FuncPEP v20: An Updated Database of Functional Short Peptides Translated from Non-Coding RNAs

Over the past decade, there have been reports of short novel functional peptides (less than 100 aa in length) translated from so-called non-coding RNAs (ncRNAs) that have been characterized using mass spectrometry (MS) and large-scale proteomics studies. Therefore, understanding the bivalent functions of some ncRNAs as transcripts that encode both functional RNAs and short peptides, which we named ncPEPs, will deepen our understanding of biology and disease. In 2020, we published the first database of functional peptides translated from non-coding RNAs-FuncPEP. Herein, we have performed an update including the newly published ncPEPs from the last 3 years along with the categorization of host ncRNAs. FuncPEP v2.0 contains 152 functional ncPEPs, out of which 40 are novel entries. A PubMed search from August 2020 to July 2023 incorporating specific keywords was performed and screened for publications reporting validated functional peptides derived from ncRNAs. We did not observe a significant increase in newly discovered functional ncPEPs, but a steady increase. The novel identified ncPEPs included in the database were characterized by a wide array of molecular and physiological parameters (i.e., types of host ncRNA, species distribution, chromosomal density, distribution of ncRNA length, identification methods, molecular weight, and functional distribution across humans and other species). We consider that, despite the fact that MS can now easily identify ncPEPs, there still are important limitations in proving their functionality

RPPA Space: An R Package for Normalization and Quantitation of Reverse-Phase Protein Array Data

SUMMARY: Reverse-Phase Protein Array (RPPA) is a robust high-throughput, cost-effective platform for quantitatively measuring proteins in biological specimens. However, converting raw RPPA data into normalized, analysis-ready data remains a challenging task. Here, we present the RPPA SPACE (RPPA Superposition Analysis and Concentration Evaluation) R package, a substantially improved successor to SuperCurve, to meet that challenge. SuperCurve has been used to normalize over 170 000 samples to date. RPPA SPACE allows exclusion of poor-quality samples from the normalization process to improve the quality of the remaining samples. It also features a novel quality-control metric, \u27noise\u27, that estimates the level of random errors present in each RPPA slide. The noise metric can help to determine the quality and reliability of the data. In addition, RPPA SPACE has simpler input requirements and is more flexible than SuperCurve, it is much faster with greatly improved error reporting. AVAILABILITY AND IMPLEMENTATION: The standalone RPPA SPACE R package, tutorials and sample data are available via https://rppa.space/, CRAN (https://cran.r-project.org/web/packages/RPPASPACE/index.html) and GitHub (https://github.com/MD-Anderson-Bioinformatics/RPPASPACE). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Fibroblast Growth Factor Receptor 1 Drives the Metastatic Progression of Prostate Cancer

BACKGROUND: No curative therapy is currently available for metastatic prostate cancer (PCa). The diverse mechanisms of progression include fibroblast growth factor (FGF) axis activation. OBJECTIVE: To investigate the molecular and clinical implications of fibroblast growth factor receptor 1 (FGFR1) and its isoforms (α/β) in the pathogenesis of PCa bone metastases. DESIGN, SETTING, AND PARTICIPANTS: In silico, in vitro, and in vivo preclinical approaches were used. RNA-sequencing and immunohistochemical (IHC) studies in human samples were conducted. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: In mice, bone metastases (chi-square/Fisher's test) and survival (Mantel-Cox) were assessed. In human samples, FGFR1 and ladinin 1 (LAD1) analysis associated with PCa progression were evaluated (IHC studies, Fisher's test). RESULTS AND LIMITATIONS: FGFR1 isoform expression varied among PCa subtypes. Intracardiac injection of mice with FGFR1-expressing PC3 cells reduced mouse survival (α, p < 0.0001; β, p = 0.032) and increased the incidence of bone metastases (α, p < 0.0001; β, p = 0.02). Accordingly, IHC studies of human castration-resistant PCa (CRPC) bone metastases revealed significant enrichment of FGFR1 expression compared with treatment-naïve, nonmetastatic primary tumors (p = 0.0007). Expression of anchoring filament protein LAD1 increased in FGFR1-expressing PC3 cells and was enriched in human CRPC bone metastases (p = 0.005). CONCLUSIONS: FGFR1 expression induces bone metastases experimentally and is significantly enriched in human CRPC bone metastases, supporting its prometastatic effect in PCa. LAD1 expression, found in the prometastatic PCa cells expressing FGFR1, was also enriched in CRPC bone metastases. Our studies support and provide a roadmap for the development of FGFR blockade for advanced PCa. PATIENT SUMMARY: We studied the role of fibroblast growth factor receptor 1 (FGFR1) in prostate cancer (PCa) progression. We found that PCa cells with high FGFR1 expression increase metastases and that FGFR1 expression is increased in human PCa bone metastases, and identified genes that could participate in the metastases induced by FGFR1. These studies will help pinpoint PCa patients who use fibroblast growth factor to progress and will benefit by the inhibition of this pathway.Fil: Labanca, Estefania. University of Texas; Estados UnidosFil: Yang, Jun. University of Texas; Estados UnidosFil: Shepherd, Peter D. A.. University of Texas; Estados UnidosFil: Wan, Xinhai. University of Texas; Estados UnidosFil: Starbuck, Michael W.. University of Texas; Estados UnidosFil: Guerra, Leah D.. University of Texas; Estados UnidosFil: Anselmino, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Bizzotto, Juan Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Dong, Jiabin. University of Texas; Estados UnidosFil: Chinnaiyan, Arul M.. University Of Michigan Medical School; Estados UnidosFil: Ravoori, Murali K.. University of Texas; Estados UnidosFil: Kundra, Vikas. University of Texas; Estados UnidosFil: Broom, Bradley M.. University of Texas; Estados UnidosFil: Corn, Paul G.. University of Texas; Estados UnidosFil: Troncoso, Patricia. University of Texas; Estados UnidosFil: Gueron, Geraldine. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Logothethis, Christopher J.. University of Texas; Estados UnidosFil: Navone, Nora. University of Texas; Estados Unido

