Bulk and single-cell transcriptome reveal the immuno-prognostic subtypes and tumour microenvironment heterogeneity in HCC.

BACKGROUND & AIMS: Accumulating evidences suggest tumour microenvironment (TME) profoundly influence clinical outcome in hepatocellular carcinoma (HCC). Existing immune subtypes are susceptible to batch effects, and integrative analysis of bulk and single-cell transcriptome is helpful to recognize immune subtypes and TME in HCC. METHODS: Based on the relative expression ordering (REO) of 1259 immune-related genes, an immuno-prognostic signature was developed and validated in 907 HCC samples from five bulk transcriptomic cohorts, including 72 in-house samples. The machine learning models based on subtype-specific gene pairs with stable REOs were constructed to jointly predict immuno-prognostic subtypes in single-cell RNA-seq data and validated in another single-cell data. Then, cancer characteristics, immune landscape, underlying mechanism and therapeutic benefits between subtypes were analysed. RESULTS: An immune-related signature with 29 gene pairs stratified HCC samples individually into two risk subgroups (C1 and C2), which was an independent prognostic factor for overall survival. The machine learning models verified the immune subtypes from five bulk cohorts to two single-cell transcriptomic data. Integrative analysis revealed that C1 had poorer outcomes, higher CNV burden and malignant scores, higher sensitivity to sorafenib, and exhibited an immunosuppressive phenotype with more regulators, e.g., myeloid-derived suppressor cells (MDSCs), Mø_SPP1, while C2 was characterized with better outcomes, higher metabolism, more benefit from immunotherapy, and displayed active immune with more effectors, e.g., tumour infiltrating lymphocyte and dendritic cell. Moreover, both two single-cell data revealed the crosstalk of SPP1-related L-R pairs between cancer and immune cells, especially SPP1-CD44, might lead to immunosuppression in C1. CONCLUSIONS: The REO-based immuno-prognostic subtypes were conducive to individualized prognosis prediction and treatment options for HCC. This study paved the way for understanding TME heterogeneity between immuno-prognostic subtypes of HCC.

Satisfaction with clinical pathway implementation versus job performance of clinicians: empirical evidence on the mediating role of work engagement from public hospitals in Sichuan, China.

BACKGROUND: The job performance of clinicians is a clear indicator of both hospital capacity and the level of hospital service. It plays a crucial role in maintaining the effectiveness and quality of medical care. Clinical pathways are a systematic method of quality improvement successfully recommended by broader healthcare systems. Since clinicians play a key role in implementing clinical pathways in public hospitals, this study aims to investigate the effect of the satisfaction of clinicians in public hospitals with clinical pathway implementation on their job performance. METHODS: A cross-sectional study design was used. Questionnaires were administered online. A total of 794 clinicians completed the questionnaires in seven tertiary public hospitals in Sichuan Province, China, of which 723 were valid for analysis. Questionnaires contained questions on social demographic characteristics, satisfaction with clinical pathway implementation, work engagement, and job performance. Structural Equation Model (SEM) was used to test the hypotheses. RESULTS: The satisfaction of clinicians in public hospitals with clinical pathway implementation was significantly positively correlated with work engagement (r = 0.570, P < 0.01) and job performance (r = 0.522, P < 0.01). A strong indirect effect of clinicians' satisfaction with clinical pathway implementation on job performance mediated by work engagement was observed, and the value of this effect was 0.383 (boot 95%CI [0.323, 0.448]). CONCLUSION: The satisfaction of clinicians in public hospitals with clinical pathway implementation not only directly influences their job performance, but also indirectly affects it through the mediating variable of work engagement. Therefore, managers of public hospitals need to pay close attention to clinicians' evaluation and perception of the clinical pathway implementation. This entails taking adequate measures, such as providing strong organizational support and creating a favorable environment for the clinical pathway implementation. Additionally, focusing on teamwork to increase clinicians' satisfaction can further enhance job performance. Furthermore, managers should give higher priority to increasing employees' work engagement to improve clinicians' job performance.

