Pattern Computer Announces Hepatocellular Carcinoma Pattern Identification and Model Creation Study

Yahoo

27-05-2025

Study leveraged Pattern Discovery Engine™ to construct highly accurate model to predict whether or not a given cell is cancerous
Identified nine genes that are crucial for prediction and may have other uses in diagnostics and/or therapeutics
Highlights use of the Pattern Discovery Engine as a hypothesis discovery tool
REDMOND, Wash., May 27, 2025 (GLOBE NEWSWIRE) -- Pattern Computer®, Inc. ('Pattern' or 'the Company'), the global leader in Pattern Discovery, today announced the submission for peer review of a study titled "Explainable Molecular Stratification and Co-regulation Pattern Identification in Hepatocellular Carcinoma Single Cell Transcriptomics Data." In this study the Company's Pattern Discovery Engine ™ (PDE), a suite of proprietary algorithms, was used to analyze a liver cancer dataset, build predictive models to differentiate Hepatocellular carcinoma (HCC) from normal liver tissues, and uncover differences in gene regulation between the cancer and non-cancer samples. The PDE constructed a highly accurate model (97% accuracy) to predict whether or not a given cell is cancerous.
The Company noted that the PDE identified a small set of nine genes with fundamentally different regulatory structure in cancer cells versus normal, which is of importance as it. highlights the use of the PDE as a hypothesis discovery tool. Mark Anderson, Pattern Chair and CEO, commented, 'While the inner workings are proprietary, the hypotheses it delivers are every bit as explicit and understandable, or more so, as hypotheses generated by human intuition – which, of course, is often a black box we like to label 'inspiration' or 'insight.' This project demonstrates a new paradigm for scientific discovery: instead of beginning with a hypothesis, we begin with data – and discover hypotheses for testing, exploration, and yes, inspiration. We don't aim to replace human intuition, but to augment it with the power to discover patterns in data that yield hypotheses about patterns in the world at large.'
The PDE suite of algorithms enables the summarization of relationships in ultra-high-dimensional datasets in simple, human-readable, symbolic equations. It can discover previously unknown patterns within large datasets, without making prior assumptions, performing feature engineering, or pruning data. These algorithms use the patterns they uncovered to build explainable predictive models – which constitute novel hypotheses.
Liver cancer remains the third leading cause of cancer deaths, amounting to 7.8% of all cancer deaths. HCC is the major form of primary liver cancer, accounting for over 90% of the cases, with 5-year survival rate of only 18%. Given its asymptomatic nature in the early stages, most HCC patients are diagnosed at advanced stages and face poor prognosis with limited treatment options. Consequently, individual strategies based on identifying early potential prognostic biomarkers and novel therapeutic targets are urgently needed. These efforts can ultimately lead to more efficient and reliable diagnoses, personalized treatment strategies, and improved patient outcomes.
From the publication:
In this study, we utilized Pattern Computer, Inc.'s Pattern Discovery Engine ™ (PDE) to establish a robust analytical framework for single-cell gene expression data, specifically targeting hepatocellular carcinoma. While the workings of the engine are proprietary, the end result is composed of sets of equations that are interpretable and human-readable – and hence constitute testable hypotheses. Our analysis identified a panel of nine signature genes that consistently distinguish cancerous from healthy tissues across diverse cell types. Next, these signature genes were used to construct an XAI model with over 97% balanced accuracy in predicting cancer status at the single-cell level. Beyond predictive power, this model offers a symbolic predictive equation, providing interpretable insights into the regulatory relationships among the genes. Finally, we generated a directed gene-to-gene regulatory network, uncovering substantial disruptions in co-regulation within cancerous cells compared to the tightly coordinated regulatory dynamics observed in healthy cells. This regulatory shift underscores the molecular dysregulation underlying hepatocellular carcinoma. These findings extend beyond classification accuracy, shedding light on the disrupted regulatory landscapes of cancer cells. By linking gene expression patterns to functional insights, our approach highlights therapeutic targets and biomarkers, paving the way for intervention strategies in this challenging disease.
Mr. Anderson added, 'Explainable Artificial Intelligence (XAI) is revolutionizing biological research by enabling precise discoveries with unmatched transparency and interpretability. Our commitment to pioneering solutions in the fight against cancer is unwavering, with each innovative milestone achieved bringing the Company closer to our overarching mission of improving outcomes for individuals affected by cancer. Leveraging our AI-enabled Pattern Discovery Engine, we have achieved significant progress in expanding the Company's industry-leading oncology pipeline against the top five cancers worldwide.'
Mr. Anderson concluded, 'Pattern's advanced computational approaches push the boundaries of cancer treatment, and we are confident in our ability to make more such discoveries across various types of challenging cancers. As we work towards transforming cancer treatment paradigms, we are looking to partner with firms to bring our cancer drug discoveries and diagnostic advances against the world's top five cancers into clinical trials.'
About PatternPattern Computer, Inc. uses its Pattern Discovery Engine™ to solve the most important and intractable problems in business and medicine. These proprietary mathematical techniques in advanced AI can find complex patterns in very-high-order data that have eluded detection by much larger systems. As the Company applies its computational platform to the challenging fields of drug discovery and diagnostics, it is also making major Pattern Discoveries for partners in other sectors, including extended biotech, materials science, aerospace manufacturing quality control, veterinary medicine, air traffic operations, and energy services. See www.patterncomputer.com.
CONTACT: Laura Guerrant-Oiye [phone] – [e-mail]
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