Arima Genomics Study Highlights Power of Whole-Genome Rearrangement Detection in Lymphoid Cancers
Arima Genomics, Inc., a biotechnology company focused on leveraging whole-genome sequence and structural information to deliver comprehensive insights for cancer therapy selection, has announced the publication of a new collaborative research study that further validates the scientific and clinical utility of its Aventa™ Lymphoma assay. The study, conducted in partnership with investigators at the University of Michigan and New York University, was published on February 20 in the peer-reviewed journal Cell Genomics.
The findings provide additional evidence supporting the value of Aventa Lymphoma, a test designed to detect clinically meaningful chromosomal rearrangements from routine formalin-fixed, paraffin-embedded (FFPE) pathology specimens. By applying the FFPE-compatible Hi-C sequencing technology that underpins the Aventa platform, researchers demonstrated high concordance with conventional diagnostic techniques while also identifying additional clinically relevant genomic alterations that had not been uncovered during prior routine testing.
Advancing Lymphoma Diagnostics Through Whole-Genome Insight
Lymphoid malignancies, including large B-cell lymphomas, plasma cell neoplasms, and other related cancers, are often driven by chromosomal rearrangements that influence disease classification, prognosis, and therapeutic decision-making. Accurate detection of these rearrangements is critical for guiding patient management. Traditionally, fluorescence in situ hybridization (FISH) has served as the standard approach for identifying specific gene rearrangements in these cancers.
However, while FISH remains widely used in clinical practice, it has inherent limitations. Each FISH assay typically evaluates the rearrangement status of a single gene locus. As a result, multiple tests may be required to assess different genomic regions, increasing cost, turnaround time, and sample utilization. Moreover, FISH testing is generally targeted—meaning it is designed to detect only known or suspected rearrangements. Unanticipated or rare structural alterations may therefore go undetected.
The newly published study illustrates how a whole-genome strategy can overcome these constraints. Using FFPE-compatible Hi-C sequencing—the same foundational technology employed in Aventa Lymphoma—the investigators analyzed 44 archival FFPE biopsy samples spanning multiple types of lymphoid malignancies. Despite the challenges typically associated with FFPE samples, which are routinely used in pathology labs but often contain fragmented DNA, the technology proved robust and reliable.
Study Design and Key Findings
The research team applied Hi-C sequencing to 44 archival FFPE biopsies from patients diagnosed with various lymphoid cancers, including:
- Large B-cell lymphomas
- Plasma cell neoplasms
- Other diverse lymphoid malignancies
These samples had previously undergone routine diagnostic workups using standard methodologies such as FISH and other molecular techniques. By comparing Hi-C–based findings with prior results, the investigators were able to assess concordance and explore the incremental value of a whole-genome structural approach.
The results showed high concordance between Hi-C sequencing and established diagnostic methods, confirming the reliability of the approach for identifying known rearrangements. Importantly, the Hi-C analysis also uncovered additional clinically relevant genomic alterations that had not been detected during earlier routine testing. These included rearrangements with potential diagnostic, prognostic, and therapeutic implications.
Such findings underscore one of the most significant advantages of whole-genome structural analysis: its ability to detect unexpected, uncommon, or cryptic rearrangements that targeted assays might miss. In the context of lymphoma, where genomic alterations can define disease subtypes and influence treatment selection, this broader perspective can be highly impactful.
Overcoming the Limitations of Conventional Testing
The study authors emphasized that conventional rearrangement detection methods, including FISH, are inherently limited in scope. Because FISH assays are designed to interrogate specific genes or loci, clinicians must anticipate which genomic abnormalities to test for. If a rearrangement falls outside those targeted regions, it may remain undetected.
In contrast, Hi-C sequencing provides a comprehensive, genome-wide view of structural variation in a single assay. Rather than focusing on predetermined loci, it captures interactions across the entire genome, enabling the identification of both known and novel rearrangements. This holistic approach reduces reliance on prior assumptions and expands the diagnostic window.
Anthony Schmitt, PhD, Senior Vice President of Science at Arima Genomics, highlighted the significance of the findings, noting that the whole-genome approach enabled by Hi-C sequencing addresses the limitations of conventional detection methods for rearrangements that drive classification and care decisions in lymphoid cancers. He stated that the new data add to the growing body of evidence supporting Aventa Lymphoma’s ability to deliver clinically relevant rearrangement insights from standard FFPE specimens.
Clinical and Research Implications
Beyond diagnostic concordance and incremental detection capability, the study also demonstrated the broader research value of Hi-C–generated data. Unlike conventional rearrangement assays that primarily report the presence or absence of specific structural changes, Hi-C sequencing captures genome architecture and long-range regulatory interactions.
This structural context provides deeper insight into how rearrangements may influence gene expression and cancer biology. By mapping interactions across chromosomal regions, researchers can investigate the potential biological impact of structural alterations, including their effects on gene regulation networks. Such information may ultimately contribute to a more nuanced understanding of disease mechanisms and therapeutic vulnerabilities.
For example, a rearrangement might juxtapose regulatory elements with oncogenes, altering gene expression patterns in ways that drive malignancy. Traditional assays may confirm that a rearrangement exists, but they typically do not provide information about its broader genomic context. Hi-C data, by contrast, can reveal how chromosomal architecture changes as a result of structural alterations, offering insights into their functional consequences.
This dual utility—supporting both clinical detection and mechanistic research—positions whole-genome Hi-C sequencing as a potentially transformative tool in hematologic oncology.
The Value of FFPE Compatibility
One of the most significant aspects of the study is its demonstration that Hi-C sequencing can be successfully applied to FFPE samples. FFPE preservation is the standard method for storing tissue specimens in pathology laboratories worldwide. However, DNA extracted from FFPE samples is often fragmented and chemically modified, posing challenges for many advanced genomic assays.
By proving that its Hi-C–based approach is compatible with routine FFPE specimens, Arima Genomics reinforces the practicality and scalability of Aventa Lymphoma within real-world clinical workflows. Laboratories can leverage existing archived samples without requiring fresh or frozen tissue, thereby expanding access to comprehensive genomic analysis.
The ability to analyze archival specimens also opens the door to retrospective studies and real-world evidence generation. Researchers can revisit stored samples to uncover new genomic insights that were not accessible at the time of original diagnosis.
Strengthening the Evidence Base for Aventa Lymphoma
The publication in Cell Genomics represents another milestone in building the evidence base for Aventa Lymphoma. As precision oncology continues to evolve, clinicians increasingly require comprehensive molecular data to guide therapeutic decisions. In lymphoid malignancies, where chromosomal rearrangements play a central role in disease classification and prognosis, the demand for accurate and comprehensive detection tools is particularly acute.
By demonstrating high concordance with standard methods and revealing additional clinically meaningful findings, the study supports the integration of whole-genome structural analysis into lymphoma diagnostics. It also highlights the potential for a single, genome-wide assay to streamline workflows and reduce the need for multiple targeted tests.
