The main objective of this work is to determine the feasibility of identification of crude and processed Radix Scrophulariae using the Fourier transform infrared spectroscopy couple with soft independent modeling of class analogy (FT-IR-SIMCA).

The aim of the study was to investigate the possibility of improving the therapeutic efficacy of the total alkaloid fraction (TAF) extracted from processed nux vomica by reducing the strychnine contents. Most strychnine was removed from TAF to obtain the modified total alkaloid fraction (MTAF). The toxicity and pharmacokinetics of TAF and MTAF were further investigated and compared besides their antitumor, analgesic and anti-inflammatory activities. The results showed that the ratios of brucine to strychnine were 1:2.05 and 2.2:1 for TAF and MTAF, respectively, and the toxicity of TAF was about 3.17-fold higher than that of MTAF. Compared to brucine alone, the elimination of brucine was found to be inhibited by other alkaloids in TAF or MTAF except strychnine. Significantly increased pharmacological activities when administered by the oral route were obtained with MTAF in comparison to TAF and nux vomica powder (NVP). In summary, MTAF might replace NVP and TAF in the clinical application of Chinese medicine to obtain much higher efficacy.

Vascular endothelial growth factor (VEGF) is pathognomonically elevated in patients with POEMS (polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy and skin changes) syndrome. However, its source of overproduction is unclear. As clinical improvement is almost always associated with VEGF reduction after anti-plasma cell therapy, its increase at diagnosis has been attributed to the underlying monoclonal gammopathy, although direct evidence is still lacking. In the current study, we systemically measured VEGF levels in POEMS patients, before and after treatment. Bone marrow plasma cells showed remarkable VEGF expression, in both mRNA and protein levels, which decreased gradually in response to therapy. Of note, statistically linear correlations were observed between serum and bone marrow plasma cell VEGF levels (mRNA vs. serum, rho 0.343, p=0.003; protein vs. serum, rho 0.644, p<0.0001), supporting bone marrow plasma cells as the main source of circulating VEGF. Intriguingly, immunophenotyping revealed that bone marrow plasma cells were polyclonal in most patients at diagnosis. A clear monoclonal population, coexistent with polytypic cells, was only detectable in 11 cases (18%), in which comparable intracellular VEGF expression was observed between these two plasma cell populations (p=0.594), while monoclonal cells showed higher intracellular interleukin-6 expression (p=0.006). These patients had more serum monoclonal protein, less post-therapeutic complete remission, and inferior overall (p=0.027) and progression-free survival (p=0.002). Collectively, bone marrow plasma cells, mainly polyclonal population, are the major source of VEGF overproduction in POEMS patients.

Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable resource for clinical researches. However, FFPE samples are usually considered an unreliable source for gene expression analysis due to the partial RNA degradation. In this study, through comparing gene expression profiles between FFPE samples and paired fresh-frozen (FF) samples for three cancer types, we firstly showed that expression measurements of thousands of genes had at least two-fold change in FFPE samples compared with paired FF samples. Therefore, for a transcriptional signature based on risk scores summarized from the expression levels of the signature genes, the risk score thresholds trained from FFPE (or FF) samples could not be applied to FF (or FFPE) samples. On the other hand, we found that more than 90% of the relative expression orderings (REOs) of gene pairs in the FF samples were maintained in their paired FFPE samples and largely unaffected by the storage time. The result suggested that the REOs of gene pairs were highly robust against partial RNA degradation in FFPE samples. Finally, as a case study, we developed a REOs-based signature to distinguish liver cirrhosis from hepatocellular carcinoma (HCC) using FFPE samples. The signature was validated in four datasets of FFPE samples and eight datasets of FF samples. In conclusion, the valuable FFPE samples can be fully exploited to identify REOs-based diagnostic and prognostic signatures which could be robustly applicable to both FF samples and FFPE samples with degraded RNA.

