An individualized prognostic signature for gastric cancer patients treated with 5-Fluorouracil-based chemotherapy and distinct multi-omics characteristics of prognostic groups

The role of metal ions in the occurrence, progression, drug resistance, and biological characteristics of gastric cancer

Metal ions exert pivotal functions within the human body, encompassing essential roles in upholding cell structure, gene expression regulation, and catalytic enzyme activity. Additionally, they significantly influence various pathways implicated in divergent mechanisms of cell death. Among the prevailing malignant tumors of the digestive tract worldwide, gastric cancer stands prominent, exhibiting persistent high mortality rates. A compelling body of evidence reveals conspicuous ion irregularities in tumor tissues, encompassing gastric cancer. Notably, metal ions have been observed to elicit distinct contributions to the progression, drug resistance, and biological attributes of gastric cancer. This review consolidates pertinent literature on the involvement of metal ions in the etiology and advancement of gastric cancer. Particular attention is directed towards metal ions, namely, Na, K, Mg, Ca, Fe, Cu, Zn, and Mn, elucidating their roles in the initiation and progression of gastric cancer, cellular demise processes, drug resistance phenomena, and therapeutic approaches.

Mutational separation and clinical outcomes of TP53 and CDH1 in gastric cancer

BACKGROUND

Gastric cancer (GC) is a deadly tumor with the fifth highest occurrence and highest global mortality rates. Owing to its heterogeneity, the underlying mechanism of GC remains unclear, and chemotherapy offers little benefit to individuals.

AIM

To investigate the clinical outcomes of TP53 and CDH1 mutations in GC.

METHODS

In this study, 202 gastric adenocarcinoma tumor tissues and their corresponding normal tissues were collected. A total of 490 genes were identified using target capture. Through t-test and Wilcoxon rank-sum test, somatic mutations, microsatellite instability, and clinical statistics, including overall survival, were detected, compared, and calculated.

RESULTS

The mutation rates of 32 genes, including TP53, SPEN, FAT1, and CDH1 exceeded 10%. TP53 mutations had a slightly lower overall occurrence rate (33%). The TP53 mutation rate was significantly higher in advanced stages (stage III/IV) than that in early stages (stage I/II) (P < 0.05). In contrast, CDH1 mutations were significantly associated with diffuse GC. TP53 is related to poor prognosis of advanced-stage tumors; nevertheless, CDH1 corresponds to a diffuse type of cancer. TP53 is exclusively mutated in CDH1 and is primarily affected by two distinct GC mechanisms.

CONCLUSION

Different somatic mutation patterns in TP53 and CDH1 indicate two major mechanisms of GC.

Application of apoptosis-related genes in a multiomics-related prognostic model study of gastric cancer

Gastric cancer (GC) is one of the most common tumors in the world, and apoptosis is closely associated with GC. A number of therapeutic methods have been implemented to increase the survival in GC patients, but the outcomes remain unsatisfactory. Apoptosis is a highly conserved form of cell death, but aberrant regulation of the process also leads to a variety of major human diseases. As variations of apoptotic genes may increase susceptibility to gastric cancer. Thus, it is critical to identify novel and potent tools to predict the overall survival (OS) and treatment efficacy of GC. The expression profiles and clinical characteristics of TCGA-STAD and GSE15459 cohorts were downloaded from TCGA and GEO. Apoptotic genes were extracted from the GeneCards database. Apoptosis risk scores were constructed by combining Cox regression and LASSO regression. The GSE15459 and TCGA internal validation sets were used for external validation. Moreover, we explored the relationship between the apoptosis risk score and clinical characteristics, drug sensitivity, tumor microenvironment (TME) and tumor mutational burden (TMB). Finally, we used GSVA to further explore the signaling pathways associated with apoptosis risk. By performing TCGA-STAD differential analysis, we obtained 839 differentially expressed genes, which were then analyzed by Cox regressions and LASSO regression to establish 23 genes associated with apoptosis risk scores. We used the test validation cohort from TCGA-STAD and the GSE15459 dataset for external validation. The AUC values of the ROC curve for 2-, 3-, and 5-years survival were 0.7, 0.71, and 0.71 in the internal validation cohort from TCGA-STAD and 0.77, 0.74, and 0.75 in the GSE15459 dataset, respectively. We constructed a nomogram by combining the apoptosis risk signature and some clinical characteristics from TCGA-STAD. Analysis of apoptosis risk scores and clinical characteristics demonstrated notable differences in apoptosis risk scores between survival status, sex, grade, stage, and T stage. Finally, the apoptosis risk score was correlated with TME characteristics, drug sensitivity, TMB, and TIDE scores.

