Biology subjects

Gralinska, E.

Publications and source records attributed to Gralinska, E..

4 recordsLinked to original sources

bioRxiv2026

PD-1-Targeted IL-2v Expands a Novel Stem-like T Cell Subset Distinct from Anti-PD-1 Therapy to Enhance Effector Differentiation

Tumor-draining lymph nodes serve as critical sites for the generation, maintenance and differentiation of stem-like CD8 T cells during antitumor immune responses. Recent evidence has shown that delivering interleukin-2 to PD1 stem-like CD8 T cells using PD1-IL2v, an immunocytokine combining PD-1 blockade and IL-2R agonism, promotes their differentiation into potent effector cells with enhanced tumor-killing capacity. However, it remains unclear how targeted interleukin-2 therapies imprint early stem-like T-cell differentiation programs. Here, using single-cell transcriptomics and T-cell receptor sequencing in murine pancreatic tumor models, we demonstrate that PD1-IL2v induces an early bifurcation in the differentiation of stem-like CD8 T cells within tumor-draining lymph nodes. We identify an effector-primed stem-like population characterized by the expression of interferon-response genes, natural killer cell receptor genes, and Cx3cr1, consistent with activation of interleukin-2 and STAT5-associated programs. Clonal tracking revealed substantial overlap between these lymph node-derived cells and intratumoral effector populations, supporting a developmental relationship between early priming in lymph nodes and downstream effector differentiation. In contrast, an alternative stem-like state that displayed features associated with T-cell exhaustion, including increased Tox expression, was observed upon PD-1 therapy. Together, these findings identify an early branch point in stem-like T-cell differentiation and provide mechanistic insight into how PD1-IL2v circumvents exhaustion pathways to preferentially generate functional antitumor immunity.

immunology↗

bioRxiv2024

Hepatocyte differentiation requires anisotropic expansion of bile canaliculi

During liver development, bipotential progenitor cells called hepatoblasts differentiate into hepatocytes or cholangiocytes. Hepatocyte differentiation is uniquely associated with multi-axial polarity, enabling the anisotropic expansion of apical lumina between adjacent cells and formation of a three-dimensional network of bile canaliculi (BC). Cholangiocytes, the cells forming the bile ducts, exhibit the vectorial polarity common to epithelial cells. Whether and how cell polarization feeds back on the gene regulatory pathways governing hepatoblast differentiation is unknown. Here, we used primary hepatoblasts to investigate the contribution of anisotropic apical expansion to hepatocyte differentiation. Silencing of the small GTPase Rab35 caused isotropic lumen expansion and formation of multicellular cysts with the vectorial polarity of cholangiocytes. Gene expression profiling revealed that these cells express reduced levels of hepatocyte markers and upregulate genes associated with cholangiocyte identity. Time-course RNA sequencing demonstrated that loss of lumen anisotropy precedes these transcriptional changes. Independent alterations in apical lumen morphology induced either by modulation of the subapical actomyosin cortex or increased intraluminal pressure caused similar transcriptional changes. These findings suggest that cell polarity and lumen morphogenesis feedback to hepatoblast-to-hepatocyte differentiation. Summary statementDifferentiation of liver progenitors to functional hepatocytes requires anisotropic elongation of their nascent apical surfaces into tubular bile canaliculi.

developmental biology↗

bioRxiv2021

Bulkhead-like apical membrane structures between hepatocytes are required for anisotropic lumen expansion and liver tissue morphogenesis

Lumen morphogenesis is key to the function of organs and results from the integration of molecular pathways and mechanical forces1-3. The mechanisms governing anisotropic lumen expansion remain elusive4-6. In contrast to epithelial cells which have simple apico-basal polarity and form tubes, hepatocytes are multi-polar and form narrow lumina that grow anisotropically between adjacent cells, collectively generating a complex 3D network of bile canaliculi (BC)7,8. Here, we studied lumen elongation and BC morphogenesis in differentiating primary mouse hepatoblasts in vitro. Remarkably, we discovered a pattern of specific extensions of the apical membrane traversing the lumen between adjacent hepatocytes and sealed by tight junctions, reminiscent of the bulkheads of boats. These structures were also present in the developing liver. A targeted screen revealed that silencing of Rab35 caused loss of the bulkheads, conversion of hepatocyte into simple epithelial polarity and formation of spherical lumina in vitro. Strikingly, we could re-engineer hepatocyte polarity and tissue morphogenesis in vivo in the embryonic liver, converting BC into simple epithelial tubes. Our results suggest that the apical bulkheads of hepatocytes are cell-intrinsic anisotropic mechanical elements that ensure stability of the elongating lumen between two cells, thus determining the structure of BC during liver tissue morphogenesis.

cell biology↗

bioRxiv2020

Association Plots: Visualizing associations in high-dimensional correspondence analysis biplots

SO_SCPLOWUMMARYC_SCPLOWIn molecular biology, just as in many other fields of science, data often come in the form of matrices or contingency tables with many measurements (rows) for a set of variables (columns). While projection methods like Principal Component Analysis or Correspondence Analysis can be applied for obtaining an overview of such data, in cases where the matrix is very large the associated loss of information upon projection into two or three dimensions may be dramatic. However, when the set of variables can be grouped into clusters, this opens up a new angle on the data. We focus on the question which measurements are associated to a cluster and distinguish it from other clusters. Correspondence Analysis employs a geometry geared towards answering this question. We exploit this feature in order to introduce Association Plots for visualizing cluster-specific measurements in complex data. Association Plots are two-dimensional, independent of the size of data matrix or cluster, and depict the measurements associated to a cluster of variables. We demonstrate our method first on a small data set and then on a genomic example comprising more than 10,000 conditions. We will show that Association Plots can clearly highlight those measurements which characterize a cluster of variables.

bioinformatics↗