Supplementary Table S1: Training cohort description with plasmaCHORD feature values. Supplementary Table S2: Description of the serial cohort. Supplementary Table S3: Validation cohort description with plasamCHORD feature values. Supplementary Table S4: Description of plasmaCHORD features. Supplementary Table S5: Correlation of cfDNA fragmentomic feature statistics between baseline and follow-up time points in the serial cohort. Supplementary Table S6: Possible CH-origin variants identified on retrospective analysis of 45 patients reviewed at the JH-MTB.

Performance of individual features in predicting variant origin in the training cohort. Receiver-operator curves and area-under the curve (AUC) values for individual model features as predictors for CH versus tumor-origin. The top performing individual features are gene heme fraction, length cluster mutant, and length max delta S. However, no individual feature performs as well as the plasmaCHORD model combining all features.

Description of the training cohort. (A) Distribution of cancer types, stage, and patient age in the training cohort. The mean age for patients in this cohort was 65 years old (range 19-87), the most common cancer type was colorectal, and most patients had early stage disease (22 stage I, 101 stage II, 48 stage III, 53 stage IV, and 1 unknown stage). (B) Distribution of WBC only versus WBC and tumor matched sequencing and determined reference variant origin. The proportion of variants with tumor-derived reference origin is slightly higher from samples that had both WBC and tumor sequencing versus WBC sequencing alone. (C) Distribution of variants included in training cohort by gene and reference variant origin. After DNMT3A, TP53 was the second-most commonly mutated gene (98 variants) of which 67 (68%) are tumor-derived and 31 are WBC-derived.

Abstract Introduction: Genomic profiling of circulating tumor DNA (ctDNA) through liquid biopsies has become an important diagnostic method in clinical oncology. However, detection of variants related to clonal hematopoiesis (CH) is a major confounder that impairs the clinical utility of liquid biopsies. Strategies that reduce biological noise from CH in plasma NGS include deep sequencing of matched WBC DNA and/or tumor tissue sequencing. While these methods effectively distinguish most CH variants, the need for extra biospecimens and sequencing raises costs and limits feasibility. Methods: Using a training cohort of 426 variants identified in ctDNA NGS from 225 patients with stage I-IV solid tumors, we developed plasmaCHORD, a machine learning model (MLM) that includes fragmentomic, variant, and patient-level features to distinguish between tumor- and CH-origin for mutations detected by fixed gene panel hybrid capture NGS. Model performance was assessed by comparison to the reference origin of each plasma variant determined from matched WBC and tumor NGS. Following locking the model parameters, we applied plasmaCHORD to an independent validation cohort of 1,412 plasma variants detected in 114 patients with metastatic cancers, as well as to cfDNA NGS from patients enrolled in a prospective liquid biopsy-informed clinical trial (NCT05585684). Results: PlasmaCHORD predicted tumor versus CH-origin in the training set with high accuracy (cross-validated AUC=0.94), outperforming individual features such as variant allele frequency and canonical CH genes. Model performance remained robust when restricted to mutant DNA fragments supported by 3-5 mutant reads (AUC = 0.84). plasmaCHORD was locked for evaluation using a score of 0.5 as cutoff for distinguishing tumor- versus CH-origin variants. In the independent validation cohort, the locked model maintained similar overall accuracy (AUC=0.9) with a sensitivity of 82%, specificity 80.3% and accuracy of 80.2%. Our approach was shown to be highly reliable in classifying variant origin in clinically actionable genes not canonically associated with CH, including AKT1, ATM, BRCA1, BRCA2, and EGFR, as well as adjudicating cellular origin for TP53 mutations that are encountered in both solid and hematologic malignancies. Performance was consistent across cancer types, sequencing platforms, mutation classes, and a wide range of allele fractions. When applied to clinically challenging cases in the context of a precision oncology clinical trial, plasmaCHORD precisely determined variant origin, preventing mismatches with genotype-targeted therapies. Conclusions: plasmaCHORD, a multi-feature machine-learning classifier, can significantly enhance the ability to identify bona fide tumor variants in routine plasma-only NGS, addressing a critical need in implementing liquid biopsy-guided therapy by minimizing misinterpretation caused by CH. Citation Format: Daniel J. Rabizadeh, Jenna VanLiere Canzoniero, Ilias Ziakas, Jaime Wehr, Archana Balan, Amna Jamali, Blair V. Landon, Susan Combs Scott, Gavin Pereira, Vincent K. Lam, Christine L. Hann, Christine M. Lovly, Jessica Tao, Patrick M. Forde, Joseph C. Murray, Mark Sausen, Gerrit A. Meijer, Geraldine Vink, Remond J. A. Fijneman, Victor E. Velculescu, Jillian Ayn Phallen, Robert Scharpf, Valsamo Anagnostou. PlasmaCHORD- A machine learning method for identifying clonal hematopoiesis variants in liquid biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 95.

