JCO precision oncology最新文献

Purpose: Robotic-assisted proctectomy (RAP) has emerged as the predominant surgical approach for patients with rectal cancer in recent years; although good postoperative patient recovery with accurate prediction is a guarantee of adaptive surveillance management, there is still a lack of easy-to-use prognostic tools and risk scores designed specifically for those patients undergoing RAP.

Methods: This study used the electronic health records of 506 RAP participants, including a National Specialist Center for da Vinci Robotic Colorectal Surgery (NSCVRCS) meta cohort, and an independent external validation Sun Yat-sen Memorial Hospital cohort. In the NSCVRCS meta cohort, patients were divided into a discovery cohort (70%, n = 268), where the best-fit model was applied to model our prediction system, RAP-AIscore. Subsequently, an internal validation process for RAP-AIscore was conducted using a replication cohort (30%, n = 116). The study designed and implemented a large-scale artificial intelligence (AI) hybrid framework to identify the best strategy for building a survival assessment system, the RAP-AIscore, from 132 potential modeling scenarios through a combination of iterative cross-validation, Monte Carlo cross-validation, and bootstrap resampling. The 10 variables most relevant to clinical interpretability were identified on the basis of the AI hybrid optimal model values, which helps provide reliable prognostic survival guidance for new patients.

Results: The consistent evaluation of discrimination, calibration, generalization, and prognostic value across cohorts reaffirmed the accuracy and robust extrapolation capability of this system. The 10 feature variables most associated with clinical interpretability on the basis of Shapley values were identified, facilitating reliable prognostic survival guidance for new patients.

Conclusion: This study introduces a promising and informative tool, the RAP-AIscore, which can be explained through nomograms for interpreting clinical outcomes. It facilitates postoperative risk stratification management and enhances clinical management of prognosis for RAP patients.

Purpose: Tumor next-generation sequencing (NGS) testing identifies possible germline pathogenic variants (PGPVs), creating a dilemma for appropriate recognition, triage, and management. The objective of this study was to determine the clinical utility of an institutional molecular tumor board (MTB) in assessing tumor NGS reports for PGPVs.

Methods: Our institutional MTB reviews all NGS reports to provide treatment and further testing recommendations, including genetic counseling referral and consideration of genetic testing (GC/GT). We studied the patients reviewed by the MTB who were recommended for GC/GT to determine the frequency of referral to a GC, germline test completion, rate of pathogenic germline variants (PGVs), factors related to PGVs, and germline conversion rate (GCR).

Results: Of the 2,355 patients reviewed by the MTB during the study period, 609 (25.9%) had a recommendation for GC/GT. Of the 609 with a GC/GT recommendation, only 181 (29.7%) were referred for GC/GT by their treating physicians, and only 107 (17.6%) completed GT. Of the 107 patients completing GT, 29 (26%) had a confirmed PGV. The only factors significantly associated with PGVs were testing due to a PGPV and higher mean variant allele fraction on the tumor NGS. Only 40 patients with a GC/GT recommendation (14.3%) due to a PGPV completed GT; however, the GCR was 42.5% (n = 17/40).

Conclusion: The MTB review of PGPV is clinically valuable, identifying PGPV in 12% of patients undergoing tumor NGS and a GCR of 42.5%. Rates of GC/GT completion were relatively low due to under-referral by treating physicians. Given the high GCR, the authors encourage institutional algorithms to help increase GC/GT rates for patients found to have PGPV following tumor NGS testing.

Imatinib may be a useful targeted agent for patients with advanced gastric adenocarcinoma who have KIT mutations.

Purpose: Cancer of unknown primary (CUP) is a syndrome comprising metastatic cancers without a clinically identified primary site. Although patients with CUP have an unfavorable prognosis, treatment with site-specific therapies guided by clinical features, standard pathology, and molecular assays can improve overall survival. The 92-gene assay (CancerTYPE ID) is a gene expression-based classifier that helps identify the tissue of origin for metastatic cancers with unknown or uncertain diagnoses. This study reports the frequency of selected molecular aberrations of oncogenes, including KRAS, IDH1/2, BRCA1/2, and BRAF, in patients with CUP in the MOSAIC database to highlight potential treatment options.

Methods: MOSAIC is a database of patients with CUP submitted for CancerTYPE ID testing and NeoTYPE biomarker testing. Tumor biopsy samples were analyzed by CancerTYPE ID for tumor type identification and further tested for molecular aberrations of oncogenes, including KRAS, IDH1/2, BRCA1/2, and BRAF.

Results: CancerTYPE ID identified a specific tumor type in 92.5% (2,929 of 3,168) of CUP cases in the MOSAIC database. The most commonly identified histological type was adenocarcinoma (75.4%), with pancreaticobiliary being the most common molecularly diagnosed cancer (24.9%). Aberrations in KRAS, IDH1/2, BRCA, and BRAF genes were identified in 18.8% (n = 597) of biopsies. A cancer-specific US Food and Drug Administration (FDA)-approved or investigational targeted therapy was potentially available for 24.6% (n = 147) of these patients.

Conclusion: This retrospective analysis supports incorporating CancerTYPE ID into the evaluation for patients with CUP to help determine the tissue of origin and identify actionable genetic alterations. This approach may allow more patients with CUP to benefit from site-specific FDA-approved targeted therapies or enrollment into clinical trials.

Total gastrectomy should be performed less often in germline CDH1 variant carriers based on mounting clinical evidence.

Socioeconomic factors influence the survival of patients with early stage melanoma and thus should be accounted for in prognostication tools.