The Transcriptional Landscape of BRAF Wild Type Metastatic Melanoma: A Pilot Study

Melanoma is a relatively rare disease worldwide; nevertheless, it has a great relevance in some countries, such as in Europe. In order to shed some light upon the transcriptional profile of skin melanoma, we compared the gene expression of six independent tumours (all progressed towards metastatic disease and with wild type BRAF) to the expression profile of non-dysplastic melanocytes (considered as a healthy control) in a pilot study. Paraffin-embedded samples were manually micro-dissected to obtain enriched samples, and then, RNA was extracted and analysed through a microarray-based approach. An exhaustive bioinformatics analysis was performed to identify differentially expressed transcripts between the two groups, as well as enriched functional terms. Overall, 50 up- and 19 downregulated transcripts were found to be significantly changed in the tumour compared to the control tissue. Among the upregulated transcripts, the majority belonged to the immune response group and to the proteasome, while most of the downregulated genes were related to cytosolic ribosomes. A Gene Set Enrichment Analysis (GSEA), along with the RNA-Seq data retrieved from the TCGA/GTEx databases, confirmed the general trend of downregulation affecting cytoribosome proteins. In contrast, transcripts coding for mitoribosome proteins showed the opposite trend.

A Qualitative Signature to Identify TERT Promoter Mutant High-Risk Tumors in Low-Grade Gliomas

Background: Telomerase reverse transcriptase promoter (TERT-p) mutation has been frequently found, but associated with contrary prognosis, in both low-grade gliomas and glioblastomas. For the low-grade gliomas (Grades II-III), TERT-p mutant patients have a better prognosis than the wildtype patients, whereas for the GBMs (Grade IV), TERT-p mutation is related to a poor prognosis. We hypothesize that there exist high-risk patients in LGGs who share GBM-like molecular features, including TERT-p mutation, and need more intensive treatment than other LGGs. A molecular signature is needed to identify these high-risk patients for an accurate and timely treatment.

Methods: Using the within-sample relative expression orderings of gene pairs, we identified the gene pairs with significantly stable REOs, respectively, in both the TERT-p mutant LGGs and GBMs but with opposite directions in the two groups. These reversely stable gene pairs were used as the molecular signature to stratify the LGGs into high-risk and low-risk groups.

Results: A signature consisting of 21 gene pairs was developed, which can classify LGGs into two groups with significantly different overall survival. The high-risk group has a similar genetic mutation profile and a similar survival profile as GBMs, and these high-risk tumors may progress to a more malignant state.

Conclusion: The 21 gene-pair signature based on REOs is capable of identifying high-risk patients in LGGs and guiding the clinical choice for appropriate and timely intervention.