TCP10L (T-complex 10 (mouse)-like) has been identified as a liver and testis-specific gene. Although a potential transcriptional suppression function of TCP10L has been reported previously, biological function of this gene still remains largely elusive. In this study, we reported for the first time that TCP10L was significantly down-regulated in clinical hepatocellular carcinoma (HCC) samples when compared to the corresponding non-tumorous liver tissues. Furthermore, TCP10L expression was highly correlated with advanced cases exceeding the Milan criteria. Overexpression of TCP10L in HCC cells suppressed colony formation, inhibited cell cycle progression through G0/G1 phase, and attenuated cell growth in vivo. Consistently, silencing of TCP10L promoted cell cycle progression and cell growth. Therefore, our study has revealed a novel suppressor role of TCP10L in HCC, by inhibiting proliferation of HCC cells, which may facilitate the diagnosis and molecular therapy in HCC.

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

Tumor angiogenesis is one of the hallmarks of cancer as well as an attractive target for cancer therapy. Characterization of novel pathways that act in parallel with the VEGF/VEGFR axis to promote tumor angiogenesis may provide insights into novel anti-angiogenic therapeutic targets. We found that the expression level of Nogo-B is positively correlated with tumor vessel density in hepatocellular carcinoma (HCC). While Nogo-B depletion inhibited tumor angiogenesis, Nogo-B overexpression promoted tumor angiogenesis in a tumor xenograft subcutaneous model of the human HCC cell line. Mechanically, Nogo-B regulates tumor angiogenesis based on its association with integrin αv β3 and activation of focal adhesion kinase. Moreover, Nogo-B antibody successfully abolished the function of Nogo-B in tumor angiogenesis in vitro and in vivo. Collectively, our results strongly suggest that Nogo-B is an important tumor angiogenic factor and blocking Nogo-B selectively inhibits tumor angiogenesis.

The amount of RNA per cell, namely the transcriptome size, may vary under many biological conditions including tumor. If the transcriptome size of two cells is different, direct comparison of the expression measurements on the same amount of total RNA for two samples can only identify genes with changes in the relative mRNA abundances, i.e., cellular mRNA concentration, rather than genes with changes in the absolute mRNA abundances.

It is a basic task in high-throughput gene expression profiling studies to identify differentially expressed genes (DEGs) between two phenotypes. But the weakly differential expression signals between two phenotypes are hardly detectable with limited sample sizes. To solve this problem, many researchers tried to combine multiple independent datasets using meta-analysis or batch effect adjustment algorithms. However, these algorithms may distort true biological differences between two phenotypes and introduce unacceptable high false rates, as demonstrated in this study. These problems pose critical obstacles for analyzing the transcriptional data in The Cancer Genome Atlas where there are many small-scale batches of data. Previously, we developed RankComp to detect DEGs for individual disease samples through exploiting the incongruous relative expression orderings between two phenotypes and further improved it here to identify DEGs using multiple independent datasets. We demonstrated the improved RankComp can directly analyze integrated cross-site data to detect DEGs between two phenotypes without the need of batch effect adjustments. Its usage was illustrated in detecting weak differential expression signals of breast cancer drug-response data using combined datasets from multiple experiments.

Cystathionine β-synthase (CBS) is responsible for the first enzymatic reaction in the transsulfuration pathway of sulfur amino acids. The molecular function and mechanism of CBS as well as that of transsulfuration pathway remain ill-defined in cell proliferation and death. In the present study, we designed, synthesized and obtained a bioactive inhibitor CH004 for human CBS, which functions in vitro and in vivo. CH004 inhibits CBS activity, elevated the cellular homocysteine and suppressed the production of hydrogen sulfide in a dose-dependent manner in cells or in vivo. Chemical or genetic inhibition of CBS demonstrates that endogenous CBS is closely coupled with cell proliferation and cell cycle. Moreover, CH004 substantially retarded in vivo tumor growth in a xenograft mice model of liver cancer. Importantly, inhibition of CBS triggers ferroptosis in hepatocellular carcinoma. Overall, the study provides several clues for studying the interplays amongst transsulfuration pathway, ferroptosis and liver cancer.