Relationship between Perceived Family Resilience, Emotional Flexibility, and Anxiety Symptoms: a Parent-Adolescent Dyadic Perspective.

Family resilience is crucial for individual's psychological health. Previous studies explored the protective factors of anxiety at the individual level, with less attention paid to the impact of family interaction from a dyadic perspective. This study utilized the Actor-Partner Interdependence Mediation Model to investigate the relationship between family resilience, emotional flexibility, and anxiety symptoms. A sample of 2144 Chinese parent-adolescent dyads (36% upper grades of primary school, 64% secondary school, 49.39% girls; 70.38% mothers) was recruited. Perceived family resilience was inversely related to anxiety symptoms, directly or indirectly, through the mediation of emotional flexibility at the individual level. At the dyadic level, adolescents' perceived family resilience was significantly associated with parents' anxiety symptoms through their own or parents' emotional flexibility. Parents' perceived family resilience was inversely link to adolescents' anxiety symptoms through parents' emotional flexibility. Parents emotional flexibility also mediated the association between adolescents' perceived family resilience and their anxiety symptoms. These findings contribute to understanding the intricate dynamics of family resilience and psychological outcomes in parent-child relationships under adversity, emphasizing the need for child-centered interventions to improve family members' mental health.

Expression pattern analysis of anti-Mullerian hormone in testis development of pearlscale angelfish (Centropyge vrolikii).

In vertebrates, anti-Mullerian hormone (Amh) secreted by Sertoli cells (SC) performs a pivotal function in male sex differentiation. Compared with that of higher vertebrates, the expression pattern of Amh is more diversified in fish. In this study, the full-length complementary DNA (cDNA) of Amh in Centropyge vrolikii (Cv-Amh) was cloned and analysed, which was 2,470 bp, including a 238 bp 5'UTR, a 1,602 bp ORF and a 633 bp 3'UTR; the similarity of Amh between Cv-Amh and other fish is relatively high. The quantitative real-time PCR (qRT-PCR) results of healthy tissues and gonads at sex reversal stages in C. vrolikii showed that the expression level of Amh in the testis was significantly higher than that in other tissues (P < 0.05). Amh was weakly expressed in the vitellogenic stage ovary and perinucleolus stage ovary, but its expression significantly increased in the gonads at the hermaphroditic stage, and finally reached the highest in the pure testis after sexual reversal. The results of in situ hybridization indicated that the positive signal of Amh was strongly concentrated in SCs of testis. After Amh knockdown in the gonads, the effect on sex-related genes was tested using qRT-PCR. Among these, the expression of Dmrt1, Cyp11a, Hsd11b2, Sox8 and Sox9 significantly decreased, whereas that of Cyp19a, Sox4, Foxl2 and Sox3 increased. These results suggested that Amh could be the pivotal gene in reproductive regulation in C. vrolikii, and the data will contribute to sex-related research of C. vrolikii in the future.

[Effect of a novel phosphodiesterase 5 inhibitor, CPD1, on renal interstitial fibrosis after unilateral renal ischemia-reperfusion injury].

This study was designed to evaluate the protective effect of CPD1, a novel phosphodiesterase 5 inhibitor, on renal interstitial fibrosis after unilateral renal ischemia-reperfusion injury (UIRI). Male BALB/c mice were subjected to UIRI, and treated with CPD1 once daily (i.g, 5 mg/kg). Contralateral nephrectomy was performed on day 10 after UIRI, and the UIRI kidneys were harvested on day 11. Hematoxylin-eosin (HE), Masson trichrome and Sirius Red staining methods were used to observe the renal tissue structural lesions and fibrosis. Immunohistochemical staining and Western blot were used to detect the expression of proteins related to fibrosis. HE, Sirius Red and Masson trichrome staining showed that CPD1-treated UIRI mice had lower extent of tubular epithelial cell injury and deposition of extracellular matrix (ECM) in renal interstitium compared with those in the fibrotic mouse kidneys. The results from immunohistochemistry and Western blot assay indicated significantly decreased protein expressions of type I collagen, fibronectin, plasminogen activator inhibitor-1 (PAI-1) and α-smooth muscle actin (α-SMA) after CPD1 treatment. In addition, CPD1 dose-dependently inhibited the expression of ECM-related proteins induced by transforming growth factor ß1 (TGF-ß1) in normal rat kidney interstitial fibroblasts (NRK-49F) and human renal tubular epithelial cell line (HK-2). In summary, the novel PDE inhibitor, CPD1, displays strong protective effects against UIRI and fibrosis by suppressing TGF-ß signaling pathway and regulating the balance between ECM synthesis and degradation through PAI-1.

