Anna Kiialainen

Bio: Anna Kiialainen is an academic researcher from Hoffmann-La Roche. The author has contributed to research in topics: Emicizumab & Medicine. The author has an hindex of 12, co-authored 21 publications receiving 1655 citations.

A transcriptionally and functionally distinct PD-1+ CD8+ T cell pool with predictive potential in non-small-cell lung cancer treated with PD-1 blockade

Abstract: Evidence from mouse chronic viral infection models suggests that CD8+ T cell subsets characterized by distinct expression levels of the receptor PD-1 diverge in their state of exhaustion and potential for reinvigoration by PD-1 blockade. However, it remains unknown whether T cells in human cancer adopt a similar spectrum of exhausted states based on PD-1 expression levels. We compared transcriptional, metabolic and functional signatures of intratumoral CD8+ T lymphocyte populations with high (PD-1T), intermediate (PD-1N) and no PD-1 expression (PD-1–) from non-small-cell lung cancer patients. PD-1T T cells showed a markedly different transcriptional and metabolic profile from PD-1N and PD-1– lymphocytes, as well as an intrinsically high capacity for tumor recognition. Furthermore, while PD-1T lymphocytes were impaired in classical effector cytokine production, they produced CXCL13, which mediates immune cell recruitment to tertiary lymphoid structures. Strikingly, the presence of PD-1T cells was strongly predictive for both response and survival in a small cohort of non-small-cell lung cancer patients treated with PD-1 blockade. The characterization of a distinct state of tumor-reactive, PD-1-bright lymphocytes in human cancer, which only partially resembles that seen in chronic infection, provides potential avenues for therapeutic intervention. Tumor-infiltrating CD8+ T cells with high expression of PD-1 in non-small-cell lung cancer are distinct from exhausted T cells in chronic virus infection, have high tumor reactivity and associate with response to PD-1-targeted immunotherapy.

Dual angiopoietin-2 and VEGFA inhibition elicits antitumor immunity that is enhanced by PD-1 checkpoint blockade

Abstract: Pathological angiogenesis is a hallmark of cancer and a therapeutic target. Vascular endothelial growth factor A (VEGFA) and angiopoietin-2 (ANGPT2; also known as ANG2) are proangiogenic cytokines that sustain tumor angiogenesis and limit antitumor immunity. We show that combined ANGPT2 and VEGFA blockade by a bispecific antibody (A2V) provided superior therapeutic benefits, as compared to the single agents, in both genetically engineered and transplant tumor models, including metastatic breast cancer (MMTV-PyMT), pancreatic neuroendocrine tumor (RIP1-Tag2), and melanoma. Mechanistically, A2V promoted vascular regression, tumor necrosis, and antigen presentation by intratumoral phagocytes. A2V also normalized the remaining blood vessels and facilitated the extravasation and perivascular accumulation of activated, interferon-γ (IFNγ)–expressing CD8+ cytotoxic T lymphocytes (CTLs). Whereas the antitumoral activity of A2V was, at least partly, CTL-dependent, perivascular T cells concurrently up-regulated the expression of the immune checkpoint ligand programmed cell death ligand 1 (PD-L1) in tumor endothelial cells. IFNγ neutralization blunted this adaptive response, and PD-1 blockade improved tumor control by A2V in different cancer models. These findings position immune cells as key effectors of antiangiogenic therapy and support the rationale for cotargeting angiogenesis and immune checkpoints in cancer therapy.

Suppression of microRNA activity amplifies IFN-γ-induced macrophage activation and promotes anti-tumour immunity

Abstract: Tumour-associated macrophages (TAMs) largely express an alternatively activated (or M2) phenotype, which entails immunosuppressive and tumour-promoting capabilities. Reprogramming TAMs towards a classically activated (M1) phenotype may thwart tumour-associated immunosuppression and unleash anti-tumour immunity. Here we show that conditional deletion of the microRNA (miRNA)-processing enzyme DICER in macrophages prompts M1-like TAM programming, characterized by hyperactive IFN-γ/STAT1 signalling. This rewiring abated the immunosuppressive capacity of TAMs and fostered the recruitment of activated cytotoxic T lymphocytes (CTLs) to the tumours. CTL-derived IFN-γ exacerbated M1 polarization of Dicer1-deficient TAMs and inhibited tumour growth. Remarkably, DICER deficiency in TAMs negated the anti-tumoral effects of macrophage depletion by anti-CSF1R antibodies, and enabled complete tumour eradication by PD1 checkpoint blockade or CD40 agonistic antibodies. Finally, genetic rescue of Let-7 miRNA activity in Dicer1-deficient TAMs partly restored their M2-like phenotype and decreased tumour-infiltrating CTLs. These findings suggest that DICER/Let-7 activity opposes IFN-γ-induced, immunostimulatory M1-like TAM activation, with potential therapeutic implications.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Automated Eukaryotic Gene Structure Annotation Using EVidenceModeler and the Program to Assemble Spliced Alignments

Abstract: EVidenceModeler (EVM) is presented as an automated eukaryotic gene structure annotation tool that reports eukaryotic gene structures as a weighted consensus of all available evidence. EVM, when combined with the Program to Assemble Spliced Alignments (PASA), yields a comprehensive, configurable annotation system that predicts protein-coding genes and alternatively spliced isoforms. Our experiments on both rice and human genome sequences demonstrate that EVM produces automated gene structure annotation approaching the quality of manual curation.

The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy

Abstract: Checkpoint inhibitor-based immunotherapies that target cytotoxic T lymphocyte antigen 4 (CTLA4) or the programmed cell death 1 (PD1) pathway have achieved impressive success in the treatment of different cancer types. Yet, only a subset of patients derive clinical benefit. It is thus critical to understand the determinants driving response, resistance and adverse effects. In this Review, we discuss recent work demonstrating that immune checkpoint inhibitor efficacy is affected by a combination of factors involving tumour genomics, host germline genetics, PD1 ligand 1 (PDL1) levels and other features of the tumour microenvironment, as well as the gut microbiome. We focus on recently identified molecular and cellular determinants of response. A better understanding of how these variables cooperate to affect tumour-host interactions is needed to optimize the implementation of precision immunotherapy.

Immune checkpoint inhibitors: recent progress and potential biomarkers.

Abstract: Cancer growth and progression are associated with immune suppression. Cancer cells have the ability to activate different immune checkpoint pathways that harbor immunosuppressive functions. Monoclonal antibodies that target immune checkpoints provided an immense breakthrough in cancer therapeutics. Among the immune checkpoint inhibitors, PD-1/PD-L1 and CTLA-4 inhibitors showed promising therapeutic outcomes, and some have been approved for certain cancer treatments, while others are under clinical trials. Recent reports have shown that patients with various malignancies benefit from immune checkpoint inhibitor treatment. However, mainstream initiation of immune checkpoint therapy to treat cancers is obstructed by the low response rate and immune-related adverse events in some cancer patients. This has given rise to the need for developing sets of biomarkers that predict the response to immune checkpoint blockade and immune-related adverse events. In this review, we discuss different predictive biomarkers for anti-PD-1/PD-L1 and anti-CTLA-4 inhibitors, including immune cells, PD-L1 overexpression, neoantigens, and genetic and epigenetic signatures. Potential approaches for further developing highly reliable predictive biomarkers should facilitate patient selection for and decision-making related to immune checkpoint inhibitor-based therapies.