bioRxiv ScienceSearch

Biology subjects

Fischer, I.

Publications and source records attributed to Fischer, I..

3 recordsLinked to original sources

FIP200 organizes the autophagy machinery at p62-ubiquitin condensates beyond activation of the ULK1 kinase

Macroautophagy is a conserved degradation pathway, which mediates cellular homeostasis by the delivery of harmful substances into lysosomes. This is achieved by the sequestration of these substances referred to as cargo within double membrane vesicles, the autophagosomes, which form de novo. Among the many cargoes that are targeted by autophagy are condensates containing p62 and ubiquitinated proteins. p62 recruits the FIP200 protein to initiate autophagosome formation at the condensates. How FIP200 in turn organizes the autophagy machinery is unclear. Here we show that FIP200 is dispensable for the recruitment of the upstream autophagy machinery to the condensates, but it is necessary for phosphatidylinositol 3-phosphate formation and WIPI2 recruitment. We further find that FIP200 is required for the activation of the ULK1 kinase. Surprisingly, ULK1 kinase activity is not strictly required for autophagosome formation at p62 condensates. Super-resolution microscopy of p62 condensates revealed that FIP200 surrounds the condensates where it spatially organizes ATG13 and ATG9A for productive autophagosome formation. Our data provide a mechanistic insight into how FIP200 orchestrates autophagosome initiation at the cargo.

cell biology

The Genomic Landscape of Prostate Cancer Brain Metastases

Lethal prostate cancer commonly metastasizes to bone, lymph nodes, and visceral organs but with more effective therapies, there is an increased frequency of metastases to the brain. Little is known about the genomic drivers of prostate cancer brain metastases (PCBM). To address this, we conducted a comprehensive multi-regional, genomic, and targeted transcriptomic analysis of PCBM from 28 patients. We compared whole-exome and targeted RNA sequencing with matched primary tumors when available (n = 10) and with publicly available genomic data from non-brain prostate cancer metastases (n = 416). In addition to common alterations in TP53, AR, RB1, and PTEN, we identified highly significant enrichment of mutations in NF1 (25% cases (6/28), q = 0.049, 95% CI = 2.38 - 26.52, OR = 8.37) and RICTOR (17.9% cases (5/28), q = 0.01, 95% CI = 6.74 - 480.15, OR = 43.7) in PCBM compared to non-brain prostate cancer metastases, suggesting possible activation of the druggable pathways RAS/RAF/MEK/ERK and PI3K/AKT/mTOR, respectively. Compared to non-brain prostate cancer metastases, PCBM were almost three times as likely to harbor DNA homologous repair (HR) alterations (42.9% cases (12/28), p =0.016, 95% CI = 1.17 - 6.64, OR = 2.8). When considering the combination of somatic mutations, copy number alteration, and Large-scale State Transitions, 64.3% of patients (18/28) were affected. HR alterations may be critical drivers of brain metastasis that potentially provide cancer cells a survival advantage during re-establishment in a special microenvironment. We demonstrate that PCBM have genomic dependencies that may be exploitable through clinical interventions including PARP inhibition.

cancer biology

Whole genome sequencing analysis of the cardiometabolic proteome

The human proteome is a crucial intermediate between complex diseases and their genetic and environmental components, and an important source of drug development targets and biomarkers. Here, we comprehensively assess the genetic architecture of 257 circulating protein biomarkers of cardiometabolic relevance through high-depth (22.5x) whole-genome sequencing (WGS) in 1,328 individuals. We discover 131 independent sequence variant associations (P<7.45x10-11) across the allele frequency spectrum, all of which replicate in an independent cohort (n=1,605, 18.4x WGS). We identify for the first time replicating evidence for rare-variant cis-acting protein quantitative trait loci for five genes, involving both coding and non-coding variation. We construct and validate polygenic scores that explain up to 45% of protein level variation. We find causal links between protein levels and disease risk, identifying high-value biomarkers and drug development targets.

genetics