Project description:The aim of this study was to compare the mutational landscape of breast cancer diagnosed during pregnancy (BCP) and breast cancer from age/stage non-pregnant patients (controls). We present whole genome sequencing data (Illumina HiSeq X ten platform) of tumor and matched normal tissues from 35 BCP patients and 20 controls. This work provides important novel biological insights and a unique resource to study the biology of breast cancer in young women and how pregnancy could modulate tumor biology.
Project description:Using a dataset of 54 pregnant and 113 age/stage-matched non-pregnant breast cancer patients with complete clinical and survival data; we evaluated the pattern of hot spot somatic mutations and performed transcriptomic profiling using Sequenom® and Affymetrix®, respectively. Breast cancer molecular subtypes were defined using PAM50 and 3-Gene classifiers. We performed Gene set enrichment analysis (GSEA) to evaluate pathways associated with diagnosis during pregnancy. We investigated the differential expression of cancer-related genes and published gene sets according to pregnancy. We finally investigated genes associated with disease-free survival. We identified 65 patients who were diagnosed with breast cancer during pregnancy. Moreover, for each case, two breast cancer patients who were not diagnosed during pregnancy or lactation, but who were matched according to age (±2 years), tumors size, nodal status, year of surgery (±2 years) and whether neoadjuvant chemotherapy was received were selected. Messenger RNA from tumor tissue has been extracted and hybridized on Affymetrix microarrays. However, due to experimental issues, 54 pregnant and 113 non-pregnant patients were remaining and used in our study.
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Project description:The aim of this study was to compare the mutational landscape of breast cancer diagnosed during pregnancy (BCP) and breast cancer from age/stage non-pregnant patients (controls). We present whole genome sequencing data (Illumina HiSeq X ten platform) of tumor and matched normal tissues from 35 BCP patients and 20 controls. This work provides important novel biological insights and a unique resource to study the biology of breast cancer in young women and how pregnancy could modulate tumor biology.
Project description:To identify novel molecular targets for triple negative breast cancer (TNBC), we have employed whole genome microarray expression profiling. We purified 30 surgically resected breast cancer tissue diagnosed triple negative by means of immunohistochemical staining and 13 normal mammary ductal cells with lasermicrobeam microdissection system (PALM MicroBeam, Carl Zeiss MicroImaging Co., Ltd), performed whole human genome microarray, and compared gene expression levels of TNBC, normal mammary ductal cells, and normal vital organs to develop molecular targets with a minimum risk.
Project description:Whole Genome Sequencing of the murine breast cancer cell line 4T1 and of the murine melanoma cell line B16-ova was carried out with the aim of identifying somatic mutations. We also ran deep Mass Spectrometry proteomics analysis on the same cell lines, aiming to determine which somatic mutations carry over to the protein expression level. Further, we tested these cancer specific protein epitopes (putative neoantigens) for immunogenicity using mouse models. Finally, the putative neoantigens that showed good immunogenic potential were used in tumor growth control experiments with mice engrafted with the two tumor cell lines. In these experiments we tested whether cancer vaccines based on individual neoantigen peptides (MHC-I) restricted the growth of the tumor compared to adequate controls. The overall aim of the project is to validate the ability of our multi-omics/bioinformatics pipeline to identify and deliver neoantigens that can be used to suppress tumor growth. File names Sample names P10859_101_S1_L001_R1_001_BHKWV3CCXY 4T1_S1_L001_R1_001_BHKWV3CCXY P10859_101_S1_L001_R2_001_BHKWV3CCXY 4T1_S1_L001_R2_001_BHKWV3CCXY P10859_101_S1_L002_R1_001_BHKWV3CCXY 4T1_S1_L002_R1_001_BHKWV3CCXY P10859_101_S1_L002_R2_001_BHKWV3CCXY 4T1_S1_L002_R2_001_BHKWV3CCXY P10859_102_S2_L003_R1_001_BHKWV3CCXY B16-OVA_S2_L003_R1_001_BHKWV3CCXY P10859_102_S2_L003_R2_001_BHKWV3CCXY B16-OVA_S2_L003_R2_001_BHKWV3CCXY P10859_102_S2_L004_R1_001_BHKWV3CCXY B16-OVA_S2_L004_R1_001_BHKWV3CCXY P10859_102_S2_L004_R2_001_BHKWV3CCXY B16-OVA_S2_L004_R2_001_BHKWV3CCXY
Project description:Molecular profiling of breast cancer has achieved great depth in defining the mutational landscapes and molecular profiles of primary tumors, though little is still known regarding cancer evolution into a recurrence. Proteogenomic workflows are particularly useful in defining the multi-layered biology of complex diseases by combining genomic, transcriptomic, and proteomic technologies so to inform not only on mutational processes, but also on their repercussion at the effector level, proteins. We employed our recently developed proteogenomic workflow to analyze a cohort of 27 primary breast cancers and their matched loco-regional recurrences by whole genome sequencing, RNA sequencing, and mass spectrometry.