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Finding biomarkers for preeclampsia. Early diagnostic biomarkers of pancreatic cancer. Better tools to identify tumor-specific peptides. Read about papers on these topics recently published in the journal Molecular & Cellular Proteomics.

Finding biomarkers for preeclampsia

Hypertension, or high blood pressure, is a leading cause of maternal and perinatal mortality, affecting 8% to 12% of pregnant women worldwide. Preeclampsia, a related condition characterized by a sudden increase in maternal blood pressure after the 20th week of pregnancy, occurs in approximately 2% to 8% of pregnancies. Routine screening for preeclampsia is crucial, as early detection and treatment are key to reducing the risk of seizures, or eclampsia, and serious complications of the brain, blood vessels, liver and kidneys. While measuring blood pressure is generally routine, it does not accurately predict preeclampsia. Therefore, researchers are searching for predictive biomarkers to improve diagnosis and management of this condition.

In a recent published in Molecular & Cellular Proteomics, Ji Hyae Lim, Jae Min Lim and colleagues at the CHA Bundand Medical Center and Kyung Hee University performed global proteomics on plasma samples from pregnant women with and without preeclampsia to identify potential diagnostic biomarkers. The researchers used liquid chromatography and tandem mass spectrometry, or LC–MS, to identify differentially expressed proteins. The authors quantified these proteins using multiple reaction monitoring, or MRM, and validated their expression using enzyme-linked immunosorbent assays. Among them, three proteins — apolipoprotein M, or APOM, lipocalin 2, or LCN2, and quiescin sulfhydryl oxidase 1, or QSOX1 — were significantly higher in the preeclampsia group and showed high diagnostic accuracy for preeclampsia detection. APOM binds primarily to high-density lipoproteins; LCN2 is a secretory glycoprotein associated with endothelial injury in preeclampsia; and QSOX1 is an enzyme that catalyzes the formation of disulfide bonds in peptides and proteins and generates hydrogen peroxide, which induces oxidative stress.

The authors concluded that LC–MS and MRM-based quantitative proteomic analyses may be valuable for identifying plasma biomarkers in other hypertensive disorders. Future directions will elucidate the functional roles of these proteins in the pathophysiology of preeclampsia.

Early diagnostic biomarkers of pancreatic cancer

Pancreatic ductal adenocarcinoma, or PDAC, is the fourth leading cause of cancer-related deaths in the U.S. PDAC has a poor prognosis, with a median survival of just 10 to 12 months with treatment. Most PDAC patients do not develop symptoms in the early stages of the disease, often resulting in diagnosis after the cancer has progressed. Therefore, scientists want to identify biomarkers that can detect PDAC prior to metastasis. The only PDAC biomarker approved by the U.S. Food and Drug Administration, carbohydrate antigen 19-9, or CA19-9, does not diagnose PDAC accurately.

In a recent published in Molecular & Cellular Proteomics, Hyeonji Kim, Sunghun Huh, Jungkap Park of Bertis Inc. and colleagues in South Korea developed a clinical-grade PDAC biomarker panel. Using a mass spectrometry technique called multiple reaction monitoring, they analyzed samples from PDAC patients and healthy controls and identified an initial panel of 35 protein candidates. The panel was refined to 12 biomarkers with the most consistent diagnostic performance. These included enzymes, binding and transport proteins, complement proteins, protease inhibitors, glycoproteins, cytoskeletal proteins and immune-related proteins. The team then developed predictive models by combining these candidates with CA19-9 detection by enzyme-linked immunosorbent assay. The combined panel demonstrated improved diagnostic performance, achieving a higher accuracy score compared to CA19-9 alone. The researchers are currently conducting a large-scale clinical validation study to confirm this panel’s clinical utility in humans.

Better tools to identify tumor-specific peptides

The immune system identifies foreign particles and fights disease by targeting cells that display bacterial, viral or tumor-specific peptides and kills transformed or infected cells displaying them. Cytotoxic T cells recognize these peptides, presented on antigen-presenting cells, and trigger an immune response. Personalized cancer immunotherapies, such as cancer vaccines and adoptive transfer of engineered T cells, leverage this system to enhance tumor cell killing by training T cells to recognize tumor-specific peptides or neoepitopes. Scientists use next-generation sequencing to find targets; however, these methods limit researchers to DNA or RNA data. Only mass spectrometry, or MS, –based methods identify displayed peptides, but these untargeted MS methods lack the sensitivity achieved by targeted assays.

Mogjiborahman Salek, Jonas D. F枚rster, Jonas P. Becker and colleagues in Germany developed a targeted MS optimization workflow to tune targeted assays for maximum detection sensitivity called optiPRM. Their was published in the journal Molecular & Cellular Proteomics. The ultrahigh sensitivity of the optiPRM approach results from optimizing acquisition parameters for each peptide. OptiPRM requires minute sample amounts and can detect peptides with low abundances. Using optiPRM, the researchers detected a neoepitope in a patient-derived xenograft pancreatic cancer cell line and five mutation-derived neoepitopes in three patients with varying cancers, including osteosarcoma, small lung cell carcinoma and liposarcoma. This method may serve as a foundation for developing personalized cancer therapies in the future by allowing scientists to identify neoepitopes from small clinical samples.