Comprehensive elaboration of database resources utilized in next-generation sequencing-based tumor somatic mutation detection

ERIC recommendations for TP53 mutation analysis in chronic lymphocytic leukemia-2024 update

In chronic lymphocytic leukemia (CLL), analysis of TP53 aberrations (deletion and/or mutation) is a crucial part of treatment decision-making algorithms. Technological and treatment advances have resulted in the need for an update of the last recommendations for TP53 analysis in CLL, published by ERIC, the European Research Initiative on CLL, in 2018. Based on the current knowledge of the relevance of low-burden TP53-mutated clones, a specific variant allele frequency (VAF) cut-off for reporting TP53 mutations is no longer recommended, but instead, the need for thorough method validation by the reporting laboratory is emphasized. The result of TP53 analyses should always be interpreted within the context of available laboratory and clinical information, treatment indication, and therapeutic options. Methodological aspects of introducing next-generation sequencing (NGS) in routine practice are discussed with a focus on reliable detection of low-burden clones. Furthermore, potential interpretation challenges are presented, and a simplified algorithm for the classification of TP53 variants in CLL is provided, representing a consensus based on previously published guidelines. Finally, the reporting requirements are highlighted, including a template for clinical reports of TP53 aberrations. These recommendations are intended to assist diagnosticians in the correct assessment of TP53 mutation status, but also physicians in the appropriate understanding of the lab reports, thus decreasing the risk of misinterpretation and incorrect management of patients in routine practice whilst also leading to improved stratification of patients with CLL in clinical trials.

Sintilimab and Chidamide for Refractory Transformed Diffuse Large B Cell Lymphoma: A Case Report and A Literature Review

Patients with relapsed/refractory (R/R) transformed diffused large B cell lymphoma (tDLBCL) have a poor prognosis and a low survival rate. In addition, no standard therapy has yet been established for R/R tDLBCL. Herein we presented a single case of a patient with R/R tDLBCL who was successfully treated with sintilimab and chidamide. The patient was a 71-year-old man with pulmonary mucosa-associated lymphoid tissue lymphoma. He did not receive any treatment until tDLBCL was confirmed 2 years later. The tDLBCL was primary refractory to R2-CHOP, R2-MTX, and Gemox regimens. However, the patient achieved sustained complete remission after the combination therapy of sintilimab and chidamide. To the best of our knowledge, this is the first report of sintilimab combined with chidamide for the treatment of R/R tDLBCL, which opens up new therapeutic possibilities for this new combination therapy in future prospective clinical trials.

Comparison of Open-access Databases for Clinical Variant Interpretation in Cancer: A Case Study of MDS/AML

BACKGROUND

Recently, guidelines for variant interpretation in cancer have been established. However, these guidelines do not mention which databases are most suited to performing this task.

MATERIALS AND METHODS

We give an overview of existing databases and evaluate their benefit in practical application. We compared three meta-databases and 12 databases for a dataset of patients with myelodysplastic syndrome or acute myeloid leukemia.

RESULTS

Clinical implications were found for 13% of all variants. One-third of variants with therapeutic implications were uniquely contained in one database. The VICC meta-database was the most extensive source of information, featuring 92% of variants with a drug association. However, a comparison of meta-databases and original sources indicated that some variants are missing in those meta-databases.

CONCLUSION

Public databases provide decision support for interpreting variants but there is still need for manual curation. Meta-databases facilitate the use of multiple resources but should be interpreted with caution.

A Review of Precision Oncology Knowledgebases for Determining the Clinical Actionability of Genetic Variants

The increased availability of tumor genetic testing and targeted cancer therapies contributes to the advancement of precision medicine in the field of oncology. Precision oncology knowledgebases provide a way of organizing clinically relevant genetic information in a way that is easily accessible for both oncologists and patients, facilitating the genetic-based clinical decision making. Many organizations and companies have built precision oncology knowledgebases, intended for multiple users. In general, these knowledgebases offer information on cancer-related genetic variants as well as their associated diagnostic, prognostic, and therapeutic implications, but they often differ in their information curations, designs, and user experiences. It is advisable that oncologists use multiple knowledgebases during their practice to have them complement each other. In the future, convergence toward common standards and formats is needed to ensure that the comprehensive knowledge across all sources can be unified to bring the oncology community closer to the achievement of the goal of precision oncology.

Next-Generation Sequencing and the Clinical Oncology Workflow: Data Challenges, Proposed Solutions, and a Call to Action

PURPOSE

Next-generation sequencing (NGS) of tumor and germline DNA is foundational for precision oncology, with rapidly expanding diagnostic, prognostic, and therapeutic implications. Although few question the importance of NGS in modern oncology care, the process of gathering primary molecular data, integrating it into electronic health records, and optimally using it as part of a clinical workflow remains far from seamless. Numerous challenges persist around data standards and interoperability, and clinicians frequently face difficulties in managing the growing amount of genomic knowledge required to care for patients and keep up to date.

METHODS

This review provides a descriptive analysis of genomic data workflows for NGS data in clinical oncology and issues that arise from the inconsistent use of standards for sharing data across systems. Potential solutions are described.

RESULTS

NGS technology, especially for somatic genomics, is well established and widely used in routine patient care, quality measurement, and research. Available genomic knowledge bases play an evolving role in patient management but lack harmonization with one another. Questions about their provenance and timeliness of updating remain. Potentially useful standards for sharing genomic data, such as HL7 FHIR and mCODE, remain primarily in the research and/or development stage. Nonetheless, their impact will likely be seen as uptake increases across care settings and laboratories. The specific use case of ASCO CancerLinQ, as a clinicogenomic database, is discussed.

CONCLUSION

Because the electronic health records of today seem ill suited for managing genomic data, other solutions are required, including universal data standards and applications that use application programming interfaces, along with a commitment on the part of sequencing laboratories to consistently provide structured genomic data for clinical use.