Biology subjects

Henrich, E.

Publications and source records attributed to Henrich, E..

6 recordsLinked to original sources

bioRxiv2025

Cell-line specific role of Cathepsin B in triple-negative breast cancer growth, invasion and response to chemotherapy

Cathepsins are papain-family cysteine proteases known to play a cell-intrinsic role in protein degradation in the lysosome, as well as in digesting ECM and surface proteins after being secreted. Both of these functions are known to mediate pro-tumorigenic effects of CTSB in a range of cancers. Here, we specifically investigate the role of CTSB in TNBC, an aggressive subtype of breast cancer, where we find that high expression of CTSB in TNBC is associated with better outcomes. We used CRISPR to knockout CTSB in two highly metastatic TNBC cell lines, MDA-MB-231 and MDA-MB-468, and find different effects. In MDA-MB-231 cells, knockout of CTSB has no effect on cell viability, increases tumor cell 3D invasion in an ECM-independent manner, and increases sensitivity to many standard of care chemotherapy drugs. However, in MDA-MB-468 cells, knockout of CTSB increases cell viability, decreases tumor cell 3D invasion, in an ECM-independent manner, and drives resistance to certain chemotherapy drugs without affecting response to others. We find that in these cells, CTSB is not secreted, and that differential downstream mTOR and Akt activation can explain the differences seen in these phenotypes. Overall, our studies demonstrate that CTSB can regulate TNBC cell phenotypes via its lysosomal cell-intrinsic role, but that effects are cell-line specific, suggesting potential heterogeneity in the role of CTSB in TNBC.

cancer biology↗

bioRxiv2023

Cell morphology best predicts tumorigenicity and metastasis in vivo across multiple TNBC cell lines of different metastatic potential

BackgroundMetastasis is the leading cause of death in breast cancer patients. For metastasis to occur, tumor cells must invade locally, intravasate, and colonize distant tissues and organs, all steps that require tumor cell migration. The majority of studies on invasion and metastasis rely on human breast cancer cell lines. While it is known that these cells have different properties and abilities for growth and metastasis, the in vitro morphological, proliferative, migratory, and invasive behavior of these cell lines and their correlation to in vivo behavior is poorly understood. Thus, we sought to classify each cell line as poorly or highly metastatic by characterizing tumor growth and metastasis in a murine model of six commonly used human triple-negative breast cancer xenografts, as well as determine which in vitro assays commonly used to study cell motility best predict in vivo metastasis. MethodsWe evaluated the liver and lung metastasis of human TNBC cell lines MDA-MB-231, MDA-MB-468, BT549, Hs578T, BT20, and SUM159 in immunocompromised mice. We characterized each cell lines cell morphology, proliferation, and motility in 2D and 3D to determine the variation in these parameters between cell lines. ResultsWe identified MDA-MB-231, MDA-MB-468, and BT549 cells as highly tumorigenic and metastatic, Hs578T as poorly tumorigenic and metastatic, BT20 as intermediate tumorigenic with poor metastasis to the lungs but highly metastatic to the livers, and SUM159 as intermediate tumorigenic but poorly metastatic to the lungs and livers. We showed that metrics that characterize cell morphology are the most predictive of tumor growth and metastatic potential to the lungs and liver. Further, we found that no single in vitro motility assay in 2D or 3D significantly correlated with metastasis in vivo. ConclusionsOur results provide an important resource for the TNBC research community, identifying the metastatic potential of 6 commonly used cell lines. Our findings also support the use of cell morphological analysis to investigate the metastatic potential and emphasize the need for multiple in vitro motility metrics using multiple cell lines to represent the heterogeneity of metastasis in vivo.

