Inocras, a leading provider of precision healthcare solutions company advancing whole-genome technology, is making an impact at the American Association for Cancer Research (AACR) 2024 annual meeting from April 5 to 10, held in San Diego. This event premieres Inocras's substantial research and pioneering innovation in cancer diagnostics, driven by cutting-edge machine learning technology.

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Inocras presenting at the 2024 American Association for Cancer Research (AACR 2024) in San Diego, USA. (Graphic: Inocras)

In their poster presentation, Inocras showcases the refined approach of machine learning in examining whole-genome sequencing (WGS) data from tissues preserved in formalin-fixed paraffin-embedded (FFPE) samples, a common preservation technique in clinical environments. The research focuses on addressing the challenges posed by the distorted genomic profiles in FFPE-derived tissues, which complicate precise cancer diagnosis. The study delves into the genomic changes induced by FFPE processing and devises computational strategies to eliminate these artifacts. This is achieved by analyzing 55 matched FFPE and fresh-frozen (FF) sample pairs across a variety of cancer types and different FFPE storage duration.

The study unveils a cutting-edge machine learning strategy to accurately identify genetic changes caused by FFPE processing. Concentrating on detecting single-nucleotide variants (SNVs), small insertions and deletions (indels), and copy-number variations (CNVs), the researchers crafted sophisticated algorithms to sift through these genomic distortions. These algorithms not only improve the precision and reliability of the genomic analysis but also tackle the inherent variability of clinical FFPE specimens. The developed classifiers show exceptional ability in differentiating actual genetic variants from FFPE-related errors. Moreover, this research sheds light on specific FFPE-induced genetic alteration patterns, such as cytosine deamination and unique mutational signatures, while proving its efficacy in assessing vital cancer and genomic metrics, including homologous recombination deficiency (HRD) and tumor mutational burden (TMB).

Young Seok Ju, Chief Genome Officer of Inocras, expresses excitement about the studies to be presented at AACR 2024 and emphasizes the company's commitment to transforming cancer care through machine learning technology. "We are thrilled to showcase the pioneering work we are doing at Inocras in leveraging machine learning to pull out the full potential of WGS analysis in cancer diagnostics and therapeutics. Our research findings presented at AACR 2024 will underscore the potential of machine learning in revolutionizing personalized cancer treatment strategies."

Inocras's participation in AACR 2024 showcases the company's relentless dedication to leveraging technological innovation to revolutionize cancer research and clinical practice. The presentations underscore Inocras's commitment to providing personalized and exhaustive insights for better patient outcomes, solidifying the company's position as a leader in AI-powered solutions for cancer diagnostics and therapeutics.

For more information about Inocras and its groundbreaking research presented at AACR 2024, please visit Inocras.

Presentations at AACR 2024 featuring Inocras:

Enhancing genomic analysis in cancer diagnostics: A machine learning approach for removing artifacts in FFPE specimens (Section 37, April 7, 2024, 1:30 pm – 5:00 pm)

About Inocras Inc:

Inocras Inc. (formerly Genome Insight, Inc) is a pioneering provider of whole genome sequencing and analytics services for cancer and rare diseases. The company is dedicated to unlocking the potential of genomic data to enable precision health for everyone.

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