Serotonin transporter gene (SLC6A4) variations are associated with poor survival in colorectal cancer patients

Comprehensive analysis of pain genes in prognosis of kidney renal clear cell carcinoma and tumor immunotherapy: A comprehensive bioinformatic study

Background

The effect of pain genes (NAV1, EHMT2, SP1, SLC6A4, COMT, OPRM1, OPRD1, CYP2D6, and CYP3A4) have not been reported previously in kidney renal clear cell carcinoma (KIRC) patients and thus we made a comprehensive analysis of pain genes in the prognosis of KIRC and tumor immunotherapy.

Methods

In this study, TCGA, Kaplan-Meier plotter, Metascape, STRING, Human Protein Atlas, Single Cell Expression Atlas database, LinkedOmics, cBioPortal, MethSurv, CancerSEA, COSMIC database and R package (ggplot2, version 3.3.3) were used for comprehensive analysis of pain genes in KIRC. Pearson and Spearman correlation coefficients were for co-expression analysis. Immunotherapy and TISIDB database were used for tumor Immunotherapy.

Results

Representative pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4) were statistically significant (p < 0.0001) in the prognosis of KIRC. Immunotherapy (anti-PD-1 therapy, anti-PD-L1 therapy, and anti-CTLA4 therapy) and immunomodulator (immunoinhibitor, immunostimulator, and MHC molecule) in KIRC were significant associated with pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4), which were the important addition to clinical decision making for patients.

Conclusions

Our study uncovered a mechanism for the effect of pain genes on KIRC outcome via the modulation of associated co-expression gene networks, gene variation, and tumor Immunotherapy.

Interplay between Serotonin, Immune Response, and Intestinal Dysbiosis in Inflammatory Bowel Disease

Inflammatory Bowel Disease (IBD) is a chronic gastrointestinal disorder characterized by periods of activity and remission. IBD includes Crohn's disease (CD) and ulcerative colitis (UC), and even though IBD has not been considered as a heritable disease, there are genetic variants associated with increased risk for the disease. 5-Hydroxytriptamine (5-HT), or serotonin, exerts a wide range of gastrointestinal effects under both normal and pathological conditions. Furthermore, Serotonin Transporter (SERT) coded by Solute Carrier Family 6 Member 4 (SLC6A4) gene (located in the 17q11.1-q12 chromosome), possesses genetic variants, such as Serotonin Transporter Gene Variable Number Tandem Repeat in Intron 2 (STin2-VNTR) and Serotonin-Transporter-linked promoter region (5-HTTLPR), which have an influence over the functionality of SERT in the re-uptake and bioavailability of serotonin. The intestinal microbiota is a crucial actor in normal human gut physiology, exerting effects on serotonin, SERT function, and inflammatory processes. As a consequence of abnormal serotonin signaling and SERT function under these inflammatory processes, the use of selective serotonin re-uptake inhibitors (SSRIs) has been seen to improve disease activity and extraintestinal manifestations, such as depression and anxiety. The aim of this study is to integrate scientific data linking the intestinal microbiota as a regulator of gut serotonin signaling and re-uptake, as well as its role in the pathogenesis of IBD. We performed a narrative review, including a literature search in the PubMed database of both review and original articles (no date restriction), as well as information about the SLC6A4 gene and its genetic variants obtained from the Ensembl website. Scientific evidence from in vitro, in vivo, and clinical trials regarding the use of selective serotonin reuptake inhibitors as an adjuvant therapy in patients with IBD is also discussed. A total of 194 articles were used between reviews, in vivo, in vitro studies, and clinical trials.

Identification of diagnostic gene biomarkers related to immune infiltration in patients with idiopathic pulmonary fibrosis based on bioinformatics strategies

Objective

The study aims to identify potential diagnostic markers of idiopathic pulmonary fibrosis (IPF) and analyze the significance of immune cell infiltration in this pathology.