Extracellular Matrix-Related Hubs Genes Have Adverse Effects on Gastric Adenocarcinoma Prognosis Based on Bioinformatics Analysis

Gastric adenocarcinoma (GAC) is the most frequent type of stomach cancer, characterized by high heterogeneity and phenotypic diversity. Although many novel strategies have been developed for treating GAC, recurrence and metastasis rates are still high. Therefore, it is necessary to screen new potential biomarkers correlated with prognosis and novel molecular targets. Gene expression profiles were obtained from the from NCBI Gene Expression Omnibus (GEO) database. We conduct an integrated analysis using the online Venny website to explore candidate hub genes between differentially expressed genes (DEGs) of two datasets. Gene ontology (GO) and Kyoto Encyclopedia 18 of Genes and Genomes (KEGG) pathway enrichment analysis found that extracellular matrix plays an important role in GAC. In addition, we applied protein-protein interaction (PPI) network analysis by using the Search Tool for the Retrieval of Interacting Genes (STRING) and visualized with Cytoscape software. Furthermore, we employed Cytoscape software to analyze the interactive relationship of candidate gene for further analysis. We found that ECM related proteins played an important role in GAC, and 15 hub genes were extracted from 123 DEGs genes. There were four hub genes (bgn, vcan, col1a1 and timp1) predicted to be associated with poor prognosis among the 15 hub genes.

Control of Biophysical and Pharmacological Properties of Potassium Channels by Ancillary Subunits

Potassium channels facilitate and regulate physiological processes as diverse as electrical signaling, ion, solute and hormone secretion, fluid homeostasis, hearing, pain sensation, muscular contraction, and the heartbeat. Potassium channels are each formed by either a tetramer or dimer of pore-forming α subunits that co-assemble to create a multimer with a K⁺-selective pore that in most cases is capable of functioning as a discrete unit to pass K⁺ ions across the cell membrane. The reality in vivo, however, is that the potassium channel α subunit multimers co-assemble with ancillary subunits to serve specific physiological functions. The ancillary subunits impart specific physiological properties that are often required for a particular activity in vivo; in addition, ancillary subunit interaction often alters the pharmacology of the resultant complex. In this chapter the modes of action of ancillary subunits on K⁺ channel physiology and pharmacology are described and categorized into various mechanistic classes.

The Effects of Age, Cigarette Smoking, Sex, and Race on the Qualitative Characteristics of Lung Transcriptome

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.

Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients

Gastric cancer (GC) is the second leading cause of cancer mortality and remains the fourth common cancer worldwide. The effective and feasible methods for predicting the possible outcomes for GC patients are still lacking. While genetic profiling might be suitable in some way, the application of gene expression signatures has been show to be a robust tool. Here, by performing a comprehensive search in PubMed, we provided an up-to-date summary of 39 prognostic gene signatures for GC patients, and described the processing procedure of the selection, calculation and construction of gene signature. We also reviewed current web tools including PROGgene and SurvExpress that can be used to analyze the prognostic value of multiple genes for GC. This review will aid in comprehensive understanding of the current prognostic gene signatures to accurately predict the outcome of GC patients, and may guide the future clinical management when the reliability of these signatures is validated in clinics.

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.

A qualitative transcriptional prognostic signature for patients with stage I-II pancreatic ductal adenocarcinoma

Accurately prognostic evaluation of patients with stage I-II pancreatic ductal adenocarcinoma (PDAC) is of importance to treatment decision and patient management. Most previously reported prognostic signatures were based on risk scores summarized from quantitative expression measurements of signature genes, which are susceptible to experimental batch effects and impractical for clinical applications. Based on the within-sample relative expression orderings of genes, we developed a robust qualitative transcriptional prognostic signature, consisting of 64 gene pairs (64-GPS), to predict the overall survival (OS) of 161 stage I-II PDAC patients in the training dataset who were treated with surgery only. Samples were classified into the high-risk group when at least 25 of 64 gene pairs suggested it was at high risk. The signature was successfully validated in 324 samples from 6 independent datasets produced by different laboratories. All samples in the low-risk group had significantly better OS than samples in the high-risk group. Multivariate Cox regression analyses showed that the 64-GPS remained significantly associated with the OS of patients after adjusting available clinical factors. Transcriptomic analysis of the 2 prognostic subgroups showed that the differential expression signals were highly reproducible in all datasets, whereas the differences between samples grouped by the TNM staging system were weak and irreproducible. The epigenomic analysis showed that the epigenetic alternations may cause consistently transcriptional changes between the 2 different prognostic groups. The genomic analysis revealed that mutation‑induced disturbances in several key genes, such as LRMDA, MAPK10, and CREBBP, might lead to poor prognosis for PDAC patients. Conclusively, the 64-GPS can robustly predict the prognosis of patients with stage I-II PDAC, which provides theoretical basis for clinical individualized treatment.

