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Machine Learning-Derived Metrics Enable Computational Method Comparison in Phosphoproteomics Research

Protein phosphorylation dysregulation has been recognized as a key feature of several diseases, especially cancer. In recent years, phosphoproteomic research has revealed novel, effective biomarkers and drug targets for disease prognosis and treatment. Tandem mass spectrometry (MS/MS)-based phosphoproteomics provides a high-throughput method to study protein phosphorylation in complex biological samples. However, translating phosphoproteomic data into relevant biological and clinical insights relies on effective data analysis.

Proteogenomics Provides New Insights into Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is the second-most common primary liver tumor and has a low 5-year survival rate of 15%. Treatment of iCCA is particularly difficult due to its markedly aggressive progression, late symptom presentation, and early metastasis. In order to improve patient prognoses, it is critical to understand the pathogenesis of iCCA more deeply and identify novel molecular pathways that may serve as a theoretical foundation for personalized treatment of the disease.

CPTAC Researchers Identify CPT1A as a Potential Therapeutic Target in Platinum-Refractory, High-Grade Serous Ovarian Cancer Patients

At present, typical treatment for patients with high-grade serous ovarian cancer (HGSOC) is surgical debulking coupled with platinum-based chemotherapy. Despite the majority of HGSOCs being sensitive to platinum-based therapy initially, most become resistant over the course of treatment. The development of more efficacious therapies for platinum-resistant disease is an urgent clinical goal. In order to more effectively combat HGSOC, researchers are striving to identify predictive biomarkers of platinum response.

CPTAC Researchers Detect Fraud in Large-Scale Molecular Omics Datasets with Exceptional Accuracy Using Machine Learning

Modern computational tools for data collection and analysis have revolutionized how scientists are able to research and respond to problems. While the growing number of large, public data sets is a great boon for researchers, the accessibility of these resources can introduce quality and security risks. Data in the biological sciences is particularly vulnerable to fraud given its massive size, making it easier to hide manipulation. Inspired in part by techniques used to detect fraud in the financial sector, Dr.

CPTAC Researchers Develop a Novel, Targeted Mass Spectrometry Assay Panel that Enables Quantification of Immunomodulatory Proteins

Immunotherapies are revolutionizing modern cancer care, but at present, many technologies do not accurately quantify the myriad soluble proteins in the tumor microenvironment which impact immunity. This, in turn, contributes to the pervasiveness of patient resistance and immune-related adverse events. In order overcome these hurdles, it is necessary to design more refined protein quantification techniques that complement immunoassays for quantifying human proteins.

The Human Melanoma Proteome Atlas: Proteogenomic Researchers Map Protein Expression in Malignant Melanoma

Earlier this year, a team from the European Cancer Moonshot Lund Center at Lund University published proteomics and corresponding proteogenomic integration studies for malignant melanomas (MM). The twin publications represent an effort to map protein levels in over 500 MM tumor samples (the MM500 study). By applying deep-learning based single-cell segmentation and phenotyping as well as proteogenomic characterization, the researchers successfully developed a novel Digital Melanoma Pathology.

CPTAC Researchers Produce a Highly Annotated, Publicly Accessible Database of Genes Associated with Platinum Resistance in Cancer

According to U.S. National Cancer Institute estimates, approximately 10–20% of all cancer patients will receive a platinum drug over the course of their treatment. Cisplatin, the first platinum-based anti-cancer therapy, was approved by the Food and Drug Administration (FDA) for treating testicular cancer in 1978; subsequently, more platinum formulations (i.e. carboplatin, oxaliplatin) were designed and approved to reduce side effects and bolster results.

Memorandum of Understanding signed by NCI, FDA and HRSA to bring cancer diagnostic devices closer to patients, particularly members of medically underserved and geographically isolated communities

On Friday, September 17, 2021, leadership from the National Cancer Institute (NCI), Food and Drug Administration (FDA), and Health Resources and Services Administration (HRSA) signed a Memorandum of Understanding (MOU) to support solutions for early cancer detection and diagnosis to improve patient outcomes, quality of life, and reduce health disparities among medically underserved, geographically isolated, and otherwise vulnerable populations.

Machine Learning Predicts Molecular Features of Endometrial Cancer with Exceptionally High Accuracy

The CPTAC research group led by Dr. David Fenyö at NYU Langone Medical Center has demonstrated the feasibility of a machine learning image processing tool designed to assist pathologists classifying endometrial cancer. Their customized multi-resolution deep convolutional neural network (CNN) model was able to provide information about patients’ histological subtypes, molecular subtypes, and mutation status rapidly and reliably from digitized H&E-stained pathological images.

Proteogenomics Provides New Insights into Pancreatic Ductal Adenocarcinoma

Despite advances in the efficacy and specificity of cancer treatments over the last decade, pancreatic cancer remains one of the leading causes of death worldwide. The most common type of pancreatic tumor, Pancreatic Ductal Adenocarcinoma (PDAC), has distinctly poor patient outcomes due to its aggressive progression and late symptom presentation.

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