow until primary surgery, usually less than a handful will succeed in establishing manifest metastases months to years later. To identify signals that support survival or outgrowth in patients, we profiled rare bone marrow-derived disseminated cancer cells (DCCs) long before manifestation of metastasis and identified IL6/PI3K-signaling as candidate pathway for DCC activation. Surprisingly, and similar to mammary epithelial cells, DCCs lacked membranous IL6 receptor expression and mechanistic dissection revealed IL6 trans-signaling to regulate a stem-like state of mammary epithelial cells via gp130. Responsiveness to IL6 trans-signals was found to be niche-dependent as bone marrow stromal and endosteal cells down-regulated gp130 in premalignant mammary epithelial cells as opposed to vascular niche cells. PIK3CA activation rendered cells independent from IL6 trans-signaling. Consistent with a bottleneck function of microenvironmental DCC control, we found PIK3CA mutations highly associated with late-stage metastatic cells while being extremely rare in early DCCs. Our data suggest that the initial steps of metastasis formation are often not cancer cell-autonomous, but also depend on microenvironmental signals.

cancer biology↗