A qualitative transcriptional signature to reclassify histological grade of ER-positive breast cancer patients

Background

Histological grade (HG) is commonly adopted as a prognostic factor for ER-positive breast cancer patients. However, HG evaluation methods, such as the pathological Nottingham grading system, are highly subjective with only 50–85% inter-observer agreements. Specifically, the subjectivity in the pathological assignment of the intermediate grade (HG2) breast cancers, comprising of about half of breast cancer cases, results in uncertain disease outcomes prediction. Here, we developed a qualitative transcriptional signature, based on within-sample relative expression orderings (REOs) of gene pairs, to define HG1 and HG3 and reclassify pathologically-determined HG2 (denoted as pHG2) breast cancer patients.

Results

From the gene pairs with significantly stable REOs in pathologically-determined HG1 (denoted as pHG1) samples and reversely stable REOs in pathologically-determined HG3 (denoted as pHG3) samples, concordantly identified from seven datasets, we extracted a signature which could determine the HG state of samples through evaluating whether the within-sample REOs match with the patterns of the pHG1 REOs or pHG3 REOs. A sample was classified into the HG3 group if at least a half of the REOs of the 10 gene pairs signature within this sample voted for HG3; otherwise, HG1. Using four datasets including samples of early stage (I–II) ER-positive breast cancer patients who accepted surgery only, we validated that this signature was able to reclassify pHG2 patients into HG1 and HG3 groups with significantly different survival time. For the original pHG1 and pHG3 patients, the signature could also more accurately and objectively stratify them into distinct prognostic groups. And the up-regulated and down down-regulated genes in HG1 compared with HG3 involved in cell proliferation and extracellular signal transduction pathways respectively. By comparing with existing signatures, 10-GPS was with prognostic significance and was more aligned with survival of patients especially for pHG2 samples.

Conclusions

The transcriptional qualitative signature can provide an objective assessment of HG states of ER-positive breast cancer patients, especially for reclassifying patients with pHG2, to assist decision making on clinical therapy.

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.

Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method

Hepatocellular carcinoma (HCC) is a serious cancer which ranked the fourth in cancer-related death worldwide. Hence, more accurate diagnostic models are urgently needed to aid the early HCC diagnosis under clinical scenarios and thus improve HCC treatment and survival. Several conventional methods have been used for discriminating HCC from cirrhosis tissues in patients without HCC (CwoHCC). However, the recognition successful rates are still far from satisfactory. In this study, we applied a computational approach that based on machine learning method to a set of microarray data generated from 1091 HCC samples and 242 CwoHCC samples. The within-sample relative expression orderings (REOs) method was used to extract numerical descriptors from gene expression profiles datasets. After removing the unrelated features by using maximum redundancy minimum relevance (mRMR) with incremental feature selection, we achieved “11-gene-pair” which could produce outstanding results. We further investigated the discriminate capability of the “11-gene-pair” for HCC recognition on several independent datasets. The wonderful results were obtained, demonstrating that the selected gene pairs can be signature for HCC. The proposed computational model can discriminate HCC and adjacent non-cancerous tissues from CwoHCC even for minimum biopsy specimens and inaccurately sampled specimens, which can be practical and effective for aiding the early HCC diagnosis at individual level.

