Accumulating evidence suggests that tumors are composed of a heterogeneous cell population with a small subset of cancer stem cells (CSCs) that sustain tumor formation and growth. Recently, there have been efforts to explain drug resistance of cancer cells based on the concept of CSCs having an intrinsic detoxifying mechanism. In the present study, to investigate the role of CSCs in acquiring chemoresistance in pancreatic cancer, gemcitabine‐resistant cells were established by exposure to serially escalated doses of gemcitabine in HPAC and CFPAC‐1 cells. Gemcitabine‐resistant cells were more tumorigenic in vitro and in vivo, and had greater sphere‐forming activity than parental cells. After high‐dose gemcitabine treatment to eliminate most of the cells, CD44+ cells proliferated and reconstituted the population of resistant cells. CD44+CD24+ESA+ cells remained as a small subset in the resistant cell population. Among ATP‐binding cassette (ABC) transporters, which are known as the mechanism of drug resistance in CSCs, ABCB1 (MDR1) was significantly augmented during the acquisition of drug resistance. ABC transporter inhibitor verapamil resensitized the resistant cells to gemcitabine in a dose‐dependent manner and RNA interference of CD44 inhibited the clonogenic activity of resistant cells. In human pancreatic cancer samples, CD44 expression was correlated with histologic grade and the patients with CD44‐positive tumors showed poor prognosis. These data indicate that cancer stem‐like cells were expanded during the acquisition of gemcitabine resistance and in therapeutic application, targeted therapy against the CD44 or ABC transporter inhibitors could be applied to overcome drug resistance in the treatment of pancreatic cancer. © 2009 UICC
Metformin use has been associated with decreased cancer risk and mortality. However, the effects of metformin on clinical outcomes of colorectal cancer (CRC) are not defined. This study aimed to evaluate the association between metformin use and mortality of CRC in diabetic patients. We identified 595 patients who were diagnosed both CRC and diabetes mellitus. Patients were compared by two groups; 258 diabetic patients taking metformin and 337 diabetic patients not taking metformin. Patient's demographics, clinical characteristics, overall mortality and CRC-specific mortality were analyzed. After a median follow-up of 41 months, there were 71 total deaths (27.5%) and 55 CRC-specific deaths (21.3%) among 258 patients who used metformin, compared with 136 total deaths (40.4%) and 104 CRC-specific deaths (30.9%) among 337 patients who did not use metformin. Metformin use was associated with decreased overall mortality (p 5 0.018) and CRC-specific mortality (p 5 0.042) by univariate analysis. After adjustment for clinically relevant factors, metformin use showed lower risk of overall mortality (HR, 0.66; 95% CI 0.47620.923; p 5 0.015) and CRC-specific mortality (HR, 0.66; 95% CI 0.4520.975; p 5 0.037) in CRC patients with diabetes. Metformin use in CRC patients with diabetes is associated with lower risk of CRC-specific and overall mortality.Colorectal cancer (CRC) is the third leading cause of cancerrelated death.
Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using 'evolutionary steering' to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, large populations of 10 8-10 9 cells grown without re-plating, longitudinal nondestructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary steering in a lung cancer model, showing that it shifts the clonal composition of the tumour in our favour, leading to collateral sensitivity and proliferative costs. Genomic profiling revealed some of the mechanisms that drive evolved sensitivity. This approach allows modelling evolutionary steering strategies that can potentially control treatment resistance.
Tumor evolution is shaped by many variables, potentially involving external selective pressures induced by therapies1. After surgery, estrogen receptor (ERα) positive breast cancer (BCa) patients are treated with adjuvant endocrine therapy2 including selective estrogen receptor modulators (SERMs) and/or aromatase inhibitors (AIs)3. However, over 20% of patients relapse within 10 years and eventually progress to incurable metastatic disease4. Here we demonstrate that the choice of therapy has a fundamental influence on the genetic landscape of relapsed diseases: in this study, 21.5% of AI-treated, relapsed patients had acquired CYP19A1 gene (aromatase) amplification (CYP19A1amp). Relapsed patients also developed numerous mutations targeting key breast cancer genes including ESR1 and CYP19A1. Strikingly, CYP19A1amp cells also emerge in vitro but only in AI resistant models. CYP19A1 amplification causes increased aromatase activity and estrogen-independent ERα binding to target genes resulting in CYP19A1amp cells displaying decreased sensitivity to AI treatment. Collectively these data suggest that AI treatment itself selects for acquired CYP19A1 amplification and promotes local autocrine estrogen signalling in AI resistant metastatic patients.
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