This randomized clinical trial evaluates the efficacy and safety of tiragolumab plus atezolizumab plus chemotherapy vs placebo plus pembrolizumab plus chemotherapy in patients with advanced nonsquamous non-small cell lung cancer. QuestionCan treatment with the combination of tiragolumab plus atezolizumab plus chemotherapy improve outcomes for patients with advanced nonsquamous non-small cell lung cancer (NSCLC)?FindingsIn this phase 3 randomized clinical trial of 542 patients with previously untreated, locally advanced unresectable or metastatic NSCLC, tiragolumab plus atezolizumab plus chemotherapy did not demonstrate a progression-free or overall survival benefit vs placebo plus pembrolizumab plus chemotherapy. Tiragolumab plus atezolizumab plus chemotherapy demonstrated a safety profile that was generally similar to that of pembrolizumab plus chemotherapy.MeaningTreatment with the combination of tiragolumab plus atezolizumab plus chemotherapy did not improve outcomes for patients with advanced nonsquamous NSCLC compared with pembrolizumab plus chemotherapy. ImportanceProgrammed cell death 1 ligand 1/programmed cell death protein 1 inhibitors, with or without chemotherapy, are standard first-line treatment for patients with advanced non-small cell lung cancer (NSCLC); however, survival benefit is limited, and many patients experience disease progression.ObjectiveTo evaluate the efficacy and safety of tiragolumab plus atezolizumab plus chemotherapy vs placebo plus pembrolizumab plus chemotherapy in patients with advanced nonsquamous NSCLC.Design, Setting, and ParticipantsSKYSCRAPER-06 was a phase 3 randomized clinical trial that recruited patients with previously untreated, locally advanced unresectable or metastatic NSCLC at 129 sites in 21 countries between December 15, 2020, and September 14, 2023 (data cutoff, April 19, 2024).InterventionPatients were randomized 1:1 to receive either tiragolumab, 600 mg, plus atezolizumab, 1200 mg, plus chemotherapy (pemetrexed, 500 mg/m2, and carboplatin [area under the curve 5], or cisplatin, 75 mg/m2) or placebo plus pembrolizumab, 200 mg, plus chemotherapy via intravenous infusion on day 1 of each 21-day cycle until disease progression, loss of clinical benefit, unacceptable toxic effect, or withdrawal of consent.Main Outcomes and MeasuresPrimary end points were investigator-assessed progression-free survival and overall survival. The safety and tolerability of the study drugs were also evaluated.ResultsOf 542 patients in the full analysis set (mean [SD] age, 63.6 [9.3] years; 353 [65.1%] male), 269 were randomized to tiragolumab plus atezolizumab plus chemotherapy and 273 to placebo plus pembrolizumab plus chemotherapy. Overall, baseline demographics were similar between treatment groups. At data cutoff (median follow-up, 11.8 months), median investigator-assessed progression-free survival was 8.3 months (95% CI, 7.1-9.6 months) with tiragolumab plus atezolizumab plus chemotherapy vs 9.9 months (95% CI, 8.7-11.9 months) with placebo plus pembrolizumab plus chemotherapy (hazard ratio, 1.27; 95% CI, 1.02-1.57; P = .99); median overall survival was 18.9 months (95% CI, 15.2-23.8 months) vs 23.1 months (95% CI, 20.7-33.0 months) in each treatment group, respectively (hazard ratio, 1.33; 95% CI, 1.02-1.73; P = .98). Grade 3 to 4 adverse events occurred in 164 of 267 patients (61.4%) in the tiragolumab plus atezolizumab plus chemotherapy group and 165 of 272 patients (60.7%) in the placebo plus pembrolizumab plus chemotherapy group, with grade 5 AEs occurring in 27 of 267 patients (10.1%) and 16 of 272 patients (5.9%) in each group, respectively.Conclusions and RelevanceIn the phase 3 SKYSCRAPER-06 randomized clinical trial, the primary end points were not met and the study has been terminated.Trial RegistrationClinicalTrials.gov Identifier: NCT04619797

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.