Prognostic potential of PRPF3 in hepatocellular carcinoma

pre-mRNA processing factor 3 (PRPF3) is an RNA binding protein in a core component of the exon junction complex. Abnormal PRPF3 expression is potentially associated with carcinogenesis. However, the biological role of PRPF3 in hepatocellular carcinoma (HCC) remains to be determined. We analyzed PRPF3 expression via multiple gene expression databases and identified its genetic alterations and functional networks using cBioPortal. Co-expressed genes with PRPF3 and its regulators were identified using LinkedOmics. The correlations between PRPF3 and cancer immune infiltrates were investigated via Tumor Immune Estimation Resource (TIMER). PRPF3 was found up-regulated with amplification in tumor tissues in multiple HCC cohorts. High PRPF3 expression was associated with poorer overall survival (OS) and disease-free survival (DFS). Functional network analysis suggested that PRPF3 regulates spliceosome, DNA replication, and cell cycle signaling via pathways involving several cancer-related kinases and E2F family. Notably, PRPF3 expression was positively correlated with infiltrating levels of CD4+ T and CD8+ T cells, macrophages, neutrophils, and dendritic cells. PRPF3 expression showed strong correlations with diverse immune marker sets in HCC. These findings suggest that PRPF3 is correlated with prognosis and immune infiltrating in HCC, laying a foundation for further study of the immune regulatory role of PRPF3 in HCC.

Qualitative transcriptional signature for predicting pathological response of colorectal cancer to FOLFOX therapy

FOLFOX (5‐fluorouracil, leucovorin and oxaliplatin) is one of the main chemotherapy regimens for colorectal cancer (CRC), but only half of CRC patients respond to this regimen. Using gene expression profiles of 96 metastatic CRC patients treated with FOLFOX, we first selected gene pairs whose within‐sample relative expression orderings (REO) were significantly associated with the response to FOLFOX using the exact binomial test. Then, from these gene pairs, we applied an optimization procedure to obtain a subset that achieved the largest F‐score in predicting pathological response of CRC to FOLFOX. The REO‐based qualitative transcriptional signature, consisting of five gene pairs, was developed in the training dataset consisting of 96 samples with an F‐score of 0.90. In an independent test dataset consisting of 25 samples with the response information, an F‐score of 0.82 was obtained. In three other independent survival datasets, the predicted responders showed significantly better progression‐free survival than the predicted non‐responders. In addition, the signature showed a better predictive performance than two published FOLFOX signatures across different datasets and is more suitable for CRC patients treated with FOLFOX than 5‐fluorouracil‐based signatures. In conclusion, the REO‐based qualitative transcriptional signature can accurately identify metastatic CRC patients who may benefit from the FOLFOX regimen.

A qualitative transcriptional signature for predicting microsatellite instability status of right-sided Colon Cancer

Background

Microsatellite instability (MSI) accounts for about 15% of colorectal cancer and is associated with prognosis. Today, MSI is usually detected by polymerase chain reaction amplification of specific microsatellite markers. However, the instability is identified by comparing the length of microsatellite repeats in tumor and normal samples. In this work, we developed a qualitative transcriptional signature to individually predict MSI status for right-sided colon cancer (RCC) based on tumor samples.

Results

Using RCC samples, based on the relative expression orderings (REOs) of gene pairs, we extracted a signature consisting of 10 gene pairs (10-GPS) to predict MSI status for RCC through a feature selection process. A sample is predicted as MSI when the gene expression orderings of at least 7 gene pairs vote for MSI; otherwise the microsatellite stability (MSS). The classification performance reached the largest F-score in the training dataset. This signature was verified in four independent datasets of RCCs with the F-scores of 1, 0.9630, 0.9412 and 0.8798, respectively. Additionally, the hierarchical clustering analyses and molecular features also supported the correctness of the reclassifications of the MSI status by 10-GPS.

Conclusions

The qualitative transcriptional signature can be used to classify MSI status of RCC samples at the individualized level.

