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Background/purpose: Previously we had identified concurrent genes, which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is to discovery biomarkers not identifiable by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection.Materials and Methods: Thirty-one comparative genomic hybridization (CGH) and 83 GE microarrays were performed, with 29 breast cancers assayed from both platforms. Potential targets were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from CGH arrays. Concurrent genes and genes with significant GISTIC scores were used to derive the extended concurrent genes signature, which was consensus from leading edge analysis across all studies and a supervised partial least square (PLS) regression predictive model of disease-free survival was constructed.Results: There were 1584 concurrent genes from 29 samples with both CGH and GE microarrays. Enriched concurrent genes sets for disease-free survival were identified independently from 83 GE arrays and another one with Han Chinese origin as well as three studies of Western origin. For five studies with disease-free survival follow up, prognostic discrepancy was observed between predicted high-risk and low-risk group patients.Conclusion: We concluded that through parallel analyses of CGH and GE microarrays, the proposed extended concurrent gene expression signature can identify biomarkers with prognostic values. [ABSTRACT FROM AUTHOR]

Background: Hemodynamic assessment in patients with pulmonary arterial hypertension (PAH) is essential for risk stratification and pharmacological management. However, the prognostic value of the hemodynamic changes after treatment is less well established. Objectives: We investigated the prognostic impacts of the changes in hemodynamic indices, including mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), right atrial pressure (RAP), and cardiac output index (CI). We conducted this systematic review with meta-regression analysis on existing clinical trials. Methods: We searched and identified all relevant randomized controlled trials from multiple databases. An analogous R2 index was used to quantify the proportion of variance explained by each predictor in the association with PAH patients' prognosis. A total of 21 trials and 3306 individuals were enrolled. Results: The changes in mPAP, PVR, RAP, and CI were all significantly associated with the change in 6MWD (∆6MWD). The change in mPAP was with the highest explanatory power for ∆6MWD (R2 analog = 0.740). Additionally, the changes in mPAP, PVR, and CI were independently predictive of adverse clinical events. The change in mPAP had the highest explanatory power for the clinical events (R2 analog = 0.911). Furthermore, the change in PVR was with the highest explanatory power for total mortality of PAH patients (R2 analog = 0.612). Conclusion: Hemodynamic changes after treatment, including mPAP, PVR, CI, and RAP, were significantly associated with adverse clinical events or mortality in treated PAH patients. It is recommended that further studies be conducted to evaluate the changes in hemodynamic indices to guide drug titration. Systematic review registration: PROSPERO CRD42019125157 [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the most common gastrointestinal malignancy worldwide. The poor specificity and sensitivity of the fecal occult blood test has prompted the development of CRC-related genetic markers for CRC screening and treatment. Gene expression profiles in stool specimens are effective, sensitive and clinically applicable. Herein, a novel advantage of using cells shed from the colon is presented for cost-effective CRC screening. Molecular panels were generated through a series of leave-one-out cross-validation and discriminant analyses. A logistic regression model following reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry was used to validate a specific panel for CRC prediction. The panel, consisting of ubiquitin-conjugating enzyme E2 N (UBE2N), inosine monophosphate dehydrogenase 1 (IMPDH1), dynein cytoplasmic 1 light intermediate chain 1 (DYNC1LI1) and phospholipase A and acyltransferase 2 (HRASLS2), accurately recognized patients with CRC and could thus be further investigated as a potential prognostic and predictive biomarker for CRC. UBE2N, IMPDH1 and DYNC1LI1 expression levels were upregulated and HRASLS2 expression was downregulated in CRC tissues. The predictive power of the panel was 96.6% [95% confidence interval (CI), 88.1-99.6%] sensitivity and 89.7% (95% CI, 72.6-97.8%) specificity at a predicted cut-off value at 0.540, suggesting that this four-gene panel testing of stool specimens can faithfully mirror the state of the colon. On the whole, the present study demonstrates that screening for CRC or cancer detection in stool specimens collected non-invasively does not require the inclusion of an excessive number of genes, and colonic defects can be identified via the detection of an aberrant protein in the mucosa or submucosa. [ABSTRACT FROM AUTHOR]

Background: The liver is the most common target organ in the metastasis of colorectal cancer (CRC). Synchronous liver metastases may confer a poorer prognosis than metachronous metastases, and genetic alterations and an inflammatory response have also been associated with a poor prognosis in cases of a liver metastasis arising from CRC. However, few studies have examined the relationship between KRAS mutations and inflammatory status in CRC, especially with respect to liver metastases. Methods: The effect of the activated mitogen-activated protein kinase pathway and another protein involved in inflammation, C-reactive protein, in liver metastases were examined. We aimed to determine the impact of the CRP-specific single nucleotide polymorphism (SNP) rs7553007 in liver metastasis on the CRC-specific survival (CSS) of patients after colorectal liver metastasectomy. Results: We found no significant differences in genotype distributions and allele frequencies at the CRP SNP rs7553007 between CRC patients with liver metastasis and the control group. CSS rates were low in the subgroup of patients with synchronous metastasis with the A-allele (A/A and A/G) at rs7553007 or mutated KRAS/BRAF in liver metastatic specimens. Furthermore, the CRP SNP rs7553007 (hazard ratio [HR] = 1.101; 95% confidence interval [CI] = 1.011–1.200; P = 0.027) and KRAS/BRAF mutations (HR = 2.377; 95% CI = 1.293–4.368; P = 0.005) remained predictive for the CSS of CRC patients with synchronous liver metastasis in multivariate analysis. Conclusions: Both the CRP SNP rs7553007 and KRAS/BRAF mutations were independent prognostic factors for CRC patients with synchronous liver metastasis. [ABSTRACT FROM AUTHOR]

Introduction: Coxsackievirus/adenovirus receptors (CARs) and desmoglein-2 (DSG2) are similar molecules to adenovirus-based vectors in the cell membrane. They have been found to be associated with lung epithelial cell tumorigenesis and can be useful markers in predicting survival outcome in lung adenocarcinoma (LUAD). Methods: A gene ontology enrichment analysis disclosed that DSG2 was highly correlated with CAR. Survival analysis was then performed on 262 samples from the Cancer Genome Atlas, forming "Stage 1A" or "Stage 1B". We therefore analyzed a tissue microarray (TMA) comprised of 108 lung samples and an immunohistochemical assay. Computer counting software was used to calculate the H-score of the immune intensity. Cox regression and Kaplan–Meier analyses were used to determine the prognostic value. Results: CAR and DSG2 genes are highly co-expressed in early stage LUAD and associated with significantly poorer survival (p = 0.0046). TMA also showed that CAR/DSG2 expressions were altered in lung cancer tissue. CAR in the TMA was correlated with proliferation, apoptosis, and epithelial–mesenchymal transition (EMT), while DSG2 was associated with proliferation only. The Kaplan–Meier survival analysis revealed that CAR, DSG2, or a co-expression of CAR/DSG2 was associated with poorer overall survival. Conclusions: The co-expression of CAR/DSG2 predicted a worse overall survival in LUAD. CAR combined with DSG2 expression can predict prognosis. [ABSTRACT FROM AUTHOR]