PURPOSE:Targeted next-generation sequencing (NGS) of cell-free DNA (cfDNA) enables comprehensive molecular profiling and can guide the selection of genotype-targeted therapies. However, the detection of variants derived from clonal hematopoiesis (CH) is a significant confounder in liquid biopsies. EXPERIMENTAL DESIGN:Using a training cohort of 426 variants identified in cfDNA NGS from 225 patients with stage I to IV solid tumors, we developed plasma Clonal Hematopoiesis ORigin Detection (plasmaCHORD), a machine learning model that includes fragment-, variant-, and patient-level features to distinguish between tumor and CH origin for each variant detected by liquid biopsies. Model performance was assessed by comparison with the reference origin for each plasma variant determined from matched white blood cell and tumor NGS. Following the locking of the model parameters, we applied plasmaCHORD to an independent validation cohort of 1,418 plasma variants detected in 114 patients with metastatic cancers, as well as to cfDNA NGS from patients enrolled in a prospective clinical trial (NCT05585684). RESULTS:plasmaCHORD predicted tumor origin versus CH origin in the training set with high accuracy (AUC = 0.94). In the independent validation cohort, the locked model maintained similar overall accuracy (AUC = 0.9) and demonstrated significant improvement in accuracy for clinically significant genes. When applied to clinically challenging cases in the context of a precision oncology clinical trial, plasmaCHORD precisely determined variant origin, preventing mismatches with genotype-targeted therapies. CONCLUSIONS:plasmaCHORD, a multifeature machine learning model, can significantly enhance the ability to identify bona fide tumor variants in routine plasma-only NGS, addressing a critical need for implementing liquid biopsy-guided therapy by minimizing misinterpretation caused by CH.

PURPOSE This observational study assessed the real-world characteristics, treatments, and outcomes of US patients with HER2-mutant advanced non-small cell lung cancer (NSCLC) overall and according to HER2 mutation type (tyrosine kinase domain [TKD] and non-TKD).METHODS Deidentified data were extracted for patients with advanced/metastatic NSCLC from the Flatiron Health-Foundation Medicine NSCLC Clinico-Genomic Database. Patients with oncogenic HER2 mutations were included. The primary objectives were to assess the prevalence of HER2 mutations and coaberrations, treatment patterns, and real-world overall survival (OS).RESULTS Overall, 559/14,768 (3.8%) patients had HER2 mutations; 262 (1.8%) were oncogenic. Patients with oncogenic TKD mutations (n = 197) were more frequently younger, female, and never-smokers than those with oncogenic non-TKD mutations (n = 65) and had fewer oncogenic coaberrations. Among patients with oncogenic HER2 mutations who underwent first-line treatment (n = 193), most received platinum-based chemoimmunotherapy (30.5%) or chemotherapy alone (27.9%); 119 patients (61.7%) received second-line treatment. Median OS after first and second lines of treatment was 13.5 months (95% CI, 11.6 to 16.9) and 11.1 months (95% CI, 9.2 to 13.6), respectively. Median OS with first-line platinum-based chemoimmunotherapy was 21.1 (95% CI, 12.2 to NA) and 11.7 months (95% CI, 8.3 to NA) in patients with TKD/non-TKD mutations, respectively, and median OS with platinum-based chemotherapy alone was 9.1 (95% CI, 5.7 to 16.0) and 17.3 (95% CI, 13.6 to NA) months, respectively.CONCLUSION NSCLC patients with oncogenic TKD HER2 mutations had different characteristics and genetic features than patients with non-TKD mutations. Real-world outcomes with first- and second-line standard-of-care treatment were suboptimal, highlighting the need for new treatment options for patients with advanced HER2-mutant NSCLC.

Model performance in the training cohort by number of mutant reads supporting the mutant DNA molecules. Receiver operator curve and AUC values for subsets of training cohort as determined by the number of mutant reads. As the number of mutant reads decreases, the margin of error in the estimated value of the summary statistics comparing distributions between wild-type and mutant reads increases. To evaluate the impact of this on the overall model performance, we determined the model performance in subsets of variants based on number of mutant reads: 3-5 reads inclusive, 6-10 reads, 11-20 reads, 21-100 reads, and >100 reads. For variants with only 3-5 mutant reads, the model performed slightly less well, with AUC = 0.841. For all subsets with >5 mutant reads, the model performed similarly well with AUC 0.89-0.939.

