👤 Zainab Noor

Pancreatic ductal adenocarcinoma (PDA) is an aggressive malignancy that lacks reliable biomarkers to guide treatment decisions. Effective prognostic tools are needed to improve its clinical management. We conducted a comprehensive proteomic analysis on 115 PDA patient samples with matched adjacent normal tissue. A 20-protein diagnostic panel was identified (LGALS1, ANXA2, LGALS3BP, CTSD, S100P, COL12A1, SFN, THBS2, CTHRC1, THBS1, SERPINB5, LAMC2, POSTN, CEACAM6, CTSE, PLEC, PKM, S100A11, TAGLN2, ALDOA). Consensus clustering analysis identified four prognostic proteomic subtypes. Subtypes with poorer prognoses exhibited upregulation of neutrophil degranulation, extracellular matrix remodeling, focal adhesion, Mesenchymal Epithelial Transition, collagen formation, and PI3K-Akt-mTOR-related pathways, indicating a predominance of basal-like and activated stromal features. In tumors with homologous recombination deficiency or Catalogue of Somatic Mutations in Cancer Signature-3, several immune-related proteins were enriched. An 18-protein (PURB, SDCBP2, CD2BP2, GALM, SERPINA3, OAS3, FAN1, ZPR1, KRT2, NUDT2, SMNDC1, SERPINA4, CUTA, WDR36, POSTN, CLEC11A, PEX14, and PI4KA) risk score was developed and validated using multicox regression analyses with LASSO regularization. The risk score demonstrated independent prognostic significance for overall survival and recurrence, and was validated in an independent proteomic dataset generated using a different proteomic technology. This study thus introduces four novel prognostic PDA subtypes, and an 18-protein risk score validated in an independent dataset, which shows promise for improving survival prediction and could serve as a valuable tool for personalized treatment guidance. The findings from this study have significant implications for the future of pancreatic cancer management. By identifying a 20-protein panel with diagnostic and screening potential, this research provides a foundation for developing early detection tools for PDA, an aggressive cancer with limited treatment options. The classification of PDA into four proteomic subtypes with distinct prognostic outcomes paves the way for subtype-specific therapeutic approaches, allowing clinicians to better stratify patients based on their risk profiles. Additionally, the validated 18-protein risk score, which enhances survival prediction and operates independently of existing clinical variables, represents a promising tool for personalized prognostic assessments. Incorporating these proteomic-based biomarkers into clinical practice could improve diagnostic accuracy, guide individualized treatment decisions, and ultimately enhance patient outcomes in PDA. This study underscores the potential of proteomic profiling to improve cancer treatment by providing targeted, actionable insights into tumor biology. Show less

Genome-wide single nucleotide polymorphism (SNP) data from 936 bipolar disorder (BD) individuals and 940 psychiatrically healthy comparison individuals of North European descent were analyzed for copy number variation (CNV). Using multiple CNV calling algorithms, and validating using in vitro molecular analyses, we identified CNVs implicating several candidate genes that encode synaptic proteins, such as DLG1, DLG2, DPP6, NRXN1, NRXN2, NRXN3, SHANK2, and EPHA5, as well as the neuronal splicing regulator RBFOX1 (A2BP1), and neuronal cell adhesion molecule CHL1. We have also identified recurrent CNVs on 15q13.3 and 16p11.2-regions previously reported as risk loci for neuropsychiatric disorders. In addition, we performed CNV analysis of individuals from 215 BD trios and identified de novo CNVs involving the NRXN1 and DRD5 genes. Our study provides further evidence of the occasional involvement of genomic mutations in the etiology of BD, however, there is no evidence of an increased burden of CNVs in BD. Further, the identification of CNVs at multiple members of the neurexin gene family in BD individuals, supports the role of synaptic disruption in the etiology of BD. Show less

Autism or autism spectrum disorder (ASD) is a range of neurodevelopmental disorders starting in early childhood and is characterized by impairments in communication and reciprocal social interaction and presence of restricted and repetitive patterns of behavior. The contribution of genetic factors to autism is clear in twin and family studies. It is apparent that, overall, ASD is a complex non-Mendelian disorder. Recent studies suggest that copy number variations (CNVs) play a significant role in the etiology of ASD. For the current work, we recruited 245 family members from 73 ASD families from Styria, Austria. The DNA from probands was genotyped with Affymetrix single nucleotide polymorphism (SNP) 6.0 microarrays to screen for CNVs in their genomes. Analysis of the microarray data was performed using three different algorithms, and a list of stringent calls was compared to existing CNV data from over 2,357 controls of European ancestry. For stringent calls not present in controls, quantitative real-time PCR (qRT-PCR) was used to validate the CNVs in the probands and in their family members. Twenty-two CNVs were validated from this set (five of which are apparently de novo), many of which appear likely to disrupt genes that may be considered as good candidates for neuropsychiatric disorders, including DLG2, S100B, ARX, DIP2A, HPCAL1, and GPHN. Several others disrupt genes that have previously been implicated in autism, such as BDNF, AUTS2, DPP6, and C18orf22, and our data add to the growing evidence of their involvement in ASD. Show less