Project description:Heterogeneity of gene expression profiles in head and neck cancer Background: Results of gene expression profiling studies from different institutes often lack consistency. This could be due to the use of different microarray platforms and protocols, or to intra-tumoral heterogeneity in mRNA expression. The aim of our study was to quantify intra-tumoral heterogeneity in head and cancer. Methods: Forty-four fresh frozen biopsies were taken from 22 patients, two per tumor. RNA was extracted, tested for quality, amplified, labeled and hybridized to a 35k oligoarray. Results: Unsupervised clustering analyses using all genes, the most variable genes, or random gene sets showed that 80-90% of biopsy pairs clustered together. A within-pair-between-pair scatter ratio analysis showed that the similarity between matching pairs was significantly greater than that between random pairs (p < 0.00001). Conclusions: Two biopsies from the same tumor show far greater similarity in gene expression than biopsies from different tumors, supporting the use of one biopsy for expression profiling.
Project description:IFN gamma signaling in cytotoxic T cells restricts antitumor responses by inhibiting the maintenance and clonality of intra-tumoral stem-like T cells
Project description:Glioblastoma (GBM) is an aggressive form of brain cancer with well-established patterns of intra-tumoral heterogeneity implicated in treatment resistance, recurrence and progression. While regional and single cell transcriptomic variations of GBM have been recently resolved, downstream phenotype-level proteomic programs have yet to be assigned to specific niches. Here, we leverage mass spectrometry to spatially align abundance levels of 4,794 proteins to GBM’s hallmark histomorphologic niches across 20 patients and define distinct molecular programs operational within these regional tumor compartments. Using machine learning, we overlay concordant transcriptional information, and define two distinct proteogenomic programs, MYC- and KRAS-axis hereon, that cooperate with hypoxia to produce a tri-dimensional model of intra-tumoral heterogeneity. Importantly, we show using multiple cohorts, that GBMs with an enhanced KRAS component harbor a more clinically aggressive and infiltrative phenotype. Conversely, tumor cells enriched along the MYC axis where mutually exclusive and had a distinct proliferative program. Moreover, by applying both experimental and computational approaches to link each of these distinct molecular axes with potential pharmacological therapies, we highlight differential drug sensitivities and a notable relative chemoresistance in GBM cell lines with enhanced KRAS programs. Importantly, pharmacological differences were less evident when using traditional expression-based subgroups supporting thattopographic phenotypic mapping ofGBM, and the proposed axes may provide new insights for targeting heterogeneity and overcoming therapy resistance in this aggressive disease.
Project description:Glioblastoma multiforme (GBM) is a highly heterogeneous disease that shows an enourmous range of genetic abnormalities in comparison to other astrocytic tumors. Intra-patient heterogeneity in GBM has been poorly characterized both at phenotypic and genomic level. During surgical GBM resections, we have extracted between 4 and 8 tumor subsamples from different areas of the malignant tissue that were at least 1cm apart. Our aim to asses the intra-tumoral heterogeneity at the gene expression level to uncover important dynamics underlying GBM progression that may have relevant implication for treatment.
Project description:Glioblastoma multiforme (GBM) is a highly heterogeneous disease that shows an wide range of genetic abnormalities in comparison to other astrocytic tumors. We have extracted between 4 and 8 tumor subsamples from different areas of the malignant tissue that were at least 1cm apart. Our aim to asses the intra-tumoral heterogeneity by comparing copy number aberrations in different tumor areas to uncover important dynamics underlying GBM progression.
Project description:Characterization of the intra-tumoral heterogeneity between two iso-clonal human colon cancer sublines HCT116 and HCT116b on their ability to undergo metastatic colonization and survive under growth factor deprivation stress (GFDS). Microarray analysis revealed an upregulation of survival and metastatic genes in the highly metastatic HCT116 primary colon tumor cells compared to the poorly metastatic HCT116b primary colon tumor cells.
Project description:Colorectal cancer (CRC) is one of the major causes of cancer-related death worldwide, for which diagnosis and prognosis are still inadequate mainly due to local recurrence and metastasis, although medical and surgical treatment in cancer therapy advanced. Diagnosis is frequently late, the high capacity of CRC to infiltrate and develop metastasis has the consequence that 40% of patients with CRC have metastasis in liver already at the time of diagnosis. The prognosis of CRC is closely related to the stage, but classification of patients is affected by a great variability in response to therapy and clinical outcome. The localization of the tumor determines a huge inter-tumoral heterogeneity and the intra-tumoral heterogeneity connected to the tumor microenvironment increases the complexity. The heterogeneity typical of CRC is also associated to the several oncogenic signaling pathways, among them the glucose-related pathways, indeed, the glucose metabolic reprogramming of cancer cells appears to be implicated in the malignant progression of CRC. This metabolic alteration seems to be associated to the epithelial-mesenchymal transition (EMT), which is considered the main event promoting the invasion and migration of CRC cells. However, the comprehensive understanding of the molecular mechanisms associated to EMT in CRC is still a challenge and despite decades of research, the process of tumor dissemination is insufficiently understood. Therefore, it is necessary to identify novel biomarkers associated with the prevention, diagnosis and treatment of CRC, as well as potential therapeutic targets. In this context, we performed a large-scale shotgun proteomic investigation on CRC with the aim of discover novel potential protein hallmarks able to distinguish with high specificity and sensitivity tumoral tissue from the health one, and to classify the superficial and the internal deep tumoral tissues. The EMT process is driven by the deep tumoral cells in CRC, therefore, to find significant differences at proteomic levels with respect to the peripheric tumoral tissue and to the healthy mucosa, and to identify specific classifying factors can be useful to individuate potential biomarkers of CRC invasiveness and potential therapy targets. Moreover, the functional enrichment analysis of proteomic data can provide information on biological processes implicated and associated to the variations of the protein profiles, and thus, help to understand the molecular mechanism associated to the CRC progression and malignance. Our approaches coupling high-throughput proteomic strategy with highly accurate statistical and enrichments analysis highlighted not only confirmation on potential biomarkers already proposed in other studies but also novel biomarkers able to distinguish with high sensitivity and specificity the deep tumor from the superficial one and to the healthy mucosa. Our investigation suggested a strong contribution of proteins implicated in metabolic pathways as catalytic and regulatory activities, some of them with high classifying power and potentially useful as biomarker and therapeutic target.
Project description:T cell responses within pediatric brain tumors (PBT) remain poorly understood. We performed single-cell RNA-seq (scRNA-seq) and paired T cell receptor sequencing (TCR-Seq) of patient-derived brain tumor-infiltrating T cells to map T cell molecular profile with TCR repertoire and clonality. We demonstrate marked clonal expansion of intra-tumoral T cells and reveal their differential phenotype, transcriptional state and functional properties within brain tumors. To understand T cell responses within highly immunogenic tumors that respond to checkpoint blockers, we undertook analysis of human non-small cell lung cancer (NSCLC). We performed single-cell RNA-seq (scRNA-seq) and paired T cell receptor sequencing (TCR-Seq) of patient-derived lung tumor-infiltrating T cells to map T cell molecular profile with clonality.