Characterization of the transcription factor Sox3 regulating the gonadal development of pearlscale angelfish (Centropyge vrolikii).

As a member of the Sox gene family, Sox3 plays a vital role in gonadal development and gametogenesis. Nevertheless, the exact expression pattern of this gene in fish is still unknown. Here, we identified the Sox3 gene of Centropyge vrolikii, namely, Cv-Sox3. The Cv-Sox3 mRNA expression in the ovary and testis was detected by reverse transcription-polymerase chain reaction (RT-PCR) analysis, and the mRNA expression level of Cv-Sox3 in the ovary in the resting stage was significantly higher than that in other tissues. The phylogenetic tree and alignment of multiple sequences were constructed to analyze the evolutionary relationships of Cv-Sox3. Cv-Sox3 was relatively conserved in the evolution of teleost fish, indicating the importance and similarity of its function. The in situ hybridization results demonstrate that Cv-Sox3 was present in the follicle cells and cytoplasm of oocytes in the ovary of different stages, and the positive signals occurred in germ cells of the testis. After interfering with Cv-Sox3, the growth rate of ovarian cells in culture became slow, and the expression of ovary-bias-related genes Cyp19a and Foxl2 significantly increased. Meanwhile, the expression of testis-bias-related genes Dmrt1, Sox9, Cyp11a, Amh, and Sox8 significantly decreased. These results suggest that Cv-Sox3 gene might be expressed in the germ cells of male and female gonads during gonadal development. This study provides a precise expression pattern of Cv-Sox3 and demonstrates that Cv-Sox3 might play a significant role in the reproductive regulation of C. vrolikii. In this study, Sox3 of C. vrolikii (Cv-Sox3) was cloned to understand the expression pattern in the gonadal development, which is expressed in germ cells, involved in the process of gonadal development. The results demonstrated that Cv-Sox3 may play a significant role in the reproductive regulation of C. vrolikii.

Two novel qualitative transcriptional signatures robustly applicable to non-research-oriented colorectal cancer samples with low-quality RNA.

Currently, due to the low quality of RNA caused by degradation or low abundance, the accuracy of gene expression measurements by transcriptome sequencing (RNA-seq) is very challenging for non-research-oriented clinical samples, majority of which are preserved in hospitals or tissue banks worldwide with complete pathological information and follow-up data. Molecular signatures consisting of several genes are rarely applied to such samples. To utilize these resources effectively, 45 stage II non-research-oriented samples which were formalin-fixed paraffin-embedded (FFPE) colorectal carcinoma samples (CRC) using RNA-seq have been analysed. Our results showed that although gene expression measurements were significantly affected, most cancer features, based on the relative expression orderings (REOs) of gene pairs, were well preserved. We then developed two REO-based signatures, which consisted of 136 gene pairs for early diagnosis of CRC, and 4500 gene pairs for predicting post-surgery relapse risk of stage II and III CRC. The performance of our signatures, which included hundreds or thousands of gene pairs, was more robust for non-research-oriented clinical samples, compared to that of two published concise REO-based signatures. In conclusion, REO-based signatures with relatively more gene pairs could be robustly applied to non-research-oriented CRC samples.

