Biology subjects

Leppa, S.

Publications and source records attributed to Leppa, S..

4 recordsLinked to original sources

bioRxiv2026

Immune-cell depleted diffuse large B-cell lymphomas have reduced expression of MHC class I

Immunotherapy has transformed treatment for many cancers. In the aggressive and genetically heterogeneous diffuse large B-cell lymphoma (DLBCL), CD19 CAR T-cell therapy is highly effective, whereas immune checkpoint blockade has shown limited benefit. Loss of MHC expression is a common mechanism to escape T-cell cytotoxicity, and loss of MHC class I (MHC-I) and II are frequent in DLBCL. We applied imaging mass cytometry to diagnostic biopsies from younger, high-risk DLBCL patients to map the tumor microenvironment (TME) spatial architecture in relation to tumor cell MHC expression, mutational status, transcriptomic and proteomic profiles. Neighborhood analyses identified four TME subtypes: immune-cell depleted and three immune-infiltrated types (mixed, CD4 T cell-rich, CD8 T-cell/macrophage-rich). Depleted cases had shorter overall survival (p = 0.033) and increased expression of proteins involved in DNA replication and proliferation markers compared to infiltrated cases. Tumor cell MHC-I expression was heterogeneous. Cases with low frequency of MHC-I-pos tumor cells were enriched for the depleted TME type. MHC-I-pos tumor cells were surrounded by CD4 and CD8 T cells and M1 macrophages, whereas MHC-I-neg tumor cells were closer to other MHC-I-neg tumor cells. These findings suggest that TME-based classification incorporating tumor cell MHC-I status may improve individualized immunotherapy selection.

cancer biology↗

bioRxiv2022

Efficacy and safety of glycosphingolipid SSEA-4 targeting CAR-T cells in solid tumors

Chimeric antigen receptor (CAR) T-cell immunotherapies for solid tumors face critical challenges such as heterogeneous antigen expression. We characterized SSEA-4 cell-surface glycolipid as a target for CAR-T cell therapy. SSEA-4 is mainly expressed during embryogenesis but is also found in several cancer types making it an attractive tumor-associated antigen. Anti-SSEA-4 CAR-T cells were generated and assessed pre-clinically in vitro and in vivo for anti-tumor response and safety. SSEA-4 CAR-T cells effectively eliminated SSEA-4 positive cells in all tested cancer cell lines whereas SSEA-4 negative cells lines were not targeted. In vivo efficacy and safety studies using NSG mice and the high-grade serous ovarian cancer cell line OVCAR4 demonstrated a remarkable and specific anti-tumor response at all CAR-T cell doses used. At high T cell doses, CAR-T cell-treated mice showed signs of health deterioration after a follow-up period. However, severity of toxicity was reduced with delayed onset when lower CAR-T cell doses were used. Our data demonstrate the efficacy of anti-SSEA-4 CAR-T therapy; however, safety strategies, such as dose-limiting and/or equipping CAR-T cells with combinatorial antigen recognition should be implemented for its potential clinical translation.

cancer biology↗

bioRxiv2020

ctDNAtools: An R package to work with sequencing data of circulating tumor DNA

SummarySequencing of cell-free DNA (cfDNA) including circulating tumor DNA (ctDNA) in minimally-invasive liquid biopsies is rapidly maturing towards clinical utility for cancer diagnostics. However, the publicly available bioinformatics tools for the specialized analysis of ctDNA sequencing data are still scarce. Here, we present the ctDNAtools R package, which provides functionalities for testing minimal residual disease (MRD) and analyzing cfDNA fragmentation. MRD detection in ctDNAtools utilizes a Monte Carlo sampling approach to test ctDNA positivity through tracking a set of pre-detected reporter mutations in follow-up samples. Additionally, ctDNAtools includes various functionalities to study cfDNA fragment size histograms, profiles and fragment ends patterns. AvailabilityThe ctDNAtools package is freely available under MIT license at https://github.com/alkodsi/ctDNAtools.

bioinformatics↗

bioRxiv2019

Immunogenomic landscape of hematological malignancies

Understanding factors that shape the immune landscape across hematological malignancies is essential for immunotherapy development. Here, we integrated over 8,000 transcriptomes and over 1,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. Infiltration of cytotoxic immune cells was associated with distinct microenvironmental responses and driver alterations in different cancers, such as TP53 in acute myeloid leukemia and DTX1 in diffuse large B cell lymphoma. Epigenetic modification of CIITA regulating antigen presentation, cancer type-specific immune checkpoints such as VISTA in myeloid malignancies, and variation in cancer antigen expression further contributed to immune heterogeneity. Prognostic models highlighted the significance of immunological properties in predicting survival. Our study represents the most comprehensive effort to date to link immunology with cancer subtypes and genomics in hematological malignancies, providing a resource to guide future studies and immunotherapy development.

immunology↗