cancer biology↗

bioRxiv2022

Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses

Systems biology approaches have been used to define molecular signatures and mechanisms of immunity to vaccination. However, most such studies have been done with single vaccines, and comparative analysis of the response to different vaccines is lacking. We integrated temporal transcriptional data of over 3,000 samples, obtained from 820 healthy adults across 28 studies of 13 different vaccines and analyzed vaccination-induced signatures associated with the antibody response. Most vaccines induced similar kinetics of shared transcriptional signatures, including signatures of innate immunity occurring 1-3 days post-vaccination, as well as the canonical plasmablast and cell cycle signatures appearing 7 days post-vaccination. However, the yellow fever vaccine YF-17D uniquely induced an early transient signature of T and B cell activation at Day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at Days 7 and 14-21, respectively. Thus, despite the shared transcriptional response to most vaccines, at any given time point there was no evidence for a "universal signature" that could be used to predict the antibody response to all vaccines. However, accounting for the asynchronous nature of responses led to the identification of a time-adjusted signature that improved prediction antibody of responses across vaccines. These results provide a transcriptional atlas of the human immune response to vaccination and define a common, time-adjusted signature of antibody responses to vaccination.

immunology↗

bioRxiv2021

The Immune Signatures Data Resource: A compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses. [Table 1]

systems biology↗

bioRxiv2021

An innate immune activation state prior to vaccination predicts responsiveness to multiple vaccines

Many factors determine whether an individual responding to vaccination will generate an immune response that can lead to protection. Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccines. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across a wide variety of vaccines. We leveraged the "Immune Signatures Data Resource" created by the NIH Human Immunology Project Consortium (HIPC) to integrate data from 28 studies involving 13 different vaccines and associate the blood transcriptional status of 820 healthy young adults with their responses. An unsupervised analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination states, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations downstream of NF{kappa}B and IRF7. Innate and adaptive immune cell subset-specific genes were also associated with the three pre-vaccination states. Importantly, individuals whose pre-vaccination state was enriched in pro-inflammatory response genes known to be downstream of NF{kappa}B tended to have higher serum antibody responses one month after vaccination. A supervised analysis of the same data resulted in a single classifier, also enriched for NF{kappa}B regulated genes, that predicted the antibody response across most of the vaccines. Projection into single-cell RNA-sequencing data suggested that this pre-vaccination state was attributable to the signature of activation of non-classical monocytes and myeloid dendritic cells. Transcriptional signatures of acute responses to bacterial and not viral infections were enriched in the high pro-inflammatory pre-vaccination state and also included NF{kappa}B regulated genes. The pro-inflammatory pre-vaccination state was highly reminiscent of the innate activation state triggered by TLR ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination. They also define a transcriptional signature NF{kappa}B activation at baseline, that is associated with a greater magnitude of antibody response to multiple vaccines, and suggest that modulation of the innate immune system by next-generation adjuvants targeting NF{kappa}B before vaccine administration may improve vaccine responsiveness.

systems biology↗

bioRxiv2019

p63 sets the threshold for induction of apoptosis using a kinetically encoded ‘doorbell-like’ mechanism

Cell fate decisions such as apoptosis require cells to translate signaling input into a binary yes/no response. A tight control of the process is required to avoid loss of cells by accidental activation of cell death pathways. One particularly critical situation exists in primary oocytes because their finite number determines the reproductive capacity of females. On the one hand a stringent genetic quality control is necessary to maintain the genetic integrity of the entire species; on the other hand an overly stringent mechanism that kills oocytes with even minor DNA damage can deplete the whole primary oocyte pool leading to infertility. The p53 homolog TAp63 is the key regulator of genome integrity in oocytes. After DNA damage TAp63 is activated by multistep phosphorylation involving multiple phosphorylation events by the kinase CK1, which triggers the transition from a dimeric and inactive conformation to an open and active tetramer. By measuring activation kinetics in ovaries and single site phosphorylation kinetics in vitro with peptides and full length protein we show that TAp63 phosphorylation follows a biphasic behavior. While the first two CK1 phosphorylation events are fast, the third one that constitutes the decisive step to form the active conformation is slow. We reveal the structural mechanism for the difference in the kinetic behavior based on an unusual CK1/TAp63 substrate interaction and demonstrate by quantitative simulation that the slow phosphorylation phase determines the threshold of DNA damage required for induction of apoptosis.

biochemistry↗