Benchmarking multi-ancestry prostate cancer polygenic risk scores in a real-world cohort.

Prostate cancer is a heritable disease with ancestry-biased incidence and mortality. Polygenic risk scores (PRSs) offer promising advancements in predicting disease risk, including prostate cancer. While their accuracy continues to improve, research aimed at enhancing their effectiveness within African and Asian populations remains key for equitable use. Recent algorithmic developments for PRS derivation have resulted in improved pan-ancestral risk prediction for several diseases. In this study, we benchmark the predictive power of six widely used PRS derivation algorithms, including four of which adjust for ancestry, against prostate cancer cases and controls from the UK Biobank and All of Us cohorts. We find modest improvement in discriminatory ability when compared with a simple method that prioritizes variants, clumping, and published polygenic risk scores. Our findings underscore the importance of improving upon risk prediction algorithms and the sampling of diverse cohorts.

Transcriptomic signatures of chronic active antibody-mediated rejection deciphered by RNA sequencing of human kidney allografts.

Natural killer (NK) cells mediate spontaneous cell-mediated cytotoxicity and antibody-dependent cell-mediated cytotoxicity. This dual functionality could enable their participation in chronic active antibody-mediated rejection (CA-ABMR). Earlier microarray profiling studies have not subcategorized antibody-mediated rejection into CA-ABMR and active-ABMR, and the gene expression pattern of CA-ABMR has not been compared with that of T cell-mediated rejection (TCMR). To fill these gaps, we RNA sequenced human kidney allograft biopsies categorized as CA-ABMR, active-ABMR, TCMR, or No Rejection (NR). Among the 15,910 genes identified in the biopsies, 60, 114, and 231 genes were uniquely overexpressed in CA-ABMR, TCMR, and active-ABMR, respectively; compared to NR, 50 genes were shared between CA-ABMR and active-ABMR, and 164 genes between CA-ABMR and TCMR. The overexpressed genes were annotated to NK cells and T cells in CA-ABMR and TCMR, and to neutrophils and monocytes in active-ABMR. The NK cell cytotoxicity and allograft rejection pathways were enriched in CA-ABMR. Genes encoding perforin, granzymes, and death receptor were overexpressed in CA-ABMR versus active-ABMR but not compared to TCMR. NK cell cytotoxicity pathway gene set variation analysis score was higher in CA-ABMR compared to active-ABMR but not in TCMR. Principal component analysis of the deconvolved immune cellular transcriptomes separated CA-ABMR and TCMR from active-ABMR and NR. Immunohistochemistry of kidney allograft biopsies validated a higher proportion of CD56+ NK cells in CA-ABMR than in active-ABMR. Thus, CA-ABMR was exemplified by the overexpression of the NK cell cytotoxicity pathway gene set and, surprisingly, molecularly more like TCMR than active-ABMR.

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.

G-Quadruplexes as pathogenic drivers in neurodegenerative disorders.

G-quadruplexes (G4s), higher-order DNA and RNA secondary structures featuring guanine-rich nucleic acid sequences with various conformations, are widely distributed in the human genome. These structural motifs are known to participate in basic cellular processes, including transcription, splicing, and translation, and their functions related to health and disease are becoming increasingly recognized. In this review, we summarize the landscape of G4s involved in major neurodegenerative disorders, describing the genes that contain G4-forming sequences and proteins that have high affinity for G4-containing elements. The functions of G4s are diverse, with potentially protective or deleterious effects in the pathogenic cascades of various neurological diseases. While the studies of the functions of G4s in vivo, including those involved in pathophysiology, are still in their early stages, we will nevertheless discuss the evidence pointing to their biological relevance. A better understanding of this unique structural element in the biological context is important for unveiling its potential roles in the pathogenesis of diseases such as neurodegeneration and for designing new diagnostic and therapeutic strategies.

Developing a predictive model for metastatic potential in pancreatic neuroendocrine tumor.

CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive. OBJECTIVE: Use machine learning to develop predictive models of PNET metastatic potential dependent upon transcriptomic signature. METHODS: RNA-sequencing data were analyzed from 95 surgically-resected primary PNETs in an international cohort. Two cohorts were generated with equally balanced metastatic PNET composition. Machine learning was used to create predictive models distinguishing between localized and metastatic tumors. Models were validated on an independent cohort of 29 formalin-fixed, paraffin-embedded samples using NanoString nCounter®, a clinically-available mRNA quantification platform. RESULTS: Gene expression analysis identified concordant differentially expressed genes between the two cohorts. Gene set enrichment analysis identified additional genes that contributed to enriched biologic pathways in metastatic PNETs. Expression values for these genes were combined with an additional 7 genes known to contribute to PNET oncogenesis and prognosis, including ARX and PDX1. Eight specific genes (AURKA, CDCA8, CPB2, MYT1L, NDC80, PAPPA2, SFMBT1, ZPLD1) were identified as sufficient to classify the metastatic status with high sensitivity (87.5% - 93.8%) and specificity (78.1% - 96.9%). These models remained predictive of the metastatic phenotype using NanoString nCounter® on the independent validation cohort, achieving a median AUROC of 0.886. CONCLUSIONS: We identified and validated an eight-gene panel predictive of the metastatic phenotype in PNETs, which can be detected using the clinically-available NanoString nCounter® system. This panel should be studied prospectively to determine its utility in guiding operative versus non-operative management.

FORMATION OF MALIGNANT, METASTATIC SMALL CELL LUNG CANCERS THROUGH OVERPRODUCTION OF cMYC PROTEIN IN TP53 AND RB1 DEPLETED PULMONARY NEUROENDOCRINE CELLS DERIVED FROM HUMAN EMBRYONIC STEM CELLS.

We recently described our initial efforts to develop a model for small cell lung cancer (SCLC) derived from human embryonic stem cells (hESCs) that were differentiated to form pulmonary neuroendocrine cells (PNECs), a putative cell of origin for neuroendocrine-positive SCLC. Although reduced expression of the tumor suppressor genes TP53 and RB1 allowed the induced PNECs to form subcutaneous growths in immune-deficient mice, the tumors did not display the aggressive characteristics of SCLC seen in human patients. Here we report that the additional, doxycycline-regulated expression of a transgene encoding wild-type or mutant cMYC protein promotes rapid growth, invasion, and metastasis of these hESC-derived cells after injection into the renal capsule. Similar to others, we find that the addition of cMYC encourages the formation of the SCLC-N subtype, marked by high levels of NEUROD1 RNA. Using paired primary and metastatic samples for RNA sequencing, we observe that the subtype of SCLC does not change upon metastatic spread and that production of NEUROD1 is maintained. We also describe histological features of these malignant, SCLC-like tumors derived from hESCs and discuss potential uses of this model in efforts to control and better understand this recalcitrant neoplasm.

Advanced Age in Humans and Mouse Models of Glioblastoma Show Decreased Survival from Extratumoral Influence.

PURPOSE: Glioblastoma (GBM) is the most common aggressive primary malignant brain tumor in adults with a median age of onset of 68 to 70 years old. Although advanced age is often associated with poorer GBM patient survival, the predominant source(s) of maladaptive aging effects remains to be established. Here, we studied intratumoral and extratumoral relationships between adult patients with GBM and mice with brain tumors across the lifespan. EXPERIMENTAL DESIGN: Electronic health records at Northwestern Medicine and the NCI SEER databases were evaluated for GBM patient age and overall survival. The commercial Tempus and Caris databases, as well as The Cancer Genome Atlas were profiled for gene expression, DNA methylation, and mutational changes with varying GBM patient age. In addition, gene expression analysis was performed on the extratumoral brain of younger and older adult mice with or without a brain tumor. The survival of young and old wild-type or transgenic (INK-ATTAC) mice with a brain tumor was evaluated after treatment with or without senolytics and/or immunotherapy. RESULTS: Human patients with GBM ≥65 years of age had a significantly decreased survival compared with their younger counterparts. While the intra-GBM molecular profiles were similar between younger and older patients with GBM, non-tumor brain tissue had a significantly different gene expression profile between young and old mice with a brain tumor and the eradication of senescent cells improved immunotherapy-dependent survival of old but not young mice. CONCLUSIONS: This work suggests a potential benefit for combining senolytics with immunotherapy in older patients with GBM.

Pan-cancer analysis reveals molecular patterns associated with age.

