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Results for “Immune Checkpoint Inhibitor”

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PubMed2000

New Developments in the Therapy of Acute Myelocytic Leukemia.

Current conventional treatment for patients with acute myelogenous leukemia results in a high percentage of clinical responses in most patients. However, a high percentage of patients still remain refractory to primary therapy or relapse later. This review examines the search for new agents and new modes of therapy. In Section I, Dr. Estey discusses new agents directed at various targets, such as CD33, angiogenesis, inappropriately methylated (suppressor) genes, cell cycle checkpoints, proteosomes, multidrug resistance (MDR) gene, mitochondrial apoptotic pathway. He also reviews preliminary results of phase I trials with the nucleoside analog troxacitabine and liposomal anthracyclin and suggests new strategies for trials of new agents. In Section II, Dr. Jones revisits differentiation therapy and presents results of preclinical and clinical studies that demonstrate that a variety of clinically applicable cell cycle inhibitors (interferon, phenylbutyrate, vitamin D, retinoids, bryostatin-1) preferentially augments growth factor-mediated induction of myeloid leukemia terminal differentiation, as well as blocks growth factors' effects on leukemia proliferation. The combination of cell cycle inhibition plus myeloid growth factors may offer a potential treatment for resistant myeloid leukemias. In Section III, Drs. Levitsky and Borrello address the question of tumor vaccination in AML and shows that, although tumor rejection antigens in AML have not been formally identified to date, a growing number of attractive candidates are ripe for testing with defined antigen-specific vaccine strategies. Interestingly, the ability to drive leukemic blasts to differentiate into competent antigen presenting cells such as dendritic cells may be exploited in the creation of cellular vaccines. Ultimately, the successful development of active immunotherapy for AML will require integration with dose-intensive chemotherapy, necessitating a more complete understanding of host immune reconstitution. In Section IV, Dr. Slavin reviews the concept of delivering non-myeloablative stem cell transplantation (NST) and delayed lymphocyte infusion (DLI) to increase tolerance in particular in high risk and older patients, and take advantage of the graft-versus-leukemia (GVL) effect. All these approaches hold promise in reducing morbidity and mortality and differ from the older concepts aiming at delivering the highest possible doses of chemotherapy and/or total body irradiation to reach maximum leukemia cell kill, whatever the toxicity to the patient.

Journal Article↗

PubMed1995

Cell cycle control of apoptosis in human leukemic T cells.

Eukaryotic cell cycle is regulated by feedback controls that can arrest the progress of the cell cycle at specific checkpoints. Failure of feedback controls may predispose cells to undergo apoptotic death in response to a variety of stimuli. Transformed cell lines often carry defects in one or more proteins that regulate cell cycle, and therefore can be used as a model to study how cell cycle controls cell death. The present study investigated whether TCR/CD3-induced apoptosis of human leukemic T cells is cell cycle dependent. Studies of Jurkat and Sup-T13, two human leukemic T cell lines, demonstrated that anti-CD3 Ab-driven activation results in a transient, reversible inhibition of DNA synthesis in Jurkat cells, but results in a persistent, irreversible inhibition of DNA synthesis in Sup-T13 cells. Anti-CD3 mAb blocked Jurkat cells at the G1/S interface without inducing cell death. In contrast, anti-CD3 mAb allowed Sup-T13 cells to enter S phase but inhibited progression into G2 phase and triggered cell death. Electron microscopy showed that anti-CD3 mAb-stimulated Sup-T13 cells acquired the characteristic morphology of apoptosis. The nuclear DNA appeared as oligonucleosome-sized fragments by gel electrophoresis, and as an apoptotic peak displaying lower fluorescence than the DNA content of cells in G1 phase by DNA flow microfluorometry. DNA fragmentation correlated with entry into S phase. The DNA synthesis inhibitor aphidicolin arrested Sup-T13 cells at the G1/S interface and prevented the apoptosis. Therefore, DNA synthesis is required for executing the apoptosis program initiated by TCR/CD3 stimulation of Sup-T13 cells. These data are consistent with the hypothesis that the suicide of activated cycling T cells upon encountering autoantigens may be one of the mechanisms for the immune system to prevent autoimmunity.

Apoptosis↗

PubMed1997

Evidence for DNA-PK-dependent and -independent DNA double-strand break repair pathways in mammalian cells as a function of the cell cycle.

