ABSTRACT
Nitrogen deposition is one of the most important factors affecting carbon (C) and nitrogen (N) cycling in terrestrial ecosystem. A six-year N addition experiment was carried out to explore how N deposition affected C and N fractions in soil aggregates in the secondary aspen forest (YHL) and primary Korean pine broad-leaved forest (HSL). We investigagted the effects of N addition on dissolved organic carbon and nitrogen (DOC and DON), microbial biomass carbon and nitrogen (MBC and MBN), particulate organic carbon and nitrogen (POC and PON) in soil aggregates with different particle sizes. The results showed that the contents of carbon and nitrogen fractions generally increased with the decrease of particle sizes of soil aggregates except for POC and PON. In soil aggregates of HSL, POC and PON significantly decreased by 20.7% and 22.6% in N treatment, respectively, but DOC increased by 11.6%. In YHL, N addition treatment had no signi-ficant effect on C and N fractions in soil aggregates. Total carbon or nitrogen correlated well with the active C and N fractions in soil aggregates, with a great significant negative correlation between POC and DOC in HSL (r=-0.503) and a significant positive correlation between DOC and MBC (r=0.462). In HSL, the negative effect of N treatment on POC and PON and the positive effect on DOC was mainly attributed to the accelerated decomposition of POM by stimulating microbial activity. Soil C and N pools in HSL were more vulnerable to N deposition than that in YHL.
Subject(s)
Carbon/analysis , Forests , Nitrogen/analysis , Soil/chemistry , China , Environmental Monitoring , Soil MicrobiologyABSTRACT
BACKGROUND & AIMS: No targeted therapies have been found to be effective against hepatocellular carcinoma (HCC), possibly due to the large degree of intratumor heterogeneity. We performed genetic analyses of different regions of HCCs to evaluate levels of intratumor heterogeneity and associate alterations with responses to different pharmacologic agents. METHODS: We obtained samples of HCCs (associated with hepatitis B virus infection) from 10 patients undergoing curative resection, before adjuvant therapy, at hospitals in China. We collected 4-9 spatially distinct samples from each tumor (55 regions total), performed histologic analyses, isolated cancer cells, and carried them low-passage culture. We performed whole-exome sequencing, copy-number analysis, and high-throughput screening of the cultured primary cancer cells. We tested responses of an additional 105 liver cancer cell lines to a fibroblast growth factor receptor (FGFR) 4 inhibitor. RESULTS: We identified a total of 3670 non-silent mutations (3192 missense, 94 splice-site variants, and 222 insertions or deletions) in the tumor samples. We observed considerable intratumor heterogeneity and branched evolution in all 10 tumors; the mean percentage of heterogeneous mutations in each tumor was 39.7% (range, 12.9%-68.5%). We found significant mutation shifts toward C>T and C>G substitutions in branches of phylogenetic trees among samples from each tumor (P < .0001). Of note, 14 of the 26 oncogenic alterations (53.8%) varied among subclones that mapped to different branches. Genetic alterations that can be targeted by existing pharmacologic agents (such as those in FGF19, DDR2, PDGFRA, and TOP1) were identified in intratumor subregions from 4 HCCs and were associated with sensitivity to these agents. However, cells from the remaining subregions, which did not have these alterations, were not sensitive to these drugs. High-throughput screening identified pharmacologic agents to which these cells were sensitive, however. Overexpression of FGF19 correlated with sensitivity of cells to an inhibitor of FGFR 4; this observation was validated in 105 liver cancer cell lines (P = .0024). CONCLUSIONS: By analyzing genetic alterations in different tumor regions of 10 HCCs, we observed extensive intratumor heterogeneity. Our patient-derived cell line-based model, integrating genetic and pharmacologic data from multiregional cancer samples, provides a platform to elucidate how intratumor heterogeneity affects sensitivity to different therapeutic agents.
