Chronological occurrence of PI3KCA mutations in breast cancer liver metastases after repeat partial liver resection

Characterizations of Cancer Gene Mutations in Chinese Metastatic Breast Cancer Patients

Background: Breast cancer (BC) is a type of disease with high heterogeneity. Molecular profiling, by revealing the intrinsic nature of its various subtypes, has extensively improved the therapeutic management of BC patients. However, the genomic mutation landscape of Chinese metastatic BC has not been fully explored. Methods: Matched plasma and mononuclear cells from 290 Chinese women with metastatic BC were sequenced using either of the two commercially-available panels consisting of 520 cancer-related and 108 BC-related genes. Both panels cover the same critical regions of 91 genes. The circulating tumor DNA mutation profile from our cohort was then compared with publicly-available metastatic BC datasets from Memorial Sloan Kettering Cancer Center (MSKCC) and Pan-cancer analysis of whole genomes (PCAWG). Results: A total of 1,201 mutations spanning 91 genes were detected from 234 patients, resulting in a mutation detection rate of 80.7%. TP53 (64.1%) was the gene with highest mutation frequency, followed by PIK3CA (31%), PTEN (11%), and RB1 (10%). Copy number amplifications (CNAs) in MYC (14.1%), FGFR1 (13.3%), CCND1 (6.6%), FGF3 (6.6%), FGF4 (6.2%) and FGF19 (6.2%) were also detected from our cohort. TP53 mutations were significantly more frequent among triple negative BC (TNBC), HR-/HER2+, and HR+/HER2+ BC, while less common in HR+/HER2- (P < 0.01). Meanwhile, PIK3CA mutations were significantly more frequent among HR+/HER2+, HR+/HER2-, and HR-/HER2+ BC, while less common in TNBC (P < 0.01). Pathogenic or likely pathogenic BRCA1/2 germline mutations were detected in 5.9% of the cohort and 4.4% in TNBC subgroup. Maximum allelic fraction (maxAF) of TP53, RB1, and PIK3CA mutations were associated with multiple organ metastasis. Patients with PIK3CA, PTEN, and RB1 mutation were more likely to have liver metastasis (P < 0.02). Compared with MSKCC and PCAWG dataset, Chinese patients had observably difference in genetic variation rates in different molecular subtypes (TNBC: TP53 73.0 vs. 91.5%, P < 0.001; PIK3CA 21.2 vs. 13.2%, P = 0.061; HR+/HER2-: FGFR1 3.3 vs. 0.7%, P = 0.035; TP 53 46.2 vs. 27.7%, P < 0.001; RB1 6.6 vs. 2.7%, P = 0.046; CDKN2A 7.7 vs. 1.0%, P < 0.001; PIK3CA 30.8 vs. 44.2%, P = 0.012; CDH1 1.1 vs. 18.2%, P < 0.001; GATA3 7.7 vs. 17.2%, P = 0.02). Conclusions: A distinct gene mutation profile was elucidated in Chinese women with metastatic BC, justifying further research. Liquid biopsy provides a quick, real-time, and minimally invasive tool for future clinical trial and routine practice.

New insights into the genomic landscape of meningiomas identified FGFR3 in a subset of patients with favorable prognoses

Background: With a prevalence of 170 000 adults in the US alone, meningiomas are the most common primary intracranial tumors. The management of skull base meningiomas is challenging due to their complexity and proximity to crucial nearby structures. The identification of oncogenic mutations has provided further insights into the tumorigenesis of meningioma and the possibility of targeted therapy.

This study aimed to further investigate the association of mutational profiles with anatomical distribution, histological subtype, WHO grade, and recurrence in patients with meningioma.

Methods: Tissue samples were collected from 71 patients diagnosed with meningioma from 2008 to 2016. A total of 51 cases were skull based. Samples were subjected to targeted sequencing using a next generation customized cancer gene panel (n = 66 genes analyzed).

Results: We detected genomic alterations (GAs) in 68 tumors, averaging 1.56 ± 1.07 genomic alterations (GAs) per sample. NF2 was the most frequently altered gene (36/71 cases). Interestingly, we identified a number of mutations in non-NF2 genes, including a hotspot TERTp c.−124: G > A mutation that may be related to poor prognosis and FGFR3 mutations that may represent biomarkers of a favorable prognosis as reported in other cancers.

Conclusions: We demonstrate that comprehensive genomic profiling in our population can reveal a potential new prognostic biomarkers of skull base meningioma. These mutations can enhance diagnostic accuracy and clinical decision-making. Among our findings were the identification of a TERTp mutation and the first report of FGFR3 mutations that may represent biomarkers for the identification of skull base meningioma patients with a favorable prognosis.