Mice homozygous for the scid (severe combined immune deficiency) mutation are defective in the repair of DNA double-strand breaks (DSBs) and are consequently very X-ray sensitive and defective in the lymphoid V(D)J recombination process. Recently, a strong candidate for the scid gene has been identified as the catalytic subunit of the DNA-dependent protein kinase (DNA-PK) complex. Here, we show that the activity of the DNA-PK complex is regulated in a cell cycle-dependent manner, with peaks of activity found at the G1/early S phase and again at the G2 phase in wild-type cells. Interestingly, only the deficit of the G1/early S phase DNA-PK activity correlated with an increased hypersensitivity to X-irradiation and a DNA DSB repair deficit in synchronized scid pre-B cells. Finally, we demonstrate that the DNA-PK activity found at the G2 phase may be required for exit from a DNA damage-induced G2 checkpoint arrest. These observations suggest the presence of two pathways (DNA-PK-dependent and -independent) of illegitimate mammalian DNA DSB repair and two distinct roles (DNA DSB repair and G2 checkpoint traversal) for DNA-PK in the cellular response to ionizing radiation.

Animals↗

PubMed2026

Papillary Thyroid Carcinoma with Terminal Immune Exhaustion Phenotype Correlates with Increased Risk of Lymph Node Metastasis: An Exploratory Study Combining Flow Cytometry and TCGA.

BACKGROUND: Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, with lymph node metastasis (LNM) being a key predictor of recurrence and poor prognosis. Preoperative detection of LNM remains challenging due to the limitations of imaging modalities, leading to inadequate surgical resection in 20-30% of patients. While immune checkpoint molecules have been implicated in PTC progression, the heterogeneity of CD8+ T cell exhaustion subsets and their specific association with LNM remain poorly defined. In this study, we aimed to perform an exploratory characterization of the distinct immune landscape of PTC prone to LNM, with a focus on terminal immune exhaustion, in order to generate hypotheses for improved risk stratification and therapeutic strategies. METHODS: Fresh PTC tissues from 40 patients (22 LNM-positive and 18 LNM-negative) were analyzed via flow cytometry (FCM) to quantify immune cell subsets, inflammatory cytokines, and chemokines. Immunohistochemistry (IHC) validated CD45+ immune cell infiltration. Transcriptomic and clinical data from 448 PTC patients in The Cancer Genome Atlas (TCGA-PTC) cohort were used for bioinformatic analysis consistent with the observed phenotype, including Gene Set Variation Analysis (GSVA) of terminal exhaustion gene signatures. RESULTS: LNM-positive PTC exhibited a unique inflammatory milieu with significantly elevated IL-6, IL-1ra, CCL5, and IL-9 levels (all p < 0.05) in tumor interstitial fluid. FCM analysis revealed that LNM-positive PTC had increased infiltration of total CD45+ immune cells, CD3+ T cells, and CD3+CD8+ T cells (all p < 0.05). Critically, terminally exhausted PD-1hiTIM-3+ CD8+ T cells were significantly enriched in LNM-positive PTC (p = 0.022) and positively correlated with extrathyroidal extension (p = 0.044). Additionally, LNM risk was associated with increased CD4+ regulatory T (Treg) cell frequency (p = 0.023) and elevated CTLA-4 expression on CD4+ T cells (p = 0.047). In TCGA-PTC validation, the terminal exhaustion gene signature was predominantly enriched in LNM-positive (p < 0.0001) and advanced-stage PTC (p < 0.001) and strongly correlated with BRAF mutation (predominantly V600E) (p < 0.0001)-the most common oncogenic driver in aggressive PTC. CONCLUSIONS: Our findings suggest a terminal immune exhaustion phenotype (characterized by PD-1hiTIM-3+ CD8+ T cells and Treg enrichment) as a potential key feature associated with LNM-prone PTC. This phenotype shows consistency across clinical samples and TCGA datasets, linking BRAF mutation (predominantly V600E) to immune suppression and metastatic potential. These insights provide a novel exploratory immune-based biomarker for LNM risk stratification and support the potential of combining anti-PD-1/TIM-3 therapy with BRAF inhibitors for high-risk PTC, which should be confirmed in future studies.

lymph node metastasis↗

PubMed2004

Modern diagnostics in chronic myeloproliferative diseases (CMPDs).

According to the new WHO classification a group of chronic myeloproliferative diseases (CMPDs) were defined: chronic myeloid leukemia (CML), chronic neutrophilic leukemia (CNL), chronic eosinophilic leukemia and hypereosinophilic syndrome (CEL/HES), polycythemia vera (PV), chronic idiopathic myelofibrosis (with extramedullary hematopoiesis, CIMF), essential thrombocythemia (ET), and so called CMPD/unclassifiable. As clinical features and laboratory findings differ widely between these diseases several diagnostic approaches are mandatory at diagnosis for classification and are needed also for follow up studies, especially for the measurement of minimal residual disease (MRD). We here outline the laboratory set up at diagnosis and during follow up in CMPDs with specific focus on the respective therapeutical consequences. Only by using a comprehensive diagnostic panel including cytomorphology, cytogenetics, and molecular genetic methods establishing the correct diagnosis, optimizing treatment as well as evaluating treatment response is possible in CMPDs today.

Blood Cell Count↗