Materials and methods

Download two publicly available gene expression profiles (GSE10667 and GSE24206 datasets) from the GEO database including 48 Idiopathic pulmonary fibrosis (IPF) samples and 21 human control samples and select for distinctly expressed genes (DEG) from them. Lasso regression model and support vector machine recursive feature elimination S,V,R,F analysis were used to check candidate biomarkers. The area under the subject's work characteristic curve (AUC) value is used to evaluate its recognition ability. The GSE53845 dataset (40 IPF patients and 8 controls) continue to validate the expression level and diagnostic value of biomarkers in IPF. Comprehensive analysis of immune infiltrated cells of IPF was performed using R software and immune cell infiltration estimation analysis tool- deconvolution algorithm (CIBERSORT).

Results

43 DEGs were identified in total. The identified DEGs mostly involve pneumonia, lung disease, collagen disease, obstructive pulmonary disease and other diseases. The activation of IL-17 signaling pathways, amoebic disease, interaction of viral proteins with cytokines and cytokine receptors, protein digestion and absorption, and flaccid hormone signaling pathways in IPF were different from the control group. The expression degree of CRTAC1, COL10A1, COMP, RPS4Y1, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 in IPF tissue were prominently higher than the normal group. Immune cell infiltration analysis showed that CRTAC1, COL10A1, COMP, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 were associated with monocytes, plasma cells, neutrophils, and regulatory (treg) T cells.

Conclusion

CRTAC1, COL10A1, COMP, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 can be used as diagnostic markers for IPF, providing new ideas for the future study of IPF occurrence and molecular mechanisms.

Role and mechanism of benzo[a]pyrene in the transformation of chronic obstructive pulmonary disease into lung adenocarcinoma

OBJECTIVE

This experiment is explores the genes that play a key role, their expression changes and the biological processes in the transformation of chronic obstructive pulmonary disease (COPD) into lung adenocarcinoma (LAC). Meanwhile, identify the effects of Benzo[a]pyrene (BaP) in the conversion of COPD into LAC.

METHODS

1. Differential expression genes of COPD and LAC were screened and analyzed by high-throughput microarray data between the two diseases and their respective control groups. 2. The screened genes were used for routine bioinformatics analysis such as functional analysis, expression verification, protein interaction analysis and functional enrichment. 3. Cigarette smoke extract (CSE) combined with lipopolysaccharide (LPS) was used to establish an in vitro COPD model. 4. MTT assay was used to detect the influence of B(a)P in effect on A549 cell proliferation. CCK-8, Transwell invasion test and scratch test were used to detect the cell proliferation, invasion and migration ability, while qPCR and Western Blot tests were used to observe the cell proliferation, apoptosis and changes in related indicators such as EMT. 5. Experimental method of separately adding agonists (tBHQ) and inhibitors (DIC) of NQO1 was used to confirm the effect of NQO1 on A549 cell proliferation, apoptosis, migration and invasion. 6. To further clarify whether BaP exerted effect on cell proliferation, apoptosis, migration and invasion through NQO1, we knocked down NQO1 gene and then infecting cells with BaP.

RESULTS

1. We screened genes of COPD and LAC using datasets from GSE151052, GSE118370, and GSE140797. After screening, the genes upregulated in COPD and downregulated in LAC were RTKN2, SLC6A4, and HBB, the gene downregulated in COPD and upregulated in LAC was NQO1, the genes downregulated in both COPD and LAC were FPR1, LYVE1 and PKHD1L1. 2. The main signaling pathways in which the target genes were enriched are cell cycle, EMT, PI3K/AKT, and apoptosis. In the data included GEPIA, PKHD1L1, FPR1, LYVE1, RTKN2, HBB, and SLC6A4 were significantly downregulated and NQO1 was upregulated in LAC relative to controls. In addition, there were 46 interaction proteins in the target genes, and the functions they enriched included hydrogen peroxide catabolism, etc. 3. When A549 cell was stimulated with 100 ng/mL LPS+ 10% CSE, the COX-2 expression indicated that COPD model in vitro was successfully established. 4. The optimal dose and action time were screened which were 1 μM and 24 h. Compared to the control group, COPD and BaP group increased cell proliferation and invasion capabilities. On the basis of COPD, adding BaP could further increase the proliferation and migration capabilities. Interestingly, the levels of NQO1 decreased in COPD models, while increased by BaP. 5. tBHQ can increase the proliferation and migration capacity of A549 cells, which is inhibited by the addition of DIC. 6. The enhanced proliferation, migration and invasion of A549 cells by BaP were attenuated after knockdown of NQO1.

