BMP1

Peptide-level insights from deep, unbiased proteomics enable protein variant analysis of patient samples, revealing potential non-small cell lung cancer biomarkersREDWOOD CITY, Calif., March 29, 2023 (GLOBE NEWSWIRE) -- Seer Inc. (NASDAQ: SEER), a life sciences company commercializing a disruptive new platform for proteomics, today announced a new scientific publication in PLOS One demonstrating the unmatched utility of the Proteograph Product Suite to uncover novel insights in human health and disease with deep, unbiased proteomics. Scientists from Seer in collaboration with Luis Diaz, M.D. from Memorial Sloan Kettering Cancer Center found previously unknown associations between four protein isoforms and non-small cell lung cancer (NSCLC) progression, constituting potential novel, disease-relevant biomarkers, or therapeutic targets. Importantly, the identified NSCLC-associated protein isoforms comprise structural variants of proteins that arise from distinct but related mRNAs produced from the same gene through the process of alternative splicing. Different protein isoforms can have distinct roles in biology, influencing disease predisposition and progression. Notably, discovery and quantification of such protein variants in a complex biological sample requires deep, unbiased interrogation of the proteome at peptide-level resolution. “These findings demonstrate that distinct protein isoforms may differentially contribute to diverse biological mechanisms and to the pathogenesis of cancers, potentially paving the road to identify new diagnostic markers or new therapeutic targets,” said Dr. Diaz, Head of the Division of Solid Tumor Oncology at Memorial Sloan Kettering Cancer Center. “What is especially encouraging here is that these protein isoforms were detected in plasma, a readily accessible sample type, enabling cancer detection and monitoring through liquid biopsy evaluation of patients.” The researchers found that the short protein isoform of bone morphogenetic protein 1 (BMP1) occurred more frequently in NSCLC patients compared with healthy participants, and with even greater abundance in patients with late-stage cancer, suggesting that this isoform of BMP1 may play a role in NSCLC progression. BMP1 is involved in collagen processing, and the short isoform of the protein lacks the ability to release collagen, which could impact the tumor microenvironment. The study analyzed 188 plasma proteomes from NSCLC patients and controls to identify disease-associated protein isoforms. In addition to BMP1, the analysis revealed three other protein isoforms with significant differential behavior in NSCLC when compared to healthy controls: complement component 4a (C4a), complement component 1r (C1r) and lactate dehydrogenase B (LDHB). “This study, which found disease-associated protein isoforms in NSCLC, could only have been achieved using an unbiased peptide-level approach that provides a deeper, more nuanced view of the human proteome,” said Asim Siddiqui, Senior Vice President of Research at Seer. “These findings demonstrate the power of unbiased proteomics to discover novel biology, especially in the context of cancer, that may otherwise be missed by genomics or targeted proteomics.” Further research is necessary to validate the utility of these protein isoforms as novel biomarkers for NSCLC, or even new therapeutic targets. Seer’s Proteograph Product Suite enables proteomics studies with an unprecedented combination of speed, scale, depth, and breadth of data, allowing an unbiased interrogation of the proteome to allow studies not previously possible. Seer’s proprietary engineered nanoparticles deliver reproducible performance across samples, labs, and experiments, providing peptide level information that is key to identifying protein variants. The accompanying Proteograph Analysis Suite offers cloud-scalable software for proteomic data analysis, visualization, and generation of biological insights. The Proteograph Product Suite makes it easy to add unbiased, deep, rapid proteomics studies at scale to any lab. About SeerSeer is a life sciences company developing transformative products that open a new gateway to the proteome. Seer’s Proteograph™ Product Suite is an integrated solution that includes proprietary engineered nanoparticles, consumables, automation instrumentation and software to perform deep, unbiased proteomic analysis at scale in a matter of hours. Seer designed the Proteograph workflow to be efficient and easy to use, leveraging widely adopted laboratory instrumentation to provide a decentralized solution that can be incorporated by nearly any lab. Seer’s Proteograph Product Suite is for research use only and is not intended for diagnostic procedures. For more information, please visit www.seer.bio. Forward-Looking StatementsThis press release contains “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995, as amended. Such forward-looking statements are based on Seer’s beliefs and assumptions and on information currently available to it on the date of this press release. Forward-looking statements may involve known and unknown risks, uncertainties and other factors that may cause Seer’s actual results, performance, or achievements to be materially different from those expressed or implied by the forward-looking statements. These statements include but are not limited to statements regarding access to proteins, discovery and quantification of protein variants and biological insights, identification and utility of protein isoforms as novel biomarkers and therapeutic targets, deep unbiased interrogation of the proteome at the peptide level, the role of BMP1 in NSCLC pathogenesis and treatment resistance, the role of BMP1 in collagen processing and the tumor microenvironment, the ability of the Proteograph Product Suite to enable proteomics studies with an unprecedented combination of speed, scale, depth, and breadth of data. These and other risks are described more fully in Seer’s filings with the Securities and Exchange Commission (“SEC”) and other documents that Seer subsequently files with the SEC from time to time. Except to the extent required by law, Seer undertakes no obligation to update such statements to reflect events that occur or circumstances that exist after the date on which they were made. Media Inquiries:Elizabeth Eatonpr@seer.bio Investor Inquiries:Carrie Mendivilinvestor@seer.bio

