Comparative analyses of gene networks mediating cancer metastatic potentials across lineage types.

Studies have identified genes and molecular pathways regulating cancer metastasis. However, it remains largely unknown whether metastatic potentials of cancer cells from different lineage types are driven by the same or different gene networks. Here, we aim to address this question through integrative analyses of 493 human cancer cells' transcriptomic profiles and their metastatic potentials in vivo. Using an unsupervised approach and considering both gene coexpression and protein-protein interaction networks, we identify different gene networks associated with various biological pathways (i.e. inflammation, cell cycle, and RNA translation), the expression of which are correlated with metastatic potentials across subsets of lineage types. By developing a regularized random forest regression model, we show that the combination of the gene module features expressed in the native cancer cells can predict their metastatic potentials with an overall Pearson correlation coefficient of 0.90. By analyzing transcriptomic profile data from cancer patients, we show that these networks are conserved in vivo and contribute to cancer aggressiveness. The intrinsic expression levels of these networks are correlated with drug sensitivity. Altogether, our study provides novel comparative insights into cancer cells' intrinsic gene networks mediating metastatic potentials across different lineage types, and our results can potentially be useful for designing personalized treatments for metastatic cancers.

Mutations in microRNA processing genes in Wilms tumors derepress the IGF2 regulator PLAG1.

Many childhood Wilms tumors are driven by mutations in the microRNA biogenesis machinery, but the mechanism by which these mutations drive tumorigenesis is unknown. Here we show that the transcription factor pleomorphic adenoma gene 1 (PLAG1) is a microRNA target gene that is overexpressed in Wilms tumors with mutations in microRNA processing genes. Wilms tumors can also overexpress PLAG1 through copy number alterations, and PLAG1 expression correlates with prognosis in Wilms tumors. PLAG1 overexpression accelerates growth of Wilms tumor cells in vitro and induces neoplastic growth in the developing mouse kidney in vivo. In both settings, PLAG1 transactivates insulin-like growth factor 2 (IGF2), a key Wilms tumor oncogene, and drives mammalian target of rapamycin complex 1 (mTORC1) signaling. These data link microRNA impairment to the PLAG1-IGF2 pathway, providing new insight into the manner in which common Wilms tumor mutations drive disease pathogenesis.

Low-input RNase footprinting for simultaneous quantification of cytosolic and mitochondrial translation.

We describe a low-input RNase footprinting approach for the rapid quantification of ribosome-protected fragments with as few as 1000 cultured cells. The assay uses a simplified procedure to selectively capture ribosome footprints based on optimized RNase digestion. It simultaneously maps cytosolic and mitochondrial translation with single-nucleotide resolution. We applied it to reveal selective functions of the elongation factor TUFM in mitochondrial translation, as well as synchronized repression of cytosolic translation after TUFM perturbation. We show the assay is applicable to small amounts of primary tissue samples with low protein synthesis rates, including snap-frozen tissues and immune cells from an individual's blood draw. We showed its feasibility to characterize the personalized immuno-translatome. Our analyses revealed that thousands of genes show lower translation efficiency in monocytes compared with lymphocytes, and identified thousands of translated noncanonical open reading frames (ORFs). Altogether, our RNase footprinting approach opens an avenue to assay transcriptome-wide translation using low-input samples from a wide range of physiological conditions.

Derivation, Validation, and Clinical Relevance of a Pediatric Sepsis Phenotype With Persistent Hypoxemia, Encephalopathy, and Shock.

OBJECTIVES: Untangling the heterogeneity of sepsis in children and identifying clinically relevant phenotypes could lead to the development of targeted therapies. Our aim was to analyze the organ dysfunction trajectories of children with sepsis-associated multiple organ dysfunction syndrome (MODS) to identify reproducible and clinically relevant sepsis phenotypes and determine if they are associated with heterogeneity of treatment effect (HTE) to common therapies. DESIGN: Multicenter observational cohort study. SETTING: Thirteen PICUs in the United States. PATIENTS: Patients admitted with suspected infections to the PICU between 2012 and 2018. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We used subgraph-augmented nonnegative matrix factorization to identify candidate trajectory-based phenotypes based on the type, severity, and progression of organ dysfunction in the first 72 hours. We analyzed the candidate phenotypes to determine reproducibility as well as prognostic, therapeutic, and biological relevance. Overall, 38,732 children had suspected infection, of which 15,246 (39.4%) had sepsis-associated MODS with an in-hospital mortality of 10.1%. We identified an organ dysfunction trajectory-based phenotype (which we termed persistent hypoxemia, encephalopathy, and shock) that was highly reproducible, had features of systemic inflammation and coagulopathy, and was independently associated with higher mortality. In a propensity score-matched analysis, patients with persistent hypoxemia, encephalopathy, and shock phenotype appeared to have HTE and benefit from adjuvant therapy with hydrocortisone and albumin. When compared with other high-risk clinical syndromes, the persistent hypoxemia, encephalopathy, and shock phenotype only overlapped with 50%-60% of patients with septic shock, moderate-to-severe pediatric acute respiratory distress syndrome, or those in the top tier of organ dysfunction burden, suggesting that it represents a nonsynonymous clinical phenotype of sepsis-associated MODS. CONCLUSIONS: We derived and validated the persistent hypoxemia, encephalopathy, and shock phenotype, which is highly reproducible, clinically relevant, and associated with HTE to common adjuvant therapies in children with sepsis.