CONCLUSION

Our study reveals that PKHD1L1, FPR1, LYVE1, RTKN2, HBB, SLC6A4 and NQO1 may play an important role in the conversion of COPD to LAC. High NQO1 expression may increase the proliferation and migration ability of A549 cells, and BaP may promote the EMT state by increasing the expression of NQO1, thereby making the COPD model in vitro expose the tumor characteristics.

In silico analysis of a SLC6A4 G100V mutation in lung cancers

SLC6A4 is a serotonin re-uptake transporter which has been a target for anti-depressant therapies but recently some mutations have been described in cancer cells. Here, we characterize mutations in SLC6A4 that appear in cancer cells. We employed several validated computational and artificial intelligence algorithms to characterize the mutations. We identified a previously uncharacterized G100V mutation in lung cancers. In sillico structural analysis reveals that this mutation may affect SLC6A4 ligand binding and subsequently its function. We also identified several other mutations that may affect the structure of the protein. This preliminary analysis highlights the role of SLC6A4 in human cancers.

Tryptophan metabolites modulate inflammatory bowel disease and colorectal cancer by affecting immune system

Tryptophan is an essential amino acid, going through three different metabolic pathways in the intestines. Indole pathway in the gut microbiota, serotonin system in the enterochromaffin cells and kynurenine pathway in the immune cells and intestinal lining are the three arms of tryptophan metabolism in the intestines. Clinical, in vivo and in vitro studies showed that each one of these arms has a significant impact on IBD. This review explains how different metabolites of tryptophan are involved in the pathophysiology of IBD and colorectal cancer, as a major complication of IBD. Indole metabolites alleviate colitis and protect against colorectal cancer while serotonin arm follows a more complicated and receptor-specific pattern. Indole metabolites and kynurenine interact with aryl hydrocarbon receptor (AHR) to induce T regulatory cells differentiation, confine Th17 and Th1 response and produce anti-inflammatory mediators. Kynurenine decreases tumor-infiltrating CD8+ cells and mediates tumor cells immune evasion. Serotonin system also increases colorectal cancer cells proliferation and metastasis while, indole metabolites can profoundly decrease colorectal cancer growth. Targeted therapy for tryptophan metabolites may improve the management of IBD and colorectal cancer, e.g. supplementation of indole metabolites such as indole-3-carbinol (I3C), inhibition of kynurenine monooxygenase (KMO) and selective stimulation or inhibition of specific serotonergic receptors can mitigate colitis. Furthermore, it will be explained how indole metabolites supplementation, inhibition of indoleamine 2,3-dioxygenase 1 (IDO1), KMO and serotonin receptors can protect against colorectal cancer. Additionally, extensive molecular interactions between tryptophan metabolites and intracellular signaling pathways will be thoroughly discussed.

A comprehensive strategy to clarify the pharmacodynamic constituents and mechanism of Wu-tou decoction based on the constituents migrating to blood and their in vivo process under pathological state

ETHNOPHARMACOLOGICAL RELEVANCE

As a traditional Chinese medicine (TCM) formula, Wu-tou decoction has been used for treating rheumatoid arthritis (RA) for more than a thousand years. Identifying pharmacodynamic constituents (PCs) of WTD and exploring their in vivo process are very meaningful for promoting the modernization of TCM. However, the pathological state might change this process.

AIM OF THE STUDY

Hence, it is necessary and significant to compare the process in vivo of drugs both in normal and disease state and clarify their action mechanism.

MATERIALS AND METHODS

Taking Wu-tou decoction (WTD) as the research object, a comprehensive strategy based on liquid chromatography coupled with mass spectrometry (LC-MS) was developed to identify PCs, clarify and compare their absorption and distribution in normal and model rats, and then explore the potential mechanism of TCM. Firstly, the PCs in WTD were identified. Then, the pharmacokinetics (PK) and tissue distribution of these ingredients were studied. Finally, the constituents with the difference between normal and model rats were selected for target network pharmacological analysis to clarify the mechanism.