Description of the independent validation cohort. (A) Distribution of plasma variant allele frequency for tumor-origin and WBC-origin variants in the validation cohort. (B) Distribution of variant origin in the validation cohort was determined in the original publication. IMPACT-BAM-matched as defined in the original publication refers to variants detected in tissue biopsy below the limit for variant calling as required for clinical reporting. Note we combined biopsy-matched and IMPACT-BAM-matched as tumor-derived. In this cohort, reference origin for plasma variants as determined by matched sequencing is 63.8% CH-derived and 36.1% tumor-derived. (C) Distribution of alterations and variant origins in genes with more than 10 variants.

Pearson correlation for each individual fragmentomic statistic between baseline and follow-up time points as determined using the serial cohort. Definition of summary statistics are provided in Supplementary Table S2. Each statistic is calculated by comparing mutant versus wild-type reads at a given locus. Statistics that were highly correlated between baseline and follow-up time points (regardless of mutation origin) were included as features in the machine learning model.

Importance:Programmed cell death 1 ligand 1/programmed cell death protein 1 inhibitors, with or without chemotherapy, are standard first-line treatment for patients with advanced non-small cell lung cancer (NSCLC); however, survival benefit is limited, and many patients experience disease progression. Objective:To evaluate the efficacy and safety of tiragolumab plus atezolizumab plus chemotherapy vs placebo plus pembrolizumab plus chemotherapy in patients with advanced nonsquamous NSCLC. Design, Setting, and Participants:SKYSCRAPER-06 was a phase 3 randomized clinical trial that recruited patients with previously untreated, locally advanced unresectable or metastatic NSCLC at 129 sites in 21 countries between December 15, 2020, and September 14, 2023 (data cutoff, April 19, 2024). Intervention:Patients were randomized 1:1 to receive either tiragolumab, 600 mg, plus atezolizumab, 1200 mg, plus chemotherapy (pemetrexed, 500 mg/m2, and carboplatin [area under the curve 5], or cisplatin, 75 mg/m2) or placebo plus pembrolizumab, 200 mg, plus chemotherapy via intravenous infusion on day 1 of each 21-day cycle until disease progression, loss of clinical benefit, unacceptable toxic effect, or withdrawal of consent. Main Outcomes and Measures:Primary end points were investigator-assessed progression-free survival and overall survival. The safety and tolerability of the study drugs were also evaluated. Results:Of 542 patients in the full analysis set (mean [SD] age, 63.6 [9.3] years; 353 [65.1%] male), 269 were randomized to tiragolumab plus atezolizumab plus chemotherapy and 273 to placebo plus pembrolizumab plus chemotherapy. Overall, baseline demographics were similar between treatment groups. At data cutoff (median follow-up, 11.8 months), median investigator-assessed progression-free survival was 8.3 months (95% CI, 7.1-9.6 months) with tiragolumab plus atezolizumab plus chemotherapy vs 9.9 months (95% CI, 8.7-11.9 months) with placebo plus pembrolizumab plus chemotherapy (hazard ratio, 1.27; 95% CI, 1.02-1.57; P = .99); median overall survival was 18.9 months (95% CI, 15.2-23.8 months) vs 23.1 months (95% CI, 20.7-33.0 months) in each treatment group, respectively (hazard ratio, 1.33; 95% CI, 1.02-1.73; P = .98). Grade 3 to 4 adverse events occurred in 164 of 267 patients (61.4%) in the tiragolumab plus atezolizumab plus chemotherapy group and 165 of 272 patients (60.7%) in the placebo plus pembrolizumab plus chemotherapy group, with grade 5 AEs occurring in 27 of 267 patients (10.1%) and 16 of 272 patients (5.9%) in each group, respectively. Conclusions and Relevance:In the phase 3 SKYSCRAPER-06 randomized clinical trial, the primary end points were not met and the study has been terminated. Trial Registration:ClinicalTrials.gov Identifier: NCT04619797.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable biomarkers.

