Molecular profiling of visible polypoid and invisible conventional intestinal-type low-grade dysplasia in patients with idiopathic inflammatory bowel disease.

AIMS: Little is known about the molecular features of visible polyps with low-grade intestinal-type dysplasia in patients with inflammatory bowel disease (IBD). To better understand their origins and biological potential, we sought to genomically profile these lesions and compare them with invisible low-grade dysplasia and sporadic adenomas from non-IBD patients. METHODS: 22 polyps within areas of colitis, 13 polyps outside areas of colitis, 10 foci of invisible dysplasia from patients with IBD and 6 sporadic tubular adenomas from non-IBD patients were analysed using the OncoPanel assay. RESULTS: Polyps arising in areas of colitis showed a greater spectrum of mutations, including APC, KRAS, FBXW7, TP53, ARID1A and TCF7L2. Polyps outside colitis and non-IBD sporadic adenomas showed a limited mutational profile, with APC and CTNNB1 mutations. Invisible dysplasia was characterised by TP53, CTNNB1 and KRAS alterations. Compared with dysplastic polyps, none of the invisible dysplastic foci showed APC alterations (73%-within colitis; p=0.0001, 92%-outside colitis; p<0.0001, 83%-sporadic adenomas; p=0.001). TP53 mutations were significantly higher in invisible dysplasia (50%) compared with polyps within colitis (9%; p=0.02) and outside colitis (8%; p=0.03). CONCLUSIONS: Molecular alterations in visible low-grade dysplastic polyps with conventional intestinal-type dysplasia from patients with IBD and sporadic adenomas from non-IBD patients overlap significantly. APC alterations appear to play a major role in the development of visible low-grade dysplastic lesions in patients with IBD, regardless of background colitis. As with IBD-associated colorectal cancers, TP53 mutations are an early event in the development of invisible, low-grade conventional intestinal-type dysplasia in patients with IBD.

Recommendations for Tumor Mutational Burden Assay Validation and Reporting: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, and Society for Immunotherapy of Cancer.

Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays.

Molecular profiling of 888 pediatric tumors informs future precision trials and data-sharing initiatives in pediatric cancer.

To inform clinical trial design and real-world precision pediatric oncology practice, we classified diagnoses, assessed the landscape of mutations, and identified genomic variants matching trials in a large unselected institutional cohort of solid tumors patients sequenced at Dana-Farber / Boston Children's Cancer and Blood Disorders Center. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel. Diagnoses were classified according to the International Classification of Diseases for Oncology (ICD-O-3.2). Over 6.5 years, 888 pediatric cancer patients with 95 distinct diagnoses had successful tumor sequencing. Overall, 33% (n = 289/888) of patients had at least 1 variant matching a precision oncology trial protocol, and 14% (41/289) were treated with molecularly targeted therapy. This study highlights opportunities to use genomic data from hospital-based sequencing performed either for research or clinical care to inform ongoing and future precision oncology clinical trials. Furthermore, the study results emphasize the importance of data sharing to define the genomic landscape and targeted treatment opportunities for the large group of rare pediatric cancers we encounter in clinical practice.

Contemporary Prognostic Signatures and Refined Risk Stratification of Gliomas: An Analysis of 4,400 Tumors.

BACKGROUND: With the significant shift in the classification, risk stratification, and standards of care for gliomas, we sought to understand how the overall survival of patients with these tumors is impacted by molecular features, clinical metrics, and treatment received. METHODS: We assembled a cohort of patients with a histopathologically diagnosed glioma from The Cancer Genome Atlas, Project Genomics Evidence Neoplasia Information Exchange, and Dana-Farber Cancer Institute/Brigham and Women's Hospital. This incorporated retrospective clinical, histological, and molecular data alongside prospective assessment of patient survival. RESULTS: 4,400 gliomas were identified: 2,195 glioblastoma, 1,198 IDH1/2-mutant astrocytoma, 531 oligodendroglioma, 271 other IDH1/2-wildtype glioma, and 205 pediatric-type glioma. Molecular classification updated 27.2% of gliomas from their original histopathologic diagnosis. Examining the distribution of molecular alterations across glioma subtypes revealed mutually exclusive alterations within tumorigenic pathways. Non-TCGA patients had significantly improved overall survival compared to TCGA patients, with 26.7%, 55.6%, and 127.8% longer survival for glioblastoma, IDH1/2-mutant astrocytoma, and oligodendroglioma respectively (all p<0.01). Several prognostic features were characterized, including NF1 alteration and 21q loss in glioblastoma, and EGFR amplification and 22q loss in IDH1/2-mutant astrocytoma. Leveraging the size of this cohort, nomograms were generated to assess the probability of overall survival based on patient age, the molecular features of a tumor, and the treatment received. CONCLUSIONS: By applying modern molecular criteria, we characterize the genomic diversity across glioma subtypes, identify clinically applicable prognostic features, and provide a contemporary update on patient survival to serve as a reference for ongoing investigations.