Depression psychotherapies have been studied using hundreds of randomized controlled trials and dozens of meta-analyses, but their findings are not consistently supportive of a single conclusion. Are the observed discrepancies attributable to specific meta-analytical decisions, or do the majority of analytical approaches arrive at a consistent conclusion?
To resolve these inconsistencies, we propose a multiverse meta-analysis encompassing all conceivable meta-analyses, employing every available statistical approach.
Our investigation encompassed four bibliographic databases—PubMed, EMBASE, PsycINFO, and the Cochrane Register of Controlled Trials—examining publications until January 1, 2022. In our study, each randomized controlled trial comparing psychotherapies against control conditions, without any restrictions on the type of psychotherapy, patient group, intervention approach, comparison group, or diagnosis, was deemed relevant. We systematically determined every meta-analysis that could be derived from the combination of these inclusion criteria and estimated the resulting pooled effect sizes using fixed-effect, random-effects, 3-level models, and robust variance estimation techniques.
A meta-analytical approach, incorporating both uniform and PET-PEESE (precision-effect test and precision-effect estimate with standard error) models, was employed. As part of the study's pre-emptive measures, this study was preregistered, and this link provides access to the registration: https//doi.org/101136/bmjopen-2021-050197.
Following the initial review of 21,563 records, 3,584 full-text articles were extracted for further scrutiny; 415 of these articles met the study inclusion criteria, representing 1,206 effect sizes and encompassing 71,454 participants. We derived 4281 meta-analyses by examining all conceivable couplings of inclusion criteria and meta-analytical methods. For these meta-analyses, a consistent pattern emerged, indicating Hedges' g as the average summary effect size.
A moderate effect size of 0.56 was noted, characterized by a range of values.
Numerical values extend between negative sixty-six and two hundred fifty-one. Overall, 90% of these meta-analyses showcased effects with clinical significance.
Psychotherapy for depression proved demonstrably effective across multiple universes, according to the findings of a comprehensive meta-analysis. Notably, meta-analyses that included studies with a high probability of bias, which compared the intervention against a control group placed on a waitlist, and that did not adjust for publication bias, showed larger effect sizes.
Through multiverse meta-analysis, the consistent efficacy of psychotherapies in treating depression was robustly demonstrated. Interestingly, meta-analyses of studies prone to high bias, which evaluated the intervention against wait-list controls without correcting for publication bias, produced inflated effect sizes.
Cellular immunotherapies for cancer work by increasing the number of tumor-specific T cells in a patient's immune system, thereby bolstering the body's natural defenses against the disease. Peripheral T cells are genetically modified in CAR therapy to be attracted to tumor cells, demonstrating impressive efficacy, particularly in blood cancers. Nevertheless, CAR-T cell therapies encounter obstacles in treating solid tumors, owing to various resistance mechanisms. The tumor microenvironment, as we and others have demonstrated, exhibits a specific metabolic landscape that hinders immune cell activity. The process of T cell differentiation, when altered within the tumor microenvironment, disrupts mitochondrial biogenesis, which subsequently triggers a significant, inherent metabolic deficiency. Our previous work, and that of others, has shown that murine T cell receptor (TCR)-transgenic cells can benefit from heightened mitochondrial biogenesis, prompting our investigation into whether a metabolic reprogramming strategy could also yield improvement in human CAR-T cells.
A549 tumor-bearing NSG mice were infused with anti-EGFR CAR-T cells. An analysis of tumor-infiltrating lymphocytes was conducted to determine their metabolic deficiencies and level of exhaustion. PPAR-gamma coactivator 1 (PGC-1) carrying lentiviruses, PGC-1.
To achieve co-transduction of T cells with anti-EGFR CAR lentiviruses, NT-PGC-1 constructs were used. check details RNA sequencing, alongside flow cytometry and Seahorse analysis, were components of our in vitro metabolic studies. Lastly, A549-carrying NSG mice received therapeutic treatment with either PGC-1 or NT-PGC-1 anti-EGFR CAR-T cells. Co-expression of PGC-1 shaped the tumor-infiltrating CAR-T cell composition, which we diligently analyzed.
Our study showcases that an engineered version of PGC-1, resistant to inhibition, is capable of metabolically reprogramming human CAR-T cells. The transcriptomic profile of CAR-T cells transduced with PGC-1 demonstrated a successful induction of mitochondrial biogenesis, but also a concomitant upregulation of programs associated with effective cellular action. Treatment with these cells in immunodeficient animals bearing human solid tumors yielded a marked enhancement of in vivo effectiveness. check details Whereas the full-length PGC-1 protein led to positive outcomes, a truncated version, NT-PGC-1, was not as successful in improving in vivo results.