The ribosome, long considered an invariant actor of gene expression, recently emerged as a contributor to translational control through chemical modifications of ribosomal RNAs (rRNAs). These modifications are guided by small nucleolar RNAs (snoRNAs), which direct modifying enzymes to specific rRNA positions. Here, we report that lung adenocarcinoma (LUAD) cells that are resistant to tyrosine kinase inhibitors (TKIs) reshape both their translational program and rRNA 2’O-ribose methylation (2’Ome) profiles. EML4-ALK-positive LUAD cells that are resistant to crizotinib (ALK inhibitor) exhibit reduced global protein synthesis and a change in selective translation of mRNAs, encoding proteins previously linked to resistance. These cells show concomitant reduction in SNORD104 and 2’Ome at its associated 28S_Cm1327 position. Functional studies reveal that SNORD104 depletion abolishes 2’Ome at 28S_Cm1327 without affecting basal translation or cell viability, but enhances both under crizotinib exposure. Moreover, SNORD104 knockdown attenuates caspase activation and PARP cleavage during treatment, supporting reduced cell death. Altogether, our findings support a role for snoRNA-guided rRNA modification as a novel non-genomic mechanism in early adaptive responses to crizotinib therapy in LUAD.

Classification schema for determining reference origin of plasma variants using matched WBC and/or tumor tissue sequencing. For each variant detected in plasma, reference origin was determined by comparison with matched WBC sequencing and tumor sequencing (if available). If patient had both WBC and tumor sequencing, then plasma variants that were detected with at least 3 read families in WBC and not detected in tumor were considered WBC-derived. Variants were considered tumor-derived if they were detected with VAF >10% in tumor, or if the variant was detected by IGV in the tumor and was detected in 1 or fewer read families in WBC sequencing. If patient had only WBC sequencing, then plasma variants that were also identified in WBC sequencing with at least 3 read families were called CH-derived. Plasma variants that were not identified in matched WBC sequencing (0 read families) where there was adequate coverage in the WBC sequencing at that locus were called tumor-derived. Variants that did not meet any of these criteria were determined to be unknown origin and were excluded from the remaining analysis.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of patients with NSCLC, including diagnosis, primary disease management, surveillance, and subsequent treatment. The panel has updated the list of recommended targeted therapies based on recent FDA approvals and clinical data. This selection from the NCCN Guidelines for NSCLC focuses on treatment recommendations for advanced or metastatic NSCLC with actionable biomarkers.

Mesothelioma is a rare cancer that originates from the mesothelial surfaces of certain sites within the body. Pleural mesothelioma is the most common type and represents approximately 85% of mesotheliomas. The NCCN Guidelines for Mesothelioma: Pleural provide recommendations for evaluation and treatment in patients with pleural mesothelioma. The NCCN Guidelines will continue to be updated annually based on available clinical evidence and panel consensus.

Assessment of fragmentomic features. (A-B) Illustrative examples of fragmentome distribution differences seen between mutant and wild-type reads from CH-origin versus tumor origin variants. (A) Tumor-derived plasma variant TP53 p.S215R with fragment length density left-shifted (shorter) for mutant compared to wild-type fragments (middle), and with the fragment endpoints relative to mutation location closer together and left-shifted in mutant versus wild-type fragments (bottom). (B) CH-origin variant TP53 p.M237I with overlapping fragment length densities (middle) and fragment endpoint locations (bottom) between mutant and wild-type reads. (C) The serial cohort used to assess fragmentomic features over time. Each column represents a variant, with points on the y-axis depicting VAF at baseline (black) and at follow-up (gray) time points. This cohort included patients with colorectal, esophageal, and NSCLC, stage I-III and included both tumor-origin and WBC-origin plasma variants. (D) Pearson’s product moment correlation of fragmentomic feature values at baseline and follow-up timepoints. Correlation of features between baseline and follow-up timepoint was calculated regardless of variant origin (black bars). Features that were correlated over time with p-value <0.05 were subsequently used for development of the machine learning model. Correlation of features between baseline and follow-up timepoint was also calculated for the subset of tumor-derived variants (red bars) and CH-derived variants (blue bars), demonstrating similar correlation of features over time regardless of variant origin.

The NCCN Guidelines for Non-Small Cell Lung Cancer (NSCLC) provide recommendations for the treatment of NSCLC. These NCCN Guidelines Insights discuss recent updates to the NCCN Guidelines, with a focus on systemic therapy options for the treatment of patients with nonmetastatic NSCLC and the corresponding molecular testing considerations.

Sequence alterations that were classified as germline (median 44.9%, range 27.3% - 73.1%) had the highest overall MAFs, compared to both tumor-derived (median 10.2%, range 0.1% - 75.7%) and clonal-hematopoiesis-derived (CH-derived) variants (median 0.8%, range 0.1 – 86.7%). Tumor-derived variants had significantly higher MAFs compared to CH-derived variants. P values were calculated using the Mann-Whitney U test. **** p < 0.0001