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23 2026

Clinical validation of WES-based HRD scoring and its prognostic value for PARP inhibitor maintenance therapy in ovarian cancer

Abstract Background:Homologous recombination deficiency (HRD) is an important biomarker for predicting response to PARP inhibitor (PARPi) therapy in ovarian cancer. This study evaluated the clinical performance and prognostic value of a whole-exome sequencing (WES)-based HRD assay.   Methods:Eighty-one ovarian cancer patients treated with PARPi therapy were analyzed using the CancerProfiler™ WES panel. HRD scores were calculated based on genomic scar signatures, while germline and somatic BRCA1/2 mutations were simultaneously assessed. The prognostic impact of HRD status and BRCA mutations on progression-free survival (PFS) was evaluated.   Results:HRD-high status (≥50) was strongly associated with improved PARPi treatment outcomes, particularly in treatment-naïve tumors. HRD-high patients showed significantly longer progression-free survival compared with HRD-low patients in both first- and second-line settings. In contrast, BRCA mutation status demonstrated more limited and treatment-dependent predictive value. HRD-high status remained an independent predictor of favorable outcomes after recurrence.   Conclusions:WES-based HRD scoring is a robust predictor of PARPi benefit in ovarian cancer and may provide broader clinical utility than BRCA mutation status alone. These findings support further validation of WES-based HRD assays as scalable alternatives for precision oncology.   Citation:DongSoo Kyung et al. “Clinical validation of WES-based HRD scoring and its prognostic value for PARP inhibitor maintenance therapy in ovarian cancer.” Presented at the American Association for Cancer Research Annual Meeting 2026, April 17–22, 2026, San Diego, CA. Published in Cancer Research 2026;86(7 Suppl): Abstract 4019.  

Clinical validation of WES-based HRD scoring and its prognostic value for PARP inhibitor maintenance therapy in ovarian cancer

American Assoiation for Cancer Research (AACR)

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22 2026

Prognostic significance of PI3K-AKT pathway alterations identified by ctDNA sequencing in metastatic castration-resistant prostate cancer

Abstract Background:PI3K-AKT pathway alterations are important drivers of metastatic castration-resistant prostate cancer (mCRPC) and are associated with treatment resistance and poor prognosis. This study evaluated the prevalence and prognostic significance of PI3K-AKT pathway alterations using circulating tumor DNA (ctDNA) sequencing.   Methods:A total of 127 mCRPC patients underwent high-depth ctDNA sequencing using the AlphaLiquid®100 assay. Genomic alterations in PI3K-AKT pathway genes were analyzed and compared with PTEN immunohistochemistry (IHC) and clinical outcomes, including overall survival (OS).   Results:Somatic ctDNA alterations were detected in 91.3% of patients. PTEN pathogenic mutations identified by ctDNA sequencing were significantly associated with worse overall survival, particularly in patients with synchronous metastasis. In contrast, PTEN loss detected by IHC did not demonstrate significant prognostic value. Alterations in PIK3CA and AKT1 also showed a trend toward poorer survival outcomes.   Conclusions:ctDNA sequencing effectively identified PI3K-AKT pathway alterations with strong prognostic significance in mCRPC. These findings support the clinical utility of ctDNA-based genomic profiling for personalized treatment strategies.   Citation:DongSoo Kyung et al. “Prognostic significance of PI3K-AKT pathway alterations identified by ctDNA sequencing in metastatic castration-resistant prostate cancer.” Presented at the American Association for Cancer Research Annual Meeting 2026, April 17–22, 2026, San Diego, CA. Published in Cancer Research 2026;86(7 Suppl): Abstract 3841.

Prognostic significance of PI3K-AKT pathway alterations identified by ctDNA sequencing in metastatic castration-resistant prostate cancer

American Assoiation for Cancer Research (AACR)

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21 2026

Postoperative minimal residual disease detection using tumor-informed circulating tumor DNA analysis in stage II–III gastric cancer: Updated analysis.

Abstract Background:Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) analysis may improve recurrence risk prediction and guide adjuvant chemotherapy (ACT) decisions in gastric cancer. This study evaluated the clinical utility of postoperative ctDNA MRD monitoring in stage II–III gastric cancer patients.   Methods:This sub-study of the EXODOX phase III trial analyzed postoperative ctDNA MRD using the CancerDetect assay developed by IMBdx. Tumor-informed personalized panels were generated for each patient, and blood samples were collected at multiple postoperative time points to assess MRD status.   Results:MRD positivity was more frequently observed in stage III disease and was strongly associated with increased recurrence risk and worse recurrence-free survival (RFS). Patients who achieved MRD clearance after adjuvant chemotherapy showed outcomes comparable to persistently MRD-negative patients, whereas persistent MRD positivity was associated with the poorest prognosis.   Conclusions:Postoperative ctDNA MRD detection effectively predicted recurrence in stage II–III gastric cancer. MRD dynamics during treatment may help guide adjuvant chemotherapy strategies and postoperative surveillance.        