A rank-based algorithm of differential expression analysis for small cell line data with statistical control.

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.

A qualitative transcriptional signature of recurrence risk for stages II-III gastric cancer patients after surgical resection.

BACKGROUND AND AIM: Metastasis is the leading cause of recurrence in gastric cancer. However, the imaging techniques and pathological examinations for tumor metastasis have a high false-positive rate or a high false-negative rate, and many proposed that metastasis-related molecular biomarkers can hardly be validated in independent datasets. METHODS: We propose to use significantly stable gene pairs with reversal relative expression orderings (REOs) between non-metastasis and metastasis gastric cancer samples as the metastasis-related gene pairs. Based on the REOs of these gene pairs, we developed a qualitative transcriptional signature for predicting the recurrence risk of stages II-III gastric cancer patients after surgical resection. RESULTS: A REOs-based signature, consisting of 19 gene pairs (19-GPS), was selected from 77 stages II-III gastric cancer patients and validated in two independent datasets. Samples in the high-risk group had shorter disease-free survival time and overall survival time than those in the low-risk group. Differentially expressed genes (DEGs) between the high- and low-risk groups classified by 19-GPS were highly reproducible comparing with those between lymph node metastasis and lymph node non-metastasis groups. Functional enrichment analysis showed that these DEGs were significantly enriched in metastasis-related pathways, such as PI3K-Akt and Rap1 signaling pathways. The multi-omics analyses suggested that the epigenetic and genomic features might cause transcriptional differences between two subgroups, which help to characterize the mechanism of gastric cancer metastasis. CONCLUSIONS: The signature could robustly identify patients at high recurrence risk after resection surgery, and the multi-omics analyses might aid in revealing the metastasis-related characteristics of gastric cancer.

A qualitative transcriptional signature for predicting the biochemical recurrence risk of prostate cancer patients after radical prostatectomy.

BACKGROUND: The qualitative transcriptional characteristics, the within-sample relative expression orderings (REOs) of genes, are highly robust against batch effects and sample quality variations. Hence, we develop a qualitative transcriptional signature based on REOs to predict the biochemical recurrence risk of prostate cancer (PCa) patients after radical prostatectomy. METHODS: Gene pairs with REOs significantly correlated with the biochemical recurrence-free survival (BFS) were identified from 131 PCa samples in the training data set. From these gene pairs, we selected a qualitative transcriptional signature based on the within-sample REOs of gene pairs which could predict the recurrence risk of PCa patients after radical prostatectomy. RESULTS: A signature consisting of 74 gene pairs, named 74-GPS, was developed for predicting the recurrence risk of PCa patients after radical prostatectomy based on the majority voting rule that a sample was assigned as high risk when at least 37 gene pairs of the 74-GPS voted for high risk; otherwise, low risk. The signature was validated in six independent datasets produced by different platforms. In each of the validation datasets, the Kaplan-Meier survival analysis showed that the average BFS of the low-risk group was significantly better than that of the high-risk group. Analyses of multiomics data of PCa samples from TCGA suggested that both the epigenomic and genomic alternations could cause the reproducible transcriptional differences between the two different prognostic groups. CONCLUSIONS: The proposed qualitative transcriptional signature can robustly stratify PCa patients after radical prostatectomy into two groups with different recurrence risk and distinct multiomics characteristics. Hence, 74-GPS may serve as a helpful tool for guiding the management of PCa patients with radical prostatectomy at the individual level.

Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung adenocarcinoma.