RESULTS

A total of 27 PCs of WTD were identified. The absorption and distribution of 20 PCs were successfully analyzed. In the disease state, the absorption and distribution of all these components were improved to have better treatment effects. The results of target network pharmacological analysis indicated that PTGS1, PTGS2, ABCB1, SLC6A4, CHRM2, ESR1, ESR2, CDK2, TNF and IL-6 are 10 key targets for WTD against RA. The regulatory effects of WTD on the expression of PTGS2 and TNF were further verified. Pathway enrichment analysis showed that the key mechanism of WTD against RA is to reduce inflammation and regulate the immune response.

CONCLUSION

These results indicated that this strategy could better understand the in vivo process and mechanism of WTD under the pathological state. Furthermore, this strategy is also appropriate for other TCM.

Genotyping data of routinely processed matched primary/metastatic tumor samples

Genotypic and phenotypic comparisons of tumors in multiple tissue samples from the same patient are important for understanding disease evolution and treatment possibilities. Panel NGS genotyping is currently widely used in this context, whereby NGS variant filtering and final evaluation constitute the basis for meaningful comparisons. Here, we present the genotype data used for genotype / phenotype comparisons between matched primary / metastatic colorectal tumors in the work by Chatzopoulos et al (doi: 10.1016/j.humpath.2020.10.009), as well as the process followed for obtaining these data. We describe key issues while processing routinely formalin-fixed paraffin-embedded (FFPE) tumors for genotyping, NGS application (Ion Torrent), a stringent variant filtering algorithm for genotype analyses in FFPE tissues and particularly in matched tumor samples, and provide the respective datasets. Apart from research, tumor NGS genotyping is currently applied for clinical diagnostic purposes in Oncology. The datasets and method description provided herein (a) are important for comprehending the peculiarities of FFPE tumor genotyping, which is still mostly based on principles of germline DNA genotyping; (b) can be used in pooled analyses, e.g., of primary / metastatic tumors for the investigation of tumor evolution.

Scanning all chromosomal abnormalities with microarray-based comparative genomic hybridization in differential diagnosis of pediatric cancers

OBJECTIVE

Despite conventional histopathological and immunohistochemical methods, difficulties may be experienced in the differential diagnosis of pediatric cancers, especially in small round-cell undifferentiated tumors. In these cases, the determination of chromosomal abnormalities may be helpful. The aim of this study was to evaluate the place of the whole genome array comparative genomic hybridization method in pediatric cancers where difficulty is experienced in differential diagnosis.

METHOD

In Comparative Genomic Hybridization (CGH), 135,000 probes were scanned as 3 probes per gene in all genomes. It was possible to analyze paraffin block tissues obtained from the archive of the Pathology Laboratory of Dr. Behcet Uz Children's Hospital. DNA extraction was made from the paraffin blocks of 24 cases where difficulty had been experienced in making the differential diagnosis and in each case, comparisons with the control samples were made for all anomalies in all chromosomes using microarray technology.

RESULTS

Together with the typically observed chromosomal anomalies, additional derangements with debatable importance were determined.

CONCLUSION

The whole genome CGH method may be useful in pediatric cancers where difficulties are experienced in making differential diagnoses. Since technical difficulties are experienced in the examination of paraffin-embedded tissue samples, storing fresh tissue samples from each tumor will be helpful for genetic and molecular examinations.

Serotonin transporter-linked polymorphic region genotypes in relation to stress conditions among patients with papillary thyroid carcinoma

The serotonin-transporter-linked polymorphic region (5-HTTLPR) gene has been reported to predispose individuals experiencing trauma to affective disorders such as anxiety and depression. We hypothesized that SS genotype of 5-HTTLPR gene would induce stress conditions and poor prognosis of papillary thyroid carcinoma (PTC). The study enrolled 287 patients with or without post-traumatic stress disorder (PTSD) following surgical treatment of PTC with their baseline characteristics collected. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was conducted to detect genotype frequency. Five self-rating scales, including Impact of Event Scale-Revised Edition (IES-R), MedicaI Coping Modes Questionnaire (MCMO), Hamilton Depression Scale (HAMD), Social Support Rating Scale (SSRS) and Stressful Life Events (SLEs), were used for depressive state assessment. Survival situations were observed through 15-year follow-up visits one time every six months. Survival rate was calculated using Life Table. Logistic regression analysis was used to analyze factors related to prognosis of PTC. Increased SS genotype and decreased LL genotypes were found in patients with PTSD. PTSD is associated with high stress, and inter-group analysis revealed that patients carrying SS genotype exhibited a high stress condition. PTSD and SS genotype correlated to large tumor size, advanced clinical stage, lymph node metastasis, and decreased 10-year and 15-year survival rate. As for patients carrying the same genotype, those suffering from PTSD showed poorer survival. Also, 5-HTTPRL, MCMQ score (confrontation/avoidance/surrender), HAMD score, SSRS total score, SLEs score, tumor size, clinical stage, and lymph node metastasis were relevant factors for prognosis of PTC. The results demonstrate SS genotype of the 5-HTTPRL gene as a contributor of high stress among patients with PTC. Thus, 5-HTTPRL and stress conditions represent potential investigative focus targets for prognosis of PTC.

