Biology subjects

Zumalave, S.

Publications and source records attributed to Zumalave, S..

4 recordsLinked to original sources

bioRxiv2026

Spatiotemporal dynamics of adoptively transferred stem-like CD8+ T cells in the tumor microenvironment following vaccination

Adoptive cell therapy (ACT) of tumor-specific T cells can improve survival in a subset of cancer patients. Current ACT approaches may be limited by using highly differentiated T cells which can be inhibited by an immunosuppressive tumor microenvironment (TME). Here, we developed an approach to optimize ACT and used spatial transcriptomics to show how stem-like and effector CD8+ T cells differentially mediate tumor control following vaccination. Spatial transcriptomic profiling of the TME showed that ACT with stem-like T cells followed by intravenous vaccination prevented immune exclusion, increased infiltration of pro-inflammatory macrophages, and reprogrammed tumor cells to upregulate Type I and Type II IFN signaling and apoptotic gene programs. The protective transcriptomic signature of the TME in this ACT model contained overlapping biomarkers with patients who responded to ACT therapy. This approach demonstrates synergy between transferred stem-like T cells and intravenous vaccination to transcriptionally remodel the TME and enhance tumor control.

immunology↗

bioRxiv2024

Synchronous L1 retrotransposition events promote chromosomal crossover early in human tumorigenesis

L1 retrotransposition is a significant source of genomic variation in human epithelial tumours, which can contribute to tumorigenesis. However, fundamental questions about the causes and consequences of L1 activity in cancer genomes remain unresolved, primarily due to the limitations of short-read sequencing technologies. Here, we employ multiplatform sequencing, with an emphasis on long reads, to analyse a fine selection of 10 tumours exhibiting high rates of somatic retrotransposition, encompassing over 6000 events. The analysis of L1 locus-specific single-nucleotide variants reveals a novel panorama of L1 loci activity. Furthermore, examination of the internal structure of somatic L1s uncovers the mechanisms behind their inactivation. A hidden landscape of chromosomal aberrations emerges in the light of long reads, where reciprocal translocations mediated by L1 insertion represent frequent events. Resolution of L1 bridges configuration elucidates the mechanisms of their formation, where typically two independent, but synchronous, somatic L1 insertions drive the reciprocal exchange between non-homologous chromosomes. Timing analyses indicate that L1 retrotransposition is an early driver of chromosomal instability, active before the first whole-genome doubling event. Overall, these findings highlight L1 activity as a more significant contributor to tumour genome plasticity than previously recognized, extending its impact beyond simple insertional mutagenesis.

cancer biology↗

bioRxiv2024

SAVANA: reliable analysis of somatic structural variants and copy number aberrations in clinical samples using long-read sequencing

Accurate detection of somatic structural variants (SVs) and copy number aberrations (SCNAs) is critical to inform the diagnosis and treatment of human cancers. Here, we describe SAVANA, a computationally efficient algorithm designed for the joint analysis of somatic SVs, SCNAs, tumour purity and ploidy using long-read sequencing data. SAVANA relies on machine learning to distinguish true somatic SVs from artefacts and provide prediction errors for individual SVs. Using high-depth Illumina and nanopore whole-genome sequencing data for 99 human tumours and matched normal samples, we establish best practices for benchmarking SV detection algorithms across the entire genome in an unbiased and data-driven manner using simulated and sequencing replicates of tumour and matched normal samples. SAVANA shows significantly higher sensitivity, and 9- and 59-times higher specificity than the second and third-best performing algorithms, yielding orders of magnitude fewer false positives in comparison to existing long-read sequencing tools across various clonality levels, genomic regions, SV types and SV sizes. In addition, SAVANA harnesses long-range phasing information to detect somatic SVs and SCNAs at single-haplotype resolution. SVs reported by SAVANA are highly consistent with those detected using short-read sequencing, including complex events causing oncogene amplification and tumour suppressor gene inactivation. In summary, SAVANA enables the application of long-read sequencing to detect SVs and SCNAs reliably in clinical samples.

cancer biology↗

bioRxiv2021

Aberrant integration of Hepatitis B virus DNA promotes major restructuring of human hepatocellular carcinoma genome architecture

Most cancers are characterized by the somatic acquisition of genomic rearrangements during tumour evolution that eventually drive the oncogenesis. There are different mutational mechanisms causing structural variation, some of which are specific to particular cancer types. Here, using multiplatform sequencing technologies, we identify and characterize a remarkable mutational mechanism in human hepatocellular carcinoma caused by Hepatitis B virus, by which DNA molecules from the virus are inserted into the tumour genome causing dramatic changes in its configuration, including non-homologous chromosomal fusions and megabase-size telomeric deletions. This aberrant mutational process, present in at least 8% of all HCC tumours, is active early during liver cancer evolution and can provide the driver rearrangements that a cancer clone requires to survive and grow.

cancer biology↗