Postoperative minimal residual disease detection using tumor-informed circulating tumor DNA analysis in stage II–III gastric cancer: Updated analysis.

2026 ASCO Gastrointestinal Cancers Symposium

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20 2026

Deep learning–based cfDNA fragment–level analysis: A genome-scanning approach for detection of colorectal cancer.

Abstract Background:Cell-free DNA (cfDNA) has emerged as a promising biomarker for cancer detection. Circulating tumor DNA (ctDNA) contains distinct genomic and epigenomic features, including mutations and fragmentomic patterns, that differentiate cancer patients fr|om healthy individuals. This study aimed to develop a deep-learning–based cancer detection method by integrating fragment-level genomic and epigenomic features.   Methods:The study analyzed cfDNA samples fr|om 768 healthy individuals and 150 colorectal cancer patients (stages I–IV). A deep-learning framework based on a 2D convolutional neural network (CNN) was developed using multi-channel genomic tensors derived fr|om sequencing reads. Six strand-specific channels, including nucleotide sequences, methylation status, and fragment alignment characteristics, were integrated for analysis. Model performance was compared with conventional approaches such as Average Methylation Fraction (AMF), Depth Profile, Fragment Size Ratio (FSR), and end-motif analysis.   Results:The proposed method demonstrated superior performance compared with conventional methods, achieving the highest mean per-marker AUC (0.769 ± 0.039). The final model achieved an overall AUC of 0.905 in the independent test set. The model also showed strong performance for both early-stage (I–II) colorectal cancer detection (AUC 0.880) and advanced-stage (III–IV) disease detection (AUC 0.929).   Conclusions:Integrating fragment-level cfDNA genomic and epigenomic features enables highly accurate colorectal cancer detection, including early-stage disease. The genome-scanning deep-learning approach also improves interpretability by visualizing cancer-associated genomic regions, highlighting its potential as a precise and clinically useful liquid biopsy platform.

Deep learning–based cfDNA fragment–level analysis: A genome-scanning approach for detection of colorectal cancer.

2026 ASCO Gastrointestinal Cancers Symposium

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19 2026

Preliminary results of tumor-informed minimal residual disease detection in pancreatic cancer patients following curative resection and FOLFIRINOX adjuvant chemotherapy.

Abstract Background:Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) testing has emerged as a promising prognostic tool in solid tumors and may help guide postoperative treatment strategies. This study evaluated the prognostic significance of ctDNA MRD monitoring in patients with pancreatic cancer who underwent curative resection followed by adjuvant FOLFIRINOX therapy.   Methods:Between October 2023 and February 2025, patients with resected pancreatic cancer receiving adjuvant FOLFIRINOX were prospectively enrolled fr|om 11 hospitals in Korea. Blood samples were collected at up to seven postoperative time points and analyzed using a tumor-informed ctDNA assay (CancerDetect, IMBdx). MRD positivity was defined as the detection of two or more mutations.   Results:A total of 86 patients were included in the analysis. The postoperative MRD positivity rate at the initial time point (P1) was 31.3%, and positivity increased with advancing disease stage. During a median follow-up of 13 months, 23.3% of patients experienced recurrence. Conventional clinicopathologic factors, including stage and T/N classification, were not significantly associated with disease-free survival (DFS). In contrast, MRD positivity at P1 was strongly associated with inferior DFS (HR 5.31, P<0.001). The prognostic impact of MRD was particularly significant in stage I and II disease. Longitudinal MRD analysis further demonstrated that patients with persistent MRD positivity had the poorest outcomes, while dynamic MRD changes were closely associated with treatment response and recurrence risk.   Conclusions:Postoperative ctDNA MRD detection strongly predicted recurrence in resected pancreatic cancer treated with adjuvant FOLFIRINOX. Longitudinal MRD dynamics also correlated with treatment response and recurrence risk, supporting the clinical utility of ctDNA MRD for postoperative surveillance and therapeutic decision-making.

Preliminary results of tumor-informed minimal residual disease detection in pancreatic cancer patients following curative resection and FOLFIRINOX adjuvant chemotherapy.

2026 ASCO Gastrointestinal Cancers Symposium

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