Differential Connectivity in Colorectal Cancer Gene Expression Network

BACKGROUND

Colorectal cancer (CRC) is one of the challenging types of cancers; thus, exploring effective biomarkers related to colorectal could lead to significant progresses toward the treatment of this disease.

METHODS

In the present study, CRC gene expression datasets have been reanalyzed. Mutual differentially expressed genes across 294 normal mucosa and adjacent tumoral samples were then utilized in order to build two independent transcriptional regulatory networks. By analyzing the networks topologically, genes with differential global connectivity related to cancer state were determined for which the potential transcriptional regulators including transcription factors were identified.

RESULTS

The majority of differentially connected genes (DCGs) were up-regulated in colorectal transcriptome experiments. Moreover, a number of these genes have been experimentally validated as cancer or CRC-associated genes. The DCGs, including GART, TGFB1, ITGA2, SLC16A5, SOX9, and MMP7, were investigated across 12 cancer types. Functional enrichment analysis followed by detailed data mining exhibited that these candidate genes could be related to CRC by mediating in metastatic cascade in addition to shared pathways with 12 cancer types by triggering the inflammatory events.

DISCUSSION

Our study uncovered correlated alterations in gene expression related to CRC susceptibility and progression that the potent candidate biomarkers could provide a link to disease.

Serotonin and human cancer: A critical view

Besides its classical functions as a neurotransmitter in the central nervous system, local mediator in the gastrointestinal tract and vasoactive agent in the blood, serotonin has more recently emerged as a growth factor for human tumor cells of different origins (carcinomas, glioma and carcinoids). Several data are also available on serotonin involvement in cancer cell migration, metastatic dissemination and tumor angiogenesis. The serotonin-induced signaling pathways that promote tumor progression are complex and only partly understood in some cancer types. The results of several studies showed that serotonin levels in the tumor played a crucial role in cancer progression. A serotonin production and secretion by neuroendocrine cells have been shown in the progression of several solid tumors and the involvement of a serotoninergic autocrine loop was proposed. Specific receptor subtypes are associated with different fundamental stages of tumor progression and the pattern of receptors expression becomes dysregulated in several human tumors when compared with normal cells or tissues. Serotonin receptors, selective serotonin transporter and serotonin synthesis pathways are potential chemotherapeutic targets for the treatment of several cancers in which therapeutic approaches are limited. Through several asked questions, this critical mini-review discusses the relevance of the involvement of serotonin in human cancer progression.

Exploring conserved mRNA-miRNA interactions in colon and lung cancers

AIM

The main goal of this analysis was prioritization of co-expressed genes and miRNAs that are thought to have important influences in the pathogenesis of colon and lung cancers.

BACKGROUND

MicroRNAs (miRNAs) as small and endogenous noncoding RNAs which regulate gene expression by repressing mRNA translation or decreasing stability of mRNAs; they have proven pivotal roles in different types of cancers. Accumulating evidence indicates the role of miRNAs in a wide range of biological processes from oncogenesis and tumor suppressors to contribution to tumor progression. Colon and lung cancers are frequently encountered challenging types of cancers; therefore, exploring trade-off among underlying biological units such as miRNA with mRNAs will probably lead to identification of promising biomarkers involved in these malignancies.