Sinisan has been widely used to treat depression. However, its pharmacologically-effective constituents are largely unknown, and the pharmacological effects and clinical efficacies of Sinisan-containing processed medicinal herbs may change. To address these important issues, we developed an ultra-high performance liquid chromatography coupled with electrospray ionization tandem quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) method coupled with multiple statistical strategies to analyze the compound profiles of Sinisan, including individual herb, herb-pair, and complicated Chinese medicinal formula. As a result, 122 different constituents from individual herb, herb-pair, and complicated Chinese medicinal formula were identified totally. Through the comparison of three progressive levels, it suggests that processing herbal medicine and/or altering medicinal formula compatibility could change herbal chemical constituents, resulting in different pharmacological effects. This is also the first report that saikosaponin h/i and saikosaponin g have been identified in Sinisan.

It has been extensively reported that the leading anti-diabetic drug, metformin, exerts significant anticancer effects. This hydrophilic, cationic drug requires cation transporters for cellular entry where it activates its intracellular target, the AMPK signalling pathway. However, clinical results on metformin therapy (used at antidiabetic doses) for breast cancer are ambiguous. It is likely that the antidiabetic dose is inadequate in patients that have breast tumours with low cation transporter expression, resulting in non-responsiveness to the drug. We postulate that cation transporter expression and metformin dose are key determinants in its antitumour efficacy in breast cancer.

Background: Previously reported transcriptional signatures for predicting the prognosis of stage I-III bladder cancer (BLCA) patients after surgical resection are commonly based on risk scores summarized from quantitative measurements of gene expression levels, which are highly sensitive to the measurement variation and sample quality and thus hardly applicable under clinical settings. It is necessary to develop a signature which can robustly predict recurrence risk of BLCA patients after surgical resection. Methods: The signature is developed based on the within-sample relative expression orderings (REOs) of genes, which are qualitative transcriptional characteristics of the samples. Results: A signature consisting of 12 gene pairs (12-GPS) was identified in training data with 158 samples. In the first validation dataset with 114 samples, the low-risk group of 54 patients had a significantly better overall survival than the high-risk group of 60 patients (HR = 3.59, 95% CI: 1.34~9.62, p = 6.61 × 10-03). The signature was also validated in the second validation dataset with 57 samples (HR = 2.75 × 1008, 95% CI: 0~Inf, p = 0.05). Comparison analysis showed that the transcriptional differences between the low- and high-risk groups were highly reproducible and significantly concordant with DNA methylation differences between the two groups. Conclusions: The 12-GPS signature can robustly predict the recurrence risk of stage I-III BLCA patients after surgical resection. It can also aid the identification of reproducible transcriptional and epigenomic features characterizing BLCA metastasis.

The Connectivity Map (CMAP) database, an important public data source for drug repositioning, archives gene expression profiles from cancer cell lines treated with and without bioactive small molecules. However, there are only one or two technical replicates for each cell line under one treatment condition. For such small-scale data, current fold-changes-based methods lack statistical control in identifying differentially expressed genes (DEGs) in treated cells. Especially, one-to-one comparison may result in too many drug-irrelevant DEGs due to random experimental factors. To tackle this problem, CMAP adopts a pattern-matching strategy to build "connection" between disease signatures and gene expression changes associated with drug treatments. However, many drug-irrelevant genes may blur the "connection" if all the genes are used instead of pre-selected DEGs induced by drug treatments.

Loss-of-function approaches provide strong evidence for determining the role of particular genes. The prevalent CRISPR/Cas9 technique is widely used to disrupt target gene with uncontrolled non-homologous end joining after the double strand breaks, which results in mosaicism and multiple genotypes in the founders. In animal models with long generation time such as the salamanders, producing homozygous offspring mutants would be rather labor intensive and time consuming. Here we utilized the base editing technique to create the loss-of-function F0 mutants without the random indels. As a proof of principle, we successfully introduced premature stop codons into the tyrosinase locus and produced the albino phenotype in the newts (Pleurodeles waltl). We further demonstrated that the knockout efficiency could be greatly improved by using multiplex sgRNAs target the same gene. The F0 mutated animals showed fully loss-of-function by both genotyping and phenotyping analysis, which could enable direct functional analysis in the founders and avoid sophisticated breeding. This study not only presented the high efficiency of single base editing in a gigantic animal genome (>20 G), but also provided new tools for interrogating gene function in other salamander species.

