Dataset Information

Genomic landscape of extraordinary responses in metastatic breast cancer.

ABSTRACT: Extreme responders to anticancer therapy are rare among advanced breast cancer patients. Researchers, however, have yet to investigate treatment responses therein on the whole exome level. We performed whole exome analysis to characterize the genomic landscape of extreme responders among metastatic breast cancer patients. Clinical samples were obtained from breast cancer patients who showed exceptional responses to anti-HER2 therapy or hormonal therapy and from those who did not. Matched breast tumor tissue (somatic DNA) and blood samples (germline DNA) were collected from a total of 30 responders and 15 non-responders. Whole exome sequencing using Illumina HiSeq2500 was performed for all 45 patients (90 samples). Somatic single nucleotide variants (SNVs), indels, and copy number variants (CNVs) were identified for the genomes of each patient. Group-specific somatic variants and mutational burden were statistically analyzed. Sequencing of cancer exomes for all patients revealed 1839 somatic SNVs (1661 missense, 120 nonsense, 43 splice-site, 15 start/stop-lost) and 368 insertions/deletions (273 frameshift, 95 in-frame), with a median of 0.7 mutations per megabase (range, 0.08 to 4.2 mutations per megabase). Responders harbored a significantly lower nonsynonymous mutational burden (median, 26 vs. 59, P = 0.02) and fewer CNVs (median 13.6 vs. 97.7, P = 0.05) than non-responders. Multivariate analyses of factors influencing progression-free survival showed that a high mutational burden and visceral metastases were significantly related with disease progression. Extreme responders to treatment for metastatic breast cancer are characterized by fewer nonsynonymous mutations and CNVs.

SUBMITTER: Lim SM

PROVIDER: S-EPMC8035393 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background and aimsMetastatic urothelial carcinoma (mUC) remains an incurable disease with limited treatment options after platinum-based chemotherapy and immune checkpoint blockade (ICB). Vinflunine has shown a modest increase in overall survival and remains a therapeutic option for chemo- and immunotherapy refractory tumours. However, biomarkers that could identify responding patients to vinflunine and possible alternative therapies after failure to treatment are still missing. In this study, we aimed to identify potential genomic biomarkers of vinflunine response in mUC patient samples and potential management alternatives.MethodsFormalin-fixed paraffin-embedded samples of mUC patients (n = 23) from three university hospitals in Spain were used for genomic targeted-sequencing and transcriptome (using the Immune Profile panel by NanoString) analyses. Patients who received vinflunine after platinum-based chemotherapy failure were classified in non-responders (NR: progressive disease ≤ 3 months; n= 11) or responders (R: response ≥ 6 months; n = 12).ResultsGenomic characterization revealed that the most common alteration, TP53 mutations, had comparable frequency in R (6/12; 50%) and NR (4/11; 36%). Non-synonymous mutations in KTM2C (4/12; 33.3%), PIK3CA (3/12; 25%) and ARID2 (3/12; 25%) were predominantly associated with response. No significant difference was observed in tumour mutational burden (TMB) between R and NR patients. The NR tumours showed increased expression of diverse immune-related genes and pathways, including various interferon gamma-related genes. We also identified increased MAGEA4 expression as a potential biomarker of non-responding tumours to vinflunine treatment.ConclusionsOur data may help to identify potential genomic biomarkers of response to vinflunine. Moreover, tumours refractory to vinflunine showed immune signatures potentially associated with response to ICB. Extensive validation studies, including longitudinal series, are needed to corroborate these findings.

Dataset Information

Genomic landscape of extraordinary responses in metastatic breast cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets