Biology subjects

Berezowska, S.

Publications and source records attributed to Berezowska, S..

4 recordsLinked to original sources

bioRxiv2026

Actionable spatial prostanoid barriers constrain BiTE-driven adoptive T cell immunity in intact human tumors

Adoptive cell therapy (ACT) in solid tumors is limited by tumor microenvironment (TME)-imposed resistance mechanisms that are inadequately addressed by conventional systems. We developed tissue-preserving patient-derived explants (PDEs) from lung and ovarian cancer to interrogate redirected T cell immunity in intact human tissue. Using mesothelin-targeting bispecific T cell engager (BiTE(R), Amgen trademark)-secreting T cells, we observed antigen-dependent but heterogeneous responses across lesions. An integrated ex vivo response score stratified responder and non-responder TMEs, revealing that resistance associates with reduced antigen density, stromal dominance, and limited myeloid licensing rather than baseline lymphocyte abundance. Elevated prostaglandin E2 (PGE2) inversely correlated with BiTE-induced T cell activation, identifying the COX/PGE2 axis as a tissue-imposed constraint. COX inhibition amplified interferon-driven immune programs enhanced intratumoral CD8 infiltration, and increased tumor-restricted apoptosis. Spatial transcriptomics localized these effects to tumor-proximal immune hubs in responders, whereas non-responders remained stromally insulated. These findings position PDEs as human-based new approach methodologies enabling combinatorial ACT pharmacodynamics and stratification. Statement of significancePatient-derived explants provide a human-based new approach methodology to interrogate adoptive immunotherapy pharmacodynamics within intact tumor microenvironments in NSCLC and HGSOC. We uncover a COX/PGE2-mediated tissue ceiling that limits BiTE-driven T cell function and demonstrate that COX inhibition reactivates tumor-proximal immune hubs to enhance intratumoral CD8 infiltration and tumor-restricted apoptosis, informing patient stratification and rational combinations.

systems biology↗

bioRxiv2024

Follicular Bcl6 reactivity is associated with a unique immune landscape and spatial transcriptome in COVID-19

The regulation of follicular (F) and germinal center (GC) immune reactivity in human lymph nodes (LNs), particularly during the early stages of viral infections, remains poorly understood. We have analyzed lung-draining lymph nodes (LD-LNs) from COVID-19 autopsies using multiplex imaging and spatial transcriptomics to examine the immune landscape and with respect to the aging. We identified three subgroups of Reactive Follicles (RFs) based on Bcl6 prevalence, RF-Bcl6no/low, RF-Bcl6int and RF-Bcl6high. RF-Bcl6high tissues express a distinct B/TFH immune landscape associated with increased prevalence of proliferating B- and TFH-cell subsets. Comparison between LD-LNs and matched subdiaphragmatic LNs revealed a disconnected Bcl6 reactivity between the two anatomical sites. LD-LNs Bcl6 reactivity was associated with a distinct spatial transcriptomic profile. TH1-associated genes/pathways (e.g. CXCR3, STAT5, TNF signaling) were significantly upregulated in RF-Bcl6no/low tissues while the RF-Bcl6high tissues exhibited significant upregulation of GC-promoting genes/pathways (e.g. CXCL13, B cell receptor signaling). Despite the similar prevalence, the in-situ transcriptome profiling indicates a higher monocyte/macrophage functionality in "Aged" compared to "Young" follicles from donors with comparable Bcl6 reactivity. Our findings reveal a heterogeneous F/GC landscape in COVID-19 LD-LNs and highlight specific molecular targets and pathways that could regulate human F/GC immune dynamics during early viral infections.

immunology↗

bioRxiv2022

Deep learning for histopathological subtyping and grading of lung adenocarcinoma

The histopathological distinction of lung adenocarcinoma (LADC) subtypes is subject to high inter-observer variability, which can compromise the optimal assessment of the patient prognosis. Therefore, this study developed convolutional neural networks (CNNs) capable of distinguishing LADC subtypes and predicting disease-specific survival, according to the LADC tumour grades established recently by the International Association for the Study of Lung Cancer pathology committee. Consensus LADC ground truth histopathological images were obtained from seventeen expert pulmonary pathologists and one pathologist in training. Two deep learning models (AI-1 and AI-2) were trained with EfficientNet b3 architecture to predict eight different LADC classes (lepidic, acinar, papillary, micropapillary, solid, invasive mucinous adenocarcinoma, other carcinoma types, and no carcinoma cells). Furthermore, the trained models were tested on an independent cohort of 133 patients. The models achieved high precision, recall, and F1-scores exceeding 0.90 for most of the LADC classes. Clear stratification of the three LADC grades was reached in predicting the disease-specific survival by the two models. Moreover, the grading prediction of one of the trained models was more accurate than those of 14 out of 15 pulmonary pathologists involved in the study (p=0.0003). Both trained models showed high stability in the segmentation of each pair of predicted grades with low variation in the hazard ratio across 200 bootstrapped samples. These findings indicate that the trained CNNs improve the diagnostic accuracy of the pathologist, standardise LADC subtype recognition, and refine LADC grade assessment. Thus, the trained models are promising tools that may assist in the routine evaluation of LADC subtypes and grades in clinical practice.

pathology↗

bioRxiv2017

Questioning the role of selected somatic PIK3C2B mutations in squamous non-small cell lung cancer oncogenesis.

PI3K signaling is frequently dysregulated in NSCLC-SQCC. In contrast to well characterized components of the PI3K signaling network contributing to the formation of SQCC, potential oncogenic effects of alterations in PIK3C2B are poorly understood. Here, a large cohort (n=362) of NSCLC-SQCC was selectively screened for four reported somatic mutations in PIK3C2B via Sanger sequencing. In addition, two mutations leading to an amino acid exchange in the kinase domain (C1181, H1208R) were examined on a functional level for their oncogenic potential.\n\nNone of the mutations were identified in the cohort while well characterized hotspot PIK3CA mutations were observed at the expected frequency. Ultimately, kinase domain mutations in PI3KC2{beta} were found to have no altering effect on downstream signaling. A set of SQCC tumors sequenced by The Cancer Genome Atlas (TCGA) equally indicates a lack of oncogenic potential of the kinase domain mutations or PIK3C2B in general.\n\nTaken together, this study suggests that PIK3C2B might only have a minor role in SQCC oncogenesis.

cancer biology↗