BACKGROUND: Immune checkpoint inhibitors are effective in some cases of lung adenocarcinoma (LUAD). Whole-exome sequencing has revealed that the tumour mutation burden (TMB) is associated with clinical benefits among patients from immune checkpoint inhibitors. Several commercial mutation panels have been developed for estimating the TMB regardless of the cancer type. However, different cancer types have different mutational landscapes; hence, this study aimed to develop a small cancer-type-specific mutation panel for high-accuracy estimation of the TMB of LUAD patients. METHODS: We developed a small cancer-type-specific mutation panel based on coding sequences (CDSs) rather than genes, for LUAD patients. Using somatic CDSs mutation data from 486 LUAD patients in The Cancer Genome Atlas (TCGA) database, we pre-selected a set of CDSs with mutation states significantly correlated with the TMB, from which we selected a CDS mutation panel with a panel-score most significantly correlated with the TMB, using a genetic algorithm. RESULTS: A mutation panel containing 106 CDSs of 100 genes with only 0.34 Mb was developed, whose length was much shorter than current commercial mutation panels of 0.80-0.92 Mb. The correlation of this panel with the TMB was validated in two independent LUAD datasets with progression-free survival data for patients treated with nivolumab plus ipilimumab and pembrolizumab immunotherapies, respectively. In both test datasets, survival analyses revealed that patients with a high TMB predicted via the 106-CDS mutation panel with a cut-point of 6.20 mutations per megabase, median panel score in the training dataset, had a significantly longer progression-free survival than those with a low predicted TMB (log-rank p = 0.0018, HR = 3.35, 95% CI 1.51-7.42; log-rank p = 0.0020, HR = 5.06, 95% CI 1.63-15.69). This small panel better predicted the efficacy of immunotherapy than current commercial mutation panels. CONCLUSIONS: The small-CDS mutation panel of only 0.34 Mb is superior to current commercial mutation panels and can better predict the efficacy of immunotherapy for LUAD patients, and its low cost and time-intensiveness make it more suitable for clinical applications.

Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

The current study suggests that the identification of predictive signatures of fluorouracil (5-FU) response for stage II and III colorectal cancer (CRC) could be confounded by chemotherapy-irrelevant low relapse risk. Using the samples of patients with stage II and III CRC who were treated with curative surgery only, we identified a signature with which to predict chemotherapy-irrelevant relapse risk for patients after curative surgery. By applying this signature to the samples of patients with stage II and III CRC who were treated with 5-FU-based adjuvant chemotherapy (ACT) after surgery, we predicted the relapse risk if treated with surgery only. From high-risk samples, we further identified another signature with which to predict therapeutic benefit from 5-FU-based ACT. On the basis of the relative expression orderings of gene pairs, a postsurgery relapse risk signature that consisted of 44 gene pairs was developed and verified in 3 independent data sets. A 5-FU therapeutic benefit signature that consisted of 4 gene pairs was then developed to predict the response of 5-FU-based ACT for those patients with high relapse risk after curative surgery. The signature was verified in 4 independent datasets. For patients with stage II and III CRC, the coupled signatures can first identify patients with high relapse risk after curative surgery, then predict therapeutic benefit from 5-FU-based ACT.-Song, K., Guo, Y., Wang, X., Cai, H., Zheng, W., Li, N., Song, X., Ao, L., Guo, Z., Zhao, W. Transcriptional signatures for coupled predictions of stage II and III colorectal cancer metastasis and fluorouracil-based adjuvant chemotherapy benefit.

Transcriptomic analysis on the effects of melatonin in gastrointestinal carcinomas.

BACKGROUND: Melatonin has been shown with anticancer property and therapeutic potential for tumors. However, there lacks a systematic study on the molecular pathways of melatonin and its antitumor effects in gastrointestinal carcinomas. METHODS: Using the gene expression profiles of four cancer cell lines from three types of gastrointestinal carcinomas before and after melatonin treatment, including gastric carcinoma (GC), colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), differentially expressed genes (DEGs) and biological pathways influenced by melatonin were identified. The qRT-PCR analyses were performed to validate the effects of melatonin on 5-FU resistance-related genes in CRC. RESULTS: There were 17 pathways commonly altered by melatonin in the three cancer types, including FoxO signaling pathways enriched by the upregulated DEGs and cell cycle signaling pathways enriched by the downregulated DEGs, confirmed the dual role of melatonin to tumor growth, pro-apoptosis and anti-proliferation. DEGs upregulated in the three types of cancer tissues but reversely downregulated by melatonin were commonly enriched in RNA transport, spliceosome and cell cycle signaling pathways, which indicate that melatonin might exert antitumor effects through these pathways. Our results further showed that melatonin can downregulate the expression levels of 5-FU resistance-related genes, such as thymidylate synthase in GC and ATR, CHEK1, BAX and MYC in CRC. The qRT-PCR results demonstrated that melatonin enhanced the sensitivity of CRC 5-FU resistant cells by decreasing the expression of ATR. CONCLUSIONS: Melatonin exerts the effects of pro-apoptosis and anti-proliferation on gastrointestinal carcinomas, and might increase the sensitivity of 5-FU in GC and CRC patients.