Role of ion channels in gastrointestinal cancer

In their seminal papers Hanahan and Weinberg described oncogenic processes a normal cell undergoes to be transformed into a cancer cell. The functions of ion channels in the gastrointestinal (GI) tract influence a variety of cellular processes, many of which overlap with these hallmarks of cancer. In this review we focus on the roles of the calcium (Ca2+), sodium (Na+), potassium (K+), chloride (Cl-) and zinc (Zn2+) transporters in GI cancer, with a special emphasis on the roles of the KCNQ1 K+ channel and CFTR Cl- channel in colorectal cancer (CRC). Ca2+ is a ubiquitous second messenger, serving as a signaling molecule for a variety of cellular processes such as control of the cell cycle, apoptosis, and migration. Various members of the TRP superfamily, including TRPM8, TRPM7, TRPM6 and TRPM2, have been implicated in GI cancers, especially through overexpression in pancreatic adenocarcinomas and down-regulation in colon cancer. Voltage-gated sodium channels (VGSCs) are classically associated with the initiation and conduction of action potentials in electrically excitable cells such as neurons and muscle cells. The VGSC NaV1.5 is abundantly expressed in human colorectal CRC cell lines as well as being highly expressed in primary CRC samples. Studies have demonstrated that conductance through NaV1.5 contributes significantly to CRC cell invasiveness and cancer progression. Zn2+ transporters of the ZIP/SLC39A and ZnT/SLC30A families are dysregulated in all major GI organ cancers, in particular, ZIP4 up-regulation in pancreatic cancer (PC). More than 70 K+ channel genes, clustered in four families, are found expressed in the GI tract, where they regulate a range of cellular processes, including gastrin secretion in the stomach and anion secretion and fluid balance in the intestinal tract. Several distinct types of K+ channels are found dysregulated in the GI tract. Notable are hERG1 upregulation in PC, gastric cancer (GC) and CRC, leading to enhanced cancer angiogenesis and invasion, and KCNQ1 down-regulation in CRC, where KCNQ1 expression is associated with enhanced disease-free survival in stage II, III, and IV disease. Cl- channels are critical for a range of cellular and tissue processes in the GI tract, especially fluid balance in the colon. Most notable is CFTR, whose deficiency leads to mucus blockage, microbial dysbiosis and inflammation in the intestinal tract. CFTR is a tumor suppressor in several GI cancers. Cystic fibrosis patients are at a significant risk for CRC and low levels of CFTR expression are associated with poor overall disease-free survival in sporadic CRC. Two other classes of chloride channels that are dysregulated in GI cancers are the chloride intracellular channels (CLIC1, 3 & 4) and the chloride channel accessory proteins (CLCA1,2,4). CLIC1 & 4 are upregulated in PC, GC, gallbladder cancer, and CRC, while the CLCA proteins have been reported to be down-regulated in CRC. In summary, it is clear, from the diverse influences of ion channels, that their aberrant expression and/or activity can contribute to malignant transformation and tumor progression. Further, because ion channels are often localized to the plasma membrane and subject to multiple layers of regulation, they represent promising clinical targets for therapeutic intervention including the repurposing of current drugs.

Emerging roles for multifunctional ion channel auxiliary subunits in cancer

Several superfamilies of plasma membrane channels which regulate transmembrane ion flux have also been shown to regulate a multitude of cellular processes, including proliferation and migration. Ion channels are typically multimeric complexes consisting of conducting subunits and auxiliary, non-conducting subunits. Auxiliary subunits modulate the function of conducting subunits and have putative non-conducting roles, further expanding the repertoire of cellular processes governed by ion channel complexes to processes such as transcellular adhesion and gene transcription. Given this expansive influence of ion channels on cellular behaviour it is perhaps no surprise that aberrant ion channel expression is a common occurrence in cancer. This review will focus on the conducting and non-conducting roles of the auxiliary subunits of various Ca2+, K+, Na+ and Cl- channels and the burgeoning evidence linking such auxiliary subunits to cancer. Several subunits are upregulated (e.g. Cavβ, Cavγ) and downregulated (e.g. Kvβ) in cancer, while other subunits have been functionally implicated as oncogenes (e.g. Navβ1, Cavα2δ1) and tumour suppressor genes (e.g. CLCA2, KCNE2, BKγ1) based on in vivo studies. The strengthening link between ion channel auxiliary subunits and cancer has exposed these subunits as potential biomarkers and therapeutic targets. However further mechanistic understanding is required into how these subunits contribute to tumour progression before their therapeutic potential can be fully realised.

