Background: There is accumulating evidence from preclinical studies that circulating endothelial cells (CECs) play an important role in neovascularization and tumor growth. The role of CECs in human cancer progression is sparsely investigated. We therefore analyzed CECs in peripheral blood of cancer patients. In addition, we correlated CEC levels in these patients with plasma levels of cytokines that are known to mobilize CECs in experimental models. Patients and methods: Viable CECs were isolated, quantified and cultured from cancer patients’ whole blood by using magnetic beads coupled to an antibody directed against CD146, a pan-endothelial marker. Viable cells were visualized by calceinAM staining. Positive staining for specific endothelial cell markers [i.e. von Willebrand factor, CD31, vascular endothelial cell growth factor (VEGF) receptor-2] was used to confirm the endothelial phenotype. Results: Cancer patients with progressive disease (95 patients) had on average 3.6-fold more CECs than healthy subjects (46 patients, P <0.001). Patients (17) with stable disease had CEC numbers equal to that circulating in healthy subjects (P = 0.69). A subset of in vitro cultured CECs incorporated into endothelial layers and formed colonies. Plasma levels of cytokines that are thought to mobilize CECs from the bone marrow [VEGF, placental growth factor, stromal cell derived factor 1α and stem cell factor (71 patients)] did not correlate with CEC amounts. The levels of viable CECs in cancer patients were modified by granulocyte colony-stimulating factor treatment and chemotherapy. Conclusion: In progressive cancer patients, the amount of CECs is increased. These CECs are viable and may contribute to vessel formation. The number of CECs is influenced by anticancer treatment.
Background: Structural rearrangements form a major class of somatic variation in cancer genomes. Local chromosome shattering, termed chromothripsis, is a mechanism proposed to be the cause of clustered chromosomal rearrangements and was recently described to occur in a small percentage of tumors. The significance of these clusters for tumor development or metastatic spread is largely unclear. Results: We used genome-wide long mate-pair sequencing and SNP array profiling to reveal that chromothripsis is a widespread phenomenon in primary colorectal cancer and metastases. We find large and small chromothripsis events in nearly every colorectal tumor sample and show that several breakpoints of chromothripsis clusters and isolated rearrangements affect cancer genes, including NOTCH2, EXO1 and MLL3. We complemented the structural variation studies by sequencing the coding regions of a cancer exome in all colorectal tumor samples and found somatic mutations in 24 genes, including APC, KRAS, SMAD4 and PIK3CA. A pairwise comparison of somatic variations in primary and metastatic samples indicated that many chromothripsis clusters, isolated rearrangements and point mutations are exclusively present in either the primary tumor or the metastasis and may affect cancer genes in a lesion-specific manner. Conclusions: We conclude that chromothripsis is a prevalent mechanism driving structural rearrangements in colorectal cancer and show that a complex interplay between point mutations, simple copy number changes and chromothripsis events drive colorectal tumor development and metastasis.
Metastatic breast cancer is the major cause of cancer-related death among women in the Western world. Invasive carcinoma cells are able to counteract apoptotic signals in the absence of anchorage, enabling cell survival during invasion and dissemination. Although loss of E-cadherin is a cardinal event in the development and progression of invasive lobular carcinoma (ILC), little is known about the underlying mechanisms that govern these processes. Using a mouse model of human ILC, we show here that cytosolic p120-catenin (p120) regulates tumor growth upon loss of E-cadherin through the induction of anoikis resistance. p120 conferred anchorage independence by indirect activation of Rho/Rock signaling through interaction and inhibition of myosin phosphatase Rho–interacting protein (Mrip), an antagonist of Rho/Rock function. Consistent with these data, primary human ILC samples expressed hallmarks of active Rock signaling, and Rock controlled the anoikis resistance of human ILC cells. Thus, we have linked loss of E-cadherin — an initiating event in ILC development — to Rho/Rock-mediated control of anchorage-independent survival. Because activation of Rho and Rock are strongly linked to cancer progression and are susceptible to pharmacological inhibition, these insights may have clinical implications for the development of tailor-made intervention strategies to better treat invasive and metastatic lobular breast cancer.
Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression ofEVI1irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications inFLT3andKMT2Awere detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.