[The development of a general drug resistance score model based on MIC50 related gene pairs in colorectal cancer cell lines].

Cancer cell line models are widely used for testing drug sensitivity and in screening for drug resistance markers. However, the general level of drug resistance in cancer cell lines is often ignored by researchers, making it difficult to apply many drug efficacy markers in clinical practice. In this study, we examined 48 colorectal cancer (CRC) cell lines to calculate the correlation coefficients between the IC50 values for 265 drugs. The general drug resistance evaluation index MIC50 was constructed using the median value of 265 drugs' IC50 values. Genes with positively correlated expression values and a MIC50 which rose to significance were selected for further study. To analyze the effect of general drug resistance on the response status and prognosis in CRC patients, the general drug resistance scoring model was established based on within-sample relative expression orderings of gene pairs. The results demonstrate that more than 99% of the IC50 correlation coefficients of 265 drugs were significantly positive (FDR<0.05), indicating that CRC cell lines possessed general drug resistance characteristics. Furthermore, we identified 602 general drug resistance related genes, and by using Metascape, we identified four functional modules closely related to tumor resistance. A scoring model of 5-FU-based general drug resistance levels consisting of 21 gene pairs was built. After performing χ 2 test, we found that the general drug resistance level in CRC patients was significantly correlated with the response information after accepting 5-FU-based combination drug therapy. Survival analysis showed that the low scoring cohort of patients had a better prognosis than the higher scoring cohort, indicating that the level of basic drug resistance was closely related to the prognosis and drug response status in these patients. These results provide basic theoretical support for further research on the mechanism of combined chemotherapy resistance and the individualized regimen of clinical drug use in patients with CRC.

A qualitative transcriptional signature for the early diagnosis of colorectal cancer.

Currently, using biopsy specimens for the early diagnosis of colorectal cancer (CRC) is not entirely reliable due to insufficient sampling amount and inaccurate sampling location. Thus, it is necessary to develop a signature that can accurately identify patients with CRC under these clinical scenarios. Based on the relative expression orderings of genes within individual samples, we developed a qualitative transcriptional signature to discriminate CRC tissues, including CRC adjacent normal tissues from non-CRC individuals. The signature was validated using multiple microarray and RNA sequencing data from different sources. In the training data, a signature consisting of 7 gene pairs was identified. It was well validated in both biopsy and surgical resection specimens from multiple datasets measured by different platforms. For biopsy specimens, 97.6% of 42 CRC tissues and 94.5% of 163 non-CRC (normal or inflammatory bowel disease) tissues were correctly classified. For surgically resected specimens, 99.5% of 854 CRC tissues and 96.3% of 81 CRC adjacent normal tissues were correctly identified as CRC. Notably, we additionally measured 33 CRC biopsy specimens by the Affymetrix platform and 13 CRC surgical resection specimens, with different proportions of tumor epithelial cells, ranging from 40% to 100%, by the RNA sequencing platform, and all these samples were correctly identified as CRC. The signature can be used for the early diagnosis of CRC, which is also suitable for minimum biopsy specimens and inaccurately sampled specimens, and thus has potential value for clinical application.

