Biology subjects

Niemiec, I.

Publications and source records attributed to Niemiec, I..

4 recordsLinked to original sources

bioRxiv2024

Single-cell spatial atlas of high-grade serous ovarian cancer unveils MHC class II as a key driver of spatial tumor ecosystems and clinical outcomes

The tumor microenvironment (TME) is a complex network of interactions between malignant and host cells, yet its orchestration in advanced high-grade serous ovarian carcinoma (HGSC) remains poorly understood. We present a comprehensive single-cell spatial atlas of 280 metastatic HGSCs, integrating high-dimensional imaging, genomics, and transcriptomics. Using 929 single-cell maps, we identify distinct spatial domains associated with phenotypically heterogeneous cellular compositions, and demonstrate that immune cell co-infiltration at the tumor-stroma interface significantly influences clinical outcomes. To uncover the key drivers of the tumor ecosystem, we developed CEFIIRA (Cell Feature Importance Identification by RAndom forest), which identified tumor cell-intrinsic MHC-II expression as a critical predictor of prolonged survival, independent of clinicomolecular profiles. Validation with external datasets confirmed that MHC-II-expressing cancer cells drive immune infiltration and orchestrate spatial tumor-immune interactions. Our atlas offers novel insights into immune surveillance mechanisms across HGSC clinicomolecular groups, paving the way for improved therapeutic strategies and patient stratification.

cancer biology↗

bioRxiv2024

Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

To uncover the intricate, chemotherapy-induced spatiotemporal remodeling of the tumor microenvironment, we conducted integrative spatial and molecular characterization of 97 high-grade serous ovarian cancer (HGSC) samples collected before and after chemotherapy. Using single-cell and spatial analyses, we identify increasingly versatile immune cell states, which form spatiotemporally dynamic microcommunities at the tumor-stroma interface. We demonstrate that chemotherapy triggers spatial redistribution and exhaustion of CD8+ T cells due to prolonged antigen presentation by macrophages, both within interconnected myeloid networks termed "Myelonets" and at the tumor stroma interface. Single-cell and spatial transcriptomics identifies prominent TIGIT-NECTIN2 ligand-receptor interactions induced by chemotherapy. Using a functional patient-derived immuno-oncology platform, we show that CD8+T-cell activity can be boosted by combining immune checkpoint blockade with chemotherapy. Our discovery of chemotherapy-induced myeloid-driven spatial T-cell exhaustion paves the way for novel immunotherapeutic strategies to unleash CD8+ T-cell-mediated anti-tumor immunity in HGSC.

cancer biology↗

bioRxiv2024

Patient-derived functional immuno-oncology platform identifies responders to ATR inhibitor and immunotherapy combinations in ovarian cancer

Responses to single agent immunotherapies have remained modest in high-grade serous ovarian cancer (HGSC), suggesting the need for combination treatments. Identifying clinically effective immunotherapy combinations (IC) requires pre-clinical testing using models representing the patient-specific immune microenvironment. Here, we established a functional immuno-oncology platform for high-throughput and functional testing of IC using HGSC patient-derived immunocompetent cultures (iPDCs) established on patient-derived omentum gel matrix. We employed genomic and single-cell analysis to assess the intricate and functional characteristics of the iPDCs combined with tumor and immune cell-specific cytotoxic responses. Corroborating the clinical response to Poly (ADP-ribose) polymerase inhibitors (PARPi), iPDCs showed homologous recombination deficiency (HRD) - specific response to PARPi. Importantly, drug responses from iPDCs of chemotherapy and PARPi refractory patients corresponded with patient outcomes and aligned with distinct pathway activities from single-cell RNA sequencing analysis. Furthermore, iPDCs from HRD tumors showed response to anti-PD1 antibody as measured by decrease in tumor cells combined with augmented T cell activation. High-throughput drug testing followed by single cell-imaging from iPDCs revealed patient-specific responses to combination of ataxia telangiectasia and Rad3-related inhibitor (ATRi) with DNA damaging agents or immunotherapies. Integration of cytotoxic responses with immune cell states uncovered patient-specific immune activation with the combination of ATRi and a novel immunotherapy targeting Autotaxin (ATX), and this response was significantly associated with a tumor-cell replication stress biomarker in single-cell analysis of tCycIF highly multiplexed imaging. In conclusion, iPDCs provide a platform for high-throughput screening and functional testing of immuno-oncology agents for precision oncology in HGSC.

cancer biology↗

bioRxiv2020

AI aided design of epitope-based vaccine for the induction of cellular immune responses against SARS-CoV-2

The heavy burden imposed by the COVID-19 pandemic on our society triggered the race towards the development of therapies or preventive strategies. Among these, antibodies and vaccines are particularly attractive because of their high specificity, low probability of drug-drug interaction, and potentially long-standing protective effects. While the threat at hand justifies the pace of research, the implementation of therapeutic strategies cannot be exempted from safety considerations. There are several potential adverse events reported after the vaccination or antibody therapy, but two are of utmost importance: antibody-dependent enhancement (ADE) and cytokine storm syndrome (CSS). On the other hand, the depletion or exhaustion of T-cells has been reported to be associated with worse prognosis in COVID-19 patients. This observation suggests a potential role of vaccines eliciting cellular immunity, which might simultaneously limit the risk of ADE and CSS. Such risk was proposed to be associated with FcR-induced activation of proinflammatory macrophages (M1) by Fu et al. 2020 and Iwasaki et al. 2020. All aspects of the newly developed vaccine (including the route of administration, delivery system, and adjuvant selection) may affect its effectiveness and safety. In this work we use a novel in silico approach (based on AI and bioinformatics methods) developed to support the design of epitope-based vaccines. We evaluated the capabilities of our method for predicting the immunogenicity of epitopes. Next, the results of our approach were compared with other vaccine-design strategies reported in the literature. The risk of immuno-toxicity was also assessed. The analysis of epitope conservation among other Coronaviridae was carried out in order to facilitate the selection of peptides shared across different SARS-CoV-2 strains and which might be conserved in emerging zootic coronavirus strains. Finally, the potential applicability of the selected epitopes for the development of a vaccine eliciting cellular immunity for COVID-19 was discussed, highlighting the benefits and challenges of such an approach.

bioinformatics↗