Widespread stable noncanonical peptides identified by integrated analyses of ribosome profiling and ORF features.

Studies have revealed dozens of functional peptides in putative 'noncoding' regions and raised the question of how many proteins are encoded by noncanonical open reading frames (ORFs). Here, we comprehensively annotate genome-wide translated ORFs across five eukaryotes (human, mouse, zebrafish, worm, and yeast) by analyzing ribosome profiling data. We develop a logistic regression model named PepScore based on ORF features (expected length, encoded domain, and conservation) to calculate the probability that the encoded peptide is stable in humans. Systematic ectopic expression validates PepScore and shows that stable complex-associating microproteins can be encoded in 5'/3' untranslated regions and overlapping coding regions of mRNAs besides annotated noncoding RNAs. Stable noncanonical proteins follow conventional rules and localize to different subcellular compartments. Inhibition of proteasomal/lysosomal degradation pathways can stabilize some peptides especially those with moderate PepScores, but cannot rescue the expression of short ones with low PepScores suggesting they are directly degraded by cellular proteases. The majority of human noncanonical peptides with high PepScores show longer lengths but low conservation across species/mammals, and hundreds contain trait-associated genetic variants. Our study presents a statistical framework to identify stable noncanonical peptides in the genome and provides a valuable resource for functional characterization of noncanonical translation during development and disease.

Rfoot-seq: Transcriptomic RNase Footprinting for Mapping Stable RNA-Protein Complexes and Rapid Ribosome Profiling.

Ribosome profiling isolates ribosome-protected fragments for sequencing and is a valuable method for studying different aspects of RNA translation. However, conventional protocols require millions of input cells and time-consuming steps to isolate translating ribosome complexes using ultracentrifugation or immunoprecipitation. These limitations have prevented their application to rare physiological samples. To address these technical barriers, we developed an RNase footprinting approach named Rfoot-seq to map stable transcriptomic RNA-protein complexes that allows rapid ribosome profiling using low-input samples (Li, Yang, Stroup, Wang, & Ji, 2022). In this assay, we treat a cell lysate with concentrated RNase without complex crosslinking and retained only RNA footprints associated with stable complexes for sequencing. The footprints in coding regions represent ribosome-protected fragments and can be used to study cytosolic and mitochondrial translation simultaneously. Rfoot-seq achieves comparable results to conventional ribosome profiling to quantify ribosome occupancy and works robustly for various cultured cells and primary tissue samples. Moreover, Rfoot-seq maps RNA fragments associated with stable non-ribosomal RNA-protein complexes in noncoding domains of small noncoding RNAs and some long noncoding RNAs. Taken together, Rfoot-seq opens an avenue to quantify transcriptomic translation and characterize functional noncoding RNA domains using low-input samples. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Harvesting and lysing adherent cells Alternate Protocol 1: Harvesting and lysing suspension cells Alternate Protocol 2: Harvesting and lysing primary tissue samples Basic Protocol 2: RNase treatment and footprint purification for low-input samples Alternate Protocol 3: RNase treatment and footprint purification for ultra-low-input samples Basic Protocol 3: Library preparation for high-throughput sequencing Support Protocol: Preparation of dsDNA markers for library size selection Basic Protocol 4: Data analysis and quality control after sequencing.

Derivation and Validation of Novel Phenotypes of Multiple Organ Dysfunction Syndrome in Critically Ill Children.