Quantitative or qualitative transcriptional diagnostic signatures? A case study for colorectal cancer.

BACKGROUND: Due to experimental batch effects, the application of a quantitative transcriptional signature for disease diagnoses commonly requires inter-sample data normalization, which would be hardly applicable under common clinical settings. Many cancers might have qualitative differences with the non-cancer states in the gene expression pattern. Therefore, it is reasonable to explore the power of qualitative diagnostic signatures which are robust against experimental batch effects and other random factors. RESULTS: Firstly, using data of technical replicate samples from the MicroArray Quality Control (MAQC) project, we demonstrated that the low-throughput PCR-based technologies also exist large measurement variations for gene expression even when the samples were measured in the same test site. Then, we demonstrated the critical limitation of low stability for classifiers based on quantitative transcriptional signatures in applications to individual samples through a case study using a support vector machine and a naïve Bayesian classifier to discriminate colorectal cancer tissues from normal tissues. To address this problem, we identified a signature consisting of three gene pairs for discriminating colorectal cancer tissues from non-cancer (normal and inflammatory bowel disease) tissues based on within-sample relative expression orderings (REOs) of these gene pairs. The signature was well verified using 22 independent datasets measured by different microarray and RNA_seq platforms, obviating the need of inter-sample data normalization. CONCLUSIONS: Subtle quantitative information of gene expression measurements tends to be unstable under current technical conditions, which will introduce uncertainty to clinical applications of the quantitative transcriptional diagnostic signatures. For diagnosis of disease states with qualitative transcriptional characteristics, the qualitative REO-based signatures could be robustly applied to individual samples measured by different platforms.

Individualized identification of disease-associated pathways with disrupted coordination of gene expression.

Current pathway analysis approaches are primarily dedicated to capturing deregulated pathways at the population level and cannot provide patient-specific pathway deregulation information. In this article, the authors present a simple approach, called individPath, to detect pathways with significantly disrupted intra-pathway relative expression orderings for each disease sample compared with the stable, normal intra-pathway relative expression orderings pre-determined in previously accumulated normal samples. Through the analysis of multiple microarray data sets for lung and breast cancer, the authors demonstrate individPath's effectiveness for detecting cancer-associated pathways with disrupted relative expression orderings at the individual level and dissecting the heterogeneity of pathway deregulation among different patients. The portable use of this simple approach in clinical contexts is exemplified by the identification of prognostic intra-pathway gene pair signatures to predict overall survival of resected early-stage lung adenocarcinoma patients and signatures to predict relapse-free survival of estrogen receptor-positive breast cancer patients after tamoxifen treatment.

A qualitative signature for early diagnosis of hepatocellular carcinoma based on relative expression orderings.

BACKGROUND & AIMS: Currently, using biopsy specimens to confirm suspicious liver lesions of early hepatocellular carcinoma are not entirely reliable because of insufficient sampling amount and inaccurate sampling location. It is necessary to develop a signature to aid early hepatocellular carcinoma diagnosis using biopsy specimens even when the sampling location is inaccurate. METHODS: Based on the within-sample relative expression orderings of gene pairs, we identified a simple qualitative signature to distinguish both hepatocellular carcinoma and adjacent non-tumour tissues from cirrhosis tissues of non-hepatocellular carcinoma patients. RESULTS: A signature consisting of 19 gene pairs was identified in the training data sets and validated in 2 large collections of samples from biopsy and surgical resection specimens. For biopsy specimens, 95.7% of 141 hepatocellular carcinoma tissues and all (100%) of 108 cirrhosis tissues of non-hepatocellular carcinoma patients were correctly classified. Especially, all (100%) of 60 hepatocellular carcinoma adjacent normal tissues and 77.5% of 80 hepatocellular carcinoma adjacent cirrhosis tissues were classified to hepatocellular carcinoma. For surgical resection specimens, 99.7% of 733 hepatocellular carcinoma specimens were correctly classified to hepatocellular carcinoma, while 96.1% of 254 hepatocellular carcinoma adjacent cirrhosis tissues and 95.9% of 538 hepatocellular carcinoma adjacent normal tissues were classified to hepatocellular carcinoma. In contrast, 17.0% of 47 cirrhosis from non-hepatocellular carcinoma patients waiting for liver transplantation were classified to hepatocellular carcinoma, indicating that some patients with long-lasting cirrhosis could have already gained hepatocellular carcinoma characteristics. CONCLUSIONS: The signature can distinguish both hepatocellular carcinoma tissues and tumour-adjacent tissues from cirrhosis tissues of non-hepatocellular carcinoma patients even using inaccurately sampled biopsy specimens, which can aid early diagnosis of hepatocellular carcinoma.