Our data, supporting the role of metabolic reprogramming in immunomodulatory treatments, also indicate the utility of genes like PGC-1 for enhanced cell therapies targeting solid tumors, integrated with chimeric receptors or TCRs.
Metabolic reshaping, as revealed by our data, plays a role in the immunomodulatory responses triggered by treatments, and genes such as PGC-1 show promise as potential additions to cell therapies targeting solid tumors, alongside chimeric receptors or T-cell receptors.
Primary and secondary resistance poses a substantial barrier to progress in cancer immunotherapy. Subsequently, a superior understanding of the underlying mechanisms related to immunotherapy resistance is vital to improving treatment outcomes.
This study explored two mouse models with an observed resistance to therapeutic vaccine-induced tumor regression. The tumor microenvironment is investigated through the combined use of high-dimensional flow cytometry and therapeutic approaches.
An identification of immunological factors which fuel immunotherapy resistance was possible due to the specified settings.
The tumor immune infiltrate, assessed during early and late regression stages, showed a modification in macrophage activity, from a configuration promoting tumor rejection to one that fosters tumor advancement. A remarkable and rapid decline in the number of tumor-infiltrating T cells was observed during the concert. CD163, a small but detectable marker, was identified through perturbation studies.
Only a distinct macrophage population, marked by a high expression level of various tumor-promoting macrophage markers and an anti-inflammatory transcriptomic pattern, is responsible for this effect; other macrophages are not. check details Thorough analyses demonstrated their localization at the invasive edges of the tumor, revealing a higher resistance to CSF1R inhibition than exhibited by other macrophages.
The activity of heme oxygenase-1, a key component in the underlying mechanism of immunotherapy resistance, was verified through various studies. The CD163 transcriptomic profile.
A human monocyte/macrophage population's characteristics are strikingly mirrored in macrophages, implying their suitability as targets to bolster the impact of immunotherapy.
This study's subject matter comprised a small set of CD163-bearing cells.
In terms of primary and secondary resistance to T-cell-based immunotherapies, tissue-resident macrophages are the identified culprit. The presence of these CD163 proteins is noteworthy,
Csf1r-targeted therapies encounter resistance in M2 macrophages, highlighting the need for a deeper understanding of the underlying mechanisms. Identifying these mechanisms enables the specific targeting of these macrophages, which opens new avenues for overcoming immunotherapy resistance.
In this examination, a small group of CD163hi tissue-resident macrophages is determined to be the cause of both initial and subsequent resistance to T-cell-based immunotherapeutic approaches. While resistant to CSF1R-targeted therapies, in-depth analysis of the underlying mechanisms driving CD163hi M2 macrophage immunotherapy resistance reveals potential for specific targeting, offering novel therapeutic interventions to overcome this resistance.
The tumor microenvironment harbors myeloid-derived suppressor cells (MDSCs), a mixed group of cells that inhibit the effectiveness of anti-tumor immunity. The unfavorable clinical trajectory in cancer is often observed alongside the expansion of various subpopulations of MDSCs. A deficiency in the key enzyme lysosomal acid lipase (LAL), impacting neutral lipid metabolism in mice (LAL-D), is associated with the differentiation of myeloid lineage cells into MDSCs. These sentences are to be rephrased ten times, with each rendition displaying diverse structural arrangements.
MDSCs' role extends beyond suppressing immune surveillance, encompassing the stimulation of cancer cell proliferation and invasion. Understanding the intricate mechanisms responsible for MDSC formation will be critical for improved cancer detection, prognosis, and stopping its expansion and dissemination.
To delineate molecular and cellular distinctions between normal and abnormal cells, single-cell RNA sequencing (scRNA-seq) was employed.
Ly6G, a cellular component stemming from bone marrow.
The myeloid lineages present in a mouse. Blood samples from NSCLC patients were assessed via flow cytometry to determine LAL expression and metabolic pathways in diverse myeloid subsets. To determine the impact of programmed death-1 (PD-1) immunotherapy, myeloid subset profiles in NSCLC patients were compared in the pre- and post-treatment phases.
RNA sequencing performed on individual cells, known as scRNA-seq.
CD11b
Ly6G
Differential gene expression patterns were observed in two distinct MDSC clusters, which also demonstrated a significant metabolic shift, favoring glucose utilization and increased reactive oxygen species (ROS) generation.