Researchers have identified several genetic variants associated with increased risk of cancer in children with non-chromosomal birth defects, such as congenital heart disease and defects of the central nervous system. While the risk of developing cancer is not as high as children with chromosomal birth defects, it is significantly higher than children with no birth defects at all, and the findings may provide a basis for early detection in these understudied patients. Researchers from Children's Hospital of Philadelphia (CHOP) have identified several genetic variants associated with increased risk of cancer in children with non-chromosomal birth defects, such as congenital heart disease and defects of the central nervous system. While the risk of developing cancer is not as high as children with chromosomal birth defects, it is significantly higher than children with no birth defects at all, and the findings may provide a basis for early detection in these understudied patients. The findings were recently published in the journal Biomarker Research. Children with birth defects are more likely to develop cancer, and that increased risk of cancer persists into adulthood. Prior studies have demonstrated that children with chromosomal birth defects, such as Down syndrome and Klinefelter syndrome, are more than 11 times more likely to be diagnosed with cancer than children without any birth defects. However, children with non-chromosomal birth defects are up to 2.5 times more likely to be diagnosed with cancer than those without birth defects. With birth defects of any kind occurring in 1 in every 33 births in the United States each year, that increased risk implicates a significant number of children. The underlying genetics of non-chromosomal birth defects have not been studied in great detail. Researchers at the Center for Applied Genomics (CAG) at CHOP wanted to determine what molecular mechanisms were at play and potentially identify genetic clues that could lead to early identification of cancer in these patients. "We assembled one of the largest pediatric oncology and birth defects projects in children as part of the Gabriella Miller Kids First program project, which helps to uncover new insights into childhood cancer and structural birth defects," said Hakon Hakonarson, MD, PhD, director of the CAG at CHOP and senior author of the study. "With this partnership, we sought to identify functional molecular pathways based on mutations we identified as part of this study." In this study, researchers used data obtained from whole genome sequencing of blood samples from 1,653 individuals without chromosomal abnormalities that were acquired from the Kids First Data Resource Center. These samples included 541 birth defect probands -- the first person in a family to receive genetic counseling or testing for hereditary risk of a disease -- with at least one type of malignant tumor, 767 birth defect probands without malignant tumors, and 345 healthy family members who are parents or siblings of the aforementioned probands. Additionally, once variants were identified, whole genome sequencing data from 40 birth defect probands from outside the data resource center, including 25 patients with at least one type of cancer, were used to further validate the study. The study identified thousands of variants of interest, including 119 genes with at least two variants in coding regions -- regions of the gene that will eventually be transcribed and translated into proteins to carry out essential functions -- and 478 genes with at least 20 variants in their non-coding regions. Five genes in particular -- AXIN2, BMP1, CR1, ERBB2, and RYR1 - are associated with birth defects and increased risk of cancer. Additionally, the researchers built a deep learning model to assess the variants of interest identified in the Kids First cohort when compared with the 40 validation samples and found that they had achieved approximately 75% accuracy, with even greater accuracy for variants that were associated with non-coding regions. Further detailed analysis of this data could identify genes and noncoding mutations that not only result in specific birth defects but also identify which types of cancer they are more prone to and whether the risk is more pronounced in childhood or adulthood. "While more research is needed to delve into the variants of interest we identified, this study represents a critical step toward the earlier detection of cancer children with non-chromosomal birth defects," Hakonarson said. The sequencing data was provided through the Gabriella Miller Kids First Pediatric Research Program consortium (Kids First), supported by the Common Fund of the Office of the Director of the National Institutes of Health. The study was supported by Institutional Development Funds from CHOP to the CAG.