Importance: Multiple organ dysfunction syndrome (MODS) is a dynamic and heterogeneous process associated with high morbidity and mortality in critically ill children. Objective: To determine whether data-driven phenotypes of MODS based on the trajectories of 6 organ dysfunctions have prognostic and therapeutic relevance in critically ill children. Design, Setting, and Participants: This cohort study included 20 827 pediatric intensive care encounters among 14 285 children admitted to 2 large academic pediatric intensive care units (PICUs) between January 2010 and August 2016. Patients were excluded if they were older than 21 years or had undergone cardiac surgery. The 6 subscores of the pediatric Sequential Organ Failure Assessment (pSOFA) score were calculated for the first 3 days, including the subscores for respiratory, cardiovascular, coagulation, hepatic, neurologic, and renal dysfunctions. MODS was defined as a pSOFA subscore of at least 2 in at least 2 organs. Encounters were split in a 80:20 ratio for derivation and validation, respectively. The trajectories of the 6 subscores were used to derive a set of data-driven phenotypes of MODS using subgraph-augmented nonnegative matrix factorization in the derivation set. Data analysis was conducted from March to October 2019. Exposures: The primary exposure was phenotype membership. In the subset of patients with vasoactive-dependent shock, the interaction between hydrocortisone and phenotype membership and its association with outcomes were examined in a matched cohort. Main Outcomes and Measures: The primary outcome was in-hospital mortality. Secondary outcomes included persistent MODS on day 7, and vasoactive-free, ventilator-free, and hospital-free days. Regression analysis was used to adjust for age, severity of illness, immunocompromised status, and study site. Results: There were 14 285 patients with 20 827 encounters (median [interquartile range] age 5.2 years [1.5-12.7] years; 11 409 [54.8%; 95% CI, 54.1%-55.5%] male patients). Of these, 5297 encounters (25.4%; 95% CI, 24.8%-26.0%) were with patients who had MODS, of which 5054 (95.4%) met the subgraph count threshold and were included in the analysis. Subgraph augmented nonnegative matrix factorization uncovered 4 data-driven phenotypes of MODS, characterized by a combination of neurologic, respiratory, coagulation, and cardiovascular dysfunction, as follows: phenotype 1, severe, persistent encephalopathy (1019 patients [19.2%]); phenotype 2, moderate, resolving hypoxemia (1828 patients [34.5%]); phenotype 3, severe, persistent hypoxemia and shock (1012 patients [19.1%]); and phenotype 4, moderate, persistent thrombocytopenia and shock (1195 patients [22.6%]). These phenotypes were reproducible in a validation set of encounters, had distinct clinical characteristics, and were independently associated with outcomes. For example, using phenotype 2 as reference, the adjusted hazard ratios (aHRs) for death by 28 days were as follows: phenotype 1, aHR of 3.0 (IQR, 2.1-4.3); phenotype 3, aHR of 2.8 (IQR, 2.0-4.1); and phenotype 4, aHR of 1.8 (IQR, 1.2-2.6). Interaction analysis in a matched cohort of patients with vasoactive-dependent shock revealed that hydrocortisone had differential treatment association with vasoactive-free days across phenotypes. For example, patients in phenotype 3 who received hydrocortisone had more vasoactive-free days than those who did not (23 days vs 18 days; P for interaction < .001), whereas patients in other phenotypes who received hydrocortisone either had no difference or had less vasoactive-free days. Conclusions and Relevance: In this study, data-driven phenotyping in critically ill children with MODS uncovered 4 distinct and reproducible phenotypes with prognostic relevance and possible therapeutic relevance. Further validation and characterization of these phenotypes is warranted.

EGF Receptor and mTORC1 Are Novel Therapeutic Targets in Nonseminomatous Germ Cell Tumors.

Germ cell tumors (GCT) are malignant tumors that arise from pluripotent embryonic germ cells and occur in children and young adults. GCTs are treated with cisplatin-based regimens which, while overall effective, fail to cure all patients and cause significant adverse late effects. The seminoma and nonseminoma forms of GCT exhibit distinct differentiation states, clinical behavior, and response to treatment; however, the molecular mechanisms of GCT differentiation are not fully understood. We tested whether the activity of the mTORC1 and MAPK pathways were differentially active in the two classes of GCT. Here we show that nonseminomatous germ cell tumors (NSGCT, including embryonal carcinoma, yolk sac tumor, and choriocarcinoma) from both children and adults display activation of the mTORC1 pathway, while seminomas do not. In seminomas, high levels of REDD1 may negatively regulate mTORC1 activity. In NSGCTs, on the other hand, EGF and FGF2 ligands can stimulate mTORC1 and MAPK signaling, and members of the EGF and FGF receptor families are more highly expressed. Finally, proliferation of NSGCT cells in vitro and in vivo is significantly inhibited by combined treatment with the clinically available agents erlotinib and rapamycin, which target EGFR and mTORC1 signaling, respectively. These results provide an understanding of the signaling network that drives GCT growth and a rationale for therapeutic targeting of GCTs with agents that antagonize the EGFR and mTORC1 pathways. Mol Cancer Ther; 17(5); 1079-89. ©2018 AACR.