The within-sample relative expression orderings (REOs) of genes, which are stable qualitative transcriptional characteristics, can provide abundant information for a disease. Methods based on REO comparisons have been proposed for identifying differentially expressed genes (DEGs) at the individual level and for detecting disease-associated genes based on one-phenotype disease data by reusing data of normal samples from other sources. Here, we evaluated the effects of common potential confounding factors, including age, cigarette smoking, sex, and race, on the REOs of gene pairs within normal lung tissues transcriptome. Our results showed that age has little effect on REOs within lung tissues. We found that about 0.23% of the significantly stable REOs of gene pairs in nonsmokers' lung tissues are reversed in smokers' lung tissues, introduced by 344 DEGs between the two groups of samples (RankCompV2, FDR <0.05), which are enriched in metabolism of xenobiotics by cytochrome P450, glutathione metabolism, and other pathways (hypergeometric test, FDR <0.05). Comparison between the normal lung tissue samples of males and females revealed fewer reversal REOs introduced by 24 DEGs between the sex groups, among which 19 DEGs are located on sex chromosomes and 5 DEGs involving in spermatogenesis and regulation of oocyte are located on autosomes. Between the normal lung tissue samples of white and black people, we identified 22 DEGs (RankCompV2, FDR <0.05) which introduced a few reversal REOs between the two races. In summary, the REO-based study should take into account the confounding factors of cigarette smoking, sex, and race.

A big challenge to clinical diagnosis and therapy of colorectal cancer (CRC) is its extreme heterogeneity, and thus it would be of special importance if we could find common biomarkers besides subtype-specific biomarkers for CRC. Here, with DNA methylation data produced by different laboratories, we firstly revealed that the relative methylation-level orderings (RMOs) of CpG sites within colorectal normal tissues are highly stable but widely disrupted in the CRC tissues. This finding provides the basis for using the RankComp algorithm to identify differentially methylated (DM) CpG sites in every individual CRC sample through comparing the RMOs within the individual sample with the stable RMOs predetermined in normal tissues. For 75 CRC samples, RankComp detected averagely 4,062 DM CpG sites per sample and reached an average precision of 91.34% in terms that the hypermethylation or hypomethylation states of the DM CpG sites detected for each cancer sample were consistent with the observed differences between this cancer sample and its paired adjacent normal sample. Finally, we applied RankComp to identify DM CpG sites for each of the 268 CRC samples from The Cancer Genome Atlas and found 26 and 143 genes whose promoter regions included CpG sites that were hypermethylated and hypomethylated, respectively, in more than 95% of the 268 CRC samples. Individualized pathway analysis identified six pathways that were significantly enriched with DM genes in more than 90% of the CRC tissues. These universal DNA methylation biomarkers could be important diagnostic makers and therapy targets for CRC.

To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data.

It is often difficult to obtain sufficient quantity of RNA molecules for gene expression profiling under many practical situations. Amplification from low-input samples may induce artificial signals.

Understanding the mechanisms of uncontrolled proliferation in cancer cells provides valuable insights into tumor development and is benefit for discovering efficient methods in cancer treatment. In this study, we identified and quantified 2,057 phosphoproteins and 9,824 unique phosphosites in three liver cell lines with high (QGY, Hep3B) and low (L02) proliferative potentials and disclosed the wide variations in phosphorylation sites and levels among them. We found that the number of identified phosphoproteins and phosphosites in these cells were negatively correlated with their proliferative abilities. The function analysis suggested that the aberrant phosphorylation of SR proteins and activation of MAPK pathway might be two critical factors to promote cancer cell proliferation. Meanwhile, the phosphorylation status of mini-chromosome maintenance (MCM) and nuclear pore (NPC) complexes are significantly different between cell lines with high and low proliferative potentials. Furthermore, the phosphosites targeted by kinase families of CDK, STE and HIPK in the proteins coded by cancer driver genes showed distinct profiles between caner and normal cell lines. These results present key phosphorylation networks involving in abnormal proliferation of cancer cells and uncovered potential molecular markers for estimating the proliferation ability of liver cancer cells.