Older age is a strong risk factor for several diseases, including cancer. The etiology and biology of age-associated differences among cancers are poorly understood. To address this knowledge gap, we aim to delineate differences in tumor molecular characteristics between younger and older patients across a variety of tumor types from The Cancer Genome Atlas. We show that these groups exhibit widespread molecular differences in select tumor types. Our work shows that tumors in younger individuals exhibit a dysregulated molecular aging phenotype and are associated with hallmarks of premature senescence. Additionally, we find that these tumors are enriched for driver gene mutations, resulting in homologous recombination defects. Lastly, we observe a trend toward decreased immune infiltration and function in older patients and find that, immunologically, young tumor tissue resembles aged healthy tissue. Taken together, we find that tumors from young individuals possess unique characteristics that may be leveraged for therapy.

Effects of B cell-activating factor on tumor immunity.

Immunotherapies that modulate T cell function have been firmly established as a pillar of cancer therapy, whereas the potential for B cells in the antitumor immune response is less established. B cell-activating factor (BAFF) is a B cell-activating cytokine belonging to the TNF ligand family that has been associated with autoimmunity, but little is known about its effects on cancer immunity. We find that BAFF upregulates multiple B cell costimulatory molecules; augments IL-12a expression, consistent with Be-1 lineage commitment; and enhances B cell antigen-presentation to CD4+ Th cells in vitro. In a syngeneic mouse model of melanoma, BAFF upregulates B cell CD40 and PD-L1 expression; it also modulates T cell function through increased T cell activation and TH1 polarization, enhanced expression of the proinflammatory leukocyte trafficking chemokine CCR6, and promotion of a memory phenotype, leading to enhanced antitumor immunity. Similarly, adjuvant BAFF promotes a memory phenotype of T cells in vaccine-draining lymph nodes and augments the antitumor efficacy of whole cell vaccines. BAFF also has distinct immunoregulatory functions, promoting the expansion of CD4+Foxp3+ Tregs in the spleen and tumor microenvironment (TME). Human melanoma data from The Cancer Genome Atlas (TCGA) demonstrate that BAFF expression is positively associated with overall survival and a TH1/IFN-γ gene signature. These data support a potential role for BAFF signaling as a cancer immunotherapy.

Publisher Correction: L3MBTL1 regulates ALS/FTD-associated proteotoxicity and quality control.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

L3MBTL1 regulates ALS/FTD-associated proteotoxicity and quality control.

Misfolded protein toxicity and failure of protein quality control underlie neurodegenerative diseases including amyotrophic lateral sclerosis and frontotemporal dementia. Here, we identified Lethal(3)malignant brain tumor-like protein 1 (L3MBTL1) as a key regulator of protein quality control, the loss of which protected against the proteotoxicity of mutant Cu/Zn superoxide dismutase or C9orf72 dipeptide repeat proteins. L3MBTL1 acts by regulating p53-dependent quality control systems that degrade misfolded proteins. SET domain-containing protein 8, an L3MBTL1-associated p53-binding protein, also regulated clearance of misfolded proteins and was increased by proteotoxicity-associated stresses in mammalian cells. Both L3MBTL1 and SET domain-containing protein 8 were upregulated in the central nervous systems of mouse models of amyotrophic lateral sclerosis and human patients with amyotrophic lateral sclerosis/frontotemporal dementia. The role of L3MBTL1 in protein quality control is conserved from Caenorhabditis elegans to mammalian neurons. These results reveal a protein quality-control pathway that operates in both normal stress response and proteotoxicity-associated neurodegenerative diseases.

Cell-type specific differences in promoter activity of the ALS-linked C9orf72 mouse ortholog.

A hexanucleotide repeat expansion in the C9orf72 gene is the most common cause of inherited forms of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). Both loss-of-function and gain-of-function mechanisms have been proposed to underlie this disease, but the pathogenic pathways are not fully understood. To better understand the involvement of different cell types in the pathogenesis of ALS, we systematically analyzed the distribution of promoter activity of the mouse ortholog of C9orf72 in the central nervous system. We demonstrate that C9orf72 promoter activity is widespread in both excitatory and inhibitory neurons as well as in oligodendrocytes and oligodendrocyte precursor cells. In contrast, few microglia and astrocytes exhibit detectable C9orf72 promoter activity. Although at a gross level, the distribution of C9orf72 promoter activity largely follows overall cellular density, we found that it is selectively enriched in subsets of neurons and glial cells that degenerate in ALS. Specifically, we show that C9orf72 promoter activity is enriched in corticospinal and spinal motor neurons as well as in oligodendrocytes in brain regions that are affected in ALS. These results suggest that cell autonomous changes in both neurons and glia may contribute to C9orf72-mediated disease, as has been shown for mutations in superoxide dismutase-1 (SOD1).