The MD Anderson prostate cancer patient-derived xenograft series (MDA PCa PDX) captures the molecular landscape of prostate cancer and facilitates marker-driven therapy development

BACKGROUND: Advances in prostate cancer (PCa) lag behind other tumor types partly due to the paucity of models reflecting key milestones in PCa progression. OBJECTIVE: To develop clinically relevant PCa models. DESIGN: Since 1996 we have generated clinically annotated patient-derived xenografts (PDXs) (the MDA PCa PDX series) linked to specific phenotypes reflecting all aspects of clinical PCa. RESULTS: We studied two cell line-derived xenografts and the first 80 PDXs derived from 47 human PCa donors. Of these, 47 PDXs derived from 22 donors are working models and can be expanded either as cell lines (MDA PCa 2a and 2b) or PDXs. The histopathologic, genomic, and molecular characteristics (AR, ERG, and PTEN loss) maintain fidelity with the human tumor and correlate with published findings. PDX growth response to mouse castration and targeted therapy illustrate their clinical utility. Comparative genomic hybridization and sequencing show significant differences in oncogenic pathways in pairs of PDXs derived from different areas of the same tumor. We also identified a recurrent focal deletion in an area that includes the SPOPL gene in PDXs derived from 7 human donors out of 28 studied (25%). SPOPL is a SPOP paralog, and SPOP mutations define a molecular subclass of PCa. SPOPL deletions are found in 7% of TCGA PCas, which suggests that our cohort is a reliable platform for targeted drug development. CONCLUSIONS: The MDA PCa PDX series is a dynamic resource that captures the molecular landscape of PCas progressing under novel treatments and enables optimization of PCa-specific, marker-driven therapy

A pan-cancer proteomic perspective on The Cancer Genome Atlas.

Protein levels and function are poorly predicted by genomic and transcriptomic analysis of patient tumours. Therefore, direct study of the functional proteome has the potential to provide a wealth of information that complements and extends genomic, epigenomic and transcriptomic analysis in The Cancer Genome Atlas (TCGA) projects. Here we use reverse-phase protein arrays to analyse 3,467 patient samples from 11 TCGA 'Pan-Cancer' diseases, using 181 high-quality antibodies that target 128 total proteins and 53 post-translationally modified proteins. The resultant proteomic data are integrated with genomic and transcriptomic analyses of the same samples to identify commonalities, differences, emergent pathways and network biology within and across tumour lineages. In addition, tissue-specific signals are reduced computationally to enhance biomarker and target discovery spanning multiple tumour lineages. This integrative analysis, with an emphasis on pathways and potentially actionable proteins, provides a framework for determining the prognostic, predictive and therapeutic relevance of the functional proteome

Spelling improvement through letter-sound and whole-word training in two multilingual Greek- and English- speaking children

Case studies of two children with spelling difficulty are reported. LK was multilingual and ED bilingual. A training programme that targeted phonic decoding (or sublexical) spelling processes was conducted with both children. Immediate and delayed post-training assessments showed improvement in spelling nonwords for LK but not for ED. Training that targeted whole word (or lexical) spelling processes was then conducted with ED. Improvement in spelling of irregular words (a marker for lexical spelling processes) was observed. Research into literacy difficulties with multilingual children is sparse, although multilingualism is increasingly widespread. Up to now theoretically based training studies have focused on monolingual children and results were promising. The present findings indicate that theoretically based training programmes for literacy difficulties can also be effective for multilingual children

The consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-beta activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts