Objectives: To elucidate clinicopathologic and molecular characteristics of IDH1 and IDH2 (IDH1/2) mutations in colorectal cancers (CRCs). Methods: We evaluated IDH1/2 mutations in 1,623 CRCs using a next-generation sequencing assay. Results: IDH1/2 mutations, predominantly IDH1 p.R132C, were detected in 15 (0.9%) CRCs and in 5 (3.0%) of 167 BRAF p.V600E–mutated CRCs. Three IDH1/2-mutated CRCs were associated with inflammatory bowel disease. They were significantly associated with old age, mucinous or signet ring cell adenocarcinoma, and high-grade histomorphology. Concordance of variant allele frequency between IDH1/2 mutants and other trunk drivers in CRCs and presence of IDH1/2 mutation in the adenoma and early adenocarcinoma indicated IDH1/2 mutations could be trunk drivers suitable for targeted therapy. Conclusions: IDH1/2 mutations in CRCs were uncommon but enriched in BRAF p.V600E–mutated CRCs and perhaps colitis-associated CRCs. Further studies on IDH1/2-mutated CRCs are needed to clarify their clinicopathologic features and implications for targeted therapy.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the ASCO Guidelines Methodology Manual . ASCO Guidelines follow the ASCO Conflict of Interest Policy for Clinical Practice Guidelines . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases, or stages of diseases. Guidance is based on review and analysis of relevant literature and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and 2 (online only) for more . PURPOSE: To provide guidance on the use of circulating tumor DNA (ctDNA) testing in patients with solid tumors or lymphoma. METHODS: A systematic review by a multidisciplinary panel with patient representation was conducted. The PubMed database was searched from January 2017 to February 2025. Guideline recommendations were based on consideration of the identified evidence. RESULTS: Fifty-four meta-analyses and 22 study reports were identified, including reports of seven randomized trials. RECOMMENDATIONS: ctDNA testing for tumor genetic alterations may be used in situations where: tumor tissue testing is challenging, not feasible, or tumor biopsy represents unacceptable risks to the patient; tumor tissue testing results may not be available within a clinically actionable time frame to determine appropriate management options; or a drug's regulatory approved indication allows for or requires ctDNA testing. If ctDNA testing results are negative, inconclusive, or inconsistent with the clinical scenario, tissue-based confirmation should be sought. Other than testing for genetic alterations, ctDNA testing may be offered if a specific, evidence-based action can be taken with the results or there is conflict or ambiguity with standard-of-care assessment that may be resolved by ctDNA testing. Fractional, percentage, or concentration-based measures of ctDNA or total cell-free DNA concentration are not recommended as a surrogate measure of disease. The panel recognizes this is a rapidly evolving field and guidelines are anticipated to change, bringing in tumor-type specific recommendations and incorporating more data on molecular residual disease settings. Additional information is available at www.asco.org/molecular-testing-and-biomarkers-guidelines .

Epstein-Barr virus (EBV) is associated with a variety of tumors and nonmalignant conditions. Latent EBV genomes in cells, including tumor cells, are often CpG methylated, whereas virion DNA is not CpG methylated. We demonstrate that methyl CpG binding magnetic beads can be used to fractionate among sources of EBV DNA (DNA extracted from laboratory-purified virions vs DNA extracted from latently infected cell lines). We then applied the technique to plasma specimens and showed that this technique can distinguish EBV DNA from patients with EBV-associated tumors (nasopharyngeal carcinoma, Hodgkin lymphoma) and viral DNA from patients without EBV-associated tumors, including immunocompromised patients and patients with EBV(−) Hodgkin lymphoma.

Purpose: Given the pace of predictive biomarker and targeted therapy development, it is unknown whether repeat annotation of the same next-generation sequencing data can identify additional clinically actionable targets that could be therapeutically leveraged. In this study, we sought to determine the predictive yield of serial reanalysis of clinical tumor sequencing data. Experimental Design: Using artificial intelligence (AI)-assisted variant annotation, we retrospectively reanalyzed sequencing data from 2,219 patients with cancer from a single academic medical center at 3-month intervals totaling 9 months in 2020. The yield of serial reanalysis was assessed by the proportion of patients with improved strength of therapeutic recommendations. Results: A total of 1,775 patients (80%) had ≥1 potentially clinically actionable mutation at baseline, including 243 (11%) patients who had an alteration targeted by an FDA-approved drug for their cancer type. By month 9, the latter increased to 458 (21%) patients mainly due to a single pan-cancer agent directed against tumors with high tumor mutation burden. Within this timeframe, 67 new therapies became available and 45 were no longer available. Variant pathogenicity classifications also changed leading to changes in treatment recommendations for 124 patients (6%). Conclusions: Serial reannotation of tumor sequencing data improved the strength of treatment recommendations (based on level of evidence) in a mixed cancer cohort and showed substantial changes in available therapies and variant classifications. These results suggest a role for repeat analysis of tumor sequencing data in clinical practice, which can be streamlined with AI support.