METHODS

Colon cancer and lung cancer expression data were downloaded from Firehose and TCGA databases and varied genes extracted by DCGL software were subjected to build two gene regulatory networks by parmigene R package. Afterwards, a network-driven integrative analysis was performed to explore prognosticates genes, miRNAs and underlying pathways.

RESULTS

A total of 192 differentially expressed miRNAs and their target genes within gene regulatory networks were derived by ARACNE algorithm. BTF3, TP53, MYC, CALR, NEM2, miR-29b-3p and miR-145 were identified as bottleneck nodes and enriched via biological gene ontology (GO) terms and pathways chiefly in biosynthesis and signaling pathways by further screening.

CONCLUSION

Our study uncovered correlated alterations in gene expression that may relate with colon and lung cancers and highlighted the potent common biomarker candidates for the two diseases.

Does preoperative depression and/or serotonin transporter gene polymorphism predict outcome after laparoscopic cholecystectomy?

OBJECTIVE

To determine whether preoperative psychological depression and/or serotonin transporter gene polymorphism are associated with poor outcomes after the common procedure of laparoscopic cholecystectomy.

DESIGN

Patients undergoing laparoscopic cholecystectomy were genotyped for the serotonin transporter gene 5-HTTLPR polymorphism and assessed for psychological morbidity before and 6 weeks after surgery. The main outcome was postoperative depression; secondary outcomes included fatigue, perceived pain, quality of life and subjective perception about return to usual.

RESULTS

Full genetic and psychological data were obtained from 273 out of 330 patients consented to the study (82% female). Significantly fewer people with preoperative depression (Beck Depression Inventory (BDI) score >5) had returned to employment (57% vs 86%, p<0.001) or made a full recovery (11% vs 44%, p<0.001) 6 weeks after surgery. Independent predictors for subjective return to usual after surgery included preoperative depression, body mass index and postoperative pain scores. Independent predictors of postoperative depression included preoperative antidepressant use and preoperative depression. SS genotype was associated with use of antidepressants preoperatively and higher anxiety levels after surgery. However, it was not associated with other salient postoperative psychosocial outcomes.

CONCLUSIONS

Depressive psychological morbidity preoperatively, pain and body mass index appear to be important factors in predicting recovery after this common surgical procedure. There may be a place to include preoperative brief psychological screening to enable targeted support. Our results suggest that the serotonin transporter gene is unlikely to be a useful clinical predictor of outcome in this group.

TRIAL REGISTRATION NUMBER

ISRCTN40219584.

ProSim: A Method for Prioritizing Disease Genes Based on Protein Proximity and Disease Similarity

Predicting disease genes for a particular genetic disease is very challenging in bioinformatics. Based on current research studies, this challenge can be tackled via network-based approaches. Furthermore, it has been highlighted that it is necessary to consider disease similarity along with the protein's proximity to disease genes in a protein-protein interaction (PPI) network in order to improve the accuracy of disease gene prioritization. In this study we propose a new algorithm called proximity disease similarity algorithm (ProSim), which takes both of the aforementioned properties into consideration, to prioritize disease genes. To illustrate the proposed algorithm, we have conducted six case studies, namely, prostate cancer, Alzheimer's disease, diabetes mellitus type 2, breast cancer, colorectal cancer, and lung cancer. We employed leave-one-out cross validation, mean enrichment, tenfold cross validation, and ROC curves to evaluate our proposed method and other existing methods. The results show that our proposed method outperforms existing methods such as PRINCE, RWR, and DADA.

Gene polymorphisms of stress hormone and cytokine receptors associate with immunomodulatory profile and psychological measurement

OBJECTIVE

We sought to identify whether stable single nucleotide polymorphisms (SNPs) of various endocrine and immune molecules could be used as biomarkers associated with specific immune alterations and chronic stress measures in normal humans.

METHODS

A total of 207 volunteer participants answered stress questionnaire and gave peripheral blood cells for identification of SNPs in genes coding for glucocorticoid receptor (GR), beta 2 adrenergic receptor (B2AR), interferon-gamma receptors (IFNGR1, IFNGR2), and interleukin-4 receptor (IL4R). Immunoregulatory profiles were measured by flow cytometry and genotyping assays were performed by allelic discrimination real-time PCR.