Evaluating hepatocellular carcinoma cell lines for tumour samples using within-sample relative expression orderings of genes.

BACKGROUND & AIMS: Concerns are raised about the representativeness of cell lines for tumours due to the culture environment and misidentification. Liver is a major metastatic destination of many cancers, which might further confuse the origin of hepatocellular carcinoma cell lines. Therefore, it is of crucial importance to understand how well they can represent hepatocellular carcinoma. METHODS: The HCC-specific gene pairs with highly stable relative expression orderings in more than 99% of hepatocellular carcinoma but with reversed relative expression orderings in at least 99% of one of the six types of cancer, colorectal carcinoma, breast carcinoma, non-small-cell lung cancer, gastric carcinoma, pancreatic carcinoma and ovarian carcinoma, were identified. RESULTS: With the simple majority rule, the HCC-specific relative expression orderings from comparisons with colorectal carcinoma and breast carcinoma could exactly discriminate primary hepatocellular carcinoma samples from both primary colorectal carcinoma and breast carcinoma samples. Especially, they correctly classified more than 90% of liver metastatic samples from colorectal carcinoma and breast carcinoma to their original tumours. Finally, using these HCC-specific relative expression orderings from comparisons with six cancer types, we identified eight of 24 hepatocellular carcinoma cell lines in the Cancer Cell Line Encyclopedia (Huh-7, Huh-1, HepG2, Hep3B, JHH-5, JHH-7, C3A and Alexander cells) that are highly representative of hepatocellular carcinoma. Evaluated with a REOs-based prognostic signature for hepatocellular carcinoma, all these eight cell lines showed the same metastatic properties of the high-risk metastatic hepatocellular carcinoma tissues. CONCLUSIONS: Caution should be taken for using hepatocellular carcinoma cell lines. Our results should be helpful to select proper hepatocellular carcinoma cell lines for biological experiments.

Membrane fouling in ultrafiltration of natural water after pretreatment to different extents.

The combined fouling during ultrafiltration (UF) of surface water pretreated to different extents was investigated to disclose the roles of polysaccharides, proteins, and inorganic particles in UF membrane fouling. Both reversible and irreversible fouling decreased with enhanced pretreatment (biologically active carbon (BAC) treatment and sand filtration). The sand filter effluent fouled the membrane very slowly. The UF membrane removed turbidity to less than 0.1 nephelometric turbidity unit (NTU), reduced polysaccharides by 25.4%-29.9%, but rejected few proteins. Both polysaccharides and inorganic particles were detected on the fouled membranes, but inorganic particles could be effectively removed by backwashing. The increase of turbidity in the sand filter effluent to 3.05 NTU did not significantly increase the fouling rate, but an increase in the turbidity in the BAC effluent to 6.11 NTU increased the fouling rate by more than 100%. The results demonstrated that the polysaccharide, not the protein, constituents of biopolymers were responsible for membrane fouling. Membrane fouling was closely associated with a small fraction of polysaccharides in the feed water. Inorganic particles exacerbated membrane fouling only when the concentration of fouling-inducing polysaccharides in the feed water was relatively high. The combined fouling was largely reversible, and polysaccharides were the predominant substances responsible for irreversible fouling.