Acute coronary syndrome （ACS） refers to a spectrum of clinical presentations ranging from unstable angina to non-ST-segment elevation myocardial infarction （NSTEMI） to ST-segment elevation myocardial infarction （...Acute coronary syndrome （ACS） refers to a spectrum of clinical presentations ranging from unstable angina to non-ST-segment elevation myocardial infarction （NSTEMI） to ST-segment elevation myocardial infarction （STEMI）. Aortic dissection, intramural hematoma and penetrating atherosclerotic ulcer （PAU） are three major acute aortic syndromes （AAS）.展开更多
A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network pers...A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.展开更多
Colorectal cancer(CRC)is a heterogeneous disease,arising from many possible etiological pathways.This heterogeneity can have important implications for CRC prognosis and clinical management.Epidemiological studies of ...Colorectal cancer(CRC)is a heterogeneous disease,arising from many possible etiological pathways.This heterogeneity can have important implications for CRC prognosis and clinical management.Epidemiological studies of CRC risk and prognosis—as well as clinical trials for the treatment of CRC—must therefore be sensitive to the molecular phenotype of colorectal tumors in patients under study.In this review,we describe four tumor markers that have been widely studied as reflections of CRC heterogeneity:(i)microsatellite instability(MSI)or DNA mismatch repair(MMR)deficiency,(ii)the CpG island methylator phenotype(CIMP),and somatic mutations in(iii)BRAF and(iv)KRAS.These tumor markers have been used to better characterize CRC epidemiology and,increasingly,may be used to guide clinical decision-making.Going beyond these traditional tumor markers,we also briefly review some more novel markers likely to be of clinical significance.Lastly,recognizing that none of these individual tumor markers are isolated attributes but,rather,a reflection of broader tumor phenotypes,we review some of the hypothesized etiological pathways of CRC development and their associated clinical differences.展开更多
文摘Acute coronary syndrome （ACS） refers to a spectrum of clinical presentations ranging from unstable angina to non-ST-segment elevation myocardial infarction （NSTEMI） to ST-segment elevation myocardial infarction （STEMI）. Aortic dissection, intramural hematoma and penetrating atherosclerotic ulcer （PAU） are three major acute aortic syndromes （AAS）.
基金supported by the National Basic Research Program of China(2010CB529200)National Natural Science Foundation of China(91029738)
文摘A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.
文摘Colorectal cancer(CRC)is a heterogeneous disease,arising from many possible etiological pathways.This heterogeneity can have important implications for CRC prognosis and clinical management.Epidemiological studies of CRC risk and prognosis—as well as clinical trials for the treatment of CRC—must therefore be sensitive to the molecular phenotype of colorectal tumors in patients under study.In this review,we describe four tumor markers that have been widely studied as reflections of CRC heterogeneity:(i)microsatellite instability(MSI)or DNA mismatch repair(MMR)deficiency,(ii)the CpG island methylator phenotype(CIMP),and somatic mutations in(iii)BRAF and(iv)KRAS.These tumor markers have been used to better characterize CRC epidemiology and,increasingly,may be used to guide clinical decision-making.Going beyond these traditional tumor markers,we also briefly review some more novel markers likely to be of clinical significance.Lastly,recognizing that none of these individual tumor markers are isolated attributes but,rather,a reflection of broader tumor phenotypes,we review some of the hypothesized etiological pathways of CRC development and their associated clinical differences.