Extract of Cycas revoluta Thunb. enhances the inhibitory effect of 5-fluorouracil on gastric cancer cells through the AKT-mTOR pathway

BACKGROUND

Gastric cancer is one of the most common and deadly malignancies worldwide. Despite recent medical progress, the 5-year survival rate of gastric cancer is still unsatisfactory. 5-fluorouracil (5-Fu) is one of the first-line antineoplastic treatments for gastric cancer, as it can effectively induce cancer cell apoptosis. However, the effect of 5-Fu is limited due to drug resistance of the malignant tumor. Previous studies have reported that Sotetsuflavone from Cycas revoluta Thunb. can markedly suppress lung cancer cell proliferation by apoptosis, though its effect on gastric cancer remains unknown.

AIM

To investigate the inhibitory effect of Cycas revoluta Thunb. and to determine whether it can overcome gastric cancer cell drug resistance to 5-Fu.

METHODS

Cell viability was examined to determine whether the natural extract of Cycas revoluta Thunb. induced gastric cancer cell death. The half-maximal effective concentration and the half-maximal lethal concentration were calculatede. Wound-healing and transwell assays were performed to examine gastric cancer cell motility. Clonogenic assays were performed to investigate the synergistic effects of Cycas revoluta Thunb. with 5-Fu, and apoptotic bodies were detected by Hoechst staining. Western blotting was performed to examine the expression of related proteins and to investigate the molecular mechanism of Cycas revoluta Thunb.-induced cancer cell apoptosis. The expressions of proteins, including mammalian target of rapamycin (mTOR) and p-AKT, were detected in different combinations of treatments for 48 h, then analyzed by ECL detection.

RESULTS

Gastric cancer cells were more sensitive to the natural extract of Cycas revoluta Thunb. compared to normal gastric epithelial cells, and the extract effectively inhibited gastric cancer cell migration and invasion. The extract improved the anti-cancer effect of 5-Fu by enhancing the chemosensitization of gastric cancer cells. Extract plus 5-Fu further reduced the expression of the drug-resistance-related proteins p-AKT and mTOR after 48 h compared to 5-Fu alone. Compared to 5-Fu treatment alone, mTOR and p-AKT expression was significantly reduced by about 50% and 75%, respectively. We also found that the natural extract of Cycas revoluta Thunb. further increased 5-Fu-induced gastric cancer cell apoptosis. Expression of apoptosis-related protein X-linked inhibitor of apoptosis protein and apoptosis inducing factor were significantly reduced and increased, respectively, in the 5-Fu-resistant gastric cancer line SGC-7901/R treated with extract plus 5-Fu, while the expression of survivin did not change.

CONCLUSION

The natural extract of Cycas revoluta Thunb. effectively inhibited gastric cancer cell growth and enhanced the anti-cancer effect of 5-Fu through the AKT-mTOR pathway.

