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The identification of biological stains at crime scene: a promising role for proteomics and machine learning

ABSTRACT: Identification of stains in criminalistics remains a critical challenge in forensic sciences. In particular, determining the biological origin of a trace can be crucial in an investigation in order to understand the circumstances in which it was deposited. This study aims to develop three distinct tests based on proteomics data for identifying human bodily fluids. The first test focuses on constructing specific peptide biomarkers for each fluid. The second test quantitatively assesses ratios between peptide abundances. The final test employs artificial intelligence, utilizing multioutput Random Forest, to distinguish between pure fluids and mixtures. Data from 20 individuals per fluid and 78 mixtures are analyzed. This research underscores the potential of proteomics in forensic bodily fluid identification. The evaluation of the different tests highlights their complementarity, as they focus on different features obtained from a single experiment.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Urine, Semen, Vaginal Fluid, Saliva, Blood

SUBMITTER: Anna Rosenberg

LAB HEAD: Joëlle Vinh

PROVIDER: PXD053891 | Pride | 2025-10-01

REPOSITORIES: Pride

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Project description:Background: Malignant ascites is often present at diagnostic in women with advanced ovarian cancer (OC) and its presence is associated with a worse outcome. Human peritoneal mesothelial cells (HPMCs) are key components of malignant ascites. Although the interplay between HPMCs and OC cells is believed to be critical for tumor progression, it has not been well characterized. The purpose of this study was to assess the effect of ascites on HPMCs and clarify the role of HPMCs in OC progression. Methods: Human OC ascites and benign peritoneal fluids were assessed for their ability to stimulate HPMC proliferation. Conditioned medium from ascites- and benign fluid-stimulated HPMCs were compared for their ability to attenuate apoptosis induced by TNF-related apoptosis-inducing ligand (TRAIL). We conducted a comparative analysis of global expression changes in ascites-stimulated HPMCs using Agilent oligonucleotide microarrays. Results: As compared to benign peritoneal fluids, malignant ascites stimulated the proliferation of HPMCs. TRAIL-induced apoptosis was attenuated in OC cells exposed to conditioned medium from ascites-stimulated HPMCs as compared to OC cells exposed to conditioned medium from benign fluid-stimulated HPMCs. A total of 649 genes were differentially expressed in ascites-stimulated HPMCs. Based on a ratio of more than 1.5-fold and a P < 0.05, 484 genes were up-regulated and 165 genes were down-regulated in ascites-exposed HPMCs. Stimulation of HPMCs with OC ascites resulted in differential expression of genes mainly associated with the regulation of cell growth and proliferation, cell death, cell cycle and cell assembly and organization, compared to benign peritoneal fluids. Top networks up-regulated by OC ascites included Akt and NF-M-NM-:B survival pathways whereas vascular endothelial growth factor (VEGF) pathway was down-regulated. Conclusions: The results of this study not only provide evidence supporting the importance of the interplay between cancer cells and HPMCs but also define the role that the tumor environment plays in these interactions. The expression profiles from human peritoneal mesothelial cells (HPMC) cultures exposed to peritoneal fluids and ovarian cancer ascites were compared using the Agilent Whole Human Genome Oligonucleotide microarrays, containing 44,000 genes. Microarrays were performed on HPMCs exposed to 3 malignant ascites from women with advanced (stage III/IV) serous OC and two benign peritoneal fluids. First, we generated lists of significantly up-regulated and down-regulated genes that were differentially expressed between OC ascites (OVC346, OVC508 and OVC509) and control OV370 peritoneal fluid. Then, the set of genes that were commonly expressed between control peritoneal fluids (OV370 and OV401) were subtracted from the first list of genes to generate a dataset of differentially expressed genes between malignant ascites and benign peritoneal fluids.

			Action	DRS
	QE240421_0967_b_eam.msf	Msf
	QE240421_0967_b_eam.raw	Raw
	QE240421_0968_b_eam.msf	Msf
	QE240421_0968_b_eam.raw	Raw
	QE240421_0969_b_eam.msf	Msf

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The identification of biological stains at crime scene: a promising role for proteomics and machine learning

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