Japanese Society of Medical Oncology/Japan Society of Clinical Oncology/Japanese Society of Pediatric Hematology/Oncology-led clinical recommendations on the diagnosis and use of immunotherapy in patients with high tumor mutational burden tumors

Agnostic Administration of Targeted Anticancer Drugs: Looking for a Balance between Hype and Caution

Many tumors have well-defined vulnerabilities, thus potentially allowing highly specific and effective treatment. There is a spectrum of actionable genetic alterations which are shared across various tumor types and, therefore, can be targeted by a given drug irrespective of tumor histology. Several agnostic drug-target matches have already been approved for clinical use, e.g., immune therapy for tumors with microsatellite instability (MSI) and/or high tumor mutation burden (TMB), NTRK1-3 and RET inhibitors for cancers carrying rearrangements in these kinases, and dabrafenib plus trametinib for BRAF V600E mutated malignancies. Multiple lines of evidence suggest that this histology-independent approach is also reasonable for tumors carrying ALK and ROS1 translocations, biallelic BRCA1/2 inactivation and/or homologous recombination deficiency (HRD), strong HER2 amplification/overexpression coupled with the absence of other MAPK pathway-activating mutations, etc. On the other hand, some well-known targets are not agnostic: for example, PD-L1 expression is predictive for the efficacy of PD-L1/PD1 inhibitors only in some but not all cancer types. Unfortunately, the individual probability of finding a druggable target in a given tumor is relatively low, even with the use of comprehensive next-generation sequencing (NGS) assays. Nevertheless, the rapidly growing utilization of NGS will significantly increase the number of patients with highly unusual or exceptionally rare tumor-target combinations. Clinical trials may provide only a framework for treatment attitudes, while the decisions for individual patients usually require case-by-case consideration of the probability of deriving benefit from agnostic versus standard therapy, drug availability, associated costs, and other circumstances. The existing format of data dissemination may not be optimal for agnostic cancer medicine, as conventional scientific journals are understandably biased towards the publication of positive findings and usually discourage the submission of case reports. Despite all the limitations and concerns, histology-independent drug-target matching is certainly feasible and, therefore, will be increasingly utilized in the future.

Genomic Landscape of Endometrial, Ovarian, and Cervical Cancers in Japan from the Database in the Center for Cancer Genomics and Advanced Therapeutics

This study aimed to comprehensively clarify the genomic landscape and its association with tumor mutational burden-high (TMB-H, ≥10 mut/Mb) and microsatellite instability-high (MSI-H) in endometrial, cervical, and ovarian cancers. We obtained genomic datasets of a comprehensive genomic profiling test, FoundationOne® CDx, with clinical information using the "Center for Cancer Genomics and Advanced Therapeutics" (C-CAT) database in Japan. Patients can undergo the tests only after standardized treatments under universal health insurance coverage. Endometrial cancers were characterized by a high frequency of TMB-H and MSI-H, especially in endometrioid carcinomas. The lower ratio of POLE exonuclease mutations and the higher ratio of TP53 mutations compared to previous reports suggested the prognostic effects of the molecular subtypes. Among the 839 cervical cancer samples, frequent mutations of KRAS, TP53, PIK3CA, STK11, CDKN2A, and ERBB2 were observed in adenocarcinomas, whereas the ratio of TMB-H was significantly higher in squamous cell carcinomas. Among the 1606 ovarian cancer samples, genomic profiling of serous, clear cell, endometrioid, and mucinous carcinomas was characterized. Pathogenic mutations in the POLE exonuclease domain were associated with high TMB, and the mutation ratio was low in both cervical and ovarian cancers. The C-CAT database is useful for determining the mutational landscape of each cancer type and histological subtype. As the dataset is exclusively collected from patients after the standardized treatments, the information on "druggable" alterations highlights the unmet needs for drug development in major gynecological cancers.