Circumvent the uncertainty in the applications of transcriptional signatures to tumor tissues sampled from different tumor sites

The expression measurements of thousands of genes are correlated with the proportions of tumor epithelial cell (PTEC) in clinical samples. Thus, for a tumor diagnostic or prognostic signature based on a summarization of expression levels of the signature genes, the risk score for a patient may dependent on the tumor tissues sampled from different tumor sites with diverse PTEC for the same patient. Here, we proposed that the within-samples relative expression orderings (REOs) based gene pairs signatures should be insensitive to PTEC variations. Firstly, by analysis of paired tumor epithelial cell and stromal cell microdissected samples from 27 cancer patients, we showed that above 80% of gene pairs had consistent REOs between the two cells, indicating these REOs would be independent of PTEC in cancer tissues. Then, by simulating tumor tissues with different PTEC using each of the 27 paired samples, we showed that about 90% REOs of gene pairs in tumor epithelial cells were maintained in tumor samples even when PTEC decreased to 30%. Especially, the REOs of gene pairs with larger expression differences in tumor epithelial cells tend to be more robust against PTEC variations. Finally, as a case study, we developed a gene pair signature which could robustly distinguish colorectal cancer tissues with various PTEC from normal tissues. We concluded that the REOs-based signatures were robust against PTEC variations.

Robust transcriptional tumor signatures applicable to both formalin-fixed paraffin-embedded and fresh-frozen samples

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.

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.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4446-y) contains supplementary material, which is available to authorized users.

Robust transcriptional signatures for low-input RNA samples based on relative expression orderings

Background

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.

Results

We compared the expression measurements of low-input mRNA samples, from 25 pg to 1000 pg mRNA, which were amplified and profiled by Smart-seq, DP-seq and CEL-seq techniques using the Illumina HiSeq 2000 platform, with those of the paired high-input (50 ng) mRNA samples. Even with 1000 pg mRNA input, we found that thousands of genes had at least 2 folds-change of expression levels in the low-input samples compared with the corresponding paired high-input samples. Consequently, a transcriptional signature based on quantitative expression values and determined from high-input RNA samples cannot be applied to low-input samples, and vice versa. In contrast, the within-sample relative expression orderings (REOs) of approximately 90% of all the gene pairs in the high-input samples were maintained in the paired low-input samples with 1000 pg input mRNA molecules. Similar results were observed in the low-input total RNA samples amplified and profiled by the Whole-Genome DASL technique using the Illumina HumanRef-8 v3.0 platform. As a proof of principle, we developed REOs-based signatures from high-input RNA samples for discriminating cancer tissues and showed that they can be robustly applied to low-input RNA samples.

Conclusions

REOs-based signatures determined from the high-input RNA samples can be robustly applied to samples profiled with the low-input RNA samples, as low as the 1000 pg and 250 pg input samples but no longer stable in samples with less than 250 pg RNA input to a certain degree.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4280-7) contains supplementary material, which is available to authorized users.

Dissect new mechanistic insights for geniposide efficacy on the hepatoprotection using multiomics approach

A multi-omics approach could yield in-depth mechanistic insights. Here, we performed an integrated analysis of miRNAome, proteome and metabolome, aimed to investigate the underlying mechanism of active product geniposide in ethanol-induced apoptosis. We found that integrative meta-analysis identified 28 miRNAs, 20 proteins and 7 metabolites significantly differentially expressed, respectively. Further analysis identified geniposide extensively regulated multiple metabolism pathways and the most important related pathway was citrate cycle (TCA cycle). In addition, geniposide can improve energy metabolism benefits using the Extracellular Flux Analyzer. Of particular significance, miR-144-5p exhibits a high positive correlation with oxoglutaric acid, isocitrate dehydrogenase (IDH) 1 and 2 that involved in the TCA cycle. Furthermore,we discovered that miR-144-5p regulates TCA cycle metabolism through IDH1 and IDH2. Collectively, we describe for the first time the hepatoprotective effect of geniposide decreased miR-144-5p level, capable of regulating TCA cycle by directly targeting IDH1 and IDH2 and promoting functional consequences in cells. Integrating metabolomics, miRNAomics and proteomics approach and thereby analyzing microRNAs and proteins as well as metabolites can give valuable information about the functional regulation pattern and action mechanism of natural products.