Multifaceted deregulation of gene expression and protein synthesis with age.

Protein synthesis represents a major metabolic activity of the cell. However, how it is affected by aging and how this in turn impacts cell function remains largely unexplored. To address this question, herein we characterized age-related changes in both the transcriptome and translatome of mouse tissues over the entire life span. We showed that the transcriptome changes govern those in the translatome and are associated with altered expression of genes involved in inflammation, extracellular matrix, and lipid metabolism. We also identified genes that may serve as candidate biomarkers of aging. At the translational level, we uncovered sustained down-regulation of a set of 5'-terminal oligopyrimidine (5'-TOP) transcripts encoding protein synthesis and ribosome biogenesis machinery and regulated by the mTOR pathway. For many of them, ribosome occupancy dropped twofold or even more. Moreover, with age, ribosome coverage gradually decreased in the vicinity of start codons and increased near stop codons, revealing complex age-related changes in the translation process. Taken together, our results reveal systematic and multidimensional deregulation of protein synthesis, showing how this major cellular process declines with age.

Protein encoded in human telomerase RNA is involved in cell protective pathways.

Several studies have described functional peptides encoded in RNA that are considered to be noncoding. Telomerase RNA together with telomerase reverse transcriptase and regulatory proteins make up the telomerase complex, the major component of the telomere length-maintaining machinery. In contrast to protein subunits, telomerase RNA is expressed constitutively in most somatic cells where telomerase reverse transcriptase is absent. We show here that the transcript of human telomerase RNA codes a 121 amino acid protein (hTERP). The existence of hTERP was shown by immunoblotting, immunofluorescence microscopy and mass spectroscopy. Gain-of-function and loss-of-function experiments showed that hTERP protects cells from drug-induced apoptosis and participates in the processing of autophagosome. We suggest that hTERP regulates crosstalk between autophagy and apoptosis and is involved in cellular adaptation under stress conditions.

Multi-omic profiling of follicular lymphoma reveals changes in tissue architecture and enhanced stromal remodeling in high-risk patients.

Follicular lymphoma (FL) is a generally incurable malignancy that evolves from developmentally blocked germinal center (GC) B cells. To promote survival and immune escape, tumor B cells undergo significant genetic changes and extensively remodel the lymphoid microenvironment. Dynamic interactions between tumor B cells and the tumor microenvironment (TME) are hypothesized to contribute to the broad spectrum of clinical behaviors observed among FL patients. Despite the urgent need, existing clinical tools do not reliably predict disease behavior. Using a multi-modal strategy, we examined cell-intrinsic and -extrinsic factors governing progression and therapeutic outcomes in FL patients enrolled onto a prospective clinical trial. By leveraging the strengths of each platform, we identify several tumor-specific features and microenvironmental patterns enriched in individuals who experience early relapse, the most high-risk FL patients. These features include stromal desmoplasia and changes to the follicular growth pattern present 20 months before first progression and first relapse.

Follicular Lymphoma Microenvironment Characteristics Associated with Tumor Cell Mutations and MHC Class II Expression.

Follicular lymphoma (FL) is a B-cell malignancy with a complex tumor microenvironment that is rich in nonmalignant immune cells. We applied single-cell RNA sequencing to characterize the diverse tumor and immune cell populations of FL and identified major phenotypic subsets of FL T cells, including a cytotoxic CD4 T-cell population. We characterized four major FL subtypes with differential representation or relative depletion of distinct T-cell subsets. By integrating exome sequencing, we observed that somatic mutations are associated with, but not definitive for, reduced MHC expression on FL cells. In turn, expression of MHCII genes by FL cells was associated with significant differences in the proportions and targetable immunophenotypic characteristics of T cells. This provides a classification framework of the FL microenvironment in association with FL genotypes and MHC expression, and informs different potential immunotherapeutic strategies based upon tumor cell MHCII expression. SIGNIFICANCE: We have characterized the FL-infiltrating T cells, identified cytotoxic CD4 T cells as an important component that is associated with tumor cell-intrinsic characteristics, and identified sets of targetable immune checkpoints on T cells that differed from FLs with normal versus low MHC expression. See related commentary by Melnick, p. 374. This article is highlighted in the In This Issue feature, p. 369.

Monoclonal antibody therapy efficacy can be boosted by combinations with other treatments: Predictions using an integrated Alzheimer's Disease Platform.

For many years, clinical research in Alzheimer's disease (AD) has focused on attempts to identify the most explicit biomarker, namely amyloid beta. Unfortunately, the numerous therapies that have been developed have failed in clinical practice. AD arises as a consequence of multiple factors, and as such it requires a more mechanistic analytical approach than statistical modeling. Quantitative systems pharmacology modeling is a valuable tool for drug development. It utilizes in vitro data for the calibration of parameters, embeds them into physiologically based structures, and explores translation between animals and humans. Such an approach allows for a quantitative study of the dynamics of the interactions between multiple factors or variables. Here, we present an overview of the quantitative translational model in AD, which embraces current preclinical and clinical data. The previously published description of amyloid physiology has been updated and joined with a model for tau pathology and multiple intraneuronal processes responsible for cellular transport, metabolism, or proteostasis. In addition, several hypotheses regarding the best correlates of cognitive deterioration have been validated using clinical data. Here, the amyloid hypothesis was unable to predict the aducanumab clinical trial data, whereas simulations of cognitive impairment coupled with tau seeding or neuronal breakdown (expressed as caspase activity) matched the data. A satisfactory validation of the data from multiple preclinical and clinical studies was followed by an attempt to predict the results of combinatorial treatment with targeted immunotherapy and activation of autophagy using rapamycin. The combination is predicted to yield better efficacy than immunotherapy alone.