RESULTS

Several significant differences were revealed in associations between stress marker and immune indicators based on SNP categories. For instance, Th1 levels of the minor alleles of GR TthIIII (AA) and IFNGR2 Q64R (Arg/Arg) groups were positively associated with chronic stress (PSS) (p = 0.024 and 0.005, respectively) compared with wild type (WT) and negatively associated with PSS in the heterozygous genotypes of GR BclI and IL4R Ile50Val (p = 0.040 and p = 0.052, respectively). Treg levels of the minor alleles of BclI (GG) and IFNGR1 T-56C (CC) groups were positively associated with PSS (p = 0.045 and p = 0.010, respectively) and negatively associated in the minor allele (Val/Val) of IL4R Ile50Va and the heterozygous genotype of IL4R Q576R (p = 0.041 and p = 0.017, respectively) compared to WT.

CONCLUSION

The data support the notion that gene polymorphisms from various components of the psychoneuroendocrine-immune network may be useful as biomarkers to categorize individual stress-associated immune responses.

DEOD: uncovering dominant effects of cancer-driver genes based on a partial covariance selection method

MOTIVATION

The generation of a large volume of cancer genomes has allowed us to identify disease-related alterations more accurately, which is expected to enhance our understanding regarding the mechanism of cancer development. With genomic alterations detected, one challenge is to pinpoint cancer-driver genes that cause functional abnormalities.

RESULTS

Here, we propose a method for uncovering the dominant effects of cancer-driver genes (DEOD) based on a partial covariance selection approach. Inspired by a convex optimization technique, it estimates the dominant effects of candidate cancer-driver genes on the expression level changes of their target genes. It constructs a gene network as a directed-weighted graph by integrating DNA copy numbers, single nucleotide mutations and gene expressions from matched tumor samples, and estimates partial covariances between driver genes and their target genes. Then, a scoring function to measure the cancer-driver score for each gene is applied. To test the performance of DEOD, a novel scheme is designed for simulating conditional multivariate normal variables (targets and free genes) given a group of variables (driver genes). When we applied the DEOD method to both the simulated data and breast cancer data, DEOD successfully uncovered driver variables in the simulation data, and identified well-known oncogenes in breast cancer. In addition, two highly ranked genes by DEOD were related to survival time. The copy number amplifications of MYC (8q24.21) and TRPS1 (8q23.3) were closely related to the survival time with P-values = 0.00246 and 0.00092, respectively. The results demonstrate that DEOD can efficiently uncover cancer-driver genes.

Epigenetic regulation in biopsychosocial pathways

Theory and empirical evidence suggest that psychological stress and other adverse psychosocial experiences can contribute to cancer progression. Research has begun to explore the potential role of epigenetic changes in these pathways. In basic, animal and human models, exposure to stressors or to the products of the physiological stress response (e.g., cortisol) has been associated with epigenetic changes, such as DNA methylation and microRNA (miR) expression, which may influence tumor growth, progression, metastasis, or chemoresistance. However, the specific biological pathways linking stress, epigenetic changes, and cancer outcomes remain unclear. Numerous opportunities exist to extend the preliminary evidence for the role of epigenetic mechanisms in the biopsychosocial pathways contributing to cancer progression. Such work will improve our understanding of how the psychosocial environment influences cancer risk and survival, potentially leading to improved prevention and treatment strategies.

The biology of depression in cancer and the relationship between depression and cancer progression

The prevalence of depressive symptoms in patients with cancer exceeds that observed in the general population and depression is associated with a poorer prognosis in cancer patients. The increased prevalence is not solely explained by the psychosocial stress associated with the diagnosis. Pro-inflammatory cytokines, which induce sickness behaviour with symptoms overlapping those of clinical depression, are validated biomarkers of increased inflammation in patients with cancer. A growing literature reveals that chronic inflammatory processes associated with stress may also underlie depression symptoms in general, and in patients with cancer in particular. Therapeutic modalities, which are frequently poorly tolerated, are used in the treatment of cancer. These interventions are associated with inflammatory reactions, which may help to explain their toxicity. There is evidence that antidepressants can effectively treat symptoms of depression in cancer patients though the database is meager. Novel agents with anti-inflammatory properties may be effective alternatives for patients with treatment-